A classification and regression tree analysis identifies subgroups of childhood type 1 diabetes
Peter Achenbach,
Markus Hippich,
Jose Zapardiel-Gonzalo,
Beate Karges,
Reinhard W. Holl,
Agnese Petrera,
Ezio Bonifacio,
Anette-G. Ziegler
Affiliations
Peter Achenbach
Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany; German Center for Diabetes Research (DZD), Munich, Germany; Technical University Munich, School of Medicine, Forschergruppe Diabetes at Klinikum rechts der Isar, Munich, Germany
Markus Hippich
Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany; German Center for Diabetes Research (DZD), Munich, Germany
Jose Zapardiel-Gonzalo
Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
Beate Karges
Division of Endocrinology and Diabetes, Medical Faculty, RWTH Aachen University, D 52074 Aachen, Germany
Reinhard W. Holl
German Center for Diabetes Research (DZD), Munich, Germany; Institute of Epidemiology and Medical Biometry, ZIBMT, University of Ulm, D 89081 Ulm, Germany
Agnese Petrera
Research Unit Protein Science and Metabolomics and Proteomics Core Facility, Helmholtz Zentrum Munich - German Research Center for Environmental Health, Neuherberg, Germany
Ezio Bonifacio
German Center for Diabetes Research (DZD), Munich, Germany; DFG Center for Regenerative Therapies Dresden, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany; Institute for Diabetes and Obesity, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
Anette-G. Ziegler
Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany; German Center for Diabetes Research (DZD), Munich, Germany; Technical University Munich, School of Medicine, Forschergruppe Diabetes at Klinikum rechts der Isar, Munich, Germany; Corresponding authors at: Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, D-85764 München-Neuherberg, Germany.
Summary: Background: Diabetes in childhood and adolescence includes autoimmune and non-autoimmune forms with heterogeneity in clinical and biochemical presentations. An unresolved question is whether there are subtypes, endotypes, or theratypes within these forms of diabetes. Methods: The multivariable classification and regression tree (CART) analysis method was used to identify subgroups of diabetes with differing residual C-peptide levels in patients with newly diagnosed diabetes before 20 years of age (n=1192). The robustness of the model was assessed in a confirmation and prognosis cohort (n=2722). Findings: The analysis selected age, haemoglobin A1c (HbA1c), and body mass index (BMI) as split parameters that classified patients into seven islet autoantibody-positive and three autoantibody-negative groups. There were substantial differences in genetics, inflammatory markers, diabetes family history, lipids, 25-OH-Vitamin D3, insulin treatment, insulin sensitivity and insulin autoimmunity among the groups, and the method stratified patients with potentially different pathogeneses and prognoses. Interferon-ɣ and/or tumour necrosis factor inflammatory signatures were enriched in the youngest islet autoantibody-positive groups and in patients with the lowest C-peptide values, while higher BMI and type 2 diabetes characteristics were found in older patients. The prognostic relevance was demonstrated by persistent differences in HbA1c at 7 years median follow-up. Interpretation: This multivariable analysis revealed subgroups of young patients with diabetes that have potential pathogenetic and therapeutic relevance. Funding: The work was supported by funds from the German Federal Ministry of Education and Research (01KX1818; FKZ 01GI0805; DZD e.V.), the Innovative Medicine Initiative 2 Joint Undertaking INNODIA (grant agreement No. 115797), the German Robert Koch Institute, and the German Diabetes Association.
