Abstract
BACKGROUND: Anti-TNF medications are the first-line treatment for Crohn's Disease (CD), despite the fact that a significant portion of the population continues to be ineffectively treated. This research aims to discover accurate intervention targets for the follow-up of anti-TNF non-responders using bioinformatics technology. METHODS: GSE16879, GSE111761, and GSE52746 retrieved from the GEO database. Unbiased differentially expressed genes (DEGs) were discovered utilizing the limma and RobustRankAggreg (RRA) tools. Then, we used weighted gene co-expression network analysis (WGCNA) to identify the module most strongly associated with non responders and subjected this module to Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis with overlapping genes of the DEGs. GSEA analysis applied to check the results of GO and KEGG. Using the Cytoscape program, the protein-protein interaction (PPI) network was constructed. The software's MCODE addon and CytoHubba addon was used to find the most important modules and the hub genes. Subsequently, we employed reverse transcription-polymerase chain reaction (RT-PCR) to confirm hub gene expression from mucosal biopsy specimens. RESULTS: There were a total of 142 genes co-upregulated and 65 genes co-downregulated. According to the WGCNA analysis, 42 genes were duplicated inside the light cyan module. GO and KEGG enrichment analyses of overlapped genes in nonresponders demonstrated an increase in the expression of genes associated with inflammation and immune response, consistent with GSEA results. The PPI network was constructed using 41 protein nodes and 177 edges. After validation, 8 of the top 10 genes were verified to be differentially expressed. CONCLUSION: Our investigation is the first to integrate three CD databases after the anti-TNF medication treatment. We identified IL1B, CCL4, CXCL1, CXCL10, CCL3, CSF3, TREM1, and IL1RN as potential therapeutic targets for patients whose anti-TNF treatment failed.