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Deep learning of left atrial structure and function provides link to atrial fibrillation risk

Author

Listed:
  • James P. Pirruccello

    (University of California San Francisco
    University of California San Francisco
    University of California San Francisco
    University of California San Francisco)

  • Paolo Achille

    (Broad Institute of MIT and Harvard
    Broad Institute of MIT and Harvard)

  • Seung Hoan Choi

    (Broad Institute)

  • Joel T. Rämö

    (Broad Institute of MIT and Harvard
    University of Helsinki)

  • Shaan Khurshid

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Massachusetts General Hospital
    Massachusetts General Hospital)

  • Mahan Nekoui

    (Broad Institute of MIT and Harvard
    Harvard Medical School)

  • Sean J. Jurgens

    (Broad Institute of MIT and Harvard
    University of Amsterdam
    University of Amsterdam)

  • Victor Nauffal

    (Broad Institute of MIT and Harvard
    Brigham and Women’s Hospital)

  • Shinwan Kany

    (Broad Institute of MIT and Harvard
    University Heart and Vascular Center Hamburg-Eppendorf)

  • Kenney Ng

    (IBM Research)

  • Samuel F. Friedman

    (Broad Institute of MIT and Harvard
    Broad Institute of MIT and Harvard)

  • Puneet Batra

    (Broad Institute of MIT and Harvard)

  • Kathryn L. Lunetta

    (Boston University School of Public Health)

  • Aarno Palotie

    (University of Helsinki
    Massachusetts General Hospital and Harvard Medical School
    Broad Institute of MIT and Harvard)

  • Anthony A. Philippakis

    (Broad Institute of MIT and Harvard)

  • Jennifer E. Ho

    (Broad Institute of MIT and Harvard
    Harvard Medical School
    Beth Israel Deaconess Medical Center)

  • Steven A. Lubitz

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Massachusetts General Hospital
    Harvard Medical School)

  • Patrick T. Ellinor

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Massachusetts General Hospital
    Harvard Medical School)

Abstract

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk.

Suggested Citation

  • James P. Pirruccello & Paolo Achille & Seung Hoan Choi & Joel T. Rämö & Shaan Khurshid & Mahan Nekoui & Sean J. Jurgens & Victor Nauffal & Shinwan Kany & Kenney Ng & Samuel F. Friedman & Puneet Batra , 2024. "Deep learning of left atrial structure and function provides link to atrial fibrillation risk," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48229-w
    DOI: 10.1038/s41467-024-48229-w
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    References listed on IDEAS

    as
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