Abstract 050: Meta-analysis of Genetic Associations in up to 339,224 Individuals Identify 66 New Loci for Bmi, Confirming a Neuronal Contribution to Body Weight Regulation and Implicating Several Novel Pathways

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Anne Justice ◽  
Kari North ◽  
Ruth Loos ◽  
Sailaja Vedantam ◽  
Felix Day ◽  
...  
Keyword(s):  
Risk Factors ◽  
Fixed Effects ◽  
Association Studies ◽  
Meta Analysis ◽  
European Ancestry ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Genome Wide

Obesity is a rising global concern as it substantially contributes to cardiovascular disease (CVD) and CVD risk factors (e.g. insulin resistance, dyslipidemia, Type 2 Diabetes). BMI (body mass index) is an easily obtained measure of obesity, which is highly heritable, and often used as a proxy when searching for genetic risk factors. Previous analyses of genome-wide association studies (GWAS) in the GIANT (Genetic Investigation of ANthropometric Traits) Consortium identified 32 loci containing common variants associated with BMI in adults of European ancestry. To enhance discovery of common causal variants for BMI, GIANT has expanded to include 82 studies with GWAS data and 43 studies with Metabochip data in more ancestrally diverse populations including up to 339,224 individuals. We performed a meta-analysis of the study-specific summary statistics for the BMI associations, assuming an additive model and using a fixed-effects inverse variance method. SNPs in 97 loci reached genome-wide significance (P<10-8), of which 31 loci had previously been identified for BMI in European-descent samples. Of the 66 novel BMI loci, three had previously been identified for association with adiposity related traits in specific populations. Many of the 97 loci contain strong biological candidates, and multiple methods were employed to pinpoint the most likely candidate gene(s) within the main signal regions. In addition to manual curation, GRAIL, and MAGENTA, we also employed a newly developed, unbiased computational approach that integrates a variety of data types (i.e. tissue-specific gene expression data, phenotypic information from mouse knockout studies, etc.) to identify potentially causal genes and pathways. Consistent with previous findings, many of these BMI loci contain genes that have a potential neuronal role in regulating appetite (e.g. MC4R, POMC, GRID1, NAV1 ). Our analyses also highlight loci with genes in pathways that were previously less apparent, such as those related to glucose and insulin homeostasis ( TCF7L2 , GIPR ), lipid metabolism ( APOE -cluster, NPC1 , NR1H3 ), the immune system ( TLR4) , and others. Additionally, many of the newly associated variants are in high LD with previously identified SNPs associated with related phenotypes, including other CVD risk factors (e.g. SNPs nearby IRS1 associated with T2D, adiposity, HDL, TG, adiponectin levels, and CHD; and SNPs near NT5C2 associated with CHD and blood pressure variables). This large-scale meta-analysis has greatly increased the number of identified obesity-susceptibility loci and continues to contribute to our understanding of the complex biology of adiposity. Our results have highlighted overlapping GWAS signals and important pathways which connect BMI and other CVD risk factors supporting the importance of pleiotropic effects in the pathogenesis of common complex diseases.

scholarly journals Genome-Wide Meta-Analysis Validates a Role for S1PR1 in Microtubule Targeting Agent-Induced Sensory Peripheral Neuropathy

2020 ◽  
Author(s):  
Katherina C. Chua ◽  
Chenling Xiong ◽  
Carol Ho ◽  
Taisei Mushiroda ◽  
Chen Jiang ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Association Studies ◽  
Meta Analysis ◽  
Regulatory Elements ◽  
Hazard Ratio ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Sensory Peripheral Neuropathy ◽  
Genome Wide ◽  
Microtubule Targeting Agents

