Ning Fan, Shuo Yuan, Yong Hai, Peng Du, Jian Li, Xiaochuan Kong, Wenyi Zhu, Yuzeng Liu, Lei Zang
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Then, analyses of the gene ontology, signaling pathways, and interaction networks for the differentially expressed genes (DEGs) were conducted using tools including the Database for Annotation, Visualization, and Integrated Discovery, Metascape, Gene Set Enrichment Analysis, Search Tool for the Retrieval of Interacting Genes, Cytoscape, Venn method, and packages of the R computing language.</p><p><strong>Results: </strong>A total of 260 DEGs were identified, including 161 upregulated and 99 downregulated genes. Gene Ontology annotation analysis showed that these DEGs were mainly associated with the extracellular region, chemotaxis, taxis, cytokine activity, and cytokine receptor binding. A Kyoto Encyclopedia of Genes and Genomes signaling pathway analysis showed that these DEGs were mainly involved in the of cytokine-cytokine receptor interaction, rheumatoid arthritis, tumor necrosis factor signaling pathway, <i>Salmonella</i> infection, and chemokine signaling pathway. The interaction network analysis indicated that 10 hub genes, including CXCL8, CXCL1, CCL20, CXCL2, CXCL5, CXCL3, CXCL6, C3, PF4, and GPER1 may play key roles in IVD degeneration.</p><p><strong>Conclusions: </strong>Bioinformatic analysis showed that CXCL8 and other nine key genes may play a role in the development of disc degeneration induced by inflammatory reactions and can be used to identify potential target genes for therapeutic applications in IVD degeneration.</p>","PeriodicalId":520682,"journal":{"name":"Journal of orthopaedic surgery (Hong Kong)","volume":" ","pages":"23094990211068203"},"PeriodicalIF":1.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Identifying the potential role of IL-1β in the molecular mechanisms of disc degeneration using gene expression profiling and bioinformatics analysis.\",\"authors\":\"Ning Fan, Shuo Yuan, Yong Hai, Peng Du, Jian Li, Xiaochuan Kong, Wenyi Zhu, Yuzeng Liu, Lei Zang\",\"doi\":\"10.1177/23094990211068203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>We performed a bioinformatics analysis to identify the key genes that were differentially expressed between degenerative intervertebral disc (IVD) cells with and without exposure to interleukin-1β and explore the related signaling pathways and interaction networks.</p><p><strong>Methods: </strong>The microarray data were downloaded from the Gene Expression Omnibus (27,494). Then, analyses of the gene ontology, signaling pathways, and interaction networks for the differentially expressed genes (DEGs) were conducted using tools including the Database for Annotation, Visualization, and Integrated Discovery, Metascape, Gene Set Enrichment Analysis, Search Tool for the Retrieval of Interacting Genes, Cytoscape, Venn method, and packages of the R computing language.</p><p><strong>Results: </strong>A total of 260 DEGs were identified, including 161 upregulated and 99 downregulated genes. Gene Ontology annotation analysis showed that these DEGs were mainly associated with the extracellular region, chemotaxis, taxis, cytokine activity, and cytokine receptor binding. A Kyoto Encyclopedia of Genes and Genomes signaling pathway analysis showed that these DEGs were mainly involved in the of cytokine-cytokine receptor interaction, rheumatoid arthritis, tumor necrosis factor signaling pathway, <i>Salmonella</i> infection, and chemokine signaling pathway. 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引用次数: 1
摘要
目的:我们进行了生物信息学分析,以确定暴露于白介素-1β和未暴露于白介素-1β的退行性椎间盘(IVD)细胞之间差异表达的关键基因,并探索相关信号通路和相互作用网络。方法:从Gene Expression Omnibus(27,494)下载微阵列数据。然后,利用Database for Annotation, Visualization, and Integrated Discovery, metscape, gene Set Enrichment Analysis, Search Tool for Retrieval of Interacting genes, Cytoscape, Venn method, and packages of R computing language等工具,对差异表达基因(deg)的基因本体、信号通路和相互作用网络进行分析。结果:共鉴定出260个deg,其中上调161个,下调99个。基因本体注释分析显示,这些deg主要与细胞外区域、趋化性、趋向性、细胞因子活性和细胞因子受体结合有关。《京都基因与基因组百科全书》信号通路分析显示,这些deg主要参与细胞因子-细胞因子受体相互作用、类风湿关节炎、肿瘤坏死因子信号通路、沙门氏菌感染和趋化因子信号通路。相互作用网络分析表明,CXCL8、CXCL1、CCL20、CXCL2、CXCL5、CXCL3、CXCL6、C3、PF4、GPER1等10个枢纽基因可能在IVD退行性变中发挥关键作用。结论:生物信息学分析显示CXCL8等9个关键基因可能在炎症反应诱导的椎间盘退变的发生发展中发挥作用,可用于寻找潜在的靶基因,用于IVD退变的治疗应用。
Identifying the potential role of IL-1β in the molecular mechanisms of disc degeneration using gene expression profiling and bioinformatics analysis.
Purpose: We performed a bioinformatics analysis to identify the key genes that were differentially expressed between degenerative intervertebral disc (IVD) cells with and without exposure to interleukin-1β and explore the related signaling pathways and interaction networks.
Methods: The microarray data were downloaded from the Gene Expression Omnibus (27,494). Then, analyses of the gene ontology, signaling pathways, and interaction networks for the differentially expressed genes (DEGs) were conducted using tools including the Database for Annotation, Visualization, and Integrated Discovery, Metascape, Gene Set Enrichment Analysis, Search Tool for the Retrieval of Interacting Genes, Cytoscape, Venn method, and packages of the R computing language.
Results: A total of 260 DEGs were identified, including 161 upregulated and 99 downregulated genes. Gene Ontology annotation analysis showed that these DEGs were mainly associated with the extracellular region, chemotaxis, taxis, cytokine activity, and cytokine receptor binding. A Kyoto Encyclopedia of Genes and Genomes signaling pathway analysis showed that these DEGs were mainly involved in the of cytokine-cytokine receptor interaction, rheumatoid arthritis, tumor necrosis factor signaling pathway, Salmonella infection, and chemokine signaling pathway. The interaction network analysis indicated that 10 hub genes, including CXCL8, CXCL1, CCL20, CXCL2, CXCL5, CXCL3, CXCL6, C3, PF4, and GPER1 may play key roles in IVD degeneration.
Conclusions: Bioinformatic analysis showed that CXCL8 and other nine key genes may play a role in the development of disc degeneration induced by inflammatory reactions and can be used to identify potential target genes for therapeutic applications in IVD degeneration.