Multiethnic meta-analysis identifies new loci for pulmonary function

AbstractNearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N=60,552), African (N=8,429), Asian (N=9,959), and Hispanic/Latino (N=11,775) ethnicities. We identified over 50 novel loci at genome-wide significance in ancestry-specific and/or multiethnic meta-analyses. Recent fine mapping methods incorporating functional annotation, gene expression, and/or differences in linkage disequilibrium between ethnicities identified potential causal variants and genes at known and newly identified loci. Sixteen of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12.

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

Circulation ◽

10.1161/circ.133.suppl_1.p260 ◽

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.

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A large Canadian cohort provides insights into the genetic architecture of human hair colour

Communications Biology ◽

10.1038/s42003-021-02764-0 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Frida Lona-Durazo ◽

Marla Mendes ◽

Rohit Thakur ◽

Karen Funderburk ◽

Tongwu Zhang ◽

...

Keyword(s):

Molecular Mechanisms ◽

Association Studies ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Hair Colour ◽

Protein Coding ◽

Coding Regions ◽

Genome Wide ◽

Causal Variants ◽

Meta Analyses

AbstractHair colour is a polygenic phenotype that results from differences in the amount and ratio of melanins located in the hair bulb. Genome-wide association studies (GWAS) have identified many loci involved in the pigmentation pathway affecting hair colour. However, most of the associated loci overlap non-protein coding regions and many of the molecular mechanisms underlying pigmentation variation are still not understood. Here, we conduct GWAS meta-analyses of hair colour in a Canadian cohort of 12,741 individuals of European ancestry. By performing fine-mapping analyses we identify candidate causal variants in pigmentation loci associated with blonde, red and brown hair colour. Additionally, we observe colocalization of several GWAS hits with expression and methylation quantitative trait loci (QTLs) of cultured melanocytes. Finally, transcriptome-wide association studies (TWAS) further nominate the expression of EDNRB and CDK10 as significantly associated with hair colour. Our results provide insights on the mechanisms regulating pigmentation biology in humans.

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Identification of novel risk loci for restless legs syndrome in genome-wide association studies in individuals of European ancestry: a meta-analysis

The Lancet Neurology ◽

10.1016/s1474-4422(17)30327-7 ◽

2017 ◽

Vol 16 (11) ◽

pp. 898-907 ◽

Cited By ~ 88

Author(s):

Barbara Schormair ◽

Chen Zhao ◽

Steven Bell ◽

Erik Tilch ◽

Aaro V Salminen ◽

...

Keyword(s):

Restless Legs Syndrome ◽

Association Studies ◽

Meta Analysis ◽

Genome Wide Association ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Restless Legs ◽

Genome Wide

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Faculty Opinions recommendation of Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.3016956.2696054 ◽

2010 ◽

Author(s):

Craig Hersh

Keyword(s):

Pulmonary Function ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Multiple Loci ◽

Genome Wide ◽

Meta Analyses

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

10.1101/2020.04.23.20076208 ◽

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.

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

Human Molecular Genetics ◽

10.1093/hmg/ddy327 ◽

2018 ◽

Vol 28 (1) ◽

pp. 166-174 ◽

Cited By ~ 109

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.

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Comment on ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ by Lam et al.

Twin Research and Human Genetics ◽

10.1017/thg.2018.12 ◽

2018 ◽

Vol 21 (2) ◽

pp. 84-88 ◽

Cited By ~ 6

Author(s):

W. David Hill

Keyword(s):

Genetic Information ◽

Drug Targets ◽

Large Scale ◽

Association Studies ◽

Meta Analysis ◽

Genetic Correlations ◽

Data Sets ◽

Genome Wide Association Studies ◽

Nootropic Drug ◽

Genome Wide

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as ‘trait specific’ to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

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

10.1101/685172 ◽

2019 ◽

Cited By ~ 3

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.

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Combined analysis of keratinocyte cancers identifies novel genome-wide loci

Human Molecular Genetics ◽

10.1093/hmg/ddz121 ◽

2019 ◽

Vol 28 (18) ◽

pp. 3148-3160 ◽

Cited By ~ 6

Author(s):

Upekha E Liyanage ◽

Matthew H Law ◽

Xikun Han ◽

Jiyuan An ◽

Jue-Sheng Ong ◽

...

Keyword(s):

Cell Carcinoma ◽

Association Studies ◽

Genetic Correlations ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Multiple Trait ◽

Total N ◽

Risk Variants ◽

Genome Wide ◽

Meta Analyses

Abstract The keratinocyte cancers (KC), basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common cancers in fair-skinned people. KC treatment represents the second highest cancer healthcare expenditure in Australia. Increasing our understanding of the genetic architecture of KC may provide new avenues for prevention and treatment. We first conducted a series of genome-wide association studies (GWAS) of KC across three European ancestry datasets from Australia, Europe and USA, and used linkage disequilibrium (LD) Score regression (LDSC) to estimate their pairwise genetic correlations. We employed a multiple-trait approach to map genes across the combined set of KC GWAS (total N = 47 742 cases, 634 413 controls). We also performed meta-analyses of BCC and SCC separately to identify trait specific loci. We found substantial genetic correlations (generally 0.5–1) between BCC and SCC suggesting overlapping genetic risk variants. The multiple trait combined KC GWAS identified 63 independent genome-wide significant loci, 29 of which were novel. Individual separate meta-analyses of BCC and SCC identified an additional 13 novel loci not found in the combined KC analysis. Three new loci were implicated using gene-based tests. New loci included common variants in BRCA2 (distinct to known rare high penetrance cancer risk variants), and in CTLA4, a target of immunotherapy in melanoma. We found shared and trait specific genetic contributions to BCC and SCC. Considering both, we identified a total of 79 independent risk loci, 45 of which are novel.

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