Document Type : Original Article


1 Department of Biology, Damghan Branch, Islamic Azad University, Damghan, Iran.

2 Rheumatology Research Center, Tehran University of Medical Sciences, Tehran, Iran. Inflammation Research Center, Tehran University of Medical Sciences, Tehran, Iran.

3 Department of Biology, School of Sciences, University of Zanjan, Zanjan, Iran.

4 Laboratory of Systems Biology and Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.


 Rheumatoid arthritis (RA) and osteoarthritis (OA) are two of the most prevalent forms of arthritis and may exhibit common etiology and clinical manifestations. Distinguishing between them is very important in determining effective treatment and management strategies.
In the present study, the Affymetrix microarray gene expression dataset (GSE55457) was retrieved from 10 healthy controls, 13 patients with RA, and 10 OA patients and analyzed to identify hub genes so as to distinguish between RA and OA by weighted gene co-expression network (WGCNA) analysis and functional enrichment analysis. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used to construct a protein-protein interaction (PPI) network.
The most significant immune pathways associated with RA disease obtained from functional enrichment analysis were Th17, Th1, and Th2 cell differentiation and cytokine-cytokine receptor interaction pathways. The results of the present study demonstrated that two hub genes,
IL2RB and HLA-DOB, may help differentiate patients with RA from those with OA at the time of diagnosis. This study introduces potential pathways and candidate biomarker genes to discriminate between RA and OA. 


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