posted on 2021-08-10, 16:30authored byRoderick 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
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
Funding
This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115881 (RHAPSODY). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This work is supported by the Swiss State Secretariat for Education‚ Research and Innovation (SERI) under contract number 16.0097-2.