Literature DB >> 16227630

New data analysis and mining approaches identify unique proteome and transcriptome markers of susceptibility to autoimmune diabetes.

Ivan C Gerling1, Sudhir Singh, Nataliya I Lenchik, Dana R Marshall, Jian Wu.   

Abstract

Non-obese diabetic (NOD) mice spontaneously develop autoimmunity to the insulin producing beta cells leading to insulin-dependent diabetes. In this study we developed and used new data analysis and mining approaches on combined proteome and transcriptome (molecular phenotype) data to define pathways affected by abnormalities in peripheral leukocytes of young NOD female mice. Cells were collected before mice show signs of autoimmunity (age, 2-4 weeks). We extracted both protein and RNA from NOD and C57BL/6 control mice to conduct both proteome analysis by two-dimensional gel electrophoresis and transcriptome analysis on Affymetrix expression arrays. We developed a new approach to analyze the two-dimensional gel proteome data that included two-way analysis of variance, cluster analysis, and principal component analysis. Lists of differentially expressed proteins and transcripts were subjected to pathway analysis using a commercial service. From the list of 24 proteins differentially expressed between strains we identified two highly significant and interconnected networks centered around oncogenes (Myc and Mycn) and apoptosis-related genes (Bcl2 and Casp3). The 273 genes with significant strain differences in RNA expression levels created six interconnected networks with a significant over-representation of genes related to cancer, cell cycle, and cell death. They contained many of the same genes found in the proteome networks (including Myc and Mycn). The combination of the eight, highly significant networks created one large network of 272 genes of which 82 had differential expression between strains either at the protein or the RNA level. We conclude that new proteome data analysis strategies and combined information from proteome and transcriptome can enhance the insights gained from either type of data alone. The overall systems biology of prediabetic NOD mice points toward abnormalities in regulation of the opposing processes of cell renewal and cell death even before there are any clear signatures of immune system activation.

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Year:  2005        PMID: 16227630     DOI: 10.1074/mcp.M500197-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  24 in total

Review 1.  Data-mining technologies for diabetes: a systematic review.

Authors:  Miroslav Marinov; Abu Saleh Mohammad Mosa; Illhoi Yoo; Suzanne Austin Boren
Journal:  J Diabetes Sci Technol       Date:  2011-11-01

Review 2.  Systems biology in immunology: a computational modeling perspective.

Authors:  Ronald N Germain; Martin Meier-Schellersheim; Aleksandra Nita-Lazar; Iain D C Fraser
Journal:  Annu Rev Immunol       Date:  2011       Impact factor: 28.527

3.  Systems biology and proteomic analysis of cerebral cavernous malformation.

Authors:  Alexander R Edelmann; Sarah Schwartz-Baxter; Christopher F Dibble; Warren C Byrd; Jim Carlson; Ivandario Saldarriaga; Sompop Bencharit
Journal:  Expert Rev Proteomics       Date:  2014-03-31       Impact factor: 3.940

4.  Preimplantation factor (PIF) analog prevents type I diabetes mellitus (TIDM) development by preserving pancreatic function in NOD mice.

Authors:  Lola Weiss; Steve Bernstein; Richard Jones; Ravi Amunugama; David Krizman; Lellean Jebailey; Osnat Almogi-Hazan; Osnat Hazan; Zhanna Yekhtin; Janna Yachtin; Reut Shiner; Israel Reibstein; Elizabeth Triche; Shimon Slavin; Reuven Or; Eytan R Barnea
Journal:  Endocrine       Date:  2011-03-22       Impact factor: 3.633

5.  Early differences in islets from prediabetic NOD mice: combined microarray and proteomic analysis.

Authors:  Inne Crèvecoeur; Valborg Gudmundsdottir; Saurabh Vig; Fernanda Marques Câmara Sodré; Wannes D'Hertog; Ana Carolina Fierro; Leentje Van Lommel; Conny Gysemans; Kathleen Marchal; Etienne Waelkens; Frans Schuit; Søren Brunak; Lut Overbergh; Chantal Mathieu
Journal:  Diabetologia       Date:  2017-01-12       Impact factor: 10.122

6.  Gene Expression Profiles of Peripheral Blood Mononuclear Cells Reveal Transcriptional Signatures as Novel Biomarkers for Cardiac Remodeling in Rats with Aldosteronism and Hypertensive Heart Disease.

Authors:  Ivan C Gerling; Robert A Ahokas; German Kamalov; Wenyuan Zhao; Syamal K Bhattacharya; Yao Sun; Karl T Weber
Journal:  JACC Heart Fail       Date:  2013-12-01       Impact factor: 12.035

7.  Proteomics-based systems biology modeling of bovine germinal vesicle stage oocyte and cumulus cell interaction.

Authors:  Divyaswetha Peddinti; Erdogan Memili; Shane C Burgess
Journal:  PLoS One       Date:  2010-06-21       Impact factor: 3.240

8.  Integrated network analysis of transcriptomic and proteomic data in psoriasis.

Authors:  Eleonora Piruzian; Sergey Bruskin; Alex Ishkin; Rustam Abdeev; Sergey Moshkovskii; Stanislav Melnik; Yuri Nikolsky; Tatiana Nikolskaya
Journal:  BMC Syst Biol       Date:  2010-04-08

9.  Response of rat lung tissue to short-term hyperoxia: a proteomic approach.

Authors:  Oliver Spelten; Wolfgang A Wetsch; Georg Wrettos; Armin Kalenka; Jochen Hinkelbein
Journal:  Mol Cell Biochem       Date:  2013-08-11       Impact factor: 3.396

10.  Time-dependent alterations of cerebral proteins following short-term normobaric hyperoxia.

Authors:  Jochen Hinkelbein; Robert E Feldmann; Armin Kalenka
Journal:  Mol Cell Biochem       Date:  2010-01-05       Impact factor: 3.396

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