scholarly journals Largest genome-wide association study for PTSD identifies genetic risk loci in European and African ancestries and implicates novel biological pathways

2018 ◽  
Author(s):  
Caroline M. Nievergelt ◽  
Adam X. Maihofer ◽  
Torsten Klengel ◽  
Elizabeth G. Atkinson ◽  
Chia-Yen Chen ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Meta Analysis ◽  
African Ancestry ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Post Traumatic Stress ◽  
Genome Wide

AbstractPost-traumatic stress disorder (PTSD) is a common and debilitating disorder. The risk of PTSD following trauma is heritable, but robust common variants have yet to be identified by genome-wide association studies (GWAS). We have collected a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls. We first demonstrate significant genetic correlations across 60 PTSD cohorts to evaluate the comparability of these phenotypically heterogeneous studies. In this largest GWAS meta-analysis of PTSD to date we identify a total of 6 genome-wide significant loci, 4 in European and 2 in African-ancestry analyses. Follow-up analyses incorporated local ancestry and sex-specific effects, and functional studies. Along with other novel genes, a non-coding RNA (ncRNA) and a Parkinson’s Disease gene,PARK2, were associated with PTSD. Consistent with previous reports, SNP-based heritability estimates for PTSD range between 10-20%. Despite a significant shared liability between PTSD and major depressive disorder, we show evidence that some of our loci may be specific to PTSD. These results demonstrate the role of genetic variation contributing to the biology of differential risk for PTSD and the necessity of expanding GWAS beyond European ancestry.

scholarly journals International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Caroline M. Nievergelt ◽  
Adam X. Maihofer ◽  
Torsten Klengel ◽  
Elizabeth G. Atkinson ◽  
Chia-Yen Chen ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Meta Analysis ◽  
African Ancestry ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome

Abstract The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5–20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson’s disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.

scholarly journals A meta-analysis of genome-wide association studies of multiple myeloma among men and women of African ancestry

2020 ◽  
Vol 4 (1) ◽  
pp. 181-190 ◽  
Author(s):  
Zhaohui Du ◽  
Niels Weinhold ◽  
Gregory Chi Song ◽  
Kristin A. Rand ◽  
David J. Van Den Berg ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Association Studies ◽  
Meta Analysis ◽  
African Ancestry ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Admixture Mapping ◽  
Genome Wide Association Studies ◽  
Risk Alleles ◽  
Genome Wide

Abstract Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10−6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10−12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

scholarly journals Heritability and genome-wide association study of diffusing capacity of the lung

2018 ◽  
Author(s):  
Natalie Terzikhan ◽  
Fangui Sun ◽  
Fien M. Verhamme ◽  
Hieab H.H. Adams ◽  
Daan Loth ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Considerable Proportion ◽  
Genome Wide Association Studies ◽  
Diffusing Capacity ◽  
Human Lung Tissue ◽  
Alveolar Volume ◽  
Genome Wide

AbstractBackgroundAlthough several genome wide association studies (GWAS) have investigated the genetics of pulmonary ventilatory function, little is known about the genetic factors that influence gas exchange.AimTo investigate the heritability of, and genetic variants associated with the diffusing capacity of the lung.MethodsGWAS was performed on diffusing capacity, measured by carbon monoxide uptake (DLCO) and per alveolar volume (DLCO/VA) using the single-breath technique, in 8,372 individuals from two population-based cohort studies, the Rotterdam Study and the Framingham Heart Study. Heritability was estimated in related (n=6,246) and unrelated (n=3,286) individuals.ResultsHeritability of DLCO and DLCO/VA ranged between 23% and 28% in unrelated individuals and between 45% and 49% in related individuals. Meta-analysis identified a genetic variant in GPR126 that is significantly associated with DLCO/VA. Gene expression analysis of GPR126 in human lung tissue revealed a decreased expression in patients with COPD and subjects with decreased DLCO/VA.ConclusionDLCO and DLCO/VA are heritable traits, with a considerable proportion of variance explained by genetics. A functional variant in GPR126 gene region was significantly associated with DLCO/VA. Pulmonary GPR126 expression was decreased in patients with COPD.

