A Novel Approach Applying CGM Metrics to Identify a Prediabetic State

描述（由申请人提供）：拟议的研究将使用先进的连续血糖监测（CGM）指标在1型糖尿病（T1D）先证者的一级亲属中检测血糖变异性指标，以获取与T1D发病机制和预测相关的新信息。我们建议使用目前在TrialNet自然历史研究（活生物库）注册的参与者。对这些受试者进行了纵向随访，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了深入的表型分析。据我们所知，在T1D临床前状态提供完整和准确的血糖漂移评估的综合方法尚未应用于TrialNet参与者在全面T1D发展和诊断之前。我们认为，结合使用基于cgm的指标来评估血糖变异性指标，将有助于识别可能发展为T1D临床发病的一级亲属。我们假设，与存在1个胰岛自身抗体的受试者相比，存在持续免疫异常（存在2或3个胰岛自身抗体：胰岛素、GAD65、IA-2和胰岛细胞抗体[ICA]）的T1D患者的一级亲属在CGM检测中表现出广泛的间质性葡萄糖变化。这种漂移也可能发生在免疫异常、空腹血糖值正常、口服葡萄糖耐量试验（OGTT）正常的亲属中，否则就不会被发现。我们最近报道了连续血糖监测-糖尿病评估图形用户界面（CGM-GUIDE）的发展，该界面提供了对患者血糖偏差的卓越评估。我们在以下方面组建了一支前所未有的顶尖专家团队：制定实践指南，以确定患者最有可能从使用CGM中获益的环境；2. 数学建模与CGM度量领域的发展和3。专门研究代谢异常和trialnet支持的T1D临床试验。该研究最终将作为一种新的工具，与其他免疫学和机制生物标志物相结合，以提高预测，了解发病机制，并最终在未来旨在预防1型糖尿病的干预试验中更准确地评估对治疗的反应。

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.