Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

IMI DIRECT Consortium; Agata Wesolowska-Andersen; Caroline A. Brorsson; Roberto Bizzotto; Andrea Mari; Andrea Tura; Robert Koivula; Anubha Mahajan; Ana Vinuela; Juan Fernandez Tajes; Sapna Sharma; Mark Haid; Cornelia Prehn; Anna Artati; Mun-Gwan Hong; Petra B. Musholt; Azra Kurbasic; Federico De Masi; Kostas Tsirigos; Helle Krogh Pedersen; Valborg Gudmundsdottir; Cecilia Engel Thomas; Karina Banasik; Chrisopher Jennison; Angus Jones; Gwen Kennedy; Jimmy Bell; Louise Thomas; Gary Frost; Henrik Thomsen; Kristine Allin; Tue Haldor Hansen; Henrik Vestergaard; Torben Hansen; Femke Rutters; Petra Elders; Leen t'Hart; Amelie Bonnefond; Mickaël Canouil; Soren Brage; Tarja Kokkola; Alison Heggie; Donna McEvoy; Andrew Hattersley; Timothy McDonald; Harriet Teare; Martin Ridderstrale; Mark Walker; Ian Forgie; Giuseppe N. Giordano; Philippe Froguel; Imre Pavo; Hartmut Ruetten; Oluf Pedersen; Emmanouil T. Dermitzakis; Paul W. Franks; Jochen M Schwenk; Jerzy Adamski; Ewan Pearson; Mark I. McCarthy; Søren Brunak

doi:10.1016/j.xcrm.2021.100477

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

IMI DIRECT Consortium, Agata Wesolowska-Andersen, Caroline A. Brorsson, Roberto Bizzotto, Andrea Mari, Andrea Tura, Robert Koivula, Anubha Mahajan, Ana Vinuela, Juan Fernandez Tajes, Sapna Sharma, Mark Haid, Cornelia Prehn, Anna Artati, Mun-Gwan Hong, Petra B. Musholt, Azra Kurbasic, Federico De Masi, Kostas Tsirigos, Helle Krogh PedersenValborg Gudmundsdottir, Cecilia Engel Thomas, Karina Banasik, Chrisopher Jennison, Angus Jones, Gwen Kennedy, Jimmy Bell, Louise Thomas, Gary Frost, Henrik Thomsen, Kristine Allin, Tue Haldor Hansen, Henrik Vestergaard, Torben Hansen, Femke Rutters, Petra Elders, Leen t'Hart, Amelie Bonnefond, Mickaël Canouil, Soren Brage, Tarja Kokkola, Alison Heggie, Donna McEvoy, Andrew Hattersley, Timothy McDonald, Harriet Teare, Martin Ridderstrale, Mark Walker, Ian Forgie, Giuseppe N. Giordano, Philippe Froguel, Imre Pavo, Hartmut Ruetten, Oluf Pedersen, Emmanouil T. Dermitzakis, Paul W. Franks, Jochen M Schwenk, Jerzy Adamski, Ewan Pearson (Lead / Corresponding author), Mark I. McCarthy (Lead / Corresponding author), Søren Brunak (Lead / Corresponding author)

Population Health and Genomics

Research output: Contribution to journal › Article › peer-review

52 Citations (Scopus)

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Abstract

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.

Original language	English
Article number	100477
Number of pages	32
Journal	Cell Reports Medicine
Volume	3
Issue number	1
Early online date	4 Jan 2022
DOIs	https://doi.org/10.1016/j.xcrm.2021.100477
Publication status	Published - 18 Jan 2022

Keywords

archetypes
disease progression
glycaemic deterioration
multi-omics
patient clustering
patient stratification
precision medicine
soft-clustering
type 2 diabetes

ASJC Scopus subject areas

General Medicine
General Biochemistry,Genetics and Molecular Biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.xcrm.2021.100477Licence: CC BY

Final Published VersionFinal published version, 6.17 MBLicence: CC BY

1 Active
2 Finished

DIRECT: Diabetes Research on Patient Stratification (joint with 25 other partners)
Colhoun, H. (Investigator), Houston, G. (Investigator), Morris, A. (Investigator), Palmer, C. (Investigator) & Pearson, E. (Investigator)
COMMISSION OF THE EUROPEAN COMMUNITIES
1/02/12 → 28/02/27
Project: Research
RHAPSODY (Joint with 25 other parties)
Palmer, C. (Investigator), Pearson, E. (Investigator) & Zhou, K. (Investigator)
COMMISSION OF THE EUROPEAN COMMUNITIES
1/04/16 → 30/09/21
Project: Research
Stratified Medicine in Type 2 Diabetes: Insights from the Study of Drug Response (New Investigator Award)
Pearson, E. (Investigator)
16/02/15 → 15/08/21
Project: Research

Health Informatics Centre
Health and Clinical Services
Facility/equipment: Facility

