A Novel Approach Applying CGM Metrics to Identify a Prediabetic State

描述（由申请人提供）：拟议的调查将使用先进的连续血糖监测（CGM）指标检查 1 型糖尿病（T1D）先证者一级亲属的血糖变异指数，以捕获与 T1D 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（活生物库）的参与者。对这些受试者进行纵向跟踪，并对多种胰岛相关自身抗体、HLA 基因分型、代谢评估和许多其他危险因素进行深入表型分析。据我们所知，在发展和诊断成熟的 T1D 之前，TrialNet 参与者尚未应用一种综合方法，对 T1D 临床前状态期间的血糖波动进行完整、准确的评估。我们相信，结合使用基于 CGM 的指标来评估血糖变异性指标将有助于识别可能进展为 T1D 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，持续免疫异常（存在 2 种或 e3 种胰岛自身抗体：胰岛素、GAD65、IA-2 和胰岛细胞抗体 [ICA]）的 T1D 患者的一级亲属表现出 CGM 检测到的广泛间质葡萄糖变化。这种偏离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，否则不会被发现。我们最近报道了连续血糖监测 - 用于糖尿病评估的图形用户界面 (CGM-GUIDE) 的开发，它可以对患者的血糖波动提供卓越的评估。我们组建了一支前所未有的领先专家团队，负责： 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. 代谢异常和 TrialNet 支持的 T1D 临床试验方面的专业知识。拟议的研究最终应可作为一种新工具，与其他免疫学和机械生物标志物相结合，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.