Chen Guangshan, Chen Xi, Duan Xingwu, Zhang Runtian, Bai Chunxiao
Department of Dermatology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Department of Orthopedics, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Front Mol Biosci. 2024 Aug 22;11:1439837. doi: 10.3389/fmolb.2024.1439837. eCollection 2024.
The functions and related signal pathways of the gene in the skin lesions of patients with psoriasis were explored through bioinformatics methods to determine the potential specific molecular markers of psoriasis.
The "limma" R package was used to analyze three datasets from the Gene Expression Omnibus database (GSE13355, GSE30999 and GSE106992), and the differential genes were screened. The STRING database was used for gene ontology (GO) enrichment analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis, and protein-protein interaction network integration. Then, the subnetwork was extracted and analyzed by gene set enrichment analysis (GSEA) using the Metascape database to verify the effectiveness of gene differentiation and disease tissue identification.
In this study, 426 differential genes were obtained, of which 322 were significantly upregulated and 104 were significantly downregulated. GO enrichment analysis showed that the differential genes were mainly involved in immunity and metabolism; the KEGG pathway enrichment analysis mainly included the chemokine signal pathway, PPAR signal pathway, and IL-17 signal pathway, among others. Based on the subnetwork analysis, it was found that was mainly involved in the biological processes of viruses, bacteria, and other microorganisms. The pathways obtained by GSEA were mainly related to immunity, metabolism, and antiviral activities. was highly expressed in psoriatic lesions and may thus be helpful in the diagnosis of psoriasis.
The differential genes, biological processes, and signal pathways of psoriasis, especially information related to and diagnostic efficiency of the gene, were obtained by bioinformatics analysis. These results are expected to provide the theoretical basis and new directions for exploring the pathogenesis of psoriasis, in addition to helping with finding diagnostic markers and developing drug treatment targets.
通过生物信息学方法探索该基因在银屑病患者皮肤病变中的功能及相关信号通路，以确定银屑病潜在的特异性分子标志物。
使用“limma”R包分析来自基因表达综合数据库（GSE13355、GSE30999和GSE106992）的三个数据集，筛选差异基因。利用STRING数据库进行基因本体（GO）富集分析、京都基因与基因组百科全书（KEGG）通路富集分析以及蛋白质-蛋白质相互作用网络整合。然后，使用Metascape数据库通过基因集富集分析（GSEA）提取并分析该子网，以验证基因分化和疾病组织鉴定的有效性。
本研究共获得426个差异基因，其中322个显著上调，104个显著下调。GO富集分析表明，差异基因主要参与免疫和代谢；KEGG通路富集分析主要包括趋化因子信号通路、PPAR信号通路和IL-17信号通路等。基于子网分析发现，该基因主要参与病毒、细菌等微生物的生物学过程。GSEA获得的通路主要与免疫、代谢和抗病毒活性相关。该基因在银屑病皮损中高表达，因此可能有助于银屑病的诊断。
通过生物信息学分析获得了银屑病的差异基因、生物学过程和信号通路，尤其是与该基因相关的信息及其诊断效率。这些结果有望为探索银屑病的发病机制提供理论依据和新方向，同时有助于寻找诊断标志物和开发药物治疗靶点。
