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肾脏病与透析肾移植杂志 ›› 2025, Vol. 34 ›› Issue (5): 406-414.DOI: 10.3969/j.issn.1006⁃298X.2025.05.002

• 论著 • 上一篇    下一篇

非靶代谢组学揭示 IgA 肾病代谢变化与诊断标志物筛选

  

  • 出版日期:2025-10-28 发布日期:2025-10-30

Untargeted metabolomics elucidates metabolic alterations and screening of diagnostic biomarkers in IgA nephropathy

  • Online:2025-10-28 Published:2025-10-30

摘要: 目的:通过非靶向代谢组学方法分析 IgA 肾病(IgAN)患儿血浆中的代谢物变化,寻找潜在的无创诊断 IgAN 的标志物。方法:收集 2024 年 1 月至 12 月南京市儿童医院住院的 IgAN 患儿血浆标本及健康体检儿童血浆标本作为对照组,采用液相色谱⁃串联质谱(LC⁃MS/MS)进行代谢组学检测,通过正交偏最小二乘判别分析(OPLS⁃DA)筛选差异代谢物,结合 KEGG 数据库进行代谢通路富集分析,利用受试者工作特征曲线(ROC)筛选潜在诊断标志物并构建联合诊断模型。结果:共检出 651 种代谢物,其中 66 种存在显著差异(P<0.05,VIP>1),主要富集于不饱和脂肪酸合成、赖氨酸降解等通路。12 种代谢物(如磷脂酰胆碱 40:4|18:0_22:4、缬氨酸⁃亮氨酸等)的曲线下面积(AUC)≥0.85,联合诊断模型 AUC=1.00,显示完美区分能力。结论:IgAN 患儿血浆代谢谱发生显著变化,脂质类和氨基酸类代谢物变化尤为显著,12 种代谢物有望作为无创诊断标志物。

关键词: IgA 肾病, 代谢组学, 生物标志物, 代谢通路

Abstract: Objective: This study aims to analyze the changes in plasma metabolites of pediatric patients with IgA nephropathy (IgAN) using non⁃targeted metabolomics, to identify potential non⁃invasive diagnostic biomarkers and provide a basis for early diagnosis of IgAN. Methodology: Plasma samples from IgAN pediatric patients hospitalized at Nanjing Children􀆳s Hospital from January to December 2024 were collected as the case group, and samples from healthy individuals undergoing physical examinations as the control group. Metabolomics analysis was performed using liquid chromatography⁃tandem mass spectrometry (LC⁃MS/MS). Differential metabolites were screened by orthogonal partial least squares discriminant analysis (OPLS⁃DA), and metabolic pathway enrichment analysis was conducted with the KEGG database. Potential diagnostic biomarkers were identified via receiver operating characteristic (ROC) curve analysis, and a combined diagnostic model was constructed. Results: A total of 651 metabolites were detected, with 66 showing significant differences (P<0.05, VIP>1), mainly enriched in pathways such as unsaturated fatty acid synthesis and lysine degradation. Twelve metabolites (e.g., PC40:4|18:0_22:4, Val⁃Leu, Deoxyadenosine) had high diagnostic accuracy (AUC ≥0.85). The combined diagnostic model achieved an AUC of 1.00, demonstrating perfect discriminative ability. Conclusion: The plasma metabolite profile of IgAN pediatric patients undergoes significant changes, with notable alterations in lipid and amino acid metabolites. These 12 metabolites have high diagnostic accuracy and potential as non⁃invasive diagnostic biomarkers for IgAN.

Key words: IgA nephropathy, metabolomics, biomarkers, metabolic pathways