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The clinical utility of combining extracellular matrix (ECM) biomarkers to predict the development of impaired systolic function following acute myocardial infarction (AMI) remains largely undetermined. A combination of ELISA and multiplexing assays were performed to measure matrix metalloproteinase (MMP)-2, MMP-3, MMP-8, MMP-9, periostin, N-terminal type I procollagen (PINP) and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) in plasma samples from 120 AMI patients. All patients had an echocardiogram within 1 year of AMI, and were divided into impaired (n = 37, LVEF n = 83, LVEF ≥ 50%) systolic function groups. Exploratory factor analysis was performed on log-transformed biomarkers using principle axis analysis with Oblimin rotation. Cluster analysis was performed on log-transformed and normalised biomarkers using Ward’s method of minimum variance and the squared Euclidean distance metric. Upon univariate analysis, current smoking, prescription of ACE inhibitors at discharge, peak hsTnT > 610 ng/L (median), MMP-8 levels, Factor 1 scores and Cluster One assignment were predictive of impaired systolic function. Upon multivariate analysis, Cluster One assignment (odds ratio [95% CI], 2.74 [1.04–7.23], p = 0.04) remained an independent predictor of systolic dysfunction in combination with clinical variables. These observations support the usefulness of combining ECM biomarkers using cluster analysis for predicting the development of impaired systolic function in AMI patients.

Plain language summary The cardiac extracellular matrix (ECM) maintains the structural integrity of the heart, and can be measured in human circulation using ECM biomarkers. Understanding the levels of variation and temporal dynamics that exist in ECM biomarkers following a heart attack is important for establishing an optimal biomarker panel that may be useful in heart research. A single blood sample was collected from 12 healthy volunteers. Multiple bloods samples were collected from 23 heart attack patients during hospital admission (day 1–3) and 6 months post heart attack. About 12 ECM biomarkers were measured from these blood samples. When compared with healthy levels, seven ECM biomarkers were significantly altered in heart attack patients, and six of these biomarkers displayed stable expression during hospital admission. Variability existed within biomarker levels and this was not well described by traditional heart attack risk factors, such as age or heart attack size. Thus, the source of biomarker variability remains unknown in this study. Overall, we suggest these seven ECM biomarkers may be of interest for future studies in the setting of heart attack research.

Recent evidence suggests that neutrophils are highly plastic cells that can display heterogeneous phenotypes. Low-density neutrophils (LDNs) have been described in many inflammatory conditions, and are thought to represent an immature, hyperactivated subtype of neutrophils. Neutrophils are significantly involved in the inflammatory response to myocardial infarction (MI), although we do not know the extent to which LDNs exist, or function, in MI. This study sought to determine the frequency and phenotype of LDNs in MI patients, compared to healthy subjects (HS). LDNs and normal-density neutrophils (NDNs) were isolated from the peripheral blood of MI subjects (n = 12) and HSs (n = 12) using density gradient centrifugation. LDNs and NDNs were analysed by flow cytometry to identify neutrophils (CD66b+CD15+CD14-CD3−CD19− cells) and examine neutrophil activation (CD11b, CD66b and CD15) and maturity (CD33 and CD16). We identified LDNs within the peripheral blood mononuclear cell (PBMC) fraction of blood, and this population is significantly enriched in MI patients (1.04 ± 0.75% of PBMCs), compared to HS (0.29 ± 0.24%, p = .003). Across both cohorts, LDNs express significantly higher levels of CD66b and CD15, indicating a heightened state of activation compared to NDNs. In this study, LDNs were described as CD33highCD16low, compared to CD33lowCD16high NDNs, indicating the immaturity of this neutrophil subtype. An increase in the frequency of hyperactivated, immature LDNs is an immunological feature of MI. We highlight a potential pathological role of LDNs in MI, which underscores the need to expand our current understanding of this subtype in MI and other cardiovascular diseases (CVDs).

Introduction: Inflammation contributes to the pathogenesis of major adverse cardiovascular events (MACE) after an acute myocardial infarction (AMI). However, the optimal way to characterise inflammation and predict risk is unclear. While various biomarkers have been used to examine the relationship between acute inflammation and MACE risk, results are inconsistent between studies. Using a range of inflammatory markers, we assessed their utility to predict MACE in AMI patients. Hypothesis: A combined inflammatory biomarker approach is superior to individual biomarkers for predicting MACE risk in AMI patients. Methods: We conducted a systematic review of multi-marker approaches to characterise inflammation following AMI. Through cohort studies, a case control study, and a time series, we also examined the relationship between inflammatory markers and MACE. The studies ranged in size from 23 to 860 patients, with an average MACE rate of 13 in 100 at one year follow up. Results: Our systematic review found four studies that attempted various combined cytokine approaches. All found statistical associations with MACE, and performed better than single markers. In our studies, we first explored simple methods of combining biomarkers (ratios of leukocyte counts, and simple addition of C-reactive protein, IL-6 and TNF-alpha). We found no independent associations with MACE when biomarkers were combined via simple methods. We then examined a more sophisticated approach for combining cytokines. We chose to use a mathematical technique (principal component analysis, PCA) that could deal with co-linearity within individual cytokine measurements and combine individual cytokine measurements into a score. We selected six cytokines, and a PCA score derived from these markers was associated with MACE on univariate analysis. Individually, IL-6 and IL-8 levels were univariate predictors of MACE. Combining these two into a PCA-derived score resulted in a stronger, independent association with MACE (odds ratio 2.77, p Conclusion: Multi-marker inflammatory scores may produce more consistent associations with MACE than single biomarkers. We suggest that PCA is a useful mathematical method for creating this type of score.

Low activity levels of the antioxidant enzyme, glutathione peroxidase (GPx), have been implicated in adverse clinical outcomes in coronary artery disease. A potential mechanistic link for this relationship is that low GPx activity predisposes patients to thrombotic complications due to impaired reactive oxygen species (ROS) metabolism. GPx potentially regulates the bioavailability of nitric oxide (NO) - a potent platelet inhibitor - therefore indirectly affecting platelet activation. This study examined the relationship between levels of GPx activity, ROS, and platelet activation in 51 acute coronary syndrome (ACS) patients. No relationship was observed between GPx activity and platelet reactivity nor between ROS levels and platelet reactivity. However patients with low GPx activity had significantly higher ROS levels (r