Highlights Principal component analysis (PCA) can create scores from collinear markers. This study shows a PCA-derived score can combine cytokines in AMI patients. An IL-6-IL-8 score using PCA independently predicts poor outcomes in AMI.

Background: Inflammatory cytokines are involved in the pathophysiology of acute coronary syndromes (ACS) and have been associated with major adverse cardiovascular events (MACE). We systematically reviewed studies investigating the ability of multiple cytokines to predict MACE in ACS patients with follow-up of at least one year. Methods: A Medical Subject Heading search criteria was applied on Ovid Medline(R), EMBASE, EMBASE Classic and Cochrane Library to systematically identify relevant studies published between 1945 and 2017 that had an observational study design or were randomised controlled trials. Studies were excluded if only one cytokine was analysed, follow-up period was less than one year, subjects were non-human, or blood samples were taken more than 10 days from symptom onset. Results: Ten observational studies met the inclusion criteria. Six had acceptable internal validity when evaluated for quality. The studies were varied in terms of study methods (time of blood collection, study population, cytokines assessed, MACE definition, follow-up length) and result reporting, so a meta-analysis could not be conducted. Six of the studies found significant associations between individual cytokines and MACE. Four studies measured the combined effects of multiple cytokines to predict MACE, and all had statistically significant results. Conclusion: A combination of multiple cytokines had a better association with MACE than individual cytokines. It appears promising for future studies to determine the optimal multi-marker methodology and confirm its predictive value.

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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Aim: This study investigated an optimal extracellular matrix (ECM) biomarker panel for measurement in acute myocardial infarction (AMI). Materials & methods: Blood samples were collected from 12 healthy volunteers, and from 23 patients during hospital admission (day 1–3) and 6 months following AMI. Protein assays measured: FGFb, MMP-2, -3, -8, -9, osteopontin, periostin, PINP, TGF-β1, TIMP-1, -4 and VEGF. Results: When compared with healthy levels, seven ECM biomarkers were significantly altered in AMI patients, and six of these biomarkers displayed stable expression during hospital admission. Clinical characteristics and baseline cardiac function were not well correlated with ECM biomarkers. Conclusion: We suggest, MMP-2, MMP-3, MMP-8, MMP-9, periostin, PINP and TIMP-1 may be useful ECM biomarkers for future studies in AMI patients.