The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
Department of Nephrology, Urology & Nephrology Center, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), China.
FEBS Open Bio. 2023 Oct;13(10):1844-1858. doi: 10.1002/2211-5463.13683. Epub 2023 Aug 11.
Diabetic kidney disease (DKD) is an important cause of end-stage renal disease with changes in metabolic characteristics. The objective of this study was to study changes in serum metabolic characteristics in patients with DKD and to examine metabolite panels to distinguish DKD from diabetes with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We recruited 40 type II diabetes mellitus (T2DM) patients with or without DKD from a single center for a cross-sectional study. Serum metabolic profiling was performed with MALDI-TOF-MS using a vertical silicon nanowire array. Differential metabolites between DKD and diabetes patients were selected, and their relevance to the clinical parameters of DKD was analyzed. We applied machine learning methods to the differential metabolite panels to distinguish DKD patients from diabetes patients. Twenty-four differential serum metabolites between DKD patients and diabetes patients were identified, which were mainly enriched in butyrate metabolism, TCA cycle, and alanine, aspartate, and glutamate metabolism. Among the metabolites, l-kynurenine was positively correlated with urinary microalbumin, urinary microalbumin/creatinine ratio (UACR), creatinine, and urea nitrogen content. l-Serine, pimelic acid, 5-methylfuran-2-carboxylic acid, 4-methylbenzaldehyde, and dihydrouracil were associated with the estimated glomerular filtration rate (eGFR). The panel of differential metabolites could be used to distinguish between DKD and diabetes patients with an AUC value reaching 0.9899-0.9949. Among the differential metabolites, l-kynurenine was related to the progression of DKD. The differential metabolites exhibited excellent performance at distinguishing between DKD and diabetes. This study provides a novel direction for metabolomics-based clinical detection of DKD.
糖尿病肾病（DKD）是一种重要的终末期肾脏疾病病因，其代谢特征发生改变。本研究旨在研究 DKD 患者血清代谢特征的变化，并使用基质辅助激光解吸电离飞行时间质谱（MALDI-TOF-MS）检测代谢物谱来区分 DKD 与糖尿病。我们从单中心招募了 40 名 2 型糖尿病（T2DM）患者，其中包括有或无 DKD 的患者，进行了横断面研究。使用垂直硅纳米线阵列的 MALDI-TOF-MS 进行血清代谢组学分析。选择 DKD 患者与糖尿病患者之间的差异代谢物，并分析其与 DKD 临床参数的相关性。我们将机器学习方法应用于差异代谢物谱，以区分 DKD 患者和糖尿病患者。在 DKD 患者和糖尿病患者之间鉴定出 24 种差异血清代谢物，主要富集在丁酸代谢、三羧酸循环和丙氨酸、天冬氨酸和谷氨酸代谢途径。在这些代谢物中，犬尿氨酸与尿微量白蛋白、尿微量白蛋白/肌酐比（UACR）、肌酐和尿素氮含量呈正相关。l-丝氨酸、戊二酸、5-甲基呋喃-2-羧酸、4-甲基苯甲醛和二氢尿嘧啶与估计肾小球滤过率（eGFR）相关。差异代谢物谱可用于区分 DKD 患者和糖尿病患者，AUC 值达到 0.9899-0.9949。在差异代谢物中，犬尿氨酸与 DKD 的进展有关。差异代谢物在区分 DKD 和糖尿病方面表现出优异的性能。本研究为基于代谢组学的 DKD 临床检测提供了新的方向。
