摘要： 目的 通过生物信息学技术探讨硬皮病发病的相关分子机制。方法 通过基因表达图谱数据库获取GSE117928芯片数据。使用R软件，|logFC|>1，调整P < 0.05为过滤条件，筛选出硬皮病差异基因，然后将差异基因进行蛋白质-蛋白质相互作用网络（PPI）分析及基因本体（GO）功能富集分析。GSE117928芯片数据进行基因集富集分析（GSEA）通路分析和免疫细胞浸润分析，获取富集通路和免疫细胞相对含量。结果 获得硬皮病差异基因722个，其中上调基因298个，下调基因424个；核心靶点包括RPS27A、BTRC、FBXO32、ZBTB16、FBXO21、VHL、ATG7、CBLB、ANAPC1、COMMD9、CSNK1E、RPS8、MPHOSPH10、KRR1、RPL5。GO富集生物功能包括中性粒细胞活化参与免疫反应、嗜中性粒细胞脱颗粒、髓系细胞分化、对脂多糖反应、积极调节防御反应等。GSEA富集通路中硬皮病组排名前五位通路包括氨基糖和核苷酸糖代谢、溶酶体、谷胱甘肽代谢、糖酵解糖异生和半乳糖代谢通路；正常对照组排名前五位通路为自然杀伤细胞介质细胞毒性、剪接体、泛素介导的蛋白水解、小细胞肺癌、T细胞受体信号通路。免疫浸润结果显示正常对照组CD8⁺ T细胞、幼稚CD4⁺ T细胞相对含量明显增加，而硬皮病组单核细胞相对含量明显增加。结论 硬皮病的发病机制可能是通过调节RPS27A、BTRC、FBXO32、ZBTB16、FBXO21、VHL、ATG7、CBLB、ANAPC1等基因，参与中性粒细胞活化参与免疫反应、嗜中性粒细胞脱颗粒等生物过程，上调氨基糖和核苷酸糖代谢、溶酶体、谷胱甘肽代谢、糖酵解糖异生和半乳糖代谢等通路来完成的。硬皮病发病与单核细胞增多密切相关。

基于生物信息学分析硬皮病的发病机制

郭嘉¹, 卞华², 陈爽¹, 单雨¹, 卞博^1,2

1. 河南中医药大学第二附属医院, 河南省中医院风湿病科, 郑州 450008;
2. 南阳理工学院张仲景国医国药学院, 河南省张仲景方药与免疫调节重点实验室, 河南 南阳 473004

收稿日期:2021-05-25出版日期:2022-09-30发布日期:2022-09-03
通讯作者:卞华E-mail:biancrown@163.com
作者简介:郭嘉（1994-），男，硕士研究生.
基金资助:国家自然科学基金（81774300，82074415）


关键词: 硬皮病, 发病机制, 生物信息学技术
Abstract: Objective To use bioinformatics to explore the molecular mechanisms underlying scleroderma. Methods R software was used to search the chip GSE117928, and the differential genes were screened by the filter conditions|logFC|>1 and adj P < 0.05. Protein-protein interaction(PPI) and gene ontology(GO) functional enrichment were used to analyze the differentially expressed genes. The chip data were analyzed by gene set enrichment analysis(GSEA) pathway enrichment and immune infiltration to obtain the enrichment pathway and the relative content of immune cells. Results A total of 722 differentially expresseol genes were obtained, including 298 up-regulated genes and 424 down-regulated genes. The core targets were RPS27A, BTRC, FBXO32, ZBTB16, FBXO21, VHL, ATG7, CBLB, ANAPC1, COMMD9, CSNK1E, RPS8, MPHOSPH10, KRR1, and RPL5, as well as GO enrichment, neutrophil activation involved in immune response, neutrophil degranulation, myeloid cell differentiation, lipopolysaccharide, active regulation of defense response, etc. The GSEA enrichment pathway in the normal group included natural killer cell cytotoxicity, splice body, ubiquitin-mediated proteolysis, small cell lung cancer, and T cell receptor signaling pathways. The GSEA enrichment pathway in the scleroderma group included amino sugar and nucleotide glucose metabolism, lysosome, glutathione metabolism, glycolysis glutathione metabolism pathway, and galactose metabolism pathway. The results of immune infiltration showed that the expression of CD8⁺T cells and immature CD4⁺T cells was significantly up-regulated in the normal group, whereas the expression of monocytes was significantly up-regulated in the scleroderma group. Conclusion The pathogenesis of scleroderma may be related to the regulation of RPS27A,BTRC,FBXO32,ZBTB16,FBXO21,VHL, ATG7,CBLB,ANAPC1, and other genes involved in neutrophil activation involved in immune response and neutrophil degranulation. Pathological phenomena are caused by the up-regulation of amino-sugar and nucleotide sugar metabolism, lysosomes, glutathione metabolism, glycolysis gluconeogenesis, and galactose metabolism. The pathogenesis of scleroderma is closely associated with mononucleosis.
Key words: scleroderma, pathogenesis, bioinformatics technology
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