DNA microarray study of genes differentiating acute myocardial infarction patients from healthy persons

CircMACF1 Attenuates Acute Myocardial Infarction Through miR-500b-5p-EMP1 Axis

It is widely accepted that circular RNA (circRNA) plays an important role in cardiovascular diseases. Therefore, this experiment aimed to investigate the pathogenesis of circMACF1 in acute myocardial infarction (AMI). qRT-PCR and immunoblotting were used to detect the expression levels of circMACF1, miR-500b-5p, and epithelial membrane protein 1 (EMP1). The role of circMACF1, miR-500b-5p, and EMP1 in cardiomyocyte apoptosis was assessed using annexin V-FITC/PI. Echocardiographic assessment, serum creatine kinase MB (CK-MB) and lactate dehydrogenase (LDH), myocardial infarct size, and TUNEL staining were applied in our research. In the MI group, the expression levels of circMACF1 and EMP1 were decreased with the increasing expression level of miR-500b-5p. CircMACF1 upregulated the expression of EMP1 as a sponge of miR-500b-5p, and circMACF1 was a direct target of miR-500b-5p. CircMACF1 impaired the progression of AMI by modulating the miR-500b-5p/EMP1 axis. CircMACF1 may be a potential therapeutic target for treating AMI. Graphical Abstract CircMACF1 upregulated EMP1 expression by sponge miR-500b-5p.

Identification of gene expression profiles in myocardial infarction: a systematic review and meta-analysis

BACKGROUND

Myocardial infarction (MI) is a multifactorial disease with complex pathogenesis, mainly the result of the interplay of genetic and environmental risk factors. The regulation of thrombosis, inflammation and cholesterol and lipid metabolism are the main factors that have been proposed thus far to be involved in the pathogenesis of MI. Traditional risk-estimation tools depend largely on conventional risk factors but there is a need for identification of novel biochemical and genetic markers. The aim of the study is to identify differentially expressed genes that are consistently associated with the incidence myocardial infarction (MI), which could be potentially incorporated into the traditional cardiovascular diseases risk factors models.

METHODS

The biomedical literature and gene expression databases, PubMed and GEO, respectively, were searched following the PRISMA guidelines. The key inclusion criteria were gene expression data derived from case-control studies on MI patients from blood samples. Gene expression datasets regarding the effect of medicinal drugs on MI were excluded. The t-test was applied to gene expression data from case-control studies in MI patients.

RESULTS

A total of 162 articles and 174 gene expression datasets were retrieved. Of those a total of 4 gene expression datasets met the inclusion criteria, which contained data on 31,180 loci in 93 MI patients and 89 healthy individuals. Collectively, 626 differentially expressed genes were detected in MI patients as compared to non-affected individuals at an FDR q-value = 0.01. Of those, 88 genes/gene products were interconnected in an interaction network. Totally, 15 genes were identified as hubs of the network.

CONCLUSIONS

Functional enrichment analyses revealed that the DEGs and that they are mainly involved in inflammatory/wound healing, RNA processing/transport mechanisms and a yet not fully characterized pathway implicated in RNA transport and nuclear pore proteins. The overlap between the DEGs identified in this study and the genes identified through genetic-association studies is minimal. These data could be useful in future studies on the molecular mechanisms of MI as well as diagnostic and prognostic markers.

A Whole Blood Molecular Signature for Acute Myocardial Infarction

Chest pain is a leading reason patients seek medical evaluation. While assays to detect myocyte death are used to diagnose a heart attack (acute myocardial infarction, AMI), there is no biomarker to indicate an impending cardiac event. Transcriptional patterns present in circulating endothelial cells (CEC) may provide a window into the plaque rupture process and identify a proximal biomarker for AMI. Thus, we aimed to identify a transcriptomic signature of AMI present in whole blood, but derived from CECs. Candidate genes indicative of AMI were nominated from microarray of enriched CEC samples, and then verified for detectability and predictive potential via qPCR in whole blood. This signature was validated in an independent cohort. Our findings suggest that a whole blood CEC-derived molecular signature identifies patients with AMI and sets the framework to potentially identify the earlier stages of an impending cardiac event when used in concert with clinical history and other diagnostics where conventional biomarkers indicative of myonecrosis remain undetected.