de Almeida Rita M C, Clendenon Sherry G, Richards William G, Boedigheimer Michael, Damore Michael, Rossetti Sandro, Harris Peter C, Herbert Britney-Shea, Xu Wei Min, Wandinger-Ness Angela, Ward Heather H, Glazier James A, Bacallao Robert L
Biocomplexity Institute and Department of Physics, Indiana University, Bloomington, IN, 47405, USA.
Instituto de Física and Instituto Nacional de Ciência e Tecnologia, Universidade Federal do Rio Grande do Sul, 91501-970, Porto Alegre, RS, Brazil.
Hum Genomics. 2016 Nov 21;10(1):37. doi: 10.1186/s40246-016-0095-x.
Autosomal dominant polycystic kidney disease (ADPKD) causes progressive loss of renal function in adults as a consequence of the accumulation of cysts. ADPKD is the most common genetic cause of end-stage renal disease. Mutations in polycystin-1 occur in 87% of cases of ADPKD and mutations in polycystin-2 are found in 12% of ADPKD patients. The complexity of ADPKD has hampered efforts to identify the mechanisms underlying its pathogenesis. No current FDA (Federal Drug Administration)-approved therapies ameliorate ADPKD progression.
We used the de Almeida laboratory's sensitive new transcriptogram method for whole-genome gene expression data analysis to analyze microarray data from cell lines developed from cell isolates of normal kidney and of both non-cystic nephrons and cysts from the kidney of a patient with ADPKD. We compared results obtained using standard Ingenuity Volcano plot analysis, Gene Set Enrichment Analysis (GSEA) and transcriptogram analysis. Transcriptogram analysis confirmed the findings of Ingenuity, GSEA, and published analysis of ADPKD kidney data and also identified multiple new expression changes in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways related to cell growth, cell death, genetic information processing, nucleotide metabolism, signal transduction, immune response, response to stimulus, cellular processes, ion homeostasis and transport and cofactors, vitamins, amino acids, energy, carbohydrates, drugs, lipids, and glycans. Transcriptogram analysis also provides significance metrics which allow us to prioritize further study of these pathways.
Transcriptogram analysis identifies novel pathways altered in ADPKD, providing new avenues to identify both ADPKD's mechanisms of pathogenesis and pharmaceutical targets to ameliorate the progression of the disease.
常染色体显性多囊肾病(ADPKD)会导致成年人肾功能渐进性丧失,这是囊肿积聚的结果。ADPKD是终末期肾病最常见的遗传病因。87%的ADPKD病例存在多囊蛋白-1突变,12%的ADPKD患者存在多囊蛋白-2突变。ADPKD的复杂性阻碍了人们对其发病机制的识别。目前美国食品药品监督管理局(FDA)批准的疗法均无法改善ADPKD的病情进展。
我们使用了德阿尔梅达实验室用于全基因组基因表达数据分析的灵敏新转录图谱方法,来分析从正常肾脏细胞分离物以及一名ADPKD患者肾脏的非囊肿性肾单位和囊肿中培养出的细胞系的微阵列数据。我们比较了使用标准的英睿达火山图分析、基因集富集分析(GSEA)和转录图谱分析所获得的结果。转录图谱分析证实了英睿达、GSEA以及已发表的对ADPKD肾脏数据的分析结果,还识别出了京都基因与基因组百科全书(KEGG)通路中与细胞生长、细胞死亡、遗传信息处理、核苷酸代谢、信号转导、免疫反应、对刺激的反应、细胞过程、离子稳态与转运以及辅因子、维生素、氨基酸、能量、碳水化合物、药物、脂质和聚糖相关的多个新的表达变化。转录图谱分析还提供了显著性指标,使我们能够确定这些通路进一步研究的优先级。
转录图谱分析识别出了ADPKD中改变的新通路,为识别ADPKD的发病机制以及改善疾病进展的药物靶点提供了新途径。