Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
James S Floyd ◽  
Colleen Sitlani ◽  
Christy L Avery ◽  
Eric A Whitsel ◽  
Leslie Lange ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Qt Interval ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Meta Analyses

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

scholarly journals Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry

2018 ◽  
Vol 28 (1) ◽  
pp. 166-174 ◽  
Author(s):  
Sara L Pulit ◽  
Charli Stoneman ◽  
Andrew P Morris ◽  
Andrew R Wood ◽  
Craig A Glastonbury ◽  
...  
Keyword(s):  
Body Fat ◽  
Association Studies ◽  
Meta Analysis ◽  
Fat Distribution ◽  
Body Fat Distribution ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

Abstract More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

scholarly journals Identification of type 2 diabetes loci in 433,540 East Asian individuals

2019 ◽  
Author(s):  
Cassandra N Spracklen ◽  
Momoko Horikoshi ◽  
Young Jin Kim ◽  
Kuang Lin ◽  
Fiona Bragg ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Association Studies ◽  
Meta Analysis ◽  
East Asian ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
European Populations

SUMMARYMeta-analyses of genome-wide association studies (GWAS) have identified >240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals in/near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.Type 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production and/or secretion by the pancreatic β cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified >240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.

scholarly journals Genome-wide association studies for canine hip dysplasia in single and multiple populations – implications and potential novel risk loci

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shizhi Wang ◽  
Erling Strandberg ◽  
Per Arvelius ◽  
Dylan N. Clements ◽  
Pamela Wiener ◽  
...  
Keyword(s):  
Hip Dysplasia ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Single Population ◽  
Positional Candidate ◽  
Genome Wide ◽  
Canine Hip Dysplasia

Abstract Background Association mapping studies of quantitative trait loci (QTL) for canine hip dysplasia (CHD) can contribute to the understanding of the genetic background of this common and debilitating disease and might contribute to its genetic improvement. The power of association studies for CHD is limited by relatively small sample numbers for CHD records within countries, suggesting potential benefits of joining data across countries. However, this is complicated due to the use of different scoring systems across countries. In this study, we incorporated routinely assessed CHD records and genotype data of German Shepherd dogs from two countries (UK and Sweden) to perform genome-wide association studies (GWAS) within populations using different variations of CHD phenotypes. As phenotypes, dogs were either classified into cases and controls based on the Fédération Cynologique Internationale (FCI) five-level grading of the worst hip or the FCI grade was treated as an ordinal trait. In a subsequent meta-analysis, we added publicly available data from a Finnish population and performed the GWAS across all populations. Genetic associations for the CHD phenotypes were evaluated in a linear mixed model using 62,089 SNPs. Results Multiple SNPs with genome-wide significant and suggestive associations were detected in single-population GWAS and the meta-analysis. Few of these SNPs overlapped between populations or between single-population GWAS and the meta-analysis, suggesting that many CHD-related QTL are population-specific. More significant or suggestive SNPs were identified when FCI grades were used as phenotypes in comparison to the case-control approach. MED13 (Chr 9) and PLEKHA7 (Chr 21) emerged as novel positional candidate genes associated with hip dysplasia. Conclusions Our findings confirm the complex genetic nature of hip dysplasia in dogs, with multiple loci associated with the trait, most of which are population-specific. Routinely assessed CHD information collected across countries provide an opportunity to increase sample sizes and statistical power for association studies. While the lack of standardisation of CHD assessment schemes across countries poses a challenge, we showed that conversion of traits can be utilised to overcome this obstacle.

scholarly journals Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry

2018 ◽  
Vol 27 (20) ◽  
pp. 3641-3649 ◽  
Author(s):  
Loic Yengo ◽  
Julia Sidorenko ◽  
Kathryn E Kemper ◽  
Zhili Zheng ◽  
Andrew R Wood ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract 56: Genome-wide Association Studies of Incident Stroke: The Charge Consortium

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Stephanie Debette ◽  
Ganesh Chauhan ◽  
Audrey Chu ◽  
Myriam Fornage ◽  
Josh C Bis ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Acute Stage ◽  
Genome Wide Association ◽  
Population Substructure ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Large Artery ◽  
Aging Research ◽  
Genome Wide

