Analysis of differentially expressed genes and biological information between rheumatoid arthritis and osteoarthritis based on the GEO database.

IF 1.3 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Zeli Li, Li Guohai, Qianwen Xiong, Jietong Zhang, Zhicheng Li, Jiuhong He, Siying Wang, Shuwen Li
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引用次数: 0

Abstract

In the present study, we investigated the relationship between rheumatoid arthritis (RA) and knee osteoarthritis (OA) using bioinformatics, aiming to identify the differentially expressed genes (DEGs) of RA and explore the possible mechanism of RA. The GSE55584 and GSE153015 microarray datasets for RA and OA gene expression profiles were acquired from the Gene Expression Omnibus (GEO) database. The DEGs of the two datasets were obtained by R language processing and analysis. The intersecting DEGs were obtained using the Venny 2.1 platform. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genome (KEGG) enrichment analyses were performed using the DAVID platform, and the microbubble map was drawn online by importing the microbubble generation platform. All the obtained DEGs and the intersecting DEGs were imported into the STRING platform to obtain a protein-protein interaction network (PPI) and then into Cytoscape 3.9.1 software to screen core genes (hub genes). A total of 665 DEGs were obtained from the GSE55584 and GSE153015 datasets, including 324 upregulated and 341 downregulated DEGs. GO enrichment analysis showed that the biological processes in which DEGs were mainly enriched included signal transduction, immune response, inflammatory response, adaptive immune response, and G protein-coupled receptor signalling pathway. KEGG enrichment analysis of the DEGs identified the following enriched pathways: cytokine-cytokine receptor interaction; chemokine signalling pathway; viral protein interaction with cytokines and cytokine receptors; and apoptosis. Ten core genes (hub genes) were screened out, namely, CD3D, CD27, KLRB1, CCL5, GZMB, GZMA, GZMK, GNLY, CD2, and NKG7. Among them, CD3D, CD27, KLRB1, CCL5, and GZMB were most significantly correlated with the occurrence and development of RA. In the present study, bioinformatics analysis provided supporting evidence for the biological process and key genes of RA.

基于GEO数据库的类风湿关节炎与骨关节炎差异表达基因及生物学信息分析。
本研究利用生物信息学方法研究类风湿关节炎(rheumatoid arthritis, RA)与膝关节骨关节炎(knee osteoarthritis, OA)之间的关系,旨在鉴定类风湿关节炎的差异表达基因(differential expressed genes, DEGs),探讨类风湿关节炎的可能发病机制。RA和OA基因表达谱的GSE55584和GSE153015微阵列数据集从gene expression Omnibus (GEO)数据库中获取。两个数据集的deg通过R语言处理和分析得到。使用Venny 2.1平台获得相交deg。使用DAVID平台进行基因本体(GO)和京都基因基因组百科全书(KEGG)富集分析,通过导入微泡生成平台在线绘制微泡图谱。将得到的所有deg及交叉的deg导入STRING平台,得到蛋白-蛋白相互作用网络(protein-protein interaction network, PPI),再导入Cytoscape 3.9.1软件筛选核心基因(hub基因)。从GSE55584和GSE153015数据集中共获得665个基因,其中324个基因上调,341个基因下调。氧化石墨烯富集分析表明,氧化石墨烯主要富集的生物过程包括信号转导、免疫反应、炎症反应、适应性免疫反应和G蛋白偶联受体信号通路。对DEGs进行KEGG富集分析,确定了以下富集途径:细胞因子-细胞因子受体相互作用;趋化因子信号通路;病毒蛋白与细胞因子和细胞因子受体的相互作用;和细胞凋亡。筛选出10个核心基因(枢纽基因),分别为CD3D、CD27、KLRB1、CCL5、GZMB、GZMA、GZMK、GNLY、CD2、NKG7。其中CD3D、CD27、KLRB1、CCL5、GZMB与RA的发生发展相关性最显著。在本研究中,生物信息学分析为RA的生物学过程和关键基因提供了支持证据。
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来源期刊
Nucleosides, Nucleotides & Nucleic Acids
Nucleosides, Nucleotides & Nucleic Acids 生物-生化与分子生物学
CiteScore
2.60
自引率
7.70%
发文量
91
审稿时长
6 months
期刊介绍: Nucleosides, Nucleotides & Nucleic Acids publishes research articles, short notices, and concise, critical reviews of related topics that focus on the chemistry and biology of nucleosides, nucleotides, and nucleic acids. Complete with experimental details, this all-inclusive journal emphasizes the synthesis, biological activities, new and improved synthetic methods, and significant observations related to new compounds.
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