A plausibly causal functional lupus-associated risk variant in the STAT1-STAT4 locus.

PubMed

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.

Incorporating Functional Annotations for Fine-Mapping Causal Variants in a Bayesian Framework Using Summary Statistics.

PubMed

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.

Identifying Mendelian disease genes with the Variant Effect Scoring Tool

PubMed Central

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

Exome Sequencing Identifies Potential Risk Variants for Mendelian Disorders at High Prevalence in Qatar

PubMed Central

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

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.

PubMed

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.

Using Extreme Phenotype Sampling to Identify the Rare Causal Variants of Quantitative Traits in Association Studies

PubMed Central

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

Three-dimensional spatial analysis of missense variants in RTEL1 identifies pathogenic variants in patients with Familial Interstitial Pneumonia.

PubMed

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

Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis

PubMed Central

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

Identifying causal linkages between environmental variables and African conflicts

NASA Astrophysics Data System (ADS)

Nguy-Robertson, A. L.; Dartevelle, S.

2017-12-01

Environmental variables that contribute to droughts, flooding, and other natural hazards are often identified as factors contributing to conflict; however, few studies attempt to quantify these causal linkages. Recent research has demonstrated that the environment operates within a dynamical system framework and the influence of variables can be identified from convergent cross mapping (CCM) between shadow manifolds. We propose to use CCM to identify causal linkages between environmental variables and incidences of conflict. This study utilizes time series data from Climate Forecast System ver. 2 and MODIS satellite sensors processed using Google Earth Engine to aggregate country and regional trends. These variables are then compared to Armed Conflict Location & Event Data Project observations at similar scales. Results provide relative rankings of variables and their linkage to conflict. Being able to identify which factors contributed more strongly to a conflict can allow policy makers to prepare solutions to mitigate future crises. Knowledge of the primary environmental factors can lead to the identification of other variables to examine in the causal network influencing conflict.

Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

PubMed

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.

Estimating genetic effects and quantifying missing heritability explained by identified rare-variant associations.

PubMed

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.

A Genome-Wide Linkage Study for Chronic Obstructive Pulmonary Disease in a Dutch Genetic Isolate Identifies Novel Rare Candidate Variants.

PubMed

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-Exome Sequencing Identifies Novel Variants for Tooth Agenesis.

PubMed

Dinckan, N; Du, R; Petty, L E; Coban-Akdemir, Z; Jhangiani, S N; Paine, I; Baugh, E H; Erdem, A P; Kayserili, H; Doddapaneni, H; Hu, J; Muzny, D M; Boerwinkle, E; Gibbs, R A; Lupski, J R; Uyguner, Z O; Below, J E; Letra, A

2018-01-01

Tooth agenesis is a common craniofacial abnormality in humans and represents failure to develop 1 or more permanent teeth. Tooth agenesis is complex, and variations in about a dozen genes have been reported as contributing to the etiology. Here, we combined whole-exome sequencing, array-based genotyping, and linkage analysis to identify putative pathogenic variants in candidate disease genes for tooth agenesis in 10 multiplex Turkish families. Novel homozygous and heterozygous variants in LRP6, DKK1, LAMA3, and COL17A1 genes, as well as known variants in WNT10A, were identified as likely pathogenic in isolated tooth agenesis. Novel variants in KREMEN1 were identified as likely pathogenic in 2 families with suspected syndromic tooth agenesis. Variants in more than 1 gene were identified segregating with tooth agenesis in 2 families, suggesting oligogenic inheritance. Structural modeling of missense variants suggests deleterious effects to the encoded proteins. Functional analysis of an indel variant (c.3607+3_6del) in LRP6 suggested that the predicted resulting mRNA is subject to nonsense-mediated decay. Our results support a major role for WNT pathways genes in the etiology of tooth agenesis while revealing new candidate genes. Moreover, oligogenic cosegregation was suggestive for complex inheritance and potentially complex gene product interactions during development, contributing to improved understanding of the genetic etiology of familial tooth agenesis.

Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci

PubMed Central

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

Identifying Seizure Onset Zone From the Causal Connectivity Inferred Using Directed Information

NASA Astrophysics Data System (ADS)

Malladi, Rakesh; Kalamangalam, Giridhar; Tandon, Nitin; Aazhang, Behnaam

2016-10-01

In this paper, we developed a model-based and a data-driven estimator for directed information (DI) to infer the causal connectivity graph between electrocorticographic (ECoG) signals recorded from brain and to identify the seizure onset zone (SOZ) in epileptic patients. Directed information, an information theoretic quantity, is a general metric to infer causal connectivity between time-series and is not restricted to a particular class of models unlike the popular metrics based on Granger causality or transfer entropy. The proposed estimators are shown to be almost surely convergent. Causal connectivity between ECoG electrodes in five epileptic patients is inferred using the proposed DI estimators, after validating their performance on simulated data. We then proposed a model-based and a data-driven SOZ identification algorithm to identify SOZ from the causal connectivity inferred using model-based and data-driven DI estimators respectively. The data-driven SOZ identification outperforms the model-based SOZ identification algorithm when benchmarked against visual analysis by neurologist, the current clinical gold standard. The causal connectivity analysis presented here is the first step towards developing novel non-surgical treatments for epilepsy.

Fine-Mapping of Common Genetic Variants Associated with Colorectal Tumor Risk Identified Potential Functional Variants

PubMed Central

Gala, Manish; Abecasis, Goncalo; Bezieau, Stephane; Brenner, Hermann; Butterbach, Katja; Caan, Bette J.; Carlson, Christopher S.; Casey, Graham; Chang-Claude, Jenny; Conti, David V.; Curtis, Keith R.; Duggan, David; Gallinger, Steven; Haile, Robert W.; Harrison, Tabitha A.; Hayes, Richard B.; Hoffmeister, Michael; Hopper, John L.; Hudson, Thomas J.; Jenkins, Mark A.; Küry, Sébastien; Le Marchand, Loic; Leal, Suzanne M.; Newcomb, Polly A.; Nickerson, Deborah A.; Potter, John D.; Schoen, Robert E.; Schumacher, Fredrick R.; Seminara, Daniela; Slattery, Martha L.; Hsu, Li; Chan, Andrew T.; White, Emily; Berndt, Sonja I.; Peters, Ulrike

2016-01-01

Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) associated with colorectal cancer risk. These SNPs may tag correlated variants with biological importance. Fine-mapping around GWAS loci can facilitate detection of functional candidates and additional independent risk variants. We analyzed 11,900 cases and 14,311 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. To fine-map genomic regions containing all known common risk variants, we imputed high-density genetic data from the 1000 Genomes Project. We tested single-variant associations with colorectal tumor risk for all variants spanning genomic regions 250-kb upstream or downstream of 31 GWAS-identified SNPs (index SNPs). We queried the University of California, Santa Cruz Genome Browser to examine evidence for biological function. Index SNPs did not show the strongest association signals with colorectal tumor risk in their respective genomic regions. Bioinformatics analysis of SNPs showing smaller P-values in each region revealed 21 functional candidates in 12 loci (5q31.1, 8q24, 11q13.4, 11q23, 12p13.32, 12q24.21, 14q22.2, 15q13, 18q21, 19q13.1, 20p12.3, and 20q13.33). We did not observe evidence of additional independent association signals in GWAS-identified regions. Our results support the utility of integrating data from comprehensive fine-mapping with expanding publicly available genomic databases to help clarify GWAS associations and identify functional candidates that warrant more onerous laboratory follow-up. Such efforts may aid the eventual discovery of disease-causing variant(s). PMID:27379672

Establishing the role of rare coding variants in known Parkinson's disease risk loci.

PubMed

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.

Kant on causal laws and powers.

PubMed

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.

Fine-mapping inflammatory bowel disease loci to single variant resolution

PubMed Central

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

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

PubMed

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.

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

PubMed Central

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

Partial Granger causality--eliminating exogenous inputs and latent variables.

PubMed

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.

Mendelian randomization analyses in cardiometabolic disease: challenges in evaluating causality

PubMed Central

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

Using whole-exome sequencing to identify variants inherited from mosaic parents

PubMed Central

Rios, Jonathan J; Delgado, Mauricio R

2015-01-01

Whole-exome sequencing (WES) has allowed the discovery of genes and variants causing rare human disease. This is often achieved by comparing nonsynonymous variants between unrelated patients, and particularly for sporadic or recessive disease, often identifies a single or few candidate genes for further consideration. However, despite the potential for this approach to elucidate the genetic cause of rare human disease, a majority of patients fail to realize a genetic diagnosis using standard exome analysis methods. Although genetic heterogeneity contributes to the difficulty of exome sequence analysis between patients, it remains plausible that rare human disease is not caused by de novo or recessive variants. Multiple human disorders have been described for which the variant was inherited from a phenotypically normal mosaic parent. Here we highlight the potential for exome sequencing to identify a reasonable number of candidate genes when dominant disease variants are inherited from a mosaic parent. We show the power of WES to identify a limited number of candidate genes using this disease model and how sequence coverage affects identification of mosaic variants by WES. We propose this analysis as an alternative to discover genetic causes of rare human disorders for which typical WES approaches fail to identify likely pathogenic variants. PMID:24986828

Knowing Who Dunnit: Infants Identify the Causal Agent in an Unseen Causal Interaction

ERIC Educational Resources Information Center

Saxe, Rebecca; Tzelnic, Tania; Carey, Susan

2007-01-01

Preverbal infants can represent the causal structure of events, including distinguishing the agentive and receptive roles and categorizing entities according to stable causal dispositions. This study investigated how infants combine these 2 kinds of causal inference. In Experiments 1 and 2, 9.5-month-olds used the position of a human hand or a…

Fine-mapping inflammatory bowel disease loci to single-variant resolution.

PubMed

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.

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

PubMed Central

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

Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease.

PubMed

Emdin, Connor A; Khera, Amit V; Chaffin, Mark; Klarin, Derek; Natarajan, Pradeep; Aragam, Krishna; Haas, Mary; Bick, Alexander; Zekavat, Seyedeh M; Nomura, Akihiro; Ardissino, Diego; Wilson, James G; Schunkert, Heribert; McPherson, Ruth; Watkins, Hugh; Elosua, Roberto; Bown, Matthew J; Samani, Nilesh J; Baber, Usman; Erdmann, Jeanette; Gupta, Namrata; Danesh, John; Chasman, Daniel; Ridker, Paul; Denny, Joshua; Bastarache, Lisa; Lichtman, Judith H; D'Onofrio, Gail; Mattera, Jennifer; Spertus, John A; Sheu, Wayne H-H; Taylor, Kent D; Psaty, Bruce M; Rich, Stephen S; Post, Wendy; Rotter, Jerome I; Chen, Yii-Der Ida; Krumholz, Harlan; Saleheen, Danish; Gabriel, Stacey; Kathiresan, Sekar

2018-04-24

Less than 3% of protein-coding genetic variants are predicted to result in loss of protein function through the introduction of a stop codon, frameshift, or the disruption of an essential splice site; however, such predicted loss-of-function (pLOF) variants provide insight into effector transcript and direction of biological effect. In >400,000 UK Biobank participants, we conduct association analyses of 3759 pLOF variants with six metabolic traits, six cardiometabolic diseases, and twelve additional diseases. We identified 18 new low-frequency or rare (allele frequency < 5%) pLOF variant-phenotype associations. pLOF variants in the gene GPR151 protect against obesity and type 2 diabetes, in the gene IL33 against asthma and allergic disease, and in the gene IFIH1 against hypothyroidism. In the gene PDE3B, pLOF variants associate with elevated height, improved body fat distribution and protection from coronary artery disease. Our findings prioritize genes for which pharmacologic mimics of pLOF variants may lower risk for disease.

Identifying direct miRNA-mRNA causal regulatory relationships in heterogeneous data.

PubMed

Zhang, Junpeng; Le, Thuc Duy; Liu, Lin; Liu, Bing; He, Jianfeng; Goodall, Gregory J; Li, Jiuyong

2014-12-01

Discovering the regulatory relationships between microRNAs (miRNAs) and mRNAs is an important problem that interests many biologists and medical researchers. A number of computational methods have been proposed to infer miRNA-mRNA regulatory relationships, and are mostly based on the statistical associations between miRNAs and mRNAs discovered in observational data. The miRNA-mRNA regulatory relationships identified by these methods can be both direct and indirect regulations. However, differentiating direct regulatory relationships from indirect ones is important for biologists in experimental designs. In this paper, we present a causal discovery based framework (called DirectTarget) to infer direct miRNA-mRNA causal regulatory relationships in heterogeneous data, including expression profiles of miRNAs and mRNAs, and miRNA target information. DirectTarget is applied to the Epithelial to Mesenchymal Transition (EMT) datasets. The validation by experimentally confirmed target databases suggests that the proposed method can effectively identify direct miRNA-mRNA regulatory relationships. To explore the upstream regulators of miRNA regulation, we further identify the causal feedforward patterns (CFFPs) of TF-miRNA-mRNA to provide insights into the miRNA regulation in EMT. DirectTarget has the potential to be applied to other datasets to elucidate the direct miRNA-mRNA causal regulatory relationships and to explore the regulatory patterns. Copyright © 2014 Elsevier Inc. All rights reserved.

Classification of BRCA1 missense variants of unknown clinical significance

PubMed Central

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

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

PubMed Central

Beecham, Ashley H; Patsopoulos, Nikolaos A; Xifara, Dionysia K; Davis, Mary F; Kemppinen, Anu; Cotsapas, Chris; Shahi, Tejas S; Spencer, Chris; Booth, David; Goris, An; Oturai, Annette; Saarela, Janna; Fontaine, Bertrand; Hemmer, Bernhard; Martin, Claes; Zipp, Frauke; D’alfonso, Sandra; Martinelli-Boneschi, Filippo; Taylor, Bruce; Harbo, Hanne F; Kockum, Ingrid; Hillert, Jan; Olsson, Tomas; Ban, Maria; Oksenberg, Jorge R; Hintzen, Rogier; Barcellos, Lisa F; Agliardi, Cristina; Alfredsson, Lars; Alizadeh, Mehdi; Anderson, Carl; Andrews, Robert; Søndergaard, Helle Bach; Baker, Amie; Band, Gavin; Baranzini, Sergio E; Barizzone, Nadia; Barrett, Jeffrey; Bellenguez, Céline; Bergamaschi, Laura; Bernardinelli, Luisa; Berthele, Achim; Biberacher, Viola; Binder, Thomas M C; Blackburn, Hannah; Bomfim, Izaura L; Brambilla, Paola; Broadley, Simon; Brochet, Bruno; Brundin, Lou; Buck, Dorothea; Butzkueven, Helmut; Caillier, Stacy J; Camu, William; Carpentier, Wassila; Cavalla, Paola; Celius, Elisabeth G; Coman, Irène; Comi, Giancarlo; Corrado, Lucia; Cosemans, Leentje; Cournu-Rebeix, Isabelle; Cree, Bruce A C; Cusi, Daniele; Damotte, Vincent; Defer, Gilles; Delgado, Silvia R; Deloukas, Panos; di Sapio, Alessia; Dilthey, Alexander T; Donnelly, Peter; Dubois, Bénédicte; Duddy, Martin; Edkins, Sarah; Elovaara, Irina; Esposito, Federica; Evangelou, Nikos; Fiddes, Barnaby; Field, Judith; Franke, Andre; Freeman, Colin; Frohlich, Irene Y; Galimberti, Daniela; Gieger, Christian; Gourraud, Pierre-Antoine; Graetz, Christiane; Graham, Andrew; Grummel, Verena; Guaschino, Clara; Hadjixenofontos, Athena; Hakonarson, Hakon; Halfpenny, Christopher; Hall, Gillian; Hall, Per; Hamsten, Anders; Harley, James; Harrower, Timothy; Hawkins, Clive; Hellenthal, Garrett; Hillier, Charles; Hobart, Jeremy; Hoshi, Muni; Hunt, Sarah E; Jagodic, Maja; Jelčić, Ilijas; Jochim, Angela; Kendall, Brian; Kermode, Allan; Kilpatrick, Trevor; Koivisto, Keijo; Konidari, Ioanna; Korn, Thomas; Kronsbein, Helena; Langford, Cordelia; Larsson, Malin; Lathrop, Mark; Lebrun-Frenay, Christine; Lechner-Scott, Jeannette; Lee, Michelle H; Leone, Maurizio A; Leppä, Virpi; Liberatore, Giuseppe; Lie, Benedicte A; Lill, Christina M; Lindén, Magdalena; Link, Jenny; Luessi, Felix; Lycke, Jan; Macciardi, Fabio; Männistö, Satu; Manrique, Clara P; Martin, Roland; Martinelli, Vittorio; Mason, Deborah; Mazibrada, Gordon; McCabe, Cristin; Mero, Inger-Lise; Mescheriakova, Julia; Moutsianas, Loukas; Myhr, Kjell-Morten; Nagels, Guy; Nicholas, Richard; Nilsson, Petra; Piehl, Fredrik; Pirinen, Matti; Price, Siân E; Quach, Hong; Reunanen, Mauri; Robberecht, Wim; Robertson, Neil P; Rodegher, Mariaemma; Rog, David; Salvetti, Marco; Schnetz-Boutaud, Nathalie C; Sellebjerg, Finn; Selter, Rebecca C; Schaefer, Catherine; Shaunak, Sandip; Shen, Ling; Shields, Simon; Siffrin, Volker; Slee, Mark; Sorensen, Per Soelberg; Sorosina, Melissa; Sospedra, Mireia; Spurkland, Anne; Strange, Amy; Sundqvist, Emilie; Thijs, Vincent; Thorpe, John; Ticca, Anna; Tienari, Pentti; van Duijn, Cornelia; Visser, Elizabeth M; Vucic, Steve; Westerlind, Helga; Wiley, James S; Wilkins, Alastair; Wilson, James F; Winkelmann, Juliane; Zajicek, John; Zindler, Eva; Haines, Jonathan L; Pericak-Vance, Margaret A; Ivinson, Adrian J; Stewart, Graeme; Hafler, David; Hauser, Stephen L; Compston, Alastair; McVean, Gil; De Jager, Philip; Sawcer, Stephen; McCauley, Jacob L

2013-01-01

Using the ImmunoChip custom genotyping array, we analysed 14,498 multiple sclerosis subjects and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (p-value < 1.0 × 10-4). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 multiple sclerosis subjects and 26,703 healthy controls. In these 80,094 individuals of European ancestry we identified 48 new susceptibility variants (p-value < 5.0 × 10-8); three found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants in 103 discrete loci outside of the Major Histocompatibility Complex. With high resolution Bayesian fine-mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalogue of multiple sclerosis risk variants and illustrates the value of fine-mapping in the resolution of GWAS signals. PMID:24076602

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

PubMed

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.

GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits.

PubMed

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.

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways

PubMed Central

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

Admixture Mapping in Lupus Identifies Multiple Functional Variants within IFIH1 Associated with Apoptosis, Inflammation, and Autoantibody Production

PubMed Central

Looger, Loren L.; Han, Shizhong; Kim-Howard, Xana; Glenn, Stuart; Adler, Adam; Kelly, Jennifer A.; Niewold, Timothy B.; Gilkeson, Gary S.; Brown, Elizabeth E.; Alarcón, Graciela S.; Edberg, Jeffrey C.; Petri, Michelle; Ramsey-Goldman, Rosalind; Reveille, John D.; Vilá, Luis M.; Freedman, Barry I.; Tsao, Betty P.; Criswell, Lindsey A.; Jacob, Chaim O.; Moore, Jason H.; Vyse, Timothy J.; Langefeld, Carl L.; Guthridge, Joel M.; Gaffney, Patrick M.; Moser, Kathy L.; Scofield, R. Hal; Alarcón-Riquelme, Marta E.; Williams, Scott M.; Merrill, Joan T.; James, Judith A.; Kaufman, Kenneth M.; Kimberly, Robert P.; Harley, John B.; Nath, Swapan K.

2013-01-01

Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease with a strong genetic component. African-Americans (AA) are at increased risk of SLE, but the genetic basis of this risk is largely unknown. To identify causal variants in SLE loci in AA, we performed admixture mapping followed by fine mapping in AA and European-Americans (EA). Through genome-wide admixture mapping in AA, we identified a strong SLE susceptibility locus at 2q22–24 (LOD = 6.28), and the admixture signal is associated with the European ancestry (ancestry risk ratio ∼1.5). Large-scale genotypic analysis on 19,726 individuals of African and European ancestry revealed three independently associated variants in the IFIH1 gene: an intronic variant, rs13023380 [Pmeta = 5.20×10−14; odds ratio, 95% confidence interval = 0.82 (0.78–0.87)], and two missense variants, rs1990760 (Ala946Thr) [Pmeta = 3.08×10−7; 0.88 (0.84–0.93)] and rs10930046 (Arg460His) [Pdom = 1.16×10−8; 0.70 (0.62–0.79)]. Both missense variants produced dramatic phenotypic changes in apoptosis and inflammation-related gene expression. We experimentally validated function of the intronic SNP by DNA electrophoresis, protein identification, and in vitro protein binding assays. DNA carrying the intronic risk allele rs13023380 showed reduced binding efficiency to a cellular protein complex including nucleolin and lupus autoantigen Ku70/80, and showed reduced transcriptional activity in vivo. Thus, in SLE patients, genetic susceptibility could create a biochemical imbalance that dysregulates nucleolin, Ku70/80, or other nucleic acid regulatory proteins. This could promote antibody hypermutation and auto-antibody generation, further destabilizing the cellular network. Together with molecular modeling, our results establish a distinct role for IFIH1 in apoptosis, inflammation, and autoantibody production, and explain the molecular basis of these three risk alleles for SLE pathogenesis. PMID

Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer

PubMed Central

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

Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer.

PubMed

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.

Causal network analysis of head and neck keloid tissue identifies potential master regulators.

PubMed

Garcia-Rodriguez, Laura; Jones, Lamont; Chen, Kang Mei; Datta, Indrani; Divine, George; Worsham, Maria J

2016-10-01

To generate novel insights and hypotheses in keloid development from potential master regulators. Prospective cohort. Six fresh keloid and six normal skin samples from 12 anonymous donors were used in a prospective cohort study. Genome-wide profiling was done previously on the cohort using the Infinium HumanMethylation450 BeadChip (Illumina, San Diego, CA). The 190 statistically significant CpG islands between keloid and normal tissue mapped to 152 genes (P < .05). The top 10 statistically significant genes (VAMP5, ACTR3C, GALNT3, KCNAB2, LRRC61, SCML4, SYNGR1, TNS1, PLEKHG5, PPP1R13-α, false discovery rate <.015) were uploaded into the Ingenuity Pathway Analysis software's Causal Network Analysis (QIAGEN, Redwood City, CA). To reflect expected gene expression direction in the context of methylation changes, the inverse of the methylation ratio from keloid versus normal tissue was used for the analysis. Causal Network Analysis identified disease-specific master regulator molecules based on downstream differentially expressed keloid-specific genes and expected directionality of expression (hypermethylated vs. hypomethylated). Causal Network Analysis software identified four hierarchical networks that included four master regulators (pyroxamide, tributyrin, PRKG2, and PENK) and 19 intermediate regulators. Causal Network Analysis of differentiated methylated gene data of keloid versus normal skin demonstrated four causal networks with four master regulators. These hierarchical networks suggest potential driver roles for their downstream keloid gene targets in the pathogenesis of the keloid phenotype, likely triggered due to perturbation/injury to normal tissue. NA Laryngoscope, 126:E319-E324, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Nonsyndromic cleft lip with or without cleft palate: Increased burden of rare variants within Gremlin-1, a component of the bone morphogenetic protein 4 pathway.

PubMed

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.

A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome

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...

Comprehensive genotyping in dyslipidemia: mendelian dyslipidemias caused by rare variants and Mendelian randomization studies using common variants.

PubMed

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.

A splice variant in the ACSL5 gene relates migraine with fatty acid activation in mitochondria

PubMed Central

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

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...

Genome-wide association analysis and replication of coronary artery disease in South Korea suggests a causal variant common to diverse populations

PubMed Central

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

Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine

PubMed Central

2016-01-01

Advances in genomic medicine have the potential to change the way we treat human disease, but translating these advances into reality for improving healthcare outcomes depends essentially on our ability to discover disease- and/or drug-associated clinically actionable genetic mutations. Integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a big data infrastructure can provide an efficient and effective way to identify clinically actionable genetic variants for personalized treatments and reduce healthcare costs. We review bioinformatics processing of next-generation sequencing (NGS) data, bioinformatics infrastructures for implementing precision medicine, and bioinformatics approaches for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs. PMID:27195526

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Investigating genetic correlations and causal effects between caffeine consumption and sleep behaviours.

PubMed

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

Utilizing population controls in rare-variant case-parent association tests.

PubMed

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.

Under What Assumptions Do Site-by-Treatment Instruments Identify Average Causal Effects?

ERIC Educational Resources Information Center

Reardon, Sean F.; Raudenbush, Stephen W.

2011-01-01

The purpose of this paper is to clarify the assumptions that must be met if this--multiple site, multiple mediator--strategy, hereafter referred to as "MSMM," is to identify the average causal effects (ATE) in the populations of interest. The authors' investigation of the assumptions of the multiple-mediator, multiple-site IV model demonstrates…

Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia

PubMed Central

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

Instrumental variable approaches to identifying the causal effect of educational attainment on dementia risk

PubMed Central

Nguyen, Thu T.; Tchetgen Tchetgen, Eric J.; Kawachi, Ichiro; Gilman, Stephen E.; Walter, Stefan; Liu, Sze Y.; Manly, Jennifer; Glymour, M. Maria

2015-01-01

Purpose Education is an established correlate of cognitive status in older adulthood, but whether expanding educational opportunities would improve cognitive functioning remains unclear given limitations of prior studies for causal inference. Therefore, we conducted instrumental variable (IV) analyses of the association between education and dementia risk, using for the first time in this area, genetic variants as instruments as well as state-level school policies. Methods IV analyses in the Health and Retirement Study cohort (1998–2010) used two sets of instruments: 1) a genetic risk score constructed from three single nucleotide polymorphisms (SNPs) (n=8,054); and 2) compulsory schooling laws (CSLs) and state school characteristics (term length, student teacher ratios, and expenditures) (n=13,167). Results Employing the genetic risk score as an IV, there was a 1.1% reduction in dementia risk per year of schooling (95% CI: −2.4, 0.02). Leveraging compulsory schooling laws and state school characteristics as IVs, there was a substantially larger protective effect (−9.5%; 95% CI: −14.8, −4.2). Analyses evaluating the plausibility of the IV assumptions indicated estimates derived from analyses relying on CSLs provide the best estimates of the causal effect of education. Conclusion IV analyses suggest education is protective against risk of dementia in older adulthood. PMID:26633592

Exome analysis of Smith-Magenis-like syndrome cohort identifies de novo likely pathogenic variants.

PubMed

Berger, Seth I; Ciccone, Carla; Simon, Karen L; Malicdan, May Christine; Vilboux, Thierry; Billington, Charles; Fischer, Roxanne; Introne, Wendy J; Gropman, Andrea; Blancato, Jan K; Mullikin, James C; Gahl, William A; Huizing, Marjan; Smith, Ann C M

2017-04-01

Smith-Magenis syndrome (SMS), a neurodevelopmental disorder characterized by dysmorphic features, intellectual disability (ID), and sleep disturbances, results from a 17p11.2 microdeletion or a mutation in the RAI1 gene. We performed exome sequencing on 6 patients with SMS-like phenotypes but without chromosomal abnormalities or RAI1 variants. We identified pathogenic de novo variants in two cases, a nonsense variant in IQSEC2 and a missense variant in the SAND domain of DEAF1, and candidate de novo missense variants in an additional two cases. One candidate variant was located in an alpha helix of Necdin (NDN), phased to the paternally inherited allele. NDN is maternally imprinted within the 15q11.2 Prader-Willi Syndrome (PWS) region. This can help clarify NDN's role in the PWS phenotype. No definitive pathogenic gene variants were detected in the remaining SMS-like cases, but we report our findings for future comparison. This study provides information about the inheritance pattern and recurrence risk for patients with identified variants and demonstrates clinical and genetic overlap of neurodevelopmental disorders. Identification and characterization of ID-related genes that assist in development of common developmental pathways and/or gene-networks, may inform disease mechanism and treatment strategies.

Identifying Causal Risk Factors for Violence among Discharged Patients

PubMed Central

Coid, Jeremy W.; Kallis, Constantinos; Doyle, Mike; Shaw, Jenny; Ullrich, Simone

2015-01-01

Background Structured Professional Judgement (SPJ) is routinely administered in mental health and criminal justice settings but cannot identify violence risk above moderate accuracy. There is no current evidence that violence can be prevented using SPJ. This may be explained by routine application of predictive instead of causal statistical models when standardising SPJ instruments. Methods We carried out a prospective cohort study of 409 male and female patients discharged from medium secure services in England and Wales to the community. Measures were taken at baseline (pre-discharge), 6 and 12 months post-discharge using the Historical, Clinical and Risk-20 items version 3 (HCR-20v3) and Structural Assessment of Protective Factors (SAPROF). Information on violence was obtained via the McArthur community violence instrument and the Police National Computer. Results In a lagged model, HCR-20v3 and SAPROF items were poor predictors of violence. Eight items of the HCR-20v3 and 4 SAPROF items did not predict violent behaviour better than chance. In re-analyses considering temporal proximity of risk/ protective factors (exposure) on violence (outcome), risk was elevated due to violent ideation (OR 6.98, 95% CI 13.85–12.65, P<0.001), instability (OR 5.41, 95% CI 3.44–8.50, P<0.001), and poor coping/ stress (OR 8.35, 95% CI 4.21–16.57, P<0.001). All 3 risk factors were explanatory variables which drove the association with violent outcome. Self-control (OR 0.13, 95% CI 0.08–0.24, P<0.001) conveyed protective effects and explained the association of other protective factors with violence. Conclusions Using two standardised SPJ instruments, predictive (lagged) methods could not identify risk and protective factors which must be targeted in interventions for discharged patients with severe mental illness. Predictive methods should be abandoned if the aim is to progress from risk assessment to effective risk management and replaced by methods which identify factors

Illustrating, Quantifying, and Correcting for Bias in Post-hoc Analysis of Gene-Based Rare Variant Tests of Association

PubMed Central

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

Causality networks from multivariate time series and application to epilepsy.

PubMed

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.

Dynamics and causalities of atmospheric and oceanic data identified by complex networks and Granger causality analysis

NASA Astrophysics Data System (ADS)

Charakopoulos, A. K.; Katsouli, G. A.; Karakasidis, T. E.

2018-04-01

Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly established. The purpose of this study was to examine the performance of two main additional methodologies for the identification of spatiotemporal underlying dynamic characteristics and patterns among atmospheric and oceanic variables from Seawatch buoys from Aegean and Ionian Sea, provided by the Hellenic Center for Marine Research (HCMR). The first approach involves the estimation of cross correlation analysis in an attempt to investigate time-lagged relationships, and further in order to identify the direction of interactions between the variables we performed the Granger causality method. According to the second approach the time series are converted into complex networks and then the main topological network properties such as degree distribution, average path length, diameter, modularity and clustering coefficient are evaluated. Our results show that the proposed analysis of complex network analysis of time series can lead to the extraction of hidden spatiotemporal characteristics. Also our findings indicate high level of positive and negative correlations and causalities among variables, both from the same buoy and also between buoys from different stations, which cannot be determined from the use of simple statistical measures.

Whole-Exome Sequencing Identifies Rare and Low-Frequency Coding Variants Associated with LDL Cholesterol

PubMed Central

Lange, Leslie A.; Hu, Youna; Zhang, He; Xue, Chenyi; Schmidt, Ellen M.; Tang, Zheng-Zheng; Bizon, Chris; Lange, Ethan M.; Smith, Joshua D.; Turner, Emily H.; Jun, Goo; Kang, Hyun Min; Peloso, Gina; Auer, Paul; Li, Kuo-ping; Flannick, Jason; Zhang, Ji; Fuchsberger, Christian; Gaulton, Kyle; Lindgren, Cecilia; Locke, Adam; Manning, Alisa; Sim, Xueling; Rivas, Manuel A.; Holmen, Oddgeir L.; Gottesman, Omri; Lu, Yingchang; Ruderfer, Douglas; Stahl, Eli A.; Duan, Qing; Li, Yun; Durda, Peter; Jiao, Shuo; Isaacs, Aaron; Hofman, Albert; Bis, Joshua C.; Correa, Adolfo; Griswold, Michael E.; Jakobsdottir, Johanna; Smith, Albert V.; Schreiner, Pamela J.; Feitosa, Mary F.; Zhang, Qunyuan; Huffman, Jennifer E.; Crosby, Jacy; Wassel, Christina L.; Do, Ron; Franceschini, Nora; Martin, Lisa W.; Robinson, Jennifer G.; Assimes, Themistocles L.; Crosslin, David R.; Rosenthal, Elisabeth A.; Tsai, Michael; Rieder, Mark J.; Farlow, Deborah N.; Folsom, Aaron R.; Lumley, Thomas; Fox, Ervin R.; Carlson, Christopher S.; Peters, Ulrike; Jackson, Rebecca D.; van Duijn, Cornelia M.; Uitterlinden, André G.; Levy, Daniel; Rotter, Jerome I.; Taylor, Herman A.; Gudnason, Vilmundur; Siscovick, David S.; Fornage, Myriam; Borecki, Ingrid B.; Hayward, Caroline; Rudan, Igor; Chen, Y. Eugene; Bottinger, Erwin P.; Loos, Ruth J.F.; Sætrom, Pål; Hveem, Kristian; Boehnke, Michael; Groop, Leif; McCarthy, Mark; Meitinger, Thomas; Ballantyne, Christie M.; Gabriel, Stacey B.; O’Donnell, Christopher J.; Post, Wendy S.; North, Kari E.; Reiner, Alexander P.; Boerwinkle, Eric; Psaty, Bruce M.; Altshuler, David; Kathiresan, Sekar; Lin, Dan-Yu; Jarvik, Gail P.; Cupples, L. Adrienne; Kooperberg, Charles; Wilson, James G.; Nickerson, Deborah A.; Abecasis, Goncalo R.; Rich, Stephen S.; Tracy, Russell P.; Willer, Cristen J.; Gabriel, Stacey B.; Altshuler, David M.; Abecasis, Gonçalo R.; Allayee, Hooman; Cresci, Sharon; Daly, Mark J.; de Bakker, Paul I.W.; DePristo, Mark A.; Do, Ron; Donnelly, Peter; Farlow, Deborah N.; Fennell, Tim; Garimella, Kiran; Hazen, Stanley L.; Hu, Youna; Jordan, Daniel M.; Jun, Goo; Kathiresan, Sekar; Kang, Hyun Min; Kiezun, Adam; Lettre, Guillaume; Li, Bingshan; Li, Mingyao; Newton-Cheh, Christopher H.; Padmanabhan, Sandosh; Peloso, Gina; Pulit, Sara; Rader, Daniel J.; Reich, David; Reilly, Muredach P.; Rivas, Manuel A.; Schwartz, Steve; Scott, Laura; Siscovick, David S.; Spertus, John A.; Stitziel, Nathaniel O.; Stoletzki, Nina; Sunyaev, Shamil R.; Voight, Benjamin F.; Willer, Cristen J.; Rich, Stephen S.; Akylbekova, Ermeg; Atwood, Larry D.; Ballantyne, Christie M.; Barbalic, Maja; Barr, R. Graham; Benjamin, Emelia J.; Bis, Joshua; Boerwinkle, Eric; Bowden, Donald W.; Brody, Jennifer; Budoff, Matthew; Burke, Greg; Buxbaum, Sarah; Carr, Jeff; Chen, Donna T.; Chen, Ida Y.; Chen, Wei-Min; Concannon, Pat; Crosby, Jacy; Cupples, L. Adrienne; D’Agostino, Ralph; DeStefano, Anita L.; Dreisbach, Albert; Dupuis, Josée; Durda, J. Peter; Ellis, Jaclyn; Folsom, Aaron R.; Fornage, Myriam; Fox, Caroline S.; Fox, Ervin; Funari, Vincent; Ganesh, Santhi K.; Gardin, Julius; Goff, David; Gordon, Ora; Grody, Wayne; Gross, Myron; Guo, Xiuqing; Hall, Ira M.; Heard-Costa, Nancy L.; Heckbert, Susan R.; Heintz, Nicholas; Herrington, David M.; Hickson, DeMarc; Huang, Jie; Hwang, Shih-Jen; Jacobs, David R.; Jenny, Nancy S.; Johnson, Andrew D.; Johnson, Craig W.; Kawut, Steven; Kronmal, Richard; Kurz, Raluca; Lange, Ethan M.; Lange, Leslie A.; Larson, Martin G.; Lawson, Mark; Lewis, Cora E.; Levy, Daniel; Li, Dalin; Lin, Honghuang; Liu, Chunyu; Liu, Jiankang; Liu, Kiang; Liu, Xiaoming; Liu, Yongmei; Longstreth, William T.; Loria, Cay; Lumley, Thomas; Lunetta, Kathryn; Mackey, Aaron J.; Mackey, Rachel; Manichaikul, Ani; Maxwell, Taylor; McKnight, Barbara; Meigs, James B.; Morrison, Alanna C.; Musani, Solomon K.; Mychaleckyj, Josyf C.; Nettleton, Jennifer A.; North, Kari; O’Donnell, Christopher J.; O’Leary, Daniel; Ong, Frank; Palmas, Walter; Pankow, James S.; Pankratz, Nathan D.; Paul, Shom; Perez, Marco; Person, Sharina D.; Polak, Joseph; Post, Wendy S.; Psaty, Bruce M.; Quinlan, Aaron R.; Raffel, Leslie J.; Ramachandran, Vasan S.; Reiner, Alexander P.; Rice, Kenneth; Rotter, Jerome I.; Sanders, Jill P.; Schreiner, Pamela; Seshadri, Sudha; Shea, Steve; Sidney, Stephen; Silverstein, Kevin; Smith, Nicholas L.; Sotoodehnia, Nona; Srinivasan, Asoke; Taylor, Herman A.; Taylor, Kent; Thomas, Fridtjof; Tracy, Russell P.; Tsai, Michael Y.; Volcik, Kelly A.; Wassel, Chrstina L.; Watson, Karol; Wei, Gina; White, Wendy; Wiggins, Kerri L.; Wilk, Jemma B.; Williams, O. Dale; Wilson, Gregory; Wilson, James G.; Wolf, Phillip; Zakai, Neil A.; Hardy, John; Meschia, James F.; Nalls, Michael; Singleton, Andrew; Worrall, Brad; Bamshad, Michael J.; Barnes, Kathleen C.; Abdulhamid, Ibrahim; Accurso, Frank; Anbar, Ran; Beaty, Terri; Bigham, Abigail; Black, Phillip; Bleecker, Eugene; Buckingham, Kati; Cairns, Anne Marie; Caplan, Daniel; Chatfield, Barbara; Chidekel, Aaron; Cho, Michael; Christiani, David C.; Crapo, James D.; Crouch, Julia; Daley, Denise; Dang, Anthony; Dang, Hong; De Paula, Alicia; DeCelie-Germana, Joan; Drumm, Allen DozorMitch; Dyson, Maynard; Emerson, Julia; Emond, Mary J.; Ferkol, Thomas; Fink, Robert; Foster, Cassandra; Froh, Deborah; Gao, Li; Gershan, William; Gibson, Ronald L.; Godwin, Elizabeth; Gondor, Magdalen; Gutierrez, Hector; Hansel, Nadia N.; Hassoun, Paul M.; Hiatt, Peter; Hokanson, John E.; Howenstine, Michelle; Hummer, Laura K.; Kanga, Jamshed; Kim, Yoonhee; Knowles, Michael R.; Konstan, Michael; Lahiri, Thomas; Laird, Nan; Lange, Christoph; Lin, Lin; Lin, Xihong; Louie, Tin L.; Lynch, David; Make, Barry; Martin, Thomas R.; Mathai, Steve C.; Mathias, Rasika A.; McNamara, John; McNamara, Sharon; Meyers, Deborah; Millard, Susan; Mogayzel, Peter; Moss, Richard; Murray, Tanda; Nielson, Dennis; Noyes, Blakeslee; O’Neal, Wanda; Orenstein, David; O’Sullivan, Brian; Pace, Rhonda; Pare, Peter; Parker, H. Worth; Passero, Mary Ann; Perkett, Elizabeth; Prestridge, Adrienne; Rafaels, Nicholas M.; Ramsey, Bonnie; Regan, Elizabeth; Ren, Clement; Retsch-Bogart, George; Rock, Michael; Rosen, Antony; Rosenfeld, Margaret; Ruczinski, Ingo; Sanford, Andrew; Schaeffer, David; Sell, Cindy; Sheehan, Daniel; Silverman, Edwin K.; Sin, Don; Spencer, Terry; Stonebraker, Jackie; Tabor, Holly K.; Varlotta, Laurie; Vergara, Candelaria I.; Weiss, Robert; Wigley, Fred; Wise, Robert A.; Wright, Fred A.; Wurfel, Mark M.; Zanni, Robert; Zou, Fei; Nickerson, Deborah A.; Rieder, Mark J.; Green, Phil; Shendure, Jay; Akey, Joshua M.; Bustamante, Carlos D.; Crosslin, David R.; Eichler, Evan E.; Fox, P. Keolu; Fu, Wenqing; Gordon, Adam; Gravel, Simon; Jarvik, Gail P.; Johnsen, Jill M.; Kan, Mengyuan; Kenny, Eimear E.; Kidd, Jeffrey M.; Lara-Garduno, Fremiet; Leal, Suzanne M.; Liu, Dajiang J.; McGee, Sean; O’Connor, Timothy D.; Paeper, Bryan; Robertson, Peggy D.; Smith, Joshua D.; Staples, Jeffrey C.; Tennessen, Jacob A.; Turner, Emily H.; Wang, Gao; Yi, Qian; Jackson, Rebecca; Peters, Ulrike; Carlson, Christopher S.; Anderson, Garnet; Anton-Culver, Hoda; Assimes, Themistocles L.; Auer, Paul L.; Beresford, Shirley; Bizon, Chris; Black, Henry; Brunner, Robert; Brzyski, Robert; Burwen, Dale; Caan, Bette; Carty, Cara L.; Chlebowski, Rowan; Cummings, Steven; Curb, J. David; Eaton, Charles B.; Ford, Leslie; Franceschini, Nora; Fullerton, Stephanie M.; Gass, Margery; Geller, Nancy; Heiss, Gerardo; Howard, Barbara V.; Hsu, Li; Hutter, Carolyn M.; Ioannidis, John; Jiao, Shuo; Johnson, Karen C.; Kooperberg, Charles; Kuller, Lewis; LaCroix, Andrea; Lakshminarayan, Kamakshi; Lane, Dorothy; Lasser, Norman; LeBlanc, Erin; Li, Kuo-Ping; Limacher, Marian; Lin, Dan-Yu; Logsdon, Benjamin A.; Ludlam, Shari; Manson, JoAnn E.; Margolis, Karen; Martin, Lisa; McGowan, Joan; Monda, Keri L.; Kotchen, Jane Morley; Nathan, Lauren; Ockene, Judith; O’Sullivan, Mary Jo; Phillips, Lawrence S.; Prentice, Ross L.; Robbins, John; Robinson, Jennifer G.; Rossouw, Jacques E.; Sangi-Haghpeykar, Haleh; Sarto, Gloria E.; Shumaker, Sally; Simon, Michael S.; Stefanick, Marcia L.; Stein, Evan; Tang, Hua; Taylor, Kira C.; Thomson, Cynthia A.; Thornton, Timothy A.; Van Horn, Linda; Vitolins, Mara; Wactawski-Wende, Jean; Wallace, Robert; Wassertheil-Smoller, Sylvia; Zeng, Donglin; Applebaum-Bowden, Deborah; Feolo, Michael; Gan, Weiniu; Paltoo, Dina N.; Sholinsky, Phyliss; Sturcke, Anne

2014-01-01

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98th or <2nd percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments. PMID:24507775

Emerging applications of genome-editing technology to examine functionality of GWAS-associated variants for complex traits.

