Moonesinghe, Ramal; Ioannidis, John P A; Flanders, W Dana; Yang, Quanhe; Truman, Benedict I; Khoury, Muin J
2012-08-01
Genome-wide association studies have identified multiple genetic susceptibility variants to several complex human diseases. However, risk-genotype frequency at loci showing robust associations might differ substantially among different populations. In this paper, we present methods to assess the contribution of genetic variants to the difference in the incidence of disease between different population groups for different scenarios. We derive expressions for the contribution of a single genetic variant, multiple genetic variants, and the contribution of the joint effect of a genetic variant and an environmental factor to the difference in the incidence of disease. The contribution of genetic variants to the difference in incidence increases with increasing difference in risk-genotype frequency, but declines with increasing difference in incidence between the two populations. The contribution of genetic variants also increases with increasing relative risk and the contribution of joint effect of genetic and environmental factors increases with increasing relative risk of the gene-environmental interaction. The contribution of genetic variants to the difference in incidence between two populations can be expressed as a function of the population attributable risks of the genetic variants in the two populations. The contribution of a group of genetic variants to the disparity in incidence of disease could change considerably by adding one more genetic variant to the group. Any estimate of genetic contribution to the disparity in incidence of disease between two populations at this stage seems to be an elusive goal.
Moonesinghe, Ramal; Ioannidis, John PA; Flanders, W Dana; Yang, Quanhe; Truman, Benedict I; Khoury, Muin J
2012-01-01
Genome-wide association studies have identified multiple genetic susceptibility variants to several complex human diseases. However, risk-genotype frequency at loci showing robust associations might differ substantially among different populations. In this paper, we present methods to assess the contribution of genetic variants to the difference in the incidence of disease between different population groups for different scenarios. We derive expressions for the contribution of a single genetic variant, multiple genetic variants, and the contribution of the joint effect of a genetic variant and an environmental factor to the difference in the incidence of disease. The contribution of genetic variants to the difference in incidence increases with increasing difference in risk-genotype frequency, but declines with increasing difference in incidence between the two populations. The contribution of genetic variants also increases with increasing relative risk and the contribution of joint effect of genetic and environmental factors increases with increasing relative risk of the gene–environmental interaction. The contribution of genetic variants to the difference in incidence between two populations can be expressed as a function of the population attributable risks of the genetic variants in the two populations. The contribution of a group of genetic variants to the disparity in incidence of disease could change considerably by adding one more genetic variant to the group. Any estimate of genetic contribution to the disparity in incidence of disease between two populations at this stage seems to be an elusive goal. PMID:22333905
Pierce, Brandon L; Ahsan, Habibul; Vanderweele, Tyler J
2011-06-01
Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.
Germline genetic variants with implications for disease risk and therapeutic outcomes.
Pasternak, Amy L; Ward, Kristen M; Luzum, Jasmine A; Ellingrod, Vicki L; Hertz, Daniel L
2017-10-01
Genetic testing has multiple clinical applications including disease risk assessment, diagnosis, and pharmacogenomics. Pharmacogenomics can be utilized to predict whether a pharmacologic therapy will be effective or to identify patients at risk for treatment-related toxicity. Although genetic tests are typically ordered for a distinct clinical purpose, the genetic variants that are found may have additional implications for either disease or pharmacology. This review will address multiple examples of germline genetic variants that are informative for both disease and pharmacogenomics. The discussed relationships are diverse. Some of the agents are targeted for the disease-causing genetic variant, while others, although not targeted therapies, have implications for the disease they are used to treat. It is also possible that the disease implications of a genetic variant are unrelated to the pharmacogenomic implications. Some of these examples are considered clinically actionable pharmacogenes, with evidence-based, pharmacologic treatment recommendations, while others are still investigative as areas for additional research. It is important that clinicians are aware of both the disease and pharmacogenomic associations of these germline genetic variants to ensure patients are receiving comprehensive personalized care. Copyright © 2017 the American Physiological Society.
Genetic variants in Alzheimer disease – molecular and brain network approaches
Gaiteri, Chris; Mostafavi, Sara; Honey, Christopher; De Jager, Philip L.; Bennett, David A.
2016-01-01
Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care for AD. However, due to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extracting actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effect of LOAD-associated genetic variants. We then discuss emerging combinations of omic data types in multiscale models, which provide a more comprehensive representation of the effect of LOAD-associated genetic variants at multiple biophysical scales. Further, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models. PMID:27282653
Zhu, Yun; Yang, Jingyun; Yeh, Fawn; Cole, Shelley A; Haack, Karin; Lee, Elisa T; Howard, Barbara V; Zhao, Jinying
2014-01-01
Cigarette smoke is a strong risk factor for obesity and cardiovascular disease. The effect of genetic variants involved in nicotine metabolism on obesity or body composition has not been well studied. Though many genetic variants have previously been associated with adiposity or body fat distribution, a single variant usually confers a minimal individual risk. The goal of this study is to evaluate the joint association of multiple variants involved in cigarette smoke or nicotine dependence with obesity-related phenotypes in American Indians. To achieve this goal, we genotyped 61 tagSNPs in seven genes encoding nicotine acetylcholine receptors (nAChRs) in 3,665 American Indians participating in the Strong Heart Family Study. Single SNP association with obesity-related traits was tested using family-based association, adjusting for traditional risk factors including smoking. Joint association of all SNPs in the seven nAChRs genes were examined by gene-family analysis based on weighted truncated product method (TPM). Multiple testing was controlled by false discovery rate (FDR). Results demonstrate that multiple SNPs showed weak individual association with one or more measures of obesity, but none survived correction for multiple testing. However, gene-family analysis revealed significant associations with waist circumference (p = 0.0001) and waist-to-hip ratio (p = 0.0001), but not body mass index (p = 0.20) and percent body fat (p = 0.29), indicating that genetic variants are jointly associated with abdominal, but not general, obesity among American Indians. The observed combined genetic effect is independent of cigarette smoking per se. In conclusion, multiple variants in the nAChR gene family are jointly associated with abdominal obesity in American Indians, independent of general obesity and cigarette smoking per se.
Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies
Liu, Zhonghua; Lin, Xihong
2017-01-01
Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391
Multiple phenotype association tests using summary statistics in genome-wide association studies.
Liu, Zhonghua; Lin, Xihong
2018-03-01
We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.
Multiple rare variants in the etiology of autism spectrum disorders
Buxbaum, Joseph D.
2009-01-01
Recent studies in autism spectrum disorders (ASDs) support an important role for multiple rare variants in these conditions. This is a clinically important finding, as, with the demonstration that a significant proportion of ASDs are the result of rare, etiological genetic variants, it becomes possible to make use of genetic testing to supplement behavioral analyses for an earlier diagnosis. As it appears that earlier interventions in ASDs will produce better outcomes, the development of genetic testing to augment behaviorally based evaluations in ASDs holds promise for improved treatment. Furthermore, these rare variants involve synaptic and neuronal genes that implicate specific paihvi/ays, cells, and subcellular compartments in ASDs, which in turn will suggest novel therapeutic approaches in ASDs, Of particular recent interest are the synaptic cell adhesion and associated molecules, including neurexin 1, neuroligin 3 and 4, and SHANK3, which implicate glutamatergic synapse abnormalities in ASDs, In the current review we will overview the evidence for a genetic etiology for ASDs, and summarize recent genetic findings in these disorders. PMID:19432386
de Haas, Sanne; Delmar, Paul; Bansal, Aruna T; Moisse, Matthieu; Miles, David W; Leighl, Natasha; Escudier, Bernard; Van Cutsem, Eric; Carmeliet, Peter; Scherer, Stefan J; Pallaud, Celine; Lambrechts, Diether
2014-10-01
Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.
Whitworth, James; Smith, Philip S; Martin, Jose-Ezequiel; West, Hannah; Luchetti, Andrea; Rodger, Faye; Clark, Graeme; Carss, Keren; Stephens, Jonathan; Stirrups, Kathleen; Penkett, Chris; Mapeta, Rutendo; Ashford, Sofie; Megy, Karyn; Shakeel, Hassan; Ahmed, Munaza; Adlard, Julian; Barwell, Julian; Brewer, Carole; Casey, Ruth T; Armstrong, Ruth; Cole, Trevor; Evans, Dafydd Gareth; Fostira, Florentia; Greenhalgh, Lynn; Hanson, Helen; Henderson, Alex; Hoffman, Jonathan; Izatt, Louise; Kumar, Ajith; Kwong, Ava; Lalloo, Fiona; Ong, Kai Ren; Paterson, Joan; Park, Soo-Mi; Chen-Shtoyerman, Rakefet; Searle, Claire; Side, Lucy; Skytte, Anne-Bine; Snape, Katie; Woodward, Emma R; Tischkowitz, Marc D; Maher, Eamonn R
2018-06-12
Multiple primary tumors (MPTs) affect a substantial proportion of cancer survivors and can result from various causes, including inherited predisposition. Currently, germline genetic testing of MPT-affected individuals for variants in cancer-predisposition genes (CPGs) is mostly targeted by tumor type. We ascertained pre-assessed MPT individuals (with at least two primary tumors by age 60 years or at least three by 70 years) from genetics centers and performed whole-genome sequencing (WGS) on 460 individuals from 440 families. Despite previous negative genetic assessment and molecular investigations, pathogenic variants in moderate- and high-risk CPGs were detected in 67/440 (15.2%) probands. WGS detected variants that would not be (or were not) detected by targeted resequencing strategies, including low-frequency structural variants (6/440 [1.4%] probands). In most individuals with a germline variant assessed as pathogenic or likely pathogenic (P/LP), at least one of their tumor types was characteristic of variants in the relevant CPG. However, in 29 probands (42.2% of those with a P/LP variant), the tumor phenotype appeared discordant. The frequency of individuals with truncating or splice-site CPG variants and at least one discordant tumor type was significantly higher than in a control population (χ 2 = 43.642; p ≤ 0.0001). 2/67 (3%) probands with P/LP variants had evidence of multiple inherited neoplasia allele syndrome (MINAS) with deleterious variants in two CPGs. Together with variant detection rates from a previous series of similarly ascertained MPT-affected individuals, the present results suggest that first-line comprehensive CPG analysis in an MPT cohort referred to clinical genetics services would detect a deleterious variant in about a third of individuals. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Use of allele scores as instrumental variables for Mendelian randomization
Burgess, Stephen; Thompson, Simon G
2013-01-01
Background An allele score is a single variable summarizing multiple genetic variants associated with a risk factor. It is calculated as the total number of risk factor-increasing alleles for an individual (unweighted score), or the sum of weights for each allele corresponding to estimated genetic effect sizes (weighted score). An allele score can be used in a Mendelian randomization analysis to estimate the causal effect of the risk factor on an outcome. Methods Data were simulated to investigate the use of allele scores in Mendelian randomization where conventional instrumental variable techniques using multiple genetic variants demonstrate ‘weak instrument’ bias. The robustness of estimates using the allele score to misspecification (for example non-linearity, effect modification) and to violations of the instrumental variable assumptions was assessed. Results Causal estimates using a correctly specified allele score were unbiased with appropriate coverage levels. The estimates were generally robust to misspecification of the allele score, but not to instrumental variable violations, even if the majority of variants in the allele score were valid instruments. Using a weighted rather than an unweighted allele score increased power, but the increase was small when genetic variants had similar effect sizes. Naive use of the data under analysis to choose which variants to include in an allele score, or for deriving weights, resulted in substantial biases. Conclusions Allele scores enable valid causal estimates with large numbers of genetic variants. The stringency of criteria for genetic variants in Mendelian randomization should be maintained for all variants in an allele score. PMID:24062299
Polygenic determinants in extremes of high-density lipoprotein cholesterol[S
Dron, Jacqueline S.; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A.; Robinson, John F.; McIntyre, Adam D.; Ban, Matthew R.; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J.; Lettre, Guillaume; Tardif, Jean-Claude
2017-01-01
HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. PMID:28870971
Polygenic determinants in extremes of high-density lipoprotein cholesterol.
Dron, Jacqueline S; Wang, Jian; Low-Kam, Cécile; Khetarpal, Sumeet A; Robinson, John F; McIntyre, Adam D; Ban, Matthew R; Cao, Henian; Rhainds, David; Dubé, Marie-Pierre; Rader, Daniel J; Lettre, Guillaume; Tardif, Jean-Claude; Hegele, Robert A
2017-11-01
HDL cholesterol (HDL-C) remains a superior biochemical predictor of CVD risk, but its genetic basis is incompletely defined. In patients with extreme HDL-C concentrations, we concurrently evaluated the contributions of multiple large- and small-effect genetic variants. In a discovery cohort of 255 unrelated lipid clinic patients with extreme HDL-C levels, we used a targeted next-generation sequencing panel to evaluate rare variants in known HDL metabolism genes, simultaneously with common variants bundled into a polygenic trait score. Two additional cohorts were used for validation and included 1,746 individuals from the Montréal Heart Institute Biobank and 1,048 individuals from the University of Pennsylvania. Findings were consistent between cohorts: we found rare heterozygous large-effect variants in 18.7% and 10.9% of low- and high-HDL-C patients, respectively. We also found common variant accumulation, indicated by extreme polygenic trait scores, in an additional 12.8% and 19.3% of overall cases of low- and high-HDL-C extremes, respectively. Thus, the genetic basis of extreme HDL-C concentrations encountered clinically is frequently polygenic, with contributions from both rare large-effect and common small-effect variants. Multiple types of genetic variants should be considered as contributing factors in patients with extreme dyslipidemia. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.
Marian, Ali J.; van Rooij, Eva; Roberts, Robert
2016-01-01
This is the first of 2 review papers on genetics and genomics appearing as part of the series on “omics.” Genomics pertains to all components of an organism’s genes, whereas genetics involves analysis of a specific gene(s) in the context of heredity. The paper provides introductory comments, describes the basis of human genetic diversity, and addresses the phenotypic consequences of genetic variants. Rare variants with large effect sizes are responsible for single-gene disorders, whereas complex polygenic diseases are typically due to multiple genetic variants, each exerting a modest effect size. To illustrate the clinical implications of genetic variants with large effect sizes, 3 common forms of hereditary cardiomyopathies are discussed as prototypic examples of single-gene disorders, including their genetics, clinical manifestations, pathogenesis, and treatment. The genetic basis of complex traits is discussed in a separate paper. PMID:28007145
Zhang, Qianqian; Guldbrandtsen, Bernt; Calus, Mario P L; Lund, Mogens Sandø; Sahana, Goutam
2016-08-17
There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared to LMM. Therefore, it is recommended to use rare variant association mapping methods to map rare genetic variants that affect quantitative traits in livestock, such as bovine populations.
Naaijen, J; Bralten, J; Poelmans, G; Glennon, J C; Franke, B; Buitelaar, J K
2017-01-10
Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) often co-occur. Both are highly heritable; however, it has been difficult to discover genetic risk variants. Glutamate and GABA are main excitatory and inhibitory neurotransmitters in the brain; their balance is essential for proper brain development and functioning. In this study we investigated the role of glutamate and GABA genetics in ADHD severity, autism symptom severity and inhibitory performance, based on gene set analysis, an approach to investigate multiple genetic variants simultaneously. Common variants within glutamatergic and GABAergic genes were investigated using the MAGMA software in an ADHD case-only sample (n=931), in which we assessed ASD symptoms and response inhibition on a Stop task. Gene set analysis for ADHD symptom severity, divided into inattention and hyperactivity/impulsivity symptoms, autism symptom severity and inhibition were performed using principal component regression analyses. Subsequently, gene-wide association analyses were performed. The glutamate gene set showed an association with severity of hyperactivity/impulsivity (P=0.009), which was robust to correcting for genome-wide association levels. The GABA gene set showed nominally significant association with inhibition (P=0.04), but this did not survive correction for multiple comparisons. None of single gene or single variant associations was significant on their own. By analyzing multiple genetic variants within candidate gene sets together, we were able to find genetic associations supporting the involvement of excitatory and inhibitory neurotransmitter systems in ADHD and ASD symptom severity in ADHD.
Identification of rare genetic variation of NLRP1 gene in familial multiple sclerosis.
Maver, Ales; Lavtar, Polona; Ristić, Smiljana; Stopinšek, Sanja; Simčič, Saša; Hočevar, Keli; Sepčić, Juraj; Drulović, Jelena; Pekmezović, Tatjana; Novaković, Ivana; Alenka, Hodžić; Rudolf, Gorazd; Šega, Saša; Starčević-Čizmarević, Nada; Palandačić, Anja; Zamolo, Gordana; Kapović, Miljenko; Likar, Tina; Peterlin, Borut
2017-06-16
The genetic etiology and the contribution of rare genetic variation in multiple sclerosis (MS) has not yet been elucidated. Although familial forms of MS have been described, no convincing rare and penetrant variants have been reported to date. We aimed to characterize the contribution of rare genetic variation in familial and sporadic MS and have identified a family with two sibs affected by concomitant MS and malignant melanoma (MM). We performed whole exome sequencing in this primary family and 38 multiplex MS families and 44 sporadic MS cases and performed transcriptional and immunologic assessment of the identified variants. We identified a potentially causative homozygous missense variant in NLRP1 gene (Gly587Ser) in the primary family. Further possibly pathogenic NLRP1 variants were identified in the expanded cohort of patients. Stimulation of peripheral blood mononuclear cells from MS patients with putatively pathogenic NLRP1 variants showed an increase in IL-1B gene expression and active cytokine IL-1β production, as well as global activation of NLRP1-driven immunologic pathways. We report a novel familial association of MS and MM, and propose a possible underlying genetic basis in NLRP1 gene. Furthermore, we provide initial evidence of the broader implications of NLRP1-related pathway dysfunction in MS.
Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.
Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei
2016-02-01
Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.
Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions
Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei
2015-01-01
Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979
Incorporating gene-environment interaction in testing for association with rare genetic variants.
Chen, Han; Meigs, James B; Dupuis, Josée
2014-01-01
The incorporation of gene-environment interactions could improve the ability to detect genetic associations with complex traits. For common genetic variants, single-marker interaction tests and joint tests of genetic main effects and gene-environment interaction have been well-established and used to identify novel association loci for complex diseases and continuous traits. For rare genetic variants, however, single-marker tests are severely underpowered due to the low minor allele frequency, and only a few gene-environment interaction tests have been developed. We aimed at developing powerful and computationally efficient tests for gene-environment interaction with rare variants. In this paper, we propose interaction and joint tests for testing gene-environment interaction of rare genetic variants. Our approach is a generalization of existing gene-environment interaction tests for multiple genetic variants under certain conditions. We show in our simulation studies that our interaction and joint tests have correct type I errors, and that the joint test is a powerful approach for testing genetic association, allowing for gene-environment interaction. We also illustrate our approach in a real data example from the Framingham Heart Study. Our approach can be applied to both binary and continuous traits, it is powerful and computationally efficient.
Value of genetic profiling for the prediction of coronary heart disease.
van der Net, Jeroen B; Janssens, A Cecile J W; Sijbrands, Eric J G; Steyerberg, Ewout W
2009-07-01
Advances in high-throughput genomics facilitate the identification of novel genetic susceptibility variants for coronary heart disease (CHD). This may improve CHD risk prediction. The aim of the present simulation study was to investigate to what degree CHD risk can be predicted by testing multiple genetic variants (genetic profiling). We simulated genetic profiles for a population of 100,000 individuals with a 10-year CHD incidence of 10%. For each combination of model parameters (number of variants, genotype frequency and odds ratio [OR]), we calculated the area under the receiver operating characteristic curve (AUC) to indicate the discrimination between individuals who will and will not develop CHD. The AUC of genetic profiles could rise to 0.90 when 100 hypothetical variants with ORs of 1.5 and genotype frequencies of 50% were simulated. The AUC of a genetic profile consisting of 10 established variants, with ORs ranging from 1.13 to 1.42, was 0.59. When 2, 5, and 10 times as many identical variants would be identified, the AUCs were 0.63, 0.69, and 0.76. To obtain AUCs similar to those of conventional CHD risk predictors, a considerable number of additional common genetic variants need to be identified with preferably strong effects.
Identifying causal variants at loci with multiple signals of association.
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-10-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. Copyright © 2014 by the Genetics Society of America.
Naaijen, J; Bralten, J; Poelmans, G; Faraone, Stephen; Asherson, Philip; Banaschewski, Tobias; Buitelaar, Jan; Franke, Barbara; P Ebstein, Richard; Gill, Michael; Miranda, Ana; D Oades, Robert; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph; Sonuga-Barke, Edmund; Anney, Richard; Mulas, Fernando; Steinhausen, Hans-Christoph; Glennon, J C; Franke, B; Buitelaar, J K
2017-01-01
Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD) often co-occur. Both are highly heritable; however, it has been difficult to discover genetic risk variants. Glutamate and GABA are main excitatory and inhibitory neurotransmitters in the brain; their balance is essential for proper brain development and functioning. In this study we investigated the role of glutamate and GABA genetics in ADHD severity, autism symptom severity and inhibitory performance, based on gene set analysis, an approach to investigate multiple genetic variants simultaneously. Common variants within glutamatergic and GABAergic genes were investigated using the MAGMA software in an ADHD case-only sample (n=931), in which we assessed ASD symptoms and response inhibition on a Stop task. Gene set analysis for ADHD symptom severity, divided into inattention and hyperactivity/impulsivity symptoms, autism symptom severity and inhibition were performed using principal component regression analyses. Subsequently, gene-wide association analyses were performed. The glutamate gene set showed an association with severity of hyperactivity/impulsivity (P=0.009), which was robust to correcting for genome-wide association levels. The GABA gene set showed nominally significant association with inhibition (P=0.04), but this did not survive correction for multiple comparisons. None of single gene or single variant associations was significant on their own. By analyzing multiple genetic variants within candidate gene sets together, we were able to find genetic associations supporting the involvement of excitatory and inhibitory neurotransmitter systems in ADHD and ASD symptom severity in ADHD. PMID:28072412
Association analysis of multiple traits by an approach of combining P values.
Chen, Lili; Wang, Yong; Zhou, Yajing
2018-03-01
Increasing evidence shows that one variant can affect multiple traits, which is a widespread phenomenon in complex diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic mechanism. Although there are many statistical methods to analyse multiple traits, most of these methods are usually suitable for detecting common variants associated with multiple traits. However, because of low minor allele frequency of rare variant, these methods are not optimal for rare variant association analysis. In this paper, we extend an adaptive combination of P values method (termed ADA) for single trait to test association between multiple traits and rare variants in the given region. For a given region, we use reverse regression model to test each rare variant associated with multiple traits and obtain the P value of single-variant test. Further, we take the weighted combination of these P values as the test statistic. Extensive simulation studies show that our approach is more powerful than several other comparison methods in most cases and is robust to the inclusion of a high proportion of neutral variants and the different directions of effects of causal variants.
Functional linear models for association analysis of quantitative traits.
Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao
2013-11-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY PERIODICALS, INC.
Joint Identification of Genetic Variants for Physical Activity in Korean Population
Kim, Jayoun; Kim, Jaehee; Min, Haesook; Oh, Sohee; Kim, Yeonjung; Lee, Andy H.; Park, Taesung
2014-01-01
There has been limited research on genome-wide association with physical activity (PA). This study ascertained genetic associations between PA and 344,893 single nucleotide polymorphism (SNP) markers in 8842 Korean samples. PA data were obtained from a validated questionnaire that included information on PA intensity and duration. Metabolic equivalent of tasks were calculated to estimate the total daily PA level for each individual. In addition to single- and multiple-SNP association tests, a pathway enrichment analysis was performed to identify the biological significance of SNP markers. Although no significant SNP was found at genome-wide significance level via single-SNP association tests, 59 genetic variants mapped to 76 genes were identified via a multiple SNP approach using a bootstrap selection stability measure. Pathway analysis for these 59 variants showed that maturity onset diabetes of the young (MODY) was enriched. Joint identification of SNPs could enable the identification of multiple SNPs with good predictive power for PA and a pathway enriched for PA. PMID:25026172
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
Koshy, Remya; Ranawat, Anop; Scaria, Vinod
2017-10-01
Middle East and North Africa (MENA) encompass very unique populations, with a rich history and encompasses characteristic ethnic, linguistic and genetic diversity. The genetic diversity of MENA region has been largely unknown. The recent availability of whole-exome and whole-genome sequences from the region has made it possible to collect population-specific allele frequencies. The integration of data sets from this region would provide insights into the landscape of genetic variants in this region. We integrated genetic variants from multiple data sets systematically, available from this region to create a compendium of over 26 million genetic variations. The variants were systematically annotated and their allele frequencies in the data sets were computed and available as a web interface which enables quick query. As a proof of principle for application of the compendium for genetic epidemiology, we analyzed the allele frequencies for variants in transglutaminase 1 (TGM1) gene, associated with autosomal recessive lamellar ichthyosis. Our analysis revealed that the carrier frequency of selected variants differed widely with significant interethnic differences. To the best of our knowledge, al mena is the first and most comprehensive repertoire of genetic variations from the Arab, Middle Eastern and North African region. We hope al mena would accelerate Precision Medicine in the region.
Uptake, Results, and Outcomes of Germline Multiple-Gene Sequencing After Diagnosis of Breast Cancer.
Kurian, Allison W; Ward, Kevin C; Hamilton, Ann S; Deapen, Dennis M; Abrahamse, Paul; Bondarenko, Irina; Li, Yun; Hawley, Sarah T; Morrow, Monica; Jagsi, Reshma; Katz, Steven J
2018-05-10
Low-cost sequencing of multiple genes is increasingly available for cancer risk assessment. Little is known about uptake or outcomes of multiple-gene sequencing after breast cancer diagnosis in community practice. To examine the effect of multiple-gene sequencing on the experience and treatment outcomes for patients with breast cancer. For this population-based retrospective cohort study, patients with breast cancer diagnosed from January 2013 to December 2015 and accrued from SEER registries across Georgia and in Los Angeles, California, were surveyed (n = 5080, response rate = 70%). Responses were merged with SEER data and results of clinical genetic tests, either BRCA1 and BRCA2 (BRCA1/2) sequencing only or including additional other genes (multiple-gene sequencing), provided by 4 laboratories. Type of testing (multiple-gene sequencing vs BRCA1/2-only sequencing), test results (negative, variant of unknown significance, or pathogenic variant), patient experiences with testing (timing of testing, who discussed results), and treatment (strength of patient consideration of, and surgeon recommendation for, prophylactic mastectomy), and prophylactic mastectomy receipt. We defined a patient subgroup with higher pretest risk of carrying a pathogenic variant according to practice guidelines. Among 5026 patients (mean [SD] age, 59.9 [10.7]), 1316 (26.2%) were linked to genetic results from any laboratory. Multiple-gene sequencing increasingly replaced BRCA1/2-only testing over time: in 2013, the rate of multiple-gene sequencing was 25.6% and BRCA1/2-only testing, 74.4%;in 2015 the rate of multiple-gene sequencing was 66.5% and BRCA1/2-only testing, 33.5%. Multiple-gene sequencing was more often ordered by genetic counselors (multiple-gene sequencing, 25.5% and BRCA1/2-only testing, 15.3%) and delayed until after surgery (multiple-gene sequencing, 32.5% and BRCA1/2-only testing, 19.9%). Multiple-gene sequencing substantially increased rate of detection of any pathogenic variant (multiple-gene sequencing: higher-risk patients, 12%; average-risk patients, 4.2% and BRCA1/2-only testing: higher-risk patients, 7.8%; average-risk patients, 2.2%) and variants of uncertain significance, especially in minorities (multiple-gene sequencing: white patients, 23.7%; black patients, 44.5%; and Asian patients, 50.9% and BRCA1/2-only testing: white patients, 2.2%; black patients, 5.6%; and Asian patients, 0%). Multiple-gene sequencing was not associated with an increase in the rate of prophylactic mastectomy use, which was highest with pathogenic variants in BRCA1/2 (BRCA1/2, 79.0%; other pathogenic variant, 37.6%; variant of uncertain significance, 30.2%; negative, 35.3%). Multiple-gene sequencing rapidly replaced BRCA1/2-only testing for patients with breast cancer in the community and enabled 2-fold higher detection of clinically relevant pathogenic variants without an associated increase in prophylactic mastectomy. However, important targets for improvement in the clinical utility of multiple-gene sequencing include postsurgical delay and racial/ethnic disparity in variants of uncertain significance.
Genetic studies of human neuropathic pain conditions: a review
Zorina-Lichtenwalter, Katerina; Parisien, Marc; Diatchenko, Luda
2018-01-01
Abstract Numerous studies have shown associations between genetic variants and neuropathic pain disorders. Rare monogenic disorders are caused by mutations of substantial effect size in a single gene, whereas common disorders are likely to have a contribution from multiple genetic variants of mild effect size, representing different biological pathways. In this review, we survey the reported genetic contributors to neuropathic pain and submit them for validation in a 150,000-participant sample of the U.K. Biobank cohort. Successfully replicated association with a neuropathic pain construct for 2 variants in IL10 underscores the importance of neuroimmune interactions, whereas genome-wide significant association with low back pain (P = 1.3e-8) and false discovery rate 5% significant associations with hip, knee, and neck pain for variant rs7734804 upstream of the MAT2B gene provide evidence of shared contributing mechanisms to overlapping pain conditions at the molecular genetic level. PMID:29240606
The genetics of celiac disease: A comprehensive review of clinical implications.
Dieli-Crimi, Romina; Cénit, M Carmen; Núñez, Concepción
2015-11-01
Celiac disease (CD) is a complex immune-related disease with a very strong genetic component. Multiple genetic findings over the last decade have added to the already known MHC influence numerous genetic variants associated to CD susceptibility. Currently, it is well-established that 6 MHC and 39 non-MHC loci, including a higher number of independent genetic variants, are associated to disease risk. Moreover, additional regions have been recently implicated in the disease, which would increase the number of involved loci. Together, the firmly described genetic variants account for roughly 31% of CD heritability, being 25% explained by the MHC influence. These new variants represent markers of disease risk and turn the identification of the causal genes and the causal variants inside the associated loci, as well as their precise biological role on the disease, into a major challenge in CD research. Numerous studies have been developed with this aim showing the high impact of risk variants on gene expression. These studies also indicate a central role of CD4(+) T cells in CD pathogenesis and point to B cells as important players, which is in accordance with the key steps highlighted by the immunological models of pathogenesis. We comprehensively summarize the current knowledge about the genetic architecture of CD, characterized by multiple low-risk variants located within diverse loci which are most likely affecting genes with immune-related functions. These findings are leading to a better understanding of CD pathogenesis and helping in the design of new treatments. The repertoire of potential drug targets for CD has largely broadened last years, bringing us closer to get alternative or complementary treatments to the life-long gluten-free diet, the only effective treatment so far. Epigenetics and microbiota are emerging as potent factors modulating disease risk and putatively affecting disease manifestation, which are also being explored as therapeutic targets. Copyright © 2015 Elsevier Ltd. All rights reserved.
Chiu, Chi-yang; Jung, Jeesun; Wang, Yifan; Weeks, Daniel E.; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Amos, Christopher I.; Mills, James L.; Boehnke, Michael; Xiong, Momiao; Fan, Ruzong
2016-01-01
In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate F-distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of high-dimensional genotype data. It is shown that approximate F-distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for: (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models which perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods. PMID:27917525
Lin, Yu-Cheng; Chang, Pi-Feng; Chang, Mei-Hwei; Ni, Yen-Hsuan
2014-04-01
A genome-wide association study identified variants in or near patatin-like phospholipase domain-containing-3 (PNPLA3), neurocan (NCAN), lysophospholipase-like 1 (LYPLAL1), glucokinase regulatory protein (GCKR), and protein phosphatase 1 regulatory subunit 3b (PPP1R3B) that were strongly associated with nonalcoholic fatty liver disease (NAFLD) in adults of European ancestry. We examined these genetic variants in obese children and tested whether their effects on NAFLD are significant in the Taiwanese Han Chinese population. We genotyped PNPLA3 rs738409, NCAN rs2228603, LYPLAL1 rs12137855, GCKR rs780094, and PPP1R3B rs4240624 in 797 obese children aged 7-18 y. NAFLD was identified by liver ultrasonography. We analyzed the effect of these genetic variants on NAFLD. NAFLD was identified in 24% of the recruited obese children. We found significant associations with NAFLD at variants in PNPLA3 and GCKR but not in NCAN, LYPLAL1, and PPP1R3B. Multiple logistic regression analysis showed that, after control for the effects of age- and sex-adjusted body mass index, waist-to-hip ratio, sex, and PNPLA3 rs738409 polymorphism, the variant GCKR rs780094 TT genotype independently increased the OR of NAFLD by 1.997 (95% CI: 1.196, 3.335; P = 0.008) compared with the CC genotype. Subjects with the variant GCKR rs780094 TT genotype had a higher mean serum alanine aminotransferase concentration than did those with the CC genotype (30.8 ± 34.7 compared with 22.2 ± 18.6 IU/L; P = 0.01). By studying the genetic variants of obese Taiwanese children, we confirmed that the genetic variants in GCKR rs780094 and PNPLA3 rs738409, but not in NCAN rs2228603, LYPLAL1 rs12137855, and PPP1R3B rs4240624, are associated with an increased risk of NAFLD. GCKR and PNPLA3 variants are the common genetic factors that may confer susceptibility to NAFLD in obese individuals across multiple ethnic groups.
Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.
Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao
2016-04-01
To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.
Yi, SoJeong; An, Hyungmi; Lee, Howard; Lee, Sangin; Ieiri, Ichiro; Lee, Youngjo; Cho, Joo-Youn; Hirota, Takeshi; Fukae, Masato; Yoshida, Kenji; Nagatsuka, Shinichiro; Kimura, Miyuki; Irie, Shin; Sugiyama, Yuichi; Shin, Dong Wan; Lim, Kyoung Soo; Chung, Jae-Yong; Yu, Kyung-Sang; Jang, In-Jin
2014-10-01
Interethnic differences in genetic polymorphism in genes encoding drug-metabolizing enzymes and transporters are one of the major factors that cause ethnic differences in drug response. This study aimed to investigate genetic polymorphisms in genes involved in drug metabolism, transport, and excretion among Korean, Japanese, and Chinese populations, the three major East Asian ethnic groups. The frequencies of 1936 variants representing 225 genes encoding drug-metabolizing enzymes and transporters were determined from 786 healthy participants (448 Korean, 208 Japanese, and 130 Chinese) using the Affymetrix Drug-Metabolizing Enzymes and Transporters Plus microarray. To compare allele or genotype frequencies in the high-dimensional data among the three East Asian ethnic groups, multiple testing, principal component analysis (PCA), and regularized multinomial logit model through least absolute shrinkage and selection operator were used. On microarray analysis, 1071 of 1936 variants (>50% of markers) were found to be monomorphic. In a large number of genetic variants, the fixation index and Pearson's correlation coefficient of minor allele frequencies were less than 0.034 and greater than 0.95, respectively, among the three ethnic groups. PCA identified 47 genetic variants with multiple testing, but was unable to discriminate ethnic groups by the first three components. Multinomial least absolute shrinkage and selection operator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups. However, none of those variants distinguished between the three ethnic groups during subsequent PCA. Korean, Japanese, and Chinese populations are not pharmacogenetically distant from one another, at least with regard to drug disposition, metabolism, and elimination.
Holmes, E.C.; Stephenson, A.G.
2014-01-01
Determining the extent and structure of intra-host genetic diversity and the magnitude and impact of population bottlenecks is central to understanding the mechanisms of viral evolution. To determine the nature of viral evolution following systemic movement through a plant, we performed deep sequencing of 23 leaves that grew sequentially along a single Cucurbita pepo vine that was infected with zucchini yellow mosaic virus (ZYMV), and on a leaf that grew in on a side branch. Strikingly, of 112 genetic (i.e. sub-consensus) variants observed in the data set as a whole, only 22 were found in multiple leaves. Similarly, only three of the 13 variants present in the inoculating population were found in the subsequent leaves on the vine. Hence, it appears that systemic movement is characterized by sequential population bottlenecks, although not sufficient to reduce the population to a single virion as multiple variants were consistently transmitted between leaves. In addition, the number of variants within a leaf increases as a function of distance from the inoculated (source) leaf, suggesting that the circulating sap may serve as a continual source of virus. Notably, multiple mutational variants were observed in the cylindrical Inclusion (CI) protein (known to be involved in both cell-to-cell and systemic movement of the virus) that were present in multiple (19/24) leaf samples. These mutations resulted in a conformational change, suggesting that they might confer a selective advantage in systemic movement within the vine. Overall, these data reveal that bottlenecks occur during systemic movement, that variants circulate in the phloem sap throughout the infection process, and that important conformational changes in CI protein may arise during individual infections. PMID:25107623
Genetic susceptibility to lung cancer—light at the end of the tunnel?
Christiani, David C.
2013-01-01
Lung cancer is one of the most common and deadliest cancers in the world. The major socio-environmental risk factor involved in the development of lung cancer is cigarette smoking. Additionally, there are multiple genetic factors, which may also play a role in lung cancer risk. Early work focused on the presence of relatively prevalent but low-penetrance alterations in candidate genes leading to increased risk of lung cancer. Development of new technologies such as genomic profiling and genome-wide association studies has been helpful in the detection of new genetic variants likely involved in lung cancer risk. In this review, we discuss the role of multiple genetic variants and review their putative role in the risk of lung cancer. Identifying genetic biomarkers and patterns of genetic risk may be useful in the earlier detection and treatment of lung cancer patients. PMID:23349013
Convergence between biological, behavioural and genetic determinants of obesity.
Ghosh, Sujoy; Bouchard, Claude
2017-12-01
Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.
Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease.
2017-12-01
Genetic variants have been associated with myriad molecular phenotypes that provide new insight into the range of mechanisms underlying genetic traits and diseases. Identifying any particular genetic variant's cascade of effects, from molecule to individual, requires assaying multiple layers of molecular complexity. We introduce the Enhancing GTEx (eGTEx) project that extends the GTEx project to combine gene expression with additional intermediate molecular measurements on the same tissues to provide a resource for studying how genetic differences cascade through molecular phenotypes to impact human health.
Tang, Jinsong; Fan, Yu; Li, Hong; Xiang, Qun; Zhang, Deng-Feng; Li, Zongchang; He, Ying; Liao, Yanhui; Wang, Ya; He, Fan; Zhang, Fengyu; Shugart, Yin Yao; Liu, Chunyu; Tang, Yanqing; Chan, Raymond C K; Wang, Chuan-Yue; Yao, Yong-Gang; Chen, Xiaogang
2017-06-20
Schizophrenia is a common disorder with a high heritability, but its genetic architecture is still elusive. We implemented whole-genome sequencing (WGS) analysis of 8 families with monozygotic (MZ) twin pairs discordant for schizophrenia to assess potential association of de novo mutations (DNMs) or inherited variants with susceptibility to schizophrenia. Eight non-synonymous DNMs (including one splicing site) were identified and shared by twins, which were either located in previously reported schizophrenia risk genes (p.V24689I mutation in TTN, p.S2506T mutation in GCN1L1, IVS3+1G > T in DOCK1) or had a benign to damaging effect according to in silico prediction analysis. By searching the inherited rare damaging or loss-of-function (LOF) variants and common susceptible alleles from three classes of schizophrenia candidate genes, we were able to distill genetic alterations in several schizophrenia risk genes, including GAD1, PLXNA2, RELN and FEZ1. Four inherited copy number variations (CNVs; including a large deletion at 16p13.11) implicated for schizophrenia were identified in four families, respectively. Most of families carried both missense DNMs and inherited risk variants, which might suggest that DNMs, inherited rare damaging variants and common risk alleles together conferred to schizophrenia susceptibility. Our results support that schizophrenia is caused by a combination of multiple genetic factors, with each DNM/variant showing a relatively small effect size. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. All rights reserved.
Genetic diversity among isolates of Autographa californica multiple nucleopolyhedrovirus
USDA-ARS?s Scientific Manuscript database
Our knowledge of genetic variation at the nucleotide sequence level of Autographa californica multiple nucleopolyhedrovirus (AcMNPV; Baculoviridae: Alphabaculovirus) derives from complete genome sequences of the C6 clonal isolate of AcMNPV and the R1 and CL3 clonal isolates of AcMNPV variants Rachip...
Khan, Waqasuddin; Saripella, Ganapathi Varma-; Ludwig, Thomas; Cuppens, Tania; Thibord, Florian; Génin, Emmanuelle; Deleuze, Jean-Francois; Trégouët, David-Alexandre
2018-05-03
Predicted deleteriousness of coding variants is a frequently used criterion to filter out variants detected in next-generation sequencing projects and to select candidates impacting on the risk of human diseases. Most available dedicated tools implement a base-to-base annotation approach that could be biased in presence of several variants in the same genetic codon. We here proposed the MACARON program that, from a standard VCF file, identifies, re-annotates and predicts the amino acid change resulting from multiple single nucleotide variants (SNVs) within the same genetic codon. Applied to the whole exome dataset of 573 individuals, MACARON identifies 114 situations where multiple SNVs within a genetic codon induce an amino acid change that is different from those predicted by standard single SNV annotation tool. Such events are not uncommon and deserve to be studied in sequencing projects with inconclusive findings. MACARON is written in python with codes available on the GENMED website (www.genmed.fr). david-alexandre.tregouet@inserm.fr. Supplementary data are available at Bioinformatics online.
Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G
2017-08-01
Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.
Park, S. Lani; Caberto, Christian P.; Lin, Yi; Goodloe, Robert J.; Dumitrescu, Logan; Love, Shelly-Ann; Matise, Tara C.; Hindorff, Lucia A.; Fowke, Jay H.; Schumacher, Fredrick R.; Beebe-Dimmer, Jennifer; Chen, Chu; Hou, Lifang; Thomas, Fridtjof; Deelman, Ewa; Han, Ying; Peters, Ulrike; North, Kari E.; Heiss, Gerardo; Crawford, Dana C.; Haiman, Christopher A.; Wilkens, Lynne R.; Bush, William S.; Kooperberg, Charles; Cheng, Iona; Le Marchand, Loïc
2014-01-01
Background Multiple primary cancers account for ~16% of all incident cancers in the U.S.. While genome-wide association studies (GWAS) have identified many common genetic variants associated with various cancer sites, no study has examined the association of these genetic variants with risk of multiple primary cancers (MPC). Methods As part of the NHGRI Population Architecture using Genomics and Epidemiology (PAGE) study, we used data from the Multiethnic Cohort and Women’s Health Initiative. Incident MPC (IMPC) cases (n=1,385) were defined as participants diagnosed with >1 incident cancers after cohort entry. Participants diagnosed with only one incident cancer after cohort entry with follow-up equal to or longer than IMPC cases served as controls (single-index cancer controls; n= 9,626). Fixed-effects meta-analyses of unconditional logistic regression analyses were used to evaluate the association between cancer risk variants and IMPC risk. To account for multiple comparisons, we used the false positive report probability (FPRP) to determine statistical significance. Results A nicotine dependence-associated and lung cancer variant, CHRNA3 rs578776 (OR=1.16, 95% CI=1.05–1.26; p=0.004) and two breast cancer variants, EMBP1 rs11249433 and TOX3 rs3803662 (OR=1.16, 95% CI=1.04–1.28; p=0.005 and OR=1.13, 95% CI=1.03–1.23; p=0.006) were significantly associated with risk of IMPC. The associations for rs578776 and rs11249433 remained (p<0.05) after removing subjects who had lung or breast cancers, respectively (p-values≤0.046). These associations did not show significant heterogeneity by smoking status (p-heterogeneity≥0.53). Conclusions Our study has identified rs578776 and rs11249433 as risk variants for IMPC. Impact These findings may help to identify genetic regions associated with IMPC risk. PMID:25139936
Genetic architecture and balancing selection: the life and death of differentiated variants.
Llaurens, Violaine; Whibley, Annabel; Joron, Mathieu
2017-05-01
Balancing selection describes any form of natural selection, which results in the persistence of multiple variants of a trait at intermediate frequencies within populations. By offering up a snapshot of multiple co-occurring functional variants and their interactions, systems under balancing selection can reveal the evolutionary mechanisms favouring the emergence and persistence of adaptive variation in natural populations. We here focus on the mechanisms by which several functional variants for a given trait can arise, a process typically requiring multiple epistatic mutations. We highlight how balancing selection can favour specific features in the genetic architecture and review the evolutionary and molecular mechanisms shaping this architecture. First, balancing selection affects the number of loci underlying differentiated traits and their respective effects. Control by one or few loci favours the persistence of differentiated functional variants by limiting intergenic recombination, or its impact, and may sometimes lead to the evolution of supergenes. Chromosomal rearrangements, particularly inversions, preventing adaptive combinations from being dissociated are increasingly being noted as features of such systems. Similarly, due to the frequency of heterozygotes maintained by balancing selection, dominance may be a key property of adaptive variants. High heterozygosity and limited recombination also influence associated genetic load, as linked recessive deleterious mutations may be sheltered. The capture of deleterious elements in a locus under balancing selection may reinforce polymorphism by further promoting heterozygotes. Finally, according to recent genomewide scans, balanced polymorphism might be more pervasive than generally thought. We stress the need for both functional and ecological studies to characterize the evolutionary mechanisms operating in these systems. © 2017 John Wiley & Sons Ltd.
Jahanshad, Neda; Kochunov, Peter; Sprooten, Emma; Mandl, René C.; Nichols, Thomas E.; Almassy, Laura; Blangero, John; Brouwer, Rachel M.; Curran, Joanne E.; de Zubicaray, Greig I.; Duggirala, Ravi; Fox, Peter T.; Hong, L. Elliot; Landman, Bennett A.; Martin, Nicholas G.; McMahon, Katie L.; Medland, Sarah E.; Mitchell, Braxton D.; Olvera, Rene L.; Peterson, Charles P.; Starr, John M.; Sussmann, Jessika E.; Toga, Arthur W.; Wardlaw, Joanna M.; Wright, Margaret J.; Hulshoff Pol, Hilleke E.; Bastin, Mark E.; McIntosh, Andrew M.; Deary, Ian J.; Thompson, Paul M.; Glahn, David C.
2013-01-01
The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA–DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18–85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/). PMID:23629049
Filtering genetic variants and placing informative priors based on putative biological function.
Friedrichs, Stefanie; Malzahn, Dörthe; Pugh, Elizabeth W; Almeida, Marcio; Liu, Xiao Qing; Bailey, Julia N
2016-02-03
High-density genetic marker data, especially sequence data, imply an immense multiple testing burden. This can be ameliorated by filtering genetic variants, exploiting or accounting for correlations between variants, jointly testing variants, and by incorporating informative priors. Priors can be based on biological knowledge or predicted variant function, or even be used to integrate gene expression or other omics data. Based on Genetic Analysis Workshop (GAW) 19 data, this article discusses diversity and usefulness of functional variant scores provided, for example, by PolyPhen2, SIFT, or RegulomeDB annotations. Incorporating functional scores into variant filters or weights and adjusting the significance level for correlations between variants yielded significant associations with blood pressure traits in a large family study of Mexican Americans (GAW19 data set). Marker rs218966 in gene PHF14 and rs9836027 in MAP4 significantly associated with hypertension; additionally, rare variants in SNUPN significantly associated with systolic blood pressure. Variant weights strongly influenced the power of kernel methods and burden tests. Apart from variant weights in test statistics, prior weights may also be used when combining test statistics or to informatively weight p values while controlling false discovery rate (FDR). Indeed, power improved when gene expression data for FDR-controlled informative weighting of association test p values of genes was used. Finally, approaches exploiting variant correlations included identity-by-descent mapping and the optimal strategy for joint testing rare and common variants, which was observed to depend on linkage disequilibrium structure.
Bralten, Janita; Franke, Barbara; Waldman, Irwin; Rommelse, Nanda; Hartman, Catharina; Asherson, Philip; Banaschewski, Tobias; Ebstein, Richard P; Gill, Michael; Miranda, Ana; Oades, Robert D; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph A; Oosterlaan, Jaap; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Faraone, Stephen V; Buitelaar, Jan K; Arias-Vásquez, Alejandro
2013-11-01
Because multiple genes with small effect sizes are assumed to play a role in attention-deficit/hyperactivity disorder (ADHD) etiology, considering multiple variants within the same analysis likely increases the total explained phenotypic variance, thereby boosting the power of genetic studies. This study investigated whether pathway-based analysis could bring scientists closer to unraveling the biology of ADHD. The pathway was described as a predefined gene selection based on a well-established database or literature data. Common genetic variants in pathways involved in dopamine/norepinephrine and serotonin neurotransmission and genes involved in neuritic outgrowth were investigated in cases from the International Multicentre ADHD Genetics (IMAGE) study. Multivariable analysis was performed to combine the effects of single genetic variants within the pathway genes. Phenotypes were DSM-IV symptom counts for inattention and hyperactivity/impulsivity (n = 871) and symptom severity measured with the Conners Parent (n = 930) and Teacher (n = 916) Rating Scales. Summing genetic effects of common genetic variants within the pathways showed a significant association with hyperactive/impulsive symptoms ((p)empirical = .007) but not with inattentive symptoms ((p)empirical = .73). Analysis of parent-rated Conners hyperactive/impulsive symptom scores validated this result ((p)empirical = .0018). Teacher-rated Conners scores were not associated. Post hoc analyses showed a significant contribution of all pathways to the hyperactive/impulsive symptom domain (dopamine/norepinephrine, (p)empirical = .0004; serotonin, (p)empirical = .0149; neuritic outgrowth, (p)empirical = .0452). The present analysis shows an association between common variants in 3 genetic pathways and the hyperactive/impulsive component of ADHD. This study demonstrates that pathway-based association analyses, using quantitative measurements of ADHD symptom domains, can increase the power of genetic analyses to identify biological risk factors involved in this disorder. Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
Rare genetic variants in Tunisian Jewish patients suffering from age-related macular degeneration.
Pras, Eran; Kristal, Dana; Shoshany, Nadav; Volodarsky, Dina; Vulih, Inna; Celniker, Gershon; Isakov, Ofer; Shomron, Noam; Pras, Elon
2015-07-01
To explore the molecular basis of familial, early onset, age-related macular degeneration (AMD) with diverse phenotypes, using whole exome sequencing (WES). We performed WES on four patients (two sibs from two families) manifesting early-onset AMD and searched for disease-causing genetic variants in previously identified macular degeneration related genes. Validation studies of the variants included bioinformatics tools, segregation analysis of mutations within the families and mutation screening in an AMD cohort of patients. The index patients were in their 50s when diagnosed and displayed a wide variety of clinical AMD presentations: from limited drusen in the posterior pole to multiple basal-laminar drusen extending peripherally. Severe visual impairment due to extensive geographic atrophy and/or choroidal-neovascularisation was common by the age of 75 years. Approximately, 400 000 genomic variants for each DNA sample were included in the downstream bioinformatics analysis, which ended in the discovery of two novel variants; in one family a single bp deletion was identified in the Hemicentin (HMCN1) gene (c.4162delC), whereas in the other, a missense variant (p.V412M) in the Complement Factor-I (CFI) gene was found. Screening for these variants in a cohort of patients with AMD identified another family with the CFI variant. This report uses WES to uncover rare genetic variants in AMD. A null-variant in HMCN1 has been identified in one AMD family, and a missense variant in CFI was discovered in two other families. These variants confirm the genetic complexity and significance of rare genetic variants in the pathogenesis of AMD. 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.
Allele-Specific Methylation Occurs at Genetic Variants Associated with Complex Disease
Hutchinson, John N.; Raj, Towfique; Fagerness, Jes; Stahl, Eli; Viloria, Fernando T.; Gimelbrant, Alexander; Seddon, Johanna; Daly, Mark; Chess, Andrew; Plenge, Robert
2014-01-01
We hypothesize that the phenomenon of allele-specific methylation (ASM) may underlie the phenotypic effects of multiple variants identified by Genome-Wide Association studies (GWAS). We evaluate ASM in a human population and document its genome-wide patterns in an initial screen at up to 380,678 sites within the genome, or up to 5% of the total genomic CpGs. We show that while substantial inter-individual variation exists, 5% of assessed sites show evidence of ASM in at least six samples; the majority of these events (81%) are under genetic influence. Many of these cis-regulated ASM variants are also eQTLs in peripheral blood mononuclear cells and monocytes and/or in high linkage-disequilibrium with variants linked to complex disease. Finally, focusing on autoimmune phenotypes, we extend this initial screen to confirm the association of cis-regulated ASM with multiple complex disease-associated variants in an independent population using next-generation bisulfite sequencing. These four variants are implicated in complex phenotypes such as ulcerative colitis and AIDS progression disease (rs10491434), Celiac disease (rs2762051), Crohn's disease, IgA nephropathy and early-onset inflammatory bowel disease (rs713875) and height (rs6569648). Our results suggest cis-regulated ASM may provide a mechanistic link between the non-coding genetic changes and phenotypic variation observed in these diseases and further suggests a route to integrating DNA methylation status with GWAS results. PMID:24911414
Accurate and fast multiple-testing correction in eQTL studies.
Sul, Jae Hoon; Raj, Towfique; de Jong, Simone; de Bakker, Paul I W; Raychaudhuri, Soumya; Ophoff, Roel A; Stranger, Barbara E; Eskin, Eleazar; Han, Buhm
2015-06-04
In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy > 98%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants.
Fadista, João; Manning, Alisa K; Florez, Jose C; Groop, Leif
2016-08-01
Genome-wide association studies (GWAS) have long relied on proposed statistical significance thresholds to be able to differentiate true positives from false positives. Although the genome-wide significance P-value threshold of 5 × 10(-8) has become a standard for common-variant GWAS, it has not been updated to cope with the lower allele frequency spectrum used in many recent array-based GWAS studies and sequencing studies. Using a whole-genome- and -exome-sequencing data set of 2875 individuals of European ancestry from the Genetics of Type 2 Diabetes (GoT2D) project and a whole-exome-sequencing data set of 13 000 individuals from five ancestries from the GoT2D and T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) projects, we describe guidelines for genome- and exome-wide association P-value thresholds needed to correct for multiple testing, explaining the impact of linkage disequilibrium thresholds for distinguishing independent variants, minor allele frequency and ancestry characteristics. We emphasize the advantage of studying recent genetic isolate populations when performing rare and low-frequency genetic association analyses, as the multiple testing burden is diminished due to higher genetic homogeneity.
Using whole-exome sequencing to identify variants inherited from mosaic parents
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
Kikuchi, Naoki; Nakazato, Koichi
2015-01-01
Training variants (type, intensity, and duration of exercise) can be selected according to individual aims and fitness assessment. Recently, various methods of resistance and endurance training have been used for muscle hypertrophy and VO2max improvement. Although several genetic variants are associated with elite athletic performance and muscle phenotypes, genetic background has not been used as variant for physical training. ACTN3 R577X is a well-studied genetic polymorphism. It is the only genotype associated with elite athletic performance in multiple cohorts. This association is strongly supported by mechanistic data from an Actn3-knockout mouse model. In this review, possible guidelines are discussed for effective utilization of ACTN3 R577X polymorphism for physical training. PMID:26526670
Fujinami, Kaoru; Strauss, Rupert W; Chiang, John Pei-Wen; Audo, Isabelle S; Bernstein, Paul S; Birch, David G; Bomotti, Samantha M; Cideciyan, Artur V; Ervin, Ann-Margret; Marino, Meghan J; Sahel, José-Alain; Mohand-Said, Saddek; Sunness, Janet S; Traboulsi, Elias I; West, Sheila; Wojciechowski, Robert; Zrenner, Eberhart; Michaelides, Michel; Scholl, Hendrik P N
2018-06-20
To describe the genetic characteristics of the cohort enrolled in the international multicentre progression of Stargardt disease 1 (STGD1) studies (ProgStar) and to determine geographic differences based on the allele frequency. 345 participants with a clinical diagnosis of STGD1 and harbouring at least one disease-causing ABCA4 variant were enrolled from 9 centres in the USA and Europe. All variants were reviewed and in silico analysis was performed including allele frequency in public databases and pathogenicity predictions. Participants with multiple likely pathogenic variants were classified into four national subgroups (USA, UK, France, Germany), with subsequent comparison analysis of the allele frequency for each prevalent allele. 211 likely pathogenic variants were identified in the total cohort, including missense (63%), splice site alteration (18%), stop (9%) and others. 50 variants were novel. Exclusively missense variants were detected in 139 (50%) of 279 patients with multiple pathogenic variants. The three most prevalent variants of these patients with multiple pathogenic variants were p.G1961E (15%), p.G863A (7%) and c.5461-10 T>C (5%). Subgroup analysis revealed a statistically significant difference between the four recruiting nations in the allele frequency of nine variants. There is a large spectrum of ABCA4 sequence variants, including 50 novel variants, in a well-characterised cohort thereby further adding to the unique allelic heterogeneity in STGD1. Approximately half of the cohort harbours missense variants only, indicating a relatively mild phenotype of the ProgStar cohort. There are significant differences in allele frequencies between nations, although the three most prevalent variants are shared as frequent variants. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Rand, Kristin A; Song, Chi; Dean, Eric; Serie, Daniel J; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S; Bock, Cathryn H; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K; Conti, David V; Zimmerman, Todd; Hwang, Amie E; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L; Berndt, Sonja I; Blot, William J; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W Ryan; Stevens, Victoria L; Lieber, Michael R; Goodman, Phyllis J; Hennis, Anselm J M; Hsing, Ann W; Mehta, Jayesh; Kittles, Rick A; Kolb, Suzanne; Klein, Eric A; Leske, Cristina; Murphy, Adam B; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S; Vij, Ravi; Rybicki, Benjamin A; Stanford, Janet L; Signorello, Lisa B; Witte, John S; Ambrosone, Christine B; Bhatti, Parveen; John, Esther M; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Birmann, Brenda M; Ingles, Sue A; Press, Michael F; Atanackovic, Djordje; Glenn, Martha J; Cannon-Albright, Lisa A; Jones, Brandt; Tricot, Guido; Martin, Thomas G; Kumar, Shaji K; Wolf, Jeffrey L; Deming Halverson, Sandra L; Rothman, Nathaniel; Brooks-Wilson, Angela R; Rajkumar, S Vincent; Kolonel, Laurence N; Chanock, Stephen J; Slager, Susan L; Severson, Richard K; Janakiraman, Nalini; Terebelo, Howard R; Brown, Elizabeth E; De Roos, Anneclaire J; Mohrbacher, Ann F; Colditz, Graham A; Giles, Graham G; Spinelli, John J; Chiu, Brian C; Munshi, Nikhil C; Anderson, Kenneth C; Levy, Joan; Zonder, Jeffrey A; Orlowski, Robert Z; Lonial, Sagar; Camp, Nicola J; Vachon, Celine M; Ziv, Elad; Stram, Daniel O; Hazelett, Dennis J; Haiman, Christopher A; Cozen, Wendy
2016-12-01
Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10 -7 ) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR. ©2016 American Association for Cancer Research.
Rosenthal, E T; Bowles, K R; Pruss, D; van Kan, A; Vail, P J; McElroy, H; Wenstrup, R J
2015-12-01
Based on current consensus guidelines and standard practice, many genetic variants detected in clinical testing are classified as disease causing based on their predicted impact on the normal expression or function of the gene in the absence of additional data. However, our laboratory has identified a subset of such variants in hereditary cancer genes for which compelling contradictory evidence emerged after the initial evaluation following the first observation of the variant. Three representative examples of variants in BRCA1, BRCA2 and MSH2 that are predicted to disrupt splicing, prematurely truncate the protein, or remove the start codon were evaluated for pathogenicity by analyzing clinical data with multiple classification algorithms. Available clinical data for all three variants contradicts the expected pathogenic classification. These variants illustrate potential pitfalls associated with standard approaches to variant classification as well as the challenges associated with monitoring data, updating classifications, and reporting potentially contradictory interpretations to the clinicians responsible for translating test outcomes to appropriate clinical action. It is important to address these challenges now as the model for clinical testing moves toward the use of large multi-gene panels and whole exome/genome analysis, which will dramatically increase the number of genetic variants identified. © 2015 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Xu, Bin; Woodroffe, Abigail; Rodriguez-Murillo, Laura; Roos, J Louw; van Rensburg, Elizabeth J; Abecasis, Gonçalo R; Gogos, Joseph A; Karayiorgou, Maria
2009-09-29
To elucidate the genetic architecture of familial schizophrenia we combine linkage analysis with studies of fine-level chromosomal variation in families recruited from the Afrikaner population in South Africa. We demonstrate that individually rare inherited copy number variants (CNVs) are more frequent in cases with familial schizophrenia as compared to unaffected controls and affect almost exclusively genic regions. Interestingly, we find that while the prevalence of rare structural variants is similar in familial and sporadic cases, the type of variants is markedly different. In addition, using a high-density linkage scan with a panel of nearly 2,000 markers, we identify a region on chromosome 13q34 that shows genome-wide significant linkage to schizophrenia and show that in the families not linked to this locus, there is evidence for linkage to chromosome 1p36. No causative CNVs were identified in either locus. Overall, our results from approaches designed to detect risk variants with relatively low frequency and high penetrance in a well-defined and relatively homogeneous population, provide strong empirical evidence supporting the notion that multiple genetic variants, including individually rare ones, that affect many different genes contribute to the genetic risk of familial schizophrenia. They also highlight differences in the genetic architecture of the familial and sporadic forms of the disease.
Systematic reconstruction of autism biology from massive genetic mutation profiles
Zhang, Chaolin; Jiang, Yong-hui
2018-01-01
Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3′,5′-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein–coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity. PMID:29651456
Systematic reconstruction of autism biology from massive genetic mutation profiles.
Luo, Weijun; Zhang, Chaolin; Jiang, Yong-Hui; Brouwer, Cory R
2018-04-01
Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3',5'-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein-coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity.
Identification of missing variants by combining multiple analytic pipelines.
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 association analyses. The current analytic practice of calling genetic variants from sequencing data using a single bioinformatics pipeline is no longer adequate with the increasingly large projects. The number and percentage of quality variants that passed quality filters but are missed by the one-pipeline approach rapidly increased with sample size.
A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants
Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.
2016-01-01
Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286
Mapping cis- and trans-regulatory effects across multiple tissues in twins
Grundberg, Elin; Small, Kerrin S.; Hedman, Åsa K.; Nica, Alexandra C.; Buil, Alfonso; Keildson, Sarah; Bell, Jordana T.; Yang, Tsun-Po; Meduri, Eshwar; Barrett, Amy; Nisbett, James; Sekowska, Magdalena; Wilk, Alicja; Shin, So-Youn; Glass, Daniel; Travers, Mary; Min, Josine L.; Ring, Sue; Ho, Karen; Thorleifsson, Gudmar; Kong, Augustine; Thorsteindottir, Unnur; Ainali, Chrysanthi; Dimas, Antigone S.; Hassanali, Neelam; Ingle, Catherine; Knowles, David; Krestyaninova, Maria; Lowe, Christopher E.; Di Meglio, Paola; Montgomery, Stephen B.; Parts, Leopold; Potter, Simon; Surdulescu, Gabriela; Tsaprouni, Loukia; Tsoka, Sophia; Bataille, Veronique; Durbin, Richard; Nestle, Frank O.; O’Rahilly, Stephen; Soranzo, Nicole; Lindgren, Cecilia M.; Zondervan, Krina T.; Ahmadi, Kourosh R.; Schadt, Eric E.; Stefansson, Kari; Smith, George Davey; McCarthy, Mark I.; Deloukas, Panos; Dermitzakis, Emmanouil T.; Spector, Tim D.
2013-01-01
Sequence-based variation in gene expression is a key driver of disease risk. Common variants regulating expression in cis have been mapped in many eQTL studies typically in single tissues from unrelated individuals. Here, we present a comprehensive analysis of gene expression across multiple tissues conducted in a large set of mono- and dizygotic twins that allows systematic dissection of genetic (cis and trans) and non-genetic effects on gene expression. Using identity-by-descent estimates, we show that at least 40% of the total heritable cis-effect on expression cannot be accounted for by common cis-variants, a finding which exposes the contribution of low frequency and rare regulatory variants with respect to both transcriptional regulation and complex trait susceptibility. We show that a substantial proportion of gene expression heritability is trans to the structural gene and identify several replicating trans-variants which act predominantly in a tissue-restricted manner and may regulate the transcription of many genes. PMID:22941192
Whole Exome Sequencing Identifies Rare Protein-Coding Variants in Behçet's Disease.
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 donor variant that may introduce a deleterious intron retention and result in a noncoding transcript variant. We used whole exome sequencing in BD for the first time and identified 2 rare putative protein-damaging genetic variants associated with this disease. These genetic variants might influence cytoskeletal regulation and DNA repair mechanisms in BD and might provide further insight into increased leukocyte tissue infiltration and the role of oxidative stress in BD. © 2016, American College of Rheumatology.
A global reference for human genetic variation
2016-01-01
The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies. PMID:26432245
Shrestha, Rima D; Grinberg, Alex; Dukkipati, Venkata S R; Pleydell, Eve J; Prattley, Deborah J; French, Nigel P
2014-05-28
Several Cryptosporidium species are known to infect cattle. However, the occurrence of mixed infections with more than one species and the impact of this phenomenon on animal and human health are poorly understood. Therefore, to detect the presence of mixed Cryptosporidium infections, 15 immunofluorescence-positive specimens obtained from 6-week-old calves' faeces (n=60) on one dairy farm were subjected to PCR-sequencing at multiple loci. DNA sequences of three Cryptosporidium species: C. parvum (15/15), C. bovis (3/15) and C. andersoni (1/15), and two new genetic variants were identified. There was evidence of mixed infections in five specimens. C. parvum, C. bovis and C. andersoni sequences were detected together in one specimen, C. parvum and C. bovis in two specimens, and C. parvum and C. parvum-like variants in the remaining two specimens. Sequencing of gp60 amplicons identified the IIaA19G4R1 (8/15) and IIaA18G3R1 (4/15) C. parvum subgenotypes. This study provides evidence of endemic mixed infections with the three main Cryptosporidium species of cattle and new genetic variants, in calves at the transition age of six weeks. The results add to the body of evidence describing Cryptosporidium isolates as genetically heterogeneous populations, and highlight the need for iterative genotyping to explore their genetic makeup. Copyright © 2014 Elsevier B.V. All rights reserved.
Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.
Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao
2015-08-01
Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.
Mendelian randomization analyses in cardiometabolic disease: challenges in evaluating causality
Holmes, Michael V; Ala-Korpela, Mika; Davey Smith, George
2017-01-01
Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings. PMID:28569269
Shaking Out Clues to Autoimmune Disease
... include type 1 diabetes, inflammatory bowel diseases and multiple sclerosis. Researchers have found many genetic variants that affect ... they examined a mouse disease that resembles human multiple sclerosis. Mice lacking SGK1 had less severe symptoms and ...
Utilising family-based designs for detecting rare variant disease associations.
Preston, Mark D; Dudbridge, Frank
2014-03-01
Rare genetic variants are thought to be important components in the causality of many diseases but discovering these associations is challenging. We demonstrate how best to use family-based designs to improve the power to detect rare variant disease associations. We show that using genetic data from enriched families (those pedigrees with greater than one affected member) increases the power and sensitivity of existing case-control rare variant tests. However, we show that transmission- (or within-family-) based tests do not benefit from this enrichment. This means that, in studies where a limited amount of genotyping is available, choosing a single case from each of many pedigrees has greater power than selecting multiple cases from fewer pedigrees. Finally, we show how a pseudo-case-control design allows a greater range of statistical tests to be applied to family data. © 2014 The Authors. Annals of Human Genetics published by John Wiley & Sons Ltd/University College London.
USDA-ARS?s Scientific Manuscript database
Melanocortin-4-receptor (MC4R) haploinsufficiency is the most common form of monogenic obesity; however, the frequency of MC4R variants and their functional effects in general populations remain uncertain. The aim of this study was to identify and characterize the effects of MC4R variants in Hispani...
[Genetic factors in myocardial infarction].
Hara, Masahiko; Sakata, Yasuhiko; Sato, Hiroshi
2013-02-01
One of the main mechanisms of acute myocardial infarction (AMI) is plaque rupture or erosion followed by intraluminal thrombus formation and occlusion of the coronary arteries. Thus far, many underlying conditions or environmental factors, such as hypertension, diabetes, dyslipidemia, smoking or obesity, as well as a family history of coronary artery diseases have been identified as risks for the onset of AMI. These risks suggest that AMI occurs due to interactions between underlying conditions and multiple genetic susceptibilities. For this reason, many target gene-disease association studies have been performed with the recent introduction of genome-wide association studies (GWAS) that have further revealed new genetic susceptibilities for AMI. GWAS is a way to examine many common genetic variants in different individuals to see if any variant is associated with a trait in a case-control fashion, and typically focuses on associations between single-nucleotide polymorphisms (SNP) and traits. SNP on chromosome 9p21 is one of the robust susceptibility variants for AMI which has been identified by many GWAS. In this review, we overview the methodology of GWAS, introduce genetic variants identified by GWAS as those with susceptibility for AMI, and describe the foresight of using GWAS to investigate genetic susceptibility to AMI.
Rare Variant Association Test with Multiple Phenotypes
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
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.
Xu, Bin; Woodroffe, Abigail; Rodriguez-Murillo, Laura; Roos, J. Louw; van Rensburg, Elizabeth J.; Abecasis, Gonçalo R.; Gogos, Joseph A.; Karayiorgou, Maria
2009-01-01
To elucidate the genetic architecture of familial schizophrenia we combine linkage analysis with studies of fine-level chromosomal variation in families recruited from the Afrikaner population in South Africa. We demonstrate that individually rare inherited copy number variants (CNVs) are more frequent in cases with familial schizophrenia as compared to unaffected controls and affect almost exclusively genic regions. Interestingly, we find that while the prevalence of rare structural variants is similar in familial and sporadic cases, the type of variants is markedly different. In addition, using a high-density linkage scan with a panel of nearly 2,000 markers, we identify a region on chromosome 13q34 that shows genome-wide significant linkage to schizophrenia and show that in the families not linked to this locus, there is evidence for linkage to chromosome 1p36. No causative CNVs were identified in either locus. Overall, our results from approaches designed to detect risk variants with relatively low frequency and high penetrance in a well-defined and relatively homogeneous population, provide strong empirical evidence supporting the notion that multiple genetic variants, including individually rare ones, that affect many different genes contribute to the genetic risk of familial schizophrenia. They also highlight differences in the genetic architecture of the familial and sporadic forms of the disease. PMID:19805367
Abrahams, M-R; Anderson, J A; Giorgi, E E; Seoighe, C; Mlisana, K; Ping, L-H; Athreya, G S; Treurnicht, F K; Keele, B F; Wood, N; Salazar-Gonzalez, J F; Bhattacharya, T; Chu, H; Hoffman, I; Galvin, S; Mapanje, C; Kazembe, P; Thebus, R; Fiscus, S; Hide, W; Cohen, M S; Karim, S Abdool; Haynes, B F; Shaw, G M; Hahn, B H; Korber, B T; Swanstrom, R; Williamson, C
2009-04-01
Identifying the specific genetic characteristics of successfully transmitted variants may prove central to the development of effective vaccine and microbicide interventions. Although human immunodeficiency virus transmission is associated with a population bottleneck, the extent to which different factors influence the diversity of transmitted viruses is unclear. We estimate here the number of transmitted variants in 69 heterosexual men and women with primary subtype C infections. From 1,505 env sequences obtained using a single genome amplification approach we show that 78% of infections involved single variant transmission and 22% involved multiple variant transmissions (median of 3). We found evidence for mutations selected for cytotoxic-T-lymphocyte or antibody escape and a high prevalence of recombination in individuals infected with multiple variants representing another potential escape pathway in these individuals. In a combined analysis of 171 subtype B and C transmission events, we found that infection with more than one variant does not follow a Poisson distribution, indicating that transmission of individual virions cannot be seen as independent events, each occurring with low probability. While most transmissions resulted from a single infectious unit, multiple variant transmissions represent a significant fraction of transmission events, suggesting that there may be important mechanistic differences between these groups that are not yet understood.
Pathway-based discovery of genetic interactions in breast cancer
Xu, Zack Z.; Boone, Charles; Lange, Carol A.
2017-01-01
Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions. PMID:28957314
USDA-ARS?s Scientific Manuscript database
Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher pr...
An integrated map of genetic variation from 1,092 human genomes
2012-01-01
Summary Through characterising the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help understand the genetic contribution to disease. We describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methodologies to integrate information across multiple algorithms and diverse data sources we provide a validated haplotype map of 38 million SNPs, 1.4 million indels and over 14 thousand larger deletions. We show that individuals from different populations carry different profiles of rare and common variants and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways and that each individual harbours hundreds of rare non-coding variants at conserved sites, such as transcription-factor-motif disrupting changes. This resource, which captures up to 98% of accessible SNPs at a frequency of 1% in populations of medical genetics focus, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. PMID:23128226
Rossi, Silvia; Motta, Caterina; Studer, Valeria; Monteleone, Fabrizia; De Chiara, Valentina; Buttari, Fabio; Barbieri, Francesca; Bernardi, Giorgio; Battistini, Luca; Cutter, Gary; Stüve, Olaf; Salvetti, Marco; Centonze, Diego
2013-01-01
Multiple sclerosis (MS) patients discontinuing natalizumab treatment are at risk of disease reactivation. No clinical or surrogate parameters exist to identify patients at risk of post-natalizumab MS reactivation. To determine the role of natalizumab-induced lymphocytosis and of Akt polymorphisms in disease reactivation after natalizumab discontinuation. Peripheral leukocyte count and composition were monitored in 93 MS patients during natalizumab treatment, and in 56 of these subjects who discontinued the treatment. Genetic variants of the anti-apoptotic protein Akt were determined in all subjects because natalizumab modulates the apoptotic pathway and lymphocyte survival is regulated by the apoptotic cascade. Natalizumab-induced peripheral lymphocytosis protected from post-natalizumab MS reactivation. Subjects who relapsed or had magnetic resonance imaging (MRI) worsening after treatment cessation, in fact, had milder peripheral lymphocyte increases during the treatment, largely caused by less marked T cell increase. Furthermore, subjects carrying a variant of the gene coding for Akt associated with reduced anti-apoptotic efficiency (rs2498804T) had lower lymphocytosis and higher risk of disease reactivation. This study identified one functionally meaningful genetic variant within the Akt signaling pathway that is associated with both lymphocyte count and composition alterations during natalizumab treatment, and with the risk of disease reactivation after natalizumab discontinuation.
Fun, Axel; Leitner, Thomas; Vandekerckhove, Linos; Däumer, Martin; Thielen, Alexander; Buchholz, Bernd; Hoepelman, Andy I M; Gisolf, Elizabeth H; Schipper, Pauline J; Wensing, Annemarie M J; Nijhuis, Monique
2018-01-05
Emergence of resistance against integrase inhibitor raltegravir in human immunodeficiency virus type 1 (HIV-1) patients is generally associated with selection of one of three signature mutations: Y143C/R, Q148K/H/R or N155H, representing three distinct resistance pathways. The mechanisms that drive selection of a specific pathway are still poorly understood. We investigated the impact of the HIV-1 genetic background and population dynamics on the emergence of raltegravir resistance. Using deep sequencing we analyzed the integrase coding sequence (CDS) in longitudinal samples from five patients who initiated raltegravir plus optimized background therapy at viral loads > 5000 copies/ml. To investigate the role of the HIV-1 genetic background we created recombinant viruses containing the viral integrase coding region from pre-raltegravir samples from two patients in whom raltegravir resistance developed through different pathways. The in vitro selections performed with these recombinant viruses were designed to mimic natural population bottlenecks. Deep sequencing analysis of the viral integrase CDS revealed that the virological response to raltegravir containing therapy inversely correlated with the relative amount of unique sequence variants that emerged suggesting diversifying selection during drug pressure. In 4/5 patients multiple signature mutations representing different resistance pathways were observed. Interestingly, the resistant population can consist of a single resistant variant that completely dominates the population but also of multiple variants from different resistance pathways that coexist in the viral population. We also found evidence for increased diversification after stronger bottlenecks. In vitro selections with low viral titers, mimicking population bottlenecks, revealed that both recombinant viruses and HXB2 reference virus were able to select mutations from different resistance pathways, although typically only one resistance pathway emerged in each individual culture. The generation of a specific raltegravir resistant variant is not predisposed in the genetic background of the viral integrase CDS. Typically, in the early phases of therapy failure the sequence space is explored and multiple resistance pathways emerge and then compete for dominance which frequently results in a switch of the dominant population over time towards the fittest variant or even multiple variants of similar fitness that can coexist in the viral population.
He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana
2017-09-07
Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Schmidt, Börge; Dragano, Nico; Scherag, André; Pechlivanis, Sonali; Hoffmann, Per; Nöthen, Markus M; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne
2014-06-16
The relevance of disease-related genetic variants for the explanation of social inequalities in complex diseases is unclear and empirical analyses are largely missing. The aim of our study was to examine whether genetic variants predisposing to diabetes mellitus are associated with socioeconomic status in a population-based cohort. We genotyped 11 selected diabetes-related single nucleotide polymorphisms in 4655 participants (age 45-75 years) of the Heinz Nixdorf Recall study. Diabetes status was self-reported or defined by blood glucose levels. Education, income and paternal occupation were assessed as indicators of socioeconomic status. Multiple regression analyses were used to examine the association of socioeconomic status and diabetes by estimating sex-specific and age-adjusted prevalence ratios and their corresponding 95%-confidence intervals. To explore the relationship between individual single nucleotide polymorphisms and socioeconomic status sex- and age-adjusted odds ratios were computed. We adjusted the alpha-level for multiple testing of 11 single nucleotide polymorphisms using Bonferroni's method (α(BF) ~ 0.005). In addition, we explored the association of a genetic risk score with socioeconomic status. Social inequalities in diabetes were observed for all indicators of socioeconomic status. However, there were no significant associations between individual diabetes-related risk alleles and socioeconomic status with odds ratios ranging from 0.87 to 1.23. Similarly, the genetic risk score analysis revealed no evidence for an association. Our data provide no evidence for an association between 11 diabetes-related risk alleles and different indicators of socioeconomic status in a population-based cohort, suggesting that the explored genetic variants do not contribute to health inequalities in diabetes.
Low, Siew-Kee; Chung, Suyoun; Takahashi, Atsushi; Zembutsu, Hitoshi; Mushiroda, Taisei; Kubo, Michiaki; Nakamura, Yusuke
2013-08-01
Chemotherapeutic agents are notoriously known to have a narrow therapeutic range that often results in life-threatening toxicity. Hence, it is clinically important to identify the patients who are at high risk for severe toxicity to certain chemotherapy through a pharmacogenomics approach. In this study, we carried out multiple genome-wide association studies (GWAS) of 13 122 cancer patients who received different chemotherapy regimens, including cyclophosphamide- and platinum-based (cisplatin and carboplatin), anthracycline-based (doxorubicin and epirubicin), and antimetabolite-based (5-fluorouracil and gemcitabine) treatment, antimicrotubule agents (paclitaxel and docetaxel), and topoisomerase inhibitors (camptothecin and etoposide), as well as combination therapy with paclitaxel and carboplatin, to identify genetic variants that are associated with the risk of severe neutropenia/leucopenia in the Japanese population. In addition, we used a weighted genetic risk scoring system to evaluate the cumulative effects of the suggestive genetic variants identified from GWAS in order to predict the risk levels of individuals who carry multiple risk alleles. Although we failed to identify genetic variants that surpassed the genome-wide significance level (P < 5.0 × 10(-8) ) through GWAS, probably due to insufficient statistical power and complex clinical features, we were able to shortlist some of the suggestive associated loci. The current study is at the relatively preliminary stage, but does highlight the complexity and problematic issues associated with retrospective pharmacogenomics studies. However, we hope that verification of these genetic variants through local and international collaborations could improve the clinical outcome for cancer patients. © 2013 Japanese Cancer Association.
Regularized rare variant enrichment analysis for case-control exome sequencing data.
Larson, Nicholas B; Schaid, Daniel J
2014-02-01
Rare variants have recently garnered an immense amount of attention in genetic association analysis. However, unlike methods traditionally used for single marker analysis in GWAS, rare variant analysis often requires some method of aggregation, since single marker approaches are poorly powered for typical sequencing study sample sizes. Advancements in sequencing technologies have rendered next-generation sequencing platforms a realistic alternative to traditional genotyping arrays. Exome sequencing in particular not only provides base-level resolution of genetic coding regions, but also a natural paradigm for aggregation via genes and exons. Here, we propose the use of penalized regression in combination with variant aggregation measures to identify rare variant enrichment in exome sequencing data. In contrast to marginal gene-level testing, we simultaneously evaluate the effects of rare variants in multiple genes, focusing on gene-based least absolute shrinkage and selection operator (LASSO) and exon-based sparse group LASSO models. By using gene membership as a grouping variable, the sparse group LASSO can be used as a gene-centric analysis of rare variants while also providing a penalized approach toward identifying specific regions of interest. We apply extensive simulations to evaluate the performance of these approaches with respect to specificity and sensitivity, comparing these results to multiple competing marginal testing methods. Finally, we discuss our findings and outline future research. © 2013 WILEY PERIODICALS, INC.
Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang
2017-01-01
Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338
Phillips, Anna Evans; LaRusch, Jessica; Greer, Phil; Abberbock, Judah; Alkaade, Samer; Amann, Stephen T; Anderson, Michelle A; Baillie, John; Banks, Peter A; Brand, Randall E; Conwell, Darwin; Coté, Gregory A; Forsmark, Christopher E; Gardner, Timothy B; Gelrud, Andres; Guda, Nalini; Lewis, Michele; Money, Mary E; Muniraj, Thiruvengadam; Sandhu, Bimaljit S; Sherman, Stuart; Singh, Vikesh K; Slivka, Adam; Tang, Gong; Wilcox, C Mel; Whitcomb, David C; Yadav, Dhiraj
2018-05-19
Multiple pathogenic genetic variants are associated with pancreatitis in patients of European (EA) and Asian ancestries, but studies on patients of African ancestry (AA) are lacking. We evaluated the prevalence of known genetic variations in African-American subjects in the US. We studied prospectively enrolled controls (n = 238) and patients with chronic (CP) (n = 232) or recurrent acute pancreatitis (RAP) (n = 45) in the NAPS2 studies from 2000-2014 of self-identified AA. Demographic and phenotypic information was obtained from structured questionnaires. Ancestry and admixture were evaluated by principal component analysis (PCA). Genotyping was performed for pathogenic genetic variants in PRSS1, SPINK1, CFTR and CTRC. Prevalence of disease-associated variants in NAPS2 subjects of AA and EA was compared. When compared with CP subjects of EA (n = 862), prevalence of established pathogenic genetic variants was infrequent in AA patients with CP, overall (29 vs. 8.19%, OR 4.60, 95% CI 2.74-7.74, p < 0.001), and after stratification by alcohol etiology (p < 0.001). On PCA, AA cases were more heterogeneous but distinct from EA subjects; no difference was observed between AA subjects with and without CP-associated variants. Of 19 A A patients with CP who had pathogenic genetic variants, 2 had variants in PRSS1 (R122H, R122C), 4 in SPINK1 (all N34S heterozygotes), 12 in CFTR (2 CFTR sev , 9 CFTR BD , 1 compound heterozygote with CFTR sev and CFTR BD ), and 1 in CTRC (R254W). Pathogenic genetic variants reported in EA patients are significantly less common in AA patients. Further studies are needed to determine the complex risk factors for AA subjects with pancreatitis. Copyright © 2018. Published by Elsevier B.V.
Identifying Common Genetic Risk Factors of Diabetic Neuropathies
Witzel, Ini-Isabée; Jelinek, Herbert F.; Khalaf, Kinda; Lee, Sungmun; Khandoker, Ahsan H.; Alsafar, Habiba
2015-01-01
Type 2 diabetes mellitus (T2DM) is a global public health problem of epidemic proportions, with 60–70% of affected individuals suffering from associated neurovascular complications that act on multiple organ systems. The most common and clinically significant neuropathies of T2DM include uremic neuropathy, peripheral neuropathy, and cardiac autonomic neuropathy. These conditions seriously impact an individual’s quality of life and significantly increase the risk of morbidity and mortality. Although advances in gene sequencing technologies have identified several genetic variants that may regulate the development and progression of T2DM, little is known about whether or not the variants are involved in disease progression and how these genetic variants are associated with diabetic neuropathy specifically. Significant missing heritability data and complex disease etiologies remain to be explained. This article is the first to provide a review of the genetic risk variants implicated in the diabetic neuropathies and to highlight potential commonalities. We thereby aim to contribute to the creation of a genetic-metabolic model that will help to elucidate the cause of diabetic neuropathies, evaluate a patient’s risk profile, and ultimately facilitate preventative and targeted treatment for the individual. PMID:26074879
Polycystic ovary syndrome is not associated with genetic variants that mark risk of type 2 diabetes.
Saxena, R; Welt, C K
2013-06-01
Polycystic ovary syndrome (PCOS) is a disorder of irregular menses, hyperandrogenism and/or polycystic ovary morphology. A large proportion of women with PCOS also exhibit insulin resistance, β-cell dysfunction, impaired glucose tolerance and/or type 2 diabetes (T2D). We therefore hypothesized that genetic variants that predispose to risk of T2D also result in risk of PCOS. Variants robustly associated with T2D in candidate gene or genome-wide association studies (GWAS; n = 56 SNPs from 33 loci) were genotyped in women of European ancestry with PCOS (n = 525) and controls (n = 472), aged 18-45 years. Metabolic, reproductive and anthropomorphic data were examined as a function of the T2D variants. All genetic association analyses were adjusted for age, BMI and ancestry and were reported after correction for multiple testing. There was a nominal association between variants in KCNJ11 and risk of PCOS. However, a risk score of 33 independent T2D-associated variants from GWAS was not significantly associated with PCOS. T2D variants were associated with PCOS phenotype parameters including those in THADA and WFS1 with testosterone levels, ENPP/PC1 with triglyceride levels, FTO with glucose levels and KCNJ11 with FSH levels. Diabetes risk variants are not important risk variants for PCOS.
Population- and individual-specific regulatory variation in Sardinia.
Pala, Mauro; Zappala, Zachary; Marongiu, Mara; Li, Xin; Davis, Joe R; Cusano, Roberto; Crobu, Francesca; Kukurba, Kimberly R; Gloudemans, Michael J; Reinier, Frederic; Berutti, Riccardo; Piras, Maria G; Mulas, Antonella; Zoledziewska, Magdalena; Marongiu, Michele; Sorokin, Elena P; Hess, Gaelen T; Smith, Kevin S; Busonero, Fabio; Maschio, Andrea; Steri, Maristella; Sidore, Carlo; Sanna, Serena; Fiorillo, Edoardo; Bassik, Michael C; Sawcer, Stephen J; Battle, Alexis; Novembre, John; Jones, Chris; Angius, Andrea; Abecasis, Gonçalo R; Schlessinger, David; Cucca, Francesco; Montgomery, Stephen B
2017-05-01
Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.
Chung, Dongjun; Kim, Hang J; Zhao, Hongyu
2017-02-01
Genome-wide association studies (GWAS) have identified tens of thousands of genetic variants associated with hundreds of phenotypes and diseases, which have provided clinical and medical benefits to patients with novel biomarkers and therapeutic targets. However, identification of risk variants associated with complex diseases remains challenging as they are often affected by many genetic variants with small or moderate effects. There has been accumulating evidence suggesting that different complex traits share common risk basis, namely pleiotropy. Recently, several statistical methods have been developed to improve statistical power to identify risk variants for complex traits through a joint analysis of multiple GWAS datasets by leveraging pleiotropy. While these methods were shown to improve statistical power for association mapping compared to separate analyses, they are still limited in the number of phenotypes that can be integrated. In order to address this challenge, in this paper, we propose a novel statistical framework, graph-GPA, to integrate a large number of GWAS datasets for multiple phenotypes using a hidden Markov random field approach. Application of graph-GPA to a joint analysis of GWAS datasets for 12 phenotypes shows that graph-GPA improves statistical power to identify risk variants compared to statistical methods based on smaller number of GWAS datasets. In addition, graph-GPA also promotes better understanding of genetic mechanisms shared among phenotypes, which can potentially be useful for the development of improved diagnosis and therapeutics. The R implementation of graph-GPA is currently available at https://dongjunchung.github.io/GGPA/.
Efficient inference for genetic association studies with multiple outcomes.
Ruffieux, Helene; Davison, Anthony C; Hager, Jorg; Irincheeva, Irina
2017-10-01
Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modeling are either too simplistic to be powerful or are impracticable for computational reasons. Inspired by Richardson and others (2010, Bayesian Statistics 9), we consider a sparse multivariate regression model that allows simultaneous selection of predictors and associated responses. As Markov chain Monte Carlo (MCMC) inference on such models can be prohibitively slow when the number of genetic variants exceeds a few thousand, we propose a variational inference approach which produces posterior information very close to that of MCMC inference, at a much reduced computational cost. Extensive numerical experiments show that our approach outperforms popular variable selection methods and tailored Bayesian procedures, dealing within hours with problems involving hundreds of thousands of genetic variants and tens to hundreds of clinical or molecular outcomes. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Kljaic-Bukvic, Blazenka; Blekic, Mario; Aberle, Neda; Curtin, John A; Hankinson, Jenny; Semic-Jusufagic, Aida; Belgrave, Danielle; Simpson, Angela; Custovic, Adnan
2014-10-01
We investigated the interaction between genetic variants in endotoxin signalling pathway and domestic endotoxin exposure in relation to asthma presence, and amongst children with asthma, we explored the association of these genetic variants and endotoxin exposure with hospital admissions due to asthma exacerbations. In a case-control study, we analysed data from 824 children (417 asthmatics, 407 controls; age 5-18 yr). Amongst asthmatics, we extracted data on hospitalization for asthma exacerbation from medical records. Endotoxin exposure was measured in dust samples collected from homes. We included 26 single-nucleotide polymorphisms (SNPs) in the final analysis (5 CD14, 7LY96 and 14 TLR4). Two variants remained significantly associated with hospital admissions with asthma exacerbations after correction for multiple testing: for CD14 SNP rs5744455, carriers of T allele had decreased risk of repeated hospital admissions compared with homozygotes for C allele [OR (95% CI), 0.42 (0.25-0.88), p = 0.01, False Discovery Rate (FDR) p = 0.02]; for LY96 SNP rs17226566, C-allele carriers were at a lower risk of hospital admissions compared with T-allele homozygotes [0.59 (0.38-0.90), p = 0.01, FDR p = 0.04]. We observed two interactions between SNPs in CD14 and LY96 with environmental endotoxin exposure in relation to hospital admissions due to asthma exacerbation which remained significant after correction for multiple testing (CD14 SNPs rs2915863 and LY96 SNP rs17226566). Amongst children with asthma, genetic variants in CD14 and LY96 may increase the risk of hospital admissions with acute exacerbations. Polymorphisms in endotoxin pathway interact with domestic endotoxin exposure in further modification of the risk of hospitalization. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Genetic variants in cellular transport do not affect mesalamine response in ulcerative colitis
Huang, Hailiang; Rivas, Manuel; Kaplan, Jess L.; Daly, Mark J.; Winter, Harland S.
