Identification of nondiabetic heart failure-associated genes by bioinformatics approaches in patients with dilated ischemic cardiomyopathy.

Abstract

Heart failure (HF) is a common pathological condition affecting 4% of the worldwide population. However, approaches for predicting or treating nondiabetic HF (ND-HF) progression are insufficient. In the current study, the gene expression profile GSE26887 was analyzed, which contained samples from 5 healthy controls, 7 diabetes mellitus-HF patients and 12 ND-HF patients with dilated ischemic cardiomyopathy. The dataset of 5 healthy controls and 12 ND-HF patients was normalized with robust multichip average analysis and the differentially expressed genes (DEGs) were screened by unequal variance t-test and multiple-testing correction. In addition, the protein-protein interaction (PPI) network of the upregulated and downregulated genes was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database and the Cytoscape software platform. Subsequently, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. A total of 122 upregulated and 133 downregulated genes were detected. The most significantly up- and downregulated genes were EIF1AY and SERPINE1, respectively. In addition, 38 and 77 nodes were obtained in the up- and downregulated PPI network. DEGs that owned the highest connectivity degree were USP9Y and UTY in the upregulated network, and CD44 in the downregulated networks, respectively. NPPA and SERPINE1 were also found to be hub genes in the PPI network. Several GO terms and pathways that were enriched by DEGs were identified, and the most significantly enriched KEGG pathways were drug metabolism and extracellular matrix-receptor interaction. In conclusion, the two DEGs, NPPA and SERPINE1, may be important in the pathogenesis of HF and may be used for the diagnosis and treatment of HF.