Examining variation and temporal dynamics of extracellular matrix biomarkers following acute myocardial infarction.

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-ß1, 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.

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 1­3) 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.

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, 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-ß1, 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.

Association between inflammatory cytokines and long-term adverse outcomes in acute coronary syndromes: A systematic review.

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.

White blood cell subtypes as predictors of adverse cardiac events.

BACKGROUND: White blood cell (WBC) subtypes have been associated with major adverse cardiovascular events (MACEs) in acute myocardial infarction (AMI). More recently, combining neutrophil and lymphocyte counts or lymphocyte and monocyte counts into a ratio has found to be promising for predicting MACE. This study aimed to confirm the association between MACE and the following WBC subtypes: neutrophils, lymphocytes, monocytes, neutrophil-lymphocyte ratio (NLR) and lymphocyte-monocyte ratio (LMR). METHODS: In a cohort of 860 AMI patients, we collected levels of WBC subtypes from the earliest blood tests recorded prior to angiography. Data on baseline demographics and one-year outcomes were also collected. RESULTS: At one year, 130 patients (15.1%) developed MACE. NLR and LMR were significantly associated with MACE on univariate analysis (P = 0.006 and 0.005, respectively). However, when combined into a multivariate model with age, hypertension, prior myocardial infarction and Type 2 diabetes, neither NLR nor LMR had significant associations (odds ratio = 1.058 and 0.966, P = 0.069 and 0.612, respectively). CONCLUSION: As NLR and LMR were correlated with MACE only on univariate analysis, we do not believe that they are predictive enough to be used alone in a clinical setting. Further studies are required to assess the prognostic ability of these ratios in combination with other inflammatory markers.

Immunoglobulin G levels predicts risk of recurrent adverse cardiovascular events in myocardial infarction patients.

Background: Patients with myocardial infarction (MI) are at an increased risk of experiencing recurrent major adverse cardiovascular events (MACE) but predicting MACE has remained challenging. Immunoglobulins are implicated in cardiovascular disease, although the predictive value of total immunoglobulin G (IgG) has not yet been evaluated in a secondary prevention setting. This study examined whether total IgG is predictive of MACE in an MI population, and how total IgG compared to the predictive value of C-reactive protein (CRP), an acute inflammatory marker. Methods: We conducted a case-control study with 40 MI subjects (cases) who experienced MACE within 1 year of their index admission. Cases were matched for age, sex, diabetes and presentation with 77 controls who did not have MACE. Pre-discharge plasma samples were analysed for total IgG and CRP. Results: We observed higher levels of total plasma IgG in MI subjects with MACE (24.9 (16.2-43.7) mg/mL) compared to controls (18.4 (9.1-37.3) mg/mL; p < 0.05). Higher levels of IgG were associated with increased risk of MACE in our MI population. MI subjects within quartiles 3 and 4 of total IgG had 6 times and 4 times, respectively, the rate of MACE compared to subjects in quartile 1. There was no difference in CRP levels between cases and controls (1.1 (0.5-3.0) vs. 1.9 (0.6-6.1) mg/mL, p = 0.10), and no relationship was observed between CRP and MACE. Conclusion: Pre-discharge IgG level was a better marker for predicting MACE post-MI than CRP, which had no predictive value in this study.

An IL-6-IL-8 score derived from principal component analysis is predictive of adverse outcome in acute myocardial infarction.

INTRODUCTION: Many studies have shown that elevated biomarkers of inflammation following acute myocardial infarction (AMI) are associated with major adverse cardiovascular events (MACE). However, the optimal way of measuring the complex inflammatory response following AMI has not been determined. In this study we explore the use of principal component analysis (PCA) utilising multiple inflammatory cytokines to generate a combined cytokine score that may be predictive of MACE post-AMI. METHODS: Thirteen inflammatory cytokines were measured in plasma of 317 AMI patients, drawn 48-72 h following symptom onset. Patients were followed-up for one year to determine the incidence of MACE. PCA was used to generate a combined score using six cytokines that were detectable in the majority of patients (IL-1ß, -6, -8, and -10; MCP-1; and RANTES), and using a subset of cytokines that were associated with MACE on univariate analysis. Multivariate models using baseline characteristics, elevated individual cytokines and PCA-derived scores determined independent predictors of MACE. RESULTS: IL-6 and IL-8 were significantly associated with MACE on univariate analysis and were combined using PCA into an IL-6-IL-8 score. The combined cytokine score and IL-6-IL-8 PCA-derived score were both significantly associated with MACE on univariate analysis. In multivariate models IL-6-IL-8 scores (OR = 2.77, p = 0.007) and IL-6 levels (OR = 2.18, p = 0.035) were found to be independent predictors of MACE. CONCLUSION: An IL-6-IL-8 score derived from PCA was found to independently predict MACE at one year and was a stronger predictor than any individual cytokine, which suggests this may be an appropriate strategy to quantify inflammation post-AMI. Further investigation is required to determine the optimal set of cytokines to measure in this context.

Endotoxin, cat, and house dust mite allergens in electrostatic cloths and bedroom dust.

Environmental exposure to endotoxin, Fel d I (cat) allergen and Der p I (house dust mite) allergen have been associated with asthma symptoms and have been measured in the environment using various sampling methods, including the electrostatic dust collector. The objectives of this study were to investigate whether levels of endotoxin and allergens were detectable in electrostatic dust collectors and to examine the correlation of allergen and endotoxin levels between electrostatic dust collectors and vacuum sampling methods (floor dust and mattress dust). Electrostatic cloths, bedroom floor dust and mattress dust samples from a subset of 60 homes were randomly selected from the Health of Occupants of Mouldy Homes study for allergen and endotoxin analysis. Fel d I and Der p I allergens were analyzed by double monoclonal antibody ELISA and endotoxin by the kinetic Limulus amoebocyte lysate assay. An enhanced ELISA method was used to analyze Der p I in the electrostatic cloths. Endotoxin was detected in all samples, however Fel d I and Der p I were not detected in all electrostatic dust collector samples (detection in 53% and 15% of cloths respectively). No correlations were found between cloth and dust samples for endotoxin or Der p I, but moderate-to-strong correlations were found between all three sampling methods for Fel d I (rs = 0.612-0.715, p < 0.001). Poor correlation was found between floor dust and mattress dust samples for Der p I (rs = 0.256, p = 0.048). Electrostatic dust collectors may provide a way to measure airborne dust and allergen. Given the moderate-to-low correlations with vacuum dust sampling, this may present a unique measurement system which, when collected alongside traditional vacuum dust sampling, could provide additional exposure measures. Further studies are required to correlate endotoxin and allergen levels measured by electrostatic dust collector with air sampling and to explore the relationships between these bioaerosols, environmental factors and asthma.