PubMed

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.

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.

Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors.

PubMed

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.

Large-Scale Gene-Centric Analysis Identifies Novel Variants for Coronary Artery Disease

PubMed Central

2011-01-01

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ∼2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10−33; LPA:p<10−19; 1p13.3:p<10−17) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10−7). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06–1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ∼4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and

Large-scale gene-centric analysis identifies novel variants for coronary artery disease.

PubMed

2011-09-01

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ∼2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10(-33); LPA:p<10(-19); 1p13.3:p<10(-17)) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10(-7)). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06-1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ∼4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and

Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.

PubMed

Lange, Leslie A; Hu, Youna; Zhang, He; Xue, Chenyi; Schmidt, Ellen M; Tang, Zheng-Zheng; Bizon, Chris; Lange, Ethan M; Smith, Joshua D; Turner, Emily H; Jun, Goo; Kang, Hyun Min; Peloso, Gina; Auer, Paul; Li, Kuo-Ping; Flannick, Jason; Zhang, Ji; Fuchsberger, Christian; Gaulton, Kyle; Lindgren, Cecilia; Locke, Adam; Manning, Alisa; Sim, Xueling; Rivas, Manuel A; Holmen, Oddgeir L; Gottesman, Omri; Lu, Yingchang; Ruderfer, Douglas; Stahl, Eli A; Duan, Qing; Li, Yun; Durda, Peter; Jiao, Shuo; Isaacs, Aaron; Hofman, Albert; Bis, Joshua C; Correa, Adolfo; Griswold, Michael E; Jakobsdottir, Johanna; Smith, Albert V; Schreiner, Pamela J; Feitosa, Mary F; Zhang, Qunyuan; Huffman, Jennifer E; Crosby, Jacy; Wassel, Christina L; Do, Ron; Franceschini, Nora; Martin, Lisa W; Robinson, Jennifer G; Assimes, Themistocles L; Crosslin, David R; Rosenthal, Elisabeth A; Tsai, Michael; Rieder, Mark J; Farlow, Deborah N; Folsom, Aaron R; Lumley, Thomas; Fox, Ervin R; Carlson, Christopher S; Peters, Ulrike; Jackson, Rebecca D; van Duijn, Cornelia M; Uitterlinden, André G; Levy, Daniel; Rotter, Jerome I; Taylor, Herman A; Gudnason, Vilmundur; Siscovick, David S; Fornage, Myriam; Borecki, Ingrid B; Hayward, Caroline; Rudan, Igor; Chen, Y Eugene; Bottinger, Erwin P; Loos, Ruth J F; Sætrom, Pål; Hveem, Kristian; Boehnke, Michael; Groop, Leif; McCarthy, Mark; Meitinger, Thomas; Ballantyne, Christie M; Gabriel, Stacey B; O'Donnell, Christopher J; Post, Wendy S; North, Kari E; Reiner, Alexander P; Boerwinkle, Eric; Psaty, Bruce M; Altshuler, David; Kathiresan, Sekar; Lin, Dan-Yu; Jarvik, Gail P; Cupples, L Adrienne; Kooperberg, Charles; Wilson, James G; Nickerson, Deborah A; Abecasis, Goncalo R; Rich, Stephen S; Tracy, Russell P; Willer, Cristen J

2014-02-06

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

PubMed

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.

An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

PubMed Central

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

Pharmacological Validation of Candidate Causal Sleep Genes Identified in an N2 Cross

PubMed Central

Brunner, Joseph I.; Gotter, Anthony L.; Millstein, Joshua; Garson, Susan; Binns, Jacquelyn; Fox, Steven V.; Savitz, Alan T.; Yang, He S.; Fitzpatrick, Karrie; Zhou, Lili; Owens, Joseph R.; Webber, Andrea L.; Vitaterna, Martha H.; Kasarskis, Andrew; Uebele, Victor N.; Turek, Fred; Renger, John J.; Winrow, Christopher J.

2013-01-01

Despite the substantial impact of sleep disturbances on human health and the many years of study dedicated to understanding sleep pathologies, the underlying genetic mechanisms that govern sleep and wake largely remain unknown. Recently, we completed large scale genetic and gene expression analyses in a segregating inbred mouse cross and identified candidate causal genes that regulate the mammalian sleep-wake cycle, across multiple traits including total sleep time, amounts of REM, non-REM, sleep bout duration and sleep fragmentation. Here we describe a novel approach toward validating candidate causal genes, while also identifying potential targets for sleep-related indications. Select small molecule antagonists and agonists were used to interrogate candidate causal gene function in rodent sleep polysomnography assays to determine impact on overall sleep architecture and to evaluate alignment with associated sleep-wake traits. Significant effects on sleep architecture were observed in validation studies using compounds targeting the muscarinic acetylcholine receptor M3 subunit (Chrm3)(wake promotion), nicotinic acetylcholine receptor alpha4 subunit (Chrna4)(wake promotion), dopamine receptor D5 subunit (Drd5)(sleep induction), serotonin 1D receptor (Htr1d)(altered REM fragmentation), glucagon-like peptide-1 receptor (Glp1r)(light sleep promotion and reduction of deep sleep), and Calcium channel, voltage-dependent, T type, alpha 1I subunit (Cacna1i)(increased bout duration slow wave sleep). Taken together, these results show the complexity of genetic components that regulate sleep-wake traits and highlight the importance of evaluating this complex behavior at a systems level. Pharmacological validation of genetically identified putative targets provides a rapid alternative to generating knock out or transgenic animal models, and may ultimately lead towards new therapeutic opportunities. PMID:22091728

Identifying the Average Causal Mediation Effects with Multiple Mediators in the Presence of Treatment Non-Compliance

ERIC Educational Resources Information Center

Park, Soojin

2015-01-01

Identifying the causal mechanisms is becoming more essential in social and medical sciences. In the presence of treatment non-compliance, the Intent-To-Treated effect (hereafter, ITT effect) is identified as long as the treatment is randomized (Angrist et al., 1996). However, the mediated portion of effect is not identified without additional…

Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.

PubMed

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.

DNA Methylation and BMI: Investigating Identified Methylation Sites at HIF3A in a Causal Framework

PubMed Central

Richmond, Rebecca C.; Ward, Mary E.; Fraser, Abigail; Lyttleton, Oliver; McArdle, Wendy L.; Ring, Susan M.; Gaunt, Tom R.; Lawlor, Debbie A.; Davey Smith, George; Relton, Caroline L.

2016-01-01

Multiple differentially methylated sites and regions associated with adiposity have now been identified in large-scale cross-sectional studies. We tested for replication of associations between previously identified CpG sites at HIF3A and adiposity in ∼1,000 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC). Availability of methylation and adiposity measures at multiple time points, as well as genetic data, allowed us to assess the temporal associations between adiposity and methylation and to make inferences regarding causality and directionality. Overall, our results were discordant with those expected if HIF3A methylation has a causal effect on BMI and provided more evidence for causality in the reverse direction (i.e., an effect of BMI on HIF3A methylation). These results are based on robust evidence from longitudinal analyses and were also partially supported by Mendelian randomization analysis, although this latter analysis was underpowered to detect a causal effect of BMI on HIF3A methylation. Our results also highlight an apparent long-lasting intergenerational influence of maternal BMI on offspring methylation at this locus, which may confound associations between own adiposity and HIF3A methylation. Further work is required to replicate and uncover the mechanisms underlying the direct and intergenerational effect of adiposity on DNA methylation. PMID:26861784

Whole Exome Sequencing Identifies Rare Protein-Coding Variants in Behçet's Disease.

PubMed

Ognenovski, Mikhail; Renauer, Paul; Gensterblum, Elizabeth; Kötter, Ina; Xenitidis, Theodoros; Henes, Jörg C; Casali, Bruno; Salvarani, Carlo; Direskeneli, Haner; Kaufman, Kenneth M; Sawalha, Amr H

2016-05-01

Behçet's disease (BD) is a systemic inflammatory disease with an incompletely understood etiology. Despite the identification of multiple common genetic variants associated with BD, rare genetic variants have been less explored. We undertook this study to investigate the role of rare variants in BD by performing whole exome sequencing in BD patients of European descent. Whole exome sequencing was performed in a discovery set comprising 14 German BD patients of European descent. For replication and validation, Sanger sequencing and Sequenom genotyping were performed in the discovery set and in 2 additional independent sets of 49 German BD patients and 129 Italian BD patients of European descent. Genetic association analysis was then performed in BD patients and 503 controls of European descent. Functional effects of associated genetic variants were assessed using bioinformatic approaches. Using whole exome sequencing, we identified 77 rare variants (in 74 genes) with predicted protein-damaging effects in BD. These variants were genotyped in 2 additional patient sets and then analyzed to reveal significant associations with BD at 2 genetic variants detected in all 3 patient sets that remained significant after Bonferroni correction. We detected genetic association between BD and LIMK2 (rs149034313), involved in regulating cytoskeletal reorganization, and between BD and NEIL1 (rs5745908), involved in base excision DNA repair (P = 3.22 × 10(-4) and P = 5.16 × 10(-4) , respectively). The LIMK2 association is a missense variant with predicted protein damage that may influence functional interactions with proteins involved in cytoskeletal regulation by Rho GTPase, inflammation mediated by chemokine and cytokine signaling pathways, T cell activation, and angiogenesis (Bonferroni-corrected P = 5.63 × 10(-14) , P = 7.29 × 10(-6) , P = 1.15 × 10(-5) , and P = 6.40 × 10(-3) , respectively). The genetic association in NEIL1 is a predicted splice

Mapping rare and common causal alleles for complex human diseases

PubMed Central

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

Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia.

PubMed

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.

Next-generation DNA sequencing identifies novel gene variants and pathways involved in specific language impairment.

PubMed

Chen, Xiaowei Sylvia; Reader, Rose H; Hoischen, Alexander; Veltman, Joris A; Simpson, Nuala H; Francks, Clyde; Newbury, Dianne F; Fisher, Simon E

2017-04-25

A significant proportion of children have unexplained problems acquiring proficient linguistic skills despite adequate intelligence and opportunity. Developmental language disorders are highly heritable with substantial societal impact. Molecular studies have begun to identify candidate loci, but much of the underlying genetic architecture remains undetermined. We performed whole-exome sequencing of 43 unrelated probands affected by severe specific language impairment, followed by independent validations with Sanger sequencing, and analyses of segregation patterns in parents and siblings, to shed new light on aetiology. By first focusing on a pre-defined set of known candidates from the literature, we identified potentially pathogenic variants in genes already implicated in diverse language-related syndromes, including ERC1, GRIN2A, and SRPX2. Complementary analyses suggested novel putative candidates carrying validated variants which were predicted to have functional effects, such as OXR1, SCN9A and KMT2D. We also searched for potential "multiple-hit" cases; one proband carried a rare AUTS2 variant in combination with a rare inherited haplotype affecting STARD9, while another carried a novel nonsynonymous variant in SEMA6D together with a rare stop-gain in SYNPR. On broadening scope to all rare and novel variants throughout the exomes, we identified biological themes that were enriched for such variants, including microtubule transport and cytoskeletal regulation.

Next-generation DNA sequencing identifies novel gene variants and pathways involved in specific language impairment

PubMed Central

Chen, Xiaowei Sylvia; Reader, Rose H.; Hoischen, Alexander; Veltman, Joris A.; Simpson, Nuala H.; Francks, Clyde; Newbury, Dianne F.; Fisher, Simon E.

2017-01-01

A significant proportion of children have unexplained problems acquiring proficient linguistic skills despite adequate intelligence and opportunity. Developmental language disorders are highly heritable with substantial societal impact. Molecular studies have begun to identify candidate loci, but much of the underlying genetic architecture remains undetermined. We performed whole-exome sequencing of 43 unrelated probands affected by severe specific language impairment, followed by independent validations with Sanger sequencing, and analyses of segregation patterns in parents and siblings, to shed new light on aetiology. By first focusing on a pre-defined set of known candidates from the literature, we identified potentially pathogenic variants in genes already implicated in diverse language-related syndromes, including ERC1, GRIN2A, and SRPX2. Complementary analyses suggested novel putative candidates carrying validated variants which were predicted to have functional effects, such as OXR1, SCN9A and KMT2D. We also searched for potential “multiple-hit” cases; one proband carried a rare AUTS2 variant in combination with a rare inherited haplotype affecting STARD9, while another carried a novel nonsynonymous variant in SEMA6D together with a rare stop-gain in SYNPR. On broadening scope to all rare and novel variants throughout the exomes, we identified biological themes that were enriched for such variants, including microtubule transport and cytoskeletal regulation. PMID:28440294

The UK10K project identifies rare variants in health and disease.

PubMed

Walter, Klaudia; Min, Josine L; Huang, Jie; Crooks, Lucy; Memari, Yasin; McCarthy, Shane; Perry, John R B; Xu, ChangJiang; Futema, Marta; Lawson, Daniel; Iotchkova, Valentina; Schiffels, Stephan; Hendricks, Audrey E; Danecek, Petr; Li, Rui; Floyd, James; Wain, Louise V; Barroso, Inês; Humphries, Steve E; Hurles, Matthew E; Zeggini, Eleftheria; Barrett, Jeffrey C; Plagnol, Vincent; Richards, J Brent; Greenwood, Celia M T; Timpson, Nicholas J; Durbin, Richard; Soranzo, Nicole

2015-10-01

The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.

Integrated sequence analysis pipeline provides one-stop solution for identifying disease-causing mutations.

PubMed

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.

HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease.

PubMed

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.

Complex Landscape of Germline Variants in Brazilian Patients With Hereditary and Early Onset Breast Cancer.

PubMed

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.

Regulatory element-based prediction identifies new susceptibility regulatory variants for osteoporosis.

PubMed

Yao, Shi; Guo, Yan; Dong, Shan-Shan; Hao, Ruo-Han; Chen, Xiao-Feng; Chen, Yi-Xiao; Chen, Jia-Bin; Tian, Qing; Deng, Hong-Wen; Yang, Tie-Lin

2017-08-01

Despite genome-wide association studies (GWASs) have identified many susceptibility genes for osteoporosis, it still leaves a large part of missing heritability to be discovered. Integrating regulatory information and GWASs could offer new insights into the biological link between the susceptibility SNPs and osteoporosis. We generated five machine learning classifiers with osteoporosis-associated variants and regulatory features data. We gained the optimal classifier and predicted genome-wide SNPs to discover susceptibility regulatory variants. We further utilized Genetic Factors for Osteoporosis Consortium (GEFOS) and three in-house GWASs samples to validate the associations for predicted positive SNPs. The random forest classifier performed best among all machine learning methods with the F1 score of 0.8871. Using the optimized model, we predicted 37,584 candidate SNPs for osteoporosis. According to the meta-analysis results, a list of regulatory variants was significantly associated with osteoporosis after multiple testing corrections and contributed to the expression of known osteoporosis-associated protein-coding genes. In summary, combining GWASs and regulatory elements through machine learning could provide additional information for understanding the mechanism of osteoporosis. The regulatory variants we predicted will provide novel targets for etiology research and treatment of osteoporosis.

Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese.

PubMed

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.

Targeted Deep Resequencing Identifies Coding Variants in the PEAR1 Gene That Play a Role in Platelet Aggregation

PubMed Central

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

DNA Methylation and BMI: Investigating Identified Methylation Sites at HIF3A in a Causal Framework.

PubMed

Richmond, Rebecca C; Sharp, Gemma C; Ward, Mary E; Fraser, Abigail; Lyttleton, Oliver; McArdle, Wendy L; Ring, Susan M; Gaunt, Tom R; Lawlor, Debbie A; Davey Smith, George; Relton, Caroline L

2016-05-01

Multiple differentially methylated sites and regions associated with adiposity have now been identified in large-scale cross-sectional studies. We tested for replication of associations between previously identified CpG sites at HIF3A and adiposity in ∼1,000 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC). Availability of methylation and adiposity measures at multiple time points, as well as genetic data, allowed us to assess the temporal associations between adiposity and methylation and to make inferences regarding causality and directionality. Overall, our results were discordant with those expected if HIF3A methylation has a causal effect on BMI and provided more evidence for causality in the reverse direction (i.e., an effect of BMI on HIF3A methylation). These results are based on robust evidence from longitudinal analyses and were also partially supported by Mendelian randomization analysis, although this latter analysis was underpowered to detect a causal effect of BMI on HIF3A methylation. Our results also highlight an apparent long-lasting intergenerational influence of maternal BMI on offspring methylation at this locus, which may confound associations between own adiposity and HIF3A methylation. Further work is required to replicate and uncover the mechanisms underlying the direct and intergenerational effect of adiposity on DNA methylation. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Exome Array Analysis Identifies a Common Variant in IL27 Associated with Chronic Obstructive Pulmonary Disease

PubMed Central

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

Identification of Inherited Retinal Disease-Associated Genetic Variants in 11 Candidate Genes.

PubMed

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.

Decoding the Effect of Isobaric Substitutions on Identifying Missing Proteins and Variant Peptides in Human Proteome.

PubMed

Choong, Wai-Kok; Lih, Tung-Shing Mamie; Chen, Yu-Ju; Sung, Ting-Yi

2017-12-01

To confirm the existence of missing proteins, we need to identify at least two unique peptides with length of 9-40 amino acids of a missing protein in bottom-up mass-spectrometry-based proteomic experiments. However, an identified unique peptide of the missing protein, even identified with high level of confidence, could possibly coincide with a peptide of a commonly observed protein due to isobaric substitutions, mass modifications, alternative splice isoforms, or single amino acid variants (SAAVs). Besides unique peptides of missing proteins, identified variant peptides (SAAV-containing peptides) could also alternatively map to peptides of other proteins due to the aforementioned issues. Therefore, we conducted a thorough comparative analysis on data sets in PeptideAtlas Tiered Human Integrated Search Proteome (THISP, 2017-03 release), including neXtProt (2017-01 release), to systematically investigate the possibility of unique peptides in missing proteins (PE2-4), unique peptides in dubious proteins, and variant peptides affected by isobaric substitutions, causing doubtful identification results. In this study, we considered 11 isobaric substitutions. From our analysis, we found <5% of the unique peptides of missing proteins and >6% of variant peptides became shared with peptides of PE1 proteins after isobaric substitutions.

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure underpinning obesity

PubMed Central

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

Trans-ancestry Fine Mapping and Molecular Assays Identify Regulatory Variants at the ANGPTL8 HDL-C GWAS Locus

PubMed Central

Cannon, Maren E.; Duan, Qing; Wu, Ying; Zeynalzadeh, Monica; Xu, Zheng; Kangas, Antti J.; Soininen, Pasi; Ala-Korpela, Mika; Civelek, Mete; Lusis, Aldons J.; Kuusisto, Johanna; Collins, Francis S.; Boehnke, Michael; Tang, Hua; Laakso, Markku; Li, Yun; Mohlke, Karen L.

2017-01-01

Recent genome-wide association studies (GWAS) have identified variants associated with high-density lipoprotein cholesterol (HDL-C) located in or near the ANGPTL8 gene. Given the extensive sharing of GWAS loci across populations, we hypothesized that at least one shared variant at this locus affects HDL-C. The HDL-C–associated variants are coincident with expression quantitative trait loci for ANGPTL8 and DOCK6 in subcutaneous adipose tissue; however, only ANGPTL8 expression levels are associated with HDL-C levels. We identified a 400-bp promoter region of ANGPTL8 and enhancer regions within 5 kb that contribute to regulating expression in liver and adipose. To identify variants functionally responsible for the HDL-C association, we performed fine-mapping analyses and selected 13 candidate variants that overlap putative regulatory regions to test for allelic differences in regulatory function. Of these variants, rs12463177-G increased transcriptional activity (1.5-fold, P = 0.004) and showed differential protein binding. Six additional variants (rs17699089, rs200788077, rs56322906, rs3760782, rs737337, and rs3745683) showed evidence of allelic differences in transcriptional activity and/or protein binding. Taken together, these data suggest a regulatory mechanism at the ANGPTL8 HDL-C GWAS locus involving tissue-selective expression and at least one functional variant. PMID:28754724

Identifying X-consumers using causal recipes: "whales" and "jumbo shrimps" casino gamblers.

PubMed

Woodside, Arch G; Zhang, Mann

2012-03-01

X-consumers are the extremely frequent (top 2-3%) users who typically consume 25% of a product category. This article shows how to use fuzzy-set qualitative comparative analysis (QCA) to provide "causal recipes" sufficient for profiling X-consumers accurately. The study extends Dik Twedt's "heavy-half" product users for building theory and strategies to nurture or control X-behavior. The study here applies QCA to offer configurations that are sufficient in identifying "whales" and "jumbo shrimps" among X-casino gamblers. The findings support the principle that not all X-consumers are alike. The theory and method are applicable for identifying the degree of consistency and coverage of alternative X-consumers among users of all product-service category and brands.

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics

PubMed Central

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

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.

PubMed

Chen, Wenan; Larrabee, Beth R; Ovsyannikova, Inna G; Kennedy, Richard B; Haralambieva, Iana H; Poland, Gregory A; Schaid, Daniel J

2015-07-01

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. Copyright © 2015 by the Genetics Society of America.

Genetic Variants Identified from Epilepsy of Unknown Etiology in Chinese Children by Targeted Exome Sequencing

PubMed Central

Wang, Yimin; Du, Xiaonan; Bin, Rao; Yu, Shanshan; Xia, Zhezhi; Zheng, Guo; Zhong, Jianmin; Zhang, Yunjian; Jiang, Yong-hui; Wang, Yi

2017-01-01

Genetic factors play a major role in the etiology of epilepsy disorders. Recent genomics studies using next generation sequencing (NGS) technique have identified a large number of genetic variants including copy number (CNV) and single nucleotide variant (SNV) in a small set of genes from individuals with epilepsy. These discoveries have contributed significantly to evaluate the etiology of epilepsy in clinic and lay the foundation to develop molecular specific treatment. However, the molecular basis for a majority of epilepsy patients remains elusive, and furthermore, most of these studies have been conducted in Caucasian children. Here we conducted a targeted exome-sequencing of 63 trios of Chinese epilepsy families using a custom-designed NGS panel that covers 412 known and candidate genes for epilepsy. We identified pathogenic and likely pathogenic variants in 15 of 63 (23.8%) families in known epilepsy genes including SCN1A, CDKL5, STXBP1, CHD2, SCN3A, SCN9A, TSC2, MBD5, POLG and EFHC1. More importantly, we identified likely pathologic variants in several novel candidate genes such as GABRE, MYH1, and CLCN6. Our results provide the evidence supporting the application of custom-designed NGS panel in clinic and indicate a conserved genetic susceptibility for epilepsy between Chinese and Caucasian children. PMID:28074849

Novel Genetic Variants of Sporadic Atrial Septal Defect (ASD) in a Chinese Population Identified by Whole-Exome Sequencing (WES).

PubMed

Liu, Yong; Cao, Yu; Li, Yaxiong; Lei, Dongyun; Li, Lin; Hou, Zong Liu; Han, Shen; Meng, Mingyao; Shi, Jianlin; Zhang, Yayong; Wang, Yi; Niu, Zhaoyi; Xie, Yanhua; Xiao, Benshan; Wang, Yuanfei; Li, Xiao; Yang, Lirong; Wang, Wenju; Jiang, Lihong

2018-03-05

BACKGROUND Recently, mutations in several genes have been described to be associated with sporadic ASD, but some genetic variants remain to be identified. The aim of this study was to use whole-exome sequencing (WES) combined with bioinformatics analysis to identify novel genetic variants in cases of sporadic congenital ASD, followed by validation by Sanger sequencing. MATERIAL AND METHODS Five Han patients with secundum ASD were recruited, and their tissue samples were analyzed by WES, followed by verification by Sanger sequencing of tissue and blood samples. Further evaluation using blood samples included 452 additional patients with sporadic secundum ASD (212 male and 240 female patients) and 519 healthy subjects (252 male and 267 female subjects) for further verification by a multiplexed MassARRAY system. Bioinformatic analyses were performed to identify novel genetic variants associated with sporadic ASD. RESULTS From five patients with sporadic ASD, a total of 181,762 genomic variants in 33 exon loci, validated by Sanger sequencing, were selected and underwent MassARRAY analysis in 452 patients with ASD and 519 healthy subjects. Three loci with high mutation frequencies, the 138665410 FOXL2 gene variant, the 23862952 MYH6 gene variant, and the 71098693 HYDIN gene variant were found to be significantly associated with sporadic ASD (P<0.05); variants in FOXL2 and MYH6 were found in patients with isolated, sporadic ASD (P<5×10^-4). CONCLUSIONS This was the first study that demonstrated variants in FOXL2 and HYDIN associated with sporadic ASD, and supported the use of WES and bioinformatics analysis to identify disease-associated mutations.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

PubMed Central

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

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

PubMed Central

Permuth, Jennifer B.; Pirie, Ailith; Ann Chen, Y.; Lin, Hui-Yi; Reid, Brett M.; Chen, Zhihua; Monteiro, Alvaro; Dennis, Joe; Mendoza-Fandino, Gustavo; Anton-Culver, Hoda; Bandera, Elisa V.; Bisogna, Maria; Brinton, Louise; Brooks-Wilson, Angela; Carney, Michael E.; Chenevix-Trench, Georgia; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; D’Aloisio, Aimee A.; Anne Doherty, Jennifer; Earp, Madalene; Edwards, Robert P.; Fridley, Brooke L.; Gayther, Simon A.; Gentry-Maharaj, Aleksandra; Goodman, Marc T.; Gronwald, Jacek; Hogdall, Estrid; Iversen, Edwin S.; Jakubowska, Anna; Jensen, Allan; Karlan, Beth Y.; Kelemen, Linda E.; Kjaer, Suzanne K.; Kraft, Peter; Le, Nhu D.; Levine, Douglas A.; Lissowska, Jolanta; Lubinski, Jan; Matsuo, Keitaro; Menon, Usha; Modugno, Rosemary; Moysich, Kirsten B.; Nakanishi, Toru; Ness, Roberta B.; Olson, Sara; Orlow, Irene; Pearce, Celeste L.; Pejovic, Tanja; Poole, Elizabeth M.; Ramus, Susan J.; Anne Rossing, Mary; Sandler, Dale P.; Shu, Xiao-Ou; Song, Honglin; Taylor, Jack A.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J.; Tworoger, Shelley S.; Webb, Penelope M.; Wentzensen, Nicolas; Wilkens, Lynne R.; Winham, Stacey; Woo, Yin-Ling; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Phelan, Catherine M.; Schildkraut, Joellen M.; Berchuck, Andrew; Goode, Ellen L.; Pharoah, Paul D. P.; Sellers, Thomas A.

2016-01-01

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10 − 7). One of the most significant signals (Pall histologies = 1.01 × 10 − 13;Pserous = 3.54 × 10 − 14) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r2 = 0.90) with a previously identified ‘best hit’ (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 − 5 > P≥5.0 ×10 − 7) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 − 5; PSKAT-o = 9.23 × 10 − 4) and KRT13 (PAML = 1.67 × 10 − 4; PSKAT-o = 1.07 × 10 − 5), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk.

PubMed

Permuth, Jennifer B; Pirie, Ailith; Ann Chen, Y; Lin, Hui-Yi; Reid, Brett M; Chen, Zhihua; Monteiro, Alvaro; Dennis, Joe; Mendoza-Fandino, Gustavo; Anton-Culver, Hoda; Bandera, Elisa V; Bisogna, Maria; Brinton, Louise; Brooks-Wilson, Angela; Carney, Michael E; Chenevix-Trench, Georgia; Cook, Linda S; Cramer, Daniel W; Cunningham, Julie M; Cybulski, Cezary; D'Aloisio, Aimee A; Anne Doherty, Jennifer; Earp, Madalene; Edwards, Robert P; Fridley, Brooke L; Gayther, Simon A; Gentry-Maharaj, Aleksandra; Goodman, Marc T; Gronwald, Jacek; Hogdall, Estrid; Iversen, Edwin S; Jakubowska, Anna; Jensen, Allan; Karlan, Beth Y; Kelemen, Linda E; Kjaer, Suzanne K; Kraft, Peter; Le, Nhu D; Levine, Douglas A; Lissowska, Jolanta; Lubinski, Jan; Matsuo, Keitaro; Menon, Usha; Modugno, Rosemary; Moysich, Kirsten B; Nakanishi, Toru; Ness, Roberta B; Olson, Sara; Orlow, Irene; Pearce, Celeste L; Pejovic, Tanja; Poole, Elizabeth M; Ramus, Susan J; Anne Rossing, Mary; Sandler, Dale P; Shu, Xiao-Ou; Song, Honglin; Taylor, Jack A; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Tworoger, Shelley S; Webb, Penelope M; Wentzensen, Nicolas; Wilkens, Lynne R; Winham, Stacey; Woo, Yin-Ling; Wu, Anna H; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Phelan, Catherine M; Schildkraut, Joellen M; Berchuck, Andrew; Goode, Ellen L; Pharoah, Paul D P; Sellers, Thomas A

2016-08-15

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10  -   7 ). One of the most significant signals (P all histologies  =   1.01 × 10  -   13 ;P serous  =   3.54 × 10  -   14 ) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r 2  =   0.90) with a previously identified 'best hit' (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10  -   5  >   P≥5.0 ×10  -   7 ) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (P AML  =   3.23 × 10  -   5 ; P SKAT-o  =   9.23 × 10  -   4 ) and KRT13 (P AML  =   1.67 × 10  -   4 ; P SKAT-o  =   1.07 × 10  -   5 ), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

PubMed

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.

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

PubMed

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.

Novel Genetic Variants of Sporadic Atrial Septal Defect (ASD) in a Chinese Population Identified by Whole-Exome Sequencing (WES)

PubMed Central

Liu, Yong; Cao, Yu; Li, Yaxiong; Lei, Dongyun; Li, Lin; Hou, Zong Liu; Han, Shen; Meng, Mingyao; Shi, Jianlin; Zhang, Yayong; Wang, Yi; Niu, Zhaoyi; Xie, Yanhua; Xiao, Benshan; Wang, Yuanfei; Li, Xiao; Yang, Lirong

2018-01-01

Background Recently, mutations in several genes have been described to be associated with sporadic ASD, but some genetic variants remain to be identified. The aim of this study was to use whole-exome sequencing (WES) combined with bioinformatics analysis to identify novel genetic variants in cases of sporadic congenital ASD, followed by validation by Sanger sequencing. Material/Methods Five Han patients with secundum ASD were recruited, and their tissue samples were analyzed by WES, followed by verification by Sanger sequencing of tissue and blood samples. Further evaluation using blood samples included 452 additional patients with sporadic secundum ASD (212 male and 240 female patients) and 519 healthy subjects (252 male and 267 female subjects) for further verification by a multiplexed MassARRAY system. Bioinformatic analyses were performed to identify novel genetic variants associated with sporadic ASD. Results From five patients with sporadic ASD, a total of 181,762 genomic variants in 33 exon loci, validated by Sanger sequencing, were selected and underwent MassARRAY analysis in 452 patients with ASD and 519 healthy subjects. Three loci with high mutation frequencies, the 138665410 FOXL2 gene variant, the 23862952 MYH6 gene variant, and the 71098693 HYDIN gene variant were found to be significantly associated with sporadic ASD (P<0.05); variants in FOXL2 and MYH6 were found in patients with isolated, sporadic ASD (P<5×10−4). Conclusions This was the first study that demonstrated variants in FOXL2 and HYDIN associated with sporadic ASD, and supported the use of WES and bioinformatics analysis to identify disease-associated mutations. PMID:29505555

Genetic Candidate Variants in Two Multigenerational Families with Childhood Apraxia of Speech

PubMed Central

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

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. 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.

Screening of whole genome sequences identified high-impact variants for stallion fertility.

PubMed

Schrimpf, Rahel; Gottschalk, Maren; Metzger, Julia; Martinsson, Gunilla; Sieme, Harald; Distl, Ottmar

2016-04-14

g.37455302G>A in NOTCH1 with the de-regressed estimated breeding values of the paternal component of the pregnancy rate per estrus (EBV-PAT). For 9 high-impact variants within the genes CFTR, OVGP1, FBXO43, TSSK6, PKD1, FOXP1, TCP11, SPATA31E1 and NOTCH1 (g.37453246G>C) absence of the homozygous mutant genotype in the validation sample of all 337 fertile stallions was obvious. Therefore, these variants were considered as potentially deleterious factors for stallion fertility. In conclusion, this study revealed 17 genetic variants with a predicted high damaging effect on protein structure and missing homozygous mutant genotype. The g.37455302G>A NOTCH1 variant was identified as a significant stallion fertility locus in Hanoverian stallions and further 9 candidate fertility loci with missing homozygous mutant genotypes were validated in a panel including 19 horse breeds. To our knowledge this is the first study in horses using next generation sequencing data to uncover strong candidate factors for stallion fertility.

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170

PubMed Central

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

Measuring missing heritability: Inferring the contribution of common variants

PubMed Central

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

Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits.

PubMed

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.

Negligible impact of rare autoimmune-locus coding-region variants on missing heritability.

PubMed

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.

Variant-aware saturating mutagenesis using multiple Cas9 nucleases identifies regulatory elements at trait-associated loci.

PubMed

Canver, Matthew C; Lessard, Samuel; Pinello, Luca; Wu, Yuxuan; Ilboudo, Yann; Stern, Emily N; Needleman, Austen J; Galactéros, Frédéric; Brugnara, Carlo; Kutlar, Abdullah; McKenzie, Colin; Reid, Marvin; Chen, Diane D; Das, Partha Pratim; A Cole, Mitchel; Zeng, Jing; Kurita, Ryo; Nakamura, Yukio; Yuan, Guo-Cheng; Lettre, Guillaume; Bauer, Daniel E; Orkin, Stuart H

2017-04-01

Cas9-mediated, high-throughput, saturating in situ mutagenesis permits fine-mapping of function across genomic segments. Disease- and trait-associated variants identified in genome-wide association studies largely cluster at regulatory loci. Here we demonstrate the use of multiple designer nucleases and variant-aware library design to interrogate trait-associated regulatory DNA at high resolution. We developed a computational tool for the creation of saturating-mutagenesis libraries with single or multiple nucleases with incorporation of variants. We applied this methodology to the HBS1L-MYB intergenic region, which is associated with red-blood-cell traits, including fetal hemoglobin levels. This approach identified putative regulatory elements that control MYB expression. Analysis of genomic copy number highlighted potential false-positive regions, thus emphasizing the importance of off-target analysis in the design of saturating-mutagenesis experiments. Together, these data establish a widely applicable high-throughput and high-resolution methodology to identify minimal functional sequences within large disease- and trait-associated regions.

Identification of a functional enhancer variant within the chronic pancreatitis-associated SPINK1 c.101A>G (p.Asn34Ser)-containing haplotype.

PubMed

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.

Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information

NASA Astrophysics Data System (ADS)

Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David

2018-05-01

The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.

A variational Bayes discrete mixture test for rare variant association

PubMed Central

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.

PubMed

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.

Resequencing the susceptibility gene, ITGAM, identifies two functionally deleterious rare variants in systemic lupus erythematosus cases

PubMed Central

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

Causal diagrams for empirical legal research: a methodology for identifying causation, avoiding bias and interpreting results

PubMed Central

VanderWeele, Tyler J.; Staudt, Nancy

2014-01-01

In this paper we introduce methodology—causal directed acyclic graphs—that empirical researchers can use to identify causation, avoid bias, and interpret empirical results. This methodology has become popular in a number of disciplines, including statistics, biostatistics, epidemiology and computer science, but has yet to appear in the empirical legal literature. Accordingly we outline the rules and principles underlying this new methodology and then show how it can assist empirical researchers through both hypothetical and real-world examples found in the extant literature. While causal directed acyclic graphs are certainly not a panacea for all empirical problems, we show they have potential to make the most basic and fundamental tasks, such as selecting covariate controls, relatively easy and straightforward. PMID:25685055

A de novo FOXP1 variant in a patient with autism, intellectual disability and severe speech and language impairment.

PubMed

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.

Computational approaches to identify functional genetic variants in cancer genomes

PubMed Central

Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris; Ritchie, Graham R.S.; Creixell, Pau; Karchin, Rachel; Vazquez, Miguel; Fink, J. Lynn; Kassahn, Karin S.; Pearson, John V.; Bader, Gary; Boutros, Paul C.; Muthuswamy, Lakshmi; Ouellette, B.F. Francis; Reimand, Jüri; Linding, Rune; Shibata, Tatsuhiro; Valencia, Alfonso; Butler, Adam; Dronov, Serge; Flicek, Paul; Shannon, Nick B.; Carter, Hannah; Ding, Li; Sander, Chris; Stuart, Josh M.; Stein, Lincoln D.; Lopez-Bigas, Nuria

2014-01-01

The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor, but only a minority drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. PMID:23900255

An innovative strategy for the molecular diagnosis of Usher syndrome identifies causal biallelic mutations in 93% of European patients.

PubMed

Bonnet, Crystel; Riahi, Zied; Chantot-Bastaraud, Sandra; Smagghe, Luce; Letexier, Mélanie; Marcaillou, Charles; Lefèvre, Gaëlle M; Hardelin, Jean-Pierre; El-Amraoui, Aziz; Singh-Estivalet, Amrit; Mohand-Saïd, Saddek; Kohl, Susanne; Kurtenbach, Anne; Sliesoraityte, Ieva; Zobor, Ditta; Gherbi, Souad; Testa, Francesco; Simonelli, Francesca; Banfi, Sandro; Fakin, Ana; Glavač, Damjan; Jarc-Vidmar, Martina; Zupan, Andrej; Battelino, Saba; Martorell Sampol, Loreto; Claveria, Maria Antonia; Catala Mora, Jaume; Dad, Shzeena; Møller, Lisbeth B; Rodriguez Jorge, Jesus; Hawlina, Marko; Auricchio, Alberto; Sahel, José-Alain; Marlin, Sandrine; Zrenner, Eberhart; Audo, Isabelle; Petit, Christine

2016-12-01

Usher syndrome (USH), the most prevalent cause of hereditary deafness-blindness, is an autosomal recessive and genetically heterogeneous disorder. Three clinical subtypes (USH1-3) are distinguishable based on the severity of the sensorineural hearing impairment, the presence or absence of vestibular dysfunction, and the age of onset of the retinitis pigmentosa. A total of 10 causal genes, 6 for USH1, 3 for USH2, and 1 for USH3, and an USH2 modifier gene, have been identified. A robust molecular diagnosis is required not only to improve genetic counseling, but also to advance gene therapy in USH patients. Here, we present an improved diagnostic strategy that is both cost- and time-effective. It relies on the sequential use of three different techniques to analyze selected genomic regions: targeted exome sequencing, comparative genome hybridization, and quantitative exon amplification. We screened a large cohort of 427 patients (139 USH1, 282 USH2, and six of undefined clinical subtype) from various European medical centers for mutations in all USH genes and the modifier gene. We identified a total of 421 different sequence variants predicted to be pathogenic, about half of which had not been previously reported. Remarkably, we detected large genomic rearrangements, most of which were novel and unique, in 9% of the patients. Thus, our strategy led to the identification of biallelic and monoallelic mutations in 92.7% and 5.8% of the USH patients, respectively. With an overall 98.5% mutation characterization rate, the diagnosis efficiency was substantially improved compared with previously reported methods.

An innovative strategy for the molecular diagnosis of Usher syndrome identifies causal biallelic mutations in 93% of European patients

PubMed Central

Bonnet, Crystel; Riahi, Zied; Chantot-Bastaraud, Sandra; Smagghe, Luce; Letexier, Mélanie; Marcaillou, Charles; Lefèvre, Gaëlle M; Hardelin, Jean-Pierre; El-Amraoui, Aziz; Singh-Estivalet, Amrit; Mohand-Saïd, Saddek; Kohl, Susanne; Kurtenbach, Anne; Sliesoraityte, Ieva; Zobor, Ditta; Gherbi, Souad; Testa, Francesco; Simonelli, Francesca; Banfi, Sandro; Fakin, Ana; Glavač, Damjan; Jarc-Vidmar, Martina; Zupan, Andrej; Battelino, Saba; Martorell Sampol, Loreto; Claveria, Maria Antonia; Catala Mora, Jaume; Dad, Shzeena; Møller, Lisbeth B; Rodriguez Jorge, Jesus; Hawlina, Marko; Auricchio, Alberto; Sahel, José-Alain; Marlin, Sandrine; Zrenner, Eberhart; Audo, Isabelle; Petit, Christine

2016-01-01

Usher syndrome (USH), the most prevalent cause of hereditary deafness–blindness, is an autosomal recessive and genetically heterogeneous disorder. Three clinical subtypes (USH1–3) are distinguishable based on the severity of the sensorineural hearing impairment, the presence or absence of vestibular dysfunction, and the age of onset of the retinitis pigmentosa. A total of 10 causal genes, 6 for USH1, 3 for USH2, and 1 for USH3, and an USH2 modifier gene, have been identified. A robust molecular diagnosis is required not only to improve genetic counseling, but also to advance gene therapy in USH patients. Here, we present an improved diagnostic strategy that is both cost- and time-effective. It relies on the sequential use of three different techniques to analyze selected genomic regions: targeted exome sequencing, comparative genome hybridization, and quantitative exon amplification. We screened a large cohort of 427 patients (139 USH1, 282 USH2, and six of undefined clinical subtype) from various European medical centers for mutations in all USH genes and the modifier gene. We identified a total of 421 different sequence variants predicted to be pathogenic, about half of which had not been previously reported. Remarkably, we detected large genomic rearrangements, most of which were novel and unique, in 9% of the patients. Thus, our strategy led to the identification of biallelic and monoallelic mutations in 92.7% and 5.8% of the USH patients, respectively. With an overall 98.5% mutation characterization rate, the diagnosis efficiency was substantially improved compared with previously reported methods. PMID:27460420

Whole exome sequencing of rare variants in EIF4G1 and VPS35 in Parkinson disease

PubMed Central

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

Identifying genetic variants that affect viability in large cohorts

PubMed Central

Berisa, Tomaz; Day, Felix R.; Perry, John R. B.

