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Objective Incorporation of novel plasma protein biomarkers may improve current models for prediction of atherosclerotic cardiovascular disease (ASCVD) risk. Approach and Results We utilized discovery mass spectrometry (MS) to determine plasma concentrations of 861 proteins in 135 myocardial infarction (MI) cases and 135 matched controls. We then measured 59markers by targeted MS in 336 ASCVD case-control pairs. Associations with MI or ASCVD were tested in single marker and multimarker analyses adjusted for established ASCVD risk factors. Twelve single markers from discovery MS were associated with MI incidence (at p<0.01) adjusting for clinical risk factors. Seven proteins in aggregate (cyclophilin A, CD5 antigen-like, cell surface glycoprotein MUC18, collagen-alpha 1 [XVIII] chain, salivary alpha-amylase 1, C-reactive protein, and multimerin-2) were highly associated with MI (p<0.0001) and significantly improved its prediction compared to a model with clinical risk factors alone (C-statistic of 0.71 vs. 0.84). Through targeted MS, twelve single proteins were predictors of ASCVD (at p<0.05) after adjusting for established risk factors. In multimarker analyses, four proteins in combination (alpha-1-acid glycoprotein 1, paraoxonase 1, tetranectin, and CD5 antigen-like, predicted incident ASCVD (p<0.0001) and moderately improved the C-statistic from the model with clinical covariates alone (C-statistic of 0.69 vs. 0.73). Conclusions Proteomics profiling identified single and multimarker protein panels that are associated with new onset ASCVD and may lead to a better understanding of underlying disease mechanisms. Our findings include many novel protein biomarkers that, if externally validated, may improve risk assessment for MI and ASCVD.

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