scholarly journals Genetics of Height and Risk of Atrial Fibrillation: A Mendelian Randomization Study

2019 ◽  
Author(s):  
Michael G. Levin ◽  
Renae Judy ◽  
Dipender Gill ◽  
Marijana Vujkovic ◽  
Matthew C. Hyman ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Standard Deviation Increase ◽  
Genome Wide ◽  
Predicted Height

ABSTRACTObjectiveTo determine whether height has a causal effect on risk of atrial fibrillationDesignMendelian randomization studySettingGenome-wide association studies of height and atrial fibrillation; Penn Medicine BiobankParticipantsMultiethnic (predominantly European ancestry) participants in genome-wide association studies of height (693,529 individuals) and atrial fibrillation (65,446 cases and 522,744 controls); 7,023 Penn Medicine Biobank participants of European ancestryExposuresHeight, cardiometabolic risk factors for atrial fibrillation, and randomly allocated genetic variants strongly associated with these traitsMain outcome measureRisk of atrial fibrillation (measured in odds ratio)ResultsAt the population level, a 1 standard deviation increase in genetically-predicted height was associated with increased odds of AF (Odds ratio [OR] 1.34; 95% Confidence Interval [CI] 1.29 to 1.40; p = 5×10−42). These findings remained consistent in sensitivity analyses that were robust to the presence of pleiotropic variants. Results from analyses considering individual-participant data were similar, even after adjustment for clinical covariates, including left atrial size.ConclusionGenetically predicted height is a positive causal risk factor for AF. This finding raises the possibility of investigating height/growth-related pathways as a means for gaining novel mechanistic insights to atrial fibrillation, as well as incorporating height into population screening strategies for atrial fibrillation.

Causal association of adipokines with osteoarthritis: a Mendelian randomization study

Rheumatology ◽  
2020 ◽  
Author(s):  
Jiayao Fan ◽  
Jiahao Zhu ◽  
Lingling Sun ◽  
Yasong Li ◽  
Tianle Wang ◽  
...  
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association ◽  
Sensitivity Analyses ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Knee Oa ◽  
Genome Wide ◽  
A Genome ◽  
Weighted Median

Abstract Objective This two-sample Mendelian randomization study aimed to delve into the effects of genetically predicted adipokine levels on OA. Methods Summary statistic data for OA originated from a meta-analysis of a genome-wide association study with an overall 50 508 subjects of European ancestry. Publicly available summary data from four genome-wide association studies were exploited to respectively identify instrumental variables of adiponectin, leptin, resistin, chemerin and retinol-blinding protein 4. Subsequently, Mendelian randomization analyses were conducted with inverse variance weighted (IVW), weighted median and Mendelian randomization-Egger regression. Furthermore, sensitivity analyses were then conducted to assess the robustness of our results. Results The positive causality between genetically predicted leptin level and risk of total OA was indicated by IVW [odds ratio (OR): 2.40, 95% CI: 1.13–5.09] and weighted median (OR: 2.94, 95% CI: 1.23–6.99). In subgroup analyses, evidence of potential harmful effects of higher level of adiponectin (OR: 1.28, 95% CI: 1.01–1.61 using IVW), leptin (OR: 3.44, 95% CI: 1.18–10.03 using IVW) and resistin (OR: 1.18, 95% CI: 1.03–1.36 using IVW) on risk of knee OA were acquired. However, the mentioned effects on risk of hip OA were not statistically significant. Slight evidence was identified supporting causality of chemerin and retinol-blinding protein 4 for OA. The findings of this study were verified by the results from sensitivity analysis. Conclusions An association between genetically predicted leptin level and risk of total OA was identified. Furthermore, association of genetically predicted levels of adiponectin, leptin and resistin with risk of knee OA were reported.

scholarly journals Genome-wide association study of atrial fibrillation in 114,539 Finnish individuals reveals novel locus associated with cardiac remodelling

