Screening for high coronary plaque volume in primary prevention: integration of multi-omics and coronary calcium scoring into cardiovascular risk assessment

Abstract

Background

Atherosclerotic plaque volume (PV) predicts future cardiovascular events. As coronary computed tomography angiography (CCTA) is unsuitable for population screening, individuals with high total (T)PV often remain undetected.

Objective

To evaluate the relative and incremental contributions of lipidomic risk score (LRS), polygenic risk score (PRS), and coronary artery calcium score (CAC) improves screening for high TPV.

Methods

Primary prevention participants in two trials underwent clinical assessment, CAC, and blood sampling for LRS and PRS. CCTA was obtained in participants with CAC>0 and ≤400. Associations between risk scores and TPV were assessed using linear regression. Logistic regression identified predictors of high TPV; model performance was evaluated using area under the curve (AUC), net reclassification index (NRI), and integrated discrimination index (IDI).

Results

In the development cohort (n = 232, mean age 58.5 years), CAC showed the strongest correlation with TPV (R²=0.69). Multivariable regression analyses showed that CAC was the only predictor for high TPV (OR 1.03 per 10-point increase [95%CI 1.02–1.03]). In the validation cohort (n = 199, mean age 61.7 years), the AUC was shown to improve from 0.50 with MESA 10-year cardiovascular risk score (without CAC) to 0.91 with the addition of LRS, PRS and CAC (p < 0.001). The continuous NRI was shown to be +1.36 and IDI to be +0.38.

Conclusion

CAC was the dominant determinant of high coronary plaque volume and accounted for the majority of predictive performance. LRS and PRS provided only modest incremental value beyond CAC and clinical risk, supporting their role as complementary rather than primary screening tools.