# Multi-trait polygenic risk scores improve genomic prediction of atrial fibrillation across diverse ancestries

## TL;DR

This study shows that multi-trait polygenic scores improve atrial fibrillation risk prediction across diverse populations, especially in non-European groups.

## Contribution

The novel approach uses multi-trait polygenic scores tailored to ancestry, improving risk prediction in underrepresented groups.

## Key findings

- Ancestry-specific multi-trait PGSs outperformed standard PGSs in Asian, Admixed American, and African ancestry groups.
- The multi-trait approach showed significant gains in non-European populations compared to Europeans.
- Risk stratification at PGS extremes identified a notable proportion of individuals with high AF risk comparable to rare genetic variants.

## Abstract

Polygenic scores (PGSs) can improve atrial fibrillation (AF) risk prediction, both alone and alongside clinical scores, offering potential for guiding targeted screening. However, their limited accuracy and cross-ancestry transferability remain major barriers to clinical translation. Here, we explored several multi-PGS approaches to generate ancestry-optimized PGSs for AF, and tested these in independent samples from the All of Us Research Program. Our ancestry-specific multi-trait approach, which leverages correlated traits, in particular outperformed the current gold-standard PGS among Asian (OR/SD = 1.76 [1.56–1.99]; AUROC = 0.637; AUPRC = 0.055), Admixed American (1.45 [1.38–1.53]; 0.595; 0.054) and African ancestry groups (1.39 [1.32–1.45]; 0.573; 0.064). Although predictive accuracy remained highest among Europeans (1.89 [1.85–1.93]; 0.646; 0.157) - in whom our PGS explained ~ 50% of SNP-heritability - our multi-trait approach yielded relatively larger gains in non-European populations. Improved risk stratification was also observed at PGS extremes, identifying a substantial proportion of European individuals with risk comparable to rare TTN variants (e.g., 5.8% with > 4-fold odds). Overall, our ancestry-tailored multi-trait PGSs advance equitable AF risk prediction and provide a foundation for implementation.