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
C Paludan-Muller ◽  
O B Vad ◽  
J H Svendsen ◽  
M S Olesen
Keyword(s):  
Myocardial Infarction ◽  
Atrial Fibrillation ◽  
Endoplasmic Reticulum ◽  
Association Studies ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Endoplasmic Reticulum Membrane ◽  
Genome Wide Association Studies ◽  
Finnish Population ◽  
Genome Wide

Abstract Background/Introduction Atrial fibrillation (AF) is the most common cardiac arrhythmia and it is associated with serious complications, such as stroke, heart failure, and premature death. Previous genome-wide association studies (GWAS) have associated more than 140 genomic loci with AF; however, these studies predominantly include subjects of European ancestry. Although, the Finnish population is European, it is genetically considered different from other European populations as it has been isolated and developed through multiple bottlenecks followed by population growth. Therefore, pathogenic variants are more easily discovered and heritably diseases are more prevalent. Methods We accessed summary statistics on atrial fibrillation and flutter (I48) from the Finngen project. Loci were defined as 1 megabase regions around lead SNPs, and loci were considered novel when the SNPs had P-values <5x10–8 after conditional analysis, and no previously reported SNPs were within the loci. FINEMAP was done with a Finnish LD reference panel, and colocalization of GWAS and eQTL signals were analysed with MetaXcan. Results A GWAS on 17,325 Finnish AF cases and 97,214 controls confirms 16 previous identified loci and reveals one novel locus on chromosome 19. The novel lead SNP, rs190065070 (odds ratio [OR] = 1.44, 95% confidence interval [CI] = 1.29–1.61, P-value = 5.96x10–11), is close to the gene EMC10, which encodes the endoplasmic reticulum membrane protein complex subunit 10. While the locus harbours other genes, our MetaXcan analysis could not provide conclusive evidence for other plausible genes. The EMC complex consists of 10 subunits and is a chaperone in endoplasmic reticulum-resident membrane proteins. Previous mouse studies have shown EMC10 to be important in angiogenesis after myocardial infarction, and it has recently been associated with a novel neurodevelopment syndrome. The EMC1 subunit has been associated with congenital heart disease. Conclusion We present a novel susceptibility locus associated with AF in the Finnish population. The locus is in proximity to the gene EMC10, which is involved in structural remodelling of the heart after myocardial infarction. These results propose a potentially novel pathophysiological pathway in AF. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): The Research Foundation RigshospitaletThe John and Birthe Meyer Foundation

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 bGWAS: an R package to perform Bayesian genome wide association studies

2020 ◽  
Vol 36 (15) ◽  
pp. 4374-4376
Author(s):  
Ninon Mounier ◽  
Zoltán Kutalik
Keyword(s):  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
R Package ◽  
Genome Wide Association ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Biological Mechanisms ◽  
Genome Wide ◽  
Related Risk

Abstract Summary Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms. Availability and implementation bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https://github.com/n-mounier/bGWAS. Supplementary information Supplementary data are available at Bioinformatics online.

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 Selecting instruments for Mendelian randomization in the wake of genome-wide association studies

2016 ◽  
Vol 45 (5) ◽  
pp. 1600-1616 ◽  
Author(s):  
Daniel I Swerdlow ◽  
Karoline B Kuchenbaecker ◽  
Sonia Shah ◽  
Reecha Sofat ◽  
Michael V Holmes ◽  
...  
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Causal Inference for Heritable Phenotypic Risk Factors Using Heterogeneous Genetic Instruments

2020 ◽  
Author(s):  
Jingshu Wang ◽  
Qingyuan Zhao ◽  
Jack Bowden ◽  
Gilbran Hemani ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Risk Factors ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Genome Wide ◽  
Genetic Instruments

Over a decade of genome-wide association studies have led to the finding that significant genetic associations tend to spread across the genome for complex traits. The extreme polygenicity where "all genes affect every complex trait" complicates Mendelian Randomization studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing Mendelian Randomization methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE (Genome-wide mR Analysis under Pervasive PLEiotropy) to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using summary statistics from genome-wide association studies, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, adjust for confounding risk factors, and determine the causal direction. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and the potential pleiotropic pathways.

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