Investigation on potential subtyping and progression biomarkers of nephrotic syndrome based on LC-MS metabolomics technology
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-pheny l alanine 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 People1s Hospital[(2020)Provincial Medical Ke Lun Shen Zi No.30].
potential markers of typing/progressionurine metabolomicsROC analysismultiple linear regression analysis
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