Background: Despite a high heritability, only few stroke risk genes are known. Genetic association studies performed in a hospital-based setting may fail to detect genes modulating both stroke susceptibility and severity, given early deaths at the acute stage. This selection bias is avoided when studying incident stroke in a population-based setting. Methods: We conducted a meta-analysis of genome-wide association studies of incident stroke in 11 community-based longitudinal studies from the Cohorts of Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Genome-wide Cox regressions were performed adjusting for age, gender and population substructure, using 1000GpIv3 imputed genotypes. Results were combined using inverse variance weighted meta-analysis. Results: The study sample comprised 65,204 participants (71.5% women) of European ancestry, aged 66.2±8.0 years at DNA draw, followed up for 10.8±3.8 years. In 11 studies, 3,389 participants developed incident stroke, and in 8 studies, 2,223 developed incident ischemic stroke (IS): 531 cardioembolic [CE] and 1,576 atherothrombotic [AT]. The most significant association with incident stroke was for a novel variant on chr9p23 (MAF=0.35), HR=1.15 [95%CI:1.09[[Unable to Display Character: &#8210;]]1.21], p=8.5х10-8: p=2.54x10-5 for IS; 1.19x10-4, AT-IS; and 0.019, CE-IS. Associations were in the same direction for all participating studies, and 5 additional SNPs in this locus reached p<10-6. The most significant association with incident IS was for rs11833579 [NINJ2], HR=1.21[1.13[[Unable to Display Character: &#8210;]]1.30], p=2.1х10-7, but p-random-effects=9.54x10-3 (p-heterogeneity=0.02, I2=57.9%). We replicated published associations for CE-IS (rs6843082-G [PITX2], HR=1.30[1.13-1.49], p=1.95x10-4) and for large artery stroke with AT-IS (rs2107595-A [HDAC9], HR=1.13[1.03[[Unable to Display Character: &#8210;]]1.24], p=0.012) Conclusion: In the largest GWAS of incident stroke, we detected one novel association with all stroke, requiring confirmation in independent samples. Expansion of the discovery sample and replication of findings are planned in the coming months. Detecting genetic variants associated with incident stroke may provide important clues for understanding pathways involved in stroke susceptibility and tolerance to acute vascular brain injury.

scholarly journals A meta-analysis of genome-wide association studies of asthma in Puerto Ricans

2017 ◽  
Vol 49 (5) ◽  
pp. 1601505 ◽  
Author(s):  
Qi Yan ◽  
John Brehm ◽  
Maria Pino-Yanes ◽  
Erick Forno ◽  
Jerome Lin ◽  
...  
Keyword(s):  
Puerto Ricans ◽  
Association Studies ◽  
Meta Analysis ◽  
Linkage Disequilibrium Block ◽  
Genome Wide Association ◽  
Health Study ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
The Usa ◽  
Meta Analyses

Puerto Ricans are disproportionately affected with asthma in the USA. In this study, we aim to identify genetic variants that confer susceptibility to asthma in Puerto Ricans.We conducted a meta-analysis of genome-wide association studies (GWAS) of asthma in Puerto Ricans, including participants from: the Genetics of Asthma in Latino Americans (GALA) I-II, the Hartford–Puerto Rico Study and the Hispanic Community Health Study. Moreover, we examined whether susceptibility loci identified in previous meta-analyses of GWAS are associated with asthma in Puerto Ricans.The only locus to achieve genome-wide significance was chromosome 17q21, as evidenced by our top single nucleotide polymorphism (SNP), rs907092 (OR 0.71, p=1.2×10−12) at IKZF3. Similar to results in non-Puerto Ricans, SNPs in genes in the same linkage disequilibrium block as IKZF3 (e.g. ZPBP2, ORMDL3 and GSDMB) were significantly associated with asthma in Puerto Ricans. With regard to results from a meta-analysis in Europeans, we replicated findings for rs2305480 at GSDMB, but not for SNPs in any other genes. On the other hand, we replicated results from a meta-analysis of North American populations for SNPs at IL1RL1, TSLP and GSDMB but not for IL33.Our findings suggest that common variants on chromosome 17q21 have the greatest effects on asthma in Puerto Ricans.

scholarly journals Genome-Wide Association between the 2q33.1 Locus and Intracranial Aneurysm Susceptibility: An Updated Meta-Analysis Including 18,019 Individuals

2019 ◽  
Vol 8 (5) ◽  
pp. 692
Author(s):  
Eun Pyo Hong ◽  
Bong Jun Kim ◽  
Jin Pyeong Jeon
Keyword(s):  
Intracranial Aneurysm ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Eqtl Analysis ◽  
Genome Wide Association Studies ◽  
Human Tissues ◽  
Genome Wide ◽  
A Genome