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 Genome-Wide Association Study Identifies Loci Associated with Sensitive Skin

Cosmetics ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 49
Author(s):  
Miranda A. Farage ◽  
Yunxuan Jiang ◽  
Jay P. Tiesman ◽  
Pierre Fontanillas ◽  
Rosemarie Osborne
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
European Ancestry ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Online Questionnaire ◽  
Sensitive Skin ◽  
Genome Wide ◽  
Skin Conditions

Individuals suffering from sensitive skin often have other skin conditions and/or diseases, such as fair skin, freckles, rosacea, or atopic dermatitis. Genome-wide association studies (GWAS) have been performed for some of these conditions, but not for sensitive skin. In this study, a total of 23,426 unrelated participants of European ancestry from the 23andMe database were evaluated for self-declared sensitive skin, other skin conditions, and diseases using an online questionnaire format. Responders were separated into two groups: those who declared they had sensitive skin (n = 8971) and those who declared their skin was not sensitive (controls, n = 14,455). A GWAS of sensitive skin individuals identified three genome-wide significance loci (p-value < 5 × 10−8) and seven suggestive loci (p-value < 1 × 10−6). Of the three most significant loci, all have been associated with pigmentation and two have been associated with acne.

scholarly journals Genome-wide association studies on endometriosis and endometriosis-related infertility

2018 ◽  
Author(s):  
Geneviève Galarneau ◽  
Pierre Fontanillas ◽  
Caterina Clementi ◽  
Tina Hu-Seliger ◽  
David-Emlyn Parfitt ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Reproductive Age ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Model Organisms ◽  
Genome Wide Association Studies ◽  
Gwas Study ◽  
Genome Wide ◽  
Genome Wide Significance

AbstractEndometriosis affects ∼10% of women of reproductive age. It is characterized by the growth of endometrial-like tissue outside the uterus and is frequently associated with severe pain and infertility. We performed the largest endometriosis genome-wide association study (GWAS) to date, with 37,183 cases and 251,258 controls. All women were of European ancestry. We also performed the first GWAS of endometriosis-related infertility, including 2,969 cases and 3,770 controls. Our endometriosis GWAS study replicated, at genome-wide significance, seven loci identified in previous endometriosis GWASs (CELA3A-CDC42, SYNE1, KDR, FSHB-ARL14EP, GREB1, ID4, and CEP112) and identified seven new candidate loci with genome-wide significance (NGF, ATP1B1-F5, CD109, HEY2, OSR2-VPS13B, WT1, and TEX11-SLC7A3). No loci demonstrated genome-wide significance for endometriosis-related infertility, however, the three most strongly associated loci (MCTP1, EPS8L3-CSF1, and LPIN1) were in or near genes associated with female fertility or embryonic lethality in model organisms. These results reveal new candidate genes with potential involvement in the pathophysiology of endometriosis and endometriosis-related infertility.

scholarly journals A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence

2017 ◽  
Author(s):  
W. D. Hill ◽  
G. Davies ◽  
A. M. McIntosh ◽  
C. R. Gale ◽  
I. J. Deary
Keyword(s):  
Household Income ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Correlated Traits ◽  
Single Measure ◽  
Combined Analysis ◽  
Genome Wide

AbstractIntelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including many physical and mental health variables. Both education and household income are strongly genetically correlated with intelligence, at rg =0.73 and rg =0.70 respectively. This allowed us to utilize a novel approach, Multi-Trait Analysis of Genome-wide association studies (MTAG; Turley et al. 2017), to combine two large genome-wide association studies (GWASs) of education and household income to increase power in the largest GWAS on intelligence so far (Sniekers et al. 2017). This study had four goals: firstly, to facilitate the discovery of new genetic loci associated with intelligence; secondly, to add to our understanding of the biology of intelligence differences; thirdly, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predict phenotypic intelligence variance in an independent sample. We apply MTAG to three large GWAS: Sniekers et al (2017) on intelligence, Okbay et al. (2016) on Educational attainment, and Hill et al. (2016) on household income. By combining these three samples our functional sample size increased from 78 308 participants to 147 194. We found 107 independent loci associated with intelligence, implicating 233 genes, using both SNP-based and gene-based GWAS. We find evidence that neurogenesis may explain some of the biological differences in intelligence as well as genes expressed in the synapse and those involved in the regulation of the nervous system. We show that the results of our combined analysis demonstrate the same pattern of genetic correlations as a single measure/the simple measure of intelligence, providing support for the meta-analysis of these genetically-related phenotypes. We find that our MTAG meta-analysis of intelligence shows similar genetic correlations to 26 other phenotypes when compared with a GWAS consisting solely of cognitive tests. Finally, using an independent sample of 6 844 individuals we were able to predict 7% of intelligence using SNP data alone.

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