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Atrial Fibrillation Genomics: Discovery and Translation

  • Cardiovascular Genomics (P Natarajan, Section Editor)
  • Published:
Current Cardiology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Our understanding of the fundamental cellular and molecular factors leading to atrial fibrillation (AF) remains stagnant despite significant advancement in ablation and device technologies. Diagnosis and prevention strategies fall behind that of treatment, but expanding knowledge in AF genetics holds the potential to drive progress. We aim to review how an understanding of the genetic contributions to AF can guide an approach to individualized risk stratification and novel avenues in drug discovery.

Recent Findings

Rare familial forms of AF identified monogenic contributions to the development of AF. Genome-wide association studies (GWAS) further identified single-nucleotide polymorphisms (SNPs) suggesting polygenic and multiplex nature of this common disease. Polygenic risk scores accounting for the multitude of associated SNPs that each confer mildly elevated risk have been developed to translate genetic information into clinical practice, though shortcomings remain. Additionally, novel laboratory methods have been empowered by recent genetic findings to enhance drug discovery efforts.

Summary

AF is increasingly recognized as a disease with a significant genetic component. With expanding sequencing technologies and accessibility, polygenic risk scores can help identify high risk individuals. Advancement in digital health tools, artificial intelligence and machine learning based on standard electrocardiograms, and genomic driven drug discovery may be integrated to deliver a sophisticated level of precision medicine in this modern era of emphasis on prevention. Randomized, prospective studies to demonstrate clinical benefits of these available tools are needed to validate this approach.

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Abbreviations

AI:

Artificial intelligence

AF:

Atrial fibrillation

CAD:

Coronary artery disease

ECG:

Electrocardiogram

EHR:

Electronic health record

HT:

High throughput

iPSC:

Induced pluripotent stem cell

GWAS:

Genome-wide association study

LD:

Linkage disequilibrium

PRS:

Polygenic risk score

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    Acknowledgments

    EDM is supported by UL1TR002550 from NCATS/NIH to The Scripps Research Institute. Dr. Ocorr has a patent US 9,186,093 B2 for the Semi-automatic Optical Heartbeat Analysis, licensed to None, available for free to researchers at www.sohasoftware.com.

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    1. Scripps Clinic, La Jolla, CA, 92037, USA

      David H. Yoo & Evan D. Muse

    2. Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, 92037, USA

      Rolf Bodmer, Karen Ocorr, Christopher J. Larson & Alexandre R. Colas

    3. Scripps Research Translational Institute, La Jolla, CA, 92037, USA

      Evan D. Muse

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    Yoo, D.H., Bodmer, R., Ocorr, K. et al. Atrial Fibrillation Genomics: Discovery and Translation. Curr Cardiol Rep 23, 164 (2021). https://doi.org/10.1007/s11886-021-01597-x

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