2018-01-01
Background and aims Mesalamine is commonly used to treat ulcerative colitis (UC). Although mesalamine acts topically, in vitro data suggest that intracellular transport is required for its beneficial effect. Genetic variants in mucosal transport proteins may affect this uptake, but the clinical relevance of these variants has not been studied. The aim of this study was to determine whether variants in genes involved in cellular transport affect the response to mesalamine in UC. Methods Subjects with UC from a 6-week clinical trial using multiple doses of mesalamine were genotyped using a genome-wide array that included common exome variants. Analysis focused on cellular transport gene variants with a minor allele frequency >5%. Mesalamine response was defined as improvement in Week 6 Physician’s Global Assessment (PGA) and non-response as a lack of improvement in Week 6 PGA. Quality control thresholds included an individual genotyping rate of >90%, SNP genotyping rate of >98%, and exclusion for subjects with cryptic relatedness. All included variants met Hardy-Weinberg equilibrium (p>0.001). Results 457 adults with UC were included with 280 responders and 177 non-responders. There were no common variants in transporter genes that were associated with response to mesalamine. The genetic risk score of responders was similar to that of non-responders (p = 0.18). Genome-wide variants demonstrating a trend towards mesalamine response included ST8SIA5 (p = 1x10-5). Conclusions Common transporter gene variants did not affect response to mesalamine in adult UC. The response to mesalamine may be due to rare genetic events or environmental factors such as the intestinal microbiome. PMID:29579042
Rand, Kristin A.; Song, Chi; Dean, Eric; Serie, Daniel J.; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H.; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S.; Bock, Cathryn H.; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K.; V.Conti, David; Zimmerman, Todd; Hwang, Amie E.; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L.; Berndt, Sonja I.; Blot, William J.; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W. Ryan; Stevens, Victoria L.; Lieber, Michael R.; Goodman, Phyllis J.; Hennis, Anselm J.M.; Hsing, Ann W.; Mehta, Jayesh; Kittles, Rick A.; Kolb, Suzanne; Klein, Eric A.; Leske, Cristina; Murphy, Adam B.; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S.; Vij, Ravi; Rybicki, Benjamin A.; Stanford, Janet L.; Signorello, Lisa B.; Witte, John S.; Ambrosone, Christine B.; Bhatti, Parveen; John, Esther M.; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F.; Hu, Jennifer J.; Ziegler, Regina G.; Nyante, Sarah J.; Bandera, Elisa V.; Birmann, Brenda M.; Ingles, Sue A.; Press, Michael F.; Atanackovic, Djordje; Glenn, Martha J.; Cannon-Albright, Lisa A.; Jones, Brandt; Tricot, Guido; Martin, Thomas G.; Kumar, Shaji K.; Wolf, Jeffrey L.; Deming, Sandra L.; Rothman, Nathaniel; Brooks-Wilson, Angela R.; Rajkumar, S. Vincent; Kolonel, Laurence N.; Chanock, Stephen J.; Slager, Susan L.; Severson, Richard K.; Janakiraman, Nalini; Terebelo, Howard R.; Brown, Elizabeth E.; De Roos, Anneclaire J.; Mohrbacher, Ann F.; Colditz, Graham A.; Giles, Graham G.; Spinelli, John J.; Chiu, Brian C.; Munshi, Nikhil C.; Anderson, Kenneth C.; Levy, Joan; Zonder, Jeffrey A.; Orlowski, Robert Z.; Lonial, Sagar; Camp, Nicola J.; Vachon, Celine M.; Ziv, Elad; Stram, Daniel O.; Hazelett, Dennis J.; Haiman, Christopher A.; Cozen, Wendy
2017-01-01
Background Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM). Methods We performed association testing of common variation in eight regions in 1,264 MM patients and 1,479 controls of European ancestry (EA) and 1,305 MM patients and 7,078 controls of African ancestry (AA) and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (p<0.05) associated with MM risk in AAs and EAs and the variant in 3p22.1 was associated in EAs only. In a combined AA-EA meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically signficantly associated with MM risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR=1.32, p=2.93×10−7) in TNFRSF13B, encodes a lymphocyte-specific protein in the tumor necrosis factor receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions We found that reported MM susceptibility regions contain risk variants important across populations supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact A subset of reported risk loci for multiple myeloma have consistent affects across populations and are likely to be functional. PMID:27587788
De Novo Coding Variants Are Strongly Associated with Tourette Disorder
Willsey, A. Jeremy; Fernandez, Thomas V.; Yu, Dongmei; King, Robert A.; Dietrich, Andrea; Xing, Jinchuan; Sanders, Stephan J.; Mandell, Jeffrey D.; Huang, Alden Y.; Richer, Petra; Smith, Louw; Dong, Shan; Samocha, Kaitlin E.; Neale, Benjamin M.; Coppola, Giovanni; Mathews, Carol A.; Tischfield, Jay A.; Scharf, Jeremiah M.; State, Matthew W.; Heiman, Gary A.
2017-01-01
SUMMARY Whole-exome sequencing (WES) and de novo variant detection have proven a powerful approach to gene discovery in complex neurodevelopmental disorders. We have completed WES of 325 Tourette disorder trios from the Tourette International Collaborative Genetics cohort and a replication sample of 186 trios from the Tourette Syndrome Association International Consortium on Genetics (511 total). We observe strong and consistent evidence for the contribution of de novo likely gene-disrupting (LGD) variants (rate ratio [RR] 2.32, p = 0.002). Additionally, de novo damaging variants (LGD and probably damaging missense) are overrepresented in probands (RR 1.37, p = 0.003). We identify four likely risk genes with multiple de novo damaging variants in unrelated probands: WWC1 (WW and C2 domain containing 1), CELSR3 (Cadherin EGF LAG seven-pass G-type receptor 3), NIPBL (Nipped-B-like), and FN1 (fibronectin 1). Overall, we estimate that de novo damaging variants in approximately 400 genes contribute risk in 12% of clinical cases. PMID:28472652
Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants
Pilling, Luke C.; Atkins, Janice L.; Bowman, Kirsty; Jones, Samuel E.; Tyrrell, Jessica; Beaumont, Robin N.; Ruth, Katherine S.; Tuke, Marcus A.; Yaghootkar, Hanieh; Wood, Andrew R.; Freathy, Rachel M.; Murray, Anna; Weedon, Michael N.; Xue, Luting; Lunetta, Kathryn; Murabito, Joanne M.; Harries, Lorna W.; Robine, Jean-Marie; Brayne, Carol; Kuchel, George A.; Ferrucci, Luigi; Frayling, Timothy M.; Melzer, David
2016-01-01
Variation in human lifespan is 20 to 30% heritable in twins but few genetic variants have been identified. We undertook a Genome Wide Association Study (GWAS) using age at death of parents of middle-aged UK Biobank participants of European decent (n=75,244 with father's and/or mother's data, excluding early deaths). Genetic risk scores for 19 phenotypes (n=777 proven variants) were also tested. In GWAS, a nicotine receptor locus (CHRNA3, previously associated with increased smoking and lung cancer) was associated with fathers' survival. Less common variants requiring further confirmation were also identified. Offspring of longer lived parents had more protective alleles for coronary artery disease, systolic blood pressure, body mass index, cholesterol and triglyceride levels, type-1 diabetes, inflammatory bowel disease and Alzheimer's disease. In candidate analyses, variants in the TOMM40/APOE locus were associated with longevity, but FOXO variants were not. Associations between extreme longevity (mother >=98 years, fathers >=95 years, n=1,339) and disease alleles were similar, with an additional association with HDL cholesterol (p=5.7×10-3). These results support a multiple protective factors model influencing lifespan and longevity (top 1% survival) in humans, with prominent roles for cardiovascular-related pathways. Several of these genetically influenced risks, including blood pressure and tobacco exposure, are potentially modifiable. PMID:27015805
European multiple sclerosis risk variants in the south Asian population.
Pandit, Lekha; Ban, Maria; Beecham, Ashley Harris; McCauley, Jacob L; Sawcer, Stephen; D'Cunha, Anitha; Malli, Chaitra; Malik, Omar
2016-10-01
In less than a decade, genomewide association studies have identified over 100 single-nucleotide variants that are associated with increased risk of developing multiple sclerosis. However, since these studies have focused almost exclusively on European populations, it is unclear what role these variants might play in determining risk in other ethnic groups. To assess the effects of European multiple sclerosis-associated risk variants in the south Asian population. Using a combination of chip-based genotyping and next-generation sequencing, we have assessed 109 European-associated variants in a total of 270 cases and 555 controls from the south Asian population. We found that two-thirds of the tested variants (72/109) showed over representation of the European risk allele in south Asian cases (p < 0.0003). In the rest of the Immunochip array, the most associated variant was rs7318477 which maps close to TNFSF13B, the gene for the B-cell-related protein BAFF. Our data indicate substantial overlap in genetic risk architecture between Europeans and south Asians and suggest that the aetiology of the disease may be largely independent of ethnicity. © The Author(s), 2016.
Assessment of the Genetic Architecture of Alzheimer's Disease Risk in Rate of Memory Decline.
Del-Aguila, Jorge L; Fernández, Maria Victoria; Schindler, Suzanne; Ibanez, Laura; Deming, Yuetiva; Ma, Shengmei; Saef, Ben; Black, Kathleen; Budde, John; Norton, Joanne; Chasse, Rachel; Harari, Oscar; Goate, Alison; Xiong, Chengjie; Morris, John C; Cruchaga, Carlos
2018-01-01
Many genetic studies for Alzheimer's disease (AD) have been focused on the identification of common genetic variants associated with AD risk and not on other aspects of the disease, such as age at onset or rate of dementia progression. There are multiple approaches to untangling the genetic architecture of these phenotypes. We hypothesized that the genetic architecture of rate of progression is different than the risk for developing AD dementia. To test this hypothesis, we used longitudinal clinical data from ADNI and the Knight-ADRC at Washington University, and we calculated PRS (polygenic risk score) based on the IGAP study to compare the genetic architecture of AD risk and dementia progression. Dementia progression was measured by the change of Clinical Dementia Rating Sum of Boxes (CDR)-SB per year. Out of the 21 loci for AD risk, no association with the rate of dementia progression was found. The PRS rate was significantly associated with the rate of dementia progression (β= 0.146, p = 0.03). In the case of rare variants, TREM2 (β= 0.309, p = 0.02) was also associated with the rate of dementia progression. TREM2 variant carriers showed a 23% faster rate of dementia compared with non-variant carriers. In conclusion, our results indicate that the recently identified common and rare variants for AD susceptibility have a limited impact on the rate of dementia progression in AD patients.
Identifying Causal Variants at Loci with Multiple Signals of Association
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-01-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20–50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515
Monogenic and polygenic determinants of sarcoma risk: an international genetic study.
Ballinger, Mandy L; Goode, David L; Ray-Coquard, Isabelle; James, Paul A; Mitchell, Gillian; Niedermayr, Eveline; Puri, Ajay; Schiffman, Joshua D; Dite, Gillian S; Cipponi, Arcadi; Maki, Robert G; Brohl, Andrew S; Myklebost, Ola; Stratford, Eva W; Lorenz, Susanne; Ahn, Sung-Min; Ahn, Jin-Hee; Kim, Jeong Eun; Shanley, Sue; Beshay, Victoria; Randall, Robert Lor; Judson, Ian; Seddon, Beatrice; Campbell, Ian G; Young, Mary-Anne; Sarin, Rajiv; Blay, Jean-Yves; O'Donoghue, Seán I; Thomas, David M
2016-09-01
Sarcomas are rare, phenotypically heterogeneous cancers that disproportionately affect the young. Outside rare syndromes, the nature, extent, and clinical significance of their genetic origins are not known. We aimed to investigate the genetic basis for bone and soft-tissue sarcoma seen in routine clinical practice. In this genetic study, we included 1162 patients with sarcoma from four cohorts (the International Sarcoma Kindred Study [ISKS], 966 probands; Project GENESIS, 48 probands; Asan Bio-Resource Center, 138 probands; and kConFab, ten probands), who were older than 15 years at the time of consent and had a histologically confirmed diagnosis of sarcoma, recruited from specialist sarcoma clinics without regard to family history. Detailed clinical, pathological, and pedigree information was collected, and cancer diagnoses in probands and relatives were independently verified. Targeted exon sequencing using blood (n=1114) or saliva (n=48) samples was done on 72 genes (selected due to associations with increased cancer risk) and rare variants were stratified into classes approximating the International Agency for Research on Cancer (IARC) clinical classification for genetic variation. We did a case-control rare variant burden analysis using 6545 Caucasian controls included from three cohorts (ISKS, 235 controls; LifePool, 2010 controls; and National Heart, Lung, and Blood Institute Exome Sequencing Project [ESP], 4300 controls). The median age at cancer diagnosis in 1162 sarcoma probands was 46 years (IQR 29-58), 170 (15%) of 1162 probands had multiple primary cancers, and 155 (17%) of 911 families with informative pedigrees fitted recognisable cancer syndromes. Using a case-control rare variant burden analysis, 638 (55%) of 1162 sarcoma probands bore an excess of pathogenic germline variants (combined odds ratio [OR] 1·43, 95% CI 1·24-1·64, p<0·0001), with 227 known or expected pathogenic variants occurring in 217 individuals. All classes of pathogenic variants (known, expected, or predicted) were associated with earlier age of cancer onset. In addition to TP53, ATM, ATR, and BRCA2, an unexpected excess of functionally pathogenic variants was seen in ERCC2. Probands were more likely than controls to have multiple pathogenic variants compared with the combined control cohort group and the LifePool control cohort (OR 2·22, 95% CI 1·57-3·14, p=1·2 × 10(-6)) and the cumulative burden of multiple variants correlated with earlier age at cancer diagnosis (Mantel-Cox log-rank test for trend, p=0·0032). 66 of 1162 probands carried notifiable variants following expert clinical review (those recognised to be clinically significant to health and about which patients should be advised), whereas 293 (25%) probands carried variants with potential therapeutic significance. About half of patients with sarcoma have putatively pathogenic monogenic and polygenic variation in known and novel cancer genes, with implications for risk management and treatment. Rainbows for Kate Foundation, Johanna Sewell Research Foundation, Australian National Health and Medical Research Council, Cancer Australia, Sarcoma UK, National Cancer Institute, Liddy Shriver Sarcoma Initiative. Copyright © 2016 Elsevier Ltd. All rights reserved.
Wang, Jian; Spitz, Margaret R; Amos, Christopher I; Wu, Xifeng; Wetter, David W; Cinciripini, Paul M; Shete, Sanjay
2012-01-01
A mediation model explores the direct and indirect effects between an independent variable and a dependent variable by including other variables (or mediators). Mediation analysis has recently been used to dissect the direct and indirect effects of genetic variants on complex diseases using case-control studies. However, bias could arise in the estimations of the genetic variant-mediator association because the presence or absence of the mediator in the study samples is not sampled following the principles of case-control study design. In this case, the mediation analysis using data from case-control studies might lead to biased estimates of coefficients and indirect effects. In this article, we investigated a multiple-mediation model involving a three-path mediating effect through two mediators using case-control study data. We propose an approach to correct bias in coefficients and provide accurate estimates of the specific indirect effects. Our approach can also be used when the original case-control study is frequency matched on one of the mediators. We employed bootstrapping to assess the significance of indirect effects. We conducted simulation studies to investigate the performance of the proposed approach, and showed that it provides more accurate estimates of the indirect effects as well as the percent mediated than standard regressions. We then applied this approach to study the mediating effects of both smoking and chronic obstructive pulmonary disease (COPD) on the association between the CHRNA5-A3 gene locus and lung cancer risk using data from a lung cancer case-control study. The results showed that the genetic variant influences lung cancer risk indirectly through all three different pathways. The percent of genetic association mediated was 18.3% through smoking alone, 30.2% through COPD alone, and 20.6% through the path including both smoking and COPD, and the total genetic variant-lung cancer association explained by the two mediators was 69.1%.
DNA mismatch repair gene MSH6 implicated in determining age at natural menopause
Perry, John R.B.; Hsu, Yi-Hsiang; Chasman, Daniel I.; Johnson, Andrew D.; Elks, Cathy; Albrecht, Eva; Andrulis, Irene L.; Beesley, Jonathan; Berenson, Gerald S.; Bergmann, Sven; Bojesen, Stig E.; Bolla, Manjeet K.; Brown, Judith; Buring, Julie E.; Campbell, Harry; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J.; Cox, Angela; Czene, Kamila; D'adamo, Adamo Pio; Davies, Gail; Deary, Ian J.; Dennis, Joe; Easton, Douglas F.; Engelhardt, Ellen G.; Eriksson, Johan G.; Esko, Tõnu; Fasching, Peter A.; Figueroa, Jonine D.; Flyger, Henrik; Fraser, Abigail; Garcia-Closas, Montse; Gasparini, Paolo; Gieger, Christian; Giles, Graham; Guenel, Pascal; Hägg, Sara; Hall, Per; Hayward, Caroline; Hopper, John; Ingelsson, Erik; Kardia, Sharon L.R.; Kasiman, Katherine; Knight, Julia A.; Lahti, Jari; Lawlor, Debbie A.; Magnusson, Patrik K.E.; Margolin, Sara; Marsh, Julie A.; Metspalu, Andres; Olson, Janet E.; Pennell, Craig E.; Polasek, Ozren; Rahman, Iffat; Ridker, Paul M.; Robino, Antonietta; Rudan, Igor; Rudolph, Anja; Salumets, Andres; Schmidt, Marjanka K.; Schoemaker, Minouk J.; Smith, Erin N.; Smith, Jennifer A.; Southey, Melissa; Stöckl, Doris; Swerdlow, Anthony J.; Thompson, Deborah J.; Truong, Therese; Ulivi, Sheila; Waldenberger, Melanie; Wang, Qin; Wild, Sarah; Wilson, James F; Wright, Alan F.; Zgaga, Lina; Ong, Ken K.; Murabito, Joanne M.; Karasik, David; Murray, Anna
2014-01-01
The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10−9), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility. PMID:24357391
Ryan, Niamh M; Lihm, Jayon; Kramer, Melissa; McCarthy, Shane; Morris, Stewart W; Arnau-Soler, Aleix; Davies, Gail; Duff, Barbara; Ghiban, Elena; Hayward, Caroline; Deary, Ian J; Blackwood, Douglas H R; Lawrie, Stephen M; McIntosh, Andrew M; Evans, Kathryn L; Porteous, David J; McCombie, W Richard; Thomson, Pippa A
2018-06-07
Psychiatric disorders are a group of genetically related diseases with highly polygenic architectures. Genome-wide association analyses have made substantial progress towards understanding the genetic architecture of these disorders. More recently, exome- and whole-genome sequencing of cases and families have identified rare, high penetrant variants that provide direct functional insight. There remains, however, a gap in the heritability explained by these complementary approaches. To understand how multiple genetic variants combine to modify both severity and penetrance of a highly penetrant variant, we sequenced 48 whole genomes from a family with a high loading of psychiatric disorder linked to a balanced chromosomal translocation. The (1;11)(q42;q14.3) translocation directly disrupts three genes: DISC1, DISC2, DISC1FP and has been linked to multiple brain imaging and neurocognitive outcomes in the family. Using DNA sequence-level linkage analysis, functional annotation and population-based association, we identified common and rare variants in GRM5 (minor allele frequency (MAF) > 0.05), PDE4D (MAF > 0.2) and CNTN5 (MAF < 0.01) that may help explain the individual differences in phenotypic expression in the family. We suggest that whole-genome sequencing in large families will improve the understanding of the combined effects of the rare and common sequence variation underlying psychiatric phenotypes.
POLE and POLD1 screening in 155 patients with multiple polyps and early-onset colorectal cancer
Esteban-Jurado, Clara; Giménez-Zaragoza, David; Muñoz, Jenifer; Franch-Expósito, Sebastià; Álvarez-Barona, Miriam; Ocaña, Teresa; Cuatrecasas, Miriam; Carballal, Sabela; López-Cerón, María; Marti-Solano, Maria; Díaz-Gay, Marcos; van Wezel, Tom; Castells, Antoni; Bujanda, Luis; Balmaña, Judith; Gonzalo, Victoria; Llort, Gemma; Ruiz-Ponte, Clara; Cubiella, Joaquín; Balaguer, Francesc; Aligué, Rosa; Castellví-Bel, Sergi
2017-01-01
Germline mutations in POLE and POLD1 have been shown to cause predisposition to colorectal multiple polyposis and a wide range of neoplasms, early-onset colorectal cancer being the most prevalent. In order to find additional mutations affecting the proofreading activity of these polymerases, we sequenced its exonuclease domain in 155 patients with multiple polyps or an early-onset colorectal cancer phenotype without alterations in the known hereditary colorectal cancer genes. Interestingly, none of the previously reported mutations in POLE and POLD1 were found. On the other hand, among the genetic variants detected, only two of them stood out as putative pathogenic in the POLE gene, c.1359 + 46del71 and c.1420G > A (p.Val474Ile). The first variant, detected in two families, was not proven to alter correct RNA splicing. Contrarily, c.1420G > A (p.Val474Ile) was detected in one early-onset colorectal cancer patient and located right next to the exonuclease domain. The pathogenicity of this change was suggested by its rarity and bioinformatics predictions, and it was further indicated by functional assays in Schizosaccharomyces pombe. This is the first study to functionally analyze a POLE genetic variant outside the exonuclease domain and widens the spectrum of genetic changes in this DNA polymerase that could lead to colorectal cancer predisposition. PMID:28423643
Genetic Misdiagnoses and the Potential for Health Disparities.
Manrai, Arjun K; Funke, Birgit H; Rehm, Heidi L; Olesen, Morten S; Maron, Bradley A; Szolovits, Peter; Margulies, David M; Loscalzo, Joseph; Kohane, Isaac S
2016-08-18
For more than a decade, risk stratification for hypertrophic cardiomyopathy has been enhanced by targeted genetic testing. Using sequencing results, clinicians routinely assess the risk of hypertrophic cardiomyopathy in a patient's relatives and diagnose the condition in patients who have ambiguous clinical presentations. However, the benefits of genetic testing come with the risk that variants may be misclassified. Using publicly accessible exome data, we identified variants that have previously been considered causal in hypertrophic cardiomyopathy and that are overrepresented in the general population. We studied these variants in diverse populations and reevaluated their initial ascertainments in the medical literature. We reviewed patient records at a leading genetic-testing laboratory for occurrences of these variants during the near-decade-long history of the laboratory. Multiple patients, all of whom were of African or unspecified ancestry, received positive reports, with variants misclassified as pathogenic on the basis of the understanding at the time of testing. Subsequently, all reported variants were recategorized as benign. The mutations that were most common in the general population were significantly more common among black Americans than among white Americans (P<0.001). Simulations showed that the inclusion of even small numbers of black Americans in control cohorts probably would have prevented these misclassifications. We identified methodologic shortcomings that contributed to these errors in the medical literature. The misclassification of benign variants as pathogenic that we found in our study shows the need for sequencing the genomes of diverse populations, both in asymptomatic controls and the tested patient population. These results expand on current guidelines, which recommend the use of ancestry-matched controls to interpret variants. As additional populations of different ancestry backgrounds are sequenced, we expect variant reclassifications to increase, particularly for ancestry groups that have historically been less well studied. (Funded by the National Institutes of Health.).
Shen, Yu-Chih; Liao, Ding-Lieh; Lu, Chao-Lin; Chen, Jen-Yeu; Liou, Ying-Jay; Chen, Tzu-Ting; Chen, Chia-Hsiang
2010-08-01
Vesicular glutamate transporters (VGLUT1-3) package glutamate into vesicles in the presynaptic terminal and regulate the release of glutamate. In mesencephalic dopamine neuron culture, the majority of isolated dopamine neurons express VGLUT2, but not VGLUT1 or 3, have been demonstrated. As related to the dysregulated glutamatergic hypothesis of schizophrenia, the gene encoding VGLUT2 is the most plausible candidate involved in the pathogenesis of this illness. We searched for genetic variants in the promoter region and 12 exons (including UTR ends) of the VGLUT2 gene using direct sequencing in a sample of Han Chinese schizophrenic patients (n=375) and non-psychotic controls (n=366) from Taiwan, and conducted a case-control association study. We identified 8 common SNPs in the VGLUT2 gene. SNP and haplotype-based analyses showed no association with schizophrenia. Besides, we identified 9 rare variants in 13 out of 375 patients, including 3 variants located at the promoter region, 2 synonymous variants located at protein coding regions, and 4 variants located at UTR ends. No rare variants were found in the control subjects. Collectively, these rare variants were significantly overrepresented in the patient group (3.5% versus 0, p value of Fisher's exact test=2.3x10(-5)), suggesting they may contribute to the pathogenesis of schizophrenia. Although the functional significance of these rare variants remains to be characterized, our study may lend support to the multiple rare mutations hypothesis of schizophrenia, and may provide genetic clues to indicate the involvement of the glutamate transmission pathway in the pathogenesis of schizophrenia. Copyright 2010 Elsevier B.V. All rights reserved.
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
Association of genetic variants of GRIN2B with autism.
Pan, Yongcheng; Chen, Jingjing; Guo, Hui; Ou, Jianjun; Peng, Yu; Liu, Qiong; Shen, Yidong; Shi, Lijuan; Liu, Yalan; Xiong, Zhimin; Zhu, Tengfei; Luo, Sanchuan; Hu, Zhengmao; Zhao, Jingping; Xia, Kun
2015-02-06
Autism (MIM 209850) is a complex neurodevelopmental disorder characterized by social communication impairments and restricted repetitive behaviors. It has a high heritability, although much remains unclear. To evaluate genetic variants of GRIN2B in autism etiology, we performed a system association study of common and rare variants of GRIN2B and autism in cohorts from a Chinese population, involving a total sample of 1,945 subjects. Meta-analysis of a triad family cohort and a case-control cohort identified significant associations of multiple common variants and autism risk (Pmin = 1.73 × 10(-4)). Significantly, the haplotype involved with the top common variants also showed significant association (P = 1.78 × 10(-6)). Sanger sequencing of 275 probands from a triad cohort identified several variants in coding regions, including four common variants and seven rare variants. Two of the common coding variants were located in the autism-related linkage disequilibrium (LD) block, and both were significantly associated with autism (P < 9 × 10(-3)) using an independent control cohort. Burden analysis and case-only analysis of rare coding variants identified by Sanger sequencing did not find this association. Our study for the first time reveals that common variants and related haplotypes of GRIN2B are associated with autism risk.
Visscher, H; Ross, C J D; Rassekh, S R; Sandor, G S S; Caron, H N; van Dalen, E C; Kremer, L C; van der Pal, H J; Rogers, P C; Rieder, M J; Carleton, B C; Hayden, M R
2013-08-01
The use of anthracyclines as effective antineoplastic drugs is limited by the occurrence of cardiotoxicity. Multiple genetic variants predictive of anthracycline-induced cardiotoxicity (ACT) in children were recently identified. The current study was aimed to assess replication of these findings in an independent cohort of children. . Twenty-three variants were tested for association with ACT in an independent cohort of 218 patients. Predictive models including genetic and clinical risk factors were constructed in the original cohort and assessed in the current replication cohort. . We confirmed the association of rs17863783 in UGT1A6 and ACT in the replication cohort (P = 0.0062, odds ratio (OR) 7.98). Additional evidence for association of rs7853758 (P = 0.058, OR 0.46) and rs885004 (P = 0.058, OR 0.42) in SLC28A3 was found (combined P = 1.6 × 10(-5) and P = 3.0 × 10(-5), respectively). A previously constructed prediction model did not significantly improve risk prediction in the replication cohort over clinical factors alone. However, an improved prediction model constructed using replicated genetic variants as well as clinical factors discriminated significantly better between cases and controls than clinical factors alone in both original (AUC 0.77 vs. 0.68, P = 0.0031) and replication cohort (AUC 0.77 vs. 0.69, P = 0.060). . We validated genetic variants in two genes predictive of ACT in an independent cohort. A prediction model combining replicated genetic variants as well as clinical risk factors might be able to identify high- and low-risk patients who could benefit from alternative treatment options. Copyright © 2013 Wiley Periodicals, Inc.
MYH9 genetic variants associated with glomerular disease: what is the role for genetic testing?
Kopp, Jeffrey B; Winkler, Cheryl A; Nelson, George W
2010-07-01
Genetic variation in MYH9, encoding nonmuscle myosin IIA heavy chain, has been associated recently with increased risk for kidney disease. Previously, MYH9 missense mutations have been shown to cause the autosomal-dominant MYH9 (ADM9) spectrum, characterized by large platelets, leukocyte Döhle bodies, and, variably, sensorineural deafness, cataracts, and glomerulopathy. Genetic testing is indicated for familial and sporadic cases that fit this spectrum. By contrast, the MYH9 kidney risk variant is characterized by multiple intronic single nucleotide polymorphisms, but the causative variant has not been identified. Disease associations include human immunodeficiency virus-associated collapsing glomerulopathy, focal segmental glomerulosclerosis, hypertension-attributed end-stage kidney disease, and diabetes-attributed end-stage kidney disease. One plausible hypothesis is that the MYH9 kidney risk variant confers a fragile podocyte phenotype. In the case of hypertension-attributed kidney disease, it remains unclear if the hypertension is a contributing cause or a consequence of glomerular injury. The MYH9 kidney risk variant is strikingly more common among individuals of African descent, but only some will develop clinical kidney disease in their lifetime. Thus, it is likely that additional genes and/or environmental factors interact with the MYH9 kidney risk variant to trigger glomerular injury. A preliminary genetic risk stratification scheme, using two single nucleotide polymorphisms, may estimate lifetime risk for kidney disease. Nevertheless, at present, no role has been established for genetic testing as part of personalized medicine, but testing should be considered in clinical studies of glomerular diseases among populations of African descent. Such studies will address critical questions pertaining to MYH9-associated kidney disease, including mechanism, course, and response to therapy. Published by Elsevier Inc.
Edenberg, Howard J; Foroud, Tatiana
2014-01-01
Multiple lines of evidence strongly indicate that genetic factors contribute to the risk for alcohol use disorders (AUD). There is substantial heterogeneity in AUD, which complicates studies seeking to identify specific genetic factors. To identify these genetic effects, several different alcohol-related phenotypes have been analyzed, including diagnosis and quantitative measures related to AUDs. Study designs have used candidate gene analyses, genetic linkage studies, genomewide association studies (GWAS), and analyses of rare variants. Two genes that encode enzymes of alcohol metabolism have the strongest effect on AUD: aldehyde dehydrogenase 2 and alcohol dehydrogenase 1B each has strongly protective variants that reduce risk, with odds ratios approximately 0.2-0.4. A number of other genes important in AUD have been identified and replicated, including GABRA2 and alcohol dehydrogenases 1B and 4. GWAS have identified additional candidates. Rare variants are likely also to play a role; studies of these are just beginning. A multifaceted approach to gene identification, targeting both rare and common variations and assembling much larger datasets for meta-analyses, is critical for identifying the key genes and pathways important in AUD. © 2014 Elsevier B.V. All rights reserved.
Abrahams, M.-R.; Anderson, J. A.; Giorgi, E. E.; Seoighe, C.; Mlisana, K.; Ping, L.-H.; Athreya, G. S.; Treurnicht, F. K.; Keele, B. F.; Wood, N.; Salazar-Gonzalez, J. F.; Bhattacharya, T.; Chu, H.; Hoffman, I.; Galvin, S.; Mapanje, C.; Kazembe, P.; Thebus, R.; Fiscus, S.; Hide, W.; Cohen, M. S.; Karim, S. Abdool; Haynes, B. F.; Shaw, G. M.; Hahn, B. H.; Korber, B. T.; Swanstrom, R.; Williamson, C.
2009-01-01
Identifying the specific genetic characteristics of successfully transmitted variants may prove central to the development of effective vaccine and microbicide interventions. Although human immunodeficiency virus transmission is associated with a population bottleneck, the extent to which different factors influence the diversity of transmitted viruses is unclear. We estimate here the number of transmitted variants in 69 heterosexual men and women with primary subtype C infections. From 1,505 env sequences obtained using a single genome amplification approach we show that 78% of infections involved single variant transmission and 22% involved multiple variant transmissions (median of 3). We found evidence for mutations selected for cytotoxic-T-lymphocyte or antibody escape and a high prevalence of recombination in individuals infected with multiple variants representing another potential escape pathway in these individuals. In a combined analysis of 171 subtype B and C transmission events, we found that infection with more than one variant does not follow a Poisson distribution, indicating that transmission of individual virions cannot be seen as independent events, each occurring with low probability. While most transmissions resulted from a single infectious unit, multiple variant transmissions represent a significant fraction of transmission events, suggesting that there may be important mechanistic differences between these groups that are not yet understood. PMID:19193811
Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa; ...
2014-09-01
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
Martin-Fernandez, Laura; Gavidia-Bovadilla, Giovana; Corrales, Irene; Brunel, Helena; Ramírez, Lorena; López, Sonia; Souto, Juan Carlos; Vidal, Francisco; Soria, José Manuel
2017-01-01
Venous thromboembolism is a complex disease with a high heritability. There are significant associations among Factor XI (FXI) levels and SNPs in the KNG1 and F11 loci. Our aim was to identify the genetic variation of KNG1 and F11 that might account for the variability of FXI levels. The KNG1 and F11 loci were sequenced completely in 110 unrelated individuals from the GAIT-2 (Genetic Analysis of Idiopathic Thrombophilia 2) Project using Next Generation Sequencing on an Illumina MiSeq. The GAIT-2 Project is a study of 935 individuals in 35 extended Spanish families selected through a proband with idiopathic thrombophilia. Among the 110 individuals, a subset of 40 individuals was chosen as a discovery sample for identifying variants. A total of 762 genetic variants were detected. Several significant associations were established among common variants and low-frequency variants sets in KNG1 and F11 with FXI levels using the PLINK and SKAT packages. Among these associations, those of rs710446 and five low-frequency variant sets in KNG1 with FXI level variation were significant after multiple testing correction and permutation. Also, two putative pathogenic mutations related to high and low FXI levels were identified by data filtering and in silico predictions. This study of KNG1 and F11 loci should help to understand the connection between genotypic variation and variation in FXI levels. The functional genetic variants should be useful as markers of thromboembolic risk.
The challenges, advantages and future of phenome-wide association studies.
Hebbring, Scott J
2014-02-01
Over the last decade, significant technological breakthroughs have revolutionized human genomic research in the form of genome-wide association studies (GWASs). GWASs have identified thousands of statistically significant genetic variants associated with hundreds of human conditions including many with immunological aetiologies (e.g. multiple sclerosis, ankylosing spondylitis and rheumatoid arthritis). Unfortunately, most GWASs fail to identify clinically significant associations. Identifying biologically significant variants by GWAS also presents a challenge. The GWAS is a phenotype-to-genotype approach. As a complementary/alternative approach to the GWAS, investigators have begun to exploit extensive electronic medical record systems to conduct a genotype-to-phenotype approach when studying human disease - specifically, the phenome-wide association study (PheWAS). Although the PheWAS approach is in its infancy, this method has already demonstrated its capacity to rediscover important genetic associations related to immunological diseases/conditions. Furthermore, PheWAS has the advantage of identifying genetic variants with pleiotropic properties. This is particularly relevant for HLA variants. For example, PheWAS results have demonstrated that the HLA-DRB1 variant associated with multiple sclerosis may also be associated with erythematous conditions including rosacea. Likewise, PheWAS has demonstrated that the HLA-B genotype is not only associated with spondylopathies, uveitis, and variability in platelet count, but may also play an important role in other conditions, such as mastoiditis. This review will discuss and compare general PheWAS methodologies, describe both the challenges and advantages of the PheWAS, and provide insight into the potential directions in which PheWAS may lead. © 2013 The Authors. Immunology Published by John Wiley & Sons Ltd.
Robinson, W P; Barbosa, J; Rich, S S; Thomson, G
1993-01-01
For complex genetic diseases involving incomplete penetrance, genetic heterogeneity, and multiple disease genes, it is often difficult to determine the molecular variant(s) responsible for the disease pathogenesis. Linkage and association studies may help identify genetic regions and molecular variants suspected of being directly responsible for disease predisposition or protection, but, especially for complex diseases, they are less useful for determining when a predisposing molecular variant has been identified. In this paper, we expand upon the simple concept that if a genetic factor predisposing to disease has been fully identified, then a parent homozygous for this factor should transmit either of his/her copies at random to any affected children. Closely linked markers are used to determine identity by descent values in affected sib pairs from a parent homozygous for a putative disease predisposing factor. The expected deviation of haplotype sharing from 50%, when not all haplotypes carrying this factor are in fact equally predisposing, has been algebraically determined for a single locus general disease model. Equations to determine expected sharing for multiple disease alleles or multiple disease locus models have been formulated. The recessive case is in practice limiting and therefore can be used to estimate the maximum proportion of putative susceptibility haplotypes which are in fact predisposing to disease when the mode of inheritance of a disease is unknown. This method has been applied to 27 DR3/DR3 parents and 50 DR4/DR4 parents who have at least 2 children affected with insulin dependent diabetes mellitus (IDDM). The transmission of both DR3 and DR4 haplotypes is statistically different from 50% (P < 0.05 and P < 0.001, respectively). An upper estimate for the proportion of DR3 haplotypes associated with a high IDDM susceptibility is 49%, and for DR4 haplotypes 38%. Our results show that the joint presence of non-Asp at DQ beta position 57 and Arg at DQ alpha position 52, which has been proposed as a strong IDDM predisposing factor, is insufficient to explain the HLA component of IDDM predisposition.
Jóri, Balazs; Kamps, Rick; Xanthoulea, Sofia; Delvoux, Bert; Blok, Marinus J; Van de Vijver, Koen K; de Koning, Bart; Oei, Felicia Trups; Tops, Carli M; Speel, Ernst Jm; Kruitwagen, Roy F; Gomez-Garcia, Encarna B; Romano, Andrea
2015-12-01
The risk to develop colorectal and endometrial cancers among subjects testing positive for a pathogenic Lynch syndrome mutation varies, making the risk prediction difficult. Genetic risk modifiers alter the risk conferred by inherited Lynch syndrome mutations, and their identification can improve genetic counseling. We aimed at identifying rare genetic modifiers of the risk of Lynch syndrome endometrial cancer. A family based approach was used to assess the presence of genetic risk modifiers among 35 Lynch syndrome mutation carriers having either a poor clinical phenotype (early age of endometrial cancer diagnosis or multiple cancers) or a neutral clinical phenotype. Putative genetic risk modifiers were identified by Next Generation Sequencing among a panel of 154 genes involved in endometrial physiology and carcinogenesis. A simple pipeline, based on an allele frequency lower than 0.001 and on predicted non-conservative amino-acid substitutions returned 54 variants that were considered putative risk modifiers. The presence of two or more risk modifying variants in women carrying a pathogenic Lynch syndrome mutation was associated with a poor clinical phenotype. A gene-panel is proposed that comprehends genes that can carry variants with putative modifying effects on the risk of Lynch syndrome endometrial cancer. Validation in further studies is warranted before considering the possible use of this tool in genetic counseling.
Munretnam, Khamsigan; Alex, Livy; Ramzi, Nurul Hanis; Chahil, Jagdish Kaur; Kavitha, I S; Hashim, Nikman Adli Nor; Lye, Say Hean; Velapasamy, Sharmila; Ler, Lian Wee
2014-01-01
There is growing global interest to stratify men into different levels of risk to developing prostate cancer, thus it is important to identify common genetic variants that confer the risk. Although many studies have identified more than a dozen common genetic variants which are highly associated with prostate cancer, none have been done in Malaysian population. To determine the association of such variants in Malaysian men with prostate cancer, we evaluated a panel of 768 SNPs found previously associated with various cancers which also included the prostate specific SNPs in a population based case control study (51 case subjects with prostate cancer and 51 control subjects) in Malaysian men of Malay, Chinese and Indian ethnicity. We identified 21 SNPs significantly associated with prostate cancer. Among these, 12 SNPs were strongly associated with increased risk of prostate cancer while remaining nine SNPs were associated with reduced risk. However, data analysis based on ethnic stratification led to only five SNPs in Malays and 3 SNPs in Chinese which remained significant. This could be due to small sample size in each ethnic group. Significant non-genetic risk factors were also identified for their association with prostate cancer. Our study is the first to investigate the involvement of multiple variants towards susceptibility for PC in Malaysian men using genotyping approach. Identified SNPs and non-genetic risk factors have a significant association with prostate cancer.
Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models
Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong
2015-01-01
In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955
Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.
Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong
2015-05-01
In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.
COGENT (COlorectal cancer GENeTics) revisited
Houlston, Richard S.
2012-01-01
Many colorectal cancers (CRCs) develop in genetically susceptible individuals most of whom are not carriers of germ line mismatch repair or APC gene mutations and much of the heritable risk of CRC appears to be attributable to the co-inheritance of multiple low-risk variants. The accumulated experience to date in identifying this class of susceptibility allele has highlighted the need to conduct statistically and methodologically rigorous studies and the need for the multi-centre collaboration. This has been the motivation for establishing the COGENT (COlorectal cancer GENeTics) consortium which now includes over 20 research groups in Europe, Australia, the Americas, China and Japan actively working on CRC genetics. Here, we review the rationale for identifying low-penetrance variants for CRC and the current and future challenges for COGENT. PMID:22294761
Hundreds of variants clustered in genomic loci and biological pathways affect human height
Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segrè, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Mägi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Åsa; Zillikens, M.Carola; Feitosa, Mary F.; Esko, Tõnu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Glazer, Nicole L.; Hayward, Caroline; Hottenga, Jouke-Jan; Jacobs, Kevin B.; Knowles, Joshua W.; Kutalik, Zoltán; Monda, Keri L.; Polasek, Ozren; Preuss, Michael; Rayner, Nigel W.; Robertson, Neil R.; Steinthorsdottir, Valgerdur; Tyrer, Jonathan P.; Voight, Benjamin F.; Wiklund, Fredrik; Xu, Jianfeng; Zhao, Jing Hua; Nyholt, Dale R.; Pellikka, Niina; Perola, Markus; Perry, John R.B.; Surakka, Ida; Tammesoo, Mari-Liis; Altmaier, Elizabeth L.; Amin, Najaf; Aspelund, Thor; Bhangale, Tushar; Boucher, Gabrielle; Chasman, Daniel I.; Chen, Constance; Coin, Lachlan; Cooper, Matthew N.; Dixon, Anna L.; Gibson, Quince; Grundberg, Elin; Hao, Ke; Junttila, M. Juhani; Kaplan, Lee M.; Kettunen, Johannes; König, Inke R.; Kwan, Tony; Lawrence, Robert W.; Levinson, Douglas F.; Lorentzon, Mattias; McKnight, Barbara; Morris, Andrew P.; Müller, Martina; Ngwa, Julius Suh; Purcell, Shaun; Rafelt, Suzanne; Salem, Rany M.; Salvi, Erika; Sanna, Serena; Shi, Jianxin; Sovio, Ulla; Thompson, John R.; Turchin, Michael C.; Vandenput, Liesbeth; Verlaan, Dominique J.; Vitart, Veronique; White, Charles C.; Ziegler, Andreas; Almgren, Peter; Balmforth, Anthony J.; Campbell, Harry; Citterio, Lorena; De Grandi, Alessandro; Dominiczak, Anna; Duan, Jubao; Elliott, Paul; Elosua, Roberto; Eriksson, Johan G.; Freimer, Nelson B.; Geus, Eco J.C.; Glorioso, Nicola; Haiqing, Shen; Hartikainen, Anna-Liisa; Havulinna, Aki S.; Hicks, Andrew A.; Hui, Jennie; Igl, Wilmar; Illig, Thomas; Jula, Antti; Kajantie, Eero; Kilpeläinen, Tuomas O.; Koiranen, Markku; Kolcic, Ivana; Koskinen, Seppo; Kovacs, Peter; Laitinen, Jaana; Liu, Jianjun; Lokki, Marja-Liisa; Marusic, Ana; Maschio, Andrea; Meitinger, Thomas; Mulas, Antonella; Paré, Guillaume; Parker, Alex N.; Peden, John F.; Petersmann, Astrid; Pichler, Irene; Pietiläinen, Kirsi H.; Pouta, Anneli; Ridderstråle, Martin; Rotter, Jerome I.; Sambrook, Jennifer G.; Sanders, Alan R.; Schmidt, Carsten Oliver; Sinisalo, Juha; Smit, Jan H.; Stringham, Heather M.; Walters, G.Bragi; Widen, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Zagato, Laura; Zgaga, Lina; Zitting, Paavo; Alavere, Helene; Farrall, Martin; McArdle, Wendy L.; Nelis, Mari; Peters, Marjolein J.; Ripatti, Samuli; van Meurs, Joyce B.J.; Aben, Katja K.; Ardlie, Kristin G; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Collins, Francis S.; Cusi, Daniele; den Heijer, Martin; Eiriksdottir, Gudny; Gejman, Pablo V.; Hall, Alistair S.; Hamsten, Anders; Huikuri, Heikki V.; Iribarren, Carlos; Kähönen, Mika; Kaprio, Jaakko; Kathiresan, Sekar; Kiemeney, Lambertus; Kocher, Thomas; Launer, Lenore J.; Lehtimäki, Terho; Melander, Olle; Mosley, Tom H.; Musk, Arthur W.; Nieminen, Markku S.; O'Donnell, Christopher J.; Ohlsson, Claes; Oostra, Ben; Palmer, Lyle J.; Raitakari, Olli; Ridker, Paul M.; Rioux, John D.; Rissanen, Aila; Rivolta, Carlo; Schunkert, Heribert; Shuldiner, Alan R.; Siscovick, David S.; Stumvoll, Michael; Tönjes, Anke; Tuomilehto, Jaakko; van Ommen, Gert-Jan; Viikari, Jorma; Heath, Andrew C.; Martin, Nicholas G.; Montgomery, Grant W.; Province, Michael A.; Kayser, Manfred; Arnold, Alice M.; Atwood, Larry D.; Boerwinkle, Eric; Chanock, Stephen J.; Deloukas, Panos; Gieger, Christian; Grönberg, Henrik; Hall, Per; Hattersley, Andrew T.; Hengstenberg, Christian; Hoffman, Wolfgang; Lathrop, G.Mark; Salomaa, Veikko; Schreiber, Stefan; Uda, Manuela; Waterworth, Dawn; Wright, Alan F.; Assimes, Themistocles L.; Barroso, Inês; Hofman, Albert; Mohlke, Karen L.; Boomsma, Dorret I.; Caulfield, Mark J.; Cupples, L.Adrienne; Erdmann, Jeanette; Fox, Caroline S.; Gudnason, Vilmundur; Gyllensten, Ulf; Harris, Tamara B.; Hayes, Richard B.; Jarvelin, Marjo-Riitta; Mooser, Vincent; Munroe, Patricia B.; Ouwehand, Willem H.; Penninx, Brenda W.; Pramstaller, Peter P.; Quertermous, Thomas; Rudan, Igor; Samani, Nilesh J.; Spector, Timothy D.; Völzke, Henry; Watkins, Hugh; Wilson, James F.; Groop, Leif C.; Haritunians, Talin; Hu, Frank B.; Kaplan, Robert C.; Metspalu, Andres; North, Kari E.; Schlessinger, David; Wareham, Nicholas J.; Hunter, David J.; O'Connell, Jeffrey R.; Strachan, David P.; Wichmann, H.-Erich; Borecki, Ingrid B.; van Duijn, Cornelia M.; Schadt, Eric E.; Thorsteinsdottir, Unnur; Peltonen, Leena; Uitterlinden, André; Visscher, Peter M.; Chatterjee, Nilanjan; Loos, Ruth J.F.; Boehnke, Michael; McCarthy, Mark I.; Ingelsson, Erik; Lindgren, Cecilia M.; Abecasis, Gonçalo R.; Stefansson, Kari; Frayling, Timothy M.; Hirschhorn, Joel N
2010-01-01
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. PMID:20881960
Zhu, Yun; Fan, Ruzong; Xiong, Momiao
2017-01-01
Investigating the pleiotropic effects of genetic variants can increase statistical power, provide important information to achieve deep understanding of the complex genetic structures of disease, and offer powerful tools for designing effective treatments with fewer side effects. However, the current multiple phenotype association analysis paradigm lacks breadth (number of phenotypes and genetic variants jointly analyzed at the same time) and depth (hierarchical structure of phenotype and genotypes). A key issue for high dimensional pleiotropic analysis is to effectively extract informative internal representation and features from high dimensional genotype and phenotype data. To explore correlation information of genetic variants, effectively reduce data dimensions, and overcome critical barriers in advancing the development of novel statistical methods and computational algorithms for genetic pleiotropic analysis, we proposed a new statistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association analysis which combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CCA). Large-scale simulations show that the QRFCCA has a much higher power than that of the ten competing statistics while retaining the appropriate type 1 errors. To further evaluate performance, the QRFCCA and ten other statistics are applied to the whole genome sequencing dataset from the TwinsUK study. We identify a total of 79 genes with rare variants and 67 genes with common variants significantly associated with the 46 traits using QRFCCA. The results show that the QRFCCA substantially outperforms the ten other statistics. PMID:29040274
DOE Office of Scientific and Technical Information (OSTI.GOV)
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
Human genetic variation and the gut microbiome in disease.
Hall, Andrew Brantley; Tolonen, Andrew C; Xavier, Ramnik J
2017-11-01
Taxonomic and functional changes to the composition of the gut microbiome have been implicated in multiple human diseases. Recent microbiome genome-wide association studies reveal that variants in many human genes involved in immunity and gut architecture are associated with an altered composition of the gut microbiome. Although many factors can affect the microbial organisms residing in the gut, a number of recent findings support the hypothesis that certain host genetic variants predispose an individual towards microbiome dysbiosis. This condition, in which the normal microbiome population structure is disturbed, is a key feature in disorders of metabolism and immunity.
Kinoti, Wycliff M; Constable, Fiona E; Nancarrow, Narelle; Plummer, Kim M; Rodoni, Brendan
2017-01-01
PCR amplicon next generation sequencing (NGS) analysis offers a broadly applicable and targeted approach to detect populations of both high- or low-frequency virus variants in one or more plant samples. In this study, amplicon NGS was used to explore the diversity of the tripartite genome virus, Prunus necrotic ringspot virus (PNRSV) from 53 PNRSV-infected trees using amplicons from conserved gene regions of each of PNRSV RNA1, RNA2 and RNA3. Sequencing of the amplicons from 53 PNRSV-infected trees revealed differing levels of polymorphism across the three different components of the PNRSV genome with a total number of 5040, 2083 and 5486 sequence variants observed for RNA1, RNA2 and RNA3 respectively. The RNA2 had the lowest diversity of sequences compared to RNA1 and RNA3, reflecting the lack of flexibility tolerated by the replicase gene that is encoded by this RNA component. Distinct PNRSV phylo-groups, consisting of closely related clusters of sequence variants, were observed in each of PNRSV RNA1, RNA2 and RNA3. Most plant samples had a single phylo-group for each RNA component. Haplotype network analysis showed that smaller clusters of PNRSV sequence variants were genetically connected to the largest sequence variant cluster within a phylo-group of each RNA component. Some plant samples had sequence variants occurring in multiple PNRSV phylo-groups in at least one of each RNA and these phylo-groups formed distinct clades that represent PNRSV genetic strains. Variants within the same phylo-group of each Prunus plant sample had ≥97% similarity and phylo-groups within a Prunus plant sample and between samples had less ≤97% similarity. Based on the analysis of diversity, a definition of a PNRSV genetic strain was proposed. The proposed definition was applied to determine the number of PNRSV genetic strains in each of the plant samples and the complexity in defining genetic strains in multipartite genome viruses was explored.
Evaluating Reported Candidate Gene Associations with Polycystic Ovary Syndrome
Pau, Cindy; Saxena, Richa; Welt, Corrine Kolka
2013-01-01
Objective To replicate variants in candidate genes associated with PCOS in a population of European PCOS and control subjects. Design Case-control association analysis and meta-analysis. Setting Major academic hospital Patients Women of European ancestry with PCOS (n=525) and controls (n=472), aged 18 to 45 years. Intervention Variants previously associated with PCOS in candidate gene studies were genotyped (n=39). Metabolic, reproductive and anthropomorphic parameters were examined as a function of the candidate variants. All genetic association analyses were adjusted for age, BMI and ancestry and were reported after correction for multiple testing. Main Outcome Measure Association of candidate gene variants with PCOS. Results Three variants, rs3797179 (SRD5A1), rs12473543 (POMC), and rs1501299 (ADIPOQ), were nominally associated with PCOS. However, they did not remain significant after correction for multiple testing and none of the variants replicated in a sufficiently powered meta-analysis. Variants in the FBN3 gene (rs17202517 and rs73503752) were associated with smaller waist circumferences and variant rs727428 in the SHBG gene was associated with lower SHBG levels. Conclusion Previously identified variants in candidate genes do not appear to be associated with PCOS risk. PMID:23375202
De Novo Coding Variants Are Strongly Associated with Tourette Disorder.
Willsey, A Jeremy; Fernandez, Thomas V; Yu, Dongmei; King, Robert A; Dietrich, Andrea; Xing, Jinchuan; Sanders, Stephan J; Mandell, Jeffrey D; Huang, Alden Y; Richer, Petra; Smith, Louw; Dong, Shan; Samocha, Kaitlin E; Neale, Benjamin M; Coppola, Giovanni; Mathews, Carol A; Tischfield, Jay A; Scharf, Jeremiah M; State, Matthew W; Heiman, Gary A
2017-05-03
Whole-exome sequencing (WES) and de novo variant detection have proven a powerful approach to gene discovery in complex neurodevelopmental disorders. We have completed WES of 325 Tourette disorder trios from the Tourette International Collaborative Genetics cohort and a replication sample of 186 trios from the Tourette Syndrome Association International Consortium on Genetics (511 total). We observe strong and consistent evidence for the contribution of de novo likely gene-disrupting (LGD) variants (rate ratio [RR] 2.32, p = 0.002). Additionally, de novo damaging variants (LGD and probably damaging missense) are overrepresented in probands (RR 1.37, p = 0.003). We identify four likely risk genes with multiple de novo damaging variants in unrelated probands: WWC1 (WW and C2 domain containing 1), CELSR3 (Cadherin EGF LAG seven-pass G-type receptor 3), NIPBL (Nipped-B-like), and FN1 (fibronectin 1). Overall, we estimate that de novo damaging variants in approximately 400 genes contribute risk in 12% of clinical cases. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.
Testing cross-phenotype effects of rare variants in longitudinal studies of complex traits.
Rudra, Pratyaydipta; Broadaway, K Alaine; Ware, Erin B; Jhun, Min A; Bielak, Lawrence F; Zhao, Wei; Smith, Jennifer A; Peyser, Patricia A; Kardia, Sharon L R; Epstein, Michael P; Ghosh, Debashis
2018-06-01
Many gene mapping studies of complex traits have identified genes or variants that influence multiple phenotypes. With the advent of next-generation sequencing technology, there has been substantial interest in identifying rare variants in genes that possess cross-phenotype effects. In the presence of such effects, modeling both the phenotypes and rare variants collectively using multivariate models can achieve higher statistical power compared to univariate methods that either model each phenotype separately or perform separate tests for each variant. Several studies collect phenotypic data over time and using such longitudinal data can further increase the power to detect genetic associations. Although rare-variant approaches exist for testing cross-phenotype effects at a single time point, there is no analogous method for performing such analyses using longitudinal outcomes. In order to fill this important gap, we propose an extension of Gene Association with Multiple Traits (GAMuT) test, a method for cross-phenotype analysis of rare variants using a framework based on the distance covariance. The approach allows for both binary and continuous phenotypes and can also adjust for covariates. Our simple adjustment to the GAMuT test allows it to handle longitudinal data and to gain power by exploiting temporal correlation. The approach is computationally efficient and applicable on a genome-wide scale due to the use of a closed-form test whose significance can be evaluated analytically. We use simulated data to demonstrate that our method has favorable power over competing approaches and also apply our approach to exome chip data from the Genetic Epidemiology Network of Arteriopathy. © 2018 WILEY PERIODICALS, INC.
Arnedo, Mireia; Taffé, Patrick; Sahli, Roland; Furrer, Hansjakob; Hirschel, Bernard; Elzi, Luigia; Weber, Rainer; Vernazza, Pietro; Bernasconi, Enos; Darioli, Roger; Bergmann, Sven; Beckmann, Jacques S; Telenti, Amalio; Tarr, Philip E
2007-09-01
HIV-1 infected individuals have an increased cardiovascular risk which is partially mediated by dyslipidemia. Single nucleotide polymorphisms in multiple genes involved in lipid transport and metabolism are presumed to modulate the risk of dyslipidemia in response to antiretroviral therapy. The contribution to dyslipidemia of 20 selected single nucleotide polymorphisms of 13 genes reported in the literature to be associated with plasma lipid levels (ABCA1, ADRB2, APOA5, APOC3, APOE, CETP, LIPC, LIPG, LPL, MDR1, MTP, SCARB1, and TNF) was assessed by longitudinally modeling more than 4400 plasma lipid determinations in 438 antiretroviral therapy-treated participants during a median period of 4.8 years. An exploratory genetic score was tested that takes into account the cumulative contribution of multiple gene variants to plasma lipids. Variants of ABCA1, APOA5, APOC3, APOE, and CETP contributed to plasma triglyceride levels, particularly in the setting of ritonavir-containing antiretroviral therapy. Variants of APOA5 and CETP contributed to high-density lipoprotein-cholesterol levels. Variants of CETP and LIPG contributed to non-high-density lipoprotein-cholesterol levels, a finding not reported previously. Sustained hypertriglyceridemia and low high-density lipoprotein-cholesterol during the study period was significantly associated with the genetic score. Single nucleotide polymorphisms of ABCA1, APOA5, APOC3, APOE, and CETP contribute to plasma triglyceride and high-density lipoprotein-cholesterol levels during antiretroviral therapy exposure. Genetic profiling may contribute to the identification of patients at risk for antiretroviral therapy-related dyslipidemia.
Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.
Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao
2016-11-30
Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.
Lindström, Sara; Yen, Yu-Chun; Spiegelman, Donna; Kraft, Peter
2009-01-01
The possibility of gene-environment interaction can be exploited to identify genetic variants associated with disease using a joint test of genetic main effect and gene-environment interaction. We consider how exposure misclassification and dependence between the true exposure E and the tested genetic variant G affect this joint test in absolute terms and relative to three other tests: the marginal test (G), the standard test for multiplicative gene-environment interaction (GE), and the case-only test for interaction (GE-CO). All tests can have inflated Type I error rate when E and G are correlated in the underlying population. For the GE and G-GE tests this inflation is only noticeable when the gene-environment dependence is unusually strong; the inflation can be large for the GE-CO test even for modest correlation. The joint G-GE test has greater power than the GE test generally, and greater power than the G test when there is no genetic main effect and the measurement error is small to moderate. The joint G-GE test is an attractive test for assessing genetic association when there is limited knowledge about casual mechanisms a priori, even in the presence of misclassification in environmental exposure measurement and correlation between exposure and genetic variants. PMID:19521099
Benefit of Preemptive Pharmacogenetic Information on Clinical Outcome.
Roden, Dan M; Van Driest, Sara L; Mosley, Jonathan D; Wells, Quinn S; Robinson, Jamie R; Denny, Joshua C; Peterson, Josh F
2018-05-01
The development of new knowledge around the genetic determinants of variable drug action has naturally raised the question of how this new knowledge can be used to improve the outcome of drug therapy. Two broad approaches have been taken: a point-of-care approach in which genotyping for specific variant(s) is undertaken at the time of drug prescription, and a preemptive approach in which multiple genetic variants are typed in an individual patient and the information archived for later use when a drug with a "pharmacogenetic story" is prescribed. This review addresses the current state of implementation, the rationale for these approaches, and barriers that must be overcome. Benefits to pharmacogenetic testing are only now being defined and will be discussed. © 2018 American Society for Clinical Pharmacology and Therapeutics.
Clinical and molecular characterization of KCNT1-related severe early-onset epilepsy
Nair, Umesh; Malhotra, Sony; Meyer, Esther; Trump, Natalie; Gazina, Elena V.; Papandreou, Apostolos; Ngoh, Adeline; Ackermann, Sally; Ambegaonkar, Gautam; Appleton, Richard; Desurkar, Archana; Eltze, Christin; Kneen, Rachel; Kumar, Ajith V.; Lascelles, Karine; Montgomery, Tara; Ramesh, Venkateswaran; Samanta, Rajib; Scott, Richard H.; Tan, Jeen; Whitehouse, William; Poduri, Annapurna; Scheffer, Ingrid E.; Chong, W.K. “Kling”; Cross, J. Helen; Topf, Maya; Petrou, Steven
2018-01-01
Objective To characterize the phenotypic spectrum, molecular genetic findings, and functional consequences of pathogenic variants in early-onset KCNT1 epilepsy. Methods We identified a cohort of 31 patients with epilepsy of infancy with migrating focal seizures (EIMFS) and screened for variants in KCNT1 using direct Sanger sequencing, a multiple-gene next-generation sequencing panel, and whole-exome sequencing. Additional patients with non-EIMFS early-onset epilepsy in whom we identified KCNT1 variants on local diagnostic multiple gene panel testing were also included. When possible, we performed homology modeling to predict the putative effects of variants on protein structure and function. We undertook electrophysiologic assessment of mutant KCNT1 channels in a xenopus oocyte model system. Results We identified pathogenic variants in KCNT1 in 12 patients, 4 of which are novel. Most variants occurred de novo. Ten patients had a clinical diagnosis of EIMFS, and the other 2 presented with early-onset severe nocturnal frontal lobe seizures. Three patients had a trial of quinidine with good clinical response in 1 patient. Computational modeling analysis implicates abnormal pore function (F346L) and impaired tetramer formation (F502V) as putative disease mechanisms. All evaluated KCNT1 variants resulted in marked gain of function with significantly increased channel amplitude and variable blockade by quinidine. Conclusions Gain-of-function KCNT1 pathogenic variants cause a spectrum of severe focal epilepsies with onset in early infancy. Currently, genotype-phenotype correlations are unclear, although clinical outcome is poor for the majority of cases. Further elucidation of disease mechanisms may facilitate the development of targeted treatments, much needed for this pharmacoresistant genetic epilepsy. PMID:29196579
Cornelius, Nanna; Frerman, Frank E; Corydon, Thomas J; Palmfeldt, Johan; Bross, Peter; Gregersen, Niels; Olsen, Rikke K J
2012-08-01
Riboflavin-responsive forms of multiple acyl-CoA dehydrogenation deficiency (RR-MADD) have been known for years, but with presumed defects in the formation of the flavin adenine dinucleotide (FAD) co-factor rather than genetic defects of electron transfer flavoprotein (ETF) or electron transfer flavoprotein-ubiquinone oxidoreductase (ETF-QO). It was only recently established that a number of RR-MADD patients carry genetic defects in ETF-QO and that the well-documented clinical efficacy of riboflavin treatment may be based on a chaperone effect that can compensate for inherited folding defects of ETF-QO. In the present study, we investigate the molecular mechanisms and the genotype-phenotype relationships for the riboflavin responsiveness in MADD, using a human HEK-293 cell expression system. We studied the influence of riboflavin and temperature on the steady-state level and the activity of variant ETF-QO proteins identified in patients with RR-MADD, or non- and partially responsive MADD. Our results showed that variant ETF-QO proteins associated with non- and partially responsive MADD caused severe misfolding of ETF-QO variant proteins when cultured in media with supplemented concentrations of riboflavin. In contrast, variant ETF-QO proteins associated with RR-MADD caused milder folding defects when cultured at the same conditions. Decreased thermal stability of the variants showed that FAD does not completely correct the structural defects induced by the variation. This may cause leakage of electrons and increased reactive oxygen species, as reflected by increased amounts of cellular peroxide production in HEK-293 cells expressing the variant ETF-QO proteins. Finally, we found indications of prolonged association of variant ETF-QO protein with the Hsp60 chaperonin in the mitochondrial matrix, supporting indications of folding defects in the variant ETF-QO proteins.
Resolving TYK2 locus genotype-to-phenotype differences in autoimmunity
Dendrou, Calliope A.; Cortes, Adrian; Shipman, Lydia; Evans, Hayley G.; Attfield, Kathrine E.; Jostins, Luke; Barber, Thomas; Kaur, Gurman; Kuttikkatte, Subita Balaram; Leach, Oliver A.; Desel, Christiane; Faergeman, Soren L.; Cheeseman, Jane; Neville, Matt J.; Sawcer, Stephen; Compston, Alastair; Johnson, Adam R.; Everett, Christine; Bell, John I.; Karpe, Fredrik; Ultsch, Mark; Eigenbrot, Charles; McVean, Gil; Fugger, Lars
2017-01-01
Thousands of genetic variants have been identified that contribute to the development of complex diseases, but determining how to fully elucidate their biological consequences for translation into clinical benefit is challenging. Conflicting evidence regarding the functional impact of genetic variants in the tyrosine kinase 2 (TYK2) gene, which is differentially associated with common autoimmune diseases, currently obscures the potential of TYK2 as a therapeutic target. We aimed to resolve this conflict by performing genetic meta-analysis across disorders, subsequent molecular, cellular, in vivo and structural functional follow-up and epidemiological studies. Our data revealed a protective homozygous effect that defined a signaling optimum between autoimmunity and immunodeficiency and identified TYK2 as a potential drug target for multiple autoimmune disorders. PMID:27807284
TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies
van der Sluis, Sophie; Posthuma, Danielle; Dolan, Conor V.
2013-01-01
To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor. PMID:23359524
Jääskeläinen, Tiina; Paananen, Jussi; Lindström, Jaana; Eriksson, Johan G; Tuomilehto, Jaakko; Uusitupa, Matti
2013-11-01
Recent genome-wide association studies have identified multiple loci associated with BMI or the waist:hip ratio (WHR). However, evidence on gene-lifestyle interactions is still scarce, and investigation of the effects of well-documented dietary and other lifestyle data is warranted to assess whether genetic risk can be modified by lifestyle. We assessed whether previously established BMI and WHR genetic variants associate with obesity and weight change in the Finnish Diabetes Prevention Study, and whether the associations are modified by dietary factors or physical activity. Individuals (n 459) completed a 3 d food record and were genotyped for twenty-six BMI- and fourteen WHR-related variants. The effects of the variants individually and in combination were investigated in relation to obesity and to 1- and 3-year weight change by calculating genetic risk scores (GRS). The GRS were separately calculated for BMI and the WHR by summing the increasing alleles weighted by their published effect sizes. At baseline, the GRS were not associated with total intakes of energy, macronutrients or fibre. The mean 1- and 3-year weight changes were not affected by the BMI or WHR GRS. During the 3-year follow-up, a trend for higher BMI by the GRS was detected especially in those who reported a diet low in fibre (P for interaction=0·065). Based on the present findings, it appears unlikely that obesity-predisposing variants substantially modify the effect of lifestyle modification on the success of weight reduction in the long term. In addition, these findings suggest that the association between the BMI-related genetic variants and obesity could be modulated by the diet.
Contribution of Large Region Joint Associations to Complex Traits Genetics
Paré, Guillaume; Asma, Senay; Deng, Wei Q.
2015-01-01
A polygenic model of inheritance, whereby hundreds or thousands of weakly associated variants contribute to a trait’s heritability, has been proposed to underlie the genetic architecture of complex traits. However, relatively few genetic variants have been positively identified so far and they collectively explain only a small fraction of the predicted heritability. We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance. Confirmation of such regional associations can help identify new loci and lead to a better understanding of known ones. To test this hypothesis, we first characterized the ability of commonly used genetic association models to identify large region joint associations. Through theoretical derivation and simulation, we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable association profile. Based on these results, we tested for large region association with height in 3,740 European participants from the Health and Retirement Study (HRS) study. Adjusting for SNPs with known association with height, we demonstrated clustering of weak associations (p = 2x10-4) in regions extending up to 433.0 Kb from known height loci. The contribution of regional associations to phenotypic variance was estimated at 0.172 (95% CI 0.063-0.279; p < 0.001), which compared favorably to 0.129 explained by known height variants. Conversely, we showed that suggestively associated regions are enriched for known height loci. To extend our findings to other traits, we also tested BMI, HDLc and CRP for large region associations, with consistent results for CRP. Our results demonstrate the presence of large region joint associations and suggest these can be used to pinpoint weakly associated SNPs. PMID:25856144
Zhu, Xiaofeng; Feng, Tao; Tayo, Bamidele O; Liang, Jingjing; Young, J Hunter; Franceschini, Nora; Smith, Jennifer A; Yanek, Lisa R; Sun, Yan V; Edwards, Todd L; Chen, Wei; Nalls, Mike; Fox, Ervin; Sale, Michele; Bottinger, Erwin; Rotimi, Charles; Liu, Yongmei; McKnight, Barbara; Liu, Kiang; Arnett, Donna K; Chakravati, Aravinda; Cooper, Richard S; Redline, Susan
2015-01-08
Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Carlson, Christopher S; Matise, Tara C; North, Kari E; Haiman, Christopher A; Fesinmeyer, Megan D; Buyske, Steven; Schumacher, Fredrick R; Peters, Ulrike; Franceschini, Nora; Ritchie, Marylyn D; Duggan, David J; Spencer, Kylee L; Dumitrescu, Logan; Eaton, Charles B; Thomas, Fridtjof; Young, Alicia; Carty, Cara; Heiss, Gerardo; Le Marchand, Loic; Crawford, Dana C; Hindorff, Lucia A; Kooperberg, Charles L
2013-09-01
The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.
Carlson, Christopher S.; Matise, Tara C.; North, Kari E.; Haiman, Christopher A.; Fesinmeyer, Megan D.; Buyske, Steven; Schumacher, Fredrick R.; Peters, Ulrike; Franceschini, Nora; Ritchie, Marylyn D.; Duggan, David J.; Spencer, Kylee L.; Dumitrescu, Logan; Eaton, Charles B.; Thomas, Fridtjof; Young, Alicia; Carty, Cara; Heiss, Gerardo; Le Marchand, Loic; Crawford, Dana C.; Hindorff, Lucia A.; Kooperberg, Charles L.
2013-01-01
The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging. PMID:24068893
SZDB: A Database for Schizophrenia Genetic Research
Wu, Yong; Yao, Yong-Gang
2017-01-01
Abstract Schizophrenia (SZ) is a debilitating brain disorder with a complex genetic architecture. Genetic studies, especially recent genome-wide association studies (GWAS), have identified multiple variants (loci) conferring risk to SZ. However, how to efficiently extract meaningful biological information from bulk genetic findings of SZ remains a major challenge. There is a pressing need to integrate multiple layers of data from various sources, eg, genetic findings from GWAS, copy number variations (CNVs), association and linkage studies, gene expression, protein–protein interaction (PPI), co-expression, expression quantitative trait loci (eQTL), and Encyclopedia of DNA Elements (ENCODE) data, to provide a comprehensive resource to facilitate the translation of genetic findings into SZ molecular diagnosis and mechanism study. Here we developed the SZDB database (http://www.szdb.org/), a comprehensive resource for SZ research. SZ genetic data, gene expression data, network-based data, brain eQTL data, and SNP function annotation information were systematically extracted, curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized SZ genes and enriched pathways. Multiple types of data from various layers of SZ research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in SZ are highly co-expressed in human brain and proteins encoded by the prioritized SZ risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important, SZDB provides convenient online tools for data search and browse, data integration, and customized data analyses. PMID:27451428
Vercellino, Marco; Fenoglio, Chiara; Galimberti, Daniela; Mattioda, Alessandra; Chiavazza, Carlotta; Binello, Eleonora; Pinessi, Lorenzo; Giobbe, Dario; Scarpini, Elio; Cavalla, Paola
2016-07-01
Progranulin (GRN) is a multifunctional protein involved in inflammation and repair, and also a neurotrophic factor critical for neuronal survival. Progranulin is strongly expressed in multiple sclerosis (MS) brains by macrophages and microglia. In this study we evaluated GRN genetic variability in 400 MS patients, in correlation with clinical variables such as disease severity and relapse recovery. We also evaluated serum progranulin levels in the different groups of GRN variants carriers. We found that incomplete recovery after a relapse is correlated with an increased frequency of the rs9897526 A allele (odds ratio (OR) 4.367, p = 0.005). A more severe disease course (Multiple Sclerosis Severity Score > 5) is correlated with an increased frequency of the rs9897526 A allele (OR 1.886, p = 0.002) and of the rs5848 T allele (OR 1.580, p = 0.019). Carriers of the variants associated with a more severe disease course (rs9897526 A, rs5848 T) have significantly lower levels of circulating progranulin (80.5 ± 9.1 ng/mL vs. 165.7 ng/mL, p = 0.01). GRN genetic polymorphisms likely influence disease course and relapse recovery in MS. © The Author(s), 2015.
Fang, Lingzhao; Sahana, Goutam; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter
2017-01-01
Connecting genome-wide association study (GWAS) to biological mechanisms underlying complex traits is a major challenge. Mastitis resistance and milk production are complex traits of economic importance in the dairy sector and are associated with intra-mammary infection (IMI). Here, we integrated IMI-relevant RNA-Seq data from Holstein cattle and sequence-based GWAS data from three dairy cattle breeds (i.e., Holstein, Nordic red cattle, and Jersey) to explore the genetic basis of mastitis resistance and milk production using post-GWAS analyses and a genomic feature linear mixed model. At 24 h post-IMI, genes responsive to IMI in the mammary gland were preferentially enriched for genetic variants associated with mastitis resistance rather than milk production. Response genes in the liver were mainly enriched for variants associated with mastitis resistance at an early time point (3 h) post-IMI, whereas responsive genes at later stages were enriched for associated variants with milk production. The up- and down-regulated genes were enriched for associated variants with mastitis resistance and milk production, respectively. The patterns were consistent across breeds, indicating that different breeds shared similarities in the genetic basis of these traits. Our approaches provide a framework for integrating multiple layers of data to understand the genetic architecture underlying complex traits. PMID:28358110
Pharmacogenomic prediction of anthracycline-induced cardiotoxicity in children.
Visscher, Henk; Ross, Colin J D; Rassekh, S Rod; Barhdadi, Amina; Dubé, Marie-Pierre; Al-Saloos, Hesham; Sandor, George S; Caron, Huib N; van Dalen, Elvira C; Kremer, Leontien C; van der Pal, Helena J; Brown, Andrew M K; Rogers, Paul C; Phillips, Michael S; Rieder, Michael J; Carleton, Bruce C; Hayden, Michael R
2012-05-01
Anthracycline-induced cardiotoxicity (ACT) is a serious adverse drug reaction limiting anthracycline use and causing substantial morbidity and mortality. Our aim was to identify genetic variants associated with ACT in patients treated for childhood cancer. We carried out a study of 2,977 single-nucleotide polymorphisms (SNPs) in 220 key drug biotransformation genes in a discovery cohort of 156 anthracycline-treated children from British Columbia, with replication in a second cohort of 188 children from across Canada and further replication of the top SNP in a third cohort of 96 patients from Amsterdam, the Netherlands. We identified a highly significant association of a synonymous coding variant rs7853758 (L461L) within the SLC28A3 gene with ACT (odds ratio, 0.35; P = 1.8 × 10(-5) for all cohorts combined). Additional associations (P < .01) with risk and protective variants in other genes including SLC28A1 and several adenosine triphosphate-binding cassette transporters (ABCB1, ABCB4, and ABCC1) were present. We further explored combining multiple variants into a single-prediction model together with clinical risk factors and classification of patients into three risk groups. In the high-risk group, 75% of patients were accurately predicted to develop ACT, with 36% developing this within the first year alone, whereas in the low-risk group, 96% of patients were accurately predicted not to develop ACT. We have identified multiple genetic variants in SLC28A3 and other genes associated with ACT. Combined with clinical risk factors, genetic risk profiling might be used to identify high-risk patients who can then be provided with safer treatment options.
Purinergic receptors P2RX4 and P2RX7 in familial multiple sclerosis
Sadovnick, A Dessa; Gu, Ben J; Traboulsee, Anthony L; Bernales, Cecily Q; Encarnacion, Mary; Yee, Irene M; Criscuoli, Maria G; Huang, Xin; Ou, Amber; Milligan, Carol J; Petrou, Steven; Wiley, James S; Vilariño-Güell, Carles
2017-01-01
Genetic variants in the purinergic receptors P2RX4 and P2RX7 have been shown to affect susceptibility to multiple sclerosis (MS). In this study we set out to evaluate whether rare coding variants of major effect could also be identified in these purinergic receptors. Sequencing analysis of P2RX4 and P2RX7 in 193 MS patients and 100 controls led to the identification of a rare three variant haplotype (P2RX7 rs140915863:C>T (p.T205M), P2RX7 rs201921967:A>G (p.N361S) and P2RX4 rs765866317:G>A (p.G135S)) segregating with disease in a multi-incident family with six family members diagnosed with MS (LOD=3.07). Functional analysis of this haplotype in HEK293 cells revealed impaired P2X7 surface expression (p<0.01), resulting in over 95% inhibition of ATP-induced pore function (p<0.001) and a marked reduction in phagocytic ability (p<0.05). In addition, transfected cells showed 40% increased peak ATP-induced inward current (p<0.01), and a greater Ca2+ response to the P2X4 135S variant compared to wild type (p<0.0001). Our study nominates rare genetic variants in P2RX4 and P2RX7 as major genetic contributors to disease, further supporting a role for these purinergic receptors in MS and suggesting the disruption of transmembrane cation channels leading to impairment of phagocytosis as the pathological mechanisms of disease. PMID:28326637
Johansen, Peter; Andersen, Jeppe Dyrberg; Madsen, Linnea Nørgård; Ullum, Henrik; Glud, Martin; Børsting, Claus; Gniadecki, Robert; Morling, Niels
2016-01-01
To investigate whether pigmentation genes involved in the melanogenic pathway (melanogenesis) contributed to melanoma predisposition, we compared pigmentary genetics with quantitative skin pigmentation measurements, the number of atypical nevi, the total nevus count, and the familial atypical multiple mole and melanoma (FAMMM) syndrome. We typed 32 pigmentary SNP markers and sequenced MC1R in 246 healthy individuals and 116 individuals attending periodic control for malignant melanoma development, 50 of which were diagnosed with FAMMM. It was observed that individuals with any two grouped MC1R variants (missense, NM_002386:c. 456C > A (p.TYR152*), or NM_002386:c.83_84insA (p.Asn29Glnfs*14) had significantly (p<0.001) lighter skin pigmentation of the upper-inner arm than those with none or one MC1R variant. We did not observe any significant association of the MC1R variants with constitutive pigmentation measured on the buttock area. We hypothesize that the effect of MC1R variants on arm pigmentation is primarily reflecting the inability to tan when subjected to UVR. A gender specific effect on skin pigmentation was also observed, and it was found that the skin pigmentation of females on average were darker than that of males (p<0.01). We conclude that MC1R variants are associated with quantitative skin colour in a lightly pigmented Danish population. We did not observe any association between any pigmentary marker and the FAMMM syndrome. We suggest that the genetics of FAMMM is not related to the genetics of the pigmentary pathway. PMID:26938746
Candidate genetic modifiers for breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers
Peterlongo, Paolo; Chang-Claude, Jenny; Moysich, Kirsten B.; Rudolph, Anja; Schmutzler, Rita K.; Simard, Jacques; Soucy, Penny; Eeles, Rosalind A.; Easton, Douglas F.; Hamann, Ute; Wilkening, Stefan; Chen, Bowang; Rookus, Matti A.; Schmidt, Marjanka K; van der Baan, Frederieke H.; Spurdle, Amanda B.; Walker, Logan C.; Lose, Felicity; Maia, Ana-Teresa; Montagna, Marco; Matricardi, Laura; Lubinski, Jan; Jakubowska, Anna; Gómez Garcia, Encarna B.; Olopade, Olufunmilayo I.; Nussbaum, Robert L.; Nathanson, Katherine L.; Domchek, Susan M.; Rebbeck, Timothy R.; Arun, Banu K.; Karlan, Beth Y.; Orsulic, Sandra; Lester, Jenny; Chung, Wendy K.; Miron, Alex; Southey, Melissa C.; Goldgar, David E.; Buys, Saundra S.; Janavicius, Ramunas; Dorfling, Cecilia M.; van Rensburg, Elizabeth J.; Ding, Yuan Chun; Neuhausen, Susan L.; Hansen, Thomas V. O.; Gerdes, Anne-Marie; Ejlertsen, Bent; Jønson, Lars; Osorio, Ana; Martínez-Bouzas, Cristina; Benitez, Javier; Conway, Edye E.; Blazer, Kathleen R.; Weitzel, Jeffrey N.; Manoukian, Siranoush; Peissel, Bernard; Zaffaroni, Daniela; Scuvera, Giulietta; Barile, Monica; Ficarazzi, Filomena; Mariette, Frederique; Fortuzzi, Stefano; Viel, Alessandra; Giannini, Giuseppe; Papi, Laura; Martayan, Aline; Tibiletti, Maria Grazia; Radice, Paolo; Vratimos, Athanassios; Fostira, Florentia; Garber, Judy E.; Donaldson, Alan; Brewer, Carole; Foo, Claire; Evans, D. Gareth R.; Frost, Debra; Eccles, Diana; Brady, Angela; Cook, Jackie; Tischkowitz, Marc; Adlard, Julian; Barwell, Julian; Walker, Lisa; Izatt, Louise; Side, Lucy E.; Kennedy, M. John; Rogers, Mark T.; Porteous, Mary E.; Morrison, Patrick J.; Platte, Radka; Davidson, Rosemarie; Hodgson, Shirley V.; Ellis, Steve; Cole, Trevor; Godwin, Andrew K.; Claes, Kathleen; Van Maerken, Tom; Meindl, Alfons; Gehrig, Andrea; Sutter, Christian; Engel, Christoph; Niederacher, Dieter; Steinemann, Doris; Plendl, Hansjoerg; Kast, Karin; Rhiem, Kerstin; Ditsch, Nina; Arnold, Norbert; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Wang-Gohrke, Shan; Bressac-de Paillerets, Brigitte; Buecher, Bruno; Delnatte, Capucine; Houdayer, Claude; Stoppa-Lyonnet, Dominique; Damiola, Francesca; Coupier, Isabelle; Barjhoux, Laure; Venat-Bouvet, Laurence; Golmard, Lisa; Boutry-Kryza, Nadia; Sinilnikova, Olga M.; Caron, Olivier; Pujol, Pascal; Mazoyer, Sylvie; Belotti, Muriel; Piedmonte, Marion; Friedlander, Michael L.; Rodriguez, Gustavo C.; Copeland, Larry J; de la Hoya, Miguel; Segura, Pedro Perez; Nevanlinna, Heli; Aittomäki, Kristiina; van Os, Theo A.M.; Meijers-Heijboer, Hanne E.J.; van der Hout, Annemarie H.; Vreeswijk, Maaike P.G.; Hoogerbrugge, Nicoline; Ausems, Margreet G.E.M.; van Doorn, Helena C.; Collée, J. Margriet; Olah, Edith; Diez, Orland; Blanco, Ignacio; Lazaro, Conxi; Brunet, Joan; Feliubadalo, Lidia; Cybulski, Cezary; Gronwald, Jacek; Durda, Katarzyna; Jaworska-Bieniek, Katarzyna; Sukiennicki, Grzegorz; Arason, Adalgeir; Chiquette, Jocelyne; Teixeira, Manuel R.; Olswold, Curtis; Couch, Fergus J.; Lindor, Noralane M.; Wang, Xianshu; Szabo, Csilla I.; Offit, Kenneth; Corines, Marina; Jacobs, Lauren; Robson, Mark E.; Zhang, Liying; Joseph, Vijai; Berger, Andreas; Singer, Christian F.; Rappaport, Christine; Kaulich, Daphne Geschwantler; Pfeiler, Georg; Tea, Muy-Kheng M.; Phelan, Catherine M.; Greene, Mark H.; Mai, Phuong L.; Rennert, Gad; Mulligan, Anna Marie; Glendon, Gord; Tchatchou, Sandrine; Andrulis, Irene L.; Toland, Amanda Ewart; Bojesen, Anders; Pedersen, Inge Sokilde; Thomassen, Mads; Jensen, Uffe Birk; Laitman, Yael; Rantala, Johanna; von Wachenfeldt, Anna; Ehrencrona, Hans; Askmalm, Marie Stenmark; Borg, Åke; Kuchenbaecker, Karoline B.; McGuffog, Lesley; Barrowdale, Daniel; Healey, Sue; Lee, Andrew; Pharoah, Paul D.P.; Chenevix-Trench, Georgia; Antoniou, Antonis C.; Friedman, Eitan
2014-01-01
Background BRCA1 and BRCA2 mutation carriers are at substantially increased risk for developing breast and ovarian cancer. The incomplete penetrance coupled with the variable age at diagnosis in carriers of the same mutation suggests the existence of genetic and non-genetic modifying factors. In this study we evaluated the putative role of variants in many candidate modifier genes. Methods Genotyping data from 15,252 BRCA1 and 8,211 BRCA2 mutation carriers, for known variants (n=3,248) located within or around 445 candidate genes, were available through the iCOGS custom-designed array. Breast and ovarian cancer association analysis was performed within a retrospective cohort approach. Results The observed p-values of association ranged between 0.005-1.000. None of the variants was significantly associated with breast or ovarian cancer risk in either BRCA1 or BRCA2 mutation carriers, after multiple testing adjustments. Conclusion There is little evidence that any of the evaluated candidate variants act as modifiers of breast and/or ovarian cancer risk in BRCA1 or BRCA2 mutation carriers. Impact Genome-wide association studies have been more successful at identifying genetic modifiers of BRCA1/2 penetrance than candidate gene studies. PMID:25336561
Dahlin, Anna M; Hollegaard, Mads V; Wibom, Carl; Andersson, Ulrika; Hougaard, David M; Deltour, Isabelle; Hjalmars, Ulf; Melin, Beatrice
2015-10-01
Recent studies have described a number of genes that are frequently altered in medulloblastoma tumors and that have putative key roles in the development of the disease. We hypothesized that common germline genetic variations in these genes may be associated with medulloblastoma development. Based on recent publications, we selected 10 genes that were frequently altered in medulloblastoma: CCND2, CTNNB1, DDX3X, GLI2, SMARCA4, MYC, MYCN, PTCH1, TP53, and MLL2 (now renamed as KMT2D). Common genetic variants (single nucleotide polymorphisms) annotating these genes (n = 221) were genotyped in germline DNA (neonatal dried blood spot samples) from 243 childhood medulloblastoma cases and 247 control subjects from Sweden and Denmark. Eight genetic variants annotating three genes in the sonic hedgehog signaling pathway; CCND2, PTCH1, and GLI2, were found to be associated with the risk of medulloblastoma (P(combined) < 0.05). The findings were however not statistically significant following correction for multiple testing by the very stringent Bonferroni method. The results do not support our hypothesis that common germline genetic variants in the ten studied genes are associated with the risk of developing medulloblastoma.
Novel PLS3 variants in X-linked osteoporosis: Exploring bone material properties.
Balasubramanian, Meena; Fratzl-Zelman, Nadja; O'Sullivan, Rory; Bull, Mary; Fa Peel, Nicola; Pollitt, Rebecca C; Jones, Rebecca; Milne, Elizabeth; Smith, Kath; Roschger, Paul; Klaushofer, Klaus; Bishop, Nicholas J
2018-05-07
Idiopathic Juvenile Osteoporosis (IJO) refers to significantly lower than expected bone mass manifesting in childhood with no identifiable aetiology. IJO classically presents in early pubertal period with multiple fractures including metaphyseal and vertebral crush fractures, and low bone-mass. Here we describe two patients and provide information on their clinical phenotype, genotype and bone material analysis in one of the patients. Patient 1: 40-year old adult male diagnosed with IJO in childhood who re-presented with a hip fracture as an adult. Genetic analysis identified a pathogenic PLS3 hemizygous variant, c.1765del in exon 16. Patient 2: 15-year old boy with multiple vertebral fractures and bone biopsy findings suggestive of IJO who also has a diagnosis of autism spectrum disorder. Genetic analysis identified a maternally inherited PLS3 pathogenic c.1295T>A variant in exon 12. Analyses of the transiliac bone sample revealed severe reduction of trabecular volume and bone turnover indices and elevated bone matrix mineralisation. We propose that genetic testing for PLS3 should be undertaken in patients presenting with a current or previous history of IJO as this has implications for genetic counselling and cascade screening. The extensive evaluation of the transiliac biopsy sample of Patient 2 revealed a novel bone phenotype. This report includes a review of IJO and genetic causes of osteoporosis, and suggests that existing cases of IJO should be screened for PLS3. Through analysis of bone material properties in Patient 2, we can conclude that PLS3 does have a role in bone mineralisation. © 2018 Wiley Periodicals, Inc.
Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval.
Lin, Honghuang; van Setten, Jessica; Smith, Albert V; Bihlmeyer, Nathan A; Warren, Helen R; Brody, Jennifer A; Radmanesh, Farid; Hall, Leanne; Grarup, Niels; Müller-Nurasyid, Martina; Boutin, Thibaud; Verweij, Niek; Lin, Henry J; Li-Gao, Ruifang; van den Berg, Marten E; Marten, Jonathan; Weiss, Stefan; Prins, Bram P; Haessler, Jeffrey; Lyytikäinen, Leo-Pekka; Mei, Hao; Harris, Tamara B; Launer, Lenore J; Li, Man; Alonso, Alvaro; Soliman, Elsayed Z; Connell, John M; Huang, Paul L; Weng, Lu-Chen; Jameson, Heather S; Hucker, William; Hanley, Alan; Tucker, Nathan R; Chen, Yii-Der Ida; Bis, Joshua C; Rice, Kenneth M; Sitlani, Colleen M; Kors, Jan A; Xie, Zhijun; Wen, Chengping; Magnani, Jared W; Nelson, Christopher P; Kanters, Jørgen K; Sinner, Moritz F; Strauch, Konstantin; Peters, Annette; Waldenberger, Melanie; Meitinger, Thomas; Bork-Jensen, Jette; Pedersen, Oluf; Linneberg, Allan; Rudan, Igor; de Boer, Rudolf A; van der Meer, Peter; Yao, Jie; Guo, Xiuqing; Taylor, Kent D; Sotoodehnia, Nona; Rotter, Jerome I; Mook-Kanamori, Dennis O; Trompet, Stella; Rivadeneira, Fernando; Uitterlinden, André; Eijgelsheim, Mark; Padmanabhan, Sandosh; Smith, Blair H; Völzke, Henry; Felix, Stephan B; Homuth, Georg; Völker, Uwe; Mangino, Massimo; Spector, Timothy D; Bots, Michiel L; Perez, Marco; Kähönen, Mika; Raitakari, Olli T; Gudnason, Vilmundur; Arking, Dan E; Munroe, Patricia B; Psaty, Bruce M; van Duijn, Cornelia M; Benjamin, Emelia J; Rosand, Jonathan; Samani, Nilesh J; Hansen, Torben; Kääb, Stefan; Polasek, Ozren; van der Harst, Pim; Heckbert, Susan R; Jukema, J Wouter; Stricker, Bruno H; Hayward, Caroline; Dörr, Marcus; Jamshidi, Yalda; Asselbergs, Folkert W; Kooperberg, Charles; Lehtimäki, Terho; Wilson, James G; Ellinor, Patrick T; Lubitz, Steven A; Isaacs, Aaron
2018-05-01
Electrical conduction from the cardiac sinoatrial node to the ventricles is critical for normal heart function. Genome-wide association studies have identified more than a dozen common genetic loci that are associated with PR interval. However, it is unclear whether rare and low-frequency variants also contribute to PR interval heritability. We performed large-scale meta-analyses of the PR interval that included 83 367 participants of European ancestry and 9436 of African ancestry. We examined both common and rare variants associated with the PR interval. We identified 31 genetic loci that were significantly associated with PR interval after Bonferroni correction ( P <1.2×10 -6 ), including 11 novel loci that have not been reported previously. Many of these loci are involved in heart morphogenesis. In gene-based analysis, we found that multiple rare variants at MYH6 ( P =5.9×10 -11 ) and SCN5A ( P =1.1×10 -7 ) were associated with PR interval. SCN5A locus also was implicated in the common variant analysis, whereas MYH6 was a novel locus. We identified common variants at 11 novel loci and rare variants within 2 gene regions that were significantly associated with PR interval. Our findings provide novel insights to the current understanding of atrioventricular conduction, which is critical for cardiac activity and an important determinant of health. © 2018 American Heart Association, Inc.
Radwan, Zaheda H.; Wang, Xingbin; Waqar, Fahad; Pirim, Dilek; Niemsiri, Vipavee; Hokanson, John E.; Hamman, Richard F.; Bunker, Clareann H.; Barmada, M. Michael; Demirci, F. Yesim; Kamboh, M. Ilyas
2014-01-01
Although common APOE genetic variation has a major influence on plasma LDL-cholesterol, its role in affecting HDL-cholesterol and triglycerides is not well established. Recent genome-wide association studies suggest that APOE also affects plasma variation in HDL-cholesterol and triglycerides. It is thus important to resequence the APOE gene to identify both common and uncommon variants that affect plasma lipid profile. Here, we have sequenced the APOE gene in 190 subjects with extreme HDL-cholesterol levels selected from two well-defined epidemiological samples of U.S. non-Hispanic Whites (NHWs) and African Blacks followed by genotyping of identified variants in the entire datasets (623 NHWs, 788 African Blacks) and association analyses with major lipid traits. We identified a total of 40 sequence variants, of which 10 are novel. A total of 32 variants, including common tagSNPs (≥5% frequency) and all uncommon variants (<5% frequency) were successfully genotyped and considered for genotype-phenotype associations. Other than the established associations of APOE*2 and APOE*4 with LDL-cholesterol, we have identified additional independent associations with LDL-cholesterol. We have also identified multiple associations of uncommon and common APOE variants with HDL-cholesterol and triglycerides. Our comprehensive sequencing and genotype-phenotype analyses indicate that APOE genetic variation impacts HDL-cholesterol and triglycerides in addition to affecting LDL-cholesterol. PMID:25502880
Strauss, David G; Vicente, Jose; Johannesen, Lars; Blinova, Ksenia; Mason, Jay W; Weeke, Peter; Behr, Elijah R; Roden, Dan M; Woosley, Ray; Kosova, Gulum; Rosenberg, Michael A; Newton-Cheh, Christopher
2017-04-04
Drug-induced QT interval prolongation, a risk factor for life-threatening ventricular arrhythmias, is a potential side effect of many marketed and withdrawn medications. The contribution of common genetic variants previously associated with baseline QT interval to drug-induced QT prolongation and arrhythmias is not known. We tested the hypothesis that a weighted combination of common genetic variants contributing to QT interval at baseline, identified through genome-wide association studies, can predict individual response to multiple QT-prolonging drugs. Genetic analysis of 22 subjects was performed in a secondary analysis of a randomized, double-blind, placebo-controlled, crossover trial of 3 QT-prolonging drugs with 15 time-matched QT and plasma drug concentration measurements. Subjects received single doses of dofetilide, quinidine, ranolazine, and placebo. The outcome was the correlation between a genetic QT score comprising 61 common genetic variants and the slope of an individual subject's drug-induced increase in heart rate-corrected QT (QTc) versus drug concentration. The genetic QT score was correlated with drug-induced QTc prolongation. Among white subjects, genetic QT score explained 30% of the variability in response to dofetilide ( r =0.55; 95% confidence interval, 0.09-0.81; P =0.02), 23% in response to quinidine ( r =0.48; 95% confidence interval, -0.03 to 0.79; P =0.06), and 27% in response to ranolazine ( r =0.52; 95% confidence interval, 0.05-0.80; P =0.03). Furthermore, the genetic QT score was a significant predictor of drug-induced torsade de pointes in an independent sample of 216 cases compared with 771 controls ( r 2 =12%, P =1×10 -7 ). We demonstrate that a genetic QT score comprising 61 common genetic variants explains a significant proportion of the variability in drug-induced QT prolongation and is a significant predictor of drug-induced torsade de pointes. These findings highlight an opportunity for recent genetic discoveries to improve individualized risk-benefit assessment for pharmacological therapies. Replication of these findings in larger samples is needed to more precisely estimate variance explained and to establish the individual variants that drive these effects. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01873950. © 2017 American Heart Association, Inc.
Zhao, Zhiguo; Wen, Wanqing; Michailidou, Kyriaki; Bolla, Manjeet K; Wang, Qin; Zhang, Ben; Long, Jirong; Shu, Xiao-Ou; Schmidt, Marjanka K; Milne, Roger L; García-Closas, Montserrat; Chang-Claude, Jenny; Lindstrom, Sara; Bojesen, Stig E; Ahsan, Habibul; Aittomäki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Blomqvist, Carl; Bogdanova, Natalia V; Børresen-Dale, Anne-Lise; Brand, Judith; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Cai, Qiuyin; Casey, Graham; Chenevix-Trench, Georgia; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Dörk, Thilo; Dumont, Martine; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gammon, Marilie; Giles, Graham G; Guénel, Pascal; Haiman, Christopher A; Hamann, Ute; Harrington, Patricia; Hartman, Mikael; Hooning, Maartje J; Hopper, John L; Jakubowska, Anna; Jasmine, Farzana; John, Esther M; Johnson, Nichola; Kabisch, Maria; Khan, Sofia; Kibriya, Muhammad; Knight, Julia A; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Le Marchand, Loic; Lee, Eunjung; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Luben, Robert; Lubinski, Jan; Malone, Kathleen E; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Miao, Hui; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Olson, Janet E; Perkins, Barbara; Peterlongo, Paolo; Phillips, Kelly-Anne; Pylkäs, Katri; Rudolph, Anja; Santella, Regina; Sawyer, Elinor J; Schmutzler, Rita K; Schoemaker, Minouk; Shah, Mitul; Shrubsole, Martha; Southey, Melissa C; Swerdlow, Anthony J; Toland, Amanda E; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Ursin, Giske; Van Der Luijt, Rob B; Verhoef, Senno; Wang-Gohrke, Shan; Whittemore, Alice S; Winqvist, Robert; Pilar Zamora, M; Zhao, Hui; Dunning, Alison M; Simard, Jacques; Hall, Per; Kraft, Peter; Pharoah, Paul; Hunter, David; Easton, Douglas F; Zheng, Wei
2016-05-01
Type 2 diabetes (T2D) has been reported to be associated with an elevated risk of breast cancer. It is unclear, however, whether this association is due to shared genetic factors. We constructed a genetic risk score (GRS) using risk variants from 33 known independent T2D susceptibility loci and evaluated its relation to breast cancer risk using the data from two consortia, including 62,328 breast cancer patients and 83,817 controls of European ancestry. Unconditional logistic regression models were used to derive adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) to measure the association of breast cancer risk with T2D GRS or T2D-associated genetic risk variants. Meta-analyses were conducted to obtain summary ORs across all studies. The T2D GRS was not found to be associated with breast cancer risk, overall, by menopausal status, or for estrogen receptor positive or negative breast cancer. Three T2D associated risk variants were individually associated with breast cancer risk after adjustment for multiple comparisons using the Bonferroni method (at p < 0.001), rs9939609 (FTO) (OR 0.94, 95 % CI = 0.92-0.95, p = 4.13E-13), rs7903146 (TCF7L2) (OR 1.04, 95 % CI = 1.02-1.06, p = 1.26E-05), and rs8042680 (PRC1) (OR 0.97, 95 % CI = 0.95-0.99, p = 8.05E-04). We have shown that several genetic risk variants were associated with the risk of both T2D and breast cancer. However, overall genetic susceptibility to T2D may not be related to breast cancer risk.
Zhao, Zhiguo; Wen, Wanqing; Michailidou, Kyriaki; Bolla, Manjeet K.; Wang, Qin; Zhang, Ben; Long, Jirong; Shu, Xiao-Ou; Schmidt, Marjanka K.; Milne, Roger L.; García-Closas, Montserrat; Chang-Claude, Jenny; Lindstrom, Sara; Bojesen, Stig E.; Ahsan, Habibul; Aittomäki, Kristiina; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Blomqvist, Carl; Bogdanova, Natalia V.; Børresen-Dale, Anne-Lise; Brand, Judith; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Cai, Qiuyin; Casey, Graham; Chenevix-Trench, Georgia; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Dörk, Thilo; Dumont, Martine; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gammon, Marilie; Giles, Graham G.; Guénel, Pascal; Haiman, Christopher A.; Hamann, Ute; Harrington, Patricia; Hartman, Mikael; Hooning, Maartje J.; Hopper, John L.; Jakubowska, Anna; Jasmine, Farzana; John, Esther M.; Johnson, Nichola; Kabisch, Maria; Khan, Sofia; Kibriya, Muhammad; Knight, Julia A.; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Le Marchand, Loic; Lee, Eunjung; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Luben, Robert; Lubinski, Jan; Malone, Kathleen E.; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Miao, Hui; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Olson, Janet E.; Perkins, Barbara; Peterlongo, Paolo; Phillips, Kelly-Anne; Pylkäs, Katri; Rudolph, Anja; Santella, Regina; Sawyer, Elinor J.; Schmutzler, Rita K.; Schoemaker, Minouk; Shah, Mitul; Shrubsole, Martha; Southey, Melissa C.; Swerdlow, Anthony J; Toland, Amanda E.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Ursin, Giske; Van Der Luijt, Rob B.; Verhoef, Senno; Wang-Gohrke, Shan; Whittemore, Alice S.; Winqvist, Robert; Zamora, M. Pilar; Zhao, Hui; Dunning, Alison M.; Simard, Jacques; Hall, Per; Kraft, Peter; Pharoah, Paul; Hunter, David; Easton, Douglas F.; Zheng, Wei
2016-01-01
Purpose Type 2 diabetes (T2D) has been reported to be associated with an elevated risk of breast cancer. It is unclear, however, whether this association is due to shared genetic factors. Methods We constructed a genetic risk score (GRS) using risk variants from 33 known independent T2D susceptibility loci and evaluated its relation to breast cancer risk using the data from two consortia, including 62,328 breast cancer patients and 83,817 controls of European ancestry. Unconditional logistic regression models were used to derive adjusted odds ratios (OR) and 95% confidence intervals (CI) to measure the association of breast cancer risk with T2D GRS or T2D-associated genetic risk variants. Meta-analyses were conducted to obtain summary ORs across all studies. Results The T2D GRS was not found to be associated with breast cancer risk, overall, by menopausal status, or for estrogen receptor positive or negative breast cancer. Three T2D associated risk variants were individually associated with breast cancer risk after adjustment for multiple comparisons using the Bonferroni method (at P < 0.001), rs9939609 (FTO) (OR = 0.94, 95% CI = 0.92 – 0.95, P = 4.13E-13), rs7903146 (TCF7L2) (OR = 1.04, 95% CI = 1.02 – 1.06, P = 1.26E-05), and rs8042680 (PRC1) (OR = 0.97, 95% CI = 0.95 – 0.99, P = 8.05E-04). Conclusions We have shown that several genetic risk variants were associated with the risk of both T2D and breast cancer. However, overall genetic susceptibility to T2D may not be related to breast cancer risk. PMID:27053251
Palmer, Nicholette D; Musani, Solomon K; Yerges-Armstrong, Laura M; Feitosa, Mary F; Bielak, Lawrence F; Hernaez, Ruben; Kahali, Bratati; Carr, J Jeffrey; Harris, Tamara B; Jhun, Min A; Kardia, Sharon LR; Langefeld, Carl D; Mosley, Thomas H; Norris, Jill M; Smith, Albert V; Taylor, Herman A; Wagenknecht, Lynne E; Liu, Jiankang; Borecki, Ingrid B; Peyser, Patricia A; Speliotes, Elizabeth K
2013-01-01
Nonalcoholic Fatty Liver Disease (NAFLD) is an obesity-related condition affecting over 50% of individuals in some populations and is expected to become the number one cause of liver disease worldwide by 2020. Common, robustly associated genetic variants in/near five genes were identified for hepatic steatosis, a quantifiable component of NAFLD, in European-ancestry individuals. Here we tested whether these variants were associated with hepatic steatosis in African and/or Hispanic Americans and fine-mapped the observed association signals. We measured hepatic steatosis using computed tomography in five African-American (n=3124) and one Hispanic-American (n=849) cohorts. All analyses controlled for variation in age, age2, gender, alcoholic drinks, and population substructure. Heritability of hepatic steatosis was estimated in three cohorts. Variants in/near PNPLA3, NCAN, LYPLAL1, GCKR, and PPP1R3B were tested for association with hepatic steatosis using a regression framework in each cohort and meta-analyzed. Fine-mapping across African-American cohorts was conducted using meta-analysis. African- and Hispanic-American cohorts were 33.9/37.5% male, with average age of 58.6/42.6 years and body mass index of 31.8/28.9kg/m2, respectively. Hepatic steatosis was 0.20–0.34 heritable in African-and Hispanic-American families (p<0.02 in each cohort). Variants in or near PNPLA3, NCAN, GCKR, PPP1R3B in African Americans and PNPLA3 and PPP1R3B in Hispanic Americans were significantly associated with hepatic steatosis; however, allele frequency and effect size varied across ancestries. Fine-mapping in African Americans highlighted missense variants at PNPLA3 and GCKR and redefined the association region at LYPLAL1. Conclusions We show for the first time that multiple genetic variants are associated with hepatic steatosis across ancestries and explain a substantial proportion of the genetic predisposition in African and Hispanic Americans. Missense variants in PNPLA3 and GCKR are likely functional across multiple ancestries. PMID:23564467
Palmer, Nicholette D; Musani, Solomon K; Yerges-Armstrong, Laura M; Feitosa, Mary F; Bielak, Lawrence F; Hernaez, Ruben; Kahali, Bratati; Carr, J Jeffrey; Harris, Tamara B; Jhun, Min A; Kardia, Sharon L R; Langefeld, Carl D; Mosley, Thomas H; Norris, Jill M; Smith, Albert V; Taylor, Herman A; Wagenknecht, Lynne E; Liu, Jiankang; Borecki, Ingrid B; Peyser, Patricia A; Speliotes, Elizabeth K
2013-09-01
Nonalcoholic fatty liver disease (NAFLD) is an obesity-related condition affecting over 50% of individuals in some populations and is expected to become the number one cause of liver disease worldwide by 2020. Common, robustly associated genetic variants in/near five genes were identified for hepatic steatosis, a quantifiable component of NAFLD, in European ancestry individuals. Here we tested whether these variants were associated with hepatic steatosis in African- and/or Hispanic-Americans and fine-mapped the observed association signals. We measured hepatic steatosis using computed tomography in five African American (n = 3,124) and one Hispanic American (n = 849) cohorts. All analyses controlled for variation in age, age(2) , gender, alcoholic drinks, and population substructure. Heritability of hepatic steatosis was estimated in three cohorts. Variants in/near PNPLA3, NCAN, LYPLAL1, GCKR, and PPP1R3B were tested for association with hepatic steatosis using a regression framework in each cohort and meta-analyzed. Fine-mapping across African American cohorts was conducted using meta-analysis. African- and Hispanic-American cohorts were 33.9/37.5% male, with average age of 58.6/42.6 years and body mass index of 31.8/28.9 kg/m(2) , respectively. Hepatic steatosis was 0.20-0.34 heritable in African- and Hispanic-American families (P < 0.02 in each cohort). Variants in or near PNPLA3, NCAN, GCKR, PPP1R3B in African Americans and PNPLA3 and PPP1R3B in Hispanic Americans were significantly associated with hepatic steatosis; however, allele frequency and effect size varied across ancestries. Fine-mapping in African Americans highlighted missense variants at PNPLA3 and GCKR and redefined the association region at LYPLAL1. Multiple genetic variants are associated with hepatic steatosis across ancestries. This explains a substantial proportion of the genetic predisposition in African- and Hispanic-Americans. Missense variants in PNPLA3 and GCKR are likely functional across multiple ancestries. © 2013 by the American Association for the Study of Liver Diseases.
Nedeljkovic, Ivana; Terzikhan, Natalie; Vonk, Judith M; van der Plaat, Diana A; Lahousse, Lies; van Diemen, Cleo C; Hobbs, Brian D; Qiao, Dandi; Cho, Michael H; Brusselle, Guy G; Postma, Dirkje S; Boezen, H M; van Duijn, Cornelia M; Amin, Najaf
2018-01-01
Chronic obstructive pulmonary disease (COPD) is a complex and heritable disease, associated with multiple genetic variants. Specific familial types of COPD may be explained by rare variants, which have not been widely studied. We aimed to discover rare genetic variants underlying COPD through a genome-wide linkage scan. Affected-only analysis was performed using the 6K Illumina Linkage IV Panel in 142 cases clustered in 27 families from a genetic isolate, the Erasmus Rucphen Family (ERF) study. Potential causal variants were identified by searching for shared rare variants in the exome-sequence data of the affected members of the families contributing most to the linkage peak. The identified rare variants were then tested for association with COPD in a large meta-analysis of several cohorts. Significant evidence for linkage was observed on chromosomes 15q14-15q25 [logarithm of the odds (LOD) score = 5.52], 11p15.4-11q14.1 (LOD = 3.71) and 5q14.3-5q33.2 (LOD = 3.49). In the chromosome 15 peak, that harbors the known COPD locus for nicotinic receptors, and in the chromosome 5 peak we could not identify shared variants. In the chromosome 11 locus, we identified four rare (minor allele frequency (MAF) <0.02), predicted pathogenic, missense variants. These were shared among the affected family members. The identified variants localize to genes including neuroblast differentiation-associated protein ( AHNAK ), previously associated with blood biomarkers in COPD, phospholipase C Beta 3 ( PLCB3 ), shown to increase airway hyper-responsiveness, solute carrier family 22-A11 ( SLC22A11 ), involved in amino acid metabolism and ion transport, and metallothionein-like protein 5 ( MTL5 ), involved in nicotinate and nicotinamide metabolism. Association of SLC22A11 and MTL5 variants were confirmed in the meta-analysis of 9,888 cases and 27,060 controls. In conclusion, we have identified novel rare variants in plausible genes related to COPD. Further studies utilizing large sample whole-genome sequencing should further confirm the associations at chromosome 11 and investigate the chromosome 15 and 5 linked regions.
Comprehensive genetic testing for female and male infertility using next-generation sequencing.
Patel, Bonny; Parets, Sasha; Akana, Matthew; Kellogg, Gregory; Jansen, Michael; Chang, Chihyu; Cai, Ying; Fox, Rebecca; Niknazar, Mohammad; Shraga, Roman; Hunter, Colby; Pollock, Andrew; Wisotzkey, Robert; Jaremko, Malgorzata; Bisignano, Alex; Puig, Oscar
2018-05-19
To develop a comprehensive genetic test for female and male infertility in support of medical decisions during assisted reproductive technology (ART) protocols. We developed a next-generation sequencing (NGS) gene panel consisting of 87 genes including promoters, 5' and 3' untranslated regions, exons, and selected introns. In addition, sex chromosome aneuploidies and Y chromosome microdeletions were analyzed concomitantly using the same panel. The NGS panel was analytically validated by retrospective analysis of 118 genomic DNA samples with known variants in loci representative of female and male infertility. Our results showed analytical accuracy of > 99%, with > 98% sensitivity for single-nucleotide variants (SNVs) and > 91% sensitivity for insertions/deletions (indels). Clinical sensitivity was assessed with samples containing variants representative of male and female infertility, and it was 100% for SNVs/indels, CFTR IVS8-5T variants, sex chromosome aneuploidies, and copy number variants (CNVs) and > 93% for Y chromosome microdeletions. Cost analysis shows potential savings when comparing this single NGS assay with the standard approach, which includes multiple assays. A single, comprehensive, NGS panel can simplify the ordering process for healthcare providers, reduce turnaround time, and lower the overall cost of testing for genetic assessment of infertility in females and males, while maintaining accuracy.
Homburger, Julian R.; Green, Eric M.; Caleshu, Colleen; Sunitha, Margaret S.; Taylor, Rebecca E.; Ruppel, Kathleen M.; Metpally, Raghu Prasad Rao; Colan, Steven D.; Michels, Michelle; Day, Sharlene M.; Olivotto, Iacopo; Bustamante, Carlos D.; Dewey, Frederick E.; Ho, Carolyn Y.; Spudich, James A.; Ashley, Euan A.
2016-01-01
Myosin motors are the fundamental force-generating elements of muscle contraction. Variation in the human β-cardiac myosin heavy chain gene (MYH7) can lead to hypertrophic cardiomyopathy (HCM), a heritable disease characterized by cardiac hypertrophy, heart failure, and sudden cardiac death. How specific myosin variants alter motor function or clinical expression of disease remains incompletely understood. Here, we combine structural models of myosin from multiple stages of its chemomechanical cycle, exome sequencing data from two population cohorts of 60,706 and 42,930 individuals, and genetic and phenotypic data from 2,913 patients with HCM to identify regions of disease enrichment within β-cardiac myosin. We first developed computational models of the human β-cardiac myosin protein before and after the myosin power stroke. Then, using a spatial scan statistic modified to analyze genetic variation in protein 3D space, we found significant enrichment of disease-associated variants in the converter, a kinetic domain that transduces force from the catalytic domain to the lever arm to accomplish the power stroke. Focusing our analysis on surface-exposed residues, we identified a larger region significantly enriched for disease-associated variants that contains both the converter domain and residues on a single flat surface on the myosin head described as the myosin mesa. Notably, patients with HCM with variants in the enriched regions have earlier disease onset than patients who have HCM with variants elsewhere. Our study provides a model for integrating protein structure, large-scale genetic sequencing, and detailed phenotypic data to reveal insight into time-shifted protein structures and genetic disease. PMID:27247418
ANRIL Genetic Variants in Iranian Breast Cancer Patients
Khorshidi, Hamid Reza; Taheri, Mohammad; Noroozi, Rezvan; Sarrafzadeh, Shaghayegh; Sayad, Arezou; Ghafouri-Fard, Soudeh
2017-01-01
Objective The genetic variants of the long non-coding RNA ANRIL (an antisense noncoding RNA in the INK4 locus) as well as its expression have been shown to be associated with several human diseases including cancers. The aim of this study was to examine the association of ANRIL variants with breast cancer susceptibility in Iranian patients. Materials and Methods In this case-control study, we genotyped rs1333045, rs4977574, rs1333048 and rs10757278 single nucleotide polymorphisms (SNPs) in 122 breast can- cer patients as well as in 200 normal age-matched subjects by tetra-primer amplification refractory mutation system polymerase chain reaction (T-ARMS-PCR). Results The TT genotype at rs1333045 was significantly over-represented among pa- tients (P=0.038) but did not remain significant after multiple-testing correction. In addi- tion, among all observed haplotypes (with SNP order of rs1333045, rs1333048 rs4977574 and rs10757278), four haplotypes were shown to be associated with breast cancer risk. However, after multiple testing corrections, TCGA was the only haplotype which remained significant. Conclusion These results suggest that breast cancer risk is significantly associated with ANRIL variants. Future work analyzing the expression of different associated ANRIL haplotypes would further shed light on the role of ANRIL in this disease. PMID:28580310
Adrian, Molly; Kiff, Cara; Glazner, Chris; Kohen, Ruth; Tracy, Julia Helen; Zhou, Chuan; McCauley, Elizabeth; Stoep, Ann Vander
2015-01-01
Objective The objective of this study was to apply a Bayesian statistical analytic approach that minimizes multiple testing problems to explore the combined effects of chronic low familial support and variants in 12 candidate genes on risk for a common and debilitating childhood mental health condition. Method Bayesian mixture modeling was used to examine gene by environment interactions among genetic variants and environmental factors (family support) associated in previous studies with the occurrence of comorbid depression and disruptive behavior disorders youth, using a sample of 255 children. Results One main effects, variants in the oxytocin receptor (OXTR, rs53576) was associated with increased risk for comorbid disorders. Two significant gene x environment and one signification gene x gene interaction emerged. Variants in the nicotinic acetylcholine receptor α5 subunit (CHRNA5, rs16969968) and in the glucocorticoid receptor chaperone protein FK506 binding protein 5 (FKBP5, rs4713902) interacted with chronic low family support in association with child mental health status. One gene x gene interaction, 5-HTTLPR variant of the serotonin transporter (SERT/SLC6A4) in combination with μ opioid receptor (OPRM1, rs1799971) was associated with comorbid depression and conduct problems. Conclusions Results indicate that Bayesian modeling is a feasible strategy for conducting behavioral genetics research. This approach, combined with an optimized genetic selection strategy (Vrieze, Iacono, & McGue, 2012), revealed genetic variants involved in stress regulation ( FKBP5, SERTxOPMR), social bonding (OXTR), and nicotine responsivity (CHRNA5) in predicting comorbid status. PMID:26228411
Common genetic variants in the 9p21 region and their associations with multiple tumours.
Gu, F; Pfeiffer, R M; Bhattacharjee, S; Han, S S; Taylor, P R; Berndt, S; Yang, H; Sigurdson, A J; Toro, J; Mirabello, L; Greene, M H; Freedman, N D; Abnet, C C; Dawsey, S M; Hu, N; Qiao, Y-L; Ding, T; Brenner, A V; Garcia-Closas, M; Hayes, R; Brinton, L A; Lissowska, J; Wentzensen, N; Kratz, C; Moore, L E; Ziegler, R G; Chow, W-H; Savage, S A; Burdette, L; Yeager, M; Chanock, S J; Chatterjee, N; Tucker, M A; Goldstein, A M; Yang, X R
2013-04-02
The chromosome 9p21.3 region has been implicated in the pathogenesis of multiple cancers. We systematically examined up to 203 tagging SNPs of 22 genes on 9p21.3 (19.9-32.8 Mb) in eight case-control studies: thyroid cancer, endometrial cancer (EC), renal cell carcinoma, colorectal cancer (CRC), colorectal adenoma (CA), oesophageal squamous cell carcinoma (ESCC), gastric cardia adenocarcinoma and osteosarcoma (OS). We used logistic regression to perform single SNP analyses for each study separately, adjusting for study-specific covariates. We combined SNP results across studies by fixed-effect meta-analyses and a newly developed subset-based statistical approach (ASSET). Gene-based P-values were obtained by the minP method using the Adaptive Rank Truncated Product program. We adjusted for multiple comparisons by Bonferroni correction. Rs3731239 in cyclin-dependent kinase inhibitors 2A (CDKN2A) was significantly associated with ESCC (P=7 × 10(-6)). The CDKN2A-ESCC association was further supported by gene-based analyses (Pgene=0.0001). In the meta-analyses by ASSET, four SNPs (rs3731239 in CDKN2A, rs615552 and rs573687 in CDKN2B and rs564398 in CDKN2BAS) showed significant associations with ESCC and EC (P<2.46 × 10(-4)). One SNP in MTAP (methylthioadenosine phosphorylase) (rs7023329) that was previously associated with melanoma and nevi in multiple genome-wide association studies was associated with CRC, CA and OS by ASSET (P=0.007). Our data indicate that genetic variants in CDKN2A, and possibly nearby genes, may be associated with ESCC and several other tumours, further highlighting the importance of 9p21.3 genetic variants in carcinogenesis.
Intrahaplotypic Variants Differentiate Complex Linkage Disequilibrium within Human MHC Haplotypes
Lam, Tze Hau; Tay, Matthew Zirui; Wang, Bei; Xiao, Ziwei; Ren, Ee Chee
2015-01-01
Distinct regions of long-range genetic fixation in the human MHC region, known as conserved extended haplotypes (CEHs), possess unique genomic characteristics and are strongly associated with numerous diseases. While CEHs appear to be homogeneous by SNP analysis, the nature of fine variations within their genomic structure is unknown. Using multiple, MHC-homozygous cell lines, we demonstrate extensive sequence conservation in two common Asian MHC haplotypes: A33-B58-DR3 and A2-B46-DR9. However, characterization of phase-resolved MHC haplotypes revealed unique intra-CEH patterns of variation and uncovered 127 single nucleotide variants (SNVs) which are missing from public databases. We further show that the strong linkage disequilibrium structure within the human MHC that typically confounds precise identification of genetic features can be resolved using intra-CEH variants, as evidenced by rs3129063 and rs448489, which affect expression of ZFP57, a gene important in methylation and epigenetic regulation. This study demonstrates an improved strategy that can be used towards genetic dissection of diseases. PMID:26593880
Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.
Flannick, Jason; Fuchsberger, Christian; Mahajan, Anubha; Teslovich, Tanya M; Agarwala, Vineeta; Gaulton, Kyle J; Caulkins, Lizz; Koesterer, Ryan; Ma, Clement; Moutsianas, Loukas; McCarthy, Davis J; Rivas, Manuel A; Perry, John R B; Sim, Xueling; Blackwell, Thomas W; Robertson, Neil R; Rayner, N William; Cingolani, Pablo; Locke, Adam E; Tajes, Juan Fernandez; Highland, Heather M; Dupuis, Josee; Chines, Peter S; Lindgren, Cecilia M; Hartl, Christopher; Jackson, Anne U; Chen, Han; Huyghe, Jeroen R; van de Bunt, Martijn; Pearson, Richard D; Kumar, Ashish; Müller-Nurasyid, Martina; Grarup, Niels; Stringham, Heather M; Gamazon, Eric R; Lee, Jaehoon; Chen, Yuhui; Scott, Robert A; Below, Jennifer E; Chen, Peng; Huang, Jinyan; Go, Min Jin; Stitzel, Michael L; Pasko, Dorota; Parker, Stephen C J; Varga, Tibor V; Green, Todd; Beer, Nicola L; Day-Williams, Aaron G; Ferreira, Teresa; Fingerlin, Tasha; Horikoshi, Momoko; Hu, Cheng; Huh, Iksoo; Ikram, Mohammad Kamran; Kim, Bong-Jo; Kim, Yongkang; Kim, Young Jin; Kwon, Min-Seok; Lee, Juyoung; Lee, Selyeong; Lin, Keng-Han; Maxwell, Taylor J; Nagai, Yoshihiko; Wang, Xu; Welch, Ryan P; Yoon, Joon; Zhang, Weihua; Barzilai, Nir; Voight, Benjamin F; Han, Bok-Ghee; Jenkinson, Christopher P; Kuulasmaa, Teemu; Kuusisto, Johanna; Manning, Alisa; Ng, Maggie C Y; Palmer, Nicholette D; Balkau, Beverley; Stančáková, Alena; Abboud, Hanna E; Boeing, Heiner; Giedraitis, Vilmantas; Prabhakaran, Dorairaj; Gottesman, Omri; Scott, James; Carey, Jason; Kwan, Phoenix; Grant, George; Smith, Joshua D; Neale, Benjamin M; Purcell, Shaun; Butterworth, Adam S; Howson, Joanna M M; Lee, Heung Man; Lu, Yingchang; Kwak, Soo-Heon; Zhao, Wei; Danesh, John; Lam, Vincent K L; Park, Kyong Soo; Saleheen, Danish; So, Wing Yee; Tam, Claudia H T; Afzal, Uzma; Aguilar, David; Arya, Rector; Aung, Tin; Chan, Edmund; Navarro, Carmen; Cheng, Ching-Yu; Palli, Domenico; Correa, Adolfo; Curran, Joanne E; Rybin, Dennis; Farook, Vidya S; Fowler, Sharon P; Freedman, Barry I; Griswold, Michael; Hale, Daniel Esten; Hicks, Pamela J; Khor, Chiea-Chuen; Kumar, Satish; Lehne, Benjamin; Thuillier, Dorothée; Lim, Wei Yen; Liu, Jianjun; Loh, Marie; Musani, Solomon K; Puppala, Sobha; Scott, William R; Yengo, Loïc; Tan, Sian-Tsung; Taylor, Herman A; Thameem, Farook; Wilson, Gregory; Wong, Tien Yin; Njølstad, Pål Rasmus; Levy, Jonathan C; Mangino, Massimo; Bonnycastle, Lori L; Schwarzmayr, Thomas; Fadista, João; Surdulescu, Gabriela L; Herder, Christian; Groves, Christopher J; Wieland, Thomas; Bork-Jensen, Jette; Brandslund, Ivan; Christensen, Cramer; Koistinen, Heikki A; Doney, Alex S F; Kinnunen, Leena; Esko, Tõnu; Farmer, Andrew J; Hakaste, Liisa; Hodgkiss, Dylan; Kravic, Jasmina; Lyssenko, Valeri; Hollensted, Mette; Jørgensen, Marit E; Jørgensen, Torben; Ladenvall, Claes; Justesen, Johanne Marie; Käräjämäki, Annemari; Kriebel, Jennifer; Rathmann, Wolfgang; Lannfelt, Lars; Lauritzen, Torsten; Narisu, Narisu; Linneberg, Allan; Melander, Olle; Milani, Lili; Neville, Matt; Orho-Melander, Marju; Qi, Lu; Qi, Qibin; Roden, Michael; Rolandsson, Olov; Swift, Amy; Rosengren, Anders H; Stirrups, Kathleen; Wood, Andrew R; Mihailov, Evelin; Blancher, Christine; Carneiro, Mauricio O; Maguire, Jared; Poplin, Ryan; Shakir, Khalid; Fennell, Timothy; DePristo, Mark; de Angelis, Martin Hrabé; Deloukas, Panos; Gjesing, Anette P; Jun, Goo; Nilsson, Peter; Murphy, Jacquelyn; Onofrio, Robert; Thorand, Barbara; Hansen, Torben; Meisinger, Christa; Hu, Frank B; Isomaa, Bo; Karpe, Fredrik; Liang, Liming; Peters, Annette; Huth, Cornelia; O'Rahilly, Stephen P; Palmer, Colin N A; Pedersen, Oluf; Rauramaa, Rainer; Tuomilehto, Jaakko; Salomaa, Veikko; Watanabe, Richard M; Syvänen, Ann-Christine; Bergman, Richard N; Bharadwaj, Dwaipayan; Bottinger, Erwin P; Cho, Yoon Shin; Chandak, Giriraj R; Chan, Juliana Cn; Chia, Kee Seng; Daly, Mark J; Ebrahim, Shah B; Langenberg, Claudia; Elliott, Paul; Jablonski, Kathleen A; Lehman, Donna M; Jia, Weiping; Ma, Ronald C W; Pollin, Toni I; Sandhu, Manjinder; Tandon, Nikhil; Froguel, Philippe; Barroso, Inês; Teo, Yik Ying; Zeggini, Eleftheria; Loos, Ruth J F; Small, Kerrin S; Ried, Janina S; DeFronzo, Ralph A; Grallert, Harald; Glaser, Benjamin; Metspalu, Andres; Wareham, Nicholas J; Walker, Mark; Banks, Eric; Gieger, Christian; Ingelsson, Erik; Im, Hae Kyung; Illig, Thomas; Franks, Paul W; Buck, Gemma; Trakalo, Joseph; Buck, David; Prokopenko, Inga; Mägi, Reedik; Lind, Lars; Farjoun, Yossi; Owen, Katharine R; Gloyn, Anna L; Strauch, Konstantin; Tuomi, Tiinamaija; Kooner, Jaspal Singh; Lee, Jong-Young; Park, Taesung; Donnelly, Peter; Morris, Andrew D; Hattersley, Andrew T; Bowden, Donald W; Collins, Francis S; Atzmon, Gil; Chambers, John C; Spector, Timothy D; Laakso, Markku; Strom, Tim M; Bell, Graeme I; Blangero, John; Duggirala, Ravindranath; Tai, E Shyong; McVean, Gilean; Hanis, Craig L; Wilson, James G; Seielstad, Mark; Frayling, Timothy M; Meigs, James B; Cox, Nancy J; Sladek, Rob; Lander, Eric S; Gabriel, Stacey; Mohlke, Karen L; Meitinger, Thomas; Groop, Leif; Abecasis, Goncalo; Scott, Laura J; Morris, Andrew P; Kang, Hyun Min; Altshuler, David; Burtt, Noël P; Florez, Jose C; Boehnke, Michael; McCarthy, Mark I
2017-12-19
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
Jason, Flannick; Fuchsberger, Christian; Mahajan, Anubha; Teslovich, Tanya M.; Agarwala, Vineeta; Gaulton, Kyle J.; Caulkins, Lizz; Koesterer, Ryan; Ma, Clement; Moutsianas, Loukas; McCarthy, Davis J.; Rivas, Manuel A.; Perry, John R. B.; Sim, Xueling; Blackwell, Thomas W.; Robertson, Neil R.; Rayner, N William; Cingolani, Pablo; Locke, Adam E.; Tajes, Juan Fernandez; Highland, Heather M.; Dupuis, Josee; Chines, Peter S.; Lindgren, Cecilia M.; Hartl, Christopher; Jackson, Anne U.; Chen, Han; Huyghe, Jeroen R.; van de Bunt, Martijn; Pearson, Richard D.; Kumar, Ashish; Müller-Nurasyid, Martina; Grarup, Niels; Stringham, Heather M.; Gamazon, Eric R.; Lee, Jaehoon; Chen, Yuhui; Scott, Robert A.; Below, Jennifer E.; Chen, Peng; Huang, Jinyan; Go, Min Jin; Stitzel, Michael L.; Pasko, Dorota; Parker, Stephen C. J.; Varga, Tibor V.; Green, Todd; Beer, Nicola L.; Day-Williams, Aaron G.; Ferreira, Teresa; Fingerlin, Tasha; Horikoshi, Momoko; Hu, Cheng; Huh, Iksoo; Ikram, Mohammad Kamran; Kim, Bong-Jo; Kim, Yongkang; Kim, Young Jin; Kwon, Min-Seok; Lee, Juyoung; Lee, Selyeong; Lin, Keng-Han; Maxwell, Taylor J.; Nagai, Yoshihiko; Wang, Xu; Welch, Ryan P.; Yoon, Joon; Zhang, Weihua; Barzilai, Nir; Voight, Benjamin F.; Han, Bok-Ghee; Jenkinson, Christopher P.; Kuulasmaa, Teemu; Kuusisto, Johanna; Manning, Alisa; Ng, Maggie C. Y.; Palmer, Nicholette D.; Balkau, Beverley; Stančáková, Alena; Abboud, Hanna E.; Boeing, Heiner; Giedraitis, Vilmantas; Prabhakaran, Dorairaj; Gottesman, Omri; Scott, James; Carey, Jason; Kwan, Phoenix; Grant, George; Smith, Joshua D.; Neale, Benjamin M.; Purcell, Shaun; Butterworth, Adam S.; Howson, Joanna M. M.; Lee, Heung Man; Lu, Yingchang; Kwak, Soo-Heon; Zhao, Wei; Danesh, John; Lam, Vincent K. L.; Park, Kyong Soo; Saleheen, Danish; So, Wing Yee; Tam, Claudia H. T.; Afzal, Uzma; Aguilar, David; Arya, Rector; Aung, Tin; Chan, Edmund; Navarro, Carmen; Cheng, Ching-Yu; Palli, Domenico; Correa, Adolfo; Curran, Joanne E.; Rybin, Dennis; Farook, Vidya S.; Fowler, Sharon P.; Freedman, Barry I.; Griswold, Michael; Hale, Daniel Esten; Hicks, Pamela J.; Khor, Chiea-Chuen; Kumar, Satish; Lehne, Benjamin; Thuillier, Dorothée; Lim, Wei Yen; Liu, Jianjun; Loh, Marie; Musani, Solomon K.; Puppala, Sobha; Scott, William R.; Yengo, Loïc; Tan, Sian-Tsung; Taylor, Herman A.; Thameem, Farook; Wilson, Gregory; Wong, Tien Yin; Njølstad, Pål Rasmus; Levy, Jonathan C.; Mangino, Massimo; Bonnycastle, Lori L.; Schwarzmayr, Thomas; Fadista, João; Surdulescu, Gabriela L.; Herder, Christian; Groves, Christopher J.; Wieland, Thomas; Bork-Jensen, Jette; Brandslund, Ivan; Christensen, Cramer; Koistinen, Heikki A.; Doney, Alex S. F.; Kinnunen, Leena; Esko, Tõnu; Farmer, Andrew J.; Hakaste, Liisa; Hodgkiss, Dylan; Kravic, Jasmina; Lyssenko, Valeri; Hollensted, Mette; Jørgensen, Marit E.; Jørgensen, Torben; Ladenvall, Claes; Justesen, Johanne Marie; Käräjämäki, Annemari; Kriebel, Jennifer; Rathmann, Wolfgang; Lannfelt, Lars; Lauritzen, Torsten; Narisu, Narisu; Linneberg, Allan; Melander, Olle; Milani, Lili; Neville, Matt; Orho-Melander, Marju; Qi, Lu; Qi, Qibin; Roden, Michael; Rolandsson, Olov; Swift, Amy; Rosengren, Anders H.; Stirrups, Kathleen; Wood, Andrew R.; Mihailov, Evelin; Blancher, Christine; Carneiro, Mauricio O.; Maguire, Jared; Poplin, Ryan; Shakir, Khalid; Fennell, Timothy; DePristo, Mark; de Angelis, Martin Hrabé; Deloukas, Panos; Gjesing, Anette P.; Jun, Goo; Nilsson, Peter; Murphy, Jacquelyn; Onofrio, Robert; Thorand, Barbara; Hansen, Torben; Meisinger, Christa; Hu, Frank B.; Isomaa, Bo; Karpe, Fredrik; Liang, Liming; Peters, Annette; Huth, Cornelia; O'Rahilly, Stephen P; Palmer, Colin N. A.; Pedersen, Oluf; Rauramaa, Rainer; Tuomilehto, Jaakko; Salomaa, Veikko; Watanabe, Richard M.; Syvänen, Ann-Christine; Bergman, Richard N.; Bharadwaj, Dwaipayan; Bottinger, Erwin P.; Cho, Yoon Shin; Chandak, Giriraj R.; Chan, Juliana CN; Chia, Kee Seng; Daly, Mark J.; Ebrahim, Shah B.; Langenberg, Claudia; Elliott, Paul; Jablonski, Kathleen A.; Lehman, Donna M.; Jia, Weiping; Ma, Ronald C. W.; Pollin, Toni I.; Sandhu, Manjinder; Tandon, Nikhil; Froguel, Philippe; Barroso, Inês; Teo, Yik Ying; Zeggini, Eleftheria; Loos, Ruth J. F.; Small, Kerrin S.; Ried, Janina S.; DeFronzo, Ralph A.; Grallert, Harald; Glaser, Benjamin; Metspalu, Andres; Wareham, Nicholas J.; Walker, Mark; Banks, Eric; Gieger, Christian; Ingelsson, Erik; Im, Hae Kyung; Illig, Thomas; Franks, Paul W.; Buck, Gemma; Trakalo, Joseph; Buck, David; Prokopenko, Inga; Mägi, Reedik; Lind, Lars; Farjoun, Yossi; Owen, Katharine R.; Gloyn, Anna L.; Strauch, Konstantin; Tuomi, Tiinamaija; Kooner, Jaspal Singh; Lee, Jong-Young; Park, Taesung; Donnelly, Peter; Morris, Andrew D.; Hattersley, Andrew T.; Bowden, Donald W.; Collins, Francis S.; Atzmon, Gil; Chambers, John C.; Spector, Timothy D.; Laakso, Markku; Strom, Tim M.; Bell, Graeme I.; Blangero, John; Duggirala, Ravindranath; Tai, E. Shyong; McVean, Gilean; Hanis, Craig L.; Wilson, James G.; Seielstad, Mark; Frayling, Timothy M.; Meigs, James B.; Cox, Nancy J.; Sladek, Rob; Lander, Eric S.; Gabriel, Stacey; Mohlke, Karen L.; Meitinger, Thomas; Groop, Leif; Abecasis, Goncalo; Scott, Laura J.; Morris, Andrew P.; Kang, Hyun Min; Altshuler, David; Burtt, Noël P.; Florez, Jose C.; Boehnke, Michael; McCarthy, Mark I.
2017-01-01
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1–5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D. PMID:29257133
Jarvi, S.I.; Farias, M.E.; Lapointe, D.A.; Belcaid, M.; Atkinson, C.T.
2013-01-01
Next-generation 454 sequencing techniques were used to re-examine diversity of mitochondrial cytochrome b lineages of avian malaria (Plasmodium relictum) in Hawaii. We document a minimum of 23 variant lineages of the parasite based on single nucleotide transitional changes, in addition to the previously reported single lineage (GRW4). A new, publicly available portal (Integroomer) was developed for initial parsing of 454 datasets. Mean variant prevalence and frequency was higher in low elevation Hawaii Amakihi (Hemignathus virens) with Avipoxvirus-like lesions (P = 0·001), suggesting that the variants may be biologically distinct. By contrast, variant prevalence and frequency did not differ significantly among mid-elevation Apapane (Himatione sanguinea) with or without lesions (P = 0·691). The low frequency and the lack of detection of variants independent of GRW4 suggest that multiple independent introductions of P. relictum to Hawaii are unlikely. Multiple variants may have been introduced in heteroplasmy with GRW4 or exist within the tandem repeat structure of the mitochondrial genome. The discovery of multiple mitochondrial lineages of P. relictum in Hawaii provides a measure of genetic diversity within a geographically isolated population of this parasite and suggests the origins and evolution of parasite diversity may be more complicated than previously recognized.
Jarvi, S I; Farias, M E; Lapointe, D A; Belcaid, M; Atkinson, C T
2013-12-01
Next-generation 454 sequencing techniques were used to re-examine diversity of mitochondrial cytochrome b lineages of avian malaria (Plasmodium relictum) in Hawaii. We document a minimum of 23 variant lineages of the parasite based on single nucleotide transitional changes, in addition to the previously reported single lineage (GRW4). A new, publicly available portal (Integroomer) was developed for initial parsing of 454 datasets. Mean variant prevalence and frequency was higher in low elevation Hawaii Amakihi (Hemignathus virens) with Avipoxvirus-like lesions (P = 0·001), suggesting that the variants may be biologically distinct. By contrast, variant prevalence and frequency did not differ significantly among mid-elevation Apapane (Himatione sanguinea) with or without lesions (P = 0·691). The low frequency and the lack of detection of variants independent of GRW4 suggest that multiple independent introductions of P. relictum to Hawaii are unlikely. Multiple variants may have been introduced in heteroplasmy with GRW4 or exist within the tandem repeat structure of the mitochondrial genome. The discovery of multiple mitochondrial lineages of P. relictum in Hawaii provides a measure of genetic diversity within a geographically isolated population of this parasite and suggests the origins and evolution of parasite diversity may be more complicated than previously recognized.
Plaiasu, Vasilica; Ochiana, Diana; Motei, Gabriela; Anca, Ioana; Georgescu, Adrian
2010-07-01
Patau syndrome (trisomy 13) is one of the most common chromosomal anomalies clinically characterized by the presence of numerous malformations with a limited survival rate for most cases. Babies are usually identified at birth and the diagnosis is confirmed with genetic testing. In this review we outline the clinical and cytogenetic aspects of trisomy 13 and associated phenotypes for 5 cases analyzed in the last 3 years, referred to our Clinical Genetics Department. For each child cytogenetic analysis was performed to determine the genetic variant; also, the patients were investigated for other associated malformations (cardiac, cerebral, renal, ocular anomalies). All 5 cases presented multiple malformations, including some but not all signs of the classical clinical triad suggestive of Patau syndrome. The cytogenetic investigation confirmed for each case the suspected diagnosis and also indicated the specific genetic variant, this being a valuable information for the genetic counselling of the families. The application of genetic analysis can increase diagnosis and prognosis accuracy and have an impact on clinical management.
Pitfalls in setting up genetic studies on preeclampsia.
Laivuori, Hannele
2013-04-01
This presentation will consider approaches to discover susceptibility genes for a complex genetic disorder such as preeclampsia. The clinical disease presumably results from the additive effects of multiple sequence variants from the mother and the foetus together with environmental factors. Disease heterogeneity and underpowered study designs are likely to be behind non-reproducible results in candidate gene association studies. To avoid spurious findings, sample size and characteristics of the study populations as well as replication studies in an independent study population should be an essential part of a study design. In family-based linkage studies relationship with genotype and phenotype may be modified by a variety of factors. The large number of families needed in discovering genetic variants with modest effect sizes is difficult to attain. Moreover, the identification of underlying mutations has proven difficult. When pooling data or performing meta-analyses from different populations, disease and locus heterogeneity may become a major issue. First genome-wide association studies (GWAS) have identified risk loci for preeclampsia. Adequately powered replication studies are critical in order to replicate the initial GWAS findings. This approach requires rigorous multiple testing correction. The expected effect sizes of individual sequence variants on preeclampsia are small, but this approach is likely to decipher new clues to the pathogenesis. The rare variants, gene-gene and gene-environmental interactions as well as noncoding genetic variations and epigenetics are expected to explain the missing heritability. Next-generation sequencing technologies will make large amount of data on genomes and transcriptomes available. Complexity of the data poses a challenge. Different depths of coverage might be chosen depending on the design of the study, and validation of the results by different methods is mandatory. In order to minimize disease heterogeneity in genetic studies of preeclampsia, identification of subtypes and intermediate phenotypes would be highly desirable. Copyright © 2013. Published by Elsevier B.V.
MetaSeq: privacy preserving meta-analysis of sequencing-based association studies.
Singh, Angad Pal; Zafer, Samreen; Pe'er, Itsik
2013-01-01
Human genetics recently transitioned from GWAS to studies based on NGS data. For GWAS, small effects dictated large sample sizes, typically made possible through meta-analysis by exchanging summary statistics across consortia. NGS studies groupwise-test for association of multiple potentially-causal alleles along each gene. They are subject to similar power constraints and therefore likely to resort to meta-analysis as well. The problem arises when considering privacy of the genetic information during the data-exchange process. Many scoring schemes for NGS association rely on the frequency of each variant thus requiring the exchange of identity of the sequenced variant. As such variants are often rare, potentially revealing the identity of their carriers and jeopardizing privacy. We have thus developed MetaSeq, a protocol for meta-analysis of genome-wide sequencing data by multiple collaborating parties, scoring association for rare variants pooled per gene across all parties. We tackle the challenge of tallying frequency counts of rare, sequenced alleles, for metaanalysis of sequencing data without disclosing the allele identity and counts, thereby protecting sample identity. This apparent paradoxical exchange of information is achieved through cryptographic means. The key idea is that parties encrypt identity of genes and variants. When they transfer information about frequency counts in cases and controls, the exchanged data does not convey the identity of a mutation and therefore does not expose carrier identity. The exchange relies on a 3rd party, trusted to follow the protocol although not trusted to learn about the raw data. We show applicability of this method to publicly available exome-sequencing data from multiple studies, simulating phenotypic information for powerful meta-analysis. The MetaSeq software is publicly available as open source.
An update on the genetic architecture of hyperuricemia and gout.
Merriman, Tony R
2015-04-10
Genome-wide association studies that scan the genome for common genetic variants associated with phenotype have greatly advanced medical knowledge. Hyperuricemia is no exception, with 28 loci identified. However, genetic control of pathways determining gout in the presence of hyperuricemia is still poorly understood. Two important pathways determining hyperuricemia have been confirmed (renal and gut excretion of uric acid with glycolysis now firmly implicated). Major urate loci are SLC2A9 and ABCG2. Recent studies show that SLC2A9 is involved in renal and gut excretion of uric acid and is implicated in antioxidant defense. Although etiological variants at SLC2A9 are yet to be identified, it is clear that considerable genetic complexity exists at the SLC2A9 locus, with multiple statistically independent genetic variants and local epistatic interactions. The positions of implicated genetic variants within or near chromatin regions involved in transcriptional control suggest that this mechanism (rather than structural changes in SLC2A9) is important in regulating the activity of SLC2A9. ABCG2 is involved primarily in extra-renal uric acid under-excretion with the etiological variant influencing expression. At the other 26 loci, probable causal genes can be identified at three (PDZK1, SLC22A11, and INHBB) with strong candidates at a further 10 loci. Confirmation of the causal gene will require a combination of re-sequencing, trans-ancestral mapping, and correlation of genetic association data with expression data. As expected, the urate loci associate with gout, although inconsistent effect sizes for gout require investigation. Finally, there has been no genome-wide association study using clinically ascertained cases to investigate the causes of gout in the presence of hyperuricemia. In such a study, use of asymptomatic hyperurcemic controls would be expected to increase the ability to detect genetic associations with gout.
Investigation of Genetic Variation Underlying Central Obesity amongst South Asians.
Scott, William R; Zhang, Weihua; Loh, Marie; Tan, Sian-Tsung; Lehne, Benjamin; Afzal, Uzma; Peralta, Juan; Saxena, Richa; Ralhan, Sarju; Wander, Gurpreet S; Bozaoglu, Kiymet; Sanghera, Dharambir K; Elliott, Paul; Scott, James; Chambers, John C; Kooner, Jaspal S
2016-01-01
South Asians are 1/4 of the world's population and have increased susceptibility to central obesity and related cardiometabolic disease. Knowledge of genetic variants affecting risk of central obesity is largely based on genome-wide association studies of common SNPs in Europeans. To evaluate the contribution of DNA sequence variation to the higher levels of central obesity (defined as waist hip ratio adjusted for body mass index, WHR) among South Asians compared to Europeans we carried out: i) a genome-wide association analysis of >6M genetic variants in 10,318 South Asians with focused analysis of population-specific SNPs; ii) an exome-wide association analysis of ~250K SNPs in protein-coding regions in 2,637 South Asians; iii) a comparison of risk allele frequencies and effect sizes of 48 known WHR SNPs in 12,240 South Asians compared to Europeans. In genome-wide analyses, we found no novel associations between common genetic variants and WHR in South Asians at P<5x10-8; variants showing equivocal association with WHR (P<1x10-5) did not replicate at P<0.05 in an independent cohort of South Asians (N = 1,922) or in published, predominantly European meta-analysis data. In the targeted analyses of 122,391 population-specific SNPs we also found no associations with WHR in South Asians at P<0.05 after multiple testing correction. Exome-wide analyses showed no new associations between genetic variants and WHR in South Asians, either individually at P<1.5x10-6 or grouped by gene locus at P<2.5x10-6. At known WHR loci, risk allele frequencies were not higher in South Asians compared to Europeans (P = 0.77), while effect sizes were unexpectedly smaller in South Asians than Europeans (P<5.0x10-8). Our findings argue against an important contribution for population-specific or cosmopolitan genetic variants underlying the increased risk of central obesity in South Asians compared to Europeans.
Investigation of Genetic Variation Underlying Central Obesity amongst South Asians
Scott, William R.; Zhang, Weihua; Loh, Marie; Tan, Sian-Tsung; Lehne, Benjamin; Afzal, Uzma; Peralta, Juan; Saxena, Richa; Ralhan, Sarju; Wander, Gurpreet S.; Bozaoglu, Kiymet; Sanghera, Dharambir K.; Elliott, Paul; Scott, James; Chambers, John C.; Kooner, Jaspal S.
2016-01-01
South Asians are 1/4 of the world’s population and have increased susceptibility to central obesity and related cardiometabolic disease. Knowledge of genetic variants affecting risk of central obesity is largely based on genome-wide association studies of common SNPs in Europeans. To evaluate the contribution of DNA sequence variation to the higher levels of central obesity (defined as waist hip ratio adjusted for body mass index, WHR) among South Asians compared to Europeans we carried out: i) a genome-wide association analysis of >6M genetic variants in 10,318 South Asians with focused analysis of population-specific SNPs; ii) an exome-wide association analysis of ~250K SNPs in protein-coding regions in 2,637 South Asians; iii) a comparison of risk allele frequencies and effect sizes of 48 known WHR SNPs in 12,240 South Asians compared to Europeans. In genome-wide analyses, we found no novel associations between common genetic variants and WHR in South Asians at P<5x10-8; variants showing equivocal association with WHR (P<1x10-5) did not replicate at P<0.05 in an independent cohort of South Asians (N = 1,922) or in published, predominantly European meta-analysis data. In the targeted analyses of 122,391 population-specific SNPs we also found no associations with WHR in South Asians at P<0.05 after multiple testing correction. Exome-wide analyses showed no new associations between genetic variants and WHR in South Asians, either individually at P<1.5x10-6 or grouped by gene locus at P<2.5x10−6. At known WHR loci, risk allele frequencies were not higher in South Asians compared to Europeans (P = 0.77), while effect sizes were unexpectedly smaller in South Asians than Europeans (P<5.0x10-8). Our findings argue against an important contribution for population-specific or cosmopolitan genetic variants underlying the increased risk of central obesity in South Asians compared to Europeans. PMID:27195708
Sanchez-Dominguez, Celia N.; Reyes-Lopez, Miguel A.; Bustamante, Adriana; Cerda-Flores, Ricardo M.; Villalobos-Torres, Maria del C.; Gallardo-Blanco, Hugo L.; Rojas-Martinez, Augusto; Martinez-Rodriguez, Herminia G.; Barrera-Saldaña, Hugo A.; Ortiz-Lopez, Rocio
2014-01-01
Environmental and genetic factors may modify or contribute to the phenotypic differences observed in multigenic and monogenic diseases, such as cystic fibrosis (CF). An analysis of modifier genes can be helpful for estimating patient prognosis and directing preventive care. The aim of this study is to determine the association between seven genetic variants of four modifier genes and CF by comparing their corresponding allelic and genotypic frequencies in CF patients (n = 81) and control subjects (n = 104). Genetic variants of MBL2 exon 1 (A, B, C and D), the IL-8 promoter (−251 A/T), the TNFα promoter (TNF1/TNF2), and SERPINA1 (PI*Z and PI*S) were tested in CF patients and control subjects from northeastern Mexico by PCR-RFLP. Results The TNF2 allele (P = 0.012, OR 3.43, 95% CI 1.25–9.38) was significantly associated with CF under the dominant and additive models but was not associated with CF under the recessive model. This association remained statistically significant after adjusting for multiple tests using the Bonferroni correction (P = 0.0482). The other tested variants and genotypes did not show any association with the disease. Conclusion An analysis of seven genetic variants of four modifier genes showed that one variant, the TNF2 allele, appears to be significantly associated with CF in Mexican patients. PMID:24603877
Analysis of Plasminogen Genetic Variants in Multiple Sclerosis Patients
Sadovnick, A. Dessa; Traboulsee, Anthony L.; Bernales, Cecily Q.; Ross, Jay P.; Forwell, Amanda L.; Yee, Irene M.; Guillot-Noel, Lena; Fontaine, Bertrand; Cournu-Rebeix, Isabelle; Alcina, Antonio; Fedetz, Maria; Izquierdo, Guillermo; Matesanz, Fuencisla; Hilven, Kelly; Dubois, Bénédicte; Goris, An; Astobiza, Ianire; Alloza, Iraide; Antigüedad, Alfredo; Vandenbroeck, Koen; Akkad, Denis A.; Aktas, Orhan; Blaschke, Paul; Buttmann, Mathias; Chan, Andrew; Epplen, Joerg T.; Gerdes, Lisa-Ann; Kroner, Antje; Kubisch, Christian; Kümpfel, Tania; Lohse, Peter; Rieckmann, Peter; Zettl, Uwe K.; Zipp, Frauke; Bertram, Lars; Lill, Christina M; Fernandez, Oscar; Urbaneja, Patricia; Leyva, Laura; Alvarez-Cermeño, Jose Carlos; Arroyo, Rafael; Garagorri, Aroa M.; García-Martínez, Angel; Villar, Luisa M.; Urcelay, Elena; Malhotra, Sunny; Montalban, Xavier; Comabella, Manuel; Berger, Thomas; Fazekas, Franz; Reindl, Markus; Schmied, Mascha C.; Zimprich, Alexander; Vilariño-Güell, Carles
2016-01-01
Multiple sclerosis (MS) is a prevalent neurological disease of complex etiology. Here, we describe the characterization of a multi-incident MS family that nominated a rare missense variant (p.G420D) in plasminogen (PLG) as a putative genetic risk factor for MS. Genotyping of PLG p.G420D (rs139071351) in 2160 MS patients, and 886 controls from Canada, identified 10 additional probands, two sporadic patients and one control with the variant. Segregation in families harboring the rs139071351 variant, identified p.G420D in 26 out of 30 family members diagnosed with MS, 14 unaffected parents, and 12 out of 30 family members not diagnosed with disease. Despite considerably reduced penetrance, linkage analysis supports cosegregation of PLG p.G420D and disease. Genotyping of PLG p.G420D in 14446 patients, and 8797 controls from Canada, France, Spain, Germany, Belgium, and Austria failed to identify significant association with disease (P = 0.117), despite an overall higher prevalence in patients (OR = 1.32; 95% CI = 0.93–1.87). To assess whether additional rare variants have an effect on MS risk, we sequenced PLG in 293 probands, and genotyped all rare variants in cases and controls. This analysis identified nine rare missense variants, and although three of them were exclusively observed in MS patients, segregation does not support pathogenicity. PLG is a plausible biological candidate for MS owing to its involvement in immune system response, blood-brain barrier permeability, and myelin degradation. Moreover, components of its activation cascade have been shown to present increased activity or expression in MS patients compared to controls; further studies are needed to clarify whether PLG is involved in MS susceptibility. PMID:27194806
HBS1L-MYB intergenic variants modulate fetal hemoglobin via long-range MYB enhancers
Stadhouders, Ralph; Aktuna, Suleyman; Thongjuea, Supat; Aghajanirefah, Ali; Pourfarzad, Farzin; van IJcken, Wilfred; Lenhard, Boris; Rooks, Helen; Best, Steve; Menzel, Stephan; Grosveld, Frank; Thein, Swee Lay; Soler, Eric
2014-01-01
Genetic studies have identified common variants within the intergenic region (HBS1L-MYB) between GTP-binding elongation factor HBS1L and myeloblastosis oncogene MYB on chromosome 6q that are associated with elevated fetal hemoglobin (HbF) levels and alterations of other clinically important human erythroid traits. It is unclear how these noncoding sequence variants affect multiple erythrocyte characteristics. Here, we determined that several HBS1L-MYB intergenic variants affect regulatory elements that are occupied by key erythroid transcription factors within this region. These elements interact with MYB, a critical regulator of erythroid development and HbF levels. We found that several HBS1L-MYB intergenic variants reduce transcription factor binding, affecting long-range interactions with MYB and MYB expression levels. These data provide a functional explanation for the genetic association of HBS1L-MYB intergenic polymorphisms with human erythroid traits and HbF levels. Our results further designate MYB as a target for therapeutic induction of HbF to ameliorate sickle cell and β-thalassemia disease severity. PMID:24614105
Methods for meta-analysis of multiple traits using GWAS summary statistics.
Ray, Debashree; Boehnke, Michael
2018-03-01
Genome-wide association studies (GWAS) for complex diseases have focused primarily on single-trait analyses for disease status and disease-related quantitative traits. For example, GWAS on risk factors for coronary artery disease analyze genetic associations of plasma lipids such as total cholesterol, LDL-cholesterol, HDL-cholesterol, and triglycerides (TGs) separately. However, traits are often correlated and a joint analysis may yield increased statistical power for association over multiple univariate analyses. Recently several multivariate methods have been proposed that require individual-level data. Here, we develop metaUSAT (where USAT is unified score-based association test), a novel unified association test of a single genetic variant with multiple traits that uses only summary statistics from existing GWAS. Although the existing methods either perform well when most correlated traits are affected by the genetic variant in the same direction or are powerful when only a few of the correlated traits are associated, metaUSAT is designed to be robust to the association structure of correlated traits. metaUSAT does not require individual-level data and can test genetic associations of categorical and/or continuous traits. One can also use metaUSAT to analyze a single trait over multiple studies, appropriately accounting for overlapping samples, if any. metaUSAT provides an approximate asymptotic P-value for association and is computationally efficient for implementation at a genome-wide level. Simulation experiments show that metaUSAT maintains proper type-I error at low error levels. It has similar and sometimes greater power to detect association across a wide array of scenarios compared to existing methods, which are usually powerful for some specific association scenarios only. When applied to plasma lipids summary data from the METSIM and the T2D-GENES studies, metaUSAT detected genome-wide significant loci beyond the ones identified by univariate analyses. Evidence from larger studies suggest that the variants additionally detected by our test are, indeed, associated with lipid levels in humans. In summary, metaUSAT can provide novel insights into the genetic architecture of a common disease or traits. © 2017 WILEY PERIODICALS, INC.
Debnath, Monojit; Mitra, Bikash; Bera, Nirmal Kumar; Chaudhuri, Tapas Kumar; Zhang, Ya-ping
2013-02-01
Schizophrenia is a chronic debilitating neuropsychiatric disorder with complex etiopathology. Growing evidence suggests a significant role of chronic low grade inflammation in the pathophysiology of schizophrenia. Multiple immunological, genetic polymorphism and gene expression studies have established crucial roles of certain pro-inflammatory cytokines in the immune-mediated risk of schizophrenia. Although genetic studies suggest some variants within the pro-inflammatory IL-1β, IL-6, and TNF-α genes conferring risk to schizophrenia, the results however have been contradictory in various populations. In the present investigation, promoter SNPs of IL-6 (-174 G>C) and TNF-α (-238 G>A) genes have been studied to evaluate whether these variants contribute to schizophrenia susceptibility in Indian Bengalee population. Genotyping of the above SNPs was done in 100 well characterized and confirmed cases of paranoid schizophrenia and equal number of healthy donors belonging to the same ethnic group by using ABI 3730 Genetic Analyzer. No significant differences in genotype as well as allele frequencies were observed for IL-6 and TNF-α variants between the patient and control groups. Copyright © 2012 Elsevier Ltd. All rights reserved.
Advances and challenges in hereditary cancer pharmacogenetics.
Cascorbi, Ingolf; Werk, Anneke Nina
2017-01-01
Cancer pharmacogenetics usually considers tumor-specific targets. However, hereditary genetic variants may interfere with the pharmacokinetics of antimetabolites and other anti-cancer drugs, which may lead to severe adverse events. Areas covered: Here, the impact of hereditary genes considered in drug labels such as thiopurine S-methyltransferase (TPMT), UDP-glucuronosyltransferase 1A1 (UTG1A1) and dihydropyrimidine dehydrogenase (DPYD) are discussed with respect to guidelines of the Clinical Pharmacogenetics Implementation Consortium (CPIC). Moreover, the association between genetic variants of drug transporters with the clinical outcome is comprehensively discussed. Expert opinion: Precision therapy in the field of oncology is developing tremendously. There are a number of somatic tumor genetic markers that are indicative for treatment with anti-cancer drugs. By contrast, for some hereditary variants, recommendations have been developed. Although we have vast knowledge on the association between drug transporter variants and clinical outcome, the overall data is inconsistent and the predictability of the related phenotype is low. Further developments in research may lead to the discovery of rare, but functionally relevant single nucleotide polymorphisms and a better understanding of multiple genomic, epigenomic as well as phenotypic factors, contributing to drug response in malignancies.
Sun Exposure, Vitamin D Receptor Polymorphisms FokI and BsmI and Risk of Multiple Primary Melanoma
Mandelcorn-Monson, Rochelle; Marrett, Loraine; Kricker, Anne; Armstrong, Bruce K.; Orlow, Irene; Goumas, Chris; Paine, Susan; Rosso, Stefano; Thomas, Nancy; Millikan, Robert C.; Pole, Jason D.; Cotignola, Javier; Rosen, Cheryl; Kanetsky, Peter A.; Lee-Taylor, Julia; Begg, Colin B.; Berwick, Marianne
2011-01-01
Sunlight exposure increases risk of melanoma. Sunlight also potentiates cutaneous synthesis of vitamin D, which can inhibit melanoma cell growth and promote apoptosis. Vitamin D effects are mediated through the vitamin D receptor (VDR). We hypothesized that genetic variation in VDR affects the relationship of sun exposure to risk of a further melanoma in people who have already had one. We investigated the interaction between VDR polymorphisms and sun exposure in a population-based multinational study comparing 1138 patients with a multiple (second or subsequent) primary melanoma (cases) to 2151 patients with a first primary melanoma (controls); essentially a case-control study of melanoma in a population of melanoma survivors. Sun exposure was assessed using a questionnaire and interview, and was shown to be associated with multiple primary melanoma. VDR was genotyped at the FokI and BsmI loci and the main effects of variants at these loci and their interactions with sun exposure were analyzed. Only the BsmI variant was associated with multiple primary melanoma (OR = 1.27, 95% CI 0.99-1.62 for the homozygous variant genotype). Joint effects analyses showed highest ORs in the high exposure, homozygous variant BsmI genotype category for each sun exposure variable. Stratified analyses showed somewhat higher ORs for the homozygous BsmI variant genotype in people with high sun exposure than with low sun exposure. P values for interaction, however, were high. These results suggest that risk of multiple primary melanoma is increased in people who have the BsmI variant of VDR. PMID:21612999
Type 2 diabetes susceptibility genes on chromosome 1q21-24.
Hasstedt, S J; Chu, W S; Das, S K; Wang, H; Elbein, S C
2008-03-01
Type 2 diabetes (T2D) has been linked to chromosome 1q21-24 in multiple samples, including a Utah family sample. Variants in 13 of the numerous candidate genes in the 1q region were tested for association with T2D in a Utah case-control sample. The most promising, 19 variants in 6 candidates, were genotyped on the Utah family sample. Herein, we tested the 19 variants individually and in pairs for an effect on T2D risk in family members using a logistic regression model that accounted for gender, age, and BMI and attributed residual genetic effects to a polygenic component. Seven variants increased risk significantly through 5 pairs of interactions. The significant variant pairs were apolipoprotein A-II (APOA2) rs6413453 interacting with calsequestrin 1 (CASQ1) rs617698, dual specificity phosphatase 12 (DUSP12) rs1503814, and retinoid X receptor gamma (RXRG) rs10918169, a poly-T insertion-deletion polymorphism in liver pyruvate kinase (PKLR) interacting with APOA2 rs12143180, and DUSP12 rs1027702 interacting with RXRG rs10918169. Genotypes of these 5 variant pairs accounted for 25.8% of the genetic variance in T2D in these pedigrees.
Gene genealogies for genetic association mapping, with application to Crohn's disease
Burkett, Kelly M.; Greenwood, Celia M. T.; McNeney, Brad; Graham, Jinko
2013-01-01
A gene genealogy describes relationships among haplotypes sampled from a population. Knowledge of the gene genealogy for a set of haplotypes is useful for estimation of population genetic parameters and it also has potential application in finding disease-predisposing genetic variants. As the true gene genealogy is unknown, Markov chain Monte Carlo (MCMC) approaches have been used to sample genealogies conditional on data at multiple genetic markers. We previously implemented an MCMC algorithm to sample from an approximation to the distribution of the gene genealogy conditional on haplotype data. Our approach samples ancestral trees, recombination and mutation rates at a genomic focal point. In this work, we describe how our sampler can be used to find disease-predisposing genetic variants in samples of cases and controls. We use a tree-based association statistic that quantifies the degree to which case haplotypes are more closely related to each other around the focal point than control haplotypes, without relying on a disease model. As the ancestral tree is a latent variable, so is the tree-based association statistic. We show how the sampler can be used to estimate the posterior distribution of the latent test statistic and corresponding latent p-values, which together comprise a fuzzy p-value. We illustrate the approach on a publicly-available dataset from a study of Crohn's disease that consists of genotypes at multiple SNP markers in a small genomic region. We estimate the posterior distribution of the tree-based association statistic and the recombination rate at multiple focal points in the region. Reassuringly, the posterior mean recombination rates estimated at the different focal points are consistent with previously published estimates. The tree-based association approach finds multiple sub-regions where the case haplotypes are more genetically related than the control haplotypes, and that there may be one or multiple disease-predisposing loci. PMID:24348515
Tanskanen, Tomas; van den Berg, Linda; Välimäki, Niko; Aavikko, Mervi; Ness-Jensen, Eivind; Hveem, Kristian; Wettergren, Yvonne; Bexe Lindskog, Elinor; Tõnisson, Neeme; Metspalu, Andres; Silander, Kaisa; Orlando, Giulia; Law, Philip J; Tuupanen, Sari; Gylfe, Alexandra E; Hänninen, Ulrika A; Cajuso, Tatiana; Kondelin, Johanna; Sarin, Antti-Pekka; Pukkala, Eero; Jousilahti, Pekka; Salomaa, Veikko; Ripatti, Samuli; Palotie, Aarno; Järvinen, Heikki; Renkonen-Sinisalo, Laura; Lepistö, Anna; Böhm, Jan; Mecklin, Jukka-Pekka; Al-Tassan, Nada A; Palles, Claire; Martin, Lynn; Barclay, Ella; Tenesa, Albert; Farrington, Susan M; Timofeeva, Maria N; Meyer, Brian F; Wakil, Salma M; Campbell, Harry; Smith, Christopher G; Idziaszczyk, Shelley; Maughan, Tim S; Kaplan, Richard; Kerr, Rachel; Kerr, David; Buchanan, Daniel D; Win, Aung K; Hopper, John; Jenkins, Mark A; Newcomb, Polly A; Gallinger, Steve; Conti, David; Schumacher, Fredrick R; Casey, Graham; Cheadle, Jeremy P; Dunlop, Malcolm G; Tomlinson, Ian P; Houlston, Richard S; Palin, Kimmo; Aaltonen, Lauri A
2018-02-01
Genome-wide association studies have been successful in elucidating the genetic basis of colorectal cancer (CRC), but there remains unexplained variability in genetic risk. To identify new risk variants and to confirm reported associations, we conducted a genome-wide association study in 1,701 CRC cases and 14,082 cancer-free controls from the Finnish population. A total of 9,068,015 genetic variants were imputed and tested, and 30 promising variants were studied in additional 11,647 cases and 12,356 controls of European ancestry. The previously reported association between the single-nucleotide polymorphism (SNP) rs992157 (2q35) and CRC was independently replicated (p = 2.08 × 10 -4 ; OR, 1.14; 95% CI, 1.06-1.23), and it was genome-wide significant in combined analysis (p = 1.50 × 10 -9 ; OR, 1.12; 95% CI, 1.08-1.16). Variants at 2q35, 6p21.2, 8q23.3, 8q24.21, 10q22.3, 10q24.2, 11q13.4, 11q23.1, 14q22.2, 15q13.3, 18q21.1, 20p12.3 and 20q13.33 were associated with CRC in the Finnish population (false discovery rate < 0.1), but new risk loci were not found. These results replicate the effects of multiple loci on the risk of CRC and identify shared risk alleles between the Finnish population isolate and outbred populations. © 2017 UICC.
Association of genetic variants in RAB23 and ANXA11 with uveitis in sarcoidosis
Davoudi, Samaneh; Chang, Victoria S.; Navarro-Gomez, Daniel; Stanwyck, Lynn K.; Sevgi, Damla Duriye; Papavasileiou, Evangelia; Ren, Aiai; Uchiyama, Eduardo; Sullivan, Lynn; Lobo, Ann-Marie; Papaliodis, George N.
2018-01-01
Purpose Uveitis occurs in a subset of patients with sarcoidosis. The purpose of this study was to determine whether genetic variants that have been associated previously with overall sarcoidosis are associated with increased risk of developing uveitis. Methods Seventy-seven subjects were enrolled, including 45 patients diagnosed with sarcoidosis-related uveitis as cases and 32 patients with systemic sarcoidosis without ocular involvement as controls. Thirty-eight single nucleotide polymorphisms (SNPs) previously associated with sarcoidosis, sarcoidosis severity, or other organ-specific sarcoidosis involvement were identified. Allele frequencies in ocular sarcoidosis cases versus controls were compared using the chi-square test, and p values were corrected for multiple hypotheses testing using permutation. All analyses were conducted with PLINK. Results SNPs rs1040461 and rs61860052, in ras-related protein RAS23 (RAB23) and annexin A11 (ANXA11) genes, respectively, were associated with sarcoidosis-associated uveitis. The T allele of rs1040461 and the A allele of rs61860052 were found to be more prevalent in ocular sarcoidosis cases. These associations remained after correction for the multiple hypotheses tested (p=0.01 and p=0.02). In a subanalysis of Caucasian Americans only, two additional variants within the major histocompatibility complex (MHC) genes on chromosome 6, in HLA-DRB5 and HLA-DRB1, were associated with uveitis as well (p=0.009 and p=0.04). Conclusions Genetic variants in RAB23 and ANXA11 genes were associated with an increased risk of sarcoidosis-associated uveitis. These loci have previously been associated with overall sarcoidosis risk. PMID:29416296
2014-01-01
In this study, we analyze the Genetic Analysis Workshop 18 (GAW18) data to identify regions of single-nucleotide polymorphisms (SNPs), which significantly influence hypertension status among individuals. We have studied the marginal impact of these regions on disease status in the past, but we extend the method to deal with environmental factors present in data collected over several exam periods. We consider the respective interactions between such traits as smoking status and age with the genetic information and hope to augment those genetic regions deemed influential marginally with those that contribute via an interactive effect. In particular, we focus only on rare variants and apply a procedure to combine signal among rare variants in a number of "fixed bins" along the chromosome. We extend the procedure in Agne et al [1] to incorporate environmental factors by dichotomizing subjects via traits such as smoking status and age, running the marginal procedure among each respective category (i.e., smokers or nonsmokers), and then combining their scores into a score for interaction. To avoid overlap of subjects, we examine each exam period individually. Out of a possible 629 fixed-bin regions in chromosome 3, we observe that 11 show up in multiple exam periods for gene-smoking score. Fifteen regions exhibit significance for multiple exam periods for gene-age score, with 4 regions deemed significant for all 3 exam periods. The procedure pinpoints SNPs in 8 "answer" genes, with 5 of these showing up as significant in multiple testing schemes (Gene-Smoking, Gene-Age for Exams 1, 2, and 3). PMID:25519400
Genetic modifiers of CHEK2*1100delC-associated breast cancer risk.
Muranen, Taru A; Greco, Dario; Blomqvist, Carl; Aittomäki, Kristiina; Khan, Sofia; Hogervorst, Frans; Verhoef, Senno; Pharoah, Paul D P; Dunning, Alison M; Shah, Mitul; Luben, Robert; Bojesen, Stig E; Nordestgaard, Børge G; Schoemaker, Minouk; Swerdlow, Anthony; García-Closas, Montserrat; Figueroa, Jonine; Dörk, Thilo; Bogdanova, Natalia V; Hall, Per; Li, Jingmei; Khusnutdinova, Elza; Bermisheva, Marina; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Investigators, Nbcs; Peto, Julian; Dos Santos Silva, Isabel; Couch, Fergus J; Olson, Janet E; Hillemans, Peter; Park-Simon, Tjoung-Won; Brauch, Hiltrud; Hamann, Ute; Burwinkel, Barbara; Marme, Frederik; Meindl, Alfons; Schmutzler, Rita K; Cox, Angela; Cross, Simon S; Sawyer, Elinor J; Tomlinson, Ian; Lambrechts, Diether; Moisse, Matthieu; Lindblom, Annika; Margolin, Sara; Hollestelle, Antoinette; Martens, John W M; Fasching, Peter A; Beckmann, Matthias W; Andrulis, Irene L; Knight, Julia A; Investigators, kConFab/Aocs; Anton-Culver, Hoda; Ziogas, Argyrios; Giles, Graham G; Milne, Roger L; Brenner, Hermann; Arndt, Volker; Mannermaa, Arto; Kosma, Veli-Matti; Chang-Claude, Jenny; Rudolph, Anja; Devilee, Peter; Seynaeve, Caroline; Hopper, John L; Southey, Melissa C; John, Esther M; Whittemore, Alice S; Bolla, Manjeet K; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Easton, Douglas F; Schmidt, Marjanka K; Nevanlinna, Heli
2017-05-01
CHEK2*1100delC is a founder variant in European populations that confers a two- to threefold increased risk of breast cancer (BC). Epidemiologic and family studies have suggested that the risk associated with CHEK2*1100delC is modified by other genetic factors in a multiplicative fashion. We have investigated this empirically using data from the Breast Cancer Association Consortium (BCAC). Using genotype data from 39,139 (624 1100delC carriers) BC patients and 40,063 (224) healthy controls from 32 BCAC studies, we analyzed the combined risk effects of CHEK2*1100delC and 77 common variants in terms of a polygenic risk score (PRS) and pairwise interaction. The PRS conferred odds ratios (OR) of 1.59 (95% CI: 1.21-2.09) per standard deviation for BC for CHEK2*1100delC carriers and 1.58 (1.55-1.62) for noncarriers. No evidence of deviation from the multiplicative model was found. The OR for the highest quintile of the PRS was 2.03 (0.86-4.78) for CHEK2*1100delC carriers, placing them in the high risk category according to UK NICE guidelines. The OR for the lowest quintile was 0.52 (0.16-1.74), indicating a lifetime risk close to the population average. Our results confirm the multiplicative nature of risk effects conferred by CHEK2*1100delC and the common susceptibility variants. Furthermore, the PRS could identify carriers at a high lifetime risk for clinical actions.Genet Med advance online publication 06 October 2016.
Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk
Curtin, Karen; Rajamanickam, Venkatesh; Jayabalan, David; Atanackovic, Djordje; Rajkumar, S. Vincent; Kumar, Shaji; Slager, Susan; Galia, Perrine; Demangel, Delphine; Salama, Mohamed; Joseph, Vijai; Lipkin, Steven M.; Dumontet, Charles; Vachon, Celine M.
2018-01-01
The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance–a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits. PMID:29389935
Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk.
Waller, Rosalie G; Darlington, Todd M; Wei, Xiaomu; Madsen, Michael J; Thomas, Alun; Curtin, Karen; Coon, Hilary; Rajamanickam, Venkatesh; Musinsky, Justin; Jayabalan, David; Atanackovic, Djordje; Rajkumar, S Vincent; Kumar, Shaji; Slager, Susan; Middha, Mridu; Galia, Perrine; Demangel, Delphine; Salama, Mohamed; Joseph, Vijai; McKay, James; Offit, Kenneth; Klein, Robert J; Lipkin, Steven M; Dumontet, Charles; Vachon, Celine M; Camp, Nicola J
2018-02-01
The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance-a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.
Shea, A A; Bernhards, R C; Cote, C K; Chase, C J; Koehler, J W; Klimko, C P; Ladner, J T; Rozak, D A; Wolcott, M J; Fetterer, D P; Kern, S J; Koroleva, G I; Lovett, S P; Palacios, G F; Toothman, R G; Bozue, J A; Worsham, P L; Welkos, S L
2017-01-01
Burkholderia pseudomallei (Bp), the agent of melioidosis, causes disease ranging from acute and rapidly fatal to protracted and chronic. Bp is highly infectious by aerosol, can cause severe disease with nonspecific symptoms, and is naturally resistant to multiple antibiotics. However, no vaccine exists. Unlike many Bp strains, which exhibit random variability in traits such as colony morphology, Bp strain MSHR5848 exhibited two distinct and relatively stable colony morphologies on sheep blood agar plates: a smooth, glossy, pale yellow colony and a flat, rough, white colony. Passage of the two variants, designated "Smooth" and "Rough", under standard laboratory conditions produced cultures composed of > 99.9% of the single corresponding type; however, both could switch to the other type at different frequencies when incubated in certain nutritionally stringent or stressful growth conditions. These MSHR5848 derivatives were extensively characterized to identify variant-associated differences. Microscopic and colony morphology differences on six differential media were observed and only the Rough variant metabolized sugars in selective agar. Antimicrobial susceptibilities and lipopolysaccharide (LPS) features were characterized and phenotype microarray profiles revealed distinct metabolic and susceptibility disparities between the variants. Results using the phenotype microarray system narrowed the 1,920 substrates to a subset which differentiated the two variants. Smooth grew more rapidly in vitro than Rough, yet the latter exhibited a nearly 10-fold lower lethal dose for mice than Smooth. Finally, the Smooth variant was phagocytosed and replicated to a greater extent and was more cytotoxic than Rough in macrophages. In contrast, multiple locus sequence type (MLST) analysis, ribotyping, and whole genome sequence analysis demonstrated the variants' genetic conservation; only a single consistent genetic difference between the two was identified for further study. These distinct differences shown by two variants of a Bp strain will be leveraged to better understand the mechanism of Bp phenotypic variability and to possibly identify in vitro markers of infection.
Constable, Fiona E.; Nancarrow, Narelle; Plummer, Kim M.; Rodoni, Brendan
2017-01-01
PCR amplicon next generation sequencing (NGS) analysis offers a broadly applicable and targeted approach to detect populations of both high- or low-frequency virus variants in one or more plant samples. In this study, amplicon NGS was used to explore the diversity of the tripartite genome virus, Prunus necrotic ringspot virus (PNRSV) from 53 PNRSV-infected trees using amplicons from conserved gene regions of each of PNRSV RNA1, RNA2 and RNA3. Sequencing of the amplicons from 53 PNRSV-infected trees revealed differing levels of polymorphism across the three different components of the PNRSV genome with a total number of 5040, 2083 and 5486 sequence variants observed for RNA1, RNA2 and RNA3 respectively. The RNA2 had the lowest diversity of sequences compared to RNA1 and RNA3, reflecting the lack of flexibility tolerated by the replicase gene that is encoded by this RNA component. Distinct PNRSV phylo-groups, consisting of closely related clusters of sequence variants, were observed in each of PNRSV RNA1, RNA2 and RNA3. Most plant samples had a single phylo-group for each RNA component. Haplotype network analysis showed that smaller clusters of PNRSV sequence variants were genetically connected to the largest sequence variant cluster within a phylo-group of each RNA component. Some plant samples had sequence variants occurring in multiple PNRSV phylo-groups in at least one of each RNA and these phylo-groups formed distinct clades that represent PNRSV genetic strains. Variants within the same phylo-group of each Prunus plant sample had ≥97% similarity and phylo-groups within a Prunus plant sample and between samples had less ≤97% similarity. Based on the analysis of diversity, a definition of a PNRSV genetic strain was proposed. The proposed definition was applied to determine the number of PNRSV genetic strains in each of the plant samples and the complexity in defining genetic strains in multipartite genome viruses was explored. PMID:28632759
Overexpression of the Cytokine BAFF and Autoimmunity Risk.
