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Aberrant metabolism involvement in early SSNS is sparsely studied, and its pathogenesis remains unclear. Therefore, the goal of this study was to investigate the changes in initiated SSNS patients\u2010related metabolites through serum and urine metabolomics and discover the novel potential metabolites and metabolic pathways.<\/jats:p><\/jats:sec>Methods<\/jats:title>Serum samples (27 SSNS and 56 controls) and urine samples (17 SSNS and 24 controls) were collected. Meanwhile, the non\u2010targeted analyses were performed by ultra\u2010high\u2010performance liquid chromatography\u2010quadrupole time of flight\u2010mass spectrometry (UHPLC\u2010QTOF\u2010MS) to determine the changes in SSNS. We applied the causal inference model, the DoWhy model, to assess the causal effects of several selected metabolites. An ultraperformance liquid chromatography\u2013tandem mass spectrometry (UPLC\u2013MS\/MS) was used to validate hits (D\u2010mannitol, dulcitol, D\u2010sorbitol, XMP, NADPH, NAD, bilirubin, and \u03b1\u2010KG\u2010like) in 41 SSNS and 43 controls. In addition, the metabolic pathways were explored.<\/jats:p><\/jats:sec>Results<\/jats:title>Compared to urine, the metabolism analysis of serum samples was more clearly discriminated at SSNS. 194 differential serum metabolites and five metabolic pathways were obtained in the SSNS group. Eight differential metabolites were identified by establishing the diagnostic model for SSNS, and four variables had a positive causal effect. After validation by targeted MS, except XMP, others have similar trends like the untargeted metabolic analysis.<\/jats:p><\/jats:sec>Conclusion<\/jats:title>With untargeted metabolomics analysis and further targeted quantitative analysis, we found seven metabolites may be new biomarkers for risk prediction and early diagnosis for SSNS.<\/jats:p><\/jats:sec>","DOI":"10.1111\/eci.13978","type":"journal-article","created":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T09:38:53Z","timestamp":1677663533000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Metabolomic profiles in serum and urine uncover novel biomarkers in children with nephrotic syndrome"],"prefix":"10.1111","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1145-2745","authenticated-orcid":false,"given":"Lidan","family":"Hu","sequence":"first","affiliation":[{"name":"Department of Nephrology, The Children's Hospital, Zhejiang 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