title: Protein biomarkers of new-onset cardiovascular disease: prospective study from the systems approach to biomarker research in cardiovascular disease initiative.
abstract: OBJECTIVE
  Incorporation of novel plasma protein biomarkers may improve current models for prediction of atherosclerotic cardiovascular disease (ASCVD) risk.
  
  
  RESULTS
  We used discovery mass spectrometry (MS) to determine plasma concentrations of 861 proteins in 135 myocardial infarction (MI) cases and 135 matched controls. Then, we measured 59 markers by targeted MS in 336 ASCVD case-control pairs. Associations with MI or ASCVD were tested in single-marker and multiple-marker 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, cluster of differentiation 5 molecule [CD5] antigen-like, cell-surface glycoprotein mucin cell surface associated protein 18 [MUC-18], collagen-α 1 [XVIII] chain, salivary α-amylase 1, C-reactive protein, and multimerin-2) were highly associated with MI (P<0.0001) and significantly improved its prediction compared with a model with clinical risk factors alone (C-statistic of 0.71 versus 0.84). Through targeted MS, 12 single proteins were predictors of ASCVD (at P<0.05) after adjusting for established risk factors. In multiple-marker analyses, 4 proteins in combination (α-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 versus 0.73).
  
  
  CONCLUSIONS
  Proteomics profiling identified single- and multiple-marker 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.
authors: From the Framingham Heart Study, Framingham, MA (X.Y., S.S., S.J.H., C.J.O., C.S.F., P.C., M.G.L., D.L.); Department of Biostatistics, Boston University, Boston, MA (M.G.L., X.Y.); Division of Intramural Research and Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, MD (S.S., S.J.H., C.J.O., C.S.F., D.L.); BG Medicine, Inc, Waltham, MA (P.J., P.M., N.G., A.A.); Department of Mathematics and Statistics, Boston University, Boston, MA (M.G.L.); and Department of Medicine and the Cardiology Division, Boston Medical Center, Boston, MA (D.L.).
authors: Xiaoyan
authors: X
authors: Yin
authors: Subha
authors: S
authors: Subramanian
authors: Shih-Jen
authors: SJ
authors: Hwang
authors: Christopher J
authors: CJ
authors: O'Donnell
authors: Caroline S
authors: CS
authors: Fox
authors: Paul
authors: P
authors: Courchesne
authors: Pieter
authors: P
authors: Muntendam
authors: Neal
authors: N
authors: Gordon
authors: Aram
authors: A
authors: Adourian
authors: Peter
authors: P
authors: Juhasz
authors: Martin G
authors: MG
authors: Larson
authors: Daniel
authors: D
authors: Levy
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D001798:Blood Proteins / Q000032:analysis*; D016022:Case-Control Studies; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D013058:Mass Spectrometry; D008404:Massachusetts / Q000453:epidemiology; D008875:Middle Aged; D009203:Myocardial Infarction / Q000097:blood* / Q000453:epidemiology; D011379:Prognosis; D011446:Prospective Studies; D040901:Proteomics / Q000379:methods; D018570:Risk Assessment; D012307:Risk Factors; D049490:Systems Biology / Q000379:methods
chemical_list: D015415:Biomarkers; D001798:Blood Proteins
keywords: biological markers; cardiovascular diseases; epidemiology; myocardial infarction; proteomics