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

Nat Commun. 2024 May 21;15(1):4304. doi: 10.1038/s41467-024-48229-w.

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.

MeSH terms

  • Aged
  • Atrial Fibrillation* / diagnostic imaging
  • Atrial Fibrillation* / genetics
  • Atrial Fibrillation* / physiopathology
  • Atrial Function, Left / physiology
  • Deep Learning*
  • Female
  • Genetic Loci
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study*
  • Heart Atria* / diagnostic imaging
  • Heart Atria* / pathology
  • Heart Atria* / physiopathology
  • Humans
  • Magnetic Resonance Imaging
  • Male
  • Mendelian Randomization Analysis
  • Middle Aged
  • Risk Factors
  • Stroke
  • Stroke Volume
  • United Kingdom / epidemiology