Sex-specific prediction of major cardiovascular events in apparently healthy individuals with multi-omics data

BackgroundWhile multi-omics approaches, incorporating polygenic risk scores (PRS), metabolomics, and proteomics have shown promise in predicting major adverse cardiovascular events (MACE), their added value beyond cardiovascular disease (CVD) risk factors remains underexplored. We aimed to assess whether integrating multi-omics biomarkers into the SCORE2 model improves the prediction of MACE in apparently healthy individuals. MethodsThis study included 24,042 UK Biobank participants without CVD or diabetes mellitus, aged 40-69 years. Multi-omics biomarkers were fitted in sex-specific models including the variables of SCORE2 and 9 metabolites, 12 proteins, and a PRS for CVD in males, as well as 7 metabolites, 11 proteins, and a PRS for CVD in females. The performance of the SCORE2 model and its multi-omics extensions was compared using Harrells C-index and the net reclassification index (NRI) in a training and test set (70% and 30% of study population). ResultsIn 10-year follow-up, 1,204 MACE events occurred. Integrating multi-omics biomarkers into SCORE2 significantly improved the predictive performance (C-index: 0.708 to 0.769, P<0.001; NRI=26.2%). In males, the C-index improved from 0.682 to 0.752 ({Delta}C-index=+0.070, P<0.001; NRI=12.4%), while in females, it increased from 0.724 to 0.782 ({Delta}C-index=+0.058, P<0.001; NRI=30.4%). However, full multi-omics measurements may not be needed because the combination of proteomics and PRS yielded comparable performance in males (C-index=0.749) and females (C-index=0.782). ConclusionsIntegrating a protein panel and a PRS significantly improves MACE risk prediction by the SCORE2 model, which includes HDL and total cholesterol. Adding further metabolites has limited additional predictive value.