2017-01-01

A number of open questions in human evolutionary genetics would become tractable if we were able to directly measure evolutionary fitness. As a step towards this goal, we developed a method to examine whether individual genetic variants, or sets of genetic variants, currently influence viability. The approach consists in testing whether the frequency of an allele varies across ages, accounting for variation in ancestry. We applied it to the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort and to the parents of participants in the UK Biobank. Across the genome, we found only a few common variants with large effects on age-specific mortality: tagging the APOE ε4 allele and near CHRNA3. These results suggest that when large, even late-onset effects are kept at low frequency by purifying selection. Testing viability effects of sets of genetic variants that jointly influence 1 of 42 traits, we detected a number of strong signals. In participants of the UK Biobank of British ancestry, we found that variants that delay puberty timing are associated with a longer parental life span (P~6.2 × 10−6 for fathers and P~2.0 × 10−3 for mothers), consistent with epidemiological studies. Similarly, variants associated with later age at first birth are associated with a longer maternal life span (P~1.4 × 10−3). Signals are also observed for variants influencing cholesterol levels, risk of coronary artery disease (CAD), body mass index, as well as risk of asthma. These signals exhibit consistent effects in the GERA cohort and among participants of the UK Biobank of non-British ancestry. We also found marked differences between males and females, most notably at the CHRNA3 locus, and variants associated with risk of CAD and cholesterol levels. Beyond our findings, the analysis serves as a proof of principle for how upcoming biomedical data sets can be used to learn about selection effects in contemporary humans. PMID:28873088

Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error.

PubMed

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

Single variant and multi-variant trend tests for genetic association with next generation sequencing that are robust to sequencing error

PubMed Central

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

Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases

PubMed Central

Puffenberger, Erik G.; Jinks, Robert N.; Sougnez, Carrie; Cibulskis, Kristian; Willert, Rebecca A.; Achilly, Nathan P.; Cassidy, Ryan P.; Fiorentini, Christopher J.; Heiken, Kory F.; Lawrence, Johnny J.; Mahoney, Molly H.; Miller, Christopher J.; Nair, Devika T.; Politi, Kristin A.; Worcester, Kimberly N.; Setton, Roni A.; DiPiazza, Rosa; Sherman, Eric A.; Eastman, James T.; Francklyn, Christopher; Robey-Bond, Susan; Rider, Nicholas L.; Gabriel, Stacey; Morton, D. Holmes; Strauss, Kevin A.

2012-01-01

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data. PMID:22279524

Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants contributing to lipid levels and coronary artery disease

PubMed Central

Lu, Xiangfeng; Peloso, Gina M; Liu, Dajiang J.; Wu, Ying; Zhang, He; Zhou, Wei; Li, Jun; Tang, Clara Sze-man; Dorajoo, Rajkumar; Li, Huaixing; Long, Jirong; Guo, Xiuqing; Xu, Ming; Spracklen, Cassandra N.; Chen, Yang; Liu, Xuezhen; Zhang, Yan; Khor, Chiea Chuen; Liu, Jianjun; Sun, Liang; Wang, Laiyuan; Gao, Yu-Tang; Hu, Yao; Yu, Kuai; Wang, Yiqin; Cheung, Chloe Yu Yan; Wang, Feijie; Huang, Jianfeng; Fan, Qiao; Cai, Qiuyin; Chen, Shufeng; Shi, Jinxiu; Yang, Xueli; Zhao, Wanting; Sheu, Wayne H.-H.; Cherny, Stacey Shawn; He, Meian; Feranil, Alan B.; Adair, Linda S.; Gordon-Larsen, Penny; Du, Shufa; Varma, Rohit; da Chen, Yii-Der I; Shu, XiaoOu; Lam, Karen Siu Ling; Wong, Tien Yin; Ganesh, Santhi K.; Mo, Zengnan; Hveem, Kristian; Fritsche, Lars; Nielsen, Jonas Bille; Tse, Hung-fat; Huo, Yong; Cheng, Ching-Yu; Chen, Y. Eugene; Zheng, Wei; Tai, E Shyong; Gao, Wei; Lin, Xu; Huang, Wei; Abecasis, Goncalo; Consortium, GLGC; Kathiresan, Sekar; Mohlke, Karen L.; Wu, Tangchun; Sham, Pak Chung; Gu, Dongfeng; Willer, Cristen J

2017-01-01

Most genome-wide association studies have been conducted in European individuals, even though most genetic variation in humans is seen only in non-European samples. To search for novel loci associated with blood lipid levels and clarify the mechanism of action at previously identified lipid loci, we examined protein-coding genetic variants in 47,532 East Asian individuals using an exome array. We identified 255 variants at 41 loci reaching chip-wide significance, including 3 novel loci and 14 East Asian-specific coding variant associations. After meta-analysis with > 300,000 European samples, we identified an additional 9 novel loci. The same 16 genes were identified by the protein-altering variants in both East Asians and Europeans, likely pointing to the functional genes. Our data demonstrate that most of the low-frequency or rare coding variants associated with lipids are population-specific, and that examining genomic data across diverse ancestries may facilitate the identification of functional genes at associated loci. PMID:29083407

Time, frequency, and time-varying Granger-causality measures in neuroscience.

PubMed

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.

Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

PubMed Central

van Leeuwen, Elisabeth M.; Karssen, Lennart C.; Deelen, Joris; Isaacs, Aaron; Medina-Gomez, Carolina; Mbarek, Hamdi; Kanterakis, Alexandros; Trompet, Stella; Postmus, Iris; Verweij, Niek; van Enckevort, David J.; Huffman, Jennifer E.; White, Charles C.; Feitosa, Mary F.; Bartz, Traci M.; Manichaikul, Ani; Joshi, Peter K.; Peloso, Gina M.; Deelen, Patrick; van Dijk, Freerk; Willemsen, Gonneke; de Geus, Eco J.; Milaneschi, Yuri; Penninx, Brenda W.J.H.; Francioli, Laurent C.; Menelaou, Androniki; Pulit, Sara L.; Rivadeneira, Fernando; Hofman, Albert; Oostra, Ben A.; Franco, Oscar H.; Leach, Irene Mateo; Beekman, Marian; de Craen, Anton J.M.; Uh, Hae-Won; Trochet, Holly; Hocking, Lynne J.; Porteous, David J.; Sattar, Naveed; Packard, Chris J.; Buckley, Brendan M.; Brody, Jennifer A.; Bis, Joshua C.; Rotter, Jerome I.; Mychaleckyj, Josyf C.; Campbell, Harry; Duan, Qing; Lange, Leslie A.; Wilson, James F.; Hayward, Caroline; Polasek, Ozren; Vitart, Veronique; Rudan, Igor; Wright, Alan F.; Rich, Stephen S.; Psaty, Bruce M.; Borecki, Ingrid B.; Kearney, Patricia M.; Stott, David J.; Adrienne Cupples, L.; Neerincx, Pieter B.T.; Elbers, Clara C.; Francesco Palamara, Pier; Pe'er, Itsik; Abdellaoui, Abdel; Kloosterman, Wigard P.; van Oven, Mannis; Vermaat, Martijn; Li, Mingkun; Laros, Jeroen F.J.; Stoneking, Mark; de Knijff, Peter; Kayser, Manfred; Veldink, Jan H.; van den Berg, Leonard H.; Byelas, Heorhiy; den Dunnen, Johan T.; Dijkstra, Martijn; Amin, Najaf; Joeri van der Velde, K.; van Setten, Jessica; Kattenberg, Mathijs; van Schaik, Barbera D.C.; Bot, Jan; Nijman, Isaäc J.; Mei, Hailiang; Koval, Vyacheslav; Ye, Kai; Lameijer, Eric-Wubbo; Moed, Matthijs H.; Hehir-Kwa, Jayne Y.; Handsaker, Robert E.; Sunyaev, Shamil R.; Sohail, Mashaal; Hormozdiari, Fereydoun; Marschall, Tobias; Schönhuth, Alexander; Guryev, Victor; Suchiman, H. Eka D.; Wolffenbuttel, Bruce H.; Platteel, Mathieu; Pitts, Steven J.; Potluri, Shobha; Cox, David R.; Li, Qibin; Li, Yingrui; Du, Yuanping; Chen, Ruoyan; Cao, Hongzhi; Li, Ning; Cao, Sujie; Wang, Jun; Bovenberg, Jasper A.; Jukema, J. Wouter; van der Harst, Pim; Sijbrands, Eric J.; Hottenga, Jouke-Jan; Uitterlinden, Andre G.; Swertz, Morris A.; van Ommen, Gert-Jan B.; de Bakker, Paul I.W.; Eline Slagboom, P.; Boomsma, Dorret I.; Wijmenga, Cisca; van Duijn, Cornelia M.

2015-01-01

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10−4), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR. PMID:25751400

Analysis of CHRNA7 rare variants in autism spectrum disorder susceptibility.

PubMed

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.

Genetic association analysis identifies variants associated with disease progression in primary sclerosing cholangitis.

PubMed

Alberts, Rudi; de Vries, Elisabeth M G; Goode, Elizabeth C; Jiang, Xiaojun; Sampaziotis, Fotis; Rombouts, Krista; Böttcher, Katrin; Folseraas, Trine; Weismüller, Tobias J; Mason, Andrew L; Wang, Weiwei; Alexander, Graeme; Alvaro, Domenico; Bergquist, Annika; Björkström, Niklas K; Beuers, Ulrich; Björnsson, Einar; Boberg, Kirsten Muri; Bowlus, Christopher L; Bragazzi, Maria C; Carbone, Marco; Chazouillères, Olivier; Cheung, Angela; Dalekos, Georgios; Eaton, John; Eksteen, Bertus; Ellinghaus, David; Färkkilä, Martti; Festen, Eleonora A M; Floreani, Annarosa; Franceschet, Irene; Gotthardt, Daniel Nils; Hirschfield, Gideon M; Hoek, Bart van; Holm, Kristian; Hohenester, Simon; Hov, Johannes Roksund; Imhann, Floris; Invernizzi, Pietro; Juran, Brian D; Lenzen, Henrike; Lieb, Wolfgang; Liu, Jimmy Z; Marschall, Hanns-Ulrich; Marzioni, Marco; Melum, Espen; Milkiewicz, Piotr; Müller, Tobias; Pares, Albert; Rupp, Christian; Rust, Christian; Sandford, Richard N; Schramm, Christoph; Schreiber, Stefan; Schrumpf, Erik; Silverberg, Mark S; Srivastava, Brijesh; Sterneck, Martina; Teufel, Andreas; Vallier, Ludovic; Verheij, Joanne; Vila, Arnau Vich; Vries, Boudewijn de; Zachou, Kalliopi; Chapman, Roger W; Manns, Michael P; Pinzani, Massimo; Rushbrook, Simon M; Lazaridis, Konstantinos N; Franke, Andre; Anderson, Carl A; Karlsen, Tom H; Ponsioen, Cyriel Y; Weersma, Rinse K

2017-08-04

Primary sclerosing cholangitis (PSC) is a genetically complex, inflammatory bile duct disease of largely unknown aetiology often leading to liver transplantation or death. Little is known about the genetic contribution to the severity and progression of PSC. The aim of this study is to identify genetic variants associated with PSC disease progression and development of complications. We collected standardised PSC subphenotypes in a large cohort of 3402 patients with PSC. After quality control, we combined 130 422 single nucleotide polymorphisms of all patients-obtained using the Illumina immunochip-with their disease subphenotypes. Using logistic regression and Cox proportional hazards models, we identified genetic variants associated with binary and time-to-event PSC subphenotypes. We identified genetic variant rs853974 to be associated with liver transplant-free survival (p=6.07×10 -9 ). Kaplan-Meier survival analysis showed a 50.9% (95% CI 41.5% to 59.5%) transplant-free survival for homozygous AA allele carriers of rs853974 compared with 72.8% (95% CI 69.6% to 75.7%) for GG carriers at 10 years after PSC diagnosis. For the candidate gene in the region, RSPO3 , we demonstrated expression in key liver-resident effector cells, such as human and murine cholangiocytes and human hepatic stellate cells. We present a large international PSC cohort, and report genetic loci associated with PSC disease progression. For liver transplant-free survival, we identified a genome-wide significant signal and demonstrated expression of the candidate gene RSPO3 in key liver-resident effector cells. This warrants further assessments of the role of this potential key PSC modifier gene. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Causal and causally separable processes

NASA Astrophysics Data System (ADS)

Oreshkov, Ognyan; Giarmatzi, Christina

2016-09-01

The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and

Multiplexed resequencing analysis to identify rare variants in pooled DNA with barcode indexing using next-generation sequencer.

PubMed

Mitsui, Jun; Fukuda, Yoko; Azuma, Kyo; Tozaki, Hirokazu; Ishiura, Hiroyuki; Takahashi, Yuji; Goto, Jun; Tsuji, Shoji

2010-07-01

We have recently found that multiple rare variants of the glucocerebrosidase gene (GBA) confer a robust risk for Parkinson disease, supporting the 'common disease-multiple rare variants' hypothesis. To develop an efficient method of identifying rare variants in a large number of samples, we applied multiplexed resequencing using a next-generation sequencer to identification of rare variants of GBA. Sixteen sets of pooled DNAs from six pooled DNA samples were prepared. Each set of pooled DNAs was subjected to polymerase chain reaction to amplify the target gene (GBA) covering 6.5 kb, pooled into one tube with barcode indexing, and then subjected to extensive sequence analysis using the SOLiD System. Individual samples were also subjected to direct nucleotide sequence analysis. With the optimization of data processing, we were able to extract all the variants from 96 samples with acceptable rates of false-positive single-nucleotide variants.

'Mendelian randomization': an approach for exploring causal relations in epidemiology.

PubMed

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.

A systematic variant screening in familial cases of congenital heart defects demonstrates the usefulness of molecular genetics in this field

PubMed Central

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

Epidemiological causality.

PubMed

Morabia, Alfredo

2005-01-01

Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population.

Identifying Conditions That Support Causal Inference in Observational Studies in Education: Empirical Evidence from within Study Comparisons

ERIC Educational Resources Information Center

Hallberg, Kelly

2013-01-01

This dissertation is a collection of three papers that employ empirical within study comparisons (WSCs) to identify conditions that support causal inference in observational studies. WSC studies empirically estimate the extent to which a given observational study reproduces the result of a randomized clinical trial (RCT) when both share the same…

Exome-Wide Association Study Identifies New Low-Frequency and Rare UGT1A1 Coding Variants and UGT1A6 Coding Variants Influencing Serum Bilirubin in Elderly Subjects

PubMed Central

Oussalah, Abderrahim; Bosco, Paolo; Anello, Guido; Spada, Rosario; Guéant-Rodriguez, Rosa-Maria; Chery, Céline; Rouyer, Pierre; Josse, Thomas; Romano, Antonino; Elia, Maurizzio; Bronowicki, Jean-Pierre; Guéant, Jean-Louis

2015-01-01

Abstract Genome-wide association studies (GWASs) have identified loci contributing to total serum bilirubin level. However, no exome-wide approaches have been performed to address this question. Using exome-wide approach, we assessed the influence of protein-coding variants on unconjugated, conjugated, and total serum bilirubin levels in a well-characterized cohort of 773 ambulatory elderly subjects from Italy. Coding variants were replicated in 227 elderly subjects from the same area. We identified 4 missense rare (minor allele frequency, MAF < 0.5%) and low-frequency (MAF, 0.5%–5%) coding variants located in the first exon of the UGT1A1 gene, which encodes for the substrate-binding domain (rs4148323 [MAF = 0.06%; p.Gly71Arg], rs144398951 [MAF = 0.06%; p.Ile215Val], rs35003977 [MAF = 0.78%; p.Val225Gly], and rs57307513 [MAF = 0.06%; p.Ser250Pro]). These variants were in strong linkage disequilibrium with 3 intronic UGT1A1 variants (rs887829, rs4148325, rs6742078), which were significantly associated with total bilirubin level (P = 2.34 × 10−34, P = 7.02 × 10−34, and P = 8.27 × 10−34), as well as unconjugated, and conjugated bilirubin levels. We also identified UGT1A6 variants in association with total (rs6759892, p.Ser7Ala, P = 1.98 × 10−26; rs2070959, p.Thr181Ala, P = 2.87 × 10−27; and rs1105879, p.Arg184Ser, P = 3.27 × 10−29), unconjugated, and conjugated bilirubin levels. All UGT1A1 intronic variants (rs887829, rs6742078, and rs4148325) and UGT1A6 coding variants (rs6759892, rs2070959, and rs1105879) were significantly associated with gallstone-related cholecystectomy risk. The UGT1A6 variant rs2070959 (p.Thr181Ala) was associated with the highest risk of gallstone–related cholecystectomy (OR, 4.58; 95% CI, 1.58–13.28; P = 3.21 × 10−3). Using an exome-wide approach we identified coding variants on UGT1A1 and UGT1A6 genes in association with serum bilirubin

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype

PubMed Central

Ferreira, Manuel A. R.; Matheson, Melanie C.; Tang, Clara S.; Granell, Raquel; Ang, Wei; Hui, Jennie; Kiefer, Amy K.; Duffy, David L.; Baltic, Svetlana; Danoy, Patrick; Bui, Minh; Price, Loren; Sly, Peter D.; Eriksson, Nicholas; Madden, Pamela A.; Abramson, Michael J.; Holt, Patrick G.; Heath, Andrew C.; Hunter, Michael; Musk, Bill; Robertson, Colin F.; Le Souëf, Peter; Montgomery, Grant W.; Henderson, A. John; Tung, Joyce Y.; Dharmage, Shyamali C.; Brown, Matthew A.; James, Alan; Thompson, Philip J.; Pennell, Craig; Martin, Nicholas G.; Evans, David M.; Hinds, David A.; Hopper, John L.

2014-01-01

Background To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. Objective We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. Methods We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). Results At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10−9) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10−8). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10−7) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10−6). Conclusion By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency. PMID:24388013

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype.

PubMed

Ferreira, Manuel A R; Matheson, Melanie C; Tang, Clara S; Granell, Raquel; Ang, Wei; Hui, Jennie; Kiefer, Amy K; Duffy, David L; Baltic, Svetlana; Danoy, Patrick; Bui, Minh; Price, Loren; Sly, Peter D; Eriksson, Nicholas; Madden, Pamela A; Abramson, Michael J; Holt, Patrick G; Heath, Andrew C; Hunter, Michael; Musk, Bill; Robertson, Colin F; Le Souëf, Peter; Montgomery, Grant W; Henderson, A John; Tung, Joyce Y; Dharmage, Shyamali C; Brown, Matthew A; James, Alan; Thompson, Philip J; Pennell, Craig; Martin, Nicholas G; Evans, David M; Hinds, David A; Hopper, John L

2014-06-01

To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10(-9)) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10(-8)). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10(-7)) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10(-6)). By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger

Genetic insights into age-related macular degeneration: Controversies addressing Risk, Causality, and Therapeutics

PubMed Central

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

Causality and Causal Inference in Social Work: Quantitative and Qualitative Perspectives

PubMed Central

Palinkas, Lawrence A.

2015-01-01

Achieving the goals of social work requires matching a specific solution to a specific problem. Understanding why the problem exists and why the solution should work requires a consideration of cause and effect. However, it is unclear whether it is desirable for social workers to identify cause and effect, whether it is possible for social workers to identify cause and effect, and, if so, what is the best means for doing so. These questions are central to determining the possibility of developing a science of social work and how we go about doing it. This article has four aims: (1) provide an overview of the nature of causality; (2) examine how causality is treated in social work research and practice; (3) highlight the role of quantitative and qualitative methods in the search for causality; and (4) demonstrate how both methods can be employed to support a “science” of social work. PMID:25821393

Nightmares in the general population: identifying potential causal factors.

PubMed

Rek, Stephanie; Sheaves, Bryony; Freeman, Daniel

2017-09-01

Nightmares are inherently distressing, prevent restorative sleep, and are associated with a number of psychiatric problems, but have rarely been the subject of empirical study. Negative affect, linked to stressful events, is generally considered the key trigger of nightmares; hence nightmares have most often been considered in the context of post-traumatic stress disorder (PTSD). However, many individuals with heightened negative affect do not have nightmares. The objective of this study was to identify mechanistically plausible factors, beyond negative affect, that may explain why individuals experience nightmares. 846 participants from the UK general population completed an online survey about nightmare occurrence and severity (pre-occupation, distress, and impairment), negative affect, worry, depersonalisation, hallucinatory experiences, paranoia, alcohol use, sleep duration, physical activity levels, PTSD symptoms, and stressful life events. Associations of nightmares with the putative predictive factors were tested controlling for levels of negative affect. Analyses were also repeated controlling for levels of PTSD and the recent occurrence of stressful life events. Nightmare occurrence, adjusting for negative affect, was associated with higher levels of worry, depersonalisation, hallucinatory experiences, paranoia, and sleep duration (odds ratios 1.25-1.45). Nightmare severity, controlling for negative affect, was associated with higher levels of worry, depersonalisation, hallucinatory experiences, and paranoia (R 2 s: 0.33-0.39). Alcohol use and physical activity levels were not associated with nightmares. The study identifies a number of potential predictors of the occurrence and severity of nightmares. Causal roles require testing in future longitudinal, experimental, and treatment studies.

Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation.

PubMed

Wood, Andrew R; Perry, John R B; Tanaka, Toshiko; Hernandez, Dena G; Zheng, Hou-Feng; Melzer, David; Gibbs, J Raphael; Nalls, Michael A; Weedon, Michael N; Spector, Tim D; Richards, J Brent; Bandinelli, Stefania; Ferrucci, Luigi; Singleton, Andrew B; Frayling, Timothy M

2013-01-01

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF <5%) and rare variants (<1%)) can enhance previously identified associations and identify novel loci, we selected 93 quantitative circulating factors where data was available from the InCHIANTI population study. These phenotypes included cytokines, binding proteins, hormones, vitamins and ions. We selected these phenotypes because many have known strong genetic associations and are potentially important to help understand disease processes. We performed a genome-wide scan for these 93 phenotypes in InCHIANTI. We identified 21 signals and 33 signals that reached P<5×10(-8) based on HapMap and 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P<5×10(-11) respectively. Imputation of 1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P<5×10(-8) in both analyses (17 of which represent well replicated signals in the NHGRI catalogue), six were captured by the same index SNP, five were nominally more strongly associated in 1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10(-12)). Our data provide important proof of principle

Imputation of Variants from the 1000 Genomes Project Modestly Improves Known Associations and Can Identify Low-frequency Variant - Phenotype Associations Undetected by HapMap Based Imputation

PubMed Central

Wood, Andrew R.; Perry, John R. B.; Tanaka, Toshiko; Hernandez, Dena G.; Zheng, Hou-Feng; Melzer, David; Gibbs, J. Raphael; Nalls, Michael A.; Weedon, Michael N.; Spector, Tim D.; Richards, J. Brent; Bandinelli, Stefania; Ferrucci, Luigi; Singleton, Andrew B.; Frayling, Timothy M.

2013-01-01

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF <5%) and rare variants (<1%)) can enhance previously identified associations and identify novel loci, we selected 93 quantitative circulating factors where data was available from the InCHIANTI population study. These phenotypes included cytokines, binding proteins, hormones, vitamins and ions. We selected these phenotypes because many have known strong genetic associations and are potentially important to help understand disease processes. We performed a genome-wide scan for these 93 phenotypes in InCHIANTI. We identified 21 signals and 33 signals that reached P<5×10−8 based on HapMap and 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P<5×10−11 respectively. Imputation of 1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P<5×10−8 in both analyses (17 of which represent well replicated signals in the NHGRI catalogue), six were captured by the same index SNP, five were nominally more strongly associated in 1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10−12). Our data provide important proof of principle

Whole exome sequencing identifies genetic variants in inherited thrombocytopenia with secondary qualitative function defects

PubMed Central

Johnson, Ben; Lowe, Gillian C.; Futterer, Jane; Lordkipanidzé, Marie; MacDonald, David; Simpson, Michael A.; Sanchez-Guiú, Isabel; Drake, Sian; Bem, Danai; Leo, Vincenzo; Fletcher, Sarah J.; Dawood, Ban; Rivera, José; Allsup, David; Biss, Tina; Bolton-Maggs, Paula HB; Collins, Peter; Curry, Nicola; Grimley, Charlotte; James, Beki; Makris, Mike; Motwani, Jayashree; Pavord, Sue; Talks, Katherine; Thachil, Jecko; Wilde, Jonathan; Williams, Mike; Harrison, Paul; Gissen, Paul; Mundell, Stuart; Mumford, Andrew; Daly, Martina E.; Watson, Steve P.; Morgan, Neil V.

2016-01-01

Inherited thrombocytopenias are a heterogeneous group of disorders characterized by abnormally low platelet counts which can be associated with abnormal bleeding. Next-generation sequencing has previously been employed in these disorders for the confirmation of suspected genetic abnormalities, and more recently in the discovery of novel disease-causing genes. However its full potential has not yet been exploited. Over the past 6 years we have sequenced the exomes from 55 patients, including 37 index cases and 18 additional family members, all of whom were recruited to the UK Genotyping and Phenotyping of Platelets study. All patients had inherited or sustained thrombocytopenia of unknown etiology with platelet counts varying from 11×109/L to 186×109/L. Of the 51 patients phenotypically tested, 37 (73%), had an additional secondary qualitative platelet defect. Using whole exome sequencing analysis we have identified “pathogenic” or “likely pathogenic” variants in 46% (17/37) of our index patients with thrombocytopenia. In addition, we report variants of uncertain significance in 12 index cases, including novel candidate genetic variants in previously unreported genes in four index cases. These results demonstrate that whole exome sequencing is an efficient method for elucidating potential pathogenic genetic variants in inherited thrombocytopenia. Whole exome sequencing also has the added benefit of discovering potentially pathogenic genetic variants for further study in novel genes not previously implicated in inherited thrombocytopenia. PMID:27479822

Exome chip meta-analysis identifies novel loci and East Asian-specific coding variants that contribute to lipid levels and coronary artery disease.

PubMed

Lu, Xiangfeng; Peloso, Gina M; Liu, Dajiang J; Wu, Ying; Zhang, He; Zhou, Wei; Li, Jun; Tang, Clara Sze-Man; Dorajoo, Rajkumar; Li, Huaixing; Long, Jirong; Guo, Xiuqing; Xu, Ming; Spracklen, Cassandra N; Chen, Yang; Liu, Xuezhen; Zhang, Yan; Khor, Chiea Chuen; Liu, Jianjun; Sun, Liang; Wang, Laiyuan; Gao, Yu-Tang; Hu, Yao; Yu, Kuai; Wang, Yiqin; Cheung, Chloe Yu Yan; Wang, Feijie; Huang, Jianfeng; Fan, Qiao; Cai, Qiuyin; Chen, Shufeng; Shi, Jinxiu; Yang, Xueli; Zhao, Wanting; Sheu, Wayne H-H; Cherny, Stacey Shawn; He, Meian; Feranil, Alan B; Adair, Linda S; Gordon-Larsen, Penny; Du, Shufa; Varma, Rohit; Chen, Yii-Der Ida; Shu, Xiao-Ou; Lam, Karen Siu Ling; Wong, Tien Yin; Ganesh, Santhi K; Mo, Zengnan; Hveem, Kristian; Fritsche, Lars G; Nielsen, Jonas Bille; Tse, Hung-Fat; Huo, Yong; Cheng, Ching-Yu; Chen, Y Eugene; Zheng, Wei; Tai, E Shyong; Gao, Wei; Lin, Xu; Huang, Wei; Abecasis, Goncalo; Kathiresan, Sekar; Mohlke, Karen L; Wu, Tangchun; Sham, Pak Chung; Gu, Dongfeng; Willer, Cristen J

2017-12-01

Most genome-wide association studies have been of European individuals, even though most genetic variation in humans is seen only in non-European samples. To search for novel loci associated with blood lipid levels and clarify the mechanism of action at previously identified lipid loci, we used an exome array to examine protein-coding genetic variants in 47,532 East Asian individuals. We identified 255 variants at 41 loci that reached chip-wide significance, including 3 novel loci and 14 East Asian-specific coding variant associations. After a meta-analysis including >300,000 European samples, we identified an additional nine novel loci. Sixteen genes were identified by protein-altering variants in both East Asians and Europeans, and thus are likely to be functional genes. Our data demonstrate that most of the low-frequency or rare coding variants associated with lipids are population specific, and that examining genomic data across diverse ancestries may facilitate the identification of functional genes at associated loci.

Association-heterogeneity mapping identifies an Asian-specific association of the GTF2I locus with rheumatoid arthritis

PubMed Central

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

Genetic variants associated with subjective well-being, depressive symptoms and neuroticism identified through genome-wide analyses

PubMed Central

Derringer, Jaime; Gratten, Jacob; Lee, James J; Liu, Jimmy Z; de Vlaming, Ronald; Ahluwalia, Tarunveer S; Buchwald, Jadwiga; Cavadino, Alana; Frazier-Wood, Alexis C; Davies, Gail; Furlotte, Nicholas A; Garfield, Victoria; Geisel, Marie Henrike; Gonzalez, Juan R; Haitjema, Saskia; Karlsson, Robert; van der Laan, Sander W; Ladwig, Karl-Heinz; Lahti, Jari; van der Lee, Sven J; Miller, Michael B; Lind, Penelope A; Liu, Tian; Matteson, Lindsay; Mihailov, Evelin; Minica, Camelia C; Nolte, Ilja M; Mook-Kanamori, Dennis O; van der Most, Peter J; Oldmeadow, Christopher; Qian, Yong; Raitakari, Olli; Rawal, Rajesh; Realo, Anu; Rueedi, Rico; Schmidt, Börge; Smith, Albert V; Stergiakouli, Evie; Tanaka, Toshiko; Taylor, Kent; Thorleifsson, Gudmar; Wedenoja, Juho; Wellmann, Juergen; Westra, Harm-Jan; Willems, Sara M; Zhao, Wei; Amin, Najaf; Bakshi, Andrew; Bergmann, Sven; Bjornsdottir, Gyda; Boyle, Patricia A; Cherney, Samantha; Cox, Simon R; Davis, Oliver S P; Ding, Jun; Direk, Nese; Eibich, Peter; Emeny, Rebecca T; Fatemifar, Ghazaleh; Faul, Jessica D; Ferrucci, Luigi; Forstner, Andreas J; Gieger, Christian; Gupta, Richa; Harris, Tamara B; Harris, Juliette M; Holliday, Elizabeth G; Hottenga, Jouke-Jan; De Jager, Philip L; Kaakinen, Marika A; Kajantie, Eero; Karhunen, Ville; Kolcic, Ivana; Kumari, Meena; Launer, Lenore J; Franke, Lude; Li-Gao, Ruifang; Liewald, David C; Koini, Marisa; Loukola, Anu; Marques-Vidal, Pedro; Montgomery, Grant W; Mosing, Miriam A; Paternoster, Lavinia; Pattie, Alison; Petrovic, Katja E; Pulkki-Råback, Laura; Quaye, Lydia; Räikkönen, Katri; Rudan, Igor; Scott, Rodney J; Smith, Jennifer A; Sutin, Angelina R; Trzaskowski, Maciej; Vinkhuyzen, Anna E; Yu, Lei; Zabaneh, Delilah; Attia, John R; Bennett, David A; Berger, Klaus; Bertram, Lars; Boomsma, Dorret I; Snieder, Harold; Chang, Shun-Chiao; Cucca, Francesco; Deary, Ian J; van Duijn, Cornelia M; Eriksson, Johan G; Bültmann, Ute; de Geus, Eco J C; Groenen, Patrick J F; Gudnason, Vilmundur; Hansen, Torben; Hartman, Catharine A; Haworth, Claire M A; Hayward, Caroline; Heath, Andrew C; Hinds, David A; Hyppönen, Elina; Iacono, William G; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L R; Keltikangas-Järvinen, Liisa; Kraft, Peter; Kubzansky, Laura D; Lehtimäki, Terho; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; Metspalu, Andres; Mills, Melinda; de Mutsert, Renée; Oldehinkel, Albertine J; Pasterkamp, Gerard; Pedersen, Nancy L; Plomin, Robert; Polasek, Ozren; Power, Christine; Rich, Stephen S; Rosendaal, Frits R; den Ruijter, Hester M; Schlessinger, David; Schmidt, Helena; Svento, Rauli; Schmidt, Reinhold; Alizadeh, Behrooz Z; Sørensen, Thorkild I A; Spector, Tim D; Starr, John M; Stefansson, Kari; Steptoe, Andrew; Terracciano, Antonio; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tiemeier, Henning; Uitterlinden, André G; Vollenweider, Peter; Wagner, Gert G; Weir, David R; Yang, Jian; Conley, Dalton C; Smith, George Davey; Hofman, Albert; Johannesson, Magnus; Laibson, David I; Medland, Sarah E; Meyer, Michelle N; Pickrell, Joseph K; Esko, Tõnu; Krueger, Robert F; Beauchamp, Jonathan P; Koellinger, Philipp D; Benjamin, Daniel J; Bartels, Meike; Cesarini, David

2016-01-01

We conducted genome-wide association studies of three phenotypes: subjective well-being (N = 298,420), depressive symptoms (N = 161,460), and neuroticism (N = 170,910). We identified three variants associated with subjective well-being, two with depressive symptoms, and eleven with neuroticism, including two inversion polymorphisms. The two depressive symptoms loci replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings, and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are strongly enriched for association. PMID:27089181

Is High-Density Lipoprotein Cholesterol Causally Related to Kidney Function? Evidence From Genetic Epidemiological Studies.

PubMed

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.

Screening for rare variants in the PNPLA3 gene in obese liver biopsy patients.

PubMed

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.

Use of Genome Sequence Information for Meat Quality Trait QTL Mining for Causal Genes and Mutations on Pig Chromosome 17

PubMed Central

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

Gene-Based Sequencing Identifies Lipid-Influencing Variants with Ethnicity-Specific Effects in African Americans

PubMed Central

Bentley, Amy R.; Chen, Guanjie; Shriner, Daniel; Doumatey, Ayo P.; Zhou, Jie; Huang, Hanxia; Mullikin, James C.; Blakesley, Robert W.; Hansen, Nancy F.; Bouffard, Gerard G.; Cherukuri, Praveen F.; Maskeri, Baishali; Young, Alice C.; Adeyemo, Adebowale; Rotimi, Charles N.

2014-01-01

Although a considerable proportion of serum lipids loci identified in European ancestry individuals (EA) replicate in African Americans (AA), interethnic differences in the distribution of serum lipids suggest that some genetic determinants differ by ethnicity. We conducted a comprehensive evaluation of five lipid candidate genes to identify variants with ethnicity-specific effects. We sequenced ABCA1, LCAT, LPL, PON1, and SERPINE1 in 48 AA individuals with extreme serum lipid concentrations (high HDLC/low TG or low HDLC/high TG). Identified variants were genotyped in the full population-based sample of AA (n = 1694) and tested for an association with serum lipids. rs328 (LPL) and correlated variants were associated with higher HDLC and lower TG. Interestingly, a stronger effect was observed on a “European” vs. “African” genetic background at this locus. To investigate this effect, we evaluated the region among West Africans (WA). For TG, the effect size among WA was the same in AA with only African local ancestry (2–3% lower TG), while the larger association among AA with local European ancestry matched previous reports in EA (10%). For HDLC, there was no association with rs328 in AA with only African local ancestry or in WA, while the association among AA with European local ancestry was much greater than what has been observed for EA (15 vs. ∼5 mg/dl), suggesting an interaction with an environmental or genetic factor that differs by ethnicity. Beyond this ancestry effect, the importance of African ancestry-focused, sequence-based work was also highlighted by serum lipid associations of variants that were in higher frequency (or present only) among those of African ancestry. By beginning our study with the sequence variation present in AA individuals, investigating local ancestry effects, and seeking replication in WA, we were able to comprehensively evaluate the role of a set of candidate genes in serum lipids in AA. PMID:24603370

A genome-wide survey of CD4+ lymphocyte regulatory genetic variants identifies novel asthma genes

PubMed Central

Sharma, Sunita; Zhou, Xiaobo; Thibault, Derek M.; Himes, Blanca E.; Liu, Andy; Szefler, Stanley J.; Strunk, Robert; Castro, Mario; Hansel, Nadia N.; Diette, Gregory B.; Vonakis, Becky M.; Adkinson, N. Franklin; Avila, Lydiana; Soto-Quiros, Manuel; Barraza-Villareal, Albino; Lemanske, Robert F.; Solway, Julian; Krishnan, Jerry; White, Steven R.; Cheadle, Chris; Berger, Alan E.; Fan, Jinshui; Boorgula, Meher Preethi; Nicolae, Dan; Gilliland, Frank; Barnes, Kathleen; London, Stephanie J.; Martinez, Fernando; Ober, Carole; Celedón, Juan C.; Carey, Vincent J.; Weiss, Scott T.; Raby, Benjamin A.

2014-01-01

Background Genome-wide association studies have yet to identify the majority of genetic variants involved in asthma. We hypothesized that expression quantitative trait locus (eQTL) mapping can identify novel asthma genes by enabling prioritization of putative functional variants for association testing. Objective We evaluated 6,706 cis-acting expression-associated variants (eSNP) identified through a genome-wide eQTL survey of CD4+ lymphocytes for association with asthma. Methods eSNP were tested for association with asthma in 359 asthma cases and 846 controls from the Childhood Asthma Management Program, with verification using family-based testing. Significant associations were tested for replication in 579 parent-child trios with asthma from Costa Rica. Further functional validation was performed by Formaldehyde Assisted Isolation of Regulatory Elements (FAIRE)-qPCR and Chromatin-Immunoprecipitation (ChIP)-PCR in lung derived epithelial cell lines (Beas-2B and A549) and Jurkat cells, a leukemia cell line derived from T lymphocytes. Results Cis-acting eSNP demonstrated associations with asthma in both cohorts. We confirmed the previously-reported association of ORMDL3/GSDMB variants with asthma (combined p=2.9 × 108). Reproducible associations were also observed for eSNP in three additional genes: FADS2 (p=0.002), NAGA (p=0.0002), and F13A1 (p=0.0001). We subsequently demonstrated that FADS2 mRNA is increased in CD4+ lymphocytes in asthmatics, and that the associated eSNPs reside within DNA segments with histone modifications that denote open chromatin status and confer enhancer activity. Conclusions Our results demonstrate the utility of eQTL mapping in the identification of novel asthma genes, and provide evidence for the importance of FADS2, NAGA, and F13A1 in the pathogenesis of asthma. PMID:24934276

BISQUE: locus- and variant-specific conversion of genomic, transcriptomic and proteomic database identifiers.

PubMed

Meyer, Michael J; Geske, Philip; Yu, Haiyuan

2016-05-15

Biological sequence databases are integral to efforts to characterize and understand biological molecules and share biological data. However, when analyzing these data, scientists are often left holding disparate biological currency-molecular identifiers from different databases. For downstream applications that require converting the identifiers themselves, there are many resources available, but analyzing associated loci and variants can be cumbersome if data is not given in a form amenable to particular analyses. Here we present BISQUE, a web server and customizable command-line tool for converting molecular identifiers and their contained loci and variants between different database conventions. BISQUE uses a graph traversal algorithm to generalize the conversion process for residues in the human genome, genes, transcripts and proteins, allowing for conversion across classes of molecules and in all directions through an intuitive web interface and a URL-based web service. BISQUE is freely available via the web using any major web browser (http://bisque.yulab.org/). Source code is available in a public GitHub repository (https://github.com/hyulab/BISQUE). haiyuan.yu@cornell.edu 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.

Whole exome sequencing identifies genetic variants in inherited thrombocytopenia with secondary qualitative function defects.

PubMed

Johnson, Ben; Lowe, Gillian C; Futterer, Jane; Lordkipanidzé, Marie; MacDonald, David; Simpson, Michael A; Sanchez-Guiú, Isabel; Drake, Sian; Bem, Danai; Leo, Vincenzo; Fletcher, Sarah J; Dawood, Ban; Rivera, José; Allsup, David; Biss, Tina; Bolton-Maggs, Paula Hb; Collins, Peter; Curry, Nicola; Grimley, Charlotte; James, Beki; Makris, Mike; Motwani, Jayashree; Pavord, Sue; Talks, Katherine; Thachil, Jecko; Wilde, Jonathan; Williams, Mike; Harrison, Paul; Gissen, Paul; Mundell, Stuart; Mumford, Andrew; Daly, Martina E; Watson, Steve P; Morgan, Neil V

2016-10-01

Inherited thrombocytopenias are a heterogeneous group of disorders characterized by abnormally low platelet counts which can be associated with abnormal bleeding. Next-generation sequencing has previously been employed in these disorders for the confirmation of suspected genetic abnormalities, and more recently in the discovery of novel disease-causing genes. However its full potential has not yet been exploited. Over the past 6 years we have sequenced the exomes from 55 patients, including 37 index cases and 18 additional family members, all of whom were recruited to the UK Genotyping and Phenotyping of Platelets study. All patients had inherited or sustained thrombocytopenia of unknown etiology with platelet counts varying from 11×10 9 /L to 186×10 9 /L. Of the 51 patients phenotypically tested, 37 (73%), had an additional secondary qualitative platelet defect. Using whole exome sequencing analysis we have identified "pathogenic" or "likely pathogenic" variants in 46% (17/37) of our index patients with thrombocytopenia. In addition, we report variants of uncertain significance in 12 index cases, including novel candidate genetic variants in previously unreported genes in four index cases. These results demonstrate that whole exome sequencing is an efficient method for elucidating potential pathogenic genetic variants in inherited thrombocytopenia. Whole exome sequencing also has the added benefit of discovering potentially pathogenic genetic variants for further study in novel genes not previously implicated in inherited thrombocytopenia. Copyright© Ferrata Storti Foundation.

The salience network causally influences default mode network activity during moral reasoning

PubMed Central

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

Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits

PubMed Central

Palmer, Cameron D.; Gudnason, Vilmundur; Eiriksdottir, Gudny; Garcia, Melissa E.; Launer, Lenore J.; Nalls, Michael A.; Clark, Jeanne M.; Mitchell, Braxton D.; Shuldiner, Alan R.; Butler, Johannah L.; Tomas, Marta; Hoffmann, Udo; Hwang, Shih-Jen; Massaro, Joseph M.; O'Donnell, Christopher J.; Sahani, Dushyant V.; Salomaa, Veikko; Schadt, Eric E.; Schwartz, Stephen M.; Siscovick, David S.; Voight, Benjamin F.; Carr, J. Jeffrey; Feitosa, Mary F.; Harris, Tamara B.; Fox, Caroline S.

