Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation

Alan Selewa, Kaixuan Luo, Michael Wasney, Linsin Smith, Xiaotong Sun, Chenwei Tang, Heather Eckart, Ivan P. Moskowitz, Anindita Basu (), Xin He () and Sebastian Pott ()
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Alan Selewa: The University of Chicago
Kaixuan Luo: The University of Chicago
Michael Wasney: The University of Chicago
Linsin Smith: The University of Chicago
Xiaotong Sun: The University of Chicago
Chenwei Tang: The University of Chicago
Heather Eckart: The University of Chicago
Ivan P. Moskowitz: The University of Chicago
Anindita Basu: The University of Chicago
Xin He: The University of Chicago
Sebastian Pott: The University of Chicago

Nature Communications, 2023, vol. 14, issue 1, 1-18

Abstract: Abstract Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.

Date: 2023
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DOI: 10.1038/s41467-023-40505-5

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