Steri, Maristella; Orrù, Valeria; Idda, M Laura; Pitzalis, Maristella; Pala, Mauro; Zara, Ilenia; Sidore, Carlo; Faà, Valeria; Floris, Matteo; Deiana, Manila; Asunis, Isadora; Porcu, Eleonora; Mulas, Antonella; Piras, Maria G; Lobina, Monia; Lai, Sandra; Marongiu, Mara; Serra, Valentina; Marongiu, Michele; Sole, Gabriella; Busonero, Fabio; Maschio, Andrea; Cusano, Roberto; Cuccuru, Gianmauro; Deidda, Francesca; Poddie, Fausto; Farina, Gabriele; Dei, Mariano; Virdis, Francesca; Olla, Stefania; Satta, Maria A; Pani, Mario; Delitala, Alessandro; Cocco, Eleonora; Frau, Jessica; Coghe, Giancarlo; Lorefice, Lorena; Fenu, Giuseppe; Ferrigno, Paola; Ban, Maria; Barizzone, Nadia; Leone, Maurizio; Guerini, Franca R; Piga, Matteo; Firinu, Davide; Kockum, Ingrid; Lima Bomfim, Izaura; Olsson, Tomas; Alfredsson, Lars; Suarez, Ana; Carreira, Patricia E; Castillo-Palma, Maria J; Marcus, Joseph H; Congia, Mauro; Angius, Andrea; Melis, Maurizio; Gonzalez, Antonio; Alarcón Riquelme, Marta E; da Silva, Berta M; Marchini, Maurizio; Danieli, Maria G; Del Giacco, Stefano; Mathieu, Alessandro; Pani, Antonello; Montgomery, Stephen B; Rosati, Giulio; Hillert, Jan; Sawcer, Stephen; D'Alfonso, Sandra; Todd, John A; Novembre, John; Abecasis, Gonçalo R; Whalen, Michael B; Marrosu, Maria G; Meloni, Alessandra; Sanna, Serena; Gorospe, Myriam; Schlessinger, David; Fiorillo, Edoardo; Zoledziewska, Magdalena; Cucca, Francesco
2017-04-27
Genomewide association studies of autoimmune diseases have mapped hundreds of susceptibility regions in the genome. However, only for a few association signals has the causal gene been identified, and for even fewer have the causal variant and underlying mechanism been defined. Coincident associations of DNA variants affecting both the risk of autoimmune disease and quantitative immune variables provide an informative route to explore disease mechanisms and drug-targetable pathways. Using case-control samples from Sardinia, Italy, we performed a genomewide association study in multiple sclerosis followed by TNFSF13B locus-specific association testing in systemic lupus erythematosus (SLE). Extensive phenotyping of quantitative immune variables, sequence-based fine mapping, cross-population and cross-phenotype analyses, and gene-expression studies were used to identify the causal variant and elucidate its mechanism of action. Signatures of positive selection were also investigated. A variant in TNFSF13B, encoding the cytokine and drug target B-cell activating factor (BAFF), was associated with multiple sclerosis as well as SLE. The disease-risk allele was also associated with up-regulated humoral immunity through increased levels of soluble BAFF, B lymphocytes, and immunoglobulins. The causal variant was identified: an insertion-deletion variant, GCTGT→A (in which A is the risk allele), yielded a shorter transcript that escaped microRNA inhibition and increased production of soluble BAFF, which in turn up-regulated humoral immunity. Population genetic signatures indicated that this autoimmunity variant has been evolutionarily advantageous, most likely by augmenting resistance to malaria. A TNFSF13B variant was associated with multiple sclerosis and SLE, and its effects were clarified at the population, cellular, and molecular levels. (Funded by the Italian Foundation for Multiple Sclerosis and others.).
Peters, James E.; Lyons, Paul A.; Lee, James C.; Richard, Arianne C.; Fortune, Mary D.; Newcombe, Paul J.; Richardson, Sylvia; Smith, Kenneth G. C.
2016-01-01
Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases. PMID:27015630
Cerebral palsy: causes, pathways, and the role of genetic variants.
MacLennan, Alastair H; Thompson, Suzanna C; Gecz, Jozef
2015-12-01
Cerebral palsy (CP) is heterogeneous with different clinical types, comorbidities, brain imaging patterns, causes, and now also heterogeneous underlying genetic variants. Few are solely due to severe hypoxia or ischemia at birth. This common myth has held back research in causation. The cost of litigation has devastating effects on maternity services with unnecessarily high cesarean delivery rates and subsequent maternal morbidity and mortality. CP rates have remained the same for 50 years despite a 6-fold increase in cesarean birth. Epidemiological studies have shown that the origins of most CP are prior to labor. Increased risk is associated with preterm delivery, congenital malformations, intrauterine infection, fetal growth restriction, multiple pregnancy, and placental abnormalities. Hypoxia at birth may be primary or secondary to preexisting pathology and international criteria help to separate the few cases of CP due to acute intrapartum hypoxia. Until recently, 1-2% of CP (mostly familial) had been linked to causative mutations. Recent genetic studies of sporadic CP cases using new-generation exome sequencing show that 14% of cases have likely causative single-gene mutations and up to 31% have clinically relevant copy number variations. The genetic variants are heterogeneous and require function investigations to prove causation. Whole genome sequencing, fine scale copy number variant investigations, and gene expression studies may extend the percentage of cases with a genetic pathway. Clinical risk factors could act as triggers for CP where there is genetic susceptibility. These new findings should refocus research about the causes of these complex and varied neurodevelopmental disorders. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
Masson, Emmanuelle; Chen, Jian-Min; Audrézet, Marie-Pierre; Cooper, David N; Férec, Claude
2013-01-01
Idiopathic chronic pancreatitis (ICP) has traditionally been defined as chronic pancreatitis in the absence of any obvious precipitating factors (e.g. alcohol abuse) and family history of the disease. Studies over the past 15 years have revealed that ICP has a highly complex genetic architecture involving multiple gene loci. Here, we have attempted to provide a conservative assessment of the major genetic causes of ICP in a sample of 253 young French ICP patients. For the first time, conventional types of mutation (comprising coding sequence variants and variants at intron/exon boundaries) and gross genomic rearrangements were screened for in all four major pancreatitis genes, PRSS1, SPINK1, CTRC and CFTR. For the purposes of the study, synonymous, intronic and 5'- or 3'-untranslated region variants were excluded from the analysis except where there was persuasive evidence of functional consequences. The remaining sequence variants/genotypes were classified into causative, contributory or neutral categories by consideration of (i) their allele frequencies in patient and normal control populations, (ii) their presumed or experimentally confirmed functional effects, (iii) the relative importance of their associated genes in the pathogenesis of chronic pancreatitis and (iv) gene-gene interactions wherever applicable. Adoption of this strategy allowed us to assess the pathogenic relevance of specific variants/genotypes to their respective carriers to an unprecedented degree. The genetic cause of ICP could be assigned in 23.7% of individuals in the study group. A strong genetic susceptibility factor was also present in an additional 24.5% of cases. Taken together, up to 48.2% of the studied ICP patients were found to display evidence of a genetic basis for their pancreatitis. Whereas these particular proportions may not be extrapolable to all ICP patients, the approach employed should serve as a useful framework for acquiring a better understanding of the role of genetic factors in causing this oligogenic disease.
Olney, Nicholas T.; Spina, Salvatore; Miller, Bruce L.
2017-01-01
Frontotemporal Dementia (FTD) is a heterogeneous disorder with distinct clinical phenotypes associated with multiple neuropathologic entities. Presently, the term FTD encompasses clinical disorders that include changes in behavior, language, executive control and often motor symptoms. The core FTD spectrum disorders include: behavioral variant FTD (bvFTD), nonfluent/agrammatic variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA). Related FTD disorders include frontotemporal dementia with motor neuron disease (FTD-MND), progressive supranuclear palsy syndrome (PSP-S) and corticobasal syndrome (CBS). In this chapter we will discuss the clinic presentation, diagnostic criteria, neuropathology, genetics and treatments of these disorders. PMID:28410663
A Shared Genetic Basis for Self-Limited Delayed Puberty and Idiopathic Hypogonadotropic Hypogonadism
Zhu, Jia; Choa, Ruth E.-Y.; Guo, Michael H.; Plummer, Lacey; Buck, Cassandra; Palmert, Mark R.; Hirschhorn, Joel N.; Seminara, Stephanie B.
2015-01-01
Context: Delayed puberty (DP) is a common issue and, in the absence of an underlying condition, is typically self limited. Alhough DP seems to be heritable, no specific genetic cause for DP has yet been reported. In contrast, many genetic causes have been found for idiopathic hypogonadotropic hypogonadism (IHH), a rare disorder characterized by absent or stalled pubertal development. Objective: The objective of this retrospective study, conducted at academic medical centers, was to determine whether variants in IHH genes contribute to the pathogenesis of DP. Subjects and Outcome Measures: Potentially pathogenic variants in IHH genes were identified in two cohorts: 1) DP family members of an IHH proband previously found to have a variant in an IHH gene, with unaffected family members serving as controls, and 2) DP individuals with no family history of IHH, with ethnically matched control subjects drawn from the Exome Aggregation Consortium. Results: In pedigrees with an IHH proband, the proband's variant was shared by 53% (10/19) of DP family members vs 12% (4/33) of unaffected family members (P = .003). In DP subjects with no family history of IHH, 14% (8/56) had potentially pathogenic variants in IHH genes vs 5.6% (1 907/33 855) of controls (P = .01). Potentially pathogenic variants were found in multiple DP subjects for the genes IL17RD and TAC3. Conclusions: These findings suggest that variants in IHH genes can contribute to the pathogenesis of self-limited DP. Thus, at least in some cases, self-limited DP shares an underlying pathophysiology with IHH. PMID:25636053
Early developmental gene enhancers affect subcortical volumes in the adult human brain.
Becker, Martin; Guadalupe, Tulio; Franke, Barbara; Hibar, Derrek P; Renteria, Miguel E; Stein, Jason L; Thompson, Paul M; Francks, Clyde; Vernes, Sonja C; Fisher, Simon E
2016-05-01
Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype-phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations. Hum Brain Mapp 37:1788-1800, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Wang, Julia; Al-Ouran, Rami; Hu, Yanhui; Kim, Seon-Young; Wan, Ying-Wooi; Wangler, Michael F; Yamamoto, Shinya; Chao, Hsiao-Tuan; Comjean, Aram; Mohr, Stephanie E; Perrimon, Norbert; Liu, Zhandong; Bellen, Hugo J
2017-06-01
One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Genomic analysis identifies masqueraders of full-term cerebral palsy.
Takezawa, Yusuke; Kikuchi, Atsuo; Haginoya, Kazuhiro; Niihori, Tetsuya; Numata-Uematsu, Yurika; Inui, Takehiko; Yamamura-Suzuki, Saeko; Miyabayashi, Takuya; Anzai, Mai; Suzuki-Muromoto, Sato; Okubo, Yukimune; Endo, Wakaba; Togashi, Noriko; Kobayashi, Yasuko; Onuma, Akira; Funayama, Ryo; Shirota, Matsuyuki; Nakayama, Keiko; Aoki, Yoko; Kure, Shigeo
2018-05-01
Cerebral palsy is a common, heterogeneous neurodevelopmental disorder that causes movement and postural disabilities. Recent studies have suggested genetic diseases can be misdiagnosed as cerebral palsy. We hypothesized that two simple criteria, that is, full-term births and nonspecific brain MRI findings, are keys to extracting masqueraders among cerebral palsy cases due to the following: (1) preterm infants are susceptible to multiple environmental factors and therefore demonstrate an increased risk of cerebral palsy and (2) brain MRI assessment is essential for excluding environmental causes and other particular disorders. A total of 107 patients-all full-term births-without specific findings on brain MRI were identified among 897 patients diagnosed with cerebral palsy who were followed at our center. DNA samples were available for 17 of the 107 cases for trio whole-exome sequencing and array comparative genomic hybridization. We prioritized variants in genes known to be relevant in neurodevelopmental diseases and evaluated their pathogenicity according to the American College of Medical Genetics guidelines. Pathogenic/likely pathogenic candidate variants were identified in 9 of 17 cases (52.9%) within eight genes: CTNNB1 , CYP2U1 , SPAST , GNAO1 , CACNA1A , AMPD2 , STXBP1 , and SCN2A . Five identified variants had previously been reported. No pathogenic copy number variations were identified. The AMPD2 missense variant and the splice-site variants in CTNNB1 and AMPD2 were validated by in vitro functional experiments. The high rate of detecting causative genetic variants (52.9%) suggests that patients diagnosed with cerebral palsy in full-term births without specific MRI findings may include genetic diseases masquerading as cerebral palsy.
Tzeng, Jung-Ying; Zhang, Daowen; Pongpanich, Monnat; Smith, Chris; McCarthy, Mark I.; Sale, Michèle M.; Worrall, Bradford B.; Hsu, Fang-Chi; Thomas, Duncan C.; Sullivan, Patrick F.
2011-01-01
Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis. PMID:21835306
Taylor, Robert W; Pyle, Angela; Griffin, Helen; Blakely, Emma L; Duff, Jennifer; He, Langping; Smertenko, Tania; Alston, Charlotte L; Neeve, Vivienne C; Best, Andrew; Yarham, John W; Kirschner, Janbernd; Schara, Ulrike; Talim, Beril; Topaloglu, Haluk; Baric, Ivo; Holinski-Feder, Elke; Abicht, Angela; Czermin, Birgit; Kleinle, Stephanie; Morris, Andrew A M; Vassallo, Grace; Gorman, Grainne S; Ramesh, Venkateswaran; Turnbull, Douglass M; Santibanez-Koref, Mauro; McFarland, Robert; Horvath, Rita; Chinnery, Patrick F
2014-07-02
Mitochondrial disorders have emerged as a common cause of inherited disease, but their diagnosis remains challenging. Multiple respiratory chain complex defects are particularly difficult to diagnose at the molecular level because of the massive number of nuclear genes potentially involved in intramitochondrial protein synthesis, with many not yet linked to human disease. To determine the molecular basis of multiple respiratory chain complex deficiencies. We studied 53 patients referred to 2 national centers in the United Kingdom and Germany between 2005 and 2012. All had biochemical evidence of multiple respiratory chain complex defects but no primary pathogenic mitochondrial DNA mutation. Whole-exome sequencing was performed using 62-Mb exome enrichment, followed by variant prioritization using bioinformatic prediction tools, variant validation by Sanger sequencing, and segregation of the variant with the disease phenotype in the family. Presumptive causal variants were identified in 28 patients (53%; 95% CI, 39%-67%) and possible causal variants were identified in 4 (8%; 95% CI, 2%-18%). Together these accounted for 32 patients (60% 95% CI, 46%-74%) and involved 18 different genes. These included recurrent mutations in RMND1, AARS2, and MTO1, each on a haplotype background consistent with a shared founder allele, and potential novel mutations in 4 possible mitochondrial disease genes (VARS2, GARS, FLAD1, and PTCD1). Distinguishing clinical features included deafness and renal involvement associated with RMND1 and cardiomyopathy with AARS2 and MTO1. However, atypical clinical features were present in some patients, including normal liver function and Leigh syndrome (subacute necrotizing encephalomyelopathy) seen in association with TRMU mutations and no cardiomyopathy with founder SCO2 mutations. It was not possible to confidently identify the underlying genetic basis in 21 patients (40%; 95% CI, 26%-54%). Exome sequencing enhances the ability to identify potential nuclear gene mutations in patients with biochemically defined defects affecting multiple mitochondrial respiratory chain complexes. Additional study is required in independent patient populations to determine the utility of this approach in comparison with traditional diagnostic methods.
Moore, Carrie B.; Wallace, John R.; Wolfe, Daniel J.; Frase, Alex T.; Pendergrass, Sarah A.; Weiss, Kenneth M.; Ritchie, Marylyn D.
2013-01-01
Analyses investigating low frequency variants have the potential for explaining additional genetic heritability of many complex human traits. However, the natural frequencies of rare variation between human populations strongly confound genetic analyses. We have applied a novel collapsing method to identify biological features with low frequency variant burden differences in thirteen populations sequenced by the 1000 Genomes Project. Our flexible collapsing tool utilizes expert biological knowledge from multiple publicly available database sources to direct feature selection. Variants were collapsed according to genetically driven features, such as evolutionary conserved regions, regulatory regions genes, and pathways. We have conducted an extensive comparison of low frequency variant burden differences (MAF<0.03) between populations from 1000 Genomes Project Phase I data. We found that on average 26.87% of gene bins, 35.47% of intergenic bins, 42.85% of pathway bins, 14.86% of ORegAnno regulatory bins, and 5.97% of evolutionary conserved regions show statistically significant differences in low frequency variant burden across populations from the 1000 Genomes Project. The proportion of bins with significant differences in low frequency burden depends on the ancestral similarity of the two populations compared and types of features tested. Even closely related populations had notable differences in low frequency burden, but fewer differences than populations from different continents. Furthermore, conserved or functionally relevant regions had fewer significant differences in low frequency burden than regions under less evolutionary constraint. This degree of low frequency variant differentiation across diverse populations and feature elements highlights the critical importance of considering population stratification in the new era of DNA sequencing and low frequency variant genomic analyses. PMID:24385916
Hill, W D; Davies, G; Harris, S E; Hagenaars, S P; Liewald, D C; Penke, L; Gale, C R; Deary, I J
2016-12-13
Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fahrenkrog, Annette M.; Neves, Leandro G.; Resende, Jr., Marcio F. R.
Genome-wide association studies (GWAS) have been used extensively to dissect the genetic regulation of complex traits in plants. These studies have focused largely on the analysis of common genetic variants despite the abundance of rare polymorphisms in several species, and their potential role in trait variation. Here, we conducted the first GWAS in Populus deltoides, a genetically diverse keystone forest species in North America and an important short rotation woody crop for the bioenergy industry. We searched for associations between eight growth and wood composition traits, and common and low-frequency single-nucleotide polymorphisms detected by targeted resequencing of 18 153 genesmore » in a population of 391 unrelated individuals. To increase power to detect associations with low-frequency variants, multiple-marker association tests were used in combination with single-marker association tests. Significant associations were discovered for all phenotypes and are indicative that low-frequency polymorphisms contribute to phenotypic variance of several bioenergy traits. Our results suggest that both common and low-frequency variants need to be considered for a comprehensive understanding of the genetic regulation of complex traits, particularly in species that carry large numbers of rare polymorphisms. Lastly, these polymorphisms may be critical for the development of specialized plant feedstocks for bioenergy.« less
Hill, W D; Davies, G; Harris, S E; Hagenaars, S P; Davies, Gail; Deary, Ian J; Debette, Stephanie; Verbaas, Carla I; Bressler, Jan; Schuur, Maaike; Smith, Albert V; Bis, Joshua C; Bennett, David A; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosley Jr, Thomas H; Liewald, D C; Penke, L; Gale, C R; Deary, I J
2016-01-01
Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions. PMID:27959336
Genetic Analyses in Small-for-Gestational-Age Newborns.
Stalman, Susanne E; Solanky, Nita; Ishida, Miho; Alemán-Charlet, Cristina; Abu-Amero, Sayeda; Alders, Marielle; Alvizi, Lucas; Baird, William; Demetriou, Charalambos; Henneman, Peter; James, Chela; Knegt, Lia C; Leon, Lydia J; Mannens, Marcel M A M; Mul, Adi N; Nibbering, Nicole A; Peskett, Emma; Rezwan, Faisal I; Ris-Stalpers, Carrie; van der Post, Joris A M; Kamp, Gerdine A; Plötz, Frans B; Wit, Jan M; Stanier, Philip; Moore, Gudrun E; Hennekam, Raoul C
2018-03-01
Small for gestational age (SGA) can be the result of fetal growth restriction, which is associated with perinatal morbidity and mortality. Mechanisms that control prenatal growth are poorly understood. The aim of the current study was to gain more insight into prenatal growth failure and determine an effective diagnostic approach in SGA newborns. We hypothesized that one or more copy number variations (CNVs) and disturbed methylation and sequence variants may be present in genes associated with fetal growth. A prospective cohort study of subjects with a low birth weight for gestational age. The study was conducted at an academic pediatric research institute. A total of 21 SGA newborns with a mean birth weight below the first centile and a control cohort of 24 appropriate-for-gestational-age newborns were studied. Array comparative genomic hybridization, genome-wide methylation studies, and exome sequencing were performed. The numbers of CNVs, methylation disturbances, and sequence variants. The genetic analyses demonstrated three CNVs, one systematically disturbed methylation pattern, and one sequence variant explaining SGA. Additional methylation disturbances and sequence variants were present in 20 patients. In 19 patients, multiple abnormalities were found. Our results confirm the influence of a large number of mechanisms explaining dysregulation of fetal growth. We concluded that CNVs, methylation disturbances, and sequence variants all contribute to prenatal growth failure. These genetic workups can be an effective diagnostic approach in SGA newborns.
Gene-environment interplay in the etiology of psychosis.
Zwicker, Alyson; Denovan-Wright, Eileen M; Uher, Rudolf
2018-01-15
Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene-environment interactions. Only a few specific gene-environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene-environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.
Epstein-Barr virus in oral shedding of children with multiple sclerosis
Yea, Carmen; Tellier, Raymond; Chong, Patrick; Westmacott, Garrett; Marrie, Ruth Ann; Bar-Or, Amit
2013-01-01
Objective: To investigate Epstein-Barr virus (EBV) oral shedding frequency and EBV genetic diversity in pediatric patients with multiple sclerosis (MS). Methods: This was a prospective case-control study. We used PCR-based assays to detect viral DNA in the monthly mouth swabs of 22 pediatric patients with MS and 77 age- and sex-matched healthy controls. EBV-positive samples were further analyzed for sequence variation in the EBV BCRF1 (ebvIL-10) gene using direct DNA sequencing methods, and in the EBV LMP1 gene by mass spectrometry. Results: Nineteen of the 22 (86.4%) children with MS were seropositive for remote EBV infection compared to 35 out of 77 (45.5%) healthy controls (p = 0.008). Baseline analysis of mouth swabs revealed a higher proportion of EBV-positive samples from EBV-seropositive patients with MS compared to EBV-seropositive healthy controls (52.6% vs 20%, p = 0.007). Longitudinal analysis of monthly swabs revealed average EBV detection rates of 50.6% in patients with MS and 20.4% in controls (p = 0.01). The oral shedding frequencies of Herpesviruses herpes simplex virus–1, cytomegalovirus, human herpesvirus (HHV)-6, and HHV-7 did not differ between groups. Changes in the predominant EBV genetic variants were detected more frequently in patients with MS; however, no specific EBV genetic variant was preferentially associated with MS. Conclusion: Children with MS demonstrate abnormally increased rates of EBV viral reactivation and a broader range of genetic variants, suggesting a selective impairment in their immunologic control of EBV. PMID:24014504
Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong
2017-01-01
To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696
Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong
2017-02-01
To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.
Applications of the 1000 Genomes Project resources
Zheng-Bradley, Xiangqun
2017-01-01
Abstract The 1000 Genomes Project created a valuable, worldwide reference for human genetic variation. Common uses of the 1000 Genomes dataset include genotype imputation supporting Genome-wide Association Studies, mapping expression Quantitative Trait Loci, filtering non-pathogenic variants from exome, whole genome and cancer genome sequencing projects, and genetic analysis of population structure and molecular evolution. In this article, we will highlight some of the multiple ways that the 1000 Genomes data can be and has been utilized for genetic studies. PMID:27436001
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
High frequency, spontaneous motA mutations in Campylobacter jejuni strain 81-176.
Mohawk, Krystle L; Poly, Frédéric; Sahl, Jason W; Rasko, David A; Guerry, Patricia
2014-01-01
Campylobacter jejuni is an important cause of bacterial diarrhea worldwide. The pathogenesis of C. jejuni is poorly understood and complicated by phase variation of multiple surface structures including lipooligosaccharide, capsule, and flagellum. When C. jejuni strain 81-176 was plated on blood agar for single colonies, the presence of translucent, non-motile colonial variants was noted among the majority of opaque, motile colonies. High-throughput genomic sequencing of two flagellated translucent and two opaque variants as well as the parent strain revealed multiple genetic changes compared to the published genome. However, the only mutated open reading frame common between the two translucent variants and absent from the opaque variants and the parent was motA, encoding a flagellar motor protein. A total of 18 spontaneous motA mutations were found that mapped to four distinct sites in the gene, with only one class of mutation present in a phase variable region. This study exemplifies the mutative/adaptive properties of C. jejuni and demonstrates additional variability in C. jejuni beyond phase variation.
Park, Jae Hyon; Kim, Joo Hi; Jo, Kye Eun; Na, Se Whan; Eisenhut, Michael; Kronbichler, Andreas; Lee, Keum Hwa; Shin, Jae Il
2018-07-01
To provide an up-to-date summary of multiple sclerosis-susceptible gene variants and assess the noteworthiness in hopes of finding true associations, we investigated the results of 44 meta-analyses on gene variants and multiple sclerosis published through December 2016. Out of 70 statistically significant genotype associations, roughly a fifth (21%) of the comparisons showed noteworthy false-positive rate probability (FPRP) at a statistical power to detect an OR of 1.5 and at a prior probability of 10 -6 assumed for a random single nucleotide polymorphism. These associations (IRF8/rs17445836, STAT3/rs744166, HLA/rs4959093, HLA/rs2647046, HLA/rs7382297, HLA/rs17421624, HLA/rs2517646, HLA/rs9261491, HLA/rs2857439, HLA/rs16896944, HLA/rs3132671, HLA/rs2857435, HLA/rs9261471, HLA/rs2523393, HLA-DRB1/rs3135388, RGS1/rs2760524, PTGER4/rs9292777) also showed a noteworthy Bayesian false discovery probability (BFDP) and one additional association (CD24 rs8734/rs52812045) was also noteworthy via BFDP computation. Herein, we have identified several noteworthy biomarkers of multiple sclerosis susceptibility. We hope these data are used to study multiple sclerosis genetics and inform future screening programs.
Johnson, George E.; Battaion, Hannah L.; Slob, Wout; Gollapudi, B.
2017-01-01
There is growing interest in quantitative analysis of in vivo genetic toxicity dose‐response data, and use of point‐of‐departure (PoD) metrics such as the benchmark dose (BMD) for human health risk assessment (HHRA). Currently, multiple transgenic rodent (TGR) assay variants, employing different rodent strains and reporter transgenes, are used for the assessment of chemically‐induced genotoxic effects in vivo. However, regulatory issues arise when different PoD values (e.g., lower BMD confidence intervals or BMDLs) are obtained for the same compound across different TGR assay variants. This study therefore employed the BMD approach to examine the ability of different TGR variants to yield comparable genotoxic potency estimates. Review of over 2000 dose‐response datasets identified suitably‐matched dose‐response data for three compounds (ethyl methanesulfonate or EMS, N‐ethyl‐N‐nitrosourea or ENU, and dimethylnitrosamine or DMN) across four commonly‐used murine TGR variants (Muta™Mouse lacZ, Muta™Mouse cII, gpt delta and BigBlue® lacI). Dose‐response analyses provided no conclusive evidence that TGR variant choice significantly influences the derived genotoxic potency estimate. This conclusion was reliant upon taking into account the importance of comparing BMD confidence intervals as opposed to directly comparing PoD values (e.g., comparing BMDLs). Comparisons with earlier works suggested that with respect to potency determination, tissue choice is potentially more important than choice of TGR assay variant. Scoring multiple tissues selected on the basis of supporting toxicokinetic information is therefore recommended. Finally, we used typical within‐group variances to estimate preliminary endpoint‐specific benchmark response (BMR) values across several TGR variants/tissues. We discuss why such values are required for routine use of genetic toxicity PoDs for HHRA. Environ. Mol. Mutagen. 58:632–643, 2017. © 2017 Her Majesty the Queen in Right of Canada. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc. PMID:28945287
Multiple Myeloma Genomics: A Systematic Review.
Weaver, Casey J; Tariman, Joseph D
2017-08-01
This integrative review describes the genomic variants that have been found to be associated with poor prognosis in patients diagnosed with multiple myeloma (MM). Second, it identifies MM genetic and genomic changes using next-generation sequencing, specifically whole-genome sequencing or exome sequencing. A search for peer-reviewed articles through PubMed, EBSCOhost, and DePaul WorldCat Libraries Worldwide yielded 33 articles that were included in the final analysis. The most commonly reported genetic changes were KRAS, NRAS, TP53, FAM46C, BRAF, DIS3, ATM, and CCND1. These genetic changes play a role in the pathogenesis of MM, prognostication, and therapeutic targets for novel therapies. MM genetics and genomics are expanding rapidly; oncology nurse clinicians must have basic competencies in genetics and genomics to help patients understand the complexities of genetic and genomic alterations and be able to refer patients to appropriate genomic professionals if needed. Copyright © 2017 Elsevier Inc. All rights reserved.
Sun exposure, vitamin D receptor polymorphisms FokI and BsmI and risk of multiple primary melanoma.
Mandelcorn-Monson, Rochelle; Marrett, Loraine; Kricker, Anne; Armstrong, Bruce K; Orlow, Irene; Goumas, Chris; Paine, Susan; Rosso, Stefano; Thomas, Nancy; Millikan, Robert C; Pole, Jason D; Cotignola, Javier; Rosen, Cheryl; Kanetsky, Peter A; Lee-Taylor, Julia; Begg, Colin B; Berwick, Marianne
2011-12-01
Sunlight exposure increases risk of melanoma. Sunlight also potentiates cutaneous synthesis of vitamin D, which can inhibit melanoma cell growth and promote apoptosis. Vitamin D effects are mediated through the vitamin D receptor (VDR). We hypothesized that genetic variation in VDR affects the relationship of sun exposure to risk of a further melanoma in people who have already had one. We investigated the interaction between VDR polymorphisms and sun exposure in a population-based multinational study comparing 1138 patients with a multiple (second or subsequent) primary melanoma (cases) to 2151 patients with a first primary melanoma (controls); essentially a case-control study of melanoma in a population of melanoma survivors. Sun exposure was assessed using a questionnaire and interview, and was shown to be associated with multiple primary melanoma. VDR was genotyped at the FokI and BsmI loci and the main effects of variants at these loci and their interactions with sun exposure were analyzed. Only the BsmI variant was associated with multiple primary melanoma (OR=1.27, 95% CI 0.99-1.62 for the homozygous variant genotype). Joint effects analyses showed highest ORs in the high exposure, homozygous variant BsmI genotype category for each sun exposure variable. Stratified analyses showed somewhat higher ORs for the homozygous BsmI variant genotype in people with high sun exposure than with low sun exposure. P values for interaction, however, were high. These results suggest that risk of multiple primary melanoma is increased in people who have the BsmI variant of VDR. Copyright © 2011 Elsevier Ltd. All rights reserved.
Identification of genomic variants putatively targeted by selection during dog domestication.
Cagan, Alex; Blass, Torsten
2016-01-12
Dogs [Canis lupus familiaris] were the first animal species to be domesticated and continue to occupy an important place in human societies. Recent studies have begun to reveal when and where dog domestication occurred. While much progress has been made in identifying the genetic basis of phenotypic differences between dog breeds we still know relatively little about the genetic changes underlying the phenotypes that differentiate all dogs from their wild progenitors, wolves [Canis lupus]. In particular, dogs generally show reduced aggression and fear towards humans compared to wolves. Therefore, selection for tameness was likely a necessary prerequisite for dog domestication. With the increasing availability of whole-genome sequence data it is possible to try and directly identify the genetic variants contributing to the phenotypic differences between dogs and wolves. We analyse the largest available database of genome-wide polymorphism data in a global sample of dogs 69 and wolves 7. We perform a scan to identify regions of the genome that are highly differentiated between dogs and wolves. We identify putatively functional genomic variants that are segregating or at high frequency [> = 0.75 Fst] for alternative alleles between dogs and wolves. A biological pathways analysis of the genes containing these variants suggests that there has been selection on the 'adrenaline and noradrenaline biosynthesis pathway', well known for its involvement in the fight-or-flight response. We identify 11 genes with putatively functional variants fixed for alternative alleles between dogs and wolves. The segregating variants in these genes are strong candidates for having been targets of selection during early dog domestication. We present the first genome-wide analysis of the different categories of putatively functional variants that are fixed or segregating at high frequency between a global sampling of dogs and wolves. We find evidence that selection has been strongest around non-synonymous variants. Strong selection in the initial stages of dog domestication appears to have occurred on multiple genes involved in the fight-or-flight response, particularly in the catecholamine synthesis pathway. Different alleles in some of these genes have been associated with behavioral differences between modern dog breeds, suggesting an important role for this pathway at multiple stages in the domestication process.
PLAIASU, Vasilica; OCHIANA, Diana; MOTEI, Gabriela; ANCA, Ioana; GEORGESCU, Adrian
2010-01-01
ABSTRACT Introduction: Patau syndrome (trisomy 13) is one of the most common chromosomal anomalies clinically characterized by the presence of numerous malformations with a limited survival rate for most cases. Babies are usually identified at birth and the diagnosis is confirmed with genetic testing. Materials and methods: In this review we outline the clinical and cytogenetic aspects of trisomy 13 and associated phenotypes for 5 cases analyzed in the last 3 years, referred to our Clinical Genetics Department. For each child cytogenetic analysis was performed to determine the genetic variant; also, the patients were investigated for other associated malformations (cardiac, cerebral, renal, ocular anomalies). Discussion: All 5 cases presented multiple malformations, including some but not all signs of the classical clinical triad suggestive of Patau syndrome. The cytogenetic investigation confirmed for each case the suspected diagnosis and also indicated the specific genetic variant, this being a valuable information for the genetic counselling of the families. Conclusion: The application of genetic analysis can increase diagnosis and prognosis accuracy and have an impact on clinical management. PMID:21977150
Leblond, Claire S; Heinrich, Jutta; Delorme, Richard; Proepper, Christian; Betancur, Catalina; Huguet, Guillaume; Konyukh, Marina; Chaste, Pauline; Ey, Elodie; Rastam, Maria; Anckarsäter, Henrik; Nygren, Gudrun; Gillberg, I Carina; Melke, Jonas; Toro, Roberto; Regnault, Beatrice; Fauchereau, Fabien; Mercati, Oriane; Lemière, Nathalie; Skuse, David; Poot, Martin; Holt, Richard; Monaco, Anthony P; Järvelä, Irma; Kantojärvi, Katri; Vanhala, Raija; Curran, Sarah; Collier, David A; Bolton, Patrick; Chiocchetti, Andreas; Klauck, Sabine M; Poustka, Fritz; Freitag, Christine M; Waltes, Regina; Kopp, Marnie; Duketis, Eftichia; Bacchelli, Elena; Minopoli, Fiorella; Ruta, Liliana; Battaglia, Agatino; Mazzone, Luigi; Maestrini, Elena; Sequeira, Ana F; Oliveira, Barbara; Vicente, Astrid; Oliveira, Guiomar; Pinto, Dalila; Scherer, Stephen W; Zelenika, Diana; Delepine, Marc; Lathrop, Mark; Bonneau, Dominique; Guinchat, Vincent; Devillard, Françoise; Assouline, Brigitte; Mouren, Marie-Christine; Leboyer, Marion; Gillberg, Christopher; Boeckers, Tobias M; Bourgeron, Thomas
2012-02-01
Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders with a complex inheritance pattern. While many rare variants in synaptic proteins have been identified in patients with ASD, little is known about their effects at the synapse and their interactions with other genetic variations. Here, following the discovery of two de novo SHANK2 deletions by the Autism Genome Project, we identified a novel 421 kb de novo SHANK2 deletion in a patient with autism. We then sequenced SHANK2 in 455 patients with ASD and 431 controls and integrated these results with those reported by Berkel et al. 2010 (n = 396 patients and n = 659 controls). We observed a significant enrichment of variants affecting conserved amino acids in 29 of 851 (3.4%) patients and in 16 of 1,090 (1.5%) controls (P = 0.004, OR = 2.37, 95% CI = 1.23-4.70). In neuronal cell cultures, the variants identified in patients were associated with a reduced synaptic density at dendrites compared to the variants only detected in controls (P = 0.0013). Interestingly, the three patients with de novo SHANK2 deletions also carried inherited CNVs at 15q11-q13 previously associated with neuropsychiatric disorders. In two cases, the nicotinic receptor CHRNA7 was duplicated and in one case the synaptic translation repressor CYFIP1 was deleted. These results strengthen the role of synaptic gene dysfunction in ASD but also highlight the presence of putative modifier genes, which is in keeping with the "multiple hit model" for ASD. A better knowledge of these genetic interactions will be necessary to understand the complex inheritance pattern of ASD.
Leblond, Claire S.; Heinrich, Jutta; Delorme, Richard; Proepper, Christian; Betancur, Catalina; Huguet, Guillaume; Konyukh, Marina; Chaste, Pauline; Ey, Elodie; Rastam, Maria; Anckarsäter, Henrik; Nygren, Gudrun; Gillberg, I. Carina; Melke, Jonas; Toro, Roberto; Regnault, Beatrice; Fauchereau, Fabien; Mercati, Oriane; Lemière, Nathalie; Skuse, David; Poot, Martin; Holt, Richard; Monaco, Anthony P.; Järvelä, Irma; Kantojärvi, Katri; Vanhala, Raija; Curran, Sarah; Collier, David A.; Bolton, Patrick; Chiocchetti, Andreas; Klauck, Sabine M.; Poustka, Fritz; Freitag, Christine M.; Waltes, Regina; Kopp, Marnie; Duketis, Eftichia; Bacchelli, Elena; Minopoli, Fiorella; Ruta, Liliana; Battaglia, Agatino; Mazzone, Luigi; Maestrini, Elena; Sequeira, Ana F.; Oliveira, Barbara; Vicente, Astrid; Oliveira, Guiomar; Pinto, Dalila; Scherer, Stephen W.; Zelenika, Diana; Delepine, Marc; Lathrop, Mark; Bonneau, Dominique; Guinchat, Vincent; Devillard, Françoise; Assouline, Brigitte; Mouren, Marie-Christine; Leboyer, Marion; Gillberg, Christopher; Boeckers, Tobias M.; Bourgeron, Thomas
2012-01-01
Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders with a complex inheritance pattern. While many rare variants in synaptic proteins have been identified in patients with ASD, little is known about their effects at the synapse and their interactions with other genetic variations. Here, following the discovery of two de novo SHANK2 deletions by the Autism Genome Project, we identified a novel 421 kb de novo SHANK2 deletion in a patient with autism. We then sequenced SHANK2 in 455 patients with ASD and 431 controls and integrated these results with those reported by Berkel et al. 2010 (n = 396 patients and n = 659 controls). We observed a significant enrichment of variants affecting conserved amino acids in 29 of 851 (3.4%) patients and in 16 of 1,090 (1.5%) controls (P = 0.004, OR = 2.37, 95% CI = 1.23–4.70). In neuronal cell cultures, the variants identified in patients were associated with a reduced synaptic density at dendrites compared to the variants only detected in controls (P = 0.0013). Interestingly, the three patients with de novo SHANK2 deletions also carried inherited CNVs at 15q11–q13 previously associated with neuropsychiatric disorders. In two cases, the nicotinic receptor CHRNA7 was duplicated and in one case the synaptic translation repressor CYFIP1 was deleted. These results strengthen the role of synaptic gene dysfunction in ASD but also highlight the presence of putative modifier genes, which is in keeping with the “multiple hit model” for ASD. A better knowledge of these genetic interactions will be necessary to understand the complex inheritance pattern of ASD. PMID:22346768
Reitz, Christiane; Jun, Gyungah; Naj, Adam; Rajbhandary, Ruchita; Vardarajan, Badri Narayan; Wang, Li-San; Valladares, Otto; Lin, Chiao-Feng; Larson, Eric B; Graff-Radford, Neill R; Evans, Denis; De Jager, Philip L; Crane, Paul K; Buxbaum, Joseph D; Murrell, Jill R; Raj, Towfique; Ertekin-Taner, Nilufer; Logue, Mark; Baldwin, Clinton T; Green, Robert C; Barnes, Lisa L; Cantwell, Laura B; Fallin, M Daniele; Go, Rodney C P; Griffith, Patrick; Obisesan, Thomas O; Manly, Jennifer J; Lunetta, Kathryn L; Kamboh, M Ilyas; Lopez, Oscar L; Bennett, David A; Hendrie, Hugh; Hall, Kathleen S; Goate, Alison M; Byrd, Goldie S; Kukull, Walter A; Foroud, Tatiana M; Haines, Jonathan L; Farrer, Lindsay A; Pericak-Vance, Margaret A; Schellenberg, Gerard D; Mayeux, Richard
2013-04-10
Genetic variants associated with susceptibility to late-onset Alzheimer disease are known for individuals of European ancestry, but whether the same or different variants account for the genetic risk of Alzheimer disease in African American individuals is unknown. Identification of disease-associated variants helps identify targets for genetic testing, prevention, and treatment. To identify genetic loci associated with late-onset Alzheimer disease in African Americans. The Alzheimer Disease Genetics Consortium (ADGC) assembled multiple data sets representing a total of 5896 African Americans (1968 case participants, 3928 control participants) 60 years or older that were collected between 1989 and 2011 at multiple sites. The association of Alzheimer disease with genotyped and imputed single-nucleotide polymorphisms (SNPs) was assessed in case-control and in family-based data sets. Results from individual data sets were combined to perform an inverse variance-weighted meta-analysis, first with genome-wide analyses and subsequently with gene-based tests for previously reported loci. Presence of Alzheimer disease according to standardized criteria. Genome-wide significance in fully adjusted models (sex, age, APOE genotype, population stratification) was observed for a SNP in ABCA7 (rs115550680, allele = G; frequency, 0.09 cases and 0.06 controls; odds ratio [OR], 1.79 [95% CI, 1.47-2.12]; P = 2.2 × 10(-9)), which is in linkage disequilibrium with SNPs previously associated with Alzheimer disease in Europeans (0.8 < D' < 0.9). The effect size for the SNP in ABCA7 was comparable with that of the APOE ϵ4-determining SNP rs429358 (allele = C; frequency, 0.30 cases and 0.18 controls; OR, 2.31 [95% CI, 2.19-2.42]; P = 5.5 × 10(-47)). Several loci previously associated with Alzheimer disease but not reaching significance in genome-wide analyses were replicated in gene-based analyses accounting for linkage disequilibrium between markers and correcting for number of tests performed per gene (CR1, BIN1, EPHA1, CD33; 0.0005 < empirical P < .001). In this meta-analysis of data from African American participants, Alzheimer disease was significantly associated with variants in ABCA7 and with other genes that have been associated with Alzheimer disease in individuals of European ancestry. Replication and functional validation of this finding is needed before this information is used in clinical settings.
Vyshkina, Tamara; Sylvester, Andrew; Sadiq, Saud; Bonilla, Eduardo; Canter, Jeff A.; Perl, Andras; Kalman, Bernadette
2008-01-01
Mitochondrial dysfunction has been implicated in the pathogenesis of multiple sclerosis (MS) and systemic lupus erythematosus (SLE). This study re-investigates the roles of previously suggested candidate genes of energy metabolism (Complex I genes located in the nucleus and in the mitochondria) in patients with MS relative to ethnically matched SLE patients and healthy controls. After stringent correction for multiple testing, we reproduce the association of the mitochondrial (mt)DNA haplotype K* with MS, but reject the importance of previously suggested borderline associations with nuclear genes of Complex I. In addition, we detect the association of common variants of the mitochondrial ND2 and ATP6 genes with both MS and SLE, which raises the possibility of a shared mitochondrial genetic background of these two autoimmune diseases. PMID:18708297
Testing Genetic Pleiotropy with GWAS Summary Statistics for Marginal and Conditional Analyses.
Deng, Yangqing; Pan, Wei
2017-12-01
There is growing interest in testing genetic pleiotropy, which is when a single genetic variant influences multiple traits. Several methods have been proposed; however, these methods have some limitations. First, all the proposed methods are based on the use of individual-level genotype and phenotype data; in contrast, for logistical, and other, reasons, summary statistics of univariate SNP-trait associations are typically only available based on meta- or mega-analyzed large genome-wide association study (GWAS) data. Second, existing tests are based on marginal pleiotropy, which cannot distinguish between direct and indirect associations of a single genetic variant with multiple traits due to correlations among the traits. Hence, it is useful to consider conditional analysis, in which a subset of traits is adjusted for another subset of traits. For example, in spite of substantial lowering of low-density lipoprotein cholesterol (LDL) with statin therapy, some patients still maintain high residual cardiovascular risk, and, for these patients, it might be helpful to reduce their triglyceride (TG) level. For this purpose, in order to identify new therapeutic targets, it would be useful to identify genetic variants with pleiotropic effects on LDL and TG after adjusting the latter for LDL; otherwise, a pleiotropic effect of a genetic variant detected by a marginal model could simply be due to its association with LDL only, given the well-known correlation between the two types of lipids. Here, we develop a new pleiotropy testing procedure based only on GWAS summary statistics that can be applied for both marginal analysis and conditional analysis. Although the main technical development is based on published union-intersection testing methods, care is needed in specifying conditional models to avoid invalid statistical estimation and inference. In addition to the previously used likelihood ratio test, we also propose using generalized estimating equations under the working independence model for robust inference. We provide numerical examples based on both simulated and real data, including two large lipid GWAS summary association datasets based on ∼100,000 and ∼189,000 samples, respectively, to demonstrate the difference between marginal and conditional analyses, as well as the effectiveness of our new approach. Copyright © 2017 by the Genetics Society of America.
Candidate genetic modifiers for breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers.
Peterlongo, Paolo; Chang-Claude, Jenny; Moysich, Kirsten B; Rudolph, Anja; Schmutzler, Rita K; Simard, Jacques; Soucy, Penny; Eeles, Rosalind A; Easton, Douglas F; Hamann, Ute; Wilkening, Stefan; Chen, Bowang; Rookus, Matti A; Schmidt, Marjanka K; van der Baan, Frederieke H; Spurdle, Amanda B; Walker, Logan C; Lose, Felicity; Maia, Ana-Teresa; Montagna, Marco; Matricardi, Laura; Lubinski, Jan; Jakubowska, Anna; Gómez Garcia, Encarna B; Olopade, Olufunmilayo I; Nussbaum, Robert L; Nathanson, Katherine L; Domchek, Susan M; Rebbeck, Timothy R; Arun, Banu K; Karlan, Beth Y; Orsulic, Sandra; Lester, Jenny; Chung, Wendy K; Miron, Alex; Southey, Melissa C; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Dorfling, Cecilia M; van Rensburg, Elizabeth J; Ding, Yuan Chun; Neuhausen, Susan L; Hansen, Thomas V O; Gerdes, Anne-Marie; Ejlertsen, Bent; Jønson, Lars; Osorio, Ana; Martínez-Bouzas, Cristina; Benitez, Javier; Conway, Edye E; Blazer, Kathleen R; Weitzel, Jeffrey N; Manoukian, Siranoush; Peissel, Bernard; Zaffaroni, Daniela; Scuvera, Giulietta; Barile, Monica; Ficarazzi, Filomena; Mariette, Frederique; Fortuzzi, Stefano; Viel, Alessandra; Giannini, Giuseppe; Papi, Laura; Martayan, Aline; Tibiletti, Maria Grazia; Radice, Paolo; Vratimos, Athanassios; Fostira, Florentia; Garber, Judy E; Donaldson, Alan; Brewer, Carole; Foo, Claire; Evans, D Gareth R; Frost, Debra; Eccles, Diana; Brady, Angela; Cook, Jackie; Tischkowitz, Marc; Adlard, Julian; Barwell, Julian; Walker, Lisa; Izatt, Louise; Side, Lucy E; Kennedy, M John; Rogers, Mark T; Porteous, Mary E; Morrison, Patrick J; Platte, Radka; Davidson, Rosemarie; Hodgson, Shirley V; Ellis, Steve; Cole, Trevor; Godwin, Andrew K; Claes, Kathleen; Van Maerken, Tom; Meindl, Alfons; Gehrig, Andrea; Sutter, Christian; Engel, Christoph; Niederacher, Dieter; Steinemann, Doris; Plendl, Hansjoerg; Kast, Karin; Rhiem, Kerstin; Ditsch, Nina; Arnold, Norbert; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Wang-Gohrke, Shan; Bressac-de Paillerets, Brigitte; Buecher, Bruno; Delnatte, Capucine; Houdayer, Claude; Stoppa-Lyonnet, Dominique; Damiola, Francesca; Coupier, Isabelle; Barjhoux, Laure; Venat-Bouvet, Laurence; Golmard, Lisa; Boutry-Kryza, Nadia; Sinilnikova, Olga M; Caron, Olivier; Pujol, Pascal; Mazoyer, Sylvie; Belotti, Muriel; Piedmonte, Marion; Friedlander, Michael L; Rodriguez, Gustavo C; Copeland, Larry J; de la Hoya, Miguel; Segura, Pedro Perez; Nevanlinna, Heli; Aittomäki, Kristiina; van Os, Theo A M; Meijers-Heijboer, Hanne E J; van der Hout, Annemarie H; Vreeswijk, Maaike P G; Hoogerbrugge, Nicoline; Ausems, Margreet G E M; van Doorn, Helena C; Collée, J Margriet; Olah, Edith; Diez, Orland; Blanco, Ignacio; Lazaro, Conxi; Brunet, Joan; Feliubadalo, Lidia; Cybulski, Cezary; Gronwald, Jacek; Durda, Katarzyna; Jaworska-Bieniek, Katarzyna; Sukiennicki, Grzegorz; Arason, Adalgeir; Chiquette, Jocelyne; Teixeira, Manuel R; Olswold, Curtis; Couch, Fergus J; Lindor, Noralane M; Wang, Xianshu; Szabo, Csilla I; Offit, Kenneth; Corines, Marina; Jacobs, Lauren; Robson, Mark E; Zhang, Liying; Joseph, Vijai; Berger, Andreas; Singer, Christian F; Rappaport, Christine; Kaulich, Daphne Geschwantler; Pfeiler, Georg; Tea, Muy-Kheng M; Phelan, Catherine M; Greene, Mark H; Mai, Phuong L; Rennert, Gad; Mulligan, Anna Marie; Glendon, Gord; Tchatchou, Sandrine; Andrulis, Irene L; Toland, Amanda Ewart; Bojesen, Anders; Pedersen, Inge Sokilde; Thomassen, Mads; Jensen, Uffe Birk; Laitman, Yael; Rantala, Johanna; von Wachenfeldt, Anna; Ehrencrona, Hans; Askmalm, Marie Stenmark; Borg, Åke; Kuchenbaecker, Karoline B; McGuffog, Lesley; Barrowdale, Daniel; Healey, Sue; Lee, Andrew; Pharoah, Paul D P; Chenevix-Trench, Georgia; Antoniou, Antonis C; Friedman, Eitan
2015-01-01
BRCA1 and BRCA2 mutation carriers are at substantially increased risk for developing breast and ovarian cancer. The incomplete penetrance coupled with the variable age at diagnosis in carriers of the same mutation suggests the existence of genetic and nongenetic modifying factors. In this study, we evaluated the putative role of variants in many candidate modifier genes. Genotyping data from 15,252 BRCA1 and 8,211 BRCA2 mutation carriers, for known variants (n = 3,248) located within or around 445 candidate genes, were available through the iCOGS custom-designed array. Breast and ovarian cancer association analysis was performed within a retrospective cohort approach. The observed P values of association ranged between 0.005 and 1.000. None of the variants was significantly associated with breast or ovarian cancer risk in either BRCA1 or BRCA2 mutation carriers, after multiple testing adjustments. There is little evidence that any of the evaluated candidate variants act as modifiers of breast and/or ovarian cancer risk in BRCA1 or BRCA2 mutation carriers. Genome-wide association studies have been more successful at identifying genetic modifiers of BRCA1/2 penetrance than candidate gene studies. ©2014 American Association for Cancer Research.
Uncovering Local Trends in Genetic Effects of Multiple Phenotypes via Functional Linear Models.
Vsevolozhskaya, Olga A; Zaykin, Dmitri V; Barondess, David A; Tong, Xiaoren; Jadhav, Sneha; Lu, Qing
2016-04-01
Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. Although the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear model approach. In this work we extend previous developments to allow inclusion of multiple traits and adjustment for additional covariates. Our functional approach is unique in that it provides a nuanced depiction of effects and interactions for the variables in the model by representing them as curves varying over a genetic region. We demonstrate flexibility and competitive power of our approach by contrasting its performance with commonly used statistical tools and illustrate its potential for discovery and characterization of genetic architecture of complex traits using sequencing data from the Dallas Heart Study. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
Renin-Angiotensin System Gene Variants and Type 2 Diabetes Mellitus: Influence of Angiotensinogen
Joyce-Tan, Siew Mei; Zain, Shamsul Mohd; Abdul Sattar, Munavvar Zubaid; Abdullah, Nor Azizan
2016-01-01
Genome-wide association studies (GWAS) have been successfully used to call for variants associated with diseases including type 2 diabetes mellitus (T2DM). However, some variants are not included in the GWAS to avoid penalty in multiple hypothetic testing. Thus, candidate gene approach is still useful even at GWAS era. This study attempted to assess whether genetic variations in the renin-angiotensin system (RAS) and their gene interactions are associated with T2DM risk. We genotyped 290 T2DM patients and 267 controls using three genes of the RAS, namely, angiotensin converting enzyme (ACE), angiotensinogen (AGT), and angiotensin II type 1 receptor (AGTR1). There were significant differences in allele frequencies between cases and controls for AGT variants (P = 0.05) but not for ACE and AGTR1. Haplotype TCG of the AGT was associated with increased risk of T2DM (OR 1.92, 95% CI 1.15–3.20, permuted P = 0.012); however, no evidence of significant gene-gene interactions was seen. Nonetheless, our analysis revealed that the associations of the AGT variants with T2DM were independently associated. Thus, this study suggests that genetic variants of the RAS can modestly influence the T2DM risk. PMID:26682227
Multiple Independent Genetic Factors at NOS1AP Modulate the QT Interval in a Multi-Ethnic Population
Arking, Dan E.; Khera, Amit; Xing, Chao; Kao, W. H. Linda; Post, Wendy; Boerwinkle, Eric; Chakravarti, Aravinda
2009-01-01
Extremes of electrocardiographic QT interval are associated with increased risk for sudden cardiac death (SCD); thus, identification and characterization of genetic variants that modulate QT interval may elucidate the underlying etiology of SCD. Previous studies have revealed an association between a common genetic variant in NOS1AP and QT interval in populations of European ancestry, but this finding has not been extended to other ethnic populations. We sought to characterize the effects of NOS1AP genetic variants on QT interval in the multi-ethnic population-based Dallas Heart Study (DHS, n = 3,072). The SNP most strongly associated with QT interval in previous samples of European ancestry, rs16847548, was the most strongly associated in White (P = 0.005) and Black (P = 3.6×10−5) participants, with the same direction of effect in Hispanics (P = 0.17), and further showed a significant SNP × sex-interaction (P = 0.03). A second SNP, rs16856785, uncorrelated with rs16847548, was also associated with QT interval in Blacks (P = 0.01), with qualitatively similar results in Whites and Hispanics. In a previously genotyped cohort of 14,107 White individuals drawn from the combined Atherosclerotic Risk in Communities (ARIC) and Cardiovascular Health Study (CHS) cohorts, we validated both the second locus at rs16856785 (P = 7.63×10−8), as well as the sex-interaction with rs16847548 (P = 8.68×10−6). These data extend the association of genetic variants in NOS1AP with QT interval to a Black population, with similar trends, though not statistically significant at P<0.05, in Hispanics. In addition, we identify a strong sex-interaction and the presence of a second independent site within NOS1AP associated with the QT interval. These results highlight the consistent and complex role of NOS1AP genetic variants in modulating QT interval. PMID:19180230
Excessive burden of lysosomal storage disorder gene variants in Parkinson's disease.
Robak, Laurie A; Jansen, Iris E; van Rooij, Jeroen; Uitterlinden, André G; Kraaij, Robert; Jankovic, Joseph; Heutink, Peter; Shulman, Joshua M
2017-12-01
Mutations in the glucocerebrosidase gene (GBA), which cause Gaucher disease, are also potent risk factors for Parkinson's disease. We examined whether a genetic burden of variants in other lysosomal storage disorder genes is more broadly associated with Parkinson's disease susceptibility. The sequence kernel association test was used to interrogate variant burden among 54 lysosomal storage disorder genes, leveraging whole exome sequencing data from 1156 Parkinson's disease cases and 1679 control subjects. We discovered a significant burden of rare, likely damaging lysosomal storage disorder gene variants in association with Parkinson's disease risk. The association signal was robust to the exclusion of GBA, and consistent results were obtained in two independent replication cohorts, including 436 cases and 169 controls with whole exome sequencing and an additional 6713 cases and 5964 controls with exome-wide genotyping. In secondary analyses designed to highlight the specific genes driving the aggregate signal, we confirmed associations at the GBA and SMPD1 loci and newly implicate CTSD, SLC17A5, and ASAH1 as candidate Parkinson's disease susceptibility genes. In our discovery cohort, the majority of Parkinson's disease cases (56%) have at least one putative damaging variant in a lysosomal storage disorder gene, and 21% carry multiple alleles. Our results highlight several promising new susceptibility loci and reinforce the importance of lysosomal mechanisms in Parkinson's disease pathogenesis. We suggest that multiple genetic hits may act in combination to degrade lysosomal function, enhancing Parkinson's disease susceptibility. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Pathogenic Germline Variants in 10,389 Adult Cancers.
Huang, Kuan-Lin; Mashl, R Jay; Wu, Yige; Ritter, Deborah I; Wang, Jiayin; Oh, Clara; Paczkowska, Marta; Reynolds, Sheila; Wyczalkowski, Matthew A; Oak, Ninad; Scott, Adam D; Krassowski, Michal; Cherniack, Andrew D; Houlahan, Kathleen E; Jayasinghe, Reyka; Wang, Liang-Bo; Zhou, Daniel Cui; Liu, Di; Cao, Song; Kim, Young Won; Koire, Amanda; McMichael, Joshua F; Hucthagowder, Vishwanathan; Kim, Tae-Beom; Hahn, Abigail; Wang, Chen; McLellan, Michael D; Al-Mulla, Fahd; Johnson, Kimberly J; Lichtarge, Olivier; Boutros, Paul C; Raphael, Benjamin; Lazar, Alexander J; Zhang, Wei; Wendl, Michael C; Govindan, Ramaswamy; Jain, Sanjay; Wheeler, David; Kulkarni, Shashikant; Dipersio, John F; Reimand, Jüri; Meric-Bernstam, Funda; Chen, Ken; Shmulevich, Ilya; Plon, Sharon E; Chen, Feng; Ding, Li
2018-04-05
We conducted the largest investigation of predisposition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large deletions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) loss of heterozygosity or biallelic two-hit events. We also discovered 33 such variants in oncogenes, including missenses in MET, RET, and PTPN11 associated with high gene expression. We nominated 47 additional predisposition variants from prioritized VUSs supported by multiple evidences involving case-control frequency, loss of heterozygosity, expression effect, and co-localization with mutations and modified residues. Our integrative approach links rare predisposition variants to functional consequences, informing future guidelines of variant classification and germline genetic testing in cancer. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Aggressive behavior, related conduct problems, and variation in genes affecting dopamine turnover.
Grigorenko, Elena L; De Young, Colin G; Eastman, Maria; Getchell, Marya; Haeffel, Gerald J; Klinteberg, Britt af; Koposov, Roman A; Oreland, Lars; Pakstis, Andrew J; Ponomarev, Oleg A; Ruchkin, Vladislav V; Singh, Jay P; Yrigollen, Carolyn M
2010-01-01
A number of dopamine-related genes have been implicated in the etiology of violent behavior and conduct problems. Of these genes, the ones that code for the enzymes that influence the turnover of dopamine (DA) have received the most attention. In this study, we investigated 12 genetic polymorphisms in four genes involved with DA functioning (COMT, MAOA and MAOB, and DbetaH) in 179 incarcerated male Russian adolescents and two groups of matched controls: boys without criminal records referred to by their teachers as (a) "troubled-behavior-free" boys, n=182; and (b) "troubled-behavior" boys, n=60. The participants were classified as (1) being incarcerated or not, (2) having the DSM-IV diagnosis of conduct disorder (CD) or not, and (3) having committed violent or nonviolent crimes (for the incarcerated individuals only). The findings indicate that, although no single genetic variant in any of the four genes differentiated individuals in the investigated groups, various linear combinations (i.e., haplotypes) and nonlinear combinations (i.e., interactions between variants within and across genes) of genetic variants resulted in informative and robust classifications for two of the three groupings. These combinations of genetic variants differentiated individuals in incarceration vs. nonincarcerated and CD vs. no-CD groups; no informative combinations were established consistently for the grouping by crime within the incarcerated individuals. This study underscores the importance of considering multiple rather than single markers within candidate genes and their additive and interactive combinations, both with themselves and with nongenetic indicators, while attempting to understand the genetic background of such complex behaviors as serious conduct problems. (c) 2010 Wiley-Liss, Inc.
Lester, Kathryn J; Coleman, Jonathan R I; Roberts, Susanna; Keers, Robert; Breen, Gerome; Bögels, Susan; Creswell, Cathy; Hudson, Jennifer L; McKinnon, Anna; Nauta, Maaike; Rapee, Ronald M; Schneider, Silvia; Silverman, Wendy K; Thastum, Mikael; Waite, Polly; Wergeland, Gro Janne H; Eley, Thalia C
2017-03-01
Extinction learning is an important mechanism in the successful psychological treatment of anxiety. Individual differences in response and relapse following Cognitive Behavior Therapy may in part be explained by variability in the ease with which fears are extinguished or the vulnerability of these fears to re-emerge. Given the role of the endocannabinoid system in fear extinction, this study investigates whether genetic variation in the endocannabinoid system explains individual differences in response to CBT. Children (N = 1,309) with a primary anxiety disorder diagnosis were recruited. We investigated the relationship between variation in the CNR1, CNR2, and FAAH genes and change in primary anxiety disorder severity between pre- and post-treatment and during the follow-up period in the full sample and a subset with fear-based anxiety disorder diagnoses. Change in symptom severity during active treatment was nominally associated (P < 0.05) with two SNPs. During the follow-up period, five SNPs were nominally associated with a poorer treatment response (rs806365 [CNR1]; rs2501431 [CNR2]; rs2070956 [CNR2]; rs7769940 [CNR1]; rs2209172 [FAAH]) and one with a more favorable response (rs6928813 [CNR1]). Within the fear-based subset, the effect of rs806365 survived multiple testing corrections (P < 0.0016). We found very limited evidence for an association between variants in endocannabinoid system genes and treatment response once multiple testing corrections were applied. Larger, more homogenous cohorts are needed to allow the identification of variants of small but statistically significant effect and to estimate effect sizes for these variants with greater precision in order to determine their potential clinical utility. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
Complex nature of SNP genotype effects on gene expression in primary human leucocytes.
Heap, Graham A; Trynka, Gosia; Jansen, Ritsert C; Bruinenberg, Marcel; Swertz, Morris A; Dinesen, Lotte C; Hunt, Karen A; Wijmenga, Cisca; Vanheel, David A; Franke, Lude
2009-01-07
Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown. We correlated gene expression and genetic variation in untouched primary leucocytes (n = 110) from individuals with celiac disease - a common condition with multiple risk variants identified. We compared our observations with an EBV-transformed HapMap B cell line dataset (n = 90), and performed a meta-analysis to increase power to detect non-tissue specific effects. In celiac peripheral blood, 2,315 SNP variants influenced gene expression at 765 different transcripts (< 250 kb from SNP, at FDR = 0.05, cis expression quantitative trait loci, eQTLs). 135 of the detected SNP-probe effects (reflecting 51 unique probes) were also detected in a HapMap B cell line published dataset, all with effects in the same allelic direction. Overall gene expression differences within the two datasets predominantly explain the limited overlap in observed cis-eQTLs. Celiac associated risk variants from two regions, containing genes IL18RAP and CCR3, showed significant cis genotype-expression correlations in the peripheral blood but not in the B cell line datasets. We identified 14 genes where a SNP affected the expression of different probes within the same gene, but in opposite allelic directions. By incorporating genetic variation in co-expression analyses, functional relationships between genes can be more significantly detected. In conclusion, the complex nature of genotypic effects in human populations makes the use of a relevant tissue, large datasets, and analysis of different exons essential to enable the identification of the function for many genetic risk variants in common diseases.
Imani, Saber; Cheng, Jingliang; Shasaltaneh, Marzieh Dehghan; Wei, Chunli; Yang, Lisha; Fu, Shangyi; Zou, Hui; Khan, Md. Asaduzzaman; Zhang, Xianqin; Chen, Hanchun; Zhang, Dianzheng; Duan, Chengxia; Lv, Hongbin; Li, Yumei; Chen, Rui; Fu, Junjiang
2018-01-01
Stargardt disease-4 (STGD4) is an autosomal dominant complex, genetically heterogeneous macular degeneration/dystrophy (MD) disorder. In this paper, we used targeted next generation sequencing and multiple molecular dynamics analyses to identify and characterize a disease-causing genetic variant in four generations of a Chinese family with STGD4-like MD. We found a novel heterozygous missense mutation, c.734T>C (p.L245P) in the PROM1 gene. Structurally, this mutation most likely impairs PROM1 protein stability, flexibility, and amino acid interaction network after changing the amino acid residue Leucine into Proline in the basic helix-loop-helix leucine zipper domain. Molecular dynamic simulation and principal component analysis provide compelling evidence that this PROM1 mutation contributes to disease causativeness or susceptibility variants in patients with STGD4-like MD. Thus, this finding defines new approaches in genetic characterization, accurate diagnosis, and prevention of STGD4-like MD. PMID:29416601
Chatterjee, Nilanjan; Kalaylioglu, Zeynep; Moslehi, Roxana; Peters, Ulrike; Wacholder, Sholom
2006-12-01
In modern genetic epidemiology studies, the association between the disease and a genomic region, such as a candidate gene, is often investigated using multiple SNPs. We propose a multilocus test of genetic association that can account for genetic effects that might be modified by variants in other genes or by environmental factors. We consider use of the venerable and parsimonious Tukey's 1-degree-of-freedom model of interaction, which is natural when individual SNPs within a gene are associated with disease through a common biological mechanism; in contrast, many standard regression models are designed as if each SNP has unique functional significance. On the basis of Tukey's model, we propose a novel but computationally simple generalized test of association that can simultaneously capture both the main effects of the variants within a genomic region and their interactions with the variants in another region or with an environmental exposure. We compared performance of our method with that of two standard tests of association, one ignoring gene-gene/gene-environment interactions and the other based on a saturated model of interactions. We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data.
Kringel, D; Ultsch, A; Zimmermann, M; Jansen, J-P; Ilias, W; Freynhagen, R; Griessinger, N; Kopf, A; Stein, C; Doehring, A; Resch, E; Lötsch, J
2017-01-01
Next-generation sequencing (NGS) provides unrestricted access to the genome, but it produces ‘big data’ exceeding in amount and complexity the classical analytical approaches. We introduce a bioinformatics-based classifying biomarker that uses emergent properties in genetics to separate pain patients requiring extremely high opioid doses from controls. Following precisely calculated selection of the 34 most informative markers in the OPRM1, OPRK1, OPRD1 and SIGMAR1 genes, pattern of genotypes belonging to either patient group could be derived using a k-nearest neighbor (kNN) classifier that provided a diagnostic accuracy of 80.6±4%. This outperformed alternative classifiers such as reportedly functional opioid receptor gene variants or complex biomarkers obtained via multiple regression or decision tree analysis. The accumulation of several genetic variants with only minor functional influences may result in a qualitative consequence affecting complex phenotypes, pointing at emergent properties in genetics. PMID:27139154
Kringel, D; Ultsch, A; Zimmermann, M; Jansen, J-P; Ilias, W; Freynhagen, R; Griessinger, N; Kopf, A; Stein, C; Doehring, A; Resch, E; Lötsch, J
2017-10-01
Next-generation sequencing (NGS) provides unrestricted access to the genome, but it produces 'big data' exceeding in amount and complexity the classical analytical approaches. We introduce a bioinformatics-based classifying biomarker that uses emergent properties in genetics to separate pain patients requiring extremely high opioid doses from controls. Following precisely calculated selection of the 34 most informative markers in the OPRM1, OPRK1, OPRD1 and SIGMAR1 genes, pattern of genotypes belonging to either patient group could be derived using a k-nearest neighbor (kNN) classifier that provided a diagnostic accuracy of 80.6±4%. This outperformed alternative classifiers such as reportedly functional opioid receptor gene variants or complex biomarkers obtained via multiple regression or decision tree analysis. The accumulation of several genetic variants with only minor functional influences may result in a qualitative consequence affecting complex phenotypes, pointing at emergent properties in genetics.
Personalized Approaches to Clopidogrel Therapy: Are We There Yet?
Anderson, Christopher D.; Biffi, Alessandro; Greenberg, Steven M.; Rosand, Jonathan
2010-01-01
Clopidogrel is one of the most commonly prescribed medications world-wide. Recent advisories from the US Food and Drug Administration (FDA) have drawn attention to the possibility of personalized decision-making for individuals who are candidates for clopidogrel. As is the case with antihypertensives, statins and warfarin, common genetic sequence variants can influence clopidogrel metabolism and its effect on platelet activity. These genetic variants have, in multiple studies, been associated with adverse clinical outcomes. Concurrent medication use also influences the body's handling of clopidogrel. Proton pump inhibitors, widely prescribed in conjunction with clopidogrel, may blunt its effectiveness. We address implications for bedside decision-making in light of accumulated data and current FDA advisories, and conclude that genetic testing for CYP2C19 genotype and limitation of PPI interactions do not yet appear to offer an opportunity to optimize treatment given the current state of knowledge. PMID:21030701
Determinants of virulence of influenza A virus
Schrauwen, Eefje J.A.; de Graaf, Miranda; Herfst, Sander; Rimmelzwaan, Guus F.; Osterhaus, Albert D.M.E.; Fouchier, Ron A.M.
2013-01-01
Influenza A viruses cause yearly seasonal epidemics and occasional global pandemics in humans. In the last century, four human influenza A virus pandemics have occured. Ocasionally, influenza A viruses that circulate in other species, cross the species barrier and infect humans. Virus re-assortment (i.e. mixing of gene segments of multiple viruses) and the accumulation of mutations contribute to the emergence of new influenza A virus variants. Fortunately, most of these variants do not have the ability to spread among humans and subsequently cause a pandemic. In this review we focus on the threat of animal influenza A viruses which have shown the ability to infect humans. In addition, genetic factors which could alter the virulence of influenza A viruses are discussed. Identification and characterization of these factors may provide insights into genetic traits which change virulence and help us to understand which genetic determinants are of importance for the pandemic potential of animal influenza A viruses. PMID:24078062
Pleiotropic analysis of cancer risk loci on esophageal adenocarcinoma risk
Lee, Eunjung; Stram, Daniel O.; Ek, Weronica E.; Onstad, Lynn E; MacGregor, Stuart; Gharahkhani, Puya; Ye, Weimin; Lagergren, Jesper; Shaheen, Nicholas J.; Murray, Liam J.; Hardie, Laura J; Gammon, Marilie D.; Chow, Wong-Ho; Risch, Harvey A.; Corley, Douglas A.; Levine, David M; Whiteman, David C.; Bernstein, Leslie; Bird, Nigel C.; Vaughan, Thomas L.; Wu, Anna H.
2015-01-01
Background Several cancer-associated loci identified from genome-wide association studies (GWAS) have been associated with risks of multiple cancer sites, suggesting pleiotropic effects. We investigated whether GWAS-identified risk variants for other common cancers are associated with risk of esophageal adenocarcinoma (EA) or its precursor, Barrett's esophagus (BE). Methods We examined the associations between risks of EA and BE and 387 single nucleotide polymorphisms (SNPs) that have been associated with risks of other cancers, by using genotype imputation data on 2,163 control participants and 3,885 (1,501 EA and 2,384 BE) case patients from the Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study, and investigated effect modification by smoking history, body mass index (BMI), and reflux/heartburn. Results After correcting for multiple testing, none of the tested 387 SNPs were statistically significantly associated with risk of EA or BE. No evidence of effect modification by smoking, BMI, or reflux/heartburn was observed. Conclusions Genetic risk variants for common cancers identified from GWAS appear not to be associated with risks of EA or BE. Impact To our knowledge, this is the first investigation of pleiotropic genetic associations with risks of EA and BE. PMID:26364162
Verma, Kapil; Sharma, Sapna; Sharma, Arun; Dalal, Jyoti; Bhardwaj, Tapeshwar
2018-06-01
Genetic variations among humans occur both within and among populations and range from single nucleotide changes to multiple-nucleotide variants. These multiple-nucleotide variants are useful for studying the relationships among individuals or various population groups. The study of human genetic variations can help scientists understand how different population groups are biologically related to one another. Sequence analysis of hypervariable regions of human mitochondrial DNA (mtDNA) has been successfully used for the genetic characterization of different population groups for forensic purposes. It is well established that different ethnic or population groups differ significantly in their mtDNA distributions. In the last decade, very little research has been conducted on mtDNA variations in the Indian population, although such data would be useful for elucidating the history of human population expansion across the world. Moreover, forensic studies on mtDNA variations in the Indian subcontinent are also scarce, particularly in the northern part of India. In this report, variations in the hypervariable regions of mtDNA were analyzed in the Yadav population of Haryana. Different molecular diversity indices were computed. Further, the obtained haplotypes were classified into different haplogroups and the phylogenetic relationship between different haplogroups was inferred.
Genetic variations in taste perception modify alcohol drinking behavior in Koreans.
Choi, Jeong-Hwa; Lee, Jeonghee; Yang, Sarah; Kim, Jeongseon
2017-06-01
The sensory components of alcohol affect the onset of individual's drinking. Therefore, variations in taste receptor genes may lead to differential sensitivity for alcohol taste, which may modify an individual's drinking behavior. This study examined the influence of genetic variants in the taste-sensing mechanism on alcohol drinking behavior and the choice of alcoholic beverages. A total of 1829 Koreans were analyzed for their alcohol drinking status (drinker/non-drinker), total alcohol consumption (g/day), heavy drinking (≥30 g/day) and type of regularly consumed alcoholic beverages. Twenty-one genetic variations in bitterness, sweetness, umami and fatty acid sensing were also genotyped. Our findings suggested that multiple genetic variants modified individuals' alcohol drinking behavior. Genetic variations in the T2R bitterness receptor family were associated with overall drinking behavior. Subjects with the TAS2R38 AVI haplotype were less likely to be a drinker [odds ratio (OR): 0.75, 95% confidence interval (CI): 0.59-0.95], and TAS2R5 rs2227264 predicted the level of total alcohol consumption (p = 0.01). In contrast, the T1R sweet and umami receptor family was associated with heavy drinking. TAS1R3 rs307355 CT carriers were more likely to be heavy drinkers (OR: 1.53, 95% CI: 1.06-2.19). The genetic variants were also associated with the choice of alcoholic beverages. The homo-recessive type of TAS2R4 rs2233998 (OR: 1.62, 95% CI: 1.11-2.37) and TAS2R5 rs2227264 (OR: 1.72, 95% CI: 1.14-2.58) were associated with consumption of rice wine. However, TAS1R2 rs35874116 was associated with wine drinking (OR: 0.65, 95% CI: 0.43-0.98) and the consumption level (p = 0.04). These findings suggest that multiple genetic variations in taste receptors influence drinking behavior in Koreans. Genetic variations are also responsible for the preference of particular alcoholic beverages, which may contribute to an individual's alcohol drinking behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.
Whiffin, Nicola; Walsh, Roddy; Govind, Risha; Edwards, Matthew; Ahmad, Mian; Zhang, Xiaolei; Tayal, Upasana; Buchan, Rachel; Midwinter, William; Wilk, Alicja E; Najgebauer, Hanna; Francis, Catherine; Wilkinson, Sam; Monk, Thomas; Brett, Laura; O'Regan, Declan P; Prasad, Sanjay K; Morris-Rosendahl, Deborah J; Barton, Paul J R; Edwards, Elizabeth; Ware, James S; Cook, Stuart A
2018-01-25
PurposeInternationally adopted variant interpretation guidelines from the American College of Medical Genetics and Genomics (ACMG) are generic and require disease-specific refinement. Here we developed CardioClassifier (http://www.cardioclassifier.org), a semiautomated decision-support tool for inherited cardiac conditions (ICCs).MethodsCardioClassifier integrates data retrieved from multiple sources with user-input case-specific information, through an interactive interface, to support variant interpretation. Combining disease- and gene-specific knowledge with variant observations in large cohorts of cases and controls, we refined 14 computational ACMG criteria and created three ICC-specific rules.ResultsWe benchmarked CardioClassifier on 57 expertly curated variants and show full retrieval of all computational data, concordantly activating 87.3% of rules. A generic annotation tool identified fewer than half as many clinically actionable variants (64/219 vs. 156/219, Fisher's P = 1.1 × 10 -18 ), with important false positives, illustrating the critical importance of disease and gene-specific annotations. CardioClassifier identified putatively disease-causing variants in 33.7% of 327 cardiomyopathy cases, comparable with leading ICC laboratories. Through addition of manually curated data, variants found in over 40% of cardiomyopathy cases are fully annotated, without requiring additional user-input data.ConclusionCardioClassifier is an ICC-specific decision-support tool that integrates expertly curated computational annotations with case-specific data to generate fast, reproducible, and interactive variant pathogenicity reports, according to best practice guidelines.GENETICS in MEDICINE advance online publication, 25 January 2018; doi:10.1038/gim.2017.258.
Overview of the Genetics of Alcohol Use Disorder
Tawa, Elisabeth A.; Hall, Samuel D.; Lohoff, Falk W.
2016-01-01
Aims Alcohol Use Disorder (AUD) is a chronic psychiatric illness characterized by harmful drinking patterns leading to negative emotional, physical, and social ramifications. While the underlying pathophysiology of AUD is poorly understood, there is substantial evidence for a genetic component; however, identification of universal genetic risk variants for AUD has been difficult. Recent efforts in the search for AUD susceptibility genes will be reviewed in this article. Methods In this review, we provide an overview of genetic studies on AUD, including twin studies, linkage studies, candidate gene studies, and genome-wide association studies (GWAS). Results Several potential genetic susceptibility factors for AUD have been identified, but the genes of alcohol metabolism, alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), have been found to be protective against the development of AUD. GWAS have also identified a heterogeneous list of SNPs associated with AUD and alcohol-related phenotypes, emphasizing the complexity and heterogeneity of the disorder. In addition, many of these findings have small effect sizes when compared to alcohol metabolism genes, and biological relevance is often unknown. Conclusions Although studies spanning multiple approaches have suggested a genetic basis for AUD, identification of the genetic risk variants has been challenging. Some promising results are emerging from GWAS studies; however, larger sample sizes are needed to improve GWAS results and resolution. As the field of genetics is rapidly developing, whole genome sequencing could soon become the new standard of interrogation of the genes and neurobiological pathways which contribute to the complex phenotype of AUD. Short summary This review examines the genetic underpinnings of Alcohol Use Disorder (AUD), with an emphasis on GWAS approaches for identifying genetic risk variants. The most promising results associated with AUD and alcohol-related phenotypes have included SNPs of the alcohol metabolism genes ADH and ALDH. PMID:27445363
Could age modify the effect of genetic variants in IL6 and TNF-α genes in multiple myeloma?
Martino, Alessandro; Buda, Gabriele; Maggini, Valentina; Lapi, Francesco; Lupia, Antonella; Di Bello, Domenica; Orciuolo, Enrico; Galimberti, Sara; Barale, Roberto; Petrini, Mario; Rossi, Anna Maria
2012-05-01
Cytokines play a central role in multiple myeloma (MM) pathogenesis thus genetic variations within cytokines coding genes could influence MM susceptibility and therapy outcome. We investigated the impact of 8 SNPs in these genes in 202 MM cases and 235 controls also evaluating their impact on therapy outcome in a subset of 91 patients. Despite the overall negative findings, we found a significant age-modified effect of IL6 and TNF-α SNPs, on MM risk and therapy outcome, respectively. Therefore, this observation suggests that genetic variation in inflammation-related genes could be an important mediator of the complex interplay between ageing and cancer. Copyright © 2012 Elsevier Ltd. All rights reserved.
Genetic Structures of Copy Number Variants Revealed by Genotyping Single Sperm
Luo, Minjie; Cui, Xiangfeng; Fredman, David; Brookes, Anthony J.; Azaro, Marco A.; Greenawalt, Danielle M.; Hu, Guohong; Wang, Hui-Yun; Tereshchenko, Irina V.; Lin, Yong; Shentu, Yue; Gao, Richeng; Shen, Li; Li, Honghua
2009-01-01
Background Copy number variants (CNVs) occupy a significant portion of the human genome and may have important roles in meiotic recombination, human genome evolution and gene expression. Many genetic diseases may be underlain by CNVs. However, because of the presence of their multiple copies, variability in copy numbers and the diploidy of the human genome, detailed genetic structure of CNVs cannot be readily studied by available techniques. Methodology/Principal Findings Single sperm samples were used as the primary subjects for the study so that CNV haplotypes in the sperm donors could be studied individually. Forty-eight CNVs characterized in a previous study were analyzed using a microarray-based high-throughput genotyping method after multiplex amplification. Seventeen single nucleotide polymorphisms (SNPs) were also included as controls. Two single-base variants, either allelic or paralogous, could be discriminated for all markers. Microarray data were used to resolve SNP alleles and CNV haplotypes, to quantitatively assess the numbers and compositions of the paralogous segments in each CNV haplotype. Conclusions/Significance This is the first study of the genetic structure of CNVs on a large scale. Resulting information may help understand evolution of the human genome, gain insight into many genetic processes, and discriminate between CNVs and SNPs. The highly sensitive high-throughput experimental system with haploid sperm samples as subjects may be used to facilitate detailed large-scale CNV analysis. PMID:19384415
Coleman, Jonathan R. I.; Roberts, Susanna; Keers, Robert; Breen, Gerome; Bögels, Susan; Creswell, Cathy; Hudson, Jennifer L.; McKinnon, Anna; Nauta, Maaike; Rapee, Ronald M.; Schneider, Silvia; Silverman, Wendy K.; Thastum, Mikael; Waite, Polly; Wergeland, Gro Janne H.; Eley, Thalia C.
2016-01-01
Extinction learning is an important mechanism in the successful psychological treatment of anxiety. Individual differences in response and relapse following Cognitive Behavior Therapy may in part be explained by variability in the ease with which fears are extinguished or the vulnerability of these fears to re‐emerge. Given the role of the endocannabinoid system in fear extinction, this study investigates whether genetic variation in the endocannabinoid system explains individual differences in response to CBT. Children (N = 1,309) with a primary anxiety disorder diagnosis were recruited. We investigated the relationship between variation in the CNR1, CNR2, and FAAH genes and change in primary anxiety disorder severity between pre‐ and post‐treatment and during the follow‐up period in the full sample and a subset with fear‐based anxiety disorder diagnoses. Change in symptom severity during active treatment was nominally associated (P < 0.05) with two SNPs. During the follow‐up period, five SNPs were nominally associated with a poorer treatment response (rs806365 [CNR1]; rs2501431 [CNR2]; rs2070956 [CNR2]; rs7769940 [CNR1]; rs2209172 [FAAH]) and one with a more favorable response (rs6928813 [CNR1]). Within the fear‐based subset, the effect of rs806365 survived multiple testing corrections (P < 0.0016). We found very limited evidence for an association between variants in endocannabinoid system genes and treatment response once multiple testing corrections were applied. Larger, more homogenous cohorts are needed to allow the identification of variants of small but statistically significant effect and to estimate effect sizes for these variants with greater precision in order to determine their potential clinical utility. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc. PMID:27346075
Pharmacogenetics of drug-metabolizing enzymes in US Hispanics
Duconge, Jorge; Cadilla, Carmen L.; Ruaño, Gualberto
2015-01-01
Although the Hispanic population is continuously growing in the United States, they are underrepresented in pharmacogenetic studies. This review addresses the need for compiling available pharmacogenetic data in US Hispanics, discussing the prevalence of clinically relevant polymorphisms in pharmacogenes encoding for drug-metabolizing enzymes. CYP3A5*3 (0.245–0.867) showed the largest frequency in a US Hispanic population. A higher prevalence of CYP2C9*3, CYP2C19*4, and UGT2B7 IVS1+985 A>Gwas observed in US Hispanic vs. non-Hispanic populations. We found interethnic and intraethnic variability in frequencies of genetic polymorphisms for metabolizing enzymes, which highlights the need to define the ancestries of participants in pharmacogenetic studies. New approaches should be integrated in experimental designs to gain knowledge about the clinical relevance of the unique combination of genetic variants occurring in this admixed population. Ethnic subgroups in the US Hispanic population may harbor variants that might be part of multiple causative loci or in linkage-disequilibrium with functional variants. Pharmacogenetic studies in Hispanics should not be limited to ascertain commonly studied polymorphisms that were originally identified in their parental populations. The success of the Personalized Medicine paradigm will depend on recognizing genetic diversity between and within US Hispanics and the uniqueness of their genetic backgrounds. PMID:25431893
Zheng, Wei; Zhang, Ben; Cai, Qiuyin; Sung, Hyuna; Michailidou, Kyriaki; Shi, Jiajun; Choi, Ji-Yeob; Long, Jirong; Dennis, Joe; Humphreys, Manjeet K.; Wang, Qin; Lu, Wei; Gao, Yu-Tang; Li, Chun; Cai, Hui; Park, Sue K.; Yoo, Keun-Young; Noh, Dong-Young; Han, Wonshik; Dunning, Alison M.; Benitez, Javier; Vincent, Daniel; Bacot, Francois; Tessier, Daniel; Kim, Sung-Won; Lee, Min Hyuk; Lee, Jong Won; Lee, Jong-Young; Xiang, Yong-Bing; Zheng, Ying; Wang, Wenjin; Ji, Bu-Tian; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tanaka, Hideo; Wu, Anna H.; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O.; Teo, Soo Hwang; Yip, Cheng Har; Kang, In Nee; Wong, Tien Y.; Shen, Chen-Yang; Yu, Jyh-Cherng; Huang, Chiun-Sheng; Hou, Ming-Feng; Hartman, Mikael; Miao, Hui; Lee, Soo Chin; Putti, Thomas Choudary; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Sangrajrang, Suleeporn; Shen, Hongbing; Chen, Kexin; Wu, Pei-Ei; Ren, Zefang; Haiman, Christopher A.; Sueta, Aiko; Kim, Mi Kyung; Khoo, Ui Soon; Iwasaki, Motoki; Pharoah, Paul D.P.; Wen, Wanqing; Hall, Per; Shu, Xiao-Ou; Easton, Douglas F.; Kang, Daehee
2013-01-01
In a consortium including 23 637 breast cancer patients and 25 579 controls of East Asian ancestry, we investigated 70 single-nucleotide polymorphisms (SNPs) in 67 independent breast cancer susceptibility loci recently identified by genome-wide association studies (GWASs) conducted primarily in European-ancestry populations. SNPs in 31 loci showed an association with breast cancer risk at P < 0.05 in a direction consistent with that reported previously. Twenty-one of them remained statistically significant after adjusting for multiple comparisons with the Bonferroni-corrected significance level of <0.0015. Eight of the 70 SNPs showed a significantly different association with breast cancer risk by estrogen receptor (ER) status at P < 0.05. With the exception of rs2046210 at 6q25.1, the seven other SNPs showed a stronger association with ER-positive than ER-negative cancer. This study replicated all five genetic risk variants initially identified in Asians and provided evidence for associations of breast cancer risk in the East Asian population with nearly half of the genetic risk variants initially reported in GWASs conducted in European descendants. Taken together, these common genetic risk variants explain ∼10% of excess familial risk of breast cancer in Asian populations. PMID:23535825
Genome-wide association study reveals putative regulators of bioenergy traits in Populus deltoides
Fahrenkrog, Annette M.; Neves, Leandro G.; Resende, Jr., Marcio F. R.; ...
2016-09-06
Genome-wide association studies (GWAS) have been used extensively to dissect the genetic regulation of complex traits in plants. These studies have focused largely on the analysis of common genetic variants despite the abundance of rare polymorphisms in several species, and their potential role in trait variation. Here, we conducted the first GWAS in Populus deltoides, a genetically diverse keystone forest species in North America and an important short rotation woody crop for the bioenergy industry. We searched for associations between eight growth and wood composition traits, and common and low-frequency single-nucleotide polymorphisms detected by targeted resequencing of 18 153 genesmore » in a population of 391 unrelated individuals. To increase power to detect associations with low-frequency variants, multiple-marker association tests were used in combination with single-marker association tests. Significant associations were discovered for all phenotypes and are indicative that low-frequency polymorphisms contribute to phenotypic variance of several bioenergy traits. Our results suggest that both common and low-frequency variants need to be considered for a comprehensive understanding of the genetic regulation of complex traits, particularly in species that carry large numbers of rare polymorphisms. Lastly, these polymorphisms may be critical for the development of specialized plant feedstocks for bioenergy.« less
A rare variant in COL11A1 is strongly associated with adult height in Chinese Han population.
Shen, Changbing; Zheng, Xiaodong; Gao, Jing; Zhu, Caihong; Ko, Randy; Tang, Xianfa; Yang, Chao; Dou, Jinfa; Lin, Yan; Cheng, Yuyan; Liu, Lu; Xu, Shuangjun; Chen, Gang; Zuo, Xianbo; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Yang, Sen; Zhang, Xuejun; Zhou, Fusheng
2016-09-20
Human height is a highly heritable trait in which multiple genes are involved. Recent genome-wide association studies (GWASs) have identified that COL11A1 is an important susceptibility gene for human height. To determine whether the variants of COL11A1 are associated with adult and children height, we analyzed splicing and coding single-nucleotide variants across COL11A1 through exome-targeted sequencing and two validation stages with a total 20,426 Chinese Han samples. A total of 105 variants were identified by exome-targeted sequencing, of which 30 SNPs were located in coding region. The strongest association signal was Chr1_103380393 with P value of 4.8 × 10(-7). Chr1_103380393 also showed nominal significance in the validation stage (P = 1.21 × 10(-6)). Combined analysis of 16,738 samples strengthened the original association of chr1_103380393 with adult height (Pcombined = 3.1 × 10(-8)), with an increased height of 0.292sd (standard deviation) per G allele (95% CI: 0.19-0.40). There was no evidence (P = 0.843) showing that chr1_103380393 altered child height in 3688 child samples. Only the group of 12-15 years showed slight significance with P value of 0.0258. This study firstly shows that genetic variants of COL11A1 contribute to adult height in Chinese Han population but not to children height, which expand our knowledge of the genetic factors underlying height variation and the biological regulation of human height. Copyright © 2016 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. All rights reserved.
