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

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 GudmundsdottirCecilia 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, Oluf Pedersen, Søren Brunak, IMI-DIRECT consortium

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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 languageEnglish
Article number100477
JournalCell Reports Medicine
Volume3
Issue number1
Number of pages25
ISSN2666-3791
DOIs
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2021 The Authors

Keywords

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

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