Simultaneous consideration of multiple candidate protein biomarkers for long-term risk for cardiovascular events.

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.

Duke Scholars

Author William Erle Kraus Medicine, Cardiology

Author Megan Lee Neely Biostatistics & Bioinformatics, Division of Biostatistics

Author Svati Hasmukh Shah Medicine, Cardiology

Author Elizabeth Rebecca Hauser Biostatistics & Bioinformatics

Author Christopher Bull Granger Medicine, Cardiology

Author Laura Kristin Newby Medicine, Cardiology