Altered lipid metabolism in the aging kidney identified by three layered omic analysis

Fabian Braun, Markus M. Rinschen, Valerie Bartels, Peter Frommolt, Bianca Habermann, Jan H.J. Hoeijmakers, Björn Schumacher, Martijn E.T. Dollé, Roman Ulrich Müller, Thomas Benzing, Bernhard Schermer, Christine E. Kurschat

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)

Abstract

Aging-associated diseases and their comorbidities affect the life of a constantly growing proportion of the population in developed countries. At the center of these comorbidities are changes of kidney structure and function as agerelated chronic kidney disease predisposes to the development of cardiovascular diseases such as stroke, myocardial infarction or heart failure. To detect molecular mechanisms involved in kidney aging, we analyzed gene expression profiles of kidneys from adult and aged wild-type mice by transcriptomic, proteomic and targeted lipidomic methodologies. Interestingly, transcriptome and proteome analyses revealed differential expression of genes primarily involved in lipid metabolism and immune response. Additional lipidomic analyses uncovered significant age-related differences in the total amount of phosphatidylethanolamines, phosphatidylcholines and sphingomyelins as well as in subspecies of phosphatidylserines and ceramides with age. By integration of these datasets we identified Aldh1a1, a key enzyme in vitamin A metabolism specifically expressed in the medullary ascending limb, as one of the most prominent upregulated proteins in old kidneys. Moreover, ceramidase Asah1 was highly expressed in aged kidneys, consistent with a decrease in ceramide C16. In summary, our data suggest that changes in lipid metabolism are involved in the process of kidney aging and in the development of chronic kidney disease.

Original languageEnglish
Pages (from-to)441-454
Number of pages14
JournalAging
Volume8
Issue number3
DOIs
Publication statusPublished - 2016
Externally publishedYes

Keywords

  • Gene expression profiling
  • Lipidomics
  • Microarray analysis
  • Proteomics
  • Renal aging

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