2011-01-01

Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%–27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10−8) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT–assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits. PMID:21423719

Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits.

PubMed

Speliotes, Elizabeth K; Yerges-Armstrong, Laura M; Wu, Jun; Hernaez, Ruben; Kim, Lauren J; Palmer, Cameron D; Gudnason, Vilmundur; Eiriksdottir, Gudny; Garcia, Melissa E; Launer, Lenore J; Nalls, Michael A; Clark, Jeanne M; Mitchell, Braxton D; Shuldiner, Alan R; Butler, Johannah L; Tomas, Marta; Hoffmann, Udo; Hwang, Shih-Jen; Massaro, Joseph M; O'Donnell, Christopher J; Sahani, Dushyant V; Salomaa, Veikko; Schadt, Eric E; Schwartz, Stephen M; Siscovick, David S; Voight, Benjamin F; Carr, J Jeffrey; Feitosa, Mary F; Harris, Tamara B; Fox, Caroline S; Smith, Albert V; Kao, W H Linda; Hirschhorn, Joel N; Borecki, Ingrid B

2011-03-01

Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8)) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.

Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes.

PubMed

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.

Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes

PubMed Central

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

A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

PubMed

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.

A low-frequency inactivating AKT2 variant enriched in the Finnish population is associated with fasting insulin levels and type 2 diabetes risk

PubMed Central

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

SEPTIN12 Genetic Variants Confer Susceptibility to Teratozoospermia

PubMed Central

Lin, Ying-Hung; Wang, Ya-Yun; Chen, Hau-Inh; Kuo, Yung-Che; Chiou, Yu-Wei; Lin, Hsi-Hui; Wu, Ching-Ming; Hsu, Chao-Chin; Chiang, Han-Sun; Kuo, Pao-Lin

2012-01-01

It is estimated that 10–15% of couples are infertile and male factors account for about half of these cases. With the advent of intracytoplasmic sperm injection (ICSI), many infertile men have been able to father offspring. However, teratozoospermia still remains a big challenge to tackle. Septins belong to a family of cytoskeletal proteins with GTPase activity and are involved in various biological processes e.g. morphogenesis, compartmentalization, apoptosis and cytokinesis. SEPTIN12, identified by c-DNA microarray analysis of infertile men, is exclusively expressed in the post meiotic male germ cells. Septin12+/+/Septin12+/− chimeric mice have multiple reproductive defects including the presence of immature sperm in the semen, and sperm with bent neck (defect of the annulus) and nuclear DNA damage. These facts make SEPTIN12 a potential sterile gene in humans. In this study, we sequenced the entire coding region of SEPTIN12 in infertile men (n = 160) and fertile controls (n = 200) and identified ten variants. Among them is the c.474 G>A variant within exon 5 that encodes part of the GTP binding domain. The variant creates a novel splice donor site that causes skipping of a portion of exon 5, resulting in a truncated protein lacking the C-terminal half of SEPTIN12. Most individuals homozygous for the c.474 A allele had teratozoospermia (abnormal sperm <14%) and their sperm showed bent tail and de-condensed nucleus with significant DNA damage. Ex vivo experiment showed truncated SEPT12 inhibits filament formation in a dose-dependent manner. This study provides the first causal link between SEPTIN12 genetic variant and male infertility with distinctive sperm pathology. Our finding also suggests vital roles of SEPT12 in sperm nuclear integrity and tail development. PMID:22479503

Developing Causal Understanding with Causal Maps: The Impact of Total Links, Temporal Flow, and Lateral Position of Outcome Nodes

ERIC Educational Resources Information Center

Jeong, Allan; Lee, Woon Jee

2012-01-01

This study examined some of the methodological approaches used by students to construct causal maps in order to determine which approaches help students understand the underlying causes and causal mechanisms in a complex system. This study tested the relationship between causal understanding (ratio of root causes correctly/incorrectly identified,…

Causal Inference and Developmental Psychology

ERIC Educational Resources Information Center

Foster, E. Michael

2010-01-01

Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

Missense variants in hMLH1 identified in patients from the German HNPCC consortium and functional studies.

PubMed

Hardt, Karin; Heick, Sven Boris; Betz, Beate; Goecke, Timm; Yazdanparast, Haniyeh; Küppers, Robin; Servan, Kati; Steinke, Verena; Rahner, Nils; Morak, Monika; Holinski-Feder, Elke; Engel, Christoph; Möslein, Gabriela; Schackert, Hans-Konrad; von Knebel Doeberitz, Magnus; Pox, Christian; Hegemann, Johannes H; Royer-Pokora, Brigitte

2011-06-01

Missense mutations of the DNA mismatch repair gene MLH1 are found in a significant fraction of patients with Lynch syndrome (hereditary nonpolyposis colorectal cancer, HNPCC) and their pathogenicity often remains unclear. We report here all 88 MLH1 missense variants identified in families from the German HNPCC consortium with clinical details of these patients/families. We investigated 23 MLH1 missense variants by two functional in vivo assays in yeast; seven map to the ATPase and 16 to the protein interaction domain. In the yeast-2-hybrid (Y2H) assay three variants in the ATPase and twelve variants in the interaction domain showed no or a reduced interaction with PMS2; seven showed a normal and one a significantly higher interaction. Using the Lys2A (14) reporter system to study the dominant negative mutator effect (DNE), 16 variants showed no or a low mutator effect, suggesting that these are nonfunctional, three were intermediate and four wild type in this assay. The DNE and Y2H results were concordant for all variants in the interaction domain, whereas slightly divergent results were obtained for variants in the ATPase domain. Analysis of the stability of the missense proteins in yeast and human embryonic kidney cells (293T) revealed a very low expression for seven of the variants in yeast and for nine in human cells. In total 15 variants were classified as deleterious, five were classified as variants of unclassified significance (VUS) and three were basically normal in the functional assays, P603R, K618R, Q689R, suggesting that these are neutral.

Comprehensive genomic analysis identifies pathogenic variants in maturity-onset diabetes of the young (MODY) patients in South India.

PubMed

Mohan, Viswanathan; Radha, Venkatesan; Nguyen, Thong T; Stawiski, Eric W; Pahuja, Kanika Bajaj; Goldstein, Leonard D; Tom, Jennifer; Anjana, Ranjit Mohan; Kong-Beltran, Monica; Bhangale, Tushar; Jahnavi, Suresh; Chandni, Radhakrishnan; Gayathri, Vijay; George, Paul; Zhang, Na; Murugan, Sakthivel; Phalke, Sameer; Chaudhuri, Subhra; Gupta, Ravi; Zhang, Jingli; Santhosh, Sam; Stinson, Jeremy; Modrusan, Zora; Ramprasad, V L; Seshagiri, Somasekar; Peterson, Andrew S

2018-02-13

Maturity-onset diabetes of the young (MODY) is an early-onset, autosomal dominant form of non-insulin dependent diabetes. Genetic diagnosis of MODY can transform patient management. Earlier data on the genetic predisposition to MODY have come primarily from familial studies in populations of European origin. In this study, we carried out a comprehensive genomic analysis of 289 individuals from India that included 152 clinically diagnosed MODY cases to identify variants in known MODY genes. Further, we have analyzed exome data to identify putative MODY relevant variants in genes previously not implicated in MODY. Functional validation of MODY relevant variants was also performed. We found MODY 3 (HNF1A; 7.2%) to be most frequently mutated followed by MODY 12 (ABCC8; 3.3%). They together account for ~ 11% of the cases. In addition to known MODY genes, we report the identification of variants in RFX6, WFS1, AKT2, NKX6-1 that may contribute to development of MODY. Functional assessment of the NKX6-1 variants showed that they are functionally impaired. Our findings showed HNF1A and ABCC8 to be the most frequently mutated MODY genes in south India. Further we provide evidence for additional MODY relevant genes, such as NKX6-1, and these require further validation.

Causal discovery and inference: concepts and recent methodological advances.

PubMed

Spirtes, Peter; Zhang, Kun

This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.

Functional and pharmacological evaluation of novel GLA variants in Fabry disease identifies six (two de novo) causative mutations and two amenable variants to the chaperone DGJ.

PubMed

Ferri, Lorenzo; Malesci, Duccio; Fioravanti, Antonella; Bagordo, Gaia; Filippini, Armando; Ficcadenti, Anna; Manna, Raffaele; Antuzzi, Daniela; Verrecchia, Elena; Donati, Ilaria; Mignani, Renzo; Cavicchi, Catia; Guerrini, Renzo; Morrone, Amelia

2018-06-01

Allelic heterogeneity is an important feature of the GLA gene for which almost 900 known genetic variants have been discovered so far. Pathogenetic GLA variants cause alpha-galactosidase A (α-Gal A) enzyme deficiency leading to the X-linked lysosomal storage disorder Fabry disease (FD). Benign GLA intronic and exonic variants (e.g. pseudodeficient p.Asp313Tyr) have also been described. Some GLA missense variants, previously deemed to be pathogenetic (e.g. p.Glu66Gln and p.Arg118Cys), they have been reclassified as benign after re-evaluation by functional and population studies. Hence, the functional role of novel GLA variants should be investigated to assess their clinical relevance. We identified six GLA variants in 4 males and 2 females who exhibited symptoms of FD: c.159C>G p.(Asn53Lys), c.400T>C p.(Tyr134His), c.680G>C (p.Arg227Pro), c.815A>T p.(Asn272Ile), c.907A>T p.(Ile303Phe) and c.1163_1165delTCC (p.Leu388del). We evaluated their impact on the α-Gal A protein by bioinformatic analysis and homology modelling, by analysis of the GLA mRNA, and by site-directed mutagenesis and in vitro expression studies. We also measured their responsiveness to the pharmacological chaperone DGJ. The six detected GLA variants cause deficient α-Gal A activity and impairment or loss of the protein wild-type structure. We found p.Asn53Lys and p.Ile303Phe variants to be susceptible to DGJ. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Two splice variants of the bovine lactoferrin gene identified in Staphylococcus aureus isolated from mastitis in dairy cattle.

PubMed

Huang, J M; Wang, Z Y; Ju, Z H; Wang, C F; Li, Q L; Sun, T; Hou, Q L; Hang, S Q; Hou, M H; Zhong, J F

2011-12-21

Bovine lactoferrin (bLF) is a member of the transferrin family; it plays an important role in the innate immune response. We identified novel splice variants of the bLF gene in mastitis-infected and healthy cows. Reverse transcription-polymerase chain reaction (RT-PCR) and clone sequencing analysis were used to screen the splice variants of the bLF gene in the mammary gland, spleen and liver tissues. One main transcript corresponding to the bLF reference sequence was found in three tissues in both healthy and mastitis-infected cows. Quantitative real-time PCR analysis showed that the expression levels of the LF gene's main transcript were not significantly different in tissues from healthy versus mastitis-infected cows. However, the new splice variant, LF-AS2, which has the exon-skipping alternative splicing pattern, was only identified in mammary glands infected with Staphylococcus aureus. Sequencing analysis showed that the new splice variant was 251 bp in length, including exon 1, part of exon 2, part of exon 16, and exon 17. We conclude that bLF may play a role in resistance to mastitis through alternative splicing mechanisms.

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability

PubMed Central

Chen, Huan; Gu, Xiao-hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-01-01

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10−10, maximum β −2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level. PMID:28155865

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability.

PubMed

Chen, Huan; Gu, Xiao-Hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-02-03

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10 -10 , maximum β -2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level.

Stable Causal Relationships Are Better Causal Relationships.

PubMed

Vasilyeva, Nadya; Blanchard, Thomas; Lombrozo, Tania

2018-05-01

We report three experiments investigating whether people's judgments about causal relationships are sensitive to the robustness or stability of such relationships across a range of background circumstances. In Experiment 1, we demonstrate that people are more willing to endorse causal and explanatory claims based on stable (as opposed to unstable) relationships, even when the overall causal strength of the relationship is held constant. In Experiment 2, we show that this effect is not driven by a causal generalization's actual scope of application. In Experiment 3, we offer evidence that stable causal relationships may be seen as better guides to action. Collectively, these experiments document a previously underappreciated factor that shapes people's causal reasoning: the stability of the causal relationship. Copyright © 2018 Cognitive Science Society, Inc.

A novel variant of FGFR3 causes proportionate short stature.

PubMed

Kant, Sarina G; Cervenkova, Iveta; Balek, Lukas; Trantirek, Lukas; Santen, Gijs W E; de Vries, Martine C; van Duyvenvoorde, Hermine A; van der Wielen, Michiel J R; Verkerk, Annemieke J M H; Uitterlinden, André G; Hannema, Sabine E; Wit, Jan M; Oostdijk, Wilma; Krejci, Pavel; Losekoot, Monique

2015-06-01

Mutations of the fibroblast growth factor receptor 3 (FGFR3) cause various forms of short stature, of which the least severe phenotype is hypochondroplasia, mainly characterized by disproportionate short stature. Testing for an FGFR3 mutation is currently not part of routine diagnostic testing in children with short stature without disproportion. A three-generation family A with dominantly transmitted proportionate short stature was studied by whole-exome sequencing to identify the causal gene mutation. Functional studies and protein modeling studies were performed to confirm the pathogenicity of the mutation found in FGFR3. We performed Sanger sequencing in a second family B with dominant proportionate short stature and identified a rare variant in FGFR3. Exome sequencing and/or Sanger sequencing was performed, followed by functional studies using transfection of the mutant FGFR3 into cultured cells; homology modeling was used to construct a three-dimensional model of the two FGFR3 variants. A novel p.M528I mutation in FGFR3 was detected in family A, which segregates with short stature and proved to be activating in vitro. In family B, a rare variant (p.F384L) was found in FGFR3, which did not segregate with short stature and showed normal functionality in vitro compared with WT. Proportionate short stature can be caused by a mutation in FGFR3. Sequencing of this gene can be considered in patients with short stature, especially when there is an autosomal dominant pattern of inheritance. However, functional studies and segregation studies should be performed before concluding that a variant is pathogenic. © 2015 European Society of Endocrinology.

Single nucleotide variants and InDels identified from whole-genome re-sequencing of Guzerat, Gyr, Girolando and Holstein cattle breeds.

PubMed

Stafuzza, Nedenia Bonvino; Zerlotini, Adhemar; Lobo, Francisco Pereira; Yamagishi, Michel Eduardo Beleza; Chud, Tatiane Cristina Seleguim; Caetano, Alexandre Rodrigues; Munari, Danísio Prado; Garrick, Dorian J; Machado, Marco Antonio; Martins, Marta Fonseca; Carvalho, Maria Raquel; Cole, John Bruce; Barbosa da Silva, Marcos Vinicius Gualberto

2017-01-01

Whole-genome re-sequencing, alignment and annotation analyses were undertaken for 12 sires representing four important cattle breeds in Brazil: Guzerat (multi-purpose), Gyr, Girolando and Holstein (dairy production). A total of approximately 4.3 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.7 to 16.4-fold genome coverage. A total of 27,441,279 single nucleotide variations (SNVs) and 3,828,041 insertions/deletions (InDels) were detected in the samples, of which 2,557,670 SNVs and 883,219 InDels were novel. The submission of these genetic variants to the dbSNP database significantly increased the number of known variants, particularly for the indicine genome. The concordance rate between genotypes obtained using the Bovine HD BeadChip array and the same variants identified by sequencing was about 99.05%. The annotation of variants identified numerous non-synonymous SNVs and frameshift InDels which could affect phenotypic variation. Functional enrichment analysis was performed and revealed that variants in the olfactory transduction pathway was over represented in all four cattle breeds, while the ECM-receptor interaction pathway was over represented in Girolando and Guzerat breeds, the ABC transporters pathway was over represented only in Holstein breed, and the metabolic pathways was over represented only in Gyr breed. The genetic variants discovered here provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Gyr, Girolando, Guzerat and Holstein breeding programs.

Single nucleotide variants and InDels identified from whole-genome re-sequencing of Guzerat, Gyr, Girolando and Holstein cattle breeds

PubMed Central

Lobo, Francisco Pereira; Yamagishi, Michel Eduardo Beleza; Chud, Tatiane Cristina Seleguim; Caetano, Alexandre Rodrigues; Munari, Danísio Prado; Garrick, Dorian J.; Machado, Marco Antonio; Martins, Marta Fonseca; Carvalho, Maria Raquel; Cole, John Bruce; Barbosa da Silva, Marcos Vinicius Gualberto

2017-01-01

Whole-genome re-sequencing, alignment and annotation analyses were undertaken for 12 sires representing four important cattle breeds in Brazil: Guzerat (multi-purpose), Gyr, Girolando and Holstein (dairy production). A total of approximately 4.3 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.7 to 16.4-fold genome coverage. A total of 27,441,279 single nucleotide variations (SNVs) and 3,828,041 insertions/deletions (InDels) were detected in the samples, of which 2,557,670 SNVs and 883,219 InDels were novel. The submission of these genetic variants to the dbSNP database significantly increased the number of known variants, particularly for the indicine genome. The concordance rate between genotypes obtained using the Bovine HD BeadChip array and the same variants identified by sequencing was about 99.05%. The annotation of variants identified numerous non-synonymous SNVs and frameshift InDels which could affect phenotypic variation. Functional enrichment analysis was performed and revealed that variants in the olfactory transduction pathway was over represented in all four cattle breeds, while the ECM-receptor interaction pathway was over represented in Girolando and Guzerat breeds, the ABC transporters pathway was over represented only in Holstein breed, and the metabolic pathways was over represented only in Gyr breed. The genetic variants discovered here provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Gyr, Girolando, Guzerat and Holstein breeding programs. PMID:28323836

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

PubMed Central

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

BETASEQ: a powerful novel method to control type-I error inflation in partially sequenced data for rare variant association testing.

PubMed

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

Identification of rare paired box 3 variant in strabismus by whole exome sequencing.

PubMed

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.

Causality and headache triggers

PubMed Central

Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.

2013-01-01

Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872

Next generation sequencing to identify novel genetic variants causative of autosomal dominant familial hypercholesterolemia associated with increased risk of coronary heart disease.

PubMed

Al-Allaf, Faisal A; Athar, Mohammad; Abduljaleel, Zainularifeen; Taher, Mohiuddin M; Khan, Wajahatullah; Ba-Hammam, Faisal A; Abalkhail, Hala; Alashwal, Abdullah

2015-07-01

Familial hypercholesterolemia (FH) is an autosomal dominant inherited disease characterized by elevated plasma low-density lipoprotein cholesterol (LDL-C). It is an autosomal dominant disease, caused by variants in Ldlr, ApoB or Pcsk9, which results in high levels of LDL-cholesterol (LDL-C) leading to early coronary heart disease. Sequencing whole genome for screening variants for FH are not suitable due to high cost. Hence, in this study we performed targeted customized sequencing of FH 12 genes (Ldlr, ApoB, Pcsk9, Abca1, Apoa2, Apoc3, Apon2, Arh, Ldlrap1, Apoc2, ApoE, and Lpl) that have been implicated in the homozygous phenotype of a proband pedigree to identify candidate variants by NGS Ion torrent PGM. Only three genes (Ldlr, ApoB, and Pcsk9) were found to be highly associated with FH based on the variant rate. The results showed that seven deleterious variants in Ldlr, ApoB, and Pcsk9 genes were pathological and were clinically significant based on predictions identified by SIFT and PolyPhen. Targeted customized sequencing is an efficient technique for screening variants among targeted FH genes. Final validation of seven deleterious variants conducted by capillary resulted to only one novel variant in Ldlr gene that was found in exon 14 (c.2026delG, p. Gly676fs). The variant found in Ldlr gene was a novel heterozygous variant derived from a male in the proband. Copyright © 2015 Elsevier B.V. All rights reserved.

Molecular genetic and functional characterization implicate muscle-restricted coiled-coil gene (MURC) as a causal gene for familial dilated cardiomyopathy.

PubMed

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.

Influence of Resting Venous Blood Volume Fraction on Dynamic Causal Modeling and System Identifiability

PubMed Central

Hu, Zhenghui; Ni, Pengyu; Wan, Qun; Zhang, Yan; Shi, Pengcheng; Lin, Qiang

2016-01-01

Changes in BOLD signals are sensitive to the regional blood content associated with the vasculature, which is known as V0 in hemodynamic models. In previous studies involving dynamic causal modeling (DCM) which embodies the hemodynamic model to invert the functional magnetic resonance imaging signals into neuronal activity, V0 was arbitrarily set to a physiolog-ically plausible value to overcome the ill-posedness of the inverse problem. It is interesting to investigate how the V0 value influences DCM. In this study we addressed this issue by using both synthetic and real experiments. The results show that the ability of DCM analysis to reveal information about brain causality depends critically on the assumed V0 value used in the analysis procedure. The choice of V0 value not only directly affects the strength of system connections, but more importantly also affects the inferences about the network architecture. Our analyses speak to a possible refinement of how the hemody-namic process is parameterized (i.e., by making V0 a free parameter); however, the conditional dependencies induced by a more complex model may create more problems than they solve. Obtaining more realistic V0 information in DCM can improve the identifiability of the system and would provide more reliable inferences about the properties of brain connectivity. PMID:27389074

Influence of Resting Venous Blood Volume Fraction on Dynamic Causal Modeling and System Identifiability.

PubMed

Hu, Zhenghui; Ni, Pengyu; Wan, Qun; Zhang, Yan; Shi, Pengcheng; Lin, Qiang

2016-07-08

Changes in BOLD signals are sensitive to the regional blood content associated with the vasculature, which is known as V0 in hemodynamic models. In previous studies involving dynamic causal modeling (DCM) which embodies the hemodynamic model to invert the functional magnetic resonance imaging signals into neuronal activity, V0 was arbitrarily set to a physiolog-ically plausible value to overcome the ill-posedness of the inverse problem. It is interesting to investigate how the V0 value influences DCM. In this study we addressed this issue by using both synthetic and real experiments. The results show that the ability of DCM analysis to reveal information about brain causality depends critically on the assumed V0 value used in the analysis procedure. The choice of V0 value not only directly affects the strength of system connections, but more importantly also affects the inferences about the network architecture. Our analyses speak to a possible refinement of how the hemody-namic process is parameterized (i.e., by making V0 a free parameter); however, the conditional dependencies induced by a more complex model may create more problems than they solve. Obtaining more realistic V0 information in DCM can improve the identifiability of the system and would provide more reliable inferences about the properties of brain connectivity.

Genetic association study of exfoliation syndrome identifies a protective rare variant at LOXL1 and five new susceptibility loci.

PubMed

Aung, Tin; Ozaki, Mineo; Lee, Mei Chin; Schlötzer-Schrehardt, Ursula; Thorleifsson, Gudmar; Mizoguchi, Takanori; Igo, Robert P; Haripriya, Aravind; Williams, Susan E; Astakhov, Yury S; Orr, Andrew C; Burdon, Kathryn P; Nakano, Satoko; Mori, Kazuhiko; Abu-Amero, Khaled; Hauser, Michael; Li, Zheng; Prakadeeswari, Gopalakrishnan; Bailey, Jessica N Cooke; Cherecheanu, Alina Popa; Kang, Jae H; Nelson, Sarah; Hayashi, Ken; Manabe, Shin-Ichi; Kazama, Shigeyasu; Zarnowski, Tomasz; Inoue, Kenji; Irkec, Murat; Coca-Prados, Miguel; Sugiyama, Kazuhisa; Järvelä, Irma; Schlottmann, Patricio; Lerner, S Fabian; Lamari, Hasnaa; Nilgün, Yildirim; Bikbov, Mukharram; Park, Ki Ho; Cha, Soon Cheol; Yamashiro, Kenji; Zenteno, Juan C; Jonas, Jost B; Kumar, Rajesh S; Perera, Shamira A; Chan, Anita S Y; Kobakhidze, Nino; George, Ronnie; Vijaya, Lingam; Do, Tan; Edward, Deepak P; de Juan Marcos, Lourdes; Pakravan, Mohammad; Moghimi, Sasan; Ideta, Ryuichi; Bach-Holm, Daniella; Kappelgaard, Per; Wirostko, Barbara; Thomas, Samuel; Gaston, Daniel; Bedard, Karen; Greer, Wenda L; Yang, Zhenglin; Chen, Xueyi; Huang, Lulin; Sang, Jinghong; Jia, Hongyan; Jia, Liyun; Qiao, Chunyan; Zhang, Hui; Liu, Xuyang; Zhao, Bowen; Wang, Ya-Xing; Xu, Liang; Leruez, Stéphanie; Reynier, Pascal; Chichua, George; Tabagari, Sergo; Uebe, Steffen; Zenkel, Matthias; Berner, Daniel; Mossböck, Georg; Weisschuh, Nicole; Hoja, Ursula; Welge-Luessen, Ulrich-Christoph; Mardin, Christian; Founti, Panayiota; Chatzikyriakidou, Anthi; Pappas, Theofanis; Anastasopoulos, Eleftherios; Lambropoulos, Alexandros; Ghosh, Arkasubhra; Shetty, Rohit; Porporato, Natalia; Saravanan, Vijayan; Venkatesh, Rengaraj; Shivkumar, Chandrashekaran; Kalpana, Narendran; Sarangapani, Sripriya; Kanavi, Mozhgan R; Beni, Afsaneh Naderi; Yazdani, Shahin; Lashay, Alireza; Naderifar, Homa; Khatibi, Nassim; Fea, Antonio; Lavia, Carlo; Dallorto, Laura; Rolle, Teresa; Frezzotti, Paolo; Paoli, Daniela; Salvi, Erika; Manunta, Paolo; Mori, Yosai; Miyata, Kazunori; Higashide, Tomomi; Chihara, Etsuo; Ishiko, Satoshi; Yoshida, Akitoshi; Yanagi, Masahide; Kiuchi, Yoshiaki; Ohashi, Tsutomu; Sakurai, Toshiya; Sugimoto, Takako; Chuman, Hideki; Aihara, Makoto; Inatani, Masaru; Miyake, Masahiro; Gotoh, Norimoto; Matsuda, Fumihiko; Yoshimura, Nagahisa; Ikeda, Yoko; Ueno, Morio; Sotozono, Chie; Jeoung, Jin Wook; Sagong, Min; Park, Kyu Hyung; Ahn, Jeeyun; Cruz-Aguilar, Marisa; Ezzouhairi, Sidi M; Rafei, Abderrahman; Chong, Yaan Fun; Ng, Xiao Yu; Goh, Shuang Ru; Chen, Yueming; Yong, Victor H K; Khan, Muhammad Imran; Olawoye, Olusola O; Ashaye, Adeyinka O; Ugbede, Idakwo; Onakoya, Adeola; Kizor-Akaraiwe, Nkiru; Teekhasaenee, Chaiwat; Suwan, Yanin; Supakontanasan, Wasu; Okeke, Suhanya; Uche, Nkechi J; Asimadu, Ifeoma; Ayub, Humaira; Akhtar, Farah; Kosior-Jarecka, Ewa; Lukasik, Urszula; Lischinsky, Ignacio; Castro, Vania; Grossmann, Rodolfo Perez; Sunaric Megevand, Gordana; Roy, Sylvain; Dervan, Edward; Silke, Eoin; Rao, Aparna; Sahay, Priti; Fornero, Pablo; Cuello, Osvaldo; Sivori, Delia; Zompa, Tamara; Mills, Richard A; Souzeau, Emmanuelle; Mitchell, Paul; Wang, Jie Jin; Hewitt, Alex W; Coote, Michael; Crowston, Jonathan G; Astakhov, Sergei Y; Akopov, Eugeny L; Emelyanov, Anton; Vysochinskaya, Vera; Kazakbaeva, Gyulli; Fayzrakhmanov, Rinat; Al-Obeidan, Saleh A; Owaidhah, Ohoud; Aljasim, Leyla Ali; Chowbay, Balram; Foo, Jia Nee; Soh, Raphael Q; Sim, Kar Seng; Xie, Zhicheng; Cheong, Augustine W O; Mok, Shi Qi; Soo, Hui Meng; Chen, Xiao Yin; Peh, Su Qin; Heng, Khai Koon; Husain, Rahat; Ho, Su-Ling; Hillmer, Axel M; Cheng, Ching-Yu; Escudero-Domínguez, Francisco A; González-Sarmiento, Rogelio; Martinon-Torres, Frederico; Salas, Antonio; Pathanapitoon, Kessara; Hansapinyo, Linda; Wanichwecharugruang, Boonsong; Kitnarong, Naris; Sakuntabhai, Anavaj; Nguyn, Hip X; Nguyn, Giang T T; Nguyn, Trình V; Zenz, Werner; Binder, Alexander; Klobassa, Daniela S; Hibberd, Martin L; Davila, Sonia; Herms, Stefan; Nöthen, Markus M; Moebus, Susanne; Rautenbach, Robyn M; Ziskind, Ari; Carmichael, Trevor R; Ramsay, Michele; Álvarez, Lydia; García, Montserrat; González-Iglesias, Héctor; Rodríguez-Calvo, Pedro P; Fernández-Vega Cueto, Luis; Oguz, Çilingir; Tamcelik, Nevbahar; Atalay, Eray; Batu, Bilge; Aktas, Dilek; Kasım, Burcu; Wilson, M Roy; Coleman, Anne L; Liu, Yutao; Challa, Pratap; Herndon, Leon; Kuchtey, Rachel W; Kuchtey, John; Curtin, Karen; Chaya, Craig J; Crandall, Alan; Zangwill, Linda M; Wong, Tien Yin; Nakano, Masakazu; Kinoshita, Shigeru; den Hollander, Anneke I; Vesti, Eija; Fingert, John H; Lee, Richard K; Sit, Arthur J; Shingleton, Bradford J; Wang, Ningli; Cusi, Daniele; Qamar, Raheel; Kraft, Peter; Pericak-Vance, Margaret A; Raychaudhuri, Soumya; Heegaard, Steffen; Kivelä, Tero; Reis, André; Kruse, Friedrich E; Weinreb, Robert N; Pasquale, Louis R; Haines, Jonathan L; Thorsteinsdottir, Unnur; Jonasson, Fridbert; Allingham, R Rand; Milea, Dan; Ritch, Robert; Kubota, Toshiaki; Tashiro, Kei; Vithana, Eranga N; Micheal, Shazia; Topouzis, Fotis; Craig, Jamie E; Dubina, Michael; Sundaresan, Periasamy; Stefansson, Kari; Wiggs, Janey L; Pasutto, Francesca; Khor, Chiea Chuen

2017-07-01

Exfoliation syndrome (XFS) is the most common known risk factor for secondary glaucoma and a major cause of blindness worldwide. Variants in two genes, LOXL1 and CACNA1A, have previously been associated with XFS. To further elucidate the genetic basis of XFS, we collected a global sample of XFS cases to refine the association at LOXL1, which previously showed inconsistent results across populations, and to identify new variants associated with XFS. We identified a rare protective allele at LOXL1 (p.Phe407, odds ratio (OR) = 25, P = 2.9 × 10 -14 ) through deep resequencing of XFS cases and controls from nine countries. A genome-wide association study (GWAS) of XFS cases and controls from 24 countries followed by replication in 18 countries identified seven genome-wide significant loci (P < 5 × 10 -8 ). We identified association signals at 13q12 (POMP), 11q23.3 (TMEM136), 6p21 (AGPAT1), 3p24 (RBMS3) and 5q23 (near SEMA6A). These findings provide biological insights into the pathology of XFS and highlight a potential role for naturally occurring rare LOXL1 variants in disease biology.

Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

ERIC Educational Resources Information Center

Johnson, Samuel G. B.; Ahn, Woo-kyoung

2015-01-01

Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge--an interconnected causal "network," where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms--causal "islands"--such that events in different…

Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.

PubMed

Johnson, Samuel G B; Ahn, Woo-kyoung

2015-09-01

Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make transitive judgments about causal chains by inferring, given A causes B and B causes C, that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links ((Experiments 1-3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4 and 5). Copyright © 2015 Cognitive Science Society, Inc.

Trans-ethnic follow-up of breast cancer GWAS hits using the preferential linkage disequilibrium approach

PubMed Central

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

Whole-exome sequencing identified a variant in EFTUD2 gene in establishing a genetic diagnosis.

PubMed

Rengasamy Venugopalan, S; Farrow, E G; Lypka, M

2017-06-01

Craniofacial anomalies are complex and have an overlapping phenotype. Mandibulofacial Dysostosis and Oculo-Auriculo-Vertebral Spectrum are conditions that share common craniofacial phenotype and present a challenge in arriving at a diagnosis. In this report, we present a case of female proband who was given a differential diagnosis of Treacher Collins syndrome or Hemifacial Microsomia without certainty. Prior genetic testing reported negative for 22q deletion and FGFR screenings. The objective of this study was to demonstrate the critical role of whole-exome sequencing in establishing a genetic diagnosis of the proband. The participants were 14½-year-old affected female proband/parent trio. Proband/parent trio were enrolled in the study. Surgical tissue sample from the proband and parental blood samples were collected and prepared for whole-exome sequencing. Illumina HiSeq 2500 instrument was used for sequencing (125 nucleotide reads/84X coverage). Analyses of variants were performed using custom-developed software, RUNES and VIKING. Variant analyses following whole-exome sequencing identified a heterozygous de novo pathogenic variant, c.259C>T (p.Gln87*), in EFTUD2 (NM_004247.3) gene in the proband. Previous studies have reported that the variants in EFTUD2 gene were associated with Mandibulofacial Dysostosis with Microcephaly. Patients with facial asymmetry, micrognathia, choanal atresia and microcephaly should be analyzed for variants in EFTUD2 gene. Next-generation sequencing techniques, such as whole-exome sequencing offer great promise to improve the understanding of etiologies of sporadic genetic diseases. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

PubMed

Barnett, Lionel; Seth, Anil K

2017-01-01

Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity

Many amino acid substitution variants identified in DNA repair genes during human population screenings are predicted to impact protein function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xi, T; Jones, I M; Mohrenweiser, H W

2003-11-03

Over 520 different amino acid substitution variants have been previously identified in the systematic screening of 91 human DNA repair genes for sequence variation. Two algorithms were employed to predict the impact of these amino acid substitutions on protein activity. Sorting Intolerant From Tolerant (SIFT) classified 226 of 508 variants (44%) as ''Intolerant''. Polymorphism Phenotyping (PolyPhen) classed 165 of 489 amino acid substitutions (34%) as ''Probably or Possibly Damaging''. Another 9-15% of the variants were classed as ''Potentially Intolerant or Damaging''. The results from the two algorithms are highly associated, with concordance in predicted impact observed for {approx}62% of themore » variants. Twenty one to thirty one percent of the variant proteins are predicted to exhibit reduced activity by both algorithms. These variants occur at slightly lower individual allele frequency than do the variants classified as ''Tolerant'' or ''Benign''. Both algorithms correctly predicted the impact of 26 functionally characterized amino acid substitutions in the APE1 protein on biochemical activity, with one exception. It is concluded that a substantial fraction of the missense variants observed in the general human population are functionally relevant. These variants are expected to be the molecular genetic and biochemical basis for the associations of reduced DNA repair capacity phenotypes with elevated cancer risk.« less

Identifying the Deleterious Effect of Rare LHX4 Allelic Variants, a Challenging Issue

PubMed Central

Rochette, Claire; Jullien, Nicolas; Saveanu, Alexandru; Caldagues, Emmanuelle; Bergada, Ignacio; Braslavsky, Debora; Pfeifer, Marija; Reynaud, Rachel; Herman, Jean-Paul; Barlier, Anne; Brue, Thierry; Enjalbert, Alain; Castinetti, Frederic

2015-01-01

LHX4 is a LIM homeodomain transcription factor involved in the early steps of pituitary ontogenesis. To date, 8 heterozygous LHX4 mutations have been reported as responsible of combined pituitary hormone deficiency (CPHD) in Humans. We identified 4 new LHX4 heterozygous allelic variants in patients with congenital hypopituitarism: W204X, delK242, N271S and Q346R. Our objective was to determine the role of LHX4 variants in patients’ phenotypes. Heterologous HEK293T cells were transfected with plasmids encoding for wild-type or mutant LHX4. Protein expression was analysed by Western Blot, and DNA binding by electro-mobility shift assay experiments. Target promoters of LHX4 were cotransfected with wild type or mutant LHX4 to test the transactivating abilities of each variant. Our results show that the W204X mutation was associated with early GH and TSH deficiencies and later onset ACTH deficiency. It led to a truncated protein unable to bind to alpha-Gsu promoter binding consensus sequence. W204X was not able to activate target promoters in vitro. Cotransfection experiments did not favour a dominant negative effect. In contrast, all other mutants were able to bind the promoters and led to an activation similar as that observed with wild type LHX4, suggesting that they were likely polymorphisms. To conclude, our study underlines the need for functional in vitro studies to ascertain the role of rare allelic variants of LHX4 in disease phenotypes. It supports the causative role of the W204X mutation in CPHD and adds up childhood onset ACTH deficiency to the clinical spectrum of the various phenotypes related to LHX4 mutations. PMID:25955177

Twelve novel HGD gene variants identified in 99 alkaptonuria patients: focus on 'black bone disease' in Italy.

PubMed

Nemethova, Martina; Radvanszky, Jan; Kadasi, Ludevit; Ascher, David B; Pires, Douglas E V; Blundell, Tom L; Porfirio, Berardino; Mannoni, Alessandro; Santucci, Annalisa; Milucci, Lia; Sestini, Silvia; Biolcati, Gianfranco; Sorge, Fiammetta; Aurizi, Caterina; Aquaron, Robert; Alsbou, Mohammed; Lourenço, Charles Marques; Ramadevi, Kanakasabapathi; Ranganath, Lakshminarayan R; Gallagher, James A; van Kan, Christa; Hall, Anthony K; Olsson, Birgitta; Sireau, Nicolas; Ayoob, Hana; Timmis, Oliver G; Sang, Kim-Hanh Le Quan; Genovese, Federica; Imrich, Richard; Rovensky, Jozef; Srinivasaraghavan, Rangan; Bharadwaj, Shruthi K; Spiegel, Ronen; Zatkova, Andrea

2016-01-01

Alkaptonuria (AKU) is an autosomal recessive disorder caused by mutations in homogentisate-1,2-dioxygenase (HGD) gene leading to the deficiency of HGD enzyme activity. The DevelopAKUre project is underway to test nitisinone as a specific treatment to counteract this derangement of the phenylalanine-tyrosine catabolic pathway. We analysed DNA of 40 AKU patients enrolled for SONIA1, the first study in DevelopAKUre, and of 59 other AKU patients sent to our laboratory for molecular diagnostics. We identified 12 novel DNA variants: one was identified in patients from Brazil (c.557T>A), Slovakia (c.500C>T) and France (c.440T>C), three in patients from India (c.469+6T>C, c.650-85A>G, c.158G>A), and six in patients from Italy (c.742A>G, c.614G>A, c.1057A>C, c.752G>A, c.119A>C, c.926G>T). Thus, the total number of potential AKU-causing variants found in 380 patients reported in the HGD mutation database is now 129. Using mCSM and DUET, computational approaches based on the protein 3D structure, the novel missense variants are predicted to affect the activity of the enzyme by three mechanisms: decrease of stability of individual protomers, disruption of protomer-protomer interactions or modification of residues in the region of the active site. We also present an overview of AKU in Italy, where so far about 60 AKU cases are known and DNA analysis has been reported for 34 of them. In this rather small group, 26 different HGD variants affecting function were described, indicating rather high heterogeneity. Twelve of these variants seem to be specific for Italy.

Model Selection Approach Suggests Causal Association between 25-Hydroxyvitamin D and Colorectal Cancer

PubMed Central

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

A method for rapid, targeted CNV genotyping identifies rare variants associated with neurocognitive disease.

PubMed

Mefford, Heather C; Cooper, Gregory M; Zerr, Troy; Smith, Joshua D; Baker, Carl; Shafer, Neil; Thorland, Erik C; Skinner, Cindy; Schwartz, Charles E; Nickerson, Deborah A; Eichler, Evan E

2009-09-01

Copy-number variants (CNVs) are substantial contributors to human disease. A central challenge in CNV-disease association studies is to characterize the pathogenicity of rare and possibly incompletely penetrant events, which requires the accurate detection of rare CNVs in large numbers of individuals. Cost and throughput issues limit our ability to perform these studies. We have adapted the Illumina BeadXpress SNP genotyping assay and developed an algorithm, SNP-Conditional OUTlier detection (SCOUT), to rapidly and accurately detect both rare and common CNVs in large cohorts. This approach is customizable, cost effective, highly parallelized, and largely automated. We applied this method to screen 69 loci in 1105 children with unexplained intellectual disability, identifying pathogenic variants in 3.1% of these individuals and potentially pathogenic variants in an additional 2.3%. We identified seven individuals (0.7%) with a deletion of 16p11.2, which has been previously associated with autism. Our results widen the phenotypic spectrum of these deletions to include intellectual disability without autism. We also detected 1.65-3.4 Mbp duplications at 16p13.11 in 1.1% of affected individuals and 350 kbp deletions at 15q11.2, near the Prader-Willi/Angelman syndrome critical region, in 0.8% of affected individuals. Compared to published CNVs in controls they are significantly (P = 4.7 x 10(-5) and 0.003, respectively) enriched in these children, supporting previously published hypotheses that they are neurocognitive disease risk factors. More generally, this approach offers a previously unavailable balance between customization, cost, and throughput for analysis of CNVs and should prove valuable for targeted CNV detection in both research and diagnostic settings.

Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm.

PubMed

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.

Exploratory Causal Analysis in Bivariate Time Series Data

NASA Astrophysics Data System (ADS)

McCracken, James M.

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data

Education and myopia: assessing the direction of causality by mendelian randomisation

PubMed Central

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

A frameshift variant of CYP2C8 was identified in a patient who suffered from rhabdomyolysis after administration of cerivastatin.

PubMed

Ishikawa, Chikako; Ozaki, Hiroshi; Nakajima, Toshiaki; Ishii, Toshihiro; Kanai, Saburo; Anjo, Saeko; Shirai, Kohji; Inoue, Ituro

2004-01-01

A hypercholesterolemic patient medicated with cerivastatin for 22 days resulted in acute rhabdomyolysis. CYP2C8 and CYP3A4 are the major enzymes responsible for the metabolism of cerivastatin, and a transporter, OATP2, contributes to uptake of cerivastatin to the liver. In this study, the patient's DNA was sequenced in order to identify a variant that would lead to the adverse effect of cerivastatin. Three nucleotide variants, 475delA, G874C, and T1551C, were found in the exons of CYP2C8. The patient was homozygous for 475delA variant that leads to frameshift and premature termination. Accordingly, the patient is most likely lacking the enzyme activity. The patient's children were both heterozygous for the mutation. The patient had three nucleotide variants in exon 4 (A388G) and exon 5 (C571T and C597T) of OATP2 that were all heterozygous. No nucleotide variation in the exons of CYP3A4 was identified. To our knowledge, this is the first report showing that the adverse effect of cerivastatin might be caused by the genetic variant of CYP2C8.

Causal imprinting in causal structure learning.

PubMed

Taylor, Eric G; Ahn, Woo-Kyoung

2012-11-01

Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. Copyright © 2012 Elsevier Inc. All rights reserved.

Causal Imprinting in Causal Structure Learning

PubMed Central

Taylor, Eric G.; Ahn, Woo-kyoung

2012-01-01

Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures “causal imprinting.” Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. PMID:22859019

Rare high-impact disease variants: properties and identifications.

PubMed

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.

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms

PubMed Central

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

Tools for Detecting Causality in Space Systems

NASA Astrophysics Data System (ADS)

Johnson, J.; Wing, S.

2017-12-01

Complex systems such as the solar and magnetospheric envivonment often exhibit patterns of behavior that suggest underlying organizing principles. Causality is a key organizing principle that is particularly difficult to establish in strongly coupled nonlinear systems, but essential for understanding and modeling the behavior of systems. While traditional methods of time-series analysis can identify linear correlations, they do not adequately quantify the distinction between causal and coincidental dependence. We discuss tools for detecting causality including: granger causality, transfer entropy, conditional redundancy, and convergent cross maps. The tools are illustrated by applications to magnetospheric and solar physics including radiation belt, Dst (a magnetospheric state variable), substorm, and solar cycle dynamics.

Regression and Data Mining Methods for Analyses of Multiple Rare Variants in the Genetic Analysis Workshop 17 Mini-Exome Data

PubMed Central

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

A Cytogenetic Abnormality and Rare Coding Variants Identify ABCA13 as a Candidate Gene in Schizophrenia, Bipolar Disorder, and Depression

PubMed Central

Knight, Helen M.; Pickard, Benjamin S.; Maclean, Alan; Malloy, Mary P.; Soares, Dinesh C.; McRae, Allan F.; Condie, Alison; White, Angela; Hawkins, William; McGhee, Kevin; van Beck, Margaret; MacIntyre, Donald J.; Starr, John M.; Deary, Ian J.; Visscher, Peter M.; Porteous, David J.; Cannon, Ronald E.; St Clair, David; Muir, Walter J.; Blackwood, Douglas H.R.

2009-01-01

Schizophrenia and bipolar disorder are leading causes of morbidity across all populations, with heritability estimates of ∼80% indicating a substantial genetic component. Population genetics and genome-wide association studies suggest an overlap of genetic risk factors between these illnesses but it is unclear how this genetic component is divided between common gene polymorphisms, rare genomic copy number variants, and rare gene sequence mutations. We report evidence that the lipid transporter gene ABCA13 is a susceptibility factor for both schizophrenia and bipolar disorder. After the initial discovery of its disruption by a chromosome abnormality in a person with schizophrenia, we resequenced ABCA13 exons in 100 cases with schizophrenia and 100 controls. Multiple rare coding variants were identified including one nonsense and nine missense mutations and compound heterozygosity/homozygosity in six cases. Variants were genotyped in additional schizophrenia, bipolar, depression (n > 1600), and control (n > 950) cohorts and the frequency of all rare variants combined was greater than controls in schizophrenia (OR = 1.93, p = 0.0057) and bipolar disorder (OR = 2.71, p = 0.00007). The population attributable risk of these mutations was 2.2% for schizophrenia and 4.0% for bipolar disorder. In a study of 21 families of mutation carriers, we genotyped affected and unaffected relatives and found significant linkage (LOD = 4.3) of rare variants with a phenotype including schizophrenia, bipolar disorder, and major depression. These data identify a candidate gene, highlight the genetic overlap between schizophrenia, bipolar disorder, and depression, and suggest that rare coding variants may contribute significantly to risk of these disorders. PMID:19944402

Identification of rare paired box 3 variant in strabismus by whole exome sequencing

PubMed Central

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

EFHC1 variants in juvenile myoclonic epilepsy: reanalysis according to NHGRI and ACMG guidelines for assigning disease causality.

PubMed

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.

Allele frequencies of variants in ultra conserved elements identify selective pressure on transcription factor binding.

PubMed

Silla, Toomas; Kepp, Katrin; Tai, E Shyong; Goh, Liang; Davila, Sonia; Catela Ivkovic, Tina; Calin, George A; Voorhoeve, P Mathijs

2014-01-01

Ultra-conserved genes or elements (UCGs/UCEs) in the human genome are extreme examples of conservation. We characterized natural variations in 2884 UCEs and UCGs in two distinct populations; Singaporean Chinese (n = 280) and Italian (n = 501) by using a pooled sample, targeted capture, sequencing approach. We identify, with high confidence, in these regions the abundance of rare SNVs (MAF<0.5%) of which 75% is not present in dbSNP137. UCEs association studies for complex human traits can use this information to model expected background variation and thus necessary power for association studies. By combining our data with 1000 Genome Project data, we show in three independent datasets that prevalent UCE variants (MAF>5%) are more often found in relatively less-conserved nucleotides within UCEs, compared to rare variants. Moreover, prevalent variants are less likely to overlap transcription factor binding site. Using SNPfold we found no significant influence of RNA secondary structure on UCE conservation. All together, these results suggest UCEs are not under selective pressure as a stretch of DNA but are under differential evolutionary pressure on the single nucleotide level.

Optimal causal inference: estimating stored information and approximating causal architecture.

PubMed

Still, Susanne; Crutchfield, James P; Ellison, Christopher J

2010-09-01

We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.

Amodal causal capture in the tunnel effect.

PubMed

Bae, Gi Yeul; Flombaum, Jonathan I

2011-01-01

In addition to identifying individual objects in the world, the visual system must also characterize the relationships between objects, for instance when objects occlude one another or cause one another to move. Here we explored the relationship between perceived causality and occlusion. Can one perceive causality in an occluded location? In several experiments, observers judged whether a centrally presented event involved a single object passing behind an occluder, or one object causally launching another (out of view and behind the occluder). With no additional context, the centrally presented event was typically judged as a non-causal pass, even when the occluding and disoccluding objects were different colors--an illusion known as the 'tunnel effect' that results from spatiotemporal continuity. However, when a synchronized context event involved an unambiguous causal launch, participants perceived a causal launch behind the occluder. This percept of an occluded causal interaction could also be driven by grouping and synchrony cues in the absence of any explicitly causal interaction. These results reinforce the hypothesis that causality is an aspect of perception. It is among the interpretations of the world that are independently available to vision when resolving ambiguity, and that the visual system can 'fill in' amodally.

Molecular Genetic and Functional Characterization Implicate Muscle-Restricted Coiled-Coil Gene (MURC) as a Causal Gene for Familial Dilated Cardiomyopathy

PubMed Central

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

Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach.

PubMed

Zou, Cunlu; Ladroue, Christophe; Guo, Shuixia; Feng, Jianfeng

2010-06-21

Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs) and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE), Bayesian networks, information theory and Granger Causality. Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins). For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.

Imputation of Exome Sequence Variants into Population- Based Samples and Blood-Cell-Trait-Associated Loci in African Americans: NHLBI GO Exome Sequencing Project

PubMed Central

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

Leveraging blood serotonin as an endophenotype to identify de novo and rare variants involved in autism.

PubMed

Chen, Rui; Davis, Lea K; Guter, Stephen; Wei, Qiang; Jacob, Suma; Potter, Melissa H; Cox, Nancy J; Cook, Edwin H; Sutcliffe, James S; Li, Bingshan

2017-01-01

Autism spectrum disorder (ASD) is one of the most highly heritable neuropsychiatric disorders, but underlying molecular mechanisms are still unresolved due to extreme locus heterogeneity. Leveraging meaningful endophenotypes or biomarkers may be an effective strategy to reduce heterogeneity to identify novel ASD genes. Numerous lines of evidence suggest a link between hyperserotonemia, i.e., elevated serotonin (5-hydroxytryptamine or 5-HT) in whole blood, and ASD. However, the genetic determinants of blood 5-HT level and their relationship to ASD are largely unknown. In this study, pursuing the hypothesis that de novo variants (DNVs) and rare risk alleles acting in a recessive mode may play an important role in predisposition of hyperserotonemia in people with ASD, we carried out whole exome sequencing (WES) in 116 ASD parent-proband trios with most (107) probands having 5-HT measurements. Combined with published ASD DNVs, we identified USP15 as having recurrent de novo loss of function mutations and discovered evidence supporting two other known genes with recurrent DNVs ( FOXP1 and KDM5B ). Genes harboring functional DNVs significantly overlap with functional/disease gene sets known to be involved in ASD etiology, including FMRP targets and synaptic formation and transcriptional regulation genes. We grouped the probands into High-5HT and Normal-5HT groups based on normalized serotonin levels, and used network-based gene set enrichment analysis (NGSEA) to identify novel hyperserotonemia-related ASD genes based on LoF and missense DNVs. We found enrichment in the High-5HT group for a gene network module (DAWN-1) previously implicated in ASD, and this points to the TGF-β pathway and cell junction processes. Through analysis of rare recessively acting variants (RAVs), we also found that rare compound heterozygotes (CHs) in the High-5HT group were enriched for loci in an ASD-associated gene set. Finally, we carried out rare variant group-wise transmission

Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

PubMed

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.

Trans-Ethnic Meta-Analysis Identifies Common and Rare Variants Associated with Hepatocyte Growth Factor Levels in the Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Larson, Nicholas B.; Berardi, Cecilia; Decker, Paul A.; Wassel, Christina L.; Kirsch, Phillip S.; Pankow, James S.; Sale, Michele M.; de Andrade, Mariza; Sicotte, Hugues; Tang, Weihong; Hanson, Naomi Q.; Tsai, Michael Y.; Taylor, Kent D.; Bielinski, Suzette J.

2015-01-01

Summary Hepatocyte growth factor (HGF) is a mesenchyme-derived pleiotropic factor that regulates cell growth, motility, mitogenesis, and morphogenesis in a variety of cells, and increased serum levels of HGF have been linked to a number of clinical and subclinical cardiovascular disease phenotypes. However, little is currently known regarding what genetic factors influence HGF levels, despite evidence of substantial genetic contributions to HGF variation. Based upon ethnicity-stratified single-variant association analysis and trans-ethnic meta-analysis of 6201 participants of the Multi-Ethnic Study of Atherosclerosis (MESA), we discovered five statistically significant common and low-frequency variants: HGF missense polymorphism rs5745687 (p.E299K) as well as four variants (rs16844364, rs4690098, rs114303452, rs3748034) within or in proximity to HGFAC. We also identified two significant ethnicity-specific gene-level associations (A1BG in African Americans; FASN in Chinese Americans) based upon low-frequency/rare variants, while meta-analysis of gene-level results identified a significant association for HGFAC. However, identified single-variant associations explained modest proportions of the total trait variation and were not significantly associated with coronary artery calcium or coronary heart disease. Our findings indicate genetic factors influencing circulating HGF levels may be complex and ethnically diverse. PMID:25998175

Causality

NASA Astrophysics Data System (ADS)

Pearl, Judea

2000-03-01

Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.

Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.

PubMed

Conlon, Anna; Taylor, Jeremy; Li, Yun; Diaz-Ordaz, Karla; Elliott, Michael

2017-11-30

Two paradigms for the evaluation of surrogate markers in randomized clinical trials have been proposed: the causal effects paradigm and the causal association paradigm. Each of these paradigms rely on assumptions that must be made to proceed with estimation and to validate a candidate surrogate marker (S) for the true outcome of interest (T). We consider the setting in which S and T are Gaussian and are generated from structural models that include an unobserved confounder. Under the assumed structural models, we relate the quantities used to evaluate surrogacy within both the causal effects and causal association frameworks. We review some of the common assumptions made to aid in estimating these quantities and show that assumptions made within one framework can imply strong assumptions within the alternative framework. We demonstrate that there is a similarity, but not exact correspondence between the quantities used to evaluate surrogacy within each framework, and show that the conditions for identifiability of the surrogacy parameters are different from the conditions, which lead to a correspondence of these quantities. Copyright © 2017 John Wiley & Sons, Ltd.

Twelve novel HGD gene variants identified in 99 alkaptonuria patients: focus on ‘black bone disease' in Italy

PubMed Central

Nemethova, Martina; Radvanszky, Jan; Kadasi, Ludevit; Ascher, David B; Pires, Douglas E V; Blundell, Tom L; Porfirio, Berardino; Mannoni, Alessandro; Santucci, Annalisa; Milucci, Lia; Sestini, Silvia; Biolcati, Gianfranco; Sorge, Fiammetta; Aurizi, Caterina; Aquaron, Robert; Alsbou, Mohammed; Marques Lourenço, Charles; Ramadevi, Kanakasabapathi; Ranganath, Lakshminarayan R; Gallagher, James A; van Kan, Christa; Hall, Anthony K; Olsson, Birgitta; Sireau, Nicolas; Ayoob, Hana; Timmis, Oliver G; Le Quan Sang, Kim-Hanh; Genovese, Federica; Imrich, Richard; Rovensky, Jozef; Srinivasaraghavan, Rangan; Bharadwaj, Shruthi K; Spiegel, Ronen; Zatkova, Andrea

2016-01-01

Alkaptonuria (AKU) is an autosomal recessive disorder caused by mutations in homogentisate-1,2-dioxygenase (HGD) gene leading to the deficiency of HGD enzyme activity. The DevelopAKUre project is underway to test nitisinone as a specific treatment to counteract this derangement of the phenylalanine-tyrosine catabolic pathway. We analysed DNA of 40 AKU patients enrolled for SONIA1, the first study in DevelopAKUre, and of 59 other AKU patients sent to our laboratory for molecular diagnostics. We identified 12 novel DNA variants: one was identified in patients from Brazil (c.557T>A), Slovakia (c.500C>T) and France (c.440T>C), three in patients from India (c.469+6T>C, c.650–85A>G, c.158G>A), and six in patients from Italy (c.742A>G, c.614G>A, c.1057A>C, c.752G>A, c.119A>C, c.926G>T). Thus, the total number of potential AKU-causing variants found in 380 patients reported in the HGD mutation database is now 129. Using mCSM and DUET, computational approaches based on the protein 3D structure, the novel missense variants are predicted to affect the activity of the enzyme by three mechanisms: decrease of stability of individual protomers, disruption of protomer-protomer interactions or modification of residues in the region of the active site. We also present an overview of AKU in Italy, where so far about 60 AKU cases are known and DNA analysis has been reported for 34 of them. In this rather small group, 26 different HGD variants affecting function were described, indicating rather high heterogeneity. Twelve of these variants seem to be specific for Italy. PMID:25804398

Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population

PubMed Central

Najmi, Laeya Abdoli; Aukrust, Ingvild; Flannick, Jason; Molnes, Janne; Burtt, Noel; Molven, Anders; Groop, Leif; Altshuler, David; Johansson, Stefan; Njølstad, Pål Rasmus

2017-01-01

Variants in HNF1A encoding hepatocyte nuclear factor 1α (HNF-1A) are associated with maturity-onset diabetes of the young form 3 (MODY 3) and type 2 diabetes. We investigated whether functional classification of HNF1A rare coding variants can inform models of diabetes risk prediction in the general population by analyzing the effect of 27 HNF1A variants identified in well-phenotyped populations (n = 4,115). Bioinformatics tools classified 11 variants as likely pathogenic and showed no association with diabetes risk (combined minor allele frequency [MAF] 0.22%; odds ratio [OR] 2.02; 95% CI 0.73–5.60; P = 0.18). However, a different set of 11 variants that reduced HNF-1A transcriptional activity to <60% of normal (wild-type) activity was strongly associated with diabetes in the general population (combined MAF 0.22%; OR 5.04; 95% CI 1.99–12.80; P = 0.0007). Our functional investigations indicate that 0.44% of the population carry HNF1A variants that result in a substantially increased risk for developing diabetes. These results suggest that functional characterization of variants within MODY genes may overcome the limitations of bioinformatics tools for the purposes of presymptomatic diabetes risk prediction in the general population. PMID:27899486

CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS

PubMed Central

Shpitser, Ilya; Tchetgen, Eric Tchetgen

2017-01-01

Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl’s front-door criterion. PMID:28919652

CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS.

PubMed

Shpitser, Ilya; Tchetgen, Eric Tchetgen

2016-12-01

Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl's front-door criterion.

Causality Analysis: Identifying the Leading Element in a Coupled Dynamical System

PubMed Central

BozorgMagham, Amir E.; Motesharrei, Safa; Penny, Stephen G.; Kalnay, Eugenia

2015-01-01

Physical systems with time-varying internal couplings are abundant in nature. While the full governing equations of these systems are typically unknown due to insufficient understanding of their internal mechanisms, there is often interest in determining the leading element. Here, the leading element is defined as the sub-system with the largest coupling coefficient averaged over a selected time span. Previously, the Convergent Cross Mapping (CCM) method has been employed to determine causality and dominant component in weakly coupled systems with constant coupling coefficients. In this study, CCM is applied to a pair of coupled Lorenz systems with time-varying coupling coefficients, exhibiting switching between dominant sub-systems in different periods. Four sets of numerical experiments are carried out. The first three cases consist of different coupling coefficient schemes: I) Periodic–constant, II) Normal, and III) Mixed Normal/Non-normal. In case IV, numerical experiment of cases II and III are repeated with imposed temporal uncertainties as well as additive normal noise. Our results show that, through detecting directional interactions, CCM identifies the leading sub-system in all cases except when the average coupling coefficients are approximately equal, i.e., when the dominant sub-system is not well defined. PMID:26125157

Salt-Sensitive Hypertension and Cardiac Hypertrophy in Transgenic Mice Expressing a Corin Variant Identified in African Americans

PubMed Central

Wang, Wei; Cui, Yujie; Shen, Jianzhong; Jiang, Jingjing; Chen, Shenghan; Peng, Jianhao; Wu, Qingyu

2012-01-01

African Americans represent a high risk population for salt-sensitive hypertension and heart disease but the underlying mechanism remains unclear. Corin is a cardiac protease that regulates blood pressure by activating natriuretic peptides. A corin gene variant (T555I/Q568P) was identified in African Americans with hypertension and cardiac hypertrophy. In this study, we test the hypothesis that the corin variant contributes to the hypertensive and cardiac hypertrophic phenotype in vivo. Transgenic mice were generated to express wild-type or T555I/Q568P variant corin in the heart under the control of α-myosin heavy chain promoter. The mice were crossed into a corin knockout background to create KO/TgWT and KO/TgV mice that expressed WT or variant corin, respectively, in the heart. Functional studies showed that KO/TgV mice had significantly higher levels of pro-atrial natriuretic peptide in the heart compared with that in control KO/TgWT mice, indicating that the corin variant was defective in processing natriuretic peptides in vivo. By radiotelemetry, corin KO/TgV mice were found to have hypertension that was sensitive to dietary salt loading. The mice also developed cardiac hypertrophy at 12–14 months of age when fed a normal salt diet or at a younger age when fed a high salt diet. The phenotype of salt-sensitive hypertension and cardiac hypertrophy in KO/TgV mice closely resembles the pathological findings in African Americans who carry the corin variant. The results indicate that corin defects may represent an important mechanism in salt-sensitive hypertension and cardiac hypertrophy in African Americans. PMID:22987923

Exploring the Epileptic Brain Network Using Time-Variant Effective Connectivity and Graph Theory.

PubMed

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.

Breast Cancer Clinical Trial of Chemotherapy and Trastuzumab: Potential Tool to Identify Cardiac Modifying Variants of Dilated Cardiomyopathy

PubMed Central

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

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

PubMed Central

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

Lupus Risk Variant Increases pSTAT1 Binding and Decreases ETS1 Expression

PubMed Central

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

Effective connectivity: Influence, causality and biophysical modeling

PubMed Central

Valdes-Sosa, Pedro A.; Roebroeck, Alard; Daunizeau, Jean; Friston, Karl

2011-01-01

This is the final paper in a Comments and Controversies series dedicated to “The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution”. We argue that discovering effective connectivity depends critically on state-space models with biophysically informed observation and state equations. These models have to be endowed with priors on unknown parameters and afford checks for model Identifiability. We consider the similarities and differences among Dynamic Causal Modeling, Granger Causal Modeling and other approaches. We establish links between past and current statistical causal modeling, in terms of Bayesian dependency graphs and Wiener–Akaike–Granger–Schweder influence measures. We show that some of the challenges faced in this field have promising solutions and speculate on future developments. PMID:21477655

Education and myopia: assessing the direction of causality by mendelian randomisation.

PubMed

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

Deep Resequencing of GWAS Loci Identifies Rare Variants in CARD9, IL23R and RNF186 That Are Associated with Ulcerative Colitis

PubMed Central

Boucher, Gabrielle; Lo, Ken Sin; Rivas, Manuel A.; Stevens, Christine; Alikashani, Azadeh; Ladouceur, Martin; Ellinghaus, David; Törkvist, Leif; Goel, Gautam; Lagacé, Caroline; Annese, Vito; Bitton, Alain; Begun, Jakob; Brant, Steve R.; Bresso, Francesca; Cho, Judy H.; Duerr, Richard H.; Halfvarson, Jonas; McGovern, Dermot P. B.; Radford-Smith, Graham; Schreiber, Stefan; Schumm, Philip L.; Sharma, Yashoda; Silverberg, Mark S.; Weersma, Rinse K.; D'Amato, Mauro; Vermeire, Severine; Franke, Andre; Lettre, Guillaume; Xavier, Ramnik J.; Daly, Mark J.; Rioux, John D.

2013-01-01

Genome-wide association studies and follow-up meta-analyses in Crohn's disease (CD) and ulcerative colitis (UC) have recently identified 163 disease-associated loci that meet genome-wide significance for these two inflammatory bowel diseases (IBD). These discoveries have already had a tremendous impact on our understanding of the genetic architecture of these diseases and have directed functional studies that have revealed some of the biological functions that are important to IBD (e.g. autophagy). Nonetheless, these loci can only explain a small proportion of disease variance (∼14% in CD and 7.5% in UC), suggesting that not only are additional loci to be found but that the known loci may contain high effect rare risk variants that have gone undetected by GWAS. To test this, we have used a targeted sequencing approach in 200 UC cases and 150 healthy controls (HC), all of French Canadian descent, to study 55 genes in regions associated with UC. We performed follow-up genotyping of 42 rare non-synonymous variants in independent case-control cohorts (totaling 14,435 UC cases and 20,204 HC). Our results confirmed significant association to rare non-synonymous coding variants in both IL23R and CARD9, previously identified from sequencing of CD loci, as well as identified a novel association in RNF186. With the exception of CARD9 (OR = 0.39), the rare non-synonymous variants identified were of moderate effect (OR = 1.49 for RNF186 and OR = 0.79 for IL23R). RNF186 encodes a protein with a RING domain having predicted E3 ubiquitin-protein ligase activity and two transmembrane domains. Importantly, the disease-coding variant is located in the ubiquitin ligase domain. Finally, our results suggest that rare variants in genes identified by genome-wide association in UC are unlikely to contribute significantly to the overall variance for the disease. Rather, these are expected to help focus functional studies of the corresponding disease loci. PMID:24068945

Contributions of Function-Altering Variants in Genes Implicated in Pubertal Timing and Body Mass for Self-Limited Delayed Puberty.

PubMed

Howard, Sasha R; Guasti, Leonardo; Poliandri, Ariel; David, Alessia; Cabrera, Claudia P; Barnes, Michael R; Wehkalampi, Karoliina; O'Rahilly, Stephen; Aiken, Catherine E; Coll, Anthony P; Ma, Marcella; Rimmington, Debra; Yeo, Giles S H; Dunkel, Leo

2018-02-01

Self-limited delayed puberty (DP) is often associated with a delay in physical maturation, but although highly heritable the causal genetic factors remain elusive. Genome-wide association studies of the timing of puberty have identified multiple loci for age at menarche in females and voice break in males, particularly in pathways controlling energy balance. We sought to assess the contribution of rare variants in such genes to the phenotype of familial DP. We performed whole-exome sequencing in 67 pedigrees (125 individuals with DP and 35 unaffected controls) from our unique cohort of familial self-limited DP. Using a whole-exome sequencing filtering pipeline one candidate gene [fat mass and obesity-associated gene (FTO)] was identified. In silico, in vitro, and mouse model studies were performed to investigate the pathogenicity of FTO variants and timing of puberty in FTO+/- mice. We identified potentially pathogenic, rare variants in genes in linkage disequilibrium with genome-wide association studies of age at menarche loci in 283 genes. Of these, five genes were implicated in the control of body mass. After filtering for segregation with trait, one candidate, FTO, was retained. Two FTO variants, found in 14 affected individuals from three families, were also associated with leanness in these patients with DP. One variant (p.Leu44Val) demonstrated altered demethylation activity of the mutant protein in vitro. Fto+/- mice displayed a significantly delayed timing of pubertal onset (P < 0.05). Mutations in genes implicated in body mass and timing of puberty in the general population may contribute to the pathogenesis of self-limited DP. Copyright © 2017 Endocrine Society

Oligonucleotide-directed mutagenesis screen to identify pathogenic Lynch syndrome-associated MSH2 DNA mismatch repair gene variants

PubMed Central

Houlleberghs, Hellen; Dekker, Marleen; Lantermans, Hildo; Kleinendorst, Roos; Dubbink, Hendrikus Jan; Hofstra, Robert M. W.; Verhoef, Senno; te Riele, Hein

2016-01-01

Single-stranded DNA oligonucleotides can achieve targeted base-pair substitution with modest efficiency but high precision. We show that “oligo targeting” can be used effectively to study missense mutations in DNA mismatch repair (MMR) genes. Inherited inactivating mutations in DNA MMR genes are causative for the cancer predisposition Lynch syndrome (LS). Although overtly deleterious mutations in MMR genes can clearly be ascribed as the cause of LS, the functional implications of missense mutations are often unclear. We developed a genetic screen to determine the pathogenicity of these variants of uncertain significance (VUS), focusing on mutator S homolog 2 (MSH2). VUS were introduced into the endogenous Msh2 gene of mouse embryonic stem cells by oligo targeting. Subsequent selection for MMR-deficient cells using the guanine analog 6-thioguanine allowed the detection of MMR-abrogating VUS. The screen was able to distinguish weak and strong pathogenic variants from polymorphisms and was used to investigate 59 Msh2 VUS. Nineteen of the 59 VUS were identified as pathogenic. Functional assays revealed that 14 of the 19 detected variants fully abrogated MMR activity and that five of the detected variants attenuated MMR activity. Implementation of the screen in clinical practice allows proper counseling of mutation carriers and treatment of their tumors. PMID:26951660

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

PubMed Central

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

High-density genotyping of immune-related loci identifies new SLE risk variants in individuals with Asian ancestry.

PubMed

Sun, Celi; Molineros, Julio E; Looger, Loren L; Zhou, Xu-Jie; Kim, Kwangwoo; Okada, Yukinori; Ma, Jianyang; Qi, Yuan-Yuan; Kim-Howard, Xana; Motghare, Prasenjeet; Bhattarai, Krishna; Adler, Adam; Bang, So-Young; Lee, Hye-Soon; Kim, Tae-Hwan; Kang, Young Mo; Suh, Chang-Hee; Chung, Won Tae; Park, Yong-Beom; Choe, Jung-Yoon; Shim, Seung Cheol; Kochi, Yuta; Suzuki, Akari; Kubo, Michiaki; Sumida, Takayuki; Yamamoto, Kazuhiko; Lee, Shin-Seok; Kim, Young Jin; Han, Bok-Ghee; Dozmorov, Mikhail; Kaufman, Kenneth M; Wren, Jonathan D; Harley, John B; Shen, Nan; Chua, Kek Heng; Zhang, Hong; Bae, Sang-Cheol; Nath, Swapan K

2016-03-01

Systemic lupus erythematosus (SLE) has a strong but incompletely understood genetic architecture. We conducted an association study with replication in 4,478 SLE cases and 12,656 controls from six East Asian cohorts to identify new SLE susceptibility loci and better localize known loci. We identified ten new loci and confirmed 20 known loci with genome-wide significance. Among the new loci, the most significant locus was GTF2IRD1-GTF2I at 7q11.23 (rs73366469, Pmeta = 3.75 × 10(-117), odds ratio (OR) = 2.38), followed by DEF6, IL12B, TCF7, TERT, CD226, PCNXL3, RASGRP1, SYNGR1 and SIGLEC6. We identified the most likely functional variants at each locus by analyzing epigenetic marks and gene expression data. Ten candidate variants are known to alter gene expression in cis or in trans. Enrichment analysis highlights the importance of these loci in B cell and T cell biology. The new loci, together with previously known loci, increase the explained heritability of SLE to 24%. The new loci share functional and ontological characteristics with previously reported loci and are possible drug targets for SLE therapeutics.

Targeted deep sequencing identifies rare loss-of-function variants in IFNGR1 for risk of atopic dermatitis complicated by eczema herpeticum.

PubMed

Gao, Li; Bin, Lianghua; Rafaels, Nicholas M; Huang, Lili; Potee, Joseph; Ruczinski, Ingo; Beaty, Terri H; Paller, Amy S; Schneider, Lynda C; Gallo, Rich; Hanifin, Jon M; Beck, Lisa A; Geha, Raif S; Mathias, Rasika A; Barnes, Kathleen C; Leung, Donald Y M

2015-12-01

A subset of atopic dermatitis is associated with increased susceptibility to eczema herpeticum (ADEH+). We previously reported that common single nucleotide polymorphisms (SNPs) in the IFN-γ (IFNG) and IFN-γ receptor 1 (IFNGR1) genes were associated with the ADEH+ phenotype. We sought to interrogate the role of rare variants in interferon pathway genes for the risk of ADEH+. We performed targeted sequencing of interferon pathway genes (IFNG, IFNGR1, IFNAR1, and IL12RB1) in 228 European American patients with AD selected according to their eczema herpeticum status, and severity was measured by using the Eczema Area and Severity Index. Replication genotyping was performed in independent samples of 219 European American and 333 African American subjects. Functional investigation of loss-of-function variants was conducted by using site-directed mutagenesis. We identified 494 single nucleotide variants encompassing 105 kb of sequence, including 145 common, 349 (70.6%) rare (minor allele frequency <5%), and 86 (17.4%) novel variants, of which 2.8% were coding synonymous, 93.3% were noncoding (64.6% intronic), and 3.8% were missense. We identified 6 rare IFNGR1 missense variants, including 3 damaging variants (Val14Met [V14M], Val61Ile, and Tyr397Cys [Y397C]) conferring a higher risk for ADEH+ (P = .031). Variants V14M and Y397C were confirmed to be deleterious, leading to partial IFNGR1 deficiency. Seven common IFNGR1 SNPs, along with common protective haplotypes (2-7 SNPs), conferred a reduced risk of ADEH+ (P = .015-.002 and P = .0015-.0004, respectively), and both SNP and haplotype associations were replicated in an independent African American sample (P = .004-.0001 and P = .001-.0001, respectively). Our results provide evidence that both genetic variants in the gene encoding IFNGR1 are implicated in susceptibility to the ADEH+ phenotype. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Population differences in platinum toxicity as a means to identify novel genetic susceptibility variants

PubMed Central

O'Donnell, Peter H.; Gamazon, Eric; Zhang, Wei; Stark, Amy L.; Kistner-Griffin, Emily O.; Huang, R. Stephanie; Dolan, M. Eileen

2010-01-01

Objectives Clinical studies show that Asians (ASN) are more susceptible to toxicities associated with platinum-containing regimens. We hypothesized that studying ASN as an `enriched phenotype' population could enable the discovery of novel genetic determinants of platinum susceptibility. Methods Using well-genotyped lymphoblastoid cell lines from the HapMap, we determined cisplatin and carboplatin cytotoxicity phenotypes (IC50s) for ASN, Caucasians (CEU), and Africans (YRI). IC50s were used in genome-wide association studies. Results ASN were most sensitive to platinums, corroborating clinical findings. ASN genome-wide association studies produced 479 single-nucleotide polymorphisms (SNPs) associating with cisplatin susceptibility and 199 with carboplatin susceptibility (P<10−4). Considering only the most significant variants (P< 9.99 × 10−6), backwards elimination was then used to identify reduced-model SNPs, which robustly described the drug phenotypes within ASN. These SNPs comprised highly descriptive genetic signatures of susceptibility, with 12 SNPs explaining more than 95% of the susceptibility phenotype variation for cisplatin, and eight SNPs approximately 75% for carboplatin. To determine the possible function of these variants in ASN, the SNPs were tested for association with differential expression of target genes. SNPs were highly associated with the expression of multiple target genes, and notably, the histone H3 family was implicated for both drugs, suggesting a platinum-class mechanism. Histone H3 has repeatedly been described as regulating the formation of platinum-DNA adducts, but this is the first evidence that specific genetic variants might mediate these interactions in a pharmacogenetic manner. Finally, to determine whether any ASN-identified SNPs might also be important in other human populations, we interrogated all 479/199 SNPs for association with platinum susceptibility in an independent combined CEU/YRI population. Three unique SNPs

Inferring Causalities in Landscape Genetics: An Extension of Wright's Causal Modeling to Distance Matrices.

PubMed

Fourtune, Lisa; Prunier, Jérôme G; Paz-Vinas, Ivan; Loot, Géraldine; Veyssière, Charlotte; Blanchet, Simon

2018-04-01

Identifying landscape features that affect functional connectivity among populations is a major challenge in fundamental and applied sciences. Landscape genetics combines landscape and genetic data to address this issue, with the main objective of disentangling direct and indirect relationships among an intricate set of variables. Causal modeling has strong potential to address the complex nature of landscape genetic data sets. However, this statistical approach was not initially developed to address the pairwise distance matrices commonly used in landscape genetics. Here, we aimed to extend the applicability of two causal modeling methods-that is, maximum-likelihood path analysis and the directional separation test-by developing statistical approaches aimed at handling distance matrices and improving functional connectivity inference. Using simulations, we showed that these approaches greatly improved the robustness of the absolute (using a frequentist approach) and relative (using an information-theoretic approach) fits of the tested models. We used an empirical data set combining genetic information on a freshwater fish species (Gobio occitaniae) and detailed landscape descriptors to demonstrate the usefulness of causal modeling to identify functional connectivity in wild populations. Specifically, we demonstrated how direct and indirect relationships involving altitude, temperature, and oxygen concentration influenced within- and between-population genetic diversity of G. occitaniae.

Short communication: Validation of 4 candidate causative trait variants in 2 cattle breeds using targeted sequence imputation.

PubMed

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.

Virtual Whipple: preoperative surgical planning with volume-rendered MDCT images to identify arterial variants relevant to the Whipple procedure.

PubMed

Brennan, Darren D; Zamboni, Giulia; Sosna, Jacob; Callery, Mark P; Vollmer, Charles M V; Raptopoulos, Vassilios D; Kruskal, Jonathan B

2007-05-01

The purposes of this study were to combine a thorough understanding of the technical aspects of the Whipple procedure with advanced rendering techniques by introducing a virtual Whipple procedure and to evaluate the utility of this new rendering technique in prediction of the arterial variants that cross the anticipated surgical resection plane. The virtual Whipple is a novel technique that follows the complex surgical steps in a Whipple procedure. Three-dimensional reconstructed angiographic images are used to identify arterial variants for the surgeon as part of the preoperative radiologic assessment of pancreatic and ampullary tumors.

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk

PubMed Central

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

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

PubMed

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.

A Genome-wide Association Study of Nonsyndromic Cleft Palate Identifies an Etiologic Missense Variant in GRHL3.

PubMed

Leslie, Elizabeth J; Liu, Huan; Carlson, Jenna C; Shaffer, John R; Feingold, Eleanor; Wehby, George; Laurie, Cecelia A; Jain, Deepti; Laurie, Cathy C; Doheny, Kimberly F; McHenry, Toby; Resick, Judith; Sanchez, Carla; Jacobs, Jennifer; Emanuele, Beth; Vieira, Alexandre R; Neiswanger, Katherine; Standley, Jennifer; Czeizel, Andrew E; Deleyiannis, Frederic; Christensen, Kaare; Munger, Ronald G; Lie, Rolv T; Wilcox, Allen; Romitti, Paul A; Field, L Leigh; Padilla, Carmencita D; Cutiongco-de la Paz, Eva Maria C; Lidral, Andrew C; Valencia-Ramirez, Luz Consuelo; Lopez-Palacio, Ana Maria; Valencia, Dora Rivera; Arcos-Burgos, Mauricio; Castilla, Eduardo E; Mereb, Juan C; Poletta, Fernando A; Orioli, Iêda M; Carvalho, Flavia M; Hecht, Jacqueline T; Blanton, Susan H; Buxó, Carmen J; Butali, Azeez; Mossey, Peter A; Adeyemo, Wasiu L; James, Olutayo; Braimah, Ramat O; Aregbesola, Babatunde S; Eshete, Mekonen A; Deribew, Milliard; Koruyucu, Mine; Seymen, Figen; Ma, Lian; de Salamanca, Javier Enríquez; Weinberg, Seth M; Moreno, Lina; Cornell, Robert A; Murray, Jeffrey C; Marazita, Mary L

2016-04-07

Cleft palate (CP) is a common birth defect occurring in 1 in 2,500 live births. Approximately half of infants with CP have a syndromic form, exhibiting other physical and cognitive disabilities. The other half have nonsyndromic CP, and to date, few genes associated with risk for nonsyndromic CP have been characterized. To identify such risk factors, we performed a genome-wide association study of this disorder. We discovered a genome-wide significant association with a missense variant in GRHL3 (p.Thr454Met [c.1361C>T]; rs41268753; p = 4.08 × 10(-9)) and replicated the result in an independent sample of case and control subjects. In both the discovery and replication samples, rs41268753 conferred increased risk for CP (OR = 8.3, 95% CI 4.1-16.8; OR = 2.16, 95% CI 1.43-3.27, respectively). In luciferase transactivation assays, p.Thr454Met had about one-third of the activity of wild-type GRHL3, and in zebrafish embryos, perturbed periderm development. We conclude that this mutation is an etiologic variant for nonsyndromic CP and is one of few functional variants identified to date for nonsyndromic orofacial clefting. This finding advances our understanding of the genetic basis of craniofacial development and might ultimately lead to improvements in recurrence risk prediction, treatment, and prognosis. Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

[Causal analysis approaches in epidemiology].

PubMed

Dumas, O; Siroux, V; Le Moual, N; Varraso, R

2014-02-01

Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the

Sequencing of sporadic Attention-Deficit Hyperactivity Disorder (ADHD) identifies novel and potentially pathogenic de novo variants and excludes overlap with genes associated with autism spectrum disorder.

PubMed

Kim, Daniel Seung; Burt, Amber A; Ranchalis, Jane E; Wilmot, Beth; Smith, Joshua D; Patterson, Karynne E; Coe, Bradley P; Li, Yatong K; Bamshad, Michael J; Nikolas, Molly; Eichler, Evan E; Swanson, James M; Nigg, Joel T; Nickerson, Deborah A; Jarvik, Gail P

2017-06-01

Attention-Deficit Hyperactivity Disorder (ADHD) has high heritability; however, studies of common variation account for <5% of ADHD variance. Using data from affected participants without a family history of ADHD, we sought to identify de novo variants that could account for sporadic ADHD. Considering a total of 128 families, two analyses were conducted in parallel: first, in 11 unaffected parent/affected proband trios (or quads with the addition of an unaffected sibling) we completed exome sequencing. Six de novo missense variants at highly conserved bases were identified and validated from four of the 11 families: the brain-expressed genes TBC1D9, DAGLA, QARS, CSMD2, TRPM2, and WDR83. Separately, in 117 unrelated probands with sporadic ADHD, we sequenced a panel of 26 genes implicated in intellectual disability (ID) and autism spectrum disorder (ASD) to evaluate whether variation in ASD/ID-associated genes were also present in participants with ADHD. Only one putative deleterious variant (Gln600STOP) in CHD1L was identified; this was found in a single proband. Notably, no other nonsense, splice, frameshift, or highly conserved missense variants in the 26 gene panel were identified and validated. These data suggest that de novo variant analysis in families with independently adjudicated sporadic ADHD diagnosis can identify novel genes implicated in ADHD pathogenesis. Moreover, that only one of the 128 cases (0.8%, 11 exome, and 117 MIP sequenced participants) had putative deleterious variants within our data in 26 genes related to ID and ASD suggests significant independence in the genetic pathogenesis of ADHD as compared to ASD and ID phenotypes. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Combining GWAS and RNA-Seq Approaches for Detection of the Causal Mutation for Hereditary Junctional Epidermolysis Bullosa in Sheep

PubMed Central

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

Combining GWAS and RNA-Seq Approaches for Detection of the Causal Mutation for Hereditary Junctional Epidermolysis Bullosa in Sheep.

PubMed

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.

Integration of bioinformatics and imaging informatics for identifying rare PSEN1 variants in Alzheimer's disease.

PubMed

Nho, Kwangsik; Horgusluoglu, Emrin; Kim, Sungeun; Risacher, Shannon L; Kim, Dokyoon; Foroud, Tatiana; Aisen, Paul S; Petersen, Ronald C; Jack, Clifford R; Shaw, Leslie M; Trojanowski, John Q; Weiner, Michael W; Green, Robert C; Toga, Arthur W; Saykin, Andrew J

2016-08-12

Pathogenic mutations in PSEN1 are known to cause familial early-onset Alzheimer's disease (EOAD) but common variants in PSEN1 have not been found to strongly influence late-onset AD (LOAD). The association of rare variants in PSEN1 with LOAD-related endophenotypes has received little attention. In this study, we performed a rare variant association analysis of PSEN1 with quantitative biomarkers of LOAD using whole genome sequencing (WGS) by integrating bioinformatics and imaging informatics. A WGS data set (N = 815) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort was used in this analysis. 757 non-Hispanic Caucasian participants underwent WGS from a blood sample and high resolution T1-weighted structural MRI at baseline. An automated MRI analysis technique (FreeSurfer) was used to measure cortical thickness and volume of neuroanatomical structures. We assessed imaging and cerebrospinal fluid (CSF) biomarkers as LOAD-related quantitative endophenotypes. Single variant analyses were performed using PLINK and gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). A total of 839 rare variants (MAF < 1/√(2 N) = 0.0257) were found within a region of ±10 kb from PSEN1. Among them, six exonic (three non-synonymous) variants were observed. A single variant association analysis showed that the PSEN1 p. E318G variant increases the risk of LOAD only in participants carrying APOE ε4 allele where individuals carrying the minor allele of this PSEN1 risk variant have lower CSF Aβ1-42 and higher CSF tau. A gene-based analysis resulted in a significant association of rare but not common (MAF ≥ 0.0257) PSEN1 variants with bilateral entorhinal cortical thickness. This is the first study to show that PSEN1 rare variants collectively show a significant association with the brain atrophy in regions preferentially affected by LOAD, providing further support for a role of PSEN1 in LOAD

Beta-glucosidase I variants with improved properties

DOEpatents

Bott, Richard R.; Kaper, Thijs; Kelemen, Bradley; Goedegebuur, Frits; Hommes, Ronaldus Wilhelmus; Kralj, Slavko; Kruithof, Paulien; Nikolaev, Igor; Van Der Kley, Wilhelmus Antonious Hendricus; Van Lieshout, Johannes Franciscus Thomas; Van Stigt Thans, Sander

2016-09-20

The present disclosure is generally directed to enzymes and in particular beta-glucosidase variants. Also described are nucleic acids encoding beta-glucosidase variants, compositions comprising beta-glucosidase variants, methods of using beta-glucosidase variants, and methods of identifying additional useful beta-glucosidase variants.

