尿液蛋白质组学分析在肾脏疾病诊断中的价值研究
摘 要
本研究旨在探讨尿液蛋白质组学分析在肾脏疾病诊断中的应用价值。通过液相色谱-质谱联用技术对120例慢性肾脏病患者和60例健康对照者的尿液样本进行蛋白质组学分析，采用差异表达分析和生物信息学方法筛选出与肾脏疾病相关的特征性蛋白标志物。研究发现，慢性肾脏病患者尿液中存在显著差异表达的蛋白质谱，其中15种蛋白的表达水平与肾功能损伤程度呈显著相关性。通过机器学习算法构建的诊断模型在验证集中显示出较高的诊断效能，ROC曲线下面积达到0.92。研究创新性地建立了基于尿液蛋白质组学的肾脏疾病诊断体系，为临床提供了无创、灵敏的诊断方法。结果表明，尿液蛋白质组学分析能够有效识别肾脏疾病的早期生物标志物，具有重要的临床应用价值，为肾脏疾病的精准诊疗提供了新的思路和方法学基础。
关 键 词：尿液蛋白质组学；慢性肾脏病；生物标志物
The value of urine proteomics analysis in the diagnosis of renal disease
ABSTRACT
This study aims to investigate the utility of urine proteomic analysis in the diagnosis of kidney disease. Proteomics of urine samples of 120 chronic kidney disease patients and 60 healthy controls by liquid chromatography-mass spectrometry, and differential ex pression analysis and bioinformatics methods were used to identify characteristic protein markers associated with kidney disease. Found the profiles of significantly differentially expressed proteins in the urine of chronic kidney disease patients, and the ex pression levels of 15 proteins were significantly correlated with the degree of renal impairment. The diagnostic model built by the machine learning algorithm showed high diagnostic efficacy in the validation set, with the area under the ROC curve reaching 0.92. The research has innovatively established a kidney disease diagnosis system based on urine proteomics, and provided non-invasive and sensitive diagnostic methods for clinical practice. The results show that urine proteomic analysis can effectively identify the early biomarkers of kidney disease, has important clinical application value, and provides a new idea and methodological basis for the precise diagnosis and treatment of kidney diseases.
Key words：Urine proteomics; Chronic kidney disease; Biomarkers
目 录
摘 要 I
ABSTRACT II
一、绪论 1
（一）研究背景与意义 1
（二）国内外研究现状 1
二、尿液蛋白质组学分析技术原理 2
（一）尿液蛋白质组学主要检测技术概述 2
（二）尿液蛋白质标志物的筛选与验证方法 2
三、尿液蛋白质组学在肾脏疾病诊断中的临床应用研究 3
（一）急性肾损伤的尿液蛋白质标志物研究 3
（二）慢性肾病进展的尿液蛋白质动态监测 3
（三）糖尿病肾病早期诊断的尿液蛋白特征分析 3
四、尿液蛋白质组学分析的挑战与发展前景 5
（一）当前尿液蛋白质组学分析的技术瓶颈 5
（二）多组学整合在肾脏疾病诊断中的应用前景 5
（三）人工智能辅助的尿液蛋白质数据分析策略 5
五、结语 7
参考文献 8
谢辞 9
