Development and validation of a risk prediction algorithm for high-risk populations combining genetic and conventional risk factors of cardiovascular disease.

ABSTRACT:

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 2002-2017 and 2018-2022 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 perio

SUBMITTER: Puusepp T 

PROVIDER: S-EPMC12539690 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature