Transcriptional profiling reveals progeroid Ercc1 -/Δ mice as a model system for glomerular aging
- Equal contributors
1 Department II of Internal Medicine and Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany
2 Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
3 Systems Biology of Ageing Cologne, SyBaCol, University of Cologne, Cologne, Germany
4 Cologne Center for Genomics, University of Cologne, Cologne, Germany
5 Max Planck Institute for Biology of Ageing, Cologne, Germany
6 Life and Medical Sciences Institute, University of Bonn, Bonn, Germany
7 Laboratory for Health Protection Research, National Institute of Public Health and the Environment, Bilthoven, The Netherlands
8 Department of Cell Biology and Genetics, Medical Genetics Centre, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
BMC Genomics 2013, 14:559 doi:10.1186/1471-2164-14-559Published: 16 August 2013
Aging-related kidney diseases are a major health concern. Currently, models to study renal aging are lacking. Due to a reduced life-span progeroid models hold the promise to facilitate aging studies and allow examination of tissue-specific changes. Defects in genome maintenance in the Ercc1-/Δ progeroid mouse model result in premature aging and typical age-related pathologies. Here, we compared the glomerular transcriptome of young and aged Ercc1-deficient mice to young and aged WT mice in order to establish a novel model for research of aging-related kidney disease.
In a principal component analysis, age and genotype emerged as first and second principal components. Hierarchical clustering of all 521 genes differentially regulated between young and old WT and young and old Ercc1-/Δ mice showed cluster formation between young WT and Ercc1-/Δ as well as old WT and Ercc1-/Δ samples. An unexpectedly high number of 77 genes were differentially regulated in both WT and Ercc1-/Δ mice (p < 0.0001). GO term enrichment analysis revealed these genes to be involved in immune and inflammatory response, cell death, and chemotaxis. In a network analysis, these genes were part of insulin signaling, chemokine and cytokine signaling and extracellular matrix pathways.
Beyond insulin signaling, we find chemokine and cytokine signaling as well as modifiers of extracellular matrix composition to be subject to major changes in the aging glomerulus. At the level of the transcriptome, the pattern of gene activities is similar in the progeroid Ercc1-/Δ mouse model constituting a valuable tool for future studies of aging-associated glomerular pathologies.