Integrating bioinformatics and experimental analysis to explore key genes and mechanisms in ulcerative colitis and gout

Ulcerative colitis (UC) is a chronic nonspecific inflammatory disease of the gut, and gout is a form of inflammatory arthritis. Previous studies have shown that UC and gout are related diseases, but the specific etiological mechanisms underlying their coexistence remain unclear. Transcriptome datasets related to UC and gout were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained using the R “limma” package. Hub genes were obtained using weighted gene co-expression network (WGCNA), protein–protein interaction (PPI) network, and three machine learning algorithms. Gene function enrichment analysis was used to explore the functions and regulatory pathways of co-DEGs. Their reliability and potential mechanisms were explored through immunohistochemistry experiments and cell experiments. In addition, we performed transcriptional regulation, gene set enrichment (GSEA), and immune infiltration analyses of the hub genes. Based on the DEGs, 29 common differential genes were identified, mainly enriched in immune-related pathways. Immune cell infiltration analysis revealed significant dysregulation of several immune cell populations. Receiver operating characteristic (ROC) analysis indicates that matrix metalloproteinase-1 (MMP1) may serve as a tissue biomarker reflecting inflammatory activity in ulcerative colitis, while also exhibiting disease-associated expression patterns in existing gout datasets. Immunohistochemical staining showed that the pivotal gene was widely expressed in clinical samples and markedly expressed in animal models. In addition, cell experiments indicated that the IL-17 signaling pathway may exert its effects by regulating MMP1. This study found that the MMP1 and IL-17 signaling pathways may play a role in UC and also in gout, providing a potential new hypothesis regarding the pathogenesis of these two diseases.