Identification of key biomarkers and immune infiltration in the synovial tissue of osteoarthritis by bioinformatics analysis.

Weisong Cai, Haohuan Li, Yubiao Zhang, Guangtao Han
Author Information
  1. Weisong Cai: Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.
  2. Haohuan Li: Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.
  3. Yubiao Zhang: Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.
  4. Guangtao Han: Department of Orthopedics, Renmin Hospital of Wuhan University, Wuhan, China.

Abstract

BACKGROUND: Osteoarthritis (OA) is the most common chronic degenerative joint disease and is mainly characterized by cartilage degeneration, subcartilage bone hyperplasia, osteophyte formation and joint space stenosis. Recent studies showed that synovitis might also be an important pathological change of OA. However, the molecular mechanisms of synovitis in OA are still not well understood.
OBJECTIVE: This study was designed to identify key biomarkers and immune infiltration in the synovial tissue of osteoarthritis by bioinformatics analysis.
MATERIALS AND METHODS: The gene expression profiles of GSE12021, GSE55235 and GSE55457 were downloaded from the GEO database. The differentially expressed genes (DEGs) were identified by the LIMMA package in Bioconductor, and functional enrichment analyses were performed. A protein-protein interaction network (PPI) was constructed, and module analysis was performed using STRING and Cytoscape. The CIBERSORT algorithm was used to analyze the immune infiltration of synovial tissue between OA and normal controls.
RESULTS: A total of 106 differentially expressed genes, including 68 downregulated genes and 38 upregulated genes, were detected. The PPI network was assessed, and the most significant module containing 14 hub genes was identified. Gene Ontology analysis revealed that the hub genes were significantly enriched in immune cell chemotaxis and cytokine activity. KEGG pathway analysis showed that the hub genes were significantly enriched in the rheumatoid arthritis signaling pathway, IL-17 signaling pathway and cytokine-cytokine receptor interaction signaling pathway. The immune infiltration profiles varied significantly between osteoarthritis and normal controls. Compared with normal tissue, OA synovial tissue contained a higher proportion of memory B cells, naive CD4+ T cells, regulatory T cells, resting dendritic cells and resting mast cells, while naive CD4+ T cells, activated NK cells, activated mast cells and eosinophils contributed to a relatively lower portion ( > 0.05). Finally, the expression levels of 11 hub genes were confirmed by RT-PCR.
CONCLUSION: The hub genes and the difference in immune infiltration in synovial tissue between osteoarthritis and normal controls might provide new insight for understanding OA development.

Keywords

References

  1. Pain. 2019 Apr;160(4):895-907 [PMID: 30585984]
  2. Bioinformatics. 2012 Mar 15;28(6):882-3 [PMID: 22257669]
  3. Int Immunopharmacol. 2017 Dec;53:114-124 [PMID: 29078090]
  4. Arthritis Rheum. 2011 Feb;63(2):391-400 [PMID: 21279996]
  5. Arthritis Res Ther. 2015 Sep 04;17:239 [PMID: 26337028]
  6. Ital J Biochem. 2005 Sep-Dec;54(3-4):248-57 [PMID: 16688934]
  7. PLoS One. 2013 Dec 11;8(12):e82033 [PMID: 24349175]
  8. J Toxicol Sci. 2012 Feb;37(1):157-67 [PMID: 22293420]
  9. Ann Rheum Dis. 2011 Aug;70(8):1458-60 [PMID: 20378913]
  10. Cancer Med. 2018 Sep;7(9):4496-4508 [PMID: 30117315]
  11. Nature. 2009 Mar 26;458(7237):524-8 [PMID: 19204730]
  12. Genes (Basel). 2018 Jul 04;9(7):null [PMID: 29973527]
  13. Osteoarthritis Cartilage. 2015 Nov;23(11):1843-52 [PMID: 26521730]
  14. Rheumatology (Oxford). 2015 Aug;54(8):1385-91 [PMID: 25691769]
  15. J Bone Miner Res. 2016 May;31(5):911-24 [PMID: 27163679]
  16. Osteoarthritis Cartilage. 2005 May;13(5):361-7 [PMID: 15882559]
  17. Sci Rep. 2017 Jun 14;7(1):3451 [PMID: 28615667]
  18. Osteoarthritis Cartilage. 2017 Oct;25(10):1577-1587 [PMID: 28705606]
  19. J Orthop Res. 2017 Apr;35(4):735-739 [PMID: 27808445]
  20. Rheumatol Int. 2008 Nov;29(1):31-6 [PMID: 18597092]
  21. Acta Orthop. 2012 Feb;83(1):59-64 [PMID: 22206448]
  22. Expert Rev Proteomics. 2019 Mar;16(3):201-213 [PMID: 30654662]
  23. Int J Mol Sci. 2018 Mar 12;19(3):null [PMID: 29534535]
  24. J Orthop Res. 2016 Feb;34(2):262-9 [PMID: 26250062]
  25. Arthritis Res Ther. 2017 Feb 2;19(1):18 [PMID: 28148295]
  26. Cleve Clin J Med. 2002;69 Suppl 1:SI40-6 [PMID: 12086292]
  27. Ann Rheum Dis. 2011 May;70(5):805-11 [PMID: 21187293]
  28. Arthritis Res Ther. 2012 Feb 21;14(1):R38 [PMID: 22353730]
  29. Front Immunol. 2014 Oct 20;5:511 [PMID: 25368616]
  30. PLoS Med. 2016 Dec 13;13(12):e1002194 [PMID: 27959923]
  31. Arthritis Rheum. 2001 Feb;44(2):343-50 [PMID: 11229465]
  32. Ann Rheum Dis. 2011 Oct;70(10):1804-9 [PMID: 21791448]
  33. J Cell Physiol. 2018 Feb;233(2):1342-1358 [PMID: 28513840]
  34. Arthritis Rheum. 2002 Jan;46(1):52-63 [PMID: 11817609]
  35. Nat Rev Rheumatol. 2012 May 29;8(7):390-8 [PMID: 22641138]
  36. Growth Factors. 2018 Dec;36(5-6):263-273 [PMID: 30764675]
  37. Nat Rev Rheumatol. 2010 Nov;6(11):625-35 [PMID: 20924410]
  38. Clin Calcium. 2011 Aug;21(8):1187-92 [PMID: 21814024]