Universidade Camilo Castelo Branco-UNICASTELO, Biomedical Engineering Institute, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondesan, 500, São José dos Campos, São Paulo 12247-015, Brazil.
J Biomed Opt. 2013 Aug;18(8):87004. doi: 10.1117/1.JBO.18.8.087004.
Patients with diabetes mellitus and hypertension (HT) diseases are predisposed to kidney diseases. The objective of this study was to identify potential biomarkers in the urine of diabetic and hypertensive patients through Raman spectroscopy in order to predict the evolution to complications and kidney failure. Urine samples were collected from control subjects (CTR) and patients with diabetes and HT with no complications (lower risk, LR), high degree of complications (higher risk, HR), and doing blood dialysis (DI). Urine samples were stored frozen (-20°C) before spectral analysis. Raman spectra were obtained using a dispersive spectrometer (830-nm, 300-mW power, and 20-s accumulation). Spectra were then submitted to principal component analysis (PCA) followed by discriminant analysis. The first PCA loading vectors revealed spectral features of urea, creatinine, and glucose. It has been found that the amounts of urea and creatinine decreased as disease evoluted from CTR to LR/HR and DI (PC1, p<0.05), and the amount of glucose increased in the urine of LR/HR compared to CTR (PC3, p<0.05). The discriminating model showed better overall classification rate of 70%. These results could lead to diagnostic information of possible complications and a better disease prognosis.
患有糖尿病和高血压（HT）疾病的患者易患肾脏疾病。本研究的目的是通过拉曼光谱在糖尿病和高血压患者的尿液中识别潜在的生物标志物，以预测向并发症和肾衰竭的发展。收集了来自对照组（CTR）和无并发症的糖尿病和 HT 患者（低风险，LR）、高并发症程度（高风险，HR）以及进行血液透析（DI）的患者的尿液样本。尿液样本在进行光谱分析之前储存在冷冻（-20°C）中。使用分光光度计（830nm，300mW 功率，20s 累积）获得拉曼光谱。然后将光谱提交给主成分分析（PCA）和判别分析。第一个 PCA 加载向量揭示了尿素、肌酐和葡萄糖的光谱特征。结果发现，随着疾病从 CTR 发展到 LR/HR 和 DI，尿素和肌酐的量减少（PC1，p<0.05），而 LR/HR 尿液中的葡萄糖量增加（PC3，p<0.05）。判别模型显示出更好的总体分类率为 70%。这些结果可能导致对可能并发症的诊断信息和更好的疾病预后。
