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

AbstractRestless legs syndrome (RLS) is a common neurological sensorimotor disorder often described as an unpleasant sensation associated with an urge to move the legs. Here we report findings from a meta-analysis of genome-wide association studies of RLS including 480,982 Caucasians (cases = 10,257) and a follow up sample of 24,977 (cases = 6,651). We confirm 19 of the 20 previously reported RLS sequence variants at 19 loci and report three novel RLS associations; rs112716420-G (OR = 1.25, P = 1.5 × 10−18), rs10068599-T (OR = 1.09, P = 6.9 × 10−10) and rs10769894-A (OR = 0.90, P = 9.4 × 10−14). At four of the 22 RLS loci, cis-eQTL analysis indicates a causal impact on gene expression. Through polygenic risk score for RLS we extended prior epidemiological findings implicating obesity, smoking and high alcohol intake as risk factors for RLS. To improve our understanding, with the purpose of seeking better treatments, more genetics studies yielding deeper insights into the disease biology are needed.

Download Full-text

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.

Download Full-text

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.

Download Full-text

Family and genome-wide association studies of restless legs syndrome

The Genetic Basis of Sleep and Sleep Disorders ◽

10.1017/cbo9781139649469.034 ◽

2013 ◽

pp. 335-350

Author(s):

Eva C. Schulte ◽

Juliane Winkelmann

Keyword(s):

Restless Legs Syndrome ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Restless Legs ◽

Genome Wide

Download Full-text

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.

Download Full-text

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

Human Molecular Genetics ◽

10.1093/hmg/ddy271 ◽

2018 ◽

Vol 27 (20) ◽

pp. 3641-3649 ◽

Cited By ~ 401

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

Download Full-text

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

Stroke ◽

10.1161/str.45.suppl_1.56 ◽

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: ‒]]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: ‒]]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: ‒]]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.

Download Full-text

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

Journal of Clinical Medicine ◽

10.3390/jcm8050692 ◽

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.

Download Full-text

What’s next after the exciting discovery and reassuring replications of genome-wide association studies of restless legs syndrome?

Sleep Medicine ◽

10.1016/j.sleep.2011.08.001 ◽

2011 ◽

Vol 12 (8) ◽

pp. 733-734 ◽

Cited By ~ 2

Author(s):

Lan Xiong

Keyword(s):

Restless Legs Syndrome ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Restless Legs ◽

Genome Wide

Download Full-text

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

10.1101/374553 ◽

2018 ◽

Cited By ~ 1

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.

Download Full-text