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Bioinformatics analysis of gene expression profile data to screen key genes involved in intracranial aneurysms.

ABSTRACT: Intracranial aneurysm (IA) is a cerebrovascular disease with a high mortality rate. The pathogenesis of IA remains unclear and the treatment limited. The purpose of the present study was to identify the key genes expressed in IAs and provide the basis for further research and treatment. The raw dataset GSE75436 was downloaded from Gene Expression Omnibus, including 15 IA samples and 15 matched superficial temporal artery (STA) samples. Then, differentially expressed genes (DEGs) were identified using the limma package in R software. Hierarchical clustering analysis was performed on the DEGs using the gplot2 package in R. Database for Annotation, Visualization, and Integrated Discovery (DAVID) online tools were used to perform gene ontology (GO) functional enrichment analysis. DAVID and gene set enrichment analysis were separately used to perform the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The intersections of the two results were selected as common KEGG pathways. Protein?protein interaction (PPI) analysis among the DEGs involved in the common KEGG pathways was performed using Search Tool for the Retrieval of Interacting Genes online tools, and visualized with Cytoscape software. A total of 782 DEGs were identified, comprising 392 upregulated and 390 downregulated DEGs. Hierarchical clustering demonstrated that the DEGs could precisely distinguish the IAs from the STAs. The GO enrichment analysis demonstrated that the upregulated DEGs were mainly involved in the inflammatory response and the management of extracellular matrix, and the downregulated DEGs were mainly involved in the process of vascular smooth muscle contraction. The KEGG pathway enrichment analysis demonstrated that the common pathways were 'leishmaniasis', 'Toll?like receptor signaling pathway' and 'vascular smooth muscle contraction'. In the PPI network, tumor necrosis factor (TNF), interleukin 8 and Toll?like receptor 4 had the highest degrees; they were associated with the inflammatory response. The Toll?like receptor signaling pathway and TNF gene may serve as targets for future research and treatment.

SUBMITTER: Guo T

PROVIDER: S-EPMC6797989 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Bioinformatics analysis of gene expression profile data to screen key genes involved in intracranial aneurysms.

Guo Tie T Hou Dan D Yu Dan D

Molecular medicine reports 20190923 5

Intracranial aneurysm (IA) is a cerebrovascular disease with a high mortality rate. The pathogenesis of IA remains unclear and the treatment limited. The purpose of the present study was to identify the key genes expressed in IAs and provide the basis for further research and treatment. The raw dataset GSE75436 was downloaded from Gene Expression Omnibus, including 15 IA samples and 15 matched superficial temporal artery (STA) samples. Then, differentially expressed genes (DEGs) were identified ...[more]

PMID: 31545495

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Project description:BackgroundIntracranial aneurysm (IA) is the most common cerebrovascular disease, and subarachnoid hemorrhage caused by its rupture can seriously impede nerve function. Pyroptosis is an inflammatory mode of cell death whose underlying mechanisms involving the occurrence and rupture of IAs remain unclear. In this study, using bioinformatics analysis, we identified the potential pyroptosis-related genes (PRGs) and performed their inflammatory response mechanisms in IAs.MethodsThe mRNA expression matrix of the IA tissue was obtained from the Gene Expression Omnibus database, and 51 PRGs were obtained from previous articles collected from PubMed. The differentially expressed PRGs (DEPRGs) were performed using R software. Subsequently, we performed enrichment analysis, constructed a protein-protein interaction network, performed weighted gene coexpression network analysis (WGCNA) and external validation using another dataset, and identified a correlation between hub genes and immune cell infiltration. Finally, the expression and tissue distribution of these hub genes in IA tissues were detected using Western blotting and immunohistochemical (IHC) staining.ResultsIn total, 12 DEPRGs associated with IA were identified in our analysis, which included 11 up-regulated and one down-regulated genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the DEPRGs were mostly enriched in the NOD-like receptor signaling pathway, interleukin-1 beta production, and the inflammasome complex. Three hub genes, NLRP3, IL1B and IL18, were identified using Cytoscape software and the WGCNA correlation module, and external validation revealed statistically significant differences between the expression of these hub genes in the ruptured and unruptured aneurysm groups (p < 0.05). Furthermore, all AUC values were > 0.75. Immune cell infiltration analysis suggested that the hub genes are related to CD8 T cell, macrophages and mast cells. Finally, IHC staining revealed that the protein levels of these hub genes were higher in ruptured and unruptured IA tissues than in normal tissues (p < 0.05).ConclusionThe results of bioinformatics analysis showed that pyroptosis is closely related to the formation and rupture of IA, and identified three potential hub genes involved in the pyroptosis and infiltration ofcells. Our findings may improve the understanding of the mechanisms underlying pyroptosis in IA.

Dataset Information

Bioinformatics analysis of gene expression profile data to screen key genes involved in intracranial aneurysms.

Publications

Bioinformatics analysis of gene expression profile data to screen key genes involved in intracranial aneurysms.

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