摘要
BACKGROUND The pathogenesis of ulcerative colitis(UC)is complex,and recent therapeutic advances remain unable to fully alleviate the condition.AIM To inform the development of novel UC treatments,bioinformatics was used to explore the autophagy-related pathogenesis associated with the active phase of UC.METHODS The GEO database was searched for UC-related datasets that included healthy controls who met the screening criteria.Differential analysis was conducted to obtain differentially expressed genes(DEGs).Au-tophagy-related targets were collected and intersected with the DEGs to identiy differentially expressed autophagy-related genes(DEARGs)associated with active UC.DEARGs were then subjected to KEGG,GO,and DisGeNET disease enrichment analyses using R software.Differential analysis of immune infiltrating cells was performed using the CiberSort algorithm.The least absolute shrinkage and selection operator algorithm and protein-protein interaction network were used to narrow down the DEARGs,and the top five targets in the Dgree ranking were designated as core targets.RESULTS A total of 4822 DEGs were obtained,of which 58 were classified as DEARGs.SERPINA1,BAG3,HSPA5,CASP1,and CX3CL1 were identified as core targets.GO enrichment analysis revealed that DEARGs were primarily enriched in processes related to autophagy regulation and macroautophagy.KEGG enrichment analysis showed that DEARGs were predominantly associated with NOD-like receptor signaling and other signaling pathways.Disease enrichment analysis indicated that DEARGs were significantly linked to diseases such as malignant glioma and middle cerebral artery occlusion.Immune infiltration analysis demonstrated a higher presence of immune cells like activated memory CD4 T cells and follicular helper T cells in active UC patients than in healthy controls.CONCLUSION Autophagy is closely related to the active phase of UC and the potential targets obtained from the analysis in this study may provide new insight into the treatment of active UC patients.
