Clinically Significant Novel Biomarkers for Prediction of First Ever Myocardial Infarction: The Tromsø Study.

Link to article at PubMed

Clinically Significant Novel Biomarkers for Prediction of First Ever Myocardial Infarction: The Tromsø Study.

Circ Cardiovasc Genet. 2015 Jan 22;

Authors: Wilsgaard T, Mathiesen EB, Patwardhan A, Rowe MW, Schirmer H, Løchen ML, Sudduth-Klinger J, Hamren S, Bønaa KH, Njølstad I

Abstract
BACKGROUND: -Identification of individuals with high risk for first-ever myocardial infarction (MI) can be improved. The objectives of the study were to survey multiple protein biomarkers for association with the 10-year risk of incident MI and identify a clinically significant risk model that adds information to current common risk models.
METHODS AND RESULTS: -We employed an immunoassay platform that utilizes a sensitive, sample efficient molecular counting technology to measure 51 proteins in samples from the fourth survey (1994) in the Tromsø Study, a longitudinal study of men and women in Tromsø, Norway. A case control design was used with 419 first-ever MI cases (169 females/250 males) and 398 controls (244 females/154 males). Of the proteins measured, 17 were predictors of MI when considered individually after adjustment for traditional risk factors either in men, women or both. The 6 biomarkers adjusted for traditional risk factors that were selected in a multivariable model (odds ratios per standard deviation) using a stepwise procedure were apolipoprotein B/apolipoprotein A1 ratio (1.40), kallikrein (0.73), lipoprotein a (1.29), matrix metalloproteinase 9 (1.30), the interaction term IP-10/CXCL10*women (0.69), and the interaction term thrombospondin 4*men (1.38). The composite risk of these biomarkers added significantly to the traditional risk factor model with a net reclassification improvement of 14% (p=0.0002), while the ROC area increased from 0.757 to 0.791, p = 0.0004.
CONCLUSIONS: -Novel protein biomarker models improve identification of 10-year MI risk above and beyond traditional risk factors with 14% better allocation to either high or low risk group.

PMID: 25613532 [PubMed - as supplied by publisher]

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