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Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease

  • BEAt-DKD consortium
  • , Abigail C Lay
  • , Van Du T Tran
  • , Viji Nair
  • , Virginie Betin
  • , Jennifer A Hurcombe
  • , Alexandra F Barrington
  • , Robert Jp Pope
  • , Frédéric Burdet
  • , Florence Mehl
  • , Dmytro Kryvokhyzha
  • , Abrar Ahmad
  • , Matthew C Sinton
  • , Philip Lewis
  • , Marieangela C Wilson
  • , Rajasree Menon
  • , Edgar Otto
  • , Kate J Heesom
  • , Mark Ibberson
  • , Helen C Looker
  • Robert G Nelson, Wenjun Ju, Matthias Kretzler, Simon C Satchell, Maria F Gomez, Richard J M Coward

Research output: Contribution to journalArticle (Academic Journal)peer-review

18 Citations (Scopus)
28 Downloads (Pure)

Abstract

Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin sensitive and resistant conditions, and perform simultaneous transcriptomics and proteomics for integrated analysis. Our data is further compared with bulk- and single-cell transcriptomic kidney biopsy data from early- and advanced-stage DKD patient cohorts. We identify several consistent changes (individual genes, proteins, and molecular pathways) occurring across all insulin-resistant kidney cell types, together with cell-line-specific changes occurring in response to insulin resistance, which are replicated in DKD biopsies. This study provides a rich data resource to direct future studies in elucidating underlying kidney signalling pathways and potential therapeutic targets in DKD.
Original languageEnglish
Article number10018
Number of pages19
JournalNature Communications
Volume15
Issue number1
DOIs
Publication statusPublished - 19 Nov 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Humans
  • Diabetic Nephropathies/metabolism
  • Insulin Resistance
  • Biopsy
  • Kidney/pathology
  • Transcriptome
  • Gene Expression Profiling
  • Proteomics
  • Signal Transduction

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