Enhanced prediction and risk stratification of atrial fibrillation with polygenic risk score in Chinese patients with type 2 diabetes

Abstract Background Atrial fibrillation (AF) is a common adverse outcome in patients with type 2 diabetes (T2D); however, the role of genetics in identifying those at risk of AF within this high-risk group have not been comprehensively studied. Methods A total of 20,009 individuals from two prospective cohorts of Chinese patients with T2D were analyzed. We calculated a polygenic risk score (PRS AF ) comprising 97 variants previously associated with AF risk. Associations of PRS AF with incident AF and other cardiovascular endpoints were assessed using Cox regression, adjusted for baseline covariates. We also determined whether adding PRS AF improved prediction compared to the CHARGE-AF score using C-index, net reclassification improvement index, and integrated discrimination improvement index. Results Incident AF occurred in 986 patients (5.1%) across the two cohorts. A higher PRS AF , adjusted for sex, age, duration of diabetes, and principal components, was associated with increased risks of incident AF (HR [95% CI] per SD = 1.42 [1.33–1.51]), stroke (1.07 [1.01–1.12]), and congestive heart failure (1.10 [1.04–1.17]). These associations remained significant in the fully adjusted model. Patients in the top PRS AF quintile were over 2.5-fold (95% CI = 2.08–3.17) as likely to develop AF than those in the bottom quintile. A novel risk score that integrates the PRS AF into the CHARGE-AF score significantly improved both discrimination and reclassification compared to the CHARGE-AF score alone. Conclusions In patients with T2D, PRS AF is an independent risk factor for AF, providing incremental value in prediction and risk stratification, beyond that achieved with a validated clinical risk score.