Impact of platelet phenotype on myocardial infarction

Crosstalk between Circulatory Microenvironment and Vascular Endothelial Cells in Acute Myocardial Infarction

Background

The reason of high mortality of acute myocardial infarction (AMI) was the lack of exploring the cellular and molecular mechanism of AMI. Therefore, we explored the crosstalk among cells, as well as its potential molecular mechanism of mediating AMI.

Methods

The gene expression profile of peripheral blood, endothelial, platelets and mononuclear cells were applied to differentially expressed genes (DEGs) analysis. ClusterProfiler and the package of gene set enrichment analysis (GSEA) were applied to explore the potential functional pathways of DEGs in 3 types of intravascular cells (endothelial, platelets and mononuclear cells) and peripheral blood. Subsequently, we extracted the surface receptors, secreted proteins and extracellular matrix from the up-regulated DEGs to explore their potential interactions mechanism of AMI by crosstalk and pivot analysis.

Findings

A total 11 common regulated DEGs (CDEGs) were identified, which might be potential biomarkers for AMI diagnosis. The abnormal pathways involved in DEGs of 3 types of intravascular cells and peripheral blood were shown, which also verified by GSEA. Afterwards, it was found that there was crosstalk in 3 types of intravascular cells and peripheral blood. Furthermore, we constructed a cell–cell interaction map among cells in AMI regulated by exosome lncRNA, which was involved in the development of AMI. Finally, we identified 8 hub genes, which might be potential biomarkers of AMI.

Interpretation

The result of this study can not only be used as a reference for subsequent experiments and further exploration, but also contribute to the development of novel cell and molecular therapies.

Comparative clinical implications of admission electrocardiographic findings for patients with non-ST-segment elevation myocardial infarction

Early risk stratification is crucial for appropriate management using invasive strategies in non-ST elevation myocardial infarction (NSTEMI), and electrocardiography (ECG) has been widely used for risk stratification. However, ECG findings in NSTEMI vary, and there is a need to define the clinical characteristics and outcomes according to ECG.We analyzed the admission ECGs of 345 NSTEMI patients who underwent coronary angiography from 2006 to 2013. Demographics, procedural characteristics, and clinical outcomes were analyzed.The ST-segment depression, T-wave inversion, and no ECG change groups included 114, 90, and 141 patients, respectively. The ST-segment depression group trended toward older, nonsmoking, and female, with a lower body mass index (BMI) and a higher incidence of comorbidities, than the no ECG change group. The ST-segment depression group also had a higher Killip class, a lower left ventricular ejection fraction, a higher regional wall motion score index (RWMSI), and 3-vessel coronary artery disease angiographically, than the no ECG change group. Patients with T-wave inversion trended toward older, female, lower BMI, less smoking, lower creatine kinase MB, and more left anterior descending (LAD) artery involvement, than the no ECG change group. In clinical outcomes, the ST-segment depression group had a higher mortality rate at 30 days and 12 months after the index procedure than the no ECG change group, whereas the T-wave inversion group showed similar clinical outcomes.Patients with ST-segment depression have a greater burden of comorbidities with risk factors and worse clinical outcomes, whereas patients with T-wave inversion have an intermediate number of risk factors but similar outcomes, compared with the no ECG change group. Further study is necessary to evaluate the prognostic impact of the baseline ECG on admission.

Genotype/allelic combinations as potential predictors of myocardial infarction

In order to find new informative predictors of myocardial infarction, we performed an analysis of genotype frequencies of polymorphic markers of SELE (rs2076059, 3832T > C), SELP (rs6131, S290 N), SELL (rs1131498, F206L), ICAM1 (rs5498, K469E), VCAM1 (rs3917010, c.928 + 420A > C), PECAM1 (rs668, V125L), VEGFA (rs35569394, -2549(18)I/D), CCL2 (rs1024611, -2518A > G), NOS3 (rs1799983, E298D), and DDAH1 (rs669173, c.303 + 30998A > G) genes in the group of Russian men with myocardial infarction (N = 315) and the control group of corresponding ethnicity, gender, and age (N = 286). Using Markov chain Monte-Carlo method (APSampler), we found genotype combinations associated with increased and decreased risk of myocardial infarction. The most significant associations were detected for PECAM1*V/V + DDAH1*C (OR = 4.17 CI 1.56-11.15 Pperm = 0.005) SELE*C + VEGFA*I + CCL2*G + VCAM1*A + NOS3*D (OR = 2.74 CI 1.66-4.52 Pperm = 2.09 × 10(-5)), and VEGFA*D/D + CCL2*A + DDAH1*C (OR = 0.44 CI 0.28-0.7 Pperm = 7.89 × 10(-5)) genotype combinations.