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Abstract

BackgroundIntegrating polygenic scores (PGS) into population-based stroke prevention strategies may help reduce the stroke burden at both individual and population levels. However, prospective evidence regarding the interaction between genetic and modifiable risk factors remains limited, particularly in East Asian populations. MethodsWe evaluated the influence of modifiable risk factors across PGS levels in the prospective population-based Tohoku Medical Megabank Community-Based Cohort Study. Stroke PGS was calculated using a model developed by the GIGASTROKE project. ResultsDuring a median follow-up of 4.84 years (121,843.2 person-years), 246 incident stroke events were identified. Compared with participants in the intermediate PGS group (third quintile), those in the highest PGS group (fifth quintile) had a 60% greater risk of incident stroke (hazard ratio [HR], 1.60; 95% confidence interval [CI], 1.10-2.34). When participants with intermediate genetic risk and no modifiable risk factors were used as the reference group, hypertension (HR, 2.17; 95% CI, 1.11-4.25) and diabetes (HR, 2.10; 95% CI, 1.04-4.27) were significantly associated with an increased stroke risk in the intermediate PGS group. In contrast, multiple modifiable risk factors were significantly associated with stroke risk in the highest PGS group, including hypertension (HR, 2.90; 95% CI, 1.53-5.48), diabetes (HR, 2.07; 95% CI, 1.02-4.20), dyslipidemia (HR, 2.20; 95% CI, 1.28-3.79), obesity (HR, 1.98; 95% CI, 1.19-3.30), and smoking (HR, 2.57; 95% CI, 1.34-4.89). Participants with both the highest PGS and [≥] 4 modifiable risk factors had a substantially elevated stroke risk (HR, 2.76; 95% CI, 1.28-5.92). The combination of genetic and modifiable risk factors significantly influenced the cumulative incidence of stroke (P<0.001). ConclusionsModifiable risk factors substantially influenced stroke risk even among participants with high genetic susceptibility. The relative importance of modifiable risk factors for stroke prevention may differ according to an individuals genetic risk level.

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