Related Experiment Videos
Clinically significant novel biomarkers for prediction of first ever myocardial infarction: the Tromsø Study
Tom Wilsgaard1, Ellisiv Bøgeberg Mathiesen2, Anil Patwardhan2
1From the Departments of Community Medicine (T.W., M.-L.L., K.H.B., I.N.) and Clinical Medicine (E.B.M. H.S.), UiT The Arctic University of Norway, Norway; Division of Cardiothoracic and Respiratory Medicine, University Hospital of North Norway, Tromsø, Norway (H.S.); Tethys Bioscience, Emeryville, CA (A.P., M.W.R., J.S.-K.); Life Science Department, Singulex, Inc., Alameda, CA (S.H.); and Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway (K.H.B.). Tom.Wilsgaard@uit.no.
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 used an immunoassay platform that uses 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 [OR] 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), whereas the receiver operating characteristic 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.