Pathway-based variant enrichment analysis on the example of dilated cardiomyopathy.
Backes, Christina; Meder, Benjamin; Lai, Alan; Stoll, Monika; Rühle, Frank; Katus, Hugo A; Keller, Andreas
2016-01-01
Genome-wide association (GWA) studies have significantly contributed to the understanding of human genetic variation and its impact on clinical traits. Frequently only a limited number of highly significant associations were considered as biologically relevant. Increasingly, network analysis of affected genes is used to explore the potential role of the genetic background on disease mechanisms. Instead of first determining affected genes or calculating scores for genes and performing pathway analysis on the gene level, we integrated both steps and directly calculated enrichment on the genetic variant level. The respective approach has been tested on dilated cardiomyopathy (DCM) GWA data as showcase. To compute significance values, 5000 permutation tests were carried out and p values were adjusted for multiple testing. For 282 KEGG pathways, we computed variant enrichment scores and significance values. Of these, 65 were significant. Surprisingly, we discovered the "nucleotide excision repair" and "tuberculosis" pathways to be most significantly associated with DCM (p = 10(-9)). The latter pathway is driven by genes of the HLA-D antigen group, a finding that closely resembles previous discoveries made by expression quantitative trait locus analysis in the context of DCM-GWA. Next, we implemented a sub-network-based analysis, which searches for affected parts of KEGG, however, independent on the pre-defined pathways. Here, proteins of the contractile apparatus of cardiac cells as well as the FAS sub-network were found to be affected by common polymorphisms in DCM. In this work, we performed enrichment analysis directly on variants, leveraging the potential to discover biological information in thousands of published GWA studies. The applied approach is cutoff free and considers a ranked list of genetic variants as input.
Identification of Inherited Retinal Disease-Associated Genetic Variants in 11 Candidate Genes.
Astuti, Galuh D N; van den Born, L Ingeborgh; Khan, M Imran; Hamel, Christian P; Bocquet, Béatrice; Manes, Gaël; Quinodoz, Mathieu; Ali, Manir; Toomes, Carmel; McKibbin, Martin; El-Asrag, Mohammed E; Haer-Wigman, Lonneke; Inglehearn, Chris F; Black, Graeme C M; Hoyng, Carel B; Cremers, Frans P M; Roosing, Susanne
2018-01-10
Inherited retinal diseases (IRDs) display an enormous genetic heterogeneity. Whole exome sequencing (WES) recently identified genes that were mutated in a small proportion of IRD cases. Consequently, finding a second case or family carrying pathogenic variants in the same candidate gene often is challenging. In this study, we searched for novel candidate IRD gene-associated variants in isolated IRD families, assessed their causality, and searched for novel genotype-phenotype correlations. Whole exome sequencing was performed in 11 probands affected with IRDs. Homozygosity mapping data was available for five cases. Variants with minor allele frequencies ≤ 0.5% in public databases were selected as candidate disease-causing variants. These variants were ranked based on their: (a) presence in a gene that was previously implicated in IRD; (b) minor allele frequency in the Exome Aggregation Consortium database (ExAC); (c) in silico pathogenicity assessment using the combined annotation dependent depletion (CADD) score; and (d) interaction of the corresponding protein with known IRD-associated proteins. Twelve unique variants were found in 11 different genes in 11 IRD probands. Novel autosomal recessive and dominant inheritance patterns were found for variants in Small Nuclear Ribonucleoprotein U5 Subunit 200 ( SNRNP200 ) and Zinc Finger Protein 513 ( ZNF513 ), respectively. Using our pathogenicity assessment, a variant in DEAH-Box Helicase 32 ( DHX32 ) was the top ranked novel candidate gene to be associated with IRDs, followed by eight medium and lower ranked candidate genes. The identification of candidate disease-associated sequence variants in 11 single families underscores the notion that the previously identified IRD-associated genes collectively carry > 90% of the defects implicated in IRDs. To identify multiple patients or families with variants in the same gene and thereby provide extra proof for pathogenicity, worldwide data sharing is needed.
Viazovaia, A A; Solov'eva, N S; Zhuravlev, V Iu; Mokrousov, I V; Manicheva, O A; Vishnevskiĭ, B I; Narvskaia, O V
2013-01-01
Molecular-genetic characteristic of M. tuberculosis strains isolated from operation material of patients with tuberculous spondylitis. 107 strains of M. tuberculosis isolated in 2007 - 2011 from patients with spine tuberculosis were studied by methods of spoligotyping and MIRU-VNTR by 12 and 24 loci. Strains of genetic family Beijing dominated (n = 80), 78% of those had multiple drug resistance (MDR). Strains of genetic families T, H3 (Ural), LAM, Manu, H4 and S were also detected. Differentiating of 80 strains of Beijing genotype by MIRU-VNTR method by 24 loci revealed 24 variants (HGI = 0.83) including 7 clusters, the largest of those (100-32) included 23 strains (87% MDR). The leading role of Beijing genotype M. tuberculosis strains in development of tuberculous spondylitis with multiple drug resistance of the causative agent is shown.
Anaya, Juan-Manuel; Kim-Howard, Xana; Prahalad, Sampath; Cherñavsky, Alejandra; Cañas, Carlos; Rojas-Villarraga, Adriana; Bohnsack, John; Jonsson, Roland; Bolstad, Anne Isine; Brun, Johan G; Cobb, Beth; Moser, Kathy L; James, Judith A; Harley, John B; Nath, Swapan K
2012-02-01
Many autoimmune diseases (ADs) share similar underlying pathology and have a tendency to cluster within families, supporting the involvement of shared susceptibility genes. To date, most of the genetic variants associated with systemic lupus erythematosus (SLE) susceptibility also show association with others ADs. ITGAM and its associated 'predisposing' variant (rs1143679, Arg77His), predicted to alter the tertiary structures of the ligand-binding domain of ITGAM, may play a key role for SLE pathogenesis. The aim of this study is to examine whether the ITGAM variant is also associated with other ADs. We evaluated case-control association between rs1143679 and ADs (N=18,457) including primary Sjögren's syndrome, systemic sclerosis, multiple sclerosis, rheumatoid arthritis, juvenile idiopathic arthritis, celiac disease, and type-1 diabetes. We also performed meta-analyses using our data in addition to available published data. Although the risk allele 'A' is relatively more frequent among cases for each disease, it was not significantly associated with any other ADs tested in this study. However, the meta-analysis for systemic sclerosis was associated with rs1143679 (p(meta)=0.008). In summary, this study explored the role of ITGAM in general autoimmunity in seven non-lupus ADs, and only found association for systemic sclerosis when our results were combined with published results. Thus ITGAM may not be a general autoimmunity gene but this variant may be specifically associated with SLE and systemic sclerosis. Copyright © 2011 Elsevier B.V. All rights reserved.
Koel, Björn F.; van der Vliet, Stefan; Burke, David F.; Bestebroer, Theo M.; Bharoto, Eny E.; Yasa, I. Wayan W.; Herliana, Inna; Laksono, Brigitta M.; Xu, Kemin; Skepner, Eugene; Russell, Colin A.; Rimmelzwaan, Guus F.; Perez, Daniel R.; Osterhaus, Albert D. M. E.; Smith, Derek J.; Prajitno, Teguh Y.
2014-01-01
ABSTRACT Highly pathogenic avian influenza (HPAI) viruses of the H5N1 subtype are genetically highly variable and have diversified into multiple phylogenetic clades over the past decade. Antigenic drift is a well-studied phenomenon for seasonal human influenza viruses, but much less is known about the antigenic evolution of HPAI H5N1 viruses that circulate in poultry. In this study, we focused on HPAI H5N1 viruses that are enzootic to Indonesia. We selected representative viruses from genetically distinct lineages that are currently circulating and determined their antigenic properties by hemagglutination inhibition assays. At least six antigenic variants have circulated between 2003, when H5N1 clade 2.1 viruses were first detected in Indonesia, and 2011. During this period, multiple antigenic variants cocirculated in the same geographic regions. Mutant viruses were constructed by site-directed mutagenesis to represent each of the circulating antigenic variants, revealing that antigenic differences between clade 2.1 viruses were due to only one or very few amino acid substitutions immediately adjacent to the receptor binding site. Antigenic variants of H5N1 virus evaded recognition by both ferret and chicken antibodies. The molecular basis for antigenic change in clade 2.1 viruses closely resembled that of seasonal human influenza viruses, indicating that the hemagglutinin of influenza viruses from different hosts and subtypes may be similarly restricted to evade antibody recognition. PMID:24917596
Applications of the 1000 Genomes Project resources.
Zheng-Bradley, Xiangqun; Flicek, Paul
2017-05-01
The 1000 Genomes Project created a valuable, worldwide reference for human genetic variation. Common uses of the 1000 Genomes dataset include genotype imputation supporting Genome-wide Association Studies, mapping expression Quantitative Trait Loci, filtering non-pathogenic variants from exome, whole genome and cancer genome sequencing projects, and genetic analysis of population structure and molecular evolution. In this article, we will highlight some of the multiple ways that the 1000 Genomes data can be and has been utilized for genetic studies. © The Author 2016. Published by Oxford University Press.
Rare variants in axonogenesis genes connect three families with sound-color synesthesia.
Tilot, Amanda K; Kucera, Katerina S; Vino, Arianna; Asher, Julian E; Baron-Cohen, Simon; Fisher, Simon E
2018-03-20
Synesthesia is a rare nonpathological phenomenon where stimulation of one sense automatically provokes a secondary perception in another. Hypothesized to result from differences in cortical wiring during development, synesthetes show atypical structural and functional neural connectivity, but the underlying molecular mechanisms are unknown. The trait also appears to be more common among people with autism spectrum disorder and savant abilities. Previous linkage studies searching for shared loci of large effect size across multiple families have had limited success. To address the critical lack of candidate genes, we applied whole-exome sequencing to three families with sound-color (auditory-visual) synesthesia affecting multiple relatives across three or more generations. We identified rare genetic variants that fully cosegregate with synesthesia in each family, uncovering 37 genes of interest. Consistent with reports indicating genetic heterogeneity, no variants were shared across families. Gene ontology analyses highlighted six genes- COL4A1 , ITGA2 , MYO10 , ROBO3 , SLC9A6 , and SLIT2 -associated with axonogenesis and expressed during early childhood when synesthetic associations are formed. These results are consistent with neuroimaging-based hypotheses about the role of hyperconnectivity in the etiology of synesthesia and offer a potential entry point into the neurobiology that organizes our sensory experiences. Copyright © 2018 the Author(s). Published by PNAS.
General Framework for Meta-analysis of Rare Variants in Sequencing Association Studies
Lee, Seunggeun; Teslovich, Tanya M.; Boehnke, Michael; Lin, Xihong
2013-01-01
We propose a general statistical framework for meta-analysis of gene- or region-based multimarker rare variant association tests in sequencing association studies. In genome-wide association studies, single-marker meta-analysis has been widely used to increase statistical power by combining results via regression coefficients and standard errors from different studies. In analysis of rare variants in sequencing studies, region-based multimarker tests are often used to increase power. We propose meta-analysis methods for commonly used gene- or region-based rare variants tests, such as burden tests and variance component tests. Because estimation of regression coefficients of individual rare variants is often unstable or not feasible, the proposed method avoids this difficulty by calculating score statistics instead that only require fitting the null model for each study and then aggregating these score statistics across studies. Our proposed meta-analysis rare variant association tests are conducted based on study-specific summary statistics, specifically score statistics for each variant and between-variant covariance-type (linkage disequilibrium) relationship statistics for each gene or region. The proposed methods are able to incorporate different levels of heterogeneity of genetic effects across studies and are applicable to meta-analysis of multiple ancestry groups. We show that the proposed methods are essentially as powerful as joint analysis by directly pooling individual level genotype data. We conduct extensive simulations to evaluate the performance of our methods by varying levels of heterogeneity across studies, and we apply the proposed methods to meta-analysis of rare variant effects in a multicohort study of the genetics of blood lipid levels. PMID:23768515
Temporal Expression Profiling Identifies Pathways Mediating Effect of Causal Variant on Phenotype
Gupta, Saumya; Radhakrishnan, Aparna; Raharja-Liu, Pandu; Lin, Gen; Steinmetz, Lars M.; Gagneur, Julien; Sinha, Himanshu
2015-01-01
Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants’ effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage of analyzing allele-specific transcriptional dynamics of mediating genes. Applications in higher eukaryotes can be valuable for inferring causal molecular pathways underlying complex dynamic processes, such as development, physiology and disease progression. PMID:26039065
Fejerman, Laura
2013-01-01
Hispanic women in the USA have lower breast cancer incidence than non-Hispanic white (NHW) women. Genetic factors may contribute to this difference. Breast cancer genome-wide association studies (GWAS) conducted in women of European or Asian descent have identified multiple risk variants. We tested the association between 10 previously reported single nucleotide polymorphisms (SNPs) and risk of breast cancer in a sample of 4697 Hispanic and 3077 NHW women recruited as part of three population-based case–control studies of breast cancer. We used stratified logistic regression analyses to compare the associations with different genetic variants in NHWs and Hispanics classified by their proportion of Indigenous American (IA) ancestry. Five of 10 SNPs were statistically significantly associated with breast cancer risk. Three of the five significant variants (rs17157903-RELN, rs7696175-TLR1 and rs13387042-2q35) were associated with risk among Hispanics but not in NHWs. The odds ratio (OR) for the heterozygous at 2q35 was 0.75 [95% confidence interval (CI) = 0.50–1.15] for low IA ancestry and 1.38 (95% CI = 1.04–1.82) for high IA ancestry (P interaction 0.02). The ORs for association at RELN were 0.87 (95% CI = 0.59–1.29) and 1.69 (95% CI = 1.04–2.73), respectively (P interaction 0.03). At the TLR1 locus, the ORs for women homozygous for the rare allele were 0.74 (95% CI = 0.42–1.31) and 1.73 (95% CI = 1.19–2.52) (P interaction 0.03). Our results suggest that the proportion of IA ancestry modifies the magnitude and direction of the association of 3 of the 10 previously reported variants. Genetic ancestry should be considered when assessing risk in women of mixed descent and in studies designed to discover causal mutations. PMID:23563089
A Novel aadA Aminoglycoside Resistance Gene in Bovine and Porcine Pathogens.
Cameron, Andrew; Klima, Cassidy L; Ha, Reuben; Gruninger, Robert J; Zaheer, Rahat; McAllister, Tim A
2018-01-01
A novel variant of the AAD(3″) class of aminoglycoside-modifying enzymes was discovered in fatal bovine respiratory disease-associated pathogens Pasteurella multocida and Histophilus somni . The aadA31 gene encodes a spectinomycin/streptomycin adenylyltransferase and was located in a variant of the integrative and conjugative element ICE Mh1 , a mobile genetic element transmissible among members of the family Pasteurellaceae . The gene was also detected in Mannheimia haemolytica from a case of porcine pneumonia and in Moraxella bovoculi from a case of keratoconjunctivitis. IMPORTANCE Aminoglycosides are important antimicrobials used worldwide for prophylaxis and/or therapy in multiple production animal species. The emergence of new resistance genes jeopardizes current pathogen detection and treatment methods. The risk of resistance gene transfer to other animal and human pathogens is elevated when resistance genes are carried by mobile genetic elements. This study identified a new variant of a spectinomycin/streptomycin resistance gene harbored in a self-transmissible mobile element. The gene was also present in four different bovine pathogen species.
A Novel aadA Aminoglycoside Resistance Gene in Bovine and Porcine Pathogens
Cameron, Andrew; Klima, Cassidy L.; Ha, Reuben; Gruninger, Robert J.; Zaheer, Rahat
2018-01-01
ABSTRACT A novel variant of the AAD(3″) class of aminoglycoside-modifying enzymes was discovered in fatal bovine respiratory disease-associated pathogens Pasteurella multocida and Histophilus somni. The aadA31 gene encodes a spectinomycin/streptomycin adenylyltransferase and was located in a variant of the integrative and conjugative element ICEMh1, a mobile genetic element transmissible among members of the family Pasteurellaceae. The gene was also detected in Mannheimia haemolytica from a case of porcine pneumonia and in Moraxella bovoculi from a case of keratoconjunctivitis. IMPORTANCE Aminoglycosides are important antimicrobials used worldwide for prophylaxis and/or therapy in multiple production animal species. The emergence of new resistance genes jeopardizes current pathogen detection and treatment methods. The risk of resistance gene transfer to other animal and human pathogens is elevated when resistance genes are carried by mobile genetic elements. This study identified a new variant of a spectinomycin/streptomycin resistance gene harbored in a self-transmissible mobile element. The gene was also present in four different bovine pathogen species. PMID:29507894
Chen, Li-Shiun; Saccone, Nancy L.; Culverhouse, Robert C.; Bracci, Paige M.; Chen, Chien-Hsiun; Dueker, Nicole; Han, Younghun; Huang, Hongyan; Jin, Guangfu; Kohno, Takashi; Ma, Jennie Z.; Przybeck, Thomas R.; Sanders, Alan R.; Smith, Jennifer A.; Sung, Yun Ju; Wenzlaff, Angie S.; Wu, Chen; Yoon, Dankyu; Chen, Ying-Ting; Cheng, Yu-Ching; Cho, Yoon Shin; David, Sean P.; Duan, Jubao; Eaton, Charles B.; Furberg, Helena; Goate, Alison M.; Gu, Dongfeng; Hansen, Helen M.; Hartz, Sarah; Hu, Zhibin; Kim, Young Jin; Kittner, Steven J.; Levinson, Douglas F.; Mosley, Thomas H.; Payne, Thomas J.; Rao, DC; Rice, John P.; Rice, Treva K.; Schwantes-An, Tae-Hwi; Shete, Sanjay S.; Shi, Jianxin; Spitz, Margaret R.; Sun, Yan V.; Tsai, Fuu-Jen; Wang, Jen C.; Wrensch, Margaret R.; Xian, Hong; Gejman, Pablo V.; He, Jiang; Hunt, Steven C.; Kardia, Sharon L.; Li, Ming D.; Lin, Dongxin; Mitchell, Braxton D.; Park, Taesung; Schwartz, Ann G.; Shen, Hongbing; Wiencke, John K.; Wu, Jer-Yuarn; Yokota, Jun; Amos, Christopher I.; Bierut, Laura J.
2012-01-01
Recent meta-analyses of European ancestry subjects show strong evidence for association between smoking quantity and multiple genetic variants on chromosome 15q25. This meta-analysis extends the examination of association between distinct genes in the CHRNA5-CHRNA3-CHRNB4 region and smoking quantity to Asian and African American populations to confirm and refine specific reported associations. Association results for a dichotomized cigarettes smoked per day (CPD) phenotype in 27 datasets (European ancestry (N=14,786), Asian (N=6,889), and African American (N=10,912) for a total of 32,587 smokers) were meta-analyzed by population and results were compared across all three populations. We demonstrate association between smoking quantity and markers in the chromosome 15q25 region across all three populations, and narrow the region of association. Of the variants tested, only rs16969968 is associated with smoking (p < 0.01) in each of these three populations (OR=1.33, 95%C.I.=1.25–1.42, p=1.1×10−17 in meta-analysis across all population samples). Additional variants displayed a consistent signal in both European ancestry and Asian datasets, but not in African Americans. The observed consistent association of rs16969968 with heavy smoking across multiple populations, combined with its known biological significance, suggests rs16969968 is most likely a functional variant that alters risk for heavy smoking. We interpret additional association results that differ across populations as providing evidence for additional functional variants, but we are unable to further localize the source of this association. Using the cross-population study paradigm provides valuable insights to narrow regions of interest and inform future biological experiments. PMID:22539395
Chen, Li-Shiun; Saccone, Nancy L; Culverhouse, Robert C; Bracci, Paige M; Chen, Chien-Hsiun; Dueker, Nicole; Han, Younghun; Huang, Hongyan; Jin, Guangfu; Kohno, Takashi; Ma, Jennie Z; Przybeck, Thomas R; Sanders, Alan R; Smith, Jennifer A; Sung, Yun Ju; Wenzlaff, Angie S; Wu, Chen; Yoon, Dankyu; Chen, Ying-Ting; Cheng, Yu-Ching; Cho, Yoon Shin; David, Sean P; Duan, Jubao; Eaton, Charles B; Furberg, Helena; Goate, Alison M; Gu, Dongfeng; Hansen, Helen M; Hartz, Sarah; Hu, Zhibin; Kim, Young Jin; Kittner, Steven J; Levinson, Douglas F; Mosley, Thomas H; Payne, Thomas J; Rao, D C; Rice, John P; Rice, Treva K; Schwantes-An, Tae-Hwi; Shete, Sanjay S; Shi, Jianxin; Spitz, Margaret R; Sun, Yan V; Tsai, Fuu-Jen; Wang, Jen C; Wrensch, Margaret R; Xian, Hong; Gejman, Pablo V; He, Jiang; Hunt, Steven C; Kardia, Sharon L; Li, Ming D; Lin, Dongxin; Mitchell, Braxton D; Park, Taesung; Schwartz, Ann G; Shen, Hongbing; Wiencke, John K; Wu, Jer-Yuarn; Yokota, Jun; Amos, Christopher I; Bierut, Laura J
2012-05-01
Recent meta-analyses of European ancestry subjects show strong evidence for association between smoking quantity and multiple genetic variants on chromosome 15q25. This meta-analysis extends the examination of association between distinct genes in the CHRNA5-CHRNA3-CHRNB4 region and smoking quantity to Asian and African American populations to confirm and refine specific reported associations. Association results for a dichotomized cigarettes smoked per day phenotype in 27 datasets (European ancestry (N = 14,786), Asian (N = 6,889), and African American (N = 10,912) for a total of 32,587 smokers) were meta-analyzed by population and results were compared across all three populations. We demonstrate association between smoking quantity and markers in the chromosome 15q25 region across all three populations, and narrow the region of association. Of the variants tested, only rs16969968 is associated with smoking (P < 0.01) in each of these three populations (odds ratio [OR] = 1.33, 95% CI = 1.25-1.42, P = 1.1 × 10(-17) in meta-analysis across all population samples). Additional variants displayed a consistent signal in both European ancestry and Asian datasets, but not in African Americans. The observed consistent association of rs16969968 with heavy smoking across multiple populations, combined with its known biological significance, suggests rs16969968 is most likely a functional variant that alters risk for heavy smoking. We interpret additional association results that differ across populations as providing evidence for additional functional variants, but we are unable to further localize the source of this association. Using the cross-population study paradigm provides valuable insights to narrow regions of interest and inform future biological experiments. © 2012 Wiley Periodicals, Inc.
Li, Yong; Sekula, Peggy; Wuttke, Matthias; Wahrheit, Judith; Hausknecht, Birgit; Schultheiss, Ulla T; Gronwald, Wolfram; Schlosser, Pascal; Tucci, Sara; Ekici, Arif B; Spiekerkoetter, Ute; Kronenberg, Florian; Eckardt, Kai-Uwe; Oefner, Peter J; Köttgen, Anna
2018-05-01
Background The kidneys have a central role in the generation, turnover, transport, and excretion of metabolites, and these functions can be altered in CKD. Genetic studies of metabolite concentrations can identify proteins performing these functions. Methods We conducted genome-wide association studies and aggregate rare variant tests of the concentrations of 139 serum metabolites and 41 urine metabolites, as well as their pairwise ratios and fractional excretions in up to 1168 patients with CKD. Results After correction for multiple testing, genome-wide significant associations were detected for 25 serum metabolites, two urine metabolites, and 259 serum and 14 urinary metabolite ratios. These included associations already known from population-based studies. Additional findings included an association for the uremic toxin putrescine and variants upstream of an enzyme catalyzing the oxidative deamination of polyamines ( AOC1 , P -min=2.4×10 -12 ), a relatively high carrier frequency (2%) for rare deleterious missense variants in ACADM that are collectively associated with serum ratios of medium-chain acylcarnitines ( P -burden=6.6×10 -16 ), and associations of a common variant in SLC7A9 with several ratios of lysine to neutral amino acids in urine, including the lysine/glutamine ratio ( P =2.2×10 -23 ). The associations of this SLC7A9 variant with ratios of lysine to specific neutral amino acids were much stronger than the association with lysine concentration alone. This finding is consistent with SLC7A9 functioning as an exchanger of urinary cationic amino acids against specific intracellular neutral amino acids at the apical membrane of proximal tubular cells. Conclusions Metabolomic indices of specific kidney functions in genetic studies may provide insight into human renal physiology. Copyright © 2018 by the American Society of Nephrology.
Alosi, Daniela; Bisgaard, Marie Luise; Hemmingsen, Sophie Nowak; Krogh, Lotte Nylandsted; Mikkelsen, Hanne Birte; Binderup, Marie Louise Mølgaard
2017-02-01
Evaluation of the pathogenicity of a gene variant of unknown significance (VUS) is crucial for molecular diagnosis and genetic counseling, but can be challenging. This is especially so in phenotypically variable diseases, such as von Hippel-Lindau disease (vHL). vHL is caused by germline mutations in the VHL gene, which predispose to the development of multiple tumors such as central nervous system hemangioblastomas and renal cell carcinoma (RCC). We propose a method for the evaluation of VUS pathogenicity through our experience with the VHL missense mutation c.241C>T (p.P81S). 1) Clinical evaluation of known variant carriers: We evaluated a family of five VHL p.P81S carriers, as well as the clinical characteristics of all the p.P81S carriers reported in the literature; 2) Evaluation of tumor tissue via genetic analysis, histology, and immunohistochemistry (IHC); 3) Assessment of the variant's impact on protein structure and function, using multiple databases, in silico algorithms, and reports of functional studies. Only one family member had clinical signs of vHL with early-onset RCC. IHC analysis showed no VHL protein expressed in the tumor, consistent with biallelic VHL inactivation. The majority of in silico algorithms reported p.P81S as possibly pathogenic in relation to vHL or RCC, but there were discrepancies. Functional studies suggest that p.P81S impairs the VHL protein's function. The VHL p.P81S mutation is most likely a low-penetrant pathogenic variant predisposing to RCC development. We suggest the above-mentioned method for VUS evaluation with use of different methods, especially a variety of in silico methods and tumor tissue analysis.
Fernandez, Bridget A.; Scherer, Stephen W.
2017-01-01
Autism spectrum disorder (ASD) encompasses a group of neurodevelopmental conditions diagnosed solely on the basis of behavioral assessments that reveal social deficits. Progress has been made in understanding its genetic underpinnings, but most ASD-associated genetic variants, which include copy number variants (CNVs) and mutations in ASD-risk genes, account for no more than 1 % of ASD cases. This high level of genetic heterogeneity leads to challenges obtaining and interpreting genetic testing in clinical settings. The traditional definition of syndromic ASD is a disorder with a clinically defined pattern of somatic abnormalities and a neurobehavioral phenotype that may include ASD. Most have a known genetic cause. Examples include fragile X syndrome and tuberous sclerosis complex. We propose dividing syndromic autism into the following two groups: (i) ASD that occurs in the context of a clinically defined syndrome-recognizing these disorders depends on the familiarity of the clinician with the features of the syndrome, and the diagnosis is typically confirmed by targeted genetic testing (eg, mutation screening of FMR1); (ii) ASD that occurs as a feature of a molecularly defined syndrome-for this group of patients, ASD-associated variants are identified by genome-wide testing that is not hypothesis driven (eg, microarray, whole exome sequencing). These ASD groups cannot be easily clinically defined because patients with a given variant have variable somatic abnormalities (dysmorphism and birth defects). In this article, we review common diagnoses from the above categories and suggest a testing strategy for patients, guided by determining whether the individual has essential or complex ASD; patients in the latter group have multiple morphologic anomalies on physical examination. Finally, we recommend that the syndromic versus nonsyndromic designation ultimately be replaced by classification of ASD according to its genetic etiology, which will inform about the associated spectrum and penetrance of neurobehavioral and somatic manifestations. PMID:29398931
Meyer, Nuala J.; Li, Mingyao; Feng, Rui; Bradfield, Jonathan; Gallop, Robert; Bellamy, Scarlett; Fuchs, Barry D.; Lanken, Paul N.; Albelda, Steven M.; Rushefski, Melanie; Aplenc, Richard; Abramova, Helen; Atochina-Vasserman, Elena N.; Beers, Michael F.; Calfee, Carolyn S.; Cohen, Mitchell J.; Pittet, Jean-Francois; Christiani, David C.; O'Keefe, Grant E.; Ware, Lorraine B.; May, Addison K.; Wurfel, Mark M.; Hakonarson, Hakon; Christie, Jason D.
2011-01-01
Rationale: Acute lung injury (ALI) acts as a complex genetic trait, yet its genetic risk factors remain incompletely understood. Large-scale genotyping has not previously been reported for ALI. Objectives: To identify ALI risk variants after major trauma using a large-scale candidate gene approach. Methods: We performed a two-stage genetic association study. We derived findings in an African American cohort (n = 222) using a cardiopulmonary disease–centric 50K single nucleotide polymorphism (SNP) array. Genotype and haplotype distributions were compared between subjects with ALI and without ALI, with adjustment for clinical factors. Top performing SNPs (P < 10−4) were tested in a multicenter European American trauma-associated ALI case-control population (n = 600 ALI; n = 2,266 population-based control subjects) for replication. The ALI-associated genomic region was sequenced, analyzed for in silico prediction of function, and plasma was assayed by ELISA and immunoblot. Measurements and Main Results: Five SNPs demonstrated a significant association with ALI after adjustment for covariates in Stage I. Two SNPs in ANGPT2 (rs1868554 and rs2442598) replicated their significant association with ALI in Stage II. rs1868554 was robust to multiple comparison correction: odds ratio 1.22 (1.06–1.40), P = 0.0047. Resequencing identified predicted novel splice sites in linkage disequilibrium with rs1868554, and immunoblots showed higher proportion of variant angiopoietin-2 (ANG2) isoform associated with rs1868554T (0.81 vs. 0.48; P = 0.038). Conclusions: An ANGPT2 region is associated with both ALI and variation in plasma angiopoietin-2 isoforms. Characterization of the variant isoform and its genetic regulation may yield important insights about ALI pathogenesis and susceptibility. PMID:21257790
Reduced genetic influence on childhood obesity in small for gestational age children
2013-01-01
Background Children born small-for-gestational-age (SGA) are at increased risk of developing obesity and metabolic diseases later in life, a risk which is magnified if followed by accelerated postnatal growth. We investigated whether common gene variants associated with adult obesity were associated with increased postnatal growth, as measured by BMI z-score, in children born SGA and appropriate for gestational age (AGA) in the Auckland Birthweight Collaborative. Methods A total of 37 candidate SNPs were genotyped on 547 European children (228 SGA and 319 AGA). Repeated measures of BMI (z-score) were used for assessing obesity status, and results were corrected for multiple testing using the false discovery rate. Results SGA children had a lower BMI z-score than non-SGA children at assessment age 3.5, 7 and 11 years. We confirmed 27 variants within 14 obesity risk genes to be individually associated with increasing early childhood BMI, predominantly in those born AGA. Conclusions Genetic risk variants are less important in influencing early childhood BMI in those born SGA than in those born AGA, suggesting that non-genetic or environmental factors may be more important in influencing childhood BMI in those born SGA. PMID:23339409
Katagiri, Satoshi; Hayashi, Takaaki; Mizobuchi, Kei; Yoshitake, Kazutoshi; Iwata, Takeshi; Nakano, Tadashi
2018-06-01
It is known that PRPH2 variants appear to be rare causes of retinitis pigmentosa (RP) in the Japanese population. The purpose of this study was to describe clinical and genetic features in autosomal dominant RP (adRP) patients with a novel disease-causing variant in the PRHP2 gene. A total of 57 unrelated Japanese probands with adRP were investigated in this study. Comprehensive ophthalmic examinations include fundus photography, fundus autofluorescence imaging, spectral-domain optical coherence tomography, and electroretinography. Whole exome sequencing or Sanger sequencing for 25 targeted exons of multiple genes causing adRP was performed to identify disease-causing variants. Co-segregation and haplotype analyses were performed to determine a disease-causing gene variant and its haplotype. Genetic analysis identified a novel heterozygous PRPH2 variant (c.748T>G, p.Cys250Gly) as disease causing in four probands from four families. The variant co-segregated with the RP phenotype in the eight affected patients in all families. At least three of the four families shared the same haplotype for the variant allele. Clinically, seven of the eight affected patients exhibited typical RP presentation, as well as variable macular involvement including cystoid macular change, vitelliform-like appearance, choroidal neovascularization, and macular atrophy. The same disease haplotype that included a novel PRPH2 variant (p.Cys250Gly) was identified in three of the four Japanese families with adRP, suggesting a founder effect. Our clinical findings indicate that adRP caused by the p.Cys250Gly variant may accompany macular involvement with high frequency.
New Genes and New Insights from Old Genes: Update on Alzheimer Disease
Ringman, John M.; Coppola, Giovanni
2013-01-01
Purpose of Review: This article discusses the current status of knowledge regarding the genetic basis of Alzheimer disease (AD) with a focus on clinically relevant aspects. Recent Findings: The genetic architecture of AD is complex, as it includes multiple susceptibility genes and likely nongenetic factors. Rare but highly penetrant autosomal dominant mutations explain a small minority of the cases but have allowed tremendous advances in understanding disease pathogenesis. The identification of a strong genetic risk factor, APOE, reshaped the field and introduced the notion of genetic risk for AD. More recently, large-scale genome-wide association studies are adding to the picture a number of common variants with very small effect sizes. Large-scale resequencing studies are expected to identify additional risk factors, including rare susceptibility variants and structural variation. Summary: Genetic assessment is currently of limited utility in clinical practice because of the low frequency (Mendelian mutations) or small effect size (common risk factors) of the currently known susceptibility genes. However, genetic studies are identifying with confidence a number of novel risk genes, and this will further our understanding of disease biology and possibly the identification of therapeutic targets. PMID:23558482
Diverse point mutations in the human gene for polymorphic N-acetyltransferase
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vatsis, K.P.; Martell, K.J.; Weber, W.W.
1991-07-15
Classification of humans as rapid or slow acetylators is based on hereditary differences in rates of N-acetylation of therapeutic and carcinogenic agents, but N-acetylation of certain arylamine drugs displays no genetic variation. Two highly homologous human genes for N-acetyltransferase NAT1 and NAT2, presumably code for the genetically invariant and variant NAT proteins, respectively. In the present investigation, 1.9-kilobase human genomic EcoRI fragments encoding NAT2 were generated by the polymerase chain reaction with liver and leukocyte DNA from seven subjects phenotyped as homozygous and heterozygous acetylators. Direct sequencing revealed multiple point mutations in the coding region of two distinct NAT2 variants.more » One of these was derived from leukocytes of a slow acetylator and was distinguished by a silent mutation (coden 94) and a separate G {r arrow} A transition (position 590) leading to replacement of Arg-197 by Gln; the mutated guanine was part of a CpG dinucleotide and a Taq I site. The second NAT2 variant originated from liver with low N-acetylation activity. It was characterized by three nucleotide transitions giving rise to a silent mutation (codon 161), accompanied by obliteration of the sole Kpn I site, and two amino acid substitutions. The results show conclusively that the genetically variant NAT is encoded by NAT2.« less
Weber, Stefanie; Büscher, Anja K; Hagmann, Henning; Liebau, Max C; Heberle, Christian; Ludwig, Michael; Rath, Sabine; Alberer, Martin; Beissert, Antje; Zenker, Martin; Hoyer, Peter F; Konrad, Martin; Klein, Hanns-Georg; Hoefele, Julia
2016-01-01
Steroid-resistant nephrotic syndrome (SRNS) is a severe cause of progressive renal disease. Genetic forms of SRNS can present with autosomal recessive or autosomal dominant inheritance. Recent studies have identified mutations in multiple podocyte genes responsible for SRNS. Improved sequencing methods (next-generation sequencing, NGS) now promise rapid mutational testing of SRNS genes. In the present study, a simultaneous screening of ten SRNS genes in 37 SRNS patients was performed by NGS. In 38 % of the patients, causative mutations in one SRNS gene were found. In 22 % of the patients, in addition to these mutations, a secondary variant in a different gene was identified. This high incidence of accumulating sequence variants was unexpected but, although they might have modifier effects, the pathogenic potential of these additional sequence variants seems unclear so far. The example of molecular diagnostics by NGS in SRNS patients shows that these new sequencing technologies might provide further insight into molecular pathogenicity in genetic disorders but will also generate results, which will be difficult to interpret and complicate genetic counseling. Although NGS promises more frequent identification of disease-causing mutations, the identification of causative mutations, the interpretation of incidental findings and possible pitfalls might pose problems, which hopefully will decrease by further experience and elucidation of molecular interactions.
Epigenome-wide inheritance of cytosine methylation variants in a recombinant inbred population
Schmitz, Robert J.; He, Yupeng; Valdés-López, Oswaldo; Khan, Saad M.; Joshi, Trupti; Urich, Mark A.; Nery, Joseph R.; Diers, Brian; Xu, Dong; Stacey, Gary; Ecker, Joseph R.
2013-01-01
Cytosine DNA methylation is one avenue for passing information through cell divisions. Here, we present epigenomic analyses of soybean recombinant inbred lines (RILs) and their parents. Identification of differentially methylated regions (DMRs) revealed that DMRs mostly cosegregated with the genotype from which they were derived, but examples of the uncoupling of genotype and epigenotype were identified. Linkage mapping of methylation states assessed from whole-genome bisulfite sequencing of 83 RILs uncovered widespread evidence for local methylQTL. This epigenomics approach provides a comprehensive study of the patterns and heritability of methylation variants in a complex genetic population over multiple generations, paving the way for understanding how methylation variants contribute to phenotypic variation. PMID:23739894
Epigenome-wide inheritance of cytosine methylation variants in a recombinant inbred population.
Schmitz, Robert J; He, Yupeng; Valdés-López, Oswaldo; Khan, Saad M; Joshi, Trupti; Urich, Mark A; Nery, Joseph R; Diers, Brian; Xu, Dong; Stacey, Gary; Ecker, Joseph R
2013-10-01
Cytosine DNA methylation is one avenue for passing information through cell divisions. Here, we present epigenomic analyses of soybean recombinant inbred lines (RILs) and their parents. Identification of differentially methylated regions (DMRs) revealed that DMRs mostly cosegregated with the genotype from which they were derived, but examples of the uncoupling of genotype and epigenotype were identified. Linkage mapping of methylation states assessed from whole-genome bisulfite sequencing of 83 RILs uncovered widespread evidence for local methylQTL. This epigenomics approach provides a comprehensive study of the patterns and heritability of methylation variants in a complex genetic population over multiple generations, paving the way for understanding how methylation variants contribute to phenotypic variation.
Pare, Guillaume; Mao, Shihong; Deng, Wei Q
2016-06-08
Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance.
Pare, Guillaume; Mao, Shihong; Deng, Wei Q.
2016-01-01
Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance. PMID:27273519
m6ASNP: a tool for annotating genetic variants by m6A function.
Jiang, Shuai; Xie, Yubin; He, Zhihao; Zhang, Ya; Zhao, Yuli; Chen, Li; Zheng, Yueyuan; Miao, Yanyan; Zuo, Zhixiang; Ren, Jian
2018-05-01
Large-scale genome sequencing projects have identified many genetic variants for diverse diseases. A major goal of these projects is to characterize these genetic variants to provide insight into their function and roles in diseases. N6-methyladenosine (m6A) is one of the most abundant RNA modifications in eukaryotes. Recent studies have revealed that aberrant m6A modifications are involved in many diseases. In this study, we present a user-friendly web server called "m6ASNP" that is dedicated to the identification of genetic variants that target m6A modification sites. A random forest model was implemented in m6ASNP to predict whether the methylation status of an m6A site is altered by the variants that surround the site. In m6ASNP, genetic variants in a standard variant call format (VCF) are accepted as the input data, and the output includes an interactive table that contains the genetic variants annotated by m6A function. In addition, statistical diagrams and a genome browser are provided to visualize the characteristics and to annotate the genetic variants. We believe that m6ASNP is a very convenient tool that can be used to boost further functional studies investigating genetic variants. The web server "m6ASNP" is implemented in JAVA and PHP and is freely available at [60].
Landscape of Pleiotropic Proteins Causing Human Disease: Structural and System Biology Insights.
Ittisoponpisan, Sirawit; Alhuzimi, Eman; Sternberg, Michael J E; David, Alessia
2017-03-01
Pleiotropy is the phenomenon by which the same gene can result in multiple phenotypes. Pleiotropic proteins are emerging as important contributors to rare and common disorders. Nevertheless, little is known on the mechanisms underlying pleiotropy and the characteristic of pleiotropic proteins. We analyzed disease-causing proteins reported in UniProt and observed that 12% are pleiotropic (variants in the same protein cause more than one disease). Pleiotropic proteins were enriched in deleterious and rare variants, but not in common variants. Pleiotropic proteins were more likely to be involved in the pathogenesis of neoplasms, neurological, and circulatory diseases and congenital malformations, whereas non-pleiotropic proteins in endocrine and metabolic disorders. Pleiotropic proteins were more essential and had a higher number of interacting partners compared with non-pleiotropic proteins. Significantly more pleiotropic than non-pleiotropic proteins contained at least one intrinsically long disordered region (P < 0.001). Deleterious variants occurring in structurally disordered regions were more commonly found in pleiotropic, rather than non-pleiotropic proteins. In conclusion, pleiotropic proteins are an important contributor to human disease. They represent a biologically different class of proteins compared with non-pleiotropic proteins and a better understanding of their characteristics and genetic variants can greatly aid in the interpretation of genetic studies and drug design. © 2016 WILEY PERIODICALS, INC.
Bartter syndrome presenting as poor weight gain and abdominal mass in an infant.
Heffernan, Annie; Steffensen, Thora S; Gilbert-Barness, Enid; Perlman, Sharon
2008-01-01
Bartter syndrome, a group of disorders that encompasses multiple genetic defects with similar clinical presentation, has been divided into six different genotypes, according to different genetic defects, and into three main clinical variants (or phenotypes). Classic laboratory findings in all variants include hypochloremia, hypokalemia, and metabolic alkalosis with excessive excretion of chloride and potassium. Classic Bartter syndrome, neonatal Bartter syndrome, and Gitelman syndrome are the three main clinical variants. Classic Bartter syndrome and neonatal Bartter syndrome have defects in genes that affect transport channels in the ascending loop of Henle, where as in Gitleman syndrome the defect occurs in the transport channels of the distal convoluted tubule. Classic Bartter syndrome and neonatal Bartter syndrome have similar presenting symptoms, potential outcomes, and treatment, but different ages at presentation. Gitelman syndrome, a more benign condition than the other clinical variants, has the classic hallmark finding of hypomagnesemia and low to normal excretion of calcium. This differentiates it from the classic and neonatal variants of the disease. With early diagnosis and proper treatment, Bartter syndrome has a good prognosis. But failure to identify it can lead to tubulointerstitial nephritis and renal failure. We present a case of a 6-month-old boy with Bartter syndrome who presented with poor weight gain and an abdominal mass.
van Deursen, F J; Hino, K; Wyatt, D; Molyneaux, P; Yates, P; Wallace, L A; Dow, B C; Carman, W F
1998-01-01
AIMS: To assess the relevance of genetic variants of hepatitis B virus (HBV) and to demonstrate the usefulness of the polymerase chain reaction (PCR) in cases of HBV diagnostic difficulty. METHODS: Five serum samples from patients that presented diagnostic difficulty in routine laboratories were sent to a research laboratory for PCR, and if appropriate, S gene sequencing, in vitro expression, and antigenic analysis. RESULTS: The demonstration of HBV in serum by PCR allowed a definitive diagnosis of current infection. One serum sample with poor reactivity in a diagnostic assay had a minor hepatitis B surface antigen (HBsAg) variant and another with very poor reactivity had multiple variants of HBsAg. Transient HBsAg reactivity was observed in a recently vaccinated patient. A hepatitis Be antigen (HBeAg) false positive reaction was noted in a patient from a well defined risk group for HBV. One patient who was strongly HBsAg/HBeAg positive, but anti-hepatitis B core antibody negative, was viraemic. CONCLUSIONS: PCR may become the gold standard for the diagnosis of current HBV infection. HBV variants are responsible for a proportion of diagnostically difficult cases. Modification of commercial assays is necessary to increase the sensitivity of detection of such variants. PMID:9602690
Yang, Baiyu; Thrift, Aaron P.; Figueiredo, Jane C.; Jenkins, Mark A.; Schumacher, Fredrick R.; Conti, David V.; Lin, Yi; Win, Aung Ko; Limburg, Paul J.; Berndt, Sonja I.; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Hoffmeister, Michael; Hudson, Thomas J.; Marchand, Loïc Le; Newcomb, Polly A.; Slattery, Martha L.; White, Emily; Peters, Ulrike; Casey, Graham; Campbell, Peter T.
2016-01-01
Background Obesity is a convincing risk factor for colorectal cancer. Genetic variants in or near FTO and MC4R are consistently associated with body mass index and other body size measures, but whether they are also associated with colorectal cancer risk is unclear. Methods In the discovery stage, we tested associations of 677 FTO and 323 MC4R single nucleotide polymorphisms (SNPs) 100kb upstream and 300kb downstream from each respective locus with risk of colorectal cancer in data from the Colon Cancer Family Registry (CCFR: 1,960 cases; 1,777 controls). Next, all SNPs that were nominally statistically signif icant (p<0.05) in the discovery stage were included in replication analyses in data from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO: 9,716 cases; 9,844 controls). Results In the discovery stage, 43 FTO variants and 18 MC4R variants were associated with colorectal cancer risk (p<0.05). No SNPs remained statistically significant in the replication analysis after accounting for multiple comparisons. Conclusion We found no evidence that individual variants in or near the obesity-related genes FTO and MC4R are associated with risk of colorectal cancer. PMID:27449576
Yang, Baiyu; Thrift, Aaron P; Figueiredo, Jane C; Jenkins, Mark A; Schumacher, Fredrick R; Conti, David V; Lin, Yi; Win, Aung Ko; Limburg, Paul J; Berndt, Sonja I; Brenner, Hermann; Chan, Andrew T; Chang-Claude, Jenny; Hoffmeister, Michael; Hudson, Thomas J; Marchand, Loïc Le; Newcomb, Polly A; Slattery, Martha L; White, Emily; Peters, Ulrike; Casey, Graham; Campbell, Peter T
2016-10-01
Obesity is a convincing risk factor for colorectal cancer. Genetic variants in or near FTO and MC4R are consistently associated with body mass index and other body size measures, but whether they are also associated with colorectal cancer risk is unclear. In the discovery stage, we tested associations of 677 FTO and 323 MC4R single nucleotide polymorphisms (SNPs) 100kb upstream and 300kb downstream from each respective locus with risk of colorectal cancer in data from the Colon Cancer Family Registry (CCFR: 1960 cases; 1777 controls). Next, all SNPs that were nominally statistically significant (p<0.05) in the discovery stage were included in replication analyses in data from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO: 9716 cases; 9844 controls). In the discovery stage, 43 FTO variants and 18 MC4R variants were associated with colorectal cancer risk (p<0.05). No SNPs remained statistically significant in the replication analysis after accounting for multiple comparisons. We found no evidence that individual variants in or near the obesity-related genes FTO and MC4R are associated with risk of colorectal cancer. Copyright © 2016 Elsevier Ltd. All rights reserved.
2014-01-01
Background Abnormal lipid concentrations are risk factors for atherosclerosis and cardiovascular disease. The pathological susceptibility to cardiovascular disease risks such as metabolic syndrome, diabetes mellitus, hypertension, insulin resistance, and so on differs between Sasang constitutional types. Methods We used multiple regression analyses to study the association between lipid-related traits and genetic variants from several genome-wide association studies according to Sasang constitutional types, considering that the Tae-Eum (TE) has predominant cardiovascular risk. Results By analyzing 26 variants of 20 loci in two Korean populations (8,597 subjects), we found that 12 and 5 variants, respectively, were replicably associated with lipid levels and dyslipidemia risk. By analyzing TE and non-TE type (each 2,664 subjects) populations classified on the basis of Sasang constitutional medicine, we found that the minor allele effects of three variants enriched in TE type had a harmful influence on lipid risk (near apolipoprotein A-V (APOA5)-APOA4-APOC3-APOA1 on increased triglyceride: p = 8.90 × 10-11, in APOE-APOC1-APOC4 on increased low-density lipoprotein cholesterol: p = 1.63 × 10-5, and near endothelial lipase gene on decreased high-density lipoprotein cholesterol: p = 4.28 × 10-3), whereas those of three variants (near angiopoietin-like 3 gene, APOA5-APOA4-APOC3-APOA1, and near lipoprotein lipase gene on triglyceride and high-density lipoprotein cholesterol) associated in non-TE type had neutral influences because of a compensating effect. Conclusions These results implied that the minor allele effects of lipid-associated variants may predispose TE type subjects to high cardiovascular disease risk because of their genetic susceptibility to lipid-related disorders. PMID:25005712
Genetic and functional analysis of the gene encoding GAP-43 in schizophrenia.
Shen, Yu-Chih; Tsai, Ho-Min; Cheng, Min-Chih; Hsu, Shih-Hsin; Chen, Shih-Fen; Chen, Chia-Hsiang
2012-02-01
In earlier reports, growth-associated protein 43 (GAP-43) has been shown to be critical for initial establishment or reorganization of synaptic connections, a process thought to be disrupted in schizophrenia. Additionally, abnormal GAP-43 expression in different brain regions has been linked to this disorder in postmortem brain studies. In this study, we investigated the involvement of the gene encoding GAP-43 in the susceptibility to schizophrenia. We searched for genetic variants in the promoter region and 3 exons (including both UTR ends) of the GAP-43 gene using direct sequencing in a sample of patients with schizophrenia (n=586) and non-psychotic controls (n=576), both being Han Chinese from Taiwan, and conducted an association and functional study. We identified 11 common polymorphisms in the GAP-43 gene. SNP and haplotype-based analyses displayed no associations with schizophrenia. Additionally, we identified 4 rare variants in 5 out of 586 patients, including 1 variant located at the promoter region (c.-258-4722G>T) and 1 synonymous (V110V) and 2 missense (G150R and P188L) variants located at exon 2. No rare variants were found in the control subjects. The results of the reporter gene assay demonstrated that the regulatory activity of construct containing c.-258-4722T was significantly lower as compared to the wild type construct (c.-258-4722G; p<0.001). In silico analysis also demonstrated the functional relevance of other rare variants. Our study lends support to the hypothesis of multiple rare mutations in schizophrenia, and it provides genetic clues that indicate the involvement of GAP-43 in this disorder. Copyright © 2011 Elsevier B.V. All rights reserved.
Influence of 6 genetic variants on the efficacy of statins in patients with dyslipidemia.
Cano-Corres, Ruth; Candás-Estébanez, Beatriz; Padró-Miquel, Ariadna; Fanlo-Maresma, Marta; Pintó, Xavier; Alía-Ramos, Pedro
2018-05-07
Patients with dyslipidemia are often treated with statins to reduce lipids and hence cardiovascular risk, but treatment response is variable, partly due to genetic factors. We studied the influence of 6 gene variants (APOE c.526C > T (APOE2), APOE c.388T > C (APOE4), SLCO1B1 c.521T > C, CYP3A4 c.-392G > A, HMGCR c.1564-106A > G, and LPA c.3947 + 467T > C) on statin efficacy assessing 2 indicators: the percent reduction in total cholesterol (TC) and non-HDL cholesterol (non-HDL), as well as the achievement of therapeutic goals. The study was performed in a group of patients (n = 100) without previous pharmacological treatment. Multiple regression models were used to calculate the percentage of explanation in response variability added by every variant to a basal model constructed with significant nongenetic control variables. The most influential variant was HMGCR c.1564-106A > G (rs3846662), and carriers showed a significantly lower reduction in TC and non-HDL. This variant is related to an alternative splicing involving exon 13, which is also regulated by lipid concentrations in patients without the variant. Concerning therapeutic goals, HMGCR c.1564-106A > G hindered the achievement of TC targets on patients. The HMGCR c.1564-106A > G variant was associated with less statin efficacy to decrease cholesterol. © 2018 Wiley Periodicals, Inc.
An expanded genetic code in mammalian cells with a functional quadruplet codon.
Niu, Wei; Schultz, Peter G; Guo, Jiantao
2013-07-19
We have utilized in vitro evolution to identify tRNA variants with significantly enhanced activity for the incorporation of unnatural amino acids into proteins in response to a quadruplet codon in both bacterial and mammalian cells. This approach will facilitate the creation of an optimized and standardized system for the genetic incorporation of unnatural amino acids using quadruplet codons, which will allow the biosynthesis of biopolymers that contain multiple unnatural building blocks.
Chang, Hongjuan; Yan, Qiuge; Tang, Lina; Huang, Juan; Ma, Yuqiao; Ye, Xiaozhou; Wu, Chunxia; Wu, Linguo; Yu, Yizhen
2018-01-01
Genetic predisposition is an important factor leading to aggressive behavior. However, the relationship between genetic polymorphisms and aggressive behavior has not been elucidated. We identified candidate genes located in the dopaminergic and serotonin system (DRD3, DRD4, and FEV) that had been previously reported to be associated with aggressive behavior. We investigated 14 tag single-nucleotide polymorphisms (SNPs) using a multi-analytic strategy combining logistic regression (LR) and classification and regression tree (CART) to explore higher-order interactions between these SNPs and aggressive behavior in 318 patients and 558 controls. Both LR and CART analyses suggested that the rs16859448 polymorphism is the strongest individual factor associated with aggressive behavior risk. In CART analysis, individuals carrying the combined genotypes of rs16859448TT/GT-rs11246228CT/TT-rs3773679TT had the highest risk, while rs16859448GG-rs2134655CT had the lowest risk (OR = 5.25, 95% CI: 2.53-10.86). This study adds to the growing evidence on the association of single- and multiple-risk variants in DRD3, DRD4, and FEV with aggressive behavior in Chinese adolescents. However, the aggressive behavior scale used to diagnose aggression in this study did not account for comorbid conditions; therefore, further studies are needed to confirm our observations. Copyright © 2017 Elsevier B.V. All rights reserved.
Engineering posttranslational proofreading to discriminate nonstandard amino acids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kunjapur, Aditya M.; Stork, Devon A.; Kuru, Erkin
Accurate incorporation of nonstandard amino acids (nsAAs) is central for genetic code expansion to increase the chemical diversity of proteins. However, aminoacyl-tRNA synthetases are polyspecific and facilitate incorporation of multiple nsAAs. We investigated and repurposed a natural protein degradation pathway, the N-end rule pathway, to devise an innovative system for rapid assessment of the accuracy of nsAA incorporation. Using this tool to monitor incorporation of the nsAA biphenylalanine allowed the identification of tyrosyl-tRNA synthetase (TyrRS) variants with improved amino acid specificity. The evolved TyrRS variants enhanced our ability to contain unwanted proliferation of genetically modified organisms. In conclusion, this posttranslationalmore » proofreading system will aid the evolution of orthogonal translation systems for specific incorporation of diverse nsAAs.« less
Engineering posttranslational proofreading to discriminate nonstandard amino acids
Kunjapur, Aditya M.; Stork, Devon A.; Kuru, Erkin; ...
2018-01-04
Accurate incorporation of nonstandard amino acids (nsAAs) is central for genetic code expansion to increase the chemical diversity of proteins. However, aminoacyl-tRNA synthetases are polyspecific and facilitate incorporation of multiple nsAAs. We investigated and repurposed a natural protein degradation pathway, the N-end rule pathway, to devise an innovative system for rapid assessment of the accuracy of nsAA incorporation. Using this tool to monitor incorporation of the nsAA biphenylalanine allowed the identification of tyrosyl-tRNA synthetase (TyrRS) variants with improved amino acid specificity. The evolved TyrRS variants enhanced our ability to contain unwanted proliferation of genetically modified organisms. In conclusion, this posttranslationalmore » proofreading system will aid the evolution of orthogonal translation systems for specific incorporation of diverse nsAAs.« less
Nicoletti, Paola; Bansal, Mukesh; Lefebvre, Celine; Guarnieri, Paolo; Shen, Yufeng; Pe'er, Itsik; Califano, Andrea; Floratos, Aris
2015-01-01
Stevens-Johnson syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) represent rare but serious adverse drug reactions (ADRs). Both are characterized by distinctive blistering lesions and significant mortality rates. While there is evidence for strong drug-specific genetic predisposition related to HLA alleles, recent genome wide association studies (GWAS) on European and Asian populations have failed to identify genetic susceptibility alleles that are common across multiple drugs. We hypothesize that this is a consequence of the low to moderate effect size of individual genetic risk factors. To test this hypothesis we developed Pointer, a new algorithm that assesses the aggregate effect of multiple low risk variants on a pathway using a gene set enrichment approach. A key advantage of our method is the capability to associate SNPs with genes by exploiting physical proximity as well as by using expression quantitative trait loci (eQTLs) that capture information about both cis- and trans-acting regulatory effects. We control for known bias-inducing aspects of enrichment based analyses, such as: 1) gene length, 2) gene set size, 3) presence of biologically related genes within the same linkage disequilibrium (LD) region, and, 4) genes shared among multiple gene sets. We applied this approach to publicly available SJS/TEN genome-wide genotype data and identified the ABC transporter and Proteasome pathways as potentially implicated in the genetic susceptibility of non-drug-specific SJS/TEN. We demonstrated that the innovative SNP-to-gene mapping phase of the method was essential in detecting the significant enrichment for those pathways. Analysis of an independent gene expression dataset provides supportive functional evidence for the involvement of Proteasome pathways in SJS/TEN cutaneous lesions. These results suggest that Pointer provides a useful framework for the integrative analysis of pharmacogenetic GWAS data, by increasing the power to detect aggregate effects of multiple low risk variants. The software is available for download at https://sourceforge.net/projects/pointergsa/.
Tong, Pin; Monahan, Jack; Prendergast, James G D
2017-03-01
Large-scale gene expression datasets are providing an increasing understanding of the location of cis-eQTLs in the human genome and their role in disease. However, little is currently known regarding the extent of regulatory site-sharing between genes. This is despite it having potentially wide-ranging implications, from the determination of the way in which genetic variants may shape multiple phenotypes to the understanding of the evolution of human gene order. By first identifying the location of non-redundant cis-eQTLs, we show that regulatory site-sharing is a relatively common phenomenon in the human genome, with over 10% of non-redundant regulatory variants linked to the expression of multiple nearby genes. We show that these shared, local regulatory sites are linked to high levels of chromatin looping between the regulatory sites and their associated genes. In addition, these co-regulated gene modules are found to be strongly conserved across mammalian species, suggesting that shared regulatory sites have played an important role in shaping human gene order. The association of these shared cis-eQTLs with multiple genes means they also appear to be unusually important in understanding the genetics of human phenotypes and pleiotropy, with shared regulatory sites more often linked to multiple human phenotypes than other regulatory variants. This study shows that regulatory site-sharing is likely an underappreciated aspect of gene regulation and has important implications for the understanding of various biological phenomena, including how the two and three dimensional structures of the genome have been shaped and the potential causes of disease pleiotropy outside coding regions.
Genetic complexity and multiple infections with more Parvovirus species in naturally infected cats
2011-01-01
Parvoviruses of carnivores include three closely related autonomous parvoviruses: canine parvovirus (CPV), feline panleukopenia virus (FPV) and mink enteritis virus (MEV). These viruses cause a variety of serious diseases, especially in young patients, since they have a remarkable predilection for replication in rapidly dividing cells. FPV is not the only parvovirus species which infects cats; in addition to MEV, the new variants of canine parvovirus, CPV-2a, 2b and 2c have also penetrated the feline host-range, and they are able to infect and replicate in cats, causing diseases indistinguishable from feline panleukopenia. Furthermore, as cats are susceptible to both CPV-2 and FPV viruses, superinfection and co-infection with multiple parvovirus strains may occur, potentially facilitating recombination and high genetic heterogeneity. In the light of the importance of cats as a potential source of genetic diversity for parvoviruses and, since feline panleukopenia virus has re-emerged as a major cause of mortality in felines, the present study has explored the molecular characteristics of parvovirus strains circulating in cat populations. The most significant findings reported in this study were (a) the detection of mixed infection FPV/CPV with the presence of one parvovirus variant which is a true intermediate between FPV/CPV and (b) the quasispecies cloud size of one CPV sample variant 2c. In conclusion, this study provides new important results about the evolutionary dynamics of CPV infections in cats, showing that CPV has presumably started a new process of readaptation in feline hosts. PMID:21366901
Liu, Jiewei; Li, Ming; Su, Bing
2016-12-01
Genome-wide association studies (GWASs) have identified multiple schizophrenia (SCZ) risk variants for samples of European and East Asian descent, but most of the identified susceptibility variants are population-specific to either Europeans or East Asians. This strong genetic heterogeneity suggests that differential population histories may play a role in SCZ susceptibility. Here, we explored this possibility by examining the allele frequency divergence of 136 previously reported genome-wide SCZ risk SNPs between European and East Asian populations. Our results showed that two SNPs (rs11038167 and rs11038172) at TSPAN18, reported as genome-wide significant SCZ risk variants in Han Chinese, were entirely monomorphic in Europeans, indicating a deep between-population divergence at this gene locus. To explore the evolutionary history of TSPAN18 in East Asians, we conducted population genetic analyses including multiple neutrality tests, the haplotype-based iHS and EHH tests, as well as haplotype bifurcation map and network constructions. We found that the protective allele of rs11038172 (G allele) had a long extended haplotype with much slower decay compared to the A allele. The star-like shape of the G-allele-carrying haplotypes indicates a recent enrichment in East Asians. Together, the evidences suggest that the protective allele of rs11038172 has experienced recent Darwinian positive selection in East Asians. These findings provide new insights that may help explain the strong genetic heterogeneity in SCZ risk and previous inconsistent association results for SCZ among both Europeans and East Asians. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Pritchard, Antonia L; Johansson, Peter A; Nathan, Vaishnavi; Howlie, Madeleine; Symmons, Judith; Palmer, Jane M; Hayward, Nicholas K
2018-01-01
While a number of autosomal dominant and autosomal recessive cancer syndromes have an associated spectrum of cancers, the prevalence and variety of cancer predisposition mutations in patients with multiple primary cancers have not been extensively investigated. An understanding of the variants predisposing to more than one cancer type could improve patient care, including screening and genetic counselling, as well as advancing the understanding of tumour development. A cohort of 57 patients ascertained due to their cutaneous melanoma (CM) diagnosis and with a history of two or more additional non-cutaneous independent primary cancer types were recruited for this study. Patient blood samples were assessed by whole exome or whole genome sequencing. We focussed on variants in 525 pre-selected genes, including 65 autosomal dominant and 31 autosomal recessive cancer predisposition genes, 116 genes involved in the DNA repair pathway, and 313 commonly somatically mutated in cancer. The same genes were analysed in exome sequence data from 1358 control individuals collected as part of non-cancer studies (UK10K). The identified variants were classified for pathogenicity using online databases, literature and in silico prediction tools. No known pathogenic autosomal dominant or previously described compound heterozygous mutations in autosomal recessive genes were observed in the multiple cancer cohort. Variants typically found somatically in haematological malignancies (in JAK1, JAK2, SF3B1, SRSF2, TET2 and TYK2) were present in lymphocyte DNA of patients with multiple primary cancers, all of whom had a history of haematological malignancy and cutaneous melanoma, as well as colorectal cancer and/or prostate cancer. Other potentially pathogenic variants were discovered in BUB1B, POLE2, ROS1 and DNMT3A. Compared to controls, multiple cancer cases had significantly more likely damaging mutations (nonsense, frameshift ins/del) in tumour suppressor and tyrosine kinase genes and higher overall burden of mutations in all cancer genes. We identified several pathogenic variants that likely predispose to at least one of the tumours in patients with multiple cancers. We additionally present evidence that there may be a higher burden of variants of unknown significance in 'cancer genes' in patients with multiple cancer types. Further screens of this nature need to be carried out to build evidence to show if the cancers observed in these patients form part of a cancer spectrum associated with single germline variants in these genes, whether multiple layers of susceptibility exist (oligogenic or polygenic), or if the occurrence of multiple different cancers is due to random chance.
Reitz, Christiane; Jun, Gyungah; Naj, Adam; Rajbhandary, Ruchita; Vardarajan, Badri Narayan; Wang, Li-San; Valladares, Otto; Lin, Chiao-Feng; Larson, Eric B.; Graff-Radford, Neill R.; Evans, Denis; De Jager, Philip L.; Crane, Paul K.; Buxbaum, Joseph D.; Murrell, Jill R.; Raj, Towfique; Ertekin-Taner, Nilufer; Logue, Mark; Baldwin, Clinton T.; Green, Robert C.; Barnes, Lisa L.; Cantwell, Laura B.; Fallin, M. Daniele; Go, Rodney C. P.; Griffith, Patrick; Obisesan, Thomas O.; Manly, Jennifer J.; Lunetta, Kathryn L.; Kamboh, M. Ilyas; Lopez, Oscar L.; Bennett, David A.; Hendrie, Hugh; Hall, Kathleen S.; Goate, Alison M.; Byrd, Goldie S.; Kukull, Walter A.; Foroud, Tatiana M.; Haines, Jonathan L.; Farrer, Lindsay A.; Pericak-Vance, Margaret A.; Schellenberg, Gerard D.; Mayeux, Richard
2013-01-01
Importance Genetic variants associated with susceptibility to late-onset Alzheimer disease are known for individuals of European ancestry, but whether the same or different variants account for the genetic risk of Alzheimer disease in African American individuals is unknown. Identification of disease-associated variants helps identify targets for genetic testing, prevention, and treatment. Objective To identify genetic loci associated with late-onset Alzheimer disease in African Americans. Design, Setting, and Participants The Alzheimer Disease Genetics Consortium (ADGC) assembled multiple data sets representing a total of 5896 African Americans (1968 case participants, 3928 control participants) 60 years or older that were collected between 1989 and 2011 at multiple sites. The association of Alzheimer disease with genotyped and imputed single-nucleotide polymorphisms (SNPs) was assessed in case-control and in family-based data sets. Results from individual data sets were combined to perform an inverse variance–weighted meta-analysis, first with genome-wide analyses and subsequently with gene-based tests for previously reported loci. Main Outcomes and Measures Presence of Alzheimer disease according to standardized criteria. Results Genome-wide significance in fully adjusted models (sex, age, APOE genotype, population stratification) was observed for a SNP in ABCA7 (rs115550680, allele = G; frequency, 0.09 cases and 0.06 controls; odds ratio [OR], 1.79 [95% CI, 1.47-2.12]; P = 2.2 × 10–9), which is in linkage disequilibrium with SNPs previously associated with Alzheimer disease in Europeans (0.8
Chang, Tien-Jyun; Wang, Wen-Chang; Hsiung, Chao A; He, Chih-Tsueng; Lin, Ming-Wei; Sheu, Wayne Huey-Herng; Chang, Yi-Cheng; Quertermous, Tom; Chen, Ida; Rotter, Jerome; Chuang, Lee-Ming
2016-03-01
Essential hypertension is a complex disease involving multiple genetic and environmental factors. A human gene containing a sorbin homology domain and 3 SH3 domains in the C-terminal region, termed SORBS1, plays a significant role in insulin signaling. We previously found a significant association between the T228A polymorphism and insulin resistance, obesity, and type 2 diabetes. It has been hypothesized that a set of genes responsible for insulin resistance may be closely linked with genes susceptible to the development of hypertension. Identification of insulin resistance-related genetic factors may, therefore, enhance our understanding of essential hypertension. This study aimed to examine whether common SORBS1 genetic variations are associated with blood pressure and age at onset of hypertension in an ethnic Chinese cohort.We genotyped 9 common tagged single nucleotide polymorphisms of the SORBS1 gene in 1136 subjects of Chinese origin from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance family study. Blood pressure was measured upon enrolment. The associations of the SORBS1 single nucleotide polymorphisms with blood pressure and the presence of hypertension were analyzed with a generalized estimating equation model. We used the false-discovery rate measure Q value with a cutoff <0.1 to adjust for multiple comparisons. In the Cox regression analysis for hypertension-free survival, a robust sandwich variance estimator was used to deal with the within-family correlations with age at onset of hypertension. Gender, body mass index, and antihypertension medication were adjustment covariates in the Cox regression analysis.In this study, genetic variants of rs2281939 and rs2274490 were significantly associated with both systolic and diastolic blood pressure. A genetic variant of rs2274490 was also significantly associated with the presence of hypertension. Furthermore, genetic variants of rs2281939 and rs2274490 were associated with age at onset of hypertension after adjustment for gender, body mass index, and antihypertension medication.In conclusion, we provide evidence for an association between common SORBS1 genetic variations and blood pressure, presence of hypertension, and age at onset of hypertension. The biological mechanism of genetic variation associated with blood pressure regulation needs further investigation.
Souto, Cintia P; Mathiasen, Paula; Acosta, María Cristina; Quiroga, María Paula; Vidal-Russell, Romina; Echeverría, Cristian; Premoli, Andrea C
2015-01-01
Conservation planning requires setting priorities at the same spatial scale at which decision-making processes are undertaken considering all levels of biodiversity, but current methods for identifying biodiversity hotspots ignore its genetic component. We developed a fine-scale approach based on the definition of genetic hotspots, which have high genetic diversity and unique variants that represent their evolutionary potential and evolutionary novelties. Our hypothesis is that wide-ranging taxa with similar ecological tolerances, yet of phylogenetically independent lineages, have been and currently are shaped by ecological and evolutionary forces that result in geographically concordant genetic patterns. We mapped previously published genetic diversity and unique variants of biparentally inherited markers and chloroplast sequences for 9 species from 188 and 275 populations, respectively, of the 4 woody dominant families of the austral temperate forest, an area considered a biodiversity hotspot. Spatial distribution patterns of genetic polymorphisms differed among taxa according to their ecological tolerances. Eight genetic hotspots were detected and we recommend conservation actions for some in the southern Coastal Range in Chile. Existing spatially explicit genetic data from multiple populations and species can help to identify biodiversity hotspots and guide conservation actions to establish science-based protected areas that will preserve the evolutionary potential of key habitats and species. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Davies, Neil M; Gaunt, Tom R; Lewis, Sarah J; Holly, Jeff; Donovan, Jenny L; Hamdy, Freddie C; Kemp, John P; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Al Olama, Ali Amin; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Neal, David; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lathrop, Mark; Smith, George Davey; Martin, Richard M
2015-11-01
Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. We conducted a case-control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man's number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. The genetic risk scores explained 6.31 and 1.46% of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95% CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95% CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.
Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J
2017-05-01
Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.
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
Gene expression allelic imbalance in ovine brown adipose tissue impacts energy homeostasis
Ghazanfar, Shila; Vuocolo, Tony; Morrison, Janna L.; Nicholas, Lisa M.; McMillen, Isabella C.; Yang, Jean Y. H.; Buckley, Michael J.
2017-01-01
Heritable trait variation within a population of organisms is largely governed by DNA variations that impact gene transcription and protein function. Identifying genetic variants that affect complex functional traits is a primary aim of population genetics studies, especially in the context of human disease and agricultural production traits. The identification of alleles directly altering mRNA expression and thereby biological function is challenging due to difficulty in isolating direct effects of cis-acting genetic variations from indirect trans-acting genetic effects. Allele specific gene expression or allelic imbalance in gene expression (AI) occurring at heterozygous loci provides an opportunity to identify genes directly impacted by cis-acting genetic variants as indirect trans-acting effects equally impact the expression of both alleles. However, the identification of genes showing AI in the context of the expression of all genes remains a challenge due to a variety of technical and statistical issues. The current study focuses on the discovery of genes showing AI using single nucleotide polymorphisms as allelic reporters. By developing a computational and statistical process that addressed multiple analytical challenges, we ranked 5,809 genes for evidence of AI using RNA-Seq data derived from brown adipose tissue samples from a cohort of late gestation fetal lambs and then identified a conservative subgroup of 1,293 genes. Thus, AI was extensive, representing approximately 25% of the tested genes. Genes associated with AI were enriched for multiple Gene Ontology (GO) terms relating to lipid metabolism, mitochondrial function and the extracellular matrix. These functions suggest that cis-acting genetic variations causing AI in the population are preferentially impacting genes involved in energy homeostasis and tissue remodelling. These functions may contribute to production traits likely to be under genetic selection in the population. PMID:28665992
Sequence variants in oxytocin pathway genes and preterm birth: a candidate gene association study
2013-01-01
Background Preterm birth (PTB) is a complex disorder associated with significant neonatal mortality and morbidity and long-term adverse health consequences. Multiple lines of evidence suggest that genetic factors play an important role in its etiology. This study was designed to identify genetic variation associated with PTB in oxytocin pathway genes whose role in parturition is well known. Methods To identify common genetic variants predisposing to PTB, we genotyped 16 single nucleotide polymorphisms (SNPs) in the oxytocin (OXT), oxytocin receptor (OXTR), and leucyl/cystinyl aminopeptidase (LNPEP) genes in 651 case infants from the U.S. and one or both of their parents. In addition, we examined the role of rare genetic variation in susceptibility to PTB by conducting direct sequence analysis of OXTR in 1394 cases and 1112 controls from the U.S., Argentina, Denmark, and Finland. This study was further extended to maternal triads (maternal grandparents-mother of a case infant, N=309). We also performed in vitro analysis of selected rare OXTR missense variants to evaluate their functional importance. Results Maternal genetic effect analysis of the SNP genotype data revealed four SNPs in LNPEP that show significant association with prematurity. In our case–control sequence analysis, we detected fourteen coding variants in exon 3 of OXTR, all but four of which were found in cases only. Of the fourteen variants, three were previously unreported novel rare variants. When the sequence data from the maternal triads were analyzed using the transmission disequilibrium test, two common missense SNPs (rs4686302 and rs237902) in OXTR showed suggestive association for three gestational age subgroups. In vitro functional assays showed a significant difference in ligand binding between wild-type and two mutant receptors. Conclusions Our study suggests an association between maternal common polymorphisms in LNPEP and susceptibility to PTB. Maternal OXTR missense SNPs rs4686302 and rs237902 may have gestational age-dependent effects on prematurity. Most of the OXTR rare variants identified do not appear to significantly contribute to the risk of PTB, but those shown to affect receptor function in our in vitro study warrant further investigation. Future studies with larger sample sizes are needed to confirm the findings of this study. PMID:23889750
Exome Array Analysis of Susceptibility to Pneumococcal Meningitis
Kloek, Anne T.; van Setten, Jessica; van der Ende, Arie; Bots, Michiel L.; Asselbergs, Folkert W.; Serón, Mercedes Valls; Brouwer, Matthijs C.; van de Beek, Diederik; Ferwerda, Bart
2016-01-01
Host genetic variability may contribute to susceptibility of bacterial meningitis, but which genes contribute to the susceptibility to this complex disease remains undefined. We performed a genetic association study in 469 community-acquired pneumococcal meningitis cases and 2072 population-based controls from the Utrecht Health Project in order to find genetic variants associated with pneumococcal meningitis susceptibility. A HumanExome BeadChip was used to genotype 102,097 SNPs in the collected DNA samples. Associations were tested with the Fisher exact test. None of the genetic variants tested reached Bonferroni corrected significance (p-value <5 × 10−7). Our strongest signals associated with susceptibility to pneumococcal meningitis were rs139064549 on chromosome 1 in the COL11A1 gene (p = 1.51 × 10−6; G allele OR 3.21 [95% CI 2.05–5.02]) and rs9309464 in the EXOC6B gene on chromosome 2 (p = 6.01 × 10−5; G allele OR 0.66 [95% CI 0.54–0.81]). The sequence kernel association test (SKAT) tests for associations between multiple variants in a gene region and pneumococcal meningitis susceptibility yielded one significant associated gene namely COL11A1 (p = 1.03 × 10−7). Replication studies are needed to validate these results. If replicated, the functionality of these genetic variations should be further studied to identify by which means they influence the pathophysiology of pneumococcal meningitis. PMID:27389768
Pulmonary Nontuberculous Mycobacterial Infection. A Multisystem, Multigenic Disease.
Szymanski, Eva P; Leung, Janice M; Fowler, Cedar J; Haney, Carissa; Hsu, Amy P; Chen, Fei; Duggal, Priya; Oler, Andrew J; McCormack, Ryan; Podack, Eckhard; Drummond, Rebecca A; Lionakis, Michail S; Browne, Sarah K; Prevots, D Rebecca; Knowles, Michael; Cutting, Gary; Liu, Xinyue; Devine, Scott E; Fraser, Claire M; Tettelin, Hervé; Olivier, Kenneth N; Holland, Steven M
2015-09-01
The clinical features of patients infected with pulmonary nontuberculous mycobacteria (PNTM) are well described, but the genetic components of infection susceptibility are not. To examine genetic variants in patients with PNTM, their unaffected family members, and a control group. Whole-exome sequencing was done on 69 white patients with PNTM and 18 of their white unaffected family members. We performed a candidate gene analysis using immune, cystic fibrosis transmembrance conductance regulator (CFTR), cilia, and connective tissue gene sets. The numbers of patients, family members, and control subjects with variants in each category were compared, as was the average number of variants per person. A significantly higher number of patients with PNTM than the other subjects had low-frequency, protein-affecting variants in immune, CFTR, cilia, and connective tissue categories (35, 26, 90, and 90%, respectively). Patients with PNTM also had significantly more cilia and connective tissue variants per person than did control subjects (2.47 and 2.55 compared with 1.38 and 1.40, respectively; P = 1.4 × 10(-6) and P = 2.7 × 10(-8), respectively). Patients with PNTM had an average of 5.26 variants across all categories (1.98 in control subjects; P = 2.8 × 10(-17)), and they were more likely than control subjects to have variants in multiple categories. We observed similar results for family members without PNTM infection, with the exception of the immune category. Patients with PNTM have more low-frequency, protein-affecting variants in immune, CFTR, cilia, and connective tissue genes than their unaffected family members and control subjects. We propose that PNTM infection is a multigenic disease in which combinations of variants across gene categories, plus environmental exposures, increase susceptibility to the infection.
Rare versus common variants in pharmacogenetics: SLCO1B1 variation and methotrexate disposition
Ramsey, Laura B.; Bruun, Gitte H.; Yang, Wenjian; Treviño, Lisa R.; Vattathil, Selina; Scheet, Paul; Cheng, Cheng; Rosner, Gary L.; Giacomini, Kathleen M.; Fan, Yiping; Sparreboom, Alex; Mikkelsen, Torben S.; Corydon, Thomas J.; Pui, Ching-Hon; Evans, William E.; Relling, Mary V.
2012-01-01
Methotrexate is used to treat autoimmune diseases and malignancies, including acute lymphoblastic leukemia (ALL). Inter-individual variation in clearance of methotrexate results in heterogeneous systemic exposure, clinical efficacy, and toxicity. In a genome-wide association study of children with ALL, we identified SLCO1B1 as harboring multiple common polymorphisms associated with methotrexate clearance. The extent of influence of rare versus common variants on pharmacogenomic phenotypes remains largely unexplored. We tested the hypothesis that rare variants in SLCO1B1 could affect methotrexate clearance and compared the influence of common versus rare variants in addition to clinical covariates on clearance. From deep resequencing of SLCO1B1 exons in 699 children, we identified 93 SNPs, 15 of which were non-synonymous (NS). Three of these NS SNPs were common, with a minor allele frequency (MAF) >5%, one had low frequency (MAF 1%–5%), and 11 were rare (MAF <1%). NS SNPs (common or rare) predicted to be functionally damaging were more likely to be found among patients with the lowest methotrexate clearance than patients with high clearance. We verified lower function in vitro of four SLCO1B1 haplotypes that were associated with reduced methotrexate clearance. In a multivariate stepwise regression analysis adjusting for other genetic and non-genetic covariates, SLCO1B1 variants accounted for 10.7% of the population variability in clearance. Of that variability, common NS variants accounted for the majority, but rare damaging NS variants constituted 17.8% of SLCO1B1's effects (1.9% of total variation) and had larger effect sizes than common NS variants. Our results show that rare variants are likely to have an important effect on pharmacogenetic phenotypes. PMID:22147369
USDA-ARS?s Scientific Manuscript database
Plants are attacked by pathogens representing diverse taxonomic groups, such that genes providing multiple disease resistance (MDR) would likely be under positive selection pressure. We examined the novel proposition that naturally occurring allelic variants may confer MDR. To do so, we applied a ...
Air pollution is a worldwide contributor to cardiovascular disease mortality and morbidity. Traffic air pollution is a ubiquitous source of air pollution in developed nations, and is associated with multiple cardiovascular outcomes such as: coronary atherosclerosis, peripheral ar...
Burgess, Stephen; Zuber, Verena; Valdes-Marquez, Elsa; Sun, Benjamin B; Hopewell, Jemma C
2017-12-01
Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be used to assess this causal relationship. However, using too many genetic variants in the analysis can lead to spurious estimates and inflated Type 1 error rates. But if only a few genetic variants are used, then the majority of the data is ignored and estimates are highly sensitive to the particular choice of variants. We propose an approach based on summarized data only (genetic association and correlation estimates) that uses principal components analysis to form instruments. This approach has desirable theoretical properties: it takes the totality of data into account and does not suffer from numerical instabilities. It also has good properties in simulation studies: it is not particularly sensitive to varying the genetic variants included in the analysis or the genetic correlation matrix, and it does not have greatly inflated Type 1 error rates. Overall, the method gives estimates that are less precise than those from variable selection approaches (such as using a conditional analysis or pruning approach to select variants), but are more robust to seemingly arbitrary choices in the variable selection step. Methods are illustrated by an example using genetic associations with testosterone for 320 genetic variants to assess the effect of sex hormone related pathways on coronary artery disease risk, in which variable selection approaches give inconsistent inferences. © 2017 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc.
Dziedzic, Magdalena; Marjańska, Agata; Bąbol-Pokora, Katarzyna; Urbańczyk, Anna; Grześk, Elżbieta; Młynarski, Wojciech; Kołtan, Sylwia
2017-07-27
Pediatric autoinflammatory diseases are rare and still poorly understood conditions resulting from defective genetic control of innate immune system, inter alia from anomalies of NOD2 gene. The product of this gene is Nod2 protein, taking part in maintenance of immune homeostasis. Clinical form of resultant autoinflammatory condition depends on NOD2 genotype; usually patients with NOD2 defects present with Blau syndrome, NOD2-associated autoinflammatory disease (NAID) or Crohn's disease. We present the case of a 7-year-old girl with co-existing symptoms of two rare diseases, Blau syndrome and NAID. Overlapping manifestations of two syndromes raised a significant diagnostic challenge, until next-generation molecular test (NGS) identified presence of three pathogenic variants of NOD2 gene: P268S, IVS8 +158 , 1007 fs, and established the ultimate diagnosis. Presence of multiple genetical abnormalities resulted in an ambiguous clinical presentation with overlapping symptoms of Blau syndrome and NAID. Final diagnosis of autoinflammatory disease opened new therapeutic possibilities, including the use of biological treatments.
Saito, Yuri A.
2011-01-01
IBS is a common disorder that has been shown to aggregate in families, to affect multiple generations, but not in a manner consistent with a major Mendelian effect. Relatives of an individual with IBS are two to three times as likely to have IBS, with both genders being affected. The estimated genetic liability ranges between 1–20%, with heritability estimates ranging between 0–57%. Although the role of childhood events such as nasogastric tube placement, poor nutrition, abuse, and other stressors have been clearly associated with IBS, these factors have not been studied in families and are unlikely to completely explain the clustering of bowel dysfunction observed in family studies. Furthermore, the familial clustering of IBS does not appear to be explained by psychological traits, based on family studies as well as candidate gene studies of functional variants associated with other psychiatric disorders. To date, over a hundred genetic variants in over 60 genes from various pathways have been studied in a number of candidate gene studies with several positive associations reported. These findings suggest that there may be distinct, as well as shared, molecular underpinnings for IBS and its subtypes. Much new and confirmatory work remains to be performed to elucidate the role of specific genetic variants in IBS development, as well as the specific ways the genes and environment interact to result in IBS susceptibility. PMID:21333900
Tan, Li-Jun; Zhu, Hu; He, Hao; Wu, Ke-Hao; Li, Jian; Chen, Xiang-Ding; Zhang, Ji-Gang; Shen, Hui; Tian, Qing; Krousel-Wood, Marie; Papasian, Christopher J; Bouchard, Claude; Pérusse, Louis; Deng, Hong-Wen
2014-01-01
Obesity is a major public health problem with a significant genetic component. Multiple DNA polymorphisms/genes have been shown to be strongly associated with obesity, typically in populations of European descent. The aim of this study was to verify the extent to which 6 confirmed obesity genes (FTO, CTNNBL1, ADRB2, LEPR, PPARG and UCP2 genes) could be replicated in 8 different samples (n = 11,161) and to explore whether the same genes contribute to obesity-susceptibility in populations of different ancestries (five Caucasian, one Chinese, one African-American and one Hispanic population). GWAS-based data sets with 1000 G imputed variants were tested for association with obesity phenotypes individually in each population, and subsequently combined in a meta-analysis. Multiple variants at the FTO locus showed significant associations with BMI, fat mass (FM) and percentage of body fat (PBF) in meta-analysis. The strongest association was detected at rs7185735 (P-value = 1.01×10(-7) for BMI, 1.80×10(-6) for FM, and 5.29×10(-4) for PBF). Variants at the CTNNBL1, LEPR and PPARG loci demonstrated nominal association with obesity phenotypes (meta-analysis P-values ranging from 1.15×10(-3) to 4.94×10(-2)). There was no evidence of association with variants at ADRB2 and UCP2 genes. When stratified by sex and ethnicity, FTO variants showed sex-specific and ethnic-specific effects on obesity traits. Thus, it is likely that FTO has an important role in the sex- and ethnic-specific risk of obesity. Our data confirmed the role of FTO, CTNNBL1, LEPR and PPARG in obesity predisposition. These findings enhanced our knowledge of genetic associations between these genes and obesity-related phenotypes, and provided further justification for pursuing functional studies of these genes in the pathophysiology of obesity. Sex and ethnic differences in genetic susceptibility across populations of diverse ancestries may contribute to a more targeted prevention and customized treatment of obesity.
Maxwell, Rochelle R; Cole, Peter D
2017-06-01
The aim of this review is to summarize the most recent and most robust pharmacogenetic predictors of treatment-related toxicity (TRT) in childhood acute lymphoblastic leukemia (ALL). Multiple studies have examined the toxicities of the primary chemotherapeutic agents used to treat childhood ALL in relation to host genetic factors. However, few results have been replicated independently, largely due to cohort differences in ancestry, chemotherapy treatment protocols, and definitions of toxicities. To date, there is only one widely accepted clinical guideline for dose modification based on gene status: thiopurine dosing based on TPMT genotype. Based on recent data, it is likely that this guideline will be modified to incorporate other gene variants, such as NUDT15. We highlight genetic variants that have been consistently associated with TRT across treatment groups, as well as those that best illustrate the underlying pathophysiology of TRT. In the coming decade, we expect that survivorship care will routinely specify screening recommendations based on genetics. Furthermore, clinical trials testing protective interventions may modify inclusion criteria based on genetically determined risk of specific TRTs.
A place for genetic uncertainty: parents valuing an unknown in the meaning of disease.
Whitmarsh, Ian; Davis, Arlene M; Skinner, Debra; Bailey, Donald B
2007-09-01
Klinefelter, Turner, and fragile X syndromes are conditions defined by a genetic or chromosomal variant. The timing of diagnosis, tests employed, specialists involved, symptoms evident, and prognoses available vary considerably within and across these syndromes, but all three share in common a diagnosis verified through a molecular or cytogenetic test. The genetic or chromosomal variant identified designates a syndrome, even when symptoms associated with the particular syndrome are absent. This article analyzes interviews conducted with parents and grandparents of children with these syndromes from across the USA to explore how they interpret a confirmed genetic diagnosis that is associated with a range of possible symptoms that may never be exhibited. Parents' responses indicate that they see the genetic aspects of the syndrome as stable, permanent, and authoritative. But they allow, and even embrace, uncertainty about the condition by focusing on variation between diagnosed siblings, the individuality of their diagnosed child, his or her accomplishments, and other positive aspects that go beyond the genetic diagnosis. Some families counter the genetic diagnosis by arguing that in the absence of symptoms, the syndrome does not exist. They use their own expertise to question the perceived certainty of the genetic diagnosis and to employ the diagnosis strategically. These multiple and often conflicting evaluations of the diagnostic label reveal the rich ways families make meaning of the authority attributed to genetic diagnosis.
