Bioinformatics analysis of gene expression profiling for identification of potential key genes among ischemic stroke

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Abstract

This study aimed to identify the key differentially expressed genes (DEGs) following ischemic stroke (IS).

The GSE22255 microarray dataset, which contains samples from peripheral blood mononuclear cells of 20 IS patients and 20 sex- and age-matched controls, was downloaded from the Gene Expression Omnibus. After data pre-processing, DEGs were identified using the Linear Models for Microarray Data package in R. The Search Tool for the Retrieval of Interacting Genes database was used to predict the interactions among the products of DEGs, and then Cytoscape software was used to visualize the protein–protein interaction (PPI) network. DEGs in the PPI network were then analyzed using the Database for Annotation, Visualization, and Integrated Discovery online software to predict their underlying functions through functional and pathway enrichment analyses.

A total of 144 DEGs were identified in IS samples compared with control samples, including 75 upregulated and 69 downregulated genes. Genes with higher degrees in the PPI network included FOS (degree = 26), TP53 (degree = 22), JUN (degree = 20), EGR1 (degree = 18), JUNB (degree = 16), and ATF3 (degree = 15), and these genes may function in IS by interacting with each other (e.g., EGR1-JUN, EGR1-TP53, ATF3-FOS, and JUNB-FOS). Functional enrichment analysis indicated that the downregulated TP53 gene was enriched in immune response and protein targeting categories.

ATF3 and EGR1 may have an important protective effect on IS, whereas FOS, JUN, and JUNB may be associated with the development of IS. In addition, TP53 may function as an indicator of poor prognosis for IS through its association with the immune response and protein targeting.

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