Prediction of immune diagnosis and treatment genes of psoriasis based on bioinformatics
Objective To predict the immune diagnosis and treatment genes of psoriasis based on bioinformat-ics.Methods Three datasets of psoriasis gene expression profiles were downloaded from the Gene Expression Om-nibus(GEO)to analyze their gene expression.Functional enrichment analysis was performed on differentially ex-pressed genes related to psoriasis,and a weighted gene co-expression network(WGCNA)was constructed.The di-agnostic value of the predicted genes was evaluated by plotting ROC curves to compare the areas under the curves.In addition,the ssGSEA method was used to evaluate the relationship between psoriasis and immune cell infiltra-tion levels.Results Two target genes(ANKRD18A and ANKRD33B)were discovered.ROC curve analysis suggest-ed that these two genes may play an important role in the pathogenesis of psoriasis.Further gene correlation analy-sis and immune infiltration analysis revealed that these two genes may be important genes for the diagnosis and treatment of psoriasis.Conclusion ANKRD18A and ANKRD33B can be used as potential genes for the diagnosis and treatment of psoriasis.
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