Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles
Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles
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DOI：
10.1021/ac0708588
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发表时间：
2007-09-15
影响因子：
7.4
通讯作者：
Marrie, Thomas J.
中科院分区：
文献类型：
--
作者：
Slupsky, Carolyn M.;Rankin, Kathryn N.;Marrie, Thomas J.
代谢组学可能有能力通过鉴定在环境、致病或毒理学损害中变化的代谢物的分数来彻底改变疾病诊断，核磁共振波谱已经成为测量这些变化的主要工具之一，因为核磁共振波谱可以准确地识别代谢物及其浓度。分析核磁共振数据的主要方法是光谱分割技术。然而，在核磁共振光谱中识别光谱区域不足以进行诊断评估，因为不知道感兴趣的区域是严格由代谢变化引起的还是仅仅是人为的。在本文中，我们探讨了人类在性别、昼夜变化和年龄方面的差异。我们使用性别差异的例子来比较传统的光谱分束技术（核磁共振光谱区）和新的目标分析技术（代谢物及其浓度）。我们表明，有针对性的分析产生稳健的模型，生成准确的代谢物浓度数据，并提供可用于帮助理解健康人群代谢差异的数据。发现与线粒体能量代谢相关的代谢物可区分性别和年龄。饮食成分和一些与昼夜节律相关的代谢物可以区分一天中尿液收集的时间。产生这些差异的机制将是发现新的诊断测试和对疾病机制的新理解的关键。
Metabolomics may have the capacity to revolutionize disease diagnosis through the identification of scores of metabolites that vary during environmental, pathogenic, or toxicological insult NMR spectroscopy has become one of the main tools for measuring these changes since an NMR spectrum can accurately identify metabolites and their concentrations. The predominant approach in analyzing NMR data has been through the technique of spectral binning. However, identification of spectral areas in an NMR spectrum is insufficient for diagnostic evaluation, since it is unknown whether areas of interest are strictly caused by metabolic changes or are simply artifacts. In this paper, we explore differences in gender, diurnal variation, and age in a human population. We use the example of gender differences to compare traditional spectral binning techniques (NMR spectral areas) to novel targeted profiling techniques (metabolites and their concentrations). We show that targeted profiling produces robust models, generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences in a healthy population. Metabolites relating to Mitochondrial energy metabolism were found to differentiate gender and age. Dietary components and some metabolites related to circadian rhythms were found to differentiate time of day urine collection. The mechanisms by which these differences arise will be key to the discovery of new diagnostic tests and new understandings of the mechanism of disease.