Mapping rare and common causal alleles for complex human diseases
Raychaudhuri, Soumya
2011-01-01
Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual’s risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, to capitalize on this data for prevention and therapies requires the identification of causal alleles and a mechanistic understanding for how these variants contribute to the disease. After discussing the strategies currently used to map variants for complex diseases, this Primer explores how variants may be prioritized for follow-up functional studies and the challenges and approaches for assessing the contributions of rare and common variants to disease phenotypes. PMID:21962507
Linkage disequilibrium among commonly genotyped SNP and variants detected from bull sequence
USDA-ARS?s Scientific Manuscript database
Genomic prediction utilizing causal variants could increase selection accuracy above that achieved with SNP genotyped by commercial assays. A number of variants detected from sequencing influential sires are likely to be causal, but noticable improvements in prediction accuracy using imputed sequen...
Hitomi, Yuki; Tokunaga, Katsushi
2017-01-01
Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.
Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification
Faye, Laura L.; Machiela, Mitchell J.; Kraft, Peter; Bull, Shelley B.; Sun, Lei
2013-01-01
Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the author's website. PMID:23950724
Dunning, Alison M; Michailidou, Kyriaki; Kuchenbaecker, Karoline B; Thompson, Deborah; French, Juliet D; Beesley, Jonathan; Healey, Catherine S; Kar, Siddhartha; Pooley, Karen A; Lopez-Knowles, Elena; Dicks, Ed; Barrowdale, Daniel; Sinnott-Armstrong, Nicholas A; Sallari, Richard C; Hillman, Kristine M; Kaufmann, Susanne; Sivakumaran, Haran; Moradi Marjaneh, Mahdi; Lee, Jason S; Hills, Margaret; Jarosz, Monika; Drury, Suzie; Canisius, Sander; Bolla, Manjeet K; Dennis, Joe; Wang, Qin; Hopper, John L; Southey, Melissa C; Broeks, Annegien; Schmidt, Marjanka K; Lophatananon, Artitaya; Muir, Kenneth; Beckmann, Matthias W; Fasching, Peter A; Dos-Santos-Silva, Isabel; Peto, Julian; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; González-Neira, Anna; Perez, Jose I A; Anton-Culver, Hoda; Eunjung, Lee; Arndt, Volker; Brenner, Hermann; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Aittomäki, Kristiina; Blomqvist, Carl; Ito, Hidemi; Matsuo, Keitaro; Bogdanova, Natasha; Dörk, Thilo; Lindblom, Annika; Margolin, Sara; Kosma, Veli-Matti; Mannermaa, Arto; Tseng, Chiu-Chen; Wu, Anna H; Lambrechts, Diether; Wildiers, Hans; Chang-Claude, Jenny; Rudolph, Anja; Peterlongo, Paolo; Radice, Paolo; Olson, Janet E; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Henderson, Brian E; Goldberg, Mark S; Teo, Soo H; Yip, Cheng Har; Nord, Silje; Borresen-Dale, Anne-Lise; Kristensen, Vessela; Long, Jirong; Zheng, Wei; Pylkäs, Katri; Winqvist, Robert; Andrulis, Irene L; Knight, Julia A; Devilee, Peter; Seynaeve, Caroline; Figueroa, Jonine; Sherman, Mark E; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; van den Ouweland, Ans M W; Humphreys, Keith; Gao, Yu-Tang; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S; Blot, William; Cai, Qiuyin; Ghoussaini, Maya; Perkins, Barbara J; Shah, Mitul; Choi, Ji-Yeob; Kang, Daehee; Lee, Soo Chin; Hartman, Mikael; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Brennan, Paul; Sangrajrang, Suleeporn; Ambrosone, Christine B; Toland, Amanda E; Shen, Chen-Yang; Wu, Pei-Ei; Orr, Nick; Swerdlow, Anthony; McGuffog, Lesley; Healey, Sue; Lee, Andrew; Kapuscinski, Miroslav; John, Esther M; Terry, Mary Beth; Daly, Mary B; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Tihomirova, Laima; Tung, Nadine; Dorfling, Cecilia M; van Rensburg, Elizabeth J; Neuhausen, Susan L; Ejlertsen, Bent; Hansen, Thomas V O; Osorio, Ana; Benitez, Javier; Rando, Rachel; Weitzel, Jeffrey N; Bonanni, Bernardo; Peissel, Bernard; Manoukian, Siranoush; Papi, Laura; Ottini, Laura; Konstantopoulou, Irene; Apostolou, Paraskevi; Garber, Judy; Rashid, Muhammad Usman; Frost, Debra; Izatt, Louise; Ellis, Steve; Godwin, Andrew K; Arnold, Norbert; Niederacher, Dieter; Rhiem, Kerstin; Bogdanova-Markov, Nadja; Sagne, Charlotte; Stoppa-Lyonnet, Dominique; Damiola, Francesca; Sinilnikova, Olga M; Mazoyer, Sylvie; Isaacs, Claudine; Claes, Kathleen B M; De Leeneer, Kim; de la Hoya, Miguel; Caldes, Trinidad; Nevanlinna, Heli; Khan, Sofia; Mensenkamp, Arjen R; Hooning, Maartje J; Rookus, Matti A; Kwong, Ava; Olah, Edith; Diez, Orland; Brunet, Joan; Pujana, Miquel Angel; Gronwald, Jacek; Huzarski, Tomasz; Barkardottir, Rosa B; Laframboise, Rachel; Soucy, Penny; Montagna, Marco; Agata, Simona; Teixeira, Manuel R; Park, Sue Kyung; Lindor, Noralane; Couch, Fergus J; Tischkowitz, Marc; Foretova, Lenka; Vijai, Joseph; Offit, Kenneth; Singer, Christian F; Rappaport, Christine; Phelan, Catherine M; Greene, Mark H; Mai, Phuong L; Rennert, Gad; Imyanitov, Evgeny N; Hulick, Peter J; Phillips, Kelly-Anne; Piedmonte, Marion; Mulligan, Anna Marie; Glendon, Gord; Bojesen, Anders; Thomassen, Mads; Caligo, Maria A; Yoon, Sook-Yee; Friedman, Eitan; Laitman, Yael; Borg, Ake; von Wachenfeldt, Anna; Ehrencrona, Hans; Rantala, Johanna; Olopade, Olufunmilayo I; Ganz, Patricia A; Nussbaum, Robert L; Gayther, Simon A; Nathanson, Katherine L; Domchek, Susan M; Arun, Banu K; Mitchell, Gillian; Karlan, Beth Y; Lester, Jenny; Maskarinec, Gertraud; Woolcott, Christy; Scott, Christopher; Stone, Jennifer; Apicella, Carmel; Tamimi, Rulla; Luben, Robert; Khaw, Kay-Tee; Helland, Åslaug; Haakensen, Vilde; Dowsett, Mitch; Pharoah, Paul D P; Simard, Jacques; Hall, Per; García-Closas, Montserrat; Vachon, Celine; Chenevix-Trench, Georgia; Antoniou, Antonis C; Easton, Douglas F; Edwards, Stacey L
2016-04-01
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.
Dunning, Alison M; Michailidou, Kyriaki; Kuchenbaecker, Karoline B; Thompson, Deborah; French, Juliet D; Beesley, Jonathan; Healey, Catherine S; Kar, Siddhartha; Pooley, Karen A; Lopez-Knowles, Elena; Dicks, Ed; Barrowdale, Daniel; Sinnott-Armstrong, Nicholas A; Sallari, Richard C; Hillman, Kristine M; Kaufmann, Susanne; Sivakumaran, Haran; Marjaneh, Mahdi Moradi; Lee, Jason S; Hills, Margaret; Jarosz, Monika; Drury, Suzie; Canisius, Sander; Bolla, Manjeet K; Dennis, Joe; Wang, Qin; Hopper, John L; Southey, Melissa C; Broeks, Annegien; Schmidt, Marjanka K; Lophatananon, Artitaya; Muir, Kenneth; Beckmann, Matthias W; Fasching, Peter A; dos-Santos-Silva, Isabel; Peto, Julian; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; González-Neira, Anna; Perez, Jose I A; Anton-Culver, Hoda; Eunjung, Lee; Arndt, Volker; Brenner, Hermann; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Aittomäki, Kristiina; Blomqvist, Carl; Ito, Hidemi; Matsuo, Keitaro; Bogdanova, Natasha; Dörk, Thilo; Lindblom, Annika; Margolin, Sara; Kosma, Veli-Matti; Mannermaa, Arto; Tseng, Chiu-chen; Wu, Anna H; Lambrechts, Diether; Wildiers, Hans; Chang-Claude, Jenny; Rudolph, Anja; Peterlongo, Paolo; Radice, Paolo; Olson, Janet E; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Henderson, Brian E; Goldberg, Mark S; Teo, Soo H; Yip, Cheng Har; Nord, Silje; Borresen-Dale, Anne-Lise; Kristensen, Vessela; Long, Jirong; Zheng, Wei; Pylkäs, Katri; Winqvist, Robert; Andrulis, Irene L; Knight, Julia A; Devilee, Peter; Seynaeve, Caroline; Figueroa, Jonine; Sherman, Mark E; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; van den Ouweland, Ans M W; Humphreys, Keith; Gao, Yu-Tang; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S; Blot, William; Cai, Qiuyin; Ghoussaini, Maya; Perkins, Barbara J; Shah, Mitul; Choi, Ji-Yeob; Kang, Daehee; Lee, Soo Chin; Hartman, Mikael; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Brennan, Paul; Sangrajrang, Suleeporn; Ambrosone, Christine B; Toland, Amanda E; Shen, Chen-Yang; Wu, Pei-Ei; Orr, Nick; Swerdlow, Anthony; McGuffog, Lesley; Healey, Sue; Lee, Andrew; Kapuscinski, Miroslav; John, Esther M; Terry, Mary Beth; Daly, Mary B; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Tihomirova, Laima; Tung, Nadine; Dorfling, Cecilia M; van Rensburg, Elizabeth J; Neuhausen, Susan L; Ejlertsen, Bent; Hansen, Thomas V O; Osorio, Ana; Benitez, Javier; Rando, Rachel; Weitzel, Jeffrey N; Bonanni, Bernardo; Peissel, Bernard; Manoukian, Siranoush; Papi, Laura; Ottini, Laura; Konstantopoulou, Irene; Apostolou, Paraskevi; Garber, Judy; Rashid, Muhammad Usman; Frost, Debra; Izatt, Louise; Ellis, Steve; Godwin, Andrew K; Arnold, Norbert; Niederacher, Dieter; Rhiem, Kerstin; Bogdanova-Markov, Nadja; Sagne, Charlotte; Stoppa-Lyonnet, Dominique; Damiola, Francesca; Sinilnikova, Olga M; Mazoyer, Sylvie; Isaacs, Claudine; Claes, Kathleen B M; De Leeneer, Kim; de la Hoya, Miguel; Caldes, Trinidad; Nevanlinna, Heli; Khan, Sofia; Mensenkamp, Arjen R; Hooning, Maartje J; Rookus, Matti A; Kwong, Ava; Olah, Edith; Diez, Orland; Brunet, Joan; Pujana, Miquel Angel; Gronwald, Jacek; Huzarski, Tomasz; Barkardottir, Rosa B; Laframboise, Rachel; Soucy, Penny; Montagna, Marco; Agata, Simona; Teixeira, Manuel R; Park, Sue Kyung; Lindor, Noralane; Couch, Fergus J; Tischkowitz, Marc; Foretova, Lenka; Vijai, Joseph; Offit, Kenneth; Singer, Christian F; Rappaport, Christine; Phelan, Catherine M; Greene, Mark H; Mai, Phuong L; Rennert, Gad; Imyanitov, Evgeny N; Hulick, Peter J; Phillips, Kelly-Anne; Piedmonte, Marion; Mulligan, Anna Marie; Glendon, Gord; Bojesen, Anders; Thomassen, Mads; Caligo, Maria A; Yoon, Sook-Yee; Friedman, Eitan; Laitman, Yael; Borg, Ake; von Wachenfeldt, Anna; Ehrencrona, Hans; Rantala, Johanna; Olopade, Olufunmilayo I; Ganz, Patricia A; Nussbaum, Robert L; Gayther, Simon A; Nathanson, Katherine L; Domchek, Susan M; Arun, Banu K; Mitchell, Gillian; Karlan, Beth Y; Lester, Jenny; Maskarinec, Gertraud; Woolcott, Christy; Scott, Christopher; Stone, Jennifer; Apicella, Carmel; Tamimi, Rulla; Luben, Robert; Khaw, Kay-Tee; Helland, Åslaug; Haakensen, Vilde; Dowsett, Mitch; Pharoah, Paul D P; Simard, Jacques; Hall, Per; García-Closas, Montserrat; Vachon, Celine; Chenevix-Trench, Georgia; Antoniou, Antonis C; Easton, Douglas F; Edwards, Stacey L
2016-01-01
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER+ or ER−) and human ERBB2 (HER2+ or HER2−) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER− tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression. PMID:26928228
Identification of causal genes for complex traits.
Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar
2015-06-15
Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Software is freely available for download at genetics.cs.ucla.edu/caviar. © The Author 2015. Published by Oxford University Press.
Identification of causal genes for complex traits
Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar
2015-01-01
Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider ‘causal variants’ as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. Results: In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Availability and implementation: Software is freely available for download at genetics.cs.ucla.edu/caviar. Contact: eeskin@cs.ucla.edu PMID:26072484
Fritsche, Lars G.; Igl, Wilmar; Cooke Bailey, Jessica N.; Grassmann, Felix; Sengupta, Sebanti; Bragg-Gresham, Jennifer L.; Burdon, Kathryn P.; Hebbring, Scott J.; Wen, Cindy; Gorski, Mathias; Kim, Ivana K.; Cho, David; Zack, Donald; Souied, Eric; Scholl, Hendrik P. N.; Bala, Elisa; Lee, Kristine E.; Hunter, David J.; Sardell, Rebecca J.; Mitchell, Paul; Merriam, Joanna E.; Cipriani, Valentina; Hoffman, Joshua D.; Schick, Tina; Lechanteur, Yara T. E.; Guymer, Robyn H.; Johnson, Matthew P.; Jiang, Yingda; Stanton, Chloe M.; Buitendijk, Gabriëlle H. S.; Zhan, Xiaowei; Kwong, Alan M.; Boleda, Alexis; Brooks, Matthew; Gieser, Linn; Ratnapriya, Rinki; Branham, Kari E.; Foerster, Johanna R.; Heckenlively, John R.; Othman, Mohammad I.; Vote, Brendan J.; Liang, Helena Hai; Souzeau, Emmanuelle; McAllister, Ian L.; Isaacs, Timothy; Hall, Janette; Lake, Stewart; Mackey, David A.; Constable, Ian J.; Craig, Jamie E.; Kitchner, Terrie E.; Yang, Zhenglin; Su, Zhiguang; Luo, Hongrong; Chen, Daniel; Ouyang, Hong; Flagg, Ken; Lin, Danni; Mao, Guanping; Ferreyra, Henry; Stark, Klaus; von Strachwitz, Claudia N.; Wolf, Armin; Brandl, Caroline; Rudolph, Guenther; Olden, Matthias; Morrison, Margaux A.; Morgan, Denise J.; Schu, Matthew; Ahn, Jeeyun; Silvestri, Giuliana; Tsironi, Evangelia E.; Park, Kyu Hyung; Farrer, Lindsay A.; Orlin, Anton; Brucker, Alexander; Li, Mingyao; Curcio, Christine; Mohand-Saïd, Saddek; Sahel, José-Alain; Audo, Isabelle; Benchaboune, Mustapha; Cree, Angela J.; Rennie, Christina A.; Goverdhan, Srinivas V.; Grunin, Michelle; Hagbi-Levi, Shira; Campochiaro, Peter; Katsanis, Nicholas; Holz, Frank G.; Blond, Frédéric; Blanché, Hélène; Deleuze, Jean-François; Igo, Robert P.; Truitt, Barbara; Peachey, Neal S.; Meuer, Stacy M.; Myers, Chelsea E.; Moore, Emily L.; Klein, Ronald; Hauser, Michael A.; Postel, Eric A.; Courtenay, Monique D.; Schwartz, Stephen G.; Kovach, Jaclyn L.; Scott, William K.; Liew, Gerald; Tƒan, Ava G.; Gopinath, Bamini; Merriam, John C.; Smith, R. Theodore; Khan, Jane C.; Shahid, Humma; Moore, Anthony T.; McGrath, J. Allie; Laux, Reneé; Brantley, Milam A.; Agarwal, Anita; Ersoy, Lebriz; Caramoy, Albert; Langmann, Thomas; Saksens, Nicole T. M.; de Jong, Eiko K.; Hoyng, Carel B.; Cain, Melinda S.; Richardson, Andrea J.; Martin, Tammy M.; Blangero, John; Weeks, Daniel E.; Dhillon, Bal; van Duijn, Cornelia M.; Doheny, Kimberly F.; Romm, Jane; Klaver, Caroline C. W.; Hayward, Caroline; Gorin, Michael B.; Klein, Michael L.; Baird, Paul N.; den Hollander, Anneke I.; Fauser, Sascha; Yates, John R. W.; Allikmets, Rando; Wang, Jie Jin; Schaumberg, Debra A.; Klein, Barbara E. K.; Hagstrom, Stephanie A.; Chowers, Itay; Lotery, Andrew J.; Léveillard, Thierry; Zhang, Kang; Brilliant, Murray H.; Hewitt, Alex W.; Swaroop, Anand; Chew, Emily Y.; Pericak-Vance, Margaret A.; DeAngelis, Margaret; Stambolian, Dwight; Haines, Jonathan L.; Iyengar, Sudha K.; Weber, Bernhard H. F.; Abecasis, Gonçalo R.; Heid, Iris M.
2016-01-01
Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly with limited therapeutic options. Here, we report on a study of >12 million variants including 163,714 directly genotyped, most rare, protein-altering variant. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5×10–8) distributed across 34 loci. While wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first signal specific to wet AMD, near MMP9 (difference-P = 4.1×10–10). Very rare coding variants (frequency < 0.1%) in CFH, CFI, and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes. PMID:26691988
Whole exome sequencing for familial bicuspid aortic valve identifies putative variants.
Martin, Lisa J; Pilipenko, Valentina; Kaufman, Kenneth M; Cripe, Linda; Kottyan, Leah C; Keddache, Mehdi; Dexheimer, Phillip; Weirauch, Matthew T; Benson, D Woodrow
2014-10-01
Bicuspid aortic valve (BAV) is the most common congenital cardiovascular malformation. Although highly heritable, few causal variants have been identified. The purpose of this study was to identify genetic variants underlying BAV by whole exome sequencing a multiplex BAV kindred. Whole exome sequencing was performed on 17 individuals from a single family (BAV=3; other cardiovascular malformation, 3). Postvariant calling error control metrics were established after examining the relationship between Mendelian inheritance error rate and coverage, quality score, and call rate. To determine the most effective approach to identifying susceptibility variants from among 54 674 variants passing error control metrics, we evaluated 3 variant selection strategies frequently used in whole exome sequencing studies plus extended family linkage. No putative rare, high-effect variants were identified in all affected but no unaffected individuals. Eight high-effect variants were identified by ≥2 of the commonly used selection strategies; however, these were either common in the general population (>10%) or present in the majority of the unaffected family members. However, using extended family linkage, 3 synonymous variants were identified; all 3 variants were identified by at least one other strategy. These results suggest that traditional whole exome sequencing approaches, which assume causal variants alter coding sense, may be insufficient for BAV and other complex traits. Identification of disease-associated variants is facilitated by the use of segregation within families. © 2014 American Heart Association, Inc.
Generalized functional linear models for gene-based case-control association studies.
Fan, Ruzong; Wang, Yifan; Mills, James L; Carter, Tonia C; Lobach, Iryna; Wilson, Alexander F; Bailey-Wilson, Joan E; Weeks, Daniel E; Xiong, Momiao
2014-11-01
By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene region are disease related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease datasets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. © 2014 WILEY PERIODICALS, INC.
Generalized Functional Linear Models for Gene-based Case-Control Association Studies
Mills, James L.; Carter, Tonia C.; Lobach, Iryna; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Weeks, Daniel E.; Xiong, Momiao
2014-01-01
By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene are disease-related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease data sets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. PMID:25203683
Establishing the role of rare coding variants in known Parkinson's disease risk loci.
Jansen, Iris E; Gibbs, J Raphael; Nalls, Mike A; Price, T Ryan; Lubbe, Steven; van Rooij, Jeroen; Uitterlinden, André G; Kraaij, Robert; Williams, Nigel M; Brice, Alexis; Hardy, John; Wood, Nicholas W; Morris, Huw R; Gasser, Thomas; Singleton, Andrew B; Heutink, Peter; Sharma, Manu
2017-11-01
Many common genetic factors have been identified to contribute to Parkinson's disease (PD) susceptibility, improving our understanding of the related underlying biological mechanisms. The involvement of rarer variants in these loci has been poorly studied. Using International Parkinson's Disease Genomics Consortium data sets, we performed a comprehensive study to determine the impact of rare variants in 23 previously published genome-wide association studies (GWAS) loci in PD. We applied Prix fixe to select the putative causal genes underneath the GWAS peaks, which was based on underlying functional similarities. The Sequence Kernel Association Test was used to analyze the joint effect of rare, common, or both types of variants on PD susceptibility. All genes were tested simultaneously as a gene set and each gene individually. We observed a moderate association of common variants, confirming the involvement of the known PD risk loci within our genetic data sets. Focusing on rare variants, we identified additional association signals for LRRK2, STBD1, and SPATA19. Our study suggests an involvement of rare variants within several putatively causal genes underneath previously identified PD GWAS peaks. Copyright © 2017 Elsevier Inc. All rights reserved.
Molecular Diagnosis of Cystic Fibrosis.
Deignan, Joshua L; Grody, Wayne W
2016-01-01
This unit describes a recommended approach to identifying causal genetic variants in an individual suspected of having cystic fibrosis. An introduction to the genetics and clinical presentation of cystic fibrosis is initially presented, followed by a description of the two main strategies used in the molecular diagnosis of cystic fibrosis: (1) an initial targeted variant panel used to detect only the most common cystic fibrosis-causing variants in the CFTR gene, and (2) sequencing of the entire coding region of the CFTR gene to detect additional rare causal CFTR variants. Finally, the unit concludes with a discussion regarding the analytic and clinical validity of these approaches. Copyright © 2016 John Wiley & Sons, Inc.
Functional linear models for association analysis of quantitative traits.
Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao
2013-11-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY PERIODICALS, INC.
Identifying Causal Variants at Loci with Multiple Signals of Association
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-01-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20–50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515
Identifying causal variants at loci with multiple signals of association.
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-10-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. Copyright © 2014 by the Genetics Society of America.
Clinical Applications of Molecular Genetic Discoveries
Marian, A.J.
2015-01-01
Genome-wide association studies (GWAS) of complex traits have mapped more than 15,000 common single nucleotide variants (SNVs). Likewise, applications of massively parallel nucleic acid sequencing technologies often referred to as Next Generation Sequencing, to molecular genetic studies of complex traits have catalogued a large number of rare variants (population frequency of <0.01) in cases with complex traits. Moreover, high throughput nucleic acid sequencing, variant burden analysis, and linkage studies are illuminating the presence of large number of SNVs in cases and families with single gene disorders. The plethora of the genetic variants has exposed the formidable challenge of identifying the causal and pathogenic variants from the enormous number of innocuous common and rare variants that exist in the population as well as in an individual genome. The arduous task of identifying the causal and pathogenic variants is further compounded by the pleiotropic effects of the variants, complexity of cis and trans interactions in the genome, variability in phenotypic expression of the disease, as well as phenotypic plasticity, and the multifarious determinants of the phenotype. Population genetic studies offer the initial roadmaps and have the potential to elucidate novel pathways involved in the pathogenesis of the disease. However, the genome of an individual is unique, rendering unambiguous identification of the causal or pathogenic variant in a single individual exceedingly challenging. Yet, the focus of the practice of medicine is on the individual, as Sir William Osler elegantly expressed in his insightful quotation: “The good physician treats the disease; the great physician treats the patient who has the disease.” The daunting task facing physicians, patients, and researchers alike is to apply the modern genetic discoveries to care of the individual with or at risk of the disease. PMID:26548329
Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer
Lawrenson, Kate; Iversen, Edwin S.; Tyrer, Jonathan; Weber, Rachel Palmieri; Concannon, Patrick; Hazelett, Dennis J.; Li, Qiyuan; Marks, Jeffrey R.; Berchuck, Andrew; Lee, Janet M.; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Bandera, Elisa V.; Bean, Yukie; Beckmann, Matthias W.; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G.; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; Plisiecka-Halasa, Joanna; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Eccles, Diana; Easton, Douglas T.; Edwards, Robert P.; Eilber, Ursula; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Gronwald, Jacek; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Jakubowska, Anna; Paul, James; Jensen, Allan; Karlan, Beth Y.; Kjaer, Susanne Kruger; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph L.; Kiemeney, Lambertus A.; Krakstad, Camilla; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Cannioto, Rikki; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; Nevanlinna, Heli; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Noor Azmi, Mat Adenan; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Pearce, Celeste L.; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Budzilowska, Agnieszka; Sellers, Thomas A.; Shu, Xiao-Ou; Shvetsov, Yurii B.; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston, Lara; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J.; Timorek, Agnieszka; Tworoger, Shelley S.; Nieuwenhuysen, Els Van; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Coetzee, Gerhard A.; Freedman, Matthew L.; Monteiro, Alvaro N.A.; Moes-Sosnowska, Joanna; Kupryjanczyk, Jolanta; Pharoah, Paul D.; Gayther, Simon A.; Schildkraut, Joellen M.
2015-01-01
Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10–7). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r 2 with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11–1.24, P = 1.1×10−7). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10−8). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r 2 = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10-8). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene. PMID:26424751
Temporal Expression Profiling Identifies Pathways Mediating Effect of Causal Variant on Phenotype
Gupta, Saumya; Radhakrishnan, Aparna; Raharja-Liu, Pandu; Lin, Gen; Steinmetz, Lars M.; Gagneur, Julien; Sinha, Himanshu
2015-01-01
Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants’ effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage of analyzing allele-specific transcriptional dynamics of mediating genes. Applications in higher eukaryotes can be valuable for inferring causal molecular pathways underlying complex dynamic processes, such as development, physiology and disease progression. PMID:26039065
Negligible impact of rare autoimmune-locus coding-region variants on missing heritability.
Hunt, Karen A; Mistry, Vanisha; Bockett, Nicholas A; Ahmad, Tariq; Ban, Maria; Barker, Jonathan N; Barrett, Jeffrey C; Blackburn, Hannah; Brand, Oliver; Burren, Oliver; Capon, Francesca; Compston, Alastair; Gough, Stephen C L; Jostins, Luke; Kong, Yong; Lee, James C; Lek, Monkol; MacArthur, Daniel G; Mansfield, John C; Mathew, Christopher G; Mein, Charles A; Mirza, Muddassar; Nutland, Sarah; Onengut-Gumuscu, Suna; Papouli, Efterpi; Parkes, Miles; Rich, Stephen S; Sawcer, Steven; Satsangi, Jack; Simmonds, Matthew J; Trembath, Richard C; Walker, Neil M; Wozniak, Eva; Todd, John A; Simpson, Michael A; Plagnol, Vincent; van Heel, David A
2013-06-13
Genome-wide association studies (GWAS) have identified common variants of modest-effect size at hundreds of loci for common autoimmune diseases; however, a substantial fraction of heritability remains unexplained, to which rare variants may contribute. To discover rare variants and test them for association with a phenotype, most studies re-sequence a small initial sample size and then genotype the discovered variants in a larger sample set. This approach fails to analyse a large fraction of the rare variants present in the entire sample set. Here we perform simultaneous amplicon-sequencing-based variant discovery and genotyping for coding exons of 25 GWAS risk genes in 41,911 UK residents of white European origin, comprising 24,892 subjects with six autoimmune disease phenotypes and 17,019 controls, and show that rare coding-region variants at known loci have a negligible role in common autoimmune disease susceptibility. These results do not support the rare-variant synthetic genome-wide-association hypothesis (in which unobserved rare causal variants lead to association detected at common tag variants). Many known autoimmune disease risk loci contain multiple, independently associated, common and low-frequency variants, and so genes at these loci are a priori stronger candidates for harbouring rare coding-region variants than other genes. Our data indicate that the missing heritability for common autoimmune diseases may not be attributable to the rare coding-region variant portion of the allelic spectrum, but perhaps, as others have proposed, may be a result of many common-variant loci of weak effect.
Assessing the Power of Exome Chips.
Page, Christian Magnus; Baranzini, Sergio E; Mevik, Bjørn-Helge; Bos, Steffan Daniel; Harbo, Hanne F; Andreassen, Bettina Kulle
2015-01-01
Genotyping chips for rare and low-frequent variants have recently gained popularity with the introduction of exome chips, but the utility of these chips remains unclear. These chips were designed using exome sequencing data from mainly American-European individuals, enriched for a narrow set of common diseases. In addition, it is well-known that the statistical power of detecting associations with rare and low-frequent variants is much lower compared to studies exclusively involving common variants. We developed a simulation program adaptable to any exome chip design to empirically evaluate the power of the exome chips. We implemented the main properties of the Illumina HumanExome BeadChip array. The simulated data sets were used to assess the power of exome chip based studies for varying effect sizes and causal variant scenarios. We applied two widely-used statistical approaches for rare and low-frequency variants, which collapse the variants into genetic regions or genes. Under optimal conditions, we found that a sample size between 20,000 to 30,000 individuals were needed in order to detect modest effect sizes (0.5% < PAR > 1%) with 80% power. For small effect sizes (PAR <0.5%), 60,000-100,000 individuals were needed in the presence of non-causal variants. In conclusion, we found that at least tens of thousands of individuals are necessary to detect modest effects under optimal conditions. In addition, when using rare variant chips on cohorts or diseases they were not originally designed for, the identification of associated variants or genes will be even more challenging.
Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K.; Thomas, Venetta; Ambrosone, Christine B.; Bandera, Elisa V.; Berndt, Sonja I.; Bernstein, Leslie; Blot, William J.; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J.; Cheng, Iona; Chu, Lisa; Deming, Sandra L.; Driver, W. Ryan; Goodman, Phyllis; Hayes, Richard B.; Hennis, Anselm J. M.; Hsing, Ann W.; Hu, Jennifer J.; Ingles, Sue A.; John, Esther M.; Kittles, Rick A.; Kolb, Suzanne; Leske, M. Cristina; Monroe, Kristine R.; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F.; Rodriguez-Gil, Jorge L.; Rybicki, Ben A.; Schumacher, Fredrick; Stanford, Janet L.; Signorello, Lisa B.; Strom, Sara S.; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S.; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G.; Stram, Alexander H.; Kolonel, Laurence N.; Marchand, Loïc Le; Henderson, Brian E.; Haiman, Christopher A.; Stram, Daniel O.
2015-01-01
Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious. PMID:26125186
Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K; Thomas, Venetta; Ambrosone, Christine B; Bandera, Elisa V; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J; Cheng, Iona; Chu, Lisa; Deming, Sandra L; Driver, W Ryan; Goodman, Phyllis; Hayes, Richard B; Hennis, Anselm J M; Hsing, Ann W; Hu, Jennifer J; Ingles, Sue A; John, Esther M; Kittles, Rick A; Kolb, Suzanne; Leske, M Cristina; Millikan, Robert C; Monroe, Kristine R; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F; Rodriguez-Gil, Jorge L; Rybicki, Ben A; Schumacher, Fredrick; Stanford, Janet L; Signorello, Lisa B; Strom, Sara S; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G; Stram, Alexander H; Kolonel, Laurence N; Le Marchand, Loïc; Henderson, Brian E; Haiman, Christopher A; Stram, Daniel O
2015-01-01
Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.
The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.
Astle, William J; Elding, Heather; Jiang, Tao; Allen, Dave; Ruklisa, Dace; Mann, Alice L; Mead, Daniel; Bouman, Heleen; Riveros-Mckay, Fernando; Kostadima, Myrto A; Lambourne, John J; Sivapalaratnam, Suthesh; Downes, Kate; Kundu, Kousik; Bomba, Lorenzo; Berentsen, Kim; Bradley, John R; Daugherty, Louise C; Delaneau, Olivier; Freson, Kathleen; Garner, Stephen F; Grassi, Luigi; Guerrero, Jose; Haimel, Matthias; Janssen-Megens, Eva M; Kaan, Anita; Kamat, Mihir; Kim, Bowon; Mandoli, Amit; Marchini, Jonathan; Martens, Joost H A; Meacham, Stuart; Megy, Karyn; O'Connell, Jared; Petersen, Romina; Sharifi, Nilofar; Sheard, Simon M; Staley, James R; Tuna, Salih; van der Ent, Martijn; Walter, Klaudia; Wang, Shuang-Yin; Wheeler, Eleanor; Wilder, Steven P; Iotchkova, Valentina; Moore, Carmel; Sambrook, Jennifer; Stunnenberg, Hendrik G; Di Angelantonio, Emanuele; Kaptoge, Stephen; Kuijpers, Taco W; Carrillo-de-Santa-Pau, Enrique; Juan, David; Rico, Daniel; Valencia, Alfonso; Chen, Lu; Ge, Bing; Vasquez, Louella; Kwan, Tony; Garrido-Martín, Diego; Watt, Stephen; Yang, Ying; Guigo, Roderic; Beck, Stephan; Paul, Dirk S; Pastinen, Tomi; Bujold, David; Bourque, Guillaume; Frontini, Mattia; Danesh, John; Roberts, David J; Ouwehand, Willem H; Butterworth, Adam S; Soranzo, Nicole
2016-11-17
Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal. Copyright © 2016 Elsevier Inc. All rights reserved.
Common variants associated with plasma triglycerides and risk for coronary artery disease
USDA-ARS?s Scientific Manuscript database
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common va...
Tada, Hayato; Kawashiri, Masa-Aki; Yamagishi, Masakazu
2017-04-01
Dyslipidemias, especially hyper-low-density lipoprotein cholesterolemia and hypertriglyceridemia, are important causal risk factors for coronary artery disease. Comprehensive genotyping using the 'next-generation sequencing' technique has facilitated the investigation of Mendelian dyslipidemias, in addition to Mendelian randomization studies using common genetic variants associated with plasma lipids and coronary artery disease. The beneficial effects of low-density lipoprotein cholesterol-lowering therapies on coronary artery disease have been verified by many randomized controlled trials over the years, and subsequent genetic studies have supported these findings. More recently, Mendelian randomization studies have preceded randomized controlled trials. When the on-target/off-target effects of rare variants and common variants exhibit the same direction, novel drugs targeting molecules identified by investigations of rare Mendelian lipid disorders could be promising. Such a strategy could aid in the search for drug discovery seeds other than those for dyslipidemias.
Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer.
Lawrenson, Kate; Iversen, Edwin S; Tyrer, Jonathan; Weber, Rachel Palmieri; Concannon, Patrick; Hazelett, Dennis J; Li, Qiyuan; Marks, Jeffrey R; Berchuck, Andrew; Lee, Janet M; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Bandera, Elisa V; Bean, Yukie; Beckmann, Matthias W; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel W; Cunningham, Julie M; Cybulski, Cezary; Plisiecka-Halasa, Joanna; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Eccles, Diana; Easton, Douglas T; Edwards, Robert P; Eilber, Ursula; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Gronwald, Jacek; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Jakubowska, Anna; Paul, James; Jensen, Allan; Karlan, Beth Y; Kjaer, Susanne Kruger; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph L; Kiemeney, Lambertus A; Krakstad, Camilla; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Cannioto, Rikki; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Nevanlinna, Heli; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Noor Azmi, Mat Adenan; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Pearce, Celeste L; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Budzilowska, Agnieszka; Sellers, Thomas A; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston, Lara; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Coetzee, Gerhard A; Freedman, Matthew L; Monteiro, Alvaro N A; Moes-Sosnowska, Joanna; Kupryjanczyk, Jolanta; Pharoah, Paul D; Gayther, Simon A; Schildkraut, Joellen M
2015-11-01
Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
The HABP2 G534E polymorphism does not increase nonmedullary thyroid cancer risk in Hispanics
Bohórquez, Mabel E; Estrada, Ana P; Stultz, Jacob; Sahasrabudhe, Ruta; Williamson, John; Lott, Paul; Duque, Carlos S; Donado, Jorge; Mateus, Gilbert; Bolaños, Fernando; Vélez, Alejandro; Echeverry, Magdalena
2016-01-01
Familial nonmedullary thyroid cancer (NMTC) has not been clearly linked to causal germline variants, despite the large role that genetic factors play in risk. Recently, HABP2 G534E (rs7080536A) has been implicated as a causal variant in NMTC. We have previously shown that the HABP2 G534E variant is not associated with TC risk in patients from the British Isles. Hispanics are the largest and the youngest minority in the United States and NMTC is now the second most common malignancy in women from this population. In order to determine if the HABP2 G534E variant played a role in NMTC risk among Hispanic populations, we analyzed 281 cases and 1105 population-matched controls from a multicenter study in Colombia, evaluating the association through logistic regression. We found that the HABP2 G534E variant was not significantly associated with NMTC risk (P=0.843) in this Hispanic group. We also stratified available clinical data by multiple available clinicopathological variables and further analyzed the effect of HABP2 on NMTC presentation. However, we failed to detect associations between HABP2 G534E and NMTC risk, regardless of disease presentation (P≥0.273 for all cases). Therefore, without any significant associations between the HABP2 G534E variant and NMTC risk, we conclude that the variant is not causal of NMTC in this Hispanic population. PMID:27097599
Genetics of Triglycerides and the Risk of Atherosclerosis.
Dron, Jacqueline S; Hegele, Robert A
2017-07-01
Plasma triglycerides are routinely measured with a lipid profile, and elevated plasma triglycerides are commonly encountered in the clinic. The confounded nature of this trait, which is correlated with numerous other metabolic perturbations, including depressed high-density lipoprotein cholesterol (HDL-C), has thwarted efforts to directly implicate triglycerides as causal in atherogenesis. Human genetic approaches involving large-scale populations and high-throughput genomic assessment under a Mendelian randomization framework have undertaken to sort out questions of causality. We review recent large-scale meta-analyses of cohorts and population-based sequencing studies designed to address whether common and rare variants in genes whose products are determinants of plasma triglycerides are also associated with clinical cardiovascular endpoints. The studied loci include genes encoding lipoprotein lipase and proteins that interact with it, such as apolipoprotein (apo) A-V, apo C-III and angiopoietin-like proteins 3 and 4, and common polymorphisms identified in genome-wide association studies. Triglyceride-raising variant alleles of these genes showed generally strong associations with clinical cardiovascular endpoints. However, in most cases, a second lipid disturbance-usually depressed HDL-C-was concurrently associated. While the findings collectively shift our understanding towards a potential causal role for triglycerides, we still cannot rule out the possibilities that triglycerides are a component of a joint phenotype with low HDL-C or that they are but markers of deeper causal metabolic disturbances that are not routinely measured in epidemiological-scale genetic studies.
TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies
van der Sluis, Sophie; Posthuma, Danielle; Dolan, Conor V.
2013-01-01
To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor. PMID:23359524
Measuring missing heritability: Inferring the contribution of common variants
Golan, David; Lander, Eric S.; Rosset, Saharon
2014-01-01
Genome-wide association studies (GWASs), also called common variant association studies (CVASs), have uncovered thousands of genetic variants associated with hundreds of diseases. However, the variants that reach statistical significance typically explain only a small fraction of the heritability. One explanation for the “missing heritability” is that there are many additional disease-associated common variants whose effects are too small to detect with current sample sizes. It therefore is useful to have methods to quantify the heritability due to common variation, without having to identify all causal variants. Recent studies applied restricted maximum likelihood (REML) estimation to case–control studies for diseases. Here, we show that REML considerably underestimates the fraction of heritability due to common variation in this setting. The degree of underestimation increases with the rarity of disease, the heritability of the disease, and the size of the sample. Instead, we develop a general framework for heritability estimation, called phenotype correlation–genotype correlation (PCGC) regression, which generalizes the well-known Haseman–Elston regression method. We show that PCGC regression yields unbiased estimates. Applying PCGC regression to six diseases, we estimate the proportion of the phenotypic variance due to common variants to range from 25% to 56% and the proportion of heritability due to common variants from 41% to 68% (mean 60%). These results suggest that common variants may explain at least half the heritability for many diseases. PCGC regression also is readily applicable to other settings, including analyzing extreme-phenotype studies and adjusting for covariates such as sex, age, and population structure. PMID:25422463
Guidelines for investigating causality of sequence variants in human disease
MacArthur, D. G.; Manolio, T. A.; Dimmock, D. P.; Rehm, H. L.; Shendure, J.; Abecasis, G. R.; Adams, D. R.; Altman, R. B.; Antonarakis, S. E.; Ashley, E. A.; Barrett, J. C.; Biesecker, L. G.; Conrad, D. F.; Cooper, G. M.; Cox, N. J.; Daly, M. J.; Gerstein, M. B.; Goldstein, D. B.; Hirschhorn, J. N.; Leal, S. M.; Pennacchio, L. A.; Stamatoyannopoulos, J. A.; Sunyaev, S. R.; Valle, D.; Voight, B. F.; Winckler, W.; Gunter, C.
2014-01-01
The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development. PMID:24759409
Guidelines for investigating causality of sequence variants in human disease.
MacArthur, D G; Manolio, T A; Dimmock, D P; Rehm, H L; Shendure, J; Abecasis, G R; Adams, D R; Altman, R B; Antonarakis, S E; Ashley, E A; Barrett, J C; Biesecker, L G; Conrad, D F; Cooper, G M; Cox, N J; Daly, M J; Gerstein, M B; Goldstein, D B; Hirschhorn, J N; Leal, S M; Pennacchio, L A; Stamatoyannopoulos, J A; Sunyaev, S R; Valle, D; Voight, B F; Winckler, W; Gunter, C
2014-04-24
The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.
Yamagishi, Kazumasa; Tanigawa, Takeshi; Kitamura, Akihiko; Köttgen, Anna; Folsom, Aaron R; Iso, Hiroyasu
2010-08-01
Recent genome-wide association and functional studies have shown that the ABCG2 gene encodes for a urate transporter, and a common causal ABCG2 variant, rs2231142, leads to elevated uric acid levels and prevalent gout among Whites and Blacks. We examined whether this finding is observed in a Japanese population, since Asians have a high reported prevalence of the T-risk allele. A total of 3923 Japanese people from the Circulatory Risk in Communities Study aged 40-90 years were genotyped for rs2231142. Associations of the rs2231142 variant with serum uric acid levels and prevalence of gout and hyperuricaemia were examined. The frequency of the T-risk allele was 31% in this Japanese sample. Multivariable adjusted mean uric acid levels were 7-9 micromol/l higher for TG and TT than GG carriers (P-additive = 0.0006). The multivariable-adjusted odds ratio (OR) of prevalent gout was 1.37 (95% CI 0.68, 2.76) for TG and 4.37 (95% CI 1.98, 9.62) for TT compared with the GG carriers (P-additive = 0.001). When evaluating the combined outcome of hyperuricaemia and gout, the respective ORs were 1.40 (95% CI 1.04, 1.87) for TG and 1.88 (95% CI 1.23, 2.89) for TT carriers. The population attributable risk was 29% for gout and 19% for gout and/or hyperuricaemia. The association of the causal ABCG2 rs2231142 variant with uric acid levels and gout was confirmed in a sample of Japanese ancestry. Our study emphasizes the importance of this common causal variant in a population with a high risk allele frequency, especially as more Japanese adopt a Western lifestyle with a concomitant increase in mean serum uric acid levels.
Common variants associated with plasma triglycerides and risk for coronary artery disease.
Do, Ron; Willer, Cristen J; Schmidt, Ellen M; Sengupta, Sebanti; Gao, Chi; Peloso, Gina M; Gustafsson, Stefan; Kanoni, Stavroula; Ganna, Andrea; Chen, Jin; Buchkovich, Martin L; Mora, Samia; Beckmann, Jacques S; Bragg-Gresham, Jennifer L; Chang, Hsing-Yi; Demirkan, Ayşe; Den Hertog, Heleen M; Donnelly, Louise A; Ehret, Georg B; Esko, Tõnu; Feitosa, Mary F; Ferreira, Teresa; Fischer, Krista; Fontanillas, Pierre; Fraser, Ross M; Freitag, Daniel F; Gurdasani, Deepti; Heikkilä, Kauko; Hyppönen, Elina; Isaacs, Aaron; Jackson, Anne U; Johansson, Asa; Johnson, Toby; Kaakinen, Marika; Kettunen, Johannes; Kleber, Marcus E; Li, Xiaohui; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Magnusson, Patrik K E; Mangino, Massimo; Mihailov, Evelin; Montasser, May E; Müller-Nurasyid, Martina; Nolte, Ilja M; O'Connell, Jeffrey R; Palmer, Cameron D; Perola, Markus; Petersen, Ann-Kristin; Sanna, Serena; Saxena, Richa; Service, Susan K; Shah, Sonia; Shungin, Dmitry; Sidore, Carlo; Song, Ci; Strawbridge, Rona J; Surakka, Ida; Tanaka, Toshiko; Teslovich, Tanya M; Thorleifsson, Gudmar; Van den Herik, Evita G; Voight, Benjamin F; Volcik, Kelly A; Waite, Lindsay L; Wong, Andrew; Wu, Ying; Zhang, Weihua; Absher, Devin; Asiki, Gershim; Barroso, Inês; Been, Latonya F; Bolton, Jennifer L; Bonnycastle, Lori L; Brambilla, Paolo; Burnett, Mary S; Cesana, Giancarlo; Dimitriou, Maria; Doney, Alex S F; Döring, Angela; Elliott, Paul; Epstein, Stephen E; Eyjolfsson, Gudmundur Ingi; Gigante, Bruna; Goodarzi, Mark O; Grallert, Harald; Gravito, Martha L; Groves, Christopher J; Hallmans, Göran; Hartikainen, Anna-Liisa; Hayward, Caroline; Hernandez, Dena; Hicks, Andrew A; Holm, Hilma; Hung, Yi-Jen; Illig, Thomas; Jones, Michelle R; Kaleebu, Pontiano; Kastelein, John J P; Khaw, Kay-Tee; Kim, Eric; Klopp, Norman; Komulainen, Pirjo; Kumari, Meena; Langenberg, Claudia; Lehtimäki, Terho; Lin, Shih-Yi; Lindström, Jaana; Loos, Ruth J F; Mach, François; McArdle, Wendy L; Meisinger, Christa; Mitchell, Braxton D; Müller, Gabrielle; Nagaraja, Ramaiah; Narisu, Narisu; Nieminen, Tuomo V M; Nsubuga, Rebecca N; Olafsson, Isleifur; Ong, Ken K; Palotie, Aarno; Papamarkou, Theodore; Pomilla, Cristina; Pouta, Anneli; Rader, Daniel J; Reilly, Muredach P; Ridker, Paul M; Rivadeneira, Fernando; Rudan, Igor; Ruokonen, Aimo; Samani, Nilesh; Scharnagl, Hubert; Seeley, Janet; Silander, Kaisa; Stančáková, Alena; Stirrups, Kathleen; Swift, Amy J; Tiret, Laurence; Uitterlinden, Andre G; van Pelt, L Joost; Vedantam, Sailaja; Wainwright, Nicholas; Wijmenga, Cisca; Wild, Sarah H; Willemsen, Gonneke; Wilsgaard, Tom; Wilson, James F; Young, Elizabeth H; Zhao, Jing Hua; Adair, Linda S; Arveiler, Dominique; Assimes, Themistocles L; Bandinelli, Stefania; Bennett, Franklyn; Bochud, Murielle; Boehm, Bernhard O; Boomsma, Dorret I; Borecki, Ingrid B; Bornstein, Stefan R; Bovet, Pascal; Burnier, Michel; Campbell, Harry; Chakravarti, Aravinda; Chambers, John C; Chen, Yii-Der Ida; Collins, Francis S; Cooper, Richard S; Danesh, John; Dedoussis, George; de Faire, Ulf; Feranil, Alan B; Ferrières, Jean; Ferrucci, Luigi; Freimer, Nelson B; Gieger, Christian; Groop, Leif C; Gudnason, Vilmundur; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B; Hingorani, Aroon; Hirschhorn, Joel N; Hofman, Albert; Hovingh, G Kees; Hsiung, Chao Agnes; Humphries, Steve E; Hunt, Steven C; Hveem, Kristian; Iribarren, Carlos; Järvelin, Marjo-Riitta; Jula, Antti; Kähönen, Mika; Kaprio, Jaakko; Kesäniemi, Antero; Kivimaki, Mika; Kooner, Jaspal S; Koudstaal, Peter J; Krauss, Ronald M; Kuh, Diana; Kuusisto, Johanna; Kyvik, Kirsten O; Laakso, Markku; Lakka, Timo A; Lind, Lars; Lindgren, Cecilia M; Martin, Nicholas G; März, Winfried; McCarthy, Mark I; McKenzie, Colin A; Meneton, Pierre; Metspalu, Andres; Moilanen, Leena; Morris, Andrew D; Munroe, Patricia B; Njølstad, Inger; Pedersen, Nancy L; Power, Chris; Pramstaller, Peter P; Price, Jackie F; Psaty, Bruce M; Quertermous, Thomas; Rauramaa, Rainer; Saleheen, Danish; Salomaa, Veikko; Sanghera, Dharambir K; Saramies, Jouko; Schwarz, Peter E H; Sheu, Wayne H-H; Shuldiner, Alan R; Siegbahn, Agneta; Spector, Tim D; Stefansson, Kari; Strachan, David P; Tayo, Bamidele O; Tremoli, Elena; Tuomilehto, Jaakko; Uusitupa, Matti; van Duijn, Cornelia M; Vollenweider, Peter; Wallentin, Lars; Wareham, Nicholas J; Whitfield, John B; Wolffenbuttel, Bruce H R; Altshuler, David; Ordovas, Jose M; Boerwinkle, Eric; Palmer, Colin N A; Thorsteinsdottir, Unnur; Chasman, Daniel I; Rotter, Jerome I; Franks, Paul W; Ripatti, Samuli; Cupples, L Adrienne; Sandhu, Manjinder S; Rich, Stephen S; Boehnke, Michael; Deloukas, Panos; Mohlke, Karen L; Ingelsson, Erik; Abecasis, Goncalo R; Daly, Mark J; Neale, Benjamin M; Kathiresan, Sekar
2013-11-01
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
Common variants associated with plasma triglycerides and risk for coronary artery disease
Do, Ron; Willer, Cristen J.; Schmidt, Ellen M.; Sengupta, Sebanti; Gao, Chi; Peloso, Gina M.; Gustafsson, Stefan; Kanoni, Stavroula; Ganna, Andrea; Chen, Jin; Buchkovich, Martin L.; Mora, Samia; Beckmann, Jacques S.; Bragg-Gresham, Jennifer L.; Chang, Hsing-Yi; Demirkan, Ayşe; Den Hertog, Heleen M.; Donnelly, Louise A.; Ehret, Georg B.; Esko, Tõnu; Feitosa, Mary F.; Ferreira, Teresa; Fischer, Krista; Fontanillas, Pierre; Fraser, Ross M.; Freitag, Daniel F.; Gurdasani, Deepti; Heikkilä, Kauko; Hyppönen, Elina; Isaacs, Aaron; Jackson, Anne U.; Johansson, Åsa; Johnson, Toby; Kaakinen, Marika; Kettunen, Johannes; Kleber, Marcus E.; Li, Xiaohui; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Magnusson, Patrik K.E.; Mangino, Massimo; Mihailov, Evelin; Montasser, May E.; Müller-Nurasyid, Martina; Nolte, Ilja M.; O'Connell, Jeffrey R.; Palmer, Cameron D.; Perola, Markus; Petersen, Ann-Kristin; Sanna, Serena; Saxena, Richa; Service, Susan K.; Shah, Sonia; Shungin, Dmitry; Sidore, Carlo; Song, Ci; Strawbridge, Rona J.; Surakka, Ida; Tanaka, Toshiko; Teslovich, Tanya M.; Thorleifsson, Gudmar; Van den Herik, Evita G.; Voight, Benjamin F.; Volcik, Kelly A.; Waite, Lindsay L.; Wong, Andrew; Wu, Ying; Zhang, Weihua; Absher, Devin; Asiki, Gershim; Barroso, Inês; Been, Latonya F.; Bolton, Jennifer L.; Bonnycastle, Lori L; Brambilla, Paolo; Burnett, Mary S.; Cesana, Giancarlo; Dimitriou, Maria; Doney, Alex S.F.; Döring, Angela; Elliott, Paul; Epstein, Stephen E.; Eyjolfsson, Gudmundur Ingi; Gigante, Bruna; Goodarzi, Mark O.; Grallert, Harald; Gravito, Martha L.; Groves, Christopher J.; Hallmans, Göran; Hartikainen, Anna-Liisa; Hayward, Caroline; Hernandez, Dena; Hicks, Andrew A.; Holm, Hilma; Hung, Yi-Jen; Illig, Thomas; Jones, Michelle R.; Kaleebu, Pontiano; Kastelein, John J.P.; Khaw, Kay-Tee; Kim, Eric; Klopp, Norman; Komulainen, Pirjo; Kumari, Meena; Langenberg, Claudia; Lehtimäki, Terho; Lin, Shih-Yi; Lindström, Jaana; Loos, Ruth J.F.; Mach, François; McArdle, Wendy L; Meisinger, Christa; Mitchell, Braxton D.; Müller, Gabrielle; Nagaraja, Ramaiah; Narisu, Narisu; Nieminen, Tuomo V.M.; Nsubuga, Rebecca N.; Olafsson, Isleifur; Ong, Ken K.; Palotie, Aarno; Papamarkou, Theodore; Pomilla, Cristina; Pouta, Anneli; Rader, Daniel J.; Reilly, Muredach P.; Ridker, Paul M.; Rivadeneira, Fernando; Rudan, Igor; Ruokonen, Aimo; Samani, Nilesh; Scharnagl, Hubert; Seeley, Janet; Silander, Kaisa; Stančáková, Alena; Stirrups, Kathleen; Swift, Amy J.; Tiret, Laurence; Uitterlinden, Andre G.; van Pelt, L. Joost; Vedantam, Sailaja; Wainwright, Nicholas; Wijmenga, Cisca; Wild, Sarah H.; Willemsen, Gonneke; Wilsgaard, Tom; Wilson, James F.; Young, Elizabeth H.; Zhao, Jing Hua; Adair, Linda S.; Arveiler, Dominique; Assimes, Themistocles L.; Bandinelli, Stefania; Bennett, Franklyn; Bochud, Murielle; Boehm, Bernhard O.; Boomsma, Dorret I.; Borecki, Ingrid B.; Bornstein, Stefan R.; Bovet, Pascal; Burnier, Michel; Campbell, Harry; Chakravarti, Aravinda; Chambers, John C.; Chen, Yii-Der Ida; Collins, Francis S.; Cooper, Richard S.; Danesh, John; Dedoussis, George; de Faire, Ulf; Feranil, Alan B.; Ferrières, Jean; Ferrucci, Luigi; Freimer, Nelson B.; Gieger, Christian; Groop, Leif C.; Gudnason, Vilmundur; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B.; Hingorani, Aroon; Hirschhorn, Joel N.; Hofman, Albert; Hovingh, G. Kees; Hsiung, Chao Agnes; Humphries, Steve E.; Hunt, Steven C.; Hveem, Kristian; Iribarren, Carlos; Järvelin, Marjo-Riitta; Jula, Antti; Kähönen, Mika; Kaprio, Jaakko; Kesäniemi, Antero; Kivimaki, Mika; Kooner, Jaspal S.; Koudstaal, Peter J.; Krauss, Ronald M.; Kuh, Diana; Kuusisto, Johanna; Kyvik, Kirsten O.; Laakso, Markku; Lakka, Timo A.; Lind, Lars; Lindgren, Cecilia M.; Martin, Nicholas G.; März, Winfried; McCarthy, Mark I.; McKenzie, Colin A.; Meneton, Pierre; Metspalu, Andres; Moilanen, Leena; Morris, Andrew D.; Munroe, Patricia B.; Njølstad, Inger; Pedersen, Nancy L.; Power, Chris; Pramstaller, Peter P.; Price, Jackie F.; Psaty, Bruce M.; Quertermous, Thomas; Rauramaa, Rainer; Saleheen, Danish; Salomaa, Veikko; Sanghera, Dharambir K.; Saramies, Jouko; Schwarz, Peter E.H.; Sheu, Wayne H-H; Shuldiner, Alan R.; Siegbahn, Agneta; Spector, Tim D.; Stefansson, Kari; Strachan, David P.; Tayo, Bamidele O.; Tremoli, Elena; Tuomilehto, Jaakko; Uusitupa, Matti; van Duijn, Cornelia M.; Vollenweider, Peter; Wallentin, Lars; Wareham, Nicholas J.; Whitfield, John B.; Wolffenbuttel, Bruce H.R.; Altshuler, David; Ordovas, Jose M.; Boerwinkle, Eric; Palmer, Colin N.A.; Thorsteinsdottir, Unnur; Chasman, Daniel I.; Rotter, Jerome I.; Franks, Paul W.; Ripatti, Samuli; Cupples, L. Adrienne; Sandhu, Manjinder S.; Rich, Stephen S.; Boehnke, Michael; Deloukas, Panos; Mohlke, Karen L.; Ingelsson, Erik; Abecasis, Goncalo R.; Daly, Mark J.; Neale, Benjamin M.; Kathiresan, Sekar
2013-01-01
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD. PMID:24097064
Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; Karaderi, Tugce; Lempradl, Adelheid; Locke, Adam E; Mahajan, Anubha; Marouli, Eirini; Sivapalaratnam, Suthesh; Young, Kristin L; Alfred, Tamuno; Feitosa, Mary F; Masca, Nicholas GD; Manning, Alisa K; Medina-Gomez, Carolina; Mudgal, Poorva; Ng, Maggie CY; Reiner, Alex P; Vedantam, Sailaja; Willems, Sara M; Winkler, Thomas W; Abecasis, Goncalo; Aben, Katja K; Alam, Dewan S; Alharthi, Sameer E; Allison, Matthew; Amouyel, Philippe; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Bang, Lia E; Barroso, Inês; Bastarache, Lisa; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boehnke, Michael; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Brumat, Marco; Burt, Amber A; Butterworth, Adam S; Campbell, Peter T; Cappellani, Stefania; Carey, David J; Catamo, Eulalia; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der Ida; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Galbany, Jordi Corominas; Cox, Amanda J; Crosslin, David S; Cuellar-Partida, Gabriel; D'Eustacchio, Angela; Danesh, John; Davies, Gail; de Bakker, Paul IW; de Groot, Mark CH; de Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; den Heijer, Martin; den Hollander, Anneke I; den Ruijter, Hester M; Dennis, Joe G; Denny, Josh C; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dubé, Marie-Pierre; Dunning, Alison M; Easton, Douglas F; Edwards, Todd L; Ellinghaus, David; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Farooqi, I. Sadaf; Faul, Jessica D; Fauser, Sascha; Feng, Shuang; Ferrannini, Ele; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franco, Oscar H; Franke, Andre; Franks, Paul W; Friedrich, Nele; Frikke-Schmidt, Ruth; Galesloot, Tessel E.; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Gibson, Jane; Giedraitis, Vilmantas; Gjesing, Anette P; Gordon-Larsen, Penny; Gorski, Mathias; Grabe, Hans-Jörgen; Grant, Struan FA; Grarup, Niels; Griffiths, Helen L; Grove, Megan L; Gudnason, Vilmundur; Gustafsson, Stefan; Haessler, Jeff; Hakonarson, Hakon; Hammerschlag, Anke R; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Have, Christian T; Hayward, Caroline; He, Liang; Heard-Costa, Nancy L; Heath, Andrew C; Heid, Iris M; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Holmen, Oddgeir L; Hovingh, G Kees; Howson, Joanna MM; Hu, Yao; Huang, Paul L; Huffman, Jennifer E; Ikram, M Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jia, Yucheng; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon LR; Karpe, Fredrik; Kathiresan, Sekar; Kee, Frank; Kiemeney, Lambertus A; Kim, Eric; Kitajima, Hidetoshi; Komulainen, Pirjo; Kooner, Jaspal S; Kooperberg, Charles; Korhonen, Tellervo; Kovacs, Peter; Kuivaniemi, Helena; Kutalik, Zoltán; Kuulasmaa, Kari; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A; Lamparter, David; Lange, Ethan M; Lange, Leslie A; Langenberg, Claudia; Larson, Eric B; Lee, Nanette R; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Keng-Hung; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Ching-Ti; Liu, Dajiang J; Liu, Yongmei; Lo, Ken Sin; Lophatananon, Artitaya; Lotery, Andrew J; Loukola, Anu; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Männistö, Satu; Marenne, Gaëlle; Mazul, Angela L; McCarthy, Mark I; McKean-Cowdin, Roberta; Medland, Sarah E; Meidtner, Karina; Milani, Lili; Mistry, Vanisha; Mitchell, Paul; Mohlke, Karen L; Moilanen, Leena; Moitry, Marie; Montgomery, Grant W; Mook-Kanamori, Dennis O; Moore, Carmel; Mori, Trevor A; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Narisu, Narisu; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Nyholt, Dale R; O'Connel, Jeffrey R; O’Donoghue, Michelle L.; Olde Loohuis, Loes M; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin NA; Palmer, Nicholette D; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John RB; Pers, Tune H; Person, Thomas N; Peters, Annette; Petersen, Eva RB; Peyser, Patricia A; Pirie, Ailith; Polasek, Ozren; Polderman, Tinca J; Puolijoki, Hannu; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Renström, Frida; Rheinberger, Myriam; Ridker, Paul M; Rioux, John D; Rivas, Manuel A; Roberts, David J; Robertson, Neil R; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sapkota, Yadav; Sattar, Naveed; Schoen, Robert E; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati H; Sheu, Wayne H-H; Sim, Xueling; Slater, Andrew J; Small, Kerrin S; Smith, Albert Vernon; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Stefansson, Kari; Steinthorsdottir, Valgerdur; Stirrups, Kathleen E; Strauch, Konstantin; Stringham, Heather M; Stumvoll, Michael; Sun, Liang; Surendran, Praveen; Swift, Amy J; Tada, Hayato; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Uusitupa, Matti; van der Laan, Sander W; van Duijn, Cornelia M; van Leeuwen, Nienke; van Setten, Jessica; Vanhala, Mauno; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Velez Edwards, Digna R; Vermeulen, Sita H; Veronesi, Giovanni; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Völker, Uwe; Vuckovic, Dragana; Wagenknecht, Lynne E; Walker, Mark; Wallentin, Lars; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Ware, Erin B; Wareham, Nicholas J; Warren, Helen R; Waterworth, Dawn M; Wessel, Jennifer; White, Harvey D; Willer, Cristen J; Wilson, James G; Witte, Daniel R; Wood, Andrew R; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zhou, Wei; Zondervan, Krina T; Rotter, Jerome I; Pospisilik, John A; Rivadeneira, Fernando; Borecki, Ingrid B; Deloukas, Panos; Frayling, Timothy M; Lettre, Guillaume; North, Kari E; Lindgren, Cecilia M; Hirschhorn, Joel N; Loos, Ruth JF
2018-01-01
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, non-coding variants from which pinpointing causal genes remains challenging. Here, we combined data from 718,734 individuals to discover rare and low-frequency (MAF<5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which eight in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2, ZNF169) newly implicated in human obesity, two (MC4R, KSR2) previously observed in extreme obesity, and two variants in GIPR. Effect sizes of rare variants are ~10 times larger than of common variants, with the largest effect observed in carriers of an MC4R stop-codon (p.Tyr35Ter, MAF=0.01%), weighing ~7kg more than non-carriers. Pathway analyses confirmed enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically-supported therapeutic targets to treat obesity. PMID:29273807
Wood, Andrew R; Esko, Tonu; Yang, Jian; Vedantam, Sailaja; Pers, Tune H; Gustafsson, Stefan; Chu, Audrey Y; Estrada, Karol; Luan, Jian'an; Kutalik, Zoltán; Amin, Najaf; Buchkovich, Martin L; Croteau-Chonka, Damien C; Day, Felix R; Duan, Yanan; Fall, Tove; Fehrmann, Rudolf; Ferreira, Teresa; Jackson, Anne U; Karjalainen, Juha; Lo, Ken Sin; Locke, Adam E; Mägi, Reedik; Mihailov, Evelin; Porcu, Eleonora; Randall, Joshua C; Scherag, André; Vinkhuyzen, Anna A E; Westra, Harm-Jan; Winkler, Thomas W; Workalemahu, Tsegaselassie; Zhao, Jing Hua; Absher, Devin; Albrecht, Eva; Anderson, Denise; Baron, Jeffrey; Beekman, Marian; Demirkan, Ayse; Ehret, Georg B; Feenstra, Bjarke; Feitosa, Mary F; Fischer, Krista; Fraser, Ross M; Goel, Anuj; Gong, Jian; Justice, Anne E; Kanoni, Stavroula; Kleber, Marcus E; Kristiansson, Kati; Lim, Unhee; Lotay, Vaneet; Lui, Julian C; Mangino, Massimo; Mateo Leach, Irene; Medina-Gomez, Carolina; Nalls, Michael A; Nyholt, Dale R; Palmer, Cameron D; Pasko, Dorota; Pechlivanis, Sonali; Prokopenko, Inga; Ried, Janina S; Ripke, Stephan; Shungin, Dmitry; Stancáková, Alena; Strawbridge, Rona J; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van Setten, Jessica; Van Vliet-Ostaptchouk, Jana V; Wang, Zhaoming; Yengo, Loïc; Zhang, Weihua; Afzal, Uzma; Arnlöv, Johan; Arscott, Gillian M; Bandinelli, Stefania; Barrett, Amy; Bellis, Claire; Bennett, Amanda J; Berne, Christian; Blüher, Matthias; Bolton, Jennifer L; Böttcher, Yvonne; Boyd, Heather A; Bruinenberg, Marcel; Buckley, Brendan M; Buyske, Steven; Caspersen, Ida H; Chines, Peter S; Clarke, Robert; Claudi-Boehm, Simone; Cooper, Matthew; Daw, E Warwick; De Jong, Pim A; Deelen, Joris; Delgado, Graciela; Denny, Josh C; Dhonukshe-Rutten, Rosalie; Dimitriou, Maria; Doney, Alex S F; Dörr, Marcus; Eklund, Niina; Eury, Elodie; Folkersen, Lasse; Garcia, Melissa E; Geller, Frank; Giedraitis, Vilmantas; Go, Alan S; Grallert, Harald; Grammer, Tanja B; Gräßler, Jürgen; Grönberg, Henrik; de Groot, Lisette C P G M; Groves, Christopher J; Haessler, Jeffrey; Hall, Per; Haller, Toomas; Hallmans, Goran; Hannemann, Anke; Hartman, Catharina A; Hassinen, Maija; Hayward, Caroline; Heard-Costa, Nancy L; Helmer, Quinta; Hemani, Gibran; Henders, Anjali K; Hillege, Hans L; Hlatky, Mark A; Hoffmann, Wolfgang; Hoffmann, Per; Holmen, Oddgeir; Houwing-Duistermaat, Jeanine J; Illig, Thomas; Isaacs, Aaron; James, Alan L; Jeff, Janina; Johansen, Berit; Johansson, Åsa; Jolley, Jennifer; Juliusdottir, Thorhildur; Junttila, Juhani; Kho, Abel N; Kinnunen, Leena; Klopp, Norman; Kocher, Thomas; Kratzer, Wolfgang; Lichtner, Peter; Lind, Lars; Lindström, Jaana; Lobbens, Stéphane; Lorentzon, Mattias; Lu, Yingchang; Lyssenko, Valeriya; Magnusson, Patrik K E; Mahajan, Anubha; Maillard, Marc; McArdle, Wendy L; McKenzie, Colin A; McLachlan, Stela; McLaren, Paul J; Menni, Cristina; Merger, Sigrun; Milani, Lili; Moayyeri, Alireza; Monda, Keri L; Morken, Mario A; Müller, Gabriele; Müller-Nurasyid, Martina; Musk, Arthur W; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Nöthen, Markus M; Oozageer, Laticia; Pilz, Stefan; Rayner, Nigel W; Renstrom, Frida; Robertson, Neil R; Rose, Lynda M; Roussel, Ronan; Sanna, Serena; Scharnagl, Hubert; Scholtens, Salome; Schumacher, Fredrick R; Schunkert, Heribert; Scott, Robert A; Sehmi, Joban; Seufferlein, Thomas; Shi, Jianxin; Silventoinen, Karri; Smit, Johannes H; Smith, Albert Vernon; Smolonska, Joanna; Stanton, Alice V; Stirrups, Kathleen; Stott, David J; Stringham, Heather M; Sundström, Johan; Swertz, Morris A; Syvänen, Ann-Christine; Tayo, Bamidele O; Thorleifsson, Gudmar; Tyrer, Jonathan P; van Dijk, Suzanne; van Schoor, Natasja M; van der Velde, Nathalie; van Heemst, Diana; van Oort, Floor V A; Vermeulen, Sita H; Verweij, Niek; Vonk, Judith M; Waite, Lindsay L; Waldenberger, Melanie; Wennauer, Roman; Wilkens, Lynne R; Willenborg, Christina; Wilsgaard, Tom; Wojczynski, Mary K; Wong, Andrew; Wright, Alan F; Zhang, Qunyuan; Arveiler, Dominique; Bakker, Stephan J L; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boomsma, Dorret I; Bornstein, Stefan R; Bovet, Pascal; Brambilla, Paolo; Brown, Morris J; Campbell, Harry; Caulfield, Mark J; Chakravarti, Aravinda; Collins, Rory; Collins, Francis S; Crawford, Dana C; Cupples, L Adrienne; Danesh, John; de Faire, Ulf; den Ruijter, Hester M; Erbel, Raimund; Erdmann, Jeanette; Eriksson, Johan G; Farrall, Martin; Ferrannini, Ele; Ferrières, Jean; Ford, Ian; Forouhi, Nita G; Forrester, Terrence; Gansevoort, Ron T; Gejman, Pablo V; Gieger, Christian; Golay, Alain; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Haas, David W; Hall, Alistair S; Harris, Tamara B; Hattersley, Andrew T; Heath, Andrew C; Hengstenberg, Christian; Hicks, Andrew A; Hindorff, Lucia A; Hingorani, Aroon D; Hofman, Albert; Hovingh, G Kees; Humphries, Steve E; Hunt, Steven C; Hypponen, Elina; Jacobs, Kevin B; Jarvelin, Marjo-Riitta; Jousilahti, Pekka; Jula, Antti M; Kaprio, Jaakko; Kastelein, John J P; Kayser, Manfred; Kee, Frank; Keinanen-Kiukaanniemi, Sirkka M; Kiemeney, Lambertus A; Kooner, Jaspal S; Kooperberg, Charles; Koskinen, Seppo; Kovacs, Peter; Kraja, Aldi T; Kumari, Meena; Kuusisto, Johanna; Lakka, Timo A; Langenberg, Claudia; Le Marchand, Loic; Lehtimäki, Terho; Lupoli, Sara; Madden, Pamela A F; Männistö, Satu; Manunta, Paolo; Marette, André; Matise, Tara C; McKnight, Barbara; Meitinger, Thomas; Moll, Frans L; Montgomery, Grant W; Morris, Andrew D; Morris, Andrew P; Murray, Jeffrey C; Nelis, Mari; Ohlsson, Claes; Oldehinkel, Albertine J; Ong, Ken K; Ouwehand, Willem H; Pasterkamp, Gerard; Peters, Annette; Pramstaller, Peter P; Price, Jackie F; Qi, Lu; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rice, Treva K; Ritchie, Marylyn; Rudan, Igor; Salomaa, Veikko; Samani, Nilesh J; Saramies, Jouko; Sarzynski, Mark A; Schwarz, Peter E H; Sebert, Sylvain; Sever, Peter; Shuldiner, Alan R; Sinisalo, Juha; Steinthorsdottir, Valgerdur; Stolk, Ronald P; Tardif, Jean-Claude; Tönjes, Anke; Tremblay, Angelo; Tremoli, Elena; Virtamo, Jarmo; Vohl, Marie-Claude; Amouyel, Philippe; Asselbergs, Folkert W; Assimes, Themistocles L; Bochud, Murielle; Boehm, Bernhard O; Boerwinkle, Eric; Bottinger, Erwin P; Bouchard, Claude; Cauchi, Stéphane; Chambers, John C; Chanock, Stephen J; Cooper, Richard S; de Bakker, Paul I W; Dedoussis, George; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Groop, Leif C; Haiman, Christopher A; Hamsten, Anders; Hayes, M Geoffrey; Hui, Jennie; Hunter, David J; Hveem, Kristian; Jukema, J Wouter; Kaplan, Robert C; Kivimaki, Mika; Kuh, Diana; Laakso, Markku; Liu, Yongmei; Martin, Nicholas G; März, Winfried; Melbye, Mads; Moebus, Susanne; Munroe, Patricia B; Njølstad, Inger; Oostra, Ben A; Palmer, Colin N A; Pedersen, Nancy L; Perola, Markus; Pérusse, Louis; Peters, Ulrike; Powell, Joseph E; Power, Chris; Quertermous, Thomas; Rauramaa, Rainer; Reinmaa, Eva; Ridker, Paul M; Rivadeneira, Fernando; Rotter, Jerome I; Saaristo, Timo E; Saleheen, Danish; Schlessinger, David; Slagboom, P Eline; Snieder, Harold; Spector, Tim D; Strauch, Konstantin; Stumvoll, Michael; Tuomilehto, Jaakko; Uusitupa, Matti; van der Harst, Pim; Völzke, Henry; Walker, Mark; Wareham, Nicholas J; Watkins, Hugh; Wichmann, H-Erich; Wilson, James F; Zanen, Pieter; Deloukas, Panos; Heid, Iris M; Lindgren, Cecilia M; Mohlke, Karen L; Speliotes, Elizabeth K; Thorsteinsdottir, Unnur; Barroso, Inês; Fox, Caroline S; North, Kari E; Strachan, David P; Beckmann, Jacques S; Berndt, Sonja I; Boehnke, Michael; Borecki, Ingrid B; McCarthy, Mark I; Metspalu, Andres; Stefansson, Kari; Uitterlinden, André G; van Duijn, Cornelia M; Franke, Lude; Willer, Cristen J; Price, Alkes L; Lettre, Guillaume; Loos, Ruth J F; Weedon, Michael N; Ingelsson, Erik; O'Connell, Jeffrey R; Abecasis, Goncalo R; Chasman, Daniel I; Goddard, Michael E; Visscher, Peter M; Hirschhorn, Joel N; Frayling, Timothy M
2014-11-01
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
Chu, Audrey Y; Estrada, Karol; Luan, Jian’an; Kutalik, Zoltán; Amin, Najaf; Buchkovich, Martin L; Croteau-Chonka, Damien C; Day, Felix R; Duan, Yanan; Fall, Tove; Fehrmann, Rudolf; Ferreira, Teresa; Jackson, Anne U; Karjalainen, Juha; Lo, Ken Sin; Locke, Adam E; Mägi, Reedik; Mihailov, Evelin; Porcu, Eleonora; Randall, Joshua C; Scherag, André; Vinkhuyzen, Anna AE; Westra, Harm-Jan; Winkler, Thomas W; Workalemahu, Tsegaselassie; Zhao, Jing Hua; Absher, Devin; Albrecht, Eva; Anderson, Denise; Baron, Jeffrey; Beekman, Marian; Demirkan, Ayse; Ehret, Georg B; Feenstra, Bjarke; Feitosa, Mary F; Fischer, Krista; Fraser, Ross M; Goel, Anuj; Gong, Jian; Justice, Anne E; Kanoni, Stavroula; Kleber, Marcus E; Kristiansson, Kati; Lim, Unhee; Lotay, Vaneet; Lui, Julian C; Mangino, Massimo; Leach, Irene Mateo; Medina-Gomez, Carolina; Nalls, Michael A; Nyholt, Dale R; Palmer, Cameron D; Pasko, Dorota; Pechlivanis, Sonali; Prokopenko, Inga; Ried, Janina S; Ripke, Stephan; Shungin, Dmitry; Stancáková, Alena; Strawbridge, Rona J; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van Setten, Jessica; Van Vliet-Ostaptchouk, Jana V; Wang, Zhaoming; Yengo, Loïc; Zhang, Weihua; Afzal, Uzma; Ärnlöv, Johan; Arscott, Gillian M; Bandinelli, Stefania; Barrett, Amy; Bellis, Claire; Bennett, Amanda J; Berne, Christian; Blüher, Matthias; Bolton, Jennifer L; Böttcher, Yvonne; Boyd, Heather A; Bruinenberg, Marcel; Buckley, Brendan M; Buyske, Steven; Caspersen, Ida H; Chines, Peter S; Clarke, Robert; Claudi-Boehm, Simone; Cooper, Matthew; Daw, E Warwick; De Jong, Pim A; Deelen, Joris; Delgado, Graciela; Denny, Josh C; Dhonukshe-Rutten, Rosalie; Dimitriou, Maria; Doney, Alex SF; Dörr, Marcus; Eklund, Niina; Eury, Elodie; Folkersen, Lasse; Garcia, Melissa E; Geller, Frank; Giedraitis, Vilmantas; Go, Alan S; Grallert, Harald; Grammer, Tanja B; Gräßler, Jürgen; Grönberg, Henrik; de Groot, Lisette C.P.G.M.; Groves, Christopher J; Haessler, Jeffrey; Hall, Per; Haller, Toomas; Hallmans, Goran; Hannemann, Anke; Hartman, Catharina A; Hassinen, Maija; Hayward, Caroline; Heard-Costa, Nancy L; Helmer, Quinta; Hemani, Gibran; Henders, Anjali K; Hillege, Hans L; Hlatky, Mark A; Hoffmann, Wolfgang; Hoffmann, Per; Holmen, Oddgeir; Houwing-Duistermaat, Jeanine J; Illig, Thomas; Isaacs, Aaron; James, Alan L; Jeff, Janina; Johansen, Berit; Johansson, Åsa; Jolley, Jennifer; Juliusdottir, Thorhildur; Junttila, Juhani; Kho, Abel N; Kinnunen, Leena; Klopp, Norman; Kocher, Thomas; Kratzer, Wolfgang; Lichtner, Peter; Lind, Lars; Lindström, Jaana; Lobbens, Stéphane; Lorentzon, Mattias; Lu, Yingchang; Lyssenko, Valeriya; Magnusson, Patrik KE; Mahajan, Anubha; Maillard, Marc; McArdle, Wendy L; McKenzie, Colin A; McLachlan, Stela; McLaren, Paul J; Menni, Cristina; Merger, Sigrun; Milani, Lili; Moayyeri, Alireza; Monda, Keri L; Morken, Mario A; Müller, Gabriele; Müller-Nurasyid, Martina; Musk, Arthur W; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Nöthen, Markus M; Oozageer, Laticia; Pilz, Stefan; Rayner, Nigel W; Renstrom, Frida; Robertson, Neil R; Rose, Lynda M; Roussel, Ronan; Sanna, Serena; Scharnagl, Hubert; Scholtens, Salome; Schumacher, Fredrick R; Schunkert, Heribert; Scott, Robert A; Sehmi, Joban; Seufferlein, Thomas; Shi, Jianxin; Silventoinen, Karri; Smit, Johannes H; Smith, Albert Vernon; Smolonska, Joanna; Stanton, Alice V; Stirrups, Kathleen; Stott, David J; Stringham, Heather M; Sundström, Johan; Swertz, Morris A; Syvänen, Ann-Christine; Tayo, Bamidele O; Thorleifsson, Gudmar; Tyrer, Jonathan P; van Dijk, Suzanne; van Schoor, Natasja M; van der Velde, Nathalie; van Heemst, Diana; van Oort, Floor VA; Vermeulen, Sita H; Verweij, Niek; Vonk, Judith M; Waite, Lindsay L; Waldenberger, Melanie; Wennauer, Roman; Wilkens, Lynne R; Willenborg, Christina; Wilsgaard, Tom; Wojczynski, Mary K; Wong, Andrew; Wright, Alan F; Zhang, Qunyuan; Arveiler, Dominique; Bakker, Stephan JL; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boomsma, Dorret I; Bornstein, Stefan R; Bovet, Pascal; Brambilla, Paolo; Brown, Morris J; Campbell, Harry; Caulfield, Mark J; Chakravarti, Aravinda; Collins, Rory; Collins, Francis S; Crawford, Dana C; Cupples, L Adrienne; Danesh, John; de Faire, Ulf; den Ruijter, Hester M; Erbel, Raimund; Erdmann, Jeanette; Eriksson, Johan G; Farrall, Martin; Ferrannini, Ele; Ferrières, Jean; Ford, Ian; Forouhi, Nita G; Forrester, Terrence; Gansevoort, Ron T; Gejman, Pablo V; Gieger, Christian; Golay, Alain; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Haas, David W; Hall, Alistair S; Harris, Tamara B; Hattersley, Andrew T; Heath, Andrew C; Hengstenberg, Christian; Hicks, Andrew A; Hindorff, Lucia A; Hingorani, Aroon D; Hofman, Albert; Hovingh, G Kees; Humphries, Steve E; Hunt, Steven C; Hypponen, Elina; Jacobs, Kevin B; Jarvelin, Marjo-Riitta; Jousilahti, Pekka; Jula, Antti M; Kaprio, Jaakko; Kastelein, John JP; Kayser, Manfred; Kee, Frank; Keinanen-Kiukaanniemi, Sirkka M; Kiemeney, Lambertus A; Kooner, Jaspal S; Kooperberg, Charles; Koskinen, Seppo; Kovacs, Peter; Kraja, Aldi T; Kumari, Meena; Kuusisto, Johanna; Lakka, Timo A; Langenberg, Claudia; Le Marchand, Loic; Lehtimäki, Terho; Lupoli, Sara; Madden, Pamela AF; Männistö, Satu; Manunta, Paolo; Marette, André; Matise, Tara C; McKnight, Barbara; Meitinger, Thomas; Moll, Frans L; Montgomery, Grant W; Morris, Andrew D; Morris, Andrew P; Murray, Jeffrey C; Nelis, Mari; Ohlsson, Claes; Oldehinkel, Albertine J; Ong, Ken K; Ouwehand, Willem H; Pasterkamp, Gerard; Peters, Annette; Pramstaller, Peter P; Price, Jackie F; Qi, Lu; Raitakari, Olli T; Rankinen, Tuomo; Rao, DC; Rice, Treva K; Ritchie, Marylyn; Rudan, Igor; Salomaa, Veikko; Samani, Nilesh J; Saramies, Jouko; Sarzynski, Mark A; Schwarz, Peter EH; Sebert, Sylvain; Sever, Peter; Shuldiner, Alan R; Sinisalo, Juha; Steinthorsdottir, Valgerdur; Stolk, Ronald P; Tardif, Jean-Claude; Tönjes, Anke; Tremblay, Angelo; Tremoli, Elena; Virtamo, Jarmo; Vohl, Marie-Claude; Amouyel, Philippe; Asselbergs, Folkert W; Assimes, Themistocles L; Bochud, Murielle; Boehm, Bernhard O; Boerwinkle, Eric; Bottinger, Erwin P; Bouchard, Claude; Cauchi, Stéphane; Chambers, John C; Chanock, Stephen J; Cooper, Richard S; de Bakker, Paul IW; Dedoussis, George; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Groop, Leif C; Haiman, Christopher A; Hamsten, Anders; Hayes, M Geoffrey; Hui, Jennie; Hunter, David J.; Hveem, Kristian; Jukema, J Wouter; Kaplan, Robert C; Kivimaki, Mika; Kuh, Diana; Laakso, Markku; Liu, Yongmei; Martin, Nicholas G; März, Winfried; Melbye, Mads; Moebus, Susanne; Munroe, Patricia B; Njølstad, Inger; Oostra, Ben A; Palmer, Colin NA; Pedersen, Nancy L; Perola, Markus; Pérusse, Louis; Peters, Ulrike; Powell, Joseph E; Power, Chris; Quertermous, Thomas; Rauramaa, Rainer; Reinmaa, Eva; Ridker, Paul M; Rivadeneira, Fernando; Rotter, Jerome I; Saaristo, Timo E; Saleheen, Danish; Schlessinger, David; Slagboom, P Eline; Snieder, Harold; Spector, Tim D; Strauch, Konstantin; Stumvoll, Michael; Tuomilehto, Jaakko; Uusitupa, Matti; van der Harst, Pim; Völzke, Henry; Walker, Mark; Wareham, Nicholas J; Watkins, Hugh; Wichmann, H-Erich; Wilson, James F; Zanen, Pieter; Deloukas, Panos; Heid, Iris M; Lindgren, Cecilia M; Mohlke, Karen L; Speliotes, Elizabeth K; Thorsteinsdottir, Unnur; Barroso, Inês; Fox, Caroline S; North, Kari E; Strachan, David P; Beckmann, Jacques S.; Berndt, Sonja I; Boehnke, Michael; Borecki, Ingrid B; McCarthy, Mark I; Metspalu, Andres; Stefansson, Kari; Uitterlinden, André G; van Duijn, Cornelia M; Franke, Lude; Willer, Cristen J; Price, Alkes L.; Lettre, Guillaume; Loos, Ruth JF; Weedon, Michael N; Ingelsson, Erik; O’Connell, Jeffrey R; Abecasis, Goncalo R; Chasman, Daniel I; Goddard, Michael E
2014-01-01
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explain one-fifth of heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ~2,000, ~3,700 and ~9,500 SNPs explained ~21%, ~24% and ~29% of phenotypic variance. Furthermore, all common variants together captured the majority (60%) of heritability. The 697 variants clustered in 423 loci enriched for genes, pathways, and tissue-types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin, and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants. PMID:25282103
Mendelian randomization analyses in cardiometabolic disease: challenges in evaluating causality
Holmes, Michael V; Ala-Korpela, Mika; Davey Smith, George
2017-01-01
Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings. PMID:28569269
Grinde, Kelsey E.; Arbet, Jaron; Green, Alden; O'Connell, Michael; Valcarcel, Alessandra; Westra, Jason; Tintle, Nathan
2017-01-01
To date, gene-based rare variant testing approaches have focused on aggregating information across sets of variants to maximize statistical power in identifying genes showing significant association with diseases. Beyond identifying genes that are associated with diseases, the identification of causal variant(s) in those genes and estimation of their effect is crucial for planning replication studies and characterizing the genetic architecture of the locus. However, we illustrate that straightforward single-marker association statistics can suffer from substantial bias introduced by conditioning on gene-based test significance, due to the phenomenon often referred to as “winner's curse.” We illustrate the ramifications of this bias on variant effect size estimation and variant prioritization/ranking approaches, outline parameters of genetic architecture that affect this bias, and propose a bootstrap resampling method to correct for this bias. We find that our correction method significantly reduces the bias due to winner's curse (average two-fold decrease in bias, p < 2.2 × 10−6) and, consequently, substantially improves mean squared error and variant prioritization/ranking. The method is particularly helpful in adjustment for winner's curse effects when the initial gene-based test has low power and for relatively more common, non-causal variants. Adjustment for winner's curse is recommended for all post-hoc estimation and ranking of variants after a gene-based test. Further work is necessary to continue seeking ways to reduce bias and improve inference in post-hoc analysis of gene-based tests under a wide variety of genetic architectures. PMID:28959274
Zhu, Qianqian; Shepherd, Lori; Lunetta, Kathryn L.; Yao, Song; Liu, Qian; Hu, Qiang; Haddad, Stephen A.; Sucheston-Campbell, Lara; Bensen, Jeannette T.; Bandera, Elisa V.; Rosenberg, Lynn; Liu, Song; Haiman, Christopher A.; Olshan, Andrew F.; Palmer, Julie R.; Ambrosone, Christine B.
2016-01-01
Leveraging population-distinct linkage equilibrium (LD) patterns, trans-ethnic follow-up of variants discovered from genome-wide association studies (GWAS) has proved to be useful in facilitating the identification of bona fide causal variants. We previously developed the preferential LD approach, a novel method that successfully identified causal variants driving the GWAS signals within European-descent populations even when the causal variants were only weakly linked with the GWAS-discovered variants. To evaluate the performance of our approach in a trans-ethnic setting, we applied it to follow up breast cancer GWAS hits identified mostly from populations of European ancestry in African Americans (AA). We evaluated 74 breast cancer GWAS variants in 8,315 AA women from the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Only 27% of them were associated with breast cancer risk at significance level α=0.05, suggesting race-specificity of the identified breast cancer risk loci. We followed up on those replicated GWAS hits in the AMBER consortium utilizing the preferential LD approach, to search for causal variants or better breast cancer markers from the 1000 Genomes variant catalog. Our approach identified stronger breast cancer markers for 80% of the GWAS hits with at least nominal breast cancer association, and in 81% of these cases, the marker identified was among the top 10 of all 1000 Genomes variants in the corresponding locus. The results support trans-ethnic application of the preferential LD approach in search for candidate causal variants, and may have implications for future genetic research of breast cancer in AA women. PMID:27825120
Exome Sequencing in Suspected Monogenic Dyslipidemias
Stitziel, Nathan O.; Peloso, Gina M.; Abifadel, Marianne; Cefalu, Angelo B.; Fouchier, Sigrid; Motazacker, M. Mahdi; Tada, Hayato; Larach, Daniel B.; Awan, Zuhier; Haller, Jorge F.; Pullinger, Clive R.; Varret, Mathilde; Rabès, Jean-Pierre; Noto, Davide; Tarugi, Patrizia; Kawashiri, Masa-aki; Nohara, Atsushi; Yamagishi, Masakazu; Risman, Marjorie; Deo, Rahul; Ruel, Isabelle; Shendure, Jay; Nickerson, Deborah A.; Wilson, James G.; Rich, Stephen S.; Gupta, Namrata; Farlow, Deborah N.; Neale, Benjamin M.; Daly, Mark J.; Kane, John P.; Freeman, Mason W.; Genest, Jacques; Rader, Daniel J.; Mabuchi, Hiroshi; Kastelein, John J.P.; Hovingh, G. Kees; Averna, Maurizio R.; Gabriel, Stacey; Boileau, Catherine; Kathiresan, Sekar
2015-01-01
Background Exome sequencing is a promising tool for gene mapping in Mendelian disorders. We utilized this technique in an attempt to identify novel genes underlying monogenic dyslipidemias. Methods and Results We performed exome sequencing on 213 selected family members from 41 kindreds with suspected Mendelian inheritance of extreme levels of low-density lipoprotein (LDL) cholesterol (after candidate gene sequencing excluded known genetic causes for high LDL cholesterol families) or high-density lipoprotein (HDL) cholesterol. We used standard analytic approaches to identify candidate variants and also assigned a polygenic score to each individual in order to account for their burden of common genetic variants known to influence lipid levels. In nine families, we identified likely pathogenic variants in known lipid genes (ABCA1, APOB, APOE, LDLR, LIPA, and PCSK9); however, we were unable to identify obvious genetic etiologies in the remaining 32 families despite follow-up analyses. We identified three factors that limited novel gene discovery: (1) imperfect sequencing coverage across the exome hid potentially causal variants; (2) large numbers of shared rare alleles within families obfuscated causal variant identification; and (3) individuals from 15% of families carried a significant burden of common lipid-related alleles, suggesting complex inheritance can masquerade as monogenic disease. Conclusions We identified the genetic basis of disease in nine of 41 families; however, none of these represented novel gene discoveries. Our results highlight the promise and limitations of exome sequencing as a discovery technique in suspected monogenic dyslipidemias. Considering the confounders identified may inform the design of future exome sequencing studies. PMID:25632026
Nikpay, Majid; Goel, Anuj; Won, Hong-Hee; Hall, Leanne M; Willenborg, Christina; Kanoni, Stavroula; Saleheen, Danish; Kyriakou, Theodosios; Nelson, Christopher P; Hopewell, Jemma C; Webb, Thomas R; Zeng, Lingyao; Dehghan, Abbas; Alver, Maris; Armasu, Sebastian M; Auro, Kirsi; Bjonnes, Andrew; Chasman, Daniel I; Chen, Shufeng; Ford, Ian; Franceschini, Nora; Gieger, Christian; Grace, Christopher; Gustafsson, Stefan; Huang, Jie; Hwang, Shih-Jen; Kim, Yun Kyoung; Kleber, Marcus E; Lau, King Wai; Lu, Xiangfeng; Lu, Yingchang; Lyytikäinen, Leo-Pekka; Mihailov, Evelin; Morrison, Alanna C; Pervjakova, Natalia; Qu, Liming; Rose, Lynda M; Salfati, Elias; Saxena, Richa; Scholz, Markus; Smith, Albert V; Tikkanen, Emmi; Uitterlinden, Andre; Yang, Xueli; Zhang, Weihua; Zhao, Wei; de Andrade, Mariza; de Vries, Paul S; van Zuydam, Natalie R; Anand, Sonia S; Bertram, Lars; Beutner, Frank; Dedoussis, George; Frossard, Philippe; Gauguier, Dominique; Goodall, Alison H; Gottesman, Omri; Haber, Marc; Han, Bok-Ghee; Huang, Jianfeng; Jalilzadeh, Shapour; Kessler, Thorsten; König, Inke R; Lannfelt, Lars; Lieb, Wolfgang; Lind, Lars; Lindgren, Cecilia M; Lokki, Marja-Liisa; Magnusson, Patrik K; Mallick, Nadeem H; Mehra, Narinder; Meitinger, Thomas; Memon, Fazal-Ur-Rehman; Morris, Andrew P; Nieminen, Markku S; Pedersen, Nancy L; Peters, Annette; Rallidis, Loukianos S; Rasheed, Asif; Samuel, Maria; Shah, Svati H; Sinisalo, Juha; Stirrups, Kathleen E; Trompet, Stella; Wang, Laiyuan; Zaman, Khan S; Ardissino, Diego; Boerwinkle, Eric; Borecki, Ingrid B; Bottinger, Erwin P; Buring, Julie E; Chambers, John C; Collins, Rory; Cupples, L Adrienne; Danesh, John; Demuth, Ilja; Elosua, Roberto; Epstein, Stephen E; Esko, Tõnu; Feitosa, Mary F; Franco, Oscar H; Franzosi, Maria Grazia; Granger, Christopher B; Gu, Dongfeng; Gudnason, Vilmundur; Hall, Alistair S; Hamsten, Anders; Harris, Tamara B; Hazen, Stanley L; Hengstenberg, Christian; Hofman, Albert; Ingelsson, Erik; Iribarren, Carlos; Jukema, J Wouter; Karhunen, Pekka J; Kim, Bong-Jo; Kooner, Jaspal S; Kullo, Iftikhar J; Lehtimäki, Terho; Loos, Ruth J F; Melander, Olle; Metspalu, Andres; März, Winfried; Palmer, Colin N; Perola, Markus; Quertermous, Thomas; Rader, Daniel J; Ridker, Paul M; Ripatti, Samuli; Roberts, Robert; Salomaa, Veikko; Sanghera, Dharambir K; Schwartz, Stephen M; Seedorf, Udo; Stewart, Alexandre F; Stott, David J; Thiery, Joachim; Zalloua, Pierre A; O'Donnell, Christopher J; Reilly, Muredach P; Assimes, Themistocles L; Thompson, John R; Erdmann, Jeanette; Clarke, Robert; Watkins, Hugh; Kathiresan, Sekar; McPherson, Ruth; Deloukas, Panos; Schunkert, Heribert; Samani, Nilesh J; Farrall, Martin
2015-10-01
Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
Partial Granger causality--eliminating exogenous inputs and latent variables.
Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng
2008-07-15
Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.
Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; Karaderi, Tugce; Lempradl, Adelheid; Locke, Adam E; Mahajan, Anubha; Marouli, Eirini; Sivapalaratnam, Suthesh; Young, Kristin L; Alfred, Tamuno; Feitosa, Mary F; Masca, Nicholas G D; Manning, Alisa K; Medina-Gomez, Carolina; Mudgal, Poorva; Ng, Maggie C Y; Reiner, Alex P; Vedantam, Sailaja; Willems, Sara M; Winkler, Thomas W; Abecasis, Gonçalo; Aben, Katja K; Alam, Dewan S; Alharthi, Sameer E; Allison, Matthew; Amouyel, Philippe; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Bang, Lia E; Barroso, Inês; Bastarache, Lisa; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boehnke, Michael; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Brumat, Marco; Burt, Amber A; Butterworth, Adam S; Campbell, Peter T; Cappellani, Stefania; Carey, David J; Catamo, Eulalia; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der I; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Corominas Galbany, Jordi; Cox, Amanda J; Crosslin, David S; Cuellar-Partida, Gabriel; D'Eustacchio, Angela; Danesh, John; Davies, Gail; Bakker, Paul I W; Groot, Mark C H; Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; Heijer, Martin; Hollander, Anneke I; Ruijter, Hester M; Dennis, Joe G; Denny, Josh C; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dubé, Marie-Pierre; Dunning, Alison M; Easton, Douglas F; Edwards, Todd L; Ellinghaus, David; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Farooqi, I Sadaf; Faul, Jessica D; Fauser, Sascha; Feng, Shuang; Ferrannini, Ele; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franco, Oscar H; Franke, Andre; Franks, Paul W; Friedrich, Nele; Frikke-Schmidt, Ruth; Galesloot, Tessel E; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Gibson, Jane; Giedraitis, Vilmantas; Gjesing, Anette P; Gordon-Larsen, Penny; Gorski, Mathias; Grabe, Hans-Jörgen; Grant, Struan F A; Grarup, Niels; Griffiths, Helen L; Grove, Megan L; Gudnason, Vilmundur; Gustafsson, Stefan; Haessler, Jeff; Hakonarson, Hakon; Hammerschlag, Anke R; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Have, Christian T; Hayward, Caroline; He, Liang; Heard-Costa, Nancy L; Heath, Andrew C; Heid, Iris M; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Holmen, Oddgeir L; Hovingh, G Kees; Howson, Joanna M M; Hu, Yao; Huang, Paul L; Huffman, Jennifer E; Ikram, M Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jia, Yucheng; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon L R; Karpe, Fredrik; Kathiresan, Sekar; Kee, Frank; Kiemeney, Lambertus A; Kim, Eric; Kitajima, Hidetoshi; Komulainen, Pirjo; Kooner, Jaspal S; Kooperberg, Charles; Korhonen, Tellervo; Kovacs, Peter; Kuivaniemi, Helena; Kutalik, Zoltán; Kuulasmaa, Kari; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A; Lamparter, David; Lange, Ethan M; Lange, Leslie A; Langenberg, Claudia; Larson, Eric B; Lee, Nanette R; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Keng-Hung; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Ching-Ti; Liu, Dajiang J; Liu, Yongmei; Lo, Ken S; Lophatananon, Artitaya; Lotery, Andrew J; Loukola, Anu; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Männistö, Satu; Marenne, Gaëlle; Mazul, Angela L; McCarthy, Mark I; McKean-Cowdin, Roberta; Medland, Sarah E; Meidtner, Karina; Milani, Lili; Mistry, Vanisha; Mitchell, Paul; Mohlke, Karen L; Moilanen, Leena; Moitry, Marie; Montgomery, Grant W; Mook-Kanamori, Dennis O; Moore, Carmel; Mori, Trevor A; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Narisu, Narisu; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Nyholt, Dale R; O'Connel, Jeffrey R; O'Donoghue, Michelle L; Olde Loohuis, Loes M; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin N A; Palmer, Nicholette D; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John R B; Pers, Tune H; Person, Thomas N; Peters, Annette; Petersen, Eva R B; Peyser, Patricia A; Pirie, Ailith; Polasek, Ozren; Polderman, Tinca J; Puolijoki, Hannu; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Renström, Frida; Rheinberger, Myriam; Ridker, Paul M; Rioux, John D; Rivas, Manuel A; Roberts, David J; Robertson, Neil R; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sapkota, Yadav; Sattar, Naveed; Schoen, Robert E; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati H; Sheu, Wayne H-H; Sim, Xueling; Slater, Andrew J; Small, Kerrin S; Smith, Albert V; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Stefansson, Kari; Steinthorsdottir, Valgerdur; Stirrups, Kathleen E; Strauch, Konstantin; Stringham, Heather M; Stumvoll, Michael; Sun, Liang; Surendran, Praveen; Swift, Amy J; Tada, Hayato; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Uusitupa, Matti; Laan, Sander W; Duijn, Cornelia M; Leeuwen, Nienke; van Setten, Jessica; Vanhala, Mauno; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Velez Edwards, Digna R; Vermeulen, Sita H; Veronesi, Giovanni; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Völker, Uwe; Vuckovic, Dragana; Wagenknecht, Lynne E; Walker, Mark; Wallentin, Lars; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Ware, Erin B; Wareham, Nicholas J; Warren, Helen R; Waterworth, Dawn M; Wessel, Jennifer; White, Harvey D; Willer, Cristen J; Wilson, James G; Witte, Daniel R; Wood, Andrew R; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zhou, Wei; Zondervan, Krina T; Rotter, Jerome I; Pospisilik, John A; Rivadeneira, Fernando; Borecki, Ingrid B; Deloukas, Panos; Frayling, Timothy M; Lettre, Guillaume; North, Kari E; Lindgren, Cecilia M; Hirschhorn, Joel N; Loos, Ruth J F
2018-01-01
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
Kim, Kwangwoo; Bang, So-Young; Ikari, Katsunori; Yoo, Dae Hyun; Cho, Soo-Kyung; Choi, Chan-Bum; Sung, Yoon-Kyoung; Kim, Tae-Hwan; Jun, Jae-Bum; Kang, Young Mo; Suh, Chang-Hee; Shim, Seung-Cheol; Lee, Shin-Seok; Lee, Jisoo; Chung, Won Tae; Kim, Seong-Kyu; Choe, Jung-Yoon; Momohara, Shigeki; Taniguchi, Atsuo; Yamanaka, Hisashi; Nath, Swapan K.; Lee, Hye-Soon; Bae, Sang-Cheol
2016-01-01
Considerable sharing of disease alleles among populations is well-characterized in autoimmune disorders (e.g., rheumatoid arthritis), but there are some exceptional loci showing heterogenic association among populations. Here we investigated genetic variants with distinct effects on the development of rheumatoid arthritis in Asian and European populations. Ancestry-related association heterogeneity was examined using Cochran’s homogeneity tests for the disease association data from large Asian (n = 14,465; 9,299 discovery subjects and 5,166 validation subjects; 4 collections) and European (n = 45,790; 11 collections) rheumatoid arthritis case-control cohorts with Immunochip and genome-wide SNP array data. We identified significant heterogeneity between the two ancestries for the common variants in the GTF2I locus (PHeterogeneity = 9.6 × 10−9 at rs73366469) and showed that this heterogeneity was due to an Asian-specific association effect (ORMeta = 1.37 and PMeta = 4.2 × 10−13 in Asians; ORMeta = 1.00 and PMeta = 1.00 in Europeans). Trans-ancestral comparison and bioinfomatics analysis revealed a plausibly causal or disease-variant-tagging SNP (rs117026326; in linkage disequilibrium with rs73366469), whose minor allele is common in Asians but rare in Europeans. In conclusion, we identified largest-ever effect on Asian rheumatoid arthritis across human non-HLA regions at GTF2I by heterogeneity mapping followed by replication studies, and pinpointed a possible causal variant. PMID:27272985
An expanded genome-wide association study of type 2 diabetes in Europeans
Scott, Robert A; Scott, Laura J; Mägi, Reedik; Marullo, Letizia; Gaulton, Kyle J; Kaakinen, Marika; Pervjakova, Natalia; Pers, Tune H; Johnson, Andrew D; Eicher, John D; Jackson, Anne U; Ferreira, Teresa; Lee, Yeji; Ma, Clement; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Van Zuydam, Natalie R; Mahajan, Anubha; Chen, Han; Almgren, Peter; Voight, Ben F; Grallert, Harald; Müller-Nurasyid, Martina; Ried, Janina S; Rayner, William N; Robertson, Neil; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Fuchsberger, Christian; Kwan, Phoenix; Teslovich, Tanya M; Chanda, Pritam; Li, Man; Lu, Yingchang; Dina, Christian; Thuillier, Dorothee; Yengo, Loic; Jiang, Longda; Sparso, Thomas; Kestler, Hans A; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Frånberg, Mattias; Strawbridge, Rona J; Benediktsson, Rafn; Hreidarsson, Astradur B; Kong, Augustine; Sigurðsson, Gunnar; Kerrison, Nicola D; Luan, Jian'an; Liang, Liming; Meitinger, Thomas; Roden, Michael; Thorand, Barbara; Esko, Tõnu; Mihailov, Evelin; Fox, Caroline; Liu, Ching-Ti; Rybin, Denis; Isomaa, Bo; Lyssenko, Valeriya; Tuomi, Tiinamaija; Couper, David J; Pankow, James S; Grarup, Niels; Have, Christian T; Jørgensen, Marit E; Jørgensen, Torben; Linneberg, Allan; Cornelis, Marilyn C; van Dam, Rob M; Hunter, David J; Kraft, Peter; Sun, Qi; Edkins, Sarah; Owen, Katharine R; Perry, John RB; Wood, Andrew R; Zeggini, Eleftheria; Tajes-Fernandes, Juan; Abecasis, Goncalo R; Bonnycastle, Lori L; Chines, Peter S; Stringham, Heather M; Koistinen, Heikki A; Kinnunen, Leena; Sennblad, Bengt; Mühleisen, Thomas W; Nöthen, Markus M; Pechlivanis, Sonali; Baldassarre, Damiano; Gertow, Karl; Humphries, Steve E; Tremoli, Elena; Klopp, Norman; Meyer, Julia; Steinbach, Gerald; Wennauer, Roman; Eriksson, Johan G; Männistö, Satu; Peltonen, Leena; Tikkanen, Emmi; Charpentier, Guillaume; Eury, Elodie; Lobbens, Stéphane; Gigante, Bruna; Leander, Karin; McLeod, Olga; Bottinger, Erwin P; Gottesman, Omri; Ruderfer, Douglas; Blüher, Matthias; Kovacs, Peter; Tonjes, Anke; Maruthur, Nisa M; Scapoli, Chiara; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; de Faire, Ulf; Hamsten, Anders; Stumvoll, Michael; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; Ripatti, Samuli; Salomaa, Veikko; Pedersen, Nancy L; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Tuomilehto, Jaakko; Hansen, Torben; Pedersen, Oluf; Barroso, Inês; Lannfelt, Lars; Ingelsson, Erik; Lind, Lars; Lindgren, Cecilia M; Cauchi, Stephane; Froguel, Philippe; Loos, Ruth JF; Balkau, Beverley; Boeing, Heiner; Franks, Paul W; Barricarte Gurrea, Aurelio; Palli, Domenico; van der Schouw, Yvonne T; Altshuler, David; Groop, Leif C; Langenberg, Claudia; Wareham, Nicholas J; Sijbrands, Eric; van Duijn, Cornelia M; Florez, Jose C; Meigs, James B; Boerwinkle, Eric; Gieger, Christian; Strauch, Konstantin; Metspalu, Andres; Morris, Andrew D; Palmer, Colin NA; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Dupuis, Josée; Morris, Andrew P; Boehnke, Michael; McCarthy, Mark I; Prokopenko, Inga
2017-01-01
To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promising association signals were followed-up in additional data sets (of 14,545 or 7,397 T2D cases and 38,994 or 71,604 controls). We identified 13 novel T2D-associated loci (p<5×10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common SNVs. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion, and in adipocytes, monocytes and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology. PMID:28566273
Verweij, Karin J.H.; Yang, Jian; Lahti, Jari; Veijola, Juha; Hintsanen, Mirka; Pulkki-Råback, Laura; Heinonen, Kati; Pouta, Anneli; Pesonen, Anu-Katriina; Widen, Elisabeth; Taanila, Anja; Isohanni, Matti; Miettunen, Jouko; Palotie, Aarno; Penke, Lars; Service, Susan K.; Heath, Andrew C.; Montgomery, Grant W.; Raitakari, Olli; Kähönen, Mika; Viikari, Jorma; Räikkönen, Katri; Eriksson, Johan G; Keltikangas-Järvinen, Liisa; Lehtimäki, Terho; Martin, Nicholas G.; Järvelin, Marjo-Riitta; Visscher, Peter M.; Keller, Matthew C.; Zietsch, Brendan P.
2012-01-01
Personality traits are basic dimensions of behavioural variation, and twin, family, and adoption studies show that around 30% of the between-individual variation is due to genetic variation. There is rapidly-growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome-wide SNP data from >8,000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially-desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation-selection balance. PMID:23025612
Strategic approaches to unraveling genetic causes of cardiovascular diseases
USDA-ARS?s Scientific Manuscript database
DNA sequence variants are major components of the "causal field" for virtually all medical phenotypes, whether single gene familial disorders or complex traits without a clear familial aggregation. The causal variants in single gene disorders are necessary and sufficient to impart large effects. In ...
Vigorito, Elena; Kuchenbaecker, Karoline B.; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A.; Andrulis, Irene L.; Arun, Banu K.; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A.; Campbell, Ian; Chan, Salina B.; Claes, Kathleen B. M.; Cohn, David E.; Cook, Jackie; Daly, Mary B.; Damiola, Francesca; Davidson, Rosemarie; de Pauw, Antoine; Delnatte, Capucine; Diez, Orland; Domchek, Susan M.; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F.; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D. Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D.; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A.; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K.; Goldgar, David E.; Hake, Christopher R.; Hansen, Thomas V. O.; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B. L.; Houdayer, Claude; Hulick, Peter J.; Imyanitov, Evgeny N.; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M.; Vijai, Joseph; Karlan, Beth Y.; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L.; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R.; Montagna, Marco; Nathanson, Katherine L.; Neuhausen, Susan L.; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I.; Ong, Kai-ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M.; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C.; Rookus, Matti A.; Ross, Eric A.; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F.; Slavin, Thomas P.; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I.; Tea, Muy-Kheng; Teixeira, Manuel R.; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J.; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N.; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J.; Greene, Mark H.; Couch, Fergus J.; Offit, Kenneth; Pharoah, Paul D. P.; Chenevix-Trench, Georgia; Antoniou, Antonis C.
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10−16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10−6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population. PMID:27463617
Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A; Andrulis, Irene L; Arun, Banu K; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A; Campbell, Ian; Chan, Salina B; Claes, Kathleen B M; Cohn, David E; Cook, Jackie; Daly, Mary B; Damiola, Francesca; Davidson, Rosemarie; Pauw, Antoine de; Delnatte, Capucine; Diez, Orland; Domchek, Susan M; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K; Goldgar, David E; Hake, Christopher R; Hansen, Thomas V O; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B L; Houdayer, Claude; Hulick, Peter J; Imyanitov, Evgeny N; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M; Vijai, Joseph; Karlan, Beth Y; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R; Montagna, Marco; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I; Ong, Kai-Ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C; Rookus, Matti A; Ross, Eric A; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F; Slavin, Thomas P; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I; Tea, Muy-Kheng; Teixeira, Manuel R; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J; Greene, Mark H; Couch, Fergus J; Offit, Kenneth; Pharoah, Paul D P; Chenevix-Trench, Georgia; Antoniou, Antonis C
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10-16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.
Kaufman, Kenneth M; Zhao, Jian; Kelly, Jennifer A; Hughes, Travis; Adler, Adam; Sanchez, Elena; Ojwang, Joshua O; Langefeld, Carl D; Ziegler, Julie T; Williams, Adrienne H; Comeau, Mary E; Marion, Miranda C; Glenn, Stuart B; Cantor, Rita M; Grossman, Jennifer M; Hahn, Bevra H; Song, Yeong Wook; Yu, Chack-Yung; James, Judith A; Guthridge, Joel M; Brown, Elizabeth E; Alarcón, Graciela S; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Petri, Michelle A; Reveille, John D; Vilá, Luis M; Anaya, Juan-Manuel; Boackle, Susan A; Stevens, Anne M; Freedman, Barry I; Criswell, Lindsey A; Pons Estel, Bernardo A; Lee, Joo-Hyun; Lee, Ji-Seon; Chang, Deh-Ming; Scofield, R Hal A; Gilkeson, Gary S; Merrill, Joan T; Niewold, Timothy B; Vyse, Timothy James; Bae, Sang-Cheol; Alarcón-Riquelme, Marta E; Jacob, Chaim O; Moser Sivils, Kathy; Gaffney, Patrick M; Harley, John B; Sawalha, Amr H; Tsao, Betty P
2013-03-01
The Xq28 region containing IRAK1 and MECP2 has been identified as a risk locus for systemic lupus erythematosus (SLE) in previous genetic association studies. However, due to the strong linkage disequilibrium between IRAK1 and MECP2, it remains unclear which gene is affected by the underlying causal variant(s) conferring risk of SLE. We fine-mapped ≥136 SNPs in a ∼227 kb region on Xq28, containing IRAK1, MECP2 and seven adjacent genes (L1CAM, AVPR2, ARHGAP4, NAA10, RENBP, HCFC1 and TMEM187), for association with SLE in 15 783 case-control subjects derived from four different ancestral groups. Multiple SNPs showed strong association with SLE in European Americans, Asians and Hispanics at p<5×10(-8) with consistent association in subjects with African ancestry. Of these, six SNPs located in the TMEM187-IRAK1-MECP2 region captured the underlying causal variant(s) residing in a common risk haplotype shared by all four ancestral groups. Among them, rs1059702 best explained the Xq28 association signals in conditional testings and exhibited the strongest p value in transancestral meta-analysis (p(meta )= 1.3×10(-27), OR=1.43), and thus was considered to be the most likely causal variant. The risk allele of rs1059702 results in the amino acid substitution S196F in IRAK1 and had previously been shown to increase NF-κB activity in vitro. We also found that the homozygous risk genotype of rs1059702 was associated with lower mRNA levels of MECP2, but not IRAK1, in SLE patients (p=0.0012) and healthy controls (p=0.0064). These data suggest contributions of both IRAK1 and MECP2 to SLE susceptibility.
Ward, Lucas D; Kellis, Manolis
2016-01-04
More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Jensen, Majken K; Bartz, Traci M; Djoussé, Luc; Kizer, Jorge R; Zieman, Susan J; Rimm, Eric B; Siscovick, David S; Psaty, Bruce M; Ix, Joachim H; Mukamal, Kenneth J
2013-10-01
Fetuin-A levels are associated with higher risk of type 2 diabetes, but it is unknown if the association is causal. We investigated common (>5%) genetic variants in the fetuin-A gene (AHSG) fetuin-A levels, fasting glucose, and risk of type 2 diabetes. Genetic variation, fetuin-A levels, and fasting glucose were assessed in 2,893 Caucasian and 542 African American community-living individuals 65 years of age or older in 1992-1993. Common AHSG variants (rs4917 and rs2248690) were strongly associated with fetuin-A concentrations (P<0.0001). In analyses of 259 incident cases of type 2 diabetes, the single nucleotide polymorphisms (SNPs) were not associated with diabetes risk during follow-up and similar null associations were observed when 579 prevalent cases were included. As expected, higher fetuin-A levels were associated with higher fasting glucose concentrations (1.9 mg/dL [95% CI, 1.2-2.7] higher per SD in Caucasians), but Mendelian randomization analyses using both SNPs as unbiased proxies for measured fetuin-A did not support an association between genetically predicted fetuin-A levels and fasting glucose (-0.3 mg/dL [95% CI, -1.9 to 1.3] lower per SD in Caucasians). The difference between the associations of fasting glucose with actual and genetically predicted fetuin-A level was statistically significant (P=0.001). Results among the smaller sample of African Americans trended in similar directions but were statistically insignificant. Common variants in the AHSG gene are strongly associated with plasma fetuin-A concentrations, but not with risk of type 2 diabetes or glucose concentrations, raising the possibility that the association between fetuin-A and type 2 diabetes may not be causal.
Krämer, Andreas; Shah, Sohela; Rebres, Robert Anthony; Tang, Susan; Richards, Daniel Rene
2017-08-11
Next-generation sequencing is widely used to identify disease-causing variants in patients with rare genetic disorders. Identifying those variants from whole-genome or exome data can be both scientifically challenging and time consuming. A significant amount of time is spent on variant annotation, and interpretation. Fully or partly automated solutions are therefore needed to streamline and scale this process. We describe Phenotype Driven Ranking (PDR), an algorithm integrated into Ingenuity Variant Analysis, that uses observed patient phenotypes to prioritize diseases and genes in order to expedite causal-variant discovery. Our method is based on a network of phenotype-disease-gene relationships derived from the QIAGEN Knowledge Base, which allows for efficient computational association of phenotypes to implicated diseases, and also enables scoring and ranking. We have demonstrated the utility and performance of PDR by applying it to a number of clinical rare-disease cases, where the true causal gene was known beforehand. It is also shown that PDR compares favorably to a representative alternative tool.
Zaitlen, Noah A.; Ye, Chun Jimmie; Witte, John S.
2016-01-01
The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature. PMID:27197206
Burgess, Stephen; Scott, Robert A; Timpson, Nicholas J; Davey Smith, George; Thompson, Simon G
2015-07-01
Finding individual-level data for adequately-powered Mendelian randomization analyses may be problematic. As publicly-available summarized data on genetic associations with disease outcomes from large consortia are becoming more abundant, use of published data is an attractive analysis strategy for obtaining precise estimates of the causal effects of risk factors on outcomes. We detail the necessary steps for conducting Mendelian randomization investigations using published data, and present novel statistical methods for combining data on the associations of multiple (correlated or uncorrelated) genetic variants with the risk factor and outcome into a single causal effect estimate. A two-sample analysis strategy may be employed, in which evidence on the gene-risk factor and gene-outcome associations are taken from different data sources. These approaches allow the efficient identification of risk factors that are suitable targets for clinical intervention from published data, although the ability to assess the assumptions necessary for causal inference is diminished. Methods and guidance are illustrated using the example of the causal effect of serum calcium levels on fasting glucose concentrations. The estimated causal effect of a 1 standard deviation (0.13 mmol/L) increase in calcium levels on fasting glucose (mM) using a single lead variant from the CASR gene region is 0.044 (95 % credible interval -0.002, 0.100). In contrast, using our method to account for the correlation between variants, the corresponding estimate using 17 genetic variants is 0.022 (95 % credible interval 0.009, 0.035), a more clearly positive causal effect.
Association analysis of multiple traits by an approach of combining P values.
Chen, Lili; Wang, Yong; Zhou, Yajing
2018-03-01
Increasing evidence shows that one variant can affect multiple traits, which is a widespread phenomenon in complex diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic mechanism. Although there are many statistical methods to analyse multiple traits, most of these methods are usually suitable for detecting common variants associated with multiple traits. However, because of low minor allele frequency of rare variant, these methods are not optimal for rare variant association analysis. In this paper, we extend an adaptive combination of P values method (termed ADA) for single trait to test association between multiple traits and rare variants in the given region. For a given region, we use reverse regression model to test each rare variant associated with multiple traits and obtain the P value of single-variant test. Further, we take the weighted combination of these P values as the test statistic. Extensive simulation studies show that our approach is more powerful than several other comparison methods in most cases and is robust to the inclusion of a high proportion of neutral variants and the different directions of effects of causal variants.
Huang, Dandan; Yi, Xianfu; Zhang, Shijie; Zheng, Zhanye; Wang, Panwen; Xuan, Chenghao; Sham, Pak Chung; Wang, Junwen; Li, Mulin Jun
2018-05-16
Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet for most of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of non-coding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d or http://mulinlab.org/gwas4d), that systematically evaluates GWAS signals and identifies context-specific regulatory variants. The updated web server includes six major features: (i) updates the regulatory variant prioritization method with our new algorithm; (ii) incorporates 127 tissue/cell type-specific epigenomes data; (iii) integrates motifs of 1480 transcriptional regulators from 13 public resources; (iv) uniformly processes Hi-C data and generates significant interactions at 5 kb resolution across 60 tissues/cell types; (v) adds comprehensive non-coding variant functional annotations; (vi) equips a highly interactive visualization function for SNP-target interaction. Using a GWAS fine-mapped set for 161 coronary artery disease risk loci, we demonstrate that GWAS4D is able to efficiently prioritize disease-causal regulatory variants.
RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.
Xiong, Hui Y; Alipanahi, Babak; Lee, Leo J; Bretschneider, Hannes; Merico, Daniele; Yuen, Ryan K C; Hua, Yimin; Gueroussov, Serge; Najafabadi, Hamed S; Hughes, Timothy R; Morris, Quaid; Barash, Yoseph; Krainer, Adrian R; Jojic, Nebojsa; Scherer, Stephen W; Blencowe, Benjamin J; Frey, Brendan J
2015-01-09
To facilitate precision medicine and whole-genome annotation, we developed a machine-learning technique that scores how strongly genetic variants affect RNA splicing, whose alteration contributes to many diseases. Analysis of more than 650,000 intronic and exonic variants revealed widespread patterns of mutation-driven aberrant splicing. Intronic disease mutations that are more than 30 nucleotides from any splice site alter splicing nine times as often as common variants, and missense exonic disease mutations that have the least impact on protein function are five times as likely as others to alter splicing. We detected tens of thousands of disease-causing mutations, including those involved in cancers and spinal muscular atrophy. Examination of intronic and exonic variants found using whole-genome sequencing of individuals with autism revealed misspliced genes with neurodevelopmental phenotypes. Our approach provides evidence for causal variants and should enable new discoveries in precision medicine. Copyright © 2015, American Association for the Advancement of Science.
Hundreds of variants clustered in genomic loci and biological pathways affect human height
Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segrè, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Mägi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Åsa; Zillikens, M.Carola; Feitosa, Mary F.; Esko, Tõnu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Glazer, Nicole L.; Hayward, Caroline; Hottenga, Jouke-Jan; Jacobs, Kevin B.; Knowles, Joshua W.; Kutalik, Zoltán; Monda, Keri L.; Polasek, Ozren; Preuss, Michael; Rayner, Nigel W.; Robertson, Neil R.; Steinthorsdottir, Valgerdur; Tyrer, Jonathan P.; Voight, Benjamin F.; Wiklund, Fredrik; Xu, Jianfeng; Zhao, Jing Hua; Nyholt, Dale R.; Pellikka, Niina; Perola, Markus; Perry, John R.B.; Surakka, Ida; Tammesoo, Mari-Liis; Altmaier, Elizabeth L.; Amin, Najaf; Aspelund, Thor; Bhangale, Tushar; Boucher, Gabrielle; Chasman, Daniel I.; Chen, Constance; Coin, Lachlan; Cooper, Matthew N.; Dixon, Anna L.; Gibson, Quince; Grundberg, Elin; Hao, Ke; Junttila, M. Juhani; Kaplan, Lee M.; Kettunen, Johannes; König, Inke R.; Kwan, Tony; Lawrence, Robert W.; Levinson, Douglas F.; Lorentzon, Mattias; McKnight, Barbara; Morris, Andrew P.; Müller, Martina; Ngwa, Julius Suh; Purcell, Shaun; Rafelt, Suzanne; Salem, Rany M.; Salvi, Erika; Sanna, Serena; Shi, Jianxin; Sovio, Ulla; Thompson, John R.; Turchin, Michael C.; Vandenput, Liesbeth; Verlaan, Dominique J.; Vitart, Veronique; White, Charles C.; Ziegler, Andreas; Almgren, Peter; Balmforth, Anthony J.; Campbell, Harry; Citterio, Lorena; De Grandi, Alessandro; Dominiczak, Anna; Duan, Jubao; Elliott, Paul; Elosua, Roberto; Eriksson, Johan G.; Freimer, Nelson B.; Geus, Eco J.C.; Glorioso, Nicola; Haiqing, Shen; Hartikainen, Anna-Liisa; Havulinna, Aki S.; Hicks, Andrew A.; Hui, Jennie; Igl, Wilmar; Illig, Thomas; Jula, Antti; Kajantie, Eero; Kilpeläinen, Tuomas O.; Koiranen, Markku; Kolcic, Ivana; Koskinen, Seppo; Kovacs, Peter; Laitinen, Jaana; Liu, Jianjun; Lokki, Marja-Liisa; Marusic, Ana; Maschio, Andrea; Meitinger, Thomas; Mulas, Antonella; Paré, Guillaume; Parker, Alex N.; Peden, John F.; Petersmann, Astrid; Pichler, Irene; Pietiläinen, Kirsi H.; Pouta, Anneli; Ridderstråle, Martin; Rotter, Jerome I.; Sambrook, Jennifer G.; Sanders, Alan R.; Schmidt, Carsten Oliver; Sinisalo, Juha; Smit, Jan H.; Stringham, Heather M.; Walters, G.Bragi; Widen, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Zagato, Laura; Zgaga, Lina; Zitting, Paavo; Alavere, Helene; Farrall, Martin; McArdle, Wendy L.; Nelis, Mari; Peters, Marjolein J.; Ripatti, Samuli; van Meurs, Joyce B.J.; Aben, Katja K.; Ardlie, Kristin G; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Collins, Francis S.; Cusi, Daniele; den Heijer, Martin; Eiriksdottir, Gudny; Gejman, Pablo V.; Hall, Alistair S.; Hamsten, Anders; Huikuri, Heikki V.; Iribarren, Carlos; Kähönen, Mika; Kaprio, Jaakko; Kathiresan, Sekar; Kiemeney, Lambertus; Kocher, Thomas; Launer, Lenore J.; Lehtimäki, Terho; Melander, Olle; Mosley, Tom H.; Musk, Arthur W.; Nieminen, Markku S.; O'Donnell, Christopher J.; Ohlsson, Claes; Oostra, Ben; Palmer, Lyle J.; Raitakari, Olli; Ridker, Paul M.; Rioux, John D.; Rissanen, Aila; Rivolta, Carlo; Schunkert, Heribert; Shuldiner, Alan R.; Siscovick, David S.; Stumvoll, Michael; Tönjes, Anke; Tuomilehto, Jaakko; van Ommen, Gert-Jan; Viikari, Jorma; Heath, Andrew C.; Martin, Nicholas G.; Montgomery, Grant W.; Province, Michael A.; Kayser, Manfred; Arnold, Alice M.; Atwood, Larry D.; Boerwinkle, Eric; Chanock, Stephen J.; Deloukas, Panos; Gieger, Christian; Grönberg, Henrik; Hall, Per; Hattersley, Andrew T.; Hengstenberg, Christian; Hoffman, Wolfgang; Lathrop, G.Mark; Salomaa, Veikko; Schreiber, Stefan; Uda, Manuela; Waterworth, Dawn; Wright, Alan F.; Assimes, Themistocles L.; Barroso, Inês; Hofman, Albert; Mohlke, Karen L.; Boomsma, Dorret I.; Caulfield, Mark J.; Cupples, L.Adrienne; Erdmann, Jeanette; Fox, Caroline S.; Gudnason, Vilmundur; Gyllensten, Ulf; Harris, Tamara B.; Hayes, Richard B.; Jarvelin, Marjo-Riitta; Mooser, Vincent; Munroe, Patricia B.; Ouwehand, Willem H.; Penninx, Brenda W.; Pramstaller, Peter P.; Quertermous, Thomas; Rudan, Igor; Samani, Nilesh J.; Spector, Timothy D.; Völzke, Henry; Watkins, Hugh; Wilson, James F.; Groop, Leif C.; Haritunians, Talin; Hu, Frank B.; Kaplan, Robert C.; Metspalu, Andres; North, Kari E.; Schlessinger, David; Wareham, Nicholas J.; Hunter, David J.; O'Connell, Jeffrey R.; Strachan, David P.; Wichmann, H.-Erich; Borecki, Ingrid B.; van Duijn, Cornelia M.; Schadt, Eric E.; Thorsteinsdottir, Unnur; Peltonen, Leena; Uitterlinden, André; Visscher, Peter M.; Chatterjee, Nilanjan; Loos, Ruth J.F.; Boehnke, Michael; McCarthy, Mark I.; Ingelsson, Erik; Lindgren, Cecilia M.; Abecasis, Gonçalo R.; Stefansson, Kari; Frayling, Timothy M.; Hirschhorn, Joel N
2010-01-01
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. PMID:20881960
Overexpression of the Cytokine BAFF and Autoimmunity Risk.
Steri, Maristella; Orrù, Valeria; Idda, M Laura; Pitzalis, Maristella; Pala, Mauro; Zara, Ilenia; Sidore, Carlo; Faà, Valeria; Floris, Matteo; Deiana, Manila; Asunis, Isadora; Porcu, Eleonora; Mulas, Antonella; Piras, Maria G; Lobina, Monia; Lai, Sandra; Marongiu, Mara; Serra, Valentina; Marongiu, Michele; Sole, Gabriella; Busonero, Fabio; Maschio, Andrea; Cusano, Roberto; Cuccuru, Gianmauro; Deidda, Francesca; Poddie, Fausto; Farina, Gabriele; Dei, Mariano; Virdis, Francesca; Olla, Stefania; Satta, Maria A; Pani, Mario; Delitala, Alessandro; Cocco, Eleonora; Frau, Jessica; Coghe, Giancarlo; Lorefice, Lorena; Fenu, Giuseppe; Ferrigno, Paola; Ban, Maria; Barizzone, Nadia; Leone, Maurizio; Guerini, Franca R; Piga, Matteo; Firinu, Davide; Kockum, Ingrid; Lima Bomfim, Izaura; Olsson, Tomas; Alfredsson, Lars; Suarez, Ana; Carreira, Patricia E; Castillo-Palma, Maria J; Marcus, Joseph H; Congia, Mauro; Angius, Andrea; Melis, Maurizio; Gonzalez, Antonio; Alarcón Riquelme, Marta E; da Silva, Berta M; Marchini, Maurizio; Danieli, Maria G; Del Giacco, Stefano; Mathieu, Alessandro; Pani, Antonello; Montgomery, Stephen B; Rosati, Giulio; Hillert, Jan; Sawcer, Stephen; D'Alfonso, Sandra; Todd, John A; Novembre, John; Abecasis, Gonçalo R; Whalen, Michael B; Marrosu, Maria G; Meloni, Alessandra; Sanna, Serena; Gorospe, Myriam; Schlessinger, David; Fiorillo, Edoardo; Zoledziewska, Magdalena; Cucca, Francesco
2017-04-27
Genomewide association studies of autoimmune diseases have mapped hundreds of susceptibility regions in the genome. However, only for a few association signals has the causal gene been identified, and for even fewer have the causal variant and underlying mechanism been defined. Coincident associations of DNA variants affecting both the risk of autoimmune disease and quantitative immune variables provide an informative route to explore disease mechanisms and drug-targetable pathways. Using case-control samples from Sardinia, Italy, we performed a genomewide association study in multiple sclerosis followed by TNFSF13B locus-specific association testing in systemic lupus erythematosus (SLE). Extensive phenotyping of quantitative immune variables, sequence-based fine mapping, cross-population and cross-phenotype analyses, and gene-expression studies were used to identify the causal variant and elucidate its mechanism of action. Signatures of positive selection were also investigated. A variant in TNFSF13B, encoding the cytokine and drug target B-cell activating factor (BAFF), was associated with multiple sclerosis as well as SLE. The disease-risk allele was also associated with up-regulated humoral immunity through increased levels of soluble BAFF, B lymphocytes, and immunoglobulins. The causal variant was identified: an insertion-deletion variant, GCTGT→A (in which A is the risk allele), yielded a shorter transcript that escaped microRNA inhibition and increased production of soluble BAFF, which in turn up-regulated humoral immunity. Population genetic signatures indicated that this autoimmunity variant has been evolutionarily advantageous, most likely by augmenting resistance to malaria. A TNFSF13B variant was associated with multiple sclerosis and SLE, and its effects were clarified at the population, cellular, and molecular levels. (Funded by the Italian Foundation for Multiple Sclerosis and others.).
Narrow-sense heritability estimation of complex traits using identity-by-descent information.
Evans, Luke M; Tahmasbi, Rasool; Jones, Matt; Vrieze, Scott I; Abecasis, Gonçalo R; Das, Sayantan; Bjelland, Douglas W; de Candia, Teresa R; Yang, Jian; Goddard, Michael E; Visscher, Peter M; Keller, Matthew C
2018-03-28
Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while possibly avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole-genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). In simulations, the IBD-based approach produced unbiased heritability estimates, even when CVs were extremely rare, although precision was low. However, population stratification and non-genetic familial environmental effects shared across generations led to strong biases in IBD-based heritability. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in these real data, suggesting that more work may be required to understand and mitigate factors that influence IBD-based heritability estimates.
van Leeuwen, Elisabeth M; Sabo, Aniko; Bis, Joshua C; Huffman, Jennifer E; Manichaikul, Ani; Smith, Albert V; Feitosa, Mary F; Demissie, Serkalem; Joshi, Peter K; Duan, Qing; Marten, Jonathan; van Klinken, Jan B; Surakka, Ida; Nolte, Ilja M; Zhang, Weihua; Mbarek, Hamdi; Li-Gao, Ruifang; Trompet, Stella; Verweij, Niek; Evangelou, Evangelos; Lyytikäinen, Leo-Pekka; Tayo, Bamidele O; Deelen, Joris; van der Most, Peter J; van der Laan, Sander W; Arking, Dan E; Morrison, Alanna; Dehghan, Abbas; Franco, Oscar H; Hofman, Albert; Rivadeneira, Fernando; Sijbrands, Eric J; Uitterlinden, Andre G; Mychaleckyj, Josyf C; Campbell, Archie; Hocking, Lynne J; Padmanabhan, Sandosh; Brody, Jennifer A; Rice, Kenneth M; White, Charles C; Harris, Tamara; Isaacs, Aaron; Campbell, Harry; Lange, Leslie A; Rudan, Igor; Kolcic, Ivana; Navarro, Pau; Zemunik, Tatijana; Salomaa, Veikko; Kooner, Angad S; Kooner, Jaspal S; Lehne, Benjamin; Scott, William R; Tan, Sian-Tsung; de Geus, Eco J; Milaneschi, Yuri; Penninx, Brenda W J H; Willemsen, Gonneke; de Mutsert, Renée; Ford, Ian; Gansevoort, Ron T; Segura-Lepe, Marcelo P; Raitakari, Olli T; Viikari, Jorma S; Nikus, Kjell; Forrester, Terrence; McKenzie, Colin A; de Craen, Anton J M; de Ruijter, Hester M; Pasterkamp, Gerard; Snieder, Harold; Oldehinkel, Albertine J; Slagboom, P Eline; Cooper, Richard S; Kähönen, Mika; Lehtimäki, Terho; Elliott, Paul; van der Harst, Pim; Jukema, J Wouter; Mook-Kanamori, Dennis O; Boomsma, Dorret I; Chambers, John C; Swertz, Morris; Ripatti, Samuli; Willems van Dijk, Ko; Vitart, Veronique; Polasek, Ozren; Hayward, Caroline; Wilson, James G; Wilson, James F; Gudnason, Vilmundur; Rich, Stephen S; Psaty, Bruce M; Borecki, Ingrid B; Boerwinkle, Eric; Rotter, Jerome I; Cupples, L Adrienne; van Duijn, Cornelia M
2016-01-01
Background So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage. Results Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene. Conclusions This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels. PMID:27036123
GWASeq: targeted re-sequencing follow up to GWAS.
Salomon, Matthew P; Li, Wai Lok Sibon; Edlund, Christopher K; Morrison, John; Fortini, Barbara K; Win, Aung Ko; Conti, David V; Thomas, Duncan C; Duggan, David; Buchanan, Daniel D; Jenkins, Mark A; Hopper, John L; Gallinger, Steven; Le Marchand, Loïc; Newcomb, Polly A; Casey, Graham; Marjoram, Paul
2016-03-03
For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS. We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer. Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.
Meta-analysis of gene-level associations for rare variants based on single-variant statistics.
Hu, Yi-Juan; Berndt, Sonja I; Gustafsson, Stefan; Ganna, Andrea; Hirschhorn, Joel; North, Kari E; Ingelsson, Erik; Lin, Dan-Yu
2013-08-08
Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Uricchio, Lawrence H; Zaitlen, Noah A; Ye, Chun Jimmie; Witte, John S; Hernandez, Ryan D
2016-07-01
The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature. © 2016 Uricchio et al.; Published by Cold Spring Harbor Laboratory Press.
Jørgensen, Anders Berg; Frikke-Schmidt, Ruth; West, Anders Sode; Grande, Peer; Nordestgaard, Børge G; Tybjærg-Hansen, Anne
2013-06-01
Elevated non-fasting triglycerides mark elevated levels of remnant cholesterol. Using a Mendelian randomization approach, we tested whether genetically increased remnant cholesterol in hypertriglyceridaemia due to genetic variation in the apolipoprotein A5 gene (APOA5) associates with an increased risk of myocardial infarction (MI). We resequenced the core promoter and coding regions of APOA5 in individuals with the lowest 1% (n = 95) and highest 2% (n = 190) triglyceride levels in the Copenhagen City Heart Study (CCHS, n = 10 391). Genetic variants which differed in frequency between the two extreme triglyceride groups (c.-1131T > C, S19W, and c.*31C > T; P-value: 0.06 to <0.001), thus suggesting an effect on triglyceride levels, were genotyped in the Copenhagen General Population Study (CGPS), the CCHS, and the Copenhagen Ischemic Heart Disease Study (CIHDS), comprising a total of 5705 MI cases and 54 408 controls. Genotype combinations of these common variants associated with increases in non-fasting triglycerides and calculated remnant cholesterol of, respectively, up to 68% (1.10 mmol/L) and 56% (0.40 mmol/L) (P < 0.001), and with a corresponding odds ratio for MI of 1.87 (95% confidence interval: 1.25-2.81). Using APOA5 genotypes in instrumental variable analysis, the observational hazard ratio for a doubling in non-fasting triglycerides was 1.57 (1.32-2.68) compared with a causal genetic odds ratio of 1.94 (1.40-1.85) (P for comparison = 0.28). For calculated remnant cholesterol, the corresponding values were 1.67(1.38-2.02) observational and 2.23(1.48-3.35) causal (P for comparison = 0.21). These data are consistent with a causal association between elevated levels of remnant cholesterol in hypertriglyceridaemia and an increased risk of MI. Limitations include that remnants were not measured directly, and that APOA5 genetic variants may influence other lipoprotein parameters.
Kullback-Leibler divergence for detection of rare haplotype common disease association.
Lin, Shili
2015-11-01
Rare haplotypes may tag rare causal variants of common diseases; hence, detection of such rare haplotypes may also contribute to our understanding of complex disease etiology. Because rare haplotypes frequently result from common single-nucleotide polymorphisms (SNPs), focusing on rare haplotypes is much more economical compared with using rare single-nucleotide variants (SNVs) from sequencing, as SNPs are available and 'free' from already amassed genome-wide studies. Further, associated haplotypes may shed light on the underlying disease causal mechanism, a feat unmatched by SNV-based collapsing methods. In recent years, data mining approaches have been adapted to detect rare haplotype association. However, as they rely on an assumed underlying disease model and require the specification of a null haplotype, results can be erroneous if such assumptions are violated. In this paper, we present a haplotype association method based on Kullback-Leibler divergence (hapKL) for case-control samples. The idea is to compare haplotype frequencies for the cases versus the controls by computing symmetrical divergence measures. An important property of such measures is that both the frequencies and logarithms of the frequencies contribute in parallel, thus balancing the contributions from rare and common, and accommodating both deleterious and protective, haplotypes. A simulation study under various scenarios shows that hapKL has well-controlled type I error rates and good power compared with existing data mining methods. Application of hapKL to age-related macular degeneration (AMD) shows a strong association of the complement factor H (CFH) gene with AMD, identifying several individual rare haplotypes with strong signals.
Improved methods for multi-trait fine mapping of pleiotropic risk loci.
Kichaev, Gleb; Roytman, Megan; Johnson, Ruth; Eskin, Eleazar; Lindström, Sara; Kraft, Peter; Pasaniuc, Bogdan
2017-01-15
Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation. In this work we introduce a new approach, fastPAINTOR, that leverages evidence across correlated traits, as well as functional annotation data, to improve fine-mapping accuracy at pleiotropic risk loci. To improve computational efficiency, we describe an new importance sampling scheme to perform model inference. First, we demonstrate in simulations that by leveraging functional annotation data, fastPAINTOR increases fine-mapping resolution relative to existing methods. Next, we show that jointly modeling pleiotropic risk regions improves fine-mapping resolution compared to standard single trait and pleiotropic fine mapping strategies. We report a reduction in the number of SNPs required for follow-up in order to capture 90% of the causal variants from 23 SNPs per locus using a single trait to 12 SNPs when fine-mapping two traits simultaneously. Finally, we analyze summary association data from a large-scale GWAS of lipids and show that these improvements are largely sustained in real data. The fastPAINTOR framework is implemented in the PAINTOR v3.0 package which is publicly available to the research community http://bogdan.bioinformatics.ucla.edu/software/paintor CONTACT: gkichaev@ucla.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Mahajan, Anubha; Wessel, Jennifer; Willems, Sara M; Zhao, Wei; Robertson, Neil R; Chu, Audrey Y; Gan, Wei; Kitajima, Hidetoshi; Taliun, Daniel; Rayner, N William; Guo, Xiuqing; Lu, Yingchang; Li, Man; Jensen, Richard A; Hu, Yao; Huo, Shaofeng; Lohman, Kurt K; Zhang, Weihua; Cook, James P; Prins, Bram Peter; Flannick, Jason; Grarup, Niels; Trubetskoy, Vassily Vladimirovich; Kravic, Jasmina; Kim, Young Jin; Rybin, Denis V; Yaghootkar, Hanieh; Müller-Nurasyid, Martina; Meidtner, Karina; Li-Gao, Ruifang; Varga, Tibor V; Marten, Jonathan; Li, Jin; Smith, Albert Vernon; An, Ping; Ligthart, Symen; Gustafsson, Stefan; Malerba, Giovanni; Demirkan, Ayse; Tajes, Juan Fernandez; Steinthorsdottir, Valgerdur; Wuttke, Matthias; Lecoeur, Cécile; Preuss, Michael; Bielak, Lawrence F; Graff, Marielisa; Highland, Heather M; Justice, Anne E; Liu, Dajiang J; Marouli, Eirini; Peloso, Gina Marie; Warren, Helen R; Afaq, Saima; Afzal, Shoaib; Ahlqvist, Emma; Almgren, Peter; Amin, Najaf; Bang, Lia B; Bertoni, Alain G; Bombieri, Cristina; Bork-Jensen, Jette; Brandslund, Ivan; Brody, Jennifer A; Burtt, Noël P; Canouil, Mickaël; Chen, Yii-Der Ida; Cho, Yoon Shin; Christensen, Cramer; Eastwood, Sophie V; Eckardt, Kai-Uwe; Fischer, Krista; Gambaro, Giovanni; Giedraitis, Vilmantas; Grove, Megan L; de Haan, Hugoline G; Hackinger, Sophie; Hai, Yang; Han, Sohee; Tybjærg-Hansen, Anne; Hivert, Marie-France; Isomaa, Bo; Jäger, Susanne; Jørgensen, Marit E; Jørgensen, Torben; Käräjämäki, Annemari; Kim, Bong-Jo; Kim, Sung Soo; Koistinen, Heikki A; Kovacs, Peter; Kriebel, Jennifer; Kronenberg, Florian; Läll, Kristi; Lange, Leslie A; Lee, Jung-Jin; Lehne, Benjamin; Li, Huaixing; Lin, Keng-Hung; Linneberg, Allan; Liu, Ching-Ti; Liu, Jun; Loh, Marie; Mägi, Reedik; Mamakou, Vasiliki; McKean-Cowdin, Roberta; Nadkarni, Girish; Neville, Matt; Nielsen, Sune F; Ntalla, Ioanna; Peyser, Patricia A; Rathmann, Wolfgang; Rice, Kenneth; Rich, Stephen S; Rode, Line; Rolandsson, Olov; Schönherr, Sebastian; Selvin, Elizabeth; Small, Kerrin S; Stančáková, Alena; Surendran, Praveen; Taylor, Kent D; Teslovich, Tanya M; Thorand, Barbara; Thorleifsson, Gudmar; Tin, Adrienne; Tönjes, Anke; Varbo, Anette; Witte, Daniel R; Wood, Andrew R; Yajnik, Pranav; Yao, Jie; Yengo, Loïc; Young, Robin; Amouyel, Philippe; Boeing, Heiner; Boerwinkle, Eric; Bottinger, Erwin P; Chowdhury, Rajiv; Collins, Francis S; Dedoussis, George; Dehghan, Abbas; Deloukas, Panos; Ferrario, Marco M; Ferrières, Jean; Florez, Jose C; Frossard, Philippe; Gudnason, Vilmundur; Harris, Tamara B; Heckbert, Susan R; Howson, Joanna M M; Ingelsson, Martin; Kathiresan, Sekar; Kee, Frank; Kuusisto, Johanna; Langenberg, Claudia; Launer, Lenore J; Lindgren, Cecilia M; Männistö, Satu; Meitinger, Thomas; Melander, Olle; Mohlke, Karen L; Moitry, Marie; Morris, Andrew D; Murray, Alison D; de Mutsert, Renée; Orho-Melander, Marju; Owen, Katharine R; Perola, Markus; Peters, Annette; Province, Michael A; Rasheed, Asif; Ridker, Paul M; Rivadineira, Fernando; Rosendaal, Frits R; Rosengren, Anders H; Salomaa, Veikko; Sheu, Wayne H-H; Sladek, Rob; Smith, Blair H; Strauch, Konstantin; Uitterlinden, André G; Varma, Rohit; Willer, Cristen J; Blüher, Matthias; Butterworth, Adam S; Chambers, John Campbell; Chasman, Daniel I; Danesh, John; van Duijn, Cornelia; Dupuis, Josée; Franco, Oscar H; Franks, Paul W; Froguel, Philippe; Grallert, Harald; Groop, Leif; Han, Bok-Ghee; Hansen, Torben; Hattersley, Andrew T; Hayward, Caroline; Ingelsson, Erik; Kardia, Sharon L R; Karpe, Fredrik; Kooner, Jaspal Singh; Köttgen, Anna; Kuulasmaa, Kari; Laakso, Markku; Lin, Xu; Lind, Lars; Liu, Yongmei; Loos, Ruth J F; Marchini, Jonathan; Metspalu, Andres; Mook-Kanamori, Dennis; Nordestgaard, Børge G; Palmer, Colin N A; Pankow, James S; Pedersen, Oluf; Psaty, Bruce M; Rauramaa, Rainer; Sattar, Naveed; Schulze, Matthias B; Soranzo, Nicole; Spector, Timothy D; Stefansson, Kari; Stumvoll, Michael; Thorsteinsdottir, Unnur; Tuomi, Tiinamaija; Tuomilehto, Jaakko; Wareham, Nicholas J; Wilson, James G; Zeggini, Eleftheria; Scott, Robert A; Barroso, Inês; Frayling, Timothy M; Goodarzi, Mark O; Meigs, James B; Boehnke, Michael; Saleheen, Danish; Morris, Andrew P; Rotter, Jerome I; McCarthy, Mark I
2018-04-01
We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10 -7 ); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
Pardiñas, Antonio F.; Holmans, Peter; Pocklington, Andrew J.; Escott-Price, Valentina; Ripke, Stephan; Carrera, Noa; Legge, Sophie E.; Bishop, Sophie; Cameron, Darren; Hamshere, Marian L.; Han, Jun; Hubbard, Leon; Lynham, Amy; Mantripragada, Kiran; Rees, Elliott; MacCabe, James H.; McCarroll, Steven A.; Baune, Bernhard T.; Breen, Gerome; Byrne, Enda M.; Dannlowski, Udo; Eley, Thalia C.; Hayward, Caroline; Martin, Nicholas G.; McIntosh, Andrew M.; Plomin, Robert; Porteous, David J.; Wray, Naomi R.; Caballero, Armando; Geschwind, Daniel H.; Huckins, Laura M.; Ruderfer, Douglas M.; Santiago, Enrique; Sklar, Pamela; Stahl, Eli A.; Won, Hyejung; Agerbo, Esben; Als, Thomas D.; Andreassen, Ole A.; Bækvad-Hansen, Marie; Mortensen, Preben Bo; Pedersen, Carsten Bøcker; Børglum, Anders D.; Bybjerg-Grauholm, Jonas; Djurovic, Srdjan; Durmishi, Naser; Pedersen, Marianne Giørtz; Golimbet, Vera; Grove, Jakob; Hougaard, David M.; Mattheisen, Manuel; Molden, Espen; Mors, Ole; Nordentoft, Merete; Pejovic-Milovancevic, Milica; Sigurdsson, Engilbert; Silagadze, Teimuraz; Hansen, Christine Søholm; Stefansson, Kari; Stefansson, Hreinn; Steinberg, Stacy; Tosato, Sarah; Werge, Thomas; Collier, David A.; Rujescu, Dan; Kirov, George; Owen, Michael J.; O’Donovan, Michael C.; Walters, James T. R.
2018-01-01
Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population. PMID:29483656
Day, Felix R; Ruth, Katherine S; Thompson, Deborah J; Lunetta, Kathryn L; Pervjakova, Natalia; Chasman, Daniel I; Stolk, Lisette; Finucane, Hilary K; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D; Elks, Cathy E; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A; Franke, Lude L; Huffman, Jennifer E; Keller, Margaux F; McArdle, Patrick F; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M; Schick, Ursula M; Smith, Jennifer A; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L; Anton-Culver, Hoda; Antoniou, Antonis C; Arndt, Volker; Arnold, Alice M; Barbieri, Caterina; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V; Bojesen, Stig E; Bolla, Manjeet K; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J; Chapman, J Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J; Coviello, Andrea D; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W; Dennis, Joe; Devilee, Peter; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eicher, John D; Fasching, Peter A; Faul, Jessica D; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E; García-Closas, Montserrat; Giles, Graham G; Girotto, Giorgia G; Goldberg, Mark S; González-Neira, Anna; Goodarzi, Mark O; Grove, Megan L; Gudbjartsson, Daniel F; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A; Hall, Per; Hamann, Ute; Henderson, Brian E; Hocking, Lynne J; Hofman, Albert; Homuth, Georg; Hooning, Maartje J; Hopper, John L; Hu, Frank B; Huang, Jinyan; Humphreys, Keith; Hunter, David J; Jakubowska, Anna; Jones, Samuel E; Kabisch, Maria; Karasik, David; Knight, Julia A; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian'an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B; Nordestgaard, Børge G; Olson, Janet E; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D P; Pirastu, Nicola N; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F; Sanna, Serena; Sawyer, Elinor J; Schlessinger, David; Schmidt, Marjanka K; Schmidt, Frank; Schmutzler, Rita K; Schoemaker, Minouk J; Scott, Robert A; Seynaeve, Caroline M; Simard, Jacques; Sorice, Rossella; Southey, Melissa C; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D; Thorsteinsdottir, Unnur; Toland, Amanda E; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F; Winqvist, Robert; Wolffenbuttel, Bruce B H R; Wright, Alan F; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I; Buring, Julie E; Ferrucci, Luigi; Montgomery, Grant W; Gudnason, Vilmundur; Spector, Tim D; van Duijn, Cornelia M; Alizadeh, Behrooz Z; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F; Gasparini, Paolo P; Gieger, Christian; Harris, Tamara B; Hayward, Caroline; Kardia, Sharon L R; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C; Reiner, Alex P; Ridker, Paul M; Rotter, Jerome I; Toniolo, Daniela; Uitterlinden, André G; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J; Weir, David R; Yerges-Armstrong, Laura M; Price, Alkes L; Stefansson, Kari; Visser, Jenny A; Ong, Ken K; Chang-Claude, Jenny; Murabito, Joanne M; Perry, John R B; Murray, Anna
2015-11-01
Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.
Lunetta, Kathryn L.; Pervjakova, Natalia; Chasman, Daniel I.; Stolk, Lisette; Finucane, Hilary K.; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D.; Elks, Cathy E.; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A.; Franke, Lude L.; Huffman, Jennifer E.; Keller, Margaux F.; McArdle, Patrick F.; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M.; Schick, Ursula M.; Smith, Jennifer A.; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V.; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L.; Anton-Culver, Hoda; Antoniou, Antonis C.; Arndt, Volker; Arnold, Alice M.; Barbieri, Caterina; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J.; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V.; Bojesen, Stig E.; Bolla, Manjeet K.; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J.; Chapman, J. Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J.; Coviello, Andrea D.; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W.; Dennis, Joe; Devilee, Peter; Dörk, Thilo; dos-Santos-Silva, Isabel; Dunning, Alison M.; Eicher, John D.; Fasching, Peter A.; Faul, Jessica D.; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E.; García-Closas, Montserrat; Giles, Graham G.; Girotto, Giorgia G.; Goldberg, Mark S.; González-Neira, Anna; Goodarzi, Mark O.; Grove, Megan L.; Gudbjartsson, Daniel F.; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A.; Hall, Per; Hamann, Ute; Henderson, Brian E.; Hocking, Lynne J.; Hofman, Albert; Homuth, Georg; Hooning, Maartje J.; Hopper, John L.; Hu, Frank B.; Huang, Jinyan; Humphreys, Keith; Hunter, David J.; Jakubowska, Anna; Jones, Samuel E.; Kabisch, Maria; Karasik, David; Knight, Julia A.; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian’an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G.; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L.; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M.; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B.; Nordestgaard, Børge G.; Olson, Janet E.; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D.P.; Pirastu, Nicola N.; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M.; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J.; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F.; Sanna, Serena; Sawyer, Elinor J.; Schlessinger, David; Schmidt, Marjanka K.; Schmidt, Frank; Schmutzler, Rita K.; Schoemaker, Minouk J.; Scott, Robert A.; Seynaeve, Caroline M.; Simard, Jacques; Sorice, Rossella; Southey, Melissa C.; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D.; Thorsteinsdottir, Unnur; Toland, Amanda E.; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T.; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F.; Winqvist, Robert; Wolffenbuttel, Bruce B.H.R.; Wright, Alan F.; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I.; Buring, Julie E.; Ferrucci, Luigi; Montgomery, Grant W.; Gudnason, Vilmundur; Spector, Tim D.; van Duijn, Cornelia M; Alizadeh, Behrooz Z.; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F.; Gasparini, Paolo P.; Gieger, Christian; Harris, Tamara B.; Hayward, Caroline; Kardia, Sharon L.R.; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C.; Reiner, Alex P.; Ridker, Paul M.; Rotter, Jerome I.; Toniolo, Daniela; Uitterlinden, André G.; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J.; Weir, David R.; Yerges-Armstrong, Laura M.; Price, Alkes L.; Stefansson, Kari; Visser, Jenny A.; Ong, Ken K.; Chang-Claude, Jenny; Murabito, Joanne M.; Perry, John R.B.; Murray, Anna
2015-01-01
Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ~70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two harbouring additional rare missense alleles of large effect. We found enrichment of signals in/near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses revealed a major association with DNA damage-response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomisation analyses supported a causal effect of later ANM on breast cancer risk (~6% risk increase per-year, P=3×10−14), likely mediated by prolonged sex hormone exposure, rather than DDR mechanisms. PMID:26414677
The multifaceted interplay between lipids and epigenetics.
Dekkers, Koen F; Slagboom, P Eline; Jukema, J Wouter; Heijmans, Bastiaan T
2016-06-01
The interplay between lipids and epigenetic mechanisms has recently gained increased interest because of its relevance for common diseases and most notably atherosclerosis. This review discusses recent advances in unravelling this interplay with a particular focus on promising approaches and methods that will be able to establish causal relationships. Complementary approaches uncovered close links between circulating lipids and epigenetic mechanisms at multiple levels. A characterization of lipid-associated genetic variants suggests that these variants exert their influence on lipid levels through epigenetic changes in the liver. Moreover, exposure of monocytes to lipids persistently alters their epigenetic makeup resulting in more proinflammatory cells. Hence, epigenetic changes can both impact on and be induced by lipids. It is the combined application of technological advances to probe epigenetic modifications at a genome-wide scale and methodological advances aimed at causal inference (including Mendelian randomization and integrative genomics) that will elucidate the interplay between circulating lipids and epigenetics. Understanding its role in the development of atherosclerosis holds the promise of identifying a new category of therapeutic targets, since epigenetic changes are amenable to reversal.
Decoding the role of regulatory element polymorphisms in complex disease.
Vockley, Christopher M; Barrera, Alejandro; Reddy, Timothy E
2017-04-01
Genetic variation in gene regulatory elements contributes to diverse human diseases, ranging from rare and severe developmental defects to common and complex diseases such as obesity and diabetes. Early examples of regulatory mechanisms of human diseases involve large chromosomal rearrangements that change the regulatory connections within the genome. Single nucleotide variants in regulatory elements can also contribute to disease, potentially via demonstrated associations with changes in transcription factor binding, enhancer activity, post-translational histone modifications, long-range enhancer-promoter interactions, or RNA polymerase recruitment. Establishing causality between non-coding genetic variants, gene regulation, and disease has recently become more feasible with advances in genome-editing and epigenome-editing technologies. As establishing causal regulatory mechanisms of diseases becomes routine, functional annotation of target genes is likely to emerge as a major bottleneck for translation into patient benefits. In this review, we discuss the history and recent advances in understanding the regulatory mechanisms of human disease, and new challenges likely to be encountered once establishing those mechanisms becomes rote. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hammer, Christian; Begemann, Martin; McLaren, Paul J.; Bartha, István; Michel, Angelika; Klose, Beate; Schmitt, Corinna; Waterboer, Tim; Pawlita, Michael; Schulz, Thomas F.; Ehrenreich, Hannelore; Fellay, Jacques
2015-01-01
The magnitude of the human antibody response to viral antigens is highly variable. To explore the human genetic contribution to this variability, we performed genome-wide association studies of the immunoglobulin G response to 14 pathogenic viruses in 2,363 immunocompetent adults. Significant associations were observed in the major histocompatibility complex region on chromosome 6 for influenza A virus, Epstein-Barr virus, JC polyomavirus, and Merkel cell polyomavirus. Using local imputation and fine mapping, we identified specific amino acid residues in human leucocyte antigen (HLA) class II proteins as the most probable causal variants underlying these association signals. Common HLA-DRβ1 haplotypes showed virus-specific patterns of humoral-response regulation. We observed an overlap between variants affecting the humoral response to influenza A and EBV and variants previously associated with autoimmune diseases related to these viruses. The results of this study emphasize the central and pathogen-specific role of HLA class II variation in the modulation of humoral immune response to viral antigens in humans. PMID:26456283
Cho, Eun Young; Jang, Yangsoo; Shin, Eun Soon; Jang, Hye Yoon; Yoo, Yeon-Kyeong; Kim, Sook; Jang, Ji Hyun; Lee, Ji Yeon; Yun, Min Hye; Park, Min Young; Chae, Jey Sook; Lim, Jin Woo; Shin, Dong Jik; Park, Sungha; Lee, Jong Ho; Han, Bok Ghee; Rae, Kim Hyung; Cardon, Lon R; Morris, Andrew P; Lee, Jong Eun; Clarke, Geraldine M
2010-01-01
Background Recent genome-wide association (GWA) studies have identified and replicated several genetic loci associated with the risk of development of coronary artery disease (CAD) in samples from populations of Caucasian and Asian descent. However, only chromosome 9p21 has been confirmed as a major susceptibility locus conferring risk for development of CAD across multiple ethnic groups. The authors aimed to find evidence of further similarities and differences in genetic risk of CAD between Korean and other populations. Methods The authors performed a GWA study comprising 230 cases and 290 controls from a Korean population typed on 490 032 single nucleotide polymorphisms (SNPs). A total of 3148 SNPs were taken forward for genotyping in a subsequent replication study using an independent sample of 1172 cases and 1087 controls from the same population. Results The association previously observed on chromosome 9p21 was independently replicated (p=3.08e–07). Within this region, the same risk haplotype was observed in samples from both Korea and of Western European descent, suggesting that the causal mutation carried on this background occurred on a single ancestral allele. Other than 9p21, the authors were unable to replicate any of the previously reported signals for association with CAD. Furthermore, no evidence of association was found at chromosome 1q41 for risk of myocardial infarction, previously identified as conferring risk in a Japanese population. Conclusion A common causal variant is likely to be responsible for risk of CAD in Korean and Western European populations at chromosome 9p21.3. Further investigations are required to confirm non-replication of any other cross-race genetic risk factors. PMID:27325954
Genetic Misdiagnoses and the Potential for Health Disparities.
Manrai, Arjun K; Funke, Birgit H; Rehm, Heidi L; Olesen, Morten S; Maron, Bradley A; Szolovits, Peter; Margulies, David M; Loscalzo, Joseph; Kohane, Isaac S
2016-08-18
For more than a decade, risk stratification for hypertrophic cardiomyopathy has been enhanced by targeted genetic testing. Using sequencing results, clinicians routinely assess the risk of hypertrophic cardiomyopathy in a patient's relatives and diagnose the condition in patients who have ambiguous clinical presentations. However, the benefits of genetic testing come with the risk that variants may be misclassified. Using publicly accessible exome data, we identified variants that have previously been considered causal in hypertrophic cardiomyopathy and that are overrepresented in the general population. We studied these variants in diverse populations and reevaluated their initial ascertainments in the medical literature. We reviewed patient records at a leading genetic-testing laboratory for occurrences of these variants during the near-decade-long history of the laboratory. Multiple patients, all of whom were of African or unspecified ancestry, received positive reports, with variants misclassified as pathogenic on the basis of the understanding at the time of testing. Subsequently, all reported variants were recategorized as benign. The mutations that were most common in the general population were significantly more common among black Americans than among white Americans (P<0.001). Simulations showed that the inclusion of even small numbers of black Americans in control cohorts probably would have prevented these misclassifications. We identified methodologic shortcomings that contributed to these errors in the medical literature. The misclassification of benign variants as pathogenic that we found in our study shows the need for sequencing the genomes of diverse populations, both in asymptomatic controls and the tested patient population. These results expand on current guidelines, which recommend the use of ancestry-matched controls to interpret variants. As additional populations of different ancestry backgrounds are sequenced, we expect variant reclassifications to increase, particularly for ancestry groups that have historically been less well studied. (Funded by the National Institutes of Health.).
Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia
2018-06-11
Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
Describing the genetic architecture of epilepsy through heritability analysis.
Speed, Doug; O'Brien, Terence J; Palotie, Aarno; Shkura, Kirill; Marson, Anthony G; Balding, David J; Johnson, Michael R
2014-10-01
Epilepsy is a disease with substantial missing heritability; despite its high genetic component, genetic association studies have had limited success detecting common variants which influence susceptibility. In this paper, we reassess the role of common variants on epilepsy using extensions of heritability analysis. Our data set consists of 1258 UK patients with epilepsy, of which 958 have focal epilepsy, and 5129 population control subjects, with genotypes recorded for over 4 million common single nucleotide polymorphisms. Firstly, we show that on the liability scale, common variants collectively explain at least 26% (standard deviation 5%) of phenotypic variation for all epilepsy and 27% (standard deviation 5%) for focal epilepsy. Secondly we provide a new method for estimating the number of causal variants for complex traits; when applied to epilepsy, our most optimistic estimate suggests that at least 400 variants influence disease susceptibility, with potentially many thousands. Thirdly, we use bivariate analysis to assess how similar the genetic architecture of focal epilepsy is to that of non-focal epilepsy; we demonstrate both significant differences (P = 0.004) and significant similarities (P = 0.01) between the two subtypes, indicating that although the clinical definition of focal epilepsy does identify a genetically distinct epilepsy subtype, there is also scope to improve the classification of epilepsy by incorporating genotypic information. Lastly, we investigate the potential value in using genetic data to diagnose epilepsy following a single epileptic seizure; we find that a prediction model explaining 10% of phenotypic variation could have clinical utility for deciding which single-seizure individuals are likely to benefit from immediate anti-epileptic drug therapy. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.
Kant on causal laws and powers.
Henschen, Tobias
2014-12-01
The aim of the paper is threefold. Its first aim is to defend Eric Watkins's claim that for Kant, a cause is not an event but a causal power: a power that is borne by a substance, and that, when active, brings about its effect, i.e. a change of the states of another substance, by generating a continuous flow of intermediate states of that substance. The second aim of the paper is to argue against Watkins that the Kantian concept of causal power is not the pre-critical concept of real ground but the category of causality, and that Kant holds with Hume that causal laws cannot be inferred non-inductively (that he accordingly has no intention to show in the Second analogy or elsewhere that events fall under causal laws). The third aim of the paper is to compare the Kantian position on causality with central tenets of contemporary powers ontology: it argues that unlike the variants endorsed by contemporary powers theorists, the Kantian variants of these tenets are resistant to objections that neo-Humeans raise to these tenets.
FamLBL: detecting rare haplotype disease association based on common SNPs using case-parent triads.
Wang, Meng; Lin, Shili
2014-09-15
In recent years, there has been an increasing interest in using common single-nucleotide polymorphisms (SNPs) amassed in genome-wide association studies to investigate rare haplotype effects on complex diseases. Evidence has suggested that rare haplotypes may tag rare causal single-nucleotide variants, making SNP-based rare haplotype analysis not only cost effective, but also more valuable for detecting causal variants. Although a number of methods for detecting rare haplotype association have been proposed in recent years, they are population based and thus susceptible to population stratification. We propose family-triad-based logistic Bayesian Lasso (famLBL) for estimating effects of haplotypes on complex diseases using SNP data. By choosing appropriate prior distribution, effect sizes of unassociated haplotypes can be shrunk toward zero, allowing for more precise estimation of associated haplotypes, especially those that are rare, thereby achieving greater detection power. We evaluate famLBL using simulation to gauge its type I error and power. Compared with its population counterpart, LBL, highlights famLBL's robustness property in the presence of population substructure. Further investigation by comparing famLBL with Family-Based Association Test (FBAT) reveals its advantage for detecting rare haplotype association. famLBL is implemented as an R-package available at http://www.stat.osu.edu/∼statgen/SOFTWARE/LBL/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Goharian, T S; Andersen, L B; Franks, P W; Wareham, N J; Brage, S; Veidebaum, T; Ekelund, U; Lawlor, D A; Loos, R J F; Grøntved, A
2015-03-01
The aim of the study was to determine whether genetically raised fasting glucose (FG) levels are associated with blood pressure (BP) in healthy children and adolescents. We used 11 common genetic variants of FG discovered in genome-wide association studies (GWAS), including the rs560887 single-nucleotide polymorphism (SNP) located in the G6PC2 locus found to be robustly associated with FG in children and adolescents, as an instrument to associate FG with resting BP in 1506 children and adolescents from the European Youth Heart Study (EYHS). Rs560887 was associated with increased FG levels corresponding to an increase of 0.08 mmol l(-1) (P=2.4 × 10(-8)). FG was associated with BP, independent of other important determinants of BP in conventional multivariable analysis (systolic BP z-score: 0.32 s.d. per increase in mmol l(-1) (95% confidence interval (CI) 0.20-0.44, P=1.9 × 10(-7)), diastolic BP z-score: 0.13 s.d. per increase in mmol l(-1) (95% CI 0.04-0.21, P=3.2 × 10(-3)). This association was not supported by the Mendelian randomization approach, neither from instrumenting FG from all 11 variants nor from the rs560887, where non-significant associations of glucose with BP were observed. The results of this study could not support a causal association between FG and BP in healthy children and adolescents; however, it is possible that rs560887 has pleiotropic effects on unknown factors with a BP lowering effect or that these results were due to a lack of statistical power.
Use of allele scores as instrumental variables for Mendelian randomization
Burgess, Stephen; Thompson, Simon G
2013-01-01
Background An allele score is a single variable summarizing multiple genetic variants associated with a risk factor. It is calculated as the total number of risk factor-increasing alleles for an individual (unweighted score), or the sum of weights for each allele corresponding to estimated genetic effect sizes (weighted score). An allele score can be used in a Mendelian randomization analysis to estimate the causal effect of the risk factor on an outcome. Methods Data were simulated to investigate the use of allele scores in Mendelian randomization where conventional instrumental variable techniques using multiple genetic variants demonstrate ‘weak instrument’ bias. The robustness of estimates using the allele score to misspecification (for example non-linearity, effect modification) and to violations of the instrumental variable assumptions was assessed. Results Causal estimates using a correctly specified allele score were unbiased with appropriate coverage levels. The estimates were generally robust to misspecification of the allele score, but not to instrumental variable violations, even if the majority of variants in the allele score were valid instruments. Using a weighted rather than an unweighted allele score increased power, but the increase was small when genetic variants had similar effect sizes. Naive use of the data under analysis to choose which variants to include in an allele score, or for deriving weights, resulted in substantial biases. Conclusions Allele scores enable valid causal estimates with large numbers of genetic variants. The stringency of criteria for genetic variants in Mendelian randomization should be maintained for all variants in an allele score. PMID:24062299
Lee, Yujung; Kim, Changshin; Park, YoungJoon; Pyun, Jung-A; Kwack, KyuBum
2016-12-01
Premature ovarian failure (POF) is characterized by heterogeneous genetic causes such as chromosomal abnormalities and variants in causal genes. Recently, development of techniques made next generation sequencing (NGS) possible to detect genome wide variants including chromosomal abnormalities. Among 37 Korean POF patients, XY karyotype with distal part deletions of Y chromosome, Yp11.32-31 and Yp12 end part, was observed in two patients through NGS. Six deleterious variants in POF genes were also detected which might explain the pathogenesis of POF with abnormalities in the sex chromosomes. Additionally, the two POF patients had no mutation in SRY but three non-synonymous variants were detected in genes regarding sex reversal. These findings suggest candidate causes of POF and sex reversal and show the propriety of NGS to approach the heterogeneous pathogenesis of POF. Copyright © 2016 Elsevier Inc. All rights reserved.
New insights into old methods for identifying causal rare variants.
Wang, Haitian; Huang, Chien-Hsun; Lo, Shaw-Hwa; Zheng, Tian; Hu, Inchi
2011-11-29
The advance of high-throughput next-generation sequencing technology makes possible the analysis of rare variants. However, the investigation of rare variants in unrelated-individuals data sets faces the challenge of low power, and most methods circumvent the difficulty by using various collapsing procedures based on genes, pathways, or gene clusters. We suggest a new way to identify causal rare variants using the F-statistic and sliced inverse regression. The procedure is tested on the data set provided by the Genetic Analysis Workshop 17 (GAW17). After preliminary data reduction, we ranked markers according to their F-statistic values. Top-ranked markers were then subjected to sliced inverse regression, and those with higher absolute coefficients in the most significant sliced inverse regression direction were selected. The procedure yields good false discovery rates for the GAW17 data and thus is a promising method for future study on rare variants.
Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter
2016-01-01
Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308
Fine-mapping inflammatory bowel disease loci to single variant resolution
Huang, Hailiang; Fang, Ming; Jostins, Luke; Mirkov, Maša Umićević; Boucher, Gabrielle; Anderson, Carl A; Andersen, Vibeke; Cleynen, Isabelle; Cortes, Adrian; Crins, François; D'Amato, Mauro; Deffontaine, Valérie; Dimitrieva, Julia; Docampo, Elisa; Elansary, Mahmoud; Farh, Kyle Kai-How; Franke, Andre; Gori, Ann-Stephan; Goyette, Philippe; Halfvarson, Jonas; Haritunians, Talin; Knight, Jo; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mariman, Rob; Meuwissen, Theo; Mni, Myriam; Momozawa, Yukihide; Parkes, Miles; Spain, Sarah L; Théâtre, Emilie; Trynka, Gosia; Satsangi, Jack; van Sommeren, Suzanne; Vermeire, Severine; Xavier, Ramnik J; Weersma, Rinse K; Duerr, Richard H; Mathew, Christopher G; Rioux, John D; McGovern, Dermot PB; Cho, Judy H; Georges, Michel; Daly, Mark J; Barrett, Jeffrey C
2017-01-01
Summary The inflammatory bowel diseases (IBD) are chronic gastrointestinal inflammatory disorders that affect millions worldwide. Genome-wide association studies have identified 200 IBD-associated loci, but few have been conclusively resolved to specific functional variants. Here we report fine-mapping of 94 IBD loci using high-density genotyping in 67,852 individuals. We pinpointed 18 associations to a single causal variant with >95% certainty, and an additional 27 associations to a single variant with >50% certainty. These 45 variants are significantly enriched for protein-coding changes (n=13), direct disruption of transcription factor binding sites (n=3) and tissue specific epigenetic marks (n=10), with the latter category showing enrichment in specific immune cells among associations stronger in CD and in gut mucosa among associations stronger in UC. The results of this study suggest that high-resolution fine-mapping in large samples can convert many GWAS discoveries into statistically convincing causal variants, providing a powerful substrate for experimental elucidation of disease mechanisms. PMID:28658209
Bailey, Julia N; Patterson, Christopher; de Nijs, Laurence; Durón, Reyna M; Nguyen, Viet-Huong; Tanaka, Miyabi; Medina, Marco T; Jara-Prado, Aurelio; Martínez-Juárez, Iris E; Ochoa, Adriana; Molina, Yolli; Suzuki, Toshimitsu; Alonso, María E; Wight, Jenny E; Lin, Yu-Chen; Guilhoto, Laura; Targas Yacubian, Elza Marcia; Machado-Salas, Jesús; Daga, Andrea; Yamakawa, Kazuhiro; Grisar, Thierry M; Lakaye, Bernard; Delgado-Escueta, Antonio V
2017-02-01
EFHC1 variants are the most common mutations in inherited myoclonic and grand mal clonic-tonic-clonic (CTC) convulsions of juvenile myoclonic epilepsy (JME). We reanalyzed 54 EFHC1 variants associated with epilepsy from 17 cohorts based on National Human Genome Research Institute (NHGRI) and American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation of sequence variants. We calculated Bayesian LOD scores for variants in coinheritance, unconditional exact tests and odds ratios (OR) in case-control associations, allele frequencies in genome databases, and predictions for conservation/pathogenicity. We reviewed whether variants damage EFHC1 functions, whether efhc1 -/- KO mice recapitulate CTC convulsions and "microdysgenesis" neuropathology, and whether supernumerary synaptic and dendritic phenotypes can be rescued in the fly model when EFHC1 is overexpressed. We rated strengths of evidence and applied ACMG combinatorial criteria for classifying variants. Nine variants were classified as "pathogenic," 14 as "likely pathogenic," 9 as "benign," and 2 as "likely benign." Twenty variants of unknown significance had an insufficient number of ancestry-matched controls, but ORs exceeded 5 when compared with racial/ethnic-matched Exome Aggregation Consortium (ExAC) controls. NHGRI gene-level evidence and variant-level evidence establish EFHC1 as the first non-ion channel microtubule-associated protein whose mutations disturb R-type VDCC and TRPM2 calcium currents in overgrown synapses and dendrites within abnormally migrated dislocated neurons, thus explaining CTC convulsions and "microdysgenesis" neuropathology of JME.Genet Med 19 2, 144-156.
The Model Analyst’s Toolkit: Scientific Model Development, Analysis, and Validation
2013-11-20
Granger causality F-test validation 3.1.2. Dynamic time warping for uneven temporal relationships Many causal relationships are imperfectly...mapping for dynamic feedback models Granger causality and DTW can identify causal relationships and consider complex temporal factors. However, many ...variant of the tf-idf algorithm (Manning, Raghavan, Schutze et al., 2008), typically used in search engines, to “score” features. The (-log tf) in
Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J; Murcray, Cassandra Elizabeth; Conti, David
2011-12-01
Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. © 2011 Wiley Periodicals, Inc.
Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J.; Murcray, Cassandra Elizabeth; Conti, David
2014-01-01
Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. PMID:21922541
Al Chawa, Taofik; Ludwig, Kerstin U; Fier, Heide; Pötzsch, Bernd; Reich, Rudolf H; Schmidt, Gül; Braumann, Bert; Daratsianos, Nikolaos; Böhmer, Anne C; Schuencke, Hannah; Alblas, Margrieta; Fricker, Nadine; Hoffmann, Per; Knapp, Michael; Lange, Christoph; Nöthen, Markus M; Mangold, Elisabeth
2014-06-01
The genes Gremlin-1 (GREM1) and Noggin (NOG) are components of the bone morphogenetic protein 4 pathway, which has been implicated in craniofacial development. Both genes map to recently identified susceptibility loci (chromosomal region 15q13, 17q22) for nonsyndromic cleft lip with or without cleft palate (nsCL/P). The aim of the present study was to determine whether rare variants in either gene are implicated in nsCL/P etiology. The complete coding regions, untranslated regions, and splice sites of GREM1 and NOG were sequenced in 96 nsCL/P patients and 96 controls of Central European ethnicity. Three burden and four nonburden tests were performed. Statistically significant results were followed up in a second case-control sample (n = 96, respectively). For rare variants observed in cases, segregation analyses were performed. In NOG, four rare sequence variants (minor allele frequency < 1%) were identified. Here, burden and nonburden analyses generated nonsignificant results. In GREM1, 33 variants were identified, 15 of which were rare. Of these, five were novel. Significant p-values were generated in three nonburden analyses. Segregation analyses revealed incomplete penetrance for all variants investigated. Our study did not provide support for NOG being the causal gene at 17q22. However, the observation of a significant excess of rare variants in GREM1 supports the hypothesis that this is the causal gene at chr. 15q13. Because no single causal variant was identified, future sequencing analyses of GREM1 should involve larger samples and the investigation of regulatory elements. © 2014 Wiley Periodicals, Inc.
Interpreting findings from Mendelian randomization using the MR-Egger method.
Burgess, Stephen; Thompson, Simon G
2017-05-01
Mendelian randomization-Egger (MR-Egger) is an analysis method for Mendelian randomization using summarized genetic data. MR-Egger consists of three parts: (1) a test for directional pleiotropy, (2) a test for a causal effect, and (3) an estimate of the causal effect. While conventional analysis methods for Mendelian randomization assume that all genetic variants satisfy the instrumental variable assumptions, the MR-Egger method is able to assess whether genetic variants have pleiotropic effects on the outcome that differ on average from zero (directional pleiotropy), as well as to provide a consistent estimate of the causal effect, under a weaker assumption-the InSIDE (INstrument Strength Independent of Direct Effect) assumption. In this paper, we provide a critical assessment of the MR-Egger method with regard to its implementation and interpretation. While the MR-Egger method is a worthwhile sensitivity analysis for detecting violations of the instrumental variable assumptions, there are several reasons why causal estimates from the MR-Egger method may be biased and have inflated Type 1 error rates in practice, including violations of the InSIDE assumption and the influence of outlying variants. The issues raised in this paper have potentially serious consequences for causal inferences from the MR-Egger approach. We give examples of scenarios in which the estimates from conventional Mendelian randomization methods and MR-Egger differ, and discuss how to interpret findings in such cases.
Heteropolymerization of S, I, and Z α1-antitrypsin and liver cirrhosis
Mahadeva, Ravi; Chang, Wun-Shaing W.; Dafforn, Timothy R.; Oakley, Diana J.; Foreman, Richard C.; Calvin, Jacqueline; Wight, Derek G.D.; Lomas, David A.
1999-01-01
The association between Z α1-antitrypsin deficiency and juvenile cirrhosis is well-recognized, and there is now convincing evidence that the hepatic inclusions are the result of entangled polymers of mutant Z α1-antitrypsin. Four percent of the northern European Caucasian population are heterozygotes for the Z variant, but even more common is S α1-antitrypsin, which is found in up to 28% of southern Europeans. The S variant is known to have an increased susceptibility to polymerization, although this is marginal compared with the more conformationally unstable Z variant. There has been speculation that the two may interact to produce cirrhosis, but this has never been demonstrated experimentally. This hypothesis was raised again by the observation reported here of a mixed heterozygote for Z α1-antitrypsin and another conformationally unstable variant (I α1-antitrypsin; 39Arg→Cys) identified in a 34-year-old man with cirrhosis related to α1-antitrypsin deficiency. The conformational stability of the I variant has been characterized, and we have used fluorescence resonance energy transfer to demonstrate the formation of heteropolymers between S and Z α1-antitrypsin. Taken together, these results indicate that not only may mixed variants form heteropolymers, but that this can causally lead to the development of cirrhosis. PMID:10194472
New insights into susceptibility to glioma.
Liu, Yanhong; Shete, Sanjay; Hosking, Fay J; Robertson, Lindsay B; Bondy, Melissa L; Houlston, Richard S
2010-03-01
The study of inherited susceptibility to cancer has been one of the most informative areas of research in the past decade. Most of the cancer genetics studies have been focused on the common tumors such as breast and colorectal cancers. As the allelic architecture of these tumors is unraveled, research attention is turning to other rare cancers such as glioma, which are also likely to have a major genetic component as the basis of their development. In this brief review we discuss emerging data on glioma whole genome-association searches to identify risk loci. Two glioma genome-wide association studies have so far been reported. Our group identified 5 risk loci for glioma susceptibility (TERT rs2736100, CCDC26 rs4295627, CDKN2A/CDKN2B rs4977756, RTEL1 rs6010620, and PHLDB1 rs498872). Wrensch and colleagues provided further evidence to 2 risk loci (CDKN2B rs1412829 and RTEL1 rs6010620) for GBM and anaplastic astrocytoma. Although these data provide the strongest evidence to date for the role of common low-risk variants in the etiology of glioma, the single-nucleotide polymorphisms identified alone are unlikely to be candidates for causality. Identifying the causal variant at each specific locus and its biological impact now poses a significant challenge, contingent on a combination of fine mapping and functional analyses. Finally, we hope that a greater understanding of the biological basis of the disease will lead to the development of novel therapeutic interventions.
Coulonges, Cedric; Bartha, István; Lenz, Tobias L.; Deutsch, Aaron J.; Bashirova, Arman; Buchbinder, Susan; Carrington, Mary N.; Cossarizza, Andrea; Dalmau, Judith; De Luca, Andrea; Goedert, James J.; Gurdasani, Deepti; Haas, David W.; Herbeck, Joshua T.; Johnson, Eric O.; Kirk, Gregory D.; Lambotte, Olivier; Luo, Ma; Mallal, Simon; van Manen, Daniëlle; Martinez-Picado, Javier; Meyer, Laurence; Miro, José M.; Mullins, James I.; Obel, Niels; Poli, Guido; Sandhu, Manjinder S.; Schuitemaker, Hanneke; Shea, Patrick R.; Theodorou, Ioannis; Walker, Bruce D.; Weintrob, Amy C.; Winkler, Cheryl A.; Wolinsky, Steven M.; Raychaudhuri, Soumya; Goldstein, David B.; Telenti, Amalio; de Bakker, Paul I. W.; Zagury, Jean-François; Fellay, Jacques
2015-01-01
Previous genome-wide association studies (GWAS) of HIV-1–infected populations have been underpowered to detect common variants with moderate impact on disease outcome and have not assessed the phenotypic variance explained by genome-wide additive effects. By combining the majority of available genome-wide genotyping data in HIV-infected populations, we tested for association between ∼8 million variants and viral load (HIV RNA copies per milliliter of plasma) in 6,315 individuals of European ancestry. The strongest signal of association was observed in the HLA class I region that was fully explained by independent effects mapping to five variable amino acid positions in the peptide binding grooves of the HLA-B and HLA-A proteins. We observed a second genome-wide significant association signal in the chemokine (C-C motif) receptor (CCR) gene cluster on chromosome 3. Conditional analysis showed that this signal could not be fully attributed to the known protective CCR5Δ32 allele and the risk P1 haplotype, suggesting further causal variants in this region. Heritability analysis demonstrated that common human genetic variation—mostly in the HLA and CCR5 regions—explains 25% of the variability in viral load. This study suggests that analyses in non-European populations and of variant classes not assessed by GWAS should be priorities for the field going forward. PMID:26553974
Rodriguez, Gabriela; Ueyama, Tomomi; Ogata, Takehiro; Czernuszewicz', Grazyna; Tan, Yanli; Dorn, Gerald W.; Bogaev, Roberta; Amano, Katsuya; Oh, Hidemasa; Matsubara, Hiroaki; Willerson, James T.; Marian, Ali J.
2011-01-01
Background Dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are classic forms of systolic and diastolic heart failure, respectively. Mutations in genes encoding sarcomere and cytoskeletal proteins are major causes of HCM and DCM. MURC, encoding muscle-restricted coiled-coil, a Z line protein, regulates cardiac function in mice. We investigated potential causal role of MURC in human cardiomyopathies. Methods and Results We sequenced MURC in 1,199 individuals including 383 probands with DCM, 307 with HCM and 509 healthy controls. We found six heterozygous DCM-specific missense variants (p.N128K, p.R140W, p.L153P, p.S307T, p.P324L and p.S364L) in eight unrelated probands. Variants p.N128K and p.S307T segregated with inheritance of DCM in small families (χ2=8.5, p=0.003). Variants p.N128K, p.R140W, p.L153P and p.S364L were considered probably or possibly damaging. Variant p.P324L recurred in three independent probands, including one proband with a TPM1 mutation (p.M245T). A deletion variant (p.L232-R238del) was present in three unrelated HCM probands but it did not segregate with HCM in a family who also had a MYH7 mutation (p.L970V). The phenotype in mutation carriers was notable for progressive heart failure leading to heart transplantation in four patients, conduction defects and atrial arrhythmias. Expression of mutant MURC proteins in neonatal rat cardiac myocytes transduced with recombinant adenoviruses was associated with reduced RhoA activity, lower mRNA levels of hypertrophic markers and smaller myocyte size as compared to wild type MURC. Conclusions MURC mutations impart loss-of-function effects on MURC functions and are likely causal variants in human DCM. The causal role of a deletion mutation in HCM is uncertain. PMID:21642240
Rodriguez, Gabriela; Ueyama, Tomomi; Ogata, Takehiro; Czernuszewicz, Grazyna; Tan, Yanli; Dorn, Gerald W; Bogaev, Roberta; Amano, Katsuya; Oh, Hidemasa; Matsubara, Hiroaki; Willerson, James T; Marian, Ali J
2011-08-01
Dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are classic forms of systolic and diastolic heart failure, respectively. Mutations in genes encoding sarcomere and cytoskeletal proteins are major causes of HCM and DCM. MURC, encoding muscle-restricted coiled-coil, a Z-line protein, regulates cardiac function in mice. We investigated potential causal role of MURC in human cardiomyopathies. We sequenced MURC in 1199 individuals, including 383 probands with DCM, 307 with HCM, and 509 healthy control subjects. We found 6 heterozygous DCM-specific missense variants (p.N128K, p.R140W, p.L153P, p.S307T, p.P324L, and p.S364L) in 8 unrelated probands. Variants p.N128K and p.S307T segregated with inheritance of DCM in small families (χ(2)=8.5, P=0.003). Variants p.N128K, p.R140W, p.L153P, and p.S364L were considered probably or possibly damaging. Variant p.P324L recurred in 3 independent probands, including 1 proband with a TPM1 mutation (p.M245T). A deletion variant (p.L232-R238del) was present in 3 unrelated HCM probands, but it did not segregate with HCM in a family who also had a MYH7 mutation (p.L907V). The phenotype in mutation carriers was notable for progressive heart failure leading to heart transplantation in 4 patients, conduction defects, and atrial arrhythmias. Expression of mutant MURC proteins in neonatal rat cardiac myocytes transduced with recombinant adenoviruses was associated with reduced RhoA activity, lower mRNA levels of hypertrophic markers and smaller myocyte size as compared with wild-type MURC. MURC mutations impart loss-of-function effects on MURC functions and probably are causal variants in human DCM. The causal role of a deletion mutation in HCM is uncertain.
Fine-mapping inflammatory bowel disease loci to single-variant resolution.
Huang, Hailiang; Fang, Ming; Jostins, Luke; Umićević Mirkov, Maša; Boucher, Gabrielle; Anderson, Carl A; Andersen, Vibeke; Cleynen, Isabelle; Cortes, Adrian; Crins, François; D'Amato, Mauro; Deffontaine, Valérie; Dmitrieva, Julia; Docampo, Elisa; Elansary, Mahmoud; Farh, Kyle Kai-How; Franke, Andre; Gori, Ann-Stephan; Goyette, Philippe; Halfvarson, Jonas; Haritunians, Talin; Knight, Jo; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mariman, Rob; Meuwissen, Theo; Mni, Myriam; Momozawa, Yukihide; Parkes, Miles; Spain, Sarah L; Théâtre, Emilie; Trynka, Gosia; Satsangi, Jack; van Sommeren, Suzanne; Vermeire, Severine; Xavier, Ramnik J; Weersma, Rinse K; Duerr, Richard H; Mathew, Christopher G; Rioux, John D; McGovern, Dermot P B; Cho, Judy H; Georges, Michel; Daly, Mark J; Barrett, Jeffrey C
2017-07-13
Inflammatory bowel diseases are chronic gastrointestinal inflammatory disorders that affect millions of people worldwide. Genome-wide association studies have identified 200 inflammatory bowel disease-associated loci, but few have been conclusively resolved to specific functional variants. Here we report fine-mapping of 94 inflammatory bowel disease loci using high-density genotyping in 67,852 individuals. We pinpoint 18 associations to a single causal variant with greater than 95% certainty, and an additional 27 associations to a single variant with greater than 50% certainty. These 45 variants are significantly enriched for protein-coding changes (n = 13), direct disruption of transcription-factor binding sites (n = 3), and tissue-specific epigenetic marks (n = 10), with the last category showing enrichment in specific immune cells among associations stronger in Crohn's disease and in gut mucosa among associations stronger in ulcerative colitis. The results of this study suggest that high-resolution fine-mapping in large samples can convert many discoveries from genome-wide association studies into statistically convincing causal variants, providing a powerful substrate for experimental elucidation of disease mechanisms.
Meng, Xiang-He; Shen, Hui; Chen, Xiang-Ding; Xiao, Hong-Mei; Deng, Hong-Wen
2018-03-01
Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.
An update on the genetic architecture of hyperuricemia and gout.
