Screening of potential gene markers for predicting carotid atheroma plaque formation using bioinformatics approaches.

Abstract

The present study aimed to investigate potential gene markers for predicting the formation of carotid atheroma plaques using high-throughput bioinformatics methods. The GSE43292 gene expression profile was downloaded from the Gene Expression Omnibus database. Following data processing, differentially expressed genes (DEGs) were screened using a paired t-test in the Linear Models for Microarray Data package with the criteria of a false discovery rate of P<0.05 and |log2 fold-change| ≥0.58, followed by functional enrichment, protein-protein interaction (PPI) network construction, key node and module analysis, and prediction of transcription factors (TFs) targeting genes in the significant modules. The results revealed that the gene expression profiles from 32 paired samples of carotid atheroma plaque tissue and macroscopically intact tissue were obtained, based on which 886 DEGs, including 513 upregulated genes and 373 downregulated genes, were identified. The upregulated and downregulated gene sets were enriched in 24 and 13 pathways, respectively. The PPI network constructed with these DEGs comprised 35 key nodes with degrees ≥20, among which spleen tyrosine kinase (SYK), LYN and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit γ (PIK3CG) were the three highest. A significant module was mined in the PPI network, which consisted of 29 DEGs targeted by 11 TFs. The DEGs between the carotid atheroma plaque and macroscopically intact tissue samples may be involved in carotid atherogenesis. Key nodes in the PPI network constructed from these DEGs and the genes involved in the significant module, including SYK, LYN and PIK3CG, are promising for the prediction of carotid plaque formation.