Exploring the pathogenesis and potential therapeutic drug screening related to ferroptosis in vitiligo based on bioinformatics approach
Objective To analyze ferroptosis genes and related pathogenesis in vitiligo diseases by bioinformatics methods and to explore potential drugs for the treatment of vitiligo through ferroptosis related pathways.Methods Ferroptosis genes were obtained from the FerrDB database and differentially expressed genes in the dataset GSE53146 were analyzed by R.Subsequently,the two were taken to intersect.A machine learning model was constructed by SVM-REF algorithm and LASSO regression to predict key genes for ferroptosis in vitiligo and validated for gene expression by dataset GSE75819.Cell clustering analysis of the GSE203262 single-cell data identified key cell populations that were highly correlated with key genes and involved in vitiligo pathogenesis,which were subsequently validated against gene-expressing cells by the HPA database.The cAMP database was utilized to screen key gene-related small molecule drugs,and molecular docking technology was utilized to verify the ability of small molecule compounds to bind to genes.Finally,single gene immune cell correlation analysis and GSEA-KEGG analysis were performed to explore the immune mechanisms associated with small molecule drugs for treating vitiligo.Results 458 ferroptosis genes and 706 differentially expressed genes were obtained,and 23 genes were intersected by the two.The machine learning prediction model screened RRM2,LCN2,OTUB1,SNCA,CTSB,and WWTR1 as key genes.External dataset validation,single-cell clustering,and HPA data all suggested that the key genes,OTUB1,CTSB,and LCN2,were predominantly expressed in important skin cells such as keratinocytes,melanocytes,and Langerhans cells.High-throughput screening and molecular docking validation were performed to obtain triptolide as a small molecule drug for the treatment of vitiligo via the ferroptosis pathway.Immune cell correlation analysis revealed that triptolide modulates the function of immune cells such as natural killer T cell and activated CD8 T cell by affecting the key genes.GSEA-KEGG analysis revealed that triptolide may treat vitiligo through chemokine signaling pathway,body metabolic signaling pathway and NOD-like receptor signaling pathway.Conclusions Bioinformatics methods were used to discover important iron death evidence and related mechanisms in the pathogenesis of vitiligo,and this was used as an insertion point to screen triptolide as a potential therapeutic agent,which is of great significance to the study of vitiligo pathogenesis and treatment.
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