Analysis of common differential gene expression between rheumatoid arthritis and ulcerative colitis

This study employs bioinformatics analysis with the objective of identifying commonly differentially expressed genes (DEGs) in ulcerative colitis (UC) and rheumatoid arthritis (RA), as well as exploring their underlying molecular mechanisms. By doing so, it aims to provide a theoretical basis for investigating the potential associations between these two diseases and developing novel therapeutic strategies.

We downloaded multiple gene expression datasets for Rheumatoid Arthritis (RA) and Ulcerative Colitis (UC) from the Gene Expression Omnibus (GEO) database. For RA, GSE77298, GSE12021, and GSE55457 were selected as the training sets, with GSE89408 serving as the validation set. For UC, GSE36807, GSE87473, and GSE92415 were chosen as the training sets, and GSE13367 as the validation set.During data processing, we first merged the RA and UC data from each training set with standardized data, eliminated batch effects, and obtained combined datasets of differentially expressed genes (DEGs). Subsequently, we conducted a cross-analysis of the DEGs from RA and UC to identify commonly up-regulated and down-regulated genes. To gain a deeper understanding of these DEGs, we constructed a protein-protein interaction (PPI) network and identified hub genes.For further analysis of these hub genes, we utilized the GENEMANIA platform to obtain functional annotations and interaction information. Finally, we validated our analysis results using the GSE89408 and GSE13367 datasets.

After a thorough analysis of the differentially expressed genes in the cells of patients with rheumatoid arthritis (RA) and ulcerative colitis (UC) we found that genes such as CCR7, CD19, CXCL13, CXCR4, and SELL were significantly up-regulated, suggesting their crucial roles in the pathology of both diseases. This discovery not only underscores the importance of these genes as biomarkers for the differential diagnosis of RA and UC, but also highlights key nodes worthy of further validation. In the future, it may be possible to slow or halt disease progression by modulating the expression of these genes.

The results of this study reveal potential common molecular mechanisms underlying rheumatoid arthritis (RA) and ulcerative colitis (UC). The key target genes CCR7, CD19, CXCL13, CXCR4, and SELL highlight common underlying factors associated with both diseases. Further investigation and exploration of these findings can pave the way for new candidate targets and directions in therapeutic research aimed at treating RA and UC. This study emphasizes the importance of utilizing bioinformatics approaches to uncover the mechanisms of complex diseases, providing a promising pathway for the development of more effective and targeted treatments.