Understanding, Predicting and Preventing Type 2 Diabetes in Youth, Boston Clinical Center (UPP Study)

项目总结/摘要 肥胖症的增加导致糖尿病前期（preD）和2型糖尿病（T2 D）发病率空前增加 在儿童和青少年中，COVID 19大流行加剧了这一令人担忧的趋势。根据目前的证据， 仍然难以预测患有preD的儿童和青少年是否会进展为T2 D。我们的提案旨在 解决T2 D发病机制中的关键问题，重点是可改变的风险因素。利用一个 波士顿儿童医院、乔斯林糖尿病中心和马萨诸塞州总医院之间的合作， 我们与大波士顿地区的社区卫生中心合作，计划招募一个多样化的队列， 青春期早期青年（7-15岁，n=300），preD，BMI升高（≥第95百分位数）， 糖尿病和一个或多个其他风险因素。我们建议将联合收割机严格的年度临床研究与 方便的远程评估，以获得代谢，激素和环境的颗粒状了解 导致T2 D发病的因素。在目标1中，我们将测试葡萄糖稳态的测量和 发展为T2 D的preD青年与恢复正常的preD青年之间的β细胞功能不同 或保持preD。我们建议使用口服GTT和肠促胰岛素激素分析β细胞和β细胞功能 水平和评估适应社区环境，例如，动态血糖监测仪和家用糖化血红蛋白试剂盒。 在目标2中，我们将测试健康水平和体育活动量是否在患有preD的青少年之间存在差异， 与那些恢复正常或保持preD的人相比，我们建议评估健身水平 使用详细的临床评估，包括最大摄氧量，适应社区环境的评估，包括 握力，以及使用可穿戴设备和基于应用程序的活动跟踪的自由生活评估。在目标3中，我们将测试 生长和青春期身体组成的演变是否可预测T2 D的进展。我们建议 使用DXA分析身体成分（总脂肪和内脏脂肪），使用基于超声心动图的肝脏脂肪 评估，性腺激素，肾上腺雄激素和生长激素作用的介质，以及 适应社区环境的评估，例如，BMI和基于应用程序的饮食调查。作为次要目标， 我们建议建立一个数据储存库，以便评估有助于 T2 D发病在财团水平，措施包括健康的社会决定因素，邻里和 地理特征（使用地理编码技术）和环境问题。我们亦建议 创建生物储存库，以允许多组学研究识别基因组、表观遗传和/或 代谢组学标志物的进展，从preD到T2 D的青年在财团的水平。我们建议收集 纵向样品的丰富生物贮藏库（即，血浆、PBMC、尿液、粪便、毛发）， 为未来系统生物学驱动的研究奠定基础。总之，这些研究将允许开发一个 预测模型基于社区一级容易测量的变量，然后可以应用于 检测和治疗T2 D风险最高的青年。

Project Summary / Abstract Rising obesity has led to an unprecedented increase in pre-diabetes (preD) and type 2 diabetes (T2D) incidence in children and adolescents, a worrisome trend amplified by the COVID 19 pandemic. Based on current evidence, it remains difficult to predict whether children and adolescents with preD will progress to T2D. Our proposal aims to address key questions in the pathogenesis of T2D, focusing on modifiable risk factors. Leveraging a collaboration between Boston Children’s Hospital, Joslin Diabetes Center, and Massachusetts General Hospital, in partnership with community health centers in the Greater Boston area, we propose to recruit a diverse cohort of early pubertal youth (ages 7-15, n=300) with preD, elevated BMI (≥95th percentile), a positive family history of diabetes, and one or more additional risk factors. We propose to combine rigorous annual clinical studies with convenient remote assessments, to gain a granular understanding of metabolic, hormonal and environmental factors contributing to T2D pathogenesis. In Aim 1, we will test whether measures of glucose homeostasis and beta cell function differ between youth with preD who progress to T2D versus those who revert to normoglycemia or remain preD. We propose to analyze glycemia and beta cell function using oral GTT and incretin hormone levels, and assessments adaptable to community settings, e.g., continuous glucose monitors and home A1c kits. In Aim 2, we will test whether fitness level and amount of physical activity differ between youth with preD who progress to T2D versus those who revert to normoglycemia or remain preD. We propose to evaluate fitness level using detailed clinical assessments, including VO2 max, assessments adaptable to community settings including grip strength, and free-living assessments using wearables and app-based activity tracking. In Aim 3, we will test whether evolution of body composition during growth and puberty predicts progression to T2D. We propose to analyze body composition (total and visceral fat) using DXA, and hepatic fat using echography-based assessments, gonadal hormones, adrenal androgens, and mediators of growth hormone action, as well as assessments adaptable to community settings, e.g., BMI and app-based dietary surveys. As secondary aims, we propose to create a data repository to allow evaluation of social and environmental factors contributing to T2D onset at a consortium level, with measures including social determinants of health, neighborhood and geographic characteristics (using geocoding techniques), and the environmental exposome. We also propose the creation of a biological repository to allow multi-omics studies to identify genomic, epigenetic, and/or metabolomic markers for progression from preD to T2D in youth at a consortium level. We propose to collect a rich biorepository of longitudinal samples (i.e., plasma, PBMCs, urine, stool, hair) from all participants that will set the stage for future systems biology-driven studies. Together, these studies will permit development of a predictive model based on variables easily measurable at the community level, which can then be applied to the detection and treatment of youth at highest risk of T2D.