Merriman, Tony R
2015-04-10
Genome-wide association studies that scan the genome for common genetic variants associated with phenotype have greatly advanced medical knowledge. Hyperuricemia is no exception, with 28 loci identified. However, genetic control of pathways determining gout in the presence of hyperuricemia is still poorly understood. Two important pathways determining hyperuricemia have been confirmed (renal and gut excretion of uric acid with glycolysis now firmly implicated). Major urate loci are SLC2A9 and ABCG2. Recent studies show that SLC2A9 is involved in renal and gut excretion of uric acid and is implicated in antioxidant defense. Although etiological variants at SLC2A9 are yet to be identified, it is clear that considerable genetic complexity exists at the SLC2A9 locus, with multiple statistically independent genetic variants and local epistatic interactions. The positions of implicated genetic variants within or near chromatin regions involved in transcriptional control suggest that this mechanism (rather than structural changes in SLC2A9) is important in regulating the activity of SLC2A9. ABCG2 is involved primarily in extra-renal uric acid under-excretion with the etiological variant influencing expression. At the other 26 loci, probable causal genes can be identified at three (PDZK1, SLC22A11, and INHBB) with strong candidates at a further 10 loci. Confirmation of the causal gene will require a combination of re-sequencing, trans-ancestral mapping, and correlation of genetic association data with expression data. As expected, the urate loci associate with gout, although inconsistent effect sizes for gout require investigation. Finally, there has been no genome-wide association study using clinically ascertained cases to investigate the causes of gout in the presence of hyperuricemia. In such a study, use of asymptomatic hyperurcemic controls would be expected to increase the ability to detect genetic associations with gout.
Kwok, Chun T; Morris, Alex; de Belleroche, Jacqueline S
2014-04-01
Mutations in the SQSTM1 gene have been reported to be associated with amyotrophic lateral sclerosis (ALS). We sought to determine the frequency of these mutations in a UK familial ALS (FALS) cohort. Sequences of all eight exons of the SQSTM1 gene were analysed in index cases from 61 different FALS kindred lacking known FALS mutations. Six exonic variants c.463G>A, p.(Glu155Lys), c.822G>C, p.(Glu274Asp), c.888G>T, p.(=), c.954C>T, p.(=), c.1038G>A, p.(=) and c.1175C>T, p.(Pro392Leu) were identified in five FALS index cases, three of which were non-synonymous and three were synonymous. One index case harboured three variants (c.822G>C, c.888G>T and c.954C>T), and a second index case harboured two variants (c.822G>C and c.954C>T). Only the p.(Pro392Leu) and p.(Glu155Lys) mutations were predicted to be pathogenic. In one p.(Pro392Leu) kindred, the carrier developed both ALS and Paget's disease of bone (PDB), and, in the p.(Glu155Lys) kindred, the father of the proband developed PDB. All p.(Pro392Leu) carriers were heterozygous for a previously reported founder haplotype for PDB, where this mutation has an established causal effect. The frequency of the p.(Pro392Leu) mutation in this UK FALS cohort was 2.3% and 0.97% overall including three previously screened FALS cohorts. Our results confirm the presence of the p.(Pro392Leu) SQSTM1 mutation in FALS. This mutation is the most common SQSTM1 mutation found in ALS to date, and a likely pathogenicity is supported by having an established causal role in PDB. The occurrence of the same mutation in ALS and PDB is indicative of a common pathogenic pathway that converges on protein homeostasis.
USDA-ARS?s Scientific Manuscript database
Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a mor...
Gustafsson, Stefan; Rybin, Denis; Stančáková, Alena; Chen, Han; Liu, Ching-Ti; Hong, Jaeyoung; Jensen, Richard A.; Rice, Ken; Morris, Andrew P.; Mägi, Reedik; Tönjes, Anke; Prokopenko, Inga; Kleber, Marcus E.; Delgado, Graciela; Silbernagel, Günther; Jackson, Anne U.; Appel, Emil V.; Grarup, Niels; Lewis, Joshua P.; Montasser, May E.; Landenvall, Claes; Staiger, Harald; Luan, Jian’an; Frayling, Timothy M.; Weedon, Michael N.; Xie, Weijia; Morcillo, Sonsoles; Martínez-Larrad, María Teresa; Biggs, Mary L.; Chen, Yii-Der Ida; Corbaton-Anchuelo, Arturo; Færch, Kristine; Gómez-Zumaquero, Juan Miguel; Goodarzi, Mark O.; Kizer, Jorge R.; Koistinen, Heikki A.; Leong, Aaron; Lind, Lars; Lindgren, Cecilia; Machicao, Fausto; Manning, Alisa K.; Martín-Núñez, Gracia María; Rojo-Martínez, Gemma; Rotter, Jerome I.; Siscovick, David S.; Zmuda, Joseph M.; Zhang, Zhongyang; Serrano-Rios, Manuel; Smith, Ulf; Soriguer, Federico; Hansen, Torben; Jørgensen, Torben J.; Linnenberg, Allan; Pedersen, Oluf; Walker, Mark; Langenberg, Claudia; Scott, Robert A.; Wareham, Nicholas J.; Fritsche, Andreas; Häring, Hans-Ulrich; Stefan, Norbert; Groop, Leif; O’Connell, Jeff R.; Boehnke, Michael; Bergman, Richard N.; Collins, Francis S.; Mohlke, Karen L.; Tuomilehto, Jaakko; März, Winfried; Kovacs, Peter; Stumvoll, Michael; Psaty, Bruce M.; Kuusisto, Johanna; Laakso, Markku; Meigs, James B.; Dupuis, Josée; Ingelsson, Erik; Florez, Jose C.
2016-01-01
Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10−11), rs12454712 (BCL2; P = 2.7 × 10−8), and rs10506418 (FAM19A2; P = 1.9 × 10−8). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci. PMID:27416945
Coassin, Stefan; Friedel, Salome; Köttgen, Anna; Lamina, Claudia; Kronenberg, Florian
2016-11-01
A recent observational study with almost 2 million men reported an association between low high-density lipoprotein (HDL) cholesterol and worse kidney function. The causality of this association would be strongly supported if genetic variants associated with HDL cholesterol were also associated with kidney function. We used 68 genetic variants (single-nucleotide polymorphisms [SNPs]) associated with HDL cholesterol in genome-wide association studies including >188 000 subjects and tested their association with estimated glomerular filtration rate (eGFR) using summary statistics from another genome-wide association studies meta-analysis of kidney function including ≤133 413 subjects. Fourteen of the 68 SNPs (21%) had a P value <0.05 compared with the 5% expected by chance (Binomial test P=5.8×10 - 6 ). After Bonferroni correction, 6 SNPs were still significantly associated with eGFR. The genetic variants with the strongest associations with HDL cholesterol concentrations were not the same as those with the strongest association with kidney function and vice versa. An evaluation of pleiotropy indicated that the effects of the HDL-associated SNPs on eGFR were not mediated by HDL cholesterol. In addition, we performed a Mendelian randomization analysis. This analysis revealed a positive but nonsignificant causal effect of HDL cholesterol-increasing variants on eGFR. In summary, our findings indicate that HDL cholesterol does not causally influence eGFR and propose pleiotropic effects on eGFR for some HDL cholesterol-associated SNPs. This may cause the observed association by mechanisms other than the mere HDL cholesterol concentration. © 2016 The Authors.
Smith, Andrew J P; Deloukas, Panos; Munroe, Patricia B
2018-04-13
Over the last decade, genome-wide association studies (GWAS) have propelled the discovery of thousands of loci associated with complex diseases. The focus is now turning towards the function of these association signals, determining the causal variant(s) amongst those in strong linkage disequilibrium, and identifying their underlying mechanisms, such as long-range gene regulation. Genome-editing techniques utilising zinc-finger nucleases (ZFN), transcription activator-like effector nucleases (TALENs) and clustered regularly-interspaced short palindromic repeats with Cas9 nuclease (CRISPR-Cas9), are becoming the tools of choice to establish functionality for these variants, due to the ability to assess effects of single variants in vivo. This review will discuss examples of how these technologies have begun to aid functional analysis of GWAS loci for complex traits such as cardiovascular disease, type 2 diabetes, cancer, obesity and autoimmune disease. We focus on analysis of variants occurring within non-coding genomic regions, as these comprise the majority of GWAS variants, providing the greatest challenges to determining functionality, and compare editing strategies that provide different levels of evidence for variant functionality. The review describes molecular insights into some of these potentially causal variants, and how these may relate to the pathology of the trait, and look towards future directions for these technologies in post-GWAS analysis, such as base-editing.
Guillen-Ahlers, Hector; Erbe, Christy B; Chevalier, Frédéric D; Montoya, Maria J; Zimmerman, Kip D; Langefeld, Carl D; Olivier, Michael; Runge, Christina L
2018-04-19
Sensorineural hearing loss (SNHL) is a common form of hearing loss that can be inherited or triggered by environmental insults; auditory neuropathy spectrum disorder (ANSD) is a SNHL subtype with unique diagnostic criteria. The genetic factors associated with these impairments are vast and diverse, but causal genetic factors are rarely characterized. A family dyad, both cochlear implant recipients, presented with a hearing history of bilateral, progressive SNHL, and ANSD. Whole-exome sequencing was performed to identify coding sequence variants shared by both family members, and screened against genes relevant to hearing loss and variants known to be associated with SNHL and ANSD. Both family members are successful cochlear implant users, demonstrating effective auditory nerve stimulation with their devices. Genetic analyses revealed a mutation (rs35725509) in the TMTC2 gene, which has been reported previously as a likely genetic cause of SNHL in another family of Northern European descent. This study represents the first confirmation of the rs35725509 variant in an independent family as a likely cause for the complex hearing loss phenotype (SNHL and ANSD) observed in this family dyad. © 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.
Hu, Hao; Wienker, Thomas F; Musante, Luciana; Kalscheuer, Vera M; Kahrizi, Kimia; Najmabadi, Hossein; Ropers, H Hilger
2014-12-01
Next-generation sequencing has greatly accelerated the search for disease-causing defects, but even for experts the data analysis can be a major challenge. To facilitate the data processing in a clinical setting, we have developed a novel medical resequencing analysis pipeline (MERAP). MERAP assesses the quality of sequencing, and has optimized capacity for calling variants, including single-nucleotide variants, insertions and deletions, copy-number variation, and other structural variants. MERAP identifies polymorphic and known causal variants by filtering against public domain databases, and flags nonsynonymous and splice-site changes. MERAP uses a logistic model to estimate the causal likelihood of a given missense variant. MERAP considers the relevant information such as phenotype and interaction with known disease-causing genes. MERAP compares favorably with GATK, one of the widely used tools, because of its higher sensitivity for detecting indels, its easy installation, and its economical use of computational resources. Upon testing more than 1,200 individuals with mutations in known and novel disease genes, MERAP proved highly reliable, as illustrated here for five families with disease-causing variants. We believe that the clinical implementation of MERAP will expedite the diagnostic process of many disease-causing defects. © 2014 WILEY PERIODICALS, INC.
Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Alonso, M. Rosario; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Benitez, Javier; Bogdanova, Natalia V.; Bojesen, Stig E.; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M.; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F.; Fasching, Peter A.; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G.; Goldberg, Mark S.; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A.; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L.; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L.; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C.; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H.; Tessier, Daniel C.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M.; Vincent, Daniel; Winqvist, Robert; Wu, Anna H.; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D. P.; Hall, Per; Edwards, Stacey L.; Simard, Jacques; French, Juliet D.; Chenevix-Trench, Georgia; Dunning, Alison M.
2016-01-01
Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90–0.94; P = 8.96 × 10−15)) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10−09, r2 = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10−11, r2 = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus. PMID:27600471
Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Alonso, M Rosario; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Benitez, Javier; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F; Fasching, Peter A; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G; Goldberg, Mark S; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H; Tessier, Daniel C; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M; Vincent, Daniel; Winqvist, Robert; Wu, Anna H; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D P; Hall, Per; Edwards, Stacey L; Simard, Jacques; French, Juliet D; Chenevix-Trench, Georgia; Dunning, Alison M
2016-09-07
Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.
Bailey-Wilson, Joan E.; Brennan, Jennifer S.; Bull, Shelley B; Culverhouse, Robert; Kim, Yoonhee; Jiang, Yuan; Jung, Jeesun; Li, Qing; Lamina, Claudia; Liu, Ying; Mägi, Reedik; Niu, Yue S.; Simpson, Claire L.; Wang, Libo; Yilmaz, Yildiz E.; Zhang, Heping; Zhang, Zhaogong
2012-01-01
Group 14 of Genetic Analysis Workshop 17 examined several issues related to analysis of complex traits using DNA sequence data. These issues included novel methods for analyzing rare genetic variants in an aggregated manner (often termed collapsing rare variants), evaluation of various study designs to increase power to detect effects of rare variants, and the use of machine learning approaches to model highly complex heterogeneous traits. Various published and novel methods for analyzing traits with extreme locus and allelic heterogeneity were applied to the simulated quantitative and disease phenotypes. Overall, we conclude that power is (as expected) dependent on locus-specific heritability or contribution to disease risk, large samples will be required to detect rare causal variants with small effect sizes, extreme phenotype sampling designs may increase power for smaller laboratory costs, methods that allow joint analysis of multiple variants per gene or pathway are more powerful in general than analyses of individual rare variants, population-specific analyses can be optimal when different subpopulations harbor private causal mutations, and machine learning methods may be useful for selecting subsets of predictors for follow-up in the presence of extreme locus heterogeneity and large numbers of potential predictors. PMID:22128066
Böhmer, Anne C.; Bowes, John; Nikolić, Miloš; Ishorst, Nina; Wyatt, Niki; Hammond, Nigel L.; Gölz, Lina; Thieme, Frederic; Barth, Sandra; Schuenke, Hannah; Klamt, Johanna; Spielmann, Malte; Aldhorae, Khalid; Rojas-Martinez, Augusto; Nöthen, Markus M.; Rada-Iglesias, Alvaro; Dixon, Michael J.; Knapp, Michael; Mangold, Elisabeth
2017-01-01
Abstract Nonsyndromic cleft lip with or without cleft palate (nsCL/P) is among the most common human birth defects with multifactorial etiology. Here, we present results from a genome-wide imputation study of nsCL/P in which, after adding replication cohort data, four novel risk loci for nsCL/P are identified (at chromosomal regions 2p21, 14q22, 15q24 and 19p13). On a systematic level, we show that the association signals within this high-density dataset are enriched in functionally-relevant genomic regions that are active in both human neural crest cells (hNCC) and mouse embryonic craniofacial tissue. This enrichment is also detectable in hNCC regions primed for later activity. Using GCTA analyses, we suggest that 30% of the estimated variance in risk for nsCL/P in the European population can be attributed to common variants, with 25.5% contributed to by the 24 risk loci known to date. For each of these, we identify credible SNPs using a Bayesian refinement approach, with two loci harbouring only one probable causal variant. Finally, we demonstrate that there is no polygenic component of nsCL/P detectable that is shared with nonsyndromic cleft palate only (nsCPO). Our data suggest that, while common variants are strongly contributing to risk for nsCL/P, they do not seem to be involved in nsCPO which might be more often caused by rare deleterious variants. Our study generates novel insights into both nsCL/P and nsCPO etiology and provides a systematic framework for research into craniofacial development and malformation. PMID:28087736
Causality networks from multivariate time series and application to epilepsy.
Siggiridou, Elsa; Koutlis, Christos; Tsimpiris, Alkiviadis; Kimiskidis, Vasilios K; Kugiumtzis, Dimitris
2015-08-01
Granger causality and variants of this concept allow the study of complex dynamical systems as networks constructed from multivariate time series. In this work, a large number of Granger causality measures used to form causality networks from multivariate time series are assessed. For this, realizations on high dimensional coupled dynamical systems are considered and the performance of the Granger causality measures is evaluated, seeking for the measures that form networks closest to the true network of the dynamical system. In particular, the comparison focuses on Granger causality measures that reduce the state space dimension when many variables are observed. Further, the linear and nonlinear Granger causality measures of dimension reduction are compared to a standard Granger causality measure on electroencephalographic (EEG) recordings containing episodes of epileptiform discharges.
Ng, Maggie C Y; Graff, Mariaelisa; Lu, Yingchang; Justice, Anne E; Mudgal, Poorva; Liu, Ching-Ti; Young, Kristin; Yanek, Lisa R; Feitosa, Mary F; Wojczynski, Mary K; Rand, Kristin; Brody, Jennifer A; Cade, Brian E; Dimitrov, Latchezar; Duan, Qing; Guo, Xiuqing; Lange, Leslie A; Nalls, Michael A; Okut, Hayrettin; Tajuddin, Salman M; Tayo, Bamidele O; Vedantam, Sailaja; Bradfield, Jonathan P; Chen, Guanjie; Chen, Wei-Min; Chesi, Alessandra; Irvin, Marguerite R; Padhukasahasram, Badri; Smith, Jennifer A; Zheng, Wei; Allison, Matthew A; Ambrosone, Christine B; Bandera, Elisa V; Bartz, Traci M; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Bottinger, Erwin P; Carpten, John; Chanock, Stephen J; Chen, Yii-Der Ida; Conti, David V; Cooper, Richard S; Fornage, Myriam; Freedman, Barry I; Garcia, Melissa; Goodman, Phyllis J; Hsu, Yu-Han H; Hu, Jennifer; Huff, Chad D; Ingles, Sue A; John, Esther M; Kittles, Rick; Klein, Eric; Li, Jin; McKnight, Barbara; Nayak, Uma; Nemesure, Barbara; Ogunniyi, Adesola; Olshan, Andrew; Press, Michael F; Rohde, Rebecca; Rybicki, Benjamin A; Salako, Babatunde; Sanderson, Maureen; Shao, Yaming; Siscovick, David S; Stanford, Janet L; Stevens, Victoria L; Stram, Alex; Strom, Sara S; Vaidya, Dhananjay; Witte, John S; Yao, Jie; Zhu, Xiaofeng; Ziegler, Regina G; Zonderman, Alan B; Adeyemo, Adebowale; Ambs, Stefan; Cushman, Mary; Faul, Jessica D; Hakonarson, Hakon; Levin, Albert M; Nathanson, Katherine L; Ware, Erin B; Weir, David R; Zhao, Wei; Zhi, Degui; Arnett, Donna K; Grant, Struan F A; Kardia, Sharon L R; Oloapde, Olufunmilayo I; Rao, D C; Rotimi, Charles N; Sale, Michele M; Williams, L Keoki; Zemel, Babette S; Becker, Diane M; Borecki, Ingrid B; Evans, Michele K; Harris, Tamara B; Hirschhorn, Joel N; Li, Yun; Patel, Sanjay R; Psaty, Bruce M; Rotter, Jerome I; Wilson, James G; Bowden, Donald W; Cupples, L Adrienne; Haiman, Christopher A; Loos, Ruth J F; North, Kari E
2017-04-01
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.
Gorin, Michael B.
2012-01-01
Age-related macular degeneration (AMD) is a common condition among the elderly population that leads to the progressive central vision loss and serious compromise of quality of life for its sufferers. It is also one of the few disorders for whom the investigation of its genetics has yielded rich insights into its diversity and causality and holds the promise of enabling clinicians to provide better risk assessments for individuals as well as to develop and selectively deploy new therapeutics to either prevent or slow the development of disease and lessen the threat of vision loss. The genetics of AMD began initially with the appreciation of familial aggregation and increase risk and expanded with the initial association of APOE variants with the disease. The first major breakthroughs came with family-based linkage studies of affected (and discordant) sibs, which identified a number of genetic loci and led to the targeted search of the 1q31 and 10q26 loci for associated variants. Three of the initial four reports for the CFH variant, Y402H, were based on regional candidate searches, as were the two initial reports of the ARMS2/HTRA1 locus variants. Case-control association studies initially also played a role in discovering the major genetic variants for AMD, and the success of those early studies have been used to fuel enthusiasm for the methodology for a number of diseases. Until 2010, all of the subsequent genetic variants associated with AMD came from candidate gene testing based on the complement factor pathway. In 2010, several large-scale genome-wide association studies (GWAS) identified genes that had not been previously identified. Much of this historical information is available in a number of recent reviews.(Chen et al., 2010b; Deangelis et al., 2011; Fafowora and Gorin, 2012b; Francis and Klein, 2011; Kokotas et al., 2011) Large meta analysis of AMD GWAS has added new loci and variants to this collection.(Chen et al., 2010a; Kopplin et al., 2010; Yu et al., 2011) This paper will focus on the ongoing controversies that are confronting AMD genetics at this time, rather than attempting to summarize this field, which has exploded in the past 5 years. PMID:22561651
A splice variant in the ACSL5 gene relates migraine with fatty acid activation in mitochondria
Matesanz, Fuencisla; Fedetz, María; Barrionuevo, Cristina; Karaky, Mohamad; Catalá-Rabasa, Antonio; Potenciano, Victor; Bello-Morales, Raquel; López-Guerrero, Jose-Antonio; Alcina, Antonio
2016-01-01
Genome-wide association studies (GWAS) in migraine are providing the molecular basis of this heterogeneous disease, but the understanding of its aetiology is still incomplete. Although some biomarkers have currently been accepted for migraine, large amount of studies for identifying new ones is needed. The migraine-associated variant rs12355831:A>G (P=2 × 10−6), described in a GWAS of the International Headache Genetic Consortium, is localized in a non-coding sequence with unknown function. We sought to identify the causal variant and the genetic mechanism involved in the migraine risk. To this end, we integrated data of RNA sequences from the Genetic European Variation in Health and Disease (GEUVADIS) and genotypes from 1000 GENOMES of 344 lymphoblastoid cell lines (LCLs), to determine the expression quantitative trait loci (eQTLs) in the region. We found that the migraine-associated variant belongs to a linkage disequilibrium block associated with the expression of an acyl-coenzyme A synthetase 5 (ACSL5) transcript lacking exon 20 (ACSL5-Δ20). We showed by exon-skipping assay a direct causality of rs2256368-G in the exon 20 skipping of approximately 20 to 40% of ACSL5 RNA molecules. In conclusion, we identified the functional variant (rs2256368:A>G) affecting ACSL5 exon 20 skipping, as a causal factor linked to the migraine-associated rs12355831:A>G, suggesting that the activation of long-chain fatty acids by the spliced ACSL5-Δ20 molecules, a mitochondrial located enzyme, is involved in migraine pathology. PMID:27189022
Role of Adiponectin in Coronary Heart Disease Risk
Lawlor, Debbie A.; de Oliveira, Cesar; White, Jon; Horta, Bernardo Lessa; Barros, Aluísio J.D.
2016-01-01
Rationale: Hypoadiponectinemia correlates with several coronary heart disease (CHD) risk factors. However, it is unknown whether adiponectin is causally implicated in CHD pathogenesis. Objective: We aimed to investigate the causal effect of adiponectin on CHD risk. Methods and Results: We undertook a Mendelian randomization study using data from genome-wide association studies consortia. We used the ADIPOGen consortium to identify genetic variants that could be used as instrumental variables for the effect of adiponectin. Data on the association of these genetic variants with CHD risk were obtained from CARDIoGRAM (22 233 CHD cases and 64 762 controls of European ancestry) and from CARDIoGRAMplusC4D Metabochip (63 746 cases and 130 681 controls; ≈ 91% of European ancestry) consortia. Data on the association of genetic variants with adiponectin levels and with CHD were combined to estimate the influence of blood adiponectin on CHD risk. In the conservative approach (restricted to using variants within the adiponectin gene as instrumental variables), each 1 U increase in log blood adiponectin concentration was associated with an odds ratio for CHD of 0.83 (95% confidence interval, 0.68–1.01) in CARDIoGRAM and 0.97 (95% confidence interval, 0.84–1.12) in CARDIoGRAMplusC4D Metabochip. Findings from the liberal approach (including variants in any locus across the genome) indicated a protective effect of adiponectin that was attenuated to the null after adjustment for known CHD predictors. Conclusions: Overall, our findings do not support a causal role of adiponectin levels in CHD pathogenesis. PMID:27252388
Corbin, Laura J; Tan, Vanessa Y; Hughes, David A; Wade, Kaitlin H; Paul, Dirk S; Tansey, Katherine E; Butcher, Frances; Dudbridge, Frank; Howson, Joanna M; Jallow, Momodou W; John, Catherine; Kingston, Nathalie; Lindgren, Cecilia M; O'Donavan, Michael; O'Rahilly, Stephen; Owen, Michael J; Palmer, Colin N A; Pearson, Ewan R; Scott, Robert A; van Heel, David A; Whittaker, John; Frayling, Tim; Tobin, Martin D; Wain, Louise V; Smith, George Davey; Evans, David M; Karpe, Fredrik; McCarthy, Mark I; Danesh, John; Franks, Paul W; Timpson, Nicholas J
2018-02-19
Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.
van Meurs, Joyce BJ; Pare, Guillaume; Schwartz, Stephen M; Hazra, Aditi; Tanaka, Toshiko; Vermeulen, Sita H; Cotlarciuc, Ioana; Yuan, Xin; Mälarstig, Anders; Bandinelli, Stefania; Bis, Joshua C; Blom, Henk; Brown, Morris J; Chen, Constance; Chen, Yii-Der; Clarke, Robert J; Dehghan, Abbas; Erdmann, Jeanette; Ferrucci, Luigi; Hamsten, Anders; Hofman, Albert; Hunter, David J; Goel, Anuj; Johnson, Andrew D; Kathiresan, Sekar; Kampman, Ellen; Kiel, Douglas P; Kiemeney, Lambertus ALM; Chambers, John C; Kraft, Peter; Lindemans, Jan; McKnight, Barbara; Nelson, Christopher P; O'Donnell, Christopher J; Psaty, Bruce M; Ridker, Paul M; Rivadeneira, Fernando; Rose, Lynda M; Seedorf, Udo; Siscovick, David S; Schunkert, Heribert; Selhub, Jacob; Ueland, Per M; Vollenweider, Peter; Waeber, Gérard; Waterworth, Dawn M; Watkins, Hugh; Witteman, Jacqueline CM; den Heijer, Martin; Jacques, Paul; Uitterlinden, Andre G; Kooner, Jaspal S; Rader, Dan J; Reilly, Muredach P; Mooser, Vincent; Chasman, Daniel I; Samani, Nilesh J; Ahmadi, Kourosh R
2013-01-01
Background: The strong observational association between total homocysteine (tHcy) concentrations and risk of coronary artery disease (CAD) and the null associations in the homocysteine-lowering trials have prompted the need to identify genetic variants associated with homocysteine concentrations and risk of CAD. Objective: We tested whether common genetic polymorphisms associated with variation in tHcy are also associated with CAD. Design: We conducted a meta-analysis of genome-wide association studies (GWAS) on tHcy concentrations in 44,147 individuals of European descent. Polymorphisms associated with tHcy (P < 10−8) were tested for association with CAD in 31,400 cases and 92,927 controls. Results: Common variants at 13 loci, explaining 5.9% of the variation in tHcy, were associated with tHcy concentrations, including 6 novel loci in or near MMACHC (2.1 × 10−9), SLC17A3 (1.0 × 10−8), GTPB10 (1.7 × 10−8), CUBN (7.5 × 10−10), HNF1A (1.2 × 10−12), and FUT2 (6.6 × 10−9), and variants previously reported at or near the MTHFR, MTR, CPS1, MUT, NOX4, DPEP1, and CBS genes. Individuals within the highest 10% of the genotype risk score (GRS) had 3-μmol/L higher mean tHcy concentrations than did those within the lowest 10% of the GRS (P = 1 × 10−36). The GRS was not associated with risk of CAD (OR: 1.01; 95% CI: 0.98, 1.04; P = 0.49). Conclusions: We identified several novel loci that influence plasma tHcy concentrations. Overall, common genetic variants that influence plasma tHcy concentrations are not associated with risk of CAD in white populations, which further refutes the causal relevance of moderately elevated tHcy concentrations and tHcy-related pathways for CAD. PMID:23824729
Screening for rare variants in the PNPLA3 gene in obese liver biopsy patients.
Zegers, Doreen; Verrijken, An; Francque, Sven; de Freitas, Fenna; Beckers, Sigri; Aerts, Evi; Ruppert, Martin; Hubens, Guy; Michielsen, Peter; Van Hul, Wim; Van Gaal, Luc F
2016-12-01
Previous research has clearly implicated the PNPLA3 gene in the etiology of nonalcoholic fatty liver disease as a polymorphism in the gene was found to be robustly associated to the disease. However, data on the involvement of rare PNPLA3 variants in the development of nonalcoholic fatty liver disease (NAFLD) is currently limited. Therefore, we performed an extensive mutation analysis study on a cohort of obese liver biopsy patients to determine PNPLA3 variation and its correlation with fatty liver disease. We screened the entire coding region of the PNPLA3 gene in DNA samples of 393 obese liver biopsy patients with varying degrees of fatty liver disease. Mutation analysis was performed by high-resolution melting curve analysis in combination with direct sequencing. We identified several common polymorphisms as well as one rare synonymous variant (c.867G>A rs139896256), one rare intronic variant (c.979+13C>T) and 3 nonsynonymous coding variants (p.A76T, p.A104V and p.T200M) in the PNPLA3 gene. In silico analysis indicated that the p.A104V variant will probably have no functional effect, whereas for the p.A76T and p.T200M variant a possible pathogenic effect is suggested. Overall, we showed that novel variants in PNPLA3 are very rare in our liver biopsy cohort, thereby indicating that their impact on the etiology of NAFLD is probably limited. Nevertheless, for the three rare coding variants that were identified in patients with advanced liver disease, further functional characterization will be essential to verify their potential disease causality. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Xie, Weijia; Wood, Andrew R; Lyssenko, Valeriya; Weedon, Michael N; Knowles, Joshua W; Alkayyali, Sami; Assimes, Themistocles L; Quertermous, Thomas; Abbasi, Fahim; Paananen, Jussi; Häring, Hans; Hansen, Torben; Pedersen, Oluf; Smith, Ulf; Laakso, Markku; Dekker, Jacqueline M; Nolan, John J; Groop, Leif; Ferrannini, Ele; Adam, Klaus-Peter; Gall, Walter E; Frayling, Timothy M; Walker, Mark
2013-06-01
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.
Xie, Weijia; Wood, Andrew R.; Lyssenko, Valeriya; Weedon, Michael N.; Knowles, Joshua W.; Alkayyali, Sami; Assimes, Themistocles L.; Quertermous, Thomas; Abbasi, Fahim; Paananen, Jussi; Häring, Hans; Hansen, Torben; Pedersen, Oluf; Smith, Ulf; Laakso, Markku; Dekker, Jacqueline M.; Nolan, John J.; Groop, Leif; Ferrannini, Ele; Adam, Klaus-Peter; Gall, Walter E.; Frayling, Timothy M.; Walker, Mark
2013-01-01
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity–related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites—glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)—and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits. PMID:23378610
Taylor, Robert W; Pyle, Angela; Griffin, Helen; Blakely, Emma L; Duff, Jennifer; He, Langping; Smertenko, Tania; Alston, Charlotte L; Neeve, Vivienne C; Best, Andrew; Yarham, John W; Kirschner, Janbernd; Schara, Ulrike; Talim, Beril; Topaloglu, Haluk; Baric, Ivo; Holinski-Feder, Elke; Abicht, Angela; Czermin, Birgit; Kleinle, Stephanie; Morris, Andrew A M; Vassallo, Grace; Gorman, Grainne S; Ramesh, Venkateswaran; Turnbull, Douglass M; Santibanez-Koref, Mauro; McFarland, Robert; Horvath, Rita; Chinnery, Patrick F
2014-07-02
Mitochondrial disorders have emerged as a common cause of inherited disease, but their diagnosis remains challenging. Multiple respiratory chain complex defects are particularly difficult to diagnose at the molecular level because of the massive number of nuclear genes potentially involved in intramitochondrial protein synthesis, with many not yet linked to human disease. To determine the molecular basis of multiple respiratory chain complex deficiencies. We studied 53 patients referred to 2 national centers in the United Kingdom and Germany between 2005 and 2012. All had biochemical evidence of multiple respiratory chain complex defects but no primary pathogenic mitochondrial DNA mutation. Whole-exome sequencing was performed using 62-Mb exome enrichment, followed by variant prioritization using bioinformatic prediction tools, variant validation by Sanger sequencing, and segregation of the variant with the disease phenotype in the family. Presumptive causal variants were identified in 28 patients (53%; 95% CI, 39%-67%) and possible causal variants were identified in 4 (8%; 95% CI, 2%-18%). Together these accounted for 32 patients (60% 95% CI, 46%-74%) and involved 18 different genes. These included recurrent mutations in RMND1, AARS2, and MTO1, each on a haplotype background consistent with a shared founder allele, and potential novel mutations in 4 possible mitochondrial disease genes (VARS2, GARS, FLAD1, and PTCD1). Distinguishing clinical features included deafness and renal involvement associated with RMND1 and cardiomyopathy with AARS2 and MTO1. However, atypical clinical features were present in some patients, including normal liver function and Leigh syndrome (subacute necrotizing encephalomyelopathy) seen in association with TRMU mutations and no cardiomyopathy with founder SCO2 mutations. It was not possible to confidently identify the underlying genetic basis in 21 patients (40%; 95% CI, 26%-54%). Exome sequencing enhances the ability to identify potential nuclear gene mutations in patients with biochemically defined defects affecting multiple mitochondrial respiratory chain complexes. Additional study is required in independent patient populations to determine the utility of this approach in comparison with traditional diagnostic methods.
Treur, Jorien L; Gibson, Mark; Taylor, Amy E; Rogers, Peter J; Munafò, Marcus R
2018-04-22
Observationally, higher caffeine consumption is associated with poorer sleep and insomnia. We investigated whether these associations are a result of shared genetic risk factors and/or (possibly bidirectional) causal effects. Summary-level data were available from genome-wide association studies on caffeine intake (n = 91 462), plasma caffeine and caffeine metabolic rate (n = 9876), sleep duration and chronotype (being a "morning" versus an "evening" person) (n = 128 266), and insomnia complaints (n = 113 006). First, genetic correlations were calculated, reflecting the extent to which genetic variants influencing caffeine consumption and those influencing sleep overlap. Next, causal effects were estimated with bidirectional, two-sample Mendelian randomization. This approach utilizes the genetic variants most robustly associated with an exposure variable as an "instrument" to test causal effects. Estimates from individual variants were combined using inverse-variance weighted meta-analysis, weighted median regression and MR-Egger regression. We found no clear evidence for a genetic correlation between caffeine intake and sleep duration (rg = 0.000, p = .998), chronotype (rg = 0.086, p = .192) or insomnia complaints (rg = -0.034, p = .700). For plasma caffeine and caffeine metabolic rate, genetic correlations could not be calculated because of the small sample size. Mendelian randomization did not support causal effects of caffeine intake on sleep, or vice versa. There was weak evidence that higher plasma caffeine levels causally decrease the odds of being a morning person. Although caffeine may acutely affect sleep when taken shortly before bedtime, our findings suggest that a sustained pattern of high caffeine consumption is more likely to be associated with poorer sleep through shared environmental factors. Future research should identify such environments, which could aid the development of interventions to improve sleep. © 2018 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.
Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R
2016-12-01
: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. : Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.
Genetic architecture for human aggression: A study of gene-phenotype relationship in OMIM.
Zhang-James, Yanli; Faraone, Stephen V
2016-07-01
Genetic studies of human aggression have mainly focused on known candidate genes and pathways regulating serotonin and dopamine signaling and hormonal functions. These studies have taught us much about the genetics of human aggression, but no genetic locus has yet achieved genome-significance. We here present a review based on a paradoxical hypothesis that studies of rare, functional genetic variations can lead to a better understanding of the molecular mechanisms underlying complex multifactorial disorders such as aggression. We examined all aggression phenotypes catalogued in Online Mendelian Inheritance in Man (OMIM), an Online Catalog of Human Genes and Genetic Disorders. We identified 95 human disorders that have documented aggressive symptoms in at least one individual with a well-defined genetic variant. Altogether, we retrieved 86 causal genes. Although most of these genes had not been implicated in human aggression by previous studies, the most significantly enriched canonical pathways had been previously implicated in aggression (e.g., serotonin and dopamine signaling). Our findings provide strong evidence to support the causal role of these pathways in the pathogenesis of aggression. In addition, the novel genes and pathways we identified suggest additional mechanisms underlying the origins of human aggression. Genome-wide association studies with very large samples will be needed to determine if common variants in these genes are risk factors for aggression. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
Trans-ethnic meta-analysis of genome-wide association studies for Hirschsprung disease.
Tang, Clara Sze-Man; Gui, Hongsheng; Kapoor, Ashish; Kim, Jeong-Hyun; Luzón-Toro, Berta; Pelet, Anna; Burzynski, Grzegorz; Lantieri, Francesca; So, Man-Ting; Berrios, Courtney; Shin, Hyoung Doo; Fernández, Raquel M; Le, Thuy-Linh; Verheij, Joke B G M; Matera, Ivana; Cherny, Stacey S; Nandakumar, Priyanka; Cheong, Hyun Sub; Antiñolo, Guillermo; Amiel, Jeanne; Seo, Jeong-Meen; Kim, Dae-Yeon; Oh, Jung-Tak; Lyonnet, Stanislas; Borrego, Salud; Ceccherini, Isabella; Hofstra, Robert M W; Chakravarti, Aravinda; Kim, Hyun-Young; Sham, Pak Chung; Tam, Paul K H; Garcia-Barceló, Maria-Mercè
2016-12-01
Hirschsprung disease (HSCR) is the most common cause of neonatal intestinal obstruction. It is characterized by the absence of ganglia in the nerve plexuses of the lower gastrointestinal tract. So far, three common disease-susceptibility variants at the RET, SEMA3 and NRG1 loci have been detected through genome-wide association studies (GWAS) in Europeans and Asians to understand its genetic etiologies. Here we present a trans-ethnic meta-analysis of 507 HSCR cases and 1191 controls, combining all published GWAS results on HSCR to fine-map these loci and narrow down the putatively causal variants to 99% credible sets. We also demonstrate that the effects of RET and NRG1 are universal across European and Asian ancestries. In contrast, we detected a European-specific association of a low-frequency variant, rs80227144, in SEMA3 [odds ratio (OR) = 5.2, P = 4.7 × 10-10]. Conditional analyses on the lead SNPs revealed a secondary association signal, corresponding to an Asian-specific, low-frequency missense variant encoding RET p.Asp489Asn (rs9282834, conditional OR = 20.3, conditional P = 4.1 × 10-14). When in trans with the RET intron 1 enhancer risk allele, rs9282834 increases the risk of HSCR from 1.1 to 26.7. Overall, our study provides further insights into the genetic architecture of HSCR and has profound implications for future study designs. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Marsh, Sharon; Hu, Junbo; Feng, Wenke
2016-01-01
Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, and it comprises a spectrum of hepatic abnormalities from simple hepatic steatosis to steatohepatitis, fibrosis, cirrhosis, and liver cancer. While the pathogenesis of NAFLD remains incompletely understood, a multihit model has been proposed that accommodates causal factors from a variety of sources, including intestinal and adipose proinflammatory stimuli acting on the liver simultaneously. Prior cellular and molecular studies of patient and animal models have characterized several common pathogenic mechanisms of NAFLD, including proinflammation cytokines, lipotoxicity, oxidative stress, and endoplasmic reticulum stress. In recent years, gut microbiota has gained much attention, and dysbiosis is recognized as a crucial factor in NAFLD. Moreover, several genetic variants have been identified through genome-wide association studies, particularly rs738409 (Ile748Met) in PNPLA3 and rs58542926 (Glu167Lys) in TM6SF2, which are critical risk alleles of the disease. Although a high-fat diet and inactive lifestyles are typical risk factors for NAFLD, the interplay between diet, gut microbiota, and genetic background is believed to be more important in the development and progression of NAFLD. This review summarizes the common pathogenic mechanisms, the gut microbiota relevant mechanisms, and the major genetic variants leading to NAFLD and its progression. PMID:27247565
Comparison of statistical tests for association between rare variants and binary traits.
Bacanu, Silviu-Alin; Nelson, Matthew R; Whittaker, John C
2012-01-01
Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.
Chen, Wenan; McDonnell, Shannon K; Thibodeau, Stephen N; Tillmans, Lori S; Schaid, Daniel J
2016-11-01
Functional annotations have been shown to improve both the discovery power and fine-mapping accuracy in genome-wide association studies. However, the optimal strategy to incorporate the large number of existing annotations is still not clear. In this study, we propose a Bayesian framework to incorporate functional annotations in a systematic manner. We compute the maximum a posteriori solution and use cross validation to find the optimal penalty parameters. By extending our previous fine-mapping method CAVIARBF into this framework, we require only summary statistics as input. We also derived an exact calculation of Bayes factors using summary statistics for quantitative traits, which is necessary when a large proportion of trait variance is explained by the variants of interest, such as in fine mapping expression quantitative trait loci (eQTL). We compared the proposed method with PAINTOR using different strategies to combine annotations. Simulation results show that the proposed method achieves the best accuracy in identifying causal variants among the different strategies and methods compared. We also find that for annotations with moderate effects from a large annotation pool, screening annotations individually and then combining the top annotations can produce overly optimistic results. We applied these methods on two real data sets: a meta-analysis result of lipid traits and a cis-eQTL study of normal prostate tissues. For the eQTL data, incorporating annotations significantly increased the number of potential causal variants with high probabilities. Copyright © 2016 by the Genetics Society of America.
USDA-ARS?s Scientific Manuscript database
Fine-mapping of causal variants is becoming feasible for complex traits in livestock GWAS, as an increasing number of animals are sequenced. Imputation has been routinely applied to ascertain sequence variants in large genotyped populations based on small reference populations of sequenced animals. ...
USDA-ARS?s Scientific Manuscript database
Major whole genome sequencing projects promise to identify rare and causal variants within livestock species; however, the efficient selection of animals for sequencing remains a major problem within these surveys. The goal of this project was to develop a library of high accuracy genetic variants f...
USDA-ARS?s Scientific Manuscript database
Imputation has been routinely applied to ascertain sequence variants in large genotyped populations based on reference populations of sequenced animals. With the implementation of the 1000 Bull Genomes Project and increasing numbers of animals sequenced, fine-mapping of causal variants is becoming f...
Pausch, Hubert; Wurmser, Christine; Reinhardt, Friedrich; Emmerling, Reiner; Fries, Ruedi
2015-06-01
Most association studies for pinpointing trait-associated variants are performed within breed. The availability of sequence data from key ancestors of several cattle breeds now enables immediate assessment of the frequency of trait-associated variants in populations different from the mapping population and their imputation into large validation populations. The objective of this study was to validate the effects of 4 putatively causative variants on milk production traits, male fertility, and stature in German Fleckvieh and Holstein-Friesian animals using targeted sequence imputation. We used whole-genome sequence data of 456 animals to impute 4 missense mutations in DGAT1, GHR, PRLR, and PROP1 into 10,363 Fleckvieh and 8,812 Holstein animals. The accuracy of the imputed genotypes exceeded 95% for all variants. Association testing with imputed variants revealed consistent antagonistic effects of the DGAT1 p.A232K and GHR p.F279Y variants on milk yield and protein and fat contents, respectively, in both breeds. The allele frequency of both polymorphisms has changed considerably in the past 20 yr, indicating that they were targets of recent selection for milk production traits. The PRLR p.S18N variant was associated with yield traits in Fleckvieh but not in Holstein, suggesting that it may be in linkage disequilibrium with a mutation affecting yield traits rather than being causal. The reported effects of the PROP1 p.H173R variant on milk production, male fertility, and stature could not be confirmed. Our results demonstrate that population-wide imputation of candidate causal variants from sequence data is feasible, enabling their rapid validation in large independent populations. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
The salience network causally influences default mode network activity during moral reasoning
Wilson, Stephen M.; D’Esposito, Mark; Kayser, Andrew S.; Grossman, Scott N.; Poorzand, Pardis; Seeley, William W.; Miller, Bruce L.; Rankin, Katherine P.
2013-01-01
Large-scale brain networks are integral to the coordination of human behaviour, and their anatomy provides insights into the clinical presentation and progression of neurodegenerative illnesses such as Alzheimer’s disease, which targets the default mode network, and behavioural variant frontotemporal dementia, which targets a more anterior salience network. Although the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, patients with Alzheimer’s disease give normal responses to these dilemmas whereas patients with behavioural variant frontotemporal dementia give abnormal responses to these dilemmas. We hypothesized that this apparent discrepancy between activation- and patient-based studies of moral reasoning might reflect a modulatory role for the salience network in regulating default mode network activation. Using functional magnetic resonance imaging to characterize network activity of patients with behavioural variant frontotemporal dementia and healthy control subjects, we present four converging lines of evidence supporting a causal influence from the salience network to the default mode network during moral reasoning. First, as previously reported, the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, but patients with behavioural variant frontotemporal dementia producing atrophy in the salience network give abnormally utilitarian responses to these dilemmas. Second, patients with behavioural variant frontotemporal dementia have reduced recruitment of the default mode network compared with healthy control subjects when deliberating about these dilemmas. Third, a Granger causality analysis of functional neuroimaging data from healthy control subjects demonstrates directed functional connectivity from nodes of the salience network to nodes of the default mode network during moral reasoning. Fourth, this Granger causal influence is diminished in patients with behavioural variant frontotemporal dementia. These findings are consistent with a broader model in which the salience network modulates the activity of other large-scale networks, and suggest a revision to a previously proposed ‘dual-process’ account of moral reasoning. These findings also characterize network interactions underlying abnormal moral reasoning in frontotemporal dementia, which may serve as a model for the aberrant judgement and interpersonal behaviour observed in this disease and in other disorders of social function. More broadly, these findings link recent work on the dynamic interrelationships between large-scale brain networks to observable impairments in dementia syndromes, which may shed light on how diseases that target one network also alter the function of interrelated networks. PMID:23576128
Association of Rare and Common Variation in the Lipoprotein Lipase Gene with Coronary Artery Disease
Khera, Amit V.; Won, Hong-Hee; Peloso, Gina M.; O’Dushlaine, Colm; Liu, Dajiang; Stitziel, Nathan O.; Natarajan, Pradeep; Nomura, Akihiro; Emdin, Connor A.; Gupta, Namrata; Borecki, Ingrid B.; Asselta, Rosanna; Duga, Stefano; Merlini, Piera Angelica; Correa, Adolfo; Kessler, Thorsten; Wilson, James G.; Bown, Matthew J.; Hall, Alistair S.; Braund, Peter S.; Carey, David J.; Murray, Michael F.; Kirchner, H. Lester; Leader, Joseph B.; Lavage, Daniel R.; Manus, J. Neil; Hartzel, Dustin N.; Samani, Nilesh J.; Schunkert, Heribert; Marrugat, Jaume; Elosua, Roberto; McPherson, Ruth; Farrall, Martin; Watkins, Hugh; Lander, Eric S.; Rader, Daniel J.; Danesh, John; Ardissino, Diego; Gabriel, Stacey; Willer, Cristen; Abecasis, Gonçalo R.; Saleheen, Danish; Dewey, Frederick E.; Kathiresan, Sekar
2017-01-01
Importance The activity of lipoprotein lipase (LPL) is the rate-determining step in clearing triglyceride-rich lipoproteins from the circulation. Mutations that damage the LPL gene lead to lifelong deficiency in enzymatic activity and can provide insight into the relationship of LPL to human disease. Objective Determine if rare and/or common variants in the LPL gene are associated with early-onset coronary artery disease (CAD). Design, Setting, and Participants Cross-sectional study. The LPL gene was sequenced in 10 CAD case-control cohorts of the multinational Myocardial Infarction Genetics Consortium and a nested CAD case-control cohort of the Geisinger Health System DiscovEHR cohort between 2010 and 2015. Common variants were genotyped in up to 305,699 individuals of the Global Lipids Genetics Consortium and up to 120,600 individuals of the CARDIoGRAM Exome Consortium between 2012 and 2014. Study-specific estimates were pooled via meta-analysis. Exposure Rare damaging mutations in LPL included loss-of-function variants and missense variants annotated as pathogenic in a human genetics database or predicted to be damaging by computer prediction algorithms trained to identify mutations that impair protein function. Common variants in the LPL gene region included those independently associated with circulating triglyceride levels. Main Outcomes and Measures Circulating lipid levels and CAD. Results Among 46,891 individuals with LPL gene sequencing data available, mean age was 50 years (SD 12.6) and 51% were female. 188 participants (0.40%; 95%CI 0.35–0.46) carried a damaging mutation in the LPL gene – 105 of 32,646 control participants (0.32%) and 83 of 14,245 (0.58%) early-onset CAD cases. Compared to 46,703 non-carriers, the 188 heterozygous carriers of a LPL damaging mutation displayed higher plasma triglycerides (Beta coefficient= +19.6 mg/dL; 95%CI 4.6–34.6) and higher odds of CAD (odds ratio 1.84; 95%CI 1.35–2.51; P<0.001). An analysis of 6 common LPL variants noted an odds ratio for CAD of 1.51 (95%CI 1.39–1.64; P=1.1×10−22) per standard deviation increase in triglycerides. Conclusions and Relevance The presence of rare damaging mutations in the LPL gene was significantly associated with higher triglyceride levels and presence of CAD. However, further research is needed to assess causal mechanisms by which heterozygous LPL deficiency could lead to CAD. PMID:28267856
Gottlieb, Michael M; Arenillas, David J; Maithripala, Savanie; Maurer, Zachary D; Tarailo Graovac, Maja; Armstrong, Linlea; Patel, Millan; van Karnebeek, Clara; Wasserman, Wyeth W
2015-04-01
Advances in next-generation sequencing (NGS) technologies have helped reveal causal variants for genetic diseases. In order to establish causality, it is often necessary to compare genomes of unrelated individuals with similar disease phenotypes to identify common disrupted genes. When working with cases of rare genetic disorders, finding similar individuals can be extremely difficult. We introduce a web tool, GeneYenta, which facilitates the matchmaking process, allowing clinicians to coordinate detailed comparisons for phenotypically similar cases. Importantly, the system is focused on phenotype annotation, with explicit limitations on highly confidential data that create barriers to participation. The procedure for matching of patient phenotypes, inspired by online dating services, uses an ontology-based semantic case matching algorithm with attribute weighting. We evaluate the capacity of the system using a curated reference data set and 19 clinician entered cases comparing four matching algorithms. We find that the inclusion of clinician weights can augment phenotype matching. © 2015 WILEY PERIODICALS, INC.
Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, Amit V.; Kathiresan, Sekar
2018-01-01
Coronary artery disease is the leading global cause of mortality. Long recognized to be heritable, recent advances have started to unravel the genetic architecture of the disease. Common variant association studies have linked about 60 genetic loci to coronary risk. Large-scale gene sequencing efforts and functional studies have facilitated a better understanding of causal risk factors, elucidated underlying biology and informed the development of new therapeutics. Moving forward, genetic testing could enable precision medicine approaches, by identifying subgroups of patients at increased risk of CAD or those with a specific driving pathophysiology in whom a therapeutic or preventive approach is most useful. PMID:28286336
An Evolutionary Perspective on Epistasis and the Missing Heritability
Hemani, Gibran; Knott, Sara; Haley, Chris
2013-01-01
The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the “missing heritability” arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly. PMID:23509438
Burgess, Stephen; Zuber, Verena; Valdes-Marquez, Elsa; Sun, Benjamin B; Hopewell, Jemma C
2017-12-01
Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be used to assess this causal relationship. However, using too many genetic variants in the analysis can lead to spurious estimates and inflated Type 1 error rates. But if only a few genetic variants are used, then the majority of the data is ignored and estimates are highly sensitive to the particular choice of variants. We propose an approach based on summarized data only (genetic association and correlation estimates) that uses principal components analysis to form instruments. This approach has desirable theoretical properties: it takes the totality of data into account and does not suffer from numerical instabilities. It also has good properties in simulation studies: it is not particularly sensitive to varying the genetic variants included in the analysis or the genetic correlation matrix, and it does not have greatly inflated Type 1 error rates. Overall, the method gives estimates that are less precise than those from variable selection approaches (such as using a conditional analysis or pruning approach to select variants), but are more robust to seemingly arbitrary choices in the variable selection step. Methods are illustrated by an example using genetic associations with testosterone for 320 genetic variants to assess the effect of sex hormone related pathways on coronary artery disease risk, in which variable selection approaches give inconsistent inferences. © 2017 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc.
Lu, Yingchang; Justice, Anne E.; Mudgal, Poorva; Liu, Ching-Ti; Young, Kristin; Feitosa, Mary F.; Rand, Kristin; Dimitrov, Latchezar; Duan, Qing; Guo, Xiuqing; Lange, Leslie A.; Nalls, Michael A.; Okut, Hayrettin; Tayo, Bamidele O.; Vedantam, Sailaja; Bradfield, Jonathan P.; Chen, Guanjie; Chesi, Alessandra; Irvin, Marguerite R.; Padhukasahasram, Badri; Zheng, Wei; Allison, Matthew A.; Ambrosone, Christine B.; Bandera, Elisa V.; Berndt, Sonja I.; Blot, William J.; Bottinger, Erwin P.; Carpten, John; Chanock, Stephen J.; Chen, Yii-Der Ida; Conti, David V.; Cooper, Richard S.; Fornage, Myriam; Freedman, Barry I.; Garcia, Melissa; Goodman, Phyllis J.; Hsu, Yu-Han H.; Hu, Jennifer; Huff, Chad D.; Ingles, Sue A.; John, Esther M.; Kittles, Rick; Klein, Eric; Li, Jin; McKnight, Barbara; Nayak, Uma; Nemesure, Barbara; Olshan, Andrew; Salako, Babatunde; Sanderson, Maureen; Shao, Yaming; Siscovick, David S.; Stanford, Janet L.; Strom, Sara S.; Witte, John S.; Yao, Jie; Zhu, Xiaofeng; Ziegler, Regina G.; Zonderman, Alan B.; Ambs, Stefan; Cushman, Mary; Faul, Jessica D.; Hakonarson, Hakon; Levin, Albert M.; Nathanson, Katherine L.; Weir, David R.; Zhi, Degui; Arnett, Donna K.; Kardia, Sharon L. R.; Oloapde, Olufunmilayo I.; Rao, D. C.; Williams, L. Keoki; Becker, Diane M.; Borecki, Ingrid B.; Evans, Michele K.; Harris, Tamara B.; Hirschhorn, Joel N.; Psaty, Bruce M.; Wilson, James G.; Bowden, Donald W.; Cupples, L. Adrienne; Haiman, Christopher A.; Loos, Ruth J. F.; North, Kari E.
2017-01-01
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations. PMID:28430825
van Heemst, Jurgen; Huizinga, Tom J W; van der Woude, Diane; Toes, René E M
2015-05-01
To provide an update on and the context of the recent findings obtained with novel statistical methods on the association of the human leukocyte antigen (HLA) locus with rheumatic diseases. Novel single nucleotide polymorphism fine-mapping data obtained for the HLA locus have indicated the strongest association with amino acid positions 11 and 13 of HLA-DRB1 molecule for several rheumatic diseases. On the basis of these data, a dominant role for position 11/13 in driving the association with these diseases is proposed and the identification of causal variants in the HLA region in relation to disease susceptibility implicated. The HLA class II locus is the most important risk factor for several rheumatic diseases. Recently, new statistical approaches have identified previously unrecognized amino acid positions in the HLA-DR molecule that associate with anticitrullinated protein antibody-negative and anticitrullinated protein antibody-positive rheumatoid arthritis. Likewise, similar findings have been made for other rheumatic conditions such as giant-cell arteritis and systemic lupus erythematosus. Interestingly, all these studies point toward an association with the same amino acid positions: amino acid positions 11 and 13 of the HLA-DR β chain. As both these positions influence peptide binding by HLA-DR and have been implicated in antigen presentation, the novel fine-mapping approach is proposed to map causal variants in the HLA region relevant to rheumatoid arthritis and several rheumatic diseases. If these interpretations are correct, they would direct the biological research aiming to address the explanation for the HLA-disease association. Here, we provide an overview of the recent findings and evidence from literature that, although relevant new insights have been obtained on HLA-disease associations, the interpretation of the biological role of these amino acids as causal variants explaining that such associations should be taken with caution.
Utilizing population controls in rare-variant case-parent association tests.
Jiang, Yu; Satten, Glen A; Han, Yujun; Epstein, Michael P; Heinzen, Erin L; Goldstein, David B; Allen, Andrew S
2014-06-05
There is great interest in detecting associations between human traits and rare genetic variation. To address the low power implicit in single-locus tests of rare genetic variants, many rare-variant association approaches attempt to accumulate information across a gene, often by taking linear combinations of single-locus contributions to a statistic. Using the right linear combination is key-an optimal test will up-weight true causal variants, down-weight neutral variants, and correctly assign the direction of effect for causal variants. Here, we propose a procedure that exploits data from population controls to estimate the linear combination to be used in an case-parent trio rare-variant association test. Specifically, we estimate the linear combination by comparing population control allele frequencies with allele frequencies in the parents of affected offspring. These estimates are then used to construct a rare-variant transmission disequilibrium test (rvTDT) in the case-parent data. Because the rvTDT is conditional on the parents' data, using parental data in estimating the linear combination does not affect the validity or asymptotic distribution of the rvTDT. By using simulation, we show that our new population-control-based rvTDT can dramatically improve power over rvTDTs that do not use population control information across a wide variety of genetic architectures. It also remains valid under population stratification. We apply the approach to a cohort of epileptic encephalopathy (EE) trios and find that dominant (or additive) inherited rare variants are unlikely to play a substantial role within EE genes previously identified through de novo mutation studies. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
El Malti, Rajae; Liu, Hui; Doray, Bérénice; Thauvin, Christel; Maltret, Alice; Dauphin, Claire; Gonçalves-Rocha, Miguel; Teboul, Michel; Blanchet, Patricia; Roume, Joëlle; Gronier, Céline; Ducreux, Corinne; Veyrier, Magali; Marçon, François; Acar, Philippe; Lusson, Jean-René; Levy, Marilyne; Beyler, Constance; Vigneron, Jacqueline; Cordier-Alex, Marie-Pierre; Heitz, François; Sanlaville, Damien; Bonnet, Damien; Bouvagnet, Patrice
2016-01-01
The etiology of congenital heart defect (CHD) combines environmental and genetic factors. So far, there were studies reporting on the screening of a single gene on unselected CHD or on familial cases selected for specific CHD types. Our goal was to systematically screen a proband of familial cases of CHD on a set of genetic tests to evaluate the prevalence of disease-causing variant identification. A systematic screening of GATA4, NKX2-5, ZIC3 and Multiplex ligation-dependent probe amplification (MLPA) P311 Kit was setup on the proband of 154 families with at least two cases of non-syndromic CHD. Additionally, ELN screening was performed on families with supravalvular arterial stenosis. Twenty-two variants were found, but segregation analysis confirmed unambiguously the causality of 16 variants: GATA4 (1 ×), NKX2-5 (6 ×), ZIC3 (3 ×), MLPA (2 ×) and ELN (4 ×). Therefore, this approach was able to identify the causal variant in 10.4% of familial CHD cases. This study demonstrated the existence of a de novo variant even in familial CHD cases and the impact of CHD variants on adult cardiac condition even in the absence of CHD. This study showed that the systematic screening of genetic factors is useful in familial CHD cases with up to 10.4% elucidated cases. When successful, it drastically improved genetic counseling by discovering unaffected variant carriers who are at risk of transmitting their variant and are also exposed to develop cardiac complications during adulthood thus prompting long-term cardiac follow-up. This study provides an important baseline at dawning of the next-generation sequencing era. PMID:26014430
Causal Modeling the Delayed-Choice Experiment
NASA Astrophysics Data System (ADS)
Chaves, Rafael; Lemos, Gabriela Barreto; Pienaar, Jacques
2018-05-01
Wave-particle duality has become one of the flagships of quantum mechanics. This counterintuitive concept is highlighted in a delayed-choice experiment, where the experimental setup that reveals either the particle or wave nature of a quantum system is decided after the system has entered the apparatus. Here we consider delayed-choice experiments from the perspective of device-independent causal models and show their equivalence to a prepare-and-measure scenario. Within this framework, we consider Wheeler's original proposal and its variant using a quantum control and show that a simple classical causal model is capable of reproducing the quantum mechanical predictions. Nonetheless, among other results, we show that, in a slight variant of Wheeler's gedanken experiment, a photon in an interferometer can indeed generate statistics incompatible with any nonretrocausal hidden variable model, whose dimensionality is the same as that of the quantum system it is supposed to mimic. Our proposal tolerates arbitrary losses and inefficiencies, making it specially suited to loophole-free experimental implementations.
Brenner, Darren R.; Amos, Christopher I.; Brhane, Yonathan; Timofeeva, Maria N.; Caporaso, Neil; Wang, Yufei; Christiani, David C.; Bickeböller, Heike; Yang, Ping; Albanes, Demetrius; Stevens, Victoria L.; Gapstur, Susan; McKay, James; Boffetta, Paolo; Zaridze, David; Szeszenia-Dabrowska, Neonilia; Lissowska, Jolanta; Rudnai, Peter; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Krokan, Hans E.; Skorpen, Frank; Gabrielsen, Maiken E.; Vatten, Lars; Njølstad, Inger; Chen, Chu; Goodman, Gary; Lathrop, Mark; Vooder, Tõnu; Välk, Kristjan; Nelis, Mari; Metspalu, Andres; Broderick, Peter; Eisen, Timothy; Wu, Xifeng; Zhang, Di; Chen, Wei; Spitz, Margaret R.; Wei, Yongyue; Su, Li; Xie, Dong; She, Jun; Matsuo, Keitaro; Matsuda, Fumihiko; Ito, Hidemi; Risch, Angela; Heinrich, Joachim; Rosenberger, Albert; Muley, Thomas; Dienemann, Hendrik; Field, John K.; Raji, Olaide; Chen, Ying; Gosney, John; Liloglou, Triantafillos; Davies, Michael P.A.; Marcus, Michael; McLaughlin, John; Orlow, Irene; Han, Younghun; Li, Yafang; Zong, Xuchen; Johansson, Mattias; Liu, Geoffrey; Tworoger, Shelley S.; Le Marchand, Loic; Henderson, Brian E.; Wilkens, Lynne R.; Dai, Juncheng; Shen, Hongbing; Houlston, Richard S.; Landi, Maria T.; Brennan, Paul; Hung, Rayjean J.
2015-01-01
Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10−8) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10−7) and MTMR2 at 11q21 (rs10501831, P = 3.1×10−6) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10−7) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10−4 for KCNIP4, represented by rs9799795) and AC (P = 2.16×10−4 for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range. PMID:26363033
Brenner, Darren R; Amos, Christopher I; Brhane, Yonathan; Timofeeva, Maria N; Caporaso, Neil; Wang, Yufei; Christiani, David C; Bickeböller, Heike; Yang, Ping; Albanes, Demetrius; Stevens, Victoria L; Gapstur, Susan; McKay, James; Boffetta, Paolo; Zaridze, David; Szeszenia-Dabrowska, Neonilia; Lissowska, Jolanta; Rudnai, Peter; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Krokan, Hans E; Skorpen, Frank; Gabrielsen, Maiken E; Vatten, Lars; Njølstad, Inger; Chen, Chu; Goodman, Gary; Lathrop, Mark; Vooder, Tõnu; Välk, Kristjan; Nelis, Mari; Metspalu, Andres; Broderick, Peter; Eisen, Timothy; Wu, Xifeng; Zhang, Di; Chen, Wei; Spitz, Margaret R; Wei, Yongyue; Su, Li; Xie, Dong; She, Jun; Matsuo, Keitaro; Matsuda, Fumihiko; Ito, Hidemi; Risch, Angela; Heinrich, Joachim; Rosenberger, Albert; Muley, Thomas; Dienemann, Hendrik; Field, John K; Raji, Olaide; Chen, Ying; Gosney, John; Liloglou, Triantafillos; Davies, Michael P A; Marcus, Michael; McLaughlin, John; Orlow, Irene; Han, Younghun; Li, Yafang; Zong, Xuchen; Johansson, Mattias; Liu, Geoffrey; Tworoger, Shelley S; Le Marchand, Loic; Henderson, Brian E; Wilkens, Lynne R; Dai, Juncheng; Shen, Hongbing; Houlston, Richard S; Landi, Maria T; Brennan, Paul; Hung, Rayjean J
2015-11-01
Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence.
Clark, Shaunna L; McClay, Joseph L; Adkins, Daniel E; Kumar, Gaurav; Aberg, Karolina A; Nerella, Srilaxmi; Xie, Linying; Collins, Ann L; Crowley, James J; Quackenbush, Corey R; Hilliard, Christopher E; Shabalin, Andrey A; Vrieze, Scott I; Peterson, Roseann E; Copeland, William E; Silberg, Judy L; McGue, Matt; Maes, Hermine; Iacono, William G; Sullivan, Patrick F; Costello, Elizabeth J; van den Oord, Edwin J
2017-04-01
Previous genomewide association studies (GWASs) have identified a number of putative risk loci for alcohol dependence (AD). However, only a few loci have replicated and these replicated variants only explain a small proportion of AD risk. Using an innovative approach, the goal of this study was to generate hypotheses about potentially causal variants for AD that can be explored further through functional studies. We employed targeted capture of 71 candidate loci and flanking regions followed by next-generation deep sequencing (mean coverage 78X) in 806 European Americans. Regions included in our targeted capture library were genes identified through published GWAS of alcohol, all human alcohol and aldehyde dehydrogenases, reward system genes including dopaminergic and opioid receptors, prioritized candidate genes based on previous associations, and genes involved in the absorption, distribution, metabolism, and excretion of drugs. We performed single-locus tests to determine if any single variant was associated with AD symptom count. Sets of variants that overlapped with biologically meaningful annotations were tested for association in aggregate. No single, common variant was significantly associated with AD in our study. We did, however, find evidence for association with several variant sets. Two variant sets were significant at the q-value <0.10 level: a genic enhancer for ADHFE1 (p = 1.47 × 10 -5 ; q = 0.019), an alcohol dehydrogenase, and ADORA1 (p = 5.29 × 10 -5 ; q = 0.035), an adenosine receptor that belongs to a G-protein-coupled receptor gene family. To our knowledge, this is the first sequencing study of AD to examine variants in entire genes, including flanking and regulatory regions. We found that in addition to protein coding variant sets, regulatory variant sets may play a role in AD. From these findings, we have generated initial functional hypotheses about how these sets may influence AD. Copyright © 2017 by the Research Society on Alcoholism.
Using volcano plots and regularized-chi statistics in genetic association studies.
Li, Wentian; Freudenberg, Jan; Suh, Young Ju; Yang, Yaning
2014-02-01
Labor intensive experiments are typically required to identify the causal disease variants from a list of disease associated variants in the genome. For designing such experiments, candidate variants are ranked by their strength of genetic association with the disease. However, the two commonly used measures of genetic association, the odds-ratio (OR) and p-value may rank variants in different order. To integrate these two measures into a single analysis, here we transfer the volcano plot methodology from gene expression analysis to genetic association studies. In its original setting, volcano plots are scatter plots of fold-change and t-test statistic (or -log of the p-value), with the latter being more sensitive to sample size. In genetic association studies, the OR and Pearson's chi-square statistic (or equivalently its square root, chi; or the standardized log(OR)) can be analogously used in a volcano plot, allowing for their visual inspection. Moreover, the geometric interpretation of these plots leads to an intuitive method for filtering results by a combination of both OR and chi-square statistic, which we term "regularized-chi". This method selects associated markers by a smooth curve in the volcano plot instead of the right-angled lines which corresponds to independent cutoffs for OR and chi-square statistic. The regularized-chi incorporates relatively more signals from variants with lower minor-allele-frequencies than chi-square test statistic. As rare variants tend to have stronger functional effects, regularized-chi is better suited to the task of prioritization of candidate genes. Copyright © 2013 Elsevier Ltd. All rights reserved.
Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J
2017-05-01
Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.
Liu, Dajiang J; Leal, Suzanne M
2012-10-05
Next-generation sequencing has led to many complex-trait rare-variant (RV) association studies. Although single-variant association analysis can be performed, it is grossly underpowered. Therefore, researchers have developed many RV association tests that aggregate multiple variant sites across a genetic region (e.g., gene), and test for the association between the trait and the aggregated genotype. After these aggregate tests detect an association, it is only possible to estimate the average genetic effect for a group of RVs. As a result of the "winner's curse," such an estimate can be biased. Although for common variants one can obtain unbiased estimates of genetic parameters by analyzing a replication sample, for RVs it is desirable to obtain unbiased genetic estimates for the study where the association is identified. This is because there can be substantial heterogeneity of RV sites and frequencies even among closely related populations. In order to obtain an unbiased estimate for aggregated RV analysis, we developed bootstrap-sample-split algorithms to reduce the bias of the winner's curse. The unbiased estimates are greatly important for understanding the population-specific contribution of RVs to the heritability of complex traits. We also demonstrate both theoretically and via simulations that for aggregate RV analysis the genetic variance for a gene or region will always be underestimated, sometimes substantially, because of the presence of noncausal variants or because of the presence of causal variants with effects of different magnitudes or directions. Therefore, even if RVs play a major role in the complex-trait etiologies, a portion of the heritability will remain missing, and the contribution of RVs to the complex-trait etiologies will be underestimated. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Lupus Risk Variant Increases pSTAT1 Binding and Decreases ETS1 Expression
Lu, Xiaoming; Zoller, Erin E.; Weirauch, Matthew T.; Wu, Zhiguo; Namjou, Bahram; Williams, Adrienne H.; Ziegler, Julie T.; Comeau, Mary E.; Marion, Miranda C.; Glenn, Stuart B.; Adler, Adam; Shen, Nan; Nath, Swapan K.; Stevens, Anne M.; Freedman, Barry I.; Tsao, Betty P.; Jacob, Chaim O.; Kamen, Diane L.; Brown, Elizabeth E.; Gilkeson, Gary S.; Alarcón, Graciela S.; Reveille, John D.; Anaya, Juan-Manuel; James, Judith A.; Sivils, Kathy L.; Criswell, Lindsey A.; Vilá, Luis M.; Alarcón-Riquelme, Marta E.; Petri, Michelle; Scofield, R. Hal; Kimberly, Robert P.; Ramsey-Goldman, Rosalind; Joo, Young Bin; Choi, Jeongim; Bae, Sang-Cheol; Boackle, Susan A.; Graham, Deborah Cunninghame; Vyse, Timothy J.; Guthridge, Joel M.; Gaffney, Patrick M.; Langefeld, Carl D.; Kelly, Jennifer A.; Greis, Kenneth D.; Kaufman, Kenneth M.; Harley, John B.; Kottyan, Leah C.
2015-01-01
Genetic variants at chromosomal region 11q23.3, near the gene ETS1, have been associated with systemic lupus erythematosus (SLE), or lupus, in independent cohorts of Asian ancestry. Several recent studies have implicated ETS1 as a critical driver of immune cell function and differentiation, and mice deficient in ETS1 develop an SLE-like autoimmunity. We performed a fine-mapping study of 14,551 subjects from multi-ancestral cohorts by starting with genotyped variants and imputing to all common variants spanning ETS1. By constructing genetic models via frequentist and Bayesian association methods, we identified 16 variants that are statistically likely to be causal. We functionally assessed each of these variants on the basis of their likelihood of affecting transcription factor binding, miRNA binding, or chromatin state. Of the four variants that we experimentally examined, only rs6590330 differentially binds lysate from B cells. Using mass spectrometry, we found more binding of the transcription factor signal transducer and activator of transcription 1 (STAT1) to DNA near the risk allele of rs6590330 than near the non-risk allele. Immunoblot analysis and chromatin immunoprecipitation of pSTAT1 in B cells heterozygous for rs6590330 confirmed that the risk allele increased binding to the active form of STAT1. Analysis with expression quantitative trait loci indicated that the risk allele of rs6590330 is associated with decreased ETS1 expression in Han Chinese, but not other ancestral cohorts. We propose a model in which the risk allele of rs6590330 is associated with decreased ETS1 expression and increases SLE risk by enhancing the binding of pSTAT1. PMID:25865496
A plausibly causal functional lupus-associated risk variant in the STAT1-STAT4 locus.
Patel, Zubin; Lu, Xiaoming; Miller, Daniel; Forney, Carmy R; Lee, Joshua; Lynch, Arthur; Schroeder, Connor; Parks, Lois; Magnusen, Albert F; Chen, Xiaoting; Pujato, Mario; Maddox, Avery; Zoller, Erin E; Namjou, Bahram; Brunner, Hermine I; Henrickson, Michael; Huggins, Jennifer L; Williams, Adrienne H; Ziegler, Julie T; Comeau, Mary E; Marion, Miranda C; Glenn, Stuart B; Adler, Adam; Shen, Nan; Nath, Swapan K; Stevens, Anne M; Freedman, Barry I; Pons-Estel, Bernardo A; Tsao, Betty P; Jacob, Chaim O; Kamen, Diane L; Brown, Elizabeth E; Gilkeson, Gary S; Alarcón, Graciela S; Martin, Javier; Reveille, John D; Anaya, Juan-Manuel; James, Judith A; Sivils, Kathy L; Criswell, Lindsey A; Vilá, Luis M; Petri, Michelle; Scofield, R Hal; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Bang, So-Young; Lee, Hye-Soon; Bae, Sang-Cheol; Boackle, Susan A; Cunninghame Graham, Deborah; Vyse, Timothy J; Merrill, Joan T; Niewold, Timothy B; Ainsworth, Hannah C; Silverman, Earl D; Weisman, Michael H; Wallace, Daniel J; Raj, Prithvi; Guthridge, Joel M; Gaffney, Patrick M; Kelly, Jennifer A; Alarcón-Riquelme, Marta E; Langefeld, Carl D; Wakeland, Edward K; Kaufman, Kenneth M; Weirauch, Matthew T; Harley, John B; Kottyan, Leah C
2018-04-18
Systemic Lupus Erythematosus (SLE or lupus) (OMIM: 152700) is a chronic autoimmune disease with debilitating inflammation that affects multiple organ systems. The STAT1-STAT4 locus is one of the first and most highly-replicated genetic loci associated with lupus risk. We performed a fine-mapping study to identify plausible causal variants within the STAT1-STAT4 locus associated with increased lupus disease risk. Using complementary frequentist and Bayesian approaches in trans-ancestral Discovery and Replication cohorts, we found one variant whose association with lupus risk is supported across ancestries in both the Discovery and Replication cohorts: rs11889341. In B cell lines from patients with lupus and healthy controls, the lupus risk allele of rs11889341 was associated with increased STAT1 expression. We demonstrated that the transcription factor HMGA1, a member of the HMG transcription factor family with an AT-hook DNA-binding domain, has enriched binding to the risk allele compared to the non-risk allele of rs11889341. We identified a genotype-dependent repressive element in the DNA within the intron of STAT4 surrounding rs11889341. Consistent with expression quantitative trait locus (eQTL) analysis, the lupus risk allele of rs11889341 decreased the activity of this putative repressor. Altogether, we present a plausible molecular mechanism for increased lupus risk at the STAT1-STAT4 locus in which the risk allele of rs11889341, the most probable causal variant, leads to elevated STAT1 expression in B cells due to decreased repressor activity mediated by increased binding of HMGA1.
Guo, Michael; Liu, Zun; Willen, Jessie; Shaw, Cameron P; Richard, Daniel; Jagoda, Evelyn; Doxey, Andrew C; Hirschhorn, Joel; Capellini, Terence D
2017-12-05
GWAS have identified hundreds of height-associated loci. However, determining causal mechanisms is challenging, especially since height-relevant tissues (e.g. growth plates) are difficult to study. To uncover mechanisms by which height GWAS variants function, we performed epigenetic profiling of murine femoral growth plates. The profiled open chromatin regions recapitulate known chondrocyte and skeletal biology, are enriched at height GWAS loci, particularly near differentially expressed growth plate genes, and enriched for binding motifs of transcription factors with roles in chondrocyte biology. At specific loci, our analyses identified compelling mechanisms for GWAS variants. For example, at CHSY1 , we identified a candidate causal variant (rs9920291) overlapping an open chromatin region. Reporter assays demonstrated that rs9920291 shows allelic regulatory activity, and CRISPR/Cas9 targeting of human chondrocytes demonstrates that the region regulates CHSY1 expression. Thus, integrating biologically relevant epigenetic information (here, from growth plates) with genetic association results can identify biological mechanisms important for human growth.
Duan, Jubao
2015-02-01
Schizophrenia (SZ) is a devastating mental disorder afflicting 1% of the population. Recent genome-wide association studies (GWASs) of SZ have identified >100 risk loci. However, the causal variants/genes and the causal mechanisms remain largely unknown, which hinders the translation of GWAS findings into disease biology and drug targets. Most risk variants are noncoding, thus likely regulate gene expression. A major mechanism of transcriptional regulation is chromatin remodeling, and open chromatin is a versatile predictor of regulatory sequences. MicroRNA-mediated post-transcriptional regulation plays an important role in SZ pathogenesis. Neurons differentiated from patient-specific induced pluripotent stem cells (iPSCs) provide an experimental model to characterize the genetic perturbation of regulatory variants that are often specific to cell type and/or developmental stage. The emerging genome-editing technology enables the creation of isogenic iPSCs and neurons to efficiently characterize the effects of SZ-associated regulatory variants on SZ-relevant molecular and cellular phenotypes involving dopaminergic, glutamatergic, and GABAergic neurotransmissions. SZ GWAS findings equipped with the emerging functional genomics approaches provide an unprecedented opportunity for understanding new disease biology and identifying novel drug targets.
Genetic Instrumental Variable Studies of Effects of Prenatal Risk Factors
von Hinke Kessler Scholder, Stephanie
2013-01-01
Identifying the effects of maternal risk factors during pregnancy on infant and child health is an area of tremendous research interest. However, of interest to policy makers is unraveling the causal effects of prenatal risk factors, not their associations with child health, which may be confounded by several unobserved factors. In this paper, we evaluate the utility of genetic variants in three genes that have unequivocal evidence of being related to three major risk factors – CHRNA3 for smoking, ADH1B for alcohol use, and FTO for obesity – as instrumental variables for identifying the causal effects of such factors during pregnancy. Using two independent datasets, we find that these variants are overall predictive of the risk factors and are not systematically related to observed confounders, suggesting that they may be useful instruments. We also find some suggestive evidence that genetic effects are stronger during than before pregnancy. We provide an empirical example illustrating the use of these genetic variants as instruments to evaluate the effects of risk factors on birth weight. Finally, we offer suggestions for researchers contemplating the use of these variants as instruments. PMID:23701534
Milne, Roger L; Burwinkel, Barbara; Michailidou, Kyriaki; Arias-Perez, Jose-Ignacio; Zamora, M Pilar; Menéndez-Rodríguez, Primitiva; Hardisson, David; Mendiola, Marta; González-Neira, Anna; Pita, Guillermo; Alonso, M Rosario; Dennis, Joe; Wang, Qin; Bolla, Manjeet K; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk; Ko, Yon-Dschun; Brauch, Hiltrud; Hamann, Ute; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Tchatchou, Sandrine; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Li, Jingmei; Brand, Judith S; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Lambrechts, Diether; Peuteman, Gilian; Christiaens, Marie-Rose; Smeets, Ann; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katazyna; Hartman, Mikael; Hui, Miao; Yen Lim, Wei; Wan Chan, Ching; Marme, Federick; Yang, Rongxi; Bugert, Peter; Lindblom, Annika; Margolin, Sara; García-Closas, Montserrat; Chanock, Stephen J; Lissowska, Jolanta; Figueroa, Jonine D; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Hooning, Maartje J; Kriege, Mieke; van den Ouweland, Ans M W; Koppert, Linetta B; Fletcher, Olivia; Johnson, Nichola; dos-Santos-Silva, Isabel; Peto, Julian; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha J; Long, Jirong; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Schmidt, Marjanka K; Broeks, Annegien; Cornelissen, Sten; Braaf, Linde; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Noh, Dong-Young; Simard, Jacques; Dumont, Martine; Goldberg, Mark S; Labrèche, France; Fasching, Peter A; Hein, Alexander; Ekici, Arif B; Beckmann, Matthias W; Radice, Paolo; Peterlongo, Paolo; Azzollini, Jacopo; Barile, Monica; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Miller, Nicola; Hopper, John L; Schmidt, Daniel F; Makalic, Enes; Southey, Melissa C; Hwang Teo, Soo; Har Yip, Cheng; Sivanandan, Kavitta; Tay, Wan-Ting; Shen, Chen-Yang; Hsiung, Chia-Ni; Yu, Jyh-Cherng; Hou, Ming-Feng; Guénel, Pascal; Truong, Therese; Sanchez, Marie; Mulot, Claire; Blot, William; Cai, Qiuyin; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Bogdanova, Natalia; Dörk, Thilo; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Zhang, Ben; Couch, Fergus J; Toland, Amanda E; Yannoukakos, Drakoulis; Sangrajrang, Suleeporn; McKay, James; Wang, Xianshu; Olson, Janet E; Vachon, Celine; Purrington, Kristen; Severi, Gianluca; Baglietto, Laura; Haiman, Christopher A; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; Czene, Kamila; Eriksson, Mikael; Humphreys, Keith; Darabi, Hatef; Ahmed, Shahana; Shah, Mitul; Pharoah, Paul D P; Hall, Per; Giles, Graham G; Benítez, Javier; Dunning, Alison M; Chenevix-Trench, Georgia; Easton, Douglas F
2014-11-15
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04-1.10, P = 2.9 × 10(-6)], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03-1.07, P = 1.7 × 10(-6)) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07-1.12, P = 5.1 × 10(-17)). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05-1.10, P = 1.0 × 10(-8)); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04-1.07, P = 2.0 × 10(-10)). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act. © The Author 2014. Published by Oxford University Press.
Milne, Roger L.; Burwinkel, Barbara; Michailidou, Kyriaki; Arias-Perez, Jose-Ignacio; Zamora, M. Pilar; Menéndez-Rodríguez, Primitiva; Hardisson, David; Mendiola, Marta; González-Neira, Anna; Pita, Guillermo; Alonso, M. Rosario; Dennis, Joe; Wang, Qin; Bolla, Manjeet K.; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk; Ko, Yon-Dschun; Brauch, Hiltrud; Hamann, Ute; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Tchatchou, Sandrine; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Li, Jingmei; Brand, Judith S.; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Lambrechts, Diether; Peuteman, Gilian; Christiaens, Marie-Rose; Smeets, Ann; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katazyna; Hartman, Mikael; Hui, Miao; Yen Lim, Wei; Wan Chan, Ching; Marme, Federick; Yang, Rongxi; Bugert, Peter; Lindblom, Annika; Margolin, Sara; García-Closas, Montserrat; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Bojesen, Stig E.; Nordestgaard, Børge G.; Flyger, Henrik; Hooning, Maartje J.; Kriege, Mieke; van den Ouweland, Ans M.W.; Koppert, Linetta B.; Fletcher, Olivia; Johnson, Nichola; dos-Santos-Silva, Isabel; Peto, Julian; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha J.; Long, Jirong; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Cox, Angela; Cross, Simon S.; Reed, Malcolm W.R.; Schmidt, Marjanka K.; Broeks, Annegien; Cornelissen, Sten; Braaf, Linde; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Noh, Dong-Young; Simard, Jacques; Dumont, Martine; Goldberg, Mark S.; Labrèche, France; Fasching, Peter A.; Hein, Alexander; Ekici, Arif B.; Beckmann, Matthias W.; Radice, Paolo; Peterlongo, Paolo; Azzollini, Jacopo; Barile, Monica; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Miller, Nicola; Hopper, John L.; Schmidt, Daniel F.; Makalic, Enes; Southey, Melissa C.; Hwang Teo, Soo; Har Yip, Cheng; Sivanandan, Kavitta; Tay, Wan-Ting; Shen, Chen-Yang; Hsiung, Chia-Ni; Yu, Jyh-Cherng; Hou, Ming-Feng; Guénel, Pascal; Truong, Therese; Sanchez, Marie; Mulot, Claire; Blot, William; Cai, Qiuyin; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Wu, Anna H.; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O.; Bogdanova, Natalia; Dörk, Thilo; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Zhang, Ben; Couch, Fergus J.; Toland, Amanda E.; Yannoukakos, Drakoulis; Sangrajrang, Suleeporn; McKay, James; Wang, Xianshu; Olson, Janet E.; Vachon, Celine; Purrington, Kristen; Severi, Gianluca; Baglietto, Laura; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Devilee, Peter; Tollenaar, Robert A.E.M.; Seynaeve, Caroline; Czene, Kamila; Eriksson, Mikael; Humphreys, Keith; Darabi, Hatef; Ahmed, Shahana; Shah, Mitul; Pharoah, Paul D.P.; Hall, Per; Giles, Graham G.; Benítez, Javier; Dunning, Alison M.; Chenevix-Trench, Georgia; Easton, Douglas F.; Berchuck, Andrew; Eeles, Rosalind A.; Olama, Ali Amin Al; Kote-Jarai, Zsofia; Benlloch, Sara; Antoniou, Antonis; McGuffog, Lesley; Offit, Ken; Lee, Andrew; Dicks, Ed; Luccarini, Craig; Tessier, Daniel C.; Bacot, Francois; Vincent, Daniel; LaBoissière, Sylvie; Robidoux, Frederic; Nielsen, Sune F.; Cunningham, Julie M.; Windebank, Sharon A.; Hilker, Christopher A.; Meyer, Jeffrey; Angelakos, Maggie; Maskiell, Judi; van der Schoot, Ellen; Rutgers, Emiel; Verhoef, Senno; Hogervorst, Frans; Boonyawongviroj, Prat; Siriwanarungsan, Pornthep; Schrauder, Michael; Rübner, Matthias; Oeser, Sonja; Landrith, Silke; Williams, Eileen; Ryder-Mills, Elaine; Sargus, Kara; McInerney, Niall; Colleran, Gabrielle; Rowan, Andrew; Jones, Angela; Sohn, Christof; Schneeweiß, Andeas; Bugert, Peter; Álvarez, Núria; Lacey, James; Wang, Sophia; Ma, Huiyan; Lu, Yani; Deapen, Dennis; Pinder, Rich; Lee, Eunjung; Schumacher, Fred; Horn-Ross, Pam; Reynolds, Peggy; Nelson, David; Ziegler, Hartwig; Wolf, Sonja; Hermann, Volker; Lo, Wing-Yee; Justenhoven, Christina; Baisch, Christian; Fischer, Hans-Peter; Brüning, Thomas; Pesch, Beate; Rabstein, Sylvia; Lotz, Anne; Harth, Volker; Heikkinen, Tuomas; Erkkilä, Irja; Aaltonen, Kirsimari; von Smitten, Karl; Antonenkova, Natalia; Hillemanns, Peter; Christiansen, Hans; Myöhänen, Eija; Kemiläinen, Helena; Thorne, Heather; Niedermayr, Eveline; Bowtell, D; Chenevix-Trench, G; deFazio, A; Gertig, D; Green, A; Webb, P; Green, A.; Parsons, P.; Hayward, N.; Webb, P.; Whiteman, D.; Fung, Annie; Yashiki, June; Peuteman, Gilian; Smeets, Dominiek; Brussel, Thomas Van; Corthouts, Kathleen; Obi, Nadia; Heinz, Judith; Behrens, Sabine; Eilber, Ursula; Celik, Muhabbet; Olchers, Til; Manoukian, Siranoush; Peissel, Bernard; Scuvera, Giulietta; Zaffaroni, Daniela; Bonanni, Bernardo; Feroce, Irene; Maniscalco, Angela; Rossi, Alessandra; Bernard, Loris; Tranchant, Martine; Valois, Marie-France; Turgeon, Annie; Heguy, Lea; Sze Yee, Phuah; Kang, Peter; Nee, Kang In; Mariapun, Shivaani; Sook-Yee, Yoon; Lee, Daphne; Ching, Teh Yew; Taib, Nur Aishah Mohd; Otsukka, Meeri; Mononen, Kari; Selander, Teresa; Weerasooriya, Nayana; staff, OFBCR; Krol-Warmerdam, E.; Molenaar, J.; Blom, J.; Brinton, Louise; Szeszenia-Dabrowska, Neonila; Peplonska, Beata; Zatonski, Witold; Chao, Pei; Stagner, Michael; Bos, Petra; Blom, Jannet; Crepin, Ellen; Nieuwlaat, Anja; Heemskerk, Annette; Higham, Sue; Cross, Simon; Cramp, Helen; Connley, Dan; Balasubramanian, Sabapathy; Brock, Ian; Luccarini, Craig; Conroy, Don; Baynes, Caroline; Chua, Kimberley
2014-01-01
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04–1.10, P = 2.9 × 10−6], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03–1.07, P = 1.7 × 10−6) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07–1.12, P = 5.1 × 10−17). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05–1.10, P = 1.0 × 10−8); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04–1.07, P = 2.0 × 10−10). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act. PMID:24943594
Classification of BRCA1 missense variants of unknown clinical significance
Phelan, C; Dapic, V; Tice, B; Favis, R; Kwan, E; Barany, F; Manoukian, S; Radice, P; van der Luijt, R B; van Nesselrooij, B P M; Chenevix-Trench, G; kConFab; Caldes, T; de La Hoya, M; Lindquist, S; Tavtigian, S; Goldgar, D; Borg, A; Narod, S; Monteiro, A
2005-01-01
Background: BRCA1 is a tumour suppressor with pleiotropic actions. Germline mutations in BRCA1 are responsible for a large proportion of breast–ovarian cancer families. Several missense variants have been identified throughout the gene but because of lack of information about their impact on the function of BRCA1, predictive testing is not always informative. Classification of missense variants into deleterious/high risk or neutral/low clinical significance is essential to identify individuals at risk. Objective: To investigate a panel of missense variants. Methods and results: The panel was investigated in a comprehensive framework that included (1) a functional assay based on transcription activation; (2) segregation analysis and a method of using incomplete pedigree data to calculate the odds of causality; (3) a method based on interspecific sequence variation. It was shown that the transcriptional activation assay could be used as a test to characterise mutations in the carboxy-terminus region of BRCA1 encompassing residues 1396–1863. Thirteen missense variants (H1402Y, L1407P, H1421Y, S1512I, M1628T, M1628V, T1685I, G1706A, T1720A, A1752P, G1788V, V1809F, and W1837R) were specifically investigated. Conclusions: While individual classification schemes for BRCA1 alleles still present limitations, a combination of several methods provides a more powerful way of identifying variants that are causally linked to a high risk of breast and ovarian cancer. The framework presented here brings these variants nearer to clinical applicability. PMID:15689452
Kim, Minjoo; Kim, Minkyung; Huang, Limin; Jee, Sun Ha; Lee, Jong Ho
2018-05-18
We tested the hypothesis that the cumulative effects of common genetic variants related to elevated fasting glucose are collectively associated with oxidative stress. Using 25 single nucleotide polymorphisms (SNPs), a weighted genetic risk score (wGRS) was constructed by summing nine risk alleles based on nominal significance and a consistent effect direction in 1,395 controls and 718 patients with impaired fasting glucose (IFG) or newly diagnosed type 2 diabetes. All the participants were divided into the following three groups: low-wGRS, middle-wGRS, and high-wGRS groups. Among the nine SNPs, five SNPs were significantly associated with IFG and type 2 diabetes in this Korean population. wGRS was significantly associated with increased IFG and newly diagnosed type 2 diabetes (p = 6.83 × 10 -14 , odds ratio = 1.839) after adjusting for confounding factors. Among the IFG and type 2 diabetes patients, the fasting serum glucose and HbA 1c levels were significantly higher in the high-wGRS group than in the other groups. The urinary 8-epi-PGF 2α and malondialdehyde concentrations were significantly higher in the high-wGRS group than in the other groups. Moreover, general population-level instrumental variable estimation (using wGRS as an instrument) strengthened the causal effect regarding the largely adverse influence of high levels of fasting serum glucose on markers of oxidative stress in the Korean population. Thus, the combination of common genetic variants with small effects on IFG and newly diagnosed type 2 diabetes are significantly associated with oxidative stress.
Sieradzka, Dominika; Power, Robert A; Freeman, Daniel; Cardno, Alastair G; Dudbridge, Frank; Ronald, Angelica
2015-09-01
Occurrence of psychotic experiences is common amongst adolescents in the general population. Twin studies suggest that a third to a half of variance in adolescent psychotic experiences is explained by genetic influences. Here we test the extent to which common genetic variants account for some of the twin-based heritability. Psychotic experiences were assessed with the Specific Psychotic Experiences Questionnaire in a community sample of 2152 16-year-olds. Self-reported measures of Paranoia, Hallucinations, Cognitive Disorganization, Grandiosity, Anhedonia, and Parent-rated Negative Symptoms were obtained. Estimates of SNP heritability were derived and compared to the twin heritability estimates from the same sample. Three approaches to genome-wide restricted maximum likelihood (GREML) analyses were compared: (1) standard GREML performed on full genome-wide data; (2) GREML stratified by minor allele frequency (MAF); and (3) GREML performed on pruned data. The standard GREML revealed a significant SNP heritability of 20 % for Anhedonia (SE = 0.12; p < 0.046) and an estimate of 19 % for Cognitive Disorganization, which was close to significant (SE = 0.13; p < 0.059). Grandiosity and Paranoia showed modest SNP heritability estimates (17 %; SE = 0.13 and 14 %; SE = 0.13, respectively, both n.s.), and zero estimates were found for Hallucinations and Negative Symptoms. The estimates for Anhedonia, Cognitive Disorganization and Grandiosity accounted for approximately half the previously reported twin heritability. SNP heritability estimates from the MAF-stratified approach were mostly consistent with the standard estimates and offered additional information about the distribution of heritability across the MAF range of the SNPs. In contrast, the estimates derived from the pruned data were for the most part not consistent with the other two approaches. It is likely that the difference seen in the pruned estimates was driven by the loss of tagged causal variants, an issue fundamental to this approach. The current results suggest that common genetic variants play a role in the etiology of some adolescent psychotic experiences, however further research on larger samples is desired and the use of MAF-stratified approach recommended.
Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Alejandro Q; Musolf, Anthony; Matise, Tara C; Finch, Stephen J; Gordon, Derek
2012-01-01
As with any new technology, next-generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to those data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single-variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p value, no matter how many loci. Copyright © 2013 S. Karger AG, Basel.
Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Andrew; Musolf, Anthony; Matise, Tara C.; Finch, Stephen J.; Gordon, Derek
2013-01-01
As with any new technology, next generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model, based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to that data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p-value, no matter how many loci. PMID:23594495
A comprehensive global genotype-phenotype database for rare diseases.
