Atrial fibrillation variant-to-gene prioritization through cross-ancestry eQTL and single-nucleus multiomic analyses
Francis J.A. Leblanc,
Xuexin Jin,
Kai Kang,
Chang Jie Mick Lee,
Juan Xu,
Lina Xuan,
Wenbo Ma,
Hicham Belhaj,
Marouane Benzaki,
Neelam Mehta,
Roger Sik Yin Foo,
Svetlana Reilly,
Chukwuemeka George Anene-Nzelu,
Zhenwei Pan,
Stanley Nattel,
Baofeng Yang,
Guillaume Lettre
Affiliations
Francis J.A. Leblanc
Montreal Heart Institute, Montreal, QC, Canada; Department of Medicine, Université de Montréal, Montréal, QC, Canada
Xuexin Jin
Department of Pharmacology (State Key Laboratory of Frigid Zone Cardiovascular Disease, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China; Department of Cardiology, The First Affiliated Hospital, Harbin Medical University, Harbin 150001, China
Kai Kang
Department of Cardiovascular Surgery, The First Affiliated Hospital, Harbin Medical University, Harbin 150001, China
Chang Jie Mick Lee
Cardiovascular Disease Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Juan Xu
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
Lina Xuan
Department of Pharmacology (State Key Laboratory of Frigid Zone Cardiovascular Disease, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
Wenbo Ma
Department of Pharmacology (State Key Laboratory of Frigid Zone Cardiovascular Disease, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
Hicham Belhaj
Montreal Heart Institute, Montreal, QC, Canada
Marouane Benzaki
Montreal Heart Institute, Montreal, QC, Canada; Department of Medicine, Université de Montréal, Montréal, QC, Canada
Neelam Mehta
Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
Roger Sik Yin Foo
Cardiovascular Disease Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Svetlana Reilly
Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
Chukwuemeka George Anene-Nzelu
Montreal Heart Institute, Montreal, QC, Canada; Department of Medicine, Université de Montréal, Montréal, QC, Canada; Cardiovascular Disease Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Zhenwei Pan
Department of Pharmacology (State Key Laboratory of Frigid Zone Cardiovascular Disease, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
Stanley Nattel
Montreal Heart Institute, Montreal, QC, Canada; Department of Medicine, Université de Montréal, Montréal, QC, Canada; Department of Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada; IHU Liryc and Fondation Bordeaux Université, Bordeaux, France; Institute of Pharmacology, West German Heart and Vascular Center, Faculty of Medicine, University Duisburg-Essen, Essen, Germany
Baofeng Yang
Department of Pharmacology (State Key Laboratory of Frigid Zone Cardiovascular Disease, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China
Guillaume Lettre
Montreal Heart Institute, Montreal, QC, Canada; Department of Medicine, Université de Montréal, Montréal, QC, Canada; Corresponding author
Summary: Atrial fibrillation (AF) is the most common arrhythmia in the world. Human genetics can provide strong AF therapeutic candidates, but the identification of the causal genes and their functions remains challenging. Here, we applied an AF fine-mapping strategy that leverages results from a previously published cross-ancestry genome-wide association study (GWAS), expression quantitative trait loci (eQTLs) from left atrial appendages (LAAs) obtained from two cohorts with distinct ancestry, and a paired RNA sequencing (RNA-seq) and ATAC sequencing (ATAC-seq) LAA single-nucleus assay (sn-multiome). At nine AF loci, our co-localization and fine-mapping analyses implicated 14 genes. Data integration identified several candidate causal AF variants, including rs7612445 at GNB4 and rs242557 at MAPT. Finally, we showed that the repression of the strongest AF-associated eQTL gene, LINC01629, in human embryonic stem cell-derived cardiomyocytes using CRISPR inhibition results in the dysregulation of pathways linked to genes involved in the development of atrial tissue and the cardiac conduction system.