Atrial fibrillation: genetic architecture and polygenic risk prediction.

Abstract

Atrial fibrillation (AF) is a common arrhythmia associated with increased risk of stroke, heart failure and mortality. Advances in genomic research have revealed a complex genetic architecture underlying AF. Genome-wide association studies have identified hundreds of loci of common variants, while sequencing efforts have linked rare variants to cardiomyopathy-related pathways. Polygenic risk scores (PGS) offer a promising tool for AF risk stratification, demonstrating predictive value for disease onset, complications and perioperative outcomes. Multiancestry studies have improved the performance and generalisability of AF-PGS across populations. However, challenges remain in clinical translation, including still limited trial data, unbalanced ancestry representation, phenotype heterogeneity and variability in score calibration. Integration of PGS with other molecular scores may enhance predictive accuracy. Standardised evaluation metrics and prospective validation are essential to establish clinical utility. This review summarises recent advances in AF genetics and polygenic prediction, highlighting opportunities to refine risk assessment and guide personalised prevention strategies in cardiovascular care.