基于生物信息学分析鉴定类风湿关节炎和骨关节炎滑膜组织中的差异关键生物标志物。
Identification of differential key biomarkers in the synovial tissue between rheumatoid arthritis and osteoarthritis using bioinformatics analysis.
机构信息
Shanghai University of Traditional Chinese Medicine, Shanghai, 200052, China.
Department of Rheumatology, Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai, 200052, China.
出版信息
Clin Rheumatol. 2021 Dec;40(12):5103-5110. doi: 10.1007/s10067-021-05825-1. Epub 2021 Jul 5.
INTRODUCTION/OBJECTIVES: Rheumatoid arthritis (RA) and osteoarthritis (OA) are two common joint diseases with similar clinical manifestations. Our study aimed to identify differential gene biomarkers in the synovial tissue between RA and OA using bioinformatics analysis and validation.
METHOD
GSE36700, GSE1919, GSE12021, GSE55235, GSE55584, and GSE55457 datasets were downloaded from the Gene Expression Omnibus database. A total of 57 RA samples and 46 OA samples were included. The differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed. Protein-protein interaction (PPI) network of DEGs and the hub genes were constructed and visualized via Search Tool for the Retrieval of Interacting Genes/Proteins, Cytoscape, and R. Selected hub genes were validated via reverse transcription-polymerase chain reaction.
RESULTS
A total of 41 DEGs were identified. GO functional enrichment analysis showed that DEGs were enriched in immune response, signal transduction, regulation of immune response for biological process, in plasma membrane and extracellular region for cell component, and antigen binding and serine-type endopeptidase activity for molecular function. KEGG pathway analysis showed that DEGs were enriched in cytokine-cytokine receptor interaction and chemokine signaling pathway. PPI network analysis established 70 nodes and 120 edges and 15 hub genes were identified. The expression of CXCL13, CXCL10, and ADIPOQ was statistically different between RA and OA synovial tissue.
CONCLUSION
Differential expression of CXCL13, CXCL10, and ADIPOQ between RA and OA synovial tissue may provide new insights for understanding the RA development and difference between RA and OA. Key Points • Bioinformatics analysis was used to identify the differentially expressed genes in the synovial tissue between rheumatoid arthritis and osteoarthritis. • CXCL13, CXCL10, and ADIPOQ might provide new insight for understanding the differences between RA and OA.
简介/目的：类风湿关节炎（RA）和骨关节炎（OA）是两种具有相似临床表现的常见关节疾病。我们的研究旨在通过生物信息学分析和验证，鉴定滑膜组织中 RA 和 OA 之间的差异基因生物标志物。
方法
从基因表达综合数据库中下载 GSE36700、GSE1919、GSE12021、GSE55235、GSE55584 和 GSE55457 数据集。共纳入 57 例 RA 样本和 46 例 OA 样本。鉴定差异表达基因（DEGs）。还进行了基因本体论（GO）功能富集和京都基因与基因组百科全书（KEGG）通路分析。通过 Search Tool for the Retrieval of Interacting Genes/Proteins、Cytoscape 和 R 构建和可视化 DEGs 的蛋白质-蛋白质相互作用（PPI）网络和枢纽基因。通过逆转录-聚合酶链反应验证选定的枢纽基因。
结果
共鉴定出 41 个 DEGs。GO 功能富集分析表明，DEGs 富集在生物过程中的免疫反应、信号转导、免疫反应调节，细胞成分中的质膜和细胞外区，以及分子功能中的抗原结合和丝氨酸内肽酶活性。KEGG 通路分析表明，DEGs 富集在细胞因子-细胞因子受体相互作用和趋化因子信号通路中。PPI 网络分析建立了 70 个节点和 120 个边，鉴定出 15 个枢纽基因。CXCL13、CXCL10 和 ADIPOQ 在 RA 和 OA 滑膜组织中的表达存在统计学差异。
结论
RA 和 OA 滑膜组织中 CXCL13、CXCL10 和 ADIPOQ 的差异表达可能为理解 RA 的发生和 RA 与 OA 之间的差异提供新的见解。关键点：• 生物信息学分析用于鉴定类风湿关节炎和骨关节炎滑膜组织中的差异表达基因。• CXCL13、CXCL10 和 ADIPOQ 可能为理解 RA 与 OA 之间的差异提供新的见解。
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