Cluster analysis of extracellular matrix biomarkers predicts the development of impaired systolic function within 1 year of acute myocardial infarction

Abstract

AbstractThe clinical utility of combining extracellular matrix (ECM) biomarkers to predict the development of impaired systolic function following acute myocardial infarction (AMI) remains largely undetermined. A combination of ELISA and multiplexing assays were performed to measure matrix metalloproteinase (MMP)-2, MMP-3, MMP-8, MMP-9, periostin, N-terminal type I procollagen (PINP) and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) in plasma samples from 120 AMI patients. All patients had an echocardiogram within 1 year of AMI, and were divided into impaired (n = 37, LVEF < 50%) and preserved (n = 83, LVEF ≥ 50%) systolic function groups. Exploratory factor analysis was performed on log-transformed biomarkers using principle axis analysis with Oblimin rotation. Cluster analysis was performed on log-transformed and normalised biomarkers using Ward’s method of minimum variance and the squared Euclidean distance metric. Upon univariate analysis, current smoking, prescription of ACE inhibitors at discharge, peak hsTnT > 610 ng/L (median), MMP-8 levels, Factor 1 scores and Cluster One assignment were predictive of impaired systolic function. Upon multivariate analysis, Cluster One assignment (odds ratio [95% CI], 2.74 [1.04–7.23], p = 0.04) remained an independent predictor of systolic dysfunction in combination with clinical variables. These observations support the usefulness of combining ECM biomarkers using cluster analysis for predicting the development of impaired systolic function in AMI patients.