Bian Xueyan, Wang Chenwen, Wang Majie, Yin Ailing, Xu Jiayan, Liu Mijia, Wang Hui, Cao Yating, Huang Xin, Qin Chenxue, Zhang Ye, Yu Heming
Department of Nephrology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China.
Front Mol Biosci. 2025 Mar 17;12:1541440. doi: 10.3389/fmolb.2025.1541440. eCollection 2025.
Given the increasing incidence rate of diabetic kidney disease (DKD), there is an urgent need for methods to diagnose and treat DKD in clinics.
Serum samples were collected from 56 DKD patients and 32 healthy controls (HCs) at the First Affiliated Hospital of Ningbo University, and the metabolic profiles were obtained through untargeted metabolomics using gas chromatography mass spectrometry. The data were then analyzed using principal components analysis, orthogonal partial least-squares discriminant analysis, Pearson correlation analysis, and receiver operating characteristic (ROC) curve.
It was found that the serum metabolic profiles of the DKD patients were significantly different from those of the HCs. A total of 68 potential differential metabolites were identified that were involved in arginine biosynthesis, ascorbate and aldarate metabolism, and galactose metabolism, among others; a total of 31 differential metabolites were also identified between early-stage (EDG) and late-stage (LDG) DKD patients. Additionally, 30 significant metabolic differences were observed among the EDG, LDG, and HC groups. Based on Pearson correlation analysis between the abundances of the differential metabolites and clinical markers (estimated glomerular filtration rate, blood urea nitrogen, serum creatinine, and urinary albumin/creatinine ratio) and area under the ROC curve (AUROC) analysis, the AUROC values of myoinositol and gluconic acid were found to be 0.992 and 0.991, respectively, which can be used to distinguish DKD patients from HCs.
These results indicate that myoinositol and gluconic acid could possibly be used as biomarkers of DKD.
鉴于糖尿病肾病（DKD）的发病率不断上升，临床上迫切需要诊断和治疗DKD的方法。
在宁波大学第一附属医院收集了56例DKD患者和32例健康对照者（HCs）的血清样本，并通过气相色谱-质谱联用的非靶向代谢组学方法获得代谢谱。然后使用主成分分析、正交偏最小二乘判别分析、Pearson相关性分析和受试者工作特征（ROC）曲线对数据进行分析。
发现DKD患者的血清代谢谱与HCs有显著差异。共鉴定出68种潜在的差异代谢物，它们参与精氨酸生物合成、抗坏血酸和醛糖酸代谢以及半乳糖代谢等；在早期（EDG）和晚期（LDG）DKD患者之间也共鉴定出31种差异代谢物。此外，在EDG、LDG和HC组之间观察到30个显著的代谢差异。基于差异代谢物丰度与临床指标（估计肾小球滤过率、血尿素氮、血清肌酐和尿白蛋白/肌酐比值）之间的Pearson相关性分析以及ROC曲线下面积（AUROC）分析，发现肌醇和葡萄糖酸的AUROC值分别为0.992和0.991，可用于区分DKD患者和HCs。
这些结果表明肌醇和葡萄糖酸可能用作DKD的生物标志物。
