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综合生物信息学分析与实验验证揭示类风湿关节炎的核心基因

Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis.

作者信息

Luo Kun, Zhong Yumei, Guo Yanding, Nie Jingwei, Xu Yimei, Zhou Haiyan

机构信息

Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, P.R. China.

Department of Painology, Chengdu Integrated TCM & Western Medicine Hospital/Chengdu First People's Hospital, Chengdu, Sichuan 610095, P.R. China.

出版信息

Exp Ther Med. 2023 Aug 25;26(4):480. doi: 10.3892/etm.2023.12179. eCollection 2023 Oct.

Abstract

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation, especially synovitis, leading to joint damage. It is important to explore potential biomarkers and therapeutic targets to improve the clinical treatment of RA. However, the potential underlying mechanisms of action of available treatments for RA have not yet been fully elucidated. The present study investigated the potential biomarkers of RA and identified specific targets for therapeutic intervention. A comprehensive analysis was performed using mRNA files downloaded from the Gene Expression Omnibus. Differences in gene expression were analyzed and compared between the normal and RA groups. In addition, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on differentially expressed genes (DEGs). A protein-protein interaction network, Molecular Complex Detection and cytoHubba network were evaluated to identify hub genes. Finally, using an experimental RA rat model induced by Freund's complete adjuvant (FCA), the expression of potential biomarkers or target genes in RA were verified through reverse transcription-quantitative PCR. The results of the mRNA dataset processing revealed 195 DEGs in patients with RA when compared with the healthy controls. Moreover, 10 hub genes were identified in patients with RA and four candidate mRNAs were identified, as follows: Discs large homolog-associated protein 5 (), kinesin family member 20A (), maternal embryonic leucine zipper kinase () and nuclear division cycle 80 (. Finally, the bioinformatics analysis results were validated by quantifying the expression of the , , and genes in the FCA-induced experimental RA rat model. The findings of the present study suggested that the treatment of RA may be successful through the inhibition of , , and expression. Therefore, the targeting of these genes may result in more effective treatments for patients with RA.

摘要

类风湿性关节炎(RA)是一种自身免疫性疾病,其特征为全身性炎症,尤其是滑膜炎,可导致关节损伤。探索潜在的生物标志物和治疗靶点对于改善RA的临床治疗至关重要。然而,现有RA治疗方法潜在的作用机制尚未完全阐明。本研究调查了RA的潜在生物标志物,并确定了治疗干预的特定靶点。使用从基因表达综合数据库下载的mRNA文件进行了全面分析。分析并比较了正常组和RA组之间的基因表达差异。此外,对差异表达基因(DEG)进行了基因本体论和京都基因与基因组百科全书通路富集分析。评估了蛋白质-蛋白质相互作用网络、分子复合物检测和细胞枢纽网络以识别枢纽基因。最后,使用弗氏完全佐剂(FCA)诱导的实验性RA大鼠模型,通过逆转录定量PCR验证RA中潜在生物标志物或靶基因的表达。mRNA数据集处理结果显示,与健康对照相比,RA患者中有195个DEG。此外,在RA患者中鉴定出10个枢纽基因,并鉴定出4个候选mRNA,如下:盘状大同源物相关蛋白5()、驱动蛋白家族成员20A()、母体胚胎亮氨酸拉链激酶()和核分裂周期80(。最后,通过定量FCA诱导的实验性RA大鼠模型中、、和基因的表达,验证了生物信息学分析结果。本研究结果表明,通过抑制、、和的表达可能成功治疗RA。因此,针对这些基因可能为RA患者带来更有效的治疗方法。

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