Genetics of atrial fibrillation-practical applications for clinical management: if not now, when and how?

Shinwan Kany1,2, Bruno Reissmann1, Andreas Metzner1

  • 1Department of Cardiology, University Heart and Vascular Center, University Medical Center Hamburg Eppendorf, Martinistraße 52, 20251 Hamburg, Hamburg, Germany.

Insights

Predicting atrial fibrillation (AF) treatment response is crucial. Integrating genetic data with clinical factors may improve rhythm control therapies like antiarrhythmic drugs and catheter ablation for AF patients.

Area of Science:

  • Cardiology
  • Genetics
  • Pharmacogenomics

Background:

  • Atrial fibrillation (AF) prevalence and economic burden are rapidly increasing.
  • Current rhythm control therapies (antiarrhythmic drugs, catheter ablation) have variable efficacy.
  • Predicting individual patient response to AF rhythm control remains a significant challenge.

Purpose of the Study:

  • To address the knowledge gap in predicting patient response to AF rhythm control therapies.
  • To explore the role of genetic factors in modulating treatment outcomes for AF.
  • To advocate for the development of integrated clinical and genetic risk scores for personalized AF management.

Main Methods:

  • Review of genetic architecture studies in AF, including rare mutations and common variants.
  • Analysis of genome-wide association studies (GWAS) and polygenic risk scores (PRS) for AF.
  • Examination of retrospective data suggesting genetic modulation of response to antiarrhythmic drugs and catheter ablation.

Main Results:

  • Significant progress in identifying genetic variants associated with AF susceptibility and familial forms.
  • Identification of over 100 genetic loci linked to AF through GWAS.
  • Evidence suggesting common genetic variations influence response to antiarrhythmic drugs and catheter ablation.

Conclusions:

  • Understanding AF pathophysiology and genetic underpinnings is key to improving rhythm control.
  • A comprehensive clinical and genetic risk score could personalize AF treatment strategies.
  • Translating genetic insights into clinical practice promises substantial patient and healthcare system benefits.

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