姜秋竹, 杨会, 周晓霜. 狼疮肾炎中基因表达芯片的生物信息学分析[J]. 临床肾脏病杂志, 2020, 20(10): 775-779. DOI: 10.3969/j.issn.1671-2390.2020.10.002
    引用本文: 姜秋竹, 杨会, 周晓霜. 狼疮肾炎中基因表达芯片的生物信息学分析[J]. 临床肾脏病杂志, 2020, 20(10): 775-779. DOI: 10.3969/j.issn.1671-2390.2020.10.002
    shu
    JIANG Qiu-zhu, YANG Hui, ZHOU Xiao-shuang. Bioinformatics analysis of gene expression microarray in lupus nephritis[J]. Journal of Clinical Nephrology, 2020, 20(10): 775-779. DOI: 10.3969/j.issn.1671-2390.2020.10.002
    Citation: JIANG Qiu-zhu, YANG Hui, ZHOU Xiao-shuang. Bioinformatics analysis of gene expression microarray in lupus nephritis[J]. Journal of Clinical Nephrology, 2020, 20(10): 775-779. DOI: 10.3969/j.issn.1671-2390.2020.10.002
    shu

    狼疮肾炎中基因表达芯片的生物信息学分析

    Bioinformatics analysis of gene expression microarray in lupus nephritis

      摘要
    • 摘要: 目的 采用生物信息学方法探讨狼疮肾炎（lupus nephritis，LN）发生的潜在机制。方法 通过GEO数据库获得正常肾组织和LN肾组织的基因表达谱，分析二者基因表达情况，寻找差异基因，利用DAVID数据库对LN发生发展过程中的差异基因进行富集分析，使用STRING数据库和Cytoscape对差异基因进行可视化分析。结果 筛选出146个上调基因和28个下调基因。在细胞通路方面，差异基因主要参与I型干扰素信号通路等；在细胞定位方面，差异基因主要分布在胞外体等；在分子功能方面，差异基因主要与MHCⅡ类受体活性等相关。KEGG分析结果表明，差异基因与甲型流感病毒感染、金黄色葡萄球菌感染、单纯疱疹病毒感染、利什曼病和哮喘等通路有关。筛选发现IFI35、MX2、OAS3、IFI6、IRF7、OAS2、IFIT2、RSAD2、OAS1、MX1是LN发生风险相关蛋白相互作用网络中的核心基因。结论 通过对数据集的分析，利用生物信息学方法找出了LN发生过程中的关键基因，为寻找有价值的LN标志物提供了依据。

       

      Abstract: Objective To explore the potential pathogenesis of lupus nephritis(LN)with bioinformatics method.Methods The gene expression profiles of normal kidney tissue and LN kidney tissue were obtained by GEO database.The gene expression in the two kinds of tissues was analyzed look for differential genes.Enrichment analysis of the differential genes in the progression of LN were performed by DAVID database,and the differential genes were visualized analytically by STRING database and Cytoscape.Results 146 up-regulated genes and 28 down-regulated genes were screened out.In terms of cellular pathway,differential genes are mainly involved in type I interferon signaling pathway;in cell localization,differential genes are mainly distributed in extracellular bodies;in molecular function,differential genes are mainly related to MHC class II receptor activity.KEGG analysis showed that the differential genes were associated with the signaling pathways for influenza A virus infection,Staphylococcus aureus infection,herpes simplex virus infection,leishmaniasis and asthma.By screening it was found that IFI35,MX2,OAS3,IFI6,IRF7,OAS2,IFIT2,RSAD2,OAS1,MX1 are the core genes in the interaction network of proteins related to LN risk.Conclusions Through the analysis of the data set,the key genes in the progression of LN were found by using bioinformatics method,which provided the basis for finding some valuable LN markers.

       

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