基于蛋白质组学发现的尿液蛋白对糖尿病肾脏疾病发生的预警价值及机制研究

Diabetic kidney disease (DKD) has become the leading cause of chronic kidney disease. Kidney biopsy pathology is considered to be the gold standard for the diagnosis of DKD, but its clinical application is limited. However, the value of urinary albumin in predicting DKD is of limited value. This study intended to discover predictive markers of DKD at early stage and analyze the function of markers by proteomics. Urine proteomics analysis of the prospective cohort study conducted by the research team found that specific urinary haptoglobin predicts chronic renal insufficiency (CRI) in patients with type 2 diabetic proliferative retinopathy, suggesting that urinary proteomics can be used as a predictor of early Kidney injury markers. Based on this, our team used kidney puncture and pathology as the basis for the diagnosis of DKD. In a small sample, the quantitative proteomics research method of Nano-LC-ESI-MS/MS was used to analyze the urine proteomics, screen and quantify of DKD risk-related proteins at same time. To validate the significant differentially expressed proteins in prospective nested case-control samples and construct the predictive models with diabetic retinopathy; to verify the predictive models in a cohort study; and to study cell biology to prove the protein signaling pathways and mechanisms involved in DKD. This project will provide a theoretical basis for the early intervention treatment of DKD.

糖尿病肾脏疾病（DKD）已成为慢性肾脏病首要病因。肾脏活检病理被认为是诊断DKD金标准，但临床应用受限；而尿微量白蛋白对DKD发生预测价值有限。本研究拟通过尿液蛋白质组学分析，发现DKD发生预测标记物并进行功能解析。课题组前期通过前瞻性队列研究样本尿蛋白质组学分析发现，特异性尿触珠蛋白预测2型糖尿病增殖型视网膜病变患者慢性肾功能不全(CRI)发生，提示尿蛋白质组学可发现早期肾损伤标记物。在此基础上，项目组利用糖尿病肾脏疾病诊断金标准-肾脏穿刺作为DKD诊断依据，在小样本中拟采用液质联用定量蛋白质组学进行尿液蛋白质组分析，筛选并定量DKD发生风险相关蛋白；在前瞻性巢式病例对照样本中验证显著差异表达蛋白，并结合糖尿病视网膜病变构建预测模型；在队列研究中验证该预测模型；通过生物信息学及细胞生物学研究，明确验证蛋白参与DKD发生信号通路及机制。本课题将为糖尿病肾脏疾病早期干预治疗提供理论依据。

糖尿病肾脏疾病（DKD）已成为慢性肾脏病首要病因。尿微量白蛋白对DKD发生预测价值有限。基于课题组前期工作及最新研究进展，对确诊DKD和Non-DKD患者进行尿液蛋白质组学分析，验证及筛选出糖尿病肾脏疾病相关蛋白（Complement C3、Fibroblast Growth Factor 23、Alpha-2-macroglobulin、Vitamin D-binding protein、Haptoglobin、Albumin等）。通过尿液蛋白质组合对DKD发生风险识别的灵敏度与特异度分析发现：Complement C3、Fibroblast Growth Factor 23、Vitamin D-binding protein三种蛋白组合对于DKD的风险识别灵敏度为0.88，特异度为0.94。纳入筛选出Complement C3、Fibroblast Growth Factor 23、Vitamin D-结合蛋白等糖尿病肾脏疾病相关蛋白，校正相关行为因素及代谢因素，应用多因素风险预测模型分析发现，尿液蛋白质组合预测糖尿病肾病发生风险比为1.65。本课题将为糖尿病肾脏疾病早期干预治疗提供理论依据。