Polygenic Risk of New Onset Atrial Fibrillation in Nonischemic Cardiomyopathy

Polygenic risk scores for atrial fibrillation (AF) can predict lifetime and incident AF in healthy populations and patients with cardiovascular disease. Their clinical utility in predicting new onset atrial fibrillation (NOAF) in nonischemic cardiomyopathy (NICM) remains unknown.

This study utilized an atrial fibrillation polygenic risk score (PRS_AF) to improve NOAF risk stratification in an NICM cohort.

Using the UK Biobank, we constructed an NICM cohort composed of 2,661 participants without prior AF diagnosis. A PRS_AF was used to define polygenic risk. Clinical risk groups were defined using the CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation) risk score. Cox regression was used for survival analyses. Time-dependent area under the receiver-operator characteristic curve and net reclassification improvement were used to test predictive ability of PRS_AF.

There were 636 (23.9%) NOAF cases with a median follow-up post-NICM diagnosis of 55 months (Q1-Q3: 19-113 months). PRS_AF was an important predictor of NOAF (HR per 1 SD: 1.30; 95% CI: 1.18-1.42), with participants in the top 10th percentile of PRS_AF risk being 1.91 times (HR: 1.91; 95% CI: 1.42-2.60) more likely to develop NOAF compared with intermediate (10th to 89th percentile) risk participants over 20 years of follow-up. PRS_AF predicted NOAF risk across all clinical risk (CHARGE-AF) categories but did not predict poor outcomes independent of NOAF status. Lastly, integration of PRS_AF into clinical risk stratification models significantly improved predictive performance.

PRS_AF is a major risk factor for NOAF in NICM patients that can be used for AF risk stratification in conjunction with clinical risk factors.