Genetic modifiers of CHEK2*1100delC associated breast cancer risk
Muranen, Taru A.; Greco, Dario; Blomqvist, Carl; Aittomäki, Kristiina; Khan, Sofia; Hogervorst, Frans; Verhoef, Senno; Pharoah, Paul D.P.; Dunning, Alison M.; Shah, Mitul; Luben, Robert; Bojesen, Stig E.; Nordestgaard, Børge G.; Schoemaker, Minouk; Swerdlow, Anthony; García-Closas, Montserrat; Figueroa, Jonine; Dörk, Thilo; Bogdanova, Natalia V.; Hall, Per; Li, Jingmei; Khusnutdinova, Elza; Bermisheva, Marina; Kristensen, Vessela; Borresen-Dale, Anne-Lise; Peto, Julian; dos Santos Silva, Isabel; Couch, Fergus J.; Olson, Janet E.; Hillemans, Peter; Park-Simon, Tjoung-Won; Brauch, Hiltrud; Hamann, Ute; Burwinkel, Barbara; Marme, Frederik; Meindl, Alfons; Schmutzler, Rita K.; Cox, Angela; Cross, Simon S.; Sawyer, Elinor J.; Tomlinson, Ian; Lambrechts, Diether; Moisse, Matthieu; Lindblom, Annika; Margolin, Sara; Hollestelle, Antoinette; Martens, John W.M.; Fasching, Peter A.; Beckmann, Matthias W.; Andrulis, Irene L.; Knight, Julia A.; Anton-Culver, Hoda; Ziogas, Argyrios; Giles, Graham G.; Milne, Roger L.; Brenner, Hermann; Arndt, Volker; Mannermaa, Arto; Kosma, Veli-Matti; Chang-Claude, Jenny; Rudolph, Anja; Devilee, Peter; Seynaeve, Caroline; Hopper, John L.; Southey, Melissa C.; John, Esther M.; Whittemore, Alice S.; Bolla, Manjeet K.; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Easton, Douglas F.; Schmidt, Marjanka K.; Nevanlinna, Heli
2016-01-01
Purpose CHEK2*1100delC is a founder variant in European populations conferring a 2–3 fold increased risk of breast cancer (BC). Epidemiologic and family studies have suggested that the risk associated with CHEK2*1100delC is modified by other genetic factors in a multiplicative fashion. We have investigated this empirically using data from the Breast Cancer Association Consortium (BCAC). Methods With genotype data of 39,139 (624 1100delC carriers) BC patients and 40,063 (224) healthy controls from 32 BCAC studies, we analyzed the combined risk effects of CHEK2*1100delC and 77 common variants in terms of a polygenic risk score (PRS) and pairwise interaction. Results The PRS conferred an odds ratio (OR) of 1.59 [95% CI 1.21–2.09] per standard deviation for BC for CHEK2*1100delC carriers and 1.58 [1.55–1.62] for non-carriers. No evidence for deviation from the multiplicative model was found. The OR for the highest quintile of the PRS was 2.03 [0.86–4.78] for CHEK2*1100delC carriers placing them to the high risk category according to UK NICE guidelines. OR for the lowest quintile was 0.52 [0.16–1.74], indicating life-time risk close to population average. Conclusion Our results confirm the multiplicative nature of risk effects conferred by CHEK2*1100delC and the common susceptibility variants. Furthermore, the PRS could identify the carriers at a high life-time risk for clinical actions. PMID:27711073
Identifying Genetic Sources of Phenotypic Heterogeneity in Orofacial Clefts by Targeted Sequencing.
Carlson, Jenna C; Taub, Margaret A; Feingold, Eleanor; Beaty, Terri H; Murray, Jeffrey C; Marazita, Mary L; Leslie, Elizabeth J
2017-07-17
Orofacial clefts (OFCs), including nonsyndromic cleft lip with or without cleft palate (NSCL/P), are common birth defects. NSCL/P is highly heterogeneous with multiple phenotypic presentations. Two common subtypes of NSCL/P are cleft lip (CL) and cleft lip with cleft palate (CLP) which have different population prevalence. Similarly, NSCL/P can be divided into bilateral and unilateral clefts, with unilateral being the most common. Individuals with unilateral NSCL/P are more likely to be affected on the left side of the upper lip, but right side affection also occurs. Moreover, NSCL/P is twice as common in males as in females. The goal of this study is to discover genetic variants that have different effects in case subgroups. We conducted both common variant and rare variant analyses in 1034 individuals of Asian ancestry with NSCL/P, examining four sources of heterogeneity within CL/P: cleft type, sex, laterality, and side. We identified several regions associated with subtype differentiation: cleft type differences in 8q24 (p = 1.00 × 10 -4 ), laterality differences in IRF6, a gene previously implicated with wound healing (p = 2.166 × 10 -4 ), sex differences and side of unilateral CL differences in FGFR2 (p = 3.00 × 10 -4 ; p = 6.00 × 10 -4 ), and sex differences in VAX1 (p < 1.00 × 10 -4 ) among others. Many of the regions associated with phenotypic modification were either adjacent to or overlapping functional elements based on ENCODE chromatin marks and published craniofacial enhancers. We have identified multiple common and rare variants as potential phenotypic modifiers of NSCL/P, and suggest plausible elements responsible for phenotypic heterogeneity, further elucidating the complex genetic architecture of OFCs. Birth Defects Research 109:1030-1038, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
2010-01-01
Introduction Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium. Methods We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects. Results These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar. Conclusions The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified. PMID:21194473
Zwingerman, Nora; Medina-Rivera, Alejandra; Kassam, Irfahan; Wilson, Michael D.; Morange, Pierre-Emmanuel; Trégouët, David-Alexandre; Gagnon, France
2017-01-01
Background Thrombin activatable fibrinolysis inhibitor (TAFI), encoded by the Carboxypeptidase B2 gene (CPB2), is an inhibitor of fibrinolysis and plays a role in the pathogenesis of venous thrombosis. Experimental findings support a functional role of genetic variants in CPB2, while epidemiological studies have been unable to confirm associations with risk of venous thrombosis. Sex-specific effects could underlie the observed inconsistent associations between CPB2 genetic variants and venous thrombosis. Methods A comprehensive literature search was conducted for associations between Ala147Thr and Thr325Ile variants with venous thrombosis. Authors were contacted to provide sex-specific genotype counts from their studies. Combined and sex-specific random effects meta-analyses were used to estimate a pooled effect estimate for primary and secondary genetic models. Results A total of 17 studies met the inclusion criteria. A sex-specific meta-analysis applying a dominant model supported a protective effect of Ala147Thr on venous thrombosis in females (OR = 0.81, 95%CI: 0.68,0.97; p = 0.018), but not in males (OR = 1.06, 95%CI:0.96–1.16; p = 0.263). The Thr325Ile did not show a sex-specific effect but showed variation in allele frequencies by geographic region. A subgroup analysis of studies in European countries showed decreased risk, with a recessive model (OR = 0.83, 95%CI:0.71–0.97, p = 0.021) for venous thrombosis. Conclusions A comprehensive literature review, including unpublished data, provided greater statistical power for the analyses and decreased the likelihood of publication bias influencing the results. Sex-specific analyses explained apparent discrepancies across genetic studies of Ala147Thr and venous thrombosis. While, careful selection of genetic models based on population genetics, evolutionary and biological knowledge can increase power by decreasing the need to adjust for testing multiple models. PMID:28552956
Zwingerman, Nora; Medina-Rivera, Alejandra; Kassam, Irfahan; Wilson, Michael D; Morange, Pierre-Emmanuel; Trégouët, David-Alexandre; Gagnon, France
2017-01-01
Thrombin activatable fibrinolysis inhibitor (TAFI), encoded by the Carboxypeptidase B2 gene (CPB2), is an inhibitor of fibrinolysis and plays a role in the pathogenesis of venous thrombosis. Experimental findings support a functional role of genetic variants in CPB2, while epidemiological studies have been unable to confirm associations with risk of venous thrombosis. Sex-specific effects could underlie the observed inconsistent associations between CPB2 genetic variants and venous thrombosis. A comprehensive literature search was conducted for associations between Ala147Thr and Thr325Ile variants with venous thrombosis. Authors were contacted to provide sex-specific genotype counts from their studies. Combined and sex-specific random effects meta-analyses were used to estimate a pooled effect estimate for primary and secondary genetic models. A total of 17 studies met the inclusion criteria. A sex-specific meta-analysis applying a dominant model supported a protective effect of Ala147Thr on venous thrombosis in females (OR = 0.81, 95%CI: 0.68,0.97; p = 0.018), but not in males (OR = 1.06, 95%CI:0.96-1.16; p = 0.263). The Thr325Ile did not show a sex-specific effect but showed variation in allele frequencies by geographic region. A subgroup analysis of studies in European countries showed decreased risk, with a recessive model (OR = 0.83, 95%CI:0.71-0.97, p = 0.021) for venous thrombosis. A comprehensive literature review, including unpublished data, provided greater statistical power for the analyses and decreased the likelihood of publication bias influencing the results. Sex-specific analyses explained apparent discrepancies across genetic studies of Ala147Thr and venous thrombosis. While, careful selection of genetic models based on population genetics, evolutionary and biological knowledge can increase power by decreasing the need to adjust for testing multiple models.
Genetic Variants in Epigenetic Pathways and Risks of Multiple Cancers in the GAME-ON Consortium.
Toth, Reka; Scherer, Dominique; Kelemen, Linda E; Risch, Angela; Hazra, Aditi; Balavarca, Yesilda; Issa, Jean-Pierre J; Moreno, Victor; Eeles, Rosalind A; Ogino, Shuji; Wu, Xifeng; Ye, Yuanqing; Hung, Rayjean J; Goode, Ellen L; Ulrich, Cornelia M
2017-06-01
Background: Epigenetic disturbances are crucial in cancer initiation, potentially with pleiotropic effects, and may be influenced by the genetic background. Methods: In a subsets (ASSET) meta-analytic approach, we investigated associations of genetic variants related to epigenetic mechanisms with risks of breast, lung, colorectal, ovarian and prostate carcinomas using 51,724 cases and 52,001 controls. False discovery rate-corrected P values (q values < 0.05) were considered statistically significant. Results: Among 162,887 imputed or genotyped variants in 555 candidate genes, SNPs in eight genes were associated with risk of more than one cancer type. For example, variants in BABAM1 were confirmed as a susceptibility locus for squamous cell lung, overall breast, estrogen receptor (ER)-negative breast, and overall prostate, and overall serous ovarian cancer; the most significant variant was rs4808076 [OR = 1.14; 95% confidence interval (CI) = 1.10-1.19; q = 6.87 × 10 -5 ]. DPF1 rs12611084 was inversely associated with ER-negative breast, endometrioid ovarian, and overall and aggressive prostate cancer risk (OR = 0.93; 95% CI = 0.91-0.96; q = 0.005). Variants in L3MBTL3 were associated with colorectal, overall breast, ER-negative breast, clear cell ovarian, and overall and aggressive prostate cancer risk (e.g., rs9388766: OR = 1.06; 95% CI = 1.03-1.08; q = 0.02). Variants in TET2 were significantly associated with overall breast, overall prostate, overall ovarian, and endometrioid ovarian cancer risk, with rs62331150 showing bidirectional effects. Analyses of subpathways did not reveal gene subsets that contributed disproportionately to susceptibility. Conclusions: Functional and correlative studies are now needed to elucidate the potential links between germline genotype, epigenetic function, and cancer etiology. Impact: This approach provides novel insight into possible pleiotropic effects of genes involved in epigenetic processes. Cancer Epidemiol Biomarkers Prev; 26(6); 816-25. ©2017 AACR . ©2017 American Association for Cancer Research.
Bao, Riyue; Hernandez, Kyle; Huang, Lei; Kang, Wenjun; Bartom, Elizabeth; Onel, Kenan; Volchenboum, Samuel; Andrade, Jorge
2015-01-01
Whole exome sequencing has facilitated the discovery of causal genetic variants associated with human diseases at deep coverage and low cost. In particular, the detection of somatic mutations from tumor/normal pairs has provided insights into the cancer genome. Although there is an abundance of publicly-available software for the detection of germline and somatic variants, concordance is generally limited among variant callers and alignment algorithms. Successful integration of variants detected by multiple methods requires in-depth knowledge of the software, access to high-performance computing resources, and advanced programming techniques. We present ExScalibur, a set of fully automated, highly scalable and modulated pipelines for whole exome data analysis. The suite integrates multiple alignment and variant calling algorithms for the accurate detection of germline and somatic mutations with close to 99% sensitivity and specificity. ExScalibur implements streamlined execution of analytical modules, real-time monitoring of pipeline progress, robust handling of errors and intuitive documentation that allows for increased reproducibility and sharing of results and workflows. It runs on local computers, high-performance computing clusters and cloud environments. In addition, we provide a data analysis report utility to facilitate visualization of the results that offers interactive exploration of quality control files, read alignment and variant calls, assisting downstream customization of potential disease-causing mutations. ExScalibur is open-source and is also available as a public image on Amazon cloud.
Kernel-Based Measure of Variable Importance for Genetic Association Studies.
Gallego, Vicente; Luz Calle, M; Oller, Ramon
2017-06-17
The identification of genetic variants that are associated with disease risk is an important goal of genetic association studies. Standard approaches perform univariate analysis where each genetic variant, usually Single Nucleotide Polymorphisms (SNPs), is tested for association with disease status. Though many genetic variants have been identified and validated so far using this univariate approach, for most complex diseases a large part of their genetic component is still unknown, the so called missing heritability. We propose a Kernel-based measure of variable importance (KVI) that provides the contribution of a SNP, or a group of SNPs, to the joint genetic effect of a set of genetic variants. KVI can be used for ranking genetic markers individually, sets of markers that form blocks of linkage disequilibrium or sets of genetic variants that lie in a gene or a genetic pathway. We prove that, unlike the univariate analysis, KVI captures the relationship with other genetic variants in the analysis, even when measured at the individual level for each genetic variable separately. This is specially relevant and powerful for detecting genetic interactions. We illustrate the results with data from an Alzheimer's disease study and show through simulations that the rankings based on KVI improve those rankings based on two measures of importance provided by the Random Forest. We also prove with a simulation study that KVI is very powerful for detecting genetic interactions.
Packing Boxes into Multiple Containers Using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Menghani, Deepak; Guha, Anirban
2016-07-01
Container loading problems have been studied extensively in the literature and various analytical, heuristic and metaheuristic methods have been proposed. This paper presents two different variants of a genetic algorithm framework for the three-dimensional container loading problem for optimally loading boxes into multiple containers with constraints. The algorithms are designed so that it is easy to incorporate various constraints found in real life problems. The algorithms are tested on data of standard test cases from literature and are found to compare well with the benchmark algorithms in terms of utilization of containers. This, along with the ability to easily incorporate a wide range of practical constraints, makes them attractive for implementation in real life scenarios.
Monir, Md. Mamun; Zhu, Jun
2017-01-01
Most of the genome-wide association studies (GWASs) for human complex diseases have ignored dominance, epistasis and ethnic interactions. We conducted comparative GWASs for total cholesterol using full model and additive models, which illustrate the impacts of the ignoring genetic variants on analysis results and demonstrate how genetic effects of multiple loci could differ across different ethnic groups. There were 15 quantitative trait loci with 13 individual loci and 3 pairs of epistasis loci identified by full model, whereas only 14 loci (9 common loci and 5 different loci) identified by multi-loci additive model. Again, 4 full model detected loci were not detected using multi-loci additive model. PLINK-analysis identified two loci and GCTA-analysis detected only one locus with genome-wide significance. Full model identified three previously reported genes as well as several new genes. Bioinformatics analysis showed some new genes are related with cholesterol related chemicals and/or diseases. Analyses of cholesterol data and simulation studies revealed that the full model performs were better than the additive-model performs in terms of detecting power and unbiased estimations of genetic variants of complex traits. PMID:28079101
Higher criticism approach to detect rare variants using whole genome sequencing data
2014-01-01
Because of low statistical power of single-variant tests for whole genome sequencing (WGS) data, the association test for variant groups is a key approach for genetic mapping. To address the features of sparse and weak genetic effects to be detected, the higher criticism (HC) approach has been proposed and theoretically has proven optimal for detecting sparse and weak genetic effects. Here we develop a strategy to apply the HC approach to WGS data that contains rare variants as the majority. By using Genetic Analysis Workshop 18 "dose" genetic data with simulated phenotypes, we assess the performance of HC under a variety of strategies for grouping variants and collapsing rare variants. The HC approach is compared with the minimal p-value method and the sequence kernel association test. The results show that the HC approach is preferred for detecting weak genetic effects. PMID:25519367
Yavorska, Olena O; Burgess, Stephen
2017-12-01
MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data. The core functionality is to implement the inverse-variance weighted, MR-Egger and weighted median methods for multiple genetic variants. Several options are available to the user, such as the use of robust regression, fixed- or random-effects models and the penalization of weights for genetic variants with heterogeneous causal estimates. Extensions to these methods, such as allowing for variants to be correlated, can be chosen if appropriate. Graphical commands allow summarized data to be displayed in an interactive graph, or the plotting of causal estimates from multiple methods, for comparison. Although the main method of data entry is directly by the user, there is also an option for allowing summarized data to be incorporated from the PhenoScanner database of genotype-phenotype associations. We hope to develop this feature in future versions of the package. The R software environment is available for download from [https://www.r-project.org/]. The MendelianRandomization package can be downloaded from the Comprehensive R Archive Network (CRAN) within R, or directly from [https://cran.r-project.org/web/packages/MendelianRandomization/]. Both R and the MendelianRandomization package are released under GNU General Public Licenses (GPL-2|GPL-3). © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association.
Genetics of nonsyndromic obesity.
Lee, Yung Seng
2013-12-01
Common obesity is widely regarded as a complex, multifactorial trait influenced by the 'obesogenic' environment, sedentary behavior, and genetic susceptibility contributed by common and rare genetic variants. This review describes the recent advances in understanding the role of genetics in obesity. New susceptibility loci and genetic variants are being uncovered, but the collective effect is relatively small and could not explain most of the BMI heritability. Yet-to-be identified common and rare variants, epistasis, and heritable epigenetic changes may account for part of the 'missing heritability'. Evidence is emerging about the role of epigenetics in determining obesity susceptibility, mediating developmental plasticity, which confers obesity risk from early life experiences. Genetic prediction scores derived from selected genetic variants, and also differential DNA methylation levels and methylation scores, have been shown to correlate with measures of obesity and response to weight loss intervention. Genetic variants, which confer susceptibility to obesity-related morbidities like nonalcoholic fatty liver disease, were also discovered recently. We can expect discovery of more rare genetic variants with the advent of whole exome and genome sequencing, and also greater understanding of epigenetic mechanisms by which environment influences genetic expression and which mediate the gene-environment interaction.
Early-Onset Alzheimer Disease and Candidate Risk Genes Involved in Endolysosomal Transport.
Kunkle, Brian W; Vardarajan, Badri N; Naj, Adam C; Whitehead, Patrice L; Rolati, Sophie; Slifer, Susan; Carney, Regina M; Cuccaro, Michael L; Vance, Jeffery M; Gilbert, John R; Wang, Li-San; Farrer, Lindsay A; Reitz, Christiane; Haines, Jonathan L; Beecham, Gary W; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard P; Pericak-Vance, Margaret A
2017-09-01
Mutations in APP, PSEN1, and PSEN2 lead to early-onset Alzheimer disease (EOAD) but account for only approximately 11% of EOAD overall, leaving most of the genetic risk for the most severe form of Alzheimer disease unexplained. This extreme phenotype likely harbors highly penetrant risk variants, making it primed for discovery of novel risk genes and pathways for AD. To search for rare variants contributing to the risk for EOAD. In this case-control study, whole-exome sequencing (WES) was performed in 51 non-Hispanic white (NHW) patients with EOAD (age at onset <65 years) and 19 Caribbean Hispanic families previously screened as negative for established APP, PSEN1, and PSEN2 causal variants. Participants were recruited from John P. Hussman Institute for Human Genomics, Case Western Reserve University, and Columbia University. Rare, deleterious, nonsynonymous, or loss-of-function variants were filtered to identify variants in known and suspected AD genes, variants in multiple unrelated NHW patients, variants present in 19 Hispanic EOAD WES families, and genes with variants in multiple unrelated NHW patients. These variants/genes were tested for association in an independent cohort of 1524 patients with EOAD, 7046 patients with late-onset AD (LOAD), and 7001 cognitively intact controls (age at examination, >65 years) from the Alzheimer's Disease Genetics Consortium. The study was conducted from January 21, 2013, to October 13, 2016. Alzheimer disease diagnosed according to standard National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer Disease and Related Disorders Association criteria. Association between Alzheimer disease and genetic variants and genes was measured using logistic regression and sequence kernel association test-optimal gene tests, respectively. Of the 1524 NHW patients with EOAD, 765 (50.2%) were women and mean (SD) age was 60.0 (4.9) years; of the 7046 NHW patients with LOAD, 4171 (59.2%) were women and mean (SD) age was 77.4 (8.6) years; and of the 7001 NHW controls, 4215 (60.2%) were women and mean (SD) age was 77.4 (8.6) years. The gene PSD2, for which multiple unrelated NHW cases had rare missense variants, was significantly associated with EOAD (P = 2.05 × 10-6; Bonferroni-corrected P value [BP] = 1.3 × 10-3) and LOAD (P = 6.22 × 10-6; BP = 4.1 × 10-3). A missense variant in TCIRG1, present in a NHW patient and segregating in 3 cases of a Hispanic family, was more frequent in EOAD cases (odds ratio [OR], 2.13; 95% CI, 0.99-4.55; P = .06; BP = 0.413), and significantly associated with LOAD (OR, 2.23; 95% CI, 1.37-3.62; P = 7.2 × 10-4; BP = 5.0 × 10-3). A missense variant in the LOAD risk gene RIN3 showed suggestive evidence of association with EOAD after Bonferroni correction (OR, 4.56; 95% CI, 1.26-16.48; P = .02, BP = 0.091). In addition, a missense variant in RUFY1 identified in 2 NHW EOAD cases showed suggestive evidence of an association with EOAD as well (OR, 18.63; 95% CI, 1.62-213.45; P = .003; BP = 0.129). The genes PSD2, TCIRG1, RIN3, and RUFY1 all may be involved in endolysosomal transport-a process known to be important to development of AD. Furthermore, this study identified shared risk genes between EOAD and LOAD similar to previously reported genes, such as SORL1, PSEN2, and TREM2.
Etiology in psychiatry: embracing the reality of poly‐gene‐environmental causation of mental illness
Uher, Rudolf; Zwicker, Alyson
2017-01-01
Intriguing findings on genetic and environmental causation suggest a need to reframe the etiology of mental disorders. Molecular genetics shows that thousands of common and rare genetic variants contribute to mental illness. Epidemiological studies have identified dozens of environmental exposures that are associated with psychopathology. The effect of environment is likely conditional on genetic factors, resulting in gene‐environment interactions. The impact of environmental factors also depends on previous exposures, resulting in environment‐environment interactions. Most known genetic and environmental factors are shared across multiple mental disorders. Schizophrenia, bipolar disorder and major depressive disorder, in particular, are closely causally linked. Synthesis of findings from twin studies, molecular genetics and epidemiological research suggests that joint consideration of multiple genetic and environmental factors has much greater explanatory power than separate studies of genetic or environmental causation. Multi‐factorial gene‐environment interactions are likely to be a generic mechanism involved in the majority of cases of mental illness, which is only partially tapped by existing gene‐environment studies. Future research may cut across psychiatric disorders and address poly‐causation by considering multiple genetic and environmental measures across the life course with a specific focus on the first two decades of life. Integrative analyses of poly‐causation including gene‐environment and environment‐environment interactions can realize the potential for discovering causal types and mechanisms that are likely to generate new preventive and therapeutic tools. PMID:28498595
Assessing the genetic overlap between BMI and cognitive function
Marioni, R E; Yang, J; Dykiert, D; Mõttus, R; Campbell, A; Ibrahim-Verbaas, Carla A; Bressler, Jan; Debette, Stephanie; Schuur, Maaike; Smith, Albert V; Davies, Gail; Bennett, David A; Deary, Ian J; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosely Jr, Thomas H; Davies, G; Hayward, C; Porteous, D J; Visscher, P M; Deary, I J
2016-01-01
Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=−0.11; high body mass index (BMI)−low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)–GREML; independent samples bivariate GCTA–GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (s.e. 0.15) was observed using the same-sample GCTA–GREML approach compared with −0.10 (s.e. 0.08) from the independent-samples GCTA–GREML approach and −0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function. PMID:26857597
Sahakyan, Aleksandr B; Balasubramanian, Shankar
2016-03-12
The role of random mutations and genetic errors in defining the etiology of cancer and other multigenic diseases has recently received much attention. With the view that complex genes should be particularly vulnerable to such events, here we explore the link between the simple properties of the human genes, such as transcript length, number of splice variants, exon/intron composition, and their involvement in the pathways linked to cancer and other multigenic diseases. We reveal a substantial enrichment of cancer pathways with long genes and genes that have multiple splice variants. Although the latter two factors are interdependent, we show that the overall gene length and splicing complexity increase in cancer pathways in a partially decoupled manner. Our systematic survey for the pathways enriched with top lengthy genes and with genes that have multiple splice variants reveal, along with cancer pathways, the pathways involved in various neuronal processes, cardiomyopathies and type II diabetes. We outline a correlation between the gene length and the number of somatic mutations. Our work is a step forward in the assessment of the role of simple gene characteristics in cancer and a wider range of multigenic diseases. We demonstrate a significant accumulation of long genes and genes with multiple splice variants in pathways of multigenic diseases that have already been associated with de novo mutations. Unlike the cancer pathways, we note that the pathways of neuronal processes, cardiomyopathies and type II diabetes contain genes long enough for topoisomerase-dependent gene expression to also be a potential contributing factor in the emergence of pathologies, should topoisomerases become impaired.
BDNF Variants May Modulate Long-Term Visual Memory Performance in a Healthy Cohort
Avgan, Nesli; Sutherland, Heidi G.; Spriggens, Lauren K.; Yu, Chieh; Ibrahim, Omar; Bellis, Claire; Haupt, Larisa M.; Shum, David H. K.; Griffiths, Lyn R.
2017-01-01
Brain-derived neurotrophic factor (BDNF) is involved in numerous cognitive functions including learning and memory. BDNF plays an important role in synaptic plasticity in humans and rats with BDNF shown to be essential for the formation of long-term memories. We previously identified a significant association between the BDNF Val66Met polymorphism (rs6265) and long-term visual memory (p-value = 0.003) in a small cohort (n = 181) comprised of healthy individuals who had been phenotyped for various aspects of memory function. In this study, we have extended the cohort to 597 individuals and examined multiple genetic variants across both the BDNF and BDNF-AS genes for association with visual memory performance as assessed by the Wechsler Memory Scale—Fourth Edition subtests Visual Reproduction I and II (VR I and II). VR I assesses immediate visual memory, whereas VR II assesses long-term visual memory. Genetic association analyses were performed for 34 single nucleotide polymorphisms genotyped on Illumina OmniExpress BeadChip arrays with the immediate and long-term visual memory phenotypes. While none of the BDNF and BDNF-AS variants were shown to be significant for immediate visual memory, we found 10 variants (including the Val66Met polymorphism (p-value = 0.006)) that were nominally associated, and three variants (two variants in BDNF and one variant in the BDNF-AS locus) that were significantly associated with long-term visual memory. Our data therefore suggests a potential role for BDNF, and its anti-sense transcript BDNF-AS, in long-term visual memory performance. PMID:28304362
BDNF Variants May Modulate Long-Term Visual Memory Performance in a Healthy Cohort.
Avgan, Nesli; Sutherland, Heidi G; Spriggens, Lauren K; Yu, Chieh; Ibrahim, Omar; Bellis, Claire; Haupt, Larisa M; Shum, David H K; Griffiths, Lyn R
2017-03-17
Brain-derived neurotrophic factor (BDNF) is involved in numerous cognitive functions including learning and memory. BDNF plays an important role in synaptic plasticity in humans and rats with BDNF shown to be essential for the formation of long-term memories. We previously identified a significant association between the BDNF Val66Met polymorphism (rs6265) and long-term visual memory ( p -value = 0.003) in a small cohort ( n = 181) comprised of healthy individuals who had been phenotyped for various aspects of memory function. In this study, we have extended the cohort to 597 individuals and examined multiple genetic variants across both the BDNF and BDNF-AS genes for association with visual memory performance as assessed by the Wechsler Memory Scale-Fourth Edition subtests Visual Reproduction I and II (VR I and II). VR I assesses immediate visual memory, whereas VR II assesses long-term visual memory. Genetic association analyses were performed for 34 single nucleotide polymorphisms genotyped on Illumina OmniExpress BeadChip arrays with the immediate and long-term visual memory phenotypes. While none of the BDNF and BDNF-AS variants were shown to be significant for immediate visual memory, we found 10 variants (including the Val66Met polymorphism ( p -value = 0.006)) that were nominally associated, and three variants (two variants in BDNF and one variant in the BDNF-AS locus) that were significantly associated with long-term visual memory. Our data therefore suggests a potential role for BDNF , and its anti-sense transcript BDNF-AS , in long-term visual memory performance.
Validation of a next-generation sequencing assay for clinical molecular oncology.
Cottrell, Catherine E; Al-Kateb, Hussam; Bredemeyer, Andrew J; Duncavage, Eric J; Spencer, David H; Abel, Haley J; Lockwood, Christina M; Hagemann, Ian S; O'Guin, Stephanie M; Burcea, Lauren C; Sawyer, Christopher S; Oschwald, Dayna M; Stratman, Jennifer L; Sher, Dorie A; Johnson, Mark R; Brown, Justin T; Cliften, Paul F; George, Bijoy; McIntosh, Leslie D; Shrivastava, Savita; Nguyen, Tudung T; Payton, Jacqueline E; Watson, Mark A; Crosby, Seth D; Head, Richard D; Mitra, Robi D; Nagarajan, Rakesh; Kulkarni, Shashikant; Seibert, Karen; Virgin, Herbert W; Milbrandt, Jeffrey; Pfeifer, John D
2014-01-01
Currently, oncology testing includes molecular studies and cytogenetic analysis to detect genetic aberrations of clinical significance. Next-generation sequencing (NGS) allows rapid analysis of multiple genes for clinically actionable somatic variants. The WUCaMP assay uses targeted capture for NGS analysis of 25 cancer-associated genes to detect mutations at actionable loci. We present clinical validation of the assay and a detailed framework for design and validation of similar clinical assays. Deep sequencing of 78 tumor specimens (≥ 1000× average unique coverage across the capture region) achieved high sensitivity for detecting somatic variants at low allele fraction (AF). Validation revealed sensitivities and specificities of 100% for detection of single-nucleotide variants (SNVs) within coding regions, compared with SNP array sequence data (95% CI = 83.4-100.0 for sensitivity and 94.2-100.0 for specificity) or whole-genome sequencing (95% CI = 89.1-100.0 for sensitivity and 99.9-100.0 for specificity) of HapMap samples. Sensitivity for detecting variants at an observed 10% AF was 100% (95% CI = 93.2-100.0) in HapMap mixes. Analysis of 15 masked specimens harboring clinically reported variants yielded concordant calls for 13/13 variants at AF of ≥ 15%. The WUCaMP assay is a robust and sensitive method to detect somatic variants of clinical significance in molecular oncology laboratories, with reduced time and cost of genetic analysis allowing for strategic patient management. Copyright © 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.
Cammen, Kristina M; Wilcox, Lynsey A; Rosel, Patricia E; Wells, Randall S; Read, Andrew J
2015-02-01
The role the major histocompatibility complex (MHC) plays in response to exposure to environmental toxins is relatively poorly understood, particularly in comparison to its well-described role in pathogen immunity. We investigated associations between MHC diversity and resistance to brevetoxins in common bottlenose dolphins (Tursiops truncatus). A previous genome-wide association study investigating an apparent difference in harmful algal bloom (HAB) resistance among dolphin populations in the Gulf of Mexico identified genetic variation associated with survival in close genomic proximity to multiple MHC class II loci. Here, we characterized genetic variation at DQA, DQB, DRA, and DRB loci in dolphins from central-west Florida and the Florida Panhandle, including dolphins that died during HABs and dolphins presumed to have survived HAB exposure. We found that DRB and DQB exhibited patterns of genetic differentiation among geographic regions that differed from neutral microsatellite loci. In addition, genetic differentiation at DRB across multiple pairwise comparisons of live and dead dolphins was greater than differentiation observed at neutral loci. Our findings at these MHC loci did not approach the strength of association with survival previously described for a nearby genetic variant. However, the results provide evidence that selective pressures at the MHC vary among dolphin populations that differ in the frequency of HAB exposure and that the overall composition of DRB variants differs between dolphin survivors and non-survivors of HABs. These results may suggest a potential role of MHC diversity in variable survival of bottlenose dolphins exposed to HABs.
Atopic Dermatitis Susceptibility Variants in Filaggrin Hitchhike Hornerin Selective Sweep
Eaaswarkhanth, Muthukrishnan; Xu, Duo; Flanagan, Colin; Rzhetskaya, Margarita; Hayes, M. Geoffrey; Blekhman, Ran; Jablonski, Nina G.; Gokcumen, Omer
2016-01-01
Human skin has evolved rapidly, leaving evolutionary signatures in the genome. The filaggrin (FLG) gene is widely studied for its skin-barrier function in humans. The extensive genetic variation in this gene, especially common loss-of-function (LoF) mutations, has been established as primary risk factors for atopic dermatitis. To investigate the evolution of this gene, we analyzed 2,504 human genomes and genotyped the copy number variation of filaggrin repeats within FLG in 126 individuals from diverse ancestral backgrounds. We were unable to replicate a recent study claiming that LoF of FLG is adaptive in northern latitudes with lower ultraviolet light exposure. Instead, we present multiple lines of evidence suggesting that FLG genetic variation, including LoF variants, have little or no effect on fitness in modern humans. Haplotype-level scrutinization of the locus revealed signatures of a recent selective sweep in Asia, which increased the allele frequency of a haplotype group (Huxian haplogroup) in Asian populations. Functionally, we found that the Huxian haplogroup carries dozens of functional variants in FLG and hornerin (HRNR) genes, including those that are associated with atopic dermatitis susceptibility, HRNR expression levels and microbiome diversity on the skin. Our results suggest that the target of the adaptive sweep is HRNR gene function, and the functional FLG variants that involve susceptibility to atopic dermatitis, seem to hitchhike the selective sweep on HRNR. Our study presents a novel case of a locus that harbors clinically relevant common genetic variation with complex evolutionary trajectories. PMID:27678121
Next-generation sequencing for genetic testing of familial colorectal cancer syndromes.
Simbolo, Michele; Mafficini, Andrea; Agostini, Marco; Pedrazzani, Corrado; Bedin, Chiara; Urso, Emanuele D; Nitti, Donato; Turri, Giona; Scardoni, Maria; Fassan, Matteo; Scarpa, Aldo
2015-01-01
Genetic screening in families with high risk to develop colorectal cancer (CRC) prevents incurable disease and permits personalized therapeutic and follow-up strategies. The advancement of next-generation sequencing (NGS) technologies has revolutionized the throughput of DNA sequencing. A series of 16 probands for either familial adenomatous polyposis (FAP; 8 cases) or hereditary nonpolyposis colorectal cancer (HNPCC; 8 cases) were investigated for intragenic mutations in five CRC familial syndromes-associated genes (APC, MUTYH, MLH1, MSH2, MSH6) applying both a custom multigene Ion AmpliSeq NGS panel and conventional Sanger sequencing. Fourteen pathogenic variants were detected in 13/16 FAP/HNPCC probands (81.3 %); one FAP proband presented two co-existing pathogenic variants, one in APC and one in MUTYH. Thirteen of these 14 pathogenic variants were detected by both NGS and Sanger, while one MSH2 mutation (L280FfsX3) was identified only by Sanger sequencing. This is due to a limitation of the NGS approach in resolving sequences close or within homopolymeric stretches of DNA. To evaluate the performance of our NGS custom panel we assessed its capability to resolve the DNA sequences corresponding to 2225 pathogenic variants reported in the COSMIC database for APC, MUTYH, MLH1, MSH2, MSH6. Our NGS custom panel resolves the sequences where 2108 (94.7 %) of these variants occur. The remaining 117 mutations reside inside or in close proximity to homopolymer stretches; of these 27 (1.2 %) are imprecisely identified by the software but can be resolved by visual inspection of the region, while the remaining 90 variants (4.0 %) are blind spots. In summary, our custom panel would miss 4 % (90/2225) of pathogenic variants that would need a small set of Sanger sequencing reactions to be solved. The multiplex NGS approach has the advantage of analyzing multiple genes in multiple samples simultaneously, requiring only a reduced number of Sanger sequences to resolve homopolymeric DNA regions not adequately assessed by NGS. The implementation of NGS approaches in routine diagnostics of familial CRC is cost-effective and significantly reduces diagnostic turnaround times.
Identification of multiple genetic susceptibility loci in Takayasu arteritis.
Saruhan-Direskeneli, Güher; Hughes, Travis; Aksu, Kenan; Keser, Gokhan; Coit, Patrick; Aydin, Sibel Z; Alibaz-Oner, Fatma; Kamalı, Sevil; Inanc, Murat; Carette, Simon; Hoffman, Gary S; Akar, Servet; Onen, Fatos; Akkoc, Nurullah; Khalidi, Nader A; Koening, Curry; Karadag, Omer; Kiraz, Sedat; Langford, Carol A; McAlear, Carol A; Ozbalkan, Zeynep; Ates, Askin; Karaaslan, Yasar; Maksimowicz-McKinnon, Kathleen; Monach, Paul A; Ozer, Hüseyin T; Seyahi, Emire; Fresko, Izzet; Cefle, Ayse; Seo, Philip; Warrington, Kenneth J; Ozturk, Mehmet A; Ytterberg, Steven R; Cobankara, Veli; Onat, A Mesut; Guthridge, Joel M; James, Judith A; Tunc, Ercan; Duzgun, Nurşen; Bıcakcıgil, Muge; Yentür, Sibel P; Merkel, Peter A; Direskeneli, Haner; Sawalha, Amr H
2013-08-08
Takayasu arteritis is a rare inflammatory disease of large arteries. The etiology of Takayasu arteritis remains poorly understood, but genetic contribution to the disease pathogenesis is supported by the genetic association with HLA-B*52. We genotyped ~200,000 genetic variants in two ethnically divergent Takayasu arteritis cohorts from Turkey and North America by using a custom-designed genotyping platform (Immunochip). Additional genetic variants and the classical HLA alleles were imputed and analyzed. We identified and confirmed two independent susceptibility loci within the HLA region (r(2) < 0.2): HLA-B/MICA (rs12524487, OR = 3.29, p = 5.57 × 10(-16)) and HLA-DQB1/HLA-DRB1 (rs113452171, OR = 2.34, p = 3.74 × 10(-9); and rs189754752, OR = 2.47, p = 4.22 × 10(-9)). In addition, we identified and confirmed a genetic association between Takayasu arteritis and the FCGR2A/FCGR3A locus on chromosome 1 (rs10919543, OR = 1.81, p = 5.89 × 10(-12)). The risk allele in this locus results in increased mRNA expression of FCGR2A. We also established the genetic association between IL12B and Takayasu arteritis (rs56167332, OR = 1.54, p = 2.18 × 10(-8)). Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
Verloop, Herman; Dekkers, Olaf M; Peeters, Robin P; Schoones, Jan W; Smit, Johannes W A
2014-09-01
Iodothyronine deiodinases represent a family of selenoproteins involved in peripheral and local homeostasis of thyroid hormone action. Deiodinases are expressed in multiple organs and thyroid hormone affects numerous biological systems, thus genetic variation in deiodinases may affect multiple clinical endpoints. Interest in clinical effects of genetic variation in deiodinases has clearly increased. We aimed to provide an overview for the role of deiodinase polymorphisms in human physiology and morbidity. In this systematic review, studies evaluating the relationship between deiodinase polymorphisms and clinical parameters in humans were eligible. No restrictions on publication date were imposed. The following databases were searched up to August 2013: Pubmed, EMBASE (OVID-version), Web of Science, COCHRANE Library, CINAHL (EbscoHOST-version), Academic Search Premier (EbscoHOST-version), and ScienceDirect. Deiodinase physiology at molecular and tissue level is described, and finally the role of these polymorphisms in pathophysiological conditions is reviewed. Deiodinase type 1 (D1) polymorphisms particularly show moderate-to-strong relationships with thyroid hormone parameters, IGF1 production, and risk for depression. D2 variants correlate with thyroid hormone levels, insulin resistance, bipolar mood disorder, psychological well-being, mental retardation, hypertension, and risk for osteoarthritis. D3 polymorphisms showed no relationship with inter-individual variation in serum thyroid hormone parameters. One D3 polymorphism was associated with risk for osteoarthritis. Genetic deiodinase profiles only explain a small proportion of inter-individual variations in serum thyroid hormone levels. Evidence suggests a role of genetic deiodinase variants in certain pathophysiological conditions. The value for determination of deiodinase polymorphism in clinical practice needs further investigation. © 2014 European Society of Endocrinology.
Somatic mosaicism of a CDKL5 mutation identified by next-generation sequencing.
Kato, Takeshi; Morisada, Naoya; Nagase, Hiroaki; Nishiyama, Masahiro; Toyoshima, Daisaku; Nakagawa, Taku; Maruyama, Azusa; Fu, Xue Jun; Nozu, Kandai; Wada, Hiroko; Takada, Satoshi; Iijima, Kazumoto
2015-10-01
CDKL5-related encephalopathy is an X-linked dominantly inherited disorder that is characterized by early infantile epileptic encephalopathy or atypical Rett syndrome. We describe a 5-year-old Japanese boy with intractable epilepsy, severe developmental delay, and Rett syndrome-like features. Onset was at 2 months, when his electroencephalogram showed sporadic single poly spikes and diffuse irregular poly spikes. We conducted a genetic analysis using an Illumina® TruSight™ One sequencing panel on a next-generation sequencer. We identified two epilepsy-associated single nucleotide variants in our case: CDKL5 p.Ala40Val and KCNQ2 p.Glu515Asp. CDKL5 p.Ala40Val has been previously reported to be responsible for early infantile epileptic encephalopathy. In our case, the CDKL5 heterozygous mutation showed somatic mosaicism because the boy's karyotype was 46,XY. The KCNQ2 variant p.Glu515Asp is known to cause benign familial neonatal seizures-1, and this variant showed paternal inheritance. Although we believe that the somatic mosaic CDKL5 mutation is mainly responsible for the neurological phenotype in the patient, the KCNQ2 variant might have some neurological effect. Genetic analysis by next-generation sequencing is capable of identifying multiple variants in a patient. Copyright © 2015 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.
Kohli, Utkarsh; Hahn, Maureen K; English, Brett A; Sofowora, Gbenga G; Muszkat, Mordechai; Li, Chun; Blakely, Randy D; Stein, C Michael; Kurnik, Daniel
2011-04-01
The presynaptic norepinephrine transporter (NET) mediates synaptic clearance and recycling of norepinephrine. NET-deficient transgenic mice have elevated blood pressure (BP), heart rate, and catecholamine concentrations. However, the in-vivo effects of common NET variants on cardiovascular regulation at rest and during exercise are unknown. We studied cardiovascular responses and plasma catecholamine concentrations at rest and during bicycle exercise at increasing workloads (25, 50, and 75 W) in 145 healthy participants. We used multiple linear regressions to analyze the effect of common, purportedly functional polymorphisms in NET (rs2242446 and rs28386840) on cardiovascular measures. 44 and 58.9% of participants carried at least one variant allele for NET T-182C and A-3081T, respectively. Systolic BP during exercise and systolic BP-area under the curve were higher in carriers of variant NET alleles (P=0.003 and 0.009 for T-182C and A-3081T, respectively) and NET haplotype -182C/-3081T compared with -182T/-3081A (all P<0.01). Diastolic BP during exercise was also higher at lower, but not at higher exercise stages in carriers of NET -182C (P<0.01) and -3081T variants (P<0.05). NET genotypes were not associated with catecholamine concentrations or heart rate. Common genetic NET variants (-182C and -3081T) are associated with greater BP response to exercise in humans.
Apparent founder effect during the early years of the San Francisco HIV type 1 epidemic (1978-1979).
Foley, B; Pan, H; Buchbinder, S; Delwart, E L
2000-10-10
HIV-1 envelope sequence variants were RT-PCR amplified from serum samples cryopreserved in San Francisco in 1978-1979. The HIV-1 subtype B env V3-V5 sequences from four homosexual men clustered phylogenetically, with a median nucleotide distance of 2.8%, reflecting a recent common origin. These early U.S. HIV-1 env variants mapped close to the phylogenetic root of the subtype B tree while env variants collected in the United States throughout the 1980s and 1990s showed, on average, increasing genetic diversity and divergence from the subtype B consensus sequence. These results indicate that the majority of HIV-1 currently circulating in the United States may be descended from an initial introduction and rapid spread during the mid- to late 1970s of subtype B viruses with limited variability (i.e., a founder effect). As expected from the starburst-shaped phylogeny of HIV-1 subtype B, contemporary U.S. strains were, on average, more closely related at the nucleic acid and amino acid levels to the earlier 1978-1979 env variants than to each other. The growing levels of HIV-1 genetic diversity, one of multiple obstacles in designing a protective vaccine, may therefore be mitigated by using epidemic founding variants as antigenic strains for protection against contemporary strains.
Bagnall, Richard D; Crompton, Douglas E; Petrovski, Slavé; Lam, Lien; Cutmore, Carina; Garry, Sarah I; Sadleir, Lynette G; Dibbens, Leanne M; Cairns, Anita; Kivity, Sara; Afawi, Zaid; Regan, Brigid M; Duflou, Johan; Berkovic, Samuel F; Scheffer, Ingrid E; Semsarian, Christopher
2016-04-01
The leading cause of epilepsy-related premature mortality is sudden unexpected death in epilepsy (SUDEP). The cause of SUDEP remains unknown. To search for genetic risk factors in SUDEP cases, we performed an exome-based analysis of rare variants. Demographic and clinical information of 61 SUDEP cases were collected. Exome sequencing and rare variant collapsing analysis with 2,936 control exomes were performed to test for genes enriched with damaging variants. Additionally, cardiac arrhythmia, respiratory control, and epilepsy genes were screened for variants with frequency of <0.1% and predicted to be pathogenic with multiple in silico tools. The 61 SUDEP cases were categorized as definite SUDEP (n = 54), probable SUDEP (n = 5), and definite SUDEP plus (n = 2). We identified de novo mutations, previously reported pathogenic mutations, or candidate pathogenic variants in 28 of 61 (46%) cases. Four SUDEP cases (7%) had mutations in common genes responsible for the cardiac arrhythmia disease, long QT syndrome (LQTS). Nine cases (15%) had candidate pathogenic variants in dominant cardiac arrhythmia genes. Fifteen cases (25%) had mutations or candidate pathogenic variants in dominant epilepsy genes. No gene reached genome-wide significance with rare variant collapsing analysis; however, DEPDC5 (p = 0.00015) and KCNH2 (p = 0.0037) were among the top 30 genes, genome-wide. A sizeable proportion of SUDEP cases have clinically relevant mutations in cardiac arrhythmia and epilepsy genes. In cases with an LQTS gene mutation, SUDEP may occur as a result of a predictable and preventable cause. Understanding the genetic basis of SUDEP may inform cascade testing of at-risk family members. © 2016 American Neurological Association.
Genetic study of intracranial aneurysms.
Yan, Junxia; Hitomi, Toshiaki; Takenaka, Katsunobu; Kato, Masayasu; Kobayashi, Hatasu; Okuda, Hiroko; Harada, Kouji H; Koizumi, Akio
2015-03-01
Rupture of intracranial aneurysms (IAs) causes subarachnoid hemorrhage, leading to immediate death or severe disability. Identification of the genetic factors involved is critical for disease prevention and treatment. We aimed to identify the susceptibility genes for IAs. Exome sequencing was performed in 12 families with histories of multiple cases of IA (number of cases per family ≥3), with a total of 42 cases. Various filtering strategies were used to select the candidate variants. Replicate association studies of several candidate variants were performed in probands of 24 additional IA families and 426 sporadic IA cases. Functional analysis for the mutations was conducted. After sequencing and filtering, 78 variants were selected for the following reasons: allele frequencies of variants in 42 patients was significantly (P<0.05) larger than expected; variants were completely shared by all patients with IA within ≥1 family; variants predicted damage to the structure or function of the protein by PolyPhen-2 (Polymorphism Phenotyping V2) and SIFT (Sorting Intolerance From Tolerant). We selected 10 variants from 9 genes (GPR63, ADAMST15, MLL2, IL10RA, PAFAH2, THBD, IL11RA, FILIP1L, and ZNF222) to form 78 candidate variants by considering commonness in families, known disease genes, or ontology association with angiogenesis. Replicate association studies revealed that only p.E133Q in ADAMTS15 was aggregated in the familial IA cases (odds ratio, 5.96; 95% confidence interval, 2.40-14.82; P=0.0001; significant after the Bonferroni correction [P=0.05/78=0.0006]). Silencing ADAMTS15 and overexpression of ADAMTS15 p.E133Q accelerated endothelial cell migration, suggesting that ADAMTS15 may have antiangiogenic activity. ADAMTS15 is a candidate gene for IAs. © 2015 American Heart Association, Inc.
Kapplinger, Jamie D; Pundi, Krishna N; Larson, Nicholas B; Callis, Thomas E; Tester, David J; Bikker, Hennie; Wilde, Arthur A M; Ackerman, Michael J
2018-02-01
Pathogenic RYR2 variants account for ≈60% of clinically definite cases of catecholaminergic polymorphic ventricular tachycardia. However, the rate of rare benign RYR2 variants identified in the general population remains a challenge for genetic test interpretation. Therefore, we examined the results of the RYR2 genetic test among patients referred for commercial genetic testing and examined factors impacting variant interpretability. Frequency and location comparisons were made for RYR2 variants identified among 1355 total patients of varying clinical certainty and 60 706 Exome Aggregation Consortium controls. The impact of the clinical phenotype on the yield of RYR2 variants was examined. Six in silico tools were assessed using patient- and control-derived variants. A total of 18.2% (218/1200) of patients referred for commercial testing hosted rare RYR2 variants, statistically less than the 59% (46/78) yield among clinically definite cases, resulting in a much higher potential genetic false discovery rate among referrals considering the 3.2% background rate of rare, benign RYR2 variants. Exclusion of clearly putative pathogenic variants further complicates the interpretation of the next novel RYR2 variant. Exonic/topologic analyses revealed overrepresentation of patient variants in exons covering only one third of the protein. In silico tools largely failed to show evidence toward enhancement of variant interpretation. Current expert recommendations have resulted in increased use of RYR2 genetic testing in patients with questionable clinical phenotypes. Using the largest to date catecholaminergic polymorphic ventricular tachycardia patient versus control comparison, this study highlights important variables in the interpretation of variants to overcome the 3.2% background rate that confounds RYR2 variant interpretation. © 2018 American Heart Association, Inc.
Haplotype Analysis in Multiple Crosses to Identify a QTL Gene
Wang, Xiaosong; Korstanje, Ron; Higgins, David; Paigen, Beverly
2004-01-01
Identifying quantitative trait locus (QTL) genes is a challenging task. Herein, we report using a two-step process to identify Apoa2 as the gene underlying Hdlq5, a QTL for plasma high-density lipoprotein cholesterol (HDL) levels on mouse chromosome 1. First, we performed a sequence analysis of the Apoa2 coding region in 46 genetically diverse mouse strains and found five different APOA2 protein variants, which we named APOA2a to APOA2e. Second, we conducted a haplotype analysis of the strains in 21 crosses that have so far detected HDL QTLs; we found that Hdlq5 was detected only in the nine crosses where one parent had the APOA2b protein variant characterized by an Ala61-to-Val61 substitution. We then found that strains with the APOA2b variant had significantly higher (P ≤ 0.002) plasma HDL levels than those with either the APOA2a or the APOA2c variant. These findings support Apoa2 as the underlying Hdlq5 gene and suggest the Apoa2 polymorphisms responsible for the Hdlq5 phenotype. Therefore, haplotype analysis in multiple crosses can be used to support a candidate QTL gene. PMID:15310659
Haplotype analysis in multiple crosses to identify a QTL gene.
Wang, Xiaosong; Korstanje, Ron; Higgins, David; Paigen, Beverly
2004-09-01
Identifying quantitative trait locus (QTL) genes is a challenging task. Herein, we report using a two-step process to identify Apoa2 as the gene underlying Hdlq5, a QTL for plasma high-density lipoprotein cholesterol (HDL) levels on mouse chromosome 1. First, we performed a sequence analysis of the Apoa2 coding region in 46 genetically diverse mouse strains and found five different APOA2 protein variants, which we named APOA2a to APOA2e. Second, we conducted a haplotype analysis of the strains in 21 crosses that have so far detected HDL QTLs; we found that Hdlq5 was detected only in the nine crosses where one parent had the APOA2b protein variant characterized by an Ala61-to-Val61 substitution. We then found that strains with the APOA2b variant had significantly higher (P < or = 0.002) plasma HDL levels than those with either the APOA2a or the APOA2c variant. These findings support Apoa2 as the underlying Hdlq5 gene and suggest the Apoa2 polymorphisms responsible for the Hdlq5 phenotype. Therefore, haplotype analysis in multiple crosses can be used to support a candidate QTL gene.
Detecting Genomic Clustering of Risk Variants from Sequence Data: Cases vs. Controls
Schaid, Daniel J.; Sinnwell, Jason P.; McDonnell, Shannon K.; Thibodeau, Stephen N.
2013-01-01
As the ability to measure dense genetic markers approaches the limit of the DNA sequence itself, taking advantage of possible clustering of genetic variants in, and around, a gene would benefit genetic association analyses, and likely provide biological insights. The greatest benefit might be realized when multiple rare variants cluster in a functional region. Several statistical tests have been developed, one of which is based on the popular Kulldorff scan statistic for spatial clustering of disease. We extended another popular spatial clustering method – Tango’s statistic – to genomic sequence data. An advantage of Tango’s method is that it is rapid to compute, and when single test statistic is computed, its distribution is well approximated by a scaled chi-square distribution, making computation of p-values very rapid. We compared the Type-I error rates and power of several clustering statistics, as well as the omnibus sequence kernel association test (SKAT). Although our version of Tango’s statistic, which we call “Kernel Distance” statistic, took approximately half the time to compute than the Kulldorff scan statistic, it had slightly less power than the scan statistic. Our results showed that the Ionita-Laza version of Kulldorff’s scan statistic had the greatest power over a range of clustering scenarios. PMID:23842950
A comprehensive global genotype-phenotype database for rare diseases.
Trujillano, Daniel; Oprea, Gabriela-Elena; Schmitz, Yvonne; Bertoli-Avella, Aida M; Abou Jamra, Rami; Rolfs, Arndt
2017-01-01
The ability to discover genetic variants in a patient runs far ahead of the ability to interpret them. Databases with accurate descriptions of the causal relationship between the variants and the phenotype are valuable since these are critical tools in clinical genetic diagnostics. Here, we introduce a comprehensive and global genotype-phenotype database focusing on rare diseases. This database (CentoMD ® ) is a browser-based tool that enables access to a comprehensive, independently curated system utilizing stringent high-quality criteria and a quickly growing repository of genetic and human phenotype ontology (HPO)-based clinical information. Its main goals are to aid the evaluation of genetic variants, to enhance the validity of the genetic analytical workflow, to increase the quality of genetic diagnoses, and to improve evaluation of treatment options for patients with hereditary diseases. The database software correlates clinical information from consented patients and probands of different geographical backgrounds with a large dataset of genetic variants and, when available, biomarker information. An automated follow-up tool is incorporated that informs all users whenever a variant classification has changed. These unique features fully embedded in a CLIA/CAP-accredited quality management system allow appropriate data quality and enhanced patient safety. More than 100,000 genetically screened individuals are documented in the database, resulting in more than 470 million variant detections. Approximately, 57% of the clinically relevant and uncertain variants in the database are novel. Notably, 3% of the genetic variants identified and previously reported in the literature as being associated with a particular rare disease were reclassified, based on internal evidence, as clinically irrelevant. The database offers a comprehensive summary of the clinical validity and causality of detected gene variants with their associated phenotypes, and is a valuable tool for identifying new disease genes through the correlation of novel genetic variants with specific, well-defined phenotypes.
Woods, James S; Heyer, Nicholas J; Russo, Joan E; Martin, Michael D; Pillai, Pradeep B; Farin, Federico M
2013-01-01
Mercury (Hg) is neurotoxic, and children may be particularly susceptible to this effect. A current major challenge is the identification of children who may be uniquely susceptible to Hg toxicity because of genetic disposition. We examined the hypothesis that genetic variants of metallothionein (MT) that are reported to affect Hg toxicokinetics in adults would modify the neurotoxic effects of Hg in children. Five hundred seven children, 8-12 years of age at baseline, participated in a clinical trial to evaluate the neurobehavioral effects of Hg from dental amalgam tooth fillings. Subjects were evaluated at baseline and at 7 subsequent annual intervals for neurobehavioral performance and urinary Hg levels. Following the completion of the clinical trial, we performed genotyping assays for variants of MT isoforms MT1M (rs2270837) and MT2A (rs10636) on biological samples provided by 330 of the trial participants. Regression modeling strategies were employed to evaluate associations between allelic status, Hg exposure, and neurobehavioral test outcomes. Among girls, few significant interactions or independent main effects for Hg exposure and either of the MT gene variants were observed. In contrast, among boys, numerous significant interaction effects between variants of MT1M and MT2A, alone and combined, with Hg exposure were observed spanning multiple domains of neurobehavioral function. All dose-response associations between Hg exposure and test performance were restricted to boys and were in the direction of impaired performance. These findings suggest increased susceptibility to the adverse neurobehavioral effects of Hg among children with relatively common genetic variants of MT, and may have important public health implications for future strategies aimed at protecting children and adolescents from the potential health risks associated with Hg exposure. We note that because urinary Hg reflects a composite exposure index that cannot be attributed to a specific source, these findings do not support an association between Hg in dental amalgams specifically and the adverse neurobehavioral outcomes observed. © 2013.
Two Independent Functional Risk Haplotypes in TNIP1 are Associated with Systemic Lupus Erythematosus
Adrianto, Indra; Wang, Shaofeng; Wiley, Graham B.; Lessard, Christopher J.; Kelly, Jennifer A.; Adler, Adam J.; Glenn, Stuart B.; Williams, Adrienne H.; Ziegler, Julie T.; Comeau, Mary E.; Marion, Miranda C.; Wakeland, Benjamin E.; Liang, Chaoying; Kaufman, Kenneth M.; Guthridge, Joel M.; Alarcón-Riquelme, Marta E.; Alarcón, Graciela S.; Anaya, Juan-Manuel; Bae, Sang-Cheol; Kim, Jae-Hoon; Joo, Young Bin; Boackle, Susan A.; Brown, Elizabeth E.; Petri, Michelle A.; Ramsey-Goldman, Rosalind; Reveille, John D.; Vilá, Luis M.; Criswell, Lindsey A.; Edberg, Jeffrey C.; Freedman, Barry I.; Gilkeson, Gary S.; Jacob, Chaim O.; James, Judith A.; Kamen, Diane L.; Kimberly, Robert P.; Martin, Javier; Merrill, Joan T.; Niewold, Timothy B.; Pons-Estel, Bernardo A.; Scofield, R. Hal; Stevens, Anne M.; Tsao, Betty P.; Vyse, Timothy J.; Langefeld, Carl D.; Harley, John B.; Wakeland, Edward K.; Moser, Kathy L.; Montgomery, Courtney G.; Gaffney, Patrick M.
2012-01-01
Objective Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by autoantibody production and altered type I interferon expression. Genetic surveys and genome-wide association studies have identified more than 30 SLE susceptibility genes. One of these genes, TNIP1, encodes the ABIN1 protein. ABIN1 functions in the immune system by restricting the NF-κB signaling. In order to better understand the genetic factors that influence association with SLE in genes that regulate the NF-κB pathway, we analyzed a dense set of genetic markers spanning TNIP1 and TAX1BP1, as well as the TNIP1 homolog, TNIP2, in case-control sets of diverse ethnic origins. Methods We fine-mapped TNIP1, TNIP2, and TAX1BP1 in a total of 8372 SLE cases and 7492 healthy controls from European-ancestry, African-American, Hispanic, East Asian, and African-American Gullah populations. Levels of TNIP1 mRNA and ABIN1 protein were analyzed using quantitative RT-PCR and Western blotting, respectively, in EBV-transformed human B cell lines. Results We found significant associations between genetic variants within TNIP1 and SLE but not in TNIP2 or TAX1BP1. After resequencing and imputation, we identified two independent risk haplotypes within TNIP1 in individuals of European-ancestry that were also present in African-American and Hispanic populations. These risk haplotypes produced lower levels of TNIP1 mRNA and ABIN1 protein suggesting they harbor hypomorphic functional variants that influence susceptibility to SLE by restricting ABIN1 expression. Conclusion Our results confirmed the association signals between SLE and TNIP1 variants in multiple populations and provide new insight into the mechanism by which TNIP1 variants may contribute to SLE pathogenesis. PMID:22833143
2013-01-01
Background Characterising genetic diversity through the analysis of massively parallel sequencing (MPS) data offers enormous potential to significantly improve our understanding of the genetic basis for observed phenotypes, including predisposition to and progression of complex human disease. Great challenges remain in resolving genetic variants that are genuine from the millions of artefactual signals. Results FAVR is a suite of new methods designed to work with commonly used MPS analysis pipelines to assist in the resolution of some of the issues related to the analysis of the vast amount of resulting data, with a focus on relatively rare genetic variants. To the best of our knowledge, no equivalent method has previously been described. The most important and novel aspect of FAVR is the use of signatures in comparator sequence alignment files during variant filtering, and annotation of variants potentially shared between individuals. The FAVR methods use these signatures to facilitate filtering of (i) platform and/or mapping-specific artefacts, (ii) common genetic variants, and, where relevant, (iii) artefacts derived from imbalanced paired-end sequencing, as well as annotation of genetic variants based on evidence of co-occurrence in individuals. We applied conventional variant calling applied to whole-exome sequencing datasets, produced using both SOLiD and TruSeq chemistries, with or without downstream processing by FAVR methods. We demonstrate a 3-fold smaller rare single nucleotide variant shortlist with no detected reduction in sensitivity. This analysis included Sanger sequencing of rare variant signals not evident in dbSNP131, assessment of known variant signal preservation, and comparison of observed and expected rare variant numbers across a range of first cousin pairs. The principles described herein were applied in our recent publication identifying XRCC2 as a new breast cancer risk gene and have been made publically available as a suite of software tools. Conclusions FAVR is a platform-agnostic suite of methods that significantly enhances the analysis of large volumes of sequencing data for the study of rare genetic variants and their influence on phenotypes. PMID:23441864
Poulter, James A; El-Sayed, Walid; Shore, Roger C; Kirkham, Jennifer; Inglehearn, Chris F; Mighell, Alan J
2014-01-01
The conventional approach to identifying the defective gene in a family with an inherited disease is to find the disease locus through family studies. However, the rapid development and decreasing cost of next generation sequencing facilitates a more direct approach. Here, we report the identification of a frameshift mutation in LAMB3 as a cause of dominant hypoplastic amelogenesis imperfecta (AI). Whole-exome sequencing of three affected family members and subsequent filtering of shared variants, without prior genetic linkage, sufficed to identify the pathogenic variant. Simultaneous analysis of multiple family members confirms segregation, enhancing the power to filter the genetic variation found and leading to rapid identification of the pathogenic variant. LAMB3 encodes a subunit of Laminin-5, one of a family of basement membrane proteins with essential functions in cell growth, movement and adhesion. Homozygous LAMB3 mutations cause junctional epidermolysis bullosa (JEB) and enamel defects are seen in JEB cases. However, to our knowledge, this is the first report of dominant AI due to a LAMB3 mutation in the absence of JEB.
Design of DNA pooling to allow incorporation of covariates in rare variants analysis.
Guan, Weihua; Li, Chun
2014-01-01
Rapid advances in next-generation sequencing technologies facilitate genetic association studies of an increasingly wide array of rare variants. To capture the rare or less common variants, a large number of individuals will be needed. However, the cost of a large scale study using whole genome or exome sequencing is still high. DNA pooling can serve as a cost-effective approach, but with a potential limitation that the identity of individual genomes would be lost and therefore individual characteristics and environmental factors could not be adjusted in association analysis, which may result in power loss and a biased estimate of genetic effect. For case-control studies, we propose a design strategy for pool creation and an analysis strategy that allows covariate adjustment, using multiple imputation technique. Simulations show that our approach can obtain reasonable estimate for genotypic effect with only slight loss of power compared to the much more expensive approach of sequencing individual genomes. Our design and analysis strategies enable more powerful and cost-effective sequencing studies of complex diseases, while allowing incorporation of covariate adjustment.
Clop, Alex; Bertoni, Anna; Spain, Sarah L.; Simpson, Michael A.; Pullabhatla, Venu; Tonda, Raul; Hundhausen, Christian; Di Meglio, Paola; De Jong, Pieter; Hayday, Adrian C.; Nestle, Frank O.; Barker, Jonathan N.; Bell, Robert J. A.; Capon, Francesca; Trembath, Richard C.
2013-01-01
Psoriasis is an immune-mediated skin disorder that is inherited as a complex genetic trait. Although genome-wide association scans (GWAS) have identified 36 disease susceptibility regions, more than 50% of the genetic variance can be attributed to a single Major Histocompatibility Complex (MHC) locus, known as PSORS1. Genetic studies indicate that HLA-C is the strongest PSORS1 candidate gene, since markers tagging HLA-Cw*0602 consistently generate the most significant association signals in GWAS. However, it is unclear whether HLA-Cw*0602 is itself the causal PSORS1 allele, especially as the role of SNPs that may affect its expression has not been investigated. Here, we have undertaken an in-depth molecular characterization of the PSORS1 interval, with a view to identifying regulatory variants that may contribute to disease susceptibility. By analysing high-density SNP data, we refined PSORS1 to a 179 kb region encompassing HLA-C and the neighbouring HCG27 pseudogene. We compared multiple MHC sequences spanning this refined locus and identified 144 candidate susceptibility variants, which are unique to chromosomes bearing HLA-Cw*0602. In parallel, we investigated the epigenetic profile of the critical PSORS1 interval and uncovered three enhancer elements likely to be active in T lymphocytes. Finally we showed that nine candidate susceptibility SNPs map within a HLA-C enhancer and that three of these variants co-localise with binding sites for immune-related transcription factors. These data indicate that SNPs affecting HLA-Cw*0602 expression are likely to contribute to psoriasis susceptibility and highlight the importance of integrating multiple experimental approaches in the investigation of complex genomic regions such as the MHC. PMID:23990973
Widespread Site-Dependent Buffering of Human Regulatory Polymorphism
Kutyavin, Tanya; Stamatoyannopoulos, John A.
2012-01-01
The average individual is expected to harbor thousands of variants within non-coding genomic regions involved in gene regulation. However, it is currently not possible to interpret reliably the functional consequences of genetic variation within any given transcription factor recognition sequence. To address this, we comprehensively analyzed heritable genome-wide binding patterns of a major sequence-specific regulator (CTCF) in relation to genetic variability in binding site sequences across a multi-generational pedigree. We localized and quantified CTCF occupancy by ChIP-seq in 12 related and unrelated individuals spanning three generations, followed by comprehensive targeted resequencing of the entire CTCF–binding landscape across all individuals. We identified hundreds of variants with reproducible quantitative effects on CTCF occupancy (both positive and negative). While these effects paralleled protein–DNA recognition energetics when averaged, they were extensively buffered by striking local context dependencies. In the significant majority of cases buffering was complete, resulting in silent variants spanning every position within the DNA recognition interface irrespective of level of binding energy or evolutionary constraint. The prevalence of complex partial or complete buffering effects severely constrained the ability to predict reliably the impact of variation within any given binding site instance. Surprisingly, 40% of variants that increased CTCF occupancy occurred at positions of human–chimp divergence, challenging the expectation that the vast majority of functional regulatory variants should be deleterious. Our results suggest that, even in the presence of “perfect” genetic information afforded by resequencing and parallel studies in multiple related individuals, genomic site-specific prediction of the consequences of individual variation in regulatory DNA will require systematic coupling with empirical functional genomic measurements. PMID:22457641
An, S Sandy; Hanley, Anthony J G; Ziegler, Julie T; Brown, W Mark; Haffner, Steven M; Norris, Jill M; Rotter, Jerome I; Guo, Xiuqing; Chen, Y-D Ida; Wagenknecht, Lynne E; Langefeld, Carl D; Bowden, Donald W; Palmer, Nicholette D
2012-12-01
Adiponectin is an adipocytokine associated with a variety of metabolic traits. These associations in human studies, in conjunction with functional studies in model systems, have implicated adiponectin in multiple metabolic processes. We hypothesize that genetic variants associated with plasma adiponectin would also be associated with glucose homeostasis and adiposity phenotypes. The Insulin Resistance Atherosclerosis Family Study was designed to identify the genetic and environmental basis of insulin resistance and adiposity in the Hispanic- (n=1,424) and African-American (n=604) population. High quality metabolic phenotypes, e.g. insulin sensitivity (S(I)), acute insulin response (AIR), disposition index (DI), fasting glucose, body mass index (BMI), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and waist circumference, were explored. Based on association analysis of more than 40 genetic polymorphisms in the adiponectin gene (ADIPOQ), we found no consistent association of ADIPOQ variants with plasma adiponectin levels and adiposity phenotypes. However, there were two promoter variants, rs17300539 and rs822387, associated with plasma adiponectin levels (P=0.0079 and 0.021, respectively) in the Hispanic-American cohort that were also associated with S(I) (P=0.0067 and 0.013, respectively). In contrast, there was only a single promoter SNP, rs17300539, associated with plasma adiponectin levels (P=0.0018) and fasting glucose (P=0.042) in the African-American cohort. Strikingly, high impact coding variants did not show evidence of association. The lack of consistent patterns of association between variants, adiponectin levels, glucose homeostasis, and adiposity phenotypes suggests a reassessment of the influence of adiponectin in these pathways. Copyright © 2012 Elsevier Inc. All rights reserved.
Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.
Fairfax, Benjamin P; Humburg, Peter; Makino, Seiko; Naranbhai, Vivek; Wong, Daniel; Lau, Evelyn; Jostins, Luke; Plant, Katharine; Andrews, Robert; McGee, Chris; Knight, Julian C
2014-03-07
To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.
Zabalza, Michel; Subirana, Isaac; Lluis-Ganella, Carla; Sayols-Baixeras, Sergi; de Groot, Eric; Arnold, Roman; Cenarro, Ana; Ramos, Rafel; Marrugat, Jaume; Elosua, Roberto
2015-10-01
Recent studies have identified several genetic variants associated with coronary artery disease. Some of these genetic variants are not associated with classical cardiovascular risk factors and the mechanism of such associations is unclear. The aim of the study was to determine whether these genetic variants are related to subclinical atherosclerosis measured by carotid intima media thickness, carotid stiffness, and ankle brachial index. A cross-sectional study nested in the follow-up of the REGICOR cohort was undertaken. The study included 2667 individuals. Subclinical atherosclerosis measurements were performed with standardized methods. Nine genetic variants were genotyped to assess associations with subclinical atherosclerosis, individually and in a weighted genetic risk score. A systematic review and meta-analysis of previous studies that analyzed these associations was undertaken. Neither the selected genetic variants nor the genetic risk score were significantly associated with subclinical atherosclerosis. In the meta-analysis, the rs1746048 (CXCL12; n = 10581) risk allele was directly associated with carotid intima-media thickness (β = 0.008; 95% confidence interval, 0.001-0.015), whereas the rs6725887 (WDR12; n = 7801) risk allele was inversely associated with this thickness (β = -0.013; 95% confidence interval, -0.024 to -0.003). The analyzed genetic variants seem to mediate their association with coronary artery disease through different mechanisms. Our results generate the hypothesis that the CXCL12 variant appears to influence coronary artery disease risk through arterial remodeling and thickening, whereas the WDR12 risk variant could be related to higher plaque vulnerability. Copyright © 2014 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.
Multi-gene panel testing in Korean patients with common genetic generalized epilepsy syndromes.
Lee, Cha Gon; Lee, Jeehun; Lee, Munhyang
2018-01-01
Genetic heterogeneity of common genetic generalized epilepsy syndromes is frequently considered. The present study conducted a focused analysis of potential candidate or susceptibility genes for common genetic generalized epilepsy syndromes using multi-gene panel testing with next-generation sequencing. This study included patients with juvenile myoclonic epilepsy, juvenile absence epilepsy, and epilepsy with generalized tonic-clonic seizures alone. We identified pathogenic variants according to the American College of Medical Genetics and Genomics guidelines and identified susceptibility variants using case-control association analyses and family analyses for familial cases. A total of 57 patients were enrolled, including 51 sporadic cases and 6 familial cases. Twenty-two pathogenic and likely pathogenic variants of 16 different genes were identified. CACNA1H was the most frequently observed single gene. Variants of voltage-gated Ca2+ channel genes, including CACNA1A, CACNA1G, and CACNA1H were observed in 32% of variants (n = 7/22). Analyses to identify susceptibility variants using case-control association analysis indicated that KCNMA1 c.400G>C was associated with common genetic generalized epilepsy syndromes. Only 1 family (family A) exhibited a candidate pathogenic variant p.(Arg788His) on CACNA1H, as determined via family analyses. This study identified candidate genetic variants in about a quarter of patients (n = 16/57) and an average of 2.8 variants was identified in each patient. The results reinforced the polygenic disorder with very high locus and allelic heterogeneity of common GGE syndromes. Further, voltage-gated Ca2+ channels are suggested as important contributors to common genetic generalized epilepsy syndromes. This study extends our comprehensive understanding of common genetic generalized epilepsy syndromes.
Whole-genome sequencing and genetic variant analysis of a Quarter Horse mare.
Doan, Ryan; Cohen, Noah D; Sawyer, Jason; Ghaffari, Noushin; Johnson, Charlie D; Dindot, Scott V
2012-02-17
The catalog of genetic variants in the horse genome originates from a few select animals, the majority originating from the Thoroughbred mare used for the equine genome sequencing project. The purpose of this study was to identify genetic variants, including single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (INDELs), and copy number variants (CNVs) in the genome of an individual Quarter Horse mare sequenced by next-generation sequencing. Using massively parallel paired-end sequencing, we generated 59.6 Gb of DNA sequence from a Quarter Horse mare resulting in an average of 24.7X sequence coverage. Reads were mapped to approximately 97% of the reference Thoroughbred genome. Unmapped reads were de novo assembled resulting in 19.1 Mb of new genomic sequence in the horse. Using a stringent filtering method, we identified 3.1 million SNPs, 193 thousand INDELs, and 282 CNVs. Genetic variants were annotated to determine their impact on gene structure and function. Additionally, we genotyped this Quarter Horse for mutations of known diseases and for variants associated with particular traits. Functional clustering analysis of genetic variants revealed that most of the genetic variation in the horse's genome was enriched in sensory perception, signal transduction, and immunity and defense pathways. This is the first sequencing of a horse genome by next-generation sequencing and the first genomic sequence of an individual Quarter Horse mare. We have increased the catalog of genetic variants for use in equine genomics by the addition of novel SNPs, INDELs, and CNVs. The genetic variants described here will be a useful resource for future studies of genetic variation regulating performance traits and diseases in equids.
Mabuchi, Fumihiko; Sakurada, Yoichi; Kashiwagi, Kenji; Yamagata, Zentaro; Iijima, Hiroyuki; Tsukahara, Shigeo
2015-03-01
To investigate the associations between the non-intraocular pressure (IOP)-related genetic variants (genetic variants associated with vulnerability of the optic nerve independent of IOP) and primary open-angle glaucoma (POAG), including normal-tension glaucoma (NTG) and high-tension glaucoma (HTG), and between the non-IOP-related genetic variants and a family history of glaucoma. Case-control study. Japanese patients with NTG (n = 213) and HTG (n = 212) and 191 control subjects were genotyped for 5 non-IOP-related genetic variants predisposing to POAG near the SRBD1, ELOVL5, CDKN2B/CDKN2B-AS1, SIX1/SIX6, and ATOH7 genes. The load of these genetic variants was compared between the control subjects and patients with NTG or HTG and between the POAG patients with and without a family history of glaucoma. The total number of POAG risk alleles and the product of the odds ratios (POAG risk) of these genetic variants were significantly larger (P < .0025) in patients with both NTG and HTG than in the control subjects, and were significantly larger (P = .0042 and P = .023, respectively) in POAG patients with a family history of glaucoma than in those without. As the number of relatives with glaucoma increased, the total number of risk alleles and the product of the odds ratios increased (P = .012 and P = .047, respectively). Non-IOP-related genetic variants contribute to the pathogenesis of HTG as well as NTG. A positive family history of glaucoma in cases of POAG is thought to reflect the influence of genetic variants predisposing to POAG. Copyright © 2015 Elsevier Inc. All rights reserved.
Sivadas, A; Salleh, M Z; Teh, L K; Scaria, V
2017-10-01
Expanding the scope of pharmacogenomic research by including multiple global populations is integral to building robust evidence for its clinical translation. Deep whole-genome sequencing of diverse ethnic populations provides a unique opportunity to study rare and common pharmacogenomic markers that often vary in frequency across populations. In this study, we aim to build a diverse map of pharmacogenetic variants in South East Asian (SEA) Malay population using deep whole-genome sequences of 100 healthy SEA Malay individuals. We investigated the allelic diversity of potentially deleterious pharmacogenomic variants in SEA Malay population. Our analysis revealed 227 common and 466 rare potentially functional single nucleotide variants (SNVs) in 437 pharmacogenomic genes involved in drug metabolism, transport and target genes, including 74 novel variants. This study has created one of the most comprehensive maps of pharmacogenetic markers in any population from whole genomes and will hugely benefit pharmacogenomic investigations and drug dosage recommendations in SEA Malays.
Genetic basis for childhood interstitial lung disease among Japanese infants and children.
Hayasaka, Itaru; Cho, Kazutoshi; Akimoto, Takuma; Ikeda, Masahiko; Uzuki, Yutaka; Yamada, Masafumi; Nakata, Koh; Furuta, Itsuko; Ariga, Tadashi; Minakami, Hisanori
2018-02-01
BackgroundGenetic variants responsible for childhood interstitial lung disease (chILD) have not been studied extensively in Japanese patients.MethodsThe study population consisted of 62 Japanese chILD patients. Twenty-one and four patients had pulmonary hypertension resistant to treatment (PH) and hypothyroidism, respectively. Analyses of genetic variants were performed in all 62 patients for SFTPC and ABCA3, in all 21 PH patients for FOXF1, and in a limited number of patients for NKX2.1.ResultsCausative genetic variants for chILD were identified in 11 (18%) patients: SFTPC variants in six, NKX2.1 variants in three, and FOXF1 variants in two patients. No patients had ABCA3 variants. All three and two patients with NKX2.1 variants had hypothyroidism and developmental delay, respectively. We found six novel variants in this study.ConclusionMutations in SFTPC, NKX2.1, and FOXF1 were identified among Japanese infants and children with chILD, whereas ABCA3 mutations were rare.
Post-TBI cognitive performance is moderated by variation within ANKK1 and DRD2 genes
Failla, Michelle D.; Myrga, John M.; Ricker, Joseph H.; Dixon, C. Edward; Conley, Yvette P.; Wagner, Amy K.
2014-01-01
Objective As dopamine neurotransmission impacts cognition, we hypothesized variants in the linked dopamine D2 receptor (DRD2) and ankyrin repeat and kinase domain (ANKK1) genes might account for some individual variability in cognitive recovery post-TBI. Participants Prospective cohort of 108 survivors of severe TBI, recruited consecutively from a level 1 trauma center. Design We examined relationships between DRD2 genetic variation and functional recovery at 6 and 12 months post-TBI. Main Measures Cognitive performance was evaluated using 8 neuropsychological tests targeting different cognitive domains. An overall cognitive composite was developed based on normative data. We also assessed functional cognition, depression status, and global outcome. Subjects were genotyped for 6 DRD2 tagging single nucleotide polymorphisms and Taq1A within ANKK1. Results ANKK1 Taq1A heterozygotes performed better than homozygotes across several cognitive domains at both time-points post-injury. When adjusting for age, GCS, and education, the Taq1A (ANKK1) and rs6279 (DRD2) variants were associated with overall composite scores at 6 months post-TBI (p=0.0468, 0.0430, respectively). At 12 months, only Taq1A remained a significant genetic predictor of cognition (p=0.0128). Following multiple comparisons correction, there were no significant associations between examined genetic variants and functional cognition, depression status, and global outcome. Conclusion These data suggest genetic variation within DRD2 influences cognitive recovery post-TBI. Understanding genetic influences on dopaminergic systems post-TBI may impact current treatment paradigms. PMID:25931179
Genetic variation in alpha2-adrenoreceptors and heart rate recovery after exercise
Kohli, Utkarsh; Diedrich, André; Kannankeril, Prince J.; Muszkat, Mordechai; Sofowora, Gbenga G.; Hahn, Maureen K.; English, Brett A.; Blakely, Randy D.; Stein, C. Michael
2015-01-01
Heart rate recovery (HRR) after exercise is an independent predictor of adverse cardiovascular outcomes. HRR is mediated by both parasympathetic reactivation and sympathetic withdrawal and is highly heritable. We examined whether common genetic variants in adrenergic and cholinergic receptors and transporters affect HRR. In our study 126 healthy subjects (66 Caucasians, 56 African Americans) performed an 8 min step-wise bicycle exercise test with continuous computerized ECG recordings. We fitted an exponential curve to the postexercise R-R intervals for each subject to calculate the recovery constant (kr) as primary outcome. Secondary outcome was the root mean square residuals averaged over 1 min (RMS1min), a marker of parasympathetic tone. We used multiple linear regressions to determine the effect of functional candidate genetic variants in autonomic pathways (6 ADRA2A, 1 ADRA2B, 4 ADRA2C, 2 ADRB1, 3 ADRB2, 2 NET, 2 CHT, and 1 GRK5) on the outcomes before and after adjustment for potential confounders. Recovery constant was lower (indicating slower HRR) in ADRA2B 301–303 deletion carriers (n = 54, P = 0.01), explaining 3.6% of the interindividual variability in HRR. ADRA2A Asn251Lys, ADRA2C rs13118771, and ADRB1 Ser49Gly genotypes were associated with RMS1min. Genetic variability in adrenergic receptors may be associated with HRR after exercise. However, most of the interindividual variability in HRR remained unexplained by the variants examined. Noncandidate gene-driven approaches to study genetic contributions to HRR in larger cohorts will be of interest. PMID:26058836
Difficulties in diagnosing Marfan syndrome using current FBN1 databases.
Groth, Kristian A; Gaustadnes, Mette; Thorsen, Kasper; Østergaard, John R; Jensen, Uffe Birk; Gravholt, Claus H; Andersen, Niels H
2016-01-01
The diagnostic criteria of Marfan syndrome (MFS) highlight the importance of a FBN1 mutation test in diagnosing MFS. As genetic sequencing becomes better, cheaper, and more accessible, the expected increase in the number of genetic tests will become evident, resulting in numerous genetic variants that need to be evaluated for disease-causing effects based on database information. The aim of this study was to evaluate genetic variants in four databases and review the relevant literature. We assessed background data on 23 common variants registered in ESP6500 and classified as causing MFS in the Human Gene Mutation Database (HGMD). We evaluated data in four variant databases (HGMD, UMD-FBN1, ClinVar, and UniProt) according to the diagnostic criteria for MFS and compared the results with the classification of each variant in the four databases. None of the 23 variants was clearly associated with MFS, even though all classifications in the databases stated otherwise. A genetic diagnosis of MFS cannot reliably be based on current variant databases because they contain incorrectly interpreted conclusions on variants. Variants must be evaluated by time-consuming review of the background material in the databases and by combining these data with expert knowledge on MFS. This is a major problem because we expect even more genetic test results in the near future as a result of the reduced cost and process time for next-generation sequencing.Genet Med 18 1, 98-102.
Visualizing the geography of genetic variants.
Marcus, Joseph H; Novembre, John
2017-02-15
One of the key characteristics of any genetic variant is its geographic distribution. The geographic distribution can shed light on where an allele first arose, what populations it has spread to, and in turn on how migration, genetic drift, and natural selection have acted. The geographic distribution of a genetic variant can also be of great utility for medical/clinical geneticists and collectively many genetic variants can reveal population structure. Here we develop an interactive visualization tool for rapidly displaying the geographic distribution of genetic variants. Through a REST API and dynamic front-end, the Geography of Genetic Variants (GGV) browser ( http://popgen.uchicago.edu/ggv/ ) provides maps of allele frequencies in populations distributed across the globe. GGV is implemented as a website ( http://popgen.uchicago.edu/ggv/ ) which employs an API to access frequency data ( http://popgen.uchicago.edu/freq_api/ ). Python and javascript source code for the website and the API are available at: http://github.com/NovembreLab/ggv/ and http://github.com/NovembreLab/ggv-api/ . jnovembre@uchicago.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
Ripke, Stephan; van den Berg, Leonard; Buchbinder, Susan; Carrington, Mary; Cossarizza, Andrea; Dalmau, Judith; Deeks, Steven G.; Delaneau, Olivier; De Luca, Andrea; Goedert, James J.; Haas, David; Herbeck, Joshua T.; Kathiresan, Sekar; Kirk, Gregory D.; Lambotte, Olivier; Luo, Ma; Mallal, Simon; van Manen, Daniëlle; Martinez-Picado, Javier; Meyer, Laurence; Miro, José M.; Mullins, James I.; Obel, Niels; O'Brien, Stephen J.; Pereyra, Florencia; Plummer, Francis A.; Poli, Guido; Qi, Ying; Rucart, Pierre; Sandhu, Manj S.; Shea, Patrick R.; Schuitemaker, Hanneke; Theodorou, Ioannis; Vannberg, Fredrik; Veldink, Jan; Walker, Bruce D.; Weintrob, Amy; Winkler, Cheryl A.; Wolinsky, Steven; Telenti, Amalio; Goldstein, David B.; de Bakker, Paul I. W.; Zagury, Jean-François; Fellay, Jacques
2013-01-01
Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6×10−11). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception of CCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size. PMID:23935489
The impact of HIV-1 genetic diversity on the efficacy of a combinatorial RNAi-based gene therapy.
Herrera-Carrillo, E; Berkhout, B
2015-06-01
A hurdle for human immunodeficiency virus (HIV-1) therapy is the genomic diversity of circulating viruses and the possibility that drug-resistant virus variants are selected. Although RNA interference (RNAi) is a powerful tool to stably inhibit HIV-1 replication by the expression of antiviral short hairpin RNAs (shRNAs) in transduced T cells, this approach is also vulnerable to pre-existing genetic variation and the development of viral resistance through mutation. To prevent viral escape, we proposed to combine multiple shRNAs against important regions of the HIV-1 RNA genome, which should ideally be conserved in all HIV-1 subtypes. The vulnerability of RNAi therapy to viral escape has been studied for a single subtype B strain, but it is unclear whether the antiviral shRNAs can inhibit diverse virus isolates and subtypes, including drug-resistant variants that could be present in treated patients. To determine the breadth of the RNAi gene therapy approach, we studied the susceptibility of HIV-1 subtypes A-E and drug-resistant variants. In addition, we monitored the evolution of HIV-1 escape variants. We demonstrate that the combinatorial RNAi therapy is highly effective against most isolates, supporting the future testing of this gene therapy in appropriate in vivo models.
Paraoxonase promoter and intronic variants modify risk of sporadic amyotrophic lateral sclerosis
Cronin, Simon; Greenway, Matthew J; Prehn, Jochen H M; Hardiman, Orla
2007-01-01
Background The paraoxonases, PON1–3, play a major protective role both against environmental toxins and as part of the antioxidant defence system. Recently, non‐synonymous coding single nucleotide polymorphisms (SNPs), known to lower serum PON activity, have been associated with sporadic ALS (SALS) in a Polish population. A separate trio based study described a detrimental allele at the PON3 intronic variant INS2+3651 (rs10487132). Association between PON gene cluster variants and SALS requires external validation in an independent dataset. Aims To examine the association of the promoter SNPs PON1−162G>A and PON1−108T>C; the non‐synonymous functional SNPs PON1Q192R and L55M and PON2C311S and A148G; and the intronic marker PON3INS2+3651A>G, with SALS in a genetically homogenous population. Methods 221 Irish patients with SALS and 202 unrelated control subjects were genotyped using KASPar chemistries. Statistical analyses and haplotype estimations were conducted using Haploview and Unphased software. Multiple permutation testing, as implemented in Unphased, was applied to haplotype p values to correct for multiple hypotheses. Results Two of the seven SNPs were associated with SALS in the Irish population: PON155M (OR 1.52, p = 0.006) and PON3INS2+3651 G (OR 1.36, p = 0.03). Two locus haplotype analysis showed association only when both of these risk alleles were present (OR 1.7, p = 0.005), suggesting a potential effect modification. Low functioning promoter variants were observed to influence this effect when compared with wild‐type. Conclusions These data provide additional evidence that genetic variation across the paroxanase loci may be common susceptibility factors for SALS. PMID:17702780
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 for cisplatin and 10 for carboplatin replicated in CEU/YRI. Conclusion Enriched `platinum susceptible' populations can be used to discover novel genetic determinants governing interindividual platinum chemotherapy susceptibility. PMID:20393316
The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers.
