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- Title
Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study.
- Authors
Slieker, Roderick C.; Donnelly, Louise A.; Fitipaldi, Hugo; Bouland, Gerard A.; Giordano, Giuseppe N.; Åkerlund, Mikael; Gerl, Mathias J.; Ahlqvist, Emma; Ali, Ashfaq; Dragan, Iulian; Elders, Petra; Festa, Andreas; Hansen, Michael K.; van der Heijden, Amber A.; Mansour Aly, Dina; Kim, Min; Kuznetsov, Dmitry; Mehl, Florence; Klose, Christian; Simons, Kai
- Abstract
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology 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 = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows 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.
- Subjects
TYPE 2 diabetes; PI3K/AKT pathway; DIABETES; TISSUE metabolism; ISLANDS of Langerhans; RESEARCH; CROSS-sectional method; RESEARCH methodology; EVALUATION research; COMPARATIVE studies; RESEARCH funding; CLUSTER analysis (Statistics); INSULIN resistance; LONGITUDINAL method
- Publication
Diabetes, 2021, Vol 70, Issue 11, p2683
- ISSN
0012-1797
- Publication type
journal article
- DOI
10.2337/db20-1281