Key result
Cluster analysis of 10 circulating extracellular matrix biomarkers in acute myocardial infarction patients identified three distinct profiles associated with differential patient risk, including significant differences in GRACE scores and peak troponin T.
Why the study?
Extracellular matrix biomarkers reflect molecular cardiac repair after AMI, but their interrelationships and ability to define distinct risk profiles needed evaluation.
Can a combined profiling approach of circulating extracellular matrix biomarkers identify distinct risk phenotypes in patients with acute myocardial infarction?
Observational (n=140)
No
Can a combined profiling approach of circulating extracellular matrix biomarkers identify distinct risk phenotypes in patients with acute myocardial infarction?
Profiling multiple circulating extracellular matrix biomarkers in AMI patients identifies distinct phenotypic clusters associated with differential clinical risk, suggesting a combined biomarker approach may improve risk stratification.
ECM biomarker clusters may refine AMI risk assessment; hypothesis-generating and requires prospective validation before clinical use.
Extracellular matrix (ECM) biomarkers are useful for measuring underlying molecular activity associated with cardiac repair following acute myocardial infarction (AMI). The aim of this study was to conduct exploratory factor analysis (EFA) to examine the interrelationships between ECM biomarkers, and cluster analysis to identify if distinct ECM profiles could distinguish patient risk in AMI. Ten ECM biomarkers were measured from plasma in 140 AMI patients: MMP-2, -3, -8, -9, periostin, procollagen I N-Terminal propeptide, osteopontin, TGF-β1, TIMP-1 and -4. EFA grouped eight ECM biomarkers into a two-factor solution, which comprised three biomarkers in Factor 1 and five biomarkers in Factor 2. Notably, ECM biomarkers were not separated based on biological function. Cluster analysis grouped AMI patients into three distinct clusters. Cluster One (n = 54) had increased levels of MMP-8, MMP-9, and TGF-B1. Cluster Two (n = 43) had elevated levels of MMP-2, MMP-3, osteopontin, periostin and TIMP-1, and increased high-sensitivity troponin T and GRACE scores. Cluster Three (n = 43) had decreased levels of ECM biomarkers. Circulating ECM biomarkers demonstrated collinearity and entwined biological functions based on EFA analysis. Using cluster analysis, patients with similar clinical presentations could be separated into distinct ECM profiles that were associated with differential patient risk. Clinical significance remains to be determined.
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Brunton-O’Sullivan et al. (2021) conducted an observational in Acute myocardial infarction (n=140). Extracellular matrix (ECM) biomarker profiles vs. Different biomarker cluster groups was evaluated on Identification of distinct ECM biomarker profiles and their association with patient risk (GRACE score and peak hs-TnT). Cluster analysis of 10 circulating extracellular matrix biomarkers in acute myocardial infarction patients identified three distinct profiles associated with differential patient risk, including significant differences in GRACE scores and peak troponin T.
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