Abstract

IntroductionThe diabetes mellitus Incidence Cohort Registry (DiMelli) aims to characterize diabetes phenotypes by immunologic, metabolic, and genetic markers. We classified patients into three groups according to islet autoantibody status and examined whether patients with multiple diabetes-associated autoantibodies, one autoantibody, or without autoantibodies differed with respect to clinical, metabolic, and genetic parameters, including an insulin sensitivity (IS) score based on waist, HbA1c, and triglycerides. We also assessed whether metabolic markers predicted the immune status.Materials and MethodsAs of June 2012, 630 patients in Bavaria, Germany, aged <20 years diagnosed with any type of diabetes within the preceding 6 months were registered in DiMelli. We compared the clinical and laboratory parameters between islet autoantibody status defined patient groups. Parameters showing the strongest associations were included in principal component analysis. Receiver operating characteristic curves were used to assess the ability of the IS Score to predict islet autoantibody status.ResultsPatients with multiple islet autoantibodies, one autoantibody, or without autoantibodies were significantly different in terms of BMI percentile, weight loss before diagnosis, fasting C-peptide (all, P<0.001), and IS Score (P=0.034). However, principal component analysis revealed no distinct patterns according to autoantibody status. At the optimal IS Score cut-off for predicting islet autoantibody positivity (single compared to none), the specificity was 52.0% and the sensitivity was 86.8%. With respect to prediction of multiple autoantibodies (compared to none), specificity and sensitivity were slightly lower and in combination inferior to those obtained using the BMI percentile and fasting C-peptide.DiscussionThe DiMelli study indicated that patients with and without islet autoantibodies differed with respect to metabolic and genetic markers but there was considerable overlap of phenotypes, and autoantibody status could not be predicted by these parameters. Thus, our results suggest that refined diabetes classification may require both immune and metabolic phenotyping.

Highlights

  • The diabetes mellitus Incidence Cohort Registry (DiMelli) aims to characterize diabetes phenotypes by immunologic, metabolic, and genetic markers

  • In an earlier analysis of the population-based Diabetes Mellitus Incidence Cohort Registry (DiMelli), we suggested that patients could be distinguished based on the presence of multiple islet autoantibodies, one autoantibody, or no autoantibodies [8]

  • The registry includes children and young adults residing in Bavaria, Germany, who are diagnosed with diabetes of any type according to American Diabetes Association/World Health Organization criteria [13] at

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Summary

Introduction

The diabetes mellitus Incidence Cohort Registry (DiMelli) aims to characterize diabetes phenotypes by immunologic, metabolic, and genetic markers. Discussion: The DiMelli study indicated that patients with and without islet autoantibodies differed with respect to metabolic and genetic markers but there was considerable overlap of phenotypes, and autoantibody status could not be predicted by these parameters. In an earlier analysis of the population-based Diabetes Mellitus Incidence Cohort Registry (DiMelli), we suggested that patients could be distinguished based on the presence of multiple islet autoantibodies, one autoantibody, or no autoantibodies [8]. It remained unclear whether this classification is clinically useful

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