Kidney Institute, Department of Nephrology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Department of Rheumatology and Immunology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Kidney Blood Press Res. 2019;44(4):533-552. doi: 10.1159/000500458. Epub 2019 Jul 22.
BACKGROUND/AIMS: Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic form of kidney disease. High-throughput microarray analysis has been applied for elucidating key genes and pathways associated with ADPKD. Most genetic profiling data from ADPKD patients have been uploaded to public databases but not thoroughly analyzed. This study integrated 2 human microarray profile datasets to elucidate the potential pathways and protein-protein interactions (PPIs) involved in ADPKD via bioinformatics analysis in order to identify possible therapeutic targets.
The kidney tissue microarray data of ADPKD patients and normal individuals were searched and obtained from NCBI Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, and enriched pathways and central node genes were elucidated using related websites and software according to bioinformatics analysis protocols. Seven DEGs were validated between polycystic kidney disease and control kidney samples by quantitative real-time polymerase chain reaction.
Two original human microarray datasets, GSE7869 and GSE35831, were integrated and thoroughly analyzed. In total, 6,422 and 1,152 DEGs were extracted from GSE7869 and GSE35831, respectively, and of these, 561 DEGs were consistent between the databases (291 upregulated genes and 270 downregulated genes). From 421 nodes, 34 central node genes were obtained from a PPI network complex of DEGs. Two significant modules were selected from the PPI network complex by using Cytotype MCODE. Most of the identified genes are involved in protein binding, extracellular region or space, platelet degranulation, mitochondrion, and metabolic pathways.
The DEGs and related enriched pathways in ADPKD identified through this integrated bioinformatics analysis provide insights into the molecular mechanisms of ADPKD and potential therapeutic strategies. Specifically, abnormal decorin expression in different stages of ADPKD may represent a new therapeutic target in ADPKD, and regulation of metabolism and mitochondrial function in ADPKD may become a focus of future research.
背景/目的:常染色体显性多囊肾病(ADPKD)是最常见的遗传性肾脏疾病。高通量微阵列分析已被应用于阐明与 ADPKD 相关的关键基因和途径。大多数 ADPKD 患者的遗传分析数据已上传至公共数据库,但尚未进行全面分析。本研究通过生物信息学分析整合了 2 个人类微阵列数据集,以阐明 ADPKD 潜在的途径和蛋白-蛋白相互作用(PPIs),从而确定可能的治疗靶点。
从 NCBI Gene Expression Omnibus 中搜索并获取 ADPKD 患者和正常个体的肾脏组织微阵列数据。根据生物信息学分析方案,利用相关网站和软件,确定差异表达基因(DEGs),并阐明富集途径和核心节点基因。通过定量实时聚合酶链反应验证 7 个 DEGs 在多囊肾病和对照肾脏样本之间的表达。
整合并深入分析了两个原始人类微阵列数据集 GSE7869 和 GSE35831。从 GSE7869 和 GSE35831 中分别提取了 6422 和 1152 个 DEGs,其中数据库中有 561 个 DEGs是一致的(291 个上调基因和 270 个下调基因)。从 PPI 网络复杂的 DEGs 中获得了 421 个节点的 34 个核心节点基因。通过 Cytotype MCODE 从 PPI 网络复杂中选择了两个显著模块。鉴定出的大多数基因参与蛋白结合、细胞外区或空间、血小板脱颗粒、线粒体和代谢途径。
通过整合的生物信息学分析,确定了 ADPKD 中的 DEGs 和相关富集途径,为 ADPKD 的分子机制和潜在治疗策略提供了新的思路。具体而言,ADPKD 不同阶段异常的核心蛋白聚糖表达可能代表 ADPKD 的一个新治疗靶点,ADPKD 中代谢和线粒体功能的调节可能成为未来研究的重点。