Abstract
Extracellular matrix (ECM) biomarkers are useful for measuring underlying molecular activity associated with cardiac repair following acute myocardial infarction (AMI). While promising as predictive tools, integration into clinical practice has been hindered by discordant findings within the literature and investigations have largely been limited to single biomarker analysis. Thus, this thesis explored alternative strategies for examining circulating ECM biomarkers in AMI.
Firstly, we examined the feasibility of combining circulating ECM biomarkers in a cohort of 140 AMI patients. ECM biomarkers measured in this study included: fibroblast growth factor basic (FGFb), matrix metalloproteinase (MMP) -2, -3, -8, -9, osteopontin, periostin, N-terminal type I procollagen (PINP), transforming growth factor - beta 1 (TGF-β1), tissue inhibitor of matrix metalloproteinase (TIMP) -1, -4 and vascular endothelial growth factor (VEGF). Application of exploratory factor analysis (EFA), a mathematical technique to elucidate the underlying structure of variables, demonstrated collinearity between biomarkers. Combination of biomarkers using cluster analysis separated patients into three distinct clusters, with differential levels of peak high-sensitivity troponin T and global registry of acute coronary events (GRACE) scores. We demonstrate that complex interrelationships exist between ECM biomarkers and combination can distinguish ECM profiles associated with differential patient risk.
Next, we explored the temporal variability of circulating ECM biomarkers in a prospective cohort of 23 AMI patients. When compared to levels in 12 healthy volunteers, MMP-8, MMP-9, PINP and TIMP-1 were elevated in AMI patients at one or more of the time points measured, while MMP-3 and periostin were significantly decreased. Longitudinal profiles of these ECM biomarkers demonstrated some temporal variation, but no clear trend in maximal or minimal levels were identified. Furthermore, only weak-to-moderate correlations were observed between ECM biomarkers and baseline left ventricular ejection fraction (LVEF) and area under the curve (AUC) high-sensitivity Troponin T, suggesting that biomarker variation was not primarily driven by indices of myocardial damage.
Harnessing this panel of seven ECM biomarkers, we investigated the clinical utility of combined biomarker analysis to predict the development of systolic and diastolic dysfunction in patients with echocardiogram measurements within 1 year of AMI. Specifically, combination of MMP-3, MMP-8, MMP-9 and TIMP-1 using cluster analysis separated patients into two clustered groups. Assignment to Cluster One, as well as prescription of ACE inhibitors at discharge, peak high-sensitivity troponin T ≥ median levels and current smoking were independent predictors for development of systolic dysfunction. However, neither single nor combined biomarker analysis could predict development of diastolic dysfunction. Thus, these findings demonstrate both the advantages and limitations of combined ECM biomarker analysis for predicting LV remodelling processes.
Potentially, novel biomarker approaches should be developed to represent ECM activity during AMI. Therefore, the final study in this thesis examined extracellular vesicle (EV) expression in cardiac fibroblasts stimulated under pro-inflammatory and pro-fibrotic conditions in vitro. Using RNA sequencing, we identified 12 EV microRNAs differentially expressed across stimulation conditions. To the best of our knowledge, this is the first study to investigate cardiac fibroblast-derived EVs under conditions representing early cardiac repair processes, and these may provide novel putative targets for future biomarker research.
Together, findings from this thesis demonstrate the complexity of measuring ECM biomarkers in AMI. We have shown that combined biomarker analysis may more appropriately capture ECM activity than single biomarkers, and we have provided future potential targets for assessment of cellular activity in cardiac repair.