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Sequencing in over 50,000 cases identifies coding and structural variation underlying atrial fibrillation risk.

Nature genetics2025-03-07PubMed
Total: 91.5Innovation: 9Impact: 9Rigor: 9Citation: 10

Summary

This meta-analysis of genome/exome sequencing across 52,416 AF cases and 277,762 controls identifies new rare coding genes (e.g., MYBPC3, LMNA, PKP2, FAM189A2, KDM5B) and structural variants (CTNNA3 deletions, GATA4 duplications) associated with AF. Findings were broadly replicated, and CRISPR knockout of KDM5B in atrial cardiomyocytes shortened action potential duration, linking rare variants to atrial electrophysiology.

Key Findings

  • Rare coding variants in MYBPC3, LMNA, PKP2, FAM189A2, and KDM5B are associated with AF by burden testing.
  • Rare structural variants—CTNNA3 deletions and GATA4 duplications—confer AF risk.
  • CRISPR KDM5B knockout in atrial cardiomyocytes shortens action potential duration and disrupts atrial homeostasis gene programs.
  • Associations and effects replicate across independent cohorts (MyCode, deCODE, UK Biobank).

Clinical Implications

Genetic testing panels for AF may incorporate these rare coding and structural variants; mechanistic insights (e.g., KDM5B) could inform novel antiarrhythmic targets and risk stratification beyond common variant PRS.

Why It Matters

Defines the rare variant architecture of AF with functional validation, strengthening causal inference and linking AF to cardiomyopathy genes.

Limitations

  • Case-control genetic design limits direct clinical phenotyping and environmental interactions
  • Translational path from variant discovery to clinical testing and therapy requires further study across ancestries

Future Directions

Integrate rare variants into clinical AF genetic panels; test gene-specific mechanisms (e.g., KDM5B pathways) for therapeutic targeting; assess penetrance and modifiers across ancestries.

Study Information

Study Type
Meta-analysis
Research Domain
Pathophysiology/Diagnosis
Evidence Level
II - Large-scale meta-analysis of sequencing studies with functional validation
Study Design
OTHER