Journal article
Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study
University of Oxford1
Technical University of Denmark2
University of Copenhagen3
University of Bath4
University of Exeter5
University of Dundee6
University of Westminster7
Imperial College London8
Amsterdam Public Health9
Leiden University Medical Center10
Université de Lille11
Bioinformatics, Department of Health Technology, Technical University of Denmark12
University of Cambridge13
University of Eastern Finland14
Newcastle University15
Royal Victoria Infirmary16
Eli Lilly GmbH17
Technical University of Munich18
the IMI-DIRECT consortium19
Department of Health Technology, Technical University of Denmark20
Istituto di Cibernetica del C.N.R.21
University of Geneva22
Helmholtz Zentrum München - German Research Center for Environmental Health23
KTH Royal Institute of Technology24
Sanofi Aventis Deutschland GmbH25
Lund University26
...and 16 moreThe presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal.
We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months.
Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired β cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment.
We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.
Language: | English |
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Publisher: | Elsevier |
Year: | 2022 |
Pages: | 100477 |
ISSN: | 26663791 |
Types: | Journal article |
DOI: | 10.1016/j.xcrm.2021.100477 |
ORCIDs: | Brorsson, Caroline A. , De Masi, Federico , 0000-0001-8688-2814 , 0000-0002-8251-1730 , 0000-0002-1436-5591 , 0000-0002-1646-4163 , 0000-0003-3771-8537 , 0000-0001-6118-1333 , 0000-0002-1274-4715 , 0000-0001-8603-8293 , 0000-0002-1910-2619 , 0000-0001-9609-7377 , 0000-0002-7459-1603 , 0000-0001-6201-6380 , 0000-0002-9856-3236 , 0000-0003-3804-1281 , 0000-0003-4235-4694 , 0000-0002-6880-5759 , 0000-0001-5948-8993 , 0000-0002-1265-7355 , 0000-0002-3303-3912 , 0000-0003-3559-6660 , 0000-0002-3270-9167 , 0000-0002-8800-6145 , 0000-0002-6719-6680 , 0000-0001-9237-8585 , 0000-0003-0316-5866 , 0000-0003-2489-2499 , 0000-0003-3090-269X , 0000-0001-8748-3831 and 0000-0002-3321-3972 |
Adult Diabetes Mellitus, Type 2 Disease Progression Female Follow-Up Studies Genetic Predisposition to Disease Genomics Humans Male Middle Aged Phenotype Risk Factors archetypes disease progression glycaemic deterioration multi-omics patient clustering patient stratification precision medicine soft-clustering type 2 diabetes