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基于GEO数据库的IgA肾病基因的筛选和生物信息学分析 被引量:1

Screening and bioinformatics analysis of IgA nephropathy gene based upon GEO database
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摘要 目的通过生物信息学分析鉴定IgA肾病的生物标志物,旨在阐明IgA肾病疾病进展的可能分子机制。方法从GEO数据库下载包含IgA肾病患者和健康对照的微阵列数据集GSE104948、GSE93798和GSE37460数据集,并使用limma R包进行分析,以获得差异表达基因。然后进行GO分析和KEGG通路富集分析,运用STRING和Cytoscape软件构建蛋白互作网络以阐明IgA肾病的分子机制。结果应用limma R包分析鉴定出30个DEG,包括16个上调基因,14个下调基因。FN1和COL1A2等上调基因主要参与细胞外基质受体互作及PI3K-Akt信号通路。IgA肾病中ALB基因显著下调。FN1,COL1A2,ALB和FABP1基因被筛选为枢纽基因。结论FN1、COL1A2、ALB和FABP基因可能在IgA肾病的发展中起重要作用,并可能作为诊断和治疗IgA肾病的潜在分子靶标。 Objective To identify novel biomarkers of IgA nephropathy(IgAN)through bioinformatics analysis and elucidate the possible molecular mechanism of IgAN.Methods The microarray datasets of GSE104948,GSE93798 and GSE37460 containing IgAN patients and healthy controls were downloaded from the GEO database and analyzed by using the limma R package for obtaining differentially expressed genes.Then GO and KEGG pathway enrichment analyses were performed.And STRING and Cytoscape software were utilized for constructing protein interaction networks for elucidating the molecular mechanism of IgAN.Results Thirty DEGs were identified,including 16 up-regulated genes and 14 down-regulated genes.Up-regulated genes such as FN1 and COL1A2 are mainly involved in extracellular matrix receptor interaction and PI3K-Akt signaling pathway.ALB gene was significantly down-regulated in IgA nephropathy.And FN1,COL1A2,ALB and FABP genes were screened as hub genes.Conclusion FN1,COL1A2,ALB and FABP genes may play an important role in the development of IgA nephropathy and serve as potential molecular targets for diagnosing and treating IgAN.
作者 刘音 赵彬 谢裕赛 杨涛 Liu Yin;Zhao Bin;Xie Yu-sai;Yang Tao(Department of Nephrology,Beijing Haidian Hospital,Beijing 100080,China;Department of Pathology,College of Basic Medical Sciences,China Medical University,Shenyang 110112,China)
出处 《临床肾脏病杂志》 2021年第3期194-198,共5页 Journal Of Clinical Nephrology
关键词 GEO数据库 生物信息学 IGA肾病 差异表达基因 枢纽基因 GEO database Bioinformatics IgA nephropathy Differentially expressed genes Hub genes
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