Cite this

IMI DIRECT Consortium, Wesolowska-Andersen, A., Brorsson, C. A., Bizzotto, R., Mari, A., Tura, A., Koivula, R., Mahajan, A., Vinuela, A., Tajes, J. F., Sharma, S., Haid, M., Prehn, C., Artati, A., Hong, M.-G., Musholt, P. B., Kurbasic, A., De Masi, F., Tsirigos, K., ... Brunak, S. (2022). Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study. Cell Reports Medicine, 3(1), Article 100477. https://doi.org/10.1016/j.xcrm.2021.100477

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title = "Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study",

abstract = "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.",

keywords = "archetypes, disease progression, glycaemic deterioration, multi-omics, patient clustering, patient stratification, precision medicine, soft-clustering, type 2 diabetes",

author = "{IMI DIRECT Consortium} and Agata Wesolowska-Andersen and Brorsson, {Caroline A.} and Roberto Bizzotto and Andrea Mari and Andrea Tura and Robert Koivula and Anubha Mahajan and Ana Vinuela and Tajes, {Juan Fernandez} and Sapna Sharma and Mark Haid and Cornelia Prehn and Anna Artati and Mun-Gwan Hong and Musholt, {Petra B.} and Azra Kurbasic and {De Masi}, Federico and Kostas Tsirigos and Pedersen, {Helle Krogh} and Valborg Gudmundsdottir and Thomas, {Cecilia Engel} and Karina Banasik and Chrisopher Jennison and Angus Jones and Gwen Kennedy and Jimmy Bell and Louise Thomas and Gary Frost and Henrik Thomsen and Kristine Allin and Hansen, {Tue Haldor} and Henrik Vestergaard and Torben Hansen and Femke Rutters and Petra Elders and Leen t'Hart and Amelie Bonnefond and Micka{\"e}l Canouil and Soren Brage and Tarja Kokkola and Alison Heggie and Donna McEvoy and Andrew Hattersley and Timothy McDonald and Harriet Teare and Martin Ridderstrale and Mark Walker and Ian Forgie and Giordano, {Giuseppe N.} and Philippe Froguel and Imre Pavo and Hartmut Ruetten and Oluf Pedersen and Dermitzakis, {Emmanouil T.} and Franks, {Paul W.} and Schwenk, {Jochen M} and Jerzy Adamski and Ewan Pearson and McCarthy, {Mark I.} and S{\o}ren Brunak",

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doi = "10.1016/j.xcrm.2021.100477",

language = "English",

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IMI DIRECT Consortium, Wesolowska-Andersen, A, Brorsson, CA, Bizzotto, R, Mari, A, Tura, A, Koivula, R, Mahajan, A, Vinuela, A, Tajes, JF, Sharma, S, Haid, M, Prehn, C, Artati, A, Hong, M-G, Musholt, PB, Kurbasic, A, De Masi, F, Tsirigos, K, Pedersen, HK, Gudmundsdottir, V, Thomas, CE, Banasik, K, Jennison, C, Jones, A, Kennedy, G, Bell, J, Thomas, L, Frost, G, Thomsen, H, Allin, K, Hansen, TH, Vestergaard, H, Hansen, T, Rutters, F, Elders, P, t'Hart, L, Bonnefond, A, Canouil, M, Brage, S, Kokkola, T, Heggie, A, McEvoy, D, Hattersley, A, McDonald, T, Teare, H, Ridderstrale, M, Walker, M, Forgie, I, Giordano, GN, Froguel, P, Pavo, I, Ruetten, H, Pedersen, O, Dermitzakis, ET, Franks, PW, Schwenk, JM, Adamski, J, Pearson, E, McCarthy, MI & Brunak, S 2022, 'Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study', Cell Reports Medicine, vol. 3, no. 1, 100477. https://doi.org/10.1016/j.xcrm.2021.100477

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 - IMI DIRECT Consortium

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 - De Masi, Federico

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 - Giordano, Giuseppe N.

AU - Froguel, Philippe

AU - Pavo, Imre

AU - Ruetten, Hartmut

AU - Pedersen, Oluf

AU - Dermitzakis, Emmanouil T.

AU - Franks, Paul W.

AU - Schwenk, Jochen M

AU - Adamski, Jerzy

AU - Pearson, Ewan

AU - McCarthy, Mark I.

AU - Brunak, Søren

PY - 2022/1/18

Y1 - 2022/1/18

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 - Article

C2 - 35106505

SN - 2666-3791

VL - 3

JO - Cell Reports Medicine

JF - Cell Reports Medicine

IS - 1

M1 - 100477

ER -

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Projects

DIRECT: Diabetes Research on Patient Stratification (joint with 25 other partners)

RHAPSODY (Joint with 25 other parties)

Stratified Medicine in Type 2 Diabetes: Insights from the Study of Drug Response (New Investigator Award)

Equipment

Health Informatics Centre

Cite this