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The effects of angiopoietin-like protein 2 (Angptl 2) and interleukin-6 (IL-6) in inflammatory mediators on the severity of coronary arterial lesion in patients with acute myocardial infarction were investigated. One hundred and twenty-six patients with acute myocardial infarction admitted to Tianjin Union Medical Center (the myocardial infarction group) and 133 healthy individuals (the control group) were selected for retrospective analysis from January 2013 to December 2015. The levels of Angptl 2 and IL-6 in serum of patients were detected by enzyme linked immunosorbent assay (ELISA), and the correlation analysis between the levels and the degree of coronary stenosis in patients with myocardial infarction was conducted. The expression level of Angptl 2 and IL-6 in the myocardial infarction group was significantly higher than that in the control group P

Background Acute myocardial infarction (AMI) is a common disease with serious mortality and morbidity, worldwide. The present study aimed to identify differentially expressed genes (DEGs) and construct a transcription factor-gene regulatory network to further study the early diagnosis of AMI. Methods The integrated analysis of publicly available Gene Expression Omnibus datasets of AMI was performed. Differentially expressed genes were identified between AMI and normal blood samples. Gene Ontology enrichment analyses, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the transcription factor-gene regulatory network were used to obtain insights into the functions of DEGs. Quantitative real-time polymerase chain reactions (qRT-PCR) were performed to validate the expression level of DEGs. Results A total of 2,502 DEGs, including 917 up-regulated genes and 1,585 down-regulated genes, were identified between AMI and normal blood samples by integrating four expression profiles of AMI. Differentially expressed genes were significantly enriched in pathways including complement and coagulation cascades, Staphylococcus aureus infection, and cell adhesion molecules. Transcription factors were screened and performed to construct the regulatory network. The transcription factor-gene regulatory network consisted of 871 interactions between 80 transcription factors and 716 DEGs. ETS homologous factor (EHF) was one of transcription factors that had high connectivity with DEGs and regulated CACNB4 in the network. Verification by qRT-PCR revealed that EHF, KRT6A and DSG3 were significantly up-regulated, while CACNG4 was significantly down-regulated in AMI. Furthermore, CACNG6, CACNB4 and CLDN18 had a tendency to be down-regulated, and CALML3 had a tendency to be up-regulated in AMI. Conclusions The identification of important differentially expressed transcription factors and genes in the development of AMI would be the groundwork for the early diagnosis and early intervention of AMI.