Investigation on potential subtyping and progression biomarkers of nephrotic syndrome based on LC-MS metabolomics technology
10.16438/j.0513-4870.2023-1417
- VernacularTitle:基于LC-MS代谢组学技术的肾病综合征潜在分型及进展生物标志物的研究
- Author:
Qing-yu ZHANG
1
;
Qian WANG
1
;
Xing-xing ZHANG
1
;
Song-jia GUO
2
;
Ai-ping LI
1
Author Information
1. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China; The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan 030006, China; The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan 030006, China
2. Shanxi Provincial People's Hospital, Taiyuan 030012, China
- Publication Type:Research Article
- Keywords:
potential markers of typing/progression;
urine metabolomics;
ROC analysis;
multiple linear regression analysis
- From:
Acta Pharmaceutica Sinica
2024;59(6):1779-1786
- CountryChina
- Language:Chinese
-
Abstract:
Nephrotic syndrome (NS) has a variety of classifications, pathogenesis and pathological types. Clinical diagnosis primarily relies on serum biochemistry, while the specific classification necessitates renal puncture for biopsy, which is hindered by poor patient compliance. Therefore, it is of great significance for clinical diagnosis to find a non-invasive and rapid method to reflect the classification and progression of nephrotic syndrome. In this study, LC-MS metabolomics combined with receiver operating characteristic (ROC) and multiple linear regression analysis was used to screen and identify potential biomarkers capable of reflecting the typing and progression of nephrotic syndrome. According to the statistical parameters VIP>1, P<0.05 and AUC>0.5 obtained from the orthogonal partial least squares discriminant analysis (OPLS-DA) model, five potential classification markers were screened to distinguish membranous nephropathy (MN) from IgA nephropathy (IgAN), including indoleacetic acid, isoleucine proline, DL-indole-3-lactic acid, D-phenylalanine and L-tryptophan. Furthermore, using estimated glomerular filtration rate (eGFR) as the dependent variable, a multiple linear regression analysis was conducted to identify the potential progression markers capable of reflecting the progression of MN to uremia. These metabolites included alanylleucine, 9-capryloylcarnitine, gluconic acid, caprylyl glycine and sebacic acid. Potential markers of progression of IgA nephropathy to uremia comprised alanylleucine, 9-capryloylcarnitine, caprylyl glycine, and sebacic acid. This study provides a theoretical basis for the discovery of potential classification and progression biomarkers of kidney disease, and also offers a methodological reference for future research in this area. The protocol was approved by the Ethics Committee of Shanxi Provincial People's Hospital [(2020) Provincial Medical Ke Lun Shen Zi No. 30].
