BACKGROUND: Joint use of multiple molecular layers can be useful to prioritize targets for mechanistic studies. Application of coronary disease in large populations is an emerging field. METHODS: We used reported circulating proteomic data (Somascan aptamer-based) from ≈3000 individuals in the CARDIA study (Coronary Artery Risk Development in Young Adults), measuring association with prevalent and 10-year incident coronary artery calcium (CAC) score. We used a multiparametric approach to prioritize circulating protein-CAC associations via genomics of circulating protein levels and coronary artery transcription. RESULTS: Proteins linked to prevalent/incident CAC in CARDIA implicated pathogenic mechanisms of vascular disease, including fibrosis and inflammation (GDF-15 growth/differentiation factor 15, CDCP1 CUB domain–containing protein 1, GSN gelsolin, THBS2 thrombospondin-2, chemokines, RNAS6), oxidative lipid metabolism (CILP2), extracellular matrix remodeling and signaling (MMPs matrix metalloproteinases, TIMP-1, integrins), calcification (Notch 1, ARHGAP36 Rho GTPase-activating protein 36), and metabolism (GIP gastric inhibitory polypeptide), as well as new proteins not previously reported. Using protein-wide association study genetic approaches, several targets with nominal evidence in CAC proteomics were associated with atherosclerosis or myocardial infarction in over 300K individuals, including PCSK9 (proprotein convertase subtilisin/kexin type 9) and APO C 1 . Finally, the coronary artery–specific transcriptome-wide association study of CAC yielded genes with previously implicated mechanistic roles in vascular homeostasis, inflammation, and metabolism, as well as genes without previously described function in CAC. Overlap across CAC proteomics and transcriptome-wide association study highlighted genes involved in vascular inflammation (S100A9), cardiac development (HES1), vessel wall structure (SPARCL1), and vascular dysfunction or plaque (NOTCH3, TNFSF12, S100A12). CONCLUSIONS: These results report population-level multiomics in human coronary calcification, presenting a method to identify disease-relevant targets through integration of human genetic approaches with multiomics.
El-Sabawi et al. (2026) studied this question.