Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • Resource and Technical Advances
    • Clinical Medicine
    • Reviews
    • Editorials
    • Perspectives
    • Top read articles
  • JCI This Month
    • Current issue
    • Past issues

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Editorials
  • Viewpoint
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact

Submit a comment

Tissue-specific metabolic reprogramming drives nutrient flux in diabetic complications
Kelli M. Sas, … , Frank C. Brosius III, Subramaniam Pennathur
Kelli M. Sas, … , Frank C. Brosius III, Subramaniam Pennathur
Published September 22, 2016
Citation Information: JCI Insight. 2016;1(15):e86976. https://doi.org/10.1172/jci.insight.86976.
View: Text | PDF
Research Article Metabolism Nephrology

Tissue-specific metabolic reprogramming drives nutrient flux in diabetic complications

  • Text
  • PDF
Abstract

Diabetes is associated with altered cellular metabolism, but how altered metabolism contributes to the development of diabetic complications is unknown. We used the BKS db/db diabetic mouse model to investigate changes in carbohydrate and lipid metabolism in kidney cortex, peripheral nerve, and retina. A systems approach using transcriptomics, metabolomics, and metabolic flux analysis identified tissue-specific differences, with increased glucose and fatty acid metabolism in the kidney, a moderate increase in the retina, and a decrease in the nerve. In the kidney, increased metabolism was associated with enhanced protein acetylation and mitochondrial dysfunction. To confirm these findings in human disease, we analyzed diabetic kidney transcriptomic data and urinary metabolites from a cohort of Southwestern American Indians. The urinary findings were replicated in 2 independent patient cohorts, the Finnish Diabetic Nephropathy and the Family Investigation of Nephropathy and Diabetes studies. Increased concentrations of TCA cycle metabolites in urine, but not in plasma, predicted progression of diabetic kidney disease, and there was an enrichment of pathways involved in glycolysis and fatty acid and amino acid metabolism. Our findings highlight tissue-specific changes in metabolism in complication-prone tissues in diabetes and suggest that urinary TCA cycle intermediates are potential prognostic biomarkers of diabetic kidney disease progression.

Authors

Kelli M. Sas, Pradeep Kayampilly, Jaeman Byun, Viji Nair, Lucy M. Hinder, Junguk Hur, Hongyu Zhang, Chengmao Lin, Nathan R. Qi, George Michailidis, Per-Henrik Groop, Robert G. Nelson, Manjula Darshi, Kumar Sharma, Jeffrey R. Schelling, John R. Sedor, Rodica Pop-Busui, Joel M. Weinberg, Scott A. Soleimanpour, Steven F. Abcouwer, Thomas W. Gardner, Charles F. Burant, Eva L. Feldman, Matthias Kretzler, Frank C. Brosius III, Subramaniam Pennathur

×

Guidelines

The Editorial Board will only consider comments that are deemed relevant and of interest to readers. The Journal will not post data that have not been subjected to peer review; or a comment that is essentially a reiteration of another comment.

  • Comments appear on the Journal’s website and are linked from the original article’s web page.
  • Authors are notified by email if their comments are posted.
  • The Journal reserves the right to edit comments for length and clarity.
  • No appeals will be considered.
  • Comments are not indexed in PubMed.

Specific requirements

  • Maximum length, 400 words
  • Entered as plain text or HTML
  • Author’s name and email address, to be posted with the comment
  • Declaration of all potential conflicts of interest (even if these are not ultimately posted); see the Journal’s conflict-of-interest policy
  • Comments may not include figures
This field is required
This field is required
This field is required
This field is required
This field is required
This field is required

Copyright © 2023 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts