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

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 bioma...

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Autores principales:	Morgane M. Brunton-O’Sullivan, Ana S. Holley, Kathryn E. Hally, Gisela A. Kristono, Scott A. Harding, Peter D. Larsen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/94f5cedadbea4858944def346c05b785
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spelling	oai:doaj.org-article:94f5cedadbea4858944def346c05b7852021-12-02T17:41:32ZA combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction10.1038/s41598-021-92108-z2045-2322https://doaj.org/article/94f5cedadbea4858944def346c05b7852021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92108-zhttps://doaj.org/toc/2045-2322Abstract 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.Morgane M. Brunton-O’SullivanAna S. HolleyKathryn E. HallyGisela A. KristonoScott A. HardingPeter D. LarsenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Morgane M. Brunton-O’Sullivan Ana S. Holley Kathryn E. Hally Gisela A. Kristono Scott A. Harding Peter D. Larsen A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction
description	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.
format	article
author	Morgane M. Brunton-O’Sullivan Ana S. Holley Kathryn E. Hally Gisela A. Kristono Scott A. Harding Peter D. Larsen
author_facet	Morgane M. Brunton-O’Sullivan Ana S. Holley Kathryn E. Hally Gisela A. Kristono Scott A. Harding Peter D. Larsen
author_sort	Morgane M. Brunton-O’Sullivan
title	A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction
title_short	A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction
title_full	A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction
title_fullStr	A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction
title_full_unstemmed	A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction
title_sort	combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/94f5cedadbea4858944def346c05b785
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A combined biomarker approach for characterising extracellular matrix profiles in acute myocardial infarction

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