Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study
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Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals : An IMI DIRECT study. / Wesolowska-Andersen, Agata; Brorsson, Caroline A.; Bizzotto, Roberto; Mari, Andrea; Tura, Andrea; Koivula, Robert; Mahajan, Anubha; Vinuela, Ana; Tajes, Juan Fernandez; Sharma, Sapna; Haid, Mark; Prehn, Cornelia; Artati, Anna; Hong, Mun Gwan; Musholt, Petra B.; Kurbasic, Azra; Masi, Federico De; Tsirigos, Kostas; Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Thomas, Cecilia Engel; Banasik, Karina; Jennison, Chrisopher; Jones, Angus; Kennedy, Gwen; Bell, Jimmy; Thomas, Louise; Frost, Gary; Thomsen, Henrik; Allin, Kristine; Hansen, Tue Haldor; Vestergaard, Henrik; Hansen, Torben; Rutters, Femke; Elders, Petra; t'Hart, Leen; Bonnefond, Amelie; Canouil, Mickaël; Brage, Soren; Kokkola, Tarja; Heggie, Alison; McEvoy, Donna; Hattersley, Andrew; McDonald, Timothy; Teare, Harriet; Ridderstrale, Martin; Walker, Mark; Forgie, Ian; Pedersen, Oluf; Brunak, Søren; IMI-DIRECT consortium.
I: Cell Reports Medicine, Bind 3, Nr. 1, 100477, 2022.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals
T2 - An IMI DIRECT study
AU - Wesolowska-Andersen, Agata
AU - Brorsson, Caroline A.
AU - Bizzotto, Roberto
AU - Mari, Andrea
AU - Tura, Andrea
AU - Koivula, Robert
AU - Mahajan, Anubha
AU - Vinuela, Ana
AU - Tajes, Juan Fernandez
AU - Sharma, Sapna
AU - Haid, Mark
AU - Prehn, Cornelia
AU - Artati, Anna
AU - Hong, Mun Gwan
AU - Musholt, Petra B.
AU - Kurbasic, Azra
AU - Masi, Federico De
AU - Tsirigos, Kostas
AU - Pedersen, Helle Krogh
AU - Gudmundsdottir, Valborg
AU - Thomas, Cecilia Engel
AU - Banasik, Karina
AU - Jennison, Chrisopher
AU - Jones, Angus
AU - Kennedy, Gwen
AU - Bell, Jimmy
AU - Thomas, Louise
AU - Frost, Gary
AU - Thomsen, Henrik
AU - Allin, Kristine
AU - Hansen, Tue Haldor
AU - Vestergaard, Henrik
AU - Hansen, Torben
AU - Rutters, Femke
AU - Elders, Petra
AU - t'Hart, Leen
AU - Bonnefond, Amelie
AU - Canouil, Mickaël
AU - Brage, Soren
AU - Kokkola, Tarja
AU - Heggie, Alison
AU - McEvoy, Donna
AU - Hattersley, Andrew
AU - McDonald, Timothy
AU - Teare, Harriet
AU - Ridderstrale, Martin
AU - Walker, Mark
AU - Forgie, Ian
AU - Pedersen, Oluf
AU - Brunak, Søren
AU - IMI-DIRECT consortium
N1 - Publisher Copyright: © 2021 The Authors
PY - 2022
Y1 - 2022
N2 - The 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.
AB - The 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.
KW - archetypes
KW - disease progression
KW - glycaemic deterioration
KW - multi-omics
KW - patient clustering
KW - patient stratification
KW - precision medicine
KW - soft-clustering
KW - type 2 diabetes
U2 - 10.1016/j.xcrm.2021.100477
DO - 10.1016/j.xcrm.2021.100477
M3 - Journal article
C2 - 35106505
AN - SCOPUS:85122950661
VL - 3
JO - Cell Reports Medicine
JF - Cell Reports Medicine
SN - 2666-3791
IS - 1
M1 - 100477
ER -
ID: 290596736