Clinically Significant Novel Biomarkers for Prediction of First Ever Myocardial Infarction

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 i...

Full description

Bibliographic Details
Published in:Circulation: Cardiovascular Genetics
Main Authors: Wilsgaard, Tom, Mathiesen, Ellisiv Bøgeberg, Patwardhan, Anil, Rowe, Michael W., Schirmer, Henrik, Løchen, Maja-Lisa, Sudduth-Klinger, Julie, Hamren, Sarah, Bønaa, Kaare Harald, Njølstad, Inger
Format: Article in Journal/Newspaper
Language:English
Published: Ovid Technologies (Wolters Kluwer Health) 2015
Subjects:
Tromsø
Online Access:http://dx.doi.org/10.1161/circgenetics.113.000630
https://www.ahajournals.org/doi/full/10.1161/CIRCGENETICS.113.000630
Description
Summary: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.

Similar Items