Qu W, Han C, Li M, Zhang J, Li L
Endocrinology Department, Jinan Military General Hospital, Jinan, China.
Department of Cadre Ward No.1, Jinan Military General Hospital, Jinan, China.
Exp Clin Endocrinol Diabetes. 2015 Jun;123(6):353-9. doi: 10.1055/s-0035-1548849. Epub 2015 Apr 28.
To explore the molecular mechanisms of diabetic nephropathy (DN) progression and provide the theoretical basis for treating DN, GSE1009 microarray data were downloaded from Gene Expression Omnibus database. Microarray data were obtained from glomeruli isolated from normal kidneys (n=3) and kidneys from patients with DN (n=3). We first screened the differentially expressed genes (DEGs) in kidneys by the Linear Models for Microarray Data package in R. Then the function of DEGs in DN was explored through Gene Ontology (GO) and KEGG pathway enrichment analyses. Critical DEGs for DN progression were investigated by constructing PPI network and mining significant modules. Afterwards, enriched protein domains of modules were analyzed by Interpro and DAVID. At last, the regulatory miRNAs for DEGs were calculated by WebGestalt, and DEGs-miRNAs network was visualized with Cytoscape. A total of 666 DEGs including 384 up- and 282 down-regulated genes were screened out. The up-regulated DEGs were significantly enriched in plasma membrane and signal transmission, and mainly participated in pathways of cytokine-cytokine receptor and neuroactive ligand-receptor interaction. The down-regulated DEGs significantly enriched in extracellular region and cytoskeletal protein binding, and mainly participated in ECM-receptor interaction and dilated cardiomyopathy. 2 PPI networks were constructed with confidence score>0.4. One significant module obtained from PPI network for up-regulated DEGs mainly enriched in protein domain of rhodopsin-like G protein-coupled receptors. The down-regulated DEGs were mainly regulated by 10 miRNAs clusters. Together, we constructed a comprehensive molecular network for DN progression and miR-1 and miR-25 might be theoretical targets for DN.
为探究糖尿病肾病（DN）进展的分子机制并为DN治疗提供理论依据，从基因表达综合数据库下载了GSE1009芯片数据。芯片数据取自分离自正常肾脏的肾小球（n = 3）和DN患者的肾脏（n = 3）。我们首先通过R语言中的微阵列数据线性模型软件包筛选肾脏中的差异表达基因（DEG）。然后通过基因本体论（GO）和KEGG通路富集分析探究DEG在DN中的功能。通过构建蛋白质-蛋白质相互作用（PPI）网络并挖掘重要模块来研究DN进展的关键DEG。之后，通过Interpro和DAVID分析模块的富集蛋白结构域。最后，通过WebGestalt计算DEG的调控微小RNA（miRNA），并用Cytoscape可视化DEG-miRNA网络。共筛选出666个DEG，其中包括384个上调基因和282个下调基因。上调的DEG在质膜和信号转导中显著富集，主要参与细胞因子-细胞因子受体和神经活性配体-受体相互作用途径。下调的DEG在细胞外区域和细胞骨架蛋白结合中显著富集，主要参与细胞外基质-受体相互作用和扩张型心肌病。构建了2个置信度得分>0.4的PPI网络。从上调DEG的PPI网络中获得的一个重要模块主要富集在视紫红质样G蛋白偶联受体的蛋白结构域中。下调的DEG主要受10个miRNA簇调控。我们共同构建了一个DN进展的综合分子网络，miR-1和miR-25可能是DN的理论靶点。
