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肥胖患者性别差异的基因表达谱数据分析 被引量:5

Microarray data analysis of gender related gene expressions in obesity
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摘要 目的采用生物信息学手段对男女肥胖患者与正常人群的差异基因进行分析,研究肥胖个体脂肪细胞基因表达在性别上的差异。方法从公共数据库基因表达数据库(Gene Expression Omnibus,GEO)中下载肥胖相关数据集,采用Qlucore Omics Explorer(QOE)、DAIVID在线分析,并利用蛋白质相互作用数据库分子作用数据库(MINT)进行蛋白质作用网络分析。结果在女性患者中,99条基因表达上调,79条下调,男性患者中有39条高表达基因,23条下调基因。GO分析显示女性肥胖患者的差异基因所涉及GO类别较男性患者多,两组蛋白质作用网络核心节点差异较大,FYN与PDIA3分别是男性女性蛋白质作用网络中重要节点。结论肥胖发生机制存在性别差异,针对节点FYN与PDIA3的后续研究可能对肥胖的发生机制及相应并发症的研究起到重要作用。 Objective Studying the gender differences in the genes expression of obesity by bioinformatics methods.Methods The gene expression profiles downloading from gene expression omnibus were analysed by Qlucore Omics Explorer and DAVID,then the protein-protein interaction network was built by the data extracted from the data set Molecular INTeraction database (MINT).Results There were 99 different expression genes up-regulated and 79 genes down-regulated in obese female while the number of obese male group 39 were up-regulated and 23 down-regulated.The GO terms were found to be more complex in the obese female group.There was also a discrepancy between the hub-nodes of protein-protein interaction networks of female and male groups in which FYN and PDIA3 were important for each group.Conclusions The different profiling of the gene expression may lead to the different mechanisms of obesity in different gender.The two genes,FYN and PDIA3,may have the importance for the future study.
出处 《基础医学与临床》 CSCD 2015年第6期723-728,共6页 Basic and Clinical Medicine
基金 国家自然科学基金(39880032) 广东省领军人才基金(C1030925)
关键词 肥胖 性别 蛋白质作用网络 生物信息学 obesity gender protein-protein interaction network bioinformatics
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