scholarly journals Meta-analysis of genome-wide association studies for height and body mass index in ∼700,000 individuals of European ancestry

2018 ◽  
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 ◽  
Summary Statistics ◽  
Genome Wide ◽  
Independent Snps

Genome-wide association studies (GWAS) stand as powerful experimental designs for identifying DNA variants associated with complex traits and diseases. In the past decade, both the number of such studies and their sample sizes have increased dramatically. Recent GWAS of height and body mass index (BMI) in ∼250,000 European participants have led to the discovery of ∼700 and ∼100 nearly independent SNPs associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in ∼450,000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N∼700,000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3,290 and 716 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of p<1 × 10−8), including 1,185 height-associated SNPs and 554 BMI-associated SNPs located within loci not previously identified by these two GWAS. The genome-wide significant SNPs explain ∼24.6% of the variance of height and ∼5% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were 0.44 and 0.20, respectively. From analyses of integrating GWAS and eQTL data by Summary-data based Mendelian Randomization (SMR), we identified an enrichment of eQTLs amongst lead height and BMI signals, prioritisting 684 and 134 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow up studies.

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

A novel locus for body mass index on 5p15.2: A meta-analysis of two genome-wide association studies

Gene ◽  
2012 ◽  
Vol 500 (1) ◽  
pp. 80-84 ◽  
Author(s):  
Ke-Sheng Wang ◽  
Xuefeng Liu ◽  
Shimin Zheng ◽  
Min Zeng ◽  
Yue Pan ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

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.

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 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.

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.

Sign in / Sign up

Export Citation Format

Share Document