Abstract
BACKGROUND: Although individual protein biomarkers are associated with cardiovascular risk, rarely have multiple proteins been considered simultaneously to identify which set of proteins best predicts risk. METHODS AND RESULTS: In a nested case-control study of 273 death/myocardial infarction (MI) cases and 273 age- (within 10 years), sex-, and race-matched and event-free controls from among 2023 consecutive patients (median follow-up 2.5 years) with suspected coronary disease, plasma levels of 53 previously reported biomarkers of cardiovascular risk were determined in a core laboratory. Three penalized logistic regression models were fit using the elastic net to identify panels of proteins independently associated with death/MI: proteins alone (Model 1); proteins in a model constrained to retain clinical variables (Model 2); and proteins and clinical variables available for selection (Model 3). Model 1 identified 6 biomarkers strongly associated with death/MI: intercellular adhesion molecule-1, matrix metalloproteinase-3, N-terminal pro-B-type natriuretic peptide, interleukin-6, soluble CD40 ligand, and insulin-like growth factor binding protein-2. In Model 2, only soluble CD40 ligand remained strongly associated with death/MI when all clinical risk predictors were retained. Model 3 identified a set of 6 biomarkers (intercellular adhesion molecule-1, matrix metalloproteinase-3, N-terminal pro-B-type natriuretic peptide, interleukin-6, soluble CD40 ligand, and insulin-like growth factor binding protein-2) and 5 clinical variables (age, red-cell distribution width, diabetes mellitus, hemoglobin, and New York Heart Association class) strongly associated with death/MI. CONCLUSIONS: Simultaneously assessing the association between multiple putative protein biomarkers of cardiovascular risk and clinical outcomes is useful in identifying relevant biomarker panels for further assessment.