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Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes
Journal article   Open access   Peer reviewed

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes

Albert Henry, Barry London, Xiaodong Mo, Chris Finan, Mark D Chaffin, Doug Speed, Hanane Issa, Spiros Denaxas, James S Ware, Sean L Zheng, …
Nature genetics, Vol.57(4), pp.815-828
04/2025
DOI: 10.1038/s41588-024-02064-3
PMCID: PMC11985341
PMID: 40038546
url
https://doi.org/10.1038/s41588-024-02064-3View
Published (Version of record) Open Access

Abstract

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.

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