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Identification of key genes and crucial modules associated with coronary artery disease by bioinformatics analysis.

Abstract：

:The aim of this study was to identify key genes associated with coronary artery disease (CAD) and to explore the related signaling pathways. Gene expression profiles of 110 CAD and 112 non-CAD, healthy patients [CAD index (CADi) >23 and =0, respectively] were downloaded from the Gene Expression Omnibus (GEO) database (accession: GSE12288). The differentially expressed genes (DEGs) in CAD were identified using t-tests, and protein-protein interaction (PPI) networks for these DEGs were constructed using the Search Tool for the Retrieval of InteractiNg Genes (STRING) database. The Database for Annotation, Visualization and Integrated Discovery (DAVID) tool was used to identify potentially enriched biological processes (BP) among the DEGs using Gene Ontology (GO) terms, and to identify the related pathways using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. In addition, expression-activated subnetworks (crucial modules) of the constructed PPI networks were identified using the jActiveModule plug-in, and their topological properties were analyzed using NetworkAnalyzer, both available from Cytoscape. The patient specimens were classified as grade I, II and III based on CADi values. There were 151 DEGs in grade I, 362 in grade II and 425 in grade III. In the PPI network, the gene GRB2, encoding the growth factor receptor-bound protein 2, was the only common DEG among the three grades. In addition, 10 crucial modules were identified in the PPIs, 4 of which showed significant enrichment for GO BP terms. In the 12 nodes with the highest betweenness centrality, we found two genes, encoding GRB2 and the heat shock 70 kDa protein 8 (HSPA8). Moreover, the chemokine and focal adhesion signaling pathways were selected based on their relative abundance in CAD. The GRB2 and HSPA8 proteins, as well as the chemokine and focal adhension signaling pathways, might therefore be critical for the development of CAD.

journal_name

Int J Mol Med

journal_title

International journal of molecular medicine

authors

Zhang X,Cheng X,Liu H,Zheng C,Rao K,Fang Y,Zhou H,Xiong S

doi

10.3892/ijmm.2014.1817

subject

Has Abstract

pub_date

2014-09-01 00:00:00

pages

863-9

issue

eissn

1107-3756

issn

1791-244X

journal_volume

pub_type

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Identification of key genes and crucial modules associated with coronary artery disease by bioinformatics analysis.