摘要
目的通过对GEO数据库中有关糖尿病心肌病的mRNA芯片进行分析,筛选出导致糖尿病心肌病的关键基因。方法使用GEO数据库的在线分析工具GEO2R对数据集GSE4745和GSE5606进行差异基因分析后,在R中绘制差异表达基因火山图,利用在线韦恩图绘制工具分析两个数据集共同表达的差异基因,在R中利用clusterProfile包将差异表达基因进行基因本体和京都基因与基因组百科全书富集分析,GSEA软件进行基因集富集分析,同时使用STRING在线数据库构建差异基因对应蛋白的蛋白互作网络,利用Cytoscape的插件Cytohubba中最大集团中心算法计算出排名前10的基因,在原代大鼠心肌细胞中观察比较筛选出的关键基因在正常组和高糖组的表达情况。结果Pdk4、Ucp3、Hmgcs2、Asl6、Slc2a4与芯片分析结果相符,Pdk4、Ucp3、Hmgcs2在高糖(25 mmol/L)刺激72 h后的心肌细胞中表达增加,Acsl6、Slc2a4在高糖刺激后的心肌细胞中表达下降。结论Pdk4、Ucp3、Hmgcs2、Asl6、Slc2a4可能与糖尿病心肌病的发生发展相关,可能是糖尿病心肌病潜在的生物标志物。
Objective To screen out the key genes leading to diabetic cardiomyopathy by analyzing the mRNA array associated with diabetic cardiomyopathy in the GEO database.Methods The online tool GEO2 R of GEO was used to mine the differentially expressed genes(DEG) in the datasets GSE4745 and GSE5606.R was used to draw the volcano map of the DEG,and the Venn diagram was established online to identify the common DEG shared by the two datasets.The clusterProfile package in R was used for gene ontology annotation and Kyoto encyclopedia of genes and genomes pathway enrichment of the DEG.GSEA was used for gene set enrichment analysis, and STRING for the construction of a protein-protein interaction network.The maximal clique centrality algorithm in the plug-in Cytohubba of Cytoscape was used to determine the top 10 key genes. The expression of key genes was studied in the primary cardiomyocytes of rats and compared between the normal control group and high glucose group.Results The expression of Pdk4,Ucp3,Hmgcs2,Asl6,and Slc2 a4 was consistent with the array analysis results.The expression of Pdk4,Ucp3,and Hmgcs2 was up-regulated while that of Acsl6 and Slc2 a4 was down-regulated in the cardiomyocytes stimulated by high glucose(25 mmol/L) for 72 h.Conclusion Pdk4,Ucp3,Hmgcs2,Asl6,and Slc2 a4 may be associated with the occurrence and development of diabetic cardiomyopathy, and may serve as the potential biomarkers of diabetic cardiomyopathy.
作者
陈嘉敏
李莹
吴会会
刘鹏
郑燕
苏国海
CHEN Jiamin;LI Ying;WU Huihui;LIU Peng;ZHENG Yan;SU Guohai(Research Center of Translational Medicine,Jinan Central Hospital,Cheeloo College of Medicine,Shandong University,Jinan 250013,China;Research Center of Translational Medicine,Central Hospital Affiliated to Shandong First Medical University,Jinan 250013,China)
出处
《中国医学科学院学报》
CAS
CSCD
北大核心
2022年第4期545-554,共10页
Acta Academiae Medicinae Sinicae
基金
国家自然科学基金(81700217、81170087)
山东省自然科学基金(ZR2018MH003、ZR2016HB57)
济南市医学科技创新计划(201805004、201805059)
中国博士后面上项目(2019M662370)
山东省博士后创新项目(202003046)
国际规范的肿瘤免疫治疗和药物性心脏损伤临床实验关键技术平台建设(2020ZX09201025)。
