Höfundar:
Anna Eva Steindórsdóttir, Valur Emilsson, Thor Aspelund, Vilmundur Gudnason, Valborg Guðmundsdóttir
Introduction
Early detection of polygenic risk for heart failure (HF) could provide opportunities to address modifiable risk factors and reduce the burden of HF in the population. However, the predictive value of polygenic risk scores (PRSs) for HF remains unclear.
Materials and Methods
A HF-PRS was calculated for participants in the AGES study (n = 5,363, mean age = 76 years) from GWAS summary statistics using Plink with clumping and thresholding. The PRS parameters were evaluated with 500 bootstrap logistic regression iterations with lifetime HF event as outcome, defined as prevalent HF at study entry (n=220) or incident HF (n=970). The predictive value of the PRS for 10-year incident HF (n=910) was evaluated using Cox proportional hazard models from 200 bootstrap iterations.
Results
A base model with age and sex yielded an AUC of 0.66 (95% CI: 0.65 to 0.69) for lifetime risk of HF, which was increased to 0.83 (95% CI: 0.81-0.85) by the addition of the HF-PRS. For incident HF the base model yielded an AUC of 0.74 (95% CI: 0.71 to 0.76), which was increased to 0.85 (95% CI: 0.82-0.87) by the addition of the HF-PRS.
Conclusions
A PRS for HF was associated with both lifetime and incident HF in the AGES population-based cohort and added considerably to the AUC from a simple base model. Further work is required to evaluate the added value over established clinical risk factors. The results demonstrate a potential for using genetic information to identify individuals at high risk of HF.
