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A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction

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, an...

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Detalles Bibliográficos
Autores principales: Brunton-O’Sullivan, Morgane M., Holley, Ana S., Hally, Kathryn E., Kristono, Gisela A., Harding, Scott A., Larsen, Peter D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8209070/
https://www.ncbi.nlm.nih.gov/pubmed/34135421
http://dx.doi.org/10.1038/s41598-021-92108-z
Descripción
Sumario: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.