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Type 2 diabetes classification: a data-driven cluster study of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) cohort

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  • Diana Hedevang Christensen
  • Sia K Nicolaisen
  • Emma Ahlqvist, Lund University
  • ,
  • Jacob V Stidsen, Syddansk Universitet
  • ,
  • Jens Steen Nielsen, Syddansk Universitet
  • ,
  • Kurt Hojlund, Syddansk Universitet
  • ,
  • Michael H Olsen, Københavns Universitet, Syddansk Universitet
  • ,
  • Sonia García-Calzón, University of Navarra, Lund University
  • ,
  • Charlotte Ling, Lund University
  • ,
  • Jørgen Rungby, Københavns Universitet
  • ,
  • Ivan Brandslund, Syddansk Universitet
  • ,
  • Peter Vestergaard, Aalborg Universitet
  • ,
  • Niels Jessen
  • Torben Hansen, Københavns Universitet
  • ,
  • Charlotte Brøns, Gentofte Hospital
  • ,
  • Henning Beck-Nielsen, Syddansk Universitet
  • ,
  • Henrik T Sørensen
  • Reimar W Thomsen
  • Allan Vaag, Gentofte Hospital

INTRODUCTION: A Swedish data-driven cluster study identified four distinct type 2 diabetes (T2D) clusters, based on age at diagnosis, body mass index (BMI), hemoglobin A1c (HbA1c) level, and homeostatic model assessment 2 (HOMA2) estimates of insulin resistance and beta-cell function. A Danish study proposed three T2D phenotypes (insulinopenic, hyperinsulinemic, and classical) based on HOMA2 measures only. We examined these two new T2D classifications using the Danish Centre for Strategic Research in Type 2 Diabetes cohort.

RESEARCH DESIGN AND METHODS: In 3529 individuals, we first performed a k-means cluster analysis with a forced k-value of four to replicate the Swedish clusters: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild age-related (MARD), and mild obesity-related (MOD) diabetes. Next, we did an analysis open to alternative k-values (ie, data determined the optimal number of clusters). Finally, we compared the data-driven clusters with the three Danish phenotypes.

RESULTS: Compared with the Swedish findings, the replicated Danish SIDD cluster included patients with lower mean HbA1c (86 mmol/mol vs 101 mmol/mol), and the Danish MOD cluster patients were less obese (mean BMI 32 kg/m2 vs 36 kg/m2). Our data-driven alternative k-value analysis suggested the optimal number of T2D clusters in our data to be three, rather than four. When comparing the four replicated Swedish clusters with the three proposed Danish phenotypes, 81%, 79%, and 69% of the SIDD, MOD, and MARD patients, respectively, fitted the classical T2D phenotype, whereas 70% of SIRD patients fitted the hyperinsulinemic phenotype. Among the three alternative data-driven clusters, 60% of patients in the most insulin-resistant cluster constituted 76% of patients with a hyperinsulinemic phenotype.

CONCLUSION: Different HOMA2-based approaches did not classify patients with T2D in a consistent manner. The T2D classes characterized by high insulin resistance/hyperinsulinemia appeared most distinct.

OriginalsprogEngelsk
Artikelnummere002731
TidsskriftBMJ open diabetes research & care
Vol/bind10
Nummer2
Antal sider12
ISSN2052-4897
DOI
StatusUdgivet - apr. 2022

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© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

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