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      Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

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          Abstract

          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.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40246-016-0095-x) contains supplementary material, which is available to authorized users.

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          Most cited references91

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          RIG-I-mediated antiviral responses to single-stranded RNA bearing 5'-phosphates.

          Double-stranded RNA (dsRNA) produced during viral replication is believed to be the critical trigger for activation of antiviral immunity mediated by the RNA helicase enzymes retinoic acid-inducible gene I (RIG-I) and melanoma differentiation-associated gene 5 (MDA5). We showed that influenza A virus infection does not generate dsRNA and that RIG-I is activated by viral genomic single-stranded RNA (ssRNA) bearing 5'-phosphates. This is blocked by the influenza protein nonstructured protein 1 (NS1), which is found in a complex with RIG-I in infected cells. These results identify RIG-I as a ssRNA sensor and potential target of viral immune evasion and suggest that its ability to sense 5'-phosphorylated RNA evolved in the innate immune system as a means of discriminating between self and nonself.
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            Autosomal dominant polycystic kidney disease.

            Autosomal dominant polycystic kidney disease is the most prevalent, potentially lethal, monogenic disorder. It is associated with large interfamilial and intrafamilial variability, which can be explained to a large extent by its genetic heterogeneity and modifier genes. An increased understanding of the disorder's underlying genetic, molecular, and cellular mechanisms and a better appreciation of its progression and systemic manifestations have laid out the foundation for the development of clinical trials and potentially effective treatments.
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              Defective Glucose Metabolism in Polycystic Kidney Disease Identifies A Novel Therapeutic Paradigm

              Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a common genetic disorder characterized by bilateral renal cyst formation 1 . Recent identification of signaling cascades de-regulated in ADPKD has led to the initiation of several clinical trials, but an approved therapy is still lacking 2,3 . Using a metabolomic approach here we identify a pathogenic pathway in ADPKD which can be safely targeted for therapy. We show that mutation in PKD1 results in enhanced glycolysis in cells, in a murine model of PKD, and in human-derived ADPKD kidneys. Glucose deprivation reduced proliferation and sensitized PKD1 mutant cells to apoptosis. Notably, treatment of two distinct PKD mouse models with 2-deoxyglucose (2DG) ameliorates kidney volume, cystic index and reduced proliferation rates. These metabolic alterations depend on the ERK pathway acting in a dual manner by inhibiting the LKB1-AMPK axis on the one hand while activating the mTORC1-glycolytic cascade on the other. Enhanced metabolic rates further inhibit AMPK. Forced activation of AMPK acts in a negative feedback loop restoring normal ERK activity. Taken together, these data indicate that defective glucose metabolism is intimately involved in the pathobiology of ADPKD. Our findings provide a strong rationale for a novel therapeutic paradigm using existing drugs, either individually or in combination.
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                Author and article information

                Contributors
                rita@if.ufrgs.br
                sgclende@indiana.edu
                brichard@amgen.com
                mboedigh@amgen.com
                mdamore@amgen.com
                Sandro.rosssetti@otsuka-us.com
                Harris.Peter@mayo.edu
                brherber@iu.edu
                wxu1@iu.edu
                awandinger@salud.unm.edu
                hhward@unm.edu
                glazier@indiana.edu
                rbacalla@iupui.edu
                Journal
                Hum Genomics
                Hum. Genomics
                Human Genomics
                BioMed Central (London )
                1473-9542
                1479-7364
                21 November 2016
                21 November 2016
                2016
                : 10
                : 37
                Affiliations
                [1 ]Biocomplexity Institute and Department of Physics, Indiana University, Bloomington, IN 47405 USA
                [2 ]Instituto de Física and Instituto Nacional de Ciência e Tecnologia, Universidade Federal do Rio Grande do Sul, 91501-970 Porto Alegre, RS Brazil
                [3 ]Biocomplexity Institute and Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN 47405 USA
                [4 ]AMGEN Inc., One Amgen Center Drive, Thousand Oaks, CA 91320-1799 USA
                [5 ]Division of Nephrology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
                [6 ]Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
                [7 ]Division of Nephrology, Department of Medicine, Richard Roudebush VAMC and Indiana University School of Medicine, Indianapolis, IN 46202 USA
                [8 ]Department of Pathology MSC08-4640 and Cancer Research and Treatment Center, University of New Mexico Health Sciences Center, Albuquerque, NM 87131 USA
                [9 ]Division of Nephrology, Department of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131 USA
                Article
                95
                10.1186/s40246-016-0095-x
                5117508
                27871310
                709c2255-012a-43fb-b9dd-149adc9ab766
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 27 August 2016
                : 4 November 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100008590, Dr. Ralph and Marian Falk Medical Research Trust;
                Funded by: FundRef http://dx.doi.org/10.13039/100000738, U.S. Department of Veterans Affairs;
                Award ID: BX001736
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: DK 079312
                Award ID: DK097206
                Award ID: DK050141
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100002429, Amgen;
                Funded by: Indiana University Collaborative Research Grant
                Funded by: CNPq
                Funded by: CAPES
                Funded by: FAPERGS
                Funded by: Paul Teschan Research Fund
                Award ID: 3RX05
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: CA118100
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: GM11243
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000066, National Institute of Environmental Health Sciences;
                Award ID: GM076692
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000070, National Institute of Biomedical Imaging and Bioengineering;
                Award ID: GM077138
                Award Recipient :
                Categories
                Primary Research
                Custom metadata
                © The Author(s) 2016

                Genetics
                kidney,transcriptogram,cystic kidney disease,autosomal dominant polycystic kidney disease,bioinformatics,pathway identification

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