4.5 Article

Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

期刊

HUMAN GENOMICS
卷 10, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/s40246-016-0095-x

关键词

Kidney; Transcriptogram; Cystic kidney disease; Autosomal dominant polycystic kidney disease; Bioinformatics; Pathway identification

资金

  1. Brazilian agency CNPq
  2. Brazilian agency CAPES
  3. Brazilian agency FAPERGS
  4. Merit Review [BX001736]
  5. NIH NIDDK [R01 DK079312, R01 DK050141, K01 DK097206]
  6. Dr. Ralph and Marian Falk Medical Research Trust Award
  7. Indiana University Collaborative Research Grant
  8. Amgen
  9. Indiana University
  10. NIH NIGMS/NIEHS/NIBIB [R01 GM11243, R01 GM076692, R01 GM077138]
  11. NIH NCI [P30 CA118100]
  12. Paul Teschan Research Fund [3RX05]

向作者/读者索取更多资源

Background: 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. Results: 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. Conclusions: 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.

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