Skip to main content

Advertisement

Log in

Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis

  • Original Article
  • Published:
Immunogenetics Aims and scope Submit manuscript

Abstract

Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees from the Gene Expression Omnibus database, analyzed the differentially expressed genes in the normal and RA groups, and assessed their enrichment in functions and pathways using bioinformatics methods and the STRING online database to establish protein–protein interaction networks. Cytoscape software was used to obtain 10 hub genes; receiver operating characteristic (ROC) curves were calculated for each hub gene and differential expression analysis of the two groups of hub genes. The CIBERSORT algorithm was used to impute immune infiltration. We identified the signaling pathways that play important roles in RA and 10 hub genes: Ccr1, Ccr2, Ccr5, Ccr7, Cxcl5, Cxcl6, Cxcl13, Ccl13, Adcy2, and Pnoc. The diagnostic value of these 10 hub genes for RA was confirmed using ROC curves and expression analysis. Adcy2, Cxcl13, and Ccr5 are strongly associated with RA development. The study also revealed that the differential infiltration profile of different inflammatory immune cells in the synovial tissue of RA is an extremely critical factor in RA progression. This study may contribute to the understanding of signaling pathways and biological processes associated with RA and the role of inflammatory immune infiltration in the pathogenesis of RA. In addition, this study shows that Adcy2, Cxcl13, and Ccr5 have the potential to be biomarkers for RA treatment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Availability of data and material

All data are real and guarantee the validity of results.

References

Download references

Author information

Authors and Affiliations

Authors

Contributions

Sheng Fang conceived the original idea and designed the outline of the study. Xin Xu helped collected and organized the data. Lin Zhong and An-Quan Wang helped check the data. Wei-Lu Gao, Ming Lu, and Zong-Sheng Yin aided in revising the manuscript. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Zong-Sheng Yin.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fang, S., Xu, X., Zhong, L. et al. Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis. Immunogenetics 73, 435–448 (2021). https://doi.org/10.1007/s00251-021-01224-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00251-021-01224-7

Keywords

Navigation