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Region Hovedstaden - en del af Københavns Universitetshospital
E-pub ahead of print

Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes: an IMIRHAPSODY Study

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

DOI

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  • Roderick C Slieker
  • Louise A Donnelly
  • Hugo Fitipaldi
  • Gerard A Bouland
  • Giuseppe N Giordano
  • Mikael Åkerlund
  • Mathias J Gerl
  • Emma Ahlqvist
  • Ashfaq Ali
  • Iulian Dragan
  • Petra Elders
  • Andreas Festa
  • Michael K Hansen
  • Amber A van der Heijden
  • Dina Mansour Aly
  • Min Kim
  • Dmitry Kuznetsov
  • Florence Mehl
  • Christian Klose
  • Kai Simons
  • Imre Pavo
  • Timothy J Pullen
  • Tommi Suvitaival
  • Asger Wretlind
  • Peter Rossing
  • Valeriya Lyssenko
  • Cristina Legido Quigley
  • Leif Groop
  • Bernard Thorens
  • Paul W Franks
  • Mark Ibberson
  • Guy A Rutter
  • Joline Wj Beulens
  • Leen M 't Hart
  • Ewan R Pearson
Vis graf over relationer

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity a previous study clustered people with diabetes into five diabetes subtypes. The aim of the current study is to investigate the aetiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic- (N=12828), metabolomic- (N=2945), lipidomic- (N=2593) and proteomic (N=1170) data were obtained in plasma. In each datatype each cluster was compared with the other four clusters as the reference. The insulin resistant cluster showed the most distinct molecular signature, with higher BCAAs, DAG and TAG levels and aberrant protein levels in plasma enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher cytokines. A subset of the mild diabetes cluster with high HDL showed the most beneficial molecular profile with opposite effects to those seen in the insulin resistant cluster. This study showed that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.

OriginalsprogEngelsk
TidsskriftDiabetes
ISSN0012-1797
DOI
StatusE-pub ahead of print - 10 aug. 2021

ID: 67592580