AbstractMicrotubule targeting agents (MTAs) are anticancer therapies commonly prescribed for breast cancer and other solid tumors. Sensory peripheral neuropathy (PN) is the major dose-limiting toxicity for MTAs and can limit clinical efficacy. The current pharmacogenomic study aimed to identify genetic variations that explain patient susceptibility and drive mechanisms underlying development of MTA-induced PN. A meta-analysis of genome-wide association studies (GWAS) from two clinical cohorts treated with MTAs (CALGB 40502 and CALGB 40101) was conducted using a Cox regression model with cumulative dose to first instance of grade 2 or higher PN. Summary statistics from a GWAS of European subjects (n = 469) in CALGB 40502 that estimated cause-specific risk of PN were meta-analyzed with those from a previously published GWAS of European ancestry (n = 855) from CALGB 40101 that estimated the risk of PN. Novel single nucleotide polymorphisms in an enhancer region downstream of sphingosine-1-phosphate receptor 1 (S1PR1 encoding S1PR1; e.g., rs74497159, βCALGB40101 per allele log hazard ratio (95% CI) = 0.591 (0.254 - 0.928), βCALGB40502 per allele log hazard ratio (95% CI) = 0.693 (0.334 - 1.053); PMETA = 3.62×10−7) were the most highly ranked associations based on P-values with risk of developing grade 2 and higher PN. In silico functional analysis identified multiple regulatory elements and potential enhancer activity for S1PR1 within this genomic region. Inhibition of S1PR1 function in iPSC-derived human sensory neurons shows partial protection against paclitaxel-induced neurite damage. These pharmacogenetic findings further support ongoing clinical evaluations to target S1PR1 as a therapeutic strategy for prevention and/or treatment of MTA-induced neuropathy.

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.

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 Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: a genome–wide interaction study

2013 ◽  
Vol 20 (6) ◽  
pp. 875-887 ◽  
Author(s):  
Anja Rudolph ◽  
Rebecca Hein ◽  
Sara Lindström ◽  
Lars Beckmann ◽  
Sabine Behrens ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Fixed Effects ◽  
Association Studies ◽  
Meta Analysis ◽  
Case Control ◽  
Genome Wide Association Studies ◽  
Genetic Modifiers ◽  
Genome Wide ◽  
A Genome ◽  
Increased Risk

Women using menopausal hormone therapy (MHT) are at increased risk of developing breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in 11 case–control studies. We used a case-only design to assess interactions between single-nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2920 cases (541 lobular) from four genome-wide association studies. The top 1391 SNPs showing P values for interaction (Pint) <3.0×10−3 were selected for replication using pooled case–control data from 11 studies of the Breast Cancer Association Consortium, including 7689 cases (676 lobular) and 9266 controls. Fixed-effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9×10−6), two SNPs in SLC25A21 (combined Pint≤4.8×10−5), and three SNPs in PLCG2 (combined Pint≤4.5×10−5). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7×10−5), one SNP in CD80 (combined Pint≤8.2×10−6), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10−6), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6×10−5). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling, and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.

scholarly journals Genome-wide meta-analysis of insomnia in over 2.3 million individuals implicates involvement of specific biological pathways through gene-prioritization

2020 ◽  
Author(s):  
Kyoko Watanabe ◽  
Philip R. Jansen ◽  
Jeanne E. Savage ◽  
Priyanka Nandakumar ◽  
Xin Wang ◽  
...  
Keyword(s):  
Statistical Power ◽  
Association Studies ◽  
Meta Analysis ◽  
Tissue Expression ◽  
Gene Prioritization ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Gene Sets ◽  
Genome Wide ◽  
Novel Strategy

AbstractInsomnia is a heritable, highly prevalent sleep disorder, for which no sufficient treatment currently exists. Previous genome-wide association studies (GWASs) with up to 1.3 million subjects identified over 200 associated loci. This extreme polygenicity suggested many more loci to be discovered. The current study almost doubled the sample size to over 2.3 million individuals thereby increasing statistical power. We identified 554 risk loci (confirming 190 previously associated loci and detecting 364 novel), and capitalizing on this large number of loci, we propose a novel strategy to prioritize genes using external biological resources and information on functional interactions between genes across risk loci. Of all 3,898 genes naively implicated from the risk loci, we prioritize 289. For these, we find brain-tissue expression specificity and enrichment in specific gene-sets of synaptic signaling functions and neuronal differentiation. We show that the novel gene prioritization strategy yields specific hypotheses on causal mechanisms underlying insomnia, which would not fully have been detected using traditional approaches.

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