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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.
Christensen, Diana Hedevang; Nicolaisen, Sia K; Ahlqvist, Emma; Stidsen, Jacob V; Nielsen, Jens Steen; Hojlund, Kurt; Olsen, Michael H; García-Calzón, Sonia; Ling, Charlotte; Rungby, Jørgen; Brandslund, Ivan; Vestergaard, Peter; Jessen, Niels; Hansen, Torben; Brøns, Charlotte; Beck-Nielsen, Henning; Sørensen, Henrik T; Thomsen, Reimar W; Vaag, Allan.
Affiliation
  • Christensen DH; Department of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark dhcr@clin.au.dk.
  • Nicolaisen SK; Department of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.
  • Ahlqvist E; Genomics, Diabetes and Endocrinology Unit, Department of Clinical Sciences, Lund University Diabetes Center, Malmö, Sweden.
  • Stidsen JV; The Danish Centre for Strategic Research in Type 2 Diabetes (DD2), Odense University Hospital, Odense, Denmark.
  • Nielsen JS; Steno Diabetes Center Odense, Odense University Hospital, Odense, Denmark.
  • Hojlund K; The Danish Centre for Strategic Research in Type 2 Diabetes (DD2), Odense University Hospital, Odense, Denmark.
  • Olsen MH; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
  • García-Calzón S; The Danish Centre for Strategic Research in Type 2 Diabetes (DD2), Odense University Hospital, Odense, Denmark.
  • Ling C; Steno Diabetes Center Odense, Odense University Hospital, Odense, Denmark.
  • Rungby J; Department of Internal Medicine and Steno Diabetes Center Zealand, Holbæk Hospital, Holbæk, Denmark.
  • Brandslund I; Department of Regional Health Research, University of Southern Denmark, Odense, Denmark.
  • Vestergaard P; Department of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain.
  • Jessen N; Epigenetic and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Center, Scania University Hospital, Malmö, Sweden.
  • Hansen T; Epigenetic and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Center, Scania University Hospital, Malmö, Sweden.
  • Brøns C; Department of Endocrinology IC, Bispebjerg University Hospital, Copenhagen, Denmark.
  • Beck-Nielsen H; Copenhagen Center for Translational Research, Bispebjerg University Hospital, Copenhagen, Denmark.
  • Sørensen HT; Department of Clinical Biochemistry, University Hospital of Southern Denmark, Vejle, Denmark.
  • Thomsen RW; Steno Diabetes Center Aalborg, Aalborg University Hospital, Aalborg, Denmark.
  • Vaag A; Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark.
Article in En | MEDLINE | ID: mdl-35428673
ABSTRACT

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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Insulin Resistance / Diabetes Mellitus, Type 2 Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: Europa Language: En Journal: BMJ Open Diabetes Res Care Year: 2022 Document type: Article Affiliation country: Dinamarca

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Insulin Resistance / Diabetes Mellitus, Type 2 Type of study: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Country/Region as subject: Europa Language: En Journal: BMJ Open Diabetes Res Care Year: 2022 Document type: Article Affiliation country: Dinamarca