Dataset Information

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.

ABSTRACT: We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

SUBMITTER: Tcheandjieu C

PROVIDER: S-EPMC9419655 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.

Tcheandjieu Catherine C Zhu Xiang X Hilliard Austin T AT Clarke Shoa L SL Napolioni Valerio V Ma Shining S Lee Kyung Min KM Fang Huaying H Chen Fei F Lu Yingchang Y Tsao Noah L NL Raghavan Sridharan S Koyama Satoshi S Gorman Bryan R BR Vujkovic Marijana M Klarin Derek D Levin Michael G MG Sinnott-Armstrong Nasa N Wojcik Genevieve L GL Plomondon Mary E ME Maddox Thomas M TM Waldo Stephen W SW Bick Alexander G AG Pyarajan Saiju S Huang Jie J Song Rebecca R Ho Yuk-Lam YL Buyske Steven S Kooperberg Charles C Haessler Jeffrey J Loos Ruth J F RJF Do Ron R Verbanck Marie M Chaudhary Kumardeep K North Kari E KE Avery Christy L CL Graff Mariaelisa M Haiman Christopher A CA Le Marchand Loïc L Wilkens Lynne R LR Bis Joshua C JC Leonard Hampton H Shen Botong B Lange Leslie A LA Giri Ayush A Dikilitas Ozan O Kullo Iftikhar J IJ Stanaway Ian B IB Jarvik Gail P GP Gordon Adam S AS Hebbring Scott S Namjou Bahram B Kaufman Kenneth M KM Ito Kaoru K Ishigaki Kazuyoshi K Kamatani Yoichiro Y Verma Shefali S SS Ritchie Marylyn D MD Kember Rachel L RL Baras Aris A Lotta Luca A LA Kathiresan Sekar S Hauser Elizabeth R ER Miller Donald R DR Lee Jennifer S JS Saleheen Danish D Reaven Peter D PD Cho Kelly K Gaziano J Michael JM Natarajan Pradeep P Huffman Jennifer E JE Voight Benjamin F BF Rader Daniel J DJ Chang Kyong-Mi KM Lynch Julie A JA Damrauer Scott M SM Wilson Peter W F PWF Tang Hua H Sun Yan V YV Tsao Philip S PS O'Donnell Christopher J CJ Assimes Themistocles L TL

Nature medicine 20220801 8

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and d ...[more]

PMID: 35915156

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Project description:Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (http://www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatic modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.

Dataset Information

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.

Publications

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.

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