Systematic Functional Interrogation of Rare Cancer Variants Identifies Oncogenic Alleles | Office of Cancer Genomics

Cancer.gov

Cancer genome characterization efforts now provide an initial view of the somatic alterations in primary tumors. However, most point mutations occur at low frequency, and the function of these alleles remains undefined. We have developed a scalable systematic approach to interrogate the function of cancer-associated gene variants. We subjected 474 mutant alleles curated from 5,338 tumors to pooled in vivo tumor formation assays and gene expression profiling. We identified 12 transforming alleles, including two in genes (PIK3CB, POT1) that have not been shown to be tumorigenic.

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.

Whole-exome sequencing identifies common and rare variant metabolic QTLs in a Middle Eastern population.

PubMed

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.

Association of recently identified type 2 diabetes gene variants with Gestational Diabetes in Asian Indian population.

PubMed

Kanthimathi, Sekar; Chidambaram, Manickam; Bodhini, Dhanasekaran; Liju, Samuel; Bhavatharini, Aruyerchelvan; Uma, Ram; Anjana, Ranjit Mohan; Mohan, Viswanathan; Radha, Venkatesan

2017-06-01

Earlier studies have provided evidence that the gestational diabetes mellitus (GDM) and Type 2 diabetes mellitus (T2DM) share common genetic background. A recent genome wide association study (GWAS) showed a strong association of six novel gene variants with T2DM among south Asians but not with Europeans. The aim of this study was to investigate whether these variants that confer susceptibility to T2DM in Asian Indian population also correlate with GDM in Asian Indian population. In addition to these novel variants, three T2DM associated SNPs that were previously identified by GWAS in Caucasian populations, which also showed association with T2DM in south Indian population in our previous study were also evaluated for their susceptibility to GDM in our population. The study groups comprised unrelated pregnant women with GDM (n = 518) and pregnant women with normal glucose tolerance (NGT) (n = 1220). A total of nine SNPs in or near nine loci, namely AP3S2 (rs2028299), BAZ1B (rs12056034), CDKN2A/B (rs7020996), GRB14 (rs3923113), HHEX (rs7923837), HMG20A (rs7178572), HNF4A (rs4812829), ST6GAL1 (rs16861329) and VPS26A (rs1802295) were genotyped using the MassARRAY system. Among these nine SNPs that previously showed an association with T2DM in Asian Indians, HMG20A (rs7178572) and HNF4A (rs4812829) gene variants showed a significant association with GDM. The risk alleles of rs7178572 in HMG20A and rs4812829 in HNF4A gene conferred 1.24 and 1.28 times higher risk independently and about 1.44 and 1.97 times increased susceptibility to GDM for one and two risk genotypes, respectively. We report that the HMG20A (rs7178572) and HNF4A (rs4812829) variants that have previously shown a strong association with T2DM in Asian Indians also contributes significant risk to GDM in this population. This is the first report of the association of HMG20A (rs7178572) and HNF4A (rs4812829) variants with GDM.

Genetic Variants Associated with Circulating Parathyroid Hormone

PubMed Central

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.

PubMed

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.

Causal reasoning with forces

PubMed Central

Wolff, Phillip; Barbey, Aron K.

2015-01-01

Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed. PMID:25653611

Preferential association of a functional variant in complement receptor 2 with antibodies to double-stranded DNA

PubMed Central

Zhao, Jian; Giles, Brendan M; Taylor, Rhonda L; Yette, Gabriel A; Lough, Kara M; Ng, Han Leng; Abraham, Lawrence J; Wu, Hui; Kelly, Jennifer A; Glenn, Stuart B; Adler, Adam J; Williams, Adrienne H; Comeau, Mary E; Ziegler, Julie T; Marion, Miranda; Alarcón-Riquelme, Marta E; Alarcón, Graciela S; Anaya, Juan-Manuel; Bae, Sang-Cheol; Kim, Dam; Lee, Hye-Soon; Criswell, Lindsey A; Freedman, Barry I; Gilkeson, Gary S; Guthridge, Joel M; Jacob, Chaim O; James, Judith A; Kamen, Diane L; Merrill, Joan T; Sivils, Kathy Moser; Niewold, Timothy B; Petri, Michelle A; Ramsey-Goldman, Rosalind; Reveille, John D; Scofield, R Hal; Stevens, Anne M; Vilá, Luis M; Vyse, Timothy J; Kaufman, Kenneth M; Harley, John B; Langefeld, Carl D; Gaffney, Patrick M; Brown, Elizabeth E; Edberg, Jeffrey C; Kimberly, Robert P; Ulgiati, Daniela; Tsao, Betty P; Boackle, Susan A

2016-01-01

Objectives Systemic lupus erythematosus (SLE; OMIM 152700) is characterised by the production of antibodies to nuclear antigens. We previously identified variants in complement receptor 2 (CR2/CD21) that were associated with decreased risk of SLE. This study aimed to identify the causal variant for this association. Methods Genotyped and imputed genetic variants spanning CR2 were assessed for association with SLE in 15 750 case-control subjects from four ancestral groups. Allele-specific functional effects of associated variants were determined using quantitative real-time PCR, quantitative flow cytometry, electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP)-PCR. Results The strongest association signal was detected at rs1876453 in intron 1 of CR2 (pmeta=4.2×10−4, OR 0.85), specifically when subjects were stratified based on the presence of dsDNA autoantibodies (case-control pmeta=7.6×10−7, OR 0.71; case-only pmeta=1.9×10−4, OR 0.75). Although allele-specific effects on B cell CR2 mRNA or protein levels were not identified, levels of complement receptor 1 (CR1/CD35) mRNA and protein were significantly higher on B cells of subjects harbouring the minor allele (p=0.0248 and p=0.0006, respectively). The minor allele altered the formation of several DNA protein complexes by EMSA, including one containing CCCTC-binding factor (CTCF), an effect that was confirmed by ChIP-PCR. Conclusions These data suggest that rs1876453 in CR2 has long-range effects on gene regulation that decrease susceptibility to lupus. Since the minor allele at rs1876453 is preferentially associated with reduced risk of the highly specific dsDNA autoantibodies that are present in preclinical, active and severe lupus, understanding its mechanisms will have important therapeutic implications. PMID:25180293

DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in multiple sclerosis.

PubMed

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.

Identified OAS3 gene variants associated with coexistence of HBsAg and anti-HBs in chronic HBV infection.

PubMed

Wang, S; Wang, J; Fan, M-J; Li, T-Y; Pan, H; Wang, X; Liu, H-K; Lin, Q-F; Zhang, J-G; Guan, L-P; Zhernakova, D V; O'Brien, S J; Feng, Z-R; Chang, L; Dai, E-H; Lu, J-H; Xi, H-L; Zeng, Z; Yu, Y-Y; Wang, B-B

2018-03-27

The underlying mechanism of coexistence of hepatitis B surface antigen (HBsAg) and hepatitis B surface antigen antibody (anti-HBs) is still controversial. To identify the host genetic factors related to this unusual clinical phenomenon, a two-stage study was conducted in the Chinese Han population. In the first stage, we performed a case-control (1:1) age- and gender-matched study of 101 cases with concurrent HBsAg and anti-HBs and 102 controls with negative HBsAg and positive anti-HBs using whole exome sequencing. In the second validation stage, we directly sequence the 16 exons on the OAS3 gene in two dependent cohorts of 48 cases and 200 controls. Although, in the first stage, a genome-wide association study of 58,563 polymorphism variants in 101 cases and 102 controls found no significant loci (P-value ≤ .05/58563), and neither locus achieved a conservative genome-wide significance threshold (P-value ≤ 5e-08), gene-based burden analysis showed that OAS3 gene rare variants were associated with the coexistence of HBsAg and anti-HBs. (P-value = 4.127e-06 ≤ 0.05/6994). A total of 16 rare variants were screened out from 21 cases and 3 controls. In the second validation stage, one case with a stop-gained rare variant was identified. Fisher's exact test of all 149 cases and 302 controls showed that the rare coding sequence mutations were more frequent in cases vs controls (P-value = 7.299e-09, OR = 17.27, 95% CI [5.01-58.72]). Protein-coding rare variations on the OAS3 gene are associated with the coexistence of HBsAg and anti-HBs in patients with chronic HBV infection in Chinese Han population. © 2018 John Wiley & Sons Ltd.

Granger causality revisited

PubMed Central

Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

2014-01-01

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817

TMTC2 variant associated with sensorineural hearing loss and auditory neuropathy spectrum disorder in a family dyad.

PubMed

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.

A Novel BHLHE41 Variant is Associated with Short Sleep and Resistance to Sleep Deprivation in Humans

PubMed Central

Pellegrino, Renata; Kavakli, Ibrahim Halil; Goel, Namni; Cardinale, Christopher J.; Dinges, David F.; Kuna, Samuel T.; Maislin, Greg; Van Dongen, Hans P.A.; Tufik, Sergio; Hogenesch, John B.; Hakonarson, Hakon; Pack, Allan I.

2014-01-01

Study Objectives: Earlier work described a mutation in DEC2 also known as BHLHE41 (basic helix-loophelix family member e41) as causal in a family of short sleepers, who needed just 6 h sleep per night. We evaluated whether there were other variants of this gene in two well-phenotyped cohorts. Design: Sequencing of the BHLHE41 gene, electroencephalographic data, and delta power analysis and functional studies using cell-based luciferase. Results: We identified new variants of the BHLHE41 gene in two cohorts who had either acute sleep deprivation (n = 200) or chronic partial sleep deprivation (n = 217). One variant, Y362H, at another location in the same exon occurred in one twin in a dizygotic twin pair and was associated with reduced sleep duration, less recovery sleep following sleep deprivation, and fewer performance lapses during sleep deprivation than the homozygous twin. Both twins had almost identical amounts of non rapid eye movement (NREM) sleep. This variant reduced the ability of BHLHE41 to suppress CLOCK/BMAL1 and NPAS2/BMAL1 transactivation in vitro. Another variant in the same exome had no effect on sleep or response to sleep deprivation and no effect on CLOCK/BMAL1 transactivation. Random mutagenesis identified a number of other variants of BHLHE41 that affect its function. Conclusions: There are a number of mutations of BHLHE41. Mutations reduce total sleep while maintaining NREM sleep and provide resistance to the effects of sleep loss. Mutations that affect sleep also modify the normal inhibition of BHLHE41 of CLOCK/BMAL1 transactivation. Thus, clock mechanisms are likely involved in setting sleep length and the magnitude of sleep homeostasis. Citation: Pellegrino R, Kavakli IH, Goel N, Cardinale CJ, Dinges DF, Kuna ST, Maislin G, Van Dongen HP, Tufik S, Hogenesch JB, Hakonarson H, Pack AI. A novel BHLHE41 variant is associated with short sleep and resistance to sleep deprivation in humans. SLEEP 2014;37(8):1327-1336. PMID:25083013

A novel BHLHE41 variant is associated with short sleep and resistance to sleep deprivation in humans.

PubMed

Pellegrino, Renata; Kavakli, Ibrahim Halil; Goel, Namni; Cardinale, Christopher J; Dinges, David F; Kuna, Samuel T; Maislin, Greg; Van Dongen, Hans P A; Tufik, Sergio; Hogenesch, John B; Hakonarson, Hakon; Pack, Allan I

2014-08-01

Earlier work described a mutation in DEC2 also known as BHLHE41 (basic helix-loophelix family member e41) as causal in a family of short sleepers, who needed just 6 h sleep per night. We evaluated whether there were other variants of this gene in two well-phenotyped cohorts. Sequencing of the BHLHE41 gene, electroencephalographic data, and delta power analysis and functional studies using cell-based luciferase. We identified new variants of the BHLHE41 gene in two cohorts who had either acute sleep deprivation (n = 200) or chronic partial sleep deprivation (n = 217). One variant, Y362H, at another location in the same exon occurred in one twin in a dizygotic twin pair and was associated with reduced sleep duration, less recovery sleep following sleep deprivation, and fewer performance lapses during sleep deprivation than the homozygous twin. Both twins had almost identical amounts of non rapid eye movement (NREM) sleep. This variant reduced the ability of BHLHE41 to suppress CLOCK/BMAL1 and NPAS2/BMAL1 transactivation in vitro. Another variant in the same exome had no effect on sleep or response to sleep deprivation and no effect on CLOCK/BMAL1 transactivation. Random mutagenesis identified a number of other variants of BHLHE41 that affect its function. There are a number of mutations of BHLHE41. Mutations reduce total sleep while maintaining NREM sleep and provide resistance to the effects of sleep loss. Mutations that affect sleep also modify the normal inhibition of BHLHE41 of CLOCK/BMAL1 transactivation. Thus, clock mechanisms are likely involved in setting sleep length and the magnitude of sleep homeostasis. Pellegrino R, Kavakli IH, Goel N, Cardinale CJ, Dinges DF, Kuna ST, Maislin G, Van Dongen HP, Tufik S, Hogenesch JB, Hakonarson H, Pack AI. A novel BHLHE41 variant is associated with short sleep and resistance to sleep deprivation in humans. SLEEP 2014;37(8):1327-1336.

What Women Think: Cancer Causal Attributions in a Diverse Sample of Women

PubMed Central

Rodríguez, Vivian M.; Gyure, Maria E.; Corona, Rosalie; Bodurtha, Joann N.; Bowen, Deborah J.; Quillin, John M.

2014-01-01

Women hold diverse beliefs about cancer etiology, potentially affecting their use of cancer preventive behaviors. To date, research has greatly focused on the causal attributions cancer patients and survivors hold about cancer, and studies have been conducted primarily with White participants. Less is known about causal attributions held by women with and without a family history of cancer from a diverse community sample. This study sought to identify cancer causal attributions of women with and without a family history of cancer, and explore its relation to socio-cultural factors. Diverse women (60% African-American) recruited at an urban, safety-net women's health clinic (N=471) reported factors they believed cause cancer. Responses were coded into nine attributions and analyzed using chi-squares and logistic regressions. Lifestyle-choices (63%), genetics/heredity (34%), and environmental-exposures (19%) were the top causal attributions identified. Women without a family history of cancer were more likely to identify genetics/heredity as an attribution for cancer than women with a history of cancer in their families. Women who identified as White, who had a higher educational attainment, and had commercial insurance were more likely to report genetics/heredity as a causal attribution for cancer. These findings suggest that socio-cultural factors may play a role in the causal attributions individuals make about cancer, which can, in turn, inform cancer awareness and prevention messages. PMID:25398057

Granger Causality Testing with Intensive Longitudinal Data.

PubMed

Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

Inferring action structure and causal relationships in continuous sequences of human action.

PubMed

Buchsbaum, Daphna; Griffiths, Thomas L; Plunkett, Dillon; Gopnik, Alison; Baldwin, Dare

2015-02-01

In the real world, causal variables do not come pre-identified or occur in isolation, but instead are embedded within a continuous temporal stream of events. A challenge faced by both human learners and machine learning algorithms is identifying subsequences that correspond to the appropriate variables for causal inference. A specific instance of this problem is action segmentation: dividing a sequence of observed behavior into meaningful actions, and determining which of those actions lead to effects in the world. Here we present a Bayesian analysis of how statistical and causal cues to segmentation should optimally be combined, as well as four experiments investigating human action segmentation and causal inference. We find that both people and our model are sensitive to statistical regularities and causal structure in continuous action, and are able to combine these sources of information in order to correctly infer both causal relationships and segmentation boundaries. Copyright © 2014. Published by Elsevier Inc.

Identifying novel sequence variants of RNA 3D motifs

PubMed Central

Zirbel, Craig L.; Roll, James; Sweeney, Blake A.; Petrov, Anton I.; Pirrung, Meg; Leontis, Neocles B.

2015-01-01

Predicting RNA 3D structure from sequence is a major challenge in biophysics. An important sub-goal is accurately identifying recurrent 3D motifs from RNA internal and hairpin loop sequences extracted from secondary structure (2D) diagrams. We have developed and validated new probabilistic models for 3D motif sequences based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF). The SCFG/MRF models are constructed using atomic-resolution RNA 3D structures. To parameterize each model, we use all instances of each motif found in the RNA 3D Motif Atlas and annotations of pairwise nucleotide interactions generated by the FR3D software. Isostericity relations between non-Watson–Crick basepairs are used in scoring sequence variants. SCFG techniques model nested pairs and insertions, while MRF ideas handle crossing interactions and base triples. We use test sets of randomly-generated sequences to set acceptance and rejection thresholds for each motif group and thus control the false positive rate. Validation was carried out by comparing results for four motif groups to RMDetect. The software developed for sequence scoring (JAR3D) is structured to automatically incorporate new motifs as they accumulate in the RNA 3D Motif Atlas when new structures are solved and is available free for download. PMID:26130723

Comparative Analysis of Metabolic Syndrome Components in over 15,000 African Americans Identifies Pleiotropic Variants: Results from the PAGE Study

PubMed Central

Carty, Cara L.; Bhattacharjee, Samsiddhi; Haessler, Jeff; Cheng, Iona; Hindorff, Lucia A.; Aroda, Vanita; Carlson, Christopher S.; Hsu, Chun-Nan; Wilkens, Lynne; Liu, Simin; Selvin, Elizabeth; Jackson, Rebecca; North, Kari E.; Peters, Ulrike; Pankow, James S.; Chatterjee, Nilanjan; Kooperberg, Charles

2014-01-01

Background Metabolic syndrome (MetS) refers to the clustering of cardio-metabolic risk factors including dyslipidemia, central adiposity, hypertension and hyperglycemia in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS. Methods and Results Using the Metabochip array in 15,148 African Americans (AA) from the PAGE Study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models which lack power when associations for MetS components are null or have opposite effects, ASSET uses one-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With ASSET, we identify 27 SNPs in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, LPL, APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P< 2.5e-7, the Bonferroni adjusted P-value. Three loci replicate in a Hispanic population, n=5172. A novel AA-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2 and CETP variants, many with opposing effects; e.g. the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity. Conclusions We highlight a method to increase power in large-scale genomic association analyses, and report a novel variant associated with all MetS components in AA. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications. PMID:25023634

Genome-wide association study of breast cancer in Latinas identifies novel protective variants on 6q25.

PubMed

Fejerman, Laura; Ahmadiyeh, Nasim; Hu, Donglei; Huntsman, Scott; Beckman, Kenneth B; Caswell, Jennifer L; Tsung, Karen; John, Esther M; Torres-Mejia, Gabriela; Carvajal-Carmona, Luis; Echeverry, María Magdalena; Tuazon, Anna Marie D; Ramirez, Carolina; Gignoux, Christopher R; Eng, Celeste; Gonzalez-Burchard, Esteban; Henderson, Brian; Le Marchand, Loic; Kooperberg, Charles; Hou, Lifang; Agalliu, Ilir; Kraft, Peter; Lindström, Sara; Perez-Stable, Eliseo J; Haiman, Christopher A; Ziv, Elad

2014-10-20

The genetic contributions to breast cancer development among Latinas are not well understood. Here we carry out a genome-wide association study of breast cancer in Latinas and identify a genome-wide significant risk variant, located 5' of the Estrogen Receptor 1 gene (ESR1; 6q25 region). The minor allele for this variant is strongly protective (rs140068132: odds ratio (OR) 0.60, 95% confidence interval (CI) 0.53-0.67, P=9 × 10(-18)), originates from Indigenous Americans and is uncorrelated with previously reported risk variants at 6q25. The association is stronger for oestrogen receptor-negative disease (OR 0.34, 95% CI 0.21-0.54) than oestrogen receptor-positive disease (OR 0.63, 95% CI 0.49-0.80; P heterogeneity=0.01) and is also associated with mammographic breast density, a strong risk factor for breast cancer (P=0.001). rs140068132 is located within several transcription factor-binding sites and electrophoretic mobility shift assays with MCF-7 nuclear protein demonstrate differential binding of the G/A alleles at this locus. These results highlight the importance of conducting research in diverse populations.

Genome-wide association study of breast cancer in Latinas identifies novel protective variants on 6q25

PubMed Central

Fejerman, Laura; Ahmadiyeh, Nasim; Hu, Donglei; Huntsman, Scott; Beckman, Kenneth B.; Caswell, Jennifer L.; Tsung, Karen; John, Esther M.; Torres-Mejia, Gabriela; Carvajal-Carmona, Luis; Echeverry, María Magdalena; Tuazon, Anna Marie D.; Ramirez, Carolina; Carvajal-Carmona, Luis; Echeverry, María Magdalena; Bohórquez, Mabel Elena; Prieto, Rodrigo; Criollo, Ángel; Ramírez, Carolina; Estrada, Ana Patricia; Suáres, John Jairo; Mateus, Gilbert; Castro, Jorge Mario; Sánchez, Yesid; Murillo, Raúl; Lucia Serrano, Martha; Sanabria, Carolina; Olaya, Justo Germán; Bolaños, Fernando; Vélez, Alejandro; Carmona, Jenny Andrea; Vélez, Alejandro; Rodríguez, Nancy Guerrero; Serón Sousa, Cristina; Mendez, Cesar Eduardo Alvarez; Galviz, Ana Isabel Orduz; Gignoux, Christopher R.; Eng, Celeste; Gonzalez-Burchard, Esteban; Henderson, Brian; Marchand, Loic Le; Kooperberg, Charles; Hou, Lifang; Agalliu, Ilir; Kraft, Peter; Lindström, Sara; Perez-Stable, Eliseo J.; Haiman, Christopher A.; Ziv, Elad

2014-01-01

The genetic contributions to breast cancer development among Latinas are not well understood. Here we carry out a genome-wide association study of breast cancer in Latinas and identify a genome-wide significant risk variant, located 5′ of the Estrogen Receptor 1 gene (ESR1; 6q25 region). The minor allele for this variant is strongly protective (rs140068132: odds ratio (OR) 0.60, 95% confidence interval (CI) 0.53–0.67, P=9 × 10−18), originates from Indigenous Americans and is uncorrelated with previously reported risk variants at 6q25. The association is stronger for oestrogen receptor-negative disease (OR 0.34, 95% CI 0.21–0.54) than oestrogen receptor-positive disease (OR 0.63, 95% CI 0.49–0.80; P heterogeneity=0.01) and is also associated with mammographic breast density, a strong risk factor for breast cancer (P=0.001). rs140068132 is located within several transcription factor-binding sites and electrophoretic mobility shift assays with MCF-7 nuclear protein demonstrate differential binding of the G/A alleles at this locus. These results highlight the importance of conducting research in diverse populations. PMID:25327703

Whole-Exome Sequencing in Age-Related Macular Degeneration Identifies Rare Variants in COL8A1, a Component of Bruch's Membrane.

PubMed

Corominas, Jordi; Colijn, Johanna M; Geerlings, Maartje J; Pauper, Marc; Bakker, Bjorn; Amin, Najaf; Lores Motta, Laura; Kersten, Eveline; Garanto, Alejandro; Verlouw, Joost A M; van Rooij, Jeroen G J; Kraaij, Robert; de Jong, Paulus T V M; Hofman, Albert; Vingerling, Johannes R; Schick, Tina; Fauser, Sascha; de Jong, Eiko K; van Duijn, Cornelia M; Hoyng, Carel B; Klaver, Caroline C W; den Hollander, Anneke I

2018-04-26

Genome-wide association studies and targeted sequencing studies of candidate genes have identified common and rare variants that are associated with age-related macular degeneration (AMD). Whole-exome sequencing (WES) studies allow a more comprehensive analysis of rare coding variants across all genes of the genome and will contribute to a better understanding of the underlying disease mechanisms. To date, the number of WES studies in AMD case-control cohorts remains scarce and sample sizes are limited. To scrutinize the role of rare protein-altering variants in AMD cause, we performed the largest WES study in AMD to date in a large European cohort consisting of 1125 AMD patients and 1361 control participants. Genome-wide case-control association study of WES data. One thousand one hundred twenty-five AMD patients and 1361 control participants. A single variant association test of WES data was performed to detect variants that are associated individually with AMD. The cumulative effect of multiple rare variants with 1 gene was analyzed using a gene-based CMC burden test. Immunohistochemistry was performed to determine the localization of the Col8a1 protein in mouse eyes. Genetic variants associated with AMD. We detected significantly more rare protein-altering variants in the COL8A1 gene in patients (22/2250 alleles [1.0%]) than in control participants (11/2722 alleles [0.4%]; P = 7.07×10 -5 ). The association of rare variants in the COL8A1 gene is independent of the common intergenic variant (rs140647181) near the COL8A1 gene previously associated with AMD. We demonstrated that the Col8a1 protein localizes at Bruch's membrane. This study supported a role for protein-altering variants in the COL8A1 gene in AMD pathogenesis. We demonstrated the presence of Col8a1 in Bruch's membrane, further supporting the role of COL8A1 variants in AMD pathogenesis. Protein-altering variants in COL8A1 may alter the integrity of Bruch's membrane, contributing to the accumulation

The cradle of causal reasoning: newborns' preference for physical causality.

PubMed

Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca

2013-05-01

Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we asked the question about the innate origin of causal perception, never tested before at birth. Three experiments were carried out to investigate sensitivity at birth to some visual spatiotemporal cues present in a launching event. Newborn babies, only a few hours old, showed that they significantly preferred a physical causality event (i.e. Michotte's Launching effect) when matched to a delay event (i.e. a delayed launching; Experiment 1) or to a non-causal event completely identical to the causal one except for the order of the displacements of the two objects involved which was swapped temporally (Experiment 3). This preference for the launching event, moreover, also depended on the continuity of the trajectory between the objects involved in the event (Experiment 2). These results support the hypothesis that the human system possesses an early available, possibly innate basic mechanism to compute causality, such a mechanism being sensitive to the additive effect of certain well-defined spatiotemporal cues present in the causal event independently of any prior visual experience. © 2013 Blackwell Publishing Ltd.

Cause and Event: Supporting Causal Claims through Logistic Models

ERIC Educational Resources Information Center

O'Connell, Ann A.; Gray, DeLeon L.

2011-01-01

Efforts to identify and support credible causal claims have received intense interest in the research community, particularly over the past few decades. In this paper, we focus on the use of statistical procedures designed to support causal claims for a treatment or intervention when the response variable of interest is dichotomous. We identify…

Detecting causal drivers and empirical prediction of the Indian Summer Monsoon

NASA Astrophysics Data System (ADS)

Di Capua, G.; Vellore, R.; Raghavan, K.; Coumou, D.

2017-12-01

The Indian summer monsoon (ISM) is crucial for the economy, society and natural ecosystems on the Indian peninsula. Predict the total seasonal rainfall at several months lead time would help to plan effective water management strategies, improve flood or drought protection programs and prevent humanitarian crisis. However, the complexity and strong internal variability of the ISM circulation system make skillful seasonal forecasting challenging. Moreover, to adequately identify the low-frequency, and far-away processes which influence ISM behavior novel tools are needed. We applied a Response-Guided Causal Precursor Detection (RGCPD) scheme, which is a novel empirical prediction method which unites a response-guided community detection scheme with a causal discovery algorithm (CEN). These tool allow us to assess causal pathways between different components of the ISM circulation system and with far-away regions in the tropics, mid-latitudes or Arctic. The scheme has successfully been used to identify causal precursors of the Stratospheric polar vortex enabling skillful predictions at (sub) seasonal timescales (Kretschmer et al. 2016, J.Clim., Kretschmer et al. 2017, GRL). We analyze observed ISM monthly rainfall over the monsoon trough region. Applying causal discovery techniques, we identify several causal precursor communities in the fields of 2m-temperature, sea level pressure and snow depth over Eurasia. Specifically, our results suggest that surface temperature conditions in both tropical and Arctic regions contribute to ISM variability. A linear regression prediction model based on the identified set of communities has good hindcasting skills with 4-5 months lead times. Further we separate El Nino, La Nina and ENSO-neutral years from each other and find that the causal precursors are different dependent on ENSO state. The ENSO-state dependent causal precursors give even higher skill, especially for La Nina years when the ISM is relatively strong. These

Spot the difference: Causal contrasts in scientific diagrams.

PubMed

Scholl, Raphael

2016-12-01

An important function of scientific diagrams is to identify causal relationships. This commonly relies on contrasts that highlight the effects of specific difference-makers. However, causal contrast diagrams are not an obvious and easy to recognize category because they appear in many guises. In this paper, four case studies are presented to examine how causal contrast diagrams appear in a wide range of scientific reports, from experimental to observational and even purely theoretical studies. It is shown that causal contrasts can be expressed in starkly different formats, including photographs of complexly visualized macromolecules as well as line graphs, bar graphs, or plots of state spaces. Despite surface differences, however, there is a measure of conceptual unity among such diagrams. In empirical studies they often serve not only to infer and communicate specific causal claims, but also as evidence for them. The key data of some studies is given nowhere except in the diagrams. Many diagrams show multiple causal contrasts in order to demonstrate both that an effect exists and that the effect is specific - that is, to narrowly circumscribe the phenomenon to be explained. In a large range of scientific reports, causal contrast diagrams reflect the core epistemic claims of the researchers. Copyright © 2016. Published by Elsevier Ltd.

Novel pathogenic variant (c.3178G>A) in the SMC1A gene in a family with Cornelia de Lange syndrome identified by exome sequencing.

PubMed

Jang, Mi Ae; Lee, Chang Woo; Kim, Jin Kyung; Ki, Chang Seok

2015-11-01

Cornelia de Lange syndrome (CdLS) is a clinically and genetically heterogeneous congenital anomaly. Mutations in the NIPBL gene account for a half of the affected individuals. We describe a family with CdLS carrying a novel pathogenic variant of the SMC1A gene identified by exome sequencing. The proband was a 3-yr-old boy presenting with a developmental delay. He had distinctive facial features without major structural anomalies and tested negative for the NIPBL gene. His younger sister, mother, and maternal grandmother presented with mild mental retardation. By exome sequencing of the proband, a novel SMC1A variant, c.3178G>A, was identified, which was expected to cause an amino acid substitution (p.Glu1060Lys) in the highly conserved coiled-coil domain of the SMC1A protein. Sanger sequencing confirmed that the three female relatives with mental retardation also carry this variant. Our results reveal that SMC1A gene defects are associated with milder phenotypes of CdLS. Furthermore, we showed that exome sequencing could be a useful tool to identify pathogenic variants in patients with CdLS.

Normalizing the causality between time series.

PubMed

Liang, X San

2015-08-01

Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

Normalizing the causality between time series

NASA Astrophysics Data System (ADS)

Liang, X. San

2015-08-01

Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

Utilising family-based designs for detecting rare variant disease associations.

PubMed

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.

High-density genotyping of immune-related loci identifies new SLE risk variants in individuals with Asian ancestry

PubMed Central

Sun, Celi; Molineros, Julio E.; Looger, Loren L.; Zhou, Xu-jie; Kim, Kwangwoo; Okada, Yukinori; Ma, Jianyang; Qi, Yuan-yuan; Kim-Howard, Xana; Motghare, Prasenjeet; Bhattarai, Krishna; Adler, Adam; Bang, So-Young; Lee, Hye-Soon; Kim, Tae-Hwan; Kang, Young Mo; Suh, Chang-Hee; Chung, Won Tae; Park, Yong-Beom; Choe, Jung-Yoon; Shim, Seung Cheol; Kochi, Yuta; Suzuki, Akari; Kubo, Michiaki; Sumida, Takayuki; Yamamoto, Kazuhiko; Lee, Shin-Seok; Kim, Young Jin; Han, Bok-Ghee; Dozmorov, Mikhail; Kaufman, Kenneth M.; Wren, Jonathan D.; Harley, John B.; Shen, Nan; Chua, Kek Heng; Zhang, Hong; Bae, Sang-Cheol; Nath, Swapan K.

2016-01-01

Systemic lupus erythematosus (SLE) has a strong but incompletely understood genetic architecture. We conducted an association study with replication in 4,492 SLE cases and 12,675 controls from six East-Asian cohorts, to identify novel and better localize known SLE susceptibility loci. We identified 10 novel loci as well as 20 known loci with genome-wide significance. Among the novel loci, the most significant was GTF2IRD1-GTF2I at 7q11.23 (rs73366469, Pmeta=3.75×10−117, OR=2.38), followed by DEF6, IL12B, TCF7, TERT, CD226, PCNXL3, RASGRP1, SYNGR1 and SIGLEC6. We localized the most likely functional variants for each locus by analyzing epigenetic marks and gene regulation data. Ten putative variants are known to alter cis- or trans-gene expression. Enrichment analysis highlights the importance of these loci in B- and T-cell biology. Together with previously known loci, the explained heritability of SLE increases to 24%. Novel loci share functional and ontological characteristics with previously reported loci, and are possible drug targets for SLE therapeutics. PMID:26808113

In search of causal variants: refining disease association signals using cross-population contrasts.

PubMed

Saccone, Nancy L; Saccone, Scott F; Goate, Alison M; Grucza, Richard A; Hinrichs, Anthony L; Rice, John P; Bierut, Laura J

2008-08-29

Genome-wide association (GWA) using large numbers of single nucleotide polymorphisms (SNPs) is now a powerful, state-of-the-art approach to mapping human disease genes. When a GWA study detects association between a SNP and the disease, this signal usually represents association with a set of several highly correlated SNPs in strong linkage disequilibrium. The challenge we address is to distinguish among these correlated loci to highlight potential functional variants and prioritize them for follow-up. We implemented a systematic method for testing association across diverse population samples having differing histories and LD patterns, using a logistic regression framework. The hypothesis is that important underlying biological mechanisms are shared across human populations, and we can filter correlated variants by testing for heterogeneity of genetic effects in different population samples. This approach formalizes the descriptive comparison of p-values that has typified similar cross-population fine-mapping studies to date. We applied this method to correlated SNPs in the cholinergic nicotinic receptor gene cluster CHRNA5-CHRNA3-CHRNB4, in a case-control study of cocaine dependence composed of 504 European-American and 583 African-American samples. Of the 10 SNPs genotyped in the r2 > or = 0.8 bin for rs16969968, three demonstrated significant cross-population heterogeneity and are filtered from priority follow-up; the remaining SNPs include rs16969968 (heterogeneity p = 0.75). Though the power to filter out rs16969968 is reduced due to the difference in allele frequency in the two groups, the results nevertheless focus attention on a smaller group of SNPs that includes the non-synonymous SNP rs16969968, which retains a similar effect size (odds ratio) across both population samples. Filtering out SNPs that demonstrate cross-population heterogeneity enriches for variants more likely to be important and causative. Our approach provides an important and effective

Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

PubMed Central

Christophersen, Ingrid E.; Rienstra, Michiel; Roselli, Carolina; Yin, Xiaoyan; Geelhoed, Bastiaan; Barnard, John; Lin, Honghuang; Arking, Dan E.; Smith, Albert V.; Albert, Christine M.; Chaffin, Mark; Tucker, Nathan R.; Li, Molong; Klarin, Derek; Bihlmeyer, Nathan A; Low, Siew-Kee; Weeke, Peter E.; Müller-Nurasyid, Martina; Smith, J. Gustav; Brody, Jennifer A.; Niemeijer, Maartje N.; Dörr, Marcus; Trompet, Stella; Huffman, Jennifer; Gustafsson, Stefan; Schurman, Claudia; Kleber, Marcus E.; Lyytikäinen, Leo-Pekka; Seppälä, Ilkka; Malik, Rainer; Horimoto, Andrea R. V. R.; Perez, Marco; Sinisalo, Juha; Aeschbacher, Stefanie; Thériault, Sébastien; Yao, Jie; Radmanesh, Farid; Weiss, Stefan; Teumer, Alexander; Choi, Seung Hoan; Weng, Lu-Chen; Clauss, Sebastian; Deo, Rajat; Rader, Daniel J.; Shah, Svati; Sun, Albert; Hopewell, Jemma C.; Debette, Stephanie; Chauhan, Ganesh; Yang, Qiong; Worrall, Bradford B.; Paré, Guillaume; Kamatani, Yoichiro; Hagemeijer, Yanick P.; Verweij, Niek; Siland, Joylene E.; Kubo, Michiaki; Smith, Jonathan D.; Van Wagoner, David R.; Bis, Joshua C.; Perz, Siegfried; Psaty, Bruce M.; Ridker, Paul M.; Magnani, Jared W.; Harris, Tamara B.; Launer, Lenore J.; Shoemaker, M. Benjamin; Padmanabhan, Sandosh; Haessler, Jeffrey; Bartz, Traci M.; Waldenberger, Melanie; Lichtner, Peter; Arendt, Marina; Krieger, Jose E.; Kähönen, Mika; Risch, Lorenz; Mansur, Alfredo J.; Peters, Annette; Smith, Blair H.; Lind, Lars; Scott, Stuart A.; Lu, Yingchang; Bottinger, Erwin B.; Hernesniemi, Jussi; Lindgren, Cecilia M.; Wong, Jorge; Huang, Jie; Eskola, Markku; Morris, Andrew P.; Ford, Ian; Reiner, Alex P.; Delgado, Graciela; Chen, Lin Y.; Chen, Yii-Der Ida; Sandhu, Roopinder K.; Li, Man; Boerwinkle, Eric; Eisele, Lewin; Lannfelt, Lars; Rost, Natalia; Anderson, Christopher D.; Taylor, Kent D.; Campbell, Archie; Magnusson, Patrik K.; Porteous, David; Hocking, Lynne J.; Vlachopoulou, Efthymia; Pedersen, Nancy L.; Nikus, Kjell; Orho-Melander, Marju; Hamsten, Anders; Heeringa, Jan; Denny, Joshua C.; Kriebel, Jennifer; Darbar, Dawood; Newton-Cheh, Christopher; Shaffer, Christian; Macfarlane, Peter W.; Heilmann, Stefanie; Almgren, Peter; Huang, Paul L.; Sotoodehnia, Nona; Soliman, Elsayed Z.; Uitterlinden, Andre G.; Hofman, Albert; Franco, Oscar H.; Völker, Uwe; Jöckel, Karl-Heinz; Sinner, Moritz F.; Lin, Henry J.; Guo, Xiuqing; Dichgans, Martin; Ingelsson, Erik; Kooperberg, Charles; Melander, Olle; Loos, Ruth J. F.; Laurikka, Jari; Conen, David; Rosand, Jonathan; van der Harst, Pim; Lokki, Marja-Liisa; Kathiresan, Sekar; Pereira, Alexandre; Jukema, J. Wouter; Hayward, Caroline; Rotter, Jerome I.; März, Winfried; Lehtimäki, Terho; Stricker, Bruno H.; Chung, Mina K.; Felix, Stephan B.; Gudnason, Vilmundur; Alonso, Alvaro; Roden, Dan M.; Kääb, Stefan; Chasman, Daniel I.; Heckbert, Susan R.; Benjamin, Emelia J.; Tanaka, Toshihiro; Lunetta, Kathryn L.; Lubitz, Steven A.; Ellinor, Patrick T.

2017-01-01

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death.1,2 Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups.3–7 To further define the genetic basis of atrial fibrillation, we performed large-scale, multi-racial meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 18,398 individuals with atrial fibrillation and 91,536 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,806 cases and 132,612 referents. We identified 12 novel genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate new potential targets for drug discovery.8 PMID:28416818

Description and analysis of genetic variants in French hereditary breast and ovarian cancer families recorded in the UMD-BRCA1/BRCA2 databases.

PubMed

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.

Sensory Impairments and Autism: A Re-Examination of Causal Modelling

ERIC Educational Resources Information Center

Gerrard, Sue; Rugg, Gordon

2009-01-01

Sensory impairments are widely reported in autism, but remain largely unexplained by existing models. This article examines Kanner's causal reasoning and identifies unsupported assumptions implicit in later empirical work. Our analysis supports a heterogeneous causal model for autistic characteristics. We propose that the development of a…

Estimating the causal influence of body mass index on risk of Parkinson disease: A Mendelian randomisation study

PubMed Central

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

Repeated causal decision making.

PubMed

Hagmayer, York; Meder, Björn

2013-01-01

Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in such situations and how they use their knowledge to adapt to changes in the decision context. Our studies show that decision makers' behavior is strongly contingent on their causal beliefs and that people exploit their causal knowledge to assess the consequences of changes in the decision problem. A high consistency between hypotheses about causal structure, causally expected values, and actual choices was observed. The experiments show that (a) existing causal hypotheses guide the interpretation of decision feedback, (b) consequences of decisions are used to revise existing causal beliefs, and (c) decision makers use the experienced feedback to induce a causal model of the choice situation even when they have no initial causal hypotheses, which (d) enables them to adapt their choices to changes of the decision problem. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Functional analyses of rare genetic variants in complement component C9 identified in patients with age-related macular degeneration.

PubMed

Kremlitzka, Mariann; Geerlings, Maartje J; de Jong, Sarah; Bakker, Bjorn; Nilsson, Sara C; Fauser, Sascha; Hoyng, Carel B; de Jong, Eiko K; den Hollander, Anneke I; Blom, Anna M

2018-05-14

Age-related macular degeneration (AMD) is a progressive disease of the central retina and the leading cause of irreversible vision loss in the western world. The involvement of abnormal complement activation in AMD has been suggested by association of variants in genes encoding complement proteins with disease development. A low-frequency variant (p.P167S) in the complement component C9 (C9) gene was recently shown to be highly associated with AMD, however its functional outcome remains largely unexplored. In this study, we reveal five novel rare genetic variants (p.M45L, p.F62S, p.G126R, p.T170I and p.A529T) in C9 in AMD patients, and evaluate their functional effects in vitro together with the previously identified (p.R118W and p.P167S) C9 variants.Our results demonstrate that the concentration of C9 is significantly elevated in patients' sera carrying the p.M45L, p.F62S, p.P167S and p.A529T variants compared to non-carrier controls. However, no difference can be observed in soluble terminal complement complex levels between the carrier and non-carrier groups. Comparing the polymerization of the C9 variants we reveal that the p.P167S mutant spontaneously aggregates, while the other mutant proteins (except for C9 p.A529T) fail to polymerize in the presence of zinc. Altered polymerization of the p.F62S and p.P167S proteins associated with decreased lysis of sheep erythrocytes and ARPE-19 cells by carriers' sera. Our data suggest that the analysed C9 variants affect only the secretion and polymerization of C9, without influencing its classical lytic activity. Future studies need to be performed to understand the implications of the altered polymerization of C9 in AMD pathology.

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

PubMed

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.

Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series

NASA Astrophysics Data System (ADS)

Liang, X. S.

2017-12-01

Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a "Giant" for the computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming

Investigating causal associations between use of nicotine, alcohol, caffeine and cannabis: a two-sample bidirectional Mendelian randomization study.

