Interaction network analysis revealed biomarkers in myocardial infarction.

Myocardial infarction (MI) is a serious heart disease. The cardiac cells of patients with MI will die due to lack of blood for a long time. In this study, we aimed to find new targets for MI diagnosis and therapy. We downloaded GSE22229 including 12 blood samples from healthy persons and GSE29111 from Gene Expression Omnibus including 36 blood samples from MI patients. Then we identified differentially expressed genes (DEGs) in patients with MI compared to normal controls with p value < 0.05 and |logFC| > 1. Furthermore, interaction network and sub-network of these of these DEGs were constructed by NetBox. Linker genes were screened in the Global Network database. The degree of linker genes were calculated by igraph package in R language. Gene ontology and kyoto encyclopedia of genes and genomes pathway analysis were performed for DEGs and network modules. A total of 246 DEGs were identified in MI, which were enriched in the immune response. In the interaction network, LCK, CD247, CD3D, FYN, HLA-DRA, IL2, CD8A CD3E, CD4, CD3G had high degree, among which CD3E, CD4, CD3G were DEGs while others were linker genes screened from Global Network database. Genes in the sub-network were also enriched in the immune response pathway. The genes with high degree may be biomarkers for MI diagnosis and therapy.

Bioinformatics analysis of time series gene expression in left ventricle (LV) with acute myocardial infarction (AMI).

This study is to investigate the key genes and their possible function in acute myocardial infarction (AMI). The data of GSE4648 downloaded from the Gene Expression Omnibus (GEO) database include 6 time points (15 min, 60 min, 4h, 12h, 24h and 48 h) of 12 left ventricle (LV) samples, 12 surviving LV free wall (FW) samples, 12 inter-ventricular septum (IVS) samples after AMI operation and corresponding sham-operated samples. The data of each sample were analyzed with Affy and Bioconductor packages, and differentially expressed genes (DEGs) were screened out using BETR package with false discovery rate (FDR)<0.01. Then, functional enrichment analysis for DEGs was conducted with Database for Annotation, Visualization and Integrated Discovery (DAVID). Totally 194 DEGs were identified in LV, and only the gene tubulin beta 2a (Tubb2a) and natriuretic peptide B (Nppb) were respectively up-regulated in surviving FW tissue and IVS tissue. The biological process response to wounding and inflammatory response were significantly enriched, as well as leukocyte transendothelial migration pathway. Besides, the expression pattern analysis showed the DEGs mostly up-regulated at 4h after AMI, and these genes were mainly associated with immunity. Additionally, in transcriptional regulatory network, early growth response 1 (Egr1), activating transcription factor 3 (Atf3), Atf4, Myc and Fos were considered as the key transcription factors related to immune response. The key transcription factors and potential target genes might provide new information for the development of AMI, and leukocyte transendothelial migration pathway might play a vital role in AMI.