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

Slieker, Roderick C ; Donnelly, Louise A ; Fitipaldi, Hugo LU ; Bouland, Gerard A ; Giordano, Giuseppe N LU ; Åkerlund, Mikael LU ; Gerl, Mathias J ; Ahlqvist, Emma LU ; Ali, Ashfaq LU orcid and Dragan, Iulian , et al. (2021) In Diabetes 70(11). p.2683-2693
Abstract

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... (More)

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.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
ANDIS, diabetes, Diabetics
in
Diabetes
volume
70
issue
11
pages
2683 - 2693
publisher
American Diabetes Association Inc.
external identifiers
  • pmid:34376475
  • scopus:85121157132
ISSN
1939-327X
DOI
10.2337/db20-1281
language
English
LU publication?
yes
additional info
© 2021 by the American Diabetes Association.
id
07f6d2b7-e7a4-405b-ab64-3eae227558ec
date added to LUP
2021-10-22 07:27:45
date last changed
2024-11-17 11:25:28
@article{07f6d2b7-e7a4-405b-ab64-3eae227558ec,
  abstract     = {{<p>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.</p>}},
  author       = {{Slieker, Roderick C and Donnelly, Louise A and Fitipaldi, Hugo and Bouland, Gerard A and Giordano, Giuseppe N and Åkerlund, Mikael and Gerl, Mathias J and Ahlqvist, Emma and Ali, Ashfaq and Dragan, Iulian and Elders, Petra and Festa, Andreas and Hansen, Michael K and van der Heijden, Amber A and Aly, Dina Mansour and Kim, Min and Kuznetsov, Dmitry and Mehl, Florence and Klose, Christian and Simons, Kai and Pavo, Imre and Pullen, Timothy J and Suvitaival, Tommi and Wretlind, Asger and Rossing, Peter and Lyssenko, Valeriya and Quigley, Cristina Legido and Groop, Leif and Thorens, Bernard and Franks, Paul W and Ibberson, Mark and Rutter, Guy A and Beulens, Joline Wj and 't Hart, Leen M and Pearson, Ewan R}},
  issn         = {{1939-327X}},
  keywords     = {{ANDIS; diabetes; Diabetics}},
  language     = {{eng}},
  month        = {{08}},
  number       = {{11}},
  pages        = {{2683--2693}},
  publisher    = {{American Diabetes Association Inc.}},
  series       = {{Diabetes}},
  title        = {{Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes : an IMIRHAPSODY Study}},
  url          = {{http://dx.doi.org/10.2337/db20-1281}},
  doi          = {{10.2337/db20-1281}},
  volume       = {{70}},
  year         = {{2021}},
}