A Novel Approach Applying CGM Metrics to Identify a Prediabetic State

描述（由申请方提供）：拟定研究将在1型糖尿病（T1 D）先证者的一级亲属中使用高级持续葡萄糖监测（CGM）指标检查血糖变异性指标，以获取与T1 D发病机制和预测相关的新信息。我们建议利用目前参加TrialNet自然历史研究（活体生物库）的参与者。对这些受试者进行纵向随访，并就多种胰岛相关自身抗体、HLA基因分型、代谢评估和许多其他风险因素进行深入表型分析。据我们所知，在开发和诊断完全T1 D之前，尚未在TrialNet参与者中应用完整和准确评估T1 D临床前状态期间血糖波动的综合方法。我们相信，使用基于CGM的指标组合来评估血糖变异性指数将有助于识别可能进展为T1 D临床发作的一级亲属。我们假设，与存在1种胰岛自身抗体的受试者相比，存在持续免疫学异常（存在2种或e3种胰岛自身抗体：胰岛素、GAD 65、IA-2和胰岛细胞抗体[伊卡]）的T1 D患者的一级亲属通过CGM检测到广泛的间质葡萄糖变异。这种波动也可能发生在免疫异常、空腹血糖值正常和口服葡萄糖耐量试验（OGTT）正常的亲属中，否则将无法检测到。我们最近报道了持续葡萄糖监测-糖尿病评价图形用户界面（CGM-GUIDE）的开发，该界面提供了对患者血糖波动的上级评估。我们组建了一个前所未有的领先专家团队：1.制定实践指南，以确定患者最有可能从CGM的使用中受益的环境; 2.数学建模和CGM指标开发领域; 3.在代谢异常和TrialNet支持的T1 D临床试验方面的专业知识。拟议的研究最终应作为一种新的工具，与其他免疫学和机制生物标志物相结合，以改善预测，了解发病机制，并最终更准确地评估在未来旨在预防1型糖尿病的干预试验中对治疗的反应。

DESCRIPTION (provided by applicant): The proposed investigation will examine indexes of glycemic variability using advanced Continuous Glucose Monitoring (CGM) metrics in first degree relatives of Type 1 diabetic (T1D) probands to capture new information relevant to T1D pathogenesis and prediction. We propose to utilize participants who are currently enrolled in the TrialNet Natural History Study (Living Biobank). These subjects are longitudinally followed and deeply phenotyped with respect to multiple islet-related autoantibodies, HLA genotyping, metabolic assessment and many other risk factors. To the best of our knowledge, an integrated approach providing a complete and accurate assessment of glycemic excursions during the preclinical state of T1D has not been applied in TrialNet participants prior to the development and diagnosis of full-blown T1D. We believe the use of a combination of CGM-based metrics to assess indexes of glycemic variability will assist the identification of first-degree relatives likly to progress to the clinical onset of T1D. We hypothesize that first-degree relatives of T1D patients with ongoing immunological abnormalities (presence of 2 or e3 islet autoantibodies: insulin, GAD65, IA-2 and islet cell antibodies [ICA]) exhibit wide interstitial glucose variations detected by CGM as compared to subjects with the presence of 1 islet autoantibody. Such excursions may also occur in relatives with immunologic abnormalities, normal fasting glycemic values and normal Oral Glucose Tolerance Test (OGTT) and would otherwise go undetected. We have recently reported the development of the Continuous Glucose Monitoring - Graphical User Interface for Diabetes Evaluation (CGM-GUIDE) that provides a superior assessment of a patient's blood glucose excursions. We have assembled an unprecedented team of leading experts in: 1. Formulating practice guidelines for determining settings where patients are most likely to benefit from the use of CGM; 2. The field of mathematical modeling and CGM metrics development; and 3. Expertise in metabolic abnormalities and TrialNet-supported clinical trials for T1D. The proposed study should ultimately be useful as a new tool in combination with other immunologic as well as mechanistic biomarkers to improve prediction, understand the pathogenesis and ultimately to more accurately evaluate the response to treatment in future intervention trials aimed at preventing type 1 diabetes.