Amos, Christopher I; Dennis, Joe; Wang, Zhaoming; Byun, Jinyoung; Schumacher, Fredrick R; Gayther, Simon A; Casey, Graham; Hunter, David J; Sellers, Thomas A; Gruber, Stephen B; Dunning, Alison M; Michailidou, Kyriaki; Fachal, Laura; Doheny, Kimberly; Spurdle, Amanda B; Li, Yafang; Xiao, Xiangjun; Romm, Jane; Pugh, Elizabeth; Coetzee, Gerhard A; Hazelett, Dennis J; Bojesen, Stig E; Caga-Anan, Charlisse; Haiman, Christopher A; Kamal, Ahsan; Luccarini, Craig; Tessier, Daniel; Vincent, Daniel; Bacot, François; Van Den Berg, David J; Nelson, Stefanie; Demetriades, Stephen; Goldgar, David E; Couch, Fergus J; Forman, Judith L; Giles, Graham G; Conti, David V; Bickeböller, Heike; Risch, Angela; Waldenberger, Melanie; Brüske-Hohlfeld, Irene; Hicks, Belynda D; Ling, Hua; McGuffog, Lesley; Lee, Andrew; Kuchenbaecker, Karoline; Soucy, Penny; Manz, Judith; Cunningham, Julie M; Butterbach, Katja; Kote-Jarai, Zsofia; Kraft, Peter; FitzGerald, Liesel; Lindström, Sara; Adams, Marcia; McKay, James D; Phelan, Catherine M; Benlloch, Sara; Kelemen, Linda E; Brennan, Paul; Riggan, Marjorie; O'Mara, Tracy A; Shen, Hongbing; Shi, Yongyong; Thompson, Deborah J; Goodman, Marc T; Nielsen, Sune F; Berchuck, Andrew; Laboissiere, Sylvie; Schmit, Stephanie L; Shelford, Tameka; Edlund, Christopher K; Taylor, Jack A; Field, John K; Park, Sue K; Offit, Kenneth; Thomassen, Mads; Schmutzler, Rita; Ottini, Laura; Hung, Rayjean J; Marchini, Jonathan; Amin Al Olama, Ali; Peters, Ulrike; Eeles, Rosalind A; Seldin, Michael F; Gillanders, Elizabeth; Seminara, Daniela; Antoniou, Antonis C; Pharoah, Paul D P; Chenevix-Trench, Georgia; Chanock, Stephen J; Simard, Jacques; Easton, Douglas F
2017-01-01
Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR. ©2016 American Association for Cancer Research.
The OncoArray Consortium: a Network for Understanding the Genetic Architecture of Common Cancers
Amos, Christopher I.; Dennis, Joe; Wang, Zhaoming; Byun, Jinyoung; Schumacher, Fredrick R.; Gayther, Simon A.; Casey, Graham; Hunter, David J.; Sellers, Thomas A.; Gruber, Stephen B.; Dunning, Alison M.; Michailidou, Kyriaki; Fachal, Laura; Doheny, Kimberly; Spurdle, Amanda B.; Li, Yafang; Xiao, Xiangjun; Romm, Jane; Pugh, Elizabeth; Coetzee, Gerhard A.; Hazelett, Dennis J.; Bojesen, Stig E.; Caga-Anan, Charlisse; Haiman, Christopher A.; Kamal, Ahsan; Luccarini, Craig; Tessier, Daniel; Vincent, Daniel; Bacot, François; Van Den Berg, David J.; Nelson, Stefanie; Demetriades, Stephen; Goldgar, David E.; Couch, Fergus J.; Forman, Judith L.; Giles, Graham G.; Conti, David V.; Bickeböller, Heike; Risch, Angela; Waldenberger, Melanie; Brüske, Irene; Hicks, Belynda D.; Ling, Hua; McGuffog, Lesley; Lee, Andrew; Kuchenbaecker, Karoline B.; Soucy, Penny; Manz, Judith; Cunningham, Julie M.; Butterbach, Katja; Kote-Jarai, Zsofia; Kraft, Peter; FitzGerald, Liesel M.; Lindström, Sara; Adams, Marcia; McKay, James D.; Phelan, Catherine M.; Benlloch, Sara; Kelemen, Linda E.; Brennan, Paul; Riggan, Marjorie; O’Mara, Tracy A.; Shen, Hongbin; Shi, Yongyong; Thompson, Deborah J.; Goodman, Marc T.; Nielsen, Sune F.; Berchuck, Andrew; Laboissiere, Sylvie; Schmit, Stephanie L.; Shelford, Tameka; Edlund, Christopher K.; Taylor, Jack A.; Field, John K.; Park, Sue K.; Offit, Kenneth; Thomassen, Mads; Schmutzler, Rita; Ottini, Laura; Hung, Rayjean J.; Marchini, Jonathan; Al Olama, Ali Amin; Peters, Ulrike; Eeles, Rosalind A.; Seldin, Michael F.; Gillanders, Elizabeth; Seminara, Daniela; Antoniou, Antonis C.; Pharoah, Paul D.; Chenevix-Trench, Georgia; Chanock, Stephen J.; Simard, Jacques; Easton, Douglas F.
2016-01-01
Background Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers and cancer related traits. Methods The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions Results from these analyses will enable researchers to identify new susceptibility loci, perform fine mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental and lifestyle related exposures. Impact Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. PMID:27697780
Kwon, Inchan; Choi, Eun Sil
2016-01-01
Multiple-site-specific incorporation of a noncanonical amino acid into a recombinant protein would be a very useful technique to generate multiple chemical handles for bioconjugation and multivalent binding sites for the enhanced interaction. Previously combination of a mutant yeast phenylalanyl-tRNA synthetase variant and the yeast phenylalanyl-tRNA containing the AAA anticodon was used to incorporate a noncanonical amino acid into multiple UUU phenylalanine (Phe) codons in a site-specific manner. However, due to the less selective codon recognition of the AAA anticodon, there was significant misincorporation of a noncanonical amino acid into unwanted UUC Phe codons. To enhance codon selectivity, we explored degenerate leucine (Leu) codons instead of Phe degenerate codons. Combined use of the mutant yeast phenylalanyl-tRNA containing the CAA anticodon and the yPheRS_naph variant allowed incorporation of a phenylalanine analog, 2-naphthylalanine, into murine dihydrofolate reductase in response to multiple UUG Leu codons, but not to other Leu codon sites. Despite the moderate UUG codon occupancy by 2-naphthylalaine, these results successfully demonstrated that the concept of forced ambiguity of the genetic code can be achieved for the Leu codons, available for multiple-site-specific incorporation. PMID:27028506
Kwon, Inchan; Choi, Eun Sil
2016-01-01
Multiple-site-specific incorporation of a noncanonical amino acid into a recombinant protein would be a very useful technique to generate multiple chemical handles for bioconjugation and multivalent binding sites for the enhanced interaction. Previously combination of a mutant yeast phenylalanyl-tRNA synthetase variant and the yeast phenylalanyl-tRNA containing the AAA anticodon was used to incorporate a noncanonical amino acid into multiple UUU phenylalanine (Phe) codons in a site-specific manner. However, due to the less selective codon recognition of the AAA anticodon, there was significant misincorporation of a noncanonical amino acid into unwanted UUC Phe codons. To enhance codon selectivity, we explored degenerate leucine (Leu) codons instead of Phe degenerate codons. Combined use of the mutant yeast phenylalanyl-tRNA containing the CAA anticodon and the yPheRS_naph variant allowed incorporation of a phenylalanine analog, 2-naphthylalanine, into murine dihydrofolate reductase in response to multiple UUG Leu codons, but not to other Leu codon sites. Despite the moderate UUG codon occupancy by 2-naphthylalaine, these results successfully demonstrated that the concept of forced ambiguity of the genetic code can be achieved for the Leu codons, available for multiple-site-specific incorporation.
Koenen, Karestan C; DeVivo, Immaculata; Rich-Edwards, Janet; Smoller, Jordan W; Wright, Rosalind J; Purcell, Shaun M
2009-01-01
Background One in nine American women will meet criteria for the diagnosis of posttraumatic stress disorder (PTSD) in their lifetime. Although twin studies suggest genetic influences account for substantial variance in PTSD risk, little progress has been made in identifying variants in specific genes that influence liability to this common, debilitating disorder. Methods and design We are using the unique resource of the Nurses Health Study II, a prospective epidemiologic cohort of 68,518 women, to conduct what promises to be the largest candidate gene association study of PTSD to date. The entire cohort will be screened for trauma exposure and PTSD; 3,000 women will be selected for PTSD diagnostic interviews based on the screening data. Our nested case-control study will genotype1000 women who developed PTSD following a history of trauma exposure; 1000 controls will be selected from women who experienced similar traumas but did not develop PTSD. The primary aim of this study is to detect genetic variants that predict the development of PTSD following trauma. We posit inherited vulnerability to PTSD is mediated by genetic variation in three specific neurobiological systems whose alterations are implicated in PTSD etiology: the hypothalamic-pituitary-adrenal axis, the locus coeruleus/noradrenergic system, and the limbic-frontal neuro-circuitry of fear. The secondary, exploratory aim of this study is to dissect genetic influences on PTSD in the broader genetic and environmental context for the candidate genes that show significant association with PTSD in detection analyses. This will involve: conducting conditional tests to identify the causal genetic variant among multiple correlated signals; testing whether the effect of PTSD genetic risk variants is moderated by age of first trauma, trauma type, and trauma severity; and exploring gene-gene interactions using a novel gene-based statistical approach. Discussion Identification of liability genes for PTSD would represent a major advance in understanding the pathophysiology of the disorder. Such understanding could advance the development of new pharmacological agents for PTSD treatment and prevention. Moreover, the addition of PTSD assessment data will make the NHSII cohort an unparalleled resource for future genetic studies of PTSD as well as provide the unique opportunity for the prospective examination of PTSD-disease associations. PMID:19480706
Huang, Lei; Kang, Wenjun; Bartom, Elizabeth; Onel, Kenan; Volchenboum, Samuel; Andrade, Jorge
2015-01-01
Whole exome sequencing has facilitated the discovery of causal genetic variants associated with human diseases at deep coverage and low cost. In particular, the detection of somatic mutations from tumor/normal pairs has provided insights into the cancer genome. Although there is an abundance of publicly-available software for the detection of germline and somatic variants, concordance is generally limited among variant callers and alignment algorithms. Successful integration of variants detected by multiple methods requires in-depth knowledge of the software, access to high-performance computing resources, and advanced programming techniques. We present ExScalibur, a set of fully automated, highly scalable and modulated pipelines for whole exome data analysis. The suite integrates multiple alignment and variant calling algorithms for the accurate detection of germline and somatic mutations with close to 99% sensitivity and specificity. ExScalibur implements streamlined execution of analytical modules, real-time monitoring of pipeline progress, robust handling of errors and intuitive documentation that allows for increased reproducibility and sharing of results and workflows. It runs on local computers, high-performance computing clusters and cloud environments. In addition, we provide a data analysis report utility to facilitate visualization of the results that offers interactive exploration of quality control files, read alignment and variant calls, assisting downstream customization of potential disease-causing mutations. ExScalibur is open-source and is also available as a public image on Amazon cloud. PMID:26271043
Kelemen, Linda E.; Terry, Kathryn L.; Goodman, Marc T.; Webb, Penelope M.; Bandera, Elisa V.; McGuire, Valerie; Rossing, Mary Anne; Wang, Qinggang; Dicks, Ed; Tyrer, Jonathan P.; Song, Honglin; Kupryjanczyk, Jolanta; Dansonka-Mieszkowska, Agnieszka; Plisiecka-Halasa, Joanna; Timorek, Agnieszka; Menon, Usha; Gentry-Maharaj, Aleksandra; Gayther, Simon A.; Ramus, Susan J.; Narod, Steven A.; Risch, Harvey A.; McLaughlin, John R.; Siddiqui, Nadeem; Glasspool, Rosalind; Paul, James; Carty, Karen; Gronwald, Jacek; Lubiński, Jan; Jakubowska, Anna; Cybulski, Cezary; Kiemeney, Lambertus A.; Massuger, Leon F. A. G.; van Altena, Anne M.; Aben, Katja K. H.; Olson, Sara H.; Orlow, Irene; Cramer, Daniel W.; Levine, Douglas A.; Bisogna, Maria; Giles, Graham G.; Southey, Melissa C.; Bruinsma, Fiona; Kjær, Susanne Krüger; Høgdall, Estrid; Jensen, Allan; Høgdall, Claus K.; Lundvall, Lene; Engelholm, Svend-Aage; Heitz, Florian; du Bois, Andreas; Harter, Philipp; Schwaab, Ira; Butzow, Ralf; Nevanlinna, Heli; Pelttari, Liisa M.; Leminen, Arto; Thompson, Pamela J.; Lurie, Galina; Wilkens, Lynne R.; Lambrechts, Diether; Van Nieuwenhuysen, Els; Lambrechts, Sandrina; Vergote, Ignace; Beesley, Jonathan; Fasching, Peter A.; Beckmann, Matthias W.; Hein, Alexander; Ekici, Arif B.; Doherty, Jennifer A.; Wu, Anna H.; Pearce, Celeste L.; Pike, Malcolm C.; Stram, Daniel; Chang-Claude, Jenny; Rudolph, Anja; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo B.; Bogdanova, Natalia; Antonenkova, Natalia; Odunsi, Kunle; Edwards, Robert P.; Kelley, Joseph L.; Modugno, Francesmary; Ness, Roberta B.; Karlan, Beth Y.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Fridley, Brooke L.; Vierkant, Robert A.; Cunningham, Julie M.; Wu, Xifeng; Lu, Karen; Liang, Dong; Hildebrandt, Michelle A.T.; Weber, Rachel Palmieri; Iversen, Edwin S.; Tworoger, Shelley S.; Poole, Elizabeth M.; Salvesen, Helga B.; Krakstad, Camilla; Bjorge, Line; Tangen, Ingvild L.; Pejovic, Tanja; Bean, Yukie; Kellar, Melissa; Wentzensen, Nicolas; Brinton, Louise A.; Lissowska, Jolanta; Garcia-Closas, Montserrat; Campbell, Ian G.; Eccles, Diana; Whittemore, Alice S.; Sieh, Weiva; Rothstein, Joseph H.; Anton-Culver, Hoda; Ziogas, Argyrios; Phelan, Catherine M.; Moysich, Kirsten B.; Goode, Ellen L.; Schildkraut, Joellen M.; Berchuck, Andrew; Pharoah, Paul D.P.; Sellers, Thomas A.; Brooks-Wilson, Angela; Cook, Linda S.; Le, Nhu D.
2014-01-01
Scope We re-evaluated previously reported associations between variants in pathways of one-carbon (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake. Methods and Results Odds ratios (OR) for 446 genetic variants were estimated among 13,410 OC cases and 22,635 controls and among 2,281 cases and 3,444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for DPYD variants rs11587873 (OR=0.92, P=6x10−5) and rs828054 (OR=1.06, P=1x10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT and TYMS, also interacted significantly with folate in a multi-variant analysis (corrected P=9.9x10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in one-carbon transfer, previously reported with OC, suggested lower risk at higher folate (Pinteraction=0.03-0.006). Conclusions Variation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP-byfolate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC. PMID:25066213
A comparison of genetic variants between proficient low- and high-risk sport participants.
Thomson, Cynthia J; Power, Rebecca J; Carlson, Scott R; Rupert, Jim L; Michel, Grégory
2015-01-01
Athletes participating in high-risk sports consistently report higher scores on sensation-seeking measures than do low-risk athletes or non-athletic controls. To determine whether genetic variants commonly associated with sensation seeking were over-represented in such athletes, proficient practitioners of high-risk (n = 141) and low-risk sports (n = 132) were compared for scores on sensation seeking and then genotyped at 33 polymorphic loci in 14 candidate genes. As expected, athletes participating in high-risk sports score higher on sensation seeking than did low-risk sport athletes (P < .01). Genotypes were associated with high-risk sport participation for two genes (stathmin, (P = .004) and brain-derived neurotrophic factor (P = .03)) as well as when demographically matched subsets of the sport cohorts were compared (P < .05); however, in all cases, associations did not survive correction for multiple testing.
Iron Age and Anglo-Saxon genomes from East England reveal British migration history.
Schiffels, Stephan; Haak, Wolfgang; Paajanen, Pirita; Llamas, Bastien; Popescu, Elizabeth; Loe, Louise; Clarke, Rachel; Lyons, Alice; Mortimer, Richard; Sayer, Duncan; Tyler-Smith, Chris; Cooper, Alan; Durbin, Richard
2016-01-19
British population history has been shaped by a series of immigrations, including the early Anglo-Saxon migrations after 400 CE. It remains an open question how these events affected the genetic composition of the current British population. Here, we present whole-genome sequences from 10 individuals excavated close to Cambridge in the East of England, ranging from the late Iron Age to the middle Anglo-Saxon period. By analysing shared rare variants with hundreds of modern samples from Britain and Europe, we estimate that on average the contemporary East English population derives 38% of its ancestry from Anglo-Saxon migrations. We gain further insight with a new method, rarecoal, which infers population history and identifies fine-scale genetic ancestry from rare variants. Using rarecoal we find that the Anglo-Saxon samples are closely related to modern Dutch and Danish populations, while the Iron Age samples share ancestors with multiple Northern European populations including Britain.
Jalaly, Niloofar Y; Moran, Robert A; Fargahi, Farshid; Khashab, Mouen A; Kamal, Ayesha; Lennon, Anne Marie; Walsh, Christi; Makary, Martin A; Whitcomb, David C; Yadav, Dhiraj; Cebotaru, Liudmila; Singh, Vikesh K
2017-08-01
We evaluated factors associated with pathogenic genetic variants in patients with idiopathic pancreatitis. Genetic testing (PRSS1, CFTR, SPINK1, and CTRC) was performed in all eligible patients with idiopathic pancreatitis between 2010 to 2015. Patients were classified into the following groups based on a review of medical records: (1) acute recurrent idiopathic pancreatitis (ARIP) with or without underlying chronic pancreatitis; (2) idiopathic chronic pancreatitis (ICP) without a history of ARP; (3) an unexplained first episode of acute pancreatitis (AP)<35 years of age; and (4) family history of pancreatitis. Logistic regression analysis was used to determine the factors associated with pathogenic genetic variants. Among 197 ARIP and/or ICP patients evaluated from 2010 to 2015, 134 underwent genetic testing. A total of 88 pathogenic genetic variants were found in 64 (47.8%) patients. Pathogenic genetic variants were identified in 58, 63, and 27% of patients with ARIP, an unexplained first episode of AP <35 years of age, and ICP without ARP, respectively. ARIP (OR: 18.12; 95% CI: 2.16-151.87; P=0.008) and an unexplained first episode of AP<35 years of age (OR: 2.46; 95% CI: 1.18-5.15; P=0.017), but not ICP, were independently associated with pathogenic genetic variants in the adjusted analysis. Pathogenic genetic variants are most likely to be identified in patients with ARIP and an unexplained first episode of AP<35 years of age. Genetic testing in these patient populations may delineate an etiology and prevent unnecessary diagnostic testing and procedures.
Cole, Shelley A; Voruganti, V Saroja; Cai, Guowen; Haack, Karin; Kent, Jack W; Blangero, John; Comuzzie, Anthony G; McPherson, John D; Gibbs, Richard A
2010-01-01
Background: Melanocortin-4-receptor (MC4R) haploinsufficiency is the most common form of monogenic obesity; however, the frequency of MC4R variants and their functional effects in general populations remain uncertain. Objective: The aim was to identify and characterize the effects of MC4R variants in Hispanic children. Design: MC4R was resequenced in 376 parents, and the identified single nucleotide polymorphisms (SNPs) were genotyped in 613 parents and 1016 children from the Viva la Familia cohort. Measured genotype analysis (MGA) tested associations between SNPs and phenotypes. Bayesian quantitative trait nucleotide (BQTN) analysis was used to infer the most likely functional polymorphisms influencing obesity-related traits. Results: Seven rare SNPs in coding and 18 SNPs in flanking regions of MC4R were identified. MGA showed suggestive associations between MC4R variants and body size, adiposity, glucose, insulin, leptin, ghrelin, energy expenditure, physical activity, and food intake. BQTN analysis identified SNP 1704 in a predicted micro-RNA target sequence in the downstream flanking region of MC4R as a strong, probable functional variant influencing total, sedentary, and moderate activities with posterior probabilities of 1.0. SNP 2132 was identified as a variant with a high probability (1.0) of exerting a functional effect on total energy expenditure and sleeping metabolic rate. SNP rs34114122 was selected as having likely functional effects on the appetite hormone ghrelin, with a posterior probability of 0.81. Conclusion: This comprehensive investigation provides strong evidence that MC4R genetic variants are likely to play a functional role in the regulation of weight, not only through energy intake but through energy expenditure. PMID:19889825
Generalized functional linear models for gene-based case-control association studies.
Fan, Ruzong; Wang, Yifan; Mills, James L; Carter, Tonia C; Lobach, Iryna; Wilson, Alexander F; Bailey-Wilson, Joan E; Weeks, Daniel E; Xiong, Momiao
2014-11-01
By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene region are disease related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease datasets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. © 2014 WILEY PERIODICALS, INC.
Generalized Functional Linear Models for Gene-based Case-Control Association Studies
Mills, James L.; Carter, Tonia C.; Lobach, Iryna; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Weeks, Daniel E.; Xiong, Momiao
2014-01-01
By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene are disease-related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease data sets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. PMID:25203683
Stone, Jennifer; Thompson, Deborah J.; dos-Santos-Silva, Isabel; Scott, Christopher; Tamimi, Rulla M.; Lindstrom, Sara; Kraft, Peter; Hazra, Aditi; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Hall, Per; Jensen, Matt; Cunningham, Julie; Olson, Janet E.; Purrington, Kristen; Couch, Fergus J.; Brown, Judith; Leyland, Jean; Warren, Ruth M. L.; Luben, Robert N.; Khaw, Kay-Tee; Smith, Paula; Wareham, Nicholas J.; Jud, Sebastian M.; Heusinger, Katharina; Beckmann, Matthias W.; Douglas, Julie A.; Shah, Kaanan P.; Chan, Heang-Ping; Helvie, Mark A.; Le Marchand, Loic; Kolonel, Laurence N.; Woolcott, Christy; Maskarinec, Gertraud; Haiman, Christopher; Giles, Graham G.; Baglietto, Laura; Krishnan, Kavitha; Southey, Melissa C.; Apicella, Carmel; Andrulis, Irene L.; Knight, Julia A.; Ursin, Giske; Grenaker Alnaes, Grethe I.; Kristensen, Vessela N.; Borresen-Dale, Anne-Lise; Gram, Inger Torhild; Bolla, Manjeet K.; Wang, Qin; Michailidou, Kyriaki; Dennis, Joe; Simard, Jacques; Paroah, Paul; Dunning, Alison M.; Easton, Douglas F.; Fasching, Peter A.; Pankratz, V. Shane; Hopper, John; Vachon, Celine M.
2015-01-01
Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute non-dense area adjusted for study, age and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1) and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all p <10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and non-dense areas, and between rs17356907 (NTN4) and adjusted absolute non-dense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiological pathways implicated in how mammographic density predicts breast cancer risk. PMID:25862352
Association of prostate cancer risk variants with clinicopathologic characteristics of the disease
Xu, Jianfeng; Isaacs, Sarah D.; Sun, Jielin; Li, Ge; Wiley, Kathleen E.; Zhu, Yi; Hsu, Fang-Chi; Wiklund, Fredrik; Turner, Aubrey R.; Adams, Tamara S.; Liu, Wennuan; Trock, Bruce J.; Partin, Alan W.; Chang, Baoli; Walsh, Patrick C.; Grönberg, Henrik; Isaacs, William; Zheng, Siqun
2009-01-01
Purpose Fifteen independent genetic variants have been implicated in prostate cancer risk by recent genome-wide association studies. However, their association with clinicopathologic features of prostate cancer is uncertain. Experimental Design We systematically evaluated these 15 variants in 1,563 prostate cancer patients undergoing radical prostatectomy, taking advantage of the uniform tumor stage and grade information available for each of these cases. Associations of these variants with aggressiveness, pathologic Gleason scores, pathologic stage, age at diagnosis, or serum PSA levels were tested. Results After adjusting for multiple testing, none of the SNPs was individually or cumulatively associated with aggressiveness or individual clinicopathologic variables of prostate cancer such as Gleason scores, pathologic stage, or age at diagnosis of prostate cancer. The reported risk allele (G) for SNP rs2735839 in the KLK3 gene at 19q13 was more frequent in less aggressive prostate cancer patients (0.89) than in more aggressive prostate cancer patients (0.86), nominal P = 0.03, or in controls (0.86), nominal P = 0.04. Considering that this allele was also significantly associated with higher serum PSA levels among controls (nominal P = 0.003), the observed trend of higher frequency of this risk allele between less and more aggressive prostate cancer, or between less aggressive and controls may be due to detection bias of PSA screening. Conclusions Prostate cancer risk variants recently discovered from genome-wide case-control association studies are not associated with clinicopathologic variables in this population. Case-case studies are urgently needed in order to discover genetic variants that predict tumor aggressiveness. PMID:18794092
Gu, Haiyong; Qiu, Wanshan; Wan, Ying; Ding, Guowen; Tang, Weifeng; Liu, Chao; Shi, Yijun; Chen, Yijang; Chen, Suocheng
2012-05-01
Growing evidence suggests that the checkpoint kinase 2 (CHEK2) signaling pathway occupies a central position in the signaling networks of DNA-damage signaling. Many functional and molecular epidemiological studies have evaluated the association between genetic variants of CHEK2 and various cancers. To evaluate the relationship between CHEK2 functional genetic variants and esophageal cancer risk and the risk of lymph node metastasis among a Chinese population. We genotyped CHEK2 rs738722, rs2236141 and rs2236142 single nucleotide polymorphisms (SNPs) using the matrix assisted laser desorption/ionization time-of-flight mass spectrometry assay in a case-controlled study, including 380 esophageal cancer cases and 380 healthy controls in a Chinese population. We found that none of the three polymorphisms achieved significant difference in their distributions between esophageal cancer cases and controls. Multiple logistic regression analyses revealed that esophageal cancer risk was not associated significantly with the variant genotypes of the three CHEK2 polymorphisms as compared with their wild-type genotypes. However, we found that functional variant rs738722 and rs2236142 in CHEK2 might contribute to susceptibility to lymph node metastasis. Our data did not support a significant association between CHEK2 SNPs and the risk of esophageal cancer. Functional variant CHEK2 rs738722 and rs2236142 might contribute to lymph node metastasis susceptibility. The CT allele of SNP rs738722 and the GC allele of SNP rs2236142 might be a protective factor of the risk for lymph node metastasis of esophageal cancer.
Johansson, A; Bergman, H; Corander, J; Waldman, I D; Karrani, N; Salo, B; Jern, P; Algars, M; Sandnabba, K; Santtila, P; Westberg, L
2012-03-01
We explored if the disposition to react with aggression while alcohol intoxicated was moderated by polymorphic variants of the oxytocin receptor gene (OXTR). Twelve OXTR polymorphisms were genotyped in 116 Finnish men [aged 18-30, M = 22.7, standard deviation (SD) = 2.4] who were randomly assigned to an alcohol condition in which they received an alcohol dose of 0.7 g pure ethanol/kg body weight or a placebo condition. Aggressive behavior was measured using a laboratory paradigm in which it was operationalized as the level of aversive noise administered to a fictive opponent. No main effects of the polymorphisms on aggressive behavior were found after controlling for multiple testing. The interactive effects between alcohol and two of the OXTR polymorphisms (rs4564970 and rs1488467) on aggressive behavior were nominally significant and remained significant for the rs4564970 when controlled for multiple tests. To the best of our knowledge, this is the first experimental study suggesting interactive effects of specific genetic variants and alcohol on aggressive behavior in humans. © 2011 The Authors. Genes, Brain and Behavior © 2011 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.
Multiple lupus-associated ITGAM variants alter Mac-1 functions on neutrophils.
Zhou, Yebin; Wu, Jianming; Kucik, Dennis F; White, Nathan B; Redden, David T; Szalai, Alexander J; Bullard, Daniel C; Edberg, Jeffrey C
2013-11-01
Multiple studies have demonstrated that single-nucleotide polymorphisms (SNPs) in the ITGAM locus (including the nonsynonymous SNPs rs1143679, rs1143678, and rs1143683) are associated with systemic lupus erythematosus (SLE). ITGAM encodes the protein CD11b, a subunit of the β2 integrin Mac-1. The purpose of this study was to determine the effects of ITGAM genetic variation on the biologic functions of neutrophil Mac-1. Neutrophils from ITGAM-genotyped and -sequenced healthy donors were isolated for functional studies. The phagocytic capacity of neutrophil ITGAM variants was probed with complement-coated erythrocytes, serum-treated zymosan, heat-treated zymosan, and IgG-coated erythrocytes. The adhesion capacity of ITGAM variants, in adhering to either purified intercellular adhesion molecule 1 or tumor necrosis factor α-stimulated endothelial cells, was assessed in a flow chamber. Expression levels of total CD11b and activation of CD11b were assessed by flow cytometry. Mac-1-mediated neutrophil phagocytosis, determined in cultures with 2 different complement-coated particles, was significantly reduced in individuals with nonsynonymous variant alleles of ITGAM. This reduction in phagocytosis was related to variation at either rs1143679 (in the β-propeller region) or rs1143678/rs1143683 (highly linked SNPs in the cytoplasmic/calf-1 regions). Phagocytosis mediated by Fcγ receptors was also significantly reduced in donors with variant ITGAM alleles. Similarly, firm adhesion of neutrophils was significantly reduced in individuals with variant ITGAM alleles. These functional alterations were not attributable to differences in total receptor expression or activation. The nonsynonymous ITGAM variants rs1143679 and rs1143678/rs113683 contribute to altered Mac-1 function on neutrophils. These results underscore the need to consider multiple nonsynonymous SNPs when assessing the functional consequences of ITGAM variation on immune cell processes and the risk of SLE. Copyright © 2013 by the American College of Rheumatology.
Klinkenberg-Ramirez, Stephanie; Neri, Pamela M; Volk, Lynn A; Samaha, Sara J; Newmark, Lisa P; Pollard, Stephanie; Varugheese, Matthew; Baxter, Samantha; Aronson, Samuel J; Rehm, Heidi L; Bates, David W
2016-01-01
Partners HealthCare Personalized Medicine developed GeneInsight Clinic (GIC), a tool designed to communicate updated variant information from laboratory geneticists to treating clinicians through automated alerts, categorized by level of variant interpretation change. The study aimed to evaluate feedback from the initial users of the GIC, including the advantages and challenges to receiving this variant information and using this technology at the point of care. Healthcare professionals from two clinics that ordered genetic testing for cardiomyopathy and related disorders were invited to participate in one-hour semi-structured interviews and/ or a one-hour focus group. Using a Grounded Theory approach, transcript concepts were coded and organized into themes. Two genetic counselors and two physicians from two treatment clinics participated in individual interviews. Focus group participants included one genetic counselor and four physicians. Analysis resulted in 8 major themes related to structuring and communicating variant knowledge, GIC's impact on the clinic, and suggestions for improvements. The interview analysis identified longitudinal patient care, family data, and growth in genetic testing content as potential challenges to optimization of the GIC infrastructure. Participants agreed that GIC implementation increased efficiency and effectiveness of the clinic through increased access to genetic variant information at the point of care. Development of information technology (IT) infrastructure to aid in the organization and management of genetic variant knowledge will be critical as the genetic field moves towards whole exome and whole genome sequencing. Findings from this study could be applied to future development of IT support for genetic variant knowledge management that would serve to improve clinicians' ability to manage and care for patients.
Ribosomal DNA Organization Before and After Magnification in Drosophila melanogaster
Bianciardi, Alessio; Boschi, Manuela; Swanson, Ellen E.; Belloni, Massimo; Robbins, Leonard G.
2012-01-01
In all eukaryotes, the ribosomal RNA genes are stably inherited redundant elements. In Drosophila melanogaster, the presence of a Ybb− chromosome in males, or the maternal presence of the Ribosomal exchange (Rex) element, induces magnification: a heritable increase of rDNA copy number. To date, several alternative classes of mechanisms have been proposed for magnification: in situ replication or extra-chromosomal replication, either of which might act on short or extended strings of rDNA units, or unequal sister chromatid exchange. To eliminate some of these hypotheses, none of which has been clearly proven, we examined molecular-variant composition and compared genetic maps of the rDNA in the bb2 mutant and in some magnified bb+ alleles. The genetic markers used are molecular-length variants of IGS sequences and of R1 and R2 mobile elements present in many 28S sequences. Direct comparison of PCR products does not reveal any particularly intensified electrophoretic bands in magnified alleles compared to the nonmagnified bb2 allele. Hence, the increase of rDNA copy number is diluted among multiple variants. We can therefore reject mechanisms of magnification based on multiple rounds of replication of short strings. Moreover, we find no changes of marker order when pre- and postmagnification maps are compared. Thus, we can further restrict the possible mechanisms to two: replication in situ of an extended string of rDNA units or unequal exchange between sister chromatids. PMID:22505623
Evolution, revolution and heresy in the genetics of infectious disease susceptibility
Hill, Adrian V. S.
2012-01-01
Infectious pathogens have long been recognized as potentially powerful agents impacting on the evolution of human genetic diversity. Analysis of large-scale case–control studies provides one of the most direct means of identifying human genetic variants that currently impact on susceptibility to particular infectious diseases. For over 50 years candidate gene studies have been used to identify loci for many major causes of human infectious mortality, including malaria, tuberculosis, human immunodeficiency virus/acquired immunodeficiency syndrome, bacterial pneumonia and hepatitis. But with the advent of genome-wide approaches, many new loci have been identified in diverse populations. Genome-wide linkage studies identified a few loci, but genome-wide association studies are proving more successful, and both exome and whole-genome sequencing now offer a revolutionary increase in power. Opinions differ on the extent to which the genetic component to common disease susceptibility is encoded by multiple high frequency or rare variants, and the heretical view that most infectious diseases might even be monogenic has been advocated recently. Review of findings to date suggests that the genetic architecture of infectious disease susceptibility may be importantly different from that of non-infectious diseases, and it is suggested that natural selection may be the driving force underlying this difference. PMID:22312051
The Genetics of Autism: Key Issues, Recent Findings and Clinical Implications
El-Fishawy, Paul; State, Matthew W.
2010-01-01
Autism spectrum disorders (ASD’S) are highly heritable. Consequently, gene discovery promises to help illuminate the pathophysiology of these syndromes, yielding important opportunities for the development of novel treatments and a more nuanced understanding of the natural history of these disorders. Although the underlying genetic architecture of ASD’s is not yet known, the literature demonstrates that it is not, writ large, a monogenic disorder with Mendelian inheritance, but rather a group of complex genetic syndromes with risk deriving from genetic variations in multiple genes. The widely accepted “Common Disease-Common Variant” hypothesis predicts that the risk alleles in ASD’s and other complex disorders will be common in the general population. However, recent evidence from gene discovery efforts in a wide range of diseases raises important questions regarding the overall applicability of the theory and the extent of its usefulness in explaining individual genetic liability. In contrast, considerable evidence points to the importance of rare alleles both with regard to their value in providing a foothold into the molecular mechanisms of ASD and their overall contribution to the population-wide risk. This chapter reviews the origins of the common versus rare variant debate, highlights recent findings in the field, and addresses the clinical implications of both common and rare variant discoveries. PMID:20159341
Tchetgen Tchetgen, Eric
2011-03-01
This article considers the detection and evaluation of genetic effects incorporating gene-environment interaction and independence. Whereas ordinary logistic regression cannot exploit the assumption of gene-environment independence, the proposed approach makes explicit use of the independence assumption to improve estimation efficiency. This method, which uses both cases and controls, fits a constrained retrospective regression in which the genetic variant plays the role of the response variable, and the disease indicator and the environmental exposure are the independent variables. The regression model constrains the association of the environmental exposure with the genetic variant among the controls to be null, thus explicitly encoding the gene-environment independence assumption, which yields substantial gain in accuracy in the evaluation of genetic effects. The proposed retrospective regression approach has several advantages. It is easy to implement with standard software, and it readily accounts for multiple environmental exposures of a polytomous or of a continuous nature, while easily incorporating extraneous covariates. Unlike the profile likelihood approach of Chatterjee and Carroll (Biometrika. 2005;92:399-418), the proposed method does not require a model for the association of a polytomous or continuous exposure with the disease outcome, and, therefore, it is agnostic to the functional form of such a model and completely robust to its possible misspecification.
Goswami, S; Yee, SW; Stocker, S; Mosley, JD; Kubo, M; Castro, R; Mefford, JA; Wen, C; Liang, X; Witte, J; Brett, C; Maeda, S; Simpson, MD; Hedderson, MM; Davis, RL; Roden, DM; Giacomini, KM; Savic, RM
2014-01-01
One-third of type 2 diabetes patients do not respond to metformin. Genetic variants in metformin transporters have been extensively studied as a likely contributor to this high failure rate. Here, we investigate, for the first time, the effect of genetic variants in transcription factors on metformin pharmacokinetics (PK) and response. Overall, 546 patients and healthy volunteers contributed their genome-wide, pharmacokinetic (235 subjects), and HbA1c data (440 patients) for this analysis. Five variants in specificity protein 1 (SP1), a transcription factor that modulates the expression of metformin transporters, were associated with changes in treatment HbA1c (P < 0.01) and metformin secretory clearance (P < 0.05). Population pharmacokinetic modeling further confirmed a 24% reduction in apparent clearance in homozygous carriers of one such variant, rs784888. Genetic variants in other transcription factors, peroxisome proliferator–activated receptor-α and hepatocyte nuclear factor 4-α, were significantly associated with HbA1c change only. Overall, our study highlights the importance of genetic variants in transcription factors as modulators of metformin PK and response. PMID:24853734
Genetic and epigenetic mechanisms of epilepsy: a review
Chen, Tian; Giri, Mohan; Xia, Zhenyi; Subedi, Yadu Nanda; Li, Yan
2017-01-01
Epilepsy is a common episodic neurological disorder or condition characterized by recurrent epileptic seizures, and genetics seems to play a key role in its etiology. Early linkage studies have localized multiple loci that may harbor susceptibility genes to epilepsy, and mutational analyses have detected a number of mutations involved in both ion channel and nonion channel genes in patients with idiopathic epilepsy. Genome-wide studies of epilepsy have found copy number variants at 2q24.2-q24.3, 7q11.22, 15q11.2-q13.3, and 16p13.11-p13.2, some of which disrupt multiple genes, such as NRXN1, AUTS2, NLGN1, CNTNAP2, GRIN2A, PRRT2, NIPA2, and BMP5, implicated for neurodevelopmental disorders, including intellectual disability and autism. Unfortunately, only a few common genetic variants have been associated with epilepsy. Recent exome-sequencing studies have found some genetic mutations, most of which are located in nonion channel genes such as the LGI1, PRRT2, EFHC1, PRICKLE, RBFOX1, and DEPDC5 and in probands with rare forms of familial epilepsy, and some of these genes are involved with the neurodevelopment. Since epigenetics plays a role in neuronal function from embryogenesis and early brain development to tissue-specific gene expression, epigenetic regulation may contribute to the genetic mechanism of neurodevelopment through which a gene and the environment interacting with each other affect the development of epilepsy. This review focused on the analytic tools used to identify epilepsy and then provided a summary of recent linkage and association findings, indicating the existence of novel genes on several chromosomes for further understanding of the biology of epilepsy. PMID:28761347
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.
Iarossi, Giancarlo; Bertelli, Matteo; Maltese, Paolo Enrico; Gusson, Elena; Marchini, Giorgio; Bruson, Alice; Benedetti, Sabrina; Volpetti, Sabrina; Catena, Gino; Buzzonetti, Luca; Ziccardi, Lucia
2017-01-01
Familial exudative vitreoretinopathy (FEVR) is a complex disorder characterized by incomplete development of the retinal vasculature. Here, we report the results obtained on the spectrum of genetic variations and correlated phenotypes found in a cohort of Italian FEVR patients. Eight probands (age range 7-19 years) were assessed by genetic analysis and comprehensive age-appropriate ophthalmic examination. Genetic testing investigated the genes most widely associated in literature with FEVR: FZD4 , LRP5 , TSPAN12 , and NDP . Clinical and genetic evaluations were extended to relatives of probands positive to genetic testing. Six out of eight probands (75%) showed a genetic variation probably related to the phenotype. We identified four novel genetic variants, one variant already described in association with Norrie disease and one previously described linked to autosomal dominant FEVR. Pedigree analysis of patients led to the classification of four autosomal dominant cases of FEVR (caused by FZD4 and TSPAN12 variants) and two X-linked FEVR probands ( NDP variants). None of the patients showed variants in the LRP5 gene. This study represents the largest cohort study in Italian FEVR patients. Our findings are in agreement with the previous literature confirming that FEVR is a clinically and genetically heterogeneous retinal disorder, even when it manifests in the same family.
Marchini, Giorgio; Volpetti, Sabrina; Catena, Gino
2017-01-01
Familial exudative vitreoretinopathy (FEVR) is a complex disorder characterized by incomplete development of the retinal vasculature. Here, we report the results obtained on the spectrum of genetic variations and correlated phenotypes found in a cohort of Italian FEVR patients. Eight probands (age range 7–19 years) were assessed by genetic analysis and comprehensive age-appropriate ophthalmic examination. Genetic testing investigated the genes most widely associated in literature with FEVR: FZD4, LRP5, TSPAN12, and NDP. Clinical and genetic evaluations were extended to relatives of probands positive to genetic testing. Six out of eight probands (75%) showed a genetic variation probably related to the phenotype. We identified four novel genetic variants, one variant already described in association with Norrie disease and one previously described linked to autosomal dominant FEVR. Pedigree analysis of patients led to the classification of four autosomal dominant cases of FEVR (caused by FZD4 and TSPAN12 variants) and two X-linked FEVR probands (NDP variants). None of the patients showed variants in the LRP5 gene. This study represents the largest cohort study in Italian FEVR patients. Our findings are in agreement with the previous literature confirming that FEVR is a clinically and genetically heterogeneous retinal disorder, even when it manifests in the same family. PMID:28758032
Iglesias, Adriana I; Mihaescu, Raluca; Ioannidis, John P A; Khoury, Muin J; Little, Julian; van Duijn, Cornelia M; Janssens, A Cecile J W
2014-05-01
Our main objective was to raise awareness of the areas that need improvements in the reporting of genetic risk prediction articles for future publications, based on the Genetic RIsk Prediction Studies (GRIPS) statement. We evaluated studies that developed or validated a prediction model based on multiple DNA variants, using empirical data, and were published in 2010. A data extraction form based on the 25 items of the GRIPS statement was created and piloted. Forty-two studies met our inclusion criteria. Overall, more than half of the evaluated items (34 of 62) were reported in at least 85% of included articles. Seventy-seven percentage of the articles were identified as genetic risk prediction studies through title assessment, but only 31% used the keywords recommended by GRIPS in the title or abstract. Seventy-four percentage mentioned which allele was the risk variant. Overall, only 10% of the articles reported all essential items needed to perform external validation of the risk model. Completeness of reporting in genetic risk prediction studies is adequate for general elements of study design but is suboptimal for several aspects that characterize genetic risk prediction studies such as description of the model construction. Improvements in the transparency of reporting of these aspects would facilitate the identification, replication, and application of genetic risk prediction models. Copyright © 2014 Elsevier Inc. All rights reserved.
Whole-Exome Sequencing in Familial Parkinson Disease
Farlow, Janice L.; Robak, Laurie A.; Hetrick, Kurt; Bowling, Kevin; Boerwinkle, Eric; Coban-Akdemir, Zeynep H.; Gambin, Tomasz; Gibbs, Richard A.; Gu, Shen; Jain, Preti; Jankovic, Joseph; Jhangiani, Shalini; Kaw, Kaveeta; Lai, Dongbing; Lin, Hai; Ling, Hua; Liu, Yunlong; Lupski, James R.; Muzny, Donna; Porter, Paula; Pugh, Elizabeth; White, Janson; Doheny, Kimberly; Myers, Richard M.; Shulman, Joshua M.; Foroud, Tatiana
2016-01-01
IMPORTANCE Parkinson disease (PD) is a progressive neurodegenerative disease for which susceptibility is linked to genetic and environmental risk factors. OBJECTIVE To identify genetic variants contributing to disease risk in familial PD. DESIGN, SETTING, AND PARTICIPANTS A 2-stage study design that included a discovery cohort of families with PD and a replication cohort of familial probands was used. In the discovery cohort, rare exonic variants that segregated in multiple affected individuals in a family and were predicted to be conserved or damaging were retained. Genes with retained variants were prioritized if expressed in the brain and located within PD-relevant pathways. Genes in which prioritized variants were observed in at least 4 families were selected as candidate genes for replication in the replication cohort. The setting was among individuals with familial PD enrolled from academic movement disorder specialty clinics across the United States. All participants had a family history of PD. MAIN OUTCOMES AND MEASURES Identification of genes containing rare, likely deleterious, genetic variants in individuals with familial PD using a 2-stage exome sequencing study design. RESULTS The 93 individuals from 32 families in the discovery cohort (49.5% [46 of 93] female) had a mean (SD) age at onset of 61.8 (10.0) years. The 49 individuals with familial PD in the replication cohort (32.6% [16 of 49] female) had a mean (SD) age at onset of 50.1 (15.7) years. Discovery cohort recruitment dates were 1999 to 2009, and replication cohort recruitment dates were 2003 to 2014. Data analysis dates were 2011 to 2015. Three genes containing a total of 13 rare and potentially damaging variants were prioritized in the discovery cohort. Two of these genes (TNK2 and TNR) also had rare variants that were predicted to be damaging in the replication cohort. All 9 variants identified in the 2 replicated genes in 12 families across the discovery and replication cohorts were confirmed via Sanger sequencing. CONCLUSIONS AND RELEVANCE TNK2 and TNR harbored rare, likely deleterious, variants in individuals having familial PD, with similar findings in an independent cohort. To our knowledge, these genes have not been previously associated with PD, although they have been linked to critical neuronal functions. Further studies are required to confirm a potential role for these genes in the pathogenesis of PD. PMID:26595808
Sun, Hokeun; Wang, Shuang
2014-08-15
Existing association methods for rare variants from sequencing data have focused on aggregating variants in a gene or a genetic region because of the fact that analysing individual rare variants is underpowered. However, these existing rare variant detection methods are not able to identify which rare variants in a gene or a genetic region of all variants are associated with the complex diseases or traits. Once phenotypic associations of a gene or a genetic region are identified, the natural next step in the association study with sequencing data is to locate the susceptible rare variants within the gene or the genetic region. In this article, we propose a power set-based statistical selection procedure that is able to identify the locations of the potentially susceptible rare variants within a disease-related gene or a genetic region. The selection performance of the proposed selection procedure was evaluated through simulation studies, where we demonstrated the feasibility and superior power over several comparable existing methods. In particular, the proposed method is able to handle the mixed effects when both risk and protective variants are present in a gene or a genetic region. The proposed selection procedure was also applied to the sequence data on the ANGPTL gene family from the Dallas Heart Study to identify potentially susceptible rare variants within the trait-related genes. An R package 'rvsel' can be downloaded from http://www.columbia.edu/∼sw2206/ and http://statsun.pusan.ac.kr. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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.
Harmonizing the interpretation of genetic variants across the world: the Malaysian experience.
Hassan, Nik Norliza Nik; Plazzer, John-Paul; Smith, Timothy D; Halim-Fikri, Hashim; Macrae, Finlay; Zubaidi, A A L; Zilfalil, Bin Alwi
2016-02-26
Databases for gene variants are very useful for sharing genetic data and to facilitate the understanding of the genetic basis of diseases. This report summarises the issues surrounding the development of the Malaysian Human Variome Project Country Node. The focus is on human germline variants. Somatic variants, mitochondrial variants and other types of genetic variation have corresponding databases which are not covered here, as they have specific issues that do not necessarily apply to germline variations. The ethical, legal, social issues, intellectual property, ownership of the data, information technology implementation, and efforts to improve the standards and systems used in data sharing are discussed. An overarching framework such as provided by the Human Variome Project to co-ordinate activities is invaluable. Country Nodes, such as MyHVP, enable human gene variation associated with human diseases to be collected, stored and shared by all disciplines (clinicians, molecular biologists, pathologists, bioinformaticians) for a consistent interpretation of genetic variants locally and across the world.
Tanisawa, Kumpei; Arai, Yasumichi; Hirose, Nobuyoshi; Shimokata, Hiroshi; Yamada, Yoshiji; Kawai, Hisashi; Kojima, Motonaga; Obuchi, Shuichi; Hirano, Hirohiko; Yoshida, Hideyo; Suzuki, Hiroyuki; Fujiwara, Yoshinori; Ihara, Kazushige; Sugaya, Maki; Arai, Tomio; Mori, Seijiro; Sawabe, Motoji; Sato, Noriko; Muramatsu, Masaaki; Higuchi, Mitsuru; Liu, Yao-Wen; Kong, Qing-Peng
2017-01-01
Abstract Life span is a complex trait regulated by multiple genetic and environmental factors; however, the genetic determinants of extreme longevity have been largely unknown. To identify the functional coding variants associated with extreme longevity, we performed an exome-wide association study (EWAS) on a Japanese population by using an Illumina HumanExome Beadchip and a focused replication study on a Chinese population. The EWAS on two independent Japanese cohorts consisting of 530 nonagenarians/centenarians demonstrated that the G allele of CLEC3B missense variant p.S106G was associated with extreme longevity at the exome-wide level of significance (p = 2.33×10–7, odds ratio [OR] = 1.50). The CLEC3B gene encodes tetranectin, a protein implicated in the mineralization process in osteogenesis as well as in the prognosis and metastasis of cancer. The replication study consisting of 448 Chinese nonagenarians/centenarians showed that the G allele of CLEC3B p.S106G was also associated with extreme longevity (p = .027, OR = 1.51), and the p value of this variant reached 1.87×10–8 in the meta-analysis of Japanese and Chinese populations. In conclusion, the present study identified the CLEC3B p.S106G as a novel longevity-associated variant, raising the novel hypothesis that tetranectin, encoded by CLEC3B, plays a role in human longevity and aging. PMID:27154906
Ferguson, Jane F; Allayee, Hooman; Gerszten, Robert E; Ideraabdullah, Folami; Kris-Etherton, Penny M; Ordovás, José M; Rimm, Eric B; Wang, Thomas J; Bennett, Brian J
2016-06-01
Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies investigating the relationship between genetic variants and diet in modulating cardiometabolic risk, as well as the effects of dietary components on multiple "omic" measures, including transcriptomics, metabolomics, proteomics, lipidomics, epigenetic modifications, and the microbiome. Here, we describe the current state of the field of nutrigenomics with respect to cardiometabolic disease research and outline a direction for the integration of multiple omics techniques in future nutrigenomic studies aimed at understanding mechanisms and developing new therapeutic options for cardiometabolic disease treatment and prevention. © 2016 American Heart Association, Inc.
KIF16B is a candidate gene for a novel autosomal-recessive intellectual disability syndrome.
Alsahli, Saud; Arold, Stefan T; Alfares, Ahmed; Alhaddad, Bader; Al Balwi, Mohammed; Kamsteeg, Erik-Jan; Al-Twaijri, Waleed; Alfadhel, Majid
2018-05-07
Intellectual disability (ID) and global developmental delay are closely related; the latter is reserved for children under the age of 5 years as it is challenging to reliably assess clinical severity in this population. ID is a common condition, with up to 1%-3% of the population being affected and leading to a huge social and economic impact. ID is attributed to genetic abnormalities most of the time; however, the exact role of genetic involvement in ID is yet to be determined. Whole exome sequencing (WES) has gained popularity in the workup for ID, and multiple studies have been published examining the diagnostic yield in identification of the disease-causing variant (16%-55%), with the genetic involvement increasing as intelligence quotient decreases. WES has also accelerated novel disease gene discovery in this field. We identified a novel biallelic variant in the KIF16B gene (NM_024704.4:c.3611T > G) in two brothers that may be the cause of their phenotype. © 2018 Wiley Periodicals, Inc.
The curation of genetic variants: difficulties and possible solutions.
Pandey, Kapil Raj; Maden, Narendra; Poudel, Barsha; Pradhananga, Sailendra; Sharma, Amit Kumar
2012-12-01
The curation of genetic variants from biomedical articles is required for various clinical and research purposes. Nowadays, establishment of variant databases that include overall information about variants is becoming quite popular. These databases have immense utility, serving as a user-friendly information storehouse of variants for information seekers. While manual curation is the gold standard method for curation of variants, it can turn out to be time-consuming on a large scale thus necessitating the need for automation. Curation of variants described in biomedical literature may not be straightforward mainly due to various nomenclature and expression issues. Though current trends in paper writing on variants is inclined to the standard nomenclature such that variants can easily be retrieved, we have a massive store of variants in the literature that are present as non-standard names and the online search engines that are predominantly used may not be capable of finding them. For effective curation of variants, knowledge about the overall process of curation, nature and types of difficulties in curation, and ways to tackle the difficulties during the task are crucial. Only by effective curation, can variants be correctly interpreted. This paper presents the process and difficulties of curation of genetic variants with possible solutions and suggestions from our work experience in the field including literature support. The paper also highlights aspects of interpretation of genetic variants and the importance of writing papers on variants following standard and retrievable methods. Copyright © 2012. Published by Elsevier Ltd.
The Curation of Genetic Variants: Difficulties and Possible Solutions
Pandey, Kapil Raj; Maden, Narendra; Poudel, Barsha; Pradhananga, Sailendra; Sharma, Amit Kumar
2012-01-01
The curation of genetic variants from biomedical articles is required for various clinical and research purposes. Nowadays, establishment of variant databases that include overall information about variants is becoming quite popular. These databases have immense utility, serving as a user-friendly information storehouse of variants for information seekers. While manual curation is the gold standard method for curation of variants, it can turn out to be time-consuming on a large scale thus necessitating the need for automation. Curation of variants described in biomedical literature may not be straightforward mainly due to various nomenclature and expression issues. Though current trends in paper writing on variants is inclined to the standard nomenclature such that variants can easily be retrieved, we have a massive store of variants in the literature that are present as non-standard names and the online search engines that are predominantly used may not be capable of finding them. For effective curation of variants, knowledge about the overall process of curation, nature and types of difficulties in curation, and ways to tackle the difficulties during the task are crucial. Only by effective curation, can variants be correctly interpreted. This paper presents the process and difficulties of curation of genetic variants with possible solutions and suggestions from our work experience in the field including literature support. The paper also highlights aspects of interpretation of genetic variants and the importance of writing papers on variants following standard and retrievable methods. PMID:23317699
The impact of rare variation on gene expression across tissues.
Li, Xin; Kim, Yungil; Tsang, Emily K; Davis, Joe R; Damani, Farhan N; Chiang, Colby; Hess, Gaelen T; Zappala, Zachary; Strober, Benjamin J; Scott, Alexandra J; Li, Amy; Ganna, Andrea; Bassik, Michael C; Merker, Jason D; Hall, Ira M; Battle, Alexis; Montgomery, Stephen B
2017-10-11
Rare genetic variants are abundant in humans and are expected to contribute to individual disease risk. While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants. Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles, but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues, but their effects across tissues are unknown. Here we identify gene expression outliers, or individuals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release. We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes.
NASA Astrophysics Data System (ADS)
von Beeren, Christoph; Stoeckle, Mark Y.; Xia, Joyce; Burke, Griffin; Kronauer, Daniel J. C.
2015-02-01
DNA barcoding promises to be a useful tool to identify pest species assuming adequate representation of genetic variants in a reference library. Here we examined mitochondrial DNA barcodes in a global urban pest, the American cockroach (Periplaneta americana). Our sampling effort generated 284 cockroach specimens, most from New York City, plus 15 additional U.S. states and six other countries, enabling the first large-scale survey of P. americana barcode variation. Periplaneta americana barcode sequences (n = 247, including 24 GenBank records) formed a monophyletic lineage separate from other Periplaneta species. We found three distinct P. americana haplogroups with relatively small differences within (<=0.6%) and larger differences among groups (2.4%-4.7%). This could be interpreted as indicative of multiple cryptic species. However, nuclear DNA sequences (n = 77 specimens) revealed extensive gene flow among mitochondrial haplogroups, confirming a single species. This unusual genetic pattern likely reflects multiple introductions from genetically divergent source populations, followed by interbreeding in the invasive range. Our findings highlight the need for comprehensive reference databases in DNA barcoding studies, especially when dealing with invasive populations that might be derived from multiple genetically distinct source populations.
Genetics and the environment converge to dysregulate N-glycosylation in multiple sclerosis
Mkhikian, Haik; Grigorian, Ani; Li, Carey F.; Chen, Hung-Lin; Newton, Barbara; Zhou, Raymond W.; Beeton, Christine; Torossian, Sevan; Tatarian, Gevork Grikor; Lee, Sung-Uk; Lau, Ken; Walker, Erin; Siminovitch, Katherine A.; Chandy, K. George; Yu, Zhaoxia; Dennis, James W.; Demetriou, Michael
2011-01-01
How environmental factors combine with genetic risk at the molecular level to promote complex trait diseases such as multiple sclerosis (MS) is largely unknown. In mice, N-glycan branching by the Golgi enzymes Mgat1 and/or Mgat5 prevents T cell hyperactivity, cytotoxic T-lymphocyte antigen 4 (CTLA-4) endocytosis, spontaneous inflammatory demyelination and neurodegeneration, the latter pathologies characteristic of MS. Here we show that MS risk modulators converge to alter N-glycosylation and/or CTLA-4 surface retention conditional on metabolism and vitamin D3, including genetic variants in interleukin-7 receptor-α (IL7RA*C), interleukin-2 receptor-α (IL2RA*T), MGAT1 (IVAVT−T) and CTLA-4 (Thr17Ala). Downregulation of Mgat1 by IL7RA*C and IL2RA*T is opposed by MGAT1 (IVAVT−T) and vitamin D3, optimizing branching and mitigating MS risk when combined with enhanced CTLA-4 N-glycosylation by CTLA-4 Thr17. Our data suggest a molecular mechanism in MS whereby multiple environmental and genetic inputs lead to dysregulation of a final common pathway, namely N-glycosylation. PMID:21629267
An ImmunoChip study of multiple sclerosis risk in African Americans
Isobe, Noriko; Madireddy, Lohith; Khankhanian, Pouya; Matsushita, Takuya; Caillier, Stacy J.; Moré, Jayaji M.; Gourraud, Pierre-Antoine; McCauley, Jacob L.; Beecham, Ashley H.; Piccio, Laura; Herbert, Joseph; Khan, Omar; Cohen, Jeffrey; Stone, Lael; Santaniello, Adam; Cree, Bruce A. C.; Onengut-Gumuscu, Suna; Rich, Stephen S.; Hauser, Stephen L.; Sawcer, Stephen
2015-01-01
The aims of this study were: (i) to determine to what degree multiple sclerosis-associated loci discovered in European populations also influence susceptibility in African Americans; (ii) to assess the extent to which the unique linkage disequilibrium patterns in African Americans can contribute to localizing the functionally relevant regions or genes; and (iii) to search for novel African American multiple sclerosis-associated loci. Using the ImmunoChip custom array we genotyped 803 African American cases with multiple sclerosis and 1516 African American control subjects at 130 135 autosomal single nucleotide polymorphisms. We conducted association analysis with rigorous adjustments for population stratification and admixture. Of the 110 non-major histocompatibility complex multiple sclerosis-associated variants identified in Europeans, 96 passed stringent quality control in our African American data set and of these, >70% (69) showed over-representation of the same allele amongst cases, including 21 with nominally significant evidence for association (one-tailed test P < 0.05). At a further eight loci we found nominally significant association with an alternate correlated risk-tagging single nucleotide polymorphism from the same region. Outside the regions known to be associated in Europeans, we found seven potentially associated novel candidate multiple sclerosis variants (P < 10−4), one of which (rs2702180) also showed nominally significant evidence for association (one-tailed test P = 0.034) in an independent second cohort of 620 African American cases and 1565 control subjects. However, none of these novel associations reached genome-wide significance (combined P = 6.3 × 10−5). Our data demonstrate substantial overlap between African American and European multiple sclerosis variants, indicating common genetic contributions to multiple sclerosis risk. PMID:25818868
An ImmunoChip study of multiple sclerosis risk in African Americans.
Isobe, Noriko; Madireddy, Lohith; Khankhanian, Pouya; Matsushita, Takuya; Caillier, Stacy J; Moré, Jayaji M; Gourraud, Pierre-Antoine; McCauley, Jacob L; Beecham, Ashley H; Piccio, Laura; Herbert, Joseph; Khan, Omar; Cohen, Jeffrey; Stone, Lael; Santaniello, Adam; Cree, Bruce A C; Onengut-Gumuscu, Suna; Rich, Stephen S; Hauser, Stephen L; Sawcer, Stephen; Oksenberg, Jorge R
2015-06-01
The aims of this study were: (i) to determine to what degree multiple sclerosis-associated loci discovered in European populations also influence susceptibility in African Americans; (ii) to assess the extent to which the unique linkage disequilibrium patterns in African Americans can contribute to localizing the functionally relevant regions or genes; and (iii) to search for novel African American multiple sclerosis-associated loci. Using the ImmunoChip custom array we genotyped 803 African American cases with multiple sclerosis and 1516 African American control subjects at 130 135 autosomal single nucleotide polymorphisms. We conducted association analysis with rigorous adjustments for population stratification and admixture. Of the 110 non-major histocompatibility complex multiple sclerosis-associated variants identified in Europeans, 96 passed stringent quality control in our African American data set and of these, >70% (69) showed over-representation of the same allele amongst cases, including 21 with nominally significant evidence for association (one-tailed test P < 0.05). At a further eight loci we found nominally significant association with an alternate correlated risk-tagging single nucleotide polymorphism from the same region. Outside the regions known to be associated in Europeans, we found seven potentially associated novel candidate multiple sclerosis variants (P < 10(-4)), one of which (rs2702180) also showed nominally significant evidence for association (one-tailed test P = 0.034) in an independent second cohort of 620 African American cases and 1565 control subjects. However, none of these novel associations reached genome-wide significance (combined P = 6.3 × 10(-5)). Our data demonstrate substantial overlap between African American and European multiple sclerosis variants, indicating common genetic contributions to multiple sclerosis risk. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Cheng, Timothy H T; Gorman, Maggie; Martin, Lynn; Barclay, Ella; Casey, Graham; Saunders, Brian; Thomas, Huw; Clark, Sue; Tomlinson, Ian
2015-02-01
The presence of multiple (5-100) colorectal adenomas suggests an inherited predisposition, but the genetic aetiology of this phenotype is undetermined if patients test negative for Mendelian polyposis syndromes such as familial adenomatous polyposis (FAP) and MUTYH-associated polyposis (MAP). We investigated whether 18 common colorectal cancer (CRC) predisposition single-nucleotide polymorphisms (SNPs) could help to explain some cases with multiple adenomas who phenocopied FAP or MAP, but had no pathogenic APC or MUTYH variant. No multiple adenoma case had an outlying number of CRC SNP risk alleles, but multiple adenoma patients did have a significantly higher number of risk alleles than population controls (P=5.7 × 10(-7)). The association was stronger in those with ≥10 adenomas. The CRC SNPs accounted for 4.3% of the variation in multiple adenoma risk, with three SNPs (rs6983267, rs10795668, rs3802842) explaining 3.0% of the variation. In FAP patients, the CRC risk score did not differ significantly from the controls, as we expected given the overwhelming effect of pathogenic germline APC variants on the phenotype of these cases. More unexpectedly, we found no evidence that the CRC SNPs act as modifier genes for the number of colorectal adenomas in FAP patients. In conclusion, common colorectal tumour risk alleles contribute to the development of multiple adenomas in patients without pathogenic germline APC or MUTYH variants. This phenotype may have 'polygenic' or monogenic origins. The risk of CRC in relatives of multiple adenoma cases is probably much lower for cases with polygenic disease, and this should be taken into account when counselling such patients.
Changes in classification of genetic variants in BRCA1 and BRCA2.
Kast, Karin; Wimberger, Pauline; Arnold, Norbert
2018-02-01
Classification of variants of unknown significance (VUS) in the breast cancer genes BRCA1 and BRCA2 changes with accumulating evidence for clinical relevance. In most cases down-staging towards neutral variants without clinical significance is possible. We searched the database of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) for changes in classification of genetic variants as an update to our earlier publication on genetic variants in the Centre of Dresden. Changes between 2015 and 2017 were recorded. In the group of variants of unclassified significance (VUS, Class 3, uncertain), only changes of classification towards neutral genetic variants were noted. In BRCA1, 25% of the Class 3 variants (n = 2/8) changed to Class 2 (likely benign) and Class 1 (benign). In BRCA2, in 50% of the Class 3 variants (n = 16/32), a change to Class 2 (n = 10/16) or Class 1 (n = 6/16) was observed. No change in classification was noted in Class 4 (likely pathogenic) and Class 5 (pathogenic) genetic variants in both genes. No up-staging from Class 1, Class 2 or Class 3 to more clinical significance was observed. All variants with a change in classification in our cohort were down-staged towards no clinical significance by a panel of experts of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC). Prevention in families with Class 3 variants should be based on pedigree based risks and should not be guided by the presence of a VUS.
Dauber, Andrew; Golzio, Christelle; Guenot, Cécile; Jodelka, Francine M.; Kibaek, Maria; Kjaergaard, Susanne; Leheup, Bruno; Martinet, Danielle; Nowaczyk, Malgorzata J.M.; Rosenfeld, Jill A.; Zeesman, Susan; Zunich, Janice; Beckmann, Jacques S.; Hirschhorn, Joel N.; Hastings, Michelle L.; Jacquemont, Sebastien; Katsanis, Nicholas
2013-01-01
Copy-number variants (CNVs) represent a significant interpretative challenge, given that each CNV typically affects the dosage of multiple genes. Here we report on five individuals with coloboma, microcephaly, developmental delay, short stature, and craniofacial, cardiac, and renal defects who harbor overlapping microdeletions on 8q24.3. Fine mapping localized a commonly deleted 78 kb region that contains three genes: SCRIB, NRBP2, and PUF60. In vivo dissection of the CNV showed discrete contributions of the planar cell polarity effector SCRIB and the splicing factor PUF60 to the syndromic phenotype, and the combinatorial suppression of both genes exacerbated some, but not all, phenotypic components. Consistent with these findings, we identified an individual with microcephaly, short stature, intellectual disability, and heart defects with a de novo c.505C>T variant leading to a p.His169Tyr change in PUF60. Functional testing of this allele in vivo and in vitro showed that the mutation perturbs the relative dosage of two PUF60 isoforms and, subsequently, the splicing efficiency of downstream PUF60 targets. These data inform the functions of two genes not associated previously with human genetic disease and demonstrate how CNVs can exhibit complex genetic architecture, with the phenotype being the amalgam of both discrete dosage dysfunction of single transcripts and also of binary genetic interactions. PMID:24140112
Zhang, Ge; Karns, Rebekah; Sun, Guangyun; Indugula, Subba Rao; Cheng, Hong; Havas-Augustin, Dubravka; Novokmet, Natalija; Durakovic, Zijad; Missoni, Sasa; Chakraborty, Ranajit; Rudan, Pavao; Deka, Ranjan
2012-01-01
Genome-wide association studies (GWAS) have identified many common variants associated with complex traits in human populations. Thus far, most reported variants have relatively small effects and explain only a small proportion of phenotypic variance, leading to the issues of 'missing' heritability and its explanation. Using height as an example, we examined two possible sources of missing heritability: first, variants with smaller effects whose associations with height failed to reach genome-wide significance and second, allelic heterogeneity due to the effects of multiple variants at a single locus. Using a novel analytical approach we examined allelic heterogeneity of height-associated loci selected from SNPs of different significance levels based on the summary data of the GIANT (stage 1) studies. In a sample of 1,304 individuals collected from an island population of the Adriatic coast of Croatia, we assessed the extent of height variance explained by incorporating the effects of less significant height loci and multiple effective SNPs at the same loci. Our results indicate that approximately half of the 118 loci that achieved stringent genome-wide significance (p-value<5×10(-8)) showed evidence of allelic heterogeneity. Additionally, including less significant loci (i.e., p-value<5×10(-4)) and accounting for effects of allelic heterogeneity substantially improved the variance explained in height.
Schmidt, S; Pericak-Vance, M A; Sawcer, S; Barcellos, L F; Hart, J; Sims, J; Prokop, A M; van der Walt, J; DeLoa, C; Lincoln, R R; Oksenberg, J R; Compston, A; Hauser, S L; Haines, J L; Gregory, S G
2006-07-01
Discrepant findings have been reported regarding an association of the apolipoprotein E (APOE) gene with the clinical course of multiple sclerosis (MS). To resolve these discrepancies, we examined common sequence variation in six candidate genes residing in a 380-kb genomic region surrounding and including the APOE locus for an association with MS severity. We genotyped at least three polymorphisms in each of six candidate genes in 1,540 Caucasian MS families (729 single-case and multiple-case families from the United States, 811 single-case families from the UK). By applying the quantitative transmission/disequilibrium test to a recently proposed MS severity score, the only statistically significant (P=0.003) association with MS severity was found for an intronic variant in the Herpes Virus Entry Mediator-B Gene PVRL2. Additional genotyping extended the association to a 16.6 kb block spanning intron 1 to intron 2 of the gene. Sequencing of PVRL2 failed to identify variants with an obvious functional role. In conclusion, the analysis of a very large data set suggests that genetic polymorphisms in PVRL2 may influence MS severity and supports the possibility that viral factors may contribute to the clinical course of MS, consistent with previous reports.
Montesanto, Alberto; Geracitano, Silvana; Garasto, Sabrina; Fusco, Sergio; Lattanzio, Fabrizia; Passarino, Giuseppe; Corsonello, Andrea
2016-01-01
Before the last decade, attempts to identify the genetic factors involved in the susceptibility to age-related complex diseases such as cardiovascular disease, diabetes and cancer had very limited success. Recently, two important advancements have provided new opportunities to improve our knowledge in this field. Firstly, it has emerged the concept of studying the molecular mechanisms underlying the age related decline of the organism (such as cellular senescence), rather than the genetics of single disorders. In addition, advances in DNA technology have uncovered an incredible number of common susceptibility variants for several complex traits. Despite these progresses, the translation of these discoveries into clinical practice has been very difficult. To date, several attempts in translating genomics to medicine are being carried out to look for the best way by which genomic discoveries may improve our understanding of fundamental issues in the prediction and prevention of some complex diseases. The successful strategy seems to be testing simultaneously multiple susceptibility variants in combination with traditional risk factors. In fact, such approach showed that genetic factors substantially improve the prediction of complex diseases especially for coronary heart disease and prostate cancer, making possible appropriate behavioural and medical interventions. In the future, the identification of new genetic variants and their inclusion into current risk profile models will probably improve the discrimination power of these models for other complex diseases such as type 2 diabetes mellitus and breast cancer. On the other hand, for traits with low heritability, this improvement will probably be negligible, and this will urge further researches on the role played by traditional and newly discovered non-genetic risk factors.
Anand, Sonia S; Xie, Changchun; Paré, Guillaume; Montpetit, Alexandre; Rangarajan, Sumathy; McQueen, Matthew J; Cordell, Heather J; Keavney, Bernard; Yusuf, Salim; Hudson, Thomas J; Engert, James C
2009-02-01
Myocardial infarction (MI) is a leading cause of death globally, but specific genetic variants that influence MI and MI risk factors have not been assessed on a global basis. We included 8795 individuals of European, South Asian, Arab, Iranian, and Nepalese origin from the INTERHEART case-control study that genotyped 1536 single-nucleotide polymorphisms (SNPs) from 103 genes. One hundred and two SNPs were nominally associated with MI, but the statistical significance did not remain after adjustment for multiple testing. A subset of 940 SNPs from 69 genes were tested against MI risk factors. One hundred and sixty-three SNPs were nominally associated with a MI risk factor and 13 remained significant after adjusting for multiple testing. Of these 13, 11 were associated with apolipoprotein (Apo) B/A1 levels: 8 SNPs from 3 genes were associated with Apo B, and 3 cholesteryl ester transfer protein SNPs were associated with Apo A1. Seven of 8 of the SNPs associated with Apo B levels were nominally associated with MI (P<0.05), whereas none of the 3 cholesteryl ester transfer protein SNPs were associated with MI (P> or =0.17). Of the 3 SNPs most significantly associated with MI, rs7412, which defines the Apo E2 isoform, was associated with both a lower Apo B/A1 ratio (P=1.0x10(-7)) and lower MI risk (P=0.0004). Two low-density lipoprotein receptor variants, 1 intronic (rs6511720) and 1 in the 3' untranslated region (rs1433099) were both associated with a lower Apo B/A1 ratio (P<1.0x10(-5)) and a lower risk of MI (P=0.004 and P=0.003, respectively). Thirteen common SNPs were associated with MI risk factors. Importantly, SNPs associated with Apo B levels were associated with MI, whereas SNPs associated with Apo A1 levels were not. The Apo E isoform, and 2 common low-density lipoprotein receptor variants (rs1433099 and rs6511720) influence MI risk in this multiethnic sample.
Boes, Eva; Coassin, Stefan; Kollerits, Barbara; Heid, Iris M.; Kronenberg, Florian
2009-01-01
High-density lipoprotein (HDL) particles exhibit multiple antiatherogenic effects. They are key players in the reverse cholesterol transport which shuttles cholesterol from peripheral cells (e.g. macrophages) to the liver or other tissues. This complex process is thought to represent the basis for the antiatherogenic properties of HDL particles. The amount of cholesterol transported in HDL particles is measured as HDL cholesterol (HDLC) and is inversely correlated with the risk for coronary artery disease: an increase of 1 mg/dL of HDLC levels is associated with a 2% and 3% decrease of the risk for coronary artery disease in men and women, respectively. Genetically determined conditions with high HDLC levels (e.g. familial hyperalphalipoproteinemia) often coexist with longevity, and higher HDLC levels were found among healthy elderly individuals. HDLC levels are under considerable genetic control with heritability estimates of up to 80%. The identification and characterization of genetic variants associated with HDLC concentrations can provide new insights into the background of longevity. This review provides an extended overview on the current genetic-epidemiological evidence from association studies on genes involved in HDLC metabolism. It provides a path through the jungle of association studies which are sometimes confusing due to the varying and sometimes erroneous names of genetic variants, positions and directions of associations. Furthermore, it reviews the recent findings from genome-wide association studies which have identified new genes influencing HDLC levels. The yet identified genes together explain only a small amount of less than 10% of the HDLC variance, which leaves an enormous room for further yet to be identified genetic variants. This might be accomplished by large population-based genome-wide meta-analyses and by deep-sequencing approaches on the identified genes. The resulting findings will probably result in a re-drawing and extension of the involved metabolic pathways of HDLC metabolism. PMID:19041386
Causal Genetic Variation Underlying Metabolome Differences.
Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A
2017-08-01
An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.
Skorve, Espen; Vassilakopoulou, Polyxeni; Aanestad, Margunn; Grünfeld, Thomas
2017-01-01
This paper draws from the literature on collective action and the governance of the commons to address the governance of genetic data on variants of specific genes. Specifically, the data arrangements under study relate to the BRCA genes (BRCA1 and BRCA2) which are linked to breast and ovarian cancer. These data are stored in global genetic data repositories and accessed by researchers and clinicians, from both public and private institutions. The current BRCA data arrangements are fragmented and politicized as there are multiple tensions around data ownership and sharing. Three key principles are proposed for forming and evaluating data governance arrangements in the field. These principles are: equity, efficiency and sustainability.
Characterizing complex structural variation in germline and somatic genomes
Quinlan, Aaron R.; Hall, Ira M.
2011-01-01
Genome structural variation (SV) is a major source of genetic diversity in mammals and a hallmark of cancer. While SV is typically defined by its canonical forms – duplication, deletion, insertion, inversion and translocation – recent breakpoint mapping studies have revealed a surprising number of “complex” variants that evade simple classification. Complex SVs are defined by clustered breakpoints that arose through a single mutation but cannot be explained by one simple end-joining or recombination event. Some complex variants exhibit profoundly complicated rearrangements between distinct loci from multiple chromosomes, while others involve more subtle alterations at a single locus. These diverse and unpredictable features present a challenge for SV mapping experiments. Here, we review current knowledge of complex SV in mammals, and outline techniques for identifying and characterizing complex variants using next-generation DNA sequencing. PMID:22094265
Pereira, Tiago V; Mingroni-Netto, Regina C
2011-06-06
The generalized odds ratio (GOR) was recently suggested as a genetic model-free measure for association studies. However, its properties were not extensively investigated. We used Monte Carlo simulations to investigate type-I error rates, power and bias in both effect size and between-study variance estimates of meta-analyses using the GOR as a summary effect, and compared these results to those obtained by usual approaches of model specification. We further applied the GOR in a real meta-analysis of three genome-wide association studies in Alzheimer's disease. For bi-allelic polymorphisms, the GOR performs virtually identical to a standard multiplicative model of analysis (e.g. per-allele odds ratio) for variants acting multiplicatively, but augments slightly the power to detect variants with a dominant mode of action, while reducing the probability to detect recessive variants. Although there were differences among the GOR and usual approaches in terms of bias and type-I error rates, both simulation- and real data-based results provided little indication that these differences will be substantial in practice for meta-analyses involving bi-allelic polymorphisms. However, the use of the GOR may be slightly more powerful for the synthesis of data from tri-allelic variants, particularly when susceptibility alleles are less common in the populations (≤10%). This gain in power may depend on knowledge of the direction of the effects. For the synthesis of data from bi-allelic variants, the GOR may be regarded as a multiplicative-like model of analysis. The use of the GOR may be slightly more powerful in the tri-allelic case, particularly when susceptibility alleles are less common in the populations.
Marioni, Riccardo E; Deary, Ian J; Murray, Gordon D; Lowe, Gordon D O; Rafnsson, Snorri B; Strachan, Mark W J; Luciano, Michelle; Houlihan, Lorna M; Gow, Alan J; Harris, Sarah E; Stewart, Marlene C; Rumley, Ann; Fowkes, F Gerry R; Price, Jackie F
2010-01-01
It is unknown whether the relationship between raised inflammatory biomarker levels and late-life cognitive ability is causal. We explored this issue by testing the association between genetic regulators of plasma C-reactive protein (CRP) and cognition. Data were analysed from four cohorts based in central Scotland (Total N = 4,782). Associations were tested between variants in the CRP gene and both plasma CRP levels and a battery of neuropsychological tests, including a vocabulary-based estimate of peak prior cognitive ability and a general (summary) cognitive factor score, or 'g'. CRP levels were associated with a number of variants in the CRP gene (SNPs), including rs1205, rs1130864, rs1800947, and rs1417938 (P range 4.2e-06 to 0.041). Higher CRP levels were also associated with vocabulary-adjusted cognitive ability, used here to estimate lifetime cognitive change (P range 1.7e-04 to 0.038). After correction for multiple testing and adjustment for age and sex, no statistically significant associations were found between the SNPs and cognition. CRP is unlikely to be a causal determinant of late-life cognitive ability.
Cooper-Knock, Johnathan; Robins, Henry; Niedermoser, Isabell; Wyles, Matthew; Heath, Paul R; Higginbottom, Adrian; Walsh, Theresa; Kazoka, Mbombe; Ince, Paul G; Hautbergue, Guillaume M; McDermott, Christopher J; Kirby, Janine; Shaw, Pamela J
2017-01-01
Amyotrophic lateral sclerosis (ALS) is underpinned by an oligogenic rare variant architecture. Identified genetic variants of ALS include RNA-binding proteins containing prion-like domains (PrLDs). We hypothesized that screening genes encoding additional similar proteins will yield novel genetic causes of ALS. The most common genetic variant of ALS patients is a G4C2-repeat expansion within C9ORF72 . We have shown that G4C2-repeat RNA sequesters RNA-binding proteins. A logical consequence of this is that loss-of-function mutations in G4C2-binding partners might contribute to ALS pathogenesis independently of and/or synergistically with C9ORF72 expansions. Targeted sequencing of genomic DNA encoding either RNA-binding proteins or known ALS genes ( n = 274 genes) was performed in ALS patients to identify rare deleterious genetic variants and explore genotype-phenotype relationships. Genomic DNA was extracted from 103 ALS patients including 42 familial ALS patients and 61 young-onset (average age of onset 41 years) sporadic ALS patients; patients were chosen to maximize the probability of identifying genetic causes of ALS. Thirteen patients carried a G4C2-repeat expansion of C9ORF72 . We identified 42 patients with rare deleterious variants; 6 patients carried more than one variant. Twelve mutations were discovered in known ALS genes which served as a validation of our strategy. Rare deleterious variants in RNA-binding proteins were significantly enriched in ALS patients compared to control frequencies ( p = 5.31E-18). Nineteen patients featured at least one variant in a RNA-binding protein containing a PrLD. The number of variants per patient correlated with rate of disease progression ( t -test, p = 0.033). We identified eighteen patients with a single variant in a G4C2-repeat binding protein. Patients with a G4C2-binding protein variant in combination with a C9ORF72 expansion had a significantly faster disease course ( t -test, p = 0.025). Our data are consistent with an oligogenic model of ALS. We provide evidence for a number of entirely novel genetic variants of ALS caused by mutations in RNA-binding proteins. Moreover we show that these mutations act synergistically with each other and with C9ORF72 expansions to modify the clinical phenotype of ALS. A key finding is that this synergy is present only between functionally interacting variants. This work has significant implications for ALS therapy development.
Anderson, Heidi; Davison, Stephen; Hughes, Angela M.; Bouirmane, Julia; Lindqvist, Johan; Lytle, Katherine M.; Ganesan, Balasubramanian; Ottka, Claudia; Ruotanen, Päivi; Forman, Oliver P.; Fretwell, Neale; Cole, Cynthia A.; Lohi, Hannes
2018-01-01
Knowledge on the genetic epidemiology of disorders in the dog population has implications for both veterinary medicine and sustainable breeding. Limited data on frequencies of genetic disease variants across breeds exists, and the disease heritage of mixed breed dogs remains poorly explored to date. Advances in genetic screening technologies now enable comprehensive investigations of the canine disease heritage, and generate health-related big data that can be turned into action. We pursued population screening of genetic variants implicated in Mendelian disorders in the largest canine study sample examined to date by examining over 83,000 mixed breed and 18,000 purebred dogs representing 330 breeds for 152 known variants using a custom-designed beadchip microarray. We further announce the creation of MyBreedData (www.mybreeddata.com), an online updated inherited disorder prevalence resource with its foundation in the generated data. We identified the most prevalent, and rare, disease susceptibility variants across the general dog population while providing the first extensive snapshot of the mixed breed disease heritage. Approximately two in five dogs carried at least one copy of a tested disease variant. Most disease variants are shared by both mixed breeds and purebreds, while breed- or line-specificity of others is strongly suggested. Mixed breed dogs were more likely to carry a common recessive disease, whereas purebreds were more likely to be genetically affected with one, providing DNA-based evidence for hybrid vigor. We discovered genetic presence of 22 disease variants in at least one additional breed in which they were previously undescribed. Some mutations likely manifest similarly independently of breed background; however, we emphasize the need for follow up investigations in each case and provide a suggested validation protocol for broader consideration. In conclusion, our study provides unique insight into genetic epidemiology of canine disease risk variants, and their relevance for veterinary medicine, breeding programs and animal welfare. PMID:29708978
Donner, Jonas; Anderson, Heidi; Davison, Stephen; Hughes, Angela M; Bouirmane, Julia; Lindqvist, Johan; Lytle, Katherine M; Ganesan, Balasubramanian; Ottka, Claudia; Ruotanen, Päivi; Kaukonen, Maria; Forman, Oliver P; Fretwell, Neale; Cole, Cynthia A; Lohi, Hannes
2018-04-01
Knowledge on the genetic epidemiology of disorders in the dog population has implications for both veterinary medicine and sustainable breeding. Limited data on frequencies of genetic disease variants across breeds exists, and the disease heritage of mixed breed dogs remains poorly explored to date. Advances in genetic screening technologies now enable comprehensive investigations of the canine disease heritage, and generate health-related big data that can be turned into action. We pursued population screening of genetic variants implicated in Mendelian disorders in the largest canine study sample examined to date by examining over 83,000 mixed breed and 18,000 purebred dogs representing 330 breeds for 152 known variants using a custom-designed beadchip microarray. We further announce the creation of MyBreedData (www.mybreeddata.com), an online updated inherited disorder prevalence resource with its foundation in the generated data. We identified the most prevalent, and rare, disease susceptibility variants across the general dog population while providing the first extensive snapshot of the mixed breed disease heritage. Approximately two in five dogs carried at least one copy of a tested disease variant. Most disease variants are shared by both mixed breeds and purebreds, while breed- or line-specificity of others is strongly suggested. Mixed breed dogs were more likely to carry a common recessive disease, whereas purebreds were more likely to be genetically affected with one, providing DNA-based evidence for hybrid vigor. We discovered genetic presence of 22 disease variants in at least one additional breed in which they were previously undescribed. Some mutations likely manifest similarly independently of breed background; however, we emphasize the need for follow up investigations in each case and provide a suggested validation protocol for broader consideration. In conclusion, our study provides unique insight into genetic epidemiology of canine disease risk variants, and their relevance for veterinary medicine, breeding programs and animal welfare.
Sanjak, Jaleal S.; Long, Anthony D.; Thornton, Kevin R.
2017-01-01
The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. PMID:28103232
USDA-ARS?s Scientific Manuscript database
Scope: Tissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated i...
Genetic polymorphisms and the risk of stroke after cardiac surgery.
Grocott, Hilary P; White, William D; Morris, Richard W; Podgoreanu, Mihai V; Mathew, Joseph P; Nielsen, Dahlia M; Schwinn, Debra A; Newman, Mark F
2005-09-01
Stroke represents a significant cause of morbidity and mortality after cardiac surgery. Although the risk of stroke varies according to both patient and procedural factors, the impact of genetic variants on stroke risk is not well understood. Therefore, we tested the hypothesis that specific genetic polymorphisms are associated with an increased risk of stroke after cardiac surgery. Patients undergoing cardiac surgery utilizing cardiopulmonary bypass surgery were studied. DNA was isolated from preoperative blood and analyzed for 26 different single-nucleotide polymorphisms. Multivariable logistic regression modeling was used to determine the association of clinical and genetic characteristics with stroke. Permutation analysis was used to adjust for multiple comparisons inherent in genetic association studies. A total of 1635 patients experiencing 28 strokes (1.7%) were included in the final genetic model. The combination of the 2 minor alleles of C-reactive protein (CRP; 3'UTR 1846C/T) and interleukin-6 (IL-6; -174G/C) polymorphisms, occurring in 583 (35.7%) patients, was significantly associated with stroke (odds ratio, 3.3; 95% CI, 1.4 to 8.1; P=0.0023). In a multivariable logistic model adjusting for age, the CRP and IL-6 single-nucleotide polymorphism combination remained significantly associated with stroke (P=0.0020). We demonstrate that common genetic variants of CRP (3'UTR 1846C/T) and IL-6 (-174G/C) are significantly associated with the risk of stroke after cardiac surgery, suggesting a pivotal role of inflammation in post-cardiac surgery stroke.
Webb, Bryn D.; Metikala, Sanjeeva; Wheeler, Patricia G.; Sherpa, Mingma D.; Houten, Sander M.; Horb, Marko E.; Schadt, Eric E.
2017-01-01
A heterozygous nonsense variant was identified in dapper, antagonist of beta-catenin, 1 (DACT1) via whole-exome sequencing in family members with imperforate anus, structural renal abnormalities, genitourinary anomalies, and/or ear anomalies. The DACT1 c.1256G>A;p.Trp419* variant segregated appropriately in the family consistent with an autosomal dominant mode of inheritance. DACT1 is a member of the Wnt-signaling pathway, and mice homozygous for null alleles display multiple congenital anomalies including absent anus with blind-ending colon and genitourinary malformations. To investigate the DACT1 c.1256G>A variant, HEK293 cells were transfected with mutant DACT1 cDNA plasmid, and immunoblotting revealed stability of the DACT1 p.Trp419* protein. Overexpression of DACT1 c.1256G>A mRNA in Xenopus embryos revealed a specific gastrointestinal phenotype of enlargement of the proctodeum. Together, these findings suggest that the DACT1 c.1256G>A nonsense variant is causative of a specific genetic syndrome with features overlapping Townes–Brocks syndrome. PMID:28054444
Webb, Bryn D; Metikala, Sanjeeva; Wheeler, Patricia G; Sherpa, Mingma D; Houten, Sander M; Horb, Marko E; Schadt, Eric E
2017-04-01
A heterozygous nonsense variant was identified in dapper, antagonist of beta-catenin, 1 (DACT1) via whole-exome sequencing in family members with imperforate anus, structural renal abnormalities, genitourinary anomalies, and/or ear anomalies. The DACT1 c.1256G>A;p.Trp419 * variant segregated appropriately in the family consistent with an autosomal dominant mode of inheritance. DACT1 is a member of the Wnt-signaling pathway, and mice homozygous for null alleles display multiple congenital anomalies including absent anus with blind-ending colon and genitourinary malformations. To investigate the DACT1 c.1256G>A variant, HEK293 cells were transfected with mutant DACT1 cDNA plasmid, and immunoblotting revealed stability of the DACT1 p.Trp419 * protein. Overexpression of DACT1 c.1256G>A mRNA in Xenopus embryos revealed a specific gastrointestinal phenotype of enlargement of the proctodeum. Together, these findings suggest that the DACT1 c.1256G>A nonsense variant is causative of a specific genetic syndrome with features overlapping Townes-Brocks syndrome. © 2017 WILEY PERIODICALS, INC.
