Open Access

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

  • Authors:
    • Kun Luo
    • Yumei Zhong
    • Yanding Guo
    • Jingwei Nie
    • Yimei Xu
    • Haiyan Zhou
  • View Affiliations

  • Published online on: August 25, 2023     https://doi.org/10.3892/etm.2023.12179
  • Article Number: 480
  • Copyright: © Luo et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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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 (DLGAP5), kinesin family member 20A (KIF20A), maternal embryonic leucine zipper kinase (MELK) and nuclear division cycle 80 (NDC80). Finally, the bioinformatics analysis results were validated by quantifying the expression of the DLGAP5, KIF20A, MELK and NDC80 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 DLGAP5, KIF20A, MELK and NDC80 expression. Therefore, the targeting of these genes may result in more effective treatments for patients with RA.
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October-2023
Volume 26 Issue 4

Print ISSN: 1792-0981
Online ISSN:1792-1015

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Spandidos Publications style
Luo K, Zhong Y, Guo Y, Nie J, Xu Y and Zhou H: Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis. Exp Ther Med 26: 480, 2023
APA
Luo, K., Zhong, Y., Guo, Y., Nie, J., Xu, Y., & Zhou, H. (2023). Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis. Experimental and Therapeutic Medicine, 26, 480. https://doi.org/10.3892/etm.2023.12179
MLA
Luo, K., Zhong, Y., Guo, Y., Nie, J., Xu, Y., Zhou, H."Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis". Experimental and Therapeutic Medicine 26.4 (2023): 480.
Chicago
Luo, K., Zhong, Y., Guo, Y., Nie, J., Xu, Y., Zhou, H."Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis". Experimental and Therapeutic Medicine 26, no. 4 (2023): 480. https://doi.org/10.3892/etm.2023.12179