中国麻风皮肤病杂志 ›› 2022, Vol. 38 ›› Issue (6): 359-364.doi: 10.12144/zgmfskin202206359

• 论著 • 上一篇    下一篇

慢性自发性荨麻疹发病机制的生物信息学研究

贾秀娟1,乌日娜1,萨琦拉1,王百灵1,贺希格图1,特格喜白音2,郭靖雪3,齐宝鹏3,木其日1   

  1. 1内蒙古国际蒙医医院皮肤科，呼和浩特，010020；
    2内蒙古国际蒙医医院创新蒙医药工程研究中心，呼和浩特，010070；
    3内蒙古医科大学，呼和浩特，010110
  • 出版日期:2022-06-15 发布日期:2022-04-14
  • 通讯作者: 木其日，E-mail: muqiri28@163.com

Bioinformatics study on the pathogenesis of chronic spontaneous urticaria

JIA Xiujuan1, WU Rina1, SA Qila1, WANG Bailing1, HE Xigetu1, Tegexibaiyin2, GUO Jingxue3, QI Baopeng3, MU Qiri1   

  1. 1 Department of Dermatology, International Mongolian Hospital of Inner Mongolia, Hohhot 010020, China; 2 Innovative Mongolian Pharmaceutical Preparations Laboratory of Inner Mongolia, Inner Mongolia International Mongolian Hospital, Hohhot 010070, China; 3 Inner Mongolia Medical University, Hohhot 010110, China
  • Online:2022-06-15 Published:2022-04-14
  • Contact: MU Qiri, E-mail: muqiri28@163.com

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摘要： 目的：利用生物信息学技术筛选慢性自发性荨麻疹（CSU）的关键差异表达基因，为研究CSU的生物学机制与治疗靶点提供新的思路。方法：从Gene Expression Omnibus（GEO）数据库下载GSE72541数据集，使用R语言limma包筛选CSU组与健康对照组间的差异表达基因，并通过clusterProfiler R包、STRING在线软件、Cytoscape3.8.2软件的MCODE插件分别对差异表达基因的功能、通路富集与蛋白相互作用进行分析。结果：研究发现CSU组与健康对照组共有86个差异表达基因，其中上调基因64个，下调基因22个(|logFC|>1 & P.Val<0.05)，GO分析显示，差异表达基因主要富集在血小板活化、血液凝固、中性粒细胞脱颗粒等生物过程；KEGG分析显示，主要与造血细胞系、移植物抗宿主病、金黄色葡萄球菌等相关。此外，建立的PPI网络筛选出62个节点及15个关键基因（CXCL10, MMP9, SELP, MME, ITGA2B, ITGB3, CLU, GP6, C5AR1, C6orf25, GP1BB, VWF, CR1, GP9, PLAU）。结论：ITGB3，ITGA2B，MMP9及CR1等基因可能与CSU的发病密切相关。

关键词: 荨麻疹, 发病机制, 生物信息学, 差异表达基因

Abstract: Objective: To identify the key differentially expressed genes of Chronic Spontaneous Urticaria (CSU) ，in order to provide the basis of studying the pathogenesis and targeted therapy of CSU. Methods: GSE72541 data set was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes between CSU group and healthy control group were screened by R language limma package. The function of differentially expressed genes, their pathway enrichment and their protein interactions were analyzed by clusterprofiler R package and STRING online software and the MCODE plug-in of Cytoscape 3.8.2 Software. Results: The 86 differentially expressed genes in CSU group and healthy control group were screened, which including 64 up-regulated genes and 22 down-regulated genes (|logFC|>1 & adj.P.Val<0.05). GO enrichment analysis showed that the differentially expressed genes were mainly concentrated in biological processes such as platelet activation, blood coagulation and neutrophil degranulation; KEGG analysis showed that it was mainly related to hematopoietic cell line, graft-versus-host disease, Staphylococcus aureus, etc. In addition, the established PPI network screened 62 nodes and 14 key genes (CXCL10, MMP9, SELP, MME, ITGB3, CLU, GP6, C5AR1, C6orf2, GP1BB, VWF, CR1, GP9, PLAU). Conclusion: ITGB3，ITGA2B，MMP9, CR1 and other genes may be closely associated with the pathogenesis of CSU.

Key words: urticaria, pathogenesis, bioinformatics, differentially expressed genes