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Nuclear Magnetic Resonance Metabolomic Profiling and Urine Chemistries in Incident Kidney Stone Formers Compared with Controls
Journal of the American Society of Nephrology ( IF 10.3 ) Pub Date : 2022-11-01 , DOI: 10.1681/asn.2022040416
Charat Thongprayoon 1 , Ivan Vuckovic 2 , Lisa E Vaughan 3 , Slobodan Macura 2, 4 , Nicholas B Larson 3 , Matthew R D'Costa 1 , John C Lieske 1, 5 , Andrew D Rule 1, 6 , Aleksandar Denic 1
Affiliation  

Background

The urine metabolites and chemistries that contribute to kidney stone formation are not fully understood. This study examined differences between the urine metabolic and chemistries profiles of first-time stone formers and controls.

Methods

High-resolution 1H-nuclear magnetic resonance (NMR) spectroscopy-based metabolomic analysis was performed in 24-hour urine samples from a prospective cohort of 418 first-time symptomatic kidney stone formers and 440 controls. In total, 48 NMR-quantified metabolites in addition to 12 standard urine chemistries were assayed. Analysis of covariance was used to determine the association of stone former status with urine metabolites or chemistries after adjusting for age and sex and correcting for the false discovery rate. Gradient-boosted machine methods with nested cross-validation were applied to predict stone former status.

Results

Among the standard urine chemistries, stone formers had lower urine oxalate and potassium and higher urine calcium, phosphate, and creatinine. Among NMR urine metabolites, stone formers had lower hippuric acid, trigonelline, 2-furoylglycine, imidazole, and citrate and higher creatine and alanine. A cross-validated model using urine chemistries, age, and sex yielded a mean AUC of 0.76 (95% CI, 0.73 to 0.79). A cross-validated model using urine chemistries, NMR-quantified metabolites, age, and sex did not meaningfully improve the discrimination (mean AUC, 0.78; 95% CI, 0.75 to 0.81). In this combined model, among the top ten discriminating features, four were urine chemistries and six NMR-quantified metabolites.

Conclusions

Although NMR-quantified metabolites did not improve discrimination, several urine metabolic profiles were identified that may improve understanding of kidney stone pathogenesis.



中文翻译:


肾结石形成者与对照者的核磁共振代谢组学分析和尿液化学分析


 背景


导致肾结石形成的尿液代谢物和化学成分尚不完全清楚。这项研究检查了首次结石形成者和对照组的尿液代谢和化学特征之间的差异。

 方法


对来自 418 名首次出现症状的肾结石形成者和 440 名对照者的前瞻性队列的 24 小时尿液样本进行了基于高分辨率1 H 核磁共振 (NMR) 光谱的代谢组学分析。除了 12 种标准尿液化学成分外,总共还检测了 48 种 NMR 定量代谢物。在调整年龄和性别并校正错误发现率后,使用协方差分析来确定结石形成状态与尿液代谢物或化学成分的关联。应用具有嵌套交叉验证的梯度增强机器方法来预测结石形成状态。

 结果


在标准尿液化学指标中,结石形成者的尿液草酸盐和钾含量较低,而尿液钙、磷酸盐和肌酐较高。在 NMR 尿液代谢物中,结石形成者的马尿酸、葫芦巴碱、2-呋喃酰甘氨酸、咪唑和柠檬酸盐含量较低,肌酸和丙氨酸含量较高。使用尿液化学、年龄和性别的交叉验证模型得出的平均 AUC 为 0.76(95% CI,0.73 至 0.79)。使用尿液化学、NMR 量化代谢物、年龄和性别的交叉验证模型并没有显着改善区分度(平均 AUC,0.78;95% CI,0.75 至 0.81)。在这个组合模型中,前十个区分特征中,四个是尿液化学成分,六个是 NMR 量化的代谢物。

 结论


尽管核磁共振定量代谢物并不能提高辨别能力,但确定了几种尿液代谢谱,可以提高对肾结石发病机制的了解。

更新日期:2022-11-01
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