PubMed

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.

CDKL5 variants

PubMed Central

Kalscheuer, Vera M.; Hennig, Friederike; Leonard, Helen; Downs, Jenny; Clarke, Angus; Benke, Tim A.; Armstrong, Judith; Pineda, Mercedes; Bailey, Mark E.S.; Cobb, Stuart R.

2017-01-01

Objective: To provide new insights into the interpretation of genetic variants in a rare neurologic disorder, CDKL5 deficiency, in the contexts of population sequencing data and an updated characterization of the CDKL5 gene. Methods: We analyzed all known potentially pathogenic CDKL5 variants by combining data from large-scale population sequencing studies with CDKL5 variants from new and all available clinical cohorts and combined this with computational methods to predict pathogenicity. Results: The study has identified several variants that can be reclassified as benign or likely benign. With the addition of novel CDKL5 variants, we confirm that pathogenic missense variants cluster in the catalytic domain of CDKL5 and reclassify a purported missense variant as having a splicing consequence. We provide further evidence that missense variants in the final 3 exons are likely to be benign and not important to disease pathology. We also describe benign splicing and nonsense variants within these exons, suggesting that isoform hCDKL5_5 is likely to have little or no neurologic significance. We also use the available data to make a preliminary estimate of minimum incidence of CDKL5 deficiency. Conclusions: These findings have implications for genetic diagnosis, providing evidence for the reclassification of specific variants previously thought to result in CDKL5 deficiency. Together, these analyses support the view that the predominant brain isoform in humans (hCDKL5_1) is crucial for normal neurodevelopment and that the catalytic domain is the primary functional domain. PMID:29264392

Gene panel sequencing improves the diagnostic work-up of patients with idiopathic erythrocytosis and identifies new mutations

PubMed Central

Camps, Carme; Petousi, Nayia; Bento, Celeste; Cario, Holger; Copley, Richard R.; McMullin, Mary Frances; van Wijk, Richard; Ratcliffe, Peter J.; Robbins, Peter A.; Taylor, Jenny C.

2016-01-01

Erythrocytosis is a rare disorder characterized by increased red cell mass and elevated hemoglobin concentration and hematocrit. Several genetic variants have been identified as causes for erythrocytosis in genes belonging to different pathways including oxygen sensing, erythropoiesis and oxygen transport. However, despite clinical investigation and screening for these mutations, the cause of disease cannot be found in a considerable number of patients, who are classified as having idiopathic erythrocytosis. In this study, we developed a targeted next-generation sequencing panel encompassing the exonic regions of 21 genes from relevant pathways (~79 Kb) and sequenced 125 patients with idiopathic erythrocytosis. The panel effectively screened 97% of coding regions of these genes, with an average coverage of 450×. It identified 51 different rare variants, all leading to alterations of protein sequence, with 57 out of 125 cases (45.6%) having at least one of these variants. Ten of these were known erythrocytosis-causing variants, which had been missed following existing diagnostic algorithms. Twenty-two were novel variants in erythrocytosis-associated genes (EGLN1, EPAS1, VHL, BPGM, JAK2, SH2B3) and in novel genes included in the panel (e.g. EPO, EGLN2, HIF3A, OS9), some with a high likelihood of functionality, for which future segregation, functional and replication studies will be useful to provide further evidence for causality. The rest were classified as polymorphisms. Overall, these results demonstrate the benefits of using a gene panel rather than existing methods in which focused genetic screening is performed depending on biochemical measurements: the gene panel improves diagnostic accuracy and provides the opportunity for discovery of novel variants. PMID:27651169

Gene panel sequencing improves the diagnostic work-up of patients with idiopathic erythrocytosis and identifies new mutations.

PubMed

Camps, Carme; Petousi, Nayia; Bento, Celeste; Cario, Holger; Copley, Richard R; McMullin, Mary Frances; van Wijk, Richard; Ratcliffe, Peter J; Robbins, Peter A; Taylor, Jenny C

2016-11-01

Erythrocytosis is a rare disorder characterized by increased red cell mass and elevated hemoglobin concentration and hematocrit. Several genetic variants have been identified as causes for erythrocytosis in genes belonging to different pathways including oxygen sensing, erythropoiesis and oxygen transport. However, despite clinical investigation and screening for these mutations, the cause of disease cannot be found in a considerable number of patients, who are classified as having idiopathic erythrocytosis. In this study, we developed a targeted next-generation sequencing panel encompassing the exonic regions of 21 genes from relevant pathways (~79 Kb) and sequenced 125 patients with idiopathic erythrocytosis. The panel effectively screened 97% of coding regions of these genes, with an average coverage of 450×. It identified 51 different rare variants, all leading to alterations of protein sequence, with 57 out of 125 cases (45.6%) having at least one of these variants. Ten of these were known erythrocytosis-causing variants, which had been missed following existing diagnostic algorithms. Twenty-two were novel variants in erythrocytosis-associated genes (EGLN1, EPAS1, VHL, BPGM, JAK2, SH2B3) and in novel genes included in the panel (e.g. EPO, EGLN2, HIF3A, OS9), some with a high likelihood of functionality, for which future segregation, functional and replication studies will be useful to provide further evidence for causality. The rest were classified as polymorphisms. Overall, these results demonstrate the benefits of using a gene panel rather than existing methods in which focused genetic screening is performed depending on biochemical measurements: the gene panel improves diagnostic accuracy and provides the opportunity for discovery of novel variants. Copyright© Ferrata Storti Foundation.

DEVELOPMENT PLAN FOR THE CAUSAL ANALYSIS ...

EPA Pesticide Factsheets

The Causal Analysis/Diagnosis Decision Information System (CADDIS) is a web-based system that provides technical support for states, tribes and other users of the Office of Water's Stressor Identification Guidance. The Stressor Identification Guidance provides a rigorous and scientifically defensible method for determining the causes of biological impairments of aquatic ecosystems. It is being used by states as part of the TMDL process and is being applied to other impaired ecosystems such as Superfund sites. However, because of the complexity of causal relationships in ecosystems, and because the guidance includes a strength-of-evidence analysis which uses multiple causal considerations, the process is complex and information intensive. CADDIS helps users deal with that inherent complexity. Increasingly, the regulatory, remedial, and restoration actions taken to manage impaired environments are based on measurement and analysis of the biotic community. When an aquatic assemblage has been identified as impaired, an accurate and defensible assessment of the cause can help ensure that appropriate actions are taken. The U.S. EPA's Stressor Identification Guidance describes a methodology for identifying the most likely causes of observed impairments in aquatic systems. Stressor identification requires extensive knowledge of the mechanisms, symptoms, and stressor-response relationships for various specific stressors as well as the ability to use that knowledge in a

Association between lipoprotein(a) level and type 2 diabetes: no evidence for a causal role of lipoprotein(a) and insulin.

PubMed

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.

A generalized least-squares framework for rare-variant analysis in family data.

PubMed

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.

Rare variants and cardiovascular disease.

PubMed

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.

Genetically elevated non-fasting triglycerides and calculated remnant cholesterol as causal risk factors for myocardial infarction.

PubMed

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.

A Causal Model of Sentence Recall: Effects of Familiarity, Concreteness, Comprehensibility, and Interestingness.

ERIC Educational Resources Information Center

Sadoski, Mark; And Others

1993-01-01

Presents and tests a theoretically derived causal model of the recall of sentences. Notes that the causal model identifies familiarity and concreteness as causes of comprehensibility; familiarity, concreteness, and comprehensibility as causes of interestingness; and all the identified variables as causes of both immediate and delayed recall.…

Relativistic causality

NASA Astrophysics Data System (ADS)

Valente, Giovanni; Owen Weatherall, James

2014-11-01

Relativity theory is often taken to include, or to imply, a prohibition on superluminal propagation of causal processes. Yet, what exactly the prohibition on superluminal propagation amounts to and how one should deal with its possible violation have remained open philosophical problems, both in the context of the metaphysics of causation and the foundations of physics. In particular, recent work in philosophy of physics has focused on the causal structure of spacetime in relativity theory and on how this causal structure manifests itself in our most fundamental theories of matter. These topics were the subject of a workshop on "Relativistic Causality in Quantum Field Theory and General Relativity" that we organized (along with John Earman) at the Center for Philosophy of Science in Pittsburgh on April 5-7, 2013. The present Special Issue comprises contributions by speakers in that workshop as well as several other experts exploring different aspects of relativistic causality. We are grateful to the journal for hosting this Special Issue, to the journal's managing editor, Femke Kuiling, for her help and support in putting the issue together, and to the authors and the referees for their excellent work.

Encoding dependence in Bayesian causal networks

USDA-ARS?s Scientific Manuscript database

Bayesian networks (BNs) represent complex, uncertain spatio-temporal dynamics by propagation of conditional probabilities between identifiable states with a testable causal interaction model. Typically, they assume random variables are discrete in time and space with a static network structure that ...

A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome.

PubMed

Keel, B N; Nonneman, D J; Rohrer, G A

2017-08-01

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 more significant effect on phenotypic variation than do other types of genetic variants. Hence, a comprehensive list of these functional variants would be of considerable interest in swine genomic studies, particularly those targeting fertility and production traits. Whole-genome sequence was obtained from 72 of the founders of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the founding boars (12 Duroc and 12 Landrace) and 48 Yorkshire-Landrace composite sows. Sequence reads were mapped to the Sscrofa10.2 genome build, resulting in a mean of 6.1 fold (×) coverage per genome. A total of 22 342 915 high confidence SNPs were identified from the sequenced genomes. These included 21 million previously reported SNPs and 79% of the 62 163 SNPs on the PorcineSNP60 BeadChip assay. Variation was detected in the coding sequence or untranslated regions (UTRs) of 87.8% of the genes in the porcine genome: loss-of-function variants were predicted in 504 genes, 10 202 genes contained nonsynonymous variants, 10 773 had variation in UTRs and 13 010 genes contained synonymous variants. Approximately 139 000 SNPs were classified as loss-of-function, nonsynonymous or regulatory, which suggests that over 99% of the variation detected in our pigs could potentially be ignored, allowing us to focus on a much smaller number of functional SNPs during future analyses. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Whole-Exome Sequencing to Identify Rare Variants and Gene Networks that Increase Susceptibility to Scleroderma in African Americans.

PubMed

Gourh, Pravitt; Remmers, Elaine F; Boyden, Steven E; Alexander, Theresa; Morgan, Nadia D; Shah, Ami A; Mayes, Maureen D; Doumatey, Ayo; Bentley, Amy R; Shriner, Daniel; Domsic, Robyn T; Medsger, Thomas A; Steen, Virginia D; Ramos, Paula S; Silver, Richard M; Korman, Benjamin; Varga, John; Schiopu, Elena; Khanna, Dinesh; Hsu, Vivien; Gordon, Jessica K; Saketkoo, Lesley Ann; Gladue, Heather; Kron, Brynn; Criswell, Lindsey A; Derk, Chris T; Bridges, S Louis; Shanmugam, Victoria K; Kolstad, Kathleen D; Chung, Lorinda; Jan, Reem; Bernstein, Elana J; Goldberg, Avram; Trojanowski, Marcin; Kafaja, Suzanne; Maksimowicz-McKinnon, Kathleen M; Mullikin, James C; Adeyemo, Adebowale; Rotimi, Charles; Boin, Francesco; Kastner, Daniel L; Wigley, Fredrick M

2018-05-06

Whole-exome sequencing (WES) studies in systemic sclerosis (SSc) patients of European American (EA) ancestry have identified variants in the ATP8B4 gene and enrichment of variants in genes in the extracellular matrix (ECM)-related pathway increasing SSc susceptibility. Our goal was to evaluate the association of the ATP8B4 gene and the ECM-related pathway with SSc in a cohort of African Americans (AA). SSc patients of AA ancestry were enrolled from 23 academic centers across the United States under the Genome Research in African American Scleroderma Patients (GRASP) consortium. Unrelated AA individuals without serological evidence of autoimmunity enrolled in the Howard University Family Study were used as unaffected controls. Functional variants in genes reported in the two WES studies in EA SSc were selected for gene association testing using the optimized sequence kernel association test (SKAT-O) and pathway analysis by Ingenuity pathway analysis in 379 patients and 411 controls. Principal components analysis demonstrated that the patients and controls had similar ancestral backgrounds with about equal proportions of mean European admixture. Using SKAT-O, we examined the association of individual genes that were previously reported in EAs, and none remained significant including ATP8B4 (P U nCorr =0.98). However, we confirm the previously reported association of the ECM-related pathway with enrichment of variants within the COL13A1, COL18A1, COL22A1, COL4A3, COL4A4, COL5A2, PROK1, and SERPINE1 genes (P C orr =1.95×10 -4 ). This is the largest genetic study in AAs with SSc to date, corroborating the role of functional variants aggregating in a fibrotic pathway and increasing SSc susceptibility. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome

PubMed Central

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

Screening for single nucleotide variants, small indels and exon deletions with a next-generation sequencing based gene panel approach for Usher syndrome.

PubMed

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.

Causality re-established.

PubMed

D'Ariano, Giacomo Mauro

2018-07-13

Causality has never gained the status of a 'law' or 'principle' in physics. Some recent literature has even popularized the false idea that causality is a notion that should be banned from theory. Such misconception relies on an alleged universality of the reversibility of the laws of physics, based either on the determinism of classical theory, or on the multiverse interpretation of quantum theory, in both cases motivated by mere interpretational requirements for realism of the theory. Here, I will show that a properly defined unambiguous notion of causality is a theorem of quantum theory, which is also a falsifiable proposition of the theory. Such a notion of causality appeared in the literature within the framework of operational probabilistic theories. It is a genuinely theoretical notion, corresponding to establishing a definite partial order among events, in the same way as we do by using the future causal cone on Minkowski space. The notion of causality is logically completely independent of the misidentified concept of 'determinism', and, being a consequence of quantum theory, is ubiquitous in physics. In addition, as classical theory can be regarded as a restriction of quantum theory, causality holds also in the classical case, although the determinism of the theory trivializes it. I then conclude by arguing that causality naturally establishes an arrow of time. This implies that the scenario of the 'block Universe' and the connected 'past hypothesis' are incompatible with causality, and thus with quantum theory: they are both doomed to remain mere interpretations and, as such, are not falsifiable, similar to the hypothesis of 'super-determinism'.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'. © 2018 The Author(s).

Learning to learn causal models.

PubMed

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.

Causal mechanisms and balancing selection inferred from genetic associations with polycystic ovary syndrome.

PubMed

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.

Disease causality extraction based on lexical semantics and document-clause frequency from biomedical literature.

PubMed

Lee, Dong-Gi; Shin, Hyunjung

2017-05-18

Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this paper, we propose a causal disease network that implements disease causality through text mining on biomedical literature. To identify the causality between diseases, the proposed method includes two schemes: the first is the lexicon-based causality term strength, which provides the causal strength on a variety of causality terms based on lexicon analysis. The second is the frequency-based causality strength, which determines the direction and strength of causality based on document and clause frequencies in the literature. We applied the proposed method to 6,617,833 PubMed literature, and chose 195 diseases to construct a causal disease network. From all possible pairs of disease nodes in the network, 1011 causal pairs of 149 diseases were extracted. The resulting network was compared with that of a previous study. In terms of both coverage and quality, the proposed method showed outperforming results; it determined 2.7 times more causalities and showed higher correlation with associated diseases than the existing method. This research has novelty in which the proposed method circumvents the limitations of time and cost in applying all possible causalities in biological experiments and it is a more advanced text mining technique by defining the concepts of causality term strength.

Examining the causal association of fasting glucose with blood pressure in healthy children and adolescents: a Mendelian randomization study employing common genetic variants of fasting glucose.

PubMed

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.

Targeted Deep Sequencing Identifies Rare ‘loss-of-function’ Variants in IFNGR1 for Risk of Atopic Dermatitis Complicated by Eczema Herpeticum

PubMed Central

Gao, Li; Rafaels, Nicholas M; Huang, Lili; Potee, Joseph; Ruczinski, Ingo; Beaty, Terri H.; Paller, Amy S.; Schneider, Lynda C.; Gallo, Rich; Hanifin, Jon M.; Beck, Lisa A.; Geha, Raif S.; Mathias, Rasika A.; Leung, Donald Y. M.

2015-01-01

Background A subset of atopic dermatitis (AD) is associated with increased susceptibility to eczema herpeticum (ADEH+). We previously reported that common single nucleotide polymorphisms (SNPs) in interferon-gamma (IFNG) and receptor 1 (IFNGR1) were associated with ADEH+ phenotype. Objective To interrogate the role of rare variants in IFN-pathway genes for risk of ADEH+. Methods We performed targeted sequencing of interferon-pathway genes (IFNG, IFNGR1, IFNAR1 and IL12RB1) in 228 European American (EA) AD patients selected according to their EH status and severity measured by Eczema Area and Severity Index (EASI). Replication genotyping was performed in independent samples of 219 EA and 333 African Americans (AA). Functional investigation of ‘loss-of-function’ variants was conducted using site-directed mutagenesis. Results We identified 494 single nucleotide variants (SNVs) encompassing 105kb of sequence, including 145 common, 349 (70.6%) rare (minor allele frequency (MAF) <5%) and 86 (17.4%) novel variants, of which 2.8% were coding-synonymous, 93.3% were non-coding (64.6% intronic), and 3.8% were missense. We identified six rare IFNGR1 missense including three damaging variants (Val14Met (V14M), Val61Ile and Tyr397Cys (Y397C)) conferring a higher risk for ADEH+ (P=0.031). Variants V14M and Y397C were confirmed to be deleterious leading to partial IFNGR1 deficiency. Seven common IFNGR1 SNPs, along with common protective haplotypes (2 to 7-SNPs) conferred a reduced risk of ADEH+ (P=0.015-0.002, P=0.0015-0.0004, respectively), and both SNP and haplotype associations were replicated in an independent AA sample (P=0.004-0.0001 and P=0.001-0.0001, respectively). Conclusion Our results provide evidence that both genetic variants in the gene encoding IFNGR1 are implicated in susceptibility to the ADEH+ phenotype. CAPSULE SUMMARY We provided the first evidence that rare functional IFNGR1 mutations contribute to a defective systemic IFN-γ immune response that accounts

A variant of special relativity and long-distance astronomy.

PubMed

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.

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.

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma.

PubMed

Darlington, T M; Pimentel, R; Smith, K; Bakian, A V; Jerominski, L; Cardon, J; Camp, N J; Callor, W B; Grey, T; Singleton, M; Yandell, M; Renshaw, P F; Yurgelun-Todd, D A; Gray, D; Coon, H

2014-10-21

Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12,000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedigrees with increased risk for suicide completion. A number of medical conditions co-occur with suicide, including asthma, and this study was undertaken to identify genetic risk common to asthma and suicide. This study tests the hypothesis that a particular comorbid condition may identify a more homogeneous genetic subgroup, facilitating the identification of specific genetic risk factors in that group. From pedigrees at increased risk for suicide, we identified three pedigrees also at significantly increased familial risk for asthma. Five suicide decedents from each of these pedigrees, plus an additional three decedents not from these pedigrees with diagnosed asthma, and 10 decedents with close relatives with asthma were genotyped. Results were compared with 183 publicly available unaffected control exomes from 1000 Genomes and CEPH (Centre d'etude du polymorphisme humain) samples genotyped on the same platform. A further 432 suicide decedents were also genotyped as non-asthma suicide controls. Genotyping was done using the Infinium HumanExome BeadChip. For analysis, we used the pedigree extension of Variant Annotation, Analysis and Search Tool (pVAAST) to calculate the disease burden of each gene. The Phenotype Driven Variant Ontological Re-ranking tool (Phevor) then re-ranked our pVAAST results in context of the phenotype. Using asthma as a seed phenotype, Phevor traversed biomedical ontologies and identified genes with similar biological properties to those known to

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma

PubMed Central

Darlington, T M; Pimentel, R; Smith, K; Bakian, A V; Jerominski, L; Cardon, J; Camp, N J; Callor, W B; Grey, T; Singleton, M; Yandell, M; Renshaw, P F; Yurgelun-Todd, D A; Gray, D; Coon, H

2014-01-01

Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12 000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedigrees with increased risk for suicide completion. A number of medical conditions co-occur with suicide, including asthma, and this study was undertaken to identify genetic risk common to asthma and suicide. This study tests the hypothesis that a particular comorbid condition may identify a more homogeneous genetic subgroup, facilitating the identification of specific genetic risk factors in that group. From pedigrees at increased risk for suicide, we identified three pedigrees also at significantly increased familial risk for asthma. Five suicide decedents from each of these pedigrees, plus an additional three decedents not from these pedigrees with diagnosed asthma, and 10 decedents with close relatives with asthma were genotyped. Results were compared with 183 publicly available unaffected control exomes from 1000 Genomes and CEPH (Centre d'etude du polymorphisme humain) samples genotyped on the same platform. A further 432 suicide decedents were also genotyped as non-asthma suicide controls. Genotyping was done using the Infinium HumanExome BeadChip. For analysis, we used the pedigree extension of Variant Annotation, Analysis and Search Tool (pVAAST) to calculate the disease burden of each gene. The Phenotype Driven Variant Ontological Re-ranking tool (Phevor) then re-ranked our pVAAST results in context of the phenotype. Using asthma as a seed phenotype, Phevor traversed biomedical ontologies and identified genes with similar biological properties to those known to

Imputation of adverse drug reactions: Causality assessment in hospitals

PubMed Central

Mastroianni, Patricia de Carvalho

2017-01-01

Background & objectives Different algorithms have been developed to standardize the causality assessment of adverse drug reactions (ADR). Although most share common characteristics, the results of the causality assessment are variable depending on the algorithm used. Therefore, using 10 different algorithms, the study aimed to compare inter-rater and multi-rater agreement for ADR causality assessment and identify the most consistent to hospitals. Methods Using ten causality algorithms, four judges independently assessed the first 44 cases of ADRs reported during the first year of implementation of a risk management service in a medium complexity hospital in the state of Sao Paulo (Brazil). Owing to variations in the terminology used for causality, the equivalent imputation terms were grouped into four categories: definite, probable, possible and unlikely. Inter-rater and multi-rater agreement analysis was performed by calculating the Cohen´s and Light´s kappa coefficients, respectively. Results None of the algorithms showed 100% reproducibility in the causal imputation. Fair inter-rater and multi-rater agreement was found. Emanuele (1984) and WHO-UMC (2010) algorithms showed a fair rate of agreement between the judges (k = 0.36). Interpretation & conclusions Although the ADR causality assessment algorithms were poorly reproducible, our data suggest that WHO-UMC algorithm is the most consistent for imputation in hospitals, since it allows evaluating the quality of the report. However, to improve the ability of assessing the causality using algorithms, it is necessary to include criteria for the evaluation of drug-related problems, which may be related to confounding variables that underestimate the causal association. PMID:28166274

Rare Variant Association Test with Multiple Phenotypes

PubMed Central

Lee, Selyeong; Won, Sungho; Kim, Young Jin; Kim, Yongkang; Kim, Bong-Jo; Park, Taesung

2016-01-01

Although genome-wide association studies (GWAS) have now discovered thousands of genetic variants associated with common traits, such variants cannot explain the large degree of “missing heritability,” likely due to rare variants. The advent of next generation sequencing technology has allowed rare variant detection and association with common traits, often by investigating specific genomic regions for rare variant effects on a trait. Although multiply correlated phenotypes are often concurrently observed in GWAS, most studies analyze only single phenotypes, which may lessen statistical power. To increase power, multivariate analyses, which consider correlations between multiple phenotypes, can be used. However, few existing multi-variant analyses can identify rare variants for assessing multiple phenotypes. Here, we propose Multivariate Association Analysis using Score Statistics (MAAUSS), to identify rare variants associated with multiple phenotypes, based on the widely used Sequence Kernel Association Test (SKAT) for a single phenotype. We applied MAAUSS to Whole Exome Sequencing (WES) data from a Korean population of 1,058 subjects, to discover genes associated with multiple traits of liver function. We then assessed validation of those genes by a replication study, using an independent dataset of 3,445 individuals. Notably, we detected the gene ZNF620 among five significant genes. We then performed a simulation study to compare MAAUSS's performance with existing methods. Overall, MAAUSS successfully conserved type 1 error rates and in many cases, had a higher power than the existing methods. This study illustrates a feasible and straightforward approach for identifying rare variants correlated with multiple phenotypes, with likely relevance to missing heritability. PMID:28039885

Using Genetic Variation to Explore the Causal Effect of Maternal Pregnancy Adiposity on Future Offspring Adiposity: A Mendelian Randomisation Study

PubMed Central

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

Targeted Resequencing and Functional Testing Identifies Low-Frequency Missense Variants in the Gene Encoding GARP as Significant Contributors to Atopic Dermatitis Risk.

PubMed

Manz, Judith; Rodríguez, Elke; ElSharawy, Abdou; Oesau, Eva-Maria; Petersen, Britt-Sabina; Baurecht, Hansjörg; Mayr, Gabriele; Weber, Susanne; Harder, Jürgen; Reischl, Eva; Schwarz, Agatha; Novak, Natalija; Franke, Andre; Weidinger, Stephan

2016-12-01

Gene-mapping studies have consistently identified a susceptibility locus for atopic dermatitis and other inflammatory diseases on chromosome band 11q13.5, with the strongest association observed for a common variant located in an intergenic region between the two annotated genes C11orf30 and LRRC32. Using a targeted resequencing approach we identified low-frequency and rare missense mutations within the LRRC32 gene encoding the protein GARP, a receptor on activated regulatory T cells that binds latent transforming growth factor-β. Subsequent association testing in more than 2,000 atopic dermatitis patients and 2,000 control subjects showed a significant excess of these LRRC32 variants in individuals with atopic dermatitis. Structural protein modeling and bioinformatic analysis predicted a disruption of protein transport upon these variants, and overexpression assays in CD4 + CD25 - T cells showed a significant reduction in surface expression of the mutated protein. Consistently, flow cytometric (FACS) analyses of different T-cell subtypes obtained from atopic dermatitis patients showed a significantly reduced surface expression of GARP and a reduced conversion of CD4 + CD25 - T cells into regulatory T cells, along with lower expression of latency-associated protein upon stimulation in carriers of the LRRC32 A407T variant. These results link inherited disturbances of transforming growth factor-β signaling with atopic dermatitis risk. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

GWAS of cerebrospinal fluid tau levels identifies risk variants for Alzheimer's disease.

PubMed

Cruchaga, Carlos; Kauwe, John S K; Harari, Oscar; Jin, Sheng Chih; Cai, Yefei; Karch, Celeste M; Benitez, Bruno A; Jeng, Amanda T; Skorupa, Tara; Carrell, David; Bertelsen, Sarah; Bailey, Matthew; McKean, David; Shulman, Joshua M; De Jager, Philip L; Chibnik, Lori; Bennett, David A; Arnold, Steve E; Harold, Denise; Sims, Rebecca; Gerrish, Amy; Williams, Julie; Van Deerlin, Vivianna M; Lee, Virginia M-Y; Shaw, Leslie M; Trojanowski, John Q; Haines, Jonathan L; Mayeux, Richard; Pericak-Vance, Margaret A; Farrer, Lindsay A; Schellenberg, Gerard D; Peskind, Elaine R; Galasko, Douglas; Fagan, Anne M; Holtzman, David M; Morris, John C; Goate, Alison M

2013-04-24

Cerebrospinal fluid (CSF) tau, tau phosphorylated at threonine 181 (ptau), and Aβ₄₂ are established biomarkers for Alzheimer's disease (AD) and have been used as quantitative traits for genetic analyses. We performed the largest genome-wide association study for cerebrospinal fluid (CSF) tau/ptau levels published to date (n = 1,269), identifying three genome-wide significant loci for CSF tau and ptau: rs9877502 (p = 4.89 × 10⁻⁹ for tau) located at 3q28 between GEMC1 and OSTN, rs514716 (p = 1.07 × 10⁻⁸ and p = 3.22 × 10⁻⁹ for tau and ptau, respectively), located at 9p24.2 within GLIS3 and rs6922617 (p = 3.58 × 10⁻⁸ for CSF ptau) at 6p21.1 within the TREM gene cluster, a region recently reported to harbor rare variants that increase AD risk. In independent data sets, rs9877502 showed a strong association with risk for AD, tangle pathology, and global cognitive decline (p = 2.67 × 10⁻⁴, 0.039, 4.86 × 10⁻⁵, respectively) illustrating how this endophenotype-based approach can be used to identify new AD risk loci. Copyright © 2013 Elsevier Inc. All rights reserved.

Applying causal mediation analysis to personality disorder research.

PubMed

Walters, Glenn D

2018-01-01

This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Causal Analysis After Haavelmo

PubMed Central

Heckman, James; Pinto, Rodrigo

2014-01-01

Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123

Entanglement, holography and causal diamonds

NASA Astrophysics Data System (ADS)

de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.

2016-08-01

We argue that the degrees of freedom in a d-dimensional CFT can be reorganized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2 d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.

Rare ADH Variant Constellations are Specific for Alcohol Dependence

PubMed Central

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

Genetic evidence of a causal effect of insulin resistance on branched-chain amino acid levels.

PubMed

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

A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference.

PubMed

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.

The discourse of causal explanations in school science

NASA Astrophysics Data System (ADS)

Slater, Tammy Jayne Anne

Researchers and educators working from a systemic functional linguistic perspective have provided a body of work on science discourse which offers an excellent starting point for examining the linguistic aspects of the development of causal discourse in school science, discourse which Derewianka (1995) claimed is critical to success in secondary school. No work has yet described the development of causal language by identifying the linguistic features present in oral discourse or by comparing the causal discourse of native and non-native (ESL) speakers of English. The current research responds to this gap by examining the oral discourse collected from ESL and non-ESL students at the primary and high school grades. Specifically, it asks the following questions: (1) How do the teachers and students in these four contexts develop causal explanations and their relevant taxonomies through classroom interactions? (2) What are the causal discourse features being used by the students in these four contexts to construct oral causal explanations? The findings of the social practice analysis showed that the teachers in the four contexts differed in their approaches to teaching, with the primary school mainstream teacher focusing largely on the hands-on practice , the primary school ESL teacher moving from practice to theory, the high school mainstream teacher moving from theory to practice, and the high school ESL teacher relying primarily on theory. The findings from the quantitative, small corpus approach suggest that the developmental path of cause which has been identified in the writing of experts shows up not only in written texts but also in the oral texts which learners construct. Moreover, this move appears when the discourse of high school ESL and non-ESL students is compared, suggesting a developmental progression in the acquisition of these features by these students. The findings also reveal that the knowledge constructed, as shown by the concept maps created

The role of causal criteria in causal inferences: Bradford Hill's "aspects of association".

PubMed

Ward, Andrew C

2009-06-17

As noted by Wesley Salmon and many others, causal concepts are ubiquitous in every branch of theoretical science, in the practical disciplines and in everyday life. In the theoretical and practical sciences especially, people often base claims about causal relations on applications of statistical methods to data. However, the source and type of data place important constraints on the choice of statistical methods as well as on the warrant attributed to the causal claims based on the use of such methods. For example, much of the data used by people interested in making causal claims come from non-experimental, observational studies in which random allocations to treatment and control groups are not present. Thus, one of the most important problems in the social and health sciences concerns making justified causal inferences using non-experimental, observational data. In this paper, I examine one method of justifying such inferences that is especially widespread in epidemiology and the health sciences generally - the use of causal criteria. I argue that while the use of causal criteria is not appropriate for either deductive or inductive inferences, they do have an important role to play in inferences to the best explanation. As such, causal criteria, exemplified by what Bradford Hill referred to as "aspects of [statistical] associations", have an indispensible part to play in the goal of making justified causal claims.

The role of causal criteria in causal inferences: Bradford Hill's "aspects of association"

PubMed Central

Ward, Andrew C

2009-01-01

As noted by Wesley Salmon and many others, causal concepts are ubiquitous in every branch of theoretical science, in the practical disciplines and in everyday life. In the theoretical and practical sciences especially, people often base claims about causal relations on applications of statistical methods to data. However, the source and type of data place important constraints on the choice of statistical methods as well as on the warrant attributed to the causal claims based on the use of such methods. For example, much of the data used by people interested in making causal claims come from non-experimental, observational studies in which random allocations to treatment and control groups are not present. Thus, one of the most important problems in the social and health sciences concerns making justified causal inferences using non-experimental, observational data. In this paper, I examine one method of justifying such inferences that is especially widespread in epidemiology and the health sciences generally – the use of causal criteria. I argue that while the use of causal criteria is not appropriate for either deductive or inductive inferences, they do have an important role to play in inferences to the best explanation. As such, causal criteria, exemplified by what Bradford Hill referred to as "aspects of [statistical] associations", have an indispensible part to play in the goal of making justified causal claims. PMID:19534788

DHAD variants and methods of screening

DOEpatents

Kelly, Kristen J.; Ye, Rick W.

2017-02-28

Methods of screening for dihydroxy-acid dehydratase (DHAD) variants that display increased DHAD activity are disclosed, along with DHAD variants identified by these methods. Such enzymes can result in increased production of compounds from DHAD requiring biosynthetic pathways. Also disclosed are isolated nucleic acids encoding the DHAD variants, recombinant host cells comprising the isolated nucleic acid molecules, and methods of producing butanol.

The rs2231142 variant of the ABCG2 gene is associated with uric acid levels and gout among Japanese people.

PubMed

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.

Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects.

PubMed

Hibar, Derrek P; Stein, Jason L; Ryles, April B; Kohannim, Omid; Jahanshad, Neda; Medland, Sarah E; Hansell, Narelle K; McMahon, Katie L; de Zubicaray, Greig I; Montgomery, Grant W; Martin, Nicholas G; Wright, Margaret J; Saykin, Andrew J; Jack, Clifford R; Weiner, Michael W; Toga, Arthur W; Thompson, Paul M

2013-06-01

Deficits in lentiform nucleus volume and morphometry are implicated in a number of genetically influenced disorders, including Parkinson's disease, schizophrenia, and ADHD. Here we performed genome-wide searches to discover common genetic variants associated with differences in lentiform nucleus volume in human populations. We assessed structural MRI scans of the brain in two large genotyped samples: the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 706) and the Queensland Twin Imaging Study (QTIM; N = 639). Statistics of association from each cohort were combined meta-analytically using a fixed-effects model to boost power and to reduce the prevalence of false positive findings. We identified a number of associations in and around the flavin-containing monooxygenase (FMO) gene cluster. The most highly associated SNP, rs1795240, was located in the FMO3 gene; after meta-analysis, it showed genome-wide significant evidence of association with lentiform nucleus volume (P MA  = 4.79 × 10(-8)). This commonly-carried genetic variant accounted for 2.68 % and 0.84 % of the trait variability in the ADNI and QTIM samples, respectively, even though the QTIM sample was on average 50 years younger. Pathway enrichment analysis revealed significant contributions of this gene to the cytochrome P450 pathway, which is involved in metabolizing numerous therapeutic drugs for pain, seizures, mania, depression, anxiety, and psychosis. The genetic variants we identified provide replicated, genome-wide significant evidence for the FMO gene cluster's involvement in lentiform nucleus volume differences in human populations.

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.

PubMed

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I; Padyukov, Leonid; Toes, Rene E M; Huizinga, Tom W J; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I W; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert M; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-12-01

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Identification of missing variants by combining multiple analytic pipelines.

PubMed

Ren, Yingxue; Reddy, Joseph S; Pottier, Cyril; Sarangi, Vivekananda; Tian, Shulan; Sinnwell, Jason P; McDonnell, Shannon K; Biernacka, Joanna M; Carrasquillo, Minerva M; Ross, Owen A; Ertekin-Taner, Nilüfer; Rademakers, Rosa; Hudson, Matthew; Mainzer, Liudmila Sergeevna; Asmann, Yan W

2018-04-16

After decades of identifying risk factors using array-based genome-wide association studies (GWAS), genetic research of complex diseases has shifted to sequencing-based rare variants discovery. This requires large sample sizes for statistical power and has brought up questions about whether the current variant calling practices are adequate for large cohorts. It is well-known that there are discrepancies between variants called by different pipelines, and that using a single pipeline always misses true variants exclusively identifiable by other pipelines. Nonetheless, it is common practice today to call variants by one pipeline due to computational cost and assume that false negative calls are a small percent of total. We analyzed 10,000 exomes from the Alzheimer's Disease Sequencing Project (ADSP) using multiple analytic pipelines consisting of different read aligners and variant calling strategies. We compared variants identified by using two aligners in 50,100, 200, 500, 1000, and 1952 samples; and compared variants identified by adding single-sample genotyping to the default multi-sample joint genotyping in 50,100, 500, 2000, 5000 and 10,000 samples. We found that using a single pipeline missed increasing numbers of high-quality variants correlated with sample sizes. By combining two read aligners and two variant calling strategies, we rescued 30% of pass-QC variants at sample size of 2000, and 56% at 10,000 samples. The rescued variants had higher proportions of low frequency (minor allele frequency [MAF] 1-5%) and rare (MAF < 1%) variants, which are the very type of variants of interest. In 660 Alzheimer's disease cases with earlier onset ages of ≤65, 4 out of 13 (31%) previously-published rare pathogenic and protective mutations in APP, PSEN1, and PSEN2 genes were undetected by the default one-pipeline approach but recovered by the multi-pipeline approach. Identification of the complete variant set from sequencing data is the prerequisite of genetic

A Theory of Causal Learning in Children: Causal Maps and Bayes Nets

ERIC Educational Resources Information Center

Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…

Targeted resequencing identifies defective variants of decoy receptor 3 in pediatric-onset inflammatory bowel disease.

PubMed

Cardinale, C J; Wei, Z; Panossian, S; Wang, F; Kim, C E; Mentch, F D; Chiavacci, R M; Kachelries, K E; Pandey, R; Grant, S F A; Baldassano, R N; Hakonarson, H

2013-10-01

Genome-wide association studies have implicated common variation at the 20q13 locus in inflammatory bowel disease, particularly for the pediatric Crohn's form. This locus harbors tumor necrosis factor receptor superfamily (TNFRSF6B), encoding a secreted protein, decoy receptor 3 (DcR3), which binds to and neutralizes pro-inflammatory cytokines of the tumor necrosis factor superfamily. We sought to further the evidence of DcR3's role in pediatric IBD by identifying missense mutations with functional significance within TNFRSF6B. We sequenced the exons of the gene in 528 Caucasian pediatric IBD cases and 549 Caucasian healthy controls to establish the frequency of such events in each population. Sequencing revealed that our IBD cohort harbored a greater number of missense variants, yielding an odds ratio of 3.9 (P-value=0.005). Using functional assays, we established that the frequency of mutants defective in secretion from cultured cells was greater in the Crohn's category than in the controls, yielding an odds ratio of 7.1 (P-value=0.004). These results suggest that rare defective variants in TNFRSF6B have a role in the pathogenesis of some cases of IBD and that interventions targeting this group of tumor necrosis factor-family members may benefit patients with IBD.

Variant pathogenicity evaluation in the community-driven Inherited Neuropathy Variant Browser.

PubMed

Saghira, Cima; Bis, Dana M; Stanek, David; Strickland, Alleene; Herrmann, David N; Reilly, Mary M; Scherer, Steven S; Shy, Michael E; Züchner, Stephan

2018-05-01

Charcot-Marie-Tooth disease (CMT) is an umbrella term for inherited neuropathies affecting an estimated one in 2,500 people. Over 120 CMT and related genes have been identified and clinical gene panels often contain more than 100 genes. Such a large genomic space will invariantly yield variants of uncertain clinical significance (VUS) in nearly any person tested. This rise in number of VUS creates major challenges for genetic counseling. Additionally, fewer individual variants in known genes are being published as the academic merit is decreasing, and most testing now happens in clinical laboratories, which typically do not correlate their variants with clinical phenotypes. For CMT, we aim to encourage and facilitate the global capture of variant data to gain a large collection of alleles in CMT genes, ideally in conjunction with phenotypic information. The Inherited Neuropathy Variant Browser provides user-friendly open access to currently reported variation in CMT genes. Geneticists, physicians, and genetic counselors can enter variants detected by clinical tests or in research studies in addition to genetic variation gathered from published literature, which are then submitted to ClinVar biannually. Active participation of the broader CMT community will provide an advance over existing resources for interpretation of CMT genetic variation. © 2018 Wiley Periodicals, Inc.

Genetic study of congenital bile-duct dilatation identifies de novo and inherited variants in functionally related genes.

PubMed

Wong, John K L; Campbell, Desmond; Ngo, Ngoc Diem; Yeung, Fanny; Cheng, Guo; Tang, Clara S M; Chung, Patrick H Y; Tran, Ngoc Son; So, Man-Ting; Cherny, Stacey S; Sham, Pak C; Tam, Paul K; Garcia-Barcelo, Maria-Mercè

2016-12-12

Congenital dilatation of the bile-duct (CDD) is a rare, mostly sporadic, disorder that results in bile retention with severe associated complications. CDD affects mainly Asians. To our knowledge, no genetic study has ever been conducted. We aim to identify genetic risk factors by a "trio-based" exome-sequencing approach, whereby 31 CDD probands and their unaffected parents were exome-sequenced. Seven-hundred controls from the local population were used to detect gene-sets significantly enriched with rare variants in CDD patients. Twenty-one predicted damaging de novo variants (DNVs; 4 protein truncating and 17 missense) were identified in several evolutionarily constrained genes (p < 0.01). Six genes carrying DNVs were associated with human developmental disorders involving epithelial, connective or bone morphologies (PXDN, RTEL1, ANKRD11, MAP2K1, CYLD, ACAN) and four linked with cholangio- and hepatocellular carcinomas (PIK3CA, TLN1 CYLD, MAP2K1). Importantly, CDD patients have an excess of DNVs in cancer-related genes (p < 0.025). Thirteen genes were recurrently mutated at different sites, forming compound heterozygotes or functionally related complexes within patients. Our data supports a strong genetic basis for CDD and show that CDD is not only genetically heterogeneous but also non-monogenic, requiring mutations in more than one genes for the disease to develop. The data is consistent with the rarity and sporadic presentation of CDD.

Conjectures on the relations of linking and causality in causally simple spacetimes

NASA Astrophysics Data System (ADS)

Chernov, Vladimir

2018-05-01

We formulate the generalization of the Legendrian Low conjecture of Natario and Tod (proved by Nemirovski and myself before) to the case of causally simple spacetimes. We prove a weakened version of the corresponding statement. In all known examples, a causally simple spacetime can be conformally embedded as an open subset into some globally hyperbolic and the space of light rays in is an open submanifold of the space of light rays in . If this is always the case, this provides an approach to solving the conjectures relating causality and linking in causally simple spacetimes.

Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.

PubMed

Weed, Douglas L

2018-05-01

The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.

Comprehensive evaluation of disease- and trait-specific enrichment for eight functional elements among GWAS-identified variants.

