Does Diabetes Appear in Distinct Phenotypes in Young People? Results of the Diabetes Mellitus Incidence Cohort Registry (DiMelli)

Introduction
The 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 Methods
As 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.
Results
Patients 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.
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. Thus, our results suggest that refined diabetes classification may require both immune and metabolic phenotyping.

引言
糖尿病发病队列登记处（diabetes mellitus Incidence Cohort Registry, DiMelli）旨在通过免疫、代谢及遗传标志物对糖尿病表型进行特征化分析。本研究根据胰岛自身抗体（islet autoantibody）状态将患者分为三组，探究携带多种糖尿病相关自身抗体、仅携带1种自身抗体及无自身抗体的患者在临床、代谢及遗传参数上的差异，其中包括基于腰围、糖化血红蛋白（glycated hemoglobin A1c, HbA1c）与甘油三酯的胰岛素敏感性（insulin sensitivity, IS）评分。同时本研究亦评估了代谢标志物能否预测免疫状态。

材料与方法
截至2012年6月，德国巴伐利亚州共有630名年龄<20岁、近6个月内被诊断为任意类型糖尿病的患者登记入DiMelli队列。研究人员基于胰岛自身抗体状态对患者进行分组，比较各组间的临床与实验室指标。选取关联度最高的指标开展主成分分析（principal component analysis）。采用受试者工作特征曲线（receiver operating characteristic curve, ROC）评估IS评分预测胰岛自身抗体状态的效能。

结果
携带多种胰岛自身抗体、仅携带1种自身抗体及无自身抗体的患者，在BMI百分位、诊断前体重下降情况、空腹C肽（均P<0.001）及IS评分（P=0.034）方面存在显著差异。然而主成分分析未显示基于自身抗体状态的明确分布模式。以最佳临界值预测胰岛自身抗体阳性（单抗体阳性 vs 无抗体）时，IS评分的特异性为52.0%，灵敏度为86.8%。在预测多种自身抗体阳性（vs 无抗体）时，其灵敏度与特异性均略低，联合应用时的效能亦劣于BMI百分位与空腹C肽指标。

讨论
DiMelli研究显示，携带与未携带胰岛自身抗体的患者在代谢与遗传标志物层面存在差异，但表型存在大量重叠，上述指标无法有效预测自身抗体状态。因此本研究结果提示，精细化的糖尿病分型或许需要同时结合免疫表型与代谢表型。