ArticleScientific reports2021
A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- The Matrix Reloaded: The Hepatic Matrisome as a Therapeutic Opportunity to Fight Liver Fibrosis.Biomolecules · 2026Review
- The Emerging Role of Mechanobiology in Connecting Metabolic and Cardiovascular Diseases: From Fundamentals to Future Therapies.Biomedicines · 2026Review
- Serum periostin levels in myocardial infarction: Findings from forensic autopsy cases.PloS one · 2026Article
- Review
- Oxidative Stress-related Gene Signature: A Prognostic Tool for Predicting Survival in ST-elevation MI.European cardiology · 2025Article
- Acute Coronary Syndrome Subphenotypes Based on Repeated Biomarker Measurements in Relation to Long-Term Mortality Risk.Journal of the American Heart Association · 2024Observational
- Cluster analysis of extracellular matrix biomarkers predicts the development of impaired systolic function within 1 year of acute myocardial infarction.Heart and vessels · 2022Article
- Identification of Hub Genes in the Remodeling of Non-Infarcted Myocardium Following Acute Myocardial Infarction.Journal of cardiovascular development and disease · 2022Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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