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Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation

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  • Shuai Yuan

    (University of Pennsylvania Perelman School of Medicine
    Institute of Environmental Medicine
    Karolinska Institutet
    Corporal Michael J. Crescenz VA Medical Center)

  • Jie Chen

    (Central South University Third Xiangya Hospital
    Central South University)

  • Xixin Ruan

    (Central South University Third Xiangya Hospital)

  • Yuying Li

    (Karolinska Institutet)

  • Sarah A. Abramowitz

    (University of Pennsylvania Perelman School of Medicine)

  • Lijuan Wang

    (Zhejiang University School of Medicine)

  • Fangyuan Jiang

    (Zhejiang University School of Medicine)

  • Ying Xiong

    (Karolinska Institutet)

  • Michael G. Levin

    (Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania)

  • Benjamin F. Voight

    (Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania
    University of Pennsylvania
    University of Pennsylvania)

  • Dipender Gill

    (Imperial College London)

  • Stephen Burgess

    (University of Cambridge
    University of Cambridge)

  • Agneta Åkesson

    (Institute of Environmental Medicine)

  • Karl Michaëlsson

    (Uppsala University)

  • Xue Li

    (Zhejiang University School of Medicine)

  • Scott M. Damrauer

    (University of Pennsylvania Perelman School of Medicine
    Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania)

  • Susanna C. Larsson

    (Institute of Environmental Medicine
    Uppsala University)

Abstract

Atrial fibrillation (AF) is a common cardiac arrhythmia with strong genetic components, yet its underlying molecular mechanisms and potential therapeutic targets remain incompletely understood. We conducted a cross-population genome-wide meta-analysis of 168,007 AF cases and identified 525 loci that met genome-wide significance. Two loci of PITX2 and ZFHX3 genes were identified as shared across populations of different ancestries. Comprehensive gene prioritization approaches reinforced the role of muscle development and heart contraction while also uncovering additional pathways, including cellular response to transforming growth factor-beta. Population-specific genetic correlations uncovered common and unique circulatory comorbidities between Europeans and Africans. Mendelian randomization identified modifiable risk factors and circulating proteins, informing disease prevention and drug development. Integrating genomic data from this cross-population genome-wide meta-analysis with proteomic profiling significantly enhanced AF risk prediction. This study advances our understanding of the genetic etiology of AF while also enhancing risk prediction, prevention strategies, and therapeutic development.

Suggested Citation

  • Shuai Yuan & Jie Chen & Xixin Ruan & Yuying Li & Sarah A. Abramowitz & Lijuan Wang & Fangyuan Jiang & Ying Xiong & Michael G. Levin & Benjamin F. Voight & Dipender Gill & Stephen Burgess & Agneta Åkes, 2025. "Cross-population GWAS and proteomics improve risk prediction and reveal mechanisms in atrial fibrillation," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61720-2
    DOI: 10.1038/s41467-025-61720-2
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    References listed on IDEAS

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