| Objective:Psoriasis is a chronic inflammatory autoimmune disease,which is believed to be associated with immune imbalance,inflammation,abnormal function of keratinocytes,genetic and environmental factors.However,the pathophysiological mechanism of psoriasis has not been fully elucidated,and the mechanism of traditional Chinese medicine for the treatment of psoriasis needs to be further explored.Gene differential expression analysis and enrichment analysis can determine the biological functions of these genes and the related signaling pathways involved in the occurrence and development of psoriasis.Molecular network analysis can reveal the characteristics of the interaction network of these genes,thereby determining the key genes and core genes related to psoriasis.Using the above information,new directions and possible drug targets can be provided for the treatment of psoriasis,and potential therapeutic Chinese medicine can be predicted.The aim of this study was to screen for psoriasis-related pathogenic genes by using bioinformatics analysis methods,clarify the roles of gene function and related signaling pathways,determine the key genes and potential therapeutic targets,and predict potential therapeutic Chinese medicine using target information.Methods:Gene chip data of psoriasis tissue samples were screened in the GEO database.The limma package in R software was used to select differentially expressed genes.The differential expression genes were subjected to gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)annotation and enrichment analysis using DOSE,top GO,cluster Profiler,and pathview packages in R software.The Gene Set Enrichment Analysis(GSEA)was performed using the local gene expression profile data uploaded to the Lianchuan Biological Cloud Platform.The PPI network analysis was constructed using STRING and visualized using Cytoscape software.The Cyto Hubba plugin in the software was used to calculate the scores of gene nodes according to the degree algorithm,and key genes were selected.Finally,the key genes were mapped to Chinese medicine using the Coremine database and classified according to their pharmacological properties.Results:Using "psoriasis" as the keyword and selecting the following screening criteria in the GEO database: 1)species "Homo sapiens";2)disease and control samples are skin tissue,the gene chip data with the identification numbers GSE13355,GSE14905,and GSE30999 were selected.The three datasets include: GSE13355 with a total of 180 skin tissue samples,including 64 psoriatic lesion skin samples and 58 healthy skin samples;GSE14905 with a total of 82 skin tissue samples,including 33 psoriatic lesion skin samples and 21 healthy skin samples;GSE30999 with a total of 170 skin tissue samples,including 75 psoriatic lesion skin samples and 75 healthy skin samples.The differentially expressed genes were screened from GSE13355,GSE14905,and GSE30999 by using relevant tools and setting conditions.A total of 7 3 4 differentially expressed genes were screened by taking the intersection,including 258 up-regulated genes and 476down-regulated genes.GO enrichment analysis showed that the differentially expressed genes were enriched in the regulation of skin development,epidermal development,and regulation of mitotic nuclear division.KEGG enrichment analysis showed that the main pathways of differentially expressed genes were related to lipid metabolism,cell proliferation and differentiation,and nucleotide metabolism involved in the synthesis and metabolism of DNA and RNA.GSEA analysis showed that the main pathways of differentially expressed genes were related to lipid metabolism,cell proliferation and differentiation,and nucleotide metabolism involved in the synthesis and metabolism of DNA and RNA.After PPI analysis,a network with 684 nodes and 2462 edges was obtained,and 10 key genes were selected by using the degree algorithm: CDK1,CCNB2,CCNA2,CDC20,TOP2 A,CCNB1,DLGAP5,RRM2,AURKB,and BIRC5.Through the mapping of key genes obtained from the bioinformatics analysis into the Coremine Medical database,112 Chinese herbal medicines with potential therapeutic effects were predicted,including Donglingcao,Yemaizhui,and Ebusucao,which were classified into seven categories based on their pharmacological properties,including laxatives,qi-regulating analgesics,lung-nourishing cough suppressants,yin-nourishing kidney tonics,tonics and conditioners,and wind-dispelling dampness-relieving medicines.ConclusionIn this study,bioinformatics analysis was used to screen the differentially expressed genes of psoriasis,analyze their functions and interactions,and screen 1 0 key genes of CDK1,CCNB2,CCNA2,CDC20,TOP2 A,CCNB1,DLGAP5,RRM2,AURKB and BIRC5 in the gene expression spectrum of psoriasis,and found that 112 flavors of traditional Chinese medicine such as winter spirit grass had the potential to treat psoriasis through drug prediction. |
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