3.9 Article

Microarray and Bioinformatics Analysis of Gene Expression in Experimental Membranous Nephropathy

Journal

NEPHRON EXPERIMENTAL NEPHROLOGY
Volume 112, Issue 2, Pages E43-E58

Publisher

KARGER
DOI: 10.1159/000213505

Keywords

Passive Heymann nephritis; Gene expression profiling; Human nephritis; Proteinuria; Microarray; Bioinformatics; Podocyte

Funding

  1. National Institute of Health [DK60525, DK56799, DK51096]
  2. American Diabetes Association
  3. Austrian Science Fund [J2415-B11, FWF P-15679]
  4. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [R01DK056799, R01DK060525, R01DK051096] Funding Source: NIH RePORTER

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Background: Passive Heymann nephritis (PHN), the best characterized animal model of experimental membranous nephropathy, is characterized by subepithelial immune deposits, podocyte foot processes effacement and massive proteinuria beginning 4 days following disease induction. Although single genes involved in PHN have been studied, no whole genome-wide expression analysis of kidney tissue has been performed. Methods: Microarray analysis was performed to identify gene expression changes in PHN rat kidneys during the onset of proteinuria. Results: Our results showed that 234 transcripts were differentially expressed in diseased animals compared to controls. Genes exclusively upregulated in diseased animals were mainly required for cell structure and motility, immunity and defense, cell cycle, and developmental processes. The single most increased gene was transgelin (Tagln) showing a 70-fold upregulation in animals with PHN. Protein-protein interaction analysis revealed the following four processes of major relevance in disease manifestation: (i) DNA damage and repair; (ii) changes in the extracellular matrix; (iii) deregulation of cytokines and growth factors, as well as (iv) rearrangements of the cytoskeleton. Conclusion: We show for the first time the complex interplay between multiple different genes in experimental membranous nephropathy, supporting a role for genomic approaches to better understanding and defining specific disease processes. Copyright (C) 2009 S. Karger AG, Basel

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