African Journal of
Pharmacy and Pharmacology

  • Abbreviation: Afr. J. Pharm. Pharmacol.
  • Language: English
  • ISSN: 1996-0816
  • DOI: 10.5897/AJPP
  • Start Year: 2007
  • Published Articles: 2286

Full Length Research Paper

Study on transcription regulation network in rheumatoid arthritis via bioinformatics analysis

Jie Chen, Jun Xia*,Siqun Wang, Yibing Wei, Jianguo Wu, Gangyong Huang, Feiyan Chen and Jingcheng Shi    
Department of Orthopedics, Huashan Hospital affiliated to Shanghai Fudan University, No.12, Middle Urumqi Road, Shanghai, 200040, China.    
Email: [email protected]

  •  Accepted: 23 April 2012
  •  Published: 29 May 2012

Abstract

Rheumatoid arthritis (RA) is a systemic, inflammatory autoimmune disease with irreversible joint destruction. It is a form of autoimmunity, however, its cause is incompletely known. The objective of this study was to identify potential transcription regulation between transcription factors and differentially expressed genes in RA by using the microarray data and transcriptional network analysis. In addition, their underlying molecular mechanisms were also explored by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Our results showed that JUN, ETS2, CREB1, PPARG, and SPI1 were crucial transcription factors in our transcriptome networks and these transcription factors could regulate the DEGs expression to involve in RA by promoting or inhibiting effect. For example, JUN could promote FN1 expression; ETS2 promoted FLT1 expression; CREB1 promoted CD4 expression and inhibited F3 expression; PPARG could also inhibit MMP9 expression; SPI1 promoted CSF3R expression. In addition, four significant pathways were identified associated with RA development, including hematopoietic cell lineage, pathways in cancer, MAPK signaling pathway, antigen processing and presentation. ETS2 and PPARG could inhibit hematopoietic cell lineage pathway; ETS2, Jun, and SPI1 promoted the pathway in cancer; CREB1 suppressed MAKP signaling pathway, but promoted antigen processing and presentation. However, further experiments are still needed to confirm the conclusion.

 

Key words: Rheumatoid arthritis, bioinformatics, network.