Wu, X; Offenbacher, S; Lόpez, N J; Chen, D; Wang, H-Y; Rogus, J; Zhou, J; Beck, J; Jiang, S; Bao, X; Wilkins, L; Doucette-Stamm, L; Kornman, K
2015-01-01
Background and Objective Genetic markers associated with disease are often non-functional and generally tag one or more functional “causative” variants in linkage disequilibrium. Markers may not show tight linkage to the causative variants across multiple ethnicities due to evolutionary divergence, and therefore may not be informative across different population groups. Validated markers of disease suggest causative variants exist in the gene and, if the causative variants can be identified, it is reasonable to hypothesize that such variants will be informative across diverse populations. The aim of this study was to test that hypothesis using functional Interleukin-1 (IL-1) gene variations across multiple ethnic populations to replace the non-functional markers originally associated with chronic adult periodontitis in Caucasians. Material and Methods Adult chronic periodontitis cases and controls from four ethnic groups (Caucasians, African Americans, Hispanics and Asians) were recruited in the USA, Chile and China. Genotypes of IL1B gene single nucleotide polymorphisms (SNPs), including three functional SNPs (rs16944, rs1143623, rs4848306) in the promoter and one intronic SNP (rs1143633), were determined using a single base extension method or TaqMan 5′ nuclease assay. Logistic regression and other statistical analyses were used to examine the association between moderate to severe periodontitis and IL1B gene variations, including SNPs, haplotypes and composite genotypes. Genotype patterns associated with disease in the discovery study were then evaluated in independent validation studies. Results Significant associations were identified in the discovery study, consisting of Caucasians and African Americans, between moderate to severe adult chronic periodontitis and functional variations in the IL1B gene, including a pattern of four IL1B SNPs (OR = 1.87, p < 0.0001). The association between the disease and this IL1B composite genotype pattern was validated in two additional studies consisting of Hispanics (OR = 1.95, p = 0.04) or Asians (OR = 3.27, p = 0.01). A meta-analysis of the three populations supported the association between the IL-1 genotype pattern and moderate to severe periodontitis (OR 1.95; p < 0.001). Our analysis also demonstrated that IL1B gene variations had added value to conventional risk factors in predicting chronic periodontitis. Conclusion This study validated the influence of IL-1 genetic factors on the severity of chronic periodontitis in four different ethnicities. PMID:24690098
Effects of enamel matrix genes on dental caries are moderated by fluoride exposures
Shaffer, John R.; Carlson, Jenna C.; Stanley, Brooklyn O. C.; Feingold, Eleanor; Cooper, Margaret; Vanyukov, Michael M.; Maher, Brion S.; Slayton, Rebecca L.; Willing, Marcia C.; Reis, Steven E.; McNeil, Daniel W.; Crout, Richard J.; Weyant, Robert J.; Levy, Steven M.; Vieira, Alexandre R.; Marazita, Mary L.
2014-01-01
Dental caries (tooth decay) is the most common chronic disease, worldwide, affecting most children and adults. Though dental caries is highly heritable, few caries-related genes have been discovered. We investigated whether 18 genetic variants in the group of nonamelogenin enamel matrix genes (AMBN, ENAM, TUFT1, and TFIP11) were associated with dental caries experience in 13 age- and race-stratified samples from six parent studies (N=3,600). Linear regression was used to model genetic associations and test gene-byfluoride interaction effects for two sources of fluoride: daily tooth brushing and home water fluoride concentration. Meta-analysis was used to combine results across five child and eight adult samples. We observed the statistically significant association of rs2337359 upstream of TUFT1 with dental caries experience via meta-analysis across adult samples (p<0.002) and the suggestive association for multiple variants in TFIP11 across child samples (p<0.05). Moreover, we discovered two genetic variants (rs2337359 upstream of TUFT1 and missense rs7439186 in AMBN) involved in gene-by-fluoride interactions. For each interaction, participants with the risk allele/genotype exhibited greater dental caries experience only if they were not exposed to the source of fluoride. Altogether, these results confirm that variation in enamel matrix genes contributes to individual differences in dental caries liability, and demonstrate that the effects of these genes may be moderated by protective fluoride exposures. In short, genes may exert greater influence on dental caries in unprotected environments, or equivalently, the protective effects of fluoride may obviate the effects of genetic risk alleles. PMID:25373699
Development of a molecular diagnostic test for Retinitis Pigmentosa in the Japanese population.
Maeda, Akiko; Yoshida, Akiko; Kawai, Kanako; Arai, Yuki; Akiba, Ryutaro; Inaba, Akira; Takagi, Seiji; Fujiki, Ryoji; Hirami, Yasuhiko; Kurimoto, Yasuo; Ohara, Osamu; Takahashi, Masayo
2018-05-21
Retinitis Pigmentosa (RP) is the most common form of inherited retinal dystrophy caused by different genetic variants. More than 60 causative genes have been identified to date. The establishment of cost-effective molecular diagnostic tests with high sensitivity and specificity can be beneficial for patients and clinicians. Here, we developed a clinical diagnostic test for RP in the Japanese population. Evaluation of diagnostic technology, Prospective, Clinical and experimental study. A panel of 39 genes reported to cause RP in Japanese patients was established. Next generation sequence (NGS) technology was applied for the analyses of 94 probands with RP and RP-related diseases. After interpretation of detected genetic variants, molecular diagnosis based on a study of the genetic variants and a clinical phenotype was made by a multidisciplinary team including clinicians, researchers and genetic counselors. NGS analyses found 14,343 variants from 94 probands. Among them, 189 variants in 83 probands (88.3% of all cases) were selected as pathogenic variants and 64 probands (68.1%) have variants which can cause diseases. After the deliberation of these 64 cases, molecular diagnosis was made in 43 probands (45.7%). The final molecular diagnostic rate with the current system combining supplemental Sanger sequencing was 47.9% (45 of 94 cases). The RP panel provides the significant advantage of detecting genetic variants with a high molecular diagnostic rate. This type of race-specific high-throughput genotyping allows us to conduct a cost-effective and clinically useful genetic diagnostic test.
Use of whole exome sequencing for the identification of Ito-based arrhythmia mechanism and therapy.
Sturm, Amy C; Kline, Crystal F; Glynn, Patric; Johnson, Benjamin L; Curran, Jerry; Kilic, Ahmet; Higgins, Robert S D; Binkley, Philip F; Janssen, Paul M L; Weiss, Raul; Raman, Subha V; Fowler, Steven J; Priori, Silvia G; Hund, Thomas J; Carnes, Cynthia A; Mohler, Peter J
2015-05-26
Identified genetic variants are insufficient to explain all cases of inherited arrhythmia. We tested whether the integration of whole exome sequencing with well-established clinical, translational, and basic science platforms could provide rapid and novel insight into human arrhythmia pathophysiology and disease treatment. We report a proband with recurrent ventricular fibrillation, resistant to standard therapeutic interventions. Using whole-exome sequencing, we identified a variant in a previously unidentified exon of the dipeptidyl aminopeptidase-like protein-6 (DPP6) gene. This variant is the first identified coding mutation in DPP6 and augments cardiac repolarizing current (Ito) causing pathological changes in Ito and action potential morphology. We designed a therapeutic regimen incorporating dalfampridine to target Ito. Dalfampridine, approved for multiple sclerosis, normalized the ECG and reduced arrhythmia burden in the proband by >90-fold. This was combined with cilostazol to accelerate the heart rate to minimize the reverse-rate dependence of augmented Ito. We describe a novel arrhythmia mechanism and therapeutic approach to ameliorate the disease. Specifically, we identify the first coding variant of DPP6 in human ventricular fibrillation. These findings illustrate the power of genetic approaches for the elucidation and treatment of disease when carefully integrated with clinical and basic/translational research teams. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.
Cubillos, Francisco A; Brice, Claire; Molinet, Jennifer; Tisné, Sebastién; Abarca, Valentina; Tapia, Sebastián M; Oporto, Christian; García, Verónica; Liti, Gianni; Martínez, Claudio
2017-06-07
Saccharomyces cerevisiae is responsible for wine must fermentation. In this process, nitrogen represents a limiting nutrient and its scarcity results in important economic losses for the wine industry. Yeast isolates use different strategies to grow in poor nitrogen environments and their genomic plasticity enables adaptation to multiple habitats through improvements in nitrogen consumption. Here, we used a highly recombinant S. cerevisiae multi-parent population (SGRP-4X) derived from the intercross of four parental strains of different origins to identify new genetic variants responsible for nitrogen consumption differences during wine fermentation. Analysis of 165 fully sequenced F12 segregants allowed us to map 26 QTL in narrow intervals for 14 amino acid sources and ammonium, the majority of which represent genomic regions previously unmapped for these traits. To complement this strategy, we performed Bulk segregant RNA-seq (BSR-seq) analysis in segregants exhibiting extremely high and low ammonium consumption levels. This identified several QTL overlapping differentially expressed genes and refined the gene candidate search. Based on these approaches, we were able to validate ARO1 , PDC1 , CPS1 , ASI2 , LYP1 , and ALP1 allelic variants underlying nitrogen consumption differences between strains, providing evidence of many genes with small phenotypic effects. Altogether, these variants significantly shape yeast nitrogen consumption with important implications for evolution, ecological, and quantitative genomics. Copyright © 2017 Cubillos et al.
Cubillos, Francisco A.; Brice, Claire; Molinet, Jennifer; Tisné, Sebastién; Abarca, Valentina; Tapia, Sebastián M.; Oporto, Christian; García, Verónica; Liti, Gianni; Martínez, Claudio
2017-01-01
Saccharomyces cerevisiae is responsible for wine must fermentation. In this process, nitrogen represents a limiting nutrient and its scarcity results in important economic losses for the wine industry. Yeast isolates use different strategies to grow in poor nitrogen environments and their genomic plasticity enables adaptation to multiple habitats through improvements in nitrogen consumption. Here, we used a highly recombinant S. cerevisiae multi-parent population (SGRP-4X) derived from the intercross of four parental strains of different origins to identify new genetic variants responsible for nitrogen consumption differences during wine fermentation. Analysis of 165 fully sequenced F12 segregants allowed us to map 26 QTL in narrow intervals for 14 amino acid sources and ammonium, the majority of which represent genomic regions previously unmapped for these traits. To complement this strategy, we performed Bulk segregant RNA-seq (BSR-seq) analysis in segregants exhibiting extremely high and low ammonium consumption levels. This identified several QTL overlapping differentially expressed genes and refined the gene candidate search. Based on these approaches, we were able to validate ARO1, PDC1, CPS1, ASI2, LYP1, and ALP1 allelic variants underlying nitrogen consumption differences between strains, providing evidence of many genes with small phenotypic effects. Altogether, these variants significantly shape yeast nitrogen consumption with important implications for evolution, ecological, and quantitative genomics. PMID:28592651
Sheehan, Vivien A; Crosby, Jacy R; Sabo, Aniko; Mortier, Nicole A; Howard, Thad A; Muzny, Donna M; Dugan-Perez, Shannon; Aygun, Banu; Nottage, Kerri A; Boerwinkle, Eric; Gibbs, Richard A; Ware, Russell E; Flanagan, Jonathan M
2014-01-01
Hydroxyurea has proven efficacy in children and adults with sickle cell anemia (SCA), but with considerable inter-individual variability in the amount of fetal hemoglobin (HbF) produced. Sibling and twin studies indicate that some of that drug response variation is heritable. To test the hypothesis that genetic modifiers influence pharmacological induction of HbF, we investigated phenotype-genotype associations using whole exome sequencing of children with SCA treated prospectively with hydroxyurea to maximum tolerated dose (MTD). We analyzed 171 unrelated patients enrolled in two prospective clinical trials, all treated with dose escalation to MTD. We examined two MTD drug response phenotypes: HbF (final %HbF minus baseline %HbF), and final %HbF. Analyzing individual genetic variants, we identified multiple low frequency and common variants associated with HbF induction by hydroxyurea. A validation cohort of 130 pediatric sickle cell patients treated to MTD with hydroxyurea was genotyped for 13 non-synonymous variants with the strongest association with HbF response to hydroxyurea in the discovery cohort. A coding variant in Spalt-like transcription factor, or SALL2, was associated with higher final HbF in this second independent replication sample and SALL2 represents an outstanding novel candidate gene for further investigation. These findings may help focus future functional studies and provide new insights into the pharmacological HbF upregulation by hydroxyurea in patients with SCA.
Advances in Tourette syndrome: diagnoses and treatment.
Serajee, Fatema J; Mahbubul Huq, A H M
2015-06-01
Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder characterized by multiple motor tics and at least one vocal or phonic tic, and often one or more comorbid psychiatric disorders. Premonitory sensory urges before tic execution and desire for "just-right" perception are central features. The pathophysiology involves cortico-striato-thalamo-cortical circuits and possibly dopaminergic system. TS is considered a genetic disorder but the genetics is complex and likely involves rare mutations, common variants, and environmental and epigenetic factors. Treatment is multimodal and includes education and reassurance, behavioral interventions, pharmacologic, and rarely, surgical interventions. Copyright © 2015 Elsevier Inc. All rights reserved.
Novel rare variations of the oxytocin receptor (OXTR) gene in autism spectrum disorder individuals.
Liu, Xiaoxi; Kawashima, Minae; Miyagawa, Taku; Otowa, Takeshi; Latt, Khun Zaw; Thiri, Myo; Nishida, Hisami; Sugiyama, Toshiro; Tsurusaki, Yoshinori; Matsumoto, Naomichi; Mabuchi, Akihiko; Tokunaga, Katsushi; Sasaki, Tsukasa
2015-01-01
The oxytocin receptor (OXTR) gene has been implicated as a risk gene for autism spectrum disorder (ASD)-a neurodevelopmental disorder with essential features of impairments in social communication and reciprocal interaction. The genetic associations between common variations in OXTR and ASD have been reported in multiple ethnic populations. However, little is known about the distribution of rare variations within OXTR in ASD patients. In this study, we resequenced the full length of OXTR in 105 ASD individuals using an approach that combined the power of next-generation sequencing technology, long-range PCR and DNA pooling. We demonstrated that rare variants with minor allele frequency as low as 0.05% could be reliably detected by our method. We identified 28 novel variants including potential functional variants in the intron region and one rare missense variant (R150S). We subsequently performed Sanger sequencing and validated five novel variants located in previously suggested candidate regions in ASD individuals. Further sequencing of 312 healthy subjects showed that the burden of rare variants is significantly higher in ASDs compared with healthy individuals. Our results support that the rare variation in OXTR gene might be involved in ASD.
Hendricks, Audrey E; Bochukova, Elena G; Marenne, Gaëlle; Keogh, Julia M; Atanassova, Neli; Bounds, Rebecca; Wheeler, Eleanor; Mistry, Vanisha; Henning, Elana; Körner, Antje; Muddyman, Dawn; McCarthy, Shane; Hinney, Anke; Hebebrand, Johannes; Scott, Robert A; Langenberg, Claudia; Wareham, Nick J; Surendran, Praveen; Howson, Joanna M; Butterworth, Adam S; Danesh, John; Nordestgaard, Børge G; Nielsen, Sune F; Afzal, Shoaib; Papadia, Sofia; Ashford, Sofie; Garg, Sumedha; Millhauser, Glenn L; Palomino, Rafael I; Kwasniewska, Alexandra; Tachmazidou, Ioanna; O'Rahilly, Stephen; Zeggini, Eleftheria; Barroso, Inês; Farooqi, I Sadaf
2017-06-29
Obesity is a genetically heterogeneous disorder. Using targeted and whole-exome sequencing, we studied 32 human and 87 rodent obesity genes in 2,548 severely obese children and 1,117 controls. We identified 52 variants contributing to obesity in 2% of cases including multiple novel variants in GNAS, which were sometimes found with accelerated growth rather than short stature as described previously. Nominally significant associations were found for rare functional variants in BBS1, BBS9, GNAS, MKKS, CLOCK and ANGPTL6. The p.S284X variant in ANGPTL6 drives the association signal (rs201622589, MAF~0.1%, odds ratio = 10.13, p-value = 0.042) and results in complete loss of secretion in cells. Further analysis including additional case-control studies and population controls (N = 260,642) did not support association of this variant with obesity (odds ratio = 2.34, p-value = 2.59 × 10 -3 ), highlighting the challenges of testing rare variant associations and the need for very large sample sizes. Further validation in cohorts with severe obesity and engineering the variants in model organisms will be needed to explore whether human variants in ANGPTL6 and other genes that lead to obesity when deleted in mice, do contribute to obesity. Such studies may yield druggable targets for weight loss therapies.
Investigation of Maternal Genotype Effects in Autism by Genome-Wide Association
Yuan, Han; Dougherty, Joseph D.
2014-01-01
Lay Abstract Autism spectrum disorders (ASDs) are pervasive developmental disorders which have both a genetic and environmental component. One source of the environmental component is the in utero (prenatal) environment. The maternal genome can potentially contribute to the risk of autism in children by altering this prenatal environment. In this study, the possibility of maternal genotype effects was explored by looking for common variants (single nucleotide polymorphisms, or SNPs) in the maternal genome associated with increased risk of autism in children. We performed a case/control genome-wide association study (GWAS) using mothers of probands as cases and either fathers of probands or normal females as controls, using two collections of families with autism. We did not identify any SNP that reached significance and thus a common variant of large effect is unlikely. However, there was evidence for the possibility of a large number of alleles each carrying a small effect. This suggested that if there is a contribution to autism risk through common-variant maternal genetic effects, it may be the result of multiple loci of small effects. We did not investigate rare variants in this study. Scientific Abstract Like most psychiatric disorders, autism spectrum disorders have both a genetic and an environmental component. While previous studies have clearly demonstrated the contribution of in utero (prenatal) environment on autism risk, most of them focused on transient environmental factors. Based on a recent sibling study, we hypothesized that environmental factors could also come from the maternal genome, which would result in persistent effects across siblings. In this study, the possibility of maternal genotype effects was examined by looking for common variants (single nucleotide polymorphisms, or SNPs) in the maternal genome associated with increased risk of autism in children. A case/control genome-wide association study (GWAS) was performed using mothers of probands as cases and either fathers of probands or normal females as controls. Autism Genetic Resource Exchange (AGRE) and Illumina Genotype Control Database (iCon) were used as our discovery cohort (n=1616). The same analysis was then replicated on Simon Simplex Collection (SSC) and Study of Addiction: Genetics and Environment (SAGE) datasets (n=2732). We did not identify any SNP that reached genome-wide significance (p<10−8) and thus a common variant of large effect is unlikely. However, there was evidence for the possibility of a large number of alleles of effective size marginally below our power to detect. PMID:24574247
Song, Sunmi; Marcum, Christopher Steven; Wilkinson, Anna V; Shete, Sanjay; Koehly, Laura M
2018-04-24
Despite prevalent binge drinking and alcohol-dependent symptoms among Hispanics, few studies have examined how multidimensional factors influence Hispanic adolescents' binge drinking. Purpose This study examines the effects of genetic, psychological, and social network factors on binge drinking over time among Mexican heritage adolescents in the USA and whether there are correlations among genetic variants that are associated with binge drinking and psychological and network characteristics. Mexican heritage adolescents (n = 731) participated in a longitudinal study, which included genetic testing at baseline, alcohol use assessments at first and second follow-ups, and questionnaires on sensation seeking, impulsivity, and peer and family network characteristics at second follow-up. Logistic regression and Spearman correlation analyses were performed. After adjusting for demographic characteristics, underlying genetic clustering, and binge drinking at first follow-up, two genetic variants on tryptophan hydroxylase 2 (TPH2; rs17110451, rs7963717), sensation seeking and impulsivity, and having a greater fraction of peers who drink or encourage drinking alcohol were associated with greater risk whereas another genetic variant on TPH2 (rs11178999) and having a greater fraction of close family relationships were associated with reduced risk for binge drinking at second follow-up. Genetic variants in TPH1 (rs591556) were associated with sensation seeking and impulsivity, while genetic variants in TPH2 (rs17110451) were associated with the fraction of drinkers in family. Results reveal that genetic variants in the serotonin pathway, behavioral disinhibition traits, and social networks exert joint influences on binge drinking in Mexican heritage adolescents in the USA.
Scott, Robert A.; Freitag, Daniel F.; Li, Li; Chu, Audrey Y.; Surendran, Praveen; Young, Robin; Grarup, Niels; Stancáková, Alena; Chen, Yuning; V.Varga, Tibor; Yaghootkar, Hanieh; Luan, Jian'an; Zhao, Jing Hua; Willems, Sara M.; Wessel, Jennifer; Wang, Shuai; Maruthur, Nisa; Michailidou, Kyriaki; Pirie, Ailith; van der Lee, Sven J.; Gillson, Christopher; Olama, Ali Amin Al; Amouyel, Philippe; Arriola, Larraitz; Arveiler, Dominique; Aviles-Olmos, Iciar; Balkau, Beverley; Barricarte, Aurelio; Barroso, Inês; Garcia, Sara Benlloch; Bis, Joshua C.; Blankenberg, Stefan; Boehnke, Michael; Boeing, Heiner; Boerwinkle, Eric; Borecki, Ingrid B.; Bork-Jensen, Jette; Bowden, Sarah; Caldas, Carlos; Caslake, Muriel; Cupples, L. Adrienne; Cruchaga, Carlos; Czajkowski, Jacek; den Hoed, Marcel; Dunn, Janet A.; Earl, Helena M.; Ehret, Georg B.; Ferrannini, Ele; Ferrieres, Jean; Foltynie, Thomas; Ford, Ian; Forouhi, Nita G.; Gianfagna, Francesco; Gonzalez, Carlos; Grioni, Sara; Hiller, Louise; Jansson, Jan-Håkan; Jørgensen, Marit E.; Jukema, J. Wouter; Kaaks, Rudolf; Kee, Frank; Kerrison, Nicola D.; Key, Timothy J.; Kontto, Jukka; Kote-Jarai, Zsofia; Kraja, Aldi T.; Kuulasmaa, Kari; Kuusisto, Johanna; Linneberg, Allan; Liu, Chunyu; Marenne, Gaëlle; Mohlke, Karen L.; Morris, Andrew P.; Muir, Kenneth; Müller-Nurasyid, Martina; Munroe, Patricia B.; Navarro, Carmen; Nielsen, Sune F.; Nilsson, Peter M.; Nordestgaard, Børge G.; Packard, Chris J.; Palli, Domenico; Panico, Salvatore; Peloso, Gina M.; Perola, Markus; Peters, Annette; Poole, Christopher J.; Quirós, J. Ramón; Rolandsson, Olov; Sacerdote, Carlotta; Salomaa, Veikko; Sánchez, María-José; Sattar, Naveed; Sharp, Stephen J.; Sims, Rebecca; Slimani, Nadia; Smith, Jennifer A.; Thompson, Deborah J.; Trompet, Stella; Tumino, Rosario; van der A, Daphne L.; van der Schouw, Yvonne T.; Virtamo, Jarmo; Walker, Mark; Walter, Klaudia; Abraham, Jean E.; Amundadottir, Laufey T.; Aponte, Jennifer L.; Butterworth, Adam S.; Dupuis, Josée; Easton, Douglas F.; Eeles, Rosalind A.; Erdmann, Jeanette; Franks, Paul W.; Frayling, Timothy M.; Hansen, Torben; Howson, Joanna M. M.; Jørgensen, Torben; Kooner, Jaspal; Laakso, Markku; Langenberg, Claudia; McCarthy, Mark I.; Pankow, James S.; Pedersen, Oluf; Riboli, Elio; Rotter, Jerome I.; Saleheen, Danish; Samani, Nilesh J.; Schunkert, Heribert; Vollenweider, Peter; O'Rahilly, Stephen; Deloukas, Panos; Danesh, John; Goodarzi, Mark O.; Kathiresan, Sekar; Meigs, James B.; Ehm, Margaret G.; Wareham, Nicholas J.; Waterworth, Dawn M.
2016-01-01
Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to inform development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in 6 genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing, and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr;rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and lower T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomised controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process. PMID:27252175
NAD Deficiency, Congenital Malformations, and Niacin Supplementation.
Shi, Hongjun; Enriquez, Annabelle; Rapadas, Melissa; Martin, Ella M M A; Wang, Roni; Moreau, Julie; Lim, Chai K; Szot, Justin O; Ip, Eddie; Hughes, James N; Sugimoto, Kotaro; Humphreys, David T; McInerney-Leo, Aideen M; Leo, Paul J; Maghzal, Ghassan J; Halliday, Jake; Smith, Janine; Colley, Alison; Mark, Paul R; Collins, Felicity; Sillence, David O; Winlaw, David S; Ho, Joshua W K; Guillemin, Gilles J; Brown, Matthew A; Kikuchi, Kazu; Thomas, Paul Q; Stocker, Roland; Giannoulatou, Eleni; Chapman, Gavin; Duncan, Emma L; Sparrow, Duncan B; Dunwoodie, Sally L
2017-08-10
Congenital malformations can be manifested as combinations of phenotypes that co-occur more often than expected by chance. In many such cases, it has proved difficult to identify a genetic cause. We sought the genetic cause of cardiac, vertebral, and renal defects, among others, in unrelated patients. We used genomic sequencing to identify potentially pathogenic gene variants in families in which a person had multiple congenital malformations. We tested the function of the variant by using assays of in vitro enzyme activity and by quantifying metabolites in patient plasma. We engineered mouse models with similar variants using the CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 system. Variants were identified in two genes that encode enzymes of the kynurenine pathway, 3-hydroxyanthranilic acid 3,4-dioxygenase (HAAO) and kynureninase (KYNU). Three patients carried homozygous variants predicting loss-of-function changes in the HAAO or KYNU proteins (HAAO p.D162*, HAAO p.W186*, or KYNU p.V57Efs*21). Another patient carried heterozygous KYNU variants (p.Y156* and p.F349Kfs*4). The mutant enzymes had greatly reduced activity in vitro. Nicotinamide adenine dinucleotide (NAD) is synthesized de novo from tryptophan through the kynurenine pathway. The patients had reduced levels of circulating NAD. Defects similar to those in the patients developed in the embryos of Haao-null or Kynu-null mice owing to NAD deficiency. In null mice, the prevention of NAD deficiency during gestation averted defects. Disruption of NAD synthesis caused a deficiency of NAD and congenital malformations in humans and mice. Niacin supplementation during gestation prevented the malformations in mice. (Funded by the National Health and Medical Research Council of Australia and others.).
Genetic Variants Associated with Lipid Profiles in Chinese Patients with Type 2 Diabetes
Xing, Xiaoyan; Zhang, Bo; Zhang, Xuelian; Hong, Jing; Yang, Wenying
2015-01-01
Dyslipidemia is a strong risk factor for cardiovascular disease among patients with type 2 diabetes (T2D). The aim of this study was to identify lipid-related genetic variants in T2D patients of Han Chinese ancestry. Among 4,908 Chinese T2D patients who were not taking lipid-lowering medications, single nucleotide polymorphisms (SNPs) in seven genes previously found to be associated with lipid traits in genome-wide association studies conducted in populations of European ancestry (ABCA1, GCKR, BAZ1B, TOMM40, DOCK7, HNF1A, and HNF4A) were genotyped. After adjusting for multiple covariates, SNPs in ABCA1, GCKR, BAZ1B, TOMM40, and HNF1A were identified as significantly associated with triglyceride levels in T2D patients (P < 0.05). The associations between the SNPs in ABCA1 (rs3890182), GCKR (rs780094), and BAZ1B (rs2240466) remained significant even after correction for multiple testing (P = 8.85×10−3, 7.88×10−7, and 2.03×10−6, respectively). BAZ1B (rs2240466) also was associated with the total cholesterol level (P = 4.75×10−2). In addition, SNP rs157580 in TOMM40 was associated with the low-density lipoprotein cholesterol level (P = 6.94×10−3). Our findings confirm that lipid-related genetic loci are associated with lipid profiles in Chinese patients with type 2 diabetes. PMID:26252223
Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons.
Griesi-Oliveira, K; Acab, A; Gupta, A R; Sunaga, D Y; Chailangkarn, T; Nicol, X; Nunez, Y; Walker, M F; Murdoch, J D; Sanders, S J; Fernandez, T V; Ji, W; Lifton, R P; Vadasz, E; Dietrich, A; Pradhan, D; Song, H; Ming, G-L; Gu, X; Haddad, G; Marchetto, M C N; Spitzer, N; Passos-Bueno, M R; State, M W; Muotri, A R
2015-11-01
An increasing number of genetic variants have been implicated in autism spectrum disorders (ASDs), and the functional study of such variants will be critical for the elucidation of autism pathophysiology. Here, we report a de novo balanced translocation disruption of TRPC6, a cation channel, in a non-syndromic autistic individual. Using multiple models, such as dental pulp cells, induced pluripotent stem cell (iPSC)-derived neuronal cells and mouse models, we demonstrate that TRPC6 reduction or haploinsufficiency leads to altered neuronal development, morphology and function. The observed neuronal phenotypes could then be rescued by TRPC6 complementation and by treatment with insulin-like growth factor-1 or hyperforin, a TRPC6-specific agonist, suggesting that ASD individuals with alterations in this pathway may benefit from these drugs. We also demonstrate that methyl CpG binding protein-2 (MeCP2) levels affect TRPC6 expression. Mutations in MeCP2 cause Rett syndrome, revealing common pathways among ASDs. Genetic sequencing of TRPC6 in 1041 ASD individuals and 2872 controls revealed significantly more nonsynonymous mutations in the ASD population, and identified loss-of-function mutations with incomplete penetrance in two patients. Taken together, these findings suggest that TRPC6 is a novel predisposing gene for ASD that may act in a multiple-hit model. This is the first study to use iPSC-derived human neurons to model non-syndromic ASD and illustrate the potential of modeling genetically complex sporadic diseases using such cells.
Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons
Griesi-Oliveira, Karina; Acab, Allan; Gupta, Abha R.; Sunaga, Daniele Yumi; Chailangkarn, Thanathom; Nicol, Xavier; Nunez, Yanelli; Walker, Michael F.; Murdoch, John D.; Sanders, Stephan J.; Fernandez, Thomas V.; Ji, Weizhen; Lifton, Richard P.; Vadasz, Estevão; Dietrich, Alexander; Pradhan, Dennis; Song, Hongjun; Ming, Guo-li; Guoe, Xiang; Haddad, Gabriel; Marchetto, Maria C. N.; Spitzer, Nicholas; Passos-Bueno, Maria Rita; State, Matthew W.; Muotri, Alysson R.
2014-01-01
An increasing number of genetic variants have been implicated in autism spectrum disorders (ASD), and the functional study of such variants will be critical for the elucidation of autism pathophysiology. Here, we report a de novo balanced translocation disruption of TRPC6, a cation channel, in a non-syndromic autistic individual. Using multiple models, such as dental pulp cells, iPSC-derived neuronal cells and mouse models, we demonstrate that TRPC6 reduction or haploinsufficiency leads to altered neuronal development, morphology, and function. The observed neuronal phenotypes could then be rescued by TRPC6 complementation and by treatment with IGF1 or hyperforin, a TRPC6-specific agonist, suggesting that ASD individuals with alterations in this pathway might benefit from these drugs. We also demonstrate that MeCP2 levels affect TRPC6 expression. Mutations in MeCP2 cause Rett syndrome, revealing common pathways among ASDs. Genetic sequencing of TRPC6 in 1041 ASD individuals and 2872 controls revealed significantly more nonsynonymous mutations in the ASD population, and identified loss-of-function mutations with incomplete penetrance in two patients. Taken together, these findings suggest that TRPC6 is a novel predisposing gene for ASD that may act in a multiple-hit model. This is the first study to use iPSC-derived human neurons to model non-syndromic ASD and illustrate the potential of modeling genetically complex sporadic diseases using such cells. PMID:25385366
Yourshaw, Michael; Solorzano-Vargas, R. Sergio; Pickett, Lindsay A.; Lindberg, Iris; Wang, Jiafang; Cortina, Galen; Pawlikowska-Haddal, Anna; Baron, Howard; Venick, Robert S.; Nelson, Stanley F.; Martín, Martín G.
2014-01-01
Objectives Congenital diarrhea disorders are a group of genetically diverse and typically autosomal recessive disorders that have yet to be well characterized phenotypically or molecularly. Diagnostic assessments are generally limited to nutritional challenges and histologic evaluation, and many subjects eventually require a prolonged course of intravenous nutrition. Here we describe next-generation sequencing techniques to investigate a child with perplexing congenital malabsorptive diarrhea and other presumably unrelated clinical problems; this method provides an alternative approach to molecular diagnosis. Methods We screened the diploid genome of an affected individual, using exome sequencing, for uncommon variants that have observed protein-coding consequences. We assessed the functional activity of the mutant protein, as well as its lack of expression using immunohistochemistry. Results Among several rare variants detected was a homozygous nonsense mutation in the catalytic domain of the proprotein convertase subtilisin/kexin type 1 gene. The mutation abolishes prohormone convertase 1/3 endoprotease activity as well as expression in the intestine. These primary genetic findings prompted a careful endocrine reevaluation of the child at 4.5 years of age, and multiple significant problems were subsequently identified consistent with the known phenotypic consequences of proprotein convertase subtilisin/kexin type 1 (PCSK1) gene mutations. Based on the molecular diagnosis, alternate medical and dietary management was implemented for diabetes insipidus, polyphagia, and micropenis. Conclusions Whole-exome sequencing provides a powerful diagnostic tool to clinicians managing rare genetic disorders with multiple perplexing clinical manifestations. PMID:24280991
Yourshaw, Michael; Solorzano-Vargas, R Sergio; Pickett, Lindsay A; Lindberg, Iris; Wang, Jiafang; Cortina, Galen; Pawlikowska-Haddal, Anna; Baron, Howard; Venick, Robert S; Nelson, Stanley F; Martín, Martín G
2013-12-01
Congenital diarrhea disorders are a group of genetically diverse and typically autosomal recessive disorders that have yet to be well characterized phenotypically or molecularly. Diagnostic assessments are generally limited to nutritional challenges and histologic evaluation, and many subjects eventually require a prolonged course of intravenous nutrition. Here we describe next-generation sequencing techniques to investigate a child with perplexing congenital malabsorptive diarrhea and other presumably unrelated clinical problems; this method provides an alternative approach to molecular diagnosis. We screened the diploid genome of an affected individual, using exome sequencing, for uncommon variants that have observed protein-coding consequences. We assessed the functional activity of the mutant protein, as well as its lack of expression using immunohistochemistry. Among several rare variants detected was a homozygous nonsense mutation in the catalytic domain of the proprotein convertase subtilisin/kexin type 1 gene. The mutation abolishes prohormone convertase 1/3 endoprotease activity as well as expression in the intestine. These primary genetic findings prompted a careful endocrine reevaluation of the child at 4.5 years of age, and multiple significant problems were subsequently identified consistent with the known phenotypic consequences of proprotein convertase subtilisin/kexin type 1 (PCSK1) gene mutations. Based on the molecular diagnosis, alternate medical and dietary management was implemented for diabetes insipidus, polyphagia, and micropenis. Whole-exome sequencing provides a powerful diagnostic tool to clinicians managing rare genetic disorders with multiple perplexing clinical manifestations.
Adaptation Genomics of a Small-Colony Variant in a Pseudomonas chlororaphis 30-84 Biofilm
Dorosky, Robert J.; Han, Cliff S.; Lo, Chien-chi; Dichosa, Armand E. K.; Chain, Patrick S.; Yu, Jun Myoung; Pierson, Leland S.
2014-01-01
The rhizosphere-colonizing bacterium Pseudomonas chlororaphis 30-84 is an effective biological control agent against take-all disease of wheat. In this study, we characterize a small-colony variant (SCV) isolated from a P. chlororaphis 30-84 biofilm. The SCV exhibited pleiotropic phenotypes, including small cell size, slow growth and motility, low levels of phenazine production, and increased biofilm formation and resistance to antimicrobials. To better understand the genetic alterations underlying these phenotypes, RNA and whole-genome sequencing analyses were conducted comparing an SCV to the wild-type strain. Of the genome's 5,971 genes, transcriptomic profiling indicated that 1,098 (18.4%) have undergone substantial reprograming of gene expression in the SCV. Whole-genome sequence analysis revealed multiple alterations in the SCV, including mutations in yfiR (cyclic-di-GMP production), fusA (elongation factor), and cyoE (heme synthesis) and a 70-kb deletion. Genetic analysis revealed that the yfiR locus plays a major role in controlling SCV phenotypes, including colony size, growth, motility, and biofilm formation. Moreover, a point mutation in the fusA gene contributed to kanamycin resistance. Interestingly, the SCV can partially switch back to wild-type morphologies under specific conditions. Our data also support the idea that phenotypic switching in P. chlororaphis is not due to simple genetic reversions but may involve multiple secondary mutations. The emergence of these highly adherent and antibiotic-resistant SCVs within the biofilm might play key roles in P. chlororaphis natural persistence. PMID:25416762
Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Alejandro Q; Musolf, Anthony; Matise, Tara C; Finch, Stephen J; Gordon, Derek
2012-01-01
As with any new technology, next-generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to those data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single-variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p value, no matter how many loci. Copyright © 2013 S. Karger AG, Basel.
Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Andrew; Musolf, Anthony; Matise, Tara C.; Finch, Stephen J.; Gordon, Derek
2013-01-01
As with any new technology, next generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model, based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to that data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p-value, no matter how many loci. PMID:23594495
Ma, Meng; Ru, Ying; Chuang, Ling-Shiang; Hsu, Nai-Yun; Shi, Li-Song; Hakenberg, Jörg; Cheng, Wei-Yi; Uzilov, Andrew; Ding, Wei; Glicksberg, Benjamin S; Chen, Rong
2015-01-01
The invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases. Many of these genetic variants are located outside the protein coding regions, and as such, it is challenging to interpret the function of these genetic variants by traditional genetic approaches. Recent genome-wide functional genomics studies, such as FANTOM5 and ENCODE have uncovered a large number of regulatory elements across hundreds of different tissues or cell lines in the human genome. These findings provide an opportunity to study the interaction between regulatory elements and disease-associated genetic variants. Identifying these diseased-related regulatory elements will shed light on understanding the mechanisms of how these variants regulate gene expression and ultimately result in disease formation and progression. In this study, we curated and categorized 27,558 Mendelian disease variants, 20,964 complex disease variants, 5,809 cancer predisposing germline variants, and 43,364 recurrent cancer somatic mutations. Compared against nine different types of regulatory regions from FANTOM5 and ENCODE projects, we found that different types of disease variants show distinctive propensity for particular regulatory elements. Mendelian disease variants and recurrent cancer somatic mutations are 22-fold and 10- fold significantly enriched in promoter regions respectively (q<0.001), compared with allele-frequency-matched genomic background. Separate from these two categories, cancer predisposing germline variants are 27-fold enriched in histone modification regions (q<0.001), 10-fold enriched in chromatin physical interaction regions (q<0.001), and 6-fold enriched in transcription promoters (q<0.001). Furthermore, Mendelian disease variants and recurrent cancer somatic mutations share very similar distribution across types of functional effects. We further found that regulatory regions are located within over 50% coding exon regions. Transcription promoters, methylation regions, and transcription insulators have the highest density of disease variants, with 472, 239, and 72 disease variants per one million base pairs, respectively. Disease-associated variants in different disease categories are preferentially located in particular regulatory elements. These results will be useful for an overall understanding about the differences among the pathogenic mechanisms of various disease-associated variants.
2015-01-01
Background The invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases. Many of these genetic variants are located outside the protein coding regions, and as such, it is challenging to interpret the function of these genetic variants by traditional genetic approaches. Recent genome-wide functional genomics studies, such as FANTOM5 and ENCODE have uncovered a large number of regulatory elements across hundreds of different tissues or cell lines in the human genome. These findings provide an opportunity to study the interaction between regulatory elements and disease-associated genetic variants. Identifying these diseased-related regulatory elements will shed light on understanding the mechanisms of how these variants regulate gene expression and ultimately result in disease formation and progression. Results In this study, we curated and categorized 27,558 Mendelian disease variants, 20,964 complex disease variants, 5,809 cancer predisposing germline variants, and 43,364 recurrent cancer somatic mutations. Compared against nine different types of regulatory regions from FANTOM5 and ENCODE projects, we found that different types of disease variants show distinctive propensity for particular regulatory elements. Mendelian disease variants and recurrent cancer somatic mutations are 22-fold and 10- fold significantly enriched in promoter regions respectively (q<0.001), compared with allele-frequency-matched genomic background. Separate from these two categories, cancer predisposing germline variants are 27-fold enriched in histone modification regions (q<0.001), 10-fold enriched in chromatin physical interaction regions (q<0.001), and 6-fold enriched in transcription promoters (q<0.001). Furthermore, Mendelian disease variants and recurrent cancer somatic mutations share very similar distribution across types of functional effects. We further found that regulatory regions are located within over 50% coding exon regions. Transcription promoters, methylation regions, and transcription insulators have the highest density of disease variants, with 472, 239, and 72 disease variants per one million base pairs, respectively. Conclusions Disease-associated variants in different disease categories are preferentially located in particular regulatory elements. These results will be useful for an overall understanding about the differences among the pathogenic mechanisms of various disease-associated variants. PMID:26110593
Inherited genetic variants associated with occurrence of multiple primary melanoma.
Gibbs, David C; Orlow, Irene; Kanetsky, Peter A; Luo, Li; Kricker, Anne; Armstrong, Bruce K; Anton-Culver, Hoda; Gruber, Stephen B; Marrett, Loraine D; Gallagher, Richard P; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J; Cust, Anne E; Ollila, David W; Begg, Colin B; Berwick, Marianne; Thomas, Nancy E
2015-06-01
Recent studies, including genome-wide association studies, have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 SNPs from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% confidence intervals were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma, while NCOA6 rs4911442 approached significance (P = 0.06). The GEM Study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. ©2015 American Association for Cancer Research.
Inherited genetic variants associated with occurrence of multiple primary melanoma
Gibbs, David C.; Orlow, Irene; Kanetsky, Peter A.; Luo, Li; Kricker, Anne; Armstrong, Bruce K.; Anton-Culver, Hoda; Gruber, Stephen B.; Marrett, Loraine D.; Gallagher, Richard P.; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J.; Cust, Anne E.; Ollila, David W.; Begg, Colin B.; Berwick, Marianne; Thomas, Nancy E.
2015-01-01
Recent studies including genome-wide association studies have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 single nucleotide polymorphisms (SNP) from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% CIs were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma while NCOA6 rs4911442 approached significance (P = 0.06). The GEM study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. PMID:25837821
Adrianto, Indra; Wang, Shaofeng; Wiley, Graham B; Lessard, Christopher J; Kelly, Jennifer A; Adler, Adam J; Glenn, Stuart B; Williams, Adrienne H; Ziegler, Julie T; Comeau, Mary E; Marion, Miranda C; Wakeland, Benjamin E; Liang, Chaoying; Kaufman, Kenneth M; Guthridge, Joel M; Alarcón-Riquelme, Marta E; Alarcón, Graciela S; Anaya, Juan-Manuel; Bae, Sang-Cheol; Kim, Jae-Hoon; Joo, Young Bin; Boackle, Susan A; Brown, Elizabeth E; Petri, Michelle A; Ramsey-Goldman, Rosalind; Reveille, John D; Vilá, Luis M; Criswell, Lindsey A; Edberg, Jeffrey C; Freedman, Barry I; Gilkeson, Gary S; Jacob, Chaim O; James, Judith A; Kamen, Diane L; Kimberly, Robert P; Martín, Javier; Merrill, Joan T; Niewold, Timothy B; Pons-Estel, Bernardo A; Scofield, R Hal; Stevens, Anne M; Tsao, Betty P; Vyse, Timothy J; Langefeld, Carl D; Harley, John B; Wakeland, Edward K; Moser, Kathy L; Montgomery, Courtney G; Gaffney, Patrick M
2012-11-01
Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by autoantibody production and altered type I interferon expression. Genetic surveys and genome-wide association studies have identified >30 SLE susceptibility genes. One of these genes, TNIP1, encodes the ABIN1 protein. ABIN1 functions in the immune system by restricting NF-κB signaling. The present study was undertaken to investigate the genetic factors that influence association with SLE in genes that regulate the NF-κB pathway. We analyzed a dense set of genetic markers spanning TNIP1 and TAX1BP1, as well as the TNIP1 homolog TNIP2, in case-control populations of diverse ethnic origins. TNIP1, TNIP2, and TAX1BP1 were fine-mapped in a total of 8,372 SLE cases and 7,492 healthy controls from European-ancestry, African American, Hispanic, East Asian, and African American Gullah populations. Levels of TNIP1 messenger RNA (mRNA) and ABIN1 protein in Epstein-Barr virus-transformed human B cell lines were analyzed by quantitative reverse transcription-polymerase chain reaction and Western blotting, respectively. We found significant associations between SLE and genetic variants within TNIP1, but not in TNIP2 or TAX1BP1. After resequencing and imputation, we identified 2 independent risk haplotypes within TNIP1 in individuals of European ancestry that were also present in African American and Hispanic populations. Levels of TNIP1 mRNA and ABIN1 protein were reduced among subjects with these haplotypes, suggesting that they harbor hypomorphic functional variants that influence susceptibility to SLE by restricting ABIN1 expression. Our results confirm the association signals between SLE and TNIP1 variants in multiple populations and provide new insight into the mechanism by which TNIP1 variants may contribute to SLE pathogenesis. Copyright © 2012 by the American College of Rheumatology.
Joon, Aron; Brewster, Abenaa M.; Chen, Wei V.; Eng, Cathy; Shete, Sanjay; Casey, Graham; Schumacher, Fredrick; Lin, Yi; Harrison, Tabitha A.; White, Emily; Ahsan, Habibul; Andrulis, Irene L.; Whittemore, Alice S.; Ko Win, Aung; Schmidt, Daniel F.; Kapuscinski, Miroslaw K.; Ochs-Balcom, Heather M.; Gallinger, Steven; Jenkins, Mark A.; Newcomb, Polly A.; Lindor, Noralane M.; Peters, Ulrike; Amos, Christopher I.; Lynch, Patrick M.
2018-01-01
Background Clustering of breast and colorectal cancer has been observed within some families and cannot be explained by chance or known high-risk mutations in major susceptibility genes. Potential shared genetic susceptibility between breast and colorectal cancer, not explained by high-penetrance genes, has been postulated. We hypothesized that yet undiscovered genetic variants predispose to a breast-colorectal cancer phenotype. Methods To identify variants associated with a breast-colorectal cancer phenotype, we analyzed genome-wide association study (GWAS) data from cases and controls that met the following criteria: cases (n = 985) were women with breast cancer who had one or more first- or second-degree relatives with colorectal cancer, men/women with colorectal cancer who had one or more first- or second-degree relatives with breast cancer, and women diagnosed with both breast and colorectal cancer. Controls (n = 1769), were unrelated, breast and colorectal cancer-free, and age- and sex- frequency-matched to cases. After imputation, 6,220,060 variants were analyzed using the discovery set and variants associated with the breast-colorectal cancer phenotype at P<5.0E-04 (n = 549, at 60 loci) were analyzed for replication (n = 293 cases and 2,103 controls). Results Multiple correlated SNPs in intron 1 of the ROBO1 gene were suggestively associated with the breast-colorectal cancer phenotype in the discovery and replication data (most significant; rs7430339, Pdiscovery = 1.2E-04; rs7429100, Preplication = 2.8E-03). In meta-analysis of the discovery and replication data, the most significant association remained at rs7429100 (P = 1.84E-06). Conclusion The results of this exploratory analysis did not find clear evidence for a susceptibility locus with a pleiotropic effect on hereditary breast and colorectal cancer risk, although the suggestive association of genetic variation in the region of ROBO1, a potential tumor suppressor gene, merits further investigation. PMID:29698419
Zeng, Yanni; Navarro, Pau; Xia, Charley; Amador, Carmen; Fernandez-Pujals, Ana M; Thomson, Pippa A; Campbell, Archie; Nagy, Reka; Clarke, Toni-Kim; Hafferty, Jonathan D; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M
2016-12-01
Both genetic and environmental factors contribute to risk of depression, but estimates of their relative contributions are limited. Commonalities between clinically-assessed major depressive disorder (MDD) and self-declared depression (SDD) are also unclear. Using data from a large Scottish family-based cohort (GS:SFHS, N=19,994), we estimated the genetic and environmental variance components for MDD and SDD. The components representing the genetic effect associated with genome-wide common genetic variants (SNP heritability), the additional pedigree-associated genetic effect and non-genetic effects associated with common environments were estimated in a linear mixed model (LMM). Both MDD and SDD had significant contributions from components representing the effect from common genetic variants, the additional genetic effect associated with the pedigree and the common environmental effect shared by couples. The estimate of correlation between SDD and MDD was high (r=1.00, se=0.20) for common-variant-associated genetic effect and lower for the additional genetic effect from the pedigree (r=0.57, se=0.08) and the couple-shared environmental effect (r=0.53, se=0.22). Both genetics and couple-shared environmental effects were major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Roffman, Joshua L; Brohawn, David G; Nitenson, Adam Z; Macklin, Eric A; Smoller, Jordan W; Goff, Donald C
2013-03-01
Low serum folate levels previously have been associated with negative symptom risk in schizophrenia, as has the hypofunctional 677C>T variant of the MTHFR gene. This study examined whether other missense polymorphisms in folate-regulating enzymes, in concert with MTHFR, influence negative symptoms in schizophrenia, and whether total risk allele load interacts with serum folate status to further stratify negative symptom risk. Medicated outpatients with schizophrenia (n = 219), all of European origin and some included in a previous report, were rated with the Positive and Negative Syndrome Scale. A subset of 82 patients also underwent nonfasting serum folate testing. Patients were genotyped for the MTHFR 677C>T (rs1801133), MTHFR 1298A>C (rs1801131), MTR 2756A>G (rs1805087), MTRR 203A>G (rs1801394), FOLH1 484T>C (rs202676), RFC 80A>G (rs1051266), and COMT 675G>A (rs4680) polymorphisms. All genotypes were entered into a linear regression model to determine significant predictors of negative symptoms, and risk scores were calculated based on total risk allele dose. Four variants, MTHFR 677T, MTR 2756A, FOLH1 484C, and COMT 675A, emerged as significant independent predictors of negative symptom severity, accounting for significantly greater variance in negative symptoms than MTHFR 677C>T alone. Total allele dose across the 4 variants predicted negative symptom severity only among patients with low folate levels. These findings indicate that multiple genetic variants within the folate metabolic pathway contribute to negative symptoms of schizophrenia. A relationship between folate level and negative symptom severity among patients with greater genetic vulnerability is biologically plausible and suggests the utility of folate supplementation in these patients.
Rzehak, Peter; Thijs, Carel; Standl, Marie; Mommers, Monique; Glaser, Claudia; Jansen, Eugène; Klopp, Norman; Koppelman, Gerard H.; Singmann, Paula; Postma, Dirkje S.; Sausenthaler, Stefanie; Dagnelie, Pieter C.; van den Brandt, Piet A.; Koletzko, Berthold; Heinrich, Joachim
2010-01-01
Background Association of genetic-variants in the FADS1-FADS2-gene-cluster with fatty-acid-composition in blood of adult-populations is well established. We analyze this genetic-association in two children-cohort-studies. In addition, the association between variants in the FADS-gene-cluster and blood-fatty-acid-composition with eczema was studied. Methods and Principal Findings Data of two population-based-birth-cohorts in the Netherlands and Germany (KOALA, LISA) were pooled (n = 879) and analyzed by (logistic) regression regarding the mutual influence of single-nucleotide-polymorphisms (SNPs) in the FADS-gene-cluster (rs174545, rs174546, rs174556, rs174561, rs3834458), on polyunsaturated fatty acids (PUFA) in blood and parent-reported eczema until the age of 2 years. All SNPs were highly significantly associated with all PUFAs except for alpha-linolenic-acid and eicosapentaenoic-acid, also after correction for multiple-testing. All tested SNPs showed associations with eczema in the LISA-study, but not in the KOALA-study. None of the PUFAs was significantly associated with eczema neither in the pooled nor in the analyses stratified by study-cohort. Conclusions and Significance PUFA-composition in young children's blood is under strong control of the FADS-gene-cluster. Inconsistent results were found for a link between these genetic-variants with eczema. PUFA in blood was not associated with eczema. Thus the hypothesis of an inflammatory-link between PUFA and eczema by the metabolic-pathway of LC-PUFAs as precursors for inflammatory prostaglandins and leukotrienes could not be confirmed by these data. PMID:20948998
Staphylococcus aureus innate immune evasion is lineage-specific: a bioinfomatics study.
McCarthy, Alex J; Lindsay, Jodi A
2013-10-01
Staphylococcus aureus is a major human pathogen, and is targeted by the host innate immune system. In response, S. aureus genomes encode dozens of secreted proteins that inhibit complement, chemotaxis and neutrophil activation resulting in successful evasion of innate immune responses. These proteins include immune evasion cluster proteins (IEC; Chp, Sak, Scn), staphylococcal superantigen-like proteins (SSLs), phenol soluble modulins (PSMs) and several leukocidins. Biochemical studies have indicated that genetic variants of these proteins can have unique functions. To ascertain the scale of genetic variation in secreted immune evasion proteins, whole genome sequences of 88 S. aureus isolates, representing 25 clonal complex (CC) lineages, in the public domain were analysed across 43 genes encoding 38 secreted innate immune evasion protein complexes. Twenty-three genes were variable, with between 2 and 15 variants, and the variants had lineage-specific distributions. They include genes encoding Eap, Ecb, Efb, Flipr/Flipr-like, Hla, Hld, Hlg, Sbi, Scin-B/C and 13 SSLs. Most of these protein complexes inhibit complement, chemotaxis and neutrophil activation suggesting that isolates from each S. aureus lineage respond to the innate immune system differently. In contrast, protein complexes that lyse neutrophils (LukSF-PVL, LukMF, LukED and PSMs) were highly conserved, but can be carried on mobile genetic elements (MGEs). MGEs also encode proteins with narrow host-specificities arguing that their acquisition has important roles in host/environmental adaptation. In conclusion, this data suggests that each lineage of S. aureus evades host immune responses differently, and that isolates can adapt to new host environments by acquiring MGEs and the immune evasion protein complexes that they encode. Cocktail therapeutics that targets multiple variant proteins may be the most appropriate strategy for controlling S. aureus infections. Copyright © 2013 Elsevier B.V. All rights reserved.
APOL1 Nephropathy: A Population Genetics and Evolutionary Medicine Detective Story.
Kruzel-Davila, Etty; Wasser, Walter G; Skorecki, Karl
2017-11-01
Common DNA sequence variants rarely have a high-risk association with a common disease. When such associations do occur, evolutionary forces must be sought, such as in the association of apolipoprotein L1 (APOL1) gene risk variants with nondiabetic kidney diseases in populations of African ancestry. The variants originated in West Africa and provided pathogenic resistance in the heterozygous state that led to high allele frequencies owing to an adaptive evolutionary selective sweep. However, the homozygous state is disadvantageous and is associated with a markedly increased risk of a spectrum of kidney diseases encompassing hypertension-attributed kidney disease, focal segmental glomerulosclerosis, human immunodeficiency virus nephropathy, sickle cell nephropathy, and progressive lupus nephritis. This scientific success story emerged with the help of the tools developed over the past 2 decades in human genome sequencing and population genomic databases. In this introductory article to a timely issue dedicated to illuminating progress in this area, we describe this unique population genetics and evolutionary medicine detective story. We emphasize the paradox of the inheritance mode, the missing heritability, and unresolved associations, including cardiovascular risk and diabetic nephropathy. We also highlight how genetic epidemiology elucidates mechanisms and how the principles of evolution can be used to unravel conserved pathways affected by APOL1 that may lead to novel therapies. The APOL1 gene provides a compelling example of a common variant association with common forms of nondiabetic kidney disease occurring in a continental population isolate with subsequent global admixture. Scientific collaboration using multiple experimental model systems and approaches should further clarify pathomechanisms further, leading to novel therapies. Copyright © 2017 Elsevier Inc. All rights reserved.
Fenton-May, Angharad E.; Dilernia, Dario A.; Kilembe, William; Allen, Susan A.; Borrow, Persephone; Hunter, Eric
2015-01-01
Heterosexual transmission of HIV-1 is characterized by a genetic bottleneck that selects a single viral variant, the transmitted/founder (TF), during most transmission events. To assess viral characteristics influencing HIV-1 transmission, we sequenced 167 near full-length viral genomes and generated 40 infectious molecular clones (IMC) including TF variants and multiple non-transmitted (NT) HIV-1 subtype C variants from six linked heterosexual transmission pairs near the time of transmission. Consensus-like genomes sensitive to donor antibodies were selected for during transmission in these six transmission pairs. However, TF variants did not demonstrate increased viral fitness in terms of particle infectivity or viral replicative capacity in activated peripheral blood mononuclear cells (PBMC) and monocyte-derived dendritic cells (MDDC). In addition, resistance of the TF variant to the antiviral effects of interferon-α (IFN-α) was not significantly different from that of non-transmitted variants from the same transmission pair. Thus neither in vitro viral replicative capacity nor IFN-α resistance discriminated the transmission potential of viruses in the quasispecies of these chronically infected individuals. However, our findings support the hypothesis that within-host evolution of HIV-1 in response to adaptive immune responses reduces viral transmission potential. PMID:26378795
Derived variants at six genes explain nearly half of size reduction in dog breeds.
Rimbault, Maud; Beale, Holly C; Schoenebeck, Jeffrey J; Hoopes, Barbara C; Allen, Jeremy J; Kilroy-Glynn, Paul; Wayne, Robert K; Sutter, Nathan B; Ostrander, Elaine A
2013-12-01
Selective breeding of dogs by humans has generated extraordinary diversity in body size. A number of multibreed analyses have been undertaken to identify the genetic basis of this diversity. We analyzed four loci discovered in a previous genome-wide association study that used 60,968 SNPs to identify size-associated genomic intervals, which were too large to assign causative roles to genes. First, we performed fine-mapping to define critical intervals that included the candidate genes GHR, HMGA2, SMAD2, and STC2, identifying five highly associated markers at the four loci. We hypothesize that three of the variants are likely to be causative. We then genotyped each marker, together with previously reported size-associated variants in the IGF1 and IGF1R genes, on a panel of 500 domestic dogs from 93 breeds, and identified the ancestral allele by genotyping the same markers on 30 wild canids. We observed that the derived alleles at all markers correlated with reduced body size, and smaller dogs are more likely to carry derived alleles at multiple markers. However, breeds are not generally fixed at all markers; multiple combinations of genotypes are found within most breeds. Finally, we show that 46%-52.5% of the variance in body size of dog breeds can be explained by seven markers in proximity to exceptional candidate genes. Among breeds with standard weights <41 kg (90 lb), the genotypes accounted for 64.3% of variance in weight. This work advances our understanding of mammalian growth by describing genetic contributions to canine size determination in non-giant dog breeds.
HFE gene variants, iron, and lipids: a novel connection in Alzheimer's disease.
Ali-Rahmani, Fatima; Schengrund, Cara-Lynne; Connor, James R
2014-01-01
Iron accumulation and associated oxidative stress in the brain have been consistently found in several neurodegenerative diseases. Multiple genetic studies have been undertaken to try to identify a cause of neurodegenerative diseases but direct connections have been rare. In the iron field, variants in the HFE gene that give rise to a protein involved in cellular iron regulation, are associated with iron accumulation in multiple organs including the brain. There is also substantial epidemiological, genetic, and molecular evidence of disruption of cholesterol homeostasis in several neurodegenerative diseases, in particular Alzheimer's disease (AD). Despite the efforts that have been made to identify factors that can trigger the pathological events associated with neurodegenerative diseases they remain mostly unknown. Because molecular phenotypes such as oxidative stress, synaptic failure, neuronal loss, and cognitive decline, characteristics associated with AD, have been shown to result from disruption of a number of pathways, one can easily argue that the phenotype seen may not arise from a linear sequence of events. Therefore, a multi-targeted approach is needed to understand a complex disorder like AD. This can be achieved only when knowledge about interactions between the different pathways and the potential influence of environmental factors on them becomes available. Toward this end, this review discusses what is known about the roles and interactions of iron and cholesterol in neurodegenerative diseases. It highlights the effects of gene variants of HFE (H63D- and C282Y-HFE) on iron and cholesterol metabolism and how they may contribute to understanding the etiology of complex neurodegenerative diseases.
HFE gene variants, iron, and lipids: a novel connection in Alzheimer’s disease
Ali-Rahmani, Fatima; Schengrund, Cara-Lynne; Connor, James R.
2014-01-01
Iron accumulation and associated oxidative stress in the brain have been consistently found in several neurodegenerative diseases. Multiple genetic studies have been undertaken to try to identify a cause of neurodegenerative diseases but direct connections have been rare. In the iron field, variants in the HFE gene that give rise to a protein involved in cellular iron regulation, are associated with iron accumulation in multiple organs including the brain. There is also substantial epidemiological, genetic, and molecular evidence of disruption of cholesterol homeostasis in several neurodegenerative diseases, in particular Alzheimer’s disease (AD). Despite the efforts that have been made to identify factors that can trigger the pathological events associated with neurodegenerative diseases they remain mostly unknown. Because molecular phenotypes such as oxidative stress, synaptic failure, neuronal loss, and cognitive decline, characteristics associated with AD, have been shown to result from disruption of a number of pathways, one can easily argue that the phenotype seen may not arise from a linear sequence of events. Therefore, a multi-targeted approach is needed to understand a complex disorder like AD. This can be achieved only when knowledge about interactions between the different pathways and the potential influence of environmental factors on them becomes available. Toward this end, this review discusses what is known about the roles and interactions of iron and cholesterol in neurodegenerative diseases. It highlights the effects of gene variants of HFE (H63D- and C282Y-HFE) on iron and cholesterol metabolism and how they may contribute to understanding the etiology of complex neurodegenerative diseases. PMID:25071582
Bone, William P.; Washington, Nicole L.; Buske, Orion J.; Adams, David R.; Davis, Joie; Draper, David; Flynn, Elise D.; Girdea, Marta; Godfrey, Rena; Golas, Gretchen; Groden, Catherine; Jacobsen, Julius; Köhler, Sebastian; Lee, Elizabeth M. J.; Links, Amanda E.; Markello, Thomas C.; Mungall, Christopher J.; Nehrebecky, Michele; Robinson, Peter N.; Sincan, Murat; Soldatos, Ariane G.; Tifft, Cynthia J.; Toro, Camilo; Trang, Heather; Valkanas, Elise; Vasilevsky, Nicole; Wahl, Colleen; Wolfe, Lynne A.; Boerkoel, Cornelius F.; Brudno, Michael; Haendel, Melissa A.; Gahl, William A.; Smedley, Damian
2016-01-01
Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Genet Med 18 6, 608–617. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein–protein association neighbors. Genet Med 18 6, 608–617. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Genet Med 18 6, 608–617. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders. Genet Med 18 6, 608–617. PMID:26562225
Genetic architecture for susceptibility to gout in the KARE cohort study.
Shin, Jimin; Kim, Younyoung; Kong, Minyoung; Lee, Chaeyoung
2012-06-01
This study aimed to identify functional associations of cis-regulatory regions with gout susceptibility using data resulted from a genome-wide association study (GWAS), and to show a genetic architecture for gout with interaction effects among genes within each of the identified functions. The GWAS was conducted with 8314 control subjects and 520 patients with gout in the Korea Association REsource cohort. However, genetic associations with any individual nucleotide variants were not discovered by Bonferroni multiple testing in the GWAS (P>1.42 × 10(-7)). Genomic regions enrichment analysis was employed to identify functional associations of cis-regulatory regions. This analysis revealed several biological processes associated with gout susceptibility, and they were quite different from those with serum uric acid level. Epistasis for susceptibility to gout was estimated using entropy decomposition with selected genes within each biological process identified by the genomic regions enrichment analysis. Some epistases among nucleotide sequence variants for gout susceptibility were found to be larger than their individual effects. This study provided the first evidence that genetic factors for gout susceptibility greatly differed from those for serum uric acid level, which may suggest that research endeavors for identifying genetic factors for gout susceptibility should not be heavily dependent on pathogenesis of uric acid. Interaction effects between genes should be examined to explain a large portion of phenotypic variability for gout susceptibility.
Dridi, M; Rosseel, T; Orton, R; Johnson, P; Lecollinet, S; Muylkens, B; Lambrecht, B; Van Borm, S
2015-10-01
West Nile virus (WNV) occurs as a population of genetic variants (quasispecies) infecting a single animal. Previous low-resolution viral genetic diversity estimates in sampled wild birds and mosquitoes, and in multiple-passage adaptation studies in vivo or in cell culture, suggest that WNV genetic diversification is mostly limited to the mosquito vector. This study investigated genetic diversification of WNV in avian hosts during a single passage using next-generation sequencing. Wild-captured carrion crows were subcutaneously infected using a clonal Middle-East WNV. Blood samples were collected 2 and 4 days post-infection. A reverse-transcription (RT)-PCR approach was used to amplify the WNV genome directly from serum samples prior to next-generation sequencing resulting in an average depth of at least 700 × in each sample. Appropriate controls were sequenced to discriminate biologically relevant low-frequency variants from experimentally introduced errors. The WNV populations in the wild crows showed significant diversification away from the inoculum virus quasispecies structure. By contrast, WNV populations in intracerebrally infected day-old chickens did not diversify from that of the inoculum. Where previous studies concluded that WNV genetic diversification is only experimentally demonstrated in its permissive insect vector species, we have experimentally shown significant diversification of WNV populations in a wild bird reservoir species.
Rioux Paquette, Sébastien; Talbot, Benoit; Garant, Dany; Mainguy, Julien; Pelletier, Fanie
2014-08-01
Predicting the geographic spread of wildlife epidemics requires knowledge about the movement patterns of disease hosts or vectors. The field of landscape genetics provides valuable approaches to study dispersal indirectly, which in turn may be used to understand patterns of disease spread. Here, we applied landscape genetic analyses and spatially explicit models to identify the potential path of raccoon rabies spread in a mesocarnivore community. We used relatedness estimates derived from microsatellite genotypes of raccoons and striped skunks to investigate their dispersal patterns in a heterogeneous landscape composed predominantly of agricultural, forested and residential areas. Samples were collected in an area covering 22 000 km(2) in southern Québec, where the raccoon rabies variant (RRV) was first detected in 2006. Multiple regressions on distance matrices revealed that genetic distance among male raccoons was strictly a function of geographic distance, while dispersal in female raccoons was significantly reduced by the presence of agricultural fields. In skunks, our results suggested that dispersal is increased in edge habitats between fields and forest fragments in both males and females. Resistance modelling allowed us to identify likely dispersal corridors used by these two rabies hosts, which may prove especially helpful for surveillance and control (e.g. oral vaccination) activities.
Association of Alzheimer's disease GWAS loci with MRI markers of brain aging.
Chauhan, Ganesh; Adams, Hieab H H; Bis, Joshua C; Weinstein, Galit; Yu, Lei; Töglhofer, Anna Maria; Smith, Albert Vernon; van der Lee, Sven J; Gottesman, Rebecca F; Thomson, Russell; Wang, Jing; Yang, Qiong; Niessen, Wiro J; Lopez, Oscar L; Becker, James T; Phan, Thanh G; Beare, Richard J; Arfanakis, Konstantinos; Fleischman, Debra; Vernooij, Meike W; Mazoyer, Bernard; Schmidt, Helena; Srikanth, Velandai; Knopman, David S; Jack, Clifford R; Amouyel, Philippe; Hofman, Albert; DeCarli, Charles; Tzourio, Christophe; van Duijn, Cornelia M; Bennett, David A; Schmidt, Reinhold; Longstreth, William T; Mosley, Thomas H; Fornage, Myriam; Launer, Lenore J; Seshadri, Sudha; Ikram, M Arfan; Debette, Stephanie
2015-04-01
Whether novel risk variants of Alzheimer's disease (AD) identified through genome-wide association studies also influence magnetic resonance imaging-based intermediate phenotypes of AD in the general population is unclear. We studied association of 24 AD risk loci with intracranial volume, total brain volume, hippocampal volume (HV), white matter hyperintensity burden, and brain infarcts in a meta-analysis of genetic association studies from large population-based samples (N = 8175-11,550). In single-SNP based tests, AD risk allele of APOE (rs2075650) was associated with smaller HV (p = 0.0054) and CD33 (rs3865444) with smaller intracranial volume (p = 0.0058). In gene-based tests, there was associations of HLA-DRB1 with total brain volume (p = 0.0006) and BIN1 with HV (p = 0.00089). A weighted AD genetic risk score was associated with smaller HV (beta ± SE = -0.047 ± 0.013, p = 0.00041), even after excluding the APOE locus (p = 0.029). However, only association of AD genetic risk score with HV, including APOE, was significant after multiple testing correction (including number of independent phenotypes tested). These results suggest that novel AD genetic risk variants may contribute to structural brain aging in nondemented older community persons. Copyright © 2015 Elsevier Inc. All rights reserved.
Huang, Xueqing; Ding, Jia; Effgen, Sigi; Turck, Franziska; Koornneef, Maarten
2013-08-01
Shoot branching is a major determinant of plant architecture. Genetic variants for reduced stem branching in the axils of cauline leaves of Arabidopsis were found in some natural accessions and also at low frequency in the progeny of multiparent crosses. Detailed genetic analysis using segregating populations derived from backcrosses with the parental lines and bulked segregant analysis was used to identify the allelic variation controlling reduced stem branching. Eight quantitative trait loci (QTLs) contributing to natural variation for reduced stem branching were identified (REDUCED STEM BRANCHING 1-8 (RSB1-8)). Genetic analysis showed that RSB6 and RSB7, corresponding to flowering time genes FLOWERING LOCUS C (FLC) and FRIGIDA (FRI), epistatically regulate stem branching. Furthermore, FLOWERING LOCUS T (FT), which corresponds to RSB8 as demonstrated by fine-mapping, transgenic complementation and expression analysis, caused pleiotropic effects not only on flowering time, but, in the specific background of active FRI and FLC alleles, also on the RSB trait. The consequence of allelic variation only expressed in late-flowering genotypes revealed novel and thus far unsuspected roles of several genes well characterized for their roles in flowering time control. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.
Genetic Relationships Between Schizophrenia, Bipolar Disorder, and Schizoaffective Disorder
Cardno, Alastair G.
2014-01-01
There is substantial evidence for partial overlap of genetic influences on schizophrenia and bipolar disorder, with family, twin, and adoption studies showing a genetic correlation between the disorders of around 0.6. Results of genome-wide association studies are consistent with commonly occurring genetic risk variants, contributing to both the shared and nonshared aspects, while studies of large, rare chromosomal structural variants, particularly copy number variants, show a stronger influence on schizophrenia than bipolar disorder to date. Schizoaffective disorder has been less investigated but shows substantial familial overlap with both schizophrenia and bipolar disorder. A twin analysis is consistent with genetic influences on schizoaffective episodes being entirely shared with genetic influences on schizophrenic and manic episodes, while association studies suggest the possibility of some relatively specific genetic influences on broadly defined schizoaffective disorder, bipolar subtype. Further insights into genetic relationships between these disorders are expected as studies continue to increase in sample size and in technical and analytical sophistication, information on phenotypes beyond clinical diagnoses are increasingly incorporated, and approaches such as next-generation sequencing identify additional types of genetic risk variant. PMID:24567502
Vail, Paris J; Morris, Brian; van Kan, Aric; Burdett, Brianna C; Moyes, Kelsey; Theisen, Aaron; Kerr, Iain D; Wenstrup, Richard J; Eggington, Julie M
2015-10-01
Genetic variants of uncertain clinical significance (VUSs) are a common outcome of clinical genetic testing. Locus-specific variant databases (LSDBs) have been established for numerous disease-associated genes as a research tool for the interpretation of genetic sequence variants to facilitate variant interpretation via aggregated data. If LSDBs are to be used for clinical practice, consistent and transparent criteria regarding the deposition and interpretation of variants are vital, as variant classifications are often used to make important and irreversible clinical decisions. In this study, we performed a retrospective analysis of 2017 consecutive BRCA1 and BRCA2 genetic variants identified from 24,650 consecutive patient samples referred to our laboratory to establish an unbiased dataset representative of the types of variants seen in the US patient population, submitted by clinicians and researchers for BRCA1 and BRCA2 testing. We compared the clinical classifications of these variants among five publicly accessible BRCA1 and BRCA2 variant databases: BIC, ClinVar, HGMD (paid version), LOVD, and the UMD databases. Our results show substantial disparity of variant classifications among publicly accessible databases. Furthermore, it appears that discrepant classifications are not the result of a single outlier but widespread disagreement among databases. This study also shows that databases sometimes favor a clinical classification when current best practice guidelines (ACMG/AMP/CAP) would suggest an uncertain classification. Although LSDBs have been well established for research applications, our results suggest several challenges preclude their wider use in clinical practice.
Tang, Haiming; Thomas, Paul D
2016-07-15
PANTHER-PSEP is a new software tool for predicting non-synonymous genetic variants that may play a causal role in human disease. Several previous variant pathogenicity prediction methods have been proposed that quantify evolutionary conservation among homologous proteins from different organisms. PANTHER-PSEP employs a related but distinct metric based on 'evolutionary preservation': homologous proteins are used to reconstruct the likely sequences of ancestral proteins at nodes in a phylogenetic tree, and the history of each amino acid can be traced back in time from its current state to estimate how long that state has been preserved in its ancestors. Here, we describe the PSEP tool, and assess its performance on standard benchmarks for distinguishing disease-associated from neutral variation in humans. On these benchmarks, PSEP outperforms not only previous tools that utilize evolutionary conservation, but also several highly used tools that include multiple other sources of information as well. For predicting pathogenic human variants, the trace back of course starts with a human 'reference' protein sequence, but the PSEP tool can also be applied to predicting deleterious or pathogenic variants in reference proteins from any of the ∼100 other species in the PANTHER database. PANTHER-PSEP is freely available on the web at http://pantherdb.org/tools/csnpScoreForm.jsp Users can also download the command-line based tool at ftp://ftp.pantherdb.org/cSNP_analysis/PSEP/ CONTACT: pdthomas@usc.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.
Xu, Wen; Sun, Jing; Wang, Wenbo; Wang, Xiran; Jiang, Yan; Huang, Wei; Zheng, Xin; Wang, Qiuping; Ning, Zhiwei; Pei, Yu; Nie, Min; Li, Mei; Wang, Ou; Xing, Xiaoping; Yu, Wei; Lin, Qiang; Xu, Ling; Xia, Weibo
2014-01-01
To determine if GC (group-specific component globulin) and CYP2R1 genetic variants have an association with serum 25-OHD3 levels, BMD or bone turnover markers in a population of Chinese postmenopausal women. We randomly selected 1494 postmenopausal women of the Han ethnic group from seven communities in Beijing. BMD was determined by dual energy X-ray absorptiometry; serum bone turnover markers and 25-OHD3 were measured by the automated Roche electrochemiluminescence system; genotypes of GC and CYP2R1 were detected by the TaqMan allelic discrimination assay. Multiple statistic methods were used to test the associations of SNP genotypes and vitamin D levels. In our sample, 89.6% women had vitamin D deficiency and another 9.8% had vitamin D insufficiency. The variants of rs2298849 (β=0.105, P<0.001) in GC were significantly associated with serum 25-OHD3 levels. Allele G of rs2298849 might be protective for serum 25-OHD3 level. Among the haplotypes of rs222020-rs2298849, CG (β=0.104, P=0.001) corresponded to increasing serum 25-OHD3 concentrations. CYP2R1 polymorphisms showed some significant association with serum β-CTX and P1NP levels. We found that GC variants had a significant association with serum 25-OHD3 levels among postmenopausal women of the Han ethnic group in Beijing, while CYP2R1 variants were not found to be significant.
Burnside, Elizabeth S.; Liu, Jie; Wu, Yirong; Onitilo, Adedayo A.; McCarty, Catherine; Page, C. David; Peissig, Peggy; Trentham-Dietz, Amy; Kitchner, Terrie; Fan, Jun; Yuan, Ming
2015-01-01
Rationale and Objectives The discovery of germline genetic variants associated with breast cancer has engendered interest in risk stratification for improved, targeted detection and diagnosis. However, there has yet to be a comparison of the predictive ability of these genetic variants with mammography abnormality descriptors. Materials and Methods Our IRB-approved, HIPAA-compliant study utilized a personalized medicine registry in which participants consented to provide a DNA sample and participate in longitudinal follow-up. In our retrospective, age-matched, case-controlled study of 373 cases and 395 controls who underwent breast biopsy, we collected risk factors selected a priori based on the literature including: demographic variables based on the Gail model, common germline genetic variants, and diagnostic mammography findings according to BI-RADS. We developed predictive models using logistic regression to determine the predictive ability of: 1) demographic variables, 2) 10 selected genetic variants, or 3) mammography BI-RADS features. We evaluated each model in turn by calculating a risk score for each patient using 10-fold cross validation; used this risk estimate to construct ROC curves; and compared the AUC of each using the DeLong method. Results The performance of the regression model using demographic risk factors was not statistically different from the model using genetic variants (p=0.9). The model using mammography features (AUC = 0.689) was superior to both the demographic model (AUC = .598; p<0.001) and the genetic model (AUC = .601; p<0.001). Conclusion BI-RADS features exceeded the ability of demographic and 10 selected germline genetic variants to predict breast cancer in women recommended for biopsy. PMID:26514439
Somatic Mosaicism: Implications for Disease and Transmission Genetics
Campbell, Ian M.; Shaw, Chad A.; Stankiewicz, Pawel; Lupski, James R.
2015-01-01
Nearly all of the genetic material among cells within an organism is identical. However, single nucleotide variants (SNVs), indels, copy number variants (CNVs), and other structural variants (SVs) continually accumulate as cells divide during development. This process results in an organism composed of countless cells, each with its own unique personal genome. Thus, every human is undoubtedly mosaic. Mosaic mutations can go unnoticed, underlie genetic disease or normal human variation, and may be transmitted to the next generation as constitutional variants. Here, we review the influence of the developmental timing of mutations, the mechanisms by which they arise, methods for detecting mosaic variants, and the risk of passing these mutations on to the next generation. PMID:25910407
Montalbano, Maria; Segreto, Roberta; Di Gerlando, Rosalia; Mastrangelo, Salvatore; Sardina, Maria Teresa
2016-02-01
The study was conducted to develop a high-performance liquid chromatographic (HPLC) method to quantify casein genetic variants (αs2-, β-, and κ-casein) in milk of homozygous individuals of Girgentana goat breed. For calibration experiments, pure genetic variants were extracted from individual milk samples of animals with known genotypes. The described HPLC approach was precise, accurate and highly suitable for quantification of goat casein genetic variants of homozygous individuals. The amount of each casein per allele was: αs2-casein A = 2.9 ± 0.8 g/L and F = 1.8 ± 0.4 g/L; β-casein C = 3.0 ± 0.8 g/L and C1 = 2.0 ± 0.7 g/L and κ-casein A = 1.6 ± 0.3 g/L and B = 1.1 ± 0.2 g/L. A good correlation was found between the quantities of αs2-casein genetic variants A and F, and β-casein C and C1 with other previously described method. The main important result was obtained for κ-casein because, till now, no data were available on quantification of single genetic variants for this protein. Copyright © 2015 Elsevier Ltd. All rights reserved.
Kallianpur, Asha R.; Jia, Peilin; Ellis, Ronald J.; Zhao, Zhongming; Bloss, Cinnamon; Wen, Wanqing; Marra, Christina M.; Hulgan, Todd; Simpson, David M.; Morgello, Susan; McArthur, Justin C.; Clifford, David B.; Collier, Ann C.; Gelman, Benjamin B.; McCutchan, J. Allen; Franklin, Donald; Samuels, David C.; Rosario, Debralee; Holzinger, Emily; Murdock, Deborah G.; Letendre, Scott; Grant, Igor
2014-01-01
HIV sensory neuropathy and distal neuropathic pain (DNP) are common, disabling complications associated with combination antiretroviral therapy (cART). We previously associated iron-regulatory genetic polymorphisms with a reduced risk of HIV sensory neuropathy during more neurotoxic types of cART. We here evaluated the impact of polymorphisms in 19 iron-regulatory genes on DNP in 560 HIV-infected subjects from a prospective, observational study, who underwent neurological examinations to ascertain peripheral neuropathy and structured interviews to ascertain DNP. Genotype-DNP associations were explored by logistic regression and permutation-based analytical methods. Among 559 evaluable subjects, 331 (59%) developed HIV-SN, and 168 (30%) reported DNP. Fifteen polymorphisms in 8 genes (p<0.05) and 5 variants in 4 genes (p<0.01) were nominally associated with DNP: polymorphisms in TF, TFRC, BMP6, ACO1, SLC11A2, and FXN conferred reduced risk (adjusted odds ratios [ORs] ranging from 0.2 to 0.7, all p<0.05); other variants in TF, CP, ACO1, BMP6, and B2M conferred increased risk (ORs ranging from 1.3 to 3.1, all p<0.05). Risks associated with some variants were statistically significant either in black or white subgroups but were consistent in direction. ACO1 rs2026739 remained significantly associated with DNP in whites (permutation p<0.0001) after correction for multiple tests. Several of the same iron-regulatory-gene polymorphisms, including ACO1 rs2026739, were also associated with severity of DNP (all p<0.05). Common polymorphisms in iron-management genes are associated with DNP and with DNP severity in HIV-infected persons receiving cART. Consistent risk estimates across population subgroups and persistence of the ACO1 rs2026739 association after adjustment for multiple testing suggest that genetic variation in iron-regulation and transport modulates susceptibility to DNP. PMID:25144566
Wang, Xueling; Lin, Xiao-Jiang; Tang, Xiangrong; Chai, Yong-Chuan; Yu, De-Hong; Chen, Dong-Ye; Wu, Hao
2017-11-01
The purpose of this study was to identify the genetic causes of a family presenting with multiple symptoms overlapping Usher syndrome type II (USH2) and Waardenburg syndrome type IV (WS4). Targeted next-generation sequencing including the exon and flanking intron sequences of 79 deafness genes was performed on the proband. Co-segregation of the disease phenotype and the detected variants were confirmed in all family members by PCR amplification and Sanger sequencing. The affected members of this family had two different recessive disorders, USH2 and WS4. By targeted next-generation sequencing, we identified that USH2 was caused by a novel missense mutation, p.V4907D in GPR98; whereas WS4 due to p.V185M in EDNRB. This is the first report of homozygous p.V185M mutation in EDNRB in patient with WS4. This study reported a Chinese family with multiple independent and overlapping phenotypes. In condition, molecular level analysis was efficient to identify the causative variant p.V4907D in GPR98 and p.V185M in EDNRB, also was helpful to confirm the clinical diagnosis of USH2 and WS4. Copyright © 2017 Elsevier B.V. All rights reserved.
Barbato, Ersilia; Traversa, Alice; Guarnieri, Rosanna; Giovannetti, Agnese; Genovesi, Maria Luce; Magliozzi, Maria Rosa; Paolacci, Stefano; Ciolfi, Andrea; Pizzi, Simone; Di Giorgio, Roberto; Tartaglia, Marco; Pizzuti, Antonio; Caputo, Viviana
2018-07-01
The aim of this study was the clinical and molecular characterization of a family segregating a trait consisting of a phenotype specifically involving the maxillary canines, including agenesis, impaction and ectopic eruption, characterized by incomplete penetrance and variable expressivity. Clinical standardized assessment of 14 family members and a whole-exome sequencing (WES) of three affected subjects were performed. WES data analyses (sequence alignment, variant calling, annotation and prioritization) were carried out using an in-house implemented pipeline. Variant filtering retained coding and splice-site high quality private and rare variants. Variant prioritization was performed taking into account both the disruptive impact and the biological relevance of individual variants and genes. Sanger sequencing was performed to validate the variants of interest and to carry out segregation analysis. Prioritization of variants "by function" allowed the identification of multiple variants contributing to the trait, including two concomitant heterozygous variants in EDARADD (c.308C>T, p.Ser103Phe) and COL5A1 (c.1588G>A, p.Gly530Ser), specifically associated with a more severe phenotype (i.e. canine agenesis). Differently, heterozygous variants in genes encoding proteins with a role in the WNT pathway were shared by subjects showing a phenotype of impacted/ectopic erupted canines. This study characterized the genetic contribution underlying a complex trait consisting of isolated canine anomalies in a medium-sized family, highlighting the role of WNT and EDA cell signaling pathways in tooth development. Copyright © 2018 Elsevier Ltd. All rights reserved.
Casas-Agustench, Patricia; Arnett, Donna K.; Smith, Caren E.; Lai, Chao-Qiang; Parnell, Laurence D.; Borecki, Ingrid B.; Frazier-Wood, Alexis C.; Allison, Matthew; Chen, Yii-Der Ida; Taylor, Kent D.; Rich, Stephen S.; Rotter, Jerome I.; Lee, Yu-Chi; Ordovás, José M.
2014-01-01
Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and BMI in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake and to replicate findings in Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 US Caucasian participants from GOLDN and 2035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although to determine the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. PMID:24794412
Derrien, Thomas; Axelsson, Erik; Rosengren Pielberg, Gerli; Sigurdsson, Snaevar; Fall, Tove; Seppälä, Eija H.; Hansen, Mark S. T.; Lawley, Cindy T.; Karlsson, Elinor K.; Bannasch, Danika; Vilà, Carles; Lohi, Hannes; Galibert, Francis; Fredholm, Merete; Häggström, Jens; Hedhammar, Åke; André, Catherine; Lindblad-Toh, Kerstin; Hitte, Christophe; Webster, Matthew T.
2011-01-01
The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease. PMID:22022279
Vaysse, Amaury; Ratnakumar, Abhirami; Derrien, Thomas; Axelsson, Erik; Rosengren Pielberg, Gerli; Sigurdsson, Snaevar; Fall, Tove; Seppälä, Eija H; Hansen, Mark S T; Lawley, Cindy T; Karlsson, Elinor K; Bannasch, Danika; Vilà, Carles; Lohi, Hannes; Galibert, Francis; Fredholm, Merete; Häggström, Jens; Hedhammar, Ake; André, Catherine; Lindblad-Toh, Kerstin; Hitte, Christophe; Webster, Matthew T
2011-10-01
The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.
DNA repair pathways underlie a common genetic mechanism modulating onset in polyglutamine diseases
Bettencourt, Conceição; Hensman‐Moss, Davina; Flower, Michael; Wiethoff, Sarah; Brice, Alexis; Goizet, Cyril; Stevanin, Giovanni; Koutsis, Georgios; Karadima, Georgia; Panas, Marios; Yescas‐Gómez, Petra; García‐Velázquez, Lizbeth Esmeralda; Alonso‐Vilatela, María Elisa; Lima, Manuela; Raposo, Mafalda; Traynor, Bryan; Sweeney, Mary; Wood, Nicholas; Giunti, Paola; Durr, Alexandra; Holmans, Peter; Houlden, Henry; Tabrizi, Sarah J.
2016-01-01
Objective The polyglutamine diseases, including Huntington's disease (HD) and multiple spinocerebellar ataxias (SCAs), are among the commonest hereditary neurodegenerative diseases. They are caused by expanded CAG tracts, encoding glutamine, in different genes. Longer CAG repeat tracts are associated with earlier ages at onset, but this does not account for all of the difference, and the existence of additional genetic modifying factors has been suggested in these diseases. A recent genome‐wide association study (GWAS) in HD found association between age at onset and genetic variants in DNA repair pathways, and we therefore tested whether the modifying effects of variants in DNA repair genes have wider effects in the polyglutamine diseases. Methods We assembled an independent cohort of 1,462 subjects with HD and polyglutamine SCAs, and genotyped single‐nucleotide polymorphisms (SNPs) selected from the most significant hits in the HD study. Results In the analysis of DNA repair genes as a group, we found the most significant association with age at onset when grouping all polyglutamine diseases (HD+SCAs; p = 1.43 × 10–5). In individual SNP analysis, we found significant associations for rs3512 in FAN1 with HD+SCAs (p = 1.52 × 10–5) and all SCAs (p = 2.22 × 10–4) and rs1805323 in PMS2 with HD+SCAs (p = 3.14 × 10–5), all in the same direction as in the HD GWAS. Interpretation We show that DNA repair genes significantly modify age at onset in HD and SCAs, suggesting a common pathogenic mechanism, which could operate through the observed somatic expansion of repeats that can be modulated by genetic manipulation of DNA repair in disease models. This offers novel therapeutic opportunities in multiple diseases. Ann Neurol 2016;79:983–990 PMID:27044000
Copy number variants are frequent in genetic generalized epilepsy with intellectual disability
Mullen, Saul A.; Carvill, Gemma L.; Bellows, Susannah; Bayly, Marta A.; Berkovic, Samuel F.; Dibbens, Leanne M.
2013-01-01
Objective: We examined whether copy number variants (CNVs) were more common in those with a combination of intellectual disability (ID) and genetic generalized epilepsy (GGE) than in those with either phenotype alone via a case-control study. Methods: CNVs contribute to the genetics of multiple neurodevelopmental disorders with complex inheritance, including GGE and ID. Three hundred fifty-nine probands with GGE and 60 probands with ID-GGE were screened for GGE-associated recurrent microdeletions at 15q13.3, 15q11.2, and 16p13.11 via quantitative PCR or loss of heterozygosity. Deletions were confirmed by comparative genomic hybridization (CGH). ID-GGE probands also had genome-wide CGH. Results: ID-GGE probands showed a significantly higher rate of CNVs compared with probands with GGE alone, with 17 of 60 (28%) ID-GGE probands having one or more potentially causative CNVs. The patients with ID-GGE had a 3-fold-higher rate of the 3 GGE-associated recurrent microdeletions than probands with GGE alone (10% vs 3%, p = 0.02). They also showed a high rate (13/60, 22%) of rare CNVs identified using genome-wide CGH. Conclusions: This study shows that CNVs are common in those with ID-GGE with recurrent deletions at 15q13.3, 15q11.2, and 16p13.11, particularly enriched compared with individuals with GGE or ID alone. Recurrent CNVs are likely to act as risk factors for multiple phenotypes not just at the population level, but also in any given individual. Testing for CNVs in ID-GGE will have a high diagnostic yield in a clinical setting and will inform genetic counseling. PMID:24068782
Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G; Tybjaerg-Hansen, Anne; Sing, Charles F
2009-05-01
This article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515-527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2,258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors.