| Title: | Combining polygenic and clinical risk scores in atrial fibrillation risk prediction: Implications for population screening |
| Journal: | Heart Rhythm |
| Published: | 25 Apr 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40288473/ |
| DOI: | https://doi.org/10.1016/j.hrthm.2025.04.032 |
Publication 15799
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
BACKGROUND: Atrial fibrillation (AF) development is determined by clinical risk factors and genetic predisposition. Few studies have explored whether incorporating polygenic risk scores (PRS) improves clinical-risk prediction beyond existing models.</p>
OBJECTIVES: We evaluated the interaction between AF-PRS and the hypertension, age, raised body mass index, male sex, sleep apnea, and smoking-AF (HARMS2-AF) and Cohorts for Heart and Aging Research in Genetic Epidemiology for AF (CHARGE-AF) clinical-risk scores on incident AF risk among the United Kingdom Biobank.</p>
METHODS: AF-PRS was examined in those with and without incident AF based on International Classification of Diseases, Tenth Revision coding and divided into tertiles defined as low, intermediate, and high-risk categories. Regression analysis examined the impact of AF-PRS combined with the HARMS2-AF and CHARGE-AF risk scores and AF risk.</p>
RESULTS: Among 285,734 participants with available whole genome sequencing data (52% women, age 57 years [50-63], 84.6% Caucasian), AF incidence was 6.6% with a median time to AF 8.5 (5.0-11.2) over a median 12.9 years follow-up. High AF-PRS tertile was independently associated with incident AF risk, after adjustment for clinical-risk factors (hazard ratio 2.75, 95% confidence interval 2.62-2.89, P<.001). AF-PRS enhanced AF risk prediction when combined with the HARMS2-AF risk model area under curve (AUC) 0.828 improved to 0.839 with the addition of AF-PRS (DeLong P<.001) with overall net reclassification index of 13.5% (12.8%-14.1%), and the CHARGE-AF risk model (AUC 0.808 improved to 0.828 with the addition of AF-PRS (DeLong P<.001) with overall net reclassification index of 7.3% (6.7%-7.9%).</p>
CONCLUSIONS: Combining genetic and clinical risk using the HARMS2-AF and CHARGE-AF risk scores significantly improved AF risk prediction. Incorporating polygenic to clinical-risk scores may enhance population screening and promote targeted interventions to reduce the incidence of AF.</p>
15 Keywords
- Adult
- Aged
- Atrial Fibrillation
- Female
- Follow-Up Studies
- Genetic Predisposition to Disease
- Humans
- Incidence
- Male
- Mass Screening
- Middle Aged
- Multifactorial Inheritance
- Risk Assessment
- Risk Factors
- United Kingdom
15 Authors
- Louise Segan
- William Wing Ho Ho
- Rose Crowley
- Jeremy William
- Kenneth Cho
- Sandeep Prabh
- David Chieng
- Hariharan Sugumar
- Aleksandr Voskoboinik
- Liang-Han Ling
- Jonathan M Kalman
- Dominic Abrams
- Diane Fatkin
- Fumihiko Takeuchi
- Peter M Kistler
Enabling scientific discoveries that improve human health