Trujillano, Daniel; Oprea, Gabriela-Elena; Schmitz, Yvonne; Bertoli-Avella, Aida M; Abou Jamra, Rami; Rolfs, Arndt
2017-01-01
The ability to discover genetic variants in a patient runs far ahead of the ability to interpret them. Databases with accurate descriptions of the causal relationship between the variants and the phenotype are valuable since these are critical tools in clinical genetic diagnostics. Here, we introduce a comprehensive and global genotype-phenotype database focusing on rare diseases. This database (CentoMD ® ) is a browser-based tool that enables access to a comprehensive, independently curated system utilizing stringent high-quality criteria and a quickly growing repository of genetic and human phenotype ontology (HPO)-based clinical information. Its main goals are to aid the evaluation of genetic variants, to enhance the validity of the genetic analytical workflow, to increase the quality of genetic diagnoses, and to improve evaluation of treatment options for patients with hereditary diseases. The database software correlates clinical information from consented patients and probands of different geographical backgrounds with a large dataset of genetic variants and, when available, biomarker information. An automated follow-up tool is incorporated that informs all users whenever a variant classification has changed. These unique features fully embedded in a CLIA/CAP-accredited quality management system allow appropriate data quality and enhanced patient safety. More than 100,000 genetically screened individuals are documented in the database, resulting in more than 470 million variant detections. Approximately, 57% of the clinically relevant and uncertain variants in the database are novel. Notably, 3% of the genetic variants identified and previously reported in the literature as being associated with a particular rare disease were reclassified, based on internal evidence, as clinically irrelevant. The database offers a comprehensive summary of the clinical validity and causality of detected gene variants with their associated phenotypes, and is a valuable tool for identifying new disease genes through the correlation of novel genetic variants with specific, well-defined phenotypes.
Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.
Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei
2016-02-01
Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.
Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions
Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei
2015-01-01
Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979
Olson, Heather E; Jean-Marçais, Nolwenn; Yang, Edward; Heron, Delphine; Tatton-Brown, Katrina; van der Zwaag, Paul A; Bijlsma, Emilia K; Krock, Bryan L; Backer, E; Kamsteeg, Erik-Jan; Sinnema, Margje; Reijnders, Margot R F; Bearden, David; Begtrup, Amber; Telegrafi, Aida; Lunsing, Roelineke J; Burglen, Lydie; Lesca, Gaetan; Cho, Megan T; Smith, Lacey A; Sheidley, Beth R; Moufawad El Achkar, Christelle; Pearl, Phillip L; Poduri, Annapurna; Skraban, Cara M; Tarpinian, Jennifer; Nesbitt, Addie I; Fransen van de Putte, Dietje E; Ruivenkamp, Claudia A L; Rump, Patrick; Chatron, Nicolas; Sabatier, Isabelle; De Bellescize, Julitta; Guibaud, Laurent; Sweetser, David A; Waxler, Jessica L; Wierenga, Klaas J; Donadieu, Jean; Narayanan, Vinodh; Ramsey, Keri M; Nava, Caroline; Rivière, Jean-Baptiste; Vitobello, Antonio; Tran Mau-Them, Frédéric; Philippe, Christophe; Bruel, Ange-Line; Duffourd, Yannis; Thomas, Laurel; Lelieveld, Stefan H; Schuurs-Hoeijmakers, Janneke; Brunner, Han G; Keren, Boris; Thevenon, Julien; Faivre, Laurence; Thomas, Gary; Thauvin-Robinet, Christel
2018-05-03
Developmental and epileptic encephalopathies (DEEs) represent a large clinical and genetic heterogeneous group of neurodevelopmental diseases. The identification of pathogenic genetic variants in DEEs remains crucial for deciphering this complex group and for accurately caring for affected individuals (clinical diagnosis, genetic counseling, impacting medical, precision therapy, clinical trials, etc.). Whole-exome sequencing and intensive data sharing identified a recurrent de novo PACS2 heterozygous missense variant in 14 unrelated individuals. Their phenotype was characterized by epilepsy, global developmental delay with or without autism, common cerebellar dysgenesis, and facial dysmorphism. Mixed focal and generalized epilepsy occurred in the neonatal period, controlled with difficulty in the first year, but many improved in early childhood. PACS2 is an important PACS1 paralog and encodes a multifunctional sorting protein involved in nuclear gene expression and pathway traffic regulation. Both proteins harbor cargo(furin)-binding regions (FBRs) that bind cargo proteins, sorting adaptors, and cellular kinase. Compared to the defined PACS1 recurrent variant series, individuals with PACS2 variant have more consistently neonatal/early-infantile-onset epilepsy that can be challenging to control. Cerebellar abnormalities may be similar but PACS2 individuals exhibit a pattern of clear dysgenesis ranging from mild to severe. Functional studies demonstrated that the PACS2 recurrent variant reduces the ability of the predicted autoregulatory domain to modulate the interaction between the PACS2 FBR and client proteins, which may disturb cellular function. These findings support the causality of this recurrent de novo PACS2 heterozygous missense in DEEs with facial dysmorphim and cerebellar dysgenesis. Copyright © 2018 American Society of Human Genetics. All rights reserved.
Milillo, Annamaria; La Carpia, Francesca; Costanzi, Stefano; D'Urbano, Vanessa; Martini, Maurizio; Lanuti, Paola; Vischini, Gisella; Larocca, Luigi M; Marchisio, Marco; Miscia, Sebastiano; Amoroso, Antonio; Gurrieri, Fiorella; Sangiorgi, Eugenio
2015-12-01
IgA nephropathy (IgAN) represents the most common primary glomerulonephritis worldwide with a prevalence of 25-50% among patients with primary glomerulopathies. In ~5-10% of the patients the disease segregates with an autosomal dominant (AD) pattern. Association studies identified loci on chromosomes 1q32, 6p21, 8p23, 17p13, 22q12, whereas classical linkage studies on AD families identified loci on chromosomes 2q36, 4q26-31, 6q22, 17q12-22. We have studied a large Sicilian family where IgAN segregates with an AD transmission. To identify the causal gene, the exomes of two affected and one unaffected individual have been sequenced. From the bioinformatics analysis a p.(Arg119Trp) variant in the SPRY2 gene was identified as the probable disease-causing mutation. Moreover, functional characterization of this variant showed that it is responsible for the inhibition of the MAPK/ERK1/2 pathway. The same effect was observed in two sporadic IgAN patients carriers of wild-type SPRY2, suggesting that downregulation of the MAPK/ERK1/2 pathway represents a common mechanism leading to IgAN.
Buchmann, Nikolaus; Scholz, Markus; Lill, Christina M; Burkhardt, Ralph; Eckardt, Rahel; Norman, Kristina; Loeffler, Markus; Bertram, Lars; Thiery, Joachim; Steinhagen-Thiessen, Elisabeth; Demuth, Ilja
2017-11-01
Inverse relationships have been described between the largely genetically determined levels of serum/plasma lipoprotein(a) [Lp(a)], type 2 diabetes (T2D) and fasting insulin. Here, we aimed to evaluate the nature of these relationships with respect to causality. We tested whether we could replicate the recent negative findings on causality between Lp(a) and T2D by employing the Mendelian randomization (MR) approach using cross-sectional data from three independent cohorts, Berlin Aging Study II (BASE-II; n = 2012), LIFE-Adult (n = 3281) and LIFE-Heart (n = 2816). Next, we explored another frequently discussed hypothesis in this context: Increasing insulin levels during the course of T2D disease development inhibits hepatic Lp(a) synthesis and thereby might explain the inverse Lp(a)-T2D association. We used two fasting insulin-associated variants, rs780094 and rs10195252, as instrumental variables in MR analysis of n = 4937 individuals from BASE-II and LIFE-Adult. We further investigated causality of the association between fasting insulin and Lp(a) by combined MR analysis of 12 additional SNPs in LIFE-Adult. While an Lp(a)-T2D association was observed in the combined analysis (meta-effect of OR [95% CI] = 0.91 [0.87-0.96] per quintile, p = 1.3x10 -4 ), we found no evidence of causality in the Lp(a)-T2D association (p = 0.29, fixed effect model) when using the variant rs10455872 as the instrumental variable in the MR analyses. Likewise, no evidence of a causal effect of insulin on Lp(a) levels was found. While these results await confirmation in larger cohorts, the nature of the inverse Lp(a)-T2D association remains to be elucidated.
Causal Systems Categories: Differences in Novice and Expert Categorization of Causal Phenomena
ERIC Educational Resources Information Center
Rottman, Benjamin M.; Gentner, Dedre; Goldwater, Micah B.
2012-01-01
We investigated the understanding of causal systems categories--categories defined by common causal structure rather than by common domain content--among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative…
[Personal genome research and neurological diseases: overview].
Toda, Tatsushi
2013-03-01
Neurological diseases include those caused by a single defective gene,e.g., Huntington's disease, other polyglutamine diseases, and muscular dystrophies, and those that are mostly sporadic but rarely show Mendelian inheritance in some families, e.g., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and epilepsy. The latter diseases are considered polygenic disorders. Both sporadic and Mendelian cases of these diseases are believed to share some common pathological mechanisms. Since the detection of causal genes for the Mendelian cases, studies have been initiated on disease pathology. SNPs and rare gene variants play important roles in common neurological diseases. From a technological perspective, next-generation sequencers have become widely available and have contributed to the advancement of research based on individual genome sequences (personal genome). This paper presents an overview, as well as a historical context, of the contribution of personal genome research to neurological disease studies.
Gomes, Clarissa P C; Nagata, Tatsuya; de Jesus, Waldir C; Neto, Carlos R Borges; Pappas, Georgios J; Martin, Darren P
2008-01-16
Citrus sudden death (CSD), a disease that rapidly kills orange trees, is an emerging threat to the Brazilian citrus industry. Although the causal agent of CSD has not been definitively determined, based on the disease's distribution and symptomatology it is suspected that the agent may be a new strain of Citrus tristeza virus (CTV). CTV genetic variation was therefore assessed in two Brazilian orange trees displaying CSD symptoms and a third with more conventional CTV symptoms. A total of 286 RNA-dependent-RNA polymerase (RdRp) and 284 heat shock protein 70 homolog (HSP70h) gene fragments were determined for CTV variants infecting the three trees. It was discovered that, despite differences in symptomatology, the trees were all apparently coinfected with similar populations of divergent CTV variants. While mixed CTV infections are common, the genetic distance between the most divergent population members observed (24.1% for RdRp and 11.0% for HSP70h) was far greater than that in previously described mixed infections. Recombinants of five distinct RdRp lineages and three distinct HSP70h lineages were easily detectable but respectively accounted for only 5.9 and 11.9% of the RdRp and HSP70h gene fragments analysed and there was no evidence of an association between particular recombinant mosaics and CSD. Also, comparisons of CTV population structures indicated that the two most similar CTV populations were those of one of the trees with CSD and the tree without CSD. We suggest that if CTV is the causal agent of CSD, it is most likely a subtle feature of population structures within mixed infections and not merely the presence (or absence) of a single CTV variant within these populations that triggers the disease.
'Mendelian randomization': an approach for exploring causal relations in epidemiology.
Gupta, V; Walia, G K; Sachdeva, M P
2017-04-01
To assess the current status of Mendelian randomization (MR) approach in effectively influencing the observational epidemiology for examining causal relationships. Narrative review on studies related to principle, strengths, limitations, and achievements of MR approach. Observational epidemiological studies have repeatedly produced several beneficiary associations which were discarded when tested by standard randomized controlled trials (RCTs). The technique which is more feasible, highly similar to RCTs, and has the potential to establish a causal relationship between modifiable exposures and disease outcomes is known as MR. The technique uses genetic variants related to modifiable traits/exposures as instruments for detecting causal and directional associations with outcomes. In the last decade, the approach of MR has methodologically developed and progressed to a stage of high acceptance among the epidemiologists and is gradually expanding the landscape of causal relationships in non-communicable chronic diseases. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
CRISPR-directed mitotic recombination enables genetic mapping without crosses.
Sadhu, Meru J; Bloom, Joshua S; Day, Laura; Kruglyak, Leonid
2016-05-27
Linkage and association studies have mapped thousands of genomic regions that contribute to phenotypic variation, but narrowing these regions to the underlying causal genes and variants has proven much more challenging. Resolution of genetic mapping is limited by the recombination rate. We developed a method that uses CRISPR (clustered, regularly interspaced, short palindromic repeats) to build mapping panels with targeted recombination events. We tested the method by generating a panel with recombination events spaced along a yeast chromosome arm, mapping trait variation, and then targeting a high density of recombination events to the region of interest. Using this approach, we fine-mapped manganese sensitivity to a single polymorphism in the transporter Pmr1. Targeting recombination events to regions of interest allows us to rapidly and systematically identify causal variants underlying trait differences. Copyright © 2016, American Association for the Advancement of Science.
Genomic Influences on Hyperuricemia and Gout.
Merriman, Tony
2017-08-01
Genome-wide association studies (GWAS) have identified nearly 30 loci associated with urate concentrations that also influence the subsequent risk of gout. The ABCG2 Q141 K variant is highly likely to be causal and results in internalization of ABCG2, which can be rescued by drugs. Three other GWAS loci contain uric acid transporter genes, which are also highly likely to be causal. However identification of causal genes at other urate loci is challenging. Finally, relatively little is known about the genetic control of progression from hyperuricemia to gout. Only 4 small GWAS have been published for gout. Copyright © 2017 Elsevier Inc. All rights reserved.
Asgari, Samira; McLaren, Paul J; Peake, Jane; Wong, Melanie; Wong, Richard; Bartha, Istvan; Francis, Joshua R; Abarca, Katia; Gelderman, Kyra A; Agyeman, Philipp; Aebi, Christoph; Berger, Christoph; Fellay, Jacques; Schlapbach, Luregn J
2016-01-01
One out of three pediatric sepsis deaths in high income countries occur in previously healthy children. Primary immunodeficiencies (PIDs) have been postulated to underlie fulminant sepsis, but this concept remains to be confirmed in clinical practice. Pseudomonas aeruginosa ( P. aeruginosa ) is a common bacterium mostly associated with health care-related infections in immunocompromised individuals. However, in rare cases, it can cause sepsis in previously healthy children. We used exome sequencing and bioinformatic analysis to systematically search for genetic factors underpinning severe P. aeruginosa infection in the pediatric population. We collected blood samples from 11 previously healthy children, with no family history of immunodeficiency, who presented with severe sepsis due to community-acquired P. aeruginosa bacteremia. Genomic DNA was extracted from blood or tissue samples obtained intravitam or postmortem. We obtained high-coverage exome sequencing data and searched for rare loss-of-function variants. After rigorous filtrations, 12 potentially causal variants were identified. Two out of eight (25%) fatal cases were found to carry novel pathogenic variants in PID genes, including BTK and DNMT3B . This study demonstrates that exome sequencing allows to identify rare, deleterious human genetic variants responsible for fulminant sepsis in apparently healthy children. Diagnosing PIDs in such patients is of high relevance to survivors and affected families. We propose that unusually severe and fatal sepsis cases in previously healthy children should be considered for exome/genome sequencing to search for underlying PIDs.
Asgari, Samira; McLaren, Paul J.; Peake, Jane; Wong, Melanie; Wong, Richard; Bartha, Istvan; Francis, Joshua R.; Abarca, Katia; Gelderman, Kyra A.; Agyeman, Philipp; Aebi, Christoph; Berger, Christoph; Fellay, Jacques; Schlapbach, Luregn J.; Posfay-Barbe, Klara
2016-01-01
One out of three pediatric sepsis deaths in high income countries occur in previously healthy children. Primary immunodeficiencies (PIDs) have been postulated to underlie fulminant sepsis, but this concept remains to be confirmed in clinical practice. Pseudomonas aeruginosa (P. aeruginosa) is a common bacterium mostly associated with health care-related infections in immunocompromised individuals. However, in rare cases, it can cause sepsis in previously healthy children. We used exome sequencing and bioinformatic analysis to systematically search for genetic factors underpinning severe P. aeruginosa infection in the pediatric population. We collected blood samples from 11 previously healthy children, with no family history of immunodeficiency, who presented with severe sepsis due to community-acquired P. aeruginosa bacteremia. Genomic DNA was extracted from blood or tissue samples obtained intravitam or postmortem. We obtained high-coverage exome sequencing data and searched for rare loss-of-function variants. After rigorous filtrations, 12 potentially causal variants were identified. Two out of eight (25%) fatal cases were found to carry novel pathogenic variants in PID genes, including BTK and DNMT3B. This study demonstrates that exome sequencing allows to identify rare, deleterious human genetic variants responsible for fulminant sepsis in apparently healthy children. Diagnosing PIDs in such patients is of high relevance to survivors and affected families. We propose that unusually severe and fatal sepsis cases in previously healthy children should be considered for exome/genome sequencing to search for underlying PIDs. PMID:27703454
Zhao, Wei; Niu, Guannan; Shen, Botao; Zheng, Yang; Gong, Fangchao; Wang, Xianfu; Lee, Jiyun; Mulvihill, John J; Chen, Xiaohui; Li, Shibo
2013-12-01
As patients with congenital heart disease (CHD) increasingly survive to childbearing age, it becomes important to understand the genetic origins of CHD. In children, CHD is frequently caused by chromosomal imbalances. We searched for submicroscopic imbalances in adults with CHD focusing on simple-to-moderate phenotypes, without associated dysmorphic features, a group not previously examined. A total of 100 Han Chinese adults with a diverse range of isolated CHD and 65 ethnically matched controls were screened using whole-genome array comparative genomic hybridization. Forty-five large (>100 kb) rare copy number variants (CNVs) were identified in 36/100 patients. These variants were not listed in the Database of Genomic Variants nor found in controls. In three of these genomic imbalances (22q11.2, 18q23, 3q21.3), genes that play an important role in cardiac development were implicated, including CRKL, NFATC1, PLXNA1, the latter has not been associated with human CHD before. This study detected a 0.7 Mb 22q11.2 deletion, which marginally overlapped the common 3 Mb 22q11.2 deletion, in one patient with a perimembranous ventricular septal defect without any extracardiac manifestation. Furthermore, we detected a novel inherited aberration dup (16q23.1). Although a causal relationship with CHD remains to be established, this CNVs profile provides a spectrum of genomic imbalances in this condition, and improves the CNV-phenotype correlations. © 2013 Wiley Periodicals, Inc.
Fairfield, Beth; Mammarella, Nicola; Di Domenico, Alberto; D'Aurora, Marco; Stuppia, Liborio; Gatta, Valentina
2017-08-30
False memories are common memory distortions in everyday life and seem to increase with affectively connoted complex information. In line with recent studies showing a significant interaction between the noradrenergic system and emotional memory, we investigated whether healthy volunteer carriers of the deletion variant of the ADRA2B gene that codes for the α2b-adrenergic receptor are more prone to false memories than non-carriers. In this study, we collected genotype data from 212 healthy female volunteers; 91 ADRA2B carriers and 121 non-carriers. To assess gene effects on false memories for affective information, factorial mixed model analysis of variances (ANOVAs) were conducted with genotype as the between-subjects factor and type of memory error as the within-subjects factor. We found that although carriers and non-carriers made comparable numbers of false memory errors, they showed differences in the direction of valence biases, especially for inferential causal errors. Specifically, carriers produced fewer causal false memory errors for scripts with a negative outcome, whereas non-carriers showed a more general emotional effect and made fewer causal errors with both positive and negative outcomes. These findings suggest that putatively higher levels of noradrenaline in deletion carriers may enhance short-term consolidation of negative information and lead to fewer memory distortions when facing negative events. Copyright © 2017 Elsevier B.V. All rights reserved.
Rare high-impact disease variants: properties and identifications.
Park, Leeyoung; Kim, Ju Han
2016-03-21
Although many genome-wide association studies have been performed, the identification of disease polymorphisms remains important. It is now suspected that many rare disease variants induce the association signal of common variants in linkage disequilibrium (LD). Based on recent development of genetic models, the current study provides explanations of the existence of rare variants with high impacts and common variants with low impacts. Disease variants are neither necessary nor sufficient due to gene-gene or gene-environment interactions. A new method was developed based on theoretical aspects to identify both rare and common disease variants by their genotypes. Common disease variants were identified with relatively small odds ratios and relatively small sample sizes, except for specific situations in which the disease variants were in strong LD with a variant with a higher frequency. Rare disease variants with small impacts were difficult to identify without increasing sample sizes; however, the method was reasonably accurate for rare disease variants with high impacts. For rare variants, dominant variants generally showed better Type II error rates than recessive variants; however, the trend was reversed for common variants. Type II error rates increased in gene regions containing more than two disease variants because the more common variant, rather than both disease variants, was usually identified. The proposed method would be useful for identifying common disease variants with small impacts and rare disease variants with large impacts when disease variants have the same effects on disease presentation.
Wendelsdorf, Katherine; Shah, Sohela
2015-09-01
There is on-going effort in the biomedical research community to leverage Next Generation Sequencing (NGS) technology to identify genetic variants that affect our health. The main challenge facing researchers is getting enough samples from individuals either sick or healthy - to be able to reliably identify the few variants that are causal for a phenotype among all other variants typically seen among individuals. At the same time, more and more individuals are having their genome sequenced either out of curiosity or to identify the cause of an illness. These individuals may benefit from of a way to view and understand their data. QIAGEN's Ingenuity Variant Analysis is an online application that allows users with and without extensive bioinformatics training to incorporate information from published experiments, genetic databases, and a variety of statistical models to identify variants, from a long list of candidates, that are most likely causal for a phenotype as well as annotate variants with what is already known about them in the literature and databases. Ingenuity Variant Analysis is also an information sharing platform where users may exchange samples and analyses. The Empowered Genome Community (EGC) is a new program in which QIAGEN is making this on-line tool freely available to any individual who wishes to analyze their own genetic sequence. EGC members are then able to make their data available to other Ingenuity Variant Analysis users to be used in research. Here we present and describe the Empowered Genome Community in detail. We also present a preliminary, proof-of-concept study that utilizes the 200 genomes currently available through the EGC. The goal of this program is to allow individuals to access and understand their own data as well as facilitate citizen-scientist collaborations that can drive research forward and spur quality scientific dialogue in the general public.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xie, Wei; Schimmel, Paul; Yang, Xiang-Lei, E-mail: xlyang@scripps.edu
2006-12-01
Crystallization and preliminary X-ray analysis of a native human tRNA synthetase whose allelic variants are associated with Charcot–Marie–Tooth Disease. Glycyl-tRNA synthetase (GlyRS) is one of a group of enzymes that catalyze the synthesis of aminoacyl-tRNAs for translation. Mutations of human and mouse GlyRSs are causally associated with Charcot–Marie–Tooth disease, the most common genetic disorder of the peripheral nervous system. As the first step towards a structure–function analysis of this disease, native human GlyRS was expressed, purified and crystallized. The crystal belonged to space group P4{sub 3}2{sub 1}2 or its enantiomorphic space group P4{sub 1}2{sub 1}2, with unit-cell parameters a =more » b = 91.74, c = 247.18 Å, and diffracted X-rays to 3.0 Å resolution. The asymmetric unit contained one GlyRS molecule and had a solvent content of 69%.« less
Genes Contributing to Genetic Variation of Muscling in Sheep
Tellam, Ross L.; Cockett, Noelle E.; Vuocolo, Tony; Bidwell, Christopher A.
2012-01-01
Selective breeding programs aiming to increase the productivity and profitability of the sheep meat industry use elite, progeny tested sires. The broad genetic traits of primary interest in the progeny of these sires include skeletal muscle yield, fat content, eating quality, and reproductive efficiency. Natural mutations in sheep that enhance muscling have been identified, while a number of genome scans have identified and confirmed quantitative trait loci (QTL) for skeletal muscle traits. The detailed phenotypic characteristics of sheep carrying these mutations or QTL affecting skeletal muscle show a number of common biological themes, particularly changes in developmental growth trajectories, alterations of whole animal morphology, and a shift toward fast twitch glycolytic fibers. The genetic, developmental, and biochemical mechanisms underpinning the actions of some of these genetic variants are described. This review critically assesses this research area, identifies gaps in knowledge, and highlights mechanistic linkages between genetic polymorphisms and skeletal muscle phenotypic changes. This knowledge may aid the discovery of new causal genetic variants and in some cases lead to the development of biochemical and immunological strategies aimed at enhancing skeletal muscle. PMID:22952470
Regulatory polymorphisms modulate the expression of HLA class II molecules and promote autoimmunity
Raj, Prithvi; Rai, Ekta; Song, Ran; Khan, Shaheen; Wakeland, Benjamin E; Viswanathan, Kasthuribai; Arana, Carlos; Liang, Chaoying; Zhang, Bo; Dozmorov, Igor; Carr-Johnson, Ferdicia; Mitrovic, Mitja; Wiley, Graham B; Kelly, Jennifer A; Lauwerys, Bernard R; Olsen, Nancy J; Cotsapas, Chris; Garcia, Christine K; Wise, Carol A; Harley, John B; Nath, Swapan K; James, Judith A; Jacob, Chaim O; Tsao, Betty P; Pasare, Chandrashekhar; Karp, David R; Li, Quan Zhen; Gaffney, Patrick M; Wakeland, Edward K
2016-01-01
Targeted sequencing of sixteen SLE risk loci among 1349 Caucasian cases and controls produced a comprehensive dataset of the variations causing susceptibility to systemic lupus erythematosus (SLE). Two independent disease association signals in the HLA-D region identified two regulatory regions containing 3562 polymorphisms that modified thirty-seven transcription factor binding sites. These extensive functional variations are a new and potent facet of HLA polymorphism. Variations modifying the consensus binding motifs of IRF4 and CTCF in the XL9 regulatory complex modified the transcription of HLA-DRB1, HLA-DQA1 and HLA-DQB1 in a chromosome-specific manner, resulting in a 2.5-fold increase in the surface expression of HLA-DR and DQ molecules on dendritic cells with SLE risk genotypes, which increases to over 4-fold after stimulation. Similar analyses of fifteen other SLE risk loci identified 1206 functional variants tightly linked with disease-associated SNPs and demonstrated that common disease alleles contain multiple causal variants modulating multiple immune system genes. DOI: http://dx.doi.org/10.7554/eLife.12089.001 PMID:26880555
Kottyan, Leah C; Zoller, Erin E; Bene, Jessica; Lu, Xiaoming; Kelly, Jennifer A; Rupert, Andrew M; Lessard, Christopher J; Vaughn, Samuel E; Marion, Miranda; Weirauch, Matthew T; Namjou, Bahram; Adler, Adam; Rasmussen, Astrid; Glenn, Stuart; Montgomery, Courtney G; Hirschfield, Gideon M; Xie, Gang; Coltescu, Catalina; Amos, Chris; Li, He; Ice, John A; Nath, Swapan K; Mariette, Xavier; Bowman, Simon; Rischmueller, Maureen; Lester, Sue; Brun, Johan G; Gøransson, Lasse G; Harboe, Erna; Omdal, Roald; Cunninghame-Graham, Deborah S; Vyse, Tim; Miceli-Richard, Corinne; Brennan, Michael T; Lessard, James A; Wahren-Herlenius, Marie; Kvarnström, Marika; Illei, Gabor G; Witte, Torsten; Jonsson, Roland; Eriksson, Per; Nordmark, Gunnel; Ng, Wan-Fai; Anaya, Juan-Manuel; Rhodus, Nelson L; Segal, Barbara M; Merrill, Joan T; James, Judith A; Guthridge, Joel M; Scofield, R Hal; Alarcon-Riquelme, Marta; Bae, Sang-Cheol; Boackle, Susan A; Criswell, Lindsey A; Gilkeson, Gary; Kamen, Diane L; Jacob, Chaim O; Kimberly, Robert; Brown, Elizabeth; Edberg, Jeffrey; Alarcón, Graciela S; Reveille, John D; Vilá, Luis M; Petri, Michelle; Ramsey-Goldman, Rosalind; Freedman, Barry I; Niewold, Timothy; Stevens, Anne M; Tsao, Betty P; Ying, Jun; Mayes, Maureen D; Gorlova, Olga Y; Wakeland, Ward; Radstake, Timothy; Martin, Ezequiel; Martin, Javier; Siminovitch, Katherine; Moser Sivils, Kathy L; Gaffney, Patrick M; Langefeld, Carl D; Harley, John B; Kaufman, Kenneth M
2015-01-15
Exploiting genotyping, DNA sequencing, imputation and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5-TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE), we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3230 IRF5-TNPO3 high-quality, common variants across 5 ethnicities in 8395 SLE cases and 7367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (P-valuemeta = 6 × 10(-49); OR = 1.38-1.97). The second genetic effect spanned an 85.5-kb, 24-variant haplotype that included the genes IRF5 and TNPO3 (P-valuesEU = 10(-27)-10(-32), OR = 1.7-1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögren's syndrome and systemic sclerosis whereas only the IRF5-TNPO3 gene-spanning haplotype is associated with primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5-TNPO3. Published by Oxford University Press 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Kottyan, Leah C.; Zoller, Erin E.; Bene, Jessica; Lu, Xiaoming; Kelly, Jennifer A.; Rupert, Andrew M.; Lessard, Christopher J.; Vaughn, Samuel E.; Marion, Miranda; Weirauch, Matthew T.; Namjou, Bahram; Adler, Adam; Rasmussen, Astrid; Glenn, Stuart; Montgomery, Courtney G.; Hirschfield, Gideon M.; Xie, Gang; Coltescu, Catalina; Amos, Chris; Li, He; Ice, John A.; Nath, Swapan K.; Mariette, Xavier; Bowman, Simon; Rischmueller, Maureen; Lester, Sue; Brun, Johan G.; Gøransson, Lasse G.; Harboe, Erna; Omdal, Roald; Cunninghame-Graham, Deborah S.; Vyse, Tim; Miceli-Richard, Corinne; Brennan, Michael T.; Lessard, James A.; Wahren-Herlenius, Marie; Kvarnström, Marika; Illei, Gabor G.; Witte, Torsten; Jonsson, Roland; Eriksson, Per; Nordmark, Gunnel; Ng, Wan-Fai; Anaya, Juan-Manuel; Rhodus, Nelson L.; Segal, Barbara M.; Merrill, Joan T.; James, Judith A.; Guthridge, Joel M.; Hal Scofield, R.; Alarcon-Riquelme, Marta; Bae, Sang-Cheol; Boackle, Susan A.; Criswell, Lindsey A.; Gilkeson, Gary; Kamen, Diane L.; Jacob, Chaim O.; Kimberly, Robert; Brown, Elizabeth; Edberg, Jeffrey; Alarcón, Graciela S.; Reveille, John D.; Vilá, Luis M.; Petri, Michelle; Ramsey-Goldman, Rosalind; Freedman, Barry I.; Niewold, Timothy; Stevens, Anne M.; Tsao, Betty P.; Ying, Jun; Mayes, Maureen D.; Gorlova, Olga Y.; Wakeland, Ward; Radstake, Timothy; Martin, Ezequiel; Martin, Javier; Siminovitch, Katherine; Moser Sivils, Kathy L.; Gaffney, Patrick M.; Langefeld, Carl D.; Harley, John B.; Kaufman, Kenneth M.
2015-01-01
Exploiting genotyping, DNA sequencing, imputation and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5–TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE), we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3230 IRF5–TNPO3 high-quality, common variants across 5 ethnicities in 8395 SLE cases and 7367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (P-valuemeta = 6 × 10−49; OR = 1.38–1.97). The second genetic effect spanned an 85.5-kb, 24-variant haplotype that included the genes IRF5 and TNPO3 (P-valuesEU = 10−27–10−32, OR = 1.7–1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögren's syndrome and systemic sclerosis whereas only the IRF5–TNPO3 gene-spanning haplotype is associated with primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5–TNPO3. PMID:25205108
Clinical analysis of genome next-generation sequencing data using the Omicia platform
Coonrod, Emily M; Margraf, Rebecca L; Russell, Archie; Voelkerding, Karl V; Reese, Martin G
2013-01-01
Aims Next-generation sequencing is being implemented in the clinical laboratory environment for the purposes of candidate causal variant discovery in patients affected with a variety of genetic disorders. The successful implementation of this technology for diagnosing genetic disorders requires a rapid, user-friendly method to annotate variants and generate short lists of clinically relevant variants of interest. This report describes Omicia’s Opal platform, a new software tool designed for variant discovery and interpretation in a clinical laboratory environment. The software allows clinical scientists to process, analyze, interpret and report on personal genome files. Materials & Methods To demonstrate the software, the authors describe the interactive use of the system for the rapid discovery of disease-causing variants using three cases. Results & Conclusion Here, the authors show the features of the Opal system and their use in uncovering variants of clinical significance. PMID:23895124
Irum, Bushra; Khan, Arif O.; Wang, Qiwei; Li, David; Khan, Asma A.; Husnain, Tayyab; Akram, Javed; Riazuddin, Sheikh
2016-01-01
Purpose This study was performed to investigate the genetic determinants of autosomal recessive congenital cataracts in large consanguineous families. Methods Affected individuals underwent a detailed ophthalmological examination and slit-lamp photographs of the cataractous lenses were obtained. An aliquot of blood was collected from all participating family members and genomic DNA was extracted from white blood cells. Initially, a genome-wide scan was performed with genomic DNAs of family PKCC025 followed by exclusion analysis of our familial cohort of congenital cataracts. Protein-coding exons of CRYBB1, CRYBB2, CRYBB3, and CRYBA4 were sequenced bidirectionally. A haplotype was constructed with SNPs flanking the causal mutation for affected individuals in all four families, while the probability that the four familial cases have a common founder was estimated using EM and CHM-based algorithms. The expression of Crybb3 in the developing murine lens was investigated using TaqMan assays. Results The clinical and ophthalmological examinations suggested that all affected individuals had nuclear cataracts. Genome-wide linkage analysis localized the causal phenotype in family PKCC025 to chromosome 22q with statistically significant two-point logarithm of odds (LOD) scores. Subsequently, we localized three additional families, PKCC063, PKCC131, and PKCC168 to chromosome 22q. Bidirectional Sanger sequencing identified a missense variation: c.493G>C (p.Gly165Arg) in CRYBB3 that segregated with the disease phenotype in all four familial cases. This variation was not found in ethnically matched control chromosomes, the NHLBI exome variant server, or the 1000 Genomes or dbSNP databases. Interestingly, all four families harbor a unique disease haplotype that strongly suggests a common founder of the causal mutation (p<1.64E-10). We observed expression of Crybb3 in the mouse lens as early as embryonic day 15 (E15), and expression remained relatively steady throughout development. Conclusion Here, we report a common ancestral mutation in CRYBB3 associated with autosomal recessive congenital cataracts identified in four familial cases of Pakistani origin. PMID:27326458
Felix, Janine F.; Gaillard, Romy; McMahon, George
2017-01-01
Background It has been suggested that greater maternal adiposity during pregnancy affects lifelong risk of offspring fatness via intrauterine mechanisms. Our aim was to use Mendelian randomisation (MR) to investigate the causal effect of intrauterine exposure to greater maternal body mass index (BMI) on offspring BMI and fat mass from childhood to early adulthood. Methods and Findings We used maternal genetic variants as instrumental variables (IVs) to test the causal effect of maternal BMI in pregnancy on offspring fatness (BMI and dual-energy X-ray absorptiometry [DXA] determined fat mass index [FMI]) in a MR approach. This was investigated, with repeat measurements, from ages 7 to 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 2,521 to 3,720 for different ages). We then sought to replicate findings with results for BMI at age 6 in Generation R (n = 2,337 for replication sample; n = 6,057 for total pooled sample). In confounder-adjusted multivariable regression in ALSPAC, a 1 standard deviation (SD, equivalent of 3.7 kg/m2) increase in maternal BMI was associated with a 0.25 SD (95% CI 0.21–0.29) increase in offspring BMI at age 7, with similar results at later ages and when FMI was used as the outcome. A weighted genetic risk score was generated from 32 genetic variants robustly associated with BMI (minimum F-statistic = 45 in ALSPAC). The MR results using this genetic risk score as an IV in ALSPAC were close to the null at all ages (e.g., 0.04 SD (95% CI -0.21–0.30) at age 7 and 0.03 SD (95% CI -0.26–0.32) at age 18 per SD increase in maternal BMI), which was similar when a 97 variant generic risk score was used in ALSPAC. When findings from age 7 in ALSPAC were meta-analysed with those from age 6 in Generation R, the pooled confounder-adjusted multivariable regression association was 0.22 SD (95% CI 0.19–0.25) per SD increase in maternal BMI and the pooled MR effect (pooling the 97 variant score results from ALSPAC with the 32 variant score results from Generation R) was 0.05 SD (95%CI -0.11–0.21) per SD increase in maternal BMI (p-value for difference between the two results = 0.05). A number of sensitivity analyses exploring violation of the MR results supported our main findings. However, power was limited for some of the sensitivity tests and further studies with relevant data on maternal, offspring, and paternal genotype are required to obtain more precise (and unbiased) causal estimates. Conclusions Our findings provide little evidence to support a strong causal intrauterine effect of incrementally greater maternal BMI resulting in greater offspring adiposity. PMID:28118352
Transethnic differences in GWAS signals: A simulation study.
Zanetti, Daniela; Weale, Michael E
2018-05-07
Genome-wide association studies (GWASs) have allowed researchers to identify thousands of single nucleotide polymorphisms (SNPs) and other variants associated with particular complex traits. Previous studies have reported differences in the strength and even the direction of GWAS signals across different populations. These differences could be due to a combination of (1) lack of power, (2) allele frequency differences, (3) linkage disequilibrium (LD) differences, and (4) true differences in causal variant effect sizes. To determine whether properties (1)-(3) on their own might be sufficient to explain the patterns previously noted in strong GWAS signals, we simulated case-control data of European, Asian and African ancestry, applying realistic allele frequencies and LD from 1000 Genomes data but enforcing equal causal effect sizes across populations. Much of the observed differences in strong GWAS signals could indeed be accounted for by allele frequency and LD differences, enhanced by the Euro-centric SNP bias and lower SNP coverage found in older GWAS panels. While we cannot rule out a role for true transethnic effect size differences, our results suggest that strong causal effects may be largely shared among human populations, motivating the use of transethnic data for fine-mapping. © 2018 John Wiley & Sons Ltd/University College London.
Carnitine Palmitoyltransferase 1A P479L and Infant Death: Policy Implications of Emerging Data
Fohner, Alison E.; Garrison, Nanibaa’ A.; Austin, Melissa A.; Burke, Wylie
2017-01-01
Carnitine Palmitoyltransferase 1 Isoform A (CPT1A) is a crucial enzyme for the transport of long chain fatty acids into the mitochondria. The CPT1A P479L variant is found in high frequencies among indigenous populations residing on the west and north coasts of Alaska and Canada and in northeast Siberia and Greenland. Epidemiological studies have reported a statistical association between P479L homozygosity and infant death in Alaska Native and Canadian Inuit populations. Here, we review the available evidence about the P479L variant and apply to these data the epidemiological criteria for assessing causal associations. We find insufficient evidence to support a causal association with infant death and further, that if a causal association is present, the genotype is likely to be only one of a complex set of factors contributing to an increased risk of infant death. We conclude that additional research is needed to clarify the observed association and to inform effective preventative measures for infant death. In light of these findings, we discuss the policy implications for public health efforts, as policies based on the observed association between P479L homozygosity and infant death data are premature. PMID:28125087
Kim, Seon-Hee; Kong, Yoon; Bae, Young-An
2017-06-01
Autonomous retrotransposons, in which replication and transcription are coupled, encode the essential gag and pol genes as a fusion or separate overlapping form(s) that are expressed in single transcripts regulated by a common upstream promoter. The element-specific expression strategies have driven development of relevant translational recoding mechanisms including ribosomal frameshifting to satisfy the protein stoichiometry critical for the assembly of infectious virus-like particles. Retrotransposons with different recoding strategies exhibit a mosaic distribution pattern across the diverse families of reverse transcribing elements, even though their respective distributions are substantially skewed towards certain family groups. However, only a few investigations to date have focused on the emergence of retrotransposons evolving novel expression strategy and causal genetic drivers of the structural variants. In this study, the bulk of genomic and transcribed sequences of a Ty3/gypsy-like CsRn1 retrotransposon in Clonorchis sinensis were analyzed for the comprehensive examination of its expression strategy. Our results demonstrated that structural variants with single open reading frame (ORF) have recurrently emerged from precedential CsRn1 copies encoding overlapping gag-pol ORFs by a single-nucleotide insertion in an upstream region of gag stop codon. In the parasite genome, some of the newly evolved variants appeared to undergo proliferative burst as active master lineages together with their ancestral copies. The genetic event was similarly observed in Opisthorchis viverrini, the closest neighbor of C. sinensis, whereas the resulting structural variants might have failed to overcome purifying selection and comprised minor remnant copies in the Opisthorchis genome. Copyright © 2017 Elsevier B.V. All rights reserved.
Vasan, Ramachandran S; Glazer, Nicole L; Felix, Janine F; Lieb, Wolfgang; Wild, Philipp S; Felix, Stephan B; Watzinger, Norbert; Larson, Martin G; Smith, Nicholas L; Dehghan, Abbas; Grosshennig, Anika; Schillert, Arne; Teumer, Alexander; Schmidt, Reinhold; Kathiresan, Sekar; Lumley, Thomas; Aulchenko, Yurii S; König, Inke R; Zeller, Tanja; Homuth, Georg; Struchalin, Maksim; Aragam, Jayashri; Bis, Joshua C; Rivadeneira, Fernando; Erdmann, Jeanette; Schnabel, Renate B; Dörr, Marcus; Zweiker, Robert; Lind, Lars; Rodeheffer, Richard J; Greiser, Karin Halina; Levy, Daniel; Haritunians, Talin; Deckers, Jaap W; Stritzke, Jan; Lackner, Karl J; Völker, Uwe; Ingelsson, Erik; Kullo, Iftikhar; Haerting, Johannes; O'Donnell, Christopher J; Heckbert, Susan R; Stricker, Bruno H; Ziegler, Andreas; Reffelmann, Thorsten; Redfield, Margaret M; Werdan, Karl; Mitchell, Gary F; Rice, Kenneth; Arnett, Donna K; Hofman, Albert; Gottdiener, John S; Uitterlinden, Andre G; Meitinger, Thomas; Blettner, Maria; Friedrich, Nele; Wang, Thomas J; Psaty, Bruce M; van Duijn, Cornelia M; Wichmann, H-Erich; Munzel, Thomas F; Kroemer, Heyo K; Benjamin, Emelia J; Rotter, Jerome I; Witteman, Jacqueline C; Schunkert, Heribert; Schmidt, Helena; Völzke, Henry; Blankenberg, Stefan
2009-07-08
Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease. To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples. Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort. Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size. In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance). We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.
Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander
2016-01-01
Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894
Marioni, Riccardo E; Deary, Ian J; Murray, Gordon D; Lowe, Gordon D O; Rafnsson, Snorri B; Strachan, Mark W J; Luciano, Michelle; Houlihan, Lorna M; Gow, Alan J; Harris, Sarah E; Stewart, Marlene C; Rumley, Ann; Fowkes, F Gerry R; Price, Jackie F
2010-01-01
It is unknown whether the relationship between raised inflammatory biomarker levels and late-life cognitive ability is causal. We explored this issue by testing the association between genetic regulators of plasma C-reactive protein (CRP) and cognition. Data were analysed from four cohorts based in central Scotland (Total N = 4,782). Associations were tested between variants in the CRP gene and both plasma CRP levels and a battery of neuropsychological tests, including a vocabulary-based estimate of peak prior cognitive ability and a general (summary) cognitive factor score, or 'g'. CRP levels were associated with a number of variants in the CRP gene (SNPs), including rs1205, rs1130864, rs1800947, and rs1417938 (P range 4.2e-06 to 0.041). Higher CRP levels were also associated with vocabulary-adjusted cognitive ability, used here to estimate lifetime cognitive change (P range 1.7e-04 to 0.038). After correction for multiple testing and adjustment for age and sex, no statistically significant associations were found between the SNPs and cognition. CRP is unlikely to be a causal determinant of late-life cognitive ability.
Boulling, Arnaud; Masson, Emmanuelle; Zou, Wen-Bin; Paliwal, Sumit; Wu, Hao; Issarapu, Prachand; Bhaskar, Seema; Génin, Emmanuelle; Cooper, David N; Li, Zhao-Shen; Chandak, Giriraj R; Liao, Zhuan; Chen, Jian-Min; Férec, Claude
2017-08-01
The haplotype harboring the SPINK1 c.101A>G (p.Asn34Ser) variant (also known as rs17107315:T>C) represents the most important heritable risk factor for idiopathic chronic pancreatitis identified to date. The causal variant contained within this risk haplotype has however remained stubbornly elusive. Herein, we set out to resolve this enigma by employing a hypothesis-driven approach. First, we searched for variants in strong linkage disequilibrium (LD) with rs17107315:T>C using HaploReg v4.1. Second, we identified two candidate SNPs by visual inspection of sequences spanning all 25 SNPs found to be in LD with rs17107315:T>C, guided by prior knowledge of pancreas-specific transcription factors and their cognate binding sites. Third, employing a novel cis-regulatory module (CRM)-guided approach to further filter the two candidate SNPs yielded a solitary candidate causal variant. Finally, combining data from phylogenetic conservation and chromatin accessibility, cotransfection transactivation experiments, and population genetic studies, we suggest that rs142703147:C>A, which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A-PTF1L CRM located ∼4 kb upstream of the SPINK1 promoter, contributes to the aforementioned chronic pancreatitis risk haplotype. Further studies are required not only to improve the characterization of this functional SNP but also to identify other functional components that might contribute to this high-risk haplotype. © 2017 Wiley Periodicals, Inc.
Kos, M Z; Yan, J; Dick, D M; Agrawal, A; Bucholz, K K; Rice, J P; Johnson, E O; Schuckit, M; Kuperman, S; Kramer, J; Goate, A M; Tischfield, J A; Foroud, T; Nurnberger, J; Hesselbrock, V; Porjesz, B; Bierut, L J; Edenberg, H J; Almasy, L
2013-07-01
Alcohol dependence (AD) is a heritable substance addiction with adverse physical and psychological consequences, representing a major health and economic burden on societies worldwide. Genes thus far implicated via linkage, candidate gene and genome-wide association studies (GWAS) account for only a small fraction of its overall risk, with effects varying across ethnic groups. Here we investigate the genetic architecture of alcoholism and report on the extent to which common, genome-wide SNPs collectively account for risk of AD in two US populations, African-Americans (AAs) and European-Americans (EAs). Analyzing GWAS data for two independent case-control sample sets, we compute polymarker scores that are significantly associated with alcoholism (P = 1.64 × 10(-3) and 2.08 × 10(-4) for EAs and AAs, respectively), reflecting the small individual effects of thousands of variants derived from patterns of allelic architecture that are population specific. Simulations show that disease models based on rare and uncommon causal variants (MAF < 0.05) best fit the observed distribution of polymarker signals. When scoring bins were annotated for gene location and examined for constituent biological networks, gene enrichment is observed for several cellular processes and functions in both EA and AA populations, transcending their underlying allelic differences. Our results reveal key insights into the complex etiology of AD, raising the possibility of an important role for rare and uncommon variants, and identify polygenic mechanisms that encompass a spectrum of disease liability, with some, such as chloride transporters and glycine metabolism genes, displaying subtle, modifying effects that are likely to escape detection in most GWAS designs. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
Price, T. Ryan; De Pablo-Fernandez, Eduardo; Haycock, Philip C.; Schrag, Anette; Lees, Andrew J.; Hardy, John; Singleton, Andrew; Nalls, Mike A.; Pearce, Neil; Wood, Nicholas W.
2017-01-01
Background Both positive and negative associations between higher body mass index (BMI) and Parkinson disease (PD) have been reported in observational studies, but it has been difficult to establish causality because of the possibility of residual confounding or reverse causation. To our knowledge, Mendelian randomisation (MR)—the use of genetic instrumental variables (IVs) to explore causal effects—has not previously been used to test the effect of BMI on PD. Methods and findings Two-sample MR was undertaken using genome-wide association (GWA) study data. The associations between the genetic instruments and BMI were obtained from the GIANT consortium and consisted of the per-allele difference in mean BMI for 77 independent variants that reached genome-wide significance. The per-allele difference in log-odds of PD for each of these variants was estimated from a recent meta-analysis, which included 13,708 cases of PD and 95,282 controls. The inverse-variance weighted method was used to estimate a pooled odds ratio (OR) for the effect of a 5-kg/m2 higher BMI on PD. Evidence of directional pleiotropy averaged across all variants was sought using MR–Egger regression. Frailty simulations were used to assess whether causal associations were affected by mortality selection. A combined genetic IV expected to confer a lifetime exposure of 5-kg/m2 higher BMI was associated with a lower risk of PD (OR 0.82, 95% CI 0.69–0.98). MR–Egger regression gave similar results, suggesting that directional pleiotropy was unlikely to be biasing the result (intercept 0.002; p = 0.654). However, the apparent protective influence of higher BMI could be at least partially induced by survival bias in the PD GWA study, as demonstrated by frailty simulations. Other important limitations of this application of MR include the inability to analyse non-linear associations, to undertake subgroup analyses, and to gain mechanistic insights. Conclusions In this large study using two-sample MR, we found that variants known to influence BMI had effects on PD in a manner consistent with higher BMI leading to lower risk of PD. The mechanism underlying this apparent protective effect warrants further study. PMID:28609445
Time, frequency, and time-varying Granger-causality measures in neuroscience.
Cekic, Sezen; Grandjean, Didier; Renaud, Olivier
2018-05-20
This article proposes a systematic methodological review and an objective criticism of existing methods enabling the derivation of time, frequency, and time-varying Granger-causality statistics in neuroscience. The capacity to describe the causal links between signals recorded at different brain locations during a neuroscience experiment is indeed of primary interest for neuroscientists, who often have very precise prior hypotheses about the relationships between recorded brain signals. The increasing interest and the huge number of publications related to this topic calls for this systematic review, which describes the very complex methodological aspects underlying the derivation of these statistics. In this article, we first present a general framework that allows us to review and compare Granger-causality statistics in the time domain, and the link with transfer entropy. Then, the spectral and the time-varying extensions are exposed and discussed together with their estimation and distributional properties. Although not the focus of this article, partial and conditional Granger causality, dynamical causal modelling, directed transfer function, directed coherence, partial directed coherence, and their variant are also mentioned. Copyright © 2018 John Wiley & Sons, Ltd.
The genetics of celiac disease: A comprehensive review of clinical implications.
Dieli-Crimi, Romina; Cénit, M Carmen; Núñez, Concepción
2015-11-01
Celiac disease (CD) is a complex immune-related disease with a very strong genetic component. Multiple genetic findings over the last decade have added to the already known MHC influence numerous genetic variants associated to CD susceptibility. Currently, it is well-established that 6 MHC and 39 non-MHC loci, including a higher number of independent genetic variants, are associated to disease risk. Moreover, additional regions have been recently implicated in the disease, which would increase the number of involved loci. Together, the firmly described genetic variants account for roughly 31% of CD heritability, being 25% explained by the MHC influence. These new variants represent markers of disease risk and turn the identification of the causal genes and the causal variants inside the associated loci, as well as their precise biological role on the disease, into a major challenge in CD research. Numerous studies have been developed with this aim showing the high impact of risk variants on gene expression. These studies also indicate a central role of CD4(+) T cells in CD pathogenesis and point to B cells as important players, which is in accordance with the key steps highlighted by the immunological models of pathogenesis. We comprehensively summarize the current knowledge about the genetic architecture of CD, characterized by multiple low-risk variants located within diverse loci which are most likely affecting genes with immune-related functions. These findings are leading to a better understanding of CD pathogenesis and helping in the design of new treatments. The repertoire of potential drug targets for CD has largely broadened last years, bringing us closer to get alternative or complementary treatments to the life-long gluten-free diet, the only effective treatment so far. Epigenetics and microbiota are emerging as potent factors modulating disease risk and putatively affecting disease manifestation, which are also being explored as therapeutic targets. Copyright © 2015 Elsevier Ltd. All rights reserved.
NGS Technologies as a Turning Point in Rare Disease Research, Diagnosis and Treatment
Fernández-Marmiesse, Ana; Gouveia, Sofía; Couce, María L.
2018-01-01
Approximately 25-50 million Americans, 30 million Europeans, and 8% of the Aus-tralian population have a rare disease. Rare diseases are thus a common problem for clini-cians and account for enormous healthcare costs worldwide due to the difficulty of establish-ing a specific diagnosis. In this article, we review the milestones achieved in our understanding of rare diseases since the emergence of next-generation sequencing (NGS) technologies and analyze how these advances have influenced research and diagnosis. The first half of this review describes how NGS has changed diagnostic workflows and provided an unprecedent-ed, simple way of discovering novel disease-associated genes. We focus particularly on meta-bolic and neurodevelopmental disorders. NGS has enabled cheap and rapid genetic diagnosis, highlighted the relevance of mosaic and de novo mutations, brought to light the wide pheno-typic spectrum of most genes, detected digenic inheritance or the presence of more than one rare disease in the same patient, and paved the way for promising new therapies. In the sec-ond part of the review, we look at the limitations and challenges of NGS, including determina-tion of variant causality, the loss of variants in coding and non-coding regions, and the detec-tion of somatic mosaicism variants and epigenetic mutations, and discuss how these can be overcome in the near future. PMID:28721829
NGS Technologies as a Turning Point in Rare Disease Research , Diagnosis and Treatment.
Fernandez-Marmiesse, Ana; Gouveia, Sofia; Couce, Maria L
2018-01-30
Approximately 25-50 million Americans, 30 million Europeans, and 8% of the Australian population have a rare disease. Rare diseases are thus a common problem for clinicians and account for enormous healthcare costs worldwide due to the difficulty of establishing a specific diagnosis. In this article, we review the milestones achieved in our understanding of rare diseases since the emergence of next-generation sequencing (NGS) technologies and analyze how these advances have influenced research and diagnosis. The first half of this review describes how NGS has changed diagnostic workflows and provided an unprecedented, simple way of discovering novel disease-associated genes. We focus particularly on metabolic and neurodevelopmental disorders. NGS has enabled cheap and rapid genetic diagnosis, highlighted the relevance of mosaic and de novo mutations, brought to light the wide phenotypic spectrum of most genes, detected digenic inheritance or the presence of more than one rare disease in the same patient, and paved the way for promising new therapies. In the second part of the review, we look at the limitations and challenges of NGS, including determination of variant causality, the loss of variants in coding and non-coding regions, and the detection of somatic mosaicism variants and epigenetic mutations, and discuss how these can be overcome in the near future. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Implication of Genes for the N-Methyl-D-Aspartate (NMDA) Receptor in Substance Addictions.
Chen, Jiali; Ma, Yunlong; Fan, Rongli; Yang, Zhongli; Li, Ming D
2018-02-10
Drug dependence is a chronic brain disease with harmful consequences for both individual users and society. Glutamate is a primary excitatory neurotransmitter in the brain, and both in vivo and in vitro experiments have implicated N-methyl-D-aspartate (NMDA) receptor, a glutamate receptor, as an element in various types of addiction. Recent findings from genetics-based approaches such as genome-wide linkage, candidate gene association, genome-wide association (GWA), and next-generation sequencing have demonstrated the significant association of NMDA receptor subunit genes such as GluN3A, GluN2B, and GluN2A with various addiction-related phenotypes. Of these genes, GluN3A has been the most studied, and it has been revealed to play crucial roles in the etiology of addictions. In this communication, we provide an updated view of the genetic effects of NMDA receptor subunit genes and their functions in the etiology of addictions based on the findings from investigation of both common and rare variants as well as SNP-SNP interactions. To better understand the molecular mechanisms underlying addiction-related behaviors and to promote the development of specific medicines for the prevention and treatment of addictions, current efforts aim not only to identify more causal variants in NMDA receptor subunits by using large independent samples but also to reveal the molecular functions of these variants in addictions.
Xu, Min; Bi, Yufang; Huang, Ya; Xie, Lan; Hao, Mingli; Zhao, Zhiyun; Xu, Yu; Lu, Jieli; Chen, Yuhong; Sun, Yimin; Qi, Lu; Wang, Weiqing; Ning, Guang
2016-01-01
Background Type 2 diabetes (T2D) is a risk factor for dysregulation of glomerular filtration rate (GFR) and albuminuria. However, whether the association is causal remains unestablished. Research Design and Methods We performed a Mendelian Randomization (MR) analysis in 11,502 participants aged 40 and above, from a well-defined community in Shanghai during 2011–2013, to explore the causal association between T2D and decreased estimated GFR (eGFR) and increased urinary albumin-to-creatinine ratio (uACR). We genotyped 34 established T2D common variants in East Asians, and created a T2D-genetic risk score (GRS). We defined decreased eGFR as eGFR < 90 ml/min/1.73 m2 and increased uACR as uACR ≥ 30 mg/g. We used the T2D_GRS as the instrumental variable (IV) to quantify the causal effect of T2D on decreased eGFR and increased uACR. Results Each 1-standard deviation (SD, 3.90 points) increment in T2D_GRS was associated with decreased eGFR: odds ratio (OR) = 1.18 (95% confidence interval [CI]: 1.01, 1.30). In the MR analysis, we demonstrated a causal relationship between genetically determined T2D and decreased eGFR (OR = 1.47, 95% CI: 1.15, 1.88, P = 0.0003). When grouping the genetic loci according to their relations with either insulin secretion (IS) or insulin resistance (IR), we found both IS_GRS and IR_GRS were significantly related to decreased eGFR (both P < 0.02). In addition, T2D_GRS and IS_GRS were significantly associated with Log-uACR (both P = 0.04). Conclusion Our results provide novel evidence for a causal association between T2D and decreased eGFR by using MR approach in a Chinese population. PMID:27211558
Xu, Min; Bi, Yufang; Huang, Ya; Xie, Lan; Hao, Mingli; Zhao, Zhiyun; Xu, Yu; Lu, Jieli; Chen, Yuhong; Sun, Yimin; Qi, Lu; Wang, Weiqing; Ning, Guang
2016-04-01
Type 2 diabetes (T2D) is a risk factor for dysregulation of glomerular filtration rate (GFR) and albuminuria. However, whether the association is causal remains unestablished. We performed a Mendelian Randomization (MR) analysis in 11,502 participants aged 40 and above, from a well-defined community in Shanghai during 2011-2013, to explore the causal association between T2D and decreased estimated GFR (eGFR) and increased urinary albumin-to-creatinine ratio (uACR). We genotyped 34 established T2D common variants in East Asians, and created a T2D-genetic risk score (GRS). We defined decreased eGFR as eGFR<90ml/min/1.73m(2) and increased uACR as uACR≥30mg/g. We used the T2D_GRS as the instrumental variable (IV) to quantify the causal effect of T2D on decreased eGFR and increased uACR. Each 1-standard deviation (SD, 3.90 points) increment in T2D_GRS was associated with decreased eGFR: odds ratio (OR)=1.18 (95% confidence interval [CI]: 1.01, 1.30). In the MR analysis, we demonstrated a causal relationship between genetically determined T2D and decreased eGFR (OR=1.47, 95% CI: 1.15, 1.88, P=0.0003). When grouping the genetic loci according to their relations with either insulin secretion (IS) or insulin resistance (IR), we found both IS_GRS and IR_GRS were significantly related to decreased eGFR (both P<0.02). In addition, T2D_GRS and IS_GRS were significantly associated with Log-uACR (both P=0.04). Our results provide novel evidence for a causal association between T2D and decreased eGFR by using MR approach in a Chinese population. Copyright © 2016. Published by Elsevier B.V.
A variant of special relativity and long-distance astronomy.
Segal, I E
1974-03-01
THE REDSHIFT, MICROWAVE BACKGROUND, AND OTHER OBSERVABLE ASTRONOMICAL FEATURES ARE DEDUCED FROM TWO THEORETICAL ASSUMPTIONS: (1) global space-time is a certain variant of Minkowski space, locally indistinguishable in causality and covariance features but globally admitting the full conformal group as symmetries although having a spherical space component; (2) the true energy operator corresponds to a certain generator of this group which is not globally scale-covariant, whereas laboratory frequency measurements are inevitably such and correspond to the conventional energy operator [unk]/i[unk]/[unk]t.
Day, Felix R.; Hinds, David A.; Tung, Joyce Y.; Stolk, Lisette; Styrkarsdottir, Unnur; Saxena, Richa; Bjonnes, Andrew; Broer, Linda; Dunger, David B.; Halldorsson, Bjarni V.; Lawlor, Debbie A.; Laval, Guillaume; Mathieson, Iain; McCardle, Wendy L.; Louwers, Yvonne; Meun, Cindy; Ring, Susan; Scott, Robert A.; Sulem, Patrick; Uitterlinden, André G.; Wareham, Nicholas J.; Thorsteinsdottir, Unnur; Welt, Corrine; Stefansson, Kari; Laven, Joop S. E.; Ong, Ken K.; Perry, John R. B.
2015-01-01
Polycystic ovary syndrome (PCOS) is the most common reproductive disorder in women, yet there is little consensus regarding its aetiology. Here we perform a genome-wide association study of PCOS in up to 5,184 self-reported cases of White European ancestry and 82,759 controls, with follow-up in a further ∼2,000 clinically validated cases and ∼100,000 controls. We identify six signals for PCOS at genome-wide statistical significance (P<5 × 10−8), in/near genes ERBB4/HER4, YAP1, THADA, FSHB, RAD50 and KRR1. Variants in/near three of the four epidermal growth factor receptor genes (ERBB2/HER2, ERBB3/HER3 and ERBB4/HER4) are associated with PCOS at or near genome-wide significance. Mendelian randomization analyses indicate causal roles in PCOS aetiology for higher BMI (P=2.5 × 10−9), higher insulin resistance (P=6 × 10−4) and lower serum sex hormone binding globulin concentrations (P=5 × 10−4). Furthermore, genetic susceptibility to later menopause is associated with higher PCOS risk (P=1.6 × 10−8) and PCOS-susceptibility alleles are associated with higher serum anti-Müllerian hormone concentrations in girls (P=8.9 × 10−5). This large-scale study implicates an aetiological role of the epidermal growth factor receptors, infers causal mechanisms relevant to clinical management and prevention, and suggests balancing selection mechanisms involved in PCOS risk. PMID:26416764
Day, Felix R; Hinds, David A; Tung, Joyce Y; Stolk, Lisette; Styrkarsdottir, Unnur; Saxena, Richa; Bjonnes, Andrew; Broer, Linda; Dunger, David B; Halldorsson, Bjarni V; Lawlor, Debbie A; Laval, Guillaume; Mathieson, Iain; McCardle, Wendy L; Louwers, Yvonne; Meun, Cindy; Ring, Susan; Scott, Robert A; Sulem, Patrick; Uitterlinden, André G; Wareham, Nicholas J; Thorsteinsdottir, Unnur; Welt, Corrine; Stefansson, Kari; Laven, Joop S E; Ong, Ken K; Perry, John R B
2015-09-29
Polycystic ovary syndrome (PCOS) is the most common reproductive disorder in women, yet there is little consensus regarding its aetiology. Here we perform a genome-wide association study of PCOS in up to 5,184 self-reported cases of White European ancestry and 82,759 controls, with follow-up in a further ∼2,000 clinically validated cases and ∼100,000 controls. We identify six signals for PCOS at genome-wide statistical significance (P<5 × 10(-8)), in/near genes ERBB4/HER4, YAP1, THADA, FSHB, RAD50 and KRR1. Variants in/near three of the four epidermal growth factor receptor genes (ERBB2/HER2, ERBB3/HER3 and ERBB4/HER4) are associated with PCOS at or near genome-wide significance. Mendelian randomization analyses indicate causal roles in PCOS aetiology for higher BMI (P=2.5 × 10(-9)), higher insulin resistance (P=6 × 10(-4)) and lower serum sex hormone binding globulin concentrations (P=5 × 10(-4)). Furthermore, genetic susceptibility to later menopause is associated with higher PCOS risk (P=1.6 × 10(-8)) and PCOS-susceptibility alleles are associated with higher serum anti-Müllerian hormone concentrations in girls (P=8.9 × 10(-5)). This large-scale study implicates an aetiological role of the epidermal growth factor receptors, infers causal mechanisms relevant to clinical management and prevention, and suggests balancing selection mechanisms involved in PCOS risk.
Spieler, Derek; Kaffe, Maria; Knauf, Franziska; Bessa, José; Tena, Juan J; Giesert, Florian; Schormair, Barbara; Tilch, Erik; Lee, Heekyoung; Horsch, Marion; Czamara, Darina; Karbalai, Nazanin; von Toerne, Christine; Waldenberger, Melanie; Gieger, Christian; Lichtner, Peter; Claussnitzer, Melina; Naumann, Ronald; Müller-Myhsok, Bertram; Torres, Miguel; Garrett, Lillian; Rozman, Jan; Klingenspor, Martin; Gailus-Durner, Valérie; Fuchs, Helmut; Hrabě de Angelis, Martin; Beckers, Johannes; Hölter, Sabine M; Meitinger, Thomas; Hauck, Stefanie M; Laumen, Helmut; Wurst, Wolfgang; Casares, Fernando; Gómez-Skarmeta, Jose Luis; Winkelmann, Juliane
2014-04-01
Genome-wide association studies (GWAS) identified the MEIS1 locus for Restless Legs Syndrome (RLS), but causal single nucleotide polymorphisms (SNPs) and their functional relevance remain unknown. This locus contains a large number of highly conserved noncoding regions (HCNRs) potentially functioning as cis-regulatory modules. We analyzed these HCNRs for allele-dependent enhancer activity in zebrafish and mice and found that the risk allele of the lead SNP rs12469063 reduces enhancer activity in the Meis1 expression domain of the murine embryonic ganglionic eminences (GE). CREB1 binds this enhancer and rs12469063 affects its binding in vitro. In addition, MEIS1 target genes suggest a role in the specification of neuronal progenitors in the GE, and heterozygous Meis1-deficient mice exhibit hyperactivity, resembling the RLS phenotype. Thus, in vivo and in vitro analysis of a common SNP with small effect size showed allele-dependent function in the prospective basal ganglia representing the first neurodevelopmental region implicated in RLS.
Mancuso, Nicholas; Shi, Huwenbo; Goddard, Pagé; Kichaev, Gleb; Gusev, Alexander; Pasaniuc, Bogdan
2017-03-02
Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Yousri, Noha A; Fakhro, Khalid A; Robay, Amal; Rodriguez-Flores, Juan L; Mohney, Robert P; Zeriri, Hassina; Odeh, Tala; Kader, Sara Abdul; Aldous, Eman K; Thareja, Gaurav; Kumar, Manish; Al-Shakaki, Alya; Chidiac, Omar M; Mohamoud, Yasmin A; Mezey, Jason G; Malek, Joel A; Crystal, Ronald G; Suhre, Karsten
2018-01-23
Metabolomics-genome-wide association studies (mGWAS) have uncovered many metabolic quantitative trait loci (mQTLs) influencing human metabolic individuality, though predominantly in European cohorts. By combining whole-exome sequencing with a high-resolution metabolomics profiling for a highly consanguineous Middle Eastern population, we discover 21 common variant and 12 functional rare variant mQTLs, of which 45% are novel altogether. We fine-map 10 common variant mQTLs to new metabolite ratio associations, and 11 common variant mQTLs to putative protein-altering variants. This is the first work to report common and rare variant mQTLs linked to diseases and/or pharmacological targets in a consanguineous Arab cohort, with wide implications for precision medicine in the Middle East.
2012-01-01
The increasing size and complexity of exome/genome sequencing data requires new tools for clinical geneticists to discover disease-causing variants. Bottlenecks in identifying the causative variation include poor cross-sample querying, constantly changing functional annotation and not considering existing knowledge concerning the phenotype. We describe a methodology that facilitates exploration of patient sequencing data towards identification of causal variants under different genetic hypotheses. Annotate-it facilitates handling, analysis and interpretation of high-throughput single nucleotide variant data. We demonstrate our strategy using three case studies. Annotate-it is freely available and test data are accessible to all users at http://www.annotate-it.org. PMID:23013645
C-terminal oligomerization of podocin mediates interallelic interactions.
Stráner, Pál; Balogh, Eszter; Schay, Gusztáv; Arrondel, Christelle; Mikó, Ágnes; L'Auné, Gerda; Benmerah, Alexandre; Perczel, András; K Menyhárd, Dóra; Antignac, Corinne; Mollet, Géraldine; Tory, Kálmán
2018-07-01
Interallelic interactions of membrane proteins are not taken into account while evaluating the pathogenicity of sequence variants in autosomal recessive disorders. Podocin, a membrane-anchored component of the slit diaphragm, is encoded by NPHS2, the major gene mutated in hereditary podocytopathies. We formerly showed that its R229Q variant is only pathogenic when trans-associated to specific 3' mutations and suggested the causal role of an abnormal C-terminal dimerization. Here we show by FRET analysis and size exclusion chromatography that podocin oligomerization occurs exclusively through the C-terminal tail (residues 283-382): principally through the first C-terminal helical region (H1, 283-313), which forms a coiled coil as shown by circular dichroism spectroscopy, and through the 332-348 region. We show the principal role of the oligomerization sites in mediating interallelic interactions: while the monomer-forming R286Tfs*17 podocin remains membranous irrespective of the coexpressed podocin variant identity, podocin variants with an intact H1 significantly influence each other's localization (r 2 = 0.68, P = 9.2 × 10 -32 ). The dominant negative effect resulting in intracellular retention of the pathogenic F344Lfs*4-R229Q heterooligomer occurs in parallel with a reduction in the FRET efficiency, suggesting the causal role of a conformational rearrangement. On the other hand, oligomerization can also promote the membrane localization: it can prevent the endocytosis of F344Lfs*4 or F344* podocin mutants induced by C-terminal truncation. In conclusion, C-terminal oligomerization of podocin can mediate both a dominant negative effect and interallelic complementation. Interallelic interactions of NPHS2 are not restricted to the R229Q variant and have to be considered in compound heterozygous individuals. Copyright © 2018 Elsevier B.V. All rights reserved.
Genetics of Lipid and Lipoprotein Disorders and Traits.
Dron, Jacqueline S; Hegele, Robert A
2016-01-01
Plasma lipids, namely cholesterol and triglyceride, and lipoproteins, such as low-density lipoprotein (LDL) and high-density lipoprotein, serve numerous physiological roles. Perturbed levels of these traits underlie monogenic dyslipidemias, a diverse group of multisystem disorders. We are on the verge of having a relatively complete picture of the human dyslipidemias and their components. Recent advances in genetics of plasma lipids and lipoproteins include the following: (1) expanding the range of genes causing monogenic dyslipidemias, particularly elevated LDL cholesterol; (2) appreciating the role of polygenic effects in such traits as familial hypercholesterolemia and combined hyperlipidemia; (3) accumulating a list of common variants that determine plasma lipids and lipoproteins; (4) applying exome sequencing to identify collections of rare variants determining plasma lipids and lipoproteins that via Mendelian randomization have also implicated gene products such as NPC1L1 , APOC3 , LDLR , APOA5 , and ANGPTL4 as causal for atherosclerotic cardiovascular disease; and (5) using naturally occurring genetic variation to identify new drug targets, including inhibitors of apolipoprotein (apo) C-III, apo(a), ANGPTL3, and ANGPTL4. Here, we compile this disparate range of data linking human genetic variation to plasma lipids and lipoproteins, providing a "one stop shop" for the interested reader.
Genetic Susceptibility to ANCA-Associated Vasculitis: State of the Art
Bonatti, Francesco; Reina, Michele; Neri, Tauro Maria; Martorana, Davide
2014-01-01
ANCA-associated vasculitis (AAV) is a group of disorders that is caused by inflammation affecting small blood vessels. Both arteries and veins are affected. AAV includes microscopic polyangiitis (MPA), granulomatosis with polyangiitis (GPA) renamed from Wegener’s granulomatosis, and eosinophilic granulomatosis with polyangiitis (EGPA), renamed from Churg–Strauss syndrome. AAV is primarily due to leukocyte migration and resultant damage. Despite decades of research, the mechanisms behind AAV disease etiology are still not fully understood, although it is clear that genetic and environmental factors are involved. To improve the understanding of the disease, the genetic component has been extensively studied by candidate association studies and two genome-wide association studies. The majority of the identified genetic AAV risk factors are common variants. These have uncovered information that still needs further investigation to clarify its importance. In this review, we summarize and discuss the results of the genetic studies in AAV. We also present the novel approaches to identifying the causal variants in complex susceptibility loci and disease mechanisms. Finally, we discuss the limitations of current methods and the challenges that we still have to face in order to incorporate genomic and epigenomic data into clinical practice. PMID:25452756
Genotype imputation in a tropical crossbred dairy cattle population
USDA-ARS?s Scientific Manuscript database
The application of new tools, such as genomic selection and genotype imputation, still presents challenges in crossbred populations because relationships of causal variants with markers may vary across breeds. In order to make genomic selection more cost effective, cheap low density chips are often ...
Hu, Zhi-Liang; Ramos, Antonio M.; Humphray, Sean J.; Rogers, Jane; Reecy, James M.; Rothschild, Max F.
2011-01-01
The newly available pig genome sequence has provided new information to fine map quantitative trait loci (QTL) in order to eventually identify causal variants. With targeted genomic sequencing efforts, we were able to obtain high quality BAC sequences that cover a region on pig chromosome 17 where a number of meat quality QTL have been previously discovered. Sequences from 70 BAC clones were assembled to form an 8-Mbp contig. Subsequently, we successfully mapped five previously identified QTL, three for meat color and two for lactate related traits, to the contig. With an additional 25 genetic markers that were identified by sequence comparison, we were able to carry out further linkage disequilibrium analysis to narrow down the genomic locations of these QTL, which allowed identification of the chromosomal regions that likely contain the causative variants. This research has provided one practical approach to combine genetic and molecular information for QTL mining. PMID:22303339
Genetics: Implications for Prevention and Management of Coronary Artery Disease.
Assimes, Themistocles L; Roberts, Robert
2016-12-27
An exciting new era has dawned for the prevention and management of coronary artery disease (CAD) utilizing genetic risk variants. The recent identification of over 60 susceptibility loci for CAD confirms not only the importance of established risk factors, but also the existence of many novel causal pathways that are expected to improve our understanding of the genetic basis of CAD and facilitate the development of new therapeutic agents over time. Concurrently, Mendelian randomization studies have provided intriguing insights on the causal relationship between CAD-related traits, and highlight the potential benefits of long-term modifications of risk factors. Last, genetic risk scores of CAD may serve not only as prognostic, but also as predictive markers, and carry the potential to considerably improve the delivery of established prevention strategies. This review will summarize the evolution and discovery of genetic risk variants for CAD and their current and future clinical applications. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Burgess, Stephen; Daniel, Rhian M; Butterworth, Adam S; Thompson, Simon G
2015-01-01
Background: Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. Methods: We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. Results: These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. Conclusions: These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes. PMID:25150977
Wang, Nan; Zhang, Yeting; Gedvilaite, Erika; Loh, Jui Wan; Lin, Timothy; Liu, Xiuping; Liu, Chang-Gong; Kumar, Dibyendu; Donnelly, Robert; Raymond, Kimiyo; Schuchman, Edward H; Sleat, David E; Lobel, Peter; Xing, Jinchuan
2017-11-01
Lysosomes are membrane-bound, acidic eukaryotic cellular organelles that play important roles in the degradation of macromolecules. Mutations that cause the loss of lysosomal protein function can lead to a group of disorders categorized as the lysosomal storage diseases (LSDs). Suspicion of LSD is frequently based on clinical and pathologic findings, but in some cases, the underlying genetic and biochemical defects remain unknown. Here, we performed whole-exome sequencing (WES) on 14 suspected LSD cases to evaluate the feasibility of using WES for identifying causal mutations. By examining 2,157 candidate genes potentially associated with lysosomal function, we identified eight variants in five genes as candidate disease-causing variants in four individuals. These included both known and novel mutations. Variants were corroborated by targeted sequencing and, when possible, functional assays. In addition, we identified nonsense mutations in two individuals in genes that are not known to have lysosomal function. However, mutations in these genes could have resulted in phenotypes that were diagnosed as LSDs. This study demonstrates that WES can be used to identify causal mutations in suspected LSD cases. We also demonstrate cases where a confounding clinical phenotype may potentially reflect more than one lysosomal protein defect. © 2017 Wiley Periodicals, Inc.
Association of genetic variants of GRIN2B with autism.
Pan, Yongcheng; Chen, Jingjing; Guo, Hui; Ou, Jianjun; Peng, Yu; Liu, Qiong; Shen, Yidong; Shi, Lijuan; Liu, Yalan; Xiong, Zhimin; Zhu, Tengfei; Luo, Sanchuan; Hu, Zhengmao; Zhao, Jingping; Xia, Kun
2015-02-06
Autism (MIM 209850) is a complex neurodevelopmental disorder characterized by social communication impairments and restricted repetitive behaviors. It has a high heritability, although much remains unclear. To evaluate genetic variants of GRIN2B in autism etiology, we performed a system association study of common and rare variants of GRIN2B and autism in cohorts from a Chinese population, involving a total sample of 1,945 subjects. Meta-analysis of a triad family cohort and a case-control cohort identified significant associations of multiple common variants and autism risk (Pmin = 1.73 × 10(-4)). Significantly, the haplotype involved with the top common variants also showed significant association (P = 1.78 × 10(-6)). Sanger sequencing of 275 probands from a triad cohort identified several variants in coding regions, including four common variants and seven rare variants. Two of the common coding variants were located in the autism-related linkage disequilibrium (LD) block, and both were significantly associated with autism (P < 9 × 10(-3)) using an independent control cohort. Burden analysis and case-only analysis of rare coding variants identified by Sanger sequencing did not find this association. Our study for the first time reveals that common variants and related haplotypes of GRIN2B are associated with autism risk.
Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing
2011-07-01
Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.
Theodoratou, Evropi; Farrington, Susan M.; Tenesa, Albert; Dunlop, Malcolm G.; McKeigue, Paul; Campbell, Harry
2013-01-01
Introduction Vitamin D deficiency has been associated with increased risk of colorectal cancer (CRC), but causal relationship has not yet been confirmed. We investigate the direction of causation between vitamin D and CRC by extending the conventional approaches to allow pleiotropic relationships and by explicitly modelling unmeasured confounders. Methods Plasma 25-hydroxyvitamin D (25-OHD), genetic variants associated with 25-OHD and CRC, and other relevant information was available for 2645 individuals (1057 CRC cases and 1588 controls) and included in the model. We investigate whether 25-OHD is likely to be causally associated with CRC, or vice versa, by selecting the best modelling hypothesis according to Bayesian predictive scores. We examine consistency for a range of prior assumptions. Results Model comparison showed preference for the causal association between low 25-OHD and CRC over the reverse causal hypothesis. This was confirmed for posterior mean deviances obtained for both models (11.5 natural log units in favour of the causal model), and also for deviance information criteria (DIC) computed for a range of prior distributions. Overall, models ignoring hidden confounding or pleiotropy had significantly poorer DIC scores. Conclusion Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations. PMID:23717431
Dai, James Y.; Chan, Kwun Chuen Gary; Hsu, Li
2014-01-01
Instrumental variable regression is one way to overcome unmeasured confounding and estimate causal effect in observational studies. Built on structural mean models, there has been considerale work recently developed for consistent estimation of causal relative risk and causal odds ratio. Such models can sometimes suffer from identification issues for weak instruments. This hampered the applicability of Mendelian randomization analysis in genetic epidemiology. When there are multiple genetic variants available as instrumental variables, and causal effect is defined in a generalized linear model in the presence of unmeasured confounders, we propose to test concordance between instrumental variable effects on the intermediate exposure and instrumental variable effects on the disease outcome, as a means to test the causal effect. We show that a class of generalized least squares estimators provide valid and consistent tests of causality. For causal effect of a continuous exposure on a dichotomous outcome in logistic models, the proposed estimators are shown to be asymptotically conservative. When the disease outcome is rare, such estimators are consistent due to the log-linear approximation of the logistic function. Optimality of such estimators relative to the well-known two-stage least squares estimator and the double-logistic structural mean model is further discussed. PMID:24863158
Diogo, Dorothée; Bastarache, Lisa; Liao, Katherine P.; Graham, Robert R.; Fulton, Robert S.; Greenberg, Jeffrey D.; Eyre, Steve; Bowes, John; Cui, Jing; Lee, Annette; Pappas, Dimitrios A.; Kremer, Joel M.; Barton, Anne; Coenen, Marieke J. H.; Franke, Barbara; Kiemeney, Lambertus A.; Mariette, Xavier; Richard-Miceli, Corrine; Canhão, Helena; Fonseca, João E.; de Vries, Niek; Tak, Paul P.; Crusius, J. Bart A.; Nurmohamed, Michael T.; Kurreeman, Fina; Mikuls, Ted R.; Okada, Yukinori; Stahl, Eli A.; Larson, David E.; Deluca, Tracie L.; O'Laughlin, Michelle; Fronick, Catrina C.; Fulton, Lucinda L.; Kosoy, Roman; Ransom, Michael; Bhangale, Tushar R.; Ortmann, Ward; Cagan, Andrew; Gainer, Vivian; Karlson, Elizabeth W.; Kohane, Isaac; Murphy, Shawn N.; Martin, Javier; Zhernakova, Alexandra; Klareskog, Lars; Padyukov, Leonid; Worthington, Jane; Mardis, Elaine R.; Seldin, Michael F.; Gregersen, Peter K.; Behrens, Timothy; Raychaudhuri, Soumya; Denny, Joshua C.; Plenge, Robert M.
2015-01-01
Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3x10-21), A928V (rs35018800, OR = 0.53, P = 1.2x10-9), and I684S (rs12720356, OR = 0.86, P = 4.6x10-7). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6x10-18), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; Pomnibus = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases. PMID:25849893
Diogo, Dorothée; Bastarache, Lisa; Liao, Katherine P; Graham, Robert R; Fulton, Robert S; Greenberg, Jeffrey D; Eyre, Steve; Bowes, John; Cui, Jing; Lee, Annette; Pappas, Dimitrios A; Kremer, Joel M; Barton, Anne; Coenen, Marieke J H; Franke, Barbara; Kiemeney, Lambertus A; Mariette, Xavier; Richard-Miceli, Corrine; Canhão, Helena; Fonseca, João E; de Vries, Niek; Tak, Paul P; Crusius, J Bart A; Nurmohamed, Michael T; Kurreeman, Fina; Mikuls, Ted R; Okada, Yukinori; Stahl, Eli A; Larson, David E; Deluca, Tracie L; O'Laughlin, Michelle; Fronick, Catrina C; Fulton, Lucinda L; Kosoy, Roman; Ransom, Michael; Bhangale, Tushar R; Ortmann, Ward; Cagan, Andrew; Gainer, Vivian; Karlson, Elizabeth W; Kohane, Isaac; Murphy, Shawn N; Martin, Javier; Zhernakova, Alexandra; Klareskog, Lars; Padyukov, Leonid; Worthington, Jane; Mardis, Elaine R; Seldin, Michael F; Gregersen, Peter K; Behrens, Timothy; Raychaudhuri, Soumya; Denny, Joshua C; Plenge, Robert M
2015-01-01
Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3 x 10(-21)), A928V (rs35018800, OR = 0.53, P = 1.2 x 10(-9)), and I684S (rs12720356, OR = 0.86, P = 4.6 x 10(-7)). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6 x 10(-18)), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; P(omnibus) = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases.
de Vries, Tamar I; Monroe, Glen R; van Belzen, Martine J; van der Lans, Christian A; Savelberg, Sanne Mc; Newman, William G; van Haaften, Gijs; Nievelstein, Rutger A; van Haelst, Mieke M
2016-08-01
Rubinstein-Taybi syndrome (RTS, OMIM 180849) and Filippi syndrome (FLPIS, OMIM 272440) are both rare syndromes, with multiple congenital anomalies and intellectual deficit (MCA/ID). We present a patient with intellectual deficit, short stature, bilateral syndactyly of hands and feet, broad thumbs, ocular abnormalities, and dysmorphic facial features. These clinical features suggest both RTS and FLPIS. Initial DNA analysis of DNA isolated from blood did not identify variants to confirm either of these syndrome diagnoses. Whole-exome sequencing identified a homozygous variant in C9orf173, which was novel at the time of analysis. Further Sanger sequencing analysis of FLPIS cases tested negative for CKAP2L variants did not, however, reveal any further variants. Subsequent analysis using DNA isolated from buccal mucosa revealed a mosaic variant in CREBBP. This report highlights the importance of excluding mosaic variants in patients with a strong but atypical clinical presentation of a MCA/ID syndrome if no disease-causing variants can be detected in DNA isolated from blood samples. As the striking syndactyly observed in the present case is typical for FLPIS, we suggest CREBBP analysis in saliva samples for FLPIS syndrome cases in which no causal CKAP2L variant is detected.
Gene-environment interplay in the etiology of psychosis.
Zwicker, Alyson; Denovan-Wright, Eileen M; Uher, Rudolf
2018-01-15
Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene-environment interactions. Only a few specific gene-environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene-environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.
A Single IGF1 Allele Is a Major Determinant of Small Size in Dogs
Sutter, Nathan B.; Bustamante, Carlos D.; Chase, Kevin; Gray, Melissa M.; Zhao, Keyan; Zhu, Lan; Padhukasahasram, Badri; Karlins, Eric; Davis, Sean; Jones, Paul G.; Quignon, Pascale; Johnson, Gary S.; Parker, Heidi G.; Fretwell, Neale; Mosher, Dana S.; Lawler, Dennis F.; Satyaraj, Ebenezer; Nordborg, Magnus; Lark, K. Gordon; Wayne, Robert K.; Ostrander, Elaine A.
2009-01-01
The domestic dog exhibits greater diversity in body size than any other terrestrial vertebrate. We used a strategy that exploits the breed structure of dogs to investigate the genetic basis of size. First, through a genome-wide scan, we identified a major quantitative trait locus (QTL) on chromosome 15 influencing size variation within a single breed. Second, we examined genetic variation in the 15-megabase interval surrounding the QTL in small and giant breeds and found marked evidence for a selective sweep spanning a single gene (IGF1), encoding insulin-like growth factor 1. A single IGF1 single-nucleotide polymorphism haplotype is common to all small breeds and nearly absent from giant breeds, suggesting that the same causal sequence variant is a major contributor to body size in all small dogs. PMID:17412960
A single IGF1 allele is a major determinant of small size in dogs.
Sutter, Nathan B; Bustamante, Carlos D; Chase, Kevin; Gray, Melissa M; Zhao, Keyan; Zhu, Lan; Padhukasahasram, Badri; Karlins, Eric; Davis, Sean; Jones, Paul G; Quignon, Pascale; Johnson, Gary S; Parker, Heidi G; Fretwell, Neale; Mosher, Dana S; Lawler, Dennis F; Satyaraj, Ebenezer; Nordborg, Magnus; Lark, K Gordon; Wayne, Robert K; Ostrander, Elaine A
2007-04-06
The domestic dog exhibits greater diversity in body size than any other terrestrial vertebrate. We used a strategy that exploits the breed structure of dogs to investigate the genetic basis of size. First, through a genome-wide scan, we identified a major quantitative trait locus (QTL) on chromosome 15 influencing size variation within a single breed. Second, we examined genetic variation in the 15-megabase interval surrounding the QTL in small and giant breeds and found marked evidence for a selective sweep spanning a single gene (IGF1), encoding insulin-like growth factor 1. A single IGF1 single-nucleotide polymorphism haplotype is common to all small breeds and nearly absent from giant breeds, suggesting that the same causal sequence variant is a major contributor to body size in all small dogs.
GDNF Gene Is Associated With Tourette Syndrome in a Family Study
Huertas-Fernández, Ismael; Gómez-Garre, Pilar; Madruga-Garrido, Marcos; Bernal-Bernal, Inmaculada; Bonilla-Toribio, Marta; Martín-Rodríguez, Juan Francisco; Cáceres-Redondo, María Teresa; Vargas-González, Laura; Carrillo, Fátima; Pascual, Alberto; Tischfield, Jay A.; King, Robert A.; Heiman, Gary A.; Mir, Pablo
2016-01-01
Background Tourette syndrome is a disorder characterized by persistent motor and vocal tics, and frequently accompanied by the comorbidities attention deficit hyperactivity disorder and obsessive-compulsive disorder. Impaired synaptic neurotransmission has been implicated in its pathogenesis. Our aim was to investigate the association of 28 candidate genes, including genes related to synaptic neurotransmission and neurotrophic factors, with Tourette syndrome. Methods We genotyped 506 polymorphisms in a discovery cohort from the United States composed of 112 families and 47 unrelated singletons with Tourette syndrome (201 cases and 253 controls). Genes containing significant polymorphisms were imputed to fine-map the signal(s) to potential causal variants. Allelic analyses in Tourette syndrome cases were performed to check the role in attention deficit hyperactivity disorder and obsessive-compulsive disorder comorbidities. Target polymorphisms were further studied in a replication cohort from southern Spain composed of 37 families and three unrelated singletons (44 cases and 73 controls). Results The polymorphism rs3096140 in glial cell line–derived neurotrophic factor gene (GDNF) was significant in the discovery cohort after correction (P = 1.5 × 10−4). No linkage disequilibrium was found between rs3096140 and other functional variants in the gene. We selected rs3096140 as target polymorphism, and the association was confirmed in the replication cohort (P = 0.01). No association with any comorbidity was found. Conclusions As a conclusion, a common genetic variant in GDNF is associated with Tourette syndrome. A defect in the production of GDNF could compromise the survival of parvalbumin interneurons, thus altering the excitatory/inhibitory balance in the corticostriatal circuitry. Validation of this variant in other family cohorts is necessary. PMID:26096985
GDNF gene is associated with tourette syndrome in a family study.
Huertas-Fernández, Ismael; Gómez-Garre, Pilar; Madruga-Garrido, Marcos; Bernal-Bernal, Inmaculada; Bonilla-Toribio, Marta; Martín-Rodríguez, Juan Francisco; Cáceres-Redondo, María Teresa; Vargas-González, Laura; Carrillo, Fátima; Pascual, Alberto; Tischfield, Jay A; King, Robert A; Heiman, Gary A; Mir, Pablo
2015-07-01
Tourette syndrome is a disorder characterized by persistent motor and vocal tics, and frequently accompanied by the comorbidities attention deficit hyperactivity disorder and obsessive-compulsive disorder. Impaired synaptic neurotransmission has been implicated in its pathogenesis. Our aim was to investigate the association of 28 candidate genes, including genes related to synaptic neurotransmission and neurotrophic factors, with Tourette syndrome. We genotyped 506 polymorphisms in a discovery cohort from the United States composed of 112 families and 47 unrelated singletons with Tourette syndrome (201 cases and 253 controls). Genes containing significant polymorphisms were imputed to fine-map the signal(s) to potential causal variants. Allelic analyses in Tourette syndrome cases were performed to check the role in attention deficit hyperactivity disorder and obsessive-compulsive disorder comorbidities. Target polymorphisms were further studied in a replication cohort from southern Spain composed of 37 families and three unrelated singletons (44 cases and 73 controls). The polymorphism rs3096140 in glial cell line-derived neurotrophic factor gene (GDNF) was significant in the discovery cohort after correction (P = 1.5 × 10(-4) ). No linkage disequilibrium was found between rs3096140 and other functional variants in the gene. We selected rs3096140 as target polymorphism, and the association was confirmed in the replication cohort (P = 0.01). No association with any comorbidity was found. As a conclusion, a common genetic variant in GDNF is associated with Tourette syndrome. A defect in the production of GDNF could compromise the survival of parvalbumin interneurons, thus altering the excitatory/inhibitory balance in the corticostriatal circuitry. Validation of this variant in other family cohorts is necessary. © 2015 International Parkinson and Movement Disorder Society.
CD44 Splice Variants as Potential Players in Alzheimer's Disease Pathology.
Pinner, Elhanan; Gruper, Yaron; Ben Zimra, Micha; Kristt, Don; Laudon, Moshe; Naor, David; Zisapel, Nava
2017-01-01
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive deficits, deposition of amyloid-β (Aβ) plaques, intracellular neurofibrillary tangles, and neuronal cell death. Neuroinflammation is commonly believed to participate in AD pathogenesis. CD44 is an inflammation-related gene encoding a widely-distributed family of alternatively spliced cell surface glycoproteins that have been implicated in inflammation, metastases, and inflammation-linked neuronal injuries. Here we investigated the expression patterns of CD44S (which does not contain any alternative exon) and CD44 splice variants in postmortem hippocampal samples from AD patients and matched non-AD controls. The expression of CD44S and CD44 splice variants CD44V3, CD44V6, and CD44V10 was significantly higher in AD patients compared to non-AD controls. Immunohistochemistry of human hippocampal sections revealed that CD44S differentially localized to neuritic plaques and astrocytes, whereas CD44V3, CD44V6, and CD44V10 expression was mostly neuronal. Consistent with these findings, we found that the expression of CD44V6 and CD44V10 was induced by Aβ peptide in neuroblastoma cells and primary neurons. Furthermore, in loss of function studies we found that both CD44V10-specific siRNA and CD44V10 antibody protected neuronal cells from Aβ-induced toxicity, suggesting a causal relationship between CD44V10 and neuronal cell death. These data indicate that certain CD44 splice variants contribute to AD pathology and that CD44V10 inhibition may serve as a new neuroprotective treatment strategy for this disease.
Wang, Xulong; Philip, Vivek M.; Ananda, Guruprasad; White, Charles C.; Malhotra, Ankit; Michalski, Paul J.; Karuturi, Krishna R. Murthy; Chintalapudi, Sumana R.; Acklin, Casey; Sasner, Michael; Bennett, David A.; De Jager, Philip L.; Howell, Gareth R.; Carter, Gregory W.