PubMed

Markunas, Christina A; Johnson, Eric O; Hancock, Dana B

2017-07-01

Genome-wide association study (GWAS)-identified variants are enriched for functional elements. However, we have limited knowledge of how functional enrichment may differ by disease/trait and tissue type. We tested a broad set of eight functional elements for enrichment among GWAS-identified SNPs (p < 5×10 -8 ) from the NHGRI-EBI Catalog across seven disease/trait categories: cancer, cardiovascular disease, diabetes, autoimmune disease, psychiatric disease, neurological disease, and anthropometric traits. SNPs were annotated using HaploReg for the eight functional elements across any tissue: DNase sites, expression quantitative trait loci (eQTL), sequence conservation, enhancers, promoters, missense variants, sequence motifs, and protein binding sites. In addition, tissue-specific annotations were considered for brain vs. blood. Disease/trait SNPs were compared to a control set of 4809 SNPs matched to the GWAS SNPs (N = 1639) on allele frequency, gene density, distance to nearest gene, and linkage disequilibrium at ~3:1 ratio. Enrichment analyses were conducted using logistic regression, with Bonferroni correction. Overall, a significant enrichment was observed for all functional elements, except sequence motifs. Missense SNPs showed the strongest magnitude of enrichment. eQTLs were the only functional element significantly enriched across all diseases/traits. Magnitudes of enrichment were generally similar across diseases/traits, where enrichment was statistically significant. Blood vs. brain tissue effects on enrichment were dependent on disease/trait and functional element (e.g., cardiovascular disease: eQTLs P TissueDifference  = 1.28 × 10 -6 vs. enhancers P TissueDifference  = 0.94). Identifying disease/trait-relevant functional elements and tissue types could provide new insight into the underlying biology, by guiding a priori GWAS analyses (e.g., brain enhancer elements for psychiatric disease) or facilitating post hoc interpretation.

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…

Investigation of 95 variants identified in a genome-wide study for association with mortality after acute coronary syndrome.

PubMed

Morgan, Thomas M; House, John A; Cresci, Sharon; Jones, Philip; Allayee, Hooman; Hazen, Stanley L; Patel, Yesha; Patel, Riyaz S; Eapen, Danny J; Waddy, Salina P; Quyyumi, Arshed A; Kleber, Marcus E; März, Winfried; Winkelmann, Bernhard R; Boehm, Bernhard O; Krumholz, Harlan M; Spertus, John A

2011-09-29

Genome-wide association studies (GWAS) have identified new candidate genes for the occurrence of acute coronary syndrome (ACS), but possible effects of such genes on survival following ACS have yet to be investigated. We examined 95 polymorphisms in 69 distinct gene regions identified in a GWAS for premature myocardial infarction for their association with post-ACS mortality among 811 whites recruited from university-affiliated hospitals in Kansas City, Missouri. We then sought replication of a positive genetic association in a large, racially diverse cohort of myocardial infarction patients (N = 2284) using Kaplan-Meier survival analyses and Cox regression to adjust for relevant covariates. Finally, we investigated the apparent association further in 6086 additional coronary artery disease patients. After Cox adjustment for other ACS risk factors, of 95 SNPs tested in 811 whites only the association with the rs6922269 in MTHFD1L was statistically significant, with a 2.6-fold mortality hazard (P = 0.007). The recessive A/A genotype was of borderline significance in an age- and race-adjusted analysis of the entire combined cohort (N = 3095; P = 0.052), but this finding was not confirmed in independent cohorts (N = 6086). We found no support for the hypothesis that the GWAS-identified variants in this study substantially alter the probability of post-ACS survival. Large-scale, collaborative, genome-wide studies may be required in order to detect genetic variants that are robustly associated with survival in patients with coronary artery disease.

Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases.

PubMed

Perry, John R B; Voight, Benjamin F; Yengo, Loïc; Amin, Najaf; Dupuis, Josée; Ganser, Martha; Grallert, Harald; Navarro, Pau; Li, Man; Qi, Lu; Steinthorsdottir, Valgerdur; Scott, Robert A; Almgren, Peter; Arking, Dan E; Aulchenko, Yurii; Balkau, Beverley; Benediktsson, Rafn; Bergman, Richard N; Boerwinkle, Eric; Bonnycastle, Lori; Burtt, Noël P; Campbell, Harry; Charpentier, Guillaume; Collins, Francis S; Gieger, Christian; Green, Todd; Hadjadj, Samy; Hattersley, Andrew T; Herder, Christian; Hofman, Albert; Johnson, Andrew D; Kottgen, Anna; Kraft, Peter; Labrune, Yann; Langenberg, Claudia; Manning, Alisa K; Mohlke, Karen L; Morris, Andrew P; Oostra, Ben; Pankow, James; Petersen, Ann-Kristin; Pramstaller, Peter P; Prokopenko, Inga; Rathmann, Wolfgang; Rayner, William; Roden, Michael; Rudan, Igor; Rybin, Denis; Scott, Laura J; Sigurdsson, Gunnar; Sladek, Rob; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tuomilehto, Jaakko; Uitterlinden, Andre G; Vivequin, Sidonie; Weedon, Michael N; Wright, Alan F; Hu, Frank B; Illig, Thomas; Kao, Linda; Meigs, James B; Wilson, James F; Stefansson, Kari; van Duijn, Cornelia; Altschuler, David; Morris, Andrew D; Boehnke, Michael; McCarthy, Mark I; Froguel, Philippe; Palmer, Colin N A; Wareham, Nicholas J; Groop, Leif; Frayling, Timothy M; Cauchi, Stéphane

2012-05-01

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m²) compared to obese cases (BMI≥30 Kg/m²). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m²) or 4,123 obese cases (BMI≥30 kg/m²), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10⁻⁹, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A--previously identified in South Asians but not Europeans--was associated with type 2 diabetes in obese cases (P = 1.3×10⁻⁸, OR = 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2×10⁻¹⁴. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2×10⁻¹⁶. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify

Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases

PubMed Central

Perry, John R. B.; Voight, Benjamin F.; Yengo, Loïc; Amin, Najaf; Dupuis, Josée; Ganser, Martha; Grallert, Harald; Navarro, Pau; Li, Man; Qi, Lu; Steinthorsdottir, Valgerdur; Scott, Robert A.; Almgren, Peter; Arking, Dan E.; Aulchenko, Yurii; Balkau, Beverley; Benediktsson, Rafn; Bergman, Richard N.; Boerwinkle, Eric; Bonnycastle, Lori; Burtt, Noël P.; Campbell, Harry; Charpentier, Guillaume; Collins, Francis S.; Gieger, Christian; Green, Todd; Hadjadj, Samy; Hattersley, Andrew T.; Herder, Christian; Hofman, Albert; Johnson, Andrew D.; Kottgen, Anna; Kraft, Peter; Labrune, Yann; Langenberg, Claudia; Manning, Alisa K.; Mohlke, Karen L.; Morris, Andrew P.; Oostra, Ben; Pankow, James; Petersen, Ann-Kristin; Pramstaller, Peter P.; Prokopenko, Inga; Rathmann, Wolfgang; Rayner, William; Roden, Michael; Rudan, Igor; Rybin, Denis; Scott, Laura J.; Sigurdsson, Gunnar; Sladek, Rob; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tuomilehto, Jaakko; Uitterlinden, Andre G.; Vivequin, Sidonie; Weedon, Michael N.; Wright, Alan F.; Hu, Frank B.; Illig, Thomas; Kao, Linda; Meigs, James B.; Wilson, James F.; Stefansson, Kari; van Duijn, Cornelia; Altschuler, David; Morris, Andrew D.; Boehnke, Michael; McCarthy, Mark I.; Froguel, Philippe; Palmer, Colin N. A.; Wareham, Nicholas J.; Groop, Leif

2012-01-01

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m2) compared to obese cases (BMI≥30 Kg/m2). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m2) or 4,123 obese cases (BMI≥30 kg/m2), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10−9, OR = 1.13 [95% CI 1.09–1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00–1.06]). A variant in HMG20A—previously identified in South Asians but not Europeans—was associated with type 2 diabetes in obese cases (P = 1.3×10−8, OR = 1.11 [95% CI 1.07–1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02–1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10–1.17], P = 3.2×10−14. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05–1.08], P = 2.2×10−16. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify

A review of causal inference for biomedical informatics

PubMed Central

Kleinberg, Samantha; Hripcsak, George

2011-01-01

Causality is an important concept throughout the health sciences and is particularly vital for informatics work such as finding adverse drug events or risk factors for disease using electronic health records. While philosophers and scientists working for centuries on formalizing what makes something a cause have not reached a consensus, new methods for inference show that we can make progress in this area in many practical cases. This article reviews core concepts in understanding and identifying causality and then reviews current computational methods for inference and explanation, focusing on inference from large-scale observational data. While the problem is not fully solved, we show that graphical models and Granger causality provide useful frameworks for inference and that a more recent approach based on temporal logic addresses some of the limitations of these methods. PMID:21782035

A splicing variant of TERT identified by GWAS interacts with menopausal estrogen therapy in risk of ovarian cancer.

PubMed

Lee, Alice W; Bomkamp, Ashley; Bandera, Elisa V; Jensen, Allan; Ramus, Susan J; Goodman, Marc T; Rossing, Mary Anne; Modugno, Francesmary; Moysich, Kirsten B; Chang-Claude, Jenny; Rudolph, Anja; Gentry-Maharaj, Aleksandra; Terry, Kathryn L; Gayther, Simon A; Cramer, Daniel W; Doherty, Jennifer A; Schildkraut, Joellen M; Kjaer, Susanne K; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Mukherjee, Bhramar; Roman, Lynda; Pharoah, Paul D; Chenevix-Trench, Georgia; Olson, Sara; Hogdall, Estrid; Wu, Anna H; Pike, Malcolm C; Stram, Daniel O; Pearce, Celeste Leigh

2016-12-15

Menopausal estrogen-alone therapy (ET) is a well-established risk factor for serous and endometrioid ovarian cancer. Genetics also plays a role in ovarian cancer, which is partly attributable to 18 confirmed ovarian cancer susceptibility loci identified by genome-wide association studies. The interplay among these loci, ET use and ovarian cancer risk has yet to be evaluated. We analyzed data from 1,414 serous cases, 337 endometrioid cases and 4,051 controls across 10 case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Conditional logistic regression was used to determine the association between the confirmed susceptibility variants and risk of serous and endometrioid ovarian cancer among ET users and non-users separately and to test for statistical interaction. A splicing variant in TERT, rs10069690, showed a statistically significant interaction with ET use for risk of serous ovarian cancer (p int  = 0.013). ET users carrying the T allele had a 51% increased risk of disease (OR = 1.51, 95% CI 1.19-1.91), which was stronger for long-term ET users of 10+ years (OR = 1.85, 95% CI 1.28-2.66, p int  = 0.034). Non-users showed essentially no association (OR = 1.08, 95% CI 0.96-1.21). Two additional genomic regions harboring rs7207826 (C allele) and rs56318008 (T allele) also had significant interactions with ET use for the endometrioid histotype (p int  = 0.021 and p int  = 0.037, respectively). Hence, three confirmed susceptibility variants were identified whose associations with ovarian cancer risk are modified by ET exposure; follow-up is warranted given that these interactions are not adjusted for multiple comparisons. These findings, if validated, may elucidate the mechanism of action of these loci. © 2016 UICC.

Time-varying causality between energy consumption, CO2 emissions, and economic growth: evidence from US states.

PubMed

Tzeremes, Panayiotis

2018-02-01

This study is the first attempt to investigate the relationship between CO 2 emissions, energy consumption, and economic growth at a state level, for the 50 US states, through a time-varying causality approach using annual data over the periods 1960-2010. The time-varying causality test facilitates the better understanding of the causal relationship between the covariates owing to the fact that it might identify causalities when the time-constant hypothesis is rejected. Our findings indicate the existence of a time-varying causality at the state level. Specifically, the results probe eight bidirectional time-varying causalities between energy consumption and CO 2 emission, six cases of two-way time-varying causalities between economic growth and energy consumption, and five bidirectional time-varying causalities between economic growth and CO 2 emission. Moreover, we examine the traditional environmental Kuznets curve hypothesis for the states. Notably, our results do not endorse the validity of the EKC, albeit the majority of states support an inverted N-shaped relationship. Lastly, we can identify multiple policy implications based on the empirical results.

Substitution scanning identifies a novel, catalytically active ibrutinib-resistant BTK cysteine 481 to threonine (C481T) variant

PubMed Central

Hamasy, A; Wang, Q; Blomberg, K E M; Mohammad, D K; Yu, L; Vihinen, M; Berglöf, A; Smith, C I E

2017-01-01

Irreversible Bruton tyrosine kinase (BTK) inhibitors, ibrutinib and acalabrutinib have demonstrated remarkable clinical responses in multiple B-cell malignancies. Acquired resistance has been identified in a sub-population of patients in which mutations affecting BTK predominantly substitute cysteine 481 in the kinase domain for catalytically active serine, thereby ablating covalent binding of inhibitors. Activating substitutions in the BTK substrate phospholipase Cγ2 (PLCγ2) instead confers resistance independent of BTK. Herein, we generated all six possible amino acid substitutions due to single nucleotide alterations for the cysteine 481 codon, in addition to threonine, requiring two nucleotide substitutions, and performed functional analysis. Replacement by arginine, phenylalanine, tryptophan or tyrosine completely inactivated the catalytic activity, whereas substitution with glycine caused severe impairment. BTK with threonine replacement was catalytically active, similar to substitution with serine. We identify three potential ibrutinib resistance scenarios for cysteine 481 replacement: (1) Serine, being catalytically active and therefore predominating among patients. (2) Threonine, also being catalytically active, but predicted to be scarce, because two nucleotide changes are needed. (3) As BTK variants replaced with other residues are catalytically inactive, they presumably need compensatory mutations, therefore being very scarce. Glycine and tryptophan variants were not yet reported but likely also provide resistance. PMID:27282255

Cyclin-dependent Kinase 5: Novel role of gene variants identified in ADHD.

PubMed

Maitra, Subhamita; Chatterjee, Mahasweta; Sinha, Swagata; Mukhopadhyay, Kanchan

2017-07-28

Cortical neuronal migration and formation of filamentous actin cytoskeleton, needed for development, normal cell growth and differentiation, are regulated by the cyclin-dependent kinase 5 (Cdk5). Attention deficit hyperactivity disorder (ADHD) is associated with delayed maturation of the brain and hence we hypothesized that cdk5 may have a role in ADHD. Eight functional CDK5 gene variants were analyzed in 848 Indo-Caucasoid individuals including 217 families with ADHD probands and 250 healthy volunteers. Only three variants, rs2069454, rs2069456 and rs2069459, predicted to affect transcription, were found to be bimorphic. Significant difference in rs2069456 "AC" genotype frequency was noticed in the probands, more specifically in the males. Family based analysis revealed over transmission of rs2069454 "C" and rs2069456 "A" to the probands. Quantitative trait analysis exhibited association of haplotypes with inattention, domain specific impulsivity, and behavioral problem, though no significant contribution was noticed on the age of onset of ADHD. Gene variants also showed significant association with cognitive function and co-morbidity. Probands having rs2069459 "TT" showed betterment during follow up. It may be inferred from this pilot study that CDK5 may affect ADHD etiology, possibly by attenuating synaptic neurotransmission and could be a useful target for therapeutic intervention.

Does Causal Action Facilitate Causal Perception in Infants Younger than 6 Months of Age?

ERIC Educational Resources Information Center

Rakison, David H.; Krogh, Lauren

2012-01-01

Previous research has established that infants are unable to perceive causality until 6 1/4 months of age. The current experiments examined whether infants' ability to engage in causal action could facilitate causal perception prior to this age. In Experiment 1, 4 1/2-month-olds were randomly assigned to engage in causal action experience via…

Complex Causal Process Diagrams for Analyzing the Health Impacts of Policy Interventions

PubMed Central

Joffe, Michael; Mindell, Jennifer

2006-01-01

Causal diagrams are rigorous tools for controlling confounding. They also can be used to describe complex causal systems, which is done routinely in communicable disease epidemiology. The use of change diagrams has advantages over static diagrams, because change diagrams are more tractable, relate better to interventions, and have clearer interpretations. Causal diagrams are a useful basis for modeling. They make assumptions explicit, provide a framework for analysis, generate testable predictions, explore the effects of interventions, and identify data gaps. Causal diagrams can be used to integrate different types of information and to facilitate communication both among public health experts and between public health experts and experts in other fields. Causal diagrams allow the use of instrumental variables, which can help control confounding and reverse causation. PMID:16449586

Fine Mapping of a Clubroot Resistance Gene in Chinese Cabbage Using SNP Markers Identified from Bulked Segregant RNA Sequencing

PubMed Central

Huang, Zhen; Peng, Gary; Liu, Xunjia; Deora, Abhinandan; Falk, Kevin C.; Gossen, Bruce D.; McDonald, Mary R.; Yu, Fengqun

2017-01-01

Clubroot, caused by Plasmodiophora brassicae, is an important disease of canola (Brassica napus) in western Canada and worldwide. In this study, a clubroot resistance gene (Rcr2) was identified and fine mapped in Chinese cabbage cv. “Jazz” using single-nucleotide polymorphisms (SNP) markers identified from bulked segregant RNA sequencing (BSR-Seq) and molecular markers were developed for use in marker assisted selection. In total, 203.9 million raw reads were generated from one pooled resistant (R) and one pooled susceptible (S) sample, and >173,000 polymorphic SNP sites were identified between the R and S samples. One significant peak was observed between 22 and 26 Mb of chromosome A03, which had been predicted by BSR-Seq to contain the causal gene Rcr2. There were 490 polymorphic SNP sites identified in the region. A segregating population consisting of 675 plants was analyzed with 15 SNP sites in the region using the Kompetitive Allele Specific PCR method, and Rcr2 was fine mapped between two SNP markers, SNP_A03_32 and SNP_A03_67 with 0.1 and 0.3 cM from Rcr2, respectively. Five SNP markers co-segregated with Rcr2 in this region. Variants were identified in 14 of 36 genes annotated in the Rcr2 target region. The numbers of poly variants differed among the genes. Four genes encode TIR-NBS-LRR proteins and two of them Bra019410 and Bra019413, had high numbers of polymorphic variants and so are the most likely candidates of Rcr2. PMID:28894454

Receptor homodimerization plays a critical role in a novel dominant negative P2RY12 variant identified in a family with severe bleeding.

PubMed

Mundell, S J; Rabbolini, D; Gabrielli, S; Chen, Q; Aungraheeta, R; Hutchinson, J L; Kilo, T; Mackay, J; Ward, C M; Stevenson, W; Morel-Kopp, M-C

2018-01-01

Essentials Three dominant variants for the autosomal recessive bleeding disorder type-8 have been described. To date, there has been no phenotype/genotype correlation explaining their dominant transmission. Proline plays an important role in P2Y12R ligand binding and signaling defects. P2Y12R homodimer formation is critical for the receptor function and signaling. Background Although inherited platelet disorders are still underdiagnosed worldwide, advances in molecular techniques are improving disease diagnosis and patient management. Objective To identify and characterize the mechanism underlying the bleeding phenotype in a Caucasian family with an autosomal dominant P2RY12 variant. Methods Full blood counts, platelet aggregometry, flow cytometry and western blotting were performed before next-generation sequencing (NGS). Detailed molecular analysis of the identified variant of the P2Y12 receptor (P2Y12R) was subsequently performed in mammalian cells overexpressing receptor constructs. Results All three referred individuals had markedly impaired ADP-induced platelet aggregation with primary wave only, despite normal total and surface P2Y12R expression. By NGS, a single P2RY12:c.G794C substitution (p.R265P) was identified in all affected individuals, and this was confirmed by Sanger sequencing. Mammalian cell experiments with the R265P-P2Y12R variant showed normal receptor surface expression versus wild-type (WT) P2Y12R. Agonist-stimulated R265P-P2Y12R function (both signaling and surface receptor loss) was reduced versus WT P2Y12R. Critically, R265P-P2Y12R acted in a dominant negative manner, with agonist-stimulated WT P2Y12R activity being reduced by variant coexpression, suggesting dramatic loss of WT homodimers. Importantly, platelet P2RY12 cDNA cloning and sequencing in two affected individuals also revealed three-fold mutant mRNA overexpression, decreasing even further the likelihood of WT homodimer formation. R265 located within extracellular loop 3 (EL3) is

DoEstRare: A statistical test to identify local enrichments in rare genomic variants associated with disease.

PubMed

Persyn, Elodie; Karakachoff, Matilde; Le Scouarnec, Solena; Le Clézio, Camille; Campion, Dominique; Consortium, French Exome; Schott, Jean-Jacques; Redon, Richard; Bellanger, Lise; Dina, Christian

2017-01-01

Next-generation sequencing technologies made it possible to assay the effect of rare variants on complex diseases. As an extension of the "common disease-common variant" paradigm, rare variant studies are necessary to get a more complete insight into the genetic architecture of human traits. Association studies of these rare variations show new challenges in terms of statistical analysis. Due to their low frequency, rare variants must be tested by groups. This approach is then hindered by the fact that an unknown proportion of the variants could be neutral. The risk level of a rare variation may be determined by its impact but also by its position in the protein sequence. More generally, the molecular mechanisms underlying the disease architecture may involve specific protein domains or inter-genic regulatory regions. While a large variety of methods are optimizing functionality weights for each single marker, few evaluate variant position differences between cases and controls. Here, we propose a test called DoEstRare, which aims to simultaneously detect clusters of disease risk variants and global allele frequency differences in genomic regions. This test estimates, for cases and controls, variant position densities in the genetic region by a kernel method, weighted by a function of allele frequencies. We compared DoEstRare with previously published strategies through simulation studies as well as re-analysis of real datasets. Based on simulation under various scenarios, DoEstRare was the sole to consistently show highest performance, in terms of type I error and power both when variants were clustered or not. DoEstRare was also applied to Brugada syndrome and early-onset Alzheimer's disease data and provided complementary results to other existing tests. DoEstRare, by integrating variant position information, gives new opportunities to explain disease susceptibility. DoEstRare is implemented in a user-friendly R package.

Agency, time, and causality

PubMed Central

Widlok, Thomas

2014-01-01

Cognitive Scientists interested in causal cognition increasingly search for evidence from non-Western Educational Industrial Rich Democratic people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition. PMID:25414683

Causal mechanisms and balancing selection inferred from genetic associations with polycystic ovary syndrome

PubMed Central

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

ASXL1 and BIM germ line variants predict response and identify CML patients with the greatest risk of imatinib failure

PubMed Central

Marum, Justine E.; Yeung, David T.; Purins, Leanne; Reynolds, John; Parker, Wendy T.; Stangl, Doris; Wang, Paul P. S.; Price, David J.; Tuke, Jonathan; Schreiber, Andreas W.; Scott, Hamish S.; Hughes, Timothy P.

2017-01-01

Scoring systems used at diagnosis of chronic myeloid leukemia (CML), such as Sokal risk, provide important response prediction for patients treated with imatinib. However, the sensitivity and specificity of scoring systems could be enhanced for improved identification of patients with the highest risk. We aimed to identify genomic predictive biomarkers of imatinib response at diagnosis to aid selection of first-line therapy. Targeted amplicon sequencing was performed to determine the germ line variant profile in 517 and 79 patients treated with first-line imatinib and nilotinib, respectively. The Sokal score and ASXL1 rs4911231 and BIM rs686952 variants were independent predictors of early molecular response (MR), major MR, deep MRs (MR4 and MR4.5), and failure-free survival (FFS) with imatinib treatment. In contrast, the ASXL1 and BIM variants did not consistently predict MR or FFS with nilotinib treatment. In the imatinib-treated cohort, neither Sokal or the ASXL1 and BIM variants predicted overall survival (OS) or progression to accelerated phase or blast crisis (AP/BC). The Sokal risk score was combined with the ASXL1 and BIM variants in a classification tree model to predict imatinib response. The model distinguished an ultra-high-risk group, representing 10% of patients, that predicted inferior OS (88% vs 97%; P = .041), progression to AP/BC (12% vs 1%; P = .034), FFS (P < .001), and MRs (P < .001). The ultra-high-risk patients may be candidates for more potent or combination first-line therapy. These data suggest that germ line genetic variation contributes to the heterogeneity of response to imatinib and may contribute to a prognostic risk score that allows early optimization of therapy. PMID:29296778

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…

A Multi-Ethnic Meta-Analysis of Genome-Wide Association Studies in Over 100,000 Subjects Identifies 23 Fibrinogen-Associated Loci but no Strong Evidence of a Causal Association between Circulating Fibrinogen and Cardiovascular Disease

PubMed Central

Sabater-Lleal, Maria; Huang, Jie; Chasman, Daniel; Naitza, Silvia; Dehghan, Abbas; Johnson, Andrew D; Teumer, Alexander; Reiner, Alex P; Folkersen, Lasse; Basu, Saonli; Rudnicka, Alicja R; Trompet, Stella; Mälarstig, Anders; Baumert, Jens; Bis, Joshua C.; Guo, Xiuqing; Hottenga, Jouke J; Shin, So-Youn; Lopez, Lorna M; Lahti, Jari; Tanaka, Toshiko; Yanek, Lisa R; Oudot-Mellakh, Tiphaine; Wilson, James F; Navarro, Pau; Huffman, Jennifer E; Zemunik, Tatijana; Redline, Susan; Mehra, Reena; Pulanic, Drazen; Rudan, Igor; Wright, Alan F; Kolcic, Ivana; Polasek, Ozren; Wild, Sarah H; Campbell, Harry; Curb, J David; Wallace, Robert; Liu, Simin; Eaton, Charles B.; Becker, Diane M.; Becker, Lewis C.; Bandinelli, Stefania; Räikkönen, Katri; Widen, Elisabeth; Palotie, Aarno; Fornage, Myriam; Green, David; Gross, Myron; Davies, Gail; Harris, Sarah E; Liewald, David C; Starr, John M; Williams, Frances M.K.; Grant, P.J.; Spector, Timothy D.; Strawbridge, Rona J; Silveira, Angela; Sennblad, Bengt; Rivadeneira, Fernando; Uitterlinden, Andre G; Franco, Oscar H; Hofman, Albert; van Dongen, Jenny; Willemsen, G; Boomsma, Dorret I; Yao, Jie; Jenny, Nancy Swords; Haritunians, Talin; McKnight, Barbara; Lumley, Thomas; Taylor, Kent D; Rotter, Jerome I; Psaty, Bruce M; Peters, Annette; Gieger, Christian; Illig, Thomas; Grotevendt, Anne; Homuth, Georg; Völzke, Henry; Kocher, Thomas; Goel, Anuj; Franzosi, Maria Grazia; Seedorf, Udo; Clarke, Robert; Steri, Maristella; Tarasov, Kirill V; Sanna, Serena; Schlessinger, David; Stott, David J; Sattar, Naveed; Buckley, Brendan M; Rumley, Ann; Lowe, Gordon D; McArdle, Wendy L; Chen, Ming-Huei; Tofler, Geoffrey H; Song, Jaejoon; Boerwinkle, Eric; Folsom, Aaron R.; Rose, Lynda M.; Franco-Cereceda, Anders; Teichert, Martina; Ikram, M Arfan; Mosley, Thomas H; Bevan, Steve; Dichgans, Martin; Rothwell, Peter M.; Sudlow, Cathie L M; Hopewell, Jemma C.; Chambers, John C.; Saleheen, Danish; Kooner, Jaspal S.; Danesh, John; Nelson, Christopher P; Erdmann, Jeanette; Reilly, Muredach P.; Kathiresan, Sekar; Schunkert, Heribert; Morange, Pierre-Emmanuel; Ferrucci, Luigi; Eriksson, Johan G; Jacobs, David; Deary, Ian J; Soranzo, Nicole; Witteman, Jacqueline CM; de Geus, Eco JC; Tracy, Russell P.; Hayward, Caroline; Koenig, Wolfgang; Cucca, Francesco; Jukema, J Wouter; Eriksson, Per; Seshadri, Sudha; Markus, Hugh S.; Watkins, Hugh; Samani, Nilesh J; Wallaschofski, Henri; Smith, Nicholas L.; Tregouet, David; Ridker, Paul M.; Tang, Weihong; Strachan, David P.; Hamsten, Anders; O’Donnell, Christopher J.

2013-01-01

Background Estimates of the heritability of plasma fibrinogen concentration, an established predictor of cardiovascular disease (CVD), range from 34 to 50%. Genetic variants so far identified by genome-wide association (GWA) studies only explain a small proportion (< 2%) of its variation. Methods and Results We conducted a meta-analysis of 28 GWA studies, including more than 90,000 subjects of European ancestry, the first GWA meta-analysis of fibrinogen levels in 7 African Americans studies totaling 8,289 samples, and a GWA study in Hispanic-Americans totaling 1,366 samples. Evaluation for association of SNPs with clinical outcomes included a total of 40,695 cases and 85,582 controls for coronary artery disease (CAD), 4,752 cases and 24,030 controls for stroke, and 3,208 cases and 46,167 controls for venous thromboembolism (VTE). Overall, we identified 24 genome-wide significant (P<5×10−8) independent signals in 23 loci, including 15 novel associations, together accounting for 3.7% of plasma fibrinogen variation. Gene-set enrichment analysis highlighted key roles in fibrinogen regulation for the three structural fibrinogen genes and pathways related to inflammation, adipocytokines and thyrotrophin-releasing hormone signaling. Whereas lead SNPs in a few loci were significantly associated with CAD, the combined effect of all 24 fibrinogen-associated lead SNPs was not significant for CAD, stroke or VTE. Conclusion We identify 23 robustly associated fibrinogen loci, 15 of which are new. Clinical outcome analysis of these loci does not support a causal relationship between circulating levels of fibrinogen and CAD, stroke or VTE. PMID:23969696

The development of causal reasoning.

PubMed

Kuhn, Deanna

2012-05-01

How do inference rules for causal learning themselves change developmentally? A model of the development of causal reasoning must address this question, as well as specify the inference rules. Here, the evidence for developmental changes in processes of causal reasoning is reviewed, with the distinction made between diagnostic causal inference and causal prediction. Also addressed is the paradox of a causal reasoning literature that highlights the competencies of young children and the proneness to error among adults. WIREs Cogn Sci 2012, 3:327-335. doi: 10.1002/wcs.1160 For further resources related to this article, please visit the WIREs website. Copyright © 2012 John Wiley & Sons, Ltd.

THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

EPA Pesticide Factsheets

CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

Obesity and infection: reciprocal causality.

PubMed

Hainer, V; Zamrazilová, H; Kunešová, M; Bendlová, B; Aldhoon-Hainerová, I

2015-01-01

Associations between different infectious agents and obesity have been reported in humans for over thirty years. In many cases, as in nosocomial infections, this relationship reflects the greater susceptibility of obese individuals to infection due to impaired immunity. In such cases, the infection is not related to obesity as a causal factor but represents a complication of obesity. In contrast, several infections have been suggested as potential causal factors in human obesity. However, evidence of a causal linkage to human obesity has only been provided for adenovirus 36 (Adv36). This virus activates lipogenic and proinflammatory pathways in adipose tissue, improves insulin sensitivity, lipid profile and hepatic steatosis. The E4orf1 gene of Adv36 exerts insulin senzitizing effects, but is devoid of its pro-inflammatory modalities. The development of a vaccine to prevent Adv36-induced obesity or the use of E4orf1 as a ligand for novel antidiabetic drugs could open new horizons in the prophylaxis and treatment of obesity and diabetes. More experimental and clinical studies are needed to elucidate the mutual relations between infection and obesity, identify additional infectious agents causing human obesity, as well as define the conditions that predispose obese individuals to specific infections.

Association of genetic variants of GRIN2B with autism.

PubMed

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.

Learning a theory of causality.

PubMed

Goodman, Noah D; Ullman, Tomer D; Tenenbaum, Joshua B

2011-01-01

The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be learned from co-occurrence of events. We begin by phrasing the causal Bayes nets theory of causality and a range of alternatives in a logical language for relational theories. This allows us to explore simultaneous inductive learning of an abstract theory of causality and a causal model for each of several causal systems. We find that the correct theory of causality can be learned relatively quickly, often becoming available before specific causal theories have been learned--an effect we term the blessing of abstraction. We then explore the effect of providing a variety of auxiliary evidence and find that a collection of simple perceptual input analyzers can help to bootstrap abstract knowledge. Together, these results suggest that the most efficient route to causal knowledge may be to build in not an abstract notion of causality but a powerful inductive learning mechanism and a variety of perceptual supports. While these results are purely computational, they have implications for cognitive development, which we explore in the conclusion.

Finding the Cause: Verbal Framing Helps Children Extract Causal Evidence Embedded in a Complex Scene

ERIC Educational Resources Information Center

Butler, Lucas P.; Markman, Ellen M.

2012-01-01

In making causal inferences, children must both identify a causal problem and selectively attend to meaningful evidence. Four experiments demonstrate that verbally framing an event ("Which animals make Lion laugh?") helps 4-year-olds extract evidence from a complex scene to make accurate causal inferences. Whereas framing was unnecessary when…

Fatal neonatal encephalopathy and lactic acidosis caused by a homozygous loss-of-function variant in COQ9.

PubMed

Danhauser, Katharina; Herebian, Diran; Haack, Tobias B; Rodenburg, Richard J; Strom, Tim M; Meitinger, Thomas; Klee, Dirk; Mayatepek, Ertan; Prokisch, Holger; Distelmaier, Felix

2016-03-01

Coenzyme Q10 (CoQ10) has an important role in mitochondrial energy metabolism by way of its functioning as an electron carrier in the respiratory chain. Genetic defects disrupting the endogenous biosynthesis pathway of CoQ10 may lead to severe metabolic disorders with onset in early childhood. Using exome sequencing in a child with fatal neonatal lactic acidosis and encephalopathy, we identified a homozygous loss-of-function variant in COQ9. Functional studies in patient fibroblasts showed that the absence of the COQ9 protein was concomitant with a strong reduction of COQ7, leading to a significant accumulation of the substrate of COQ7, 6-demethoxy ubiquinone10. At the same time, the total amount of CoQ10 was severely reduced, which was reflected in a significant decrease of mitochondrial respiratory chain succinate-cytochrome c oxidoreductase (complex II/III) activity. Lentiviral expression of COQ9 restored all these parameters, confirming the causal role of the variant. Our report on the second COQ9 patient expands the clinical spectrum associated with COQ9 variants, indicating the importance of COQ9 already during prenatal development. Moreover, the rescue of cellular CoQ10 levels and respiratory chain complex activities by CoQ10 supplementation points to the importance of an early diagnosis and immediate treatment.

Analyzing brain networks with PCA and conditional Granger causality.

PubMed

Zhou, Zhenyu; Chen, Yonghong; Ding, Mingzhou; Wright, Paul; Lu, Zuhong; Liu, Yijun

2009-07-01

Identifying directional influences in anatomical and functional circuits presents one of the greatest challenges for understanding neural computations in the brain. Granger causality mapping (GCM) derived from vector autoregressive models of data has been employed for this purpose, revealing complex temporal and spatial dynamics underlying cognitive processes. However, the traditional GCM methods are computationally expensive, as signals from thousands of voxels within selected regions of interest (ROIs) are individually processed, and being based on pairwise Granger causality, they lack the ability to distinguish direct from indirect connectivity among brain regions. In this work a new algorithm called PCA based conditional GCM is proposed to overcome these problems. The algorithm implements the following two procedures: (i) dimensionality reduction in ROIs of interest with principle component analysis (PCA), and (ii) estimation of the direct causal influences in local brain networks, using conditional Granger causality. Our results show that the proposed method achieves greater accuracy in detecting network connectivity than the commonly used pairwise Granger causality method. Furthermore, the use of PCA components in conjunction with conditional GCM greatly reduces the computational cost relative to the use of individual voxel time series. Copyright 2009 Wiley-Liss, Inc

High density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

PubMed Central

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I.; Padyukov, Leonid; Toes, Rene E.M.; Huizinga, Tom W.J.; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I.W.; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A.; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-01-01

Summary Using the Immunochip custom single nucleotide polymorphism (SNP) array, designed for dense genotyping of 186 genome wide association study (GWAS) confirmed loci we analysed 11,475 rheumatoid arthritis cases of European ancestry and 15,870 controls for 129,464 markers. The data were combined in meta-analysis with GWAS data from additional independent cases (n=2,363) and controls (n=17,872). We identified fourteen novel loci; nine were associated with rheumatoid arthritis overall and 5 specifically in anti-citrillunated peptide antibody positive disease, bringing the number of confirmed European ancestry rheumatoid arthritis loci to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at six loci and association to low frequency variants (minor allele frequency <0.05) at 4 loci. Bioinformatic analysis of the data generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations. PMID:23143596

Network perturbation by recurrent regulatory variants in cancer

PubMed Central

Cho, Ara; Lee, Insuk; Choi, Jung Kyoon

2017-01-01

Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes. PMID:28333928

AOP: An R Package For Sufficient Causal Analysis in Pathway ...

EPA Pesticide Factsheets

Summary: How can I quickly find the key events in a pathway that I need to monitor to predict that a/an beneficial/adverse event/outcome will occur? This is a key question when using signaling pathways for drug/chemical screening in pharma-cology, toxicology and risk assessment. By identifying these sufficient causal key events, we have fewer events to monitor for a pathway, thereby decreasing assay costs and time, while maximizing the value of the information. I have developed the “aop” package which uses backdoor analysis of causal net-works to identify these minimal sets of key events that are suf-ficient for making causal predictions. Availability and Implementation: The source and binary are available online through the Bioconductor project (http://www.bioconductor.org/) as an R package titled “aop”. The R/Bioconductor package runs within the R statistical envi-ronment. The package has functions that can take pathways (as directed graphs) formatted as a Cytoscape JSON file as input, or pathways can be represented as directed graphs us-ing the R/Bioconductor “graph” package. The “aop” package has functions that can perform backdoor analysis to identify the minimal set of key events for making causal predictions.Contact: burgoon.lyle@epa.gov This paper describes an R/Bioconductor package that was developed to facilitate the identification of key events within an AOP that are the minimal set of sufficient key events that need to be tested/monit

αIIbβ3 variants defined by next-generation sequencing: Predicting variants likely to cause Glanzmann thrombasthenia

PubMed Central

Buitrago, Lorena; Rendon, Augusto; Liang, Yupu; Simeoni, Ilenia; Negri, Ana; Filizola, Marta; Ouwehand, Willem H.; Coller, Barry S.; Alessi, Marie-Christine; Ballmaier, Matthias; Bariana, Tadbir; Bellissimo, Daniel; Bertoli, Marta; Bray, Paul; Bury, Loredana; Carrell, Robin; Cattaneo, Marco; Collins, Peter; French, Deborah; Favier, Remi; Freson, Kathleen; Furie, Bruce; Germeshausen, Manuela; Ghevaert, Cedric; Gomez, Keith; Goodeve, Anne; Gresele, Paolo; Guerrero, Jose; Hampshire, Dan J.; Hadinnapola, Charaka; Heemskerk, Johan; Henskens, Yvonne; Hill, Marian; Hogg, Nancy; Johnsen, Jill; Kahr, Walter; Kerr, Ron; Kunishima, Shinji; Laffan, Michael; Natwani, Amit; Neerman-Arbez, Marguerite; Nurden, Paquita; Nurden, Alan; Ormiston, Mark; Othman, Maha; Ouwehand, Willem; Perry, David; Vilk, Shoshana Ravel; Reitsma, Pieter; Rondina, Matthew; Simeoni, Ilenia; Smethurst, Peter; Stephens, Jonathan; Stevenson, William; Szkotak, Artur; Turro, Ernest; Van Geet, Christel; Vries, Minka; Ward, June; Waye, John; Westbury, Sarah; Whiteheart, Sidney; Wilcox, David; Zhang, Bi

2015-01-01

Next-generation sequencing is transforming our understanding of human genetic variation but assessing the functional impact of novel variants presents challenges. We analyzed missense variants in the integrin αIIbβ3 receptor subunit genes ITGA2B and ITGB3 identified by whole-exome or -genome sequencing in the ThromboGenomics project, comprising ∼32,000 alleles from 16,108 individuals. We analyzed the results in comparison with 111 missense variants in these genes previously reported as being associated with Glanzmann thrombasthenia (GT), 20 associated with alloimmune thrombocytopenia, and 5 associated with aniso/macrothrombocytopenia. We identified 114 novel missense variants in ITGA2B (affecting ∼11% of the amino acids) and 68 novel missense variants in ITGB3 (affecting ∼9% of the amino acids). Of the variants, 96% had minor allele frequencies (MAF) < 0.1%, indicating their rarity. Based on sequence conservation, MAF, and location on a complete model of αIIbβ3, we selected three novel variants that affect amino acids previously associated with GT for expression in HEK293 cells. αIIb P176H and β3 C547G severely reduced αIIbβ3 expression, whereas αIIb P943A partially reduced αIIbβ3 expression and had no effect on fibrinogen binding. We used receiver operating characteristic curves of combined annotation-dependent depletion, Polyphen 2-HDIV, and sorting intolerant from tolerant to estimate the percentage of novel variants likely to be deleterious. At optimal cut-off values, which had 69–98% sensitivity in detecting GT mutations, between 27% and 71% of the novel αIIb or β3 missense variants were predicted to be deleterious. Our data have implications for understanding the evolutionary pressure on αIIbβ3 and highlight the challenges in predicting the clinical significance of novel missense variants. PMID:25827233

Causality discovery technology

NASA Astrophysics Data System (ADS)

Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

2012-11-01

Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

Distinguishing time-delayed causal interactions using convergent cross mapping

PubMed Central

Ye, Hao; Deyle, Ethan R.; Gilarranz, Luis J.; Sugihara, George

2015-01-01

An important problem across many scientific fields is the identification of causal effects from observational data alone. Recent methods (convergent cross mapping, CCM) have made substantial progress on this problem by applying the idea of nonlinear attractor reconstruction to time series data. Here, we expand upon the technique of CCM by explicitly considering time lags. Applying this extended method to representative examples (model simulations, a laboratory predator-prey experiment, temperature and greenhouse gas reconstructions from the Vostok ice core, and long-term ecological time series collected in the Southern California Bight), we demonstrate the ability to identify different time-delayed interactions, distinguish between synchrony induced by strong unidirectional-forcing and true bidirectional causality, and resolve transitive causal chains. PMID:26435402

Reasoning with Causal Cycles

ERIC Educational Resources Information Center

Rehder, Bob

2017-01-01

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…

A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

PubMed Central

Volkov, Petr; Olsson, Anders H.; Gillberg, Linn; Jørgensen, Sine W.; Brøns, Charlotte; Eriksson, Karl-Fredrik; Groop, Leif; Jansson, Per-Anders; Nilsson, Emma; Rönn, Tina; Vaag, Allan; Ling, Charlotte

2016-01-01

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and

Pleiotropic associations of risk variants identified for other cancers with lung cancer risk: the PAGE and TRICL consortia.