ZHENG Chaoyue, ZHANG Shengxiao, HE Peifeng, YU Qi, CHENG Lingjing, FENG Shuang, KONG Teng, SUN Xiangfei. Identification of differentially expressed genes in dermatomyositis and prediction of therapeutic drugs[J]. Journal of Clinical Medicine in Practice, 2023, 27(15): 86-92. DOI: 10.7619/jcmp.20231190
Citation: ZHENG Chaoyue, ZHANG Shengxiao, HE Peifeng, YU Qi, CHENG Lingjing, FENG Shuang, KONG Teng, SUN Xiangfei. Identification of differentially expressed genes in dermatomyositis and prediction of therapeutic drugs[J]. Journal of Clinical Medicine in Practice, 2023, 27(15): 86-92. DOI: 10.7619/jcmp.20231190

Identification of differentially expressed genes in dermatomyositis and prediction of therapeutic drugs

  • Objective To investigate the possible pathogenesis, potential therapeutic targets and drugs of dermatomyositis (DM).
    Methods Chip information was downloaded from the Gene Expression Synthesis (GEO) database for healthy people and DM patients who met screening criteria. Differentially expressed genes (DEGs) were screened using R language related software packages; the gene ontology (GO) functional enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of DEGs were analyzed. The protein interaction network was constructed using STRING online database and Cytoscape software, and key genes were screened and verified. CIBERSORT algorithm was used to analyze the infiltration of immune cells, and the correlation between the expression of hub genes and the abundance of immune cells was analyzed. The DREIMT online analysis tool and Coremine Medical database were used to predict potential drugs to treat DM diseases.
    Results Compared with healthy people, 402 DEGs were up-regulated and 150 DEGs were down-regulated in muscle tissue, 686 DEGs were up-regulated and 284 DEGs were down-regulated in skin tissue, and 170 DEGs were shared between muscle and skin. The results of GO and KEGG enrichment analysis showed that the above DEGs mainly enriched in the innate immune response, defense response to viruses, cytoplasm, plasma membrane and other items, and enriched in the novel coronavirus infection disease, influenza-A, measles, hepatitis C and other pathways. A total of 10 core genes were screened, which were STAT1, MX1, IFIT3, OAS2, IFI35, RSAD2, IFIT1, OAS1, ISG15 and IRF7. Among the 22 kinds of immune cell infiltration, plasma cell infiltration dominated in muscle tissue, while M2 macrophages penetrated in skin tissue in large numbers. Through the analysis of core genes, the top 10 small molecule chemical drugs and 9 traditional Chinese medicines were predicted.
    Conclusion In this study, the hub genes and drugs screened by bioinformatics method may play an important role in the treatment of DM.
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