Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Chani J Hodonsky, Adam W Turner, Mohammad Daud Khan, Nelson B Barrientos, Ruben Methorst, Lijiang Ma, Nicolas G Lopez, Jose Verdezoto Mosquera, Gaëlle Auguste, Emily Farber, Wei Feng Ma, Doris Wong, Suna Onengut-Gumuscu, Maryam Kavousi, Patricia A Peyser, Sander W van der Laan, Nicholas J Leeper, Jason C Kovacic, Johan L M Björkegren, Clint L Miller

Research output: Working paperPreprintAcademic

7 Downloads (Pure)

Abstract

Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary arteries and 19% exhibited cell-type-specific expression. Colocalization analysis with GWAS identified subgroups of eGenes unique to CAD and blood pressure. Fine-mapping highlighted additional eGenes of interest, including TBX20 and IL5 . Splicing (s)QTLs for 1,690 genes were also identified, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing events to accurately identify disease-relevant gene expression. Our work provides the first human coronary artery eQTL resource from a patient sample and exemplifies the necessity of diverse study populations and multi-omic approaches to characterize gene regulation in critical disease processes.

Original languageEnglish
PublishermedRxiv
DOIs
Publication statusPublished - 14 Feb 2023

Fingerprint

Dive into the research topics of 'Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci'. Together they form a unique fingerprint.

Cite this