| Title: | Polygenic Risk of New Onset Atrial Fibrillation in Nonischemic Cardiomyopathy |
| Journal: | JACC Clinical Electrophysiology |
| Published: | 27 Feb 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41790084/ |
| DOI: | https://doi.org/10.1016/j.jacep.2026.01.024 |
Publication 17592
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Abstract
BACKGROUND: 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.</p>
OBJECTIVES: This study utilized an atrial fibrillation polygenic risk score (PRSAF) to improve NOAF risk stratification in an NICM cohort.</p>
METHODS: Using the UK Biobank, we constructed an NICM cohort composed of 2,661 participants without prior AF diagnosis. A PRSAF 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 PRSAF.</p>
RESULTS: There were 636 (23.9%) NOAF cases with a median follow-up post-NICM diagnosis of 55 months (Q1-Q3: 19-113 months). PRSAF 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 PRSAF 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. PRSAF predicted NOAF risk across all clinical risk (CHARGE-AF) categories but did not predict poor outcomes independent of NOAF status. Lastly, integration of PRSAF into clinical risk stratification models significantly improved predictive performance.</p>
CONCLUSIONS: PRSAF is a major risk factor for NOAF in NICM patients that can be used for AF risk stratification in conjunction with clinical risk factors.</p>
12 Authors
- Saif F Dababneh
- Jeremy Parker
- Rayan Ahmed
- Kate Huang
- Drake Comber
- Jobanjit S Phulka
- Chia-Chen Tsai
- Glen F Tibbits
- Julia Cadrin-Tourigny
- Rafik Tadros
- Guillaume Paré
- Zachary Laksman
1 Application
| Application ID | Title |
|---|---|
| 957914 | Improving Prediction and Risk Stratification of Non-Ischemic Cardiomyopathies and Associated Risk Factors using Clinical and Molecular Risk Scores |
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