Biobehavioral Triggers, Mechanisms, and Control of Glucose Variability in T1DM

描述（由申请人提供）：与HbA1c一起，1型糖尿病（T1DM）的葡萄糖变异性（GV）越来越被视为血糖控制的主要标志。在我们过去的研究中，我们确定了GV的生理和行为相关性，并成功地测试了一种生物行为干预，同时降低了HbA1c和低血糖的风险。这项研究的一个显著特点是发展并依赖于复杂的计算机模型和先进技术，例如，迄今为止唯一被FDA接受的人类代谢计算机模拟器，作为动物研究的替代品，以及新的糖尿病助理（DiAs）平台，该平台用于第一次[全球]动态人工胰腺试验。我们现在建议通过关注以下基本假设来继续我们的研究：T1DM中的葡萄糖变异性是由挑战代谢系统的行为事件（例如饮食，胰岛素注射）触发的。行为挑战的时间和程度，以及代谢机制吸收它们的能力，决定了GV的程度。这一过程在一定的时间框架内发展，并可因治疗不当而加速，或因生物行为控制的精确时间和剂量而减弱。这一假设的检验将分三个阶段进行：第一阶段（GV的触发）将使用我们广泛的数据库设计葡萄糖变异性综合模型（IMGV），该模型将：(I)帮助理解不合时宜或不平衡处理下系统不稳定的时间和程度，（ii）通过广泛的硅实验阐明系统稳定的时间和前体，帮助设计用于第三阶段的最佳生物行为干预。第二阶段（GV机制）将结合日记、连续血糖监测和胰岛素泵现场记录，并以医院为基础的人体实验室研究为基础，这将阐明行为挑战、生理血糖调节机制和GV之间的关键关系。第3阶段（GV对照）将在随机交叉研究中使用DiAs来测试一种旨在逐渐减弱GV的新型逐步生物行为干预的有效性。该治疗将在血糖控制不良（HbA1c为8.0%）和/或有低血糖风险（有严重低血糖史）的胰岛素泵使用者中进行试验，预计在降低GV方面优于标准泵治疗。总之，该项目将证明：(1)计算机实验与观察和人体实验室研究相结合，加强了假设的制定/检验，并导致有效的治疗设计；（ii）转化为日常使用的尖端人工胰腺技术优于当前最先进的治疗方法。

DESCRIPTION (provided by applicant): Along with HbA1c, glucose variability (GV) in type 1 diabetes (T1DM) is increasingly regarded as a primary marker of glycemic control. In our past studies we identified physiological and behavioral correlates of GV and successfully tested a biobehavioral intervention reducing simultaneously HbA1c and the risk for hypoglycemia. A signature characteristic of this research was the development of, and the reliance upon, sophisticated computer models and advanced technology, e.g. the only to date computer simulator of the human metabolism accepted by the FDA as a substitute to animal studies and the new Diabetes Assistant (DiAs) platform, which was used in the first [Worldwide] trials of ambulatory artificial pancreas. We now propose to continue our investigations by focusing on the following fundamental hypothesis: Glucose variability in T1DM is triggered by behavioral events (e.g. meals, insulin injection) that challenge the metabolic system. The timing and the magnitude of the behavioral challenges, and the ability of the metabolic mechanisms to absorb them, determine the magnitude of GV. This process develops in a certain time frame, and can be accelerated by inadequate treatment, or attenuated by precise timing and dosing of bio- behavioral control. The testing of this hypothesis will proceed in three phases: Phase 1 (triggers of GV) will use our extensive database to design an Integrated Model of Glucose Variability (IMGV), which will: (I) help understand the timing and the magnitude of system destabilization with mistimed or unbalanced treatment, and (ii) assist the design of an optimal biobehavioral intervention to be employed in Phase 3 by extensive in silicon experiments clarifying the timing and the precursors of system stabilization. Phase 2 (mechanisms of GV) will use a combination of diaries, continuous glucose monitoring, and insulin pump records in the field, augmented by hospital-based human lab studies, which will clarify key relationships between behavioral challenges, physiological glucoregulatory mechanisms, and GV. Phase 3 (control of GV) will test, using DiAs in a randomized cross-over study, the effectiveness of a novel stepwise biobehavioral intervention designed to gradually attenuate GV. This treatment will be tested in insulin pump users at poor glycemic control (HbA1c>8.0%) and/or at risk for hypoglycemia (those with history of severe hypoglycemia), and is expected to be superior to standard pump therapy in terms of reduction of GV. In summary, this project will demonstrate that: (I) in silico experiments combined with observational and human lab studies enhance hypothesis formulation/testing, and result in efficient treatment design; (ii) cutting-edge artificial pancrea technology translated for everyday use is superior to state-of-the art current treatments.