Preliminary analysis of urinary exosomes metabolomic biomarkers in lupus nephritis patients
10.3760/cma.j.cn114452-20250106-00016
- VernacularTitle:狼疮性肾炎患者尿液外泌体代谢组学标志物初步分析
- Author:
Ping YANG
1
;
Wenjing LIU
;
Hong YAN
Author Information
1. 南京大学医学院附属鼓楼医院检验科，南京 210008
- Publication Type:Journal Article
- Keywords:
Lupus nephritis;
Exosomes;
Liquid chromatography-mass spectrometry;
Urine;
Biomarkers
- From:
Chinese Journal of Laboratory Medicine
2025;48(5):650-655
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the distinctive urinary exosomal metabolites in patients with lupus nephritis (LN).Methods:In this case-control study, urine samples were collected from 29 LN patients (5 males and 24 females; age, 32?±?12 years old) admitted to the Department of Rheumatology in the Nanjing University Medical School Affiliated Drum Tower Hospital form October 20th, 2022 to March 10th, 2024, as well as from 20 healthy volunteers (4 males and 16 females; age 34?±?11 years old) undergoing routine physical examinations. Exosomes were isolated using polyethylene glycol precipitation, and metabolomic profiling was performed using liquid chromatography-mass spectrometry (LC-MS). The preprocessed data matrix was analyzed via principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) use R lamguage. Differential metabolites were screened based on the variable importance in projection (VIP) values derived from the OPLS-DA model and Student′s t-test. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis.Results:Metabolomic analysis identified a total of 963 metabolites. Based on the criteria of VIP>1 and P<0.05, three differential exosomal metabolites—L-tryptophan, L-isoleucine, and L-phenylalanine—were ultimately selected. The areas under the ROC curves were 0.774, 0.783, and 0.789, respectively, with a combined AUC of 0.847. Conclusion:This study preliminarily identified characteristic urinary exosomal metabolites in LN patients, providing novel insights and strategies for the subsequent identification of biomarkers in LN.