2018-01-01
Recent technical and methodological advances have greatly enhanced genome-wide association studies (GWAS). The advent of low-cost, whole-genome sequencing facilitates high-resolution variant identification, and the development of linear mixed models (LMM) allows improved identification of putatively causal variants. While essential for correcting false positive associations due to sample relatedness and population stratification, LMMs have commonly been restricted to quantitative variables. However, phenotypic traits in association studies are often categorical, coded as binary case-control or ordered variables describing disease stages. To address these issues, we have devised a method for genomic association studies that implements a generalized LMM (GLMM) in a Bayesian framework, called Bayes-GLMM. Bayes-GLMM has four major features: (1) support of categorical, binary, and quantitative variables; (2) cohesive integration of previous GWAS results for related traits; (3) correction for sample relatedness by mixed modeling; and (4) model estimation by both Markov chain Monte Carlo sampling and maximal likelihood estimation. We applied Bayes-GLMM to the whole-genome sequencing cohort of the Alzheimer’s Disease Sequencing Project. This study contains 570 individuals from 111 families, each with Alzheimer’s disease diagnosed at one of four confidence levels. Using Bayes-GLMM we identified four variants in three loci significantly associated with Alzheimer’s disease. Two variants, rs140233081 and rs149372995, lie between PRKAR1B and PDGFA. The coded proteins are localized to the glial-vascular unit, and PDGFA transcript levels are associated with Alzheimer’s disease-related neuropathology. In summary, this work provides implementation of a flexible, generalized mixed-model approach in a Bayesian framework for association studies. PMID:29507048
Genetic Variants Associated with Circulating Parathyroid Hormone
Lutsey, Pamela L.; Kleber, Marcus E.; Nielson, Carrie M.; Mitchell, Braxton D.; Bis, Joshua C.; Eny, Karen M.; Portas, Laura; Eriksson, Joel; Lorentzon, Mattias; Koller, Daniel L.; Milaneschi, Yuri; Teumer, Alexander; Pilz, Stefan; Nethander, Maria; Selvin, Elizabeth; Tang, Weihong; Weng, Lu-Chen; Wong, Hoi Suen; Lai, Dongbing; Peacock, Munro; Hannemann, Anke; Völker, Uwe; Homuth, Georg; Nauk, Matthias; Murgia, Federico; Pattee, Jack W.; Orwoll, Eric; Zmuda, Joseph M.; Riancho, Jose Antonio; Wolf, Myles; Williams, Frances; Penninx, Brenda; Econs, Michael J.; Ryan, Kathleen A.; Ohlsson, Claes; Paterson, Andrew D.; Psaty, Bruce M.; Siscovick, David S.; Rotter, Jerome I.; Pirastu, Mario; Streeten, Elizabeth; März, Winfried; Fox, Caroline; Coresh, Josef; Wallaschofski, Henri; Pankow, James S.; de Boer, Ian H.; Kestenbaum, Bryan
2017-01-01
Parathyroid hormone (PTH) is a primary calcium regulatory hormone. Elevated serum PTH concentrations in primary and secondary hyperparathyroidism have been associated with bone disease, hypertension, and in some studies, cardiovascular mortality. Genetic causes of variation in circulating PTH concentrations are incompletely understood. We performed a genome-wide association study of serum PTH concentrations among 29,155 participants of European ancestry from 13 cohort studies (n=22,653 and n=6502 in discovery and replication analyses, respectively). We evaluated the association of single nucleotide polymorphisms (SNPs) with natural log-transformed PTH concentration adjusted for age, sex, season, study site, and principal components of ancestry. We discovered associations of SNPs from five independent regions with serum PTH concentration, including the strongest association with rs6127099 upstream of CYP24A1 (P=4.2 × 10−53), a gene that encodes the primary catabolic enzyme for 1,25-dihydroxyvitamin D and 25-dihydroxyvitamin D. Each additional copy of the minor allele at this SNP associated with 7% higher serum PTH concentration. The other SNPs associated with serum PTH concentration included rs4074995 within RGS14 (P=6.6 × 10−17), rs219779 adjacent to CLDN14 (P=3.5 × 10−16), rs4443100 near RTDR1 (P=8.7 × 10−9), and rs73186030 near CASR (P=4.8 × 10−8). Of these five SNPs, rs6127099, rs4074995, and rs219779 replicated. Thus, common genetic variants located near genes involved in vitamin D metabolism and calcium and renal phosphate transport associated with differences in circulating PTH concentrations. Future studies could identify the causal variants at these loci, and the clinical and functional relevance of these variants should be pursued. PMID:27927781
Genetic Variants Associated with Circulating Parathyroid Hormone.
Robinson-Cohen, Cassianne; Lutsey, Pamela L; Kleber, Marcus E; Nielson, Carrie M; Mitchell, Braxton D; Bis, Joshua C; Eny, Karen M; Portas, Laura; Eriksson, Joel; Lorentzon, Mattias; Koller, Daniel L; Milaneschi, Yuri; Teumer, Alexander; Pilz, Stefan; Nethander, Maria; Selvin, Elizabeth; Tang, Weihong; Weng, Lu-Chen; Wong, Hoi Suen; Lai, Dongbing; Peacock, Munro; Hannemann, Anke; Völker, Uwe; Homuth, Georg; Nauk, Matthias; Murgia, Federico; Pattee, Jack W; Orwoll, Eric; Zmuda, Joseph M; Riancho, Jose Antonio; Wolf, Myles; Williams, Frances; Penninx, Brenda; Econs, Michael J; Ryan, Kathleen A; Ohlsson, Claes; Paterson, Andrew D; Psaty, Bruce M; Siscovick, David S; Rotter, Jerome I; Pirastu, Mario; Streeten, Elizabeth; März, Winfried; Fox, Caroline; Coresh, Josef; Wallaschofski, Henri; Pankow, James S; de Boer, Ian H; Kestenbaum, Bryan
2017-05-01
Parathyroid hormone (PTH) is a primary calcium regulatory hormone. Elevated serum PTH concentrations in primary and secondary hyperparathyroidism have been associated with bone disease, hypertension, and in some studies, cardiovascular mortality. Genetic causes of variation in circulating PTH concentrations are incompletely understood. We performed a genome-wide association study of serum PTH concentrations among 29,155 participants of European ancestry from 13 cohort studies ( n =22,653 and n =6502 in discovery and replication analyses, respectively). We evaluated the association of single nucleotide polymorphisms (SNPs) with natural log-transformed PTH concentration adjusted for age, sex, season, study site, and principal components of ancestry. We discovered associations of SNPs from five independent regions with serum PTH concentration, including the strongest association with rs6127099 upstream of CYP24A1 ( P =4.2 × 10 -53 ), a gene that encodes the primary catabolic enzyme for 1,25-dihydroxyvitamin D and 25-dihydroxyvitamin D. Each additional copy of the minor allele at this SNP associated with 7% higher serum PTH concentration. The other SNPs associated with serum PTH concentration included rs4074995 within RGS14 ( P =6.6 × 10 -17 ), rs219779 adjacent to CLDN14 ( P =3.5 × 10 -16 ), rs4443100 near RTDR1 ( P =8.7 × 10 -9 ), and rs73186030 near CASR ( P =4.8 × 10 -8 ). Of these five SNPs, rs6127099, rs4074995, and rs219779 replicated. Thus, common genetic variants located near genes involved in vitamin D metabolism and calcium and renal phosphate transport associated with differences in circulating PTH concentrations. Future studies could identify the causal variants at these loci, and the clinical and functional relevance of these variants should be pursued. Copyright © 2017 by the American Society of Nephrology.
TCF7L2 is a master regulator of insulin production and processing.
Zhou, Yuedan; Park, Soo-Young; Su, Jing; Bailey, Kathleen; Ottosson-Laakso, Emilia; Shcherbina, Liliya; Oskolkov, Nikolay; Zhang, Enming; Thevenin, Thomas; Fadista, João; Bennet, Hedvig; Vikman, Petter; Wierup, Nils; Fex, Malin; Rung, Johan; Wollheim, Claes; Nobrega, Marcelo; Renström, Erik; Groop, Leif; Hansson, Ola
2014-12-15
Genome-wide association studies have revealed >60 loci associated with type 2 diabetes (T2D), but the underlying causal variants and functional mechanisms remain largely elusive. Although variants in TCF7L2 confer the strongest risk of T2D among common variants by presumed effects on islet function, the molecular mechanisms are not yet well understood. Using RNA-sequencing, we have identified a TCF7L2-regulated transcriptional network responsible for its effect on insulin secretion in rodent and human pancreatic islets. ISL1 is a primary target of TCF7L2 and regulates proinsulin production and processing via MAFA, PDX1, NKX6.1, PCSK1, PCSK2 and SLC30A8, thereby providing evidence for a coordinated regulation of insulin production and processing. The risk T-allele of rs7903146 was associated with increased TCF7L2 expression, and decreased insulin content and secretion. Using gene expression profiles of 66 human pancreatic islets donors', we also show that the identified TCF7L2-ISL1 transcriptional network is regulated in a genotype-dependent manner. Taken together, these results demonstrate that not only synthesis of proinsulin is regulated by TCF7L2 but also processing and possibly clearance of proinsulin and insulin. These multiple targets in key pathways may explain why TCF7L2 has emerged as the gene showing one of the strongest associations with T2D. © The Author 2014. Published by Oxford University Press.
Bernardinelli, Emanuele; Nofziger, Charity; Patsch, Wolfgang; Rasp, Gerd; Paulmichl, Markus; Dossena, Silvia
2018-01-01
The prevalence and spectrum of sequence alterations in the SLC26A4 gene, which codes for the anion exchanger pendrin, are population-specific and account for at least 50% of cases of non-syndromic hearing loss associated with an enlarged vestibular aqueduct. A cohort of nineteen patients from Austria with hearing loss and a radiological alteration of the vestibular aqueduct underwent Sanger sequencing of SLC26A4 and GJB2, coding for connexin 26. The pathogenicity of sequence alterations detected was assessed by determining ion transport and molecular features of the corresponding SLC26A4 protein variants. In this group, four uncharacterized sequence alterations within the SLC26A4 coding region were found. Three of these lead to protein variants with abnormal functional and molecular features, while one should be considered with no pathogenic potential. Pathogenic SLC26A4 sequence alterations were only found in 12% of patients. SLC26A4 sequence alterations commonly found in other Caucasian populations were not detected. This survey represents the first study on the prevalence and spectrum of SLC26A4 sequence alterations in an Austrian cohort and further suggests that genetic testing should always be integrated with functional characterization and determination of the molecular features of protein variants in order to unequivocally identify or exclude a causal link between genotype and phenotype. PMID:29320412
Verweij, Karin J H; Treur, Jorien L; Vink, Jacqueline M
2018-07-01
Epidemiological studies consistently show co-occurrence of use of different addictive substances. Whether these associations are causal or due to overlapping underlying influences remains an important question in addiction research. Methodological advances have made it possible to use published genetic associations to infer causal relationships between phenotypes. In this exploratory study, we used Mendelian randomization (MR) to examine the causality of well-established associations between nicotine, alcohol, caffeine and cannabis use. Two-sample MR was employed to estimate bidirectional causal effects between four addictive substances: nicotine (smoking initiation and cigarettes smoked per day), caffeine (cups of coffee per day), alcohol (units per week) and cannabis (initiation). Based on existing genome-wide association results we selected genetic variants associated with the exposure measure as an instrument to estimate causal effects. Where possible we applied sensitivity analyses (MR-Egger and weighted median) more robust to horizontal pleiotropy. Most MR tests did not reveal causal associations. There was some weak evidence for a causal positive effect of genetically instrumented alcohol use on smoking initiation and of cigarettes per day on caffeine use, but these were not supported by the sensitivity analyses. There was also some suggestive evidence for a positive effect of alcohol use on caffeine use (only with MR-Egger) and smoking initiation on cannabis initiation (only with weighted median). None of the suggestive causal associations survived corrections for multiple testing. Two-sample Mendelian randomization analyses found little evidence for causal relationships between nicotine, alcohol, caffeine and cannabis use. © 2018 Society for the Study of Addiction.
Different Kinds of Causality in Event Cognition
ERIC Educational Resources Information Center
Radvansky, Gabriel A.; Tamplin, Andrea K.; Armendarez, Joseph; Thompson, Alexis N.
2014-01-01
Narrative memory is better for information that is more causally connected and occurs at event boundaries, such as a causal break. However, it is unclear whether there are common or distinct influences of causality. For the event boundaries that arise as a result of causal breaks, the events that follow may subsequently become more causally…
Lozano, Reymundo; Vino, Arianna; Lozano, Cristina; Fisher, Simon E; Deriziotis, Pelagia
2015-12-01
FOXP1 (forkhead box protein P1) is a transcription factor involved in the development of several tissues, including the brain. An emerging phenotype of patients with protein-disrupting FOXP1 variants includes global developmental delay, intellectual disability and mild to severe speech/language deficits. We report on a female child with a history of severe hypotonia, autism spectrum disorder and mild intellectual disability with severe speech/language impairment. Clinical exome sequencing identified a heterozygous de novo FOXP1 variant c.1267_1268delGT (p.V423Hfs*37). Functional analyses using cellular models show that the variant disrupts multiple aspects of FOXP1 activity, including subcellular localization and transcriptional repression properties. Our findings highlight the importance of performing functional characterization to help uncover the biological significance of variants identified by genomics approaches, thereby providing insight into pathways underlying complex neurodevelopmental disorders. Moreover, our data support the hypothesis that de novo variants represent significant causal factors in severe sporadic disorders and extend the phenotype seen in individuals with FOXP1 haploinsufficiency.
Obesity and peripheral arterial disease: A Mendelian Randomization analysis.
Huang, Ya; Xu, Min; Xie, Lan; Wang, Tiange; Huang, Xiaolin; Lv, Xiaofei; Chen, Ying; Ding, Lin; Lin, Lin; Wang, Weiqing; Bi, Yufang; Sun, Yimin; Zhang, Yifei; Ning, Guang
2016-04-01
Observational studies showed that obesity is a major risk factor for peripheral arterial disease (PAD). However, conventional epidemiology studies are vulnerable to residual bias from confounding factors. We aimed to explore the causality of obesity in development of PAD using Mendelian Randomization (MR) approach. A MR analysis was performed in 11,477 community-dwelling adults aged 40 years and above recruited from two nearby communities during 2011-2013 in Shanghai, China. We genotyped 14 body mass index (BMI) associated common variants identified and validated in East Asians. PAD was defined as ankle-to-brachial index (ABI) <0.90 or >1.40. Weighted BMI genetic risk score (GRS) was used as the Instrumental Variable (IV). After adjusted for confounding factors, we found that each standard deviation (SD, 2.76 points) increase in BMI-GRS was associated with 0.43 (95% confidence interval [CI]: 0.36-0.49) kg/m(2) increase in BMI (P < 0.0001) and an odds ratio (OR) for PAD of 1.17 (95% CI: 1.07-1.27; P = 0.0004). Compared with the lowest quartile of BMI-GRS, the second, third and highest quartile associated with 9%, 19% and 45% increment of PAD risk, respectively (P for trend = 0.002). In the MR analysis, we demonstrated a causal relationship between obesity and PAD (OR = 1.44 per BMI-unit, 95% CI: 1.18-1.75; P = 0.0003). This study suggested that obesity may be causally associated with PAD after controlling for the potential intermediate factors like hypertension, dyslipidemia and hyperglycemia. Copyright © 2016. Published by Elsevier Ireland Ltd.
Lintas, Carla; Picinelli, Chiara; Piras, Ignazio Stefano; Sacco, Roberto; Brogna, Claudia; Persico, Antonio M
2017-03-17
Autism Spectrum Disorder (ASD) is endowed with impressive heritability estimates and high recurrence rates. Its genetic underpinnings are nonetheless very heterogeneous, with common, and rare contributing variants located in hundreds of different loci, each characterized by variable levels of penetrance. Multiplex families from single ethnic groups represent a useful means to reduce heterogeneity and enhance genetic load. We screened 19 Italian ASD multiplex families (3 triplets and 16 duplets, total N = 41 ASD subjects), using array-CGH (Agilent 180 K). Causal or ASD-relevant CNVs were detected in 36.6% (15/41) of ASD probands, corresponding to 36.8% (7/19) multiplex families with at least one affected sibling genetically positive. However, only in less than half (3/7) of positive families, affected siblings share the same causal or ASD-relevant CNV. Even in these three families, additional potentially relevant CNVs not shared by affected sib pairs were also detected. These results provide further evidence of genetic heterogeneity in ASD even within multiplex families belonging to a single ethnic group. Differences in CNV burden may likely contribute to the substantial clinical heterogeneity observed between affected siblings. In addition, Gene Ontology enrichment analysis indicates that most potentially causal or relevant ASD genes detected in our cohort belong to nervous system-specific categories, especially involved in neurite elongation and synaptic structure/function. These findings point toward the existence of genomic instability in these families, whose underlying genetic and epigenetic mechanisms deserve further scrutiny. © 2017 Wiley Periodicals, Inc.
Utilising family-based designs for detecting rare variant disease associations.
Preston, Mark D; Dudbridge, Frank
2014-03-01
Rare genetic variants are thought to be important components in the causality of many diseases but discovering these associations is challenging. We demonstrate how best to use family-based designs to improve the power to detect rare variant disease associations. We show that using genetic data from enriched families (those pedigrees with greater than one affected member) increases the power and sensitivity of existing case-control rare variant tests. However, we show that transmission- (or within-family-) based tests do not benefit from this enrichment. This means that, in studies where a limited amount of genotyping is available, choosing a single case from each of many pedigrees has greater power than selecting multiple cases from fewer pedigrees. Finally, we show how a pseudo-case-control design allows a greater range of statistical tests to be applied to family data. © 2014 The Authors. Annals of Human Genetics published by John Wiley & Sons Ltd/University College London.
Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.
Fairfax, Benjamin P; Humburg, Peter; Makino, Seiko; Naranbhai, Vivek; Wong, Daniel; Lau, Evelyn; Jostins, Luke; Plant, Katharine; Andrews, Robert; McGee, Chris; Knight, Julian C
2014-03-07
To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.
USDA-ARS?s Scientific Manuscript database
Many studies leverage targeted whole genome sequencing (WGS) experiments in order to identify rare and causal variants within populations. As a natural consequence of experimental design, many of these surveys tend to sequence redundant haplotype segments due to high frequency in the base population...
Serum iron level and kidney function: a Mendelian randomization study.
Del Greco M, Fabiola; Foco, Luisa; Pichler, Irene; Eller, Philipp; Eller, Kathrin; Benyamin, Beben; Whitfield, John B; Pramstaller, Peter P; Thompson, John R; Pattaro, Cristian; Minelli, Cosetta
2017-02-01
Iron depletion is a known consequence of chronic kidney disease (CKD), but there is contradicting epidemiological evidence on whether iron itself affects kidney function and whether its effect is protective or detrimental in the general population. While epidemiological studies tend to be affected by confounding and reverse causation, Mendelian randomization (MR) can provide unconfounded estimates of causal effects by using genes as instruments. We performed an MR study of the effect of serum iron levels on estimated glomerular filtration rate (eGFR), using genetic variants known to be associated with iron. MR estimates of the effect of iron on eGFR were derived based on the association of each variant with iron and eGFR from two large genome-wide meta-analyses on 48 978 and 74 354 individuals. We performed a similar MR analysis for ferritin, which measures iron stored in the body, using variants associated with ferritin. A combined MR estimate across all variants showed a 1.3% increase in eGFR per standard deviation increase in iron (95% confidence interval 0.4–2.1%; P = 0.004). The results for ferritin were consistent with those for iron. Secondary MR analyses of the effects of iron and ferritin on CKD did not show significant associations but had very low statistical power. Our study suggests a protective effect of iron on kidney function in the general population. Further research is required to confirm this causal association, investigate it in study populations at higher risk of CKD and explore its underlying mechanism of action.
Novel mutation in the CHST6 gene causes macular corneal dystrophy in a black South African family.
Carstens, Nadia; Williams, Susan; Goolam, Saadiah; Carmichael, Trevor; Cheung, Ming Sin; Büchmann-Møller, Stine; Sultan, Marc; Staedtler, Frank; Zou, Chao; Swart, Peter; Rice, Dennis S; Lacoste, Arnaud; Paes, Kim; Ramsay, Michèle
2016-07-20
Macular corneal dystrophy (MCD) is a rare autosomal recessive disorder that is characterized by progressive corneal opacity that starts in early childhood and ultimately progresses to blindness in early adulthood. The aim of this study was to identify the cause of MCD in a black South African family with two affected sisters. A multigenerational South African Sotho-speaking family with type I MCD was studied using whole exome sequencing. Variant filtering to identify the MCD-causal mutation included the disease inheritance pattern, variant minor allele frequency and potential functional impact. Ophthalmologic evaluation of the cases revealed a typical MCD phenotype and none of the other family members were affected. An average of 127 713 variants per individual was identified following exome sequencing and approximately 1.2 % were not present in any of the investigated public databases. Variant filtering identified a homozygous E71Q mutation in CHST6, a known MCD-causing gene encoding corneal N-acetyl glucosamine-6-O-sulfotransferase. This E71Q mutation results in a non-conservative amino acid change in a highly conserved functional domain of the human CHST6 that is essential for enzyme activity. We identified a novel E71Q mutation in CHST6 as the MCD-causal mutation in a black South African family with type I MCD. This is the first description of MCD in a black Sub-Saharan African family and therefore contributes valuable insights into the genetic aetiology of this disease, while improving genetic counselling for this and potentially other MCD families.
Arsenault, Benoit J; Boekholdt, S Matthijs; Dubé, Marie-Pierre; Rhéaume, Eric; Wareham, Nicholas J; Khaw, Kay-Tee; Sandhu, Manjinder S; Tardif, Jean-Claude
2014-06-01
Although a previous study has suggested that a genetic variant in the LPA region was associated with the presence of aortic valve stenosis (AVS), no prospective study has suggested a role for lipoprotein(a) levels in the pathophysiology of AVS. Our objective was to determine whether lipoprotein(a) levels and a common genetic variant that is strongly associated with lipoprotein(a) levels are associated with an increased risk of developing AVS. Serum lipoprotein(a) levels were measured in 17 553 participants of the European Prospective Investigation into Cancer (EPIC)-Norfolk study. Among these study participants, 118 developed AVS during a mean follow-up of 11.7 years. The rs10455872 genetic variant in LPA was genotyped in 14 735 study participants, who simultaneously had lipoprotein(a) level measurements, and in a replication study of 379 patients with echocardiography-confirmed AVS and 404 controls. In EPIC-Norfolk, compared with participants in the bottom lipoprotein(a) tertile, those in the top lipoprotein(a) tertile had a higher risk of AVS (hazard ratio, 1.57; 95% confidence interval, 1.02-2.42) after adjusting for age, sex, and smoking. Compared with rs10455872 AA homozygotes, carriers of 1 or 2 G alleles were at increased risk of AVS (hazard ratio, 1.78; 95% confidence interval, 1.11-2.87, versus hazard ratio, 4.83; 95% confidence interval, 1.77-13.20, respectively). In the replication study, the genetic variant rs10455872 also showed a positive association with AVS (odds ratio, 1.57; 95% confidence interval, 1.10-2.26). Patients with high lipoprotein(a) levels are at increased risk for AVS. The rs10455872 variant, which is associated with higher lipoprotein(a) levels, is also associated with increased risk of AVS, suggesting that this association may be causal. © 2014 American Heart Association, Inc.
Grarup, Niels; Rivas, Manuel A; Mahajan, Anubha; Locke, Adam E; Cingolani, Pablo; Pers, Tune H; Viñuela, Ana; Brown, Andrew A; Wu, Ying; Flannick, Jason; Fuchsberger, Christian; Gamazon, Eric R; Gaulton, Kyle J; Im, Hae Kyung; Teslovich, Tanya M; Blackwell, Thomas W; Bork-Jensen, Jette; Burtt, Noël P; Chen, Yuhui; Green, Todd; Hartl, Christopher; Kang, Hyun Min; Kumar, Ashish; Ladenvall, Claes; Ma, Clement; Moutsianas, Loukas; Pearson, Richard D; Perry, John R B; Rayner, N William; Robertson, Neil R; Scott, Laura J; van de Bunt, Martijn; Eriksson, Johan G; Jula, Antti; Koskinen, Seppo; Lehtimäki, Terho; Palotie, Aarno; Raitakari, Olli T; Jacobs, Suzanne BR; Wessel, Jennifer; Chu, Audrey Y; Scott, Robert A; Goodarzi, Mark O; Blancher, Christine; Buck, Gemma; Buck, David; Chines, Peter S; Gabriel, Stacey; Gjesing, Anette P; Groves, Christopher J; Hollensted, Mette; Huyghe, Jeroen R; Jackson, Anne U; Jun, Goo; Justesen, Johanne Marie; Mangino, Massimo; Murphy, Jacquelyn; Neville, Matt; Onofrio, Robert; Small, Kerrin S; Stringham, Heather M; Trakalo, Joseph; Banks, Eric; Carey, Jason; Carneiro, Mauricio O; DePristo, Mark; Farjoun, Yossi; Fennell, Timothy; Goldstein, Jacqueline I; Grant, George; de Angelis, Martin Hrabé; Maguire, Jared; Neale, Benjamin M; Poplin, Ryan; Purcell, Shaun; Schwarzmayr, Thomas; Shakir, Khalid; Smith, Joshua D; Strom, Tim M; Wieland, Thomas; Lindstrom, Jaana; Brandslund, Ivan; Christensen, Cramer; Surdulescu, Gabriela L; Lakka, Timo A; Doney, Alex S F; Nilsson, Peter; Wareham, Nicholas J; Langenberg, Claudia; Varga, Tibor V; Franks, Paul W; Rolandsson, Olov; Rosengren, Anders H; Farook, Vidya S; Thameem, Farook; Puppala, Sobha; Kumar, Satish; Lehman, Donna M; Jenkinson, Christopher P; Curran, Joanne E; Hale, Daniel Esten; Fowler, Sharon P; Arya, Rector; DeFronzo, Ralph A; Abboud, Hanna E; Syvänen, Ann-Christine; Hicks, Pamela J; Palmer, Nicholette D; Ng, Maggie C Y; Bowden, Donald W; Freedman, Barry I; Esko, Tõnu; Mägi, Reedik; Milani, Lili; Mihailov, Evelin; Metspalu, Andres; Narisu, Narisu; Kinnunen, Leena; Bonnycastle, Lori L; Swift, Amy; Pasko, Dorota; Wood, Andrew R; Fadista, João; Pollin, Toni I; Barzilai, Nir; Atzmon, Gil; Glaser, Benjamin; Thorand, Barbara; Strauch, Konstantin; Peters, Annette; Roden, Michael; Müller-Nurasyid, Martina; Liang, Liming; Kriebel, Jennifer; Illig, Thomas; Grallert, Harald; Gieger, Christian; Meisinger, Christa; Lannfelt, Lars; Musani, Solomon K; Griswold, Michael; Taylor, Herman A; Wilson, Gregory; Correa, Adolfo; Oksa, Heikki; Scott, William R; Afzal, Uzma; Tan, Sian-Tsung; Loh, Marie; Chambers, John C; Sehmi, Jobanpreet; Kooner, Jaspal Singh; Lehne, Benjamin; Cho, Yoon Shin; Lee, Jong-Young; Han, Bok-Ghee; Käräjämäki, Annemari; Qi, Qibin; Qi, Lu; Huang, Jinyan; Hu, Frank B; Melander, Olle; Orho-Melander, Marju; Below, Jennifer E; Aguilar, David; Wong, Tien Yin; Liu, Jianjun; Khor, Chiea-Chuen; Chia, Kee Seng; Lim, Wei Yen; Cheng, Ching-Yu; Chan, Edmund; Tai, E Shyong; Aung, Tin; Linneberg, Allan; Isomaa, Bo; Meitinger, Thomas; Tuomi, Tiinamaija; Hakaste, Liisa; Kravic, Jasmina; Jørgensen, Marit E; Lauritzen, Torsten; Deloukas, Panos; Stirrups, Kathleen E; Owen, Katharine R; Farmer, Andrew J; Frayling, Timothy M; O'Rahilly, Stephen P; Walker, Mark; Levy, Jonathan C; Hodgkiss, Dylan; Hattersley, Andrew T; Kuulasmaa, Teemu; Stančáková, Alena; Barroso, Inês; Bharadwaj, Dwaipayan; Chan, Juliana; Chandak, Giriraj R; Daly, Mark J; Donnelly, Peter J; Ebrahim, Shah B; Elliott, Paul; Fingerlin, Tasha; Froguel, Philippe; Hu, Cheng; Jia, Weiping; Ma, Ronald C W; McVean, Gilean; Park, Taesung; Prabhakaran, Dorairaj; Sandhu, Manjinder; Scott, James; Sladek, Rob; Tandon, Nikhil; Teo, Yik Ying; Zeggini, Eleftheria; Watanabe, Richard M; Koistinen, Heikki A; Kesaniemi, Y Antero; Uusitupa, Matti; Spector, Timothy D; Salomaa, Veikko; Rauramaa, Rainer; Palmer, Colin N A; Prokopenko, Inga; Morris, Andrew D; Bergman, Richard N; Collins, Francis S; Lind, Lars; Ingelsson, Erik; Tuomilehto, Jaakko; Karpe, Fredrik; Groop, Leif; Jørgensen, Torben; Hansen, Torben; Pedersen, Oluf; Kuusisto, Johanna; Abecasis, Gonçalo; Bell, Graeme I; Blangero, John; Cox, Nancy J; Duggirala, Ravindranath; Seielstad, Mark; Wilson, James G; Dupuis, Josee; Ripatti, Samuli; Hanis, Craig L; Florez, Jose C; Mohlke, Karen L; Meigs, James B; Laakso, Markku; Morris, Andrew P; Boehnke, Michael; Altshuler, David; McCarthy, Mark I; Gloyn, Anna L; Lindgren, Cecilia M
2017-01-01
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting insulin, a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in fasting plasma insulin (FI) levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-hour insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio=1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2. PMID:28341696
Education and myopia: assessing the direction of causality by mendelian randomisation.
Mountjoy, Edward; Davies, Neil M; Plotnikov, Denis; Smith, George Davey; Rodriguez, Santiago; Williams, Cathy E; Guggenheim, Jeremy A; Atan, Denize
2018-06-06
To determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education. Bidirectional, two sample mendelian randomisation study. Publically available genetic data from two consortiums applied to a large, independent population cohort. Genetic variants used as proxies for myopia and years of education were derived from two large genome wide association studies: 23andMe and Social Science Genetic Association Consortium (SSGAC), respectively. 67 798 men and women from England, Scotland, and Wales in the UK Biobank cohort with available information for years of completed education and refractive error. Mendelian randomisation analyses were performed in two directions: the first exposure was the genetic predisposition to myopia, measured with 44 genetic variants strongly associated with myopia in 23andMe, and the outcome was years in education; and the second exposure was the genetic predisposition to higher levels of education, measured with 69 genetic variants from SSGAC, and the outcome was refractive error. Conventional regression analyses of the observational data suggested that every additional year of education was associated with a more myopic refractive error of -0.18 dioptres/y (95% confidence interval -0.19 to -0.17; P<2e-16). Mendelian randomisation analyses suggested the true causal effect was even stronger: -0.27 dioptres/y (-0.37 to -0.17; P=4e-8). By contrast, there was little evidence to suggest myopia affected education (years in education per dioptre of refractive error -0.008 y/dioptre, 95% confidence interval -0.041 to 0.025, P=0.6). Thus, the cumulative effect of more years in education on refractive error means that a university graduate from the United Kingdom with 17 years of education would, on average, be at least -1 dioptre more myopic than someone who left school at age 16 (with 12 years of education). Myopia of this magnitude would be sufficient to necessitate the use of glasses for driving. Sensitivity analyses showed minimal evidence for genetic confounding that could have biased the causal effect estimates. This study shows that exposure to more years in education contributes to the rising prevalence of myopia. Increasing the length of time spent in education may inadvertently increase the prevalence of myopia and potential future visual disability. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Genetic evidence of a causal effect of insulin resistance on branched-chain amino acid levels.
Mahendran, Yuvaraj; Jonsson, Anna; Have, Christian T; Allin, Kristine H; Witte, Daniel R; Jørgensen, Marit E; Grarup, Niels; Pedersen, Oluf; Kilpeläinen, Tuomas O; Hansen, Torben
2017-05-01
Fasting plasma levels of branched-chain amino acids (BCAAs) are associated with insulin resistance, but it remains unclear whether there is a causal relation between the two. We aimed to disentangle the causal relations by performing a Mendelian randomisation study using genetic variants associated with circulating BCAA levels and insulin resistance as instrumental variables. We measured circulating BCAA levels in blood plasma by NMR spectroscopy in 1,321 individuals from the ADDITION-PRO cohort. We complemented our analyses by using previously published genome-wide association study (GWAS) results from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) (n = 46,186) and from a GWAS of serum BCAA levels (n = 24,925). We used a genetic risk score (GRS), calculated using ten established fasting serum insulin associated variants, as an instrumental variable for insulin resistance. A GRS of three variants increasing circulating BCAA levels was used as an instrumental variable for circulating BCAA levels. Fasting plasma BCAA levels were associated with higher HOMA-IR in ADDITION-PRO (β 0.137 [95% CI 0.08, 0.19] p = 6 × 10 -7 ). However, the GRS for circulating BCAA levels was not associated with fasting insulin levels or HOMA-IR in ADDITION-PRO (β -0.011 [95% CI -0.053, 0.032] p = 0.6 and β -0.011 [95% CI -0.054, 0.031] p = 0.6, respectively) or in GWAS results for HOMA-IR from MAGIC (β for valine-increasing GRS -0.012 [95% CI -0.069, 0.045] p = 0.7). By contrast, the insulin-resistance-increasing GRS was significantly associated with increased BCAA levels in ADDITION-PRO (β 0.027 [95% CI 0.005, 0.048] p = 0.01) and in GWAS results for serum BCAA levels (β 1.22 [95% CI 0.71, 1.73] p = 4 × 10 -6 , β 0.96 [95% CI 0.45, 1.47] p = 3 × 10 -4 , and β 0.67 [95% CI 0.16, 1.18] p = 0.01 for isoleucine, leucine and valine levels, respectively) and instrumental variable analyses in ADDITION-PRO indicated that HOMA-IR is causally related to higher circulating fasting BCAA levels (β 0.73 [95% CI 0.26, 1.19] p = 0.002). Our results suggest that higher BCAA levels do not have a causal effect on insulin resistance while increased insulin resistance drives higher circulating fasting BCAA levels.
Education and myopia: assessing the direction of causality by mendelian randomisation
Mountjoy, Edward; Davies, Neil M; Plotnikov, Denis; Smith, George Davey; Rodriguez, Santiago; Williams, Cathy E; Guggenheim, Jeremy A
2018-01-01
Abstract Objectives To determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education. Design Bidirectional, two sample mendelian randomisation study. Setting Publically available genetic data from two consortiums applied to a large, independent population cohort. Genetic variants used as proxies for myopia and years of education were derived from two large genome wide association studies: 23andMe and Social Science Genetic Association Consortium (SSGAC), respectively. Participants 67 798 men and women from England, Scotland, and Wales in the UK Biobank cohort with available information for years of completed education and refractive error. Main outcome measures Mendelian randomisation analyses were performed in two directions: the first exposure was the genetic predisposition to myopia, measured with 44 genetic variants strongly associated with myopia in 23andMe, and the outcome was years in education; and the second exposure was the genetic predisposition to higher levels of education, measured with 69 genetic variants from SSGAC, and the outcome was refractive error. Results Conventional regression analyses of the observational data suggested that every additional year of education was associated with a more myopic refractive error of −0.18 dioptres/y (95% confidence interval −0.19 to −0.17; P<2e-16). Mendelian randomisation analyses suggested the true causal effect was even stronger: −0.27 dioptres/y (−0.37 to −0.17; P=4e-8). By contrast, there was little evidence to suggest myopia affected education (years in education per dioptre of refractive error −0.008 y/dioptre, 95% confidence interval −0.041 to 0.025, P=0.6). Thus, the cumulative effect of more years in education on refractive error means that a university graduate from the United Kingdom with 17 years of education would, on average, be at least −1 dioptre more myopic than someone who left school at age 16 (with 12 years of education). Myopia of this magnitude would be sufficient to necessitate the use of glasses for driving. Sensitivity analyses showed minimal evidence for genetic confounding that could have biased the causal effect estimates. Conclusions This study shows that exposure to more years in education contributes to the rising prevalence of myopia. Increasing the length of time spent in education may inadvertently increase the prevalence of myopia and potential future visual disability. PMID:29875094
Bonilla, Carolina; Lewis, Sarah J; Rowlands, Mari-Anne; Gaunt, Tom R; Davey Smith, George; Gunnell, David; Palmer, Tom; Donovan, Jenny L; Hamdy, Freddie C; Neal, David E; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Al Olama, Ali Amin; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Grönberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lathrop, Mark; Martin, Richard M; Holly, Jeff M P
2016-10-01
Circulating insulin-like growth factors (IGFs) and their binding proteins (IGFBPs) are associated with prostate cancer. Using genetic variants as instruments for IGF peptides, we investigated whether these associations are likely to be causal. We identified from the literature 56 single nucleotide polymorphisms (SNPs) in the IGF axis previously associated with biomarker levels (8 from a genome-wide association study [GWAS] and 48 in reported candidate genes). In ∼700 men without prostate cancer and two replication cohorts (N ∼ 900 and ∼9,000), we examined the properties of these SNPS as instrumental variables (IVs) for IGF-I, IGF-II, IGFBP-2 and IGFBP-3. Those confirmed as strong IVs were tested for association with prostate cancer risk, low (< 7) vs. high (≥ 7) Gleason grade, localised vs. advanced stage, and mortality, in 22,936 controls and 22,992 cases. IV analysis was used in an attempt to estimate the causal effect of circulating IGF peptides on prostate cancer. Published SNPs in the IGFBP1/IGFBP3 gene region, particularly rs11977526, were strong instruments for IGF-II and IGFBP-3, less so for IGF-I. Rs11977526 was associated with high (vs. low) Gleason grade (OR per IGF-II/IGFBP-3 level-raising allele 1.05; 95% CI: 1.00, 1.10). Using rs11977526 as an IV we estimated the causal effect of a one SD increase in IGF-II (∼265 ng/mL) on risk of high vs. low grade disease as 1.14 (95% CI: 1.00, 1.31). Because of the potential for pleiotropy of the genetic instruments, these findings can only causally implicate the IGF pathway in general, not any one specific biomarker. © 2016 UICC.
Martin, Richard M.; Geybels, Milan S.; Stanford, Janet L.; Shui, Irene; Eeles, Rosalind; Easton, Doug; Kote‐Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G.; Travis, Ruth C; Neal, David; Pashayan, Nora; Khaw, Kay‐Tee; Blot, William; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon‐Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Donovan, Jenny; Munafò, Marcus R.
2016-01-01
Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all‐cause and prostate cancer‐specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high‐grade compared to low‐grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all‐cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer‐specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression. PMID:27741566
Exome Sequence Analysis of 14 Families With High Myopia.
Kloss, Bethany A; Tompson, Stuart W; Whisenhunt, Kristina N; Quow, Krystina L; Huang, Samuel J; Pavelec, Derek M; Rosenberg, Thomas; Young, Terri L
2017-04-01
To identify causal gene mutations in 14 families with autosomal dominant (AD) high myopia using exome sequencing. Select individuals from 14 large Caucasian families with high myopia were exome sequenced. Gene variants were filtered to identify potential pathogenic changes. Sanger sequencing was used to confirm variants in original DNA, and to test for disease cosegregation in additional family members. Candidate genes and chromosomal loci previously associated with myopic refractive error and its endophenotypes were comprehensively screened. In 14 high myopia families, we identified 73 rare and 31 novel gene variants as candidates for pathogenicity. In seven of these families, two of the novel and eight of the rare variants were within known myopia loci. A total of 104 heterozygous nonsynonymous rare variants in 104 genes were identified in 10 out of 14 probands. Each variant cosegregated with affection status. No rare variants were identified in genes known to cause myopia or in genes closest to published genome-wide association study association signals for refractive error or its endophenotypes. Whole exome sequencing was performed to determine gene variants implicated in the pathogenesis of AD high myopia. This study provides new genes for consideration in the pathogenesis of high myopia, and may aid in the development of genetic profiling of those at greatest risk for attendant ocular morbidities of this disorder.
Yan, Song; Li, Yun
2014-02-15
Despite its great capability to detect rare variant associations, next-generation sequencing is still prohibitively expensive when applied to large samples. In case-control studies, it is thus appealing to sequence only a subset of cases to discover variants and genotype the identified variants in controls and the remaining cases under the reasonable assumption that causal variants are usually enriched among cases. However, this approach leads to inflated type-I error if analyzed naively for rare variant association. Several methods have been proposed in recent literature to control type-I error at the cost of either excluding some sequenced cases or correcting the genotypes of discovered rare variants. All of these approaches thus suffer from certain extent of information loss and thus are underpowered. We propose a novel method (BETASEQ), which corrects inflation of type-I error by supplementing pseudo-variants while keeps the original sequence and genotype data intact. Extensive simulations and real data analysis demonstrate that, in most practical situations, BETASEQ leads to higher testing powers than existing approaches with guaranteed (controlled or conservative) type-I error. BETASEQ and associated R files, including documentation, examples, are available at http://www.unc.edu/~yunmli/betaseq
de Vries, Tamar I; R Monroe, Glen; van Belzen, Martine J; van der Lans, Christian A; Savelberg, Sanne MC; Newman, William G; van Haaften, Gijs; Nievelstein, Rutger A; van Haelst, Mieke M
2016-01-01
Rubinstein–Taybi syndrome (RTS, OMIM 180849) and Filippi syndrome (FLPIS, OMIM 272440) are both rare syndromes, with multiple congenital anomalies and intellectual deficit (MCA/ID). We present a patient with intellectual deficit, short stature, bilateral syndactyly of hands and feet, broad thumbs, ocular abnormalities, and dysmorphic facial features. These clinical features suggest both RTS and FLPIS. Initial DNA analysis of DNA isolated from blood did not identify variants to confirm either of these syndrome diagnoses. Whole-exome sequencing identified a homozygous variant in C9orf173, which was novel at the time of analysis. Further Sanger sequencing analysis of FLPIS cases tested negative for CKAP2L variants did not, however, reveal any further variants. Subsequent analysis using DNA isolated from buccal mucosa revealed a mosaic variant in CREBBP. This report highlights the importance of excluding mosaic variants in patients with a strong but atypical clinical presentation of a MCA/ID syndrome if no disease-causing variants can be detected in DNA isolated from blood samples. As the striking syndactyly observed in the present case is typical for FLPIS, we suggest CREBBP analysis in saliva samples for FLPIS syndrome cases in which no causal CKAP2L variant is detected. PMID:26956253
Quantum Common Causes and Quantum Causal Models
NASA Astrophysics Data System (ADS)
Allen, John-Mark A.; Barrett, Jonathan; Horsman, Dominic C.; Lee, Ciarán M.; Spekkens, Robert W.
2017-07-01
Reichenbach's principle asserts that if two observed variables are found to be correlated, then there should be a causal explanation of these correlations. Furthermore, if the explanation is in terms of a common cause, then the conditional probability distribution over the variables given the complete common cause should factorize. The principle is generalized by the formalism of causal models, in which the causal relationships among variables constrain the form of their joint probability distribution. In the quantum case, however, the observed correlations in Bell experiments cannot be explained in the manner Reichenbach's principle would seem to demand. Motivated by this, we introduce a quantum counterpart to the principle. We demonstrate that under the assumption that quantum dynamics is fundamentally unitary, if a quantum channel with input A and outputs B and C is compatible with A being a complete common cause of B and C , then it must factorize in a particular way. Finally, we show how to generalize our quantum version of Reichenbach's principle to a formalism for quantum causal models and provide examples of how the formalism works.
Structural Equations and Causal Explanations: Some Challenges for Causal SEM
ERIC Educational Resources Information Center
Markus, Keith A.
2010-01-01
One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…
GM2 Gangliosidosis in Shiba Inu Dogs with an In-Frame Deletion in HEXB.
Kolicheski, A; Johnson, G S; Villani, N A; O'Brien, D P; Mhlanga-Mutangadura, T; Wenger, D A; Mikoloski, K; Eagleson, J S; Taylor, J F; Schnabel, R D; Katz, M L
2017-09-01
Consistent with a tentative diagnosis of neuronal ceroid lipofuscinosis (NCL), autofluorescent cytoplasmic storage bodies were found in neurons from the brains of 2 related Shiba Inu dogs with a young-adult onset, progressive neurodegenerative disease. Unexpectedly, no potentially causal NCL-related variants were identified in a whole-genome sequence generated with DNA from 1 of the affected dogs. Instead, the whole-genome sequence contained a homozygous 3 base pair (bp) deletion in a coding region of HEXB. The other affected dog also was homozygous for this 3-bp deletion. Mutations in the human HEXB ortholog cause Sandhoff disease, a type of GM2 gangliosidosis. Thin-layer chromatography confirmed that GM2 ganglioside had accumulated in an affected Shiba Inu brain. Enzymatic analysis confirmed that the GM2 gangliosidosis resulted from a deficiency in the HEXB encoded protein and not from a deficiency in products from HEXA or GM2A, which are known alternative causes of GM2 gangliosidosis. We conclude that the homozygous 3-bp deletion in HEXB is the likely cause of the Shiba Inu neurodegenerative disease and that whole-genome sequencing can lead to the early identification of potentially disease-causing DNA variants thereby refocusing subsequent diagnostic analyses toward confirming or refuting candidate variant causality. Copyright © 2017 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.
Yavorska, Olena O; Burgess, Stephen
2017-12-01
MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data. The core functionality is to implement the inverse-variance weighted, MR-Egger and weighted median methods for multiple genetic variants. Several options are available to the user, such as the use of robust regression, fixed- or random-effects models and the penalization of weights for genetic variants with heterogeneous causal estimates. Extensions to these methods, such as allowing for variants to be correlated, can be chosen if appropriate. Graphical commands allow summarized data to be displayed in an interactive graph, or the plotting of causal estimates from multiple methods, for comparison. Although the main method of data entry is directly by the user, there is also an option for allowing summarized data to be incorporated from the PhenoScanner database of genotype-phenotype associations. We hope to develop this feature in future versions of the package. The R software environment is available for download from [https://www.r-project.org/]. The MendelianRandomization package can be downloaded from the Comprehensive R Archive Network (CRAN) within R, or directly from [https://cran.r-project.org/web/packages/MendelianRandomization/]. Both R and the MendelianRandomization package are released under GNU General Public Licenses (GPL-2|GPL-3). © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association.
Rare genetic variants and the risk of cancer.
Bodmer, Walter; Tomlinson, Ian
2010-06-01
There are good reasons to expect that common genetic variants do not explain all of the inherited risk of the common cancers, not least of these being the relatively low proportion of familial relative risk that common cancer SNPs currently explain. One promising source of the unexplained risk is rare, low-penetrance genetic variants, a class that ranges from low-frequency polymorphisms (allele frequency < 5%) through subpolymorphic variants (frequency 0.1-1.0%) to very low frequency or 'private' variants with frequencies of 0.1% or less. Examples of rare cancer variants include breast cancer susceptibility loci CHEK2, BRIP1 and PALB2. There are considerable challenges associated with the discovery and testing of rare predisposition alleles, many of which are illustrated by the issues associated with variants of unknown significance in the Mendelian cancer predisposition genes. However, whilst cost constraints remain, the technological barriers to rare variant discovery and large-scale genotyping no longer exist. If each individual carries many disease-causing rare variants, the so-called missing heritability of cancer might largely be explained. Whether or not rare variants do end up filling the heritability gap, it is imperative to look for them along side common variants.
Hannes, F D; Sharp, A J; Mefford, H C; de Ravel, T; Ruivenkamp, C A; Breuning, M H; Fryns, J-P; Devriendt, K; Van Buggenhout, G; Vogels, A; Stewart, H; Hennekam, R C; Cooper, G M; Regan, R; Knight, S J L; Eichler, E E; Vermeesch, J R
2009-01-01
Background: Genomic disorders are often caused by non-allelic homologous recombination between segmental duplications. Chromosome 16 is especially rich in a chromosome-specific low copy repeat, termed LCR16. Methods and Results: A bacterial artificial chromosome (BAC) array comparative genome hybridisation (CGH) screen of 1027 patients with mental retardation and/or multiple congenital anomalies (MR/MCA) was performed. The BAC array CGH screen identified five patients with deletions and five with apparently reciprocal duplications of 16p13 covering 1.65 Mb, including 15 RefSeq genes. In addition, three atypical rearrangements overlapping or flanking this region were found. Fine mapping by high-resolution oligonucleotide arrays suggests that these deletions and duplications result from non-allelic homologous recombination (NAHR) between distinct LCR16 subunits with >99% sequence identity. Deletions and duplications were either de novo or inherited from unaffected parents. To determine whether these imbalances are associated with the MR/MCA phenotype or whether they might be benign variants, a population of 2014 normal controls was screened. The absence of deletions in the control population showed that 16p13.11 deletions are significantly associated with MR/MCA (p = 0.0048). Despite phenotypic variability, common features were identified: three patients with deletions presented with MR, microcephaly and epilepsy (two of these had also short stature), and two other deletion carriers ascertained prenatally presented with cleft lip and midline defects. In contrast to its previous association with autism, the duplication seems to be a common variant in the population (5/1682, 0.29%). Conclusion: These findings indicate that deletions inherited from clinically normal parents are likely to be causal for the patients’ phenotype whereas the role of duplications (de novo or inherited) in the phenotype remains uncertain. This difference in knowledge regarding the clinical relevance of the deletion and the duplication causes a paradigm shift in (cyto)genetic counselling. PMID:18550696
Preschool Children Learn about Causal Structure from Conditional Interventions
ERIC Educational Resources Information Center
Schulz, Laura E.; Gopnik, Alison; Glymour, Clark
2007-01-01
The conditional intervention principle is a formal principle that relates patterns of interventions and outcomes to causal structure. It is a central assumption of experimental design and the causal Bayes net formalism. Two studies suggest that preschoolers can use the conditional intervention principle to distinguish causal chains, common cause…
Convergence between biological, behavioural and genetic determinants of obesity.
Ghosh, Sujoy; Bouchard, Claude
2017-12-01
Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.
Comparison of six methods for the detection of causality in a bivariate time series
NASA Astrophysics Data System (ADS)
Krakovská, Anna; Jakubík, Jozef; Chvosteková, Martina; Coufal, David; Jajcay, Nikola; Paluš, Milan
2018-04-01
In this comparative study, six causality detection methods were compared, namely, the Granger vector autoregressive test, the extended Granger test, the kernel version of the Granger test, the conditional mutual information (transfer entropy), the evaluation of cross mappings between state spaces, and an assessment of predictability improvement due to the use of mixed predictions. Seven test data sets were analyzed: linear coupling of autoregressive models, a unidirectional connection of two Hénon systems, a unidirectional connection of chaotic systems of Rössler and Lorenz type and of two different Rössler systems, an example of bidirectionally connected two-species systems, a fishery model as an example of two correlated observables without a causal relationship, and an example of mediated causality. We tested not only 20 000 points long clean time series but also noisy and short variants of the data. The standard and the extended Granger tests worked only for the autoregressive models. The remaining methods were more successful with the more complex test examples, although they differed considerably in their capability to reveal the presence and the direction of coupling and to distinguish causality from mere correlation.
C-reactive protein and genetic variants and cognitive decline in old age: The PROSPER Study
USDA-ARS?s Scientific Manuscript database
Plasma concentrations of C-reactive protein (CRP), a marker of chronic inflammation, have been associated with cognitive impairment in old age. However, it is unknown whether CRP is causally linked to cognitive decline. Within the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER) tri...
USDA-ARS?s Scientific Manuscript database
Initial genomic test results for US Ayrshire dairy cattle became available in January of 2013. Several haplotypes that showed a deficiency of homozygotes were investigated to determine if they had an effect on fertility. A haplotype on chromosome 17 was determined to affect fertility, indicating tha...
Genome-wide and fine-resolution association analysis of malaria in West Africa.
Jallow, Muminatou; Teo, Yik Ying; Small, Kerrin S; Rockett, Kirk A; Deloukas, Panos; Clark, Taane G; Kivinen, Katja; Bojang, Kalifa A; Conway, David J; Pinder, Margaret; Sirugo, Giorgio; Sisay-Joof, Fatou; Usen, Stanley; Auburn, Sarah; Bumpstead, Suzannah J; Campino, Susana; Coffey, Alison; Dunham, Andrew; Fry, Andrew E; Green, Angela; Gwilliam, Rhian; Hunt, Sarah E; Inouye, Michael; Jeffreys, Anna E; Mendy, Alieu; Palotie, Aarno; Potter, Simon; Ragoussis, Jiannis; Rogers, Jane; Rowlands, Kate; Somaskantharajah, Elilan; Whittaker, Pamela; Widden, Claire; Donnelly, Peter; Howie, Bryan; Marchini, Jonathan; Morris, Andrew; SanJoaquin, Miguel; Achidi, Eric Akum; Agbenyega, Tsiri; Allen, Angela; Amodu, Olukemi; Corran, Patrick; Djimde, Abdoulaye; Dolo, Amagana; Doumbo, Ogobara K; Drakeley, Chris; Dunstan, Sarah; Evans, Jennifer; Farrar, Jeremy; Fernando, Deepika; Hien, Tran Tinh; Horstmann, Rolf D; Ibrahim, Muntaser; Karunaweera, Nadira; Kokwaro, Gilbert; Koram, Kwadwo A; Lemnge, Martha; Makani, Julie; Marsh, Kevin; Michon, Pascal; Modiano, David; Molyneux, Malcolm E; Mueller, Ivo; Parker, Michael; Peshu, Norbert; Plowe, Christopher V; Puijalon, Odile; Reeder, John; Reyburn, Hugh; Riley, Eleanor M; Sakuntabhai, Anavaj; Singhasivanon, Pratap; Sirima, Sodiomon; Tall, Adama; Taylor, Terrie E; Thera, Mahamadou; Troye-Blomberg, Marita; Williams, Thomas N; Wilson, Michael; Kwiatkowski, Dominic P
2009-06-01
We report a genome-wide association (GWA) study of severe malaria in The Gambia. The initial GWA scan included 2,500 children genotyped on the Affymetrix 500K GeneChip, and a replication study included 3,400 children. We used this to examine the performance of GWA methods in Africa. We found considerable population stratification, and also that signals of association at known malaria resistance loci were greatly attenuated owing to weak linkage disequilibrium (LD). To investigate possible solutions to the problem of low LD, we focused on the HbS locus, sequencing this region of the genome in 62 Gambian individuals and then using these data to conduct multipoint imputation in the GWA samples. This increased the signal of association, from P = 4 × 10(-7) to P = 4 × 10(-14), with the peak of the signal located precisely at the HbS causal variant. Our findings provide proof of principle that fine-resolution multipoint imputation, based on population-specific sequencing data, can substantially boost authentic GWA signals and enable fine mapping of causal variants in African populations.
Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Davey Smith, George; de Geus, Eco J C N; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian'an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O'Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Edwards, Digna R Velez; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B
2017-06-01
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10 -8 ) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.
Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Smith, George Davey; de Geus, Eco JCN; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian’an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O’Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Velez Edwards, Digna R; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B
2018-01-01
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project–imputed genotype data in up to ~370,000 women, we identify 389 independent signals (P < 5 × 10−8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ~7.4% of the population variance in age at menarche, corresponding to ~25% of the estimated heritability. We implicate ~250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility. PMID:28436984
Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R.; Mahajan, Anubha; Asimit, Jennifer L.; Ferreira, Teresa; Locke, Adam E.; Robertson, Neil R.; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E.; Tam, Claudia H.T.; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I.; Blangero, John; Burtt, Noél P.; Duggirala, Ravindranath; Florez, Jose C.; Hanis, Craig L.; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C.N.; Ma, Ronald C.W.; Froguel, Philippe; Wilson, James G.; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B.; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S.; Chambers, John C.; Saleheen, Danish; Kadowaki, Takashi; Tai, E. Shyong; Mohlke, Karen L.; Cox, Nancy J.; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I.; Morris, Andrew P.
2016-01-01
To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. PMID:26911676
Rare deleterious mutations are associated with disease in bipolar disorder families.
Rao, A R; Yourshaw, M; Christensen, B; Nelson, S F; Kerner, B
2017-07-01
Bipolar disorder (BD) is a common, complex and heritable psychiatric disorder characterized by episodes of severe mood swings. The identification of rare, damaging genomic mutations in families with BD could inform about disease mechanisms and lead to new therapeutic interventions. To determine whether rare, damaging mutations shared identity-by-descent in families with BD could be associated with disease, exome sequencing was performed in multigenerational families of the NIMH BD Family Study followed by in silico functional prediction. Disease association and disease specificity was determined using 5090 exomes from the Sweden-Schizophrenia (SZ) Population-Based Case-Control Exome Sequencing study. We identified 14 rare and likely deleterious mutations in 14 genes that were shared identity-by-descent among affected family members. The variants were associated with BD (P<0.05 after Bonferroni's correction) and disease specificity was supported by the absence of the mutations in patients with SZ. In addition, we found rare, functional mutations in known causal genes for neuropsychiatric disorders including holoprosencephaly and epilepsy. Our results demonstrate that exome sequencing in multigenerational families with BD is effective in identifying rare genomic variants of potential clinical relevance and also disease modifiers related to coexisting medical conditions. Replication of our results and experimental validation are required before disease causation could be assumed.
Assessment of circulating copy number variant detection for cancer screening.
Molparia, Bhuvan; Nichani, Eshaan; Torkamani, Ali
2017-01-01
Current high-sensitivity cancer screening methods, largely utilizing correlative biomarkers, suffer from false positive rates that lead to unnecessary medical procedures and debatable public health benefit overall. Detection of circulating tumor DNA (ctDNA), a causal biomarker, has the potential to revolutionize cancer screening. Thus far, the majority of ctDNA studies have focused on detection of tumor-specific point mutations after cancer diagnosis for the purpose of post-treatment surveillance. However, ctDNA point mutation detection methods developed to date likely lack either the scope or analytical sensitivity necessary to be useful for cancer screening, due to the low (<1%) ctDNA fraction derived from early stage tumors. On the other hand, tumor-derived copy number variant (CNV) detection is hypothetically a superior means of ctDNA-based cancer screening for many tumor types, given that, relative to point mutations, each individual tumor CNV contributes a much larger number of ctDNA fragments to the overall pool of circulating free DNA (cfDNA). A small number of studies have demonstrated the potential of ctDNA CNV-based screening in select cancer types. Here we perform an in silico assessment of the potential for ctDNA CNV-based cancer screening across many common cancers, and suggest ctDNA CNV detection shows promise as a broad cancer screening methodology.
Whole exome sequencing of rare variants in EIF4G1 and VPS35 in Parkinson disease
Nuytemans, Karen; Bademci, Guney; Inchausti, Vanessa; Dressen, Amy; Kinnamon, Daniel D.; Mehta, Arpit; Wang, Liyong; Züchner, Stephan; Beecham, Gary W.; Martin, Eden R.; Scott, William K.
2013-01-01
Objective: Recently, vacuolar protein sorting 35 (VPS35) and eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) have been identified as 2 causal Parkinson disease (PD) genes. We used whole exome sequencing for rapid, parallel analysis of variations in these 2 genes. Methods: We performed whole exome sequencing in 213 patients with PD and 272 control individuals. Those rare variants (RVs) with <5% frequency in the exome variant server database and our own control data were considered for analysis. We performed joint gene-based tests for association using RVASSOC and SKAT (Sequence Kernel Association Test) as well as single-variant test statistics. Results: We identified 3 novel VPS35 variations that changed the coded amino acid (nonsynonymous) in 3 cases. Two variations were in multiplex families and neither segregated with PD. In EIF4G1, we identified 11 (9 nonsynonymous and 2 small indels) RVs including the reported pathogenic mutation p.R1205H, which segregated in all affected members of a large family, but also in 1 unaffected 86-year-old family member. Two additional RVs were found in isolated patients only. Whereas initial association studies suggested an association (p = 0.04) with all RVs in EIF4G1, subsequent testing in a second dataset for the driving variant (p.F1461) suggested no association between RVs in the gene and PD. Conclusions: We confirm that the specific EIF4G1 variation p.R1205H seems to be a strong PD risk factor, but is nonpenetrant in at least one 86-year-old. A few other select RVs in both genes could not be ruled out as causal. However, there was no evidence for an overall contribution of genetic variability in VPS35 or EIF4G1 to PD development in our dataset. PMID:23408866
Thyroid Signaling, Insulin Resistance, and 2 Diabetes Mellitus: A Mendelian Randomization Study.
Bos, Maxime M; Smit, Roelof A J; Trompet, Stella; van Heemst, Diana; Noordam, Raymond
2017-06-01
Increasing evidence suggests an association between thyroid-stimulating hormone (TSH), free thyroxine (fT4), and deiodinases with insulin resistance and type 2 diabetes mellitus (T2D). We examined whether TSH and fT4 levels and deiodinases are causally associated with insulin resistance and T2D, using Mendelian randomization. We selected 20 genetic variants for TSH level and four for fT4 level (identified in a genome-wide association study (GWAS) meta-analysis of European-ancestry cohorts) as instrumental variables for TSH and fT4 levels, respectively. We used summary data from GWASs on the outcomes T2D [Diabetes, Genetics Replication and Meta-analysis (DIAGRAM), n = 12,171 cases and n = 56,862 control subjects] and glycemic traits in patients without diabetes [Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), n = 46,186 for fasting glucose and insulin and n = 46,368 for hemoglobin A1c]. To examine whether the associations between TSH/fT4 levels and the study outcomes were causal, we combined the effects of the genetic instruments. Furthermore, we examined the associations among 16 variants in DIO1, DIO2, DIO3, and T2D and glycemic traits. We found no evidence for an association between the combined genetic instrumental variables for TSH and fT4 and the study outcomes. For example, we did not observe a genetically determined association between high TSH level and T2D (odds ratio, 0.91 per standard deviation TSH increase; 95% confidence interval, 0.78 to 1.07). Selected genetic variants in DIO1 (e.g., rs7527713) were associated with measures of insulin resistance. We found no evidence for a causal association between circulatory levels of TSH and fT4 with insulin resistance and T2D, but we found suggestive evidence that DIO1 affects glucose metabolism. Copyright © 2017 by the Endocrine Society
Perceptual impressions of causality are affected by common fate.
White, Peter A
2017-03-24
Many studies of perceptual impressions of causality have used a stimulus in which a moving object (the launcher) contacts a stationary object (the target) and the latter then moves off. Such stimuli give rise to an impression that the launcher makes the target move. In the present experiments, instead of a single target object, an array of four vertically aligned objects was used. The launcher contacted none of them, but stopped at a point between the two central objects. The four objects then moved with similar motion properties, exhibiting the Gestalt property of common fate. Strong impressions of causality were reported for this stimulus. It is argued that the array of four objects was perceived, by the likelihood principle, as a single object with some parts unseen, that the launcher was perceived as contacting one of the unseen parts of this object, and that the causal impression resulted from that. Supporting that argument, stimuli in which kinematic features were manipulated so as to weaken or eliminate common fate yielded weaker impressions of causality.
Verhoef, Petra; Dötsch-Klerk, Mariska; Lathrop, Mark; Xu, Peng; Nordestgaard, Børge G.; Holm, Hilma; Hopewell, Jemma C.; Saleheen, Danish; Tanaka, Toshihiro; Anand, Sonia S.; Chambers, John C.; Kleber, Marcus E.; Ouwehand, Willem H.; Yamada, Yoshiji; Elbers, Clara; Peters, Bas; Stewart, Alexandre F. R.; Reilly, Muredach M.; Thorand, Barbara; Yusuf, Salim; Engert, James C.; Assimes, Themistocles L.; Kooner, Jaspal; Danesh, John; Watkins, Hugh; Samani, Nilesh J.
2012-01-01
Background Moderately elevated blood levels of homocysteine are weakly correlated with coronary heart disease (CHD) risk, but causality remains uncertain. When folate levels are low, the TT genotype of the common C677T polymorphism (rs1801133) of the methylene tetrahydrofolate reductase gene (MTHFR) appreciably increases homocysteine levels, so “Mendelian randomization” studies using this variant as an instrumental variable could help test causality. Methods and Findings Nineteen unpublished datasets were obtained (total 48,175 CHD cases and 67,961 controls) in which multiple genetic variants had been measured, including MTHFR C677T. These datasets did not include measurements of blood homocysteine, but homocysteine levels would be expected to be about 20% higher with TT than with CC genotype in the populations studied. In meta-analyses of these unpublished datasets, the case-control CHD odds ratio (OR) and 95% CI comparing TT versus CC homozygotes was 1.02 (0.98–1.07; p = 0.28) overall, and 1.01 (0.95–1.07) in unsupplemented low-folate populations. By contrast, in a slightly updated meta-analysis of the 86 published studies (28,617 CHD cases and 41,857 controls), the OR was 1.15 (1.09–1.21), significantly discrepant (p = 0.001) with the OR in the unpublished datasets. Within the meta-analysis of published studies, the OR was 1.12 (1.04–1.21) in the 14 larger studies (those with variance of log OR<0.05; total 13,119 cases) and 1.18 (1.09–1.28) in the 72 smaller ones (total 15,498 cases). Conclusions The CI for the overall result from large unpublished datasets shows lifelong moderate homocysteine elevation has little or no effect on CHD. The discrepant overall result from previously published studies reflects publication bias or methodological problems. Please see later in the article for the Editors' Summary PMID:22363213
Genetic Candidate Variants in Two Multigenerational Families with Childhood Apraxia of Speech
Wijsman, Ellen M.; Nato, Alejandro Q.; Matsushita, Mark M.; Chapman, Kathy L.; Stanaway, Ian B.; Wolff, John; Oda, Kaori; Gabo, Virginia B.; Raskind, Wendy H.
2016-01-01
Childhood apraxia of speech (CAS) is a severe and socially debilitating form of speech sound disorder with suspected genetic involvement, but the genetic etiology is not yet well understood. Very few known or putative causal genes have been identified to date, e.g., FOXP2 and BCL11A. Building a knowledge base of the genetic etiology of CAS will make it possible to identify infants at genetic risk and motivate the development of effective very early intervention programs. We investigated the genetic etiology of CAS in two large multigenerational families with familial CAS. Complementary genomic methods included Markov chain Monte Carlo linkage analysis, copy-number analysis, identity-by-descent sharing, and exome sequencing with variant filtering. No overlaps in regions with positive evidence of linkage between the two families were found. In one family, linkage analysis detected two chromosomal regions of interest, 5p15.1-p14.1, and 17p13.1-q11.1, inherited separately from the two founders. Single-point linkage analysis of selected variants identified CDH18 as a primary gene of interest and additionally, MYO10, NIPBL, GLP2R, NCOR1, FLCN, SMCR8, NEK8, and ANKRD12, possibly with additive effects. Linkage analysis in the second family detected five regions with LOD scores approaching the highest values possible in the family. A gene of interest was C4orf21 (ZGRF1) on 4q25-q28.2. Evidence for previously described causal copy-number variations and validated or suspected genes was not found. Results are consistent with a heterogeneous CAS etiology, as is expected in many neurogenic disorders. Future studies will investigate genome variants in these and other families with CAS. PMID:27120335
ERIC Educational Resources Information Center
Besson, Ugo
2010-01-01
This paper presents an analysis of the different types of reasoning and physical explanation used in science, common thought, and physics teaching. It then reflects on the learning difficulties connected with these various approaches, and suggests some possible didactic strategies. Although causal reasoning occurs very frequently in common thought…
Rare versus common variants in pharmacogenetics: SLCO1B1 variation and methotrexate disposition
Ramsey, Laura B.; Bruun, Gitte H.; Yang, Wenjian; Treviño, Lisa R.; Vattathil, Selina; Scheet, Paul; Cheng, Cheng; Rosner, Gary L.; Giacomini, Kathleen M.; Fan, Yiping; Sparreboom, Alex; Mikkelsen, Torben S.; Corydon, Thomas J.; Pui, Ching-Hon; Evans, William E.; Relling, Mary V.
2012-01-01
Methotrexate is used to treat autoimmune diseases and malignancies, including acute lymphoblastic leukemia (ALL). Inter-individual variation in clearance of methotrexate results in heterogeneous systemic exposure, clinical efficacy, and toxicity. In a genome-wide association study of children with ALL, we identified SLCO1B1 as harboring multiple common polymorphisms associated with methotrexate clearance. The extent of influence of rare versus common variants on pharmacogenomic phenotypes remains largely unexplored. We tested the hypothesis that rare variants in SLCO1B1 could affect methotrexate clearance and compared the influence of common versus rare variants in addition to clinical covariates on clearance. From deep resequencing of SLCO1B1 exons in 699 children, we identified 93 SNPs, 15 of which were non-synonymous (NS). Three of these NS SNPs were common, with a minor allele frequency (MAF) >5%, one had low frequency (MAF 1%–5%), and 11 were rare (MAF <1%). NS SNPs (common or rare) predicted to be functionally damaging were more likely to be found among patients with the lowest methotrexate clearance than patients with high clearance. We verified lower function in vitro of four SLCO1B1 haplotypes that were associated with reduced methotrexate clearance. In a multivariate stepwise regression analysis adjusting for other genetic and non-genetic covariates, SLCO1B1 variants accounted for 10.7% of the population variability in clearance. Of that variability, common NS variants accounted for the majority, but rare damaging NS variants constituted 17.8% of SLCO1B1's effects (1.9% of total variation) and had larger effect sizes than common NS variants. Our results show that rare variants are likely to have an important effect on pharmacogenetic phenotypes. PMID:22147369
Tang, Clara S; Zhang, He; Cheung, Chloe Y Y; Xu, Ming; Ho, Jenny C Y; Zhou, Wei; Cherny, Stacey S; Zhang, Yan; Holmen, Oddgeir; Au, Ka-Wing; Yu, Haiyi; Xu, Lin; Jia, Jia; Porsch, Robert M; Sun, Lijie; Xu, Weixian; Zheng, Huiping; Wong, Lai-Yung; Mu, Yiming; Dou, Jingtao; Fong, Carol H Y; Wang, Shuyu; Hong, Xueyu; Dong, Liguang; Liao, Yanhua; Wang, Jiansong; Lam, Levina S M; Su, Xi; Yan, Hua; Yang, Min-Lee; Chen, Jin; Siu, Chung-Wah; Xie, Gaoqiang; Woo, Yu-Cho; Wu, Yangfeng; Tan, Kathryn C B; Hveem, Kristian; Cheung, Bernard M Y; Zöllner, Sebastian; Xu, Aimin; Eugene Chen, Y; Jiang, Chao Qiang; Zhang, Youyi; Lam, Tai-Hing; Ganesh, Santhi K; Huo, Yong; Sham, Pak C; Lam, Karen S L; Willer, Cristen J; Tse, Hung-Fat; Gao, Wei
2015-12-22
Blood lipids are important risk factors for coronary artery disease (CAD). Here we perform an exome-wide association study by genotyping 12,685 Chinese, using a custom Illumina HumanExome BeadChip, to identify additional loci influencing lipid levels. Single-variant association analysis on 65,671 single nucleotide polymorphisms reveals 19 loci associated with lipids at exome-wide significance (P<2.69 × 10(-7)), including three Asian-specific coding variants in known genes (CETP p.Asp459Gly, PCSK9 p.Arg93Cys and LDLR p.Arg257Trp). Furthermore, missense variants at two novel loci-PNPLA3 p.Ile148Met and PKD1L3 p.Thr429Ser-also influence levels of triglycerides and low-density lipoprotein cholesterol, respectively. Another novel gene, TEAD2, is found to be associated with high-density lipoprotein cholesterol through gene-based association analysis. Most of these newly identified coding variants show suggestive association (P<0.05) with CAD. These findings demonstrate that exome-wide genotyping on samples of non-European ancestry can identify additional population-specific possible causal variants, shedding light on novel lipid biology and CAD.
Rodriguez-Flores, Juan L.; Fakhro, Khalid; Hackett, Neil R.; Salit, Jacqueline; Fuller, Jennifer; Agosto-Perez, Francisco; Gharbiah, Maey; Malek, Joel A.; Zirie, Mahmoud; Jayyousi, Amin; Badii, Ramin; Al-Marri, Ajayeb Al-Nabet; Chouchane, Lotfi; Stadler, Dora J.; Hunter-Zinck, Haley; Mezey, Jason G.; Crystal, Ronald G.
2013-01-01
Exome sequencing of families of related individuals has been highly successful in identifying genetic polymorphisms responsible for Mendelian disorders. Here, we demonstrate the value of the reverse approach, where we use exome sequencing of a sample of unrelated individuals to analyze allele frequencies of known causal mutations for Mendelian diseases. We sequenced the exomes of 100 individuals representing the three major genetic subgroups of the Qatari population (Q1 Bedouin, Q2 Persian-South Asian, Q3 African) and identified 37 variants in 33 genes with effects on 36 clinically significant Mendelian diseases. These include variants not present in 1000 Genomes and variants at high frequency when compared to 1000 Genomes populations. Several of these Mendelian variants were only segregating in one Qatari subpopulation, where the observed subpopulation specificity trends were confirmed in an independent population of 386 Qataris. Pre-marital genetic screening in Qatar tests for only 4 out of the 37, such that this study provides a set of Mendelian disease variants with potential impact on the epidemiological profile of the population that could be incorporated into the testing program if further experimental and clinical characterization confirms high penetrance. PMID:24123366
A generalized least-squares framework for rare-variant analysis in family data.
Li, Dalin; Rotter, Jerome I; Guo, Xiuqing
2014-01-01
Rare variants may, in part, explain some of the hereditability missing in current genome-wide association studies. Many gene-based rare-variant analysis approaches proposed in recent years are aimed at population-based samples, although analysis strategies for family-based samples are clearly warranted since the family-based design has the potential to enhance our ability to enrich for rare causal variants. We have recently developed the generalized least squares, sequence kernel association test, or GLS-SKAT, approach for the rare-variant analyses in family samples, in which the kinship matrix that was computed from the high dimension genetic data was used to decorrelate the family structure. We then applied the SKAT-O approach for gene-/region-based inference in the decorrelated data. In this study, we applied this GLS-SKAT method to the systolic blood pressure data in the simulated family sample distributed by the Genetic Analysis Workshop 18. We compared the GLS-SKAT approach to the rare-variant analysis approach implemented in family-based association test-v1 and demonstrated that the GLS-SKAT approach provides superior power and good control of type I error rate.
Bouwman, Aniek C; Veerkamp, Roel F
2014-10-03
The aim of this study was to determine the consequences of splitting sequencing effort over multiple breeds for imputation accuracy from a high-density SNP chip towards whole-genome sequence. Such information would assist for instance numerical smaller cattle breeds, but also pig and chicken breeders, who have to choose wisely how to spend their sequencing efforts over all the breeds or lines they evaluate. Sequence data from cattle breeds was used, because there are currently relatively many individuals from several breeds sequenced within the 1,000 Bull Genomes project. The advantage of whole-genome sequence data is that it carries the causal mutations, but the question is whether it is possible to impute the causal variants accurately. This study therefore focussed on imputation accuracy of variants with low minor allele frequency and breed specific variants. Imputation accuracy was assessed for chromosome 1 and 29 as the correlation between observed and imputed genotypes. For chromosome 1, the average imputation accuracy was 0.70 with a reference population of 20 Holstein, and increased to 0.83 when the reference population was increased by including 3 other dairy breeds with 20 animals each. When the same amount of animals from the Holstein breed were added the accuracy improved to 0.88, while adding the 3 other breeds to the reference population of 80 Holstein improved the average imputation accuracy marginally to 0.89. For chromosome 29, the average imputation accuracy was lower. Some variants benefitted from the inclusion of other breeds in the reference population, initially determined by the MAF of the variant in each breed, but even Holstein specific variants did gain imputation accuracy from the multi-breed reference population. This study shows that splitting sequencing effort over multiple breeds and combining the reference populations is a good strategy for imputation from high-density SNP panels towards whole-genome sequence when reference populations are small and sequencing effort is limiting. When sequencing effort is limiting and interest lays in multiple breeds or lines this provides imputation of each breed.
Whole exome sequencing as a diagnostic tool for patients with ciliopathy-like phenotypes.
Castro-Sánchez, Sheila; Álvarez-Satta, María; Tohamy, Mohamed A; Beltran, Sergi; Derdak, Sophia; Valverde, Diana
2017-01-01
Ciliopathies are a group of rare disorders characterized by a high genetic and phenotypic variability, which complicates their molecular diagnosis. Hence the need to use the latest powerful approaches to faster identify the genetic defect in these patients. We applied whole exome sequencing to six consanguineous families clinically diagnosed with ciliopathy-like disease, and for which mutations in predominant Bardet-Biedl syndrome (BBS) genes had previously been excluded. Our strategy, based on first applying several filters to ciliary variants and using many of the bioinformatics tools available, allowed us to identify causal mutations in BBS2, ALMS1 and CRB1 genes in four families, thus confirming the molecular diagnosis of ciliopathy. In the remaining two families, after first rejecting the presence of pathogenic variants in common cilia-related genes, we adopted a new filtering strategy combined with prioritisation tools to rank the final candidate genes for each case. Thus, we propose CORO2B, LMO7 and ZNF17 as novel candidate ciliary genes, but further functional studies will be needed to confirm their role. Our data show the usefulness of this strategy to diagnose patients with unclear phenotypes, and therefore the success of applying such technologies to achieve a rapid and reliable molecular diagnosis, improving genetic counselling for these patients. In addition, the described pipeline also highlights the common pitfalls associated to the large volume of data we have to face and the difficulty of assigning a functional role to these changes, hence the importance of designing the most appropriate strategy according to each case.
Xu, Anping; Chen, Weidong; Xia, Yong; Zhou, Yu; Ji, Ling
2018-04-07
HbA1c is a widely used biomarker for diabetes mellitus management. Here, we evaluated the accuracy of six methods for determining HbA1c values in Chinese patients with common α- and β-globin chains variants in China. Blood samples from normal subjects and individuals exhibiting hemoglobin variants were analyzed for HbA1c, using Sebia Capillarys 2 Flex Piercing (C2FP), Bio-Rad Variant II Turbo 2.0, Tosoh HLC-723 G8 (ver. 5.24), Arkray ADAMS A1c HA-8180V fast mode, Cobas c501 and Trinity Ultra2 systems. DNA sequencing revealed five common β-globin chain variants and three common α-globin chain variants. The most common variant was Hb E, followed by Hb New York, Hb J-Bangkok, Hb G-Coushatta, Hb Q-Thailand, Hb G-Honolulu, Hb Ube-2 and Hb G-Taipei. Variant II Turbo 2.0, Ultra2 and Cobas c501 showed good agreement with C2FP for most samples with variants. HLC-723 G8 yielded no HbA1c values for Hb J-Bangkok, Hb Q-Thailand and Hb G-Honolulu. Samples with Hb E, Hb G-Coushatta, Hb G-Taipei and Hb Ube-2 produced significant negative biases for HLC-723 G8. HA-8180V showed statistically significant differences for Hb E, Hb G-Coushatta, Hb G-Taipei, Hb Q-Thailand and Hb G-Honolulu. HA-8180V yielded no HbA1c values for Hb J-Bangkok. All methods showed good agreement for samples with Hb New York. Some common hemoglobin variants can interfere with HbA1c determination by the most popular methods in China.
Quantum-coherent mixtures of causal relations
NASA Astrophysics Data System (ADS)
Maclean, Jean-Philippe W.; Ried, Katja; Spekkens, Robert W.; Resch, Kevin J.
2017-05-01
Understanding the causal influences that hold among parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common-cause acting on both. Here we show a coherent mixture of these two possibilities. We realize this nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's effect, whereby two independent causes can become correlated on observation of their common effect. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, including Bell's theorem and the search for quantum gravity.
Quantum-coherent mixtures of causal relations
MacLean, Jean-Philippe W.; Ried, Katja; Spekkens, Robert W.; Resch, Kevin J.
2017-01-01
Understanding the causal influences that hold among parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common-cause acting on both. Here we show a coherent mixture of these two possibilities. We realize this nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's effect, whereby two independent causes can become correlated on observation of their common effect. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, including Bell's theorem and the search for quantum gravity. PMID:28485394
Quantum-coherent mixtures of causal relations.
MacLean, Jean-Philippe W; Ried, Katja; Spekkens, Robert W; Resch, Kevin J
2017-05-09
Understanding the causal influences that hold among parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common-cause acting on both. Here we show a coherent mixture of these two possibilities. We realize this nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's effect, whereby two independent causes can become correlated on observation of their common effect. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, including Bell's theorem and the search for quantum gravity.
Mendelian randomization in nutritional epidemiology
Qi, Lu
2013-01-01
Nutritional epidemiology aims to identify dietary and lifestyle causes for human diseases. Causality inference in nutritional epidemiology is largely based on evidence from studies of observational design, and may be distorted by unmeasured or residual confounding and reverse causation. Mendelian randomization is a recently developed methodology that combines genetic and classical epidemiological analysis to infer causality for environmental exposures, based on the principle of Mendel’s law of independent assortment. Mendelian randomization uses genetic variants as proxiesforenvironmentalexposuresofinterest.AssociationsderivedfromMendelian randomization analysis are less likely to be affected by confounding and reverse causation. During the past 5 years, a body of studies examined the causal effects of diet/lifestyle factors and biomarkers on a variety of diseases. The Mendelian randomization approach also holds considerable promise in the study of intrauterine influences on offspring health outcomes. However, the application of Mendelian randomization in nutritional epidemiology has some limitations. PMID:19674341
Olfson, Emily; Saccone, Nancy L.; Johnson, Eric O.; Chen, Li-Shiun; Culverhouse, Robert; Doheny, Kimberly; Foltz, Steven M.; Fox, Louis; Gogarten, Stephanie M.; Hartz, Sarah; Hetrick, Kurt; Laurie, Cathy C.; Marosy, Beth; Amin, Najaf; Arnett, Donna; Barr, R. Graham; Bartz, Traci M.; Bertelsen, Sarah; Borecki, Ingrid B.; Brown, Michael R.; Chasman, Daniel I.; van Duijn, Cornelia M.; Feitosa, Mary F.; Fox, Ervin R.; Franceschini, Nora; Franco, Oscar H.; Grove, Megan L.; Guo, Xiuqing; Hofman, Albert; Kardia, Sharon L.R.; Morrison, Alanna C.; Musani, Solomon K.; Psaty, Bruce M.; Rao, D.C.; Reiner, Alex P.; Rice, Kenneth; Ridker, Paul M.; Rose, Lynda M.; Schick, Ursula M.; Schwander, Karen; Uitterlinden, Andre G.; Vojinovic, Dina; Wang, Jen-Chyong; Ware, Erin B.; Wilson, Gregory; Yao, Jie; Zhao, Wei; Breslau, Naomi; Hatsukami, Dorothy; Stitzel, Jerry A.; Rice, John; Goate, Alison; Bierut, Laura J.
2015-01-01
The common nonsynonymous variant rs16969968 in the α5 nicotinic receptor subunit gene (CHRNA5) is the strongest genetic risk factor for nicotine dependence in European Americans and contributes to risk in African Americans. To comprehensively examine whether other CHRNA5 coding variation influences nicotine dependence risk, we performed targeted sequencing on 1582 nicotine dependent cases (Fagerström Test for Nicotine Dependence score≥4) and 1238 non-dependent controls, with independent replication of common and low frequency variants using 12 studies with exome chip data. Nicotine dependence was examined using logistic regression with individual common variants (MAF≥0.05), aggregate low frequency variants (0.05>MAF≥0.005), and aggregate rare variants (MAF<0.005). Meta-analysis of primary results was performed with replication studies containing 12 174 heavy and 11 290 light smokers. Next-generation sequencing with 180X coverage identified 24 nonsynonymous variants and 2 frameshift deletions in CHRNA5, including 9 novel variants in the 2820 subjects. Meta-analysis confirmed the risk effect of the only common variant (rs16969968, European ancestry: OR=1.3, p=3.5×10−11; African ancestry: OR=1.3, p=0.01) and demonstrated that 3 low frequency variants contributed an independent risk (aggregate term, European ancestry: OR=1.3, p=0.005; African ancestry: OR=1.4, p=0.0006). The remaining 22 rare coding variants were associated with increased risk of nicotine dependence in the European American primary sample (OR=12.9, p=0.01) and in the same risk direction in African Americans (OR=1.5, p=0.37). Our results indicate that common, low frequency and rare CHRNA5 coding variants are independently associated with nicotine dependence risk. These newly identified variants likely influence risk for smoking-related diseases such as lung cancer. PMID:26239294
Olfson, E; Saccone, N L; Johnson, E O; Chen, L-S; Culverhouse, R; Doheny, K; Foltz, S M; Fox, L; Gogarten, S M; Hartz, S; Hetrick, K; Laurie, C C; Marosy, B; Amin, N; Arnett, D; Barr, R G; Bartz, T M; Bertelsen, S; Borecki, I B; Brown, M R; Chasman, D I; van Duijn, C M; Feitosa, M F; Fox, E R; Franceschini, N; Franco, O H; Grove, M L; Guo, X; Hofman, A; Kardia, S L R; Morrison, A C; Musani, S K; Psaty, B M; Rao, D C; Reiner, A P; Rice, K; Ridker, P M; Rose, L M; Schick, U M; Schwander, K; Uitterlinden, A G; Vojinovic, D; Wang, J-C; Ware, E B; Wilson, G; Yao, J; Zhao, W; Breslau, N; Hatsukami, D; Stitzel, J A; Rice, J; Goate, A; Bierut, L J
2016-05-01
The common nonsynonymous variant rs16969968 in the α5 nicotinic receptor subunit gene (CHRNA5) is the strongest genetic risk factor for nicotine dependence in European Americans and contributes to risk in African Americans. To comprehensively examine whether other CHRNA5 coding variation influences nicotine dependence risk, we performed targeted sequencing on 1582 nicotine-dependent cases (Fagerström Test for Nicotine Dependence score⩾4) and 1238 non-dependent controls, with independent replication of common and low frequency variants using 12 studies with exome chip data. Nicotine dependence was examined using logistic regression with individual common variants (minor allele frequency (MAF)⩾0.05), aggregate low frequency variants (0.05>MAF⩾0.005) and aggregate rare variants (MAF<0.005). Meta-analysis of primary results was performed with replication studies containing 12 174 heavy and 11 290 light smokers. Next-generation sequencing with 180 × coverage identified 24 nonsynonymous variants and 2 frameshift deletions in CHRNA5, including 9 novel variants in the 2820 subjects. Meta-analysis confirmed the risk effect of the only common variant (rs16969968, European ancestry: odds ratio (OR)=1.3, P=3.5 × 10(-11); African ancestry: OR=1.3, P=0.01) and demonstrated that three low frequency variants contributed an independent risk (aggregate term, European ancestry: OR=1.3, P=0.005; African ancestry: OR=1.4, P=0.0006). The remaining 22 rare coding variants were associated with increased risk of nicotine dependence in the European American primary sample (OR=12.9, P=0.01) and in the same risk direction in African Americans (OR=1.5, P=0.37). Our results indicate that common, low frequency and rare CHRNA5 coding variants are independently associated with nicotine dependence risk. These newly identified variants likely influence the risk for smoking-related diseases such as lung cancer.
Pirim, Dilek; Wang, Xingbin; Niemsiri, Vipavee; Radwan, Zaheda H.; Bunker, Clareann H.; Hokanson, John E.; Hamman, Richard F.; Barmada, M. Michael; Demirci, F. Yesim; Kamboh, M. Ilyas
2015-01-01
Background Cholesteryl ester transfer protein (CETP) plays a crucial role in lipid metabolism. Associations of common CETP variants with variation in plasma lipid levels, and/or CETP mass/activity have been extensively studied and well-documented; however, the effects of uncommon/rare CETP variants on plasma lipid profile remain undefined. Hence, resequencing of the gene in extreme phenotypes and follow-up rare-variant association analyses are essential to fill this gap. Objective To identify common and uncommon/rare variants in the CETP gene by resequencing the entire gene and test the effects of both common and uncommon/rare CETP variants on plasma lipid traits in two genetically distinct populations. Methods and Results The entire CETP gene plus flanking regions were resequenced in 190 individuals comprising 95 non-Hispanic Whites (NHWs) and 95 African blacks with extreme HDL-C levels. A total of 279 sequence variants were identified, of which 25 were novel. Selected variants were genotyped in the entire samples of 623 NHWs and 788 African blacks and 184 QC-passed variants were tested in relation to plasma lipid traits by using gene-based, single-site, haplotype and rare variant association analyses (SKAT-O). Two novel and independent associations of rs1968905 and rs289740 with HDL-C were identified in African blacks. Using SKAT-O analysis, we also identified rare variants with minor allele frequency <0.01 to be associated with HDL-C in both NHWs (P=0.024) and African blacks (P=0.009). Conclusions Our results point out that in addition to the common CETP variants, rare genetic variants in the CETP gene also contribute to the phenotypic variation of HDL-C in the general population. PMID:26683795
Fry, Andrew E.; Ghansa, Anita; Small, Kerrin S.; Palma, Alejandro; Auburn, Sarah; Diakite, Mahamadou; Green, Angela; Campino, Susana; Teo, Yik Y.; Clark, Taane G.; Jeffreys, Anna E.; Wilson, Jonathan; Jallow, Muminatou; Sisay-Joof, Fatou; Pinder, Margaret; Griffiths, Michael J.; Peshu, Norbert; Williams, Thomas N.; Newton, Charles R.; Marsh, Kevin; Molyneux, Malcolm E.; Taylor, Terrie E.; Koram, Kwadwo A.; Oduro, Abraham R.; Rogers, William O.; Rockett, Kirk A.; Sabeti, Pardis C.; Kwiatkowski, Dominic P.
2009-01-01
The prevalence of CD36 deficiency in East Asian and African populations suggests that the causal variants are under selection by severe malaria. Previous analysis of data from the International HapMap Project indicated that a CD36 haplotype bearing a nonsense mutation (T1264G; rs3211938) had undergone recent positive selection in the Yoruba of Nigeria. To investigate the global distribution of this putative selection event, we genotyped T1264G in 3420 individuals from 66 populations. We confirmed the high frequency of 1264G in the Yoruba (26%). However, the 1264G allele is less common in other African populations and absent from all non-African populations without recent African admixture. Using long-range linkage disequilibrium, we studied two West African groups in depth. Evidence for recent positive selection at the locus was demonstrable in the Yoruba, although not in Gambians. We screened 70 variants from across CD36 for an association with severe malaria phenotypes, employing a case–control study of 1350 subjects and a family study of 1288 parent–offspring trios. No marker was significantly associated with severe malaria. We focused on T1264G, genotyping 10 922 samples from four African populations. The nonsense allele was not associated with severe malaria (pooled allelic odds ratio 1.0; 95% confidence interval 0.89–1.12; P = 0.98). These results suggest a range of possible explanations including the existence of alternative selection pressures on CD36, co-evolution between host and parasite or confounding caused by allelic heterogeneity of CD36 deficiency. PMID:19403559
Fry, Andrew E; Ghansa, Anita; Small, Kerrin S; Palma, Alejandro; Auburn, Sarah; Diakite, Mahamadou; Green, Angela; Campino, Susana; Teo, Yik Y; Clark, Taane G; Jeffreys, Anna E; Wilson, Jonathan; Jallow, Muminatou; Sisay-Joof, Fatou; Pinder, Margaret; Griffiths, Michael J; Peshu, Norbert; Williams, Thomas N; Newton, Charles R; Marsh, Kevin; Molyneux, Malcolm E; Taylor, Terrie E; Koram, Kwadwo A; Oduro, Abraham R; Rogers, William O; Rockett, Kirk A; Sabeti, Pardis C; Kwiatkowski, Dominic P
2009-07-15
The prevalence of CD36 deficiency in East Asian and African populations suggests that the causal variants are under selection by severe malaria. Previous analysis of data from the International HapMap Project indicated that a CD36 haplotype bearing a nonsense mutation (T1264G; rs3211938) had undergone recent positive selection in the Yoruba of Nigeria. To investigate the global distribution of this putative selection event, we genotyped T1264G in 3420 individuals from 66 populations. We confirmed the high frequency of 1264G in the Yoruba (26%). However, the 1264G allele is less common in other African populations and absent from all non-African populations without recent African admixture. Using long-range linkage disequilibrium, we studied two West African groups in depth. Evidence for recent positive selection at the locus was demonstrable in the Yoruba, although not in Gambians. We screened 70 variants from across CD36 for an association with severe malaria phenotypes, employing a case-control study of 1350 subjects and a family study of 1288 parent-offspring trios. No marker was significantly associated with severe malaria. We focused on T1264G, genotyping 10,922 samples from four African populations. The nonsense allele was not associated with severe malaria (pooled allelic odds ratio 1.0; 95% confidence interval 0.89-1.12; P = 0.98). These results suggest a range of possible explanations including the existence of alternative selection pressures on CD36, co-evolution between host and parasite or confounding caused by allelic heterogeneity of CD36 deficiency.
Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise
Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M.
2014-01-01
Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants. PMID:25409314
Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.
Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M
2014-01-01
Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical "noise" that warrant further analysis for causal variants.
Khovidhunkit, Weerapan; Charoen, Supannika; Kiateprungvej, Arunrat; Chartyingcharoen, Palm; Muanpetch, Suwanna; Plengpanich, Wanee
2016-01-01
Severe hypertriglyceridemia usually results from a combination of genetic and environmental factors. Few data exist on the genetics of severe hypertriglyceridemia in Asian populations. To examine the genetic variants of 3 candidate genes known to influence triglyceride metabolism, LPL, APOC2, and APOA5, which encode lipoprotein lipase, apolipoprotein C-II, and apolipoprotein A-V, respectively, in a large group of Thai subjects with severe hypertriglyceridemia. We identified sequence variants of LPL, APOC2, and APOA5 by sequencing exons and exon-intron junctions in 101 subjects with triglyceride levels ≥ 10 mmol/L (886 mg/dL) and compared with those of 111 normotriglyceridemic subjects. Six different rare variants in LPL were found in 13 patients, 2 of which were novel (1 heterozygous missense variant: p.Arg270Gly and 1 frameshift variant: p.Asp308Glyfs*3). Four previously identified heterozygous missense variants in LPL were p.Ala98Thr, p.Leu279Val, p.Leu279Arg, and p.Arg432Thr. Collectively, these rare variants were found only in the hypertriglyceridemic group but not in the control group (13% vs 0%, P < .0001). One common variant in APOA5 (p.Gly185Cys, rs2075291) was found at a higher frequency in the hypertriglyceridemic group compared with the control group (25% vs 6%, respectively, P < .0005). Altogether, rare variants in LPL or APOA5 and/or the common APOA5 p.Gly185Cys variant were found in 37% of the hypertriglyceridemic group vs 6% in the controls (P = 3.1 × 10(-8)). No rare variant in APOC2 was identified. Rare variants in LPL and a common variant in APOA5 were more commonly found in Thai subjects with severe hypertriglyceridemia. A common p.Gly185Cys APOA5 variant, in particular, was quite prevalent and potentially contributed to hypertriglyceridemia in this group of patients. Copyright © 2015 National Lipid Association. Published by Elsevier Inc. All rights reserved.
