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鉴定类风湿关节炎患者中的枢纽基因和治疗药物。

Identification of hub genes and therapeutic drugs in rheumatoid arthritis patients.

机构信息

Department of Anal and Rectal Diseases, The First Affiliated Hospital, China Medical University, Shenyang, 110001, People's Republic of China.

Molecular Oncology Laboratory of Cancer Research Institute, The First Affiliated Hospital, China Medical University, 155th, Nanjing North Street, Shenyang, 110001, Liaoning, China.

出版信息

Clin Rheumatol. 2021 Aug;40(8):3299-3309. doi: 10.1007/s10067-021-05650-6. Epub 2021 Feb 18.


DOI:10.1007/s10067-021-05650-6
PMID:33604823
Abstract

OBJECTIVES: Rheumatoid arthritis (RA) is considered a chronic autoimmune inflammatory disease that causes great morbidity and shortens life expectancy; however, the precise pathogenesis of RA remains unclear. This study aimed to select hub genes correlated with the development of RA. METHODS: Two gene expression profiles, GSE55235 and GSE12021, obtained from the Gene Expression Omnibus (GEO) were used to identify differentially expressed genes (DEGs) in control and RA samples using GEO2R, followed by other bioinformatics methods, including functional enrichment analysis, protein-protein interaction (PPI) networks, miRNA-hub gene network, and drug-hub gene interactions. In addition, qRT-PCR was finally conducted to confirm the reliability and validity of the expression level of the novel DEGs via freshly collected heparinized blood samples of healthy controls and RA patients. RESULTS: A sum of 136 upregulated and 37 downregulated DEGs were selected. Functional enrichment analysis indicated that all the upregulated DEGs were correlated with immune response, B cell receptor signalling pathway, and adaptive immune response. KEGG pathway enrichment analysis revealed that the upregulated DEGs were mostly related to cytokine-cytokine receptor interaction, primary immunodeficiency, chemokine signalling pathways, and cell adhesion molecules (CAMs). In total, 12 hub genes (IL15, KLRK1, GZMA, CXCR6, IGHV4-38-2, IGLL5, CXCL13, CXCL11, MS4A1, SDC1, SLAMF1, and PDCD1LG2) were identified and all these hub genes were upregulated, of which IGLL5 and IGHV4-38-2 were first reported to be correlated with the pathogenic mechanism and prognosis of RA. Furthermore, we also used qRT-PCR to validate the overexpression of IGLL5 and IGHV4-38-2 in RA patients compared to the healthy controls. In the miRNA-hub gene network, hsa-miR-1185-5p and hsa-miR-3679-5p might inhibit the expression of IGLL5 during the progression of RA. The 15 most promising candidate drugs, which were all approved by the Food and Drug Administration, may assist with the treatment of RA. CONCLUSIONS: Overall, these findings may assist with developing diagnostic, prognostic, and therapeutic biomarkers for RA. Key Points • IGLL5 and IGHV4-38-2 were first reported to be correlated with the pathogenic mechanism and prognosis of RA. • Besides, hsa-miR-1185-5p and hsa-miR-3679-5p may inhibit the expression of IGLL5 during the progression of RA.

摘要

目的:类风湿关节炎(RA)被认为是一种慢性自身免疫性炎症性疾病,它会导致较高的发病率和缩短预期寿命;然而,RA的确切发病机制仍不清楚。本研究旨在筛选与 RA 发展相关的关键基因。

方法:从基因表达综合数据库(GEO)中使用 GEO2R 分别对 GSE55235 和 GSE12021 两个基因表达谱进行分析,以识别对照和 RA 样本中的差异表达基因(DEGs),随后进行其他生物信息学方法,包括功能富集分析、蛋白质-蛋白质相互作用(PPI)网络、miRNA-关键基因网络和药物-关键基因相互作用。此外,最后通过对健康对照者和 RA 患者的肝素化血液样本进行实时定量 PCR(qRT-PCR),以验证新型 DEGs 的表达水平的可靠性和有效性。

结果:共筛选出 136 个上调和 37 个下调的 DEGs。功能富集分析表明,所有上调的 DEGs 均与免疫反应、B 细胞受体信号通路和适应性免疫反应有关。KEGG 通路富集分析显示,上调的 DEGs 主要与细胞因子-细胞因子受体相互作用、原发性免疫缺陷、趋化因子信号通路和细胞黏附分子(CAMs)有关。总共鉴定出 12 个关键基因(IL15、KLRK1、GZMA、CXCR6、IGHV4-38-2、IGLL5、CXCL13、CXCL11、MS4A1、SDC1、SLAMF1 和 PDCD1LG2),所有这些关键基因均上调,其中 IGLL5 和 IGHV4-38-2 是首次报道与 RA 的发病机制和预后相关。此外,我们还使用 qRT-PCR 验证了 RA 患者与健康对照者相比,IGLL5 和 IGHV4-38-2 的过表达。在 miRNA-关键基因网络中,hsa-miR-1185-5p 和 hsa-miR-3679-5p 可能在 RA 进展过程中抑制 IGLL5 的表达。15 种最有前途的候选药物均已获得美国食品和药物管理局的批准,可能有助于 RA 的治疗。

结论:总之,这些发现可能有助于开发 RA 的诊断、预后和治疗生物标志物。关键点:

  • IGLL5 和 IGHV4-38-2 是首次报道与 RA 的发病机制和预后相关。
  • 此外,hsa-miR-1185-5p 和 hsa-miR-3679-5p 可能在 RA 进展过程中抑制 IGLL5 的表达。

相似文献

[1]
Identification of hub genes and therapeutic drugs in rheumatoid arthritis patients.

Clin Rheumatol. 2021-8

[2]
Three hematologic/immune system-specific expressed genes are considered as the potential biomarkers for the diagnosis of early rheumatoid arthritis through bioinformatics analysis.

J Transl Med. 2021-1-6

[3]
Identification of differential key biomarkers in the synovial tissue between rheumatoid arthritis and osteoarthritis using bioinformatics analysis.

Clin Rheumatol. 2021-12

[4]
Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high-throughput data.

Biosci Rep. 2020-12-23

[5]
Identification of pivotal genes and pathways in the synovial tissue of patients with rheumatoid arthritis and osteoarthritis through integrated bioinformatic analysis.

Mol Med Rep. 2020-10

[6]
Screening and identification of potential hub genes and immune cell infiltration in the synovial tissue of rheumatoid arthritis by bioinformatic approach.

Heliyon. 2023-1-10

[7]
Identification of hub genes in rheumatoid arthritis through an integrated bioinformatics approach.

J Orthop Surg Res. 2021-7-16

[8]
Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis.

Med Sci Monit. 2019-3-27

[9]
Analysis of common differential gene expression in synovial cells of osteoarthritis and rheumatoid arthritis.

PLoS One. 2024

[10]
Identification of Tissue-Specific Expressed Hub Genes and Potential Drugs in Rheumatoid Arthritis Using Bioinformatics Analysis.

Front Genet. 2022-3-18

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[2]
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[3]
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[4]
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[5]
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[6]
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