Key result
Combining a polygenic risk score with conventional factors improves CVD risk prediction by ~19%.
Why the study?
The study aimed to develop a CVD risk prediction model combining a polygenic risk score with traditional risk factors and assess the added value of the PRS.
Does adding a polygenic risk score to conventional risk factors improve the prediction of cardiovascular disease events in individuals without prevalent CVD?
Cohort (n=128,209)
Does adding a polygenic risk score to conventional risk factors improve the prediction of cardiovascular disease events in individuals without prevalent CVD?
Incorporating polygenic risk scores into routine risk assessment significantly improves cardiovascular disease prediction, especially in younger populations.
Aim To develop a model for cardiovascular disease (CVD) risk, combining polygenic risk score (PRS) with traditional risk factors while assessing the added value of PRS in two cohorts of biobank participants. Methods Data of 128 209 participants from the Estonian Biobank recruited between 2003– 2011 and 2018–2019 without prevalent cardiovascular disease, was included. Hazard ratios (HR) for polygenic risk versus conventional risk factors were estimated with Cox proportional hazards models, cumulative incidence was assessed with Aalen-Johansen curves. Predictive performance was tested using a split-sample approach and competing risk modelling. Age at CVD event served as the outcome, and the impact of the PRS was evaluated by age group (25–59 vs. 60+), sex, and recruitment period, using HRs, Harrell’s C-index, and net reclassification indices (NRI). Results The estimated HR per one standard deviation (SD) of PRS ranged from 1.1, 95% CI 1.06–1.15 (age 60+, earlier cohort) to 1.36, 95% CI 1.24–1.49 (men 25–59, later cohort). Adding PRS to the conventional risk factors in the age group 25–59 increased the C-statistic by 0.028 (p<0.0001) for men. In the age group 60+, the increase was 0.016 (p=0.0002) across all. In the independent validation set, the continuous NRI was 19.1% (95% CI 13.3%–24.9%) in the 25–59 group and 13.9% (95% CI 8.1%–19.6%) in the 60+ group. Conclusions In a high-risk population, PRS is a strong independent risk factor for CVD and should be considered in routine risk assessment, starting at a relatively young age.
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Jürgenson et al. (2025) conducted a cohort in Cardiovascular disease (n=128,209). Polygenic risk score (PRS) combined with conventional risk factors vs. Conventional risk factors alone was evaluated on 5-year predicted risk of incident non-fatal or fatal CVD event (Continuous Net Reclassification Index, age 25-59) (NRI 19.1%, 95% CI 13.3%-24.9%, p=<0.0001). A polygenic risk score combined with conventional risk factors significantly improved cardiovascular disease risk prediction, yielding a continuous net reclassification index of 19.1% in adults aged 25-59.
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