A Polygenic Risk Score to Predict Incident Heart Failure Across the Spectrum of Cardiovascular Risk.

Area of Science:

• Cardiovascular Genetics
• Genomic Prediction of Disease
• Heart Failure Etiology

Background:

• The clinical significance of heart failure (HF) polygenic risk scores (PRS) remains under investigation.
• Existing risk prediction models for HF may not fully capture genetic predispositions.

Purpose of the Study:

• To evaluate the predictive capability of an HF PRS for new-onset HF.
• To assess HF PRS performance across diverse cardiovascular risk populations.

Main Methods:

• Utilized a HF PRS (>1 million SNPs) to stratify individuals into low, intermediate, and high genetic risk groups.
• Employed Cox proportional hazards models to derive adjusted hazard ratios for HF hospitalization in elevated cardiovascular risk cohorts.
• Validated findings in a separate cohort of individuals at low cardiovascular risk.

Main Results:

• In 74,897 participants without HF, intermediate and high HF PRS were associated with 2-fold and 5-fold increased rates of new-onset HF, respectively.
• The HF PRS significantly improved model discrimination, increasing the area under the curve (AUC) from 0.787 to 0.822 when added to a clinical model.
• Consistent predictive performance was observed in both elevated and low cardiovascular risk groups, with a 20-year follow-up in the latter.

Conclusions:

• A HF PRS is a robust, independent predictor of new-onset HF across the spectrum of cardiovascular risk.
• Polygenic risk assessment provides complementary information to established clinical risk factors for HF.