Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study

Author:

Slieker Roderick C.12,Donnelly Louise A.3,Fitipaldi Hugo4,Bouland Gerard A.1,Giordano Giuseppe N.4,Åkerlund Mikael4,Gerl Mathias J.5,Ahlqvist Emma4,Ali Ashfaq6,Dragan Iulian7,Elders Petra8,Festa Andreas910,Hansen Michael K.11,van der Heijden Amber A.8,Mansour Aly Dina4,Kim Min612,Kuznetsov Dmitry7,Mehl Florence7,Klose Christian5,Simons Kai5,Pavo Imre9,Pullen Timothy J.1314,Suvitaival Tommi6,Wretlind Asger6,Rossing Peter615,Lyssenko Valeriya1617,Legido Quigley Cristina611,Groop Leif418,Thorens Bernard19,Franks Paul W.420,Ibberson Mark7,Rutter Guy A.1321,Beulens Joline W.J.222,’t Hart Leen M.1223ORCID,Pearson Ewan R.3ORCID

Affiliation:

1. Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands

2. Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands

3. Population Health & Genomics, School of Medicine, University of Dundee, Dundee, U.K.

4. Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, SUS, Malmö, Sweden

5. Lipotype GmbH, Dresden, Germany

6. Steno Diabetes Center Copenhagen, Gentofte, Denmark

7. Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland

8. Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands

9. Eli Lilly Regional Operations GmbH, Vienna, Austria

10. 1st Medical Department, LK Stockerau, Niederösterreich, Austria

11. Cardiovascular and Metabolic Disease Research, Janssen Research & Development, Spring House, PA

12. Institute of Pharmaceutical Science, Faculty of Life Sciences and Medicines, King’s College London, London, U.K.

13. Department of Diabetes, Guy’s Campus, King’s College London, London, U.K.

14. Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, U.K.

15. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark

16. Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway

17. Genomics, Diabetes and Endocrinology Unit, Department of Clinical Sciences Malmö, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden

18. Finnish Institute of Molecular Medicine, Helsinki University, Helsinki, Finland

19. Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland

20. Department of Nutrition, Harvard School of Public Health, Boston, MA

21. Lee Kong Chian School of Medicine, Nan Yang Technological University, Singapore

22. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands

23. Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands

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.

Publisher

American Diabetes Association

Subject

Endocrinology, Diabetes and Metabolism,Internal Medicine

Reference43 articles.

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