代谢表型的动态变化特征与新发糖尿病及并发症的关联和机制研究

糖尿病已成为影响我国居民健康和经济社会发展的重大公共卫生问题。尽管动物实验对糖尿病的发病机制已经产生大量证据，然而在人群中个体间存在较大差异，同时缺乏长期随访来观察糖尿病发生前后代谢表型指标的动态变化，潜在的规律和机制尚不明确。本项目将依托已经建立的东风-同济队列研究，利用已完成的基线、第一次和第二次随访数据分析十年间三次重复采样的体重、血糖、胰岛素、糖化血红蛋白、炎性因子、脂肪因子、肝脏因子等糖尿病相关表型指标和生物标志物的个体间差异，以及随着健康状况的变化（从血糖正常到糖尿病前期到糖尿病的全过程），糖尿病相关指标的个体内动态变化过程；并利用基因组学、表观遗传、蛋白质组学和代谢组学等多组学技术手段分析可能机制。同时探索表型变化和表型特征对新发糖尿病及糖尿病并发症的预测作用。研究将有助于寻找糖尿病及并发症的防治对策和潜在靶点，为糖尿病高危人群的早期预测、预防和个性化干预提供新的思路。

Diabetes has become a major public health threat to the people’s health and socio-economic development in China. Although mounting evidence has been generated from many animal experiments, large between-person variations exist in populations and there is a lack of long-term follow-up studies to observe the dynamic changes of metabolic phenotypes before and after diabetes diagnosis. The underlying mechanisms of the between-person and within-person variability of metabolic changes are largely unclear. The proposed project will build on the well-established Dongfeng-Tongji Cohort, and utilize the comprehensive database and biospecimen samples from the completed baseline, first and second follow-up visits from 2008 to 2018. We are going to analyze the between-person variations in the metabolic phenotypes, including but not limited to body weight, waist, fasting glucose, fasting insulin, HbA1c, inflammatory biomarkers, cytokines, hepatokines. Meanwhile, the within-person dynamic changes in those metabolic markers will also be evaluated according to the changes in health status during the 10 years. Furthermore, multi-omics technics and data will also be used to explore the underlying mechanisms for the between-person and within-person variability of metabolic changes. Finally, the predictive values of the characteristics and dynamic changes of metabolic phenotypes on incident diabetes and diabetes complications will also be explored. In conclusion, the proposed project will help find the potential targets and preventive strategies for diabetes and its complications, and provide novel means for the early prediction, prevention and personalized treatment.