Previous genome-wide association studies did not show a consistent association between the BOLL gene (rs700651, 2q33.1) and intracranial aneurysm (IA) susceptibility. We aimed to perform an updated meta-analysis for the potential IA-susceptibility locus in large-scale multi-ethnic populations. We conducted a systematic review of studies identified by an electronic search from January 1990 to March 2019. The overall estimates of the “G” allele of rs700651, indicating IA susceptibility, were calculated under the fixed- and random-effect models using the inverse-variance method. Subsequent in silico function and cis-expression quantitative trait loci (cis-eQTL) analyses were performed to evaluate biological functions and genotype-specific expressions in human tissues. We included 4513 IA patients and 13,506 controls from five studies with seven independent populations: three European-ancestry, three Japanese, and one Korean population. The overall result showed a genome-wide significance threshold between rs700651 and IA susceptibility after controlling for study heterogeneity (OR = 1.213, 95% CI: 1.135–1.296). Subsequent cis-eQTL analysis showed significant genome-wide expressions in three human tissues, i.e., testis (p = 8.04 × 10−15 for ANKRD44), tibial nerves (p = 3.18 × 10−10 for SF3B1), and thyroid glands (p = 4.61 × 10−9 for SF3B1). The rs700651 common variant of the 2q33.1 region may be involved in genetic mechanisms that increase the risk of IA and may play crucial roles in regulatory functions.

scholarly journals Genome-wide association meta-analysis of cocaine dependence: Shared genetics with comorbid conditions

2018 ◽  
Author(s):  
Judit Cabana-Domínguez ◽  
Anu Shivalikanjli ◽  
Noèlia Fernàndez-Castillo ◽  
Bru Cormand
Keyword(s):  
Risk Taking ◽  
Association Studies ◽  
Meta Analysis ◽  
Cocaine Dependence ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Comorbid Conditions ◽  
Genome Wide

AbstractCocaine dependence is a complex psychiatric disorder that is highly comorbid with other psychiatric traits. Twin and adoption studies suggest that genetic variants contribute substantially to cocaine dependence susceptibility, which has an estimated heritability of 65-79%. Here we performed a meta-analysis of genome-wide association studies of cocaine dependence using four datasets from the dbGaP repository (2,085 cases and 4,293 controls, all of them selected by their European ancestry). Although no genome-wide significant hits were found in the SNP-based analysis, the gene-based analysis identified HIST1H2BD as associated with cocaine-dependence (10% FDR). This gene is located in a region on chromosome 6 enriched in histone-related genes, previously associated with schizophrenia (SCZ). Furthermore, we performed LD Score regression analysis with comorbid conditions and found significant genetic correlations between cocaine dependence and SCZ, ADHD, major depressive disorder (MDD) and risk taking. We also found, through polygenic risk score analysis, that all tested phenotypes can significantly predict cocaine dependence status: SCZ (R2=2.28%; P=1.21e-26), ADHD (R2=1.39%; P=4.5e-17), risk taking (R2=0.60%; P=2.7e-08), MDD (R2=1.21%; P=4.35e-15), children’s aggressiveness (R2=0.3%; P=8.8e-05) and antisocial behavior (R2=1.33%; P=2.2e-16). To our knowledge, this is the largest reported cocaine dependence GWAS meta-analysis in European-ancestry individuals. We identified suggestive associations in regions that may be related to cocaine dependence and found evidence for shared genetic risk factors between cocaine dependence and several comorbid psychiatric traits. However, the sample size is limited and further studies are needed to confirm these results.

scholarly journals Caring without sharing: Meta-analysis 2.0 for massive genome-wide association studies

2018 ◽  
Author(s):  
Armin Pourshafeie ◽  
Carlos D. Bustamante ◽  
Snehit Prabhu
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Large Sample Size ◽  
Genome Wide Association Studies ◽  
Raw Data ◽  
Structure Control ◽  
Genome Wide ◽  
Sufficient Power ◽  
Meta Analyses

AbstractGenome-wide association studies have been effective at revealing the genetic architecture of simple traits. Extending this approach to more complex phenotypes has necessitated a massive increase in cohort size. To achieve sufficient power, participants are recruited across multiple collaborating institutions, leaving researchers with two choices: either collect all the raw data at a single institution or rely on meta-analyses to test for association. In this work, we present a third alternative. Here, we implement an entire GWAS workflow (quality control, population structure control, and association) in a fully decentralized setting. Our iterative approach (a) does not rely on consolidating the raw data at a single coordination center, and (b) does not hinge upon large sample size assumptions at each silo. As we show, our approach overcomes challenges faced by meta-studies when it comes to associating rare alleles and when case/control proportions are wildly imbalanced at each silo. We demonstrate the feasibility of our method in cohorts ranging in size from 2K (small) to 500K (large), and recruited across 2 to 10 collaborating institutions.

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