Manning, Alisa; Highland, Heather M; Gasser, Jessica; Sim, Xueling; Tukiainen, Taru; Fontanillas, Pierre; Grarup, Niels; Rivas, Manuel A; Mahajan, Anubha; Locke, Adam E; Cingolani, Pablo; Pers, Tune H; Viñuela, Ana; Brown, Andrew A; Wu, Ying; Flannick, Jason; Fuchsberger, Christian; Gamazon, Eric R; Gaulton, Kyle J; Im, Hae Kyung; Teslovich, Tanya M; Blackwell, Thomas W; Bork-Jensen, Jette; Burtt, Noël P; Chen, Yuhui; Green, Todd; Hartl, Christopher; Kang, Hyun Min; Kumar, Ashish; Ladenvall, Claes; Ma, Clement; Moutsianas, Loukas; Pearson, Richard D; Perry, John R B; Rayner, N William; Robertson, Neil R; Scott, Laura J; van de Bunt, Martijn; Eriksson, Johan G; Jula, Antti; Koskinen, Seppo; Lehtimäki, Terho; Palotie, Aarno; Raitakari, Olli T; Jacobs, Suzanne B R; Wessel, Jennifer; Chu, Audrey Y; Scott, Robert A; Goodarzi, Mark O; Blancher, Christine; Buck, Gemma; Buck, David; Chines, Peter S; Gabriel, Stacey; Gjesing, Anette P; Groves, Christopher J; Hollensted, Mette; Huyghe, Jeroen R; Jackson, Anne U; Jun, Goo; Justesen, Johanne Marie; Mangino, Massimo; Murphy, Jacquelyn; Neville, Matt; Onofrio, Robert; Small, Kerrin S; Stringham, Heather M; Trakalo, Joseph; Banks, Eric; Carey, Jason; Carneiro, Mauricio O; DePristo, Mark; Farjoun, Yossi; Fennell, Timothy; Goldstein, Jacqueline I; Grant, George; Hrabé de Angelis, Martin; Maguire, Jared; Neale, Benjamin M; Poplin, Ryan; Purcell, Shaun; Schwarzmayr, Thomas; Shakir, Khalid; Smith, Joshua D; Strom, Tim M; Wieland, Thomas; Lindstrom, Jaana; Brandslund, Ivan; Christensen, Cramer; Surdulescu, Gabriela L; Lakka, Timo A; Doney, Alex S F; Nilsson, Peter; Wareham, Nicholas J; Langenberg, Claudia; Varga, Tibor V; Franks, Paul W; Rolandsson, Olov; Rosengren, Anders H; Farook, Vidya S; Thameem, Farook; Puppala, Sobha; Kumar, Satish; Lehman, Donna M; Jenkinson, Christopher P; Curran, Joanne E; Hale, Daniel Esten; Fowler, Sharon P; Arya, Rector; DeFronzo, Ralph A; Abboud, Hanna E; Syvänen, Ann-Christine; Hicks, Pamela J; Palmer, Nicholette D; Ng, Maggie C Y; Bowden, Donald W; Freedman, Barry I; Esko, Tõnu; Mägi, Reedik; Milani, Lili; Mihailov, Evelin; Metspalu, Andres; Narisu, Narisu; Kinnunen, Leena; Bonnycastle, Lori L; Swift, Amy; Pasko, Dorota; Wood, Andrew R; Fadista, João; Pollin, Toni I; Barzilai, Nir; Atzmon, Gil; Glaser, Benjamin; Thorand, Barbara; Strauch, Konstantin; Peters, Annette; Roden, Michael; Müller-Nurasyid, Martina; Liang, Liming; Kriebel, Jennifer; Illig, Thomas; Grallert, Harald; Gieger, Christian; Meisinger, Christa; Lannfelt, Lars; Musani, Solomon K; Griswold, Michael; Taylor, Herman A; Wilson, Gregory; Correa, Adolfo; Oksa, Heikki; Scott, William R; Afzal, Uzma; Tan, Sian-Tsung; Loh, Marie; Chambers, John C; Sehmi, Jobanpreet; Kooner, Jaspal Singh; Lehne, Benjamin; Cho, Yoon Shin; Lee, Jong-Young; Han, Bok-Ghee; Käräjämäki, Annemari; Qi, Qibin; Qi, Lu; Huang, Jinyan; Hu, Frank B; Melander, Olle; Orho-Melander, Marju; Below, Jennifer E; Aguilar, David; Wong, Tien Yin; Liu, Jianjun; Khor, Chiea-Chuen; Chia, Kee Seng; Lim, Wei Yen; Cheng, Ching-Yu; Chan, Edmund; Tai, E Shyong; Aung, Tin; Linneberg, Allan; Isomaa, Bo; Meitinger, Thomas; Tuomi, Tiinamaija; Hakaste, Liisa; Kravic, Jasmina; Jørgensen, Marit E; Lauritzen, Torsten; Deloukas, Panos; Stirrups, Kathleen E; Owen, Katharine R; Farmer, Andrew J; Frayling, Timothy M; O'Rahilly, Stephen P; Walker, Mark; Levy, Jonathan C; Hodgkiss, Dylan; Hattersley, Andrew T; Kuulasmaa, Teemu; Stančáková, Alena; Barroso, Inês; Bharadwaj, Dwaipayan; Chan, Juliana; Chandak, Giriraj R; Daly, Mark J; Donnelly, Peter J; Ebrahim, Shah B; Elliott, Paul; Fingerlin, Tasha; Froguel, Philippe; Hu, Cheng; Jia, Weiping; Ma, Ronald C W; McVean, Gilean; Park, Taesung; Prabhakaran, Dorairaj; Sandhu, Manjinder; Scott, James; Sladek, Rob; Tandon, Nikhil; Teo, Yik Ying; Zeggini, Eleftheria; Watanabe, Richard M; Koistinen, Heikki A; Kesaniemi, Y Antero; Uusitupa, Matti; Spector, Timothy D; Salomaa, Veikko; Rauramaa, Rainer; Palmer, Colin N A; Prokopenko, Inga; Morris, Andrew D; Bergman, Richard N; Collins, Francis S; Lind, Lars; Ingelsson, Erik; Tuomilehto, Jaakko; Karpe, Fredrik; Groop, Leif; Jørgensen, Torben; Hansen, Torben; Pedersen, Oluf; Kuusisto, Johanna; Abecasis, Gonçalo; Bell, Graeme I; Blangero, John; Cox, Nancy J; Duggirala, Ravindranath; Seielstad, Mark; Wilson, James G; Dupuis, Josee; Ripatti, Samuli; Hanis, Craig L; Florez, Jose C; Mohlke, Karen L; Meigs, James B; Laakso, Markku; Morris, Andrew P; Boehnke, Michael; Altshuler, David; McCarthy, Mark I; Gloyn, Anna L; Lindgren, Cecilia M
2017-07-01
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2 . © 2017 by the American Diabetes Association.
Lewis, S J; Lawlor, D A; Davey Smith, G; Araya, R; Timpson, N; Day, I N M; Ebrahim, S
2006-04-01
Low dietary folate intake has been implicated as a risk factor for depression. However, observational epidemiological studies are plagued by problems of confounding, reverse causality and measurement error. A common polymorphism (C677T) in MTHFR is associated with methyltetrahydrofolate reductase (MTHFR) activity and circulating folate and homocysteine levels and offers insights into whether the association between low folate and depression is causal. We genotyped this polymorphism in 3,478 women in the British Women's Heart and Health Study. In these women, we looked at the association between genotype and three indicators of depression; ever diagnosed as depressed, currently taking antidepressants and the EuroQol mood question. We also carried out a systematic review and meta-analysis of all published studies which have looked at the association between MTHFR C677T genotype and depression. In the British Women's Heart and Health Study, we found evidence of an increased risk of ever being diagnosed as depressed in MTHFR C677T TT individuals compared with CC individuals, odds ratio (OR) 1.35(95% CI: 1.01, 1.80). Furthermore, we identified eight other studies, which have examined the association between depression and MTHFR C677T. We were able to include all of these studies in our meta-analysis together with our results, obtaining an overall summary OR of 1.36 (95% CI: 1.11, 1.67, P=0.003). Since this genotype influences the functioning of the folate metabolic pathway, these findings suggest that folate or its derivatives may be causally related to risk of depression. Molecular Psychiatry (2006) 11, 352-360. doi:10.1038/sj.mp.4001790; published online 10 January 2006.
Rees, Matthew G; Ng, David; Ruppert, Sarah; Turner, Clesson; Beer, Nicola L; Swift, Amy J; Morken, Mario A; Below, Jennifer E; Blech, Ilana; Mullikin, James C; McCarthy, Mark I; Biesecker, Leslie G; Gloyn, Anna L; Collins, Francis S
2012-01-01
Defining the genetic contribution of rare variants to common diseases is a major basic and clinical science challenge that could offer new insights into disease etiology and provide potential for directed gene- and pathway-based prevention and treatment. Common and rare nonsynonymous variants in the GCKR gene are associated with alterations in metabolic traits, most notably serum triglyceride levels. GCKR encodes glucokinase regulatory protein (GKRP), a predominantly nuclear protein that inhibits hepatic glucokinase (GCK) and plays a critical role in glucose homeostasis. The mode of action of rare GCKR variants remains unexplored. We identified 19 nonsynonymous GCKR variants among 800 individuals from the ClinSeq medical sequencing project. Excluding the previously described common missense variant p.Pro446Leu, all variants were rare in the cohort. Accordingly, we functionally characterized all variants to evaluate their potential phenotypic effects. Defects were observed for the majority of the rare variants after assessment of cellular localization, ability to interact with GCK, and kinetic activity of the encoded proteins. Comparing the individuals with functional rare variants to those without such variants showed associations with lipid phenotypes. Our findings suggest that, while nonsynonymous GCKR variants, excluding p.Pro446Leu, are rare in individuals of mixed European descent, the majority do affect protein function. In sum, this study utilizes computational, cell biological, and biochemical methods to present a model for interpreting the clinical significance of rare genetic variants in common disease.
ERIC Educational Resources Information Center
White, Peter A.
2009-01-01
Many kinds of common and easily observed causal relations exhibit property transmission, which is a tendency for the causal object to impose its own properties on the effect object. It is proposed that property transmission becomes a general and readily available hypothesis used to make interpretations and judgments about causal questions under…
‘US Furr’ and ‘US Furr-ST’ Mandarin
USDA-ARS?s Scientific Manuscript database
This document marks the official release of ‘US Furr’, a hybrid of ‘Clementine’ x ‘Murcott’, and ‘US Furr-ST’, an irradiated variant of ‘US Furr’ with apparent field tolerance to citrus scab (causal agent Elsinoe fawcetti Bitanc. and Jenk.). The hybridization creating ‘US Furr’ and ultimately ‘US Fu...
Kill or Die: Moral Judgment Alters Linguistic Coding of Causality
ERIC Educational Resources Information Center
De Freitas, Julian; DeScioli, Peter; Nemirow, Jason; Massenkoff, Maxim; Pinker, Steven
2017-01-01
What is the relationship between the language people use to describe an event and their moral judgments? We test the hypothesis that moral judgment and causative verbs rely on the same underlying mental model of people's actions. Experiment 1a finds that participants choose different verbs to describe the major variants of a moral dilemma, the…
Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases.
Groth, Kristian A; Von Kodolitsch, Yskert; Kutsche, Kerstin; Gaustadnes, Mette; Thorsen, Kasper; Andersen, Niels H; Gravholt, Claus H
2017-07-01
Genetic FBN1 testing is pivotal for confirming the clinical diagnosis of Marfan syndrome. In an effort to evaluate variant causality, FBN1 databases are often used. We evaluated the current databases regarding FBN1 variants and validated associated phenotype records with a new Marfan syndrome geno-phenotyping tool called the Marfan score. We evaluated four databases (UMD-FBN1, ClinVar, the Human Gene Mutation Database (HGMD), and Uniprot) containing 2,250 FBN1 variants supported by 4,904 records presented in 307 references. The Marfan score calculated for phenotype data from the records quantified variant associations with Marfan syndrome phenotype. We calculated a Marfan score for 1,283 variants, of which we confirmed the database diagnosis of Marfan syndrome in 77.1%. This represented only 35.8% of the total registered variants; 18.5-33.3% (UMD-FBN1 versus HGMD) of variants associated with Marfan syndrome in the databases could not be confirmed by the recorded phenotype. FBN1 databases can be imprecise and incomplete. Data should be used with caution when evaluating FBN1 variants. At present, the UMD-FBN1 database seems to be the biggest and best curated; therefore, it is the most comprehensive database. However, the need for better genotype-phenotype curated databases is evident, and we hereby present such a database.Genet Med advance online publication 01 December 2016.
Bone, William P.; Washington, Nicole L.; Buske, Orion J.; Adams, David R.; Davis, Joie; Draper, David; Flynn, Elise D.; Girdea, Marta; Godfrey, Rena; Golas, Gretchen; Groden, Catherine; Jacobsen, Julius; Köhler, Sebastian; Lee, Elizabeth M. J.; Links, Amanda E.; Markello, Thomas C.; Mungall, Christopher J.; Nehrebecky, Michele; Robinson, Peter N.; Sincan, Murat; Soldatos, Ariane G.; Tifft, Cynthia J.; Toro, Camilo; Trang, Heather; Valkanas, Elise; Vasilevsky, Nicole; Wahl, Colleen; Wolfe, Lynne A.; Boerkoel, Cornelius F.; Brudno, Michael; Haendel, Melissa A.; Gahl, William A.; Smedley, Damian
2016-01-01
Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Genet Med 18 6, 608–617. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein–protein association neighbors. Genet Med 18 6, 608–617. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Genet Med 18 6, 608–617. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders. Genet Med 18 6, 608–617. PMID:26562225
NASA Astrophysics Data System (ADS)
Besson, Ugo
2010-03-01
This paper presents an analysis of the different types of reasoning and physical explanation used in science, common thought, and physics teaching. It then reflects on the learning difficulties connected with these various approaches, and suggests some possible didactic strategies. Although causal reasoning occurs very frequently in common thought and daily life, it has long been the subject of debate and criticism among philosophers and scientists. In this paper, I begin by providing a description of some general tendencies of common reasoning that have been identified by didactic research. Thereafter, I briefly discuss the role of causality in science, as well as some different types of explanation employed in the field of physics. I then present some results of a study examining the causal reasoning used by students in solid and fluid mechanics. The differences found between the types of reasoning typical of common thought and those usually proposed during instruction can create learning difficulties and impede student motivation. Many students do not seem satisfied by the mere application of formal laws and functional relations. Instead, they express the need for a causal explanation, a mechanism that allows them to understand how a state of affairs has come about. I discuss few didactic strategies aimed at overcoming these problems, and describe, in general terms, two examples of mechanics teaching sequences which were developed and tested in different contexts. The paper ends with a reflection on the possible role to be played in physics learning by intuitive and imaginative thought, and the use of simple explanatory models based on physical analogies and causal mechanisms.
Torrezan, Giovana T; de Almeida, Fernanda G Dos Santos R; Figueiredo, Márcia C P; Barros, Bruna D de Figueiredo; de Paula, Cláudia A A; Valieris, Renan; de Souza, Jorge E S; Ramalho, Rodrigo F; da Silva, Felipe C C; Ferreira, Elisa N; de Nóbrega, Amanda F; Felicio, Paula S; Achatz, Maria I; de Souza, Sandro J; Palmero, Edenir I; Carraro, Dirce M
2018-01-01
Pathogenic variants in known breast cancer (BC) predisposing genes explain only about 30% of Hereditary Breast Cancer (HBC) cases, whereas the underlying genetic factors for most families remain unknown. Here, we used whole-exome sequencing (WES) to identify genetic variants associated to HBC in 17 patients of Brazil with familial BC and negative for causal variants in major BC risk genes ( BRCA1/2, TP53 , and CHEK2 c.1100delC). First, we searched for rare variants in 27 known HBC genes and identified two patients harboring truncating pathogenic variants in ATM and BARD1 . For the remaining 15 negative patients, we found a substantial vast number of rare genetic variants. Thus, for selecting the most promising variants we used functional-based variant prioritization, followed by NGS validation, analysis in a control group, cosegregation analysis in one family and comparison with previous WES studies, shrinking our list to 23 novel BC candidate genes, which were evaluated in an independent cohort of 42 high-risk BC patients. Rare and possibly damaging variants were identified in 12 candidate genes in this cohort, including variants in DNA repair genes ( ERCC1 and SXL4 ) and other cancer-related genes ( NOTCH2, ERBB2, MST1R , and RAF1 ). Overall, this is the first WES study applied for identifying novel genes associated to HBC in Brazilian patients, in which we provide a set of putative BC predisposing genes. We also underpin the value of using WES for assessing the complex landscape of HBC susceptibility, especially in less characterized populations.
Identification of POMC exonic variants associated with substance dependence and body mass index.
Wang, Fan; Gelernter, Joel; Kranzler, Henry R; Zhang, Huiping
2012-01-01
Risk of substance dependence (SD) and obesity has been linked to the function of melanocortin peptides encoded by the proopiomelanocortin gene (POMC). POMC exons were Sanger sequenced in 280 African Americans (AAs) and 308 European Americans (EAs). Among them, 311 (167 AAs and 114 EAs) were affected with substance (alcohol, cocaine, opioid and/or marijuana) dependence and 277 (113 AAs and164 EAs) were screened controls. We identified 23 variants, including two common polymorphisms (rs10654394 and rs1042571) and 21 rare variants; 12 of which were novel. We used logistic regression to analyze the association between the two common variants and SD or body mass index (BMI), with sex, age, and ancestry proportion as covariates. The common variant rs1042571 in the 3'UTR was significantly associated with BMI in EAs (Overweight: P(adj) = 0.005; Obese: P(adj) = 0.018; Overweight+Obese: P(adj) = 0.002) but not in AAs. The common variant, rs10654394, was not associated with BMI and neither common variant was associated with SD in either population. To evaluate the association between the rare variants and SD or BMI, we collapsed rare variants and tested their prevalence using Fisher's exact test. In AAs, rare variants were nominally associated with SD overall and with specific SD traits (SD: P(FET,1df) = 0.026; alcohol dependence: P(FET,1df) = 0.027; cocaine dependence: P(FET,1df) = 0.007; marijuana dependence: P(FET,1df) = 0.050) (the P-value from cocaine dependence analysis survived Bonferroni correction). There was no such effect in EAs. Although the frequency of the rare variants did not differ significantly between the normal-weight group and the overweight or obese group in either population, certain rare exonic variants occurred only in overweight or obese subjects without SD. These findings suggest that POMC exonic variants may influence risk for both SD and elevated BMI, in a population-specific manner. However, common and rare variants in this gene may exert different effects on these two phenotypes.
Multi-gene panel testing in Korean patients with common genetic generalized epilepsy syndromes.
Lee, Cha Gon; Lee, Jeehun; Lee, Munhyang
2018-01-01
Genetic heterogeneity of common genetic generalized epilepsy syndromes is frequently considered. The present study conducted a focused analysis of potential candidate or susceptibility genes for common genetic generalized epilepsy syndromes using multi-gene panel testing with next-generation sequencing. This study included patients with juvenile myoclonic epilepsy, juvenile absence epilepsy, and epilepsy with generalized tonic-clonic seizures alone. We identified pathogenic variants according to the American College of Medical Genetics and Genomics guidelines and identified susceptibility variants using case-control association analyses and family analyses for familial cases. A total of 57 patients were enrolled, including 51 sporadic cases and 6 familial cases. Twenty-two pathogenic and likely pathogenic variants of 16 different genes were identified. CACNA1H was the most frequently observed single gene. Variants of voltage-gated Ca2+ channel genes, including CACNA1A, CACNA1G, and CACNA1H were observed in 32% of variants (n = 7/22). Analyses to identify susceptibility variants using case-control association analysis indicated that KCNMA1 c.400G>C was associated with common genetic generalized epilepsy syndromes. Only 1 family (family A) exhibited a candidate pathogenic variant p.(Arg788His) on CACNA1H, as determined via family analyses. This study identified candidate genetic variants in about a quarter of patients (n = 16/57) and an average of 2.8 variants was identified in each patient. The results reinforced the polygenic disorder with very high locus and allelic heterogeneity of common GGE syndromes. Further, voltage-gated Ca2+ channels are suggested as important contributors to common genetic generalized epilepsy syndromes. This study extends our comprehensive understanding of common genetic generalized epilepsy syndromes.
Nonlocal character of quantum theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stapp, H.P.
1997-04-01
According to a common conception of causality, the truth of a statement that refers only to phenomena confined to an earlier time cannot depend upon which measurement an experimenter will freely choose to perform at a later time. According to a common idea of the theory of relativity this causality condition should be valid in all Lorentz frames. It is shown here that this concept of relativistic causality is incompatible with some simple predictions of quantum theory. {copyright} {ital 1997 American Association of Physics Teachers.}
Designs of Empirical Evaluations of Nonexperimental Methods in Field Settings.
Wong, Vivian C; Steiner, Peter M
2018-01-01
Over the last three decades, a research design has emerged to evaluate the performance of nonexperimental (NE) designs and design features in field settings. It is called the within-study comparison (WSC) approach or the design replication study. In the traditional WSC design, treatment effects from a randomized experiment are compared to those produced by an NE approach that shares the same target population. The nonexperiment may be a quasi-experimental design, such as a regression-discontinuity or an interrupted time-series design, or an observational study approach that includes matching methods, standard regression adjustments, and difference-in-differences methods. The goals of the WSC are to determine whether the nonexperiment can replicate results from a randomized experiment (which provides the causal benchmark estimate), and the contexts and conditions under which these methods work in practice. This article presents a coherent theory of the design and implementation of WSCs for evaluating NE methods. It introduces and identifies the multiple purposes of WSCs, required design components, common threats to validity, design variants, and causal estimands of interest in WSCs. It highlights two general approaches for empirical evaluations of methods in field settings, WSC designs with independent and dependent benchmark and NE arms. This article highlights advantages and disadvantages for each approach, and conditions and contexts under which each approach is optimal for addressing methodological questions.
Etiology in psychiatry: embracing the reality of poly‐gene‐environmental causation of mental illness
Uher, Rudolf; Zwicker, Alyson
2017-01-01
Intriguing findings on genetic and environmental causation suggest a need to reframe the etiology of mental disorders. Molecular genetics shows that thousands of common and rare genetic variants contribute to mental illness. Epidemiological studies have identified dozens of environmental exposures that are associated with psychopathology. The effect of environment is likely conditional on genetic factors, resulting in gene‐environment interactions. The impact of environmental factors also depends on previous exposures, resulting in environment‐environment interactions. Most known genetic and environmental factors are shared across multiple mental disorders. Schizophrenia, bipolar disorder and major depressive disorder, in particular, are closely causally linked. Synthesis of findings from twin studies, molecular genetics and epidemiological research suggests that joint consideration of multiple genetic and environmental factors has much greater explanatory power than separate studies of genetic or environmental causation. Multi‐factorial gene‐environment interactions are likely to be a generic mechanism involved in the majority of cases of mental illness, which is only partially tapped by existing gene‐environment studies. Future research may cut across psychiatric disorders and address poly‐causation by considering multiple genetic and environmental measures across the life course with a specific focus on the first two decades of life. Integrative analyses of poly‐causation including gene‐environment and environment‐environment interactions can realize the potential for discovering causal types and mechanisms that are likely to generate new preventive and therapeutic tools. PMID:28498595
Poisson Approximation-Based Score Test for Detecting Association of Rare Variants.
Fang, Hongyan; Zhang, Hong; Yang, Yaning
2016-07-01
Genome-wide association study (GWAS) has achieved great success in identifying genetic variants, but the nature of GWAS has determined its inherent limitations. Under the common disease rare variants (CDRV) hypothesis, the traditional association analysis methods commonly used in GWAS for common variants do not have enough power for detecting rare variants with a limited sample size. As a solution to this problem, pooling rare variants by their functions provides an efficient way for identifying susceptible genes. Rare variant typically have low frequencies of minor alleles, and the distribution of the total number of minor alleles of the rare variants can be approximated by a Poisson distribution. Based on this fact, we propose a new test method, the Poisson Approximation-based Score Test (PAST), for association analysis of rare variants. Two testing methods, namely, ePAST and mPAST, are proposed based on different strategies of pooling rare variants. Simulation results and application to the CRESCENDO cohort data show that our methods are more powerful than the existing methods. © 2016 John Wiley & Sons Ltd/University College London.
How important are rare variants in common disease?
Saint Pierre, Aude; Génin, Emmanuelle
2014-09-01
Genome-wide association studies have uncovered hundreds of common genetic variants involved in complex diseases. However, for most complex diseases, these common genetic variants only marginally contribute to disease susceptibility. It is now argued that rare variants located in different genes could in fact play a more important role in disease susceptibility than common variants. These rare genetic variants were not captured by genome-wide association studies using single nucleotide polymorphism-chips but with the advent of next-generation sequencing technologies, they have become detectable. It is now possible to study their contribution to common disease by resequencing samples of cases and controls or by using new genotyping exome arrays that cover rare alleles. In this review, we address the question of the contribution of rare variants in common disease by taking the examples of different diseases for which some resequencing studies have already been performed, and by summarizing the results of simulation studies conducted so far to investigate the genetic architecture of complex traits in human. So far, empirical data have not allowed the exclusion of many models except the most extreme ones involving only a small number of rare variants with large effects contributing to complex disease. To unravel the genetic architecture of complex disease, case-control data will not be sufficient, and alternative study designs need to be proposed together with methodological developments. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
A variational Bayes discrete mixture test for rare variant association
Logsdon, Benjamin A.; Dai, James Y.; Auer, Paul L.; Johnsen, Jill M.; Ganesh, Santhi K.; Smith, Nicholas L.; Wilson, James G.; Tracy, Russell P.; Lange, Leslie A.; Jiao, Shuo; Rich, Stephen S.; Lettre, Guillaume; Carlson, Christopher S.; Jackson, Rebecca D.; O’Donnell, Christopher J.; Wurfel, Mark M.; Nickerson, Deborah A.; Tang, Hua; Reiner, Alexander P.; Kooperberg, Charles
2014-01-01
Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that “aggregate” tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute’s Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans. PMID:24482836
A variational Bayes discrete mixture test for rare variant association.
Logsdon, Benjamin A; Dai, James Y; Auer, Paul L; Johnsen, Jill M; Ganesh, Santhi K; Smith, Nicholas L; Wilson, James G; Tracy, Russell P; Lange, Leslie A; Jiao, Shuo; Rich, Stephen S; Lettre, Guillaume; Carlson, Christopher S; Jackson, Rebecca D; O'Donnell, Christopher J; Wurfel, Mark M; Nickerson, Deborah A; Tang, Hua; Reiner, Alexander P; Kooperberg, Charles
2014-01-01
Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that "aggregate" tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute's Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans.
Johnsen, Jill M; Auer, Paul L; Morrison, Alanna C; Jiao, Shuo; Wei, Peng; Haessler, Jeffrey; Fox, Keolu; McGee, Sean R; Smith, Joshua D; Carlson, Christopher S; Smith, Nicholas; Boerwinkle, Eric; Kooperberg, Charles; Nickerson, Deborah A; Rich, Stephen S; Green, David; Peters, Ulrike; Cushman, Mary; Reiner, Alex P
2013-07-25
Several rare European von Willebrand disease missense variants of VWF (including p.Arg2185Gln and p.His817Gln) were recently reported to be common in apparently healthy African Americans (AAs). Using data from the NHLBI Exome Sequencing Project, we assessed the association of these and other VWF coding variants with von Willebrand factor (VWF) and factor VIII (FVIII) levels in 4468 AAs. Of 30 nonsynonymous VWF variants, 6 were significantly and independently associated (P < .001) with levels of VWF and/or FVIII. Each additional copy of the common VWF variants encoding p.Thr789Ala or p.Asp1472His was associated with 6 to 8 IU/dL higher VWF levels. The VWF variant encoding p.Arg2185Gln was associated with 7 to 13 IU/dL lower VWF and FVIII levels. The type 2N-related VWF variant encoding p.His817Gln was associated with 17 IU/dL lower FVIII level but normal VWF level. A novel, rare missense VWF variant that predicts disruption of an O-glycosylation site (p.Ser1486Leu) and a rare variant encoding p.Arg2287Trp were each associated with 30 to 40 IU/dL lower VWF level (P < .001). In summary, several common and rare VWF missense variants contribute to phenotypic differences in VWF and FVIII among AAs.
Hemani, Gibran; Yang, Jian; Vinkhuyzen, Anna; Powell, Joseph E; Willemsen, Gonneke; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Mangino, Massimo; Valdes, Ana M; Medland, Sarah E; Madden, Pamela A; Heath, Andrew C; Henders, Anjali K; Nyholt, Dale R; de Geus, Eco J C; Magnusson, Patrik K E; Ingelsson, Erik; Montgomery, Grant W; Spector, Timothy D; Boomsma, Dorret I; Pedersen, Nancy L; Martin, Nicholas G; Visscher, Peter M
2013-11-07
Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 × 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 × 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Mining the human phenome using allelic scores that index biological intermediates.
Evans, David M; Brion, Marie Jo A; Paternoster, Lavinia; Kemp, John P; McMahon, George; Munafò, Marcus; Whitfield, John B; Medland, Sarah E; Montgomery, Grant W; Timpson, Nicholas J; St Pourcain, Beate; Lawlor, Debbie A; Martin, Nicholas G; Dehghan, Abbas; Hirschhorn, Joel; Smith, George Davey
2013-10-01
It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.
USDA-ARS?s Scientific Manuscript database
Barley Mla (Mildew resistance locus a) confers allele-specific interactions with natural variants of the ascomycete fungus, Blumeria graminis f. sp. hordei (Bgh), causal agent of powdery mildew disease. Significant reprogramming of host gene expression occurs upon infection by this obligate biotrop...
Genetic maps of stem rust resistance gene Sr35 in diploid and hexaploid wheat
USDA-ARS?s Scientific Manuscript database
Puccinia graminis f. sp. tritici is the causal agent of stem rust of wheat. A new race designated TTKSK (also known as Ug99) has recently spread through East Africa, Yemen and on to Iran. TTKSK and its variants (TTKST and TTTSK) are virulent to most of the stem rust resistance genes currently deploy...
Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R; Mahajan, Anubha; Asimit, Jennifer L; Ferreira, Teresa; Locke, Adam E; Robertson, Neil R; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E; Tam, Claudia H T; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I; Blangero, John; Burtt, Noél P; Duggirala, Ravindranath; Florez, Jose C; Hanis, Craig L; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C N; Ma, Ronald C W; Froguel, Philippe; Wilson, James G; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S; Chambers, John C; Saleheen, Danish; Kadowaki, Takashi; Tai, E Shyong; Mohlke, Karen L; Cox, Nancy J; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I; Morris, Andrew P
2016-05-15
To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. © The Author 2016. Published by Oxford University Press.
Etiology of depression comorbidity in combat-related PTSD: a review of the literature.
Stander, Valerie A; Thomsen, Cynthia J; Highfill-McRoy, Robyn M
2014-03-01
Posttraumatic stress disorder is often diagnosed with other mental health problems, particularly depression. Although PTSD comorbidity has been associated with more severe and chronic symptomology, relationships among commonly co-occurring disorders are not well understood. The purpose of this study was to review the literature regarding the development of depression comorbid with combat-related PTSD among military personnel. We summarize results of commonly tested hypotheses about the etiology of PTSD and depression comorbidity, including (1) causal hypotheses, (2) common factor hypotheses, and (3) potential confounds. Evidence suggests that PTSD may be a causal risk factor for subsequent depression; however, associations are likely complex, involving bidirectional causality, common risk factors, and common vulnerabilities. The unique nature of PTSD-depression comorbidity in the context of military deployment and combat exposure is emphasized. Implications of our results for clinical practice and future research are discussed. Published by Elsevier Ltd.
Glubb, Dylan M.; Johnatty, Sharon E.; Quinn, Michael C.J.; O’Mara, Tracy A.; Tyrer, Jonathan P.; Gao, Bo; Fasching, Peter A.; Beckmann, Matthias W.; Lambrechts, Diether; Vergote, Ignace; Velez Edwards, Digna R.; Beeghly-Fadiel, Alicia; Benitez, Javier; Garcia, Maria J.; Goodman, Marc T.; Thompson, Pamela J.; Dörk, Thilo; Dürst, Matthias; Modungo, Francesmary; Moysich, Kirsten; Heitz, Florian; du Bois, Andreas; Pfisterer, Jacobus; Hillemanns, Peter; Karlan, Beth Y.; Lester, Jenny; Goode, Ellen L.; Cunningham, Julie M.; Winham, Stacey J.; Larson, Melissa C.; McCauley, Bryan M.; Kjær, Susanne Krüger; Jensen, Allan; Schildkraut, Joellen M.; Berchuck, Andrew; Cramer, Daniel W.; Terry, Kathryn L.; Salvesen, Helga B.; Bjorge, Line; Webb, Penny M.; Grant, Peter; Pejovic, Tanja; Moffitt, Melissa; Hogdall, Claus K.; Hogdall, Estrid; Paul, James; Glasspool, Rosalind; Bernardini, Marcus; Tone, Alicia; Huntsman, David; Woo, Michelle; Group, AOCS; deFazio, Anna; Kennedy, Catherine J.; Pharoah, Paul D.P.; MacGregor, Stuart; Chenevix-Trench, Georgia
2017-01-01
We previously identified associations with ovarian cancer outcome at five genetic loci. To identify putatively causal genetic variants and target genes, we prioritized two ovarian outcome loci (1q22 and 19p12) for further study. Bioinformatic and functional genetic analyses indicated that MEF2D and ZNF100 are targets of candidate outcome variants at 1q22 and 19p12, respectively. At 19p12, the chromatin interaction of a putative regulatory element with the ZNF100 promoter region correlated with candidate outcome variants. At 1q22, putative regulatory elements enhanced MEF2D promoter activity and haplotypes containing candidate outcome variants modulated these effects. In a public dataset, MEF2D and ZNF100 expression were both associated with ovarian cancer progression-free or overall survival time. In an extended set of 6,162 epithelial ovarian cancer patients, we found that functional candidates at the 1q22 and 19p12 loci, as well as other regional variants, were nominally associated with patient outcome; however, no associations reached our threshold for statistical significance (p<1×10-5). Larger patient numbers will be needed to convincingly identify any true associations at these loci. PMID:29029385
Analysis of CHRNA7 rare variants in autism spectrum disorder susceptibility.
Bacchelli, Elena; Battaglia, Agatino; Cameli, Cinzia; Lomartire, Silvia; Tancredi, Raffaella; Thomson, Susanne; Sutcliffe, James S; Maestrini, Elena
2015-04-01
Chromosome 15q13.3 recurrent microdeletions are causally associated with a wide range of phenotypes, including autism spectrum disorder (ASD), seizures, intellectual disability, and other psychiatric conditions. Whether the reciprocal microduplication is pathogenic is less certain. CHRNA7, encoding for the alpha7 subunit of the neuronal nicotinic acetylcholine receptor, is considered the likely culprit gene in mediating neurological phenotypes in 15q13.3 deletion cases. To assess if CHRNA7 rare variants confer risk to ASD, we performed copy number variant analysis and Sanger sequencing of the CHRNA7 coding sequence in a sample of 135 ASD cases. Sequence variation in this gene remains largely unexplored, given the existence of a fusion gene, CHRFAM7A, which includes a nearly identical partial duplication of CHRNA7. Hence, attempts to sequence coding exons must distinguish between CHRNA7 and CHRFAM7A, making next-generation sequencing approaches unreliable for this purpose. A CHRNA7 microduplication was detected in a patient with autism and moderate cognitive impairment; while no rare damaging variants were identified in the coding region, we detected rare variants in the promoter region, previously described to functionally reduce transcription. This study represents the first sequence variant analysis of CHRNA7 in a sample of idiopathic autism. © 2015 Wiley Periodicals, Inc.
Caputo, Sandrine; Benboudjema, Louisa; Sinilnikova, Olga; Rouleau, Etienne; Béroud, Christophe; Lidereau, Rosette
2012-01-01
BRCA1 and BRCA2 are the two main genes responsible for predisposition to breast and ovarian cancers, as a result of protein-inactivating monoallelic mutations. It remains to be established whether many of the variants identified in these two genes, so-called unclassified/unknown variants (UVs), contribute to the disease phenotype or are simply neutral variants (or polymorphisms). Given the clinical importance of establishing their status, a nationwide effort to annotate these UVs was launched by laboratories belonging to the French GGC consortium (Groupe Génétique et Cancer), leading to the creation of the UMD-BRCA1/BRCA2 databases (http://www.umd.be/BRCA1/ and http://www.umd.be/BRCA2/). These databases have been endorsed by the French National Cancer Institute (INCa) and are designed to collect all variants detected in France, whether causal, neutral or UV. They differ from other BRCA databases in that they contain co-occurrence data for all variants. Using these data, the GGC French consortium has been able to classify certain UVs also contained in other databases. In this article, we report some novel UVs not contained in the BIC database and explore their impact in cancer predisposition based on a structural approach.
regSNPs: a strategy for prioritizing regulatory single nucleotide substitutions
Teng, Mingxiang; Ichikawa, Shoji; Padgett, Leah R.; Wang, Yadong; Mort, Matthew; Cooper, David N.; Koller, Daniel L.; Foroud, Tatiana; Edenberg, Howard J.; Econs, Michael J.; Liu, Yunlong
2012-01-01
Motivation: One of the fundamental questions in genetics study is to identify functional DNA variants that are responsible to a disease or phenotype of interest. Results from large-scale genetics studies, such as genome-wide association studies (GWAS), and the availability of high-throughput sequencing technologies provide opportunities in identifying causal variants. Despite the technical advances, informatics methodologies need to be developed to prioritize thousands of variants for potential causative effects. Results: We present regSNPs, an informatics strategy that integrates several established bioinformatics tools, for prioritizing regulatory SNPs, i.e. the SNPs in the promoter regions that potentially affect phenotype through changing transcription of downstream genes. Comparing to existing tools, regSNPs has two distinct features. It considers degenerative features of binding motifs by calculating the differences on the binding affinity caused by the candidate variants and integrates potential phenotypic effects of various transcription factors. When tested by using the disease-causing variants documented in the Human Gene Mutation Database, regSNPs showed mixed performance on various diseases. regSNPs predicted three SNPs that can potentially affect bone density in a region detected in an earlier linkage study. Potential effects of one of the variants were validated using luciferase reporter assay. Contact: yunliu@iupui.edu Supplementary information: Supplementary data are available at Bioinformatics online PMID:22611130
Power, Robert A; Kyaga, Simon; Uher, Rudolf; MacCabe, James H; Långström, Niklas; Landen, Mikael; McGuffin, Peter; Lewis, Cathryn M; Lichtenstein, Paul; Svensson, Anna C
2013-01-01
It is unknown how genetic variants conferring liability to psychiatric disorders survive in the population despite strong negative selection. However, this is key to understanding their etiology and designing studies to identify risk variants. To examine the reproductive fitness of patients with schizophrenia and other psychiatric disorders vs their unaffected siblings and to evaluate the level of selection on causal genetic variants. We measured the fecundity of patients with schizophrenia, autism, bipolar disorder, depression, anorexia nervosa, or substance abuse and their unaffected siblings compared with the general population. Population databases in Sweden, including the Multi-Generation Register and the Swedish Hospital Discharge Register. In total, 2.3 million individuals among the 1950 to 1970 birth cohort in Sweden. Fertility ratio (FR), reflecting the mean number of children compared with that of the general population, accounting for age, sex, family size, and affected status. Except for women with depression, affected patients had significantly fewer children (FR range for those with psychiatric disorder, 0.23-0.93; P < 10-10). This reduction was consistently greater among men than women, suggesting that male fitness was particularly sensitive. Although sisters of patients with schizophrenia and bipolar disorder had increased fecundity (FR range, 1.02-1.03; P < .01), this was too small on its own to counterbalance the reduced fitness of affected patients. Brothers of patients with schizophrenia and autism showed reduced fecundity (FR range, 0.94-0.97; P < .001). Siblings of patients with depression and substance abuse had significantly increased fecundity (FR range, 1.01-1.05; P < 10-10). In the case of depression, this more than compensated for the lower fecundity of affected individuals. Our results suggest that strong selection exists against schizophrenia, autism, and anorexia nervosa and that these variants may be maintained by new mutations or an as-yet unknown mechanism. Bipolar disorder did not seem to be under strong negative selection. Vulnerability to depression, and perhaps substance abuse, may be preserved by balancing selection, suggesting the involvement of common genetic variants in ways that depend on other genes and on environment.
Méndez-Vidal, Cristina; González-Del Pozo, María; Vela-Boza, Alicia; Santoyo-López, Javier; López-Domingo, Francisco J; Vázquez-Marouschek, Carmen; Dopazo, Joaquin; Borrego, Salud; Antiñolo, Guillermo
2013-01-01
Retinitis pigmentosa (RP) is an inherited retinal dystrophy characterized by extreme genetic and clinical heterogeneity. Thus, the diagnosis is not always easily performed due to phenotypic and genetic overlap. Current clinical practices have focused on the systematic evaluation of a set of known genes for each phenotype, but this approach may fail in patients with inaccurate diagnosis or infrequent genetic cause. In the present study, we investigated the genetic cause of autosomal recessive RP (arRP) in a Spanish family in which the causal mutation has not yet been identified with primer extension technology and resequencing. We designed a whole-exome sequencing (WES)-based approach using NimbleGen SeqCap EZ Exome V3 sample preparation kit and the SOLiD 5500×l next-generation sequencing platform. We sequenced the exomes of both unaffected parents and two affected siblings. Exome analysis resulted in the identification of 43,204 variants in the index patient. All variants passing filter criteria were validated with Sanger sequencing to confirm familial segregation and absence in the control population. In silico prediction tools were used to determine mutational impact on protein function and the structure of the identified variants. Novel Usher syndrome type 2A (USH2A) compound heterozygous mutations, c.4325T>C (p.F1442S) and c.15188T>G (p.L5063R), located in exons 20 and 70, respectively, were identified as probable causative mutations for RP in this family. Family segregation of the variants showed the presence of both mutations in all affected members and in two siblings who were apparently asymptomatic at the time of family ascertainment. Clinical reassessment confirmed the diagnosis of RP in these patients. Using WES, we identified two heterozygous novel mutations in USH2A as the most likely disease-causing variants in a Spanish family diagnosed with arRP in which the cause of the disease had not yet been identified with commonly used techniques. Our data reinforce the clinical role of WES in the molecular diagnosis of highly heterogeneous genetic diseases where conventional genetic approaches have previously failed in achieving a proper diagnosis.
Taylor, Amy E; Martin, Richard M; Geybels, Milan S; Stanford, Janet L; Shui, Irene; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Neal, David; Pashayan, Nora; Khaw, Kay-Tee; Blot, William; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Donovan, Jenny; Munafò, Marcus R
2017-01-15
Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all-cause and prostate cancer-specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high-grade compared to low-grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all-cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer-specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression. © 2016 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.
Liao, Hsiao-Mei; Liu, Hebing; Lei, Heiyan; Li, Bingjie; Chin, Pei-Ju; Tsai, Shien; Bhatia, Kishor; Gutierrez, Marina; Epelman, Sidnei; Biggar, Robert J; Nkrumah, Francis; Neequaye, Janet; Ogwang, Martin D; Reynolds, Steven J; Lo, Shyh-Ching; Mbulaiteye, Sam M
2018-06-02
Epstein-Barr virus (EBV) is linked to several cancers, including endemic Burkitt lymphoma (eBL), but causal variants are unknown. We recently reported novel sequence variants in the LMP-1 gene and promoter in EBV genomes sequenced from 13 of 14 BL biopsies. Alignments of the novel sequence variants for 114 published EBV genomes, including 27 from BL cases, revealed four LMP-1 variant patterns, designated A to D. Pattern A variant was found in 48% of BL EBV genomes. Here, we used PCR-Sanger sequencing to evaluate 50 additional BL biopsies from Ghana, Brazil, and Argentina, and peripheral blood samples from 113 eBL cases and 115 controls in Uganda. Pattern A was found in 60.9% of 64 BL biopsies evaluated. Compared to PCR-negative subjects in Uganda, detection of Pattern A in peripheral blood was associated with eBL case status (odds ratio [OR] 31.7, 95% confidence interval: 6.8⁻149), controlling for relevant confounders. Variant Pattern A and Pattern D were associated with eBL case status, but with lower ORs (9.7 and 13.6, respectively). Our results support the hypothesis that EBV LMP-1 Pattern A may be associated with eBL, but it is not the sole associated variant. Further research is needed to replicate and elucidate our findings.
Raghavan, Avanthi; Neeli, Hemanth; Jin, Weijun; Badellino, Karen O.; Demissie, Serkalem; Manning, Alisa K.; DerOhannessian, Stephanie L.; Wolfe, Megan L.; Cupples, L. Adrienne; Li, Mingyao; Kathiresan, Sekar; Rader, Daniel J.
2011-01-01
Genome-wide association studies (GWAS) have successfully identified loci associated with quantitative traits, such as blood lipids. Deep resequencing studies are being utilized to catalogue the allelic spectrum at GWAS loci. The goal of these studies is to identify causative variants and missing heritability, including heritability due to low frequency and rare alleles with large phenotypic impact. Whereas rare variant efforts have primarily focused on nonsynonymous coding variants, we hypothesized that noncoding variants in these loci are also functionally important. Using the HDL-C gene LIPG as an example, we explored the effect of regulatory variants identified through resequencing of subjects at HDL-C extremes on gene expression, protein levels, and phenotype. Resequencing a portion of the LIPG promoter and 5′ UTR in human subjects with extreme HDL-C, we identified several rare variants in individuals from both extremes. Luciferase reporter assays were used to measure the effect of these rare variants on LIPG expression. Variants conferring opposing effects on gene expression were enriched in opposite extremes of the phenotypic distribution. Minor alleles of a common regulatory haplotype and noncoding GWAS SNPs were associated with reduced plasma levels of the LIPG gene product endothelial lipase (EL), consistent with its role in HDL-C catabolism. Additionally, we found that a common nonfunctional coding variant associated with HDL-C (rs2000813) is in linkage disequilibrium with a 5′ UTR variant (rs34474737) that decreases LIPG promoter activity. We attribute the gene regulatory role of rs34474737 to the observed association of the coding variant with plasma EL levels and HDL-C. Taken together, the findings show that both rare and common noncoding regulatory variants are important contributors to the allelic spectrum in complex trait loci. PMID:22174694
Gat-Viks, Irit; Chevrier, Nicolas; Wilentzik, Roni; Eisenhaure, Thomas; Raychowdhury, Raktima; Steuerman, Yael; Shalek, Alex; Hacohen, Nir; Amit, Ido; Regev, Aviv
2013-01-01
Individual genetic variation affects gene expression in response to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness QTLs; reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant acts as an activator of the antiviral response; using RNAi, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli. PMID:23503680
Gat-Viks, Irit; Chevrier, Nicolas; Wilentzik, Roni; Eisenhaure, Thomas; Raychowdhury, Raktima; Steuerman, Yael; Shalek, Alex K; Hacohen, Nir; Amit, Ido; Regev, Aviv
2013-04-01
Individual genetic variation affects gene responsiveness to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness quantitative trait loci or reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant responds as an activator of the antiviral response; using RNA interference, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli.
Gonzaga-Jauregui, Claudia; Harel, Tamar; Gambin, Tomasz; Kousi, Maria; Griffin, Laurie B.; Francescatto, Ludmila; Ozes, Burcak; Karaca, Ender; Jhangiani, Shalini; Bainbridge, Matthew N.; Lawson, Kim S.; Pehlivan, Davut; Okamoto, Yuji; Withers, Marjorie; Mancias, Pedro; Slavotinek, Anne; Reitnauer, Pamela J; Goksungur, Meryem T.; Shy, Michael; Crawford, Thomas O.; Koenig, Michel; Willer, Jason; Flores, Brittany N.; Pediaditrakis, Igor; Us, Onder; Wiszniewski, Wojciech; Parman, Yesim; Antonellis, Anthony; Muzny, Donna M.; Katsanis, Nicholas; Battaloglu, Esra; Boerwinkle, Eric; Gibbs, Richard A.; Lupski, James R.
2015-01-01
Charcot-Marie-Tooth (CMT) disease is a clinically and genetically heterogeneous distal symmetric polyneuropathy. Whole-exome sequencing (WES) of 40 individuals from 37 unrelated families with CMT-like peripheral neuropathy refractory to molecular diagnosis identified apparent causal mutations in ~45% (17/37) of families. Three candidate disease genes are proposed, supported by a combination of genetic and in vivo studies. Aggregate analysis of mutation data revealed a significantly increased number of rare variants across 58 neuropathy associated genes in subjects versus controls; confirmed in a second ethnically discrete neuropathy cohort, suggesting mutation burden potentially contributes to phenotypic variability. Neuropathy genes shown to have highly penetrant Mendelizing variants (HMPVs) and implicated by burden in families were shown to interact genetically in a zebrafish assay exacerbating the phenotype established by the suppression of single genes. Our findings suggest that the combinatorial effect of rare variants contributes to disease burden and variable expressivity. PMID:26257172
Identification of Inherited Retinal Disease-Associated Genetic Variants in 11 Candidate Genes.
Astuti, Galuh D N; van den Born, L Ingeborgh; Khan, M Imran; Hamel, Christian P; Bocquet, Béatrice; Manes, Gaël; Quinodoz, Mathieu; Ali, Manir; Toomes, Carmel; McKibbin, Martin; El-Asrag, Mohammed E; Haer-Wigman, Lonneke; Inglehearn, Chris F; Black, Graeme C M; Hoyng, Carel B; Cremers, Frans P M; Roosing, Susanne
2018-01-10
Inherited retinal diseases (IRDs) display an enormous genetic heterogeneity. Whole exome sequencing (WES) recently identified genes that were mutated in a small proportion of IRD cases. Consequently, finding a second case or family carrying pathogenic variants in the same candidate gene often is challenging. In this study, we searched for novel candidate IRD gene-associated variants in isolated IRD families, assessed their causality, and searched for novel genotype-phenotype correlations. Whole exome sequencing was performed in 11 probands affected with IRDs. Homozygosity mapping data was available for five cases. Variants with minor allele frequencies ≤ 0.5% in public databases were selected as candidate disease-causing variants. These variants were ranked based on their: (a) presence in a gene that was previously implicated in IRD; (b) minor allele frequency in the Exome Aggregation Consortium database (ExAC); (c) in silico pathogenicity assessment using the combined annotation dependent depletion (CADD) score; and (d) interaction of the corresponding protein with known IRD-associated proteins. Twelve unique variants were found in 11 different genes in 11 IRD probands. Novel autosomal recessive and dominant inheritance patterns were found for variants in Small Nuclear Ribonucleoprotein U5 Subunit 200 ( SNRNP200 ) and Zinc Finger Protein 513 ( ZNF513 ), respectively. Using our pathogenicity assessment, a variant in DEAH-Box Helicase 32 ( DHX32 ) was the top ranked novel candidate gene to be associated with IRDs, followed by eight medium and lower ranked candidate genes. The identification of candidate disease-associated sequence variants in 11 single families underscores the notion that the previously identified IRD-associated genes collectively carry > 90% of the defects implicated in IRDs. To identify multiple patients or families with variants in the same gene and thereby provide extra proof for pathogenicity, worldwide data sharing is needed.
Temporal and Statistical Information in Causal Structure Learning
ERIC Educational Resources Information Center
McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David
2015-01-01
Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…
A quantum causal discovery algorithm
NASA Astrophysics Data System (ADS)
Giarmatzi, Christina; Costa, Fabio
2018-03-01
Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
Dobbyn, Amanda; Huckins, Laura M; Boocock, James; Sloofman, Laura G; Glicksberg, Benjamin S; Giambartolomei, Claudia; Hoffman, Gabriel E; Perumal, Thanneer M; Girdhar, Kiran; Jiang, Yan; Raj, Towfique; Ruderfer, Douglas M; Kramer, Robin S; Pinto, Dalila; Akbarian, Schahram; Roussos, Panos; Domenici, Enrico; Devlin, Bernie; Sklar, Pamela; Stahl, Eli A; Sieberts, Solveig K
2018-06-07
Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Oliveira, Jorge; Negrão, Luís; Fineza, Isabel; Taipa, Ricardo; Melo-Pires, Manuel; Fortuna, Ana Maria; Gonçalves, Ana Rita; Froufe, Hugo; Egas, Conceição; Santos, Rosário; Sousa, Mário
2015-06-01
Muscular dystrophies (MDs) are a group of hereditary muscle disorders that include two particularly heterogeneous subgroups: limb-girdle MD and congenital MD, linked to 52 different genes (seven common to both subgroups). Massive parallel sequencing technology may avoid the usual stepwise gene-by-gene analysis. We report the whole-exome sequencing (WES) analysis of a patient with childhood-onset progressive MD, also presenting mental retardation and dilated cardiomyopathy. Conventional sequencing had excluded eight candidate genes. WES of the trio (patient and parents) was performed using the ion proton sequencing system. Data analysis resorted to filtering steps using the GEMINI software revealed a novel silent variant in the choline kinase beta (CHKB) gene. Inspection of sequence alignments ultimately identified the causal variant (CHKB:c.1031+3G>C). This splice site mutation was confirmed using Sanger sequencing and its effect was further evaluated with gene expression analysis. On reassessment of the muscle biopsy, typical abnormal mitochondrial oxidative changes were observed. Mutations in CHKB have been shown to cause phosphatidylcholine deficiency in myofibers, causing a rare form of CMD (only 21 patients reported). Notwithstanding interpretative difficulties that need to be overcome before the integration of WES in the diagnostic workflow, this work corroborates its utility in solving cases from highly heterogeneous groups of diseases, in which conventional diagnostic approaches fail to provide a definitive diagnosis.
Amin Al Olama, Ali; Dadaev, Tokhir; Hazelett, Dennis J; Li, Qiuyan; Leongamornlert, Daniel; Saunders, Edward J; Stephens, Sarah; Cieza-Borrella, Clara; Whitmore, Ian; Benlloch Garcia, Sara; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel; Gronberg, Henrik; Wiklund, Fredrik; Aly, Markus; Henderson, Brian E; Schumacher, Fredrick; Haiman, Christopher A; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; Mcdonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokołorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Butterbach, Katja; Arndt, Volker; Park, Jong Y; Sellers, Thomas; Lin, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Govindasami, Koveela; Guy, Michelle; Lophatonanon, Artitaya; Muir, Kenneth; Viñuela, Ana; Brown, Andrew A; Freedman, Mathew; Conti, David V; Easton, Douglas; Coetzee, Gerhard A; Eeles, Rosalind A; Kote-Jarai, Zsofia
2015-10-01
Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region. © The Author 2015. Published by Oxford University Press.
Burden of Common Complex Disease Variants in the Exomes of Two Healthy Centenarian Brothers.
Tindale, Lauren C; Zeng, Andy; Bretherick, Karla L; Leach, Stephen; Thiessen, Nina; Brooks-Wilson, Angela R
2015-01-01
It is not understood whether long-term good health is promoted by the absence of disease risk variants, the presence of protective variants, or both. We characterized the exomes of two exceptionally healthy centenarian brothers aged 106 and 109 years who had never been diagnosed with cancer, cardiovascular disease, diabetes, Alzheimer's disease, or major pulmonary disease. The aim of this study was to gain insight into whether exceptional health and longevity are a result of carrying fewer disease-associated variants than typical individuals. We compared the number of disease-associated alleles, and the proportion of alleles predicted to be functionally damaging, between the centenarian brothers and published population data. Mitochondrial sequence reads were extracted from the exome data in order to analyze mitochondrial variants. The brothers carry a similar number of common disease-associated variants and predicted damaging variants compared to reference groups. They did not carry any high-penetrance clinically actionable variants. They carry mitochondrial haplogroup T, and one brother has a single heteroplasmic variant. Although our small sample size does not allow for definitive conclusions, a healthy aging and longevity phenotype is not necessarily due to a decreased burden of common disease-associated variants. Instead, it may be rare 'positive' variants that play a role in this desirable phenotype. © 2015 S. Karger AG, Basel.
Generalizability of Associations from Prostate Cancer GWAS in Multiple Populations
Waters, Kevin M.; Le Marchand, Loic; Kolonel, Laurence N.; Monroe, Kristine R.; Stram, Daniel O.; Henderson, Brian E.; Haiman, Christopher A.
2010-01-01
Genome-wide association studies have identified multiple common alleles associated with prostate cancer risk in populations of European ancestry. Testing these variants in other populations is needed to assess the generalizability of the associations, and may guide fine-mapping efforts. We examined 13 of these risk variants in a multiethnic sample of 2,768 incident prostate cancer cases and 2,359 controls from the Multiethnic Cohort (MEC; African Americans, European Americans, Latinos, Japanese Americans and Native Hawaiians). We estimated ethnic-specific and pooled odds ratios and tested for ethnic heterogeneity of effects using logistic regression. In ethnic-pooled analyses, 12 of the 13 variants were positively associated with risk, with statistically significant associations (p<0.05) noted with 6 variants (odds ratio, 95% confidence interval): JAZF1, rs10486567, 1.23(1.12–1.35); Xp11.2, rs5945572, 1.31(1.13–1.51); HNF1B, rs4430796, 1.15(1.06–1.25); MSMB, rs10993994, 1.13(1.04–1.23); 11q13.2, rs7931342, 1.13(1.03–1.23); 3p12.1, rs2660753, 1.11(1.01–1.21); SLC22A3, rs9364554, 1.10(1.00–1.21); CTBP2, rs12769019, 1.11(0.99–1.25); HNF1B, rs11649743, 1.10(0.99–1.22); EHBP1, rs721048, 1.08(0.94–1.25); KLK2/3, rs2735839, 1.06(0.97–1.16); 17q24.3, rs1859962, 1.04(0.96–1.13); and LMTK2, rs6465657, 0.99(0.89–1.09). Significant ethnic heterogeneity of effects was noted for 4 variants (EHBP1, phet = 3.9×10−3; 11q13, phet = 0.023; HNF1B (rs4430796), phet = 0.026; and KLK2/3, phet = 2.0×10−3). Although power was limited in some ethnic/racial groups due to variation in sample size and allele frequencies, these findings suggest that a large fraction of prostate cancer variants identified in populations of European ancestry are global markers of risk. For many of these regions, fine-mapping in non-European samples may help localize causal alleles and better determine their contribution to prostate cancer risk in the population. PMID:19318432
Clark, Shaunna L; McClay, Joseph L; Adkins, Daniel E; Aberg, Karolina A; Kumar, Gaurav; Nerella, Sri; Xie, Linying; Collins, Ann L; Crowley, James J; Quakenbush, Corey R; Hillard, Christopher E; Gao, Guimin; Shabalin, Andrey A; Peterson, Roseann E; Copeland, William E; Silberg, Judy L; Maes, Hermine; Sullivan, Patrick F; Costello, Elizabeth J; van den Oord, Edwin J
2016-05-01
Genome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5\\CHRNA3\\CHRNB4, CHRNB3\\CHRNA6 and EGLN2\\CYP2A6. Functional follow-up studies of these loci are needed to provide insight into biological mechanisms. However, these efforts have been hampered by a lack of knowledge about the specific causal variant(s) involved. In this study, we prioritized variants in terms of the likelihood they account for the reported associations. We employed targeted capture of the CHRNA5\\CHRNA3\\CHRNB4, CHRNB3\\CHRNA6, and EGLN2\\CYP2A6 loci and flanking regions followed by next-generation deep sequencing (mean coverage 78×) to capture genomic variation in 363 individuals. We performed single locus tests to determine if any single variant accounts for the association, and examined if sets of (rare) variants that overlapped with biologically meaningful annotations account for the associations. In total, we investigated 963 variants, of which 71.1% were rare (minor allele frequency < 0.01), 6.02% were insertion/deletions, and 51.7% were catalogued in dbSNP141. The single variant results showed that no variant fully accounts for the association in any region. In the variant set results, CHRNB4 accounts for most of the signal with significant sets consisting of directly damaging variants. CHRNA6 explains most of the signal in the CHRNB3\\CHRNA6 locus with significant sets indicating a regulatory role for CHRNA6. Significant sets in CYP2A6 involved directly damaging variants while the significant variant sets suggested a regulatory role for EGLN2. We found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
McClay, Joseph L.; Adkins, Daniel E.; Aberg, Karolina A.; Kumar, Gaurav; Nerella, Sri; Xie, Linying; Collins, Ann L.; Crowley, James J.; Quakenbush, Corey R.; Hillard, Christopher E.; Gao, Guimin; Shabalin, Andrey A.; Peterson, Roseann E.; Copeland, William E.; Silberg, Judy L.; Maes, Hermine; Sullivan, Patrick F.; Costello, Elizabeth J.; van den Oord, Edwin J.
2016-01-01
Abstract Introduction: Genome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5\\CHRNA3\\CHRNB4 , CHRNB3\\CHRNA6 and EGLN2\\CYP2A6 . Functional follow-up studies of these loci are needed to provide insight into biological mechanisms. However, these efforts have been hampered by a lack of knowledge about the specific causal variant(s) involved. In this study, we prioritized variants in terms of the likelihood they account for the reported associations. Methods: We employed targeted capture of the CHRNA5\\CHRNA3\\CHRNB4 , CHRNB3\\CHRNA6 , and EGLN2\\CYP2A6 loci and flanking regions followed by next-generation deep sequencing (mean coverage 78×) to capture genomic variation in 363 individuals. We performed single locus tests to determine if any single variant accounts for the association, and examined if sets of (rare) variants that overlapped with biologically meaningful annotations account for the associations. Results: In total, we investigated 963 variants, of which 71.1% were rare (minor allele frequency < 0.01), 6.02% were insertion/deletions, and 51.7% were catalogued in dbSNP141. The single variant results showed that no variant fully accounts for the association in any region. In the variant set results, CHRNB4 accounts for most of the signal with significant sets consisting of directly damaging variants. CHRNA6 explains most of the signal in the CHRNB3\\CHRNA6 locus with significant sets indicating a regulatory role for CHRNA6 . Significant sets in CYP2A6 involved directly damaging variants while the significant variant sets suggested a regulatory role for EGLN2 . Conclusions: We found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up. PMID:26283763
Hibbeln, Joseph R; SanGiovanni, John Paul; Golding, Jean; Emmett, Pauline M; Northstone, Kate; Davis, John M; Schuckit, Marc; Heron, Jon
2017-11-01
Reducing meat consumption is often advised; however, inadvertent nutritional deficiencies during pregnancy may result in residual neurodevelopmental harms to offspring. This study assessed possible effects of maternal diets in pregnancy on adverse substance use among adolescent offspring. Pregnant women and their 13-year-old offspring taking part in a prospective birth cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC), provided Food Frequency Questionnaire data from which dietary patterns were derived using principal components analysis. Multivariable logistic regression models including potential confounders evaluated adverse alcohol, cannabis, and tobacco use of the children at 15 years of age. Lower maternal meat consumption was associated with greater problematic substance use among 15-year-old offspring in dose-response patterns. Comparing never to daily meat consumption after adjustment, risks were greater for all categories of problem substance use: alcohol, odds ratio OR = 1.75, 95% CI = (1.23, 2.56), p < 0.001; tobacco use OR = 1.85, 95% CI = (1.28, 2.63), p < 0.001; and cannabis OR = 2.70, 95% CI = (1.89, 4.00), p < 0.001. Given the likelihood of residual confounding, potential causality was evaluated using stratification for maternal allelic variants that impact biological activity of cobalamin (vitamin B12) and iron. Lower meat consumption disproportionally increased the risks of offspring substance misuse among mothers with optimally functional (homozygous) variants (rs1801198) of the gene transcobalamin 2 gene (TCN2) which encodes the vitamin B12 transport protein transcobalamin 2 implicating a causal role for cobalamin deficits. Functional maternal variants in iron metabolism were unrelated to the adverse substance use. Risks potentially attributable to cobalamin deficits during pregnancy include adverse adolescent alcohol, cannabis, and tobacco use (14, 37, and 23, respectively). Lower prenatal meat consumption was associated with increased risks of adolescent substance misuse. Interactions between TCN2 variant status and meat intake implicate cobalamin deficiencies. Copyright © 2017 by the Research Society on Alcoholism.
The HABP2 G534E Variant Is an Unlikely Cause of Familial Nonmedullary Thyroid Cancer
Sahasrabudhe, Ruta; Stultz, Jacob; Williamson, John; Lott, Paul; Estrada, Ana; Bohorquez, Mabel; Palles, Claire; Polanco-Echeverry, Guadalupe; Jaeger, Emma; Martin, Lynn; Echeverry, Maria Magdalena; Tomlinson, Ian
2016-01-01
Context: A recent study reported the nonsynonymous G534E (rs7080536, allele A) variant in the HABP2 gene as causal in familial nonmedullary thyroid cancer (NMTC). Objective: The objective of this study was to evaluate the causality of HABP2 G534E in the TCUKIN study, a multicenter population-based study of NMTC cases from the British Isles. Design and Setting: A case-control analysis of rs7080536 genotypes was performed using 2105 TCUKIN cases and 5172 UK controls. Participants: Cases comprised 2105 NMTC cases. Patient subgroups with papillary (n = 1056), follicular (n = 691), and Hürthle cell (n = 86) thyroid cancer cases were studied separately. Controls comprised 5172 individuals from the 1958 Birth Cohort and the National Blood Donor Service study. The controls had previously been genotyped using genome-wide single nucleotide polymorphism arrays by the Wellcome Trust Case Control Consortium study. Outcome Measures: Association between HABP2 G534E (rs7080536A) and NMTC risk was evaluated using logistic regression. Results: The frequency of the HABP2 G534E was 4.2% in cases and 4.6% in controls. We did not detect an association between this variant and NMTC risk (odds ratio [OR] = 0.896; 95% confidence interval, 0.746–1.071; P = .233). We also failed to detect an association between the HABP2 G534E and cases with papillary (1056 cases; G534E frequency = 3.5%; OR = 0.74; P = .017), follicular (691 cases; G534E frequency = 4.7%; OR = 1.00; P = 1.000), or Hürthle cell (86 cases; G534E frequency = 6.3%; OR = 1.40; P = .279) histology. Conclusions: We found that HABP2 G534E is a low-to-moderate frequency variant in the British Isles and failed to detect an association with NMTC risk, independent of histological type. Hence, our study does not implicate HABP2 G534E or a correlated polymorphism in familial NMTC, and additional data are required before using this variant in NMTC risk assessment. PMID:26691890
The HABP2 G534E variant is an unlikely cause of familial non-medullary thyroid cancer.
Sahasrabudhe, Ruta; Stultz, Jacob; Williamson, John; Lott, Paul; Estrada, Ana; Bohorquez, Mabel; Palles, Claire; Polanco-Echeverry, Guadalupe; Jaeger, Emma; Martin, Lynn; Magdalena Echeverry, Maria; Tomlinson, Ian; Carvajal-Carmona, Luis G
2016-03-01
A recent study reported the non-synonymous G534E (rs7080536, allele A) variant in the HABP2 gene as causal in familial non-medullary thyroid cancer (NMTC). The objective of this study was to evaluate the causality of HABP2 G534E in the TCUKIN study, a multi-center population based study of NMTC cases from the British Isles. A case-control analysis of rs7080536 genotypes was performed using 2,105 TCUKIN cases and 5,172 UK controls. Cases comprised 2,105 NMTC cases. Patients sub-groups with papillary (N=1,056), follicular (N=691) and Hurthle cell (N=86) TC cases were studied separately. Controls comprised 5,172 individuals from the 1958 Birth Cohort (58C) and the National Blood Donor Service (NBS) study. The controls had previously been genotyped using genome-wide SNP arrays by the Wellcome Trust Case Control Consortium study. Measures: Association between HABP2 G534E (rs7080536A) and NMTC risk was evaluated using logistic regression. The frequency of HABP2 G534E was 4.2% in cases and 4.6% in controls. We did not detect an association between this variant and NMTC risk (OR=0.896, 95% CI: 0.746-1.071, P=0.233). We also failed to detect an association between HABP2 G534E and cases with papillary (1056 cases, G534E frequency= 3.5%, OR=0.74, P=0.017), follicular (691 cases, G534E frequency= 4.7%, OR=1.00, P=1.000) or Hurthle cell (86 cases, G534E frequency= 6.3%, OR=1.40, P=0.279) histology. We found that HABP2 G534E is a low-to-moderate frequency variant in the British Isles and failed to detect an association with NMTC risk, independent of histological type. Hence, our study does not implicate HABP2 G534E or a correlated polymorphism in familial NMTC and additional data are required before using this variant in NMTC risk assessment.
Differential control of ageing and lifespan by isoforms and splice variants across the mTOR network.
Razquin Navas, Patricia; Thedieck, Kathrin
2017-07-15
Ageing can be defined as the gradual deterioration of physiological functions, increasing the incidence of age-related disorders and the probability of death. Therefore, the term ageing not only reflects the lifespan of an organism but also refers to progressive functional impairment and disease. The nutrient-sensing kinase mTOR (mammalian target of rapamycin) is a major determinant of ageing. mTOR promotes cell growth and controls central metabolic pathways including protein biosynthesis, autophagy and glucose and lipid homoeostasis. The concept that mTOR has a crucial role in ageing is supported by numerous reports on the lifespan-prolonging effects of the mTOR inhibitor rapamycin in invertebrate and vertebrate model organisms. Dietary restriction increases lifespan and delays ageing phenotypes as well and mTOR has been assigned a major role in this process. This may suggest a causal relationship between the lifespan of an organism and its metabolic phenotype. More than 25 years after mTOR's discovery, a wealth of metabolic and ageing-related effects have been reported. In this review, we cover the current view on the contribution of the different elements of the mTOR signalling network to lifespan and age-related metabolic impairment. We specifically focus on distinct roles of isoforms and splice variants across the mTOR network. The comprehensive analysis of mouse knockout studies targeting these variants does not support a tight correlation between lifespan prolongation and improved metabolic phenotypes and questions the strict causal relationship between them. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.
2012-01-01
Background In observational epidemiological studies type 2 diabetes (T2D) and both low and high plasma concentrations of fasting glucose have been found to be associated with lower cognitive performance. These associations could be explained by confounding. Methods In this study we looked at the association between genetic variants, known to be robustly associated with fasting glucose and T2D risk, in the mother and her offspring to determine whether there is likely to be a causal link between early life exposure to glucose and child’s intelligence quotient (IQ) scores in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. We generated a fasting glucose (FGGRS) and a T2D (T2DGRS) genetic risk score and used them in a Mendelian randomization approach. Results We found a strong correlation between the FGGRS and fasting glucose plasma measurements that were available for a subset of children, but no association of either the maternal or the offspring FGGRS with child’s IQ was observed. In contrast, the maternal T2DGRS was positively associated with offspring IQ. Conclusions Maternal and offspring genetic variants which are associated with glucose levels are not associated with offspring IQ, suggesting that there is unlikely to be a causal link between glucose exposure in utero and IQ in childhood. Further exploration in even larger cohorts is required to exclude the possibility that our null findings were due to a lack of statistical power. PMID:23013243
Welderufael, B G; Løvendahl, Peter; de Koning, Dirk-Jan; Janss, Lucas L G; Fikse, W F
2018-01-01
Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to - but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t -test and a genome-wide significance level of P -value < 10 -4 was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to - or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2 ) and genes involved in macrophage recruitment and regulation of inflammations ( PDGFD and PTX3 ) were suggested as possible causal genes for susceptibility to - and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to - and recoverability from mastitis.
Education and coronary heart disease: mendelian randomisation study.
Tillmann, Taavi; Vaucher, Julien; Okbay, Aysu; Pikhart, Hynek; Peasey, Anne; Kubinova, Ruzena; Pajak, Andrzej; Tamosiunas, Abdonas; Malyutina, Sofia; Hartwig, Fernando Pires; Fischer, Krista; Veronesi, Giovanni; Palmer, Tom; Bowden, Jack; Davey Smith, George; Bobak, Martin; Holmes, Michael V
2017-08-30
Objective To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. Design Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. Setting The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors. Participants The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin. Exposure A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education. Main outcome measure Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D). Results Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10 -8 ). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile. Conclusions This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits.
Education and coronary heart disease: mendelian randomisation study
Vaucher, Julien; Okbay, Aysu; Pikhart, Hynek; Peasey, Anne; Kubinova, Ruzena; Pajak, Andrzej; Tamosiunas, Abdonas; Malyutina, Sofia; Hartwig, Fernando Pires; Fischer, Krista; Veronesi, Giovanni; Palmer, Tom; Bowden, Jack; Davey Smith, George; Bobak, Martin; Holmes, Michael V
2017-01-01
Objective To determine whether educational attainment is a causal risk factor in the development of coronary heart disease. Design Mendelian randomisation study, using genetic data as proxies for education to minimise confounding. Setting The main analysis used genetic data from two large consortia (CARDIoGRAMplusC4D and SSGAC), comprising 112 studies from predominantly high income countries. Findings from mendelian randomisation analyses were then compared against results from traditional observational studies (164 170 participants). Finally, genetic data from six additional consortia were analysed to investigate whether longer education can causally alter the common cardiovascular risk factors. Participants The main analysis was of 543 733 men and women (from CARDIoGRAMplusC4D and SSGAC), predominantly of European origin. Exposure A one standard deviation increase in the genetic predisposition towards higher education (3.6 years of additional schooling), measured by 162 genetic variants that have been previously associated with education. Main outcome measure Combined fatal and non-fatal coronary heart disease (63 746 events in CARDIoGRAMplusC4D). Results Genetic predisposition towards 3.6 years of additional education was associated with a one third lower risk of coronary heart disease (odds ratio 0.67, 95% confidence interval 0.59 to 0.77; P=3×10−8). This was comparable to findings from traditional observational studies (prevalence odds ratio 0.73, 0.68 to 0.78; incidence odds ratio 0.80, 0.76 to 0.83). Sensitivity analyses were consistent with a causal interpretation in which major bias from genetic pleiotropy was unlikely, although this remains an untestable possibility. Genetic predisposition towards longer education was additionally associated with less smoking, lower body mass index, and a favourable blood lipid profile. Conclusions This mendelian randomisation study found support for the hypothesis that low education is a causal risk factor in the development of coronary heart disease. Potential mechanisms could include smoking, body mass index, and blood lipids. In conjunction with the results from studies with other designs, these findings suggest that increasing education may result in substantial health benefits. PMID:28855160
USDA-ARS?s Scientific Manuscript database
A new race of Puccinia graminis f. sp. tritici, the causal pathogen of stem rust of wheat, designated TTKSK (also known as Ug99) and its variants are virulent to most of the stem rust resistance genes currently deployed in wheat cultivars worldwide. Therefore, identification, mapping and deployment ...
Srivorakun, Hataichanok; Singha, Kritsada; Fucharoen, Goonnapa; Sanchaisuriya, Kanokwan; Fucharoen, Supan
2014-01-01
Background Hemoglobin (Hb) variants are structurally inherited changes of globin chains. Accurate diagnoses of these variants are important for planning of appropriate management and genetic counseling. Since no epidemiological study has been conducted before, we have investigated frequencies, molecular and hematological features of Hb variants found in a large cohort of Thai subjects. Materials and Methods Study was conducted on 26,013 unrelated subjects, inhabiting in all geographical parts of Thailand over a period of 11 years from January 2002-December 2012. Hb analysis was done on high performance liquid chromatography (HPLC) or capillary electrophoresis (CE). Mutations causing Hb variants were identified using PCR and related techniques. Results Among 26,013 subjects investigated, 636 (2.4%) were found to carry Hb variants. Of these 636 subjects, 142 (22.4%) carried α-chain variants with 13 different mutations. The remaining included 451 (70.9%) cases with 16 β-chain variants, 37 (5.8%) cases with Hb Lepore (δβ-hybrid Hb) and 6 (0.9%) cases with a single δ-chain variant. The most common α-globin chain variant was the Hb Q-Thailand (α74GAC-CAC, Asp-His) which was found in 101 cases (15.8%). For β-globin chain variants, Hb Hope (β136GGT-GAT, Gly-Asp) and Hb Tak (β146+AC, Ter-Thr) are the two most common ones, found in 121 (19.0%) and 90 (14.2%) cases, respectively. Seven Hb variants have never been found in Thai population. Hb analysis profiles on HPLC or CE of these variants were illustrated to guide presumptive diagnostics. Conclusions Hb variants are common and heterogeneous in Thai population. With varieties of thalassemias and hemoglobinopathies in the population, interactions between them leading to complex syndromes are common and render their diagnoses difficult in routine practices. Knowledge of the spectrum, molecular basis, genotype-phenotype correlation and diagnostic features should prove useful for prevention and control of the diseases in the region. PMID:25244406
van der Harst, Pim; Verweij, Niek
2018-02-02
Coronary artery disease (CAD) is a complex phenotype driven by genetic and environmental factors. Ninety-seven genetic risk loci have been identified to date, but the identification of additional susceptibility loci might be important to enhance our understanding of the genetic architecture of CAD. To expand the number of genome-wide significant loci, catalog functional insights, and enhance our understanding of the genetic architecture of CAD. We performed a genome-wide association study in 34 541 CAD cases and 261 984 controls of UK Biobank resource followed by replication in 88 192 cases and 162 544 controls from CARDIoGRAMplusC4D. We identified 75 loci that replicated and were genome-wide significant ( P <5×10 -8 ) in meta-analysis, 13 of which had not been reported previously. Next, to further identify novel loci, we identified all promising ( P <0.0001) loci in the CARDIoGRAMplusC4D data and performed reciprocal replication and meta-analyses with UK Biobank. This led to the identification of 21 additional novel loci reaching genome-wide significance ( P <5×10 -8 ) in meta-analysis. Finally, we performed a genome-wide meta-analysis of all available data revealing 30 additional novel loci ( P <5×10 -8 ) without further replication. The increase in sample size by UK Biobank raised the number of reconstituted gene sets from 4.2% to 13.9% of all gene sets to be involved in CAD. For the 64 novel loci, 155 candidate causal genes were prioritized, many without an obvious connection to CAD. Fine mapping of the 161 CAD loci generated lists of credible sets of single causal variants and genes for functional follow-up. Genetic risk variants of CAD were linked to development of atrial fibrillation, heart failure, and death. We identified 64 novel genetic risk loci for CAD and performed fine mapping of all 161 risk loci to obtain a credible set of causal variants. The large expansion of reconstituted gene sets argues in favor of an expanded omnigenic model view on the genetic architecture of CAD. © 2017 The Authors.
Learning to learn causal models.
Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B
2010-09-01
Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.
Auer, Paul L.; Johnsen, Jill M.; Johnson, Andrew D.; Logsdon, Benjamin A.; Lange, Leslie A.; Nalls, Michael A.; Zhang, Guosheng; Franceschini, Nora; Fox, Keolu; Lange, Ethan M.; Rich, Stephen S.; O’Donnell, Christopher J.; Jackson, Rebecca D.; Wallace, Robert B.; Chen, Zhao; Graubert, Timothy A.; Wilson, James G.; Tang, Hua; Lettre, Guillaume; Reiner, Alex P.; Ganesh, Santhi K.; Li, Yun
2012-01-01
Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly penetrant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants associated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demonstrating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino acid substitution of the thrombpoietin receptor gene (p = 1.5 × 10−11). Second, we identified an association between missense variants of LCT and higher white blood count (p = 4 × 10−13). Third, we identified low-frequency coding variants that might account for allelic heterogeneity at several known blood cell-associated loci: MPL c.754T>C (p.Tyr252His) was associated with higher platelet count; CD36 c.975T>G (p.Tyr325∗) was associated with lower platelet count; and several missense variants at the α-globin gene locus were associated with lower hemoglobin. By identifying low-frequency missense variants associated with blood cell traits not previously reported by genome-wide association studies, we establish that exome sequencing followed by imputation is a powerful approach to dissecting complex, genetically heterogeneous traits in large population-based studies. PMID:23103231
Pharmacogenetic testing through the direct-to-consumer genetic testing company 23andMe.
Lu, Mengfei; Lewis, Cathryn M; Traylor, Matthew
2017-06-19
Rapid advances in scientific research have led to an increase in public awareness of genetic testing and pharmacogenetics. Direct-to-consumer (DTC) genetic testing companies, such as 23andMe, allow consumers to access their genetic information directly through an online service without the involvement of healthcare professionals. Here, we evaluate the clinical relevance of pharmacogenetic tests reported by 23andMe in their UK tests. The research papers listed under each 23andMe report were evaluated, extracting information on effect size, sample size and ethnicity. A wider literature search was performed to provide a fuller assessment of the pharmacogenetic test and variants were matched to FDA recommendations. Additional evidence from CPIC guidelines, PharmGKB, and Dutch Pharmacogenetics Working Group was reviewed to determine current clinical practice. The value of the tests across ethnic groups was determined, including information on linkage disequilibrium between the tested SNP and causal pharmacogenetic variant, where relevant. 23andMe offers 12 pharmacogenetic tests to their UK customers, some of which are in standard clinical practice, and others which are less widely applied. The clinical validity and clinical utility varies extensively between tests. The variants tested are likely to have different degrees of sensitivity due to different risk allele frequencies and linkage disequilibrium patterns across populations. The clinical relevance depends on the ethnicity of the individual and variability of pharmacogenetic markers. Further research is required to determine causal variants and provide more complete assessment of drug response and side effects. 23andMe reports provide some useful pharmacogenetics information, mirroring clinical tests that are in standard use. Other tests are unspecific, providing limited guidance and may not be useful for patients without professional interpretation. Nevertheless, DTC companies like 23andMe act as a powerful intermediate step to integrate pharmacogenetic testing into clinical practice.
Wray, Naomi R; Ripke, Stephan; Mattheisen, Manuel; Trzaskowski, Maciej; Byrne, Enda M; Abdellaoui, Abdel; Adams, Mark J; Agerbo, Esben; Air, Tracy M; Andlauer, Till M F; Bacanu, Silviu-Alin; Bækvad-Hansen, Marie; Beekman, Aartjan F T; Bigdeli, Tim B; Binder, Elisabeth B; Blackwood, Douglas R H; Bryois, Julien; Buttenschøn, Henriette N; Bybjerg-Grauholm, Jonas; Cai, Na; Castelao, Enrique; Christensen, Jane Hvarregaard; Clarke, Toni-Kim; Coleman, Jonathan I R; Colodro-Conde, Lucía; Couvy-Duchesne, Baptiste; Craddock, Nick; Crawford, Gregory E; Crowley, Cheynna A; Dashti, Hassan S; Davies, Gail; Deary, Ian J; Degenhardt, Franziska; Derks, Eske M; Direk, Nese; Dolan, Conor V; Dunn, Erin C; Eley, Thalia C; Eriksson, Nicholas; Escott-Price, Valentina; Kiadeh, Farnush Hassan Farhadi; Finucane, Hilary K; Forstner, Andreas J; Frank, Josef; Gaspar, Héléna A; Gill, Michael; Giusti-Rodríguez, Paola; Goes, Fernando S; Gordon, Scott D; Grove, Jakob; Hall, Lynsey S; Hannon, Eilis; Hansen, Christine Søholm; Hansen, Thomas F; Herms, Stefan; Hickie, Ian B; Hoffmann, Per; Homuth, Georg; Horn, Carsten; Hottenga, Jouke-Jan; Hougaard, David M; Hu, Ming; Hyde, Craig L; Ising, Marcus; Jansen, Rick; Jin, Fulai; Jorgenson, Eric; Knowles, James A; Kohane, Isaac S; Kraft, Julia; Kretzschmar, Warren W; Krogh, Jesper; Kutalik, Zoltán; Lane, Jacqueline M; Li, Yihan; Li, Yun; Lind, Penelope A; Liu, Xiaoxiao; Lu, Leina; MacIntyre, Donald J; MacKinnon, Dean F; Maier, Robert M; Maier, Wolfgang; Marchini, Jonathan; Mbarek, Hamdi; McGrath, Patrick; McGuffin, Peter; Medland, Sarah E; Mehta, Divya; Middeldorp, Christel M; Mihailov, Evelin; Milaneschi, Yuri; Milani, Lili; Mill, Jonathan; Mondimore, Francis M; Montgomery, Grant W; Mostafavi, Sara; Mullins, Niamh; Nauck, Matthias; Ng, Bernard; Nivard, Michel G; Nyholt, Dale R; O'Reilly, Paul F; Oskarsson, Hogni; Owen, Michael J; Painter, Jodie N; Pedersen, Carsten Bøcker; Pedersen, Marianne Giørtz; Peterson, Roseann E; Pettersson, Erik; Peyrot, Wouter J; Pistis, Giorgio; Posthuma, Danielle; Purcell, Shaun M; Quiroz, Jorge A; Qvist, Per; Rice, John P; Riley, Brien P; Rivera, Margarita; Saeed Mirza, Saira; Saxena, Richa; Schoevers, Robert; Schulte, Eva C; Shen, Ling; Shi, Jianxin; Shyn, Stanley I; Sigurdsson, Engilbert; Sinnamon, Grant B C; Smit, Johannes H; Smith, Daniel J; Stefansson, Hreinn; Steinberg, Stacy; Stockmeier, Craig A; Streit, Fabian; Strohmaier, Jana; Tansey, Katherine E; Teismann, Henning; Teumer, Alexander; Thompson, Wesley; Thomson, Pippa A; Thorgeirsson, Thorgeir E; Tian, Chao; Traylor, Matthew; Treutlein, Jens; Trubetskoy, Vassily; Uitterlinden, André G; Umbricht, Daniel; Van der Auwera, Sandra; van Hemert, Albert M; Viktorin, Alexander; Visscher, Peter M; Wang, Yunpeng; Webb, Bradley T; Weinsheimer, Shantel Marie; Wellmann, Jürgen; Willemsen, Gonneke; Witt, Stephanie H; Wu, Yang; Xi, Hualin S; Yang, Jian; Zhang, Futao; Arolt, Volker; Baune, Bernhard T; Berger, Klaus; Boomsma, Dorret I; Cichon, Sven; Dannlowski, Udo; de Geus, E C J; DePaulo, J Raymond; Domenici, Enrico; Domschke, Katharina; Esko, Tõnu; Grabe, Hans J; Hamilton, Steven P; Hayward, Caroline; Heath, Andrew C; Hinds, David A; Kendler, Kenneth S; Kloiber, Stefan; Lewis, Glyn; Li, Qingqin S; Lucae, Susanne; Madden, Pamela F A; Magnusson, Patrik K; Martin, Nicholas G; McIntosh, Andrew M; Metspalu, Andres; Mors, Ole; Mortensen, Preben Bo; Müller-Myhsok, Bertram; Nordentoft, Merete; Nöthen, Markus M; O'Donovan, Michael C; Paciga, Sara A; Pedersen, Nancy L; Penninx, Brenda W J H; Perlis, Roy H; Porteous, David J; Potash, James B; Preisig, Martin; Rietschel, Marcella; Schaefer, Catherine; Schulze, Thomas G; Smoller, Jordan W; Stefansson, Kari; Tiemeier, Henning; Uher, Rudolf; Völzke, Henry; Weissman, Myrna M; Werge, Thomas; Winslow, Ashley R; Lewis, Cathryn M; Levinson, Douglas F; Breen, Gerome; Børglum, Anders D; Sullivan, Patrick F
2018-05-01
Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
Searching for missing heritability: Designing rare variant association studies
Zuk, Or; Schaffner, Stephen F.; Samocha, Kaitlin; Do, Ron; Hechter, Eliana; Kathiresan, Sekar; Daly, Mark J.; Neale, Benjamin M.; Sunyaev, Shamil R.; Lander, Eric S.
2014-01-01
Genetic studies have revealed thousands of loci predisposing to hundreds of human diseases and traits, revealing important biological pathways and defining novel therapeutic hypotheses. However, the genes discovered to date typically explain less than half of the apparent heritability. Because efforts have largely focused on common genetic variants, one hypothesis is that much of the missing heritability is due to rare genetic variants. Studies of common variants are typically referred to as genomewide association studies, whereas studies of rare variants are often simply called sequencing studies. Because they are actually closely related, we use the terms common variant association study (CVAS) and rare variant association study (RVAS). In this paper, we outline the similarities and differences between RVAS and CVAS and describe a conceptual framework for the design of RVAS. We apply the framework to address key questions about the sample sizes needed to detect association, the relative merits of testing disruptive alleles vs. missense alleles, frequency thresholds for filtering alleles, the value of predictors of the functional impact of missense alleles, the potential utility of isolated populations, the value of gene-set analysis, and the utility of de novo mutations. The optimal design depends critically on the selection coefficient against deleterious alleles and thus varies across genes. The analysis shows that common variant and rare variant studies require similarly large sample collections. In particular, a well-powered RVAS should involve discovery sets with at least 25,000 cases, together with a substantial replication set. PMID:24443550
Cortical Hierarchies Perform Bayesian Causal Inference in Multisensory Perception
Rohe, Tim; Noppeney, Uta
2015-01-01
To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the “causal inference problem.” Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI), and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation). At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion). Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world. PMID:25710328
ERIC Educational Resources Information Center
Kaplan, Avi; Yahia, Yasmin
2017-01-01
While motivation is commonly interpreted as an individual student's characteristic, motivational perceptions and beliefs, such as causal attributions of success and failure, are embedded in cultural meanings and contextual practices. The current study aimed to investigate causal attributions among Arab high school students in Israel and to…
Splenomegaly - Diagnostic validity, work-up, and underlying causes.
Curovic Rotbain, Emelie; Lund Hansen, Dennis; Schaffalitzky de Muckadell, Ove; Wibrand, Flemming; Meldgaard Lund, Allan; Frederiksen, Henrik
2017-01-01
Our aim was to assess the validity of the ICD-10 code for splenomegaly in the Danish National Registry of Patients (DNRP), as well as to investigate which underlying diseases explained the observed splenomegaly. Splenomegaly is a common finding in patients referred to an internal medical department and can be caused by a large spectrum of diseases, including haematological diseases and liver cirrhosis. However, some patients remain without a causal diagnosis, despite extensive medical work-up. We identified 129 patients through the DNRP, that had been given the ICD-10 splenomegaly diagnosis code in 1994-2013 at Odense University Hospital, Denmark, excluding patients with prior splenomegaly, malignant haematological neoplasia or liver cirrhosis. Medical records were reviewed for validity of the splenomegaly diagnosis, diagnostic work-up, and the underlying disease was determined. The positive predictive value (PPV) with 95% confidence interval (CI) was calculated for the splenomegaly diagnosis code. Patients with idiopathic splenomegaly in on-going follow-up were also invited to be investigated for Gaucher disease. The overall PPV was 92% (95% CI: 85, 96). Haematological diseases were the underlying causal diagnosis in 39%; hepatic diseases in 18%, infectious disease in 10% and other diseases in 8%. 25% of patients with splenomegaly remained without a causal diagnosis. Lymphoma was the most common haematological causal diagnosis and liver cirrhosis the most common hepatic causal diagnosis. None of the investigated patients with idiopathic splenomegaly had Gaucher disease. Our findings show that the splenomegaly diagnosis in the DNRP is valid and can be used in registry-based studies. However, because of suspected significant under-coding, it should be considered if supplementary data sources should be used in addition, in order to attain a more representative population. Haematological diseases were the most common cause, however in a large fraction of patients no causal diagnosis was found.
Pathogenic Anti-Müllerian Hormone Variants in Polycystic Ovary Syndrome.
Gorsic, Lidija K; Kosova, Gulum; Werstein, Brian; Sisk, Ryan; Legro, Richard S; Hayes, M Geoffrey; Teixeira, Jose M; Dunaif, Andrea; Urbanek, Margrit
2017-08-01
Polycystic ovary syndrome (PCOS), a common endocrine condition, is the leading cause of anovulatory infertility. Given that common disease-susceptibility variants account for only a small percentage of the estimated PCOS heritability, we tested the hypothesis that rare variants contribute to this deficit in heritability. Unbiased whole-genome sequencing (WGS) of 80 patients with PCOS and 24 reproductively normal control subjects identified potentially deleterious variants in AMH, the gene encoding anti-Müllerian hormone (AMH). Targeted sequencing of AMH of 643 patients with PCOS and 153 control patients was used to replicate WGS findings. Dual luciferase reporter assays measured the impact of the variants on downstream AMH signaling. We found 24 rare (minor allele frequency < 0.01) AMH variants in patients with PCOS and control subjects; 18 variants were specific to women with PCOS. Seventeen of 18 (94%) PCOS-specific variants had significantly reduced AMH signaling, whereas none of 6 variants observed in control subjects showed significant defects in signaling. Thus, we identified rare AMH coding variants that reduced AMH-mediated signaling in a subset of patients with PCOS. To our knowledge, this study is the first to identify rare genetic variants associated with a common PCOS phenotype. Our findings suggest decreased AMH signaling as a mechanism for the pathogenesis of PCOS. AMH decreases androgen biosynthesis by inhibiting CYP17 activity; a potential mechanism of action for AMH variants in PCOS, therefore, is to increase androgen biosynthesis due to decreased AMH-mediated inhibition of CYP17 activity. Copyright © 2017 Endocrine Society
Bao, Riyue; Hernandez, Kyle; Huang, Lei; Kang, Wenjun; Bartom, Elizabeth; Onel, Kenan; Volchenboum, Samuel; Andrade, Jorge
2015-01-01
Whole exome sequencing has facilitated the discovery of causal genetic variants associated with human diseases at deep coverage and low cost. In particular, the detection of somatic mutations from tumor/normal pairs has provided insights into the cancer genome. Although there is an abundance of publicly-available software for the detection of germline and somatic variants, concordance is generally limited among variant callers and alignment algorithms. Successful integration of variants detected by multiple methods requires in-depth knowledge of the software, access to high-performance computing resources, and advanced programming techniques. We present ExScalibur, a set of fully automated, highly scalable and modulated pipelines for whole exome data analysis. The suite integrates multiple alignment and variant calling algorithms for the accurate detection of germline and somatic mutations with close to 99% sensitivity and specificity. ExScalibur implements streamlined execution of analytical modules, real-time monitoring of pipeline progress, robust handling of errors and intuitive documentation that allows for increased reproducibility and sharing of results and workflows. It runs on local computers, high-performance computing clusters and cloud environments. In addition, we provide a data analysis report utility to facilitate visualization of the results that offers interactive exploration of quality control files, read alignment and variant calls, assisting downstream customization of potential disease-causing mutations. ExScalibur is open-source and is also available as a public image on Amazon cloud.
Resampling procedures to identify important SNPs using a consensus approach.
Pardy, Christopher; Motyer, Allan; Wilson, Susan
2011-11-29
Our goal is to identify common single-nucleotide polymorphisms (SNPs) (minor allele frequency > 1%) that add predictive accuracy above that gained by knowledge of easily measured clinical variables. We take an algorithmic approach to predict each phenotypic variable using a combination of phenotypic and genotypic predictors. We perform our procedure on the first simulated replicate and then validate against the others. Our procedure performs well when predicting Q1 but is less successful for the other outcomes. We use resampling procedures where possible to guard against false positives and to improve generalizability. The approach is based on finding a consensus regarding important SNPs by applying random forests and the least absolute shrinkage and selection operator (LASSO) on multiple subsamples. Random forests are used first to discard unimportant predictors, narrowing our focus to roughly 100 important SNPs. A cross-validation LASSO is then used to further select variables. We combine these procedures to guarantee that cross-validation can be used to choose a shrinkage parameter for the LASSO. If the clinical variables were unavailable, this prefiltering step would be essential. We perform the SNP-based analyses simultaneously rather than one at a time to estimate SNP effects in the presence of other causal variants. We analyzed the first simulated replicate of Genetic Analysis Workshop 17 without knowledge of the true model. Post-conference knowledge of the simulation parameters allowed us to investigate the limitations of our approach. We found that many of the false positives we identified were substantially correlated with genuine causal SNPs.
An isozyme of acid alpha-glucosidase with reduced catalytic activity for glycogen.
Beratis, N G; LaBadie, G U; Hirschhorn, K
1980-03-01
Both the common and a variant isozyme of acid alpha-glucosidase have been purified from a heterozygous placenta with CM-Sephadex, ammonium sulfate precipitation, dialysis, Amicon filtration, affinity chromatography by Sephadex G-100, and DEAE-cellulose chromatography. Three and two activity peaks, from the common and variant isozymes, respectively, were obtained by DEAE-cellulose chromatography using a linear NaCl gradient. The three peaks of activity of the common isozyme were eluted with 0.08, 0.12, and 0.17 M NaCl, whereas the two peaks of the variant, with 0.01 and 0.06 M NaCl. The pH optimum and thermal denaturation at 57 degrees C were the same in all enzyme peaks of both isozymes. Rabbit antiacid alpha-glucosidase antibodies produced against the common isozyme were found to cross-react with both peaks of the variant isozyme. The two isozymes shared antigenic identity and had similar Km's with maltose as substrate. Normal substrate saturation kinetics were observed with the common isozyme when glycogen was the substrate, but the variant produced an S-shaped saturation curve indicating a phase of negative and positive cooperativity at low and high glycogen concentrations, respectively. The activity of the variant was only 8.6% and 19.2% of the common isozyme when assayed with nonsaturating and saturating concentrations of glycogen, respectively. A similar rate of hydrolysis of isomaltose by both isozymes was found indicating that the reduced catalytic activity of the variant isozyme toward glycogen is not the result of a reduced ability of this enzyme to cleave the alpha-1,6 linkages of glycogen.
The genomic landscape shaped by selection on transposable elements across 18 mouse strains.
Nellåker, Christoffer; Keane, Thomas M; Yalcin, Binnaz; Wong, Kim; Agam, Avigail; Belgard, T Grant; Flint, Jonathan; Adams, David J; Frankel, Wayne N; Ponting, Chris P
2012-06-15
Transposable element (TE)-derived sequence dominates the landscape of mammalian genomes and can modulate gene function by dysregulating transcription and translation. Our current knowledge of TEs in laboratory mouse strains is limited primarily to those present in the C57BL/6J reference genome, with most mouse TEs being drawn from three distinct classes, namely short interspersed nuclear elements (SINEs), long interspersed nuclear elements (LINEs) and the endogenous retrovirus (ERV) superfamily. Despite their high prevalence, the different genomic and gene properties controlling whether TEs are preferentially purged from, or are retained by, genetic drift or positive selection in mammalian genomes remain poorly defined. Using whole genome sequencing data from 13 classical laboratory and 4 wild-derived mouse inbred strains, we developed a comprehensive catalogue of 103,798 polymorphic TE variants. We employ this extensive data set to characterize TE variants across the Mus lineage, and to infer neutral and selective processes that have acted over 2 million years. Our results indicate that the majority of TE variants are introduced though the male germline and that only a minority of TE variants exert detectable changes in gene expression. However, among genes with differential expression across the strains there are twice as many TE variants identified as being putative causal variants as expected. Most TE variants that cause gene expression changes appear to be purged rapidly by purifying selection. Our findings demonstrate that past TE insertions have often been highly deleterious, and help to prioritize TE variants according to their likely contribution to gene expression or phenotype variation.
Colombo, Mara; Lòpez-Perolio, Irene; Meeks, Huong D; Caleca, Laura; Parsons, Michael T; Li, Hongyan; De Vecchi, Giovanna; Tudini, Emma; Foglia, Claudia; Mondini, Patrizia; Manoukian, Siranoush; Behar, Raquel; Garcia, Encarna B Gómez; Meindl, Alfons; Montagna, Marco; Niederacher, Dieter; Schmidt, Ane Y; Varesco, Liliana; Wappenschmidt, Barbara; Bolla, Manjeet K; Dennis, Joe; Michailidou, Kyriaki; Wang, Qin; Aittomäki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Beeghly-Fadel, Alicia; Benitez, Javier; Boeckx, Bram; Bogdanova, Natalia V; Bojesen, Stig E; Bonanni, Bernardo; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Chang-Claude, Jenny; Conroy, Don M; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Eriksson, Mikael; Fasching, Peter A; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Gabrielson, Marike; García-Closas, Montserrat; Giles, Graham G; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A; Hall, Per; Hamann, Ute; Hartman, Mikael; Hauke, Jan; Hollestelle, Antoinette; Hopper, John L; Jakubowska, Anna; Jung, Audrey; Kosma, Veli-Matti; Lambrechts, Diether; Le Marchand, Loid; Lindblom, Annika; Lubinski, Jan; Mannermaa, Arto; Margolin, Sara; Miao, Hui; Milne, Roger L; Neuhausen, Susan L; Nevanlinna, Heli; Olson, Janet E; Peterlongo, Paolo; Peto, Julian; Pylkäs, Katri; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Schneeweiss, Andreas; Schoemaker, Minouk J; See, Mee Hoong; Southey, Melissa C; Swerdlow, Anthony; Teo, Soo H; Toland, Amanda E; Tomlinson, Ian; Truong, Thérèse; van Asperen, Christi J; van den Ouweland, Ans M W; van der Kolk, Lizet E; Winqvist, Robert; Yannoukakos, Drakoulis; Zheng, Wei; Dunning, Alison M; Easton, Douglas F; Henderson, Alex; Hogervorst, Frans B L; Izatt, Louise; Offitt, Kenneth; Side, Lucy E; van Rensburg, Elizabeth J; Embrace, Study; Hebon, Study; McGuffog, Lesley; Antoniou, Antonis C; Chenevix-Trench, Georgia; Spurdle, Amanda B; Goldgar, David E; Hoya, Miguel de la; Radice, Paolo
2018-05-01
Although the spliceogenic nature of the BRCA2 c.68-7T > A variant has been demonstrated, its association with cancer risk remains controversial. In this study, we accurately quantified by real-time PCR and digital PCR (dPCR), the BRCA2 isoforms retaining or missing exon 3. In addition, the combined odds ratio for causality of the variant was estimated using genetic and clinical data, and its associated cancer risk was estimated by case-control analysis in 83,636 individuals. Co-occurrence in trans with pathogenic BRCA2 variants was assessed in 5,382 families. Exon 3 exclusion rate was 4.5-fold higher in variant carriers (13%) than controls (3%), indicating an exclusion rate for the c.68-7T > A allele of approximately 20%. The posterior probability of pathogenicity was 7.44 × 10 -115 . There was neither evidence for increased risk of breast cancer (OR 1.03; 95% CI 0.86-1.24) nor for a deleterious effect of the variant when co-occurring with pathogenic variants. Our data provide for the first time robust evidence of the nonpathogenicity of the BRCA2 c.68-7T > A. Genetic and quantitative transcript analyses together inform the threshold for the ratio between functional and altered BRCA2 isoforms compatible with normal cell function. These findings might be exploited to assess the relevance for cancer risk of other BRCA2 spliceogenic variants. © 2018 The Authors. Human Mutation published by Wiley Periodicals, Inc.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Demiralp, Metin
This work focuses on the dynamics of a system of quantum multi harmonic oscillators whose Hamiltonian is conic in positions and momenta with time variant coefficients. While it is simple, this system is useful for modeling the dynamics of a number of systems in contemporary sciences where the equations governing spatial or temporal changes are described by sets of ODEs. The dynamical causal models used readily in neuroscience can be indirectly described by these systems. In this work, we want to show that it is possible to describe these systems using quantum wave function type entities and expectations if themore » dynamic of the system is related to a set of ODEs.« less
Causal Genetic Variation Underlying Metabolome Differences.
Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A
2017-08-01
An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.
DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in multiple sclerosis.
Kular, Lara; Liu, Yun; Ruhrmann, Sabrina; Zheleznyakova, Galina; Marabita, Francesco; Gomez-Cabrero, David; James, Tojo; Ewing, Ewoud; Lindén, Magdalena; Górnikiewicz, Bartosz; Aeinehband, Shahin; Stridh, Pernilla; Link, Jenny; Andlauer, Till F M; Gasperi, Christiane; Wiendl, Heinz; Zipp, Frauke; Gold, Ralf; Tackenberg, Björn; Weber, Frank; Hemmer, Bernhard; Strauch, Konstantin; Heilmann-Heimbach, Stefanie; Rawal, Rajesh; Schminke, Ulf; Schmidt, Carsten O; Kacprowski, Tim; Franke, Andre; Laudes, Matthias; Dilthey, Alexander T; Celius, Elisabeth G; Søndergaard, Helle B; Tegnér, Jesper; Harbo, Hanne F; Oturai, Annette B; Olafsson, Sigurgeir; Eggertsson, Hannes P; Halldorsson, Bjarni V; Hjaltason, Haukur; Olafsson, Elias; Jonsdottir, Ingileif; Stefansson, Kari; Olsson, Tomas; Piehl, Fredrik; Ekström, Tomas J; Kockum, Ingrid; Feinberg, Andrew P; Jagodic, Maja
2018-06-19
The human leukocyte antigen (HLA) haplotype DRB1*15:01 is the major risk factor for multiple sclerosis (MS). Here, we find that DRB1*15:01 is hypomethylated and predominantly expressed in monocytes among carriers of DRB1*15:01. A differentially methylated region (DMR) encompassing HLA-DRB1 exon 2 is particularly affected and displays methylation-sensitive regulatory properties in vitro. Causal inference and Mendelian randomization provide evidence that HLA variants mediate risk for MS via changes in the HLA-DRB1 DMR that modify HLA-DRB1 expression. Meta-analysis of 14,259 cases and 171,347 controls confirms that these variants confer risk from DRB1*15:01 and also identifies a protective variant (rs9267649, p < 3.32 × 10 -8 , odds ratio = 0.86) after conditioning for all MS-associated variants in the region. rs9267649 is associated with increased DNA methylation at the HLA-DRB1 DMR and reduced expression of HLA-DRB1, suggesting a modulation of the DRB1*15:01 effect. Our integrative approach provides insights into the molecular mechanisms of MS susceptibility and suggests putative therapeutic strategies targeting a methylation-mediated regulation of the major risk gene.
The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis
Ploner, Alexander; Fischer, Krista; Horikoshi, Momoko; Sarin, Antti-Pekka; Thorleifsson, Gudmar; Ladenvall, Claes; Kals, Mart; Kuningas, Maris; Draisma, Harmen H. M.; Ried, Janina S.; van Zuydam, Natalie R.; Huikari, Ville; Mangino, Massimo; Sonestedt, Emily; Benyamin, Beben; Nelson, Christopher P.; Rivera, Natalia V.; Kristiansson, Kati; Shen, Huei-yi; Havulinna, Aki S.; Dehghan, Abbas; Donnelly, Louise A.; Kaakinen, Marika; Nuotio, Marja-Liisa; Robertson, Neil; de Bruijn, Renée F. A. G.; Ikram, M. Arfan; Amin, Najaf; Balmforth, Anthony J.; Braund, Peter S.; Doney, Alexander S. F.; Döring, Angela; Elliott, Paul; Esko, Tõnu; Franco, Oscar H.; Gretarsdottir, Solveig; Hartikainen, Anna-Liisa; Heikkilä, Kauko; Herzig, Karl-Heinz; Holm, Hilma; Hottenga, Jouke Jan; Hyppönen, Elina; Illig, Thomas; Isaacs, Aaron; Isomaa, Bo; Karssen, Lennart C.; Kettunen, Johannes; Koenig, Wolfgang; Kuulasmaa, Kari; Laatikainen, Tiina; Laitinen, Jaana; Lindgren, Cecilia; Lyssenko, Valeriya; Läärä, Esa; Rayner, Nigel W.; Männistö, Satu; Pouta, Anneli; Rathmann, Wolfgang; Rivadeneira, Fernando; Ruokonen, Aimo; Savolainen, Markku J.; Sijbrands, Eric J. G.; Small, Kerrin S.; Smit, Jan H.; Steinthorsdottir, Valgerdur; Syvänen, Ann-Christine; Taanila, Anja; Tobin, Martin D.; Uitterlinden, Andre G.; Willems, Sara M.; Willemsen, Gonneke; Witteman, Jacqueline; Perola, Markus; Evans, Alun; Ferrières, Jean; Virtamo, Jarmo; Kee, Frank; Tregouet, David-Alexandre; Arveiler, Dominique; Amouyel, Philippe; Ferrario, Marco M.; Brambilla, Paolo; Hall, Alistair S.; Heath, Andrew C.; Madden, Pamela A. F.; Martin, Nicholas G.; Montgomery, Grant W.; Whitfield, John B.; Jula, Antti; Knekt, Paul; Oostra, Ben; van Duijn, Cornelia M.; Penninx, Brenda W. J. H.; Davey Smith, George; Kaprio, Jaakko; Samani, Nilesh J.; Gieger, Christian; Peters, Annette; Wichmann, H.-Erich; Boomsma, Dorret I.; de Geus, Eco J. C.; Tuomi, TiinaMaija; Power, Chris; Hammond, Christopher J.; Spector, Tim D.; Lind, Lars; Orho-Melander, Marju; Palmer, Colin Neil Alexander; Morris, Andrew D.; Groop, Leif; Järvelin, Marjo-Riitta; Salomaa, Veikko; Vartiainen, Erkki; Hofman, Albert; Ripatti, Samuli; Metspalu, Andres; Thorsteinsdottir, Unnur; Stefansson, Kari; Pedersen, Nancy L.; McCarthy, Mark I.; Ingelsson, Erik; Prokopenko, Inga
2013-01-01
Background The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001). Conclusions We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes. Please see later in the article for the Editors' Summary PMID:23824655
Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa
Huckins, L M; Hatzikotoulas, K; Southam, L; Thornton, L M; Steinberg, J; Aguilera-McKay, F; Treasure, J; Schmidt, U; Gunasinghe, C; Romero, A; Curtis, C; Rhodes, D; Moens, J; Kalsi, G; Dempster, D; Leung, R; Keohane, A; Burghardt, R; Ehrlich, S; Hebebrand, J; Hinney, A; Ludolph, A; Walton, E; Deloukas, P; Hofman, A; Palotie, A; Palta, P; van Rooij, F J A; Stirrups, K; Adan, R; Boni, C; Cone, R; Dedoussis, G; van Furth, E; Gonidakis, F; Gorwood, P; Hudson, J; Kaprio, J; Kas, M; Keski-Rahonen, A; Kiezebrink, K; Knudsen, G-P; Slof-Op 't Landt, M C T; Maj, M; Monteleone, A M; Monteleone, P; Raevuori, A H; Reichborn-Kjennerud, T; Tozzi, F; Tsitsika, A; van Elburg, A; Adan, R A H; Alfredsson, L; Ando, T; Andreassen, O A; Aschauer, H; Baker, J H; Barrett, J C; Bencko, V; Bergen, A W; Berrettini, W H; Birgegard, A; Boni, C; Boraska Perica, V; Brandt, H; Breen, G; Bulik, C M; Carlberg, L; Cassina, M; Cichon, S; Clementi, M; Cohen-Woods, S; Coleman, J; Cone, R D; Courtet, P; Crawford, S; Crow, S; Crowley, J; Danner, U N; Davis, O S P; de Zwaan, M; Dedoussis, G; Degortes, D; DeSocio, J E; Dick, D M; Dikeos, D; Dina, C; Ding, B; Dmitrzak-Weglarz, M; Docampo, E; Duncan, L; Egberts, K; Ehrlich, S; Escaramís, G; Esko, T; Espeseth, T; Estivill, X; Favaro, A; Fernández-Aranda, F; Fichter, M M; Finan, C; Fischer, K; Floyd, J A B; Foretova, L; Forzan, M; Franklin, C S; Gallinger, S; Gambaro, G; Gaspar, H A; Giegling, I; Gonidakis, F; Gorwood, P; Gratacos, M; Guillaume, S; Guo, Y; Hakonarson, H; Halmi, K A; Hatzikotoulas, K; Hauser, J; Hebebrand, J; Helder, S; Herms, S; Herpertz-Dahlmann, B; Herzog, W; Hilliard, C E; Hinney, A; Hübel, C; Huckins, L M; Hudson, J I; Huemer, J; Inoko, H; Janout, V; Jiménez-Murcia, S; Johnson, C; Julià, A; Juréus, A; Kalsi, G; Kaminska, D; Kaplan, A S; Kaprio, J; Karhunen, L; Karwautz, A; Kas, M J H; Kaye, W; Kennedy, J L; Keski-Rahkonen, A; Kiezebrink, K; Klareskog, L; Klump, K L; Knudsen, G P S; Koeleman, B P C; Koubek, D; La Via, M C; Landén, M; Le Hellard, S; Levitan, R D; Li, D; Lichtenstein, P; Lilenfeld, L; Lissowska, J; Lundervold, A; Magistretti, P; Maj, M; Mannik, K; Marsal, S; Martin, N; Mattingsdal, M; McDevitt, S; McGuffin, P; Merl, E; Metspalu, A; Meulenbelt, I; Micali, N; Mitchell, J; Mitchell, K; Monteleone, P; Monteleone, A M; Mortensen, P; Munn-Chernoff, M A; Navratilova, M; Nilsson, I; Norring, C; Ntalla, I; Ophoff, R A; O'Toole, J K; Palotie, A; Pante, J; Papezova, H; Pinto, D; Rabionet, R; Raevuori, A; Rajewski, A; Ramoz, N; Rayner, N W; Reichborn-Kjennerud, T; Ripatti, S; Roberts, M; Rotondo, A; Rujescu, D; Rybakowski, F; Santonastaso, P; Scherag, A; Scherer, S W; Schmidt, U; Schork, N J; Schosser, A; Slachtova, L; Sladek, R; Slagboom, P E; Slof-Op 't Landt, M C T; Slopien, A; Soranzo, N; Southam, L; Steen, V M; Strengman, E; Strober, M; Sullivan, P F; Szatkiewicz, J P; Szeszenia-Dabrowska, N; Tachmazidou, I; Tenconi, E; Thornton, L M; Tortorella, A; Tozzi, F; Treasure, J; Tsitsika, A; Tziouvas, K; van Elburg, A A; van Furth, E F; Wagner, G; Walton, E; Watson, H; Wichmann, H-E; Widen, E; Woodside, D B; Yanovski, J; Yao, S; Yilmaz, Z; Zeggini, E; Zerwas, S; Zipfel, S; Collier, D A; Sullivan, P F; Breen, G; Bulik, C M; Zeggini, E
2018-01-01
Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10−6), and rs7700147, an intergenic variant (P=2.93 × 10−5). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes. PMID:29155802
Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa.
Huckins, L M; Hatzikotoulas, K; Southam, L; Thornton, L M; Steinberg, J; Aguilera-McKay, F; Treasure, J; Schmidt, U; Gunasinghe, C; Romero, A; Curtis, C; Rhodes, D; Moens, J; Kalsi, G; Dempster, D; Leung, R; Keohane, A; Burghardt, R; Ehrlich, S; Hebebrand, J; Hinney, A; Ludolph, A; Walton, E; Deloukas, P; Hofman, A; Palotie, A; Palta, P; van Rooij, F J A; Stirrups, K; Adan, R; Boni, C; Cone, R; Dedoussis, G; van Furth, E; Gonidakis, F; Gorwood, P; Hudson, J; Kaprio, J; Kas, M; Keski-Rahonen, A; Kiezebrink, K; Knudsen, G-P; Slof-Op 't Landt, M C T; Maj, M; Monteleone, A M; Monteleone, P; Raevuori, A H; Reichborn-Kjennerud, T; Tozzi, F; Tsitsika, A; van Elburg, A; Collier, D A; Sullivan, P F; Breen, G; Bulik, C M; Zeggini, E
2018-05-01
Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10 -6 ), and rs7700147, an intergenic variant (P=2.93 × 10 -5 ). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes.
Genetic variants in cellular transport do not affect mesalamine response in ulcerative colitis
Huang, Hailiang; Rivas, Manuel; Kaplan, Jess L.; Daly, Mark J.; Winter, Harland S.
2018-01-01
Background and aims Mesalamine is commonly used to treat ulcerative colitis (UC). Although mesalamine acts topically, in vitro data suggest that intracellular transport is required for its beneficial effect. Genetic variants in mucosal transport proteins may affect this uptake, but the clinical relevance of these variants has not been studied. The aim of this study was to determine whether variants in genes involved in cellular transport affect the response to mesalamine in UC. Methods Subjects with UC from a 6-week clinical trial using multiple doses of mesalamine were genotyped using a genome-wide array that included common exome variants. Analysis focused on cellular transport gene variants with a minor allele frequency >5%. Mesalamine response was defined as improvement in Week 6 Physician’s Global Assessment (PGA) and non-response as a lack of improvement in Week 6 PGA. Quality control thresholds included an individual genotyping rate of >90%, SNP genotyping rate of >98%, and exclusion for subjects with cryptic relatedness. All included variants met Hardy-Weinberg equilibrium (p>0.001). Results 457 adults with UC were included with 280 responders and 177 non-responders. There were no common variants in transporter genes that were associated with response to mesalamine. The genetic risk score of responders was similar to that of non-responders (p = 0.18). Genome-wide variants demonstrating a trend towards mesalamine response included ST8SIA5 (p = 1x10-5). Conclusions Common transporter gene variants did not affect response to mesalamine in adult UC. The response to mesalamine may be due to rare genetic events or environmental factors such as the intestinal microbiome. PMID:29579042
Serie, Daniel J.; Crook, Julia E.; Necela, Brian M.; Axenfeld, Bianca C.; Dockter, Travis J.; Colon-Otero, Gerardo; Perez, Edith A.; Thompson, E. Aubrey; Norton, Nadine
2017-01-01
Doxorubicin and the ERBB2 targeted therapy, trastuzumab, are routinely used in the treatment of HER2+ breast cancer. In mouse models, doxorubicin is known to cause cardiomyopathy and conditional cardiac knock out of Erbb2 results in dilated cardiomyopathy and increased sensitivity to doxorubicin-induced cell death. In humans, these drugs also result in cardiac phenotypes, but severity and reversibility is highly variable. We examined the association of decline in left ventricular ejection fraction (LVEF) at 15,204 single nucleotide polymorphisms (SNPs) spanning 72 cardiomyopathy genes, in 800 breast cancer patients who received doxorubicin and trastuzumab. For 7033 common SNPs (minor allele frequency (MAF) > 0.01) we performed single marker linear regression. For all SNPs, we performed gene-based testing with SNP-set (Sequence) Kernel Association Tests: SKAT, SKAT-O and SKAT-common/rare under rare variant non-burden; rare variant optimized burden and non-burden tests; and a combination of rare and common variants respectively. Single marker analyses identified seven missense variants in OBSCN (p = 0.0045–0.0009, MAF = 0.18–0.50) and two in TTN (both p = 0.04, MAF = 0.22). Gene-based rare variant analyses, SKAT and SKAT-O, performed very similarly (ILK, TCAP, DSC2, VCL, FXN, DSP and KCNQ1, p = 0.042–0.006). Gene-based tests of rare/common variants were significant at the nominal 5% level for OBSCN as well as TCAP, DSC2, VCL, NEXN, KCNJ2 and DMD (p = 0.044–0.008). Our results suggest that rare and common variants in OBSCN, as well as in other genes, could have modifying effects in cardiomyopathy. PMID:29367538
van Rheenen, Wouter; Shatunov, Aleksey; Dekker, Annelot M; McLaughlin, Russell L; Diekstra, Frank P; Pulit, Sara L; van der Spek, Rick A A; Võsa, Urmo; de Jong, Simone; Robinson, Matthew R; Yang, Jian; Fogh, Isabella; van Doormaal, Perry TC; Tazelaar, Gijs H P; Koppers, Max; Blokhuis, Anna M; Sproviero, William; Jones, Ashley R; Kenna, Kevin P; van Eijk, Kristel R; Harschnitz, Oliver; Schellevis, Raymond D; Brands, William J; Medic, Jelena; Menelaou, Androniki; Vajda, Alice; Ticozzi, Nicola; Lin, Kuang; Rogelj, Boris; Vrabec, Katarina; Ravnik-Glavač, Metka; Koritnik, Blaž; Zidar, Janez; Leonardis, Lea; Grošelj, Leja Dolenc; Millecamps, Stéphanie; Salachas, François; Meininger, Vincent; de Carvalho, Mamede; Pinto, Susana; Mora, Jesus S; Rojas-García, Ricardo; Polak, Meraida; Chandran, Siddharthan; Colville, Shuna; Swingler, Robert; Morrison, Karen E; Shaw, Pamela J; Hardy, John; Orrell, Richard W; Pittman, Alan; Sidle, Katie; Fratta, Pietro; Malaspina, Andrea; Topp, Simon; Petri, Susanne; Abdulla, Susanne; Drepper, Carsten; Sendtner, Michael; Meyer, Thomas; Ophoff, Roel A; Staats, Kim A; Wiedau-Pazos, Martina; Lomen-Hoerth, Catherine; Van Deerlin, Vivianna M; Trojanowski, John Q; Elman, Lauren; McCluskey, Leo; Basak, A Nazli; Tunca, Ceren; Hamzeiy, Hamid; Parman, Yesim; Meitinger, Thomas; Lichtner, Peter; Radivojkov-Blagojevic, Milena; Andres, Christian R; Maurel, Cindy; Bensimon, Gilbert; Landwehrmeyer, Bernhard; Brice, Alexis; Payan, Christine A M; Saker-Delye, Safaa; Dürr, Alexandra; Wood, Nicholas W; Tittmann, Lukas; Lieb, Wolfgang; Franke, Andre; Rietschel, Marcella; Cichon, Sven; Nöthen, Markus M; Amouyel, Philippe; Tzourio, Christophe; Dartigues, Jean-François; Uitterlinden, Andre G; Rivadeneira, Fernando; Estrada, Karol; Hofman, Albert; Curtis, Charles; Blauw, Hylke M; van der Kooi, Anneke J; de Visser, Marianne; Goris, An; Weber, Markus; Shaw, Christopher E; Smith, Bradley N; Pansarasa, Orietta; Cereda, Cristina; Bo, Roberto Del; Comi, Giacomo P; D’Alfonso, Sandra; Bertolin, Cinzia; Sorarù, Gianni; Mazzini, Letizia; Pensato, Viviana; Gellera, Cinzia; Tiloca, Cinzia; Ratti, Antonia; Calvo, Andrea; Moglia, Cristina; Brunetti, Maura; Arcuti, Simona; Capozzo, Rosa; Zecca, Chiara; Lunetta, Christian; Penco, Silvana; Riva, Nilo; Padovani, Alessandro; Filosto, Massimiliano; Muller, Bernard; Stuit, Robbert Jan; Blair, Ian; Zhang, Katharine; McCann, Emily P; Fifita, Jennifer A; Nicholson, Garth A; Rowe, Dominic B; Pamphlett, Roger; Kiernan, Matthew C; Grosskreutz, Julian; Witte, Otto W; Ringer, Thomas; Prell, Tino; Stubendorff, Beatrice; Kurth, Ingo; Hübner, Christian A; Leigh, P Nigel; Casale, Federico; Chio, Adriano; Beghi, Ettore; Pupillo, Elisabetta; Tortelli, Rosanna; Logroscino, Giancarlo; Powell, John; Ludolph, Albert C; Weishaupt, Jochen H; Robberecht, Wim; Van Damme, Philip; Franke, Lude; Pers, Tune H; Brown, Robert H; Glass, Jonathan D; Landers, John E; Hardiman, Orla; Andersen, Peter M; Corcia, Philippe; Vourc’h, Patrick; Silani, Vincenzo; Wray, Naomi R; Visscher, Peter M; de Bakker, Paul I W; van Es, Michael A; Pasterkamp, R Jeroen; Lewis, Cathryn M; Breen, Gerome; Al-Chalabi, Ammar; van den Berg, Leonard H; Veldink, Jan H
2017-01-01
To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1–10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk. PMID:27455348
Spraker, Matthew B; Fain, Robert; Gopan, Olga; Zeng, Jing; Nyflot, Matthew; Jordan, Loucille; Kane, Gabrielle; Ford, Eric
Incident learning systems (ILSs) are a popular strategy for improving safety in radiation oncology (RO) clinics, but few reports focus on the causes of errors in RO. The goal of this study was to test a causal factor taxonomy developed in 2012 by the American Association of Physicists in Medicine and adopted for use in the RO: Incident Learning System (RO-ILS). Three hundred event reports were randomly selected from an institutional ILS database and Safety in Radiation Oncology (SAFRON), an international ILS. The reports were split into 3 groups of 100 events each: low-risk institutional, high-risk institutional, and SAFRON. Three raters retrospectively analyzed each event for contributing factors using the American Association of Physicists in Medicine taxonomy. No events were described by a single causal factor (median, 7). The causal factor taxonomy was found to be applicable for all events, but 4 causal factors were not described in the taxonomy: linear accelerator failure (n = 3), hardware/equipment failure (n = 2), failure to follow through with a quality improvement intervention (n = 1), and workflow documentation was misleading (n = 1). The most common causal factor categories contributing to events were similar in all event types. The most common specific causal factor to contribute to events was a "slip causing physical error." Poor human factors engineering was the only causal factor found to contribute more frequently to high-risk institutional versus low-risk institutional events. The taxonomy in the study was found to be applicable for all events and may be useful in root cause analyses and future studies. Communication and human behaviors were the most common errors affecting all types of events. Poor human factors engineering was found to specifically contribute to high-risk more than low-risk institutional events, and may represent a strategy for reducing errors in all types of events. Copyright © 2017 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.
An isozyme of acid alpha-glucosidase with reduced catalytic activity for glycogen.
Beratis, N G; LaBadie, G U; Hirschhorn, K
1980-01-01
Both the common and a variant isozyme of acid alpha-glucosidase have been purified from a heterozygous placenta with CM-Sephadex, ammonium sulfate precipitation, dialysis, Amicon filtration, affinity chromatography by Sephadex G-100, and DEAE-cellulose chromatography. Three and two activity peaks, from the common and variant isozymes, respectively, were obtained by DEAE-cellulose chromatography using a linear NaCl gradient. The three peaks of activity of the common isozyme were eluted with 0.08, 0.12, and 0.17 M NaCl, whereas the two peaks of the variant, with 0.01 and 0.06 M NaCl. The pH optimum and thermal denaturation at 57 degrees C were the same in all enzyme peaks of both isozymes. Rabbit antiacid alpha-glucosidase antibodies produced against the common isozyme were found to cross-react with both peaks of the variant isozyme. The two isozymes shared antigenic identity and had similar Km's with maltose as substrate. Normal substrate saturation kinetics were observed with the common isozyme when glycogen was the substrate, but the variant produced an S-shaped saturation curve indicating a phase of negative and positive cooperativity at low and high glycogen concentrations, respectively. The activity of the variant was only 8.6% and 19.2% of the common isozyme when assayed with nonsaturating and saturating concentrations of glycogen, respectively. A similar rate of hydrolysis of isomaltose by both isozymes was found indicating that the reduced catalytic activity of the variant isozyme toward glycogen is not the result of a reduced ability of this enzyme to cleave the alpha-1,6 linkages of glycogen. Images Fig. 2 Fig. 4 Fig. 6 PMID:6770674
[Fine mapping of complex disease susceptibility loci].
Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao
2014-01-01
Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.
Brezovský, Jan
2016-01-01
An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2. PMID:27224906
Bendl, Jaroslav; Musil, Miloš; Štourač, Jan; Zendulka, Jaroslav; Damborský, Jiří; Brezovský, Jan
2016-05-01
An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools' predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.
Sivley, R Michael; Sheehan, Jonathan H; Kropski, Jonathan A; Cogan, Joy; Blackwell, Timothy S; Phillips, John A; Bush, William S; Meiler, Jens; Capra, John A
2018-01-23
Next-generation sequencing of individuals with genetic diseases often detects candidate rare variants in numerous genes, but determining which are causal remains challenging. We hypothesized that the spatial distribution of missense variants in protein structures contains information about function and pathogenicity that can help prioritize variants of unknown significance (VUS) and elucidate the structural mechanisms leading to disease. To illustrate this approach in a clinical application, we analyzed 13 candidate missense variants in regulator of telomere elongation helicase 1 (RTEL1) identified in patients with Familial Interstitial Pneumonia (FIP). We curated pathogenic and neutral RTEL1 variants from the literature and public databases. We then used homology modeling to construct a 3D structural model of RTEL1 and mapped known variants into this structure. We next developed a pathogenicity prediction algorithm based on proximity to known disease causing and neutral variants and evaluated its performance with leave-one-out cross-validation. We further validated our predictions with segregation analyses, telomere lengths, and mutagenesis data from the homologous XPD protein. Our algorithm for classifying RTEL1 VUS based on spatial proximity to pathogenic and neutral variation accurately distinguished 7 known pathogenic from 29 neutral variants (ROC AUC = 0.85) in the N-terminal domains of RTEL1. Pathogenic proximity scores were also significantly correlated with effects on ATPase activity (Pearson r = -0.65, p = 0.0004) in XPD, a related helicase. Applying the algorithm to 13 VUS identified from sequencing of RTEL1 from patients predicted five out of six disease-segregating VUS to be pathogenic. We provide structural hypotheses regarding how these mutations may disrupt RTEL1 ATPase and helicase function. Spatial analysis of missense variation accurately classified candidate VUS in RTEL1 and suggests how such variants cause disease. Incorporating spatial proximity analyses into other pathogenicity prediction tools may improve accuracy for other genes and genetic diseases.
Welderufael, B. G.; Løvendahl, Peter; de Koning, Dirk-Jan; Janss, Lucas L. G.; Fikse, W. F.
2018-01-01
Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to – but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t-test and a genome-wide significance level of P-value < 10-4 was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to – or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2) and genes involved in macrophage recruitment and regulation of inflammations (PDGFD and PTX3) were suggested as possible causal genes for susceptibility to – and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to – and recoverability from mastitis. PMID:29755506
Mägi, Reedik; Horikoshi, Momoko; Sofer, Tamar; Mahajan, Anubha; Kitajima, Hidetoshi; Franceschini, Nora; McCarthy, Mark I.; Morris, Andrew P.
2017-01-01
Abstract Trans-ethnic meta-analysis of genome-wide association studies (GWAS) across diverse populations can increase power to detect complex trait loci when the underlying causal variants are shared between ancestry groups. However, heterogeneity in allelic effects between GWAS at these loci can occur that is correlated with ancestry. Here, a novel approach is presented to detect SNP association and quantify the extent of heterogeneity in allelic effects that is correlated with ancestry. We employ trans-ethnic meta-regression to model allelic effects as a function of axes of genetic variation, derived from a matrix of mean pairwise allele frequency differences between GWAS, and implemented in the MR-MEGA software. Through detailed simulations, we demonstrate increased power to detect association for MR-MEGA over fixed- and random-effects meta-analysis across a range of scenarios of heterogeneity in allelic effects between ethnic groups. We also demonstrate improved fine-mapping resolution, in loci containing a single causal variant, compared to these meta-analysis approaches and PAINTOR, and equivalent performance to MANTRA at reduced computational cost. Application of MR-MEGA to trans-ethnic GWAS of kidney function in 71,461 individuals indicates stronger signals of association than fixed-effects meta-analysis when heterogeneity in allelic effects is correlated with ancestry. Application of MR-MEGA to fine-mapping four type 2 diabetes susceptibility loci in 22,086 cases and 42,539 controls highlights: (i) strong evidence for heterogeneity in allelic effects that is correlated with ancestry only at the index SNP for the association signal at the CDKAL1 locus; and (ii) 99% credible sets with six or fewer variants for five distinct association signals. PMID:28911207
Rametta, Raffaela; Ruscica, Massimiliano; Dongiovanni, Paola; Macchi, Chiara; Fracanzani, Anna L; Steffani, Liliana; Fargion, Silvia; Magni, Paolo; Valenti, Luca
2014-07-01
Fetuin-A is a liver-derived peptide associated with insulin resistance. Aim of this cross-sectional study was to evaluate whether Fetuin-A is increased in patients with nonalcoholic fatty liver disease (NAFLD) vs. healthy subjects without metabolic abnormalities and the association with insulin resistance and liver damage. To investigate the causal relationship between fatty liver and Fetuin-A, we also analysed whether the inherited I148M PNPLA3 variant modulates Fetuin-A. In 137 patients with histological NAFLD, complete metabolic characterization, PNPLA3 genotype, and in 260 healthy subjects without metabolic alterations, Fetuin-A was measured by enzyme-linked immunoabsorbent assay. Serum Fetuin-A was higher in NAFLD patients than in controls (P < 0·0001), independently of age, sex, BMI, insulin resistance, dyslipidemia, adiponectin, PNPLA3 I148M and ALT levels (OR 1·006 95% CI 1·003-1·11; P = 0·003). In NAFLD patients, Fetuin-A was associated with steatosis severity (P = 0·03) and metabolic syndrome features, but not with hepatic inflammation. At multivariate analysis, Fetuin-A levels were associated with BMI, triglycerides, hyperglycemia and PNPLA3 I148M (P = 0·034) independently also of age, sex and ALT levels. As PNPLA3 I148M is a strong and inherited determinant of liver fat without affecting insulin resistance and lipid levels, these data suggest that steatosis has a causal role in determining serum Fetuin-A levels. Liver fat accumulation and the I148M variant of PNPLA3 are associated with serum Fetuin-A levels independently of insulin resistance. Fetuin-A may be implicated in the pathogenesis of metabolic complications associated with NAFLD. © 2014 Stichting European Society for Clinical Investigation Journal Foundation.
Lewis, Sarah J; Araya, Ricardo; Smith, George Davey; Freathy, Rachel; Gunnell, David; Palmer, Tom; Munafò, Marcus
2011-01-01
Smokers have a higher prevalence of major depressive episodes and depressive symptoms than the general population, but whether this association is causal, or is due to confounding or reverse causation is uncertain because of the problems inherent in some epidemiological studies. Mendelian randomization, in which a genetic variant is used as a surrogate for measuring exposure, is an approach which may be used to better understand this association. We investigated the rs1051730 single nucleotide polymorphism in the nicotine acetylcholine receptor gene cluster (CHRNA5-CHRNA3-CHRNB4), associated with smoking phenotypes, to determine whether women who continued to smoke were also more likely to report a low mood during pregnancy. We found among women who smoked pre-pregnancy, those with the 1051730 T allele smoked more and were less likely to quit smoking during pregnancy, but were also less likely to report high levels of depressed mood at 18 weeks of pregnancy (per allele OR = 0.84, 95%CI 0.72 to 0.99, p = 0.034). The association between genotype and depressed mood was limited to women who were smokers prior to pregnancy, with weak evidence of an interaction between smoking status and genotype (p = 0.07). Our results do not support a causal role of smoking on depressed mood, but are consistent with a self-medication hypothesis, whereby smoking is used to alleviate symptoms of depression. A replication study using multiple genetic variants which influence smoking via different pathways is required to confirm these findings and provide evidence that the genetic variant is reflecting the effect of quitting smoking on depressed mood, and is not directly affecting mood.
Ricaño-Ponce, Isis; Zhernakova, Daria V; Deelen, Patrick; Luo, Oscar; Li, Xingwang; Isaacs, Aaron; Karjalainen, Juha; Di Tommaso, Jennifer; Borek, Zuzanna Agnieszka; Zorro, Maria M; Gutierrez-Achury, Javier; Uitterlinden, Andre G; Hofman, Albert; van Meurs, Joyce; Netea, Mihai G; Jonkers, Iris H; Withoff, Sebo; van Duijn, Cornelia M; Li, Yang; Ruan, Yijun; Franke, Lude; Wijmenga, Cisca; Kumar, Vinod
2016-04-01
Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
de Queiroz, Casley Borges; Correia, Hilberty L Nunes; Menicucci, Renato Pedrozo; Vidigal, Pedro M Pereira; de Queiroz, Marisa Vieira
2017-05-04
Colletotrichum lindemuthianum is the causal agent of anthracnose in common beans, one of the main limiting factors of their culture. Here, we report for the first time, to our knowledge, a draft of the complete genome sequences of two isolates belonging to 83.501 and 89 A 2 2-3 of C. lindemutuianum . Copyright © 2017 de Queiroz et al.
2014-01-01
Introduction The majority of the genetic variance of systemic lupus erythematosus (SLE) remains unexplained by the common disease-common variant hypothesis. Rare variants, which are not detectable by genome-wide association studies because of their low frequencies, are predicted to explain part of this ”missing heritability.” However, recent studies identifying rare variants within known disease-susceptibility loci have failed to show genetic associations because of their extremely low frequencies, leading to the questioning of the contribution of rare variants to disease susceptibility. A common (minor allele frequency = 17.4% in cases) nonsynonymous coding variant rs1143679 (R77H) in ITGAM (CD11b), which forms half of the heterodimeric integrin receptor, complement receptor 3 (CR3), is robustly associated with SLE and has been shown to impair CR3-mediated phagocytosis. Methods We resequenced ITGAM in 73 SLE cases and identified two previously unidentified, case-specific nonsynonymous variants, F941V and G1145S. Both variants were genotyped in 2,107 and 949 additional SLE cases, respectively, to estimate their frequencies in a disease population. An in vitro model was used to assess the impact of F941V and G1145S, together with two nonsynonymous ITGAM polymorphisms, A858V (rs1143683) and M441T (rs11861251), on CR3-mediated phagocytosis. A paired two-tailed t test was used to compare the phagocytic capabilities of each variant with that of wild-type CR3. Results Both rare variants, F941V and G1145S, significantly impair CR3-mediated phagocytosis in an in vitro model (61% reduction, P = 0.006; 26% reduction, P = 0.0232). However, neither of the common variants, M441T and A858V, had an effect on phagocytosis. Neither rare variant was observed again in the genotyping of additional SLE cases, suggesting that there frequencies are extremely low. Conclusions Our results add further evidence to the functional importance of ITGAM in SLE pathogenesis through impaired phagocytosis. Additionally, this study provides a new example of the identification of rare variants in common-allele-associated loci, which, because of their extremely low frequencies, are not statistically associated. However, the demonstration of their functional effects adds support to their contribution to disease risk, and questions the current notion of dismissing the contribution of very rare variants on purely statistical analyses. PMID:24886912
Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval.
Lin, Honghuang; van Setten, Jessica; Smith, Albert V; Bihlmeyer, Nathan A; Warren, Helen R; Brody, Jennifer A; Radmanesh, Farid; Hall, Leanne; Grarup, Niels; Müller-Nurasyid, Martina; Boutin, Thibaud; Verweij, Niek; Lin, Henry J; Li-Gao, Ruifang; van den Berg, Marten E; Marten, Jonathan; Weiss, Stefan; Prins, Bram P; Haessler, Jeffrey; Lyytikäinen, Leo-Pekka; Mei, Hao; Harris, Tamara B; Launer, Lenore J; Li, Man; Alonso, Alvaro; Soliman, Elsayed Z; Connell, John M; Huang, Paul L; Weng, Lu-Chen; Jameson, Heather S; Hucker, William; Hanley, Alan; Tucker, Nathan R; Chen, Yii-Der Ida; Bis, Joshua C; Rice, Kenneth M; Sitlani, Colleen M; Kors, Jan A; Xie, Zhijun; Wen, Chengping; Magnani, Jared W; Nelson, Christopher P; Kanters, Jørgen K; Sinner, Moritz F; Strauch, Konstantin; Peters, Annette; Waldenberger, Melanie; Meitinger, Thomas; Bork-Jensen, Jette; Pedersen, Oluf; Linneberg, Allan; Rudan, Igor; de Boer, Rudolf A; van der Meer, Peter; Yao, Jie; Guo, Xiuqing; Taylor, Kent D; Sotoodehnia, Nona; Rotter, Jerome I; Mook-Kanamori, Dennis O; Trompet, Stella; Rivadeneira, Fernando; Uitterlinden, André; Eijgelsheim, Mark; Padmanabhan, Sandosh; Smith, Blair H; Völzke, Henry; Felix, Stephan B; Homuth, Georg; Völker, Uwe; Mangino, Massimo; Spector, Timothy D; Bots, Michiel L; Perez, Marco; Kähönen, Mika; Raitakari, Olli T; Gudnason, Vilmundur; Arking, Dan E; Munroe, Patricia B; Psaty, Bruce M; van Duijn, Cornelia M; Benjamin, Emelia J; Rosand, Jonathan; Samani, Nilesh J; Hansen, Torben; Kääb, Stefan; Polasek, Ozren; van der Harst, Pim; Heckbert, Susan R; Jukema, J Wouter; Stricker, Bruno H; Hayward, Caroline; Dörr, Marcus; Jamshidi, Yalda; Asselbergs, Folkert W; Kooperberg, Charles; Lehtimäki, Terho; Wilson, James G; Ellinor, Patrick T; Lubitz, Steven A; Isaacs, Aaron
2018-05-01
Electrical conduction from the cardiac sinoatrial node to the ventricles is critical for normal heart function. Genome-wide association studies have identified more than a dozen common genetic loci that are associated with PR interval. However, it is unclear whether rare and low-frequency variants also contribute to PR interval heritability. We performed large-scale meta-analyses of the PR interval that included 83 367 participants of European ancestry and 9436 of African ancestry. We examined both common and rare variants associated with the PR interval. We identified 31 genetic loci that were significantly associated with PR interval after Bonferroni correction ( P <1.2×10 -6 ), including 11 novel loci that have not been reported previously. Many of these loci are involved in heart morphogenesis. In gene-based analysis, we found that multiple rare variants at MYH6 ( P =5.9×10 -11 ) and SCN5A ( P =1.1×10 -7 ) were associated with PR interval. SCN5A locus also was implicated in the common variant analysis, whereas MYH6 was a novel locus. We identified common variants at 11 novel loci and rare variants within 2 gene regions that were significantly associated with PR interval. Our findings provide novel insights to the current understanding of atrioventricular conduction, which is critical for cardiac activity and an important determinant of health. © 2018 American Heart Association, Inc.
Common germline polymorphisms associated with breast cancer-specific survival.
Pirie, Ailith; Guo, Qi; Kraft, Peter; Canisius, Sander; Eccles, Diana M; Rahman, Nazneen; Nevanlinna, Heli; Chen, Constance; Khan, Sofia; Tyrer, Jonathan; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Michailidou, Kyriaki; Lush, Michael; Dunning, Alison M; Shah, Mitul; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Lambrechts, Dieter; Weltens, Caroline; Leunen, Karin; van Ongeval, Chantal; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Blomqvist, Carl; Aittomäki, Kristiina; Fagerholm, Rainer; Muranen, Taru A; Olsen, Janet E; Hallberg, Emily; Vachon, Celine; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Broeks, Annegien; Cornelissen, Sten; Haiman, Christopher A; Henderson, Brian E; Schumacher, Frederick; Le Marchand, Loic; Hopper, John L; Tsimiklis, Helen; Apicella, Carmel; Southey, Melissa C; Cross, Simon S; Reed, Malcolm Wr; Giles, Graham G; Milne, Roger L; McLean, Catriona; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John Wm; van den Ouweland, Ans Mw; Marme, Federick; Schneeweiss, Andreas; Yang, Rongxi; Burwinkel, Barbara; Figueroa, Jonine; Chanock, Stephen J; Lissowska, Jolanta; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Brenner, Hermann; Butterbach, Katja; Holleczek, Bernd; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Li, Jingmei; Brand, Judith S; Humphreys, Keith; Devilee, Peter; Tollenaar, Robert Aem; Seynaeve, Caroline; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Ficarazzi, Filomena; Beckmann, Matthias W; Hein, Alexander; Ekici, Arif B; Balleine, Rosemary; Phillips, Kelly-Anne; Benitez, Javier; Zamora, M Pilar; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Jakubowska, Anna; Lubinski, Jan; Gronwald, Jacek; Durda, Katarzyna; Hamann, Ute; Kabisch, Maria; Ulmer, Hans Ulrich; Rüdiger, Thomas; Margolin, Sara; Kristensen, Vessela; Nord, Siljie; Evans, D Gareth; Abraham, Jean; Earl, Helena; Poole, Christopher J; Hiller, Louise; Dunn, Janet A; Bowden, Sarah; Yang, Rose; Campa, Daniele; Diver, W Ryan; Gapstur, Susan M; Gaudet, Mia M; Hankinson, Susan; Hoover, Robert N; Hüsing, Anika; Kaaks, Rudolf; Machiela, Mitchell J; Willett, Walter; Barrdahl, Myrto; Canzian, Federico; Chin, Suet-Feung; Caldas, Carlos; Hunter, David J; Lindstrom, Sara; Garcia-Closas, Montserrat; Couch, Fergus J; Chenevix-Trench, Georgia; Mannermaa, Arto; Andrulis, Irene L; Hall, Per; Chang-Claude, Jenny; Easton, Douglas F; Bojesen, Stig E; Cox, Angela; Fasching, Peter A; Pharoah, Paul Dp; Schmidt, Marjanka K
2015-04-22
Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium. A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect. Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease. Although no variants reached genome-wide significance (P <5 x 10(-8)), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels.
Chiu, Chi-yang; Jung, Jeesun; Wang, Yifan; Weeks, Daniel E.; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Amos, Christopher I.; Mills, James L.; Boehnke, Michael; Xiong, Momiao; Fan, Ruzong
2016-01-01
In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate F-distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of high-dimensional genotype data. It is shown that approximate F-distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for: (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models which perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods. PMID:27917525
Mendelian randomisation in type 2 diabetes and coronary artery disease.
Frayling, Timothy M; Stoneman, Charli E
2018-06-20
Type 2 diabetes, coronary artery disease and hypertension are associated with anthropometric and biomarker traits, including waist-to-hip-ratio, body mass index and altered glucose and insulin levels. Clinical trials, for example of weight-loss interventions, show these factors are causal, but lifelong impact of subtle changes in body mass index and body fat distribution are less clear. The use of human genetics can quantify the causal effects of long-term exposure to subtle changes of modifiable risk factors. Mendelian randomisation (MR) uses human genetic variants associated with the risk factor to quantify the relationship between risk factor and disease outcome. The last two years have seen an increase in the number of MR studies investigating the relationship between anthropometric traits and metabolic diseases. This review provides an overview of these recent MR studies in relation to type 2 diabetes, coronary artery disease and hypertension. MR provides evidence for causal associations of waist-to-hip-ratio, body mass index and altered glucose levels with type 2 diabetes, coronary artery disease and hypertension. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.
Volaki, Konstantina; Pampanos, Andreas; Kitsiou-Tzeli, Sophia; Vrettou, Christina; Oikonomakis, Vasilis; Sofocleous, Christalena; Kanavakis, Emmanuel
2013-10-01
Molecular and neurobiological evidence for the involvement of neuroligins (particularly NLGN3 and NLGN4X genes) in autistic disorder is accumulating. However, previous mutation screening studies on these two genes have yielded controversial results. The present study explores, for the first time, the contribution of NLGN3 and NLGN4X genetic variants in Greek patients with autistic disorder. We analyzed the full exonic sequence of NLGN3 and NLGN4X genes in 40 patients strictly fulfilling the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. criteria for autistic disorder. We identified nine nucleotide changes in NLGN4X--one probable causative mutation (p.K378R) previously reported by our research group, one novel variant (c.-206G>C), one nonvalidated single nucleotide polymorphism (SNP, rs111953947), and six known human SNPs reported in the SNP database--and one known human SNP in NLGN3 also reported in the SNP database. The variants identified are expected to be benign. However, they should be investigated in the context of variants in interacting cellular pathways to assess their contribution to the etiology of autism.
de Jong, Simone; Boks, Marco P. M.; Fuller, Tova F.; Strengman, Eric; Janson, Esther; de Kovel, Carolien G. F.; Ori, Anil P. S.; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D.; Cahn, Wiepke; Kahn, René S.; Horvath, Steve; Ophoff, Roel A.
2012-01-01
Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network. PMID:22761806
Large-scale sequencing efforts are uncovering the complexity of cancer genomes, which are composed of causal "driver" mutations that promote tumor progression along with many more pathologically neutral "passenger" events. The majority of mutations, both in known cancer drivers and uncharacterized genes, are generally of low occurrence, highlighting the need to functionally annotate the long tail of infrequent mutations present in heterogeneous cancers.
Anand, Deepti; Agrawal, Smriti A; Slavotinek, Anne; Lachke, Salil A
2018-04-01
Mutations in the transcription factor genes FOXE3, HSF4, MAF, and PITX3 cause congenital lens defects including cataracts that may be accompanied by defects in other components of the eye or in nonocular tissues. We comprehensively describe here all the variants in FOXE3, HSF4, MAF, and PITX3 genes linked to human developmental defects. A total of 52 variants for FOXE3, 18 variants for HSF4, 20 variants for MAF, and 19 variants for PITX3 identified so far in isolated cases or within families are documented. This effort reveals FOXE3, HSF4, MAF, and PITX3 to have 33, 16, 18, and 7 unique causal mutations, respectively. Loss-of-function mutant animals for these genes have served to model the pathobiology of the associated human defects, and we discuss the currently known molecular function of these genes, particularly with emphasis on their role in ocular development. Finally, we make the detailed FOXE3, HSF4, MAF, and PITX3 variant information available in the Leiden Online Variation Database (LOVD) platform at https://www.LOVD.nl/FOXE3, https://www.LOVD.nl/HSF4, https://www.LOVD.nl/MAF, and https://www.LOVD.nl/PITX3. Thus, this article informs on key variants in transcription factor genes linked to cataract, aphakia, corneal opacity, glaucoma, microcornea, microphthalmia, anterior segment mesenchymal dysgenesis, and Ayme-Gripp syndrome, and facilitates their access through Web-based databases. © 2018 Wiley Periodicals, Inc.
Dissociation Between APOC3 Variants, Hepatic Triglyceride Content and Insulin Resistance
Kozlitina, Julia; Boerwinkle, Eric; Cohen, Jonathan C; Hobbs, Helen H
2011-01-01
Nonalcoholic fatty liver disease (NAFLD) is an escalating health problem that is frequently associated with obesity and insulin resistance. The mechanistic relationship between NAFLD, obesity, and insulin resistance is not well understood. A nonsynonymous variant in patatin-like phospholipase domain containing 3 (rs738409, I148M) has been reproducibly associated with increased hepatic triglyceride content (HTGC) but has not been associated with either the body mass index (BMI) or indices of insulin resistance. Conversely, two sequence variants in apolipoprotein C3 (APOC3) that have been linked to hypertriglyceridemia (rs2854117 C > T and rs2854116 T > C) have recently been reported to be associated with both hepatic fat content and insulin resistance. Here we genotyped two APOC3 variants in 1228 African Americans, 843 European Americans and 426 Hispanics from a multiethnic population based study, the Dallas Heart Study and test for association with HTGC and homeostatic model of insulin resistance (HOMA-IR). We also examined the relationship between these two variants and HOMA-IR in the Atherosclerosis Risk in Communities (ARIC) study. No significant difference in hepatic fat content was found between carriers and noncarriers in the Dallas Heart Study. Neither APOC3 variant was associated with HOMA-IR in the Dallas Heart Study; this lack of association was confirmed in the ARIC study, even after the analysis was restricted to lean (BMI < 25 kg/m2) individuals (n = 4399). Conclusion: Our data do not support a causal relationship between these two variants in APOC3 and either HTGC or insulin resistance in middle-aged men and women. (Hepatology 2011;53:467-474) PMID:21274868
Méndez-Vidal, Cristina; González-del Pozo, María; Vela-Boza, Alicia; Santoyo-López, Javier; López-Domingo, Francisco J.; Vázquez-Marouschek, Carmen; Dopazo, Joaquin; Borrego, Salud
2013-01-01
Purpose Retinitis pigmentosa (RP) is an inherited retinal dystrophy characterized by extreme genetic and clinical heterogeneity. Thus, the diagnosis is not always easily performed due to phenotypic and genetic overlap. Current clinical practices have focused on the systematic evaluation of a set of known genes for each phenotype, but this approach may fail in patients with inaccurate diagnosis or infrequent genetic cause. In the present study, we investigated the genetic cause of autosomal recessive RP (arRP) in a Spanish family in which the causal mutation has not yet been identified with primer extension technology and resequencing. Methods We designed a whole-exome sequencing (WES)-based approach using NimbleGen SeqCap EZ Exome V3 sample preparation kit and the SOLiD 5500×l next-generation sequencing platform. We sequenced the exomes of both unaffected parents and two affected siblings. Exome analysis resulted in the identification of 43,204 variants in the index patient. All variants passing filter criteria were validated with Sanger sequencing to confirm familial segregation and absence in the control population. In silico prediction tools were used to determine mutational impact on protein function and the structure of the identified variants. Results Novel Usher syndrome type 2A (USH2A) compound heterozygous mutations, c.4325T>C (p.F1442S) and c.15188T>G (p.L5063R), located in exons 20 and 70, respectively, were identified as probable causative mutations for RP in this family. Family segregation of the variants showed the presence of both mutations in all affected members and in two siblings who were apparently asymptomatic at the time of family ascertainment. Clinical reassessment confirmed the diagnosis of RP in these patients. Conclusions Using WES, we identified two heterozygous novel mutations in USH2A as the most likely disease-causing variants in a Spanish family diagnosed with arRP in which the cause of the disease had not yet been identified with commonly used techniques. Our data reinforce the clinical role of WES in the molecular diagnosis of highly heterogeneous genetic diseases where conventional genetic approaches have previously failed in achieving a proper diagnosis. PMID:24227914
Beyond Markov: Accounting for independence violations in causal reasoning.
Rehder, Bob
2018-06-01
Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people's understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network (Y 1 ←X→Y 2 ) was extended so that the effects themselves had effects (Z 1 ←Y 1 ←X→Y 2 →Z 2 ). A traditional common effect network (Y 1 →X←Y 2 ) was extended so that the causes themselves had causes (Z 1 →Y 1 →X←Y 2 ←Z 2 ). Subjects' inferences were most consistent with the beta-Q model in which consistent states of the world-those in which variables are either mostly all present or mostly all absent-are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects' inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people's causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented. Copyright © 2018 Elsevier Inc. All rights reserved.
Kim, Yoonhee; Suktitipat, Bhoom; Yanek, Lisa R.; Faraday, Nauder; Wilson, Alexander F.; Becker, Diane M.; Becker, Lewis C.; Mathias, Rasika A.
2013-01-01
Platelet aggregation is heritable, and genome-wide association studies have detected strong associations with a common intronic variant of the platelet endothelial aggregation receptor1 (PEAR1) gene both in African American and European American individuals. In this study, we used a sequencing approach to identify additional exonic variants in PEAR1 that may also determine variability in platelet aggregation in the GeneSTAR Study. A 0.3 Mb targeted region on chromosome 1q23.1 including the entire PEAR1 gene was Sanger sequenced in 104 subjects (45% male, 49% African American, age = 52±13) selected on the basis of hyper- and hypo- aggregation across three different agonists (collagen, epinephrine, and adenosine diphosphate). Single-variant and multi-variant burden tests for association were performed. Of the 235 variants identified through sequencing, 61 were novel, and three of these were missense variants. More rare variants (MAF<5%) were noted in African Americans compared to European Americans (108 vs. 45). The common intronic GWAS-identified variant (rs12041331) demonstrated the most significant association signal in African Americans (p = 4.020×10−4); no association was seen for additional exonic variants in this group. In contrast, multi-variant burden tests indicated that exonic variants play a more significant role in European Americans (p = 0.0099 for the collective coding variants compared to p = 0.0565 for intronic variant rs12041331). Imputation of the individual exonic variants in the rest of the GeneSTAR European American cohort (N = 1,965) supports the results noted in the sequenced discovery sample: p = 3.56×10−4, 2.27×10−7, 5.20×10−5 for coding synonymous variant rs56260937 and collagen, epinephrine and adenosine diphosphate induced platelet aggregation, respectively. Sequencing approaches confirm that a common intronic variant has the strongest association with platelet aggregation in African Americans, and show that exonic variants play an additional role in platelet aggregation in European Americans. PMID:23704978
Huang, Lei; Kang, Wenjun; Bartom, Elizabeth; Onel, Kenan; Volchenboum, Samuel; Andrade, Jorge
2015-01-01
Whole exome sequencing has facilitated the discovery of causal genetic variants associated with human diseases at deep coverage and low cost. In particular, the detection of somatic mutations from tumor/normal pairs has provided insights into the cancer genome. Although there is an abundance of publicly-available software for the detection of germline and somatic variants, concordance is generally limited among variant callers and alignment algorithms. Successful integration of variants detected by multiple methods requires in-depth knowledge of the software, access to high-performance computing resources, and advanced programming techniques. We present ExScalibur, a set of fully automated, highly scalable and modulated pipelines for whole exome data analysis. The suite integrates multiple alignment and variant calling algorithms for the accurate detection of germline and somatic mutations with close to 99% sensitivity and specificity. ExScalibur implements streamlined execution of analytical modules, real-time monitoring of pipeline progress, robust handling of errors and intuitive documentation that allows for increased reproducibility and sharing of results and workflows. It runs on local computers, high-performance computing clusters and cloud environments. In addition, we provide a data analysis report utility to facilitate visualization of the results that offers interactive exploration of quality control files, read alignment and variant calls, assisting downstream customization of potential disease-causing mutations. ExScalibur is open-source and is also available as a public image on Amazon cloud. PMID:26271043
DOE Office of Scientific and Technical Information (OSTI.GOV)
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
Davies, Neil M; Gaunt, Tom R; Lewis, Sarah J; Holly, Jeff; Donovan, Jenny L; Hamdy, Freddie C; Kemp, John P; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Al Olama, Ali Amin; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Neal, David; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lathrop, Mark; Smith, George Davey; Martin, Richard M
2015-11-01
Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. We conducted a case-control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man's number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. The genetic risk scores explained 6.31 and 1.46% of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95% CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95% CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.
TCIRG1-associated congenital neutropenia.
Makaryan, Vahagn; Rosenthal, Elisabeth A; Bolyard, Audrey Anna; Kelley, Merideth L; Below, Jennifer E; Bamshad, Michael J; Bofferding, Kathryn M; Smith, Joshua D; Buckingham, Kati; Boxer, Laurence A; Skokowa, Julia; Welte, Karl; Nickerson, Deborah A; Jarvik, Gail P; Dale, David C
2014-07-01
Severe congenital neutropenia (SCN) is a rare hematopoietic disorder, with estimated incidence of 1 in 200,000 individuals of European descent, many cases of which are inherited in an autosomal dominant pattern. Despite the fact that several causal genes have been identified, the genetic basis for >30% of cases remains unknown. We report a five-generation family segregating a novel single nucleotide variant (SNV) in TCIRG1. There is perfect cosegregation of the SNV with congenital neutropenia in this family; all 11 affected, but none of the unaffected, individuals carry this novel SNV. Western blot analysis show reduced levels of TCIRG1 protein in affected individuals, compared to healthy controls. Two unrelated patients with SCN, identified by independent investigators, are heterozygous for different, rare, highly conserved, coding variants in TCIRG1. © 2014 WILEY PERIODICALS, INC.
Imm, Jennifer; Kerrigan, Talitha L; Jeffries, Aaron; Lunnon, Katie
2017-11-01
It is thought that both genetic and epigenetic variation play a role in Alzheimer's disease initiation and progression. With the advent of somatic cell reprogramming into induced pluripotent stem cells it is now possible to generate patient-derived cells that are able to more accurately model and recapitulate disease. Furthermore, by combining this with recent advances in (epi)genome editing technologies, it is possible to begin to examine the functional consequence of previously nominated genetic variants and infer epigenetic causality from recently identified epigenetic variants. In this review, we explore the role of genetic and epigenetic variation in Alzheimer's disease and how the functional relevance of nominated loci can be investigated using induced pluripotent stem cells and (epi)genome editing techniques.
TCIRG1 associated Congenital Neutropenia
Makaryan, Vahagn; Rosenthal, Elisabeth A.; Bolyard, Audrey Anna; Kelley, Merideth L.; Below, Jennifer E.; Bamshad, Michael J.; Bofferding, Kathryn M.; Smith, Joshua D.; Buckingham, Kati; Boxer, Laurence A.; Skokowa, Julia; Welte, Karl; Nickerson, Deborah A.; Jarvik, Gail P.; Dale, David C.
2014-01-01
Severe congenital neutropenia (SCN) is a rare hematopoietic disorder, with estimated incidence of 1 in 200,000 individuals of European descent, many cases of which are inherited in an autosomal dominant pattern. Despite the fact that several causal genes have been identified, the genetic basis for >30% of cases remains unknown. We report a five generation family segregating a novel single nucleotide variant (SNV) in TCIRG1. There is perfect co-segregation of the SNV with congenital neutropenia in this family; all 11 affected, but none of the unaffected, individuals carry this novel SNV. Western blot analysis show reduced levels of TCIRG1 protein in affected individuals, compared to healthy controls. Two unrelated patients with SCN, identified by independent investigators, are heterozygous for different, rare, highly conserved, coding variants in TCIRG1. PMID:24753205
Rare ADH Variant Constellations are Specific for Alcohol Dependence
Zuo, Lingjun; Zhang, Heping; Malison, Robert T.; Li, Chiang-Shan R.; Zhang, Xiang-Yang; Wang, Fei; Lu, Lingeng; Lu, Lin; Wang, Xiaoping; Krystal, John H.; Zhang, Fengyu; Deng, Hong-Wen; Luo, Xingguang
2013-01-01
Aims: Some of the well-known functional alcohol dehydrogenase (ADH) gene variants (e.g. ADH1B*2, ADH1B*3 and ADH1C*2) that significantly affect the risk of alcohol dependence are rare variants in most populations. In the present study, we comprehensively examined the associations between rare ADH variants [minor allele frequency (MAF) <0.05] and alcohol dependence, with several other neuropsychiatric and neurological disorders as reference. Methods: A total of 49,358 subjects in 22 independent cohorts with 11 different neuropsychiatric and neurological disorders were analyzed, including 3 cohorts with alcohol dependence. The entire ADH gene cluster (ADH7–ADH1C–ADH1B–ADH1A–ADH6–ADH4–ADH5 at Chr4) was imputed in all samples using the same reference panels that included whole-genome sequencing data. We stringently cleaned the phenotype and genotype data to obtain a total of 870 single nucleotide polymorphisms with 0< MAF <0.05 for association analysis. Results: We found that a rare variant constellation across the entire ADH gene cluster was significantly associated with alcohol dependence in European-Americans (Fp1: simulated global P = 0.045), European-Australians (Fp5: global P = 0.027; collapsing: P = 0.038) and African-Americans (Fp5: global P = 0.050; collapsing: P = 0.038), but not with any other neuropsychiatric disease. Association signals in this region came principally from ADH6, ADH7, ADH1B and ADH1C. In particular, a rare ADH6 variant constellation showed a replicable association with alcohol dependence across these three independent cohorts. No individual rare variants were statistically significantly associated with any disease examined after group- and region-wide correction for multiple comparisons. Conclusion: We conclude that rare ADH variants are specific for alcohol dependence. The ADH gene cluster may harbor a causal variant(s) for alcohol dependence. PMID:23019235
Zhang, Qianqian; Guldbrandtsen, Bernt; Calus, Mario P L; Lund, Mogens Sandø; Sahana, Goutam
2016-08-17
There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared to LMM. Therefore, it is recommended to use rare variant association mapping methods to map rare genetic variants that affect quantitative traits in livestock, such as bovine populations.
2016-06-01
Genetic determinants of stroke, the leading neurological cause of death and disability, are poorly understood and have seldom been explored in the general population. Our aim was to identify additional loci for stroke by doing a meta-analysis of genome-wide association studies. For the discovery sample, we did a genome-wide analysis of common genetic variants associated with incident stroke risk in 18 population-based cohorts comprising 84 961 participants, of whom 4348 had stroke. Stroke diagnosis was ascertained and validated by the study investigators. Mean age at stroke ranged from 45·8 years to 76·4 years, and data collection in the studies took place between 1948 and 2013. We did validation analyses for variants yielding a significant association (at p<5 × 10(-6)) with all-stroke, ischaemic stroke, cardioembolic ischaemic stroke, or non-cardioembolic ischaemic stroke in the largest available cross-sectional studies (70 804 participants, of whom 19 816 had stroke). Summary-level results of discovery and follow-up stages were combined using inverse-variance weighted fixed-effects meta-analysis, and in-silico lookups were done in stroke subtypes. For genome-wide significant findings (at p<5 × 10(-8)), we explored associations with additional cerebrovascular phenotypes and did functional experiments using conditional (inducible) deletion of the probable causal gene in mice. We also studied the expression of orthologs of this probable causal gene and its effects on cerebral vasculature in zebrafish mutants. We replicated seven of eight known loci associated with risk for ischaemic stroke, and identified a novel locus at chromosome 6p25 (rs12204590, near FOXF2) associated with risk of all-stroke (odds ratio [OR] 1·08, 95% CI 1·05-1·12, p=1·48 × 10(-8); minor allele frequency 21%). The rs12204590 stroke risk allele was also associated with increased MRI-defined burden of white matter hyperintensity-a marker of cerebral small vessel disease-in stroke-free adults (n=21 079; p=0·0025). Consistently, young patients (aged 2-32 years) with segmental deletions of FOXF2 showed an extensive burden of white matter hyperintensity. Deletion of Foxf2 in adult mice resulted in cerebral infarction, reactive gliosis, and microhaemorrhage. The orthologs of FOXF2 in zebrafish (foxf2b and foxf2a) are expressed in brain pericytes and mutant foxf2b(-/-) cerebral vessels show decreased smooth muscle cell and pericyte coverage. We identified common variants near FOXF2 that are associated with increased stroke susceptibility. Epidemiological and experimental data suggest that FOXF2 mediates this association, potentially via differentiation defects of cerebral vascular mural cells. Further expression studies in appropriate human tissues, and further functional experiments with long follow-up periods are needed to fully understand the underlying mechanisms. NIH, NINDS, NHMRC, CIHR, European national research institutions, Fondation Leducq. Copyright © 2016 Elsevier Ltd. All rights reserved.
Benzinou, Michael; Walley, Andrew; Lobbens, Stephan; Charles, Marie-Aline; Jouret, Béatrice; Fumeron, Frédéric; Balkau, Beverley; Meyre, David; Froguel, Philippe
2006-10-01
Bardet-Biedl syndrome (BBS) is a rare developmental disorder with the cardinal features of abdominal obesity, retinopathy, polydactyly, cognitive impairment, renal and cardiac anomalies, hypertension, and diabetes. BBS is genetically heterogeneous, with nine genes identified to date and evidence for additional loci. In this study, we performed mutation analysis of the coding and conserved regions of BBS1, BBS2, BBS4, and BBS6 in 48 French Caucasian individuals. Among the 36 variants identified, 12 were selected and genotyped in 1,943 French-Caucasian case subjects and 1,299 French-Caucasian nonobese nondiabetic control subjects. Variants in BBS2, BBS4, and BBS6 showed evidence of association with common obesity in an age-dependent manner, the BBS2 single nucleotide polymorphism (SNP) being associated with common adult obesity (P = 0.0005) and the BBS4 and BBS6 SNPs being associated with common early-onset childhood obesity (P = 0.0003) and common adult morbid obesity (0.0003 < P < 0.007). The association of the BBS4 rs7178130 variant was found to be supported by transmission disequilibrium testing (P = 0.006). The BBS6 variants also showed nominal evidence of association with quantitative components of the metabolic syndrome (e.g., dyslipidemia, hyperglycemia), a complication previously described in BBS patients. In summary, our preliminary data suggest that variations at BBS genes are associated with risk of common obesity.
Zeng, Yanni; Navarro, Pau; Xia, Charley; Amador, Carmen; Fernandez-Pujals, Ana M; Thomson, Pippa A; Campbell, Archie; Nagy, Reka; Clarke, Toni-Kim; Hafferty, Jonathan D; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M
2016-12-01
Both genetic and environmental factors contribute to risk of depression, but estimates of their relative contributions are limited. Commonalities between clinically-assessed major depressive disorder (MDD) and self-declared depression (SDD) are also unclear. Using data from a large Scottish family-based cohort (GS:SFHS, N=19,994), we estimated the genetic and environmental variance components for MDD and SDD. The components representing the genetic effect associated with genome-wide common genetic variants (SNP heritability), the additional pedigree-associated genetic effect and non-genetic effects associated with common environments were estimated in a linear mixed model (LMM). Both MDD and SDD had significant contributions from components representing the effect from common genetic variants, the additional genetic effect associated with the pedigree and the common environmental effect shared by couples. The estimate of correlation between SDD and MDD was high (r=1.00, se=0.20) for common-variant-associated genetic effect and lower for the additional genetic effect from the pedigree (r=0.57, se=0.08) and the couple-shared environmental effect (r=0.53, se=0.22). Both genetics and couple-shared environmental effects were major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Family studies to find rare high risk variants in migraine.
Hansen, Rikke Dyhr; Christensen, Anne Francke; Olesen, Jes
2017-12-01
Migraine has long been known as a common complex disease caused by genetic and environmental factors. The pathophysiology and the specific genetic susceptibility are poorly understood. Common variants only explain a small part of the heritability of migraine. It is thought that rare genetic variants with bigger effect size may be involved in the disease. Since migraine has a tendency to cluster in families, a family approach might be the way to find these variants. This is also indicated by identification of migraine-associated loci in classical linkage-analyses in migraine families. A single migraine study using a candidate-gene approach was performed in 2010 identifying a rare mutation in the TRESK potassium channel segregating in a large family with migraine with aura, but this finding has later become questioned. The technologies of next-generation sequencing (NGS) now provides an affordable tool to investigate the genetic variation in the entire exome or genome. The family-based study design using NGS is described in this paper. We also review family studies using NGS that have been successful in finding rare variants in other common complex diseases in order to argue the promising application of a family approach to migraine. PubMed was searched to find studies that looked for rare genetic variants in common complex diseases through a family-based design using NGS, excluding studies looking for de-novo mutations, or using a candidate-gene approach and studies on cancer. All issues from Nature Genetics and PLOS genetics 2014, 2015 and 2016 (UTAI June) were screened for relevant papers. Reference lists from included and other relevant papers were also searched. For the description of the family-based study design using NGS an in-house protocol was used. Thirty-two successful studies, which covered 16 different common complex diseases, were included in this paper. We also found a single migraine study. Twenty-three studies found one or a few family specific variants (less than five), while other studies found several possible variants. Not all of them were genome wide significant. Four studies performed follow-up analyses in unrelated cases and controls and calculated odds ratios that supported an association between detected variants and risk of disease. Studies of 11 diseases identified rare variants that segregated fully or to a large degree with the disease in the pedigrees. It is possible to find rare high risk variants for common complex diseases through a family-based approach. One study using a family approach and NGS to find rare variants in migraine has already been published but with strong limitations. More studies are under way.
Meta-analysis of gene-level tests for rare variant association.
Liu, Dajiang J; Peloso, Gina M; Zhan, Xiaowei; Holmen, Oddgeir L; Zawistowski, Matthew; Feng, Shuang; Nikpay, Majid; Auer, Paul L; Goel, Anuj; Zhang, He; Peters, Ulrike; Farrall, Martin; Orho-Melander, Marju; Kooperberg, Charles; McPherson, Ruth; Watkins, Hugh; Willer, Cristen J; Hveem, Kristian; Melander, Olle; Kathiresan, Sekar; Abecasis, Gonçalo R
2014-02-01
The majority of reported complex disease associations for common genetic variants have been identified through meta-analysis, a powerful approach that enables the use of large sample sizes while protecting against common artifacts due to population structure and repeated small-sample analyses sharing individual-level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the focus of analysis. Here we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable-threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features from single-variant meta-analysis approaches and demonstrate its use in a study of blood lipid levels in ∼18,500 individuals genotyped with exome arrays.
Smith, Geoff; Murray, Heather; Brennan, Stephen O
2013-01-01
Commonly used methods for assay of haemoglobin A(1c) (HbA(1c)) are susceptible to interference from the presence of haemoglobin variants. In many systems, the common variants can be identified but scientists and pathologists must remain vigilant for more subtle variants that may result in spuriously high or low HbA(1c) values. It is clearly important to recognize these events whether HbA(1c) is being used as a monitoring tool or, as is increasingly the case, for diagnostic purposes. We report a patient with a rare haemoglobin variant (Hb Sinai-Baltimore) that resulted in spuriously low values of HbA(1c) when assayed using ion exchange chromatography, and the steps taken to elucidate the nature of the variant.
Fra, Anna M.; Gooptu, Bibek; Ferrarotti, Ilaria; Miranda, Elena; Scabini, Roberta; Ronzoni, Riccardo; Benini, Federica; Corda, Luciano; Medicina, Daniela; Luisetti, Maurizio; Schiaffonati, Luisa
2012-01-01
Alpha1-antitrypsin (AAT) deficiency is a hereditary disorder associated with reduced AAT plasma levels, predisposing adults to pulmonary emphysema. The most common genetic AAT variants found in patients are the mildly deficient S and the severely deficient Z alleles, but several other pathogenic rare alleles have been reported. While the plasma AAT deficiency is a common trait of the disease, only a few AAT variants, including the prototypic Z AAT and some rare variants, form cytotoxic polymers in the endoplasmic reticulum of hepatocytes and predispose to liver disease. Here we report the identification of three new rare AAT variants associated to reduced plasma levels and characterize their molecular behaviour in cellular models. The variants, called Mpisa (Lys259Ile), Etaurisano (Lys368Glu) and Yorzinuovi (Pro391His), showed reduced secretion compared to control M AAT, and accumulated to different extents in the cells as ordered polymeric structures resembling those formed by the Z variant. Structural analysis of the mutations showed that they may facilitate polymerization both by loosening ‘latch’ interactions constraining the AAT reactive loop and through effects on core packing. In conclusion, the new AAT deficiency variants, besides increasing the risk of lung disease, may predispose to liver disease, particularly if associated with the common Z variant. The new mutations cluster structurally, thus defining a region of the AAT molecule critical for regulating its conformational state. PMID:22723858
Wium-Andersen, Marie Kim; Ørsted, David Dynnes; Tolstrup, Janne Schurmann; Nordestgaard, Børge Grønne
2015-04-01
Increased alcohol consumption has been associated with depression and alcoholism, but whether these associations are causal remains unclear. We tested whether alcohol consumption is causally associated with depression and alcoholism. We included 78,154 men and women aged 20-100 years randomly selected in 1991-2010 from the general population of Copenhagen, Denmark, and genotyped 68,486 participants for two genetic variants in two alcohol dehydrogenase (ADH) genes, ADH-1B (rs1229984) and ADH-1C (rs698). We performed observational and causal analyses using a Mendelian randomization design with antidepressant medication use and hospitalization/death, with depression and alcoholism as outcomes. In prospective analyses, the multifactorially adjusted hazard ratio for participants reporting >6 drinks/day vs participants reporting 0.1-1 drinks/day was 1.28 (95% confidence interval, 1.00-1.65) for prescription antidepressant use, with a corresponding hazard ratio of 0.80 (0.45-1.45) for hospitalization/death with depression and of 11.7 (8.77-15.6) for hospitalization/death with alcoholism. For hospitalization/death with alcoholism, instrumental variable analysis yielded a causal odds ratio of 28.6 (95 % confidence interval 6.47-126) for an increase of 1 drink/day estimated from the combined genotype combination, whereas the corresponding multifactorially adjusted observational odds ratio was 1.28 (1.25-1.31). Corresponding odds ratios were 1.11 (0.67-1.83) causal and 1.04 (1.03-1.06) observational for prescription antidepressant use, and 4.52 (0.99-20.5) causal and 0.98 (0.94-1.03) observational for hospitalization/death with depression. These data indicate that the association between increased alcohol consumption and alcoholism is causal, without similar strong evidence for depression. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
Shift-Variant Multidimensional Systems.
1985-05-29
i=0,1,** *N-1 in (3.1), one will get 0() i_0,1,* ,N-1 which is nonnegative due to the Perron - Frobenius Theorem [24]. That is, the A nonnegativity ...and the current input. The state-space model was extended in order to model 2-D discrete LSV systems with support on a causality cone . Subsequently...formulated as a special system of linear equations with nonnegative coefficients whose solution is required to satisfy con- straints like nonnegativity in
Haack, Tobias B; Madignier, Florence; Herzer, Martina; Lamantea, Eleonora; Danhauser, Katharina; Invernizzi, Federica; Koch, Johannes; Freitag, Martin; Drost, Rene; Hillier, Ingo; Haberberger, Birgit; Mayr, Johannes A; Ahting, Uwe; Tiranti, Valeria; Rötig, Agnes; Iuso, Arcangela; Horvath, Rita; Tesarova, Marketa; Baric, Ivo; Uziel, Graziella; Rolinski, Boris; Sperl, Wolfgang; Meitinger, Thomas; Zeviani, Massimo; Freisinger, Peter; Prokisch, Holger
2012-02-01
Mitochondrial complex I deficiency is the most common cause of mitochondrial disease in childhood. Identification of the molecular basis is difficult given the clinical and genetic heterogeneity. Most patients lack a molecular definition in routine diagnostics. A large-scale mutation screen of 75 candidate genes in 152 patients with complex I deficiency was performed by high-resolution melting curve analysis and Sanger sequencing. The causal role of a new disease allele was confirmed by functional complementation assays. The clinical phenotype of patients carrying mutations was documented using a standardised questionnaire. Causative mutations were detected in 16 genes, 15 of which had previously been associated with complex I deficiency: three mitochondrial DNA genes encoding complex I subunits, two mitochondrial tRNA genes and nuclear DNA genes encoding six complex I subunits and four assembly factors. For the first time, a causal mutation is described in NDUFB9, coding for a complex I subunit, resulting in reduction in NDUFB9 protein and both amount and activity of complex I. These features were rescued by expression of wild-type NDUFB9 in patient-derived fibroblasts. Mutant NDUFB9 is a new cause of complex I deficiency. A molecular diagnosis related to complex I deficiency was established in 18% of patients. However, most patients are likely to carry mutations in genes so far not associated with complex I function. The authors conclude that the high degree of genetic heterogeneity in complex I disorders warrants the implementation of unbiased genome-wide strategies for the complete molecular dissection of mitochondrial complex I deficiency.
Nedeljkovic, Ivana; Terzikhan, Natalie; Vonk, Judith M; van der Plaat, Diana A; Lahousse, Lies; van Diemen, Cleo C; Hobbs, Brian D; Qiao, Dandi; Cho, Michael H; Brusselle, Guy G; Postma, Dirkje S; Boezen, H M; van Duijn, Cornelia M; Amin, Najaf
2018-01-01
Chronic obstructive pulmonary disease (COPD) is a complex and heritable disease, associated with multiple genetic variants. Specific familial types of COPD may be explained by rare variants, which have not been widely studied. We aimed to discover rare genetic variants underlying COPD through a genome-wide linkage scan. Affected-only analysis was performed using the 6K Illumina Linkage IV Panel in 142 cases clustered in 27 families from a genetic isolate, the Erasmus Rucphen Family (ERF) study. Potential causal variants were identified by searching for shared rare variants in the exome-sequence data of the affected members of the families contributing most to the linkage peak. The identified rare variants were then tested for association with COPD in a large meta-analysis of several cohorts. Significant evidence for linkage was observed on chromosomes 15q14-15q25 [logarithm of the odds (LOD) score = 5.52], 11p15.4-11q14.1 (LOD = 3.71) and 5q14.3-5q33.2 (LOD = 3.49). In the chromosome 15 peak, that harbors the known COPD locus for nicotinic receptors, and in the chromosome 5 peak we could not identify shared variants. In the chromosome 11 locus, we identified four rare (minor allele frequency (MAF) <0.02), predicted pathogenic, missense variants. These were shared among the affected family members. The identified variants localize to genes including neuroblast differentiation-associated protein ( AHNAK ), previously associated with blood biomarkers in COPD, phospholipase C Beta 3 ( PLCB3 ), shown to increase airway hyper-responsiveness, solute carrier family 22-A11 ( SLC22A11 ), involved in amino acid metabolism and ion transport, and metallothionein-like protein 5 ( MTL5 ), involved in nicotinate and nicotinamide metabolism. Association of SLC22A11 and MTL5 variants were confirmed in the meta-analysis of 9,888 cases and 27,060 controls. In conclusion, we have identified novel rare variants in plausible genes related to COPD. Further studies utilizing large sample whole-genome sequencing should further confirm the associations at chromosome 11 and investigate the chromosome 15 and 5 linked regions.
Mucopolysaccharidosis VI in cats - clarification regarding genetic testing.
Lyons, Leslie A; Grahn, Robert A; Genova, Francesca; Beccaglia, Michela; Hopwood, John J; Longeri, Maria
2016-07-02
The release of new DNA-based diagnostic tools has increased tremendously in companion animals. Over 70 different DNA variants are now known for the cat, including DNA variants in disease-associated genes and genes causing aesthetically interesting traits. The impact genetic tests have on animal breeding and health management is significant because of the ability to control the breeding of domestic cats, especially breed cats. If used properly, genetic testing can prevent the production of diseased animals, causing the reduction of the frequency of the causal variant in the population, and, potentially, the eventual eradication of the disease. However, testing of some identified DNA variants may be unwarranted and cause undo strife within the cat breeding community and unnecessary reduction of gene pools and availability of breeding animals. Testing for mucopolysaccharidosis Type VI (MPS VI) in cats, specifically the genetic testing of the L476P (c.1427T>C) and the D520N (c.1558G>A) variants in arylsulfatase B (ARSB), has come under scrutiny. No health problems are associated with the D520N (c.1558G>A) variant, however, breeders that obtain positive results for this variant are speculating as to possible correlation with health concerns. Birman cats already have a markedly reduced gene pool and have a high frequency of the MPS VI D520N variant. Further reduction of the gene pool by eliminating cats that are heterozygous or homozygous for only the MPS VI D520N variant could lead to more inbreeding depression effects on the breed population. Herein is debated the genetic testing of the MPS VI D520N variant in cats. Surveys from different laboratories suggest the L476P (c.1427T>C) disease-associated variant should be monitored in the cat breed populations, particularly breeds with Siamese derivations and outcrosses. However, the D520N has no evidence of association with disease in cats and testing is not recommended in the absence of L476P genotyping. Selection against the D520N is not warranted in cat populations. More rigorous guidelines may be required to support the genetic testing of DNA variants in all animal species.
Exploring the Epileptic Brain Network Using Time-Variant Effective Connectivity and Graph Theory.
Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Khan, Sehresh; Manganotti, Paolo; Menegaz, Gloria
2017-09-01
The application of time-varying measures of causality between source time series can be very informative to elucidate the direction of communication among the regions of an epileptic brain. The aim of the study was to identify the dynamic patterns of epileptic networks in focal epilepsy by applying multivariate adaptive directed transfer function (ADTF) analysis and graph theory to high-density electroencephalographic recordings. The cortical network was modeled after source reconstruction and topology modulations were detected during interictal spikes. First a distributed linear inverse solution, constrained to the individual grey matter, was applied to the averaged spikes and the mean source activity over 112 regions, as identified by the Harvard-Oxford Atlas, was calculated. Then, the ADTF, a dynamic measure of causality, was used to quantify the connectivity strength between pairs of regions acting as nodes in the graph, and the measure of node centrality was derived. The proposed analysis was effective in detecting the focal regions as well as in characterizing the dynamics of the spike propagation, providing evidence of the fact that the node centrality is a reliable feature for the identification of the epileptogenic zones. Validation was performed by multimodal analysis as well as from surgical outcomes. In conclusion, the time-variant connectivity analysis applied to the epileptic patients can distinguish the generator of the abnormal activity from the propagation spread and identify the connectivity pattern over time.
Analysis of MSH3 in endometrial cancers with defective DNA mismatch repair.
Swisher, E M; Mutch, D G; Herzog, T J; Rader, J S; Kowalski, L D; Elbendary, A; Goodfellow, P J
1998-01-01
To clarify the origin of defective mismatch repair (MMR) in sporadic endometrial cancers with microsatellite instability (MSI), a thorough mutation analysis was performed on the human mismatch repair gene MSH3. Twenty-eight MSI-positive endometrial cancers were investigated for mutations in the human mismatch repair gene MSH3 using single-strand conformation variant (SSCV) analysis of all 24 exons. All variants were sequenced. Loss of heterozygosity was investigated at all MSH3 polymorphisms discovered. A subset of tumors were investigated for methylation of the 5' promoter region of MSH3 using Southern blot hybridization. An identical single-base deletion (delta A) predicted to result in a truncated proteins was discovered in six tumors (21.4%). This deletion occurs in a string of eight consecutive adenosine residues (A8). Because simple repeat sequences are unstable in cells with defective MMR, the observed mutation may be an effect, rather than a cause, of MSI. Evidence of inactivation of the second MSH3 allele in tumors with the delta A mutation would strongly support a causal role for these MSH3 mutations. However, there was no evidence of a second mutation, loss of sequences, or methylation of the promoter region in any of the tumors with the delta A mutation. Although the delta A mutation is a frequent event in sporadic MSI-positive endometrial cancers, it may not be causally associated with defective DNA MMR.
Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics
Chen, Wenan; Larrabee, Beth R.; Ovsyannikova, Inna G.; Kennedy, Richard B.; Haralambieva, Iana H.; Poland, Gregory A.; Schaid, Daniel J.
2015-01-01
Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. PMID:25948564
Ben-Sasson, Ayelet
2010-01-01
Anxiety disorders and sensory over-responsivity (SOR) are common in children with autism spectrum disorders (ASD), and there is evidence for an association between these two conditions. Currently, it is unclear what causal mechanisms may exist between SOR and anxiety. We propose three possible theories to explain the association between anxiety and SOR: (a) SOR is caused by anxiety; (b) Anxiety is caused by SOR; or (c) SOR and anxiety are causally unrelated but are associated through a common risk factor or diagnostic overlap. In this paper, we examine support for each theory in the existing anxiety, autism, and neuroscience literature, and discuss how each theory informs choice of interventions and implications for future studies. PMID:20383658
Preferential Binding to Elk-1 by SLE-Associated IL10 Risk Allele Upregulates IL10 Expression
Kelly, Jennifer A.; Brown, Elizabeth E.; Harley, John B.; Bae, Sang-Cheol; Alarcόn-Riquelme, Marta E.; Edberg, Jeffrey C.; Kimberly, Robert P.; Ramsey-Goldman, Rosalind; Petri, Michelle A.; Reveille, John D.; Vilá, Luis M.; Alarcón, Graciela S.; Kaufman, Kenneth M.; Vyse, Timothy J.; Jacob, Chaim O.; Gaffney, Patrick M.; Sivils, Kathy Moser; James, Judith A.; Kamen, Diane L.; Gilkeson, Gary S.; Niewold, Timothy B.; Merrill, Joan T.; Scofield, R. Hal; Criswell, Lindsey A.; Stevens, Anne M.; Boackle, Susan A.; Kim, Jae-Hoon; Choi, Jiyoung; Pons-Estel, Bernardo A.; Freedman, Barry I.; Anaya, Juan-Manuel; Martin, Javier; Yu, C. Yung; Chang, Deh-Ming; Song, Yeong Wook; Langefeld, Carl D.; Chen, Weiling; Grossman, Jennifer M.; Cantor, Rita M.; Hahn, Bevra H.; Tsao, Betty P.
2013-01-01
Immunoregulatory cytokine interleukin-10 (IL-10) is elevated in sera from patients with systemic lupus erythematosus (SLE) correlating with disease activity. The established association of IL10 with SLE and other autoimmune diseases led us to fine map causal variant(s) and to explore underlying mechanisms. We assessed 19 tag SNPs, covering the IL10 gene cluster including IL19, IL20 and IL24, for association with SLE in 15,533 case and control subjects from four ancestries. The previously reported IL10 variant, rs3024505 located at 1 kb downstream of IL10, exhibited the strongest association signal and was confirmed for association with SLE in European American (EA) (P = 2.7×10−8, OR = 1.30), but not in non-EA ancestries. SNP imputation conducted in EA dataset identified three additional SLE-associated SNPs tagged by rs3024505 (rs3122605, rs3024493 and rs3024495 located at 9.2 kb upstream, intron 3 and 4 of IL10, respectively), and SLE-risk alleles of these SNPs were dose-dependently associated with elevated levels of IL10 mRNA in PBMCs and circulating IL-10 protein in SLE patients and controls. Using nuclear extracts of peripheral blood cells from SLE patients for electrophoretic mobility shift assays, we identified specific binding of transcription factor Elk-1 to oligodeoxynucleotides containing the risk (G) allele of rs3122605, suggesting rs3122605 as the most likely causal variant regulating IL10 expression. Elk-1 is known to be activated by phosphorylation and nuclear localization to induce transcription. Of interest, phosphorylated Elk-1 (p-Elk-1) detected only in nuclear extracts of SLE PBMCs appeared to increase with disease activity. Co-expression levels of p-Elk-1 and IL-10 were elevated in SLE T, B cells and monocytes, associated with increased disease activity in SLE B cells, and were best downregulated by ERK inhibitor. Taken together, our data suggest that preferential binding of activated Elk-1 to the IL10 rs3122605-G allele upregulates IL10 expression and confers increased risk for SLE in European Americans. PMID:24130510
Preferential binding to Elk-1 by SLE-associated IL10 risk allele upregulates IL10 expression.
Sakurai, Daisuke; Zhao, Jian; Deng, Yun; Kelly, Jennifer A; Brown, Elizabeth E; Harley, John B; Bae, Sang-Cheol; Alarcόn-Riquelme, Marta E; Edberg, Jeffrey C; Kimberly, Robert P; Ramsey-Goldman, Rosalind; Petri, Michelle A; Reveille, John D; Vilá, Luis M; Alarcón, Graciela S; Kaufman, Kenneth M; Vyse, Timothy J; Jacob, Chaim O; Gaffney, Patrick M; Sivils, Kathy Moser; James, Judith A; Kamen, Diane L; Gilkeson, Gary S; Niewold, Timothy B; Merrill, Joan T; Scofield, R Hal; Criswell, Lindsey A; Stevens, Anne M; Boackle, Susan A; Kim, Jae-Hoon; Choi, Jiyoung; Pons-Estel, Bernardo A; Freedman, Barry I; Anaya, Juan-Manuel; Martin, Javier; Yu, C Yung; Chang, Deh-Ming; Song, Yeong Wook; Langefeld, Carl D; Chen, Weiling; Grossman, Jennifer M; Cantor, Rita M; Hahn, Bevra H; Tsao, Betty P
2013-01-01
Immunoregulatory cytokine interleukin-10 (IL-10) is elevated in sera from patients with systemic lupus erythematosus (SLE) correlating with disease activity. The established association of IL10 with SLE and other autoimmune diseases led us to fine map causal variant(s) and to explore underlying mechanisms. We assessed 19 tag SNPs, covering the IL10 gene cluster including IL19, IL20 and IL24, for association with SLE in 15,533 case and control subjects from four ancestries. The previously reported IL10 variant, rs3024505 located at 1 kb downstream of IL10, exhibited the strongest association signal and was confirmed for association with SLE in European American (EA) (P = 2.7×10⁻⁸, OR = 1.30), but not in non-EA ancestries. SNP imputation conducted in EA dataset identified three additional SLE-associated SNPs tagged by rs3024505 (rs3122605, rs3024493 and rs3024495 located at 9.2 kb upstream, intron 3 and 4 of IL10, respectively), and SLE-risk alleles of these SNPs were dose-dependently associated with elevated levels of IL10 mRNA in PBMCs and circulating IL-10 protein in SLE patients and controls. Using nuclear extracts of peripheral blood cells from SLE patients for electrophoretic mobility shift assays, we identified specific binding of transcription factor Elk-1 to oligodeoxynucleotides containing the risk (G) allele of rs3122605, suggesting rs3122605 as the most likely causal variant regulating IL10 expression. Elk-1 is known to be activated by phosphorylation and nuclear localization to induce transcription. Of interest, phosphorylated Elk-1 (p-Elk-1) detected only in nuclear extracts of SLE PBMCs appeared to increase with disease activity. Co-expression levels of p-Elk-1 and IL-10 were elevated in SLE T, B cells and monocytes, associated with increased disease activity in SLE B cells, and were best downregulated by ERK inhibitor. Taken together, our data suggest that preferential binding of activated Elk-1 to the IL10 rs3122605-G allele upregulates IL10 expression and confers increased risk for SLE in European Americans.
