Identification of aberrantly expressed genes during aging in the mouse heart via integrated bioinformatics analysis.

Abstract

Cardiovascular disease (CVD) represents a global problem and is associated with high levels of morbidity/mortality in the elderly (>65 years old). The present study aimed to identify the key candidate genes and pathways in cardiac aging via integrated bioinformatics analysis. The GSE43556 and GSE8146 gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs), defined as P < .05 and |log fold-change (FC)| >0.5, were identified. Functional enrichment and protein-protein interaction network construction were subsequently performed. First, 142 DEGs shared between the two GEO datasets were identified. Second, biological functional enrichment analysis illustrated that these DEGs mainly participate in "inflammatory response" and "monocarboxylic acid metabolic process." Moreover, Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the DEGs were mainly enriched in the PI3K-Akt signaling pathway. Subsequently, the association between the expression of DEGs in the aged heart was evaluated using the Search Tool for the Retrieval of Interacting Genes database and Cytoscape software. The present study elucidated the key genes and signaling pathways associated with cardiac aging, thus improving the understanding of the molecular mechanisms underlying cardiac aging. These identified genes may be used as molecular biomarkers for the diagnosis and treatment of cardiac aging.