J Korean Neurosurg Soc.  2022 Sep;65(5):697-709. 10.3340/jkns.2021.0200.

Identification of Hub Genes in the Pathogenesis of Ischemic Stroke Based on Bioinformatics Analysis

• Yang X
• Yan S
• Wang P
• Wang G

• KMID: 2533032
• DOI: http://doi.org/10.3340/jkns.2021.0200

Abstract

Objective
: The present study aimed to identify the function of ischemic stroke (IS) patients’ peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis.
Methods
: Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network.
Results
: In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including HTLV-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene.
Conclusion
: Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

Keyword

Ischemic stroke; Computational biology; Gene expression profiling

Figure

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  Fig. 1. Volcano plot. A : Volcano plot of DEGs in GSE58294. B : Volcano plot of DEGs in GSE22255. FDR : false discovery rate, DEGs : differentially expressed genes.

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  Fig. 2. Clustering heatmap. The horizontal axis represented the gene ID, and the vertical axis represented the group name of the sample. Red indicated high gene expression, blue indicated low gene expression, and (A and B) indicated GSE58294 and GSE22255 heatmap, respectively.

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  Fig. 3. Venn diagram. A and B : They showed the intersection of up-regulated and down-regulated genes in the GSE58294 and GSE22255 data sets, respectively.

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  Fig. 4. Boxplot of GSE58294 and GSE22255 data. Con : control, IS : ischemic stroke.

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  Fig. 5. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A : GO analysis showed the enrichment of differentially expressed genes (DEGs) in cellular component (CC), biological process (BP), and molecular function (MF). B : KEGG enrichment analysis of DEGs. UV : ultraviolet, VEGF : vascular endothelial growth factor.

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  Fig. 6. A : The protein interaction network of ischemic stroke-related differentially expressed genes. The edge between two nodes represented the gene-gene interaction. B : The protein interaction network of five pivotal genes. The node color represented the degree. Red represented the highest degree and yellow represented the lowest degree.

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  Fig. 7. Integrated microRNA (miRNA)-differentially expressed genes network of the top five pivotal genes. Blue hexagons represented five central genes. Yellow triangle represented hub gene related-miRNA.

Reference

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