Parker, Margaret M.; Chen, Han; Lao, Taotao; Hardin, Megan; Qiao, Dandi; Hawrylkiewicz, Iwona; Sliwinski, Pawel; Yim, Jae-Joon; Kim, Woo Jin; Kim, Deog Kyeom; Castaldi, Peter J.; Hersh, Craig P.; Morrow, Jarrett; Celli, Bartolome R.; Pinto-Plata, Victor M.; Criner, Gerald J.; Marchetti, Nathaniel; Bueno, Raphael; Agustí, Alvar; Make, Barry J.; Crapo, James D.; Calverley, Peter M.; Donner, Claudio F.; Lomas, David A.; Wouters, Emiel F. M.; Vestbo, Jorgen; Paré, Peter D.; Levy, Robert D.; Rennard, Stephen I.; Zhou, Xiaobo; Laird, Nan M.; Lin, Xihong; Beaty, Terri H.; Silverman, Edwin K.
2016-01-01
Rationale: Chronic obstructive pulmonary disease (COPD) susceptibility is in part related to genetic variants. Most genetic studies have been focused on genome-wide common variants without a specific focus on coding variants, but common and rare coding variants may also affect COPD susceptibility. Objectives: To identify coding variants associated with COPD. Methods: We tested nonsynonymous, splice, and stop variants derived from the Illumina HumanExome array for association with COPD in five study populations enriched for COPD. We evaluated single variants with a minor allele frequency greater than 0.5% using logistic regression. Results were combined using a fixed effects meta-analysis. We replicated novel single-variant associations in three additional COPD cohorts. Measurements and Main Results: We included 6,004 control subjects and 6,161 COPD cases across five cohorts for analysis. Our top result was rs16969968 (P = 1.7 × 10−14) in CHRNA5, a locus previously associated with COPD susceptibility and nicotine dependence. Additional top results were found in AGER, MMP3, and SERPINA1. A nonsynonymous variant, rs181206, in IL27 (P = 4.7 × 10−6) was just below the level of exome-wide significance but attained exome-wide significance (P = 5.7 × 10−8) when combined with results from other cohorts. Gene expression datasets revealed an association of rs181206 and the surrounding locus with expression of multiple genes; several were differentially expressed in COPD lung tissue, including TUFM. Conclusions: In an exome array analysis of COPD, we identified nonsynonymous variants at previously described loci and a novel exome-wide significant variant in IL27. This variant is at a locus previously described in genome-wide associations with diabetes, inflammatory bowel disease, and obesity and appears to affect genes potentially related to COPD pathogenesis. PMID:26771213
Polygenic determinants in extremes of high-density lipoprotein cholesterol[S
Dron, Jacqueline S.; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A.; Robinson, John F.; McIntyre, Adam D.; Ban, Matthew R.; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J.; Lettre, Guillaume; Tardif, Jean-Claude
2017-01-01
HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. PMID:28870971
Polygenic determinants in extremes of high-density lipoprotein cholesterol.
Dron, Jacqueline S; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A; Robinson, John F; McIntyre, Adam D; Ban, Matthew R; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J; Lettre, Guillaume; Tardif, Jean-Claude; Hegele, Robert A
2017-11-01
HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.
Al Eissa, Mariam M.; Fiorentino, Alessia; Sharp, Sally I.; O'Brien, Niamh L.; Wolfe, Kate; Giaroli, Giovanni; Curtis, David; Bass, Nicholas J.
2017-01-01
Summary Schizophrenia (SCZ) is a severe, highly heritable psychiatric disorder. Elucidation of the genetic architecture of the disorder will facilitate greater understanding of the altered underlying neurobiological mechanisms. The aim of this study was to identify likely aetiological variants in subjects affected with SCZ. Exome sequence data from a SCZ cas–control sample from Sweden was analysed for likely aetiological variants using a weighted burden test. Suggestive evidence implicated the UNC‐51‐like kinase (ULK1) gene, and it was observed that four rare variants that were more common in the Swedish SCZ cases were also more common in UK10K SCZ cases, as compared to obesity cases. These three missense variants and one intronic variant were genotyped in the University College London cohort of 1304 SCZ cases and 1348 ethnically matched controls. All four variants were more common in the SCZ cases than controls and combining them produced a result significant at P = 0.02. The results presented here demonstrate the importance of following up exome sequencing studies using additional datasets. The roles of ULK1 in autophagy and mTOR signalling strengthen the case that these pathways may be important in the pathophysiology of SCZ. The findings reported here await independent replication. PMID:29148569
Cappola, Thomas P; Matkovich, Scot J; Wang, Wei; van Booven, Derek; Li, Mingyao; Wang, Xuexia; Qu, Liming; Sweitzer, Nancy K; Fang, James C; Reilly, Muredach P; Hakonarson, Hakon; Nerbonne, Jeanne M; Dorn, Gerald W
2011-02-08
Common heart failure has a strong undefined heritable component. Two recent independent cardiovascular SNP array studies identified a common SNP at 1p36 in intron 2 of the HSPB7 gene as being associated with heart failure. HSPB7 resequencing identified other risk alleles but no functional gene variants. Here, we further show no effect of the HSPB7 SNP on cardiac HSPB7 mRNA levels or splicing, suggesting that the SNP marks the position of a functional variant in another gene. Accordingly, we used massively parallel platforms to resequence all coding exons of the adjacent CLCNKA gene, which encodes the K(a) renal chloride channel (ClC-K(a)). Of 51 exonic CLCNKA variants identified, one SNP (rs10927887, encoding Arg83Gly) was common, in linkage disequilibrium with the heart failure risk SNP in HSPB7, and associated with heart failure in two independent Caucasian referral populations (n = 2,606 and 1,168; combined P = 2.25 × 10(-6)). Individual genotyping of rs10927887 in the two study populations and a third independent heart failure cohort (combined n = 5,489) revealed an additive allele effect on heart failure risk that is independent of age, sex, and prior hypertension (odds ratio = 1.27 per allele copy; P = 8.3 × 10(-7)). Functional characterization of recombinant wild-type Arg83 and variant Gly83 ClC-K(a) chloride channel currents revealed ≈ 50% loss-of-function of the variant channel. These findings identify a common, functionally significant genetic risk factor for Caucasian heart failure. The variant CLCNKA risk allele, telegraphed by linked variants in the adjacent HSPB7 gene, uncovers a previously overlooked genetic mechanism affecting the cardio-renal axis.
Luo, Li; Zhu, Yun
2012-01-01
Abstract The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T2, collapsing method, multivariate and collapsing (CMC) method, individual χ2 test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets. PMID:22651812
Luo, Li; Zhu, Yun; Xiong, Momiao
2012-06-01
The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.
Correlation between portal vein anatomy and bile duct variation in 407 living liver donors.
Takeishi, K; Shirabe, K; Yoshida, Y; Tsutsui, Y; Kurihara, T; Kimura, K; Itoh, S; Harimoto, N; Yamashita, Y-I; Ikegami, T; Yoshizumi, T; Nishie, A; Maehara, Y
2015-01-01
Our aim was to determine whether variant bile duct (BD) anatomy is associated with portal vein (PV) and/or hepatic artery (HA) anatomy. We examined the associations between BD anatomy and PV and/or HA anatomy in 407 living donor transplantation donors. We also examined whether the right posterior BD (RPBD) course was associated with the PV and/or HA anatomy. Variant PV, HA and BD anatomies were found in 11%, 25% and 25%, respectively, of 407 donors enrolled in this study. The presence of a variant BD was more frequently associated with a variant PV than with a normal PV (61% vs. 20%, p < 0.0001). By contrast, the presence of a variant HA was not associated with a variant BD. A supraportal RPBD was found in 357 donors (88%) and an infraportal RPBD was found in 50 donors (12%). An infraportal RPBD was significantly more common in donors with a variant PV than in donors with a normal PV (30% vs. 10%, p = 0.0004). Variant PV, but not variant HA, anatomies were frequently associated with variant BD anatomy. Additionally, an infraportal RPBD was more common in donors with a variant PV than in donors with a normal PV. © Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.
Functional non-synonymous variants of ABCG2 and gout risk.
Stiburkova, Blanka; Pavelcova, Katerina; Zavada, Jakub; Petru, Lenka; Simek, Pavel; Cepek, Pavel; Pavlikova, Marketa; Matsuo, Hirotaka; Merriman, Tony R; Pavelka, Karel
2017-11-01
Common dysfunctional variants of ATP binding cassette subfamily G member 2 (Junior blood group) (ABCG2), a high-capacity urate transporter gene, that result in decreased urate excretion are major causes of hyperuricemia and gout. In the present study, our objective was to determine the frequency and effect on gout of common and rare non-synonymous and other functional allelic variants in the ABCG2 gene. The main cohort recruited from the Czech Republic consisted of 145 gout patients; 115 normouricaemic controls were used for comparison. We amplified, directly sequenced and analysed 15 ABCG2 exons. The associations between genetic variants and clinical phenotype were analysed using the t-test, Fisher's exact test and a logistic and linear regression approach. Data from a New Zealand Polynesian sample set and the UK Biobank were included for the p.V12M analysis. In the ABCG2 gene, 18 intronic (one dysfunctional splicing) and 11 exonic variants were detected: 9 were non-synonymous (2 common, 7 rare including 1 novel), namely p.V12M, p.Q141K, p.R147W, p.T153M, p.F373C, p.T434M, p.S476P, p.D620N and p.K360del. The p.Q141K (rs2231142) variant had a significantly higher minor allele frequency (0.23) in the gout patients compared with the European-origin population (0.09) and was significantly more common among gout patients than among normouricaemic controls (odds ratio = 3.26, P < 0.0001). Patients with non-synonymous allelic variants had an earlier onset of gout (42 vs 48 years, P = 0.0143) and a greater likelihood of a familial history of gout (41% vs 27%, odds ratio = 1.96, P = 0.053). In a meta-analysis p.V12M exerted a protective effect from gout (P < 0.0001). Genetic variants of ABCG2, common and rare, increased the risk of gout. Non-synonymous allelic variants of ABCG2 had a significant effect on earlier onset of gout and the presence of a familial gout history. ABCG2 should thus be considered a common and significant risk factor for gout. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Rao, Shitao; Leung, Cherry She Ting; Lam, Macro Hb; Wing, Yun Kwok; Waye, Mary Miu Yee; Tsui, Stephen Kwok Wing
2017-03-01
To date almost 200 genes were found to be associated with major depressive disorder (MDD) or suicide attempts (SA), but very few genes were reported for their molecular mechanisms. This study aimed to find out whether there were common or rare variants in three candidate genes altering the risk for MDD and SA in Chinese. Three candidate genes (HOMER1, SLC6A4 and TEF) were chosen for resequencing analysis and association studies as they were reported to be involved in the etiology of MDD and SA. Following that, bioinformatics analyses were applied on those variants of interest. After resequencing analysis and alignment for the amplicons, a total of 34 common or rare variants were found in the randomly selected 36 Hong Kong Chinese patients with both MDD and SA. Among those, seven variants show potentially deleterious features. Rs60029191 and a rare variant located in regulatory region of the HOMER1 gene may affect the promoter activities through interacting with predicted transcription factors. Two missense mutations existed in the SLC6A4 coding regions were firstly reported in Hong Kong Chinese MDD and SA patients, and both of them could affect the transport efficiency of SLC6A4 to serotonin. Moreover, a common variant rs6354 located in the untranslated region of this gene may affect the expression level or exonic splicing of serotonin transporter. In addition, both of a most studied polymorphism rs738499 and a low-frequency variant in the promoter region of the TEF gene were found to be located in potential transcription factor binding sites, which may let the two variants be able to influence the promoter activities of the gene. This study elucidated the potentially molecular mechanisms of the three candidate genes altering the risk for MDD and SA. These findings implied that not only common variants but rare variants could make contributions to the genetic susceptibility to MDD and SA in Chinese. Copyright © 2016 Elsevier B.V. All rights reserved.
Novotny, Dalibor; Vaverkova, Helena; Karasek, David; Malina, Pavel
2014-08-01
The aim was to evaluate the relationships of the T-1131C (rs662799) polymorphism variants of apolipoprotein A5 (Apo A5) gene and variants of apolipoprotein E (Apo E) gene common polymorphism (rs429358, rs7412) to signs of metabolic syndrome (MetS). We examined 590 asymptomatic dyslipidemic patients divided into MetS+ (n=146) and MetS- (n=444) groups according to criteria of NCEP ATPIII Panel. We evaluated genotype frequencies and differences in MetS features between individual groups. Logistic regression analysis was used for the evaluation of Apo A5/Apo E variants as possible risk factors for MetS. We found no statistical differences between genotype and allele frequencies for both Apo A5 and Apo E polymorphisms between MetS+ and MetS- groups. In all subjects and MetS- group, we confirmed well-known association of the -1131C Apo A5 minor allele with elevated triglycerides (TG, p<0.001). The Apo E gene E2 and E4 variants were associated with higher levels of TG (p<0.01) in comparison to E33 common variant. However, no statistical differences were observed in MetS+ subjects, regardless of significantly higher TG levels in this group. Apo A5/Apo E variant analysis in all dyslipidemic patients revealed significant increase of TG levels in all subgroups in comparison to common -1131T/E3 variant carriers, the most in -1131C/E4 variant subgroup. Logistic regression analysis models showed no association of Apo A5, Apo E and all Apo A5/Apo E variants with metabolic syndrome, even after adjustment for age and sex. Our study refined the role of Apo A5 and Apo E genetic variants in the group of adult dyslipidemic patients. We demonstrate that except of TG, Apo A5 T-1131C (rs662799) and Apo E (rs429358, rs7412) polymorphisms have no remarkable effect on MetS characteristics. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Instrumental Variable Analysis with a Nonlinear Exposure–Outcome Relationship
Davies, Neil M.; Thompson, Simon G.
2014-01-01
Background: Instrumental variable methods can estimate the causal effect of an exposure on an outcome using observational data. Many instrumental variable methods assume that the exposure–outcome relation is linear, but in practice this assumption is often in doubt, or perhaps the shape of the relation is a target for investigation. We investigate this issue in the context of Mendelian randomization, the use of genetic variants as instrumental variables. Methods: Using simulations, we demonstrate the performance of a simple linear instrumental variable method when the true shape of the exposure–outcome relation is not linear. We also present a novel method for estimating the effect of the exposure on the outcome within strata of the exposure distribution. This enables the estimation of localized average causal effects within quantile groups of the exposure or as a continuous function of the exposure using a sliding window approach. Results: Our simulations suggest that linear instrumental variable estimates approximate a population-averaged causal effect. This is the average difference in the outcome if the exposure for every individual in the population is increased by a fixed amount. Estimates of localized average causal effects reveal the shape of the exposure–outcome relation for a variety of models. These methods are used to investigate the relations between body mass index and a range of cardiovascular risk factors. Conclusions: Nonlinear exposure–outcome relations should not be a barrier to instrumental variable analyses. When the exposure–outcome relation is not linear, either a population-averaged causal effect or the shape of the exposure–outcome relation can be estimated. PMID:25166881
Recent Mitochondrial DNA Mutations Increase the Risk of Developing Common Late-Onset Human Diseases
Hudson, Gavin; Gomez-Duran, Aurora; Wilson, Ian J.; Chinnery, Patrick F.
2014-01-01
Mitochondrial DNA (mtDNA) is highly polymorphic at the population level, and specific mtDNA variants affect mitochondrial function. With emerging evidence that mitochondrial mechanisms are central to common human diseases, it is plausible that mtDNA variants contribute to the “missing heritability” of several complex traits. Given the central role of mtDNA genes in oxidative phosphorylation, the same genetic variants would be expected to alter the risk of developing several different disorders, but this has not been shown to date. Here we studied 38,638 individuals with 11 major diseases, and 17,483 healthy controls. Imputing missing variants from 7,729 complete mitochondrial genomes, we captured 40.41% of European mtDNA variation. We show that mtDNA variants modifying the risk of developing one disease also modify the risk of developing other diseases, thus providing independent replication of a disease association in different case and control cohorts. High-risk alleles were more common than protective alleles, indicating that mtDNA is not at equilibrium in the human population, and that recent mutations interact with nuclear loci to modify the risk of developing multiple common diseases. PMID:24852434
Causal criteria and counterfactuals; nothing more (or less) than scientific common sense.
Phillips, Carl V; Goodman, Karen J
2006-05-26
Two persistent myths in epidemiology are that we can use a list of "causal criteria" to provide an algorithmic approach to inferring causation and that a modern "counterfactual model" can assist in the same endeavor. We argue that these are neither criteria nor a model, but that lists of causal considerations and formalizations of the counterfactual definition of causation are nevertheless useful tools for promoting scientific thinking. They set us on the path to the common sense of scientific inquiry, including testing hypotheses (really putting them to a test, not just calculating simplistic statistics), responding to the Duhem-Quine problem, and avoiding many common errors. Austin Bradford Hill's famous considerations are thus both over-interpreted by those who would use them as criteria and under-appreciated by those who dismiss them as flawed. Similarly, formalizations of counterfactuals are under-appreciated as lessons in basic scientific thinking. The need for lessons in scientific common sense is great in epidemiology, which is taught largely as an engineering discipline and practiced largely as technical tasks, making attention to core principles of scientific inquiry woefully rare.
Radwan, Zaheda H.; Wang, Xingbin; Waqar, Fahad; Pirim, Dilek; Niemsiri, Vipavee; Hokanson, John E.; Hamman, Richard F.; Bunker, Clareann H.; Barmada, M. Michael; Demirci, F. Yesim; Kamboh, M. Ilyas
2014-01-01
Although common APOE genetic variation has a major influence on plasma LDL-cholesterol, its role in affecting HDL-cholesterol and triglycerides is not well established. Recent genome-wide association studies suggest that APOE also affects plasma variation in HDL-cholesterol and triglycerides. It is thus important to resequence the APOE gene to identify both common and uncommon variants that affect plasma lipid profile. Here, we have sequenced the APOE gene in 190 subjects with extreme HDL-cholesterol levels selected from two well-defined epidemiological samples of U.S. non-Hispanic Whites (NHWs) and African Blacks followed by genotyping of identified variants in the entire datasets (623 NHWs, 788 African Blacks) and association analyses with major lipid traits. We identified a total of 40 sequence variants, of which 10 are novel. A total of 32 variants, including common tagSNPs (≥5% frequency) and all uncommon variants (<5% frequency) were successfully genotyped and considered for genotype-phenotype associations. Other than the established associations of APOE*2 and APOE*4 with LDL-cholesterol, we have identified additional independent associations with LDL-cholesterol. We have also identified multiple associations of uncommon and common APOE variants with HDL-cholesterol and triglycerides. Our comprehensive sequencing and genotype-phenotype analyses indicate that APOE genetic variation impacts HDL-cholesterol and triglycerides in addition to affecting LDL-cholesterol. PMID:25502880
Algorithms for Discovery of Multiple Markov Boundaries
Statnikov, Alexander; Lytkin, Nikita I.; Lemeire, Jan; Aliferis, Constantin F.
2013-01-01
Algorithms for Markov boundary discovery from data constitute an important recent development in machine learning, primarily because they offer a principled solution to the variable/feature selection problem and give insight on local causal structure. Over the last decade many sound algorithms have been proposed to identify a single Markov boundary of the response variable. Even though faithful distributions and, more broadly, distributions that satisfy the intersection property always have a single Markov boundary, other distributions/data sets may have multiple Markov boundaries of the response variable. The latter distributions/data sets are common in practical data-analytic applications, and there are several reasons why it is important to induce multiple Markov boundaries from such data. However, there are currently no sound and efficient algorithms that can accomplish this task. This paper describes a family of algorithms TIE* that can discover all Markov boundaries in a distribution. The broad applicability as well as efficiency of the new algorithmic family is demonstrated in an extensive benchmarking study that involved comparison with 26 state-of-the-art algorithms/variants in 15 data sets from a diversity of application domains. PMID:25285052
Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm.
Bourcier, Romain; Le Scouarnec, Solena; Bonnaud, Stéphanie; Karakachoff, Matilde; Bourcereau, Emmanuelle; Heurtebise-Chrétien, Sandrine; Menguy, Céline; Dina, Christian; Simonet, Floriane; Moles, Alexis; Lenoble, Cédric; Lindenbaum, Pierre; Chatel, Stéphanie; Isidor, Bertrand; Génin, Emmanuelle; Deleuze, Jean-François; Schott, Jean-Jacques; Le Marec, Hervé; Loirand, Gervaise; Desal, Hubert; Redon, Richard
2018-01-04
Intracranial aneurysms (IAs) are acquired cerebrovascular abnormalities characterized by localized dilation and wall thinning in intracranial arteries, possibly leading to subarachnoid hemorrhage and severe outcome in case of rupture. Here, we identified one rare nonsense variant (c.1378A>T) in the last exon of ANGPTL6 (Angiopoietin-Like 6)-which encodes a circulating pro-angiogenic factor mainly secreted from the liver-shared by the four tested affected members of a large pedigree with multiple IA-affected case subjects. We showed a 50% reduction of ANGPTL6 serum concentration in individuals heterozygous for the c.1378A>T allele (p.Lys460Ter) compared to relatives homozygous for the normal allele, probably due to the non-secretion of the truncated protein produced by the c.1378A>T transcripts. Sequencing ANGPTL6 in a series of 94 additional index case subjects with familial IA identified three other rare coding variants in five case subjects. Overall, we detected a significant enrichment (p = 0.023) in rare coding variants within this gene among the 95 index case subjects with familial IA, compared to a reference population of 404 individuals with French ancestry. Among the 6 recruited families, 12 out of 13 (92%) individuals carrying IA also carry such variants in ANGPTL6, versus 15 out of 41 (37%) unaffected ones. We observed a higher rate of individuals with a history of high blood pressure among affected versus healthy individuals carrying ANGPTL6 variants, suggesting that ANGPTL6 could trigger cerebrovascular lesions when combined with other risk factors such as hypertension. Altogether, our results indicate that rare coding variants in ANGPTL6 are causally related to familial forms of IA. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Dissociation between APOC3 variants, hepatic triglyceride content and insulin resistance.
Kozlitina, Julia; Boerwinkle, Eric; Cohen, Jonathan C; Hobbs, Helen H
2011-02-01
Nonalcoholic fatty liver disease (NAFLD) is an escalating health problem that is frequently associated with obesity and insulin resistance. The mechanistic relationship between NAFLD, obesity, and insulin resistance is not well understood. A nonsynonymous variant in patatin-like phospholipase domain containing 3 (rs738409, I148M) has been reproducibly associated with increased hepatic triglyceride content (HTGC) but has not been associated with either the body mass index (BMI) or indices of insulin resistance. Conversely, two sequence variants in apolipoprotein C3 (APOC3) that have been linked to hypertriglyceridemia (rs2854117 C > T and rs2854116 T > C) have recently been reported to be associated with both hepatic fat content and insulin resistance. Here we genotyped two APOC3 variants in 1228 African Americans, 843 European Americans and 426 Hispanics from a multiethnic population based study, the Dallas Heart Study and test for association with HTGC and homeostatic model of insulin resistance (HOMA-IR). We also examined the relationship between these two variants and HOMA-IR in the Atherosclerosis Risk in Communities (ARIC) study. No significant difference in hepatic fat content was found between carriers and noncarriers in the Dallas Heart Study. Neither APOC3 variant was associated with HOMA-IR in the Dallas Heart Study; this lack of association was confirmed in the ARIC study, even after the analysis was restricted to lean (BMI < 25 kg/m(2) ) individuals (n = 4399). Our data do not support a causal relationship between these two variants in APOC3 and either HTGC or insulin resistance in middle-aged men and women. Copyright © 2010 American Association for the Study of Liver Diseases.
Painter, Jodie N; O'Mara, Tracy A; Batra, Jyotsna; Cheng, Timothy; Lose, Felicity A; Dennis, Joe; Michailidou, Kyriaki; Tyrer, Jonathan P; Ahmed, Shahana; Ferguson, Kaltin; Healey, Catherine S; Kaufmann, Susanne; Hillman, Kristine M; Walpole, Carina; Moya, Leire; Pollock, Pamela; Jones, Angela; Howarth, Kimberley; Martin, Lynn; Gorman, Maggie; Hodgson, Shirley; De Polanco, Ma Magdalena Echeverry; Sans, Monica; Carracedo, Angel; Castellvi-Bel, Sergi; Rojas-Martinez, Augusto; Santos, Erika; Teixeira, Manuel R; Carvajal-Carmona, Luis; Shu, Xiao-Ou; Long, Jirong; Zheng, Wei; Xiang, Yong-Bing; Montgomery, Grant W; Webb, Penelope M; Scott, Rodney J; McEvoy, Mark; Attia, John; Holliday, Elizabeth; Martin, Nicholas G; Nyholt, Dale R; Henders, Anjali K; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Renner, Stefan P; Dörk, Thilo; Hillemanns, Peter; Dürst, Matthias; Runnebaum, Ingo; Lambrechts, Diether; Coenegrachts, Lieve; Schrauwen, Stefanie; Amant, Frederic; Winterhoff, Boris; Dowdy, Sean C; Goode, Ellen L; Teoman, Attila; Salvesen, Helga B; Trovik, Jone; Njolstad, Tormund S; Werner, Henrica M J; Ashton, Katie; Proietto, Tony; Otton, Geoffrey; Tzortzatos, Gerasimos; Mints, Miriam; Tham, Emma; Hall, Per; Czene, Kamila; Liu, Jianjun; Li, Jingmei; Hopper, John L; Southey, Melissa C; Ekici, Arif B; Ruebner, Matthias; Johnson, Nicola; Peto, Julian; Burwinkel, Barbara; Marme, Frederik; Brenner, Hermann; Dieffenbach, Aida K; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Depreeuw, Jeroen; Moisse, Matthieu; Chang-Claude, Jenny; Rudolph, Anja; Couch, Fergus J; Olson, Janet E; Giles, Graham G; Bruinsma, Fiona; Cunningham, Julie M; Fridley, Brooke L; Børresen-Dale, Anne-Lise; Kristensen, Vessela N; Cox, Angela; Swerdlow, Anthony J; Orr, Nicholas; Bolla, Manjeet K; Wang, Qin; Weber, Rachel Palmieri; Chen, Zhihua; Shah, Mitul; French, Juliet D; Pharoah, Paul D P; Dunning, Alison M; Tomlinson, Ian; Easton, Douglas F; Edwards, Stacey L; Thompson, Deborah J; Spurdle, Amanda B
2015-03-01
Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Painter, Jodie N.; O'Mara, Tracy A.; Batra, Jyotsna; Cheng, Timothy; Lose, Felicity A.; Dennis, Joe; Michailidou, Kyriaki; Tyrer, Jonathan P.; Ahmed, Shahana; Ferguson, Kaltin; Healey, Catherine S.; Kaufmann, Susanne; Hillman, Kristine M.; Walpole, Carina; Moya, Leire; Pollock, Pamela; Jones, Angela; Howarth, Kimberley; Martin, Lynn; Gorman, Maggie; Hodgson, Shirley; De Polanco, Ma. Magdalena Echeverry; Sans, Monica; Carracedo, Angel; Castellvi-Bel, Sergi; Rojas-Martinez, Augusto; Santos, Erika; Teixeira, Manuel R.; Carvajal-Carmona, Luis; Shu, Xiao-Ou; Long, Jirong; Zheng, Wei; Xiang, Yong-Bing; Montgomery, Grant W.; Webb, Penelope M.; Scott, Rodney J.; McEvoy, Mark; Attia, John; Holliday, Elizabeth; Martin, Nicholas G.; Nyholt, Dale R.; Henders, Anjali K.; Fasching, Peter A.; Hein, Alexander; Beckmann, Matthias W.; Renner, Stefan P.; Dörk, Thilo; Hillemanns, Peter; Dürst, Matthias; Runnebaum, Ingo; Lambrechts, Diether; Coenegrachts, Lieve; Schrauwen, Stefanie; Amant, Frederic; Winterhoff, Boris; Dowdy, Sean C.; Goode, Ellen L.; Teoman, Attila; Salvesen, Helga B.; Trovik, Jone; Njolstad, Tormund S.; Werner, Henrica M.J.; Ashton, Katie; Proietto, Tony; Otton, Geoffrey; Tzortzatos, Gerasimos; Mints, Miriam; Tham, Emma; Hall, Per; Czene, Kamila; Liu, Jianjun; Li, Jingmei; Hopper, John L.; Southey, Melissa C.; Ekici, Arif B.; Ruebner, Matthias; Johnson, Nicola; Peto, Julian; Burwinkel, Barbara; Marme, Frederik; Brenner, Hermann; Dieffenbach, Aida K.; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Depreeuw, Jeroen; Moisse, Matthieu; Chang-Claude, Jenny; Rudolph, Anja; Couch, Fergus J.; Olson, Janet E.; Giles, Graham G.; Bruinsma, Fiona; Cunningham, Julie M.; Fridley, Brooke L.; Børresen-Dale, Anne-Lise; Kristensen, Vessela N.; Cox, Angela; Swerdlow, Anthony J.; Orr, Nicholas; Bolla, Manjeet K.; Wang, Qin; Weber, Rachel Palmieri; Chen, Zhihua; Shah, Mitul; French, Juliet D.; Pharoah, Paul D.P.; Dunning, Alison M.; Tomlinson, Ian; Easton, Douglas F.; Edwards, Stacey L.; Thompson, Deborah J.; Spurdle, Amanda B.
2015-01-01
Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10−14, odds ratio = 0.86, 95% confidence interval = 0.82–0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression. PMID:25378557
Safra, Noa; Hayward, Louisa J; Aguilar, Miriam; Sacks, Benjamin N; Westropp, Jodi L; Mohr, F Charles; Mellersh, Cathryn S; Bannasch, Danika L
2015-01-01
The aim of this study was to investigate the frequency of regional DNA variants upstream to the translation initiation site of the canine Cyclooxygenase-2 (Cox-2) gene in healthy dogs. Cox-2 plays a role in various disease conditions such as acute and chronic inflammation, osteoarthritis and malignancy. A role for Cox-2 DNA variants in genetic predisposition to canine renal dysplasia has been proposed and dog breeders have been encouraged to select against these DNA variants. We sequenced 272-422 bases in 152 dogs unaffected by renal dysplasia and found 19 different haplotypes including 11 genetic variants which had not been described previously. We genotyped 7 gray wolves to ascertain the wildtype variant and found that the wolves we analyzed had predominantly the second most common DNA variant found in dogs. Our results demonstrate an elevated level of regional polymorphism that appears to be a feature of healthy domesticated dogs.
Chapple, Iain L C; Bouchard, Philippe; Cagetti, Maria Grazia; Campus, Guglielmo; Carra, Maria-Clotilde; Cocco, Fabio; Nibali, Luigi; Hujoel, Philippe; Laine, Marja L; Lingstrom, Peter; Manton, David J; Montero, Eduardo; Pitts, Nigel; Rangé, Hélène; Schlueter, Nadine; Teughels, Wim; Twetman, Svante; Van Loveren, Cor; Van der Weijden, Fridus; Vieira, Alexandre R; Schulte, Andreas G
2017-03-01
Periodontal diseases and dental caries are the most common diseases of humans and the main cause of tooth loss. Both diseases can lead to nutritional compromise and negative impacts upon self-esteem and quality of life. As complex chronic diseases, they share common risk factors, such as a requirement for a pathogenic plaque biofilm, yet they exhibit distinct pathophysiologies. Multiple exposures contribute to their causal pathways, and susceptibility involves risk factors that are inherited (e.g. genetic variants), and those that are acquired (e.g. socio-economic factors, biofilm load or composition, smoking, carbohydrate intake). Identification of these factors is crucial in the prevention of both diseases as well as in their management. To systematically appraise the scientific literature to identify potential risk factors for caries and periodontal diseases. One systematic review (genetic risk factors), one narrative review (role of diet and nutrition) and reference documentation for modifiable acquired risk factors common to both disease groups, formed the basis of the report. There is moderately strong evidence for a genetic contribution to periodontal diseases and caries susceptibility, with an attributable risk estimated to be up to 50%. The genetics literature for periodontal disease is more substantial than for caries and genes associated with chronic periodontitis are the vitamin D receptor (VDR), Fc gamma receptor IIA (Fc-γRIIA) and Interleukin 10 (IL10) genes. For caries, genes involved in enamel formation (AMELX, AMBN, ENAM, TUFT, MMP20, and KLK4), salivary characteristics (AQP5), immune regulation and dietary preferences had the largest impact. No common genetic variants were found. Fermentable carbohydrates (sugars and starches) were the most relevant common dietary risk factor for both diseases, but associated mechanisms differed. In caries, the fermentation process leads to acid production and the generation of biofilm components such as Glucans. In periodontitis, glycaemia drives oxidative stress and advanced glycation end-products may also trigger a hyper inflammatory state. Micronutrient deficiencies, such as for vitamin C, vitamin D or vitamin B12, may be related to the onset and progression of both diseases. Functional foods or probiotics could be helpful in caries prevention and periodontal disease management, although evidence is limited and biological mechanisms not fully elucidated. Hyposalivation, rheumatoid arthritis, smoking/tobacco use, undiagnosed or sub-optimally controlled diabetes and obesity are common acquired risk factors for both caries and periodontal diseases. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Common variants in Mendelian kidney disease genes and their association with renal function.
Parsa, Afshin; Fuchsberger, Christian; Köttgen, Anna; O'Seaghdha, Conall M; Pattaro, Cristian; de Andrade, Mariza; Chasman, Daniel I; Teumer, Alexander; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Kim, Young J; Taliun, Daniel; Li, Man; Feitosa, Mary; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C; Glazer, Nicole; Isaacs, Aaron; Rao, Madhumathi; Smith, Albert V; O'Connell, Jeffrey R; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Hwang, Shih-Jen; Atkinson, Elizabeth J; Lohman, Kurt; Cornelis, Marilyn C; Johansson, Asa; Tönjes, Anke; Dehghan, Abbas; Couraki, Vincent; Holliday, Elizabeth G; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Harris, Tamara B; Launer, Lenore J; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D; Boerwinkle, Eric; Schmidt, Helena; Hofer, Edith; Hu, Frank; Demirkan, Ayse; Oostra, Ben A; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S; Freedman, Barry I; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Döring, Angela; Wichmann, H-Erich; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H; Wright, Alan F; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G; Rivadeneira, Fernando; Aulchenko, Yurii S; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K; Portas, Laura; Ford, Ian; Buckley, Brendan M; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J Wouter; Probst-Hensch, Nicole M; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; van Duijn, Cornelia M; Borecki, Ingrid; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C; Rudan, Igor; Gyllensten, Ulf; Wilson, James F; Franke, Andre; Pramstaller, Peter P; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Bochud, Murielle; Heid, Iris M; Siscovick, David S; Fox, Caroline S; Kao, W Linda; Böger, Carsten A
2013-12-01
Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.
Rare variants and cardiovascular disease.
Wain, Louise V
2014-09-01
Cardiovascular disease (CVD) is a leading cause of mortality and morbidity in the Western world. Large genome-wide association studies (GWASs) of coronary artery disease, myocardial infarction, stroke and dilated cardiomyopathy have identified a number of common genetic variants with modest effects on disease risk. Similarly, studies of important modifiable risk factors of CVD have identified a large number of predominantly common variant associations, for example, with blood pressure and blood lipid levels. In each case, despite the often large numbers of loci identified, only a small proportion of the phenotypic variance is explained. It has been hypothesised that rare variants with large effects may account for some of the missing variance but large-scale studies of rare variation are in their infancy for cardiovascular traits and have yet to produce fruitful results. Studies of monogenic CVDs, inherited disorders believed to be entirely driven by individual rare mutations, have highlighted genes that play a key role in disease aetiology. In this review, we discuss how findings from studies of rare variants in monogenic disease and GWAS of predominantly common variants are converging to provide further insight into biological disease mechanisms. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Genetics of nonsyndromic obesity.
Lee, Yung Seng
2013-12-01
Common obesity is widely regarded as a complex, multifactorial trait influenced by the 'obesogenic' environment, sedentary behavior, and genetic susceptibility contributed by common and rare genetic variants. This review describes the recent advances in understanding the role of genetics in obesity. New susceptibility loci and genetic variants are being uncovered, but the collective effect is relatively small and could not explain most of the BMI heritability. Yet-to-be identified common and rare variants, epistasis, and heritable epigenetic changes may account for part of the 'missing heritability'. Evidence is emerging about the role of epigenetics in determining obesity susceptibility, mediating developmental plasticity, which confers obesity risk from early life experiences. Genetic prediction scores derived from selected genetic variants, and also differential DNA methylation levels and methylation scores, have been shown to correlate with measures of obesity and response to weight loss intervention. Genetic variants, which confer susceptibility to obesity-related morbidities like nonalcoholic fatty liver disease, were also discovered recently. We can expect discovery of more rare genetic variants with the advent of whole exome and genome sequencing, and also greater understanding of epigenetic mechanisms by which environment influences genetic expression and which mediate the gene-environment interaction.
A systematic review and meta-analysis of variations in branching patterns of the adult aortic arch.
Popieluszko, Patrick; Henry, Brandon Michael; Sanna, Beatrice; Hsieh, Wan Chin; Saganiak, Karolina; Pękala, Przemysław A; Walocha, Jerzy A; Tomaszewski, Krzysztof A
2018-07-01
The aortic arch (AA) is the main conduit of the left side of the heart, providing a blood supply to the head, neck, and upper limbs. As it travels through the thorax, the pattern in which it gives off the branches to supply these structures can vary. Variations of these branching patterns have been studied; however, a study providing a comprehensive incidence of these variations has not yet been conducted. The objective of this study was to perform a meta-analysis of all the studies that report prevalence data on AA variants and to provide incidence data on the most common variants. A systematic search of online databases including PubMed, Embase, Scopus, ScienceDirect, Web of Science, SciELO, BIOSIS, and CNKI was performed for literature describing incidence of AA variations in adults. Studies including prevalence data on adult patients or cadavers were collected and their data analyzed. A total of 51 articles were included (N = 23,882 arches). Seven of the most common variants were analyzed. The most common variants found included the classic branching pattern, defined as a brachiocephalic trunk, a left common carotid, and a left subclavian artery (80.9%); the bovine arch variant (13.6%); and the left vertebral artery variant (2.8%). Compared by geographic data, bovine arch variants were noted to have a prevalence as high as 26.8% in African populations. Although patients who have an AA variant are often asymptomatic, they compose a significant portion of the population of patients and pose a greater risk of hemorrhage and ischemia during surgery in the thorax. Because of the possibility of encountering such variants, it is prudent for surgeons to consider potential variations in planning procedures, especially of an endovascular nature, in the thorax. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.
Mariman, Edwin C M; Bouwman, Freek G; Aller, Erik E J G; van Baak, Marleen A; Wang, Ping
2015-06-01
The hypothalamus is important for regulation of energy intake. Mutations in genes involved in the function of the hypothalamus can lead to early-onset severe obesity. To look further into this, we have followed a strategy that allowed us to identify rare and common gene variants as candidates for the background of extreme obesity from a relatively small cohort. For that we focused on subjects with a well-selected phenotype and on a defined gene set and used a rich source of genetic data with stringent cut-off values. A list of 166 genes functionally related to the hypothalamus was generated. In those genes complete exome sequence data from 30 extreme obese subjects (60 genomes) were screened for novel rare indel, nonsense, and missense variants with a predicted negative impact on protein function. In addition, (moderately) common variants in those genes were analyzed for allelic association using the general population as reference (false discovery rate<0.05). Six novel rare deleterious missense variants were found in the genes for BAIAP3, NBEA, PRRC2A, RYR1, SIM1, and TRH, and a novel indel variant in LEPR. Common variants in the six genes for MBOAT4, NPC1, NPW, NUCB2, PER1, and PRRC2A showed significant allelic association with extreme obesity. Our findings underscore the complexity of the genetic background of extreme obesity involving rare and common variants of genes from defined metabolic and physiologic processes, in particular regulation of the circadian rhythm of food intake and hypothalamic signaling. Copyright © 2015 the American Physiological Society.
Bhui, Kamaldeep; Bhugra, Dinesh; Goldberg, David
2002-01-01
The literature on the primary care assessment of mental distress among Indian subcontinent origin patients suggests frequent presentations to general practitioner, but rarely for recognisable psychiatric disorders. This study investigates whether cultural variations in patients' causal explanatory models account for cultural variations in the assessment of non-psychotic mental disorders in primary care. In a two-phase survey, 272 Punjabi and 269 English subjects were screened. The second phase was completed by 209 and 180 subjects, respectively. Causal explanatory models were elicited as explanations of two vignette scenarios. One of these emphasised a somatic presentation and the other anxiety symptoms. Psychiatric disorder was assessed by GPs on a Likert scale and by a psychiatrist on the Clinical Interview Schedule. Punjabis more commonly expressed medical/somatic and religious beliefs. General practitioners were more likely to assess any subject giving psychological explanations to vignette A and English subjects giving religious explanations to vignette B as having a significant psychiatric disorder. Where medical/somatic explanations of distress were most prevalent in response to the somatic vignette, psychological, religious and work explanations were less prevalent among Punjabis but not among English subjects. Causal explanations did not fully explain cultural differences in assessments. General practitioners' assessments and causal explanations are related and influenced by culture, but causal explanations do not fully explain cultural differences in assessments.
Hb variants in Korea: effect on HbA1c using five routine methods.
Yun, Yeo-Min; Ji, Misuk; Ko, Dae-Hyun; Chun, Sail; Kwon, Gye Cheol; Lee, Kyunghoon; Song, Sang Hoon; Seong, Moon Woo; Park, Sung Sup; Song, Junghan
2017-07-26
Quantification of glycated hemoglobin (HbA1c) is a challenge in patients with hemoglobin (Hb) variants. We evaluated the impact of various Hb variants on five routine HbA1c assays by comparing with the IFCC reference measurement procedure (RMP). Whole blood samples showing warning flags or no results on routine HPLC HbA1c assays were confirmed for Hb variants and were submitted to HbA1c quantification using Sebia Capillarys 2 Flex Piercing, Roche Tina-quant HbA1c Gen. 2, Bio-Rad Variant II Turbo 2.0, ADAMS HA-8180, Tosoh G8 standard mode, and IFCC RMP using LC-MS. Among 114 samples, the most common variants were Hb G-Coushatta (n=47), Queens (n=41), Ube-4 (n=11), Chad (n=4), Yamagata (n=4), G-His-Tsou (n=2), G-Taipei (n=1), Fort de France (n=1), Hoshida (n=1), and two novel variants (Hb α-globin, HBA 52 Gly>Cys and Hb β-globin, HBB 146 His>Asn). In terms of control samples, all the result of HbA1c were "acceptable", within the criteria of ±7% compared to IFCC RMP target values. However, percentage of "unacceptable" results of samples with Hb variants were 16% for Capillarys 2, 7% for Tina-quant, 51% for Variant II Turbo 2.0, 95% for G8 standard mode, and 89% for HA-8180. The Capillarys 2 and HA-8180 assay did not provide the results in 5 and 40 samples with Hb variants, respectively. HbA1c results from five routine assays in patients with relatively common Hb variants in Korea showed various degrees of bias compared to those of IFCC RMP. Therefore, laboratories should be aware of the limitation of their methods with respect to interference from Hb variants found commonly in their local population and suggest an alternative HbA1c quantification method.
Identifying Mendelian disease genes with the Variant Effect Scoring Tool
2013-01-01
Background Whole exome sequencing studies identify hundreds to thousands of rare protein coding variants of ambiguous significance for human health. Computational tools are needed to accelerate the identification of specific variants and genes that contribute to human disease. Results We have developed the Variant Effect Scoring Tool (VEST), a supervised machine learning-based classifier, to prioritize rare missense variants with likely involvement in human disease. The VEST classifier training set comprised ~ 45,000 disease mutations from the latest Human Gene Mutation Database release and another ~45,000 high frequency (allele frequency >1%) putatively neutral missense variants from the Exome Sequencing Project. VEST outperforms some of the most popular methods for prioritizing missense variants in carefully designed holdout benchmarking experiments (VEST ROC AUC = 0.91, PolyPhen2 ROC AUC = 0.86, SIFT4.0 ROC AUC = 0.84). VEST estimates variant score p-values against a null distribution of VEST scores for neutral variants not included in the VEST training set. These p-values can be aggregated at the gene level across multiple disease exomes to rank genes for probable disease involvement. We tested the ability of an aggregate VEST gene score to identify candidate Mendelian disease genes, based on whole-exome sequencing of a small number of disease cases. We used whole-exome data for two Mendelian disorders for which the causal gene is known. Considering only genes that contained variants in all cases, the VEST gene score ranked dihydroorotate dehydrogenase (DHODH) number 2 of 2253 genes in four cases of Miller syndrome, and myosin-3 (MYH3) number 2 of 2313 genes in three cases of Freeman Sheldon syndrome. Conclusions Our results demonstrate the potential power gain of aggregating bioinformatics variant scores into gene-level scores and the general utility of bioinformatics in assisting the search for disease genes in large-scale exome sequencing studies. VEST is available as a stand-alone software package at http://wiki.chasmsoftware.org and is hosted by the CRAVAT web server at http://www.cravat.us PMID:23819870
Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa; ...
2014-09-01
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A
2018-03-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.
Pierce, Brandon L; Ahsan, Habibul; Vanderweele, Tyler J
2011-06-01
Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.
Gray, Alan; Neyton, Lucile P. A.; Barrett, Jeffrey; Stahl, Eli A.; Tenesa, Albert; Andersson, Robin; Brown, J. Ben; Faulkner, Geoffrey J.; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Kawaji, Hideya; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A.; Hacohen, Nir; Freeman, Thomas C.; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Hume, David A.
2018-01-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn’s disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits. PMID:29494619
Identification of rare paired box 3 variant in strabismus by whole exome sequencing
Gong, Hui-Min; Wang, Jing; Xu, Jing; Zhou, Zhan-Yu; Li, Jing-Wen; Chen, Shu-Fang
2017-01-01
AIM To identify the potentially pathogenic gene variants that contributes to the etiology of strabismus. METHODS A Chinese pedigree with strabismus was collected and the exomes of two affected individuals were sequenced using the next-generation sequencing technology. The resulting variants from exome sequencing were filtered by subsequent bioinformatics methods and the candidate mutation was verified as heterozygous in the affected proposita and her mother by sanger sequencing. RESULTS Whole exome sequencing and filtering identified a nonsynonymous mutation c.434G-T transition in paired box 3 (PAX3) in the two affected individuals, which were predicted to be deleterious by more than 4 bioinformatics programs. This altered amino acid residue was located in the conserved PAX domain of PAX3. This gene encodes a member of the PAX family of transcription factors, which play critical roles during fetal development. Mutations in PAX3 were associated with Waardenburg syndrome with strabismus. CONCLUSION Our results report that the c.434G-T mutation (p.R145L) in PAX3 may contribute to strabismus, expanding our understanding of the causally relevant genes for this disorder. PMID:28861346
Zhuravlyova, L V; Shekhovtsova, Y O
2015-01-01
The purpose of the present study was to determine the causal factors of the progression of metabolic disorders in pancreatic tissue and their relationships in patients with assotiated clinical variants of chronic pancreatitis (CP) and type 2 diabetes mellitus (T2DM). The study involved of 76 patients with CP and T2DM. The causes of progression of metabolic disorders in the pancreas in patients with associated clinical variants of CP and T2DM has been analyzed. The most significant of them were insulin resistance and abdominal obesity, which promotes early formation of the metabolic syndrome and the activation of fibrogenesis and steatosis in the pancreas and is caused by dyslipidemia, impaired glucose metabolism and the development of systemic inflammation and imbalance of adipocytokines. The relationships between adipocytokines, body weight and individual components of the metabolic syndrome in patients with CP and T2DM suggests the involvement of these hormones of adipose tissue in the formation of the metabolic syndrome and its components.
Mahajan, Anubha; Locke, Adam; Rayner, N William; Robertson, Neil; Scott, Robert A; Prokopenko, Inga; Scott, Laura J; Green, Todd; Sparso, Thomas; Thuillier, Dorothee; Yengo, Loic; Grallert, Harald; Wahl, Simone; Frånberg, Mattias; Strawbridge, Rona J; Kestler, Hans; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Li, Man; Chen, Han; Fuchsberger, Christian; Kwan, Phoenix; Ma, Clement; Linderman, Michael; Lu, Yingchang; Thomsen, Soren K; Rundle, Jana K; Beer, Nicola L; van de Bunt, Martijn; Chalisey, Anil; Kang, Hyun Min; Voight, Benjamin F; Abecasis, Goncalo R; Almgren, Peter; Baldassarre, Damiano; Balkau, Beverley; Benediktsson, Rafn; Blüher, Matthias; Boeing, Heiner; Bonnycastle, Lori L; Borringer, Erwin P; Burtt, Noël P; Carey, Jason; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Doney, Alex SF; Dorkhan, Mozhgan; Edkins, Sarah; Eriksson, Johan G; Esko, Tonu; Eury, Elodie; Fadista, João; Flannick, Jason; Fontanillas, Pierre; Fox, Caroline; Franks, Paul W; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Gottesman, Omri; Grant, George B; Grarup, Niels; Groves, Christopher J; Hassinen, Maija; Have, Christian T; Herder, Christian; Holmen, Oddgeir L; Hreidarsson, Astradur B; Humphries, Steve E; Hunter, David J; Jackson, Anne U; Jonsson, Anna; Jørgensen, Marit E; Jørgensen, Torben; Kerrison, Nicola D; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Kovacs, Peter; Kraft, Peter; Kravic, Jasmina; Langford, Cordelia; Leander, Karin; Liang, Liming; Lichtner, Peter; Lindgren, Cecilia M; Lindholm, Eero; Linneberg, Allan; Liu, Ching-Ti; Lobbens, Stéphane; Luan, Jian’an; Lyssenko, Valeriya; Männistö, Satu; McLeod, Olga; Meyer, Julia; Mihailov, Evelin; Mirza, Ghazala; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Navarro, Carmen; Nöthen, Markus M; Oskolkov, Nikolay N; Owen, Katharine R; Palli, Domenico; Pechlivanis, Sonali; Perry, John RB; Platou, Carl GP; Roden, Michael; Ruderfer, Douglas; Rybin, Denis; van der Schouw, Yvonne T; Sennblad, Bengt; Sigurðsson, Gunnar; Stančáková, Alena; Steinbach, Gerald; Storm, Petter; Strauch, Konstantin; Stringham, Heather M; Sun, Qi; Thorand, Barbara; Tikkanen, Emmi; Tonjes, Anke; Trakalo, Joseph; Tremoli, Elena; Tuomi, Tiinamaija; Wennauer, Roman; Wood, Andrew R; Zeggini, Eleftheria; Dunham, Ian; Birney, Ewan; Pasquali, Lorenzo; Ferrer, Jorge; Loos, Ruth JF; Dupuis, Josée; Florez, Jose C; Boerwinkle, Eric; Pankow, James S; van Duijn, Cornelia; Sijbrands, Eric; Meigs, James B; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Lakka, Timo A; Rauramaa, Rainer; Stumvoll, Michael; Pedersen, Nancy L; Lind, Lars; Keinanen-Kiukaanniemi, Sirkka M; Korpi-Hyövälti, Eeva; Saaristo, Timo E; Saltevo, Juha; Kuusisto, Johanna; Laakso, Markku; Metspalu, Andres; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Ripatti, Samuli; Salomaa, Veikko; Ingelsson, Erik; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Koistinen, Heikki; Tuomilehto, Jaakko; Hveem, Kristian; Njølstad, Inger; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; de Faire, Ulf; Hamsten, Anders; Illig, Thomas; Peters, Annette; Cauchi, Stephane; Sladek, Rob; Froguel, Philippe; Hansen, Torben; Pedersen, Oluf; Morris, Andrew D; Palmer, Collin NA; Kathiresan, Sekar; Melander, Olle; Nilsson, Peter M; Groop, Leif C; Barroso, Inês; Langenberg, Claudia; Wareham, Nicholas J; O’Callaghan, Christopher A; Gloyn, Anna L; Altshuler, David; Boehnke, Michael; Teslovich, Tanya M; McCarthy, Mark I; Morris, Andrew P
2015-01-01
We performed fine-mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in/near KCNQ1. “Credible sets” of variants most likely to drive each distinct signal mapped predominantly to non-coding sequence, implying that T2D association is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine-mapping implicated rs10830963 as driving T2D association. We confirmed that this T2D-risk allele increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D-risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease. PMID:26551672
Identification of rare paired box 3 variant in strabismus by whole exome sequencing.
Gong, Hui-Min; Wang, Jing; Xu, Jing; Zhou, Zhan-Yu; Li, Jing-Wen; Chen, Shu-Fang
2017-01-01
To identify the potentially pathogenic gene variants that contributes to the etiology of strabismus. A Chinese pedigree with strabismus was collected and the exomes of two affected individuals were sequenced using the next-generation sequencing technology. The resulting variants from exome sequencing were filtered by subsequent bioinformatics methods and the candidate mutation was verified as heterozygous in the affected proposita and her mother by sanger sequencing. Whole exome sequencing and filtering identified a nonsynonymous mutation c.434G-T transition in paired box 3 (PAX3) in the two affected individuals, which were predicted to be deleterious by more than 4 bioinformatics programs. This altered amino acid residue was located in the conserved PAX domain of PAX3. This gene encodes a member of the PAX family of transcription factors, which play critical roles during fetal development. Mutations in PAX3 were associated with Waardenburg syndrome with strabismus. Our results report that the c.434G-T mutation (p.R145L) in PAX3 may contribute to strabismus, expanding our understanding of the causally relevant genes for this disorder.
Histone modification: cause or cog?
Henikoff, Steven; Shilatifard, Ali
2011-10-01
Histone modifications are key components of chromatin packaging but whether they constitute a 'code' has been contested. We believe that the central issue is causality: are histone modifications responsible for differences between chromatin states, or are differences in modifications mostly consequences of dynamic processes, such as transcription and nucleosome remodeling? We find that inferences of causality are often based on correlation and that patterns of some key histone modifications are more easily explained as consequences of nucleosome disruption in the presence of histone modifying enzymes. We suggest that the 35-year-old DNA accessibility paradigm provides a mechanistically sound basis for understanding the role of nucleosomes in gene regulation and epigenetic inheritance. Based on this view, histone modifications and variants contribute to diversification of a chromatin landscape shaped by dynamic processes that are driven primarily by transcription and nucleosome remodeling. Copyright © 2011 Elsevier Ltd. All rights reserved.
Common variants of the EPDR1 gene and the risk of Dupuytren’s disease.
Dębniak, T; Żyluk, A; Puchalski, P; Serrano-Fernandez, P
2013-10-01
The object of this study was the investigation of 3 common variants of single nucleotide polymorphisms of the ependymin-related gene 1 and its association with the occurrence of Dupuytren's disease. DNA samples were obtained from the peripheral blood of 508 consecutive patients. The control group comprised 515 healthy adults who were age-matched with the Dupuytren's patients. 3 common variants were analysed using TaqMan® genotyping assays and sequencing. The differences in the frequencies of variants of single nucleotide polymorphisms in patients and the control group were statistically tested. Additionally, haplotype frequency and linkage disequilibrium were analysed for these variants. A statistically significant association was noted between rs16879765_CT, rs16879765_TT and rs13240429_AA variants and Dupuytren's disease. 2 haplotypes: rs2722280_C+rs13240429_A+rs16879765_C and rs2722280_C+rs13240429_G+rs16879765_T were found to be statistically significantly associated with Dupuytren's disease. Moreover, we found that rs13240429 and rs16879765 variants were in strong linkage disequilibrium, while rs2722280 was only in moderate linkage disequilibrium. No significant differences were found in the frequencies of the variants of the gene between the groups with a positive and negative familial history of Dupuytren's disease. In conclusion, results of this study suggest that EPDR1 gene can be added to a growing list of genes associated with Dupuytren's disease development. © Georg Thieme Verlag KG Stuttgart · New York.
Synonymous ABCA3 Variants Do Not Increase Risk for Neonatal Respiratory Distress Syndrome
Wambach, Jennifer A.; Wegner, Daniel J.; Heins, Hillary B.; Druley, Todd E.; Mitra, Robi D.; Hamvas, Aaron; Cole, F. Sessions
2014-01-01
Objective To determine whether synonymous variants in the adenosine triphosphate-binding cassette A3 transporter (ABCA3) gene increase the risk for neonatal respiratory distress syndrome (RDS) in term and late preterm infants of European and African descent. Study design Using next-generation pooled sequencing of race-stratified DNA samples from infants of European and African descent at $34 weeks gestation with and without RDS (n = 503), we scanned all exons of ABCA3, validated each synonymous variant with an independent genotyping platform, and evaluated race-stratified disease risk associated with common synonymous variants and collapsed frequencies of rare synonymous variants. Results The synonymous ABCA3 variant frequency spectrum differs between infants of European descent and those of African descent. Using in silico prediction programs and statistical strategies, we found no potentially disruptive synonymous ABCA3 variants or evidence of selection pressure. Individual common synonymous variants and collapsed frequencies of rare synonymous variants did not increase disease risk in term and late-preterm infants of European or African descent. Conclusion In contrast to rare, nonsynonymous ABCA3 mutations, synonymous ABCA3 variants do not increase the risk for neonatal RDS among term and late-preterm infants of European or African descent. PMID:24657120
Aggressive Variants of Papillary Thyroid Carcinoma: Hobnail, Tall Cell, Columnar, and Solid.
Nath, Meryl C; Erickson, Lori A
2018-05-01
Papillary thyroid carcinomas are the most common endocrine cancer and are usually associated with good survival. However, some variants of papillary thyroid carcinomas may behave more aggressively than classic papillary thyroid carcinomas. The tall cell variant of papillary thyroid carcinoma is the most common aggressive variant of papillary thyroid carcinoma. The aggressive behavior has been ascribed to the histologic subtype and/or to the clinicopathologic features, an issue that remains controversial. The columnar variant of papillary thyroid carcinoma can be aggressive, particularly in older patients, with larger tumors showing a diffusely infiltrative growth pattern and extrathyroidal extension. A papillary thyroid carcinoma is designated as solid/trabecular variant when all or nearly all of a tumor not belonging to any of the other variants has a solid, trabecular, or nested (insular) appearance. This tumor must be distinguished from poorly differentiated thyroid carcinoma which has the same growth pattern but lacks nuclear features of papillary thyroid carcinoma and may show tumor necrosis and high mitotic activity. New to the fourth edition of the WHO Classification of Tumours of Endocrine Organs, the hobnail variant of papillary thyroid carcinoma is a moderately differentiated papillary thyroid carcinoma variant with aggressive clinical behavior and significant mortality. All of these variants are histologically unique and important to recognize due to their aggressive behavior.
Gallo, Eduardo F; Posner, Jonathan
2016-01-01
Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by developmentally inappropriate levels of inattention and hyperactivity or impulsivity. The heterogeneity of its clinical manifestations and the differential responses to treatment and varied prognoses have long suggested myriad underlying causes. Over the past decade, clinical and basic research efforts have uncovered many behavioural and neurobiological alterations associated with ADHD, from genes to higher order neural networks. Here, we review the neurobiology of ADHD by focusing on neural circuits implicated in the disorder and discuss how abnormalities in circuitry relate to symptom presentation and treatment. We summarise the literature on genetic variants that are potentially related to the development of ADHD, and how these, in turn, might affect circuit function and relevant behaviours. Whether these underlying neurobiological factors are causally related to symptom presentation remains unresolved. Therefore, we assess efforts aimed at disentangling issues of causality, and showcase the shifting research landscape towards endophenotype refinement in clinical and preclinical settings. Furthermore, we review approaches being developed to understand the neurobiological underpinnings of this complex disorder including the use of animal models, neuromodulation, and pharmaco-imaging studies. PMID:27183902
A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference.
Hu, Shoubo; Chen, Zhitang; Chan, Laiwan
2018-05-01
Although nonstationary data are more common in the real world, most existing causal discovery methods do not take nonstationarity into consideration. In this letter, we propose a kernel embedding-based approach, ENCI, for nonstationary causal model inference where data are collected from multiple domains with varying distributions. In ENCI, we transform the complicated relation of a cause-effect pair into a linear model of variables of which observations correspond to the kernel embeddings of the cause-and-effect distributions in different domains. In this way, we are able to estimate the causal direction by exploiting the causal asymmetry of the transformed linear model. Furthermore, we extend ENCI to causal graph discovery for multiple variables by transforming the relations among them into a linear nongaussian acyclic model. We show that by exploiting the nonstationarity of distributions, both cause-effect pairs and two kinds of causal graphs are identifiable under mild conditions. Experiments on synthetic and real-world data are conducted to justify the efficacy of ENCI over major existing methods.
Lassiter, Meredith Gooding; Owens, Elizabeth Oesterling; Patel, Molini M; Kirrane, Ellen; Madden, Meagan; Richmond-Bryant, Jennifer; Hines, Erin Pias; Davis, J Allen; Vinikoor-Imler, Lisa; Dubois, Jean-Jacques
2015-04-01
The peer-reviewed literature on the health and ecological effects of lead (Pb) indicates common effects and underlying modes of action across multiple organisms for several endpoints. Based on such observations, the United States (U.S.) Environmental Protection Agency (EPA) applied a cross-species approach in the 2013 Integrated Science Assessment (ISA) for Lead for evaluating the causality of relationships between Pb exposure and specific endpoints that are shared by humans, laboratory animals, and ecological receptors (i.e., hematological effects, reproductive and developmental effects, and nervous system effects). Other effects of Pb (i.e., cardiovascular, renal, and inflammatory responses) are less commonly assessed in aquatic and terrestrial wildlife limiting the application of cross-species comparisons. Determinations of causality in ISAs are guided by a framework for classifying the weight of evidence across scientific disciplines and across related effects by considering aspects such as biological plausibility and coherence. As illustrated for effects of Pb where evidence across species exists, the integration of coherent effects and common underlying modes of action can serve as a means to substantiate conclusions regarding the causal nature of the health and ecological effects of environmental toxicants. Published by Elsevier Ireland Ltd.
Non-Gaussian Methods for Causal Structure Learning.
Shimizu, Shohei
2018-05-22
Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.
Classical Causal Models for Bell and Kochen-Specker Inequality Violations Require Fine-Tuning
NASA Astrophysics Data System (ADS)
Cavalcanti, Eric G.
2018-04-01
Nonlocality and contextuality are at the root of conceptual puzzles in quantum mechanics, and they are key resources for quantum advantage in information-processing tasks. Bell nonlocality is best understood as the incompatibility between quantum correlations and the classical theory of causality, applied to relativistic causal structure. Contextuality, on the other hand, is on a more controversial foundation. In this work, I provide a common conceptual ground between nonlocality and contextuality as violations of classical causality. First, I show that Bell inequalities can be derived solely from the assumptions of no signaling and no fine-tuning of the causal model. This removes two extra assumptions from a recent result from Wood and Spekkens and, remarkably, does not require any assumption related to independence of measurement settings—unlike all other derivations of Bell inequalities. I then introduce a formalism to represent contextuality scenarios within causal models and show that all classical causal models for violations of a Kochen-Specker inequality require fine-tuning. Thus, the quantum violation of classical causality goes beyond the case of spacelike-separated systems and already manifests in scenarios involving single systems.
Sahana, G; Guldbrandtsen, B; Thomsen, B; Holm, L-E; Panitz, F; Brøndum, R F; Bendixen, C; Lund, M S
2014-11-01
Mastitis is a mammary disease that frequently affects dairy cattle. Despite considerable research on the development of effective prevention and treatment strategies, mastitis continues to be a significant issue in bovine veterinary medicine. To identify major genes that affect mastitis in dairy cattle, 6 chromosomal regions on Bos taurus autosome (BTA) 6, 13, 16, 19, and 20 were selected from a genome scan for 9 mastitis phenotypes using imputed high-density single nucleotide polymorphism arrays. Association analyses using sequence-level variants for the 6 targeted regions were carried out to map causal variants using whole-genome sequence data from 3 breeds. The quantitative trait loci (QTL) discovery population comprised 4,992 progeny-tested Holstein bulls, and QTL were confirmed in 4,442 Nordic Red and 1,126 Jersey cattle. The targeted regions were imputed to the sequence level. The highest association signal for clinical mastitis was observed on BTA 6 at 88.97 Mb in Holstein cattle and was confirmed in Nordic Red cattle. The peak association region on BTA 6 contained 2 genes: vitamin D-binding protein precursor (GC) and neuropeptide FF receptor 2 (NPFFR2), which, based on known biological functions, are good candidates for affecting mastitis. However, strong linkage disequilibrium in this region prevented conclusive determination of the causal gene. A different QTL on BTA 6 located at 88.32 Mb in Holstein cattle affected mastitis. In addition, QTL on BTA 13 and 19 were confirmed to segregate in Nordic Red cattle and QTL on BTA 16 and 20 were confirmed in Jersey cattle. Although several candidate genes were identified in these targeted regions, it was not possible to identify a gene or polymorphism as the causal factor for any of these regions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Benavides, Julio; Perez, Valentín; Tosser-Klopp, Gwenola; Klopp, Christophe; Keennel, Stephen J.; Arranz, Juan José
2015-01-01
In this study, we demonstrate the use of a genome-wide association mapping together with RNA-seq in a reduced number of samples, as an efficient approach to detect the causal mutation for a Mendelian disease. Junctional epidermolysis bullosa is a recessive genodermatosis that manifests with neonatal mechanical fragility of the skin, blistering confined to the lamina lucida of the basement membrane and severe alteration of the hemidesmosomal junctions. In Spanish Churra sheep, junctional epidermolysis bullosa (JEB) has been detected in two commercial flocks. The JEB locus was mapped to Ovis aries chromosome 11 by GWAS and subsequently fine-mapped to an 868-kb homozygous segment using the identical-by-descent method. The ITGB4, which is located within this region, was identified as the best positional and functional candidate gene. The RNA-seq variant analysis enabled us to discover a 4-bp deletion within exon 33 of the ITGB4 gene (c.4412_4415del). The c.4412_4415del mutation causes a frameshift resulting in a premature stop codon at position 1472 of the integrin β4 protein. A functional analysis of this deletion revealed decreased levels of mRNA in JEB skin samples and the absence of integrin β4 labeling in immunohistochemical assays. Genotyping of c.4412_4415del showed perfect concordance with the recessive mode of the disease phenotype. Selection against this causal mutation will now be used to solve the problem of JEB in flocks of Churra sheep. Furthermore, the identification of the ITGB4 mutation means that affected sheep can be used as a large mammal animal model for the human form of epidermolysis bullosa with aplasia cutis. Our approach evidences that RNA-seq offers cost-effective alternative to identify variants in the species in which high resolution exome-sequencing is not straightforward. PMID:25955497
2014-01-01
Background The absence of horns, called polled phenotype, is the favored trait in modern cattle husbandry. To date, polled cattle are obtained primarily by dehorning calves. Dehorning is a practice that raises animal welfare issues, which can be addressed by selecting for genetically hornless cattle. In the past 20 years, there have been many studies worldwide to identify unique genetic markers in complete association with the polled trait in cattle and recently, two different alleles at the POLLED locus, both resulting in the absence of horns, were reported: (1) the Celtic allele, which is responsible for the polled phenotype in most breeds and for which a single candidate mutation was detected and (2) the Friesian allele, which is responsible for the polled phenotype predominantly in the Holstein-Friesian breed and in a few other breeds, but for which five candidate mutations were identified in a 260-kb haplotype. Further studies based on genome-wide sequencing and high-density SNP (single nucleotide polymorphism) genotyping confirmed the existence of the Celtic and Friesian variants and narrowed down the causal Friesian haplotype to an interval of 145 kb. Results Almost 6000 animals were genetically tested for the polled trait and we detected a recombinant animal which enabled us to reduce the Friesian POLLED haplotype to a single causal mutation, namely a 80-kb duplication. Moreover, our results clearly disagree with the recently reported perfect co-segregation of the POLLED mutation and a SNP at position 1 390 292 bp on bovine chromosome 1 in the Holstein-Friesian population. Conclusion We conclude that the 80-kb duplication, as the only remaining variant within the shortened Friesian haplotype, represents the most likely causal mutation for the polled phenotype of Friesian origin. PMID:24993890
Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Benavides, Julio; Perez, Valentín; Tosser-Klopp, Gwenola; Klopp, Christophe; Keennel, Stephen J; Arranz, Juan José
2015-01-01
In this study, we demonstrate the use of a genome-wide association mapping together with RNA-seq in a reduced number of samples, as an efficient approach to detect the causal mutation for a Mendelian disease. Junctional epidermolysis bullosa is a recessive genodermatosis that manifests with neonatal mechanical fragility of the skin, blistering confined to the lamina lucida of the basement membrane and severe alteration of the hemidesmosomal junctions. In Spanish Churra sheep, junctional epidermolysis bullosa (JEB) has been detected in two commercial flocks. The JEB locus was mapped to Ovis aries chromosome 11 by GWAS and subsequently fine-mapped to an 868-kb homozygous segment using the identical-by-descent method. The ITGB4, which is located within this region, was identified as the best positional and functional candidate gene. The RNA-seq variant analysis enabled us to discover a 4-bp deletion within exon 33 of the ITGB4 gene (c.4412_4415del). The c.4412_4415del mutation causes a frameshift resulting in a premature stop codon at position 1472 of the integrin β4 protein. A functional analysis of this deletion revealed decreased levels of mRNA in JEB skin samples and the absence of integrin β4 labeling in immunohistochemical assays. Genotyping of c.4412_4415del showed perfect concordance with the recessive mode of the disease phenotype. Selection against this causal mutation will now be used to solve the problem of JEB in flocks of Churra sheep. Furthermore, the identification of the ITGB4 mutation means that affected sheep can be used as a large mammal animal model for the human form of epidermolysis bullosa with aplasia cutis. Our approach evidences that RNA-seq offers cost-effective alternative to identify variants in the species in which high resolution exome-sequencing is not straightforward.
A Hierarchical Causal Taxonomy of Psychopathology across the Life Span
Lahey, Benjamin B.; Krueger, Robert F.; Rathouz, Paul J.; Waldman, Irwin D.; Zald, David H.
2016-01-01
We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the three levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. PMID:28004947
Empirically Driven Variable Selection for the Estimation of Causal Effects with Observational Data
ERIC Educational Resources Information Center
Keller, Bryan; Chen, Jianshen
2016-01-01
Observational studies are common in educational research, where subjects self-select or are otherwise non-randomly assigned to different interventions (e.g., educational programs, grade retention, special education). Unbiased estimation of a causal effect with observational data depends crucially on the assumption of ignorability, which specifies…
Genes Regulated by Vitamin D in Bone Cells Are Positively Selected in East Asians
Chen, Yuan; Xue, Yali; Luiselli, Donata; Tyler-Smith, Chris; Pagani, Luca; Ayub, Qasim
2015-01-01
Vitamin D and folate are activated and degraded by sunlight, respectively, and the physiological processes they control are likely to have been targets of selection as humans expanded from Africa into Eurasia. We investigated signals of positive selection in gene sets involved in the metabolism, regulation and action of these two vitamins in worldwide populations sequenced by Phase I of the 1000 Genomes Project. Comparing allele frequency-spectrum-based summary statistics between these gene sets and matched control genes, we observed a selection signal specific to East Asians for a gene set associated with vitamin D action in bones. The selection signal was mainly driven by three genes CXXC finger protein 1 (CXXC1), low density lipoprotein receptor-related protein 5 (LRP5) and runt-related transcription factor 2 (RUNX2). Examination of population differentiation and haplotypes allowed us to identify several candidate causal regulatory variants in each gene. Four of these candidate variants (one each in CXXC1 and RUNX2 and two in LRP5) had a >70% derived allele frequency in East Asians, but were present at lower (20–60%) frequency in Europeans as well, suggesting that the adaptation might have been part of a common response to climatic and dietary changes as humans expanded out of Africa, with implications for their role in vitamin D-dependent bone mineralization and osteoporosis insurgence. We also observed haplotype sharing between East Asians, Finns and an extinct archaic human (Denisovan) sample at the CXXC1 locus, which is best explained by incomplete lineage sorting. PMID:26719974
CPT1A Missense Mutation Associated With Fatty Acid Metabolism and Reduced Height in Greenlanders.
Skotte, Line; Koch, Anders; Yakimov, Victor; Zhou, Sirui; Søborg, Bolette; Andersson, Mikael; Michelsen, Sascha W; Navne, Johan E; Mistry, Jacqueline M; Dion, Patrick A; Pedersen, Michael L; Børresen, Malene L; Rouleau, Guy A; Geller, Frank; Melbye, Mads; Feenstra, Bjarke
2017-06-01
Inuit have lived for thousands of years in an extremely cold environment on a diet dominated by marine-derived fat. To investigate how this selective pressure has affected the genetic regulation of fatty acid metabolism, we assessed 233 serum metabolic phenotypes in a population-based sample of 1570 Greenlanders. Using array-based and targeted genotyping, we found that rs80356779, a p.Pro479Leu variant in CPT1A , was strongly associated with markers of n -3 fatty acid metabolism, including degree of unsaturation ( P =1.16×10 - 34 ), levels of polyunsaturated fatty acids, n -3 fatty acids, and docosahexaoenic acid relative to total fatty acid levels ( P =2.35×10 - 15 , P =4.02×10 - 19 , and P =7.92×10 - 27 ). The derived allele (L479) occurred at a frequency of 76.2% in our sample while being absent in most other populations, and we found strong signatures of positive selection at the locus. Furthermore, we found that each copy of L479 reduced height by an average of 2.1 cm ( P =1.04×10 - 9 ). In exome sequencing data from a sister population, the Nunavik Inuit, we found no other likely causal candidate variant than rs80356779. Our study shows that a common CPT1A missense mutation is strongly associated with a range of metabolic phenotypes and reduced height in Greenlanders. These findings are important from a public health perspective and highlight the usefulness of complex trait genetic studies in isolated populations. © 2017 American Heart Association, Inc.
Trans-ethnic meta-analysis of white blood cell phenotypes
Keller, Margaux F.; Reiner, Alexander P.; Okada, Yukinori; van Rooij, Frank J.A.; Johnson, Andrew D.; Chen, Ming-Huei; Smith, Albert V.; Morris, Andrew P.; Tanaka, Toshiko; Ferrucci, Luigi; Zonderman, Alan B.; Lettre, Guillaume; Harris, Tamara; Garcia, Melissa; Bandinelli, Stefania; Qayyum, Rehan; Yanek, Lisa R.; Becker, Diane M.; Becker, Lewis C.; Kooperberg, Charles; Keating, Brendan; Reis, Jared; Tang, Hua; Boerwinkle, Eric; Kamatani, Yoichiro; Matsuda, Koichi; Kamatani, Naoyuki; Nakamura, Yusuke; Kubo, Michiaki; Liu, Simin; Dehghan, Abbas; Felix, Janine F.; Hofman, Albert; Uitterlinden, André G.; van Duijn, Cornelia M.; Franco, Oscar H.; Longo, Dan L.; Singleton, Andrew B.; Psaty, Bruce M.; Evans, Michelle K.; Cupples, L. Adrienne; Rotter, Jerome I.; O'Donnell, Christopher J.; Takahashi, Atsushi; Wilson, James G.; Ganesh, Santhi K.; Nalls, Mike A.
2014-01-01
White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool. PMID:25096241
Power, Robert A; Cohen-Woods, Sarah; Ng, Mandy Y; Butler, Amy W; Craddock, Nick; Korszun, Ania; Jones, Lisa; Jones, Ian; Gill, Michael; Rice, John P; Maier, Wolfgang; Zobel, Astrid; Mors, Ole; Placentino, Anna; Rietschel, Marcella; Aitchison, Katherine J; Tozzi, Federica; Muglia, Pierandrea; Breen, Gerome; Farmer, Anne E; McGuffin, Peter; Lewis, Cathryn M; Uher, Rudolf
2013-09-01
Stressful life events are an established trigger for depression and may contribute to the heterogeneity within genome-wide association analyses. With depression cases showing an excess of exposure to stressful events compared to controls, there is difficulty in distinguishing between "true" cases and a "normal" response to a stressful environment. This potential contamination of cases, and that from genetically at risk controls that have not yet experienced environmental triggers for onset, may reduce the power of studies to detect causal variants. In the RADIANT sample of 3,690 European individuals, we used propensity score matching to pair cases and controls on exposure to stressful life events. In 805 case-control pairs matched on stressful life event, we tested the influence of 457,670 common genetic variants on the propensity to depression under comparable level of adversity with a sign test. While this analysis produced no significant findings after genome-wide correction for multiple testing, we outline a novel methodology and perspective for providing environmental context in genetic studies. We recommend contextualizing depression by incorporating environmental exposure into genome-wide analyses as a complementary approach to testing gene-environment interactions. Possible explanations for negative findings include a lack of statistical power due to small sample size and conditional effects, resulting from the low rate of adequate matching. Our findings underscore the importance of collecting information on environmental risk factors in studies of depression and other complex phenotypes, so that sufficient sample sizes are available to investigate their effect in genome-wide association analysis. Copyright © 2013 Wiley Periodicals, Inc.
Hinckley, Jesse D; Abbott, Diana; Burns, Trudy L; Heiman, Meadow; Shapiro, Amy D; Wang, Kai; Di Paola, Jorge
2013-01-01
We characterized a large Amish pedigree and, in 384 pedigree members, analyzed the genetic variance components with covariate screen as well as genome-wide quantitative trait locus (QTL) linkage analysis of red blood cell count (RBC), hemoglobin (HB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), platelet count (PLT), and white blood cell count (WBC) using SOLAR. Age and gender were found to be significant covariates in many CBC traits. We obtained significant heritability estimates for RBC, MCV, MCH, MCHC, RDW, PLT, and WBC. We report four candidate loci with Logarithm of the odds (LOD) scores above 2.0: 6q25 (MCH), 9q33 (WBC), 10p12 (RDW), and 20q13 (MCV). We also report eleven candidate loci with LOD scores between 1.5 and <2.0. Bivariate linkage analysis of MCV and MCH on chromosome 20 resulted in a higher maximum LOD score of 3.14. Linkage signals on chromosomes 4q28, 6p22, 6q25, and 20q13 are concomitant with previously reported QTL. All other linkage signals reported herein represent novel evidence of candidate QTL. Interestingly rs1800562, the most common causal variant of hereditary hemochromatosis in HFE (6p22) was associated with MCH and MCHC in this family. Linkage studies like the one presented here will allow investigators to focus the search for rare variants amidst the noise encountered in the large amounts of data generated by whole-genome sequencing. PMID:24058921
Ackermann, Maegen A; Patel, Puja D; Valenti, Jane; Takagi, Yasuharu; Homsher, Earl; Sellers, James R; Kontrogianni-Konstantopoulos, Aikaterini
2013-08-01
Myosin binding protein C (MyBP-C) is expressed in striated muscles, where it plays key roles in the modulation of actomyosin cross-bridges. Slow MyBP-C (sMyBP-C) consists of multiple variants sharing common domains but also containing unique segments within the NH2 and COOH termini. Two missense mutations in the NH2 terminus (W236R) and COOH terminus (Y856H) of sMyBP-C have been causally linked to the development of distal arthrogryposis-1 (DA-1), a severe skeletal muscle disorder. Using a combination of in vitro binding and motility assays, we show that the COOH terminus mediates binding of sMyBP-C to thick filaments, while the NH2 terminus modulates the formation of actomyosin cross-bridges in a variant-specific manner. Consistent with this, a recombinant NH2-terminal peptide that excludes residues 34-59 reduces the sliding velocity of actin filaments past myosin heads from 9.0 ± 1.3 to 5.7 ± 1.0 μm/s at 0.1 μM, while a recombinant peptide that excludes residues 21-59 fails to do so. Notably, the actomyosin regulatory properties of sMyBP-C are completely abolished by the presence of the DA-1 mutations. In summary, our studies are the first to show that the NH2 and COOH termini of sMyBP-C have distinct functions, which are regulated by differential splicing, and are compromized by the presence of missense point mutations linked to muscle disease.
The genetic architecture of type 2 diabetes.
Fuchsberger, Christian; Flannick, Jason; Teslovich, Tanya M; Mahajan, Anubha; Agarwala, Vineeta; Gaulton, Kyle J; Ma, Clement; Fontanillas, Pierre; Moutsianas, Loukas; McCarthy, Davis J; Rivas, Manuel A; Perry, John R B; Sim, Xueling; Blackwell, Thomas W; Robertson, Neil R; Rayner, N William; Cingolani, Pablo; Locke, Adam E; Tajes, Juan Fernandez; Highland, Heather M; Dupuis, Josee; Chines, Peter S; Lindgren, Cecilia M; Hartl, Christopher; Jackson, Anne U; Chen, Han; Huyghe, Jeroen R; van de Bunt, Martijn; Pearson, Richard D; Kumar, Ashish; Müller-Nurasyid, Martina; Grarup, Niels; Stringham, Heather M; Gamazon, Eric R; Lee, Jaehoon; Chen, Yuhui; Scott, Robert A; Below, Jennifer E; Chen, Peng; Huang, Jinyan; Go, Min Jin; Stitzel, Michael L; Pasko, Dorota; Parker, Stephen C J; Varga, Tibor V; Green, Todd; Beer, Nicola L; Day-Williams, Aaron G; Ferreira, Teresa; Fingerlin, Tasha; Horikoshi, Momoko; Hu, Cheng; Huh, Iksoo; Ikram, Mohammad Kamran; Kim, Bong-Jo; Kim, Yongkang; Kim, Young Jin; Kwon, Min-Seok; Lee, Juyoung; Lee, Selyeong; Lin, Keng-Han; Maxwell, Taylor J; Nagai, Yoshihiko; Wang, Xu; Welch, Ryan P; Yoon, Joon; Zhang, Weihua; Barzilai, Nir; Voight, Benjamin F; Han, Bok-Ghee; Jenkinson, Christopher P; Kuulasmaa, Teemu; Kuusisto, Johanna; Manning, Alisa; Ng, Maggie C Y; Palmer, Nicholette D; Balkau, Beverley; Stančáková, Alena; Abboud, Hanna E; Boeing, Heiner; Giedraitis, Vilmantas; Prabhakaran, Dorairaj; Gottesman, Omri; Scott, James; Carey, Jason; Kwan, Phoenix; Grant, George; Smith, Joshua D; Neale, Benjamin M; Purcell, Shaun; Butterworth, Adam S; Howson, Joanna M M; Lee, Heung Man; Lu, Yingchang; Kwak, Soo-Heon; Zhao, Wei; Danesh, John; Lam, Vincent K L; Park, Kyong Soo; Saleheen, Danish; So, Wing Yee; Tam, Claudia H T; Afzal, Uzma; Aguilar, David; Arya, Rector; Aung, Tin; Chan, Edmund; Navarro, Carmen; Cheng, Ching-Yu; Palli, Domenico; Correa, Adolfo; Curran, Joanne E; Rybin, Denis; Farook, Vidya S; Fowler, Sharon P; Freedman, Barry I; Griswold, Michael; Hale, Daniel Esten; Hicks, Pamela J; Khor, Chiea-Chuen; Kumar, Satish; Lehne, Benjamin; Thuillier, Dorothée; Lim, Wei Yen; Liu, Jianjun; van der Schouw, Yvonne T; Loh, Marie; Musani, Solomon K; Puppala, Sobha; Scott, William R; Yengo, Loïc; Tan, Sian-Tsung; Taylor, Herman A; Thameem, Farook; Wilson, Gregory; Wong, Tien Yin; Njølstad, Pål Rasmus; Levy, Jonathan C; Mangino, Massimo; Bonnycastle, Lori L; Schwarzmayr, Thomas; Fadista, João; Surdulescu, Gabriela L; Herder, Christian; Groves, Christopher J; Wieland, Thomas; Bork-Jensen, Jette; Brandslund, Ivan; Christensen, Cramer; Koistinen, Heikki A; Doney, Alex S F; Kinnunen, Leena; Esko, Tõnu; Farmer, Andrew J; Hakaste, Liisa; Hodgkiss, Dylan; Kravic, Jasmina; Lyssenko, Valeriya; Hollensted, Mette; Jørgensen, Marit E; Jørgensen, Torben; Ladenvall, Claes; Justesen, Johanne Marie; Käräjämäki, Annemari; Kriebel, Jennifer; Rathmann, Wolfgang; Lannfelt, Lars; Lauritzen, Torsten; Narisu, Narisu; Linneberg, Allan; Melander, Olle; Milani, Lili; Neville, Matt; Orho-Melander, Marju; Qi, Lu; Qi, Qibin; Roden, Michael; Rolandsson, Olov; Swift, Amy; Rosengren, Anders H; Stirrups, Kathleen; Wood, Andrew R; Mihailov, Evelin; Blancher, Christine; Carneiro, Mauricio O; Maguire, Jared; Poplin, Ryan; Shakir, Khalid; Fennell, Timothy; DePristo, Mark; de Angelis, Martin Hrabé; Deloukas, Panos; Gjesing, Anette P; Jun, Goo; Nilsson, Peter; Murphy, Jacquelyn; Onofrio, Robert; Thorand, Barbara; Hansen, Torben; Meisinger, Christa; Hu, Frank B; Isomaa, Bo; Karpe, Fredrik; Liang, Liming; Peters, Annette; Huth, Cornelia; O'Rahilly, Stephen P; Palmer, Colin N A; Pedersen, Oluf; Rauramaa, Rainer; Tuomilehto, Jaakko; Salomaa, Veikko; Watanabe, Richard M; Syvänen, Ann-Christine; Bergman, Richard N; Bharadwaj, Dwaipayan; Bottinger, Erwin P; Cho, Yoon Shin; Chandak, Giriraj R; Chan, Juliana C N; Chia, Kee Seng; Daly, Mark J; Ebrahim, Shah B; Langenberg, Claudia; Elliott, Paul; Jablonski, Kathleen A; Lehman, Donna M; Jia, Weiping; Ma, Ronald C W; Pollin, Toni I; Sandhu, Manjinder; Tandon, Nikhil; Froguel, Philippe; Barroso, Inês; Teo, Yik Ying; Zeggini, Eleftheria; Loos, Ruth J F; Small, Kerrin S; Ried, Janina S; DeFronzo, Ralph A; Grallert, Harald; Glaser, Benjamin; Metspalu, Andres; Wareham, Nicholas J; Walker, Mark; Banks, Eric; Gieger, Christian; Ingelsson, Erik; Im, Hae Kyung; Illig, Thomas; Franks, Paul W; Buck, Gemma; Trakalo, Joseph; Buck, David; Prokopenko, Inga; Mägi, Reedik; Lind, Lars; Farjoun, Yossi; Owen, Katharine R; Gloyn, Anna L; Strauch, Konstantin; Tuomi, Tiinamaija; Kooner, Jaspal Singh; Lee, Jong-Young; Park, Taesung; Donnelly, Peter; Morris, Andrew D; Hattersley, Andrew T; Bowden, Donald W; Collins, Francis S; Atzmon, Gil; Chambers, John C; Spector, Timothy D; Laakso, Markku; Strom, Tim M; Bell, Graeme I; Blangero, John; Duggirala, Ravindranath; Tai, E Shyong; McVean, Gilean; Hanis, Craig L; Wilson, James G; Seielstad, Mark; Frayling, Timothy M; Meigs, James B; Cox, Nancy J; Sladek, Rob; Lander, Eric S; Gabriel, Stacey; Burtt, Noël P; Mohlke, Karen L; Meitinger, Thomas; Groop, Leif; Abecasis, Goncalo; Florez, Jose C; Scott, Laura J; Morris, Andrew P; Kang, Hyun Min; Boehnke, Michael; Altshuler, David; McCarthy, Mark I
2016-08-04
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
The genetic architecture of type 2 diabetes
Ma, Clement; Fontanillas, Pierre; Moutsianas, Loukas; McCarthy, Davis J; Rivas, Manuel A; Perry, John R B; Sim, Xueling; Blackwell, Thomas W; Robertson, Neil R; Rayner, N William; Cingolani, Pablo; Locke, Adam E; Tajes, Juan Fernandez; Highland, Heather M; Dupuis, Josee; Chines, Peter S; Lindgren, Cecilia M; Hartl, Christopher; Jackson, Anne U; Chen, Han; Huyghe, Jeroen R; van de Bunt, Martijn; Pearson, Richard D; Kumar, Ashish; Müller-Nurasyid, Martina; Grarup, Niels; Stringham, Heather M; Gamazon, Eric R; Lee, Jaehoon; Chen, Yuhui; Scott, Robert A; Below, Jennifer E; Chen, Peng; Huang, Jinyan; Go, Min Jin; Stitzel, Michael L; Pasko, Dorota; Parker, Stephen C J; Varga, Tibor V; Green, Todd; Beer, Nicola L; Day-Williams, Aaron G; Ferreira, Teresa; Fingerlin, Tasha; Horikoshi, Momoko; Hu, Cheng; Huh, Iksoo; Ikram, Mohammad Kamran; Kim, Bong-Jo; Kim, Yongkang; Kim, Young Jin; Kwon, Min-Seok; Lee, Juyoung; Lee, Selyeong; Lin, Keng-Han; Maxwell, Taylor J; Nagai, Yoshihiko; Wang, Xu; Welch, Ryan P; Yoon, Joon; Zhang, Weihua; Barzilai, Nir; Voight, Benjamin F; Han, Bok-Ghee; Jenkinson, Christopher P; Kuulasmaa, Teemu; Kuusisto, Johanna; Manning, Alisa; Ng, Maggie C Y; Palmer, Nicholette D; Balkau, Beverley; Stančáková, Alena; Abboud, Hanna E; Boeing, Heiner; Giedraitis, Vilmantas; Prabhakaran, Dorairaj; Gottesman, Omri; Scott, James; Carey, Jason; Kwan, Phoenix; Grant, George; Smith, Joshua D; Neale, Benjamin M; Purcell, Shaun; Butterworth, Adam S; Howson, Joanna M M; Lee, Heung Man; Lu, Yingchang; Kwak, Soo-Heon; Zhao, Wei; Danesh, John; Lam, Vincent K L; Park, Kyong Soo; Saleheen, Danish; So, Wing Yee; Tam, Claudia H T; Afzal, Uzma; Aguilar, David; Arya, Rector; Aung, Tin; Chan, Edmund; Navarro, Carmen; Cheng, Ching-Yu; Palli, Domenico; Correa, Adolfo; Curran, Joanne E; Rybin, Denis; Farook, Vidya S; Fowler, Sharon P; Freedman, Barry I; Griswold, Michael; Hale, Daniel Esten; Hicks, Pamela J; Khor, Chiea-Chuen; Kumar, Satish; Lehne, Benjamin; Thuillier, Dorothée; Lim, Wei Yen; Liu, Jianjun; van der Schouw, Yvonne T; Loh, Marie; Musani, Solomon K; Puppala, Sobha; Scott, William R; Yengo, Loïc; Tan, Sian-Tsung; Taylor, Herman A; Thameem, Farook; Wilson, Gregory; Wong, Tien Yin; Njølstad, Pål Rasmus; Levy, Jonathan C; Mangino, Massimo; Bonnycastle, Lori L; Schwarzmayr, Thomas; Fadista, João; Surdulescu, Gabriela L; Herder, Christian; Groves, Christopher J; Wieland, Thomas; Bork-Jensen, Jette; Brandslund, Ivan; Christensen, Cramer; Koistinen, Heikki A; Doney, Alex S F; Kinnunen, Leena; Esko, Tõnu; Farmer, Andrew J; Hakaste, Liisa; Hodgkiss, Dylan; Kravic, Jasmina; Lyssenko, Valeriya; Hollensted, Mette; Jørgensen, Marit E; Jørgensen, Torben; Ladenvall, Claes; Justesen, Johanne Marie; Käräjämäki, Annemari; Kriebel, Jennifer; Rathmann, Wolfgang; Lannfelt, Lars; Lauritzen, Torsten; Narisu, Narisu; Linneberg, Allan; Melander, Olle; Milani, Lili; Neville, Matt; Orho-Melander, Marju; Qi, Lu; Qi, Qibin; Roden, Michael; Rolandsson, Olov; Swift, Amy; Rosengren, Anders H; Stirrups, Kathleen; Wood, Andrew R; Mihailov, Evelin; Blancher, Christine; Carneiro, Mauricio O; Maguire, Jared; Poplin, Ryan; Shakir, Khalid; Fennell, Timothy; DePristo, Mark; de Angelis, Martin Hrabé; Deloukas, Panos; Gjesing, Anette P; Jun, Goo; Nilsson, Peter; Murphy, Jacquelyn; Onofrio, Robert; Thorand, Barbara; Hansen, Torben; Meisinger, Christa; Hu, Frank B; Isomaa, Bo; Karpe, Fredrik; Liang, Liming; Peters, Annette; Huth, Cornelia; O'Rahilly, Stephen P; Palmer, Colin N A; Pedersen, Oluf; Rauramaa, Rainer; Tuomilehto, Jaakko; Salomaa, Veikko; Watanabe, Richard M; Syvänen, Ann-Christine; Bergman, Richard N; Bharadwaj, Dwaipayan; Bottinger, Erwin P; Cho, Yoon Shin; Chandak, Giriraj R; Chan, Juliana C N; Chia, Kee Seng; Daly, Mark J; Ebrahim, Shah B; Langenberg, Claudia; Elliott, Paul; Jablonski, Kathleen A; Lehman, Donna M; Jia, Weiping; Ma, Ronald C W; Pollin, Toni I; Sandhu, Manjinder; Tandon, Nikhil; Froguel, Philippe; Barroso, Inês; Teo, Yik Ying; Zeggini, Eleftheria; Loos, Ruth J F; Small, Kerrin S; Ried, Janina S; DeFronzo, Ralph A; Grallert, Harald; Glaser, Benjamin; Metspalu, Andres; Wareham, Nicholas J; Walker, Mark; Banks, Eric; Gieger, Christian; Ingelsson, Erik; Im, Hae Kyung; Illig, Thomas; Franks, Paul W; Buck, Gemma; Trakalo, Joseph; Buck, David; Prokopenko, Inga; Mägi, Reedik; Lind, Lars; Farjoun, Yossi; Owen, Katharine R; Gloyn, Anna L; Strauch, Konstantin; Tuomi, Tiinamaija; Kooner, Jaspal Singh; Lee, Jong-Young; Park, Taesung; Donnelly, Peter; Morris, Andrew D; Hattersley, Andrew T; Bowden, Donald W; Collins, Francis S; Atzmon, Gil; Chambers, John C; Spector, Timothy D; Laakso, Markku; Strom, Tim M; Bell, Graeme I; Blangero, John; Duggirala, Ravindranath; Tai, E Shyong; McVean, Gilean; Hanis, Craig L; Wilson, James G; Seielstad, Mark; Frayling, Timothy M; Meigs, James B; Cox, Nancy J; Sladek, Rob; Lander, Eric S; Gabriel, Stacey; Burtt, Noël P; Mohlke, Karen L; Meitinger, Thomas; Groop, Leif; Abecasis, Goncalo; Florez, Jose C; Scott, Laura J; Morris, Andrew P; Kang, Hyun Min; Boehnke, Michael; Altshuler, David; McCarthy, Mark I
2016-01-01
The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes. PMID:27398621
Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred
2014-01-01
Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield. PMID:25333064
Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred
2014-09-01
Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield.