Coen Muireann, Holmes Elaine, Lindon John C, Nicholson Jeremy K
Department of Biomolecular Medicine, Surgery, Oncology, Reproductive Biology and Anesthetics Division, Faculty of Medicine, Imperial College London, London, UK.
Chem Res Toxicol. 2008 Jan;21(1):9-27. doi: 10.1021/tx700335d. Epub 2008 Jan 3.
We have reviewed the main contributions to the development of NMR-based metabonomic and metabolic profiling approaches for toxicological assessment, biomarker discovery, and studies on toxic mechanisms. The metabonomic approach, (defined as the quantitative measurement of the multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification) was originally developed to assist interpretation in NMR-based toxicological studies. However, in recent years there has been extensive fusion with metabolomic and other metabolic profiling approaches developed in plant biology, and there is much wider coverage of the biomedical and environmental fields. Specifically, metabonomics involves the use of spectroscopic techniques with statistical and mathematical tools to elucidate dominant patterns and trends directly correlated with time-related metabolic fluctuations within spectral data sets usually derived from biofluids or tissue samples. Temporal multivariate metabolic signatures can be used to discover biomarkers of toxic effect, as general toxicity screening aids, or to provide novel mechanistic information. This approach is complementary to proteomics and genomics and is applicable to a wide range of problems, including disease diagnosis, evaluation of xenobiotic toxicity, functional genomics, and nutritional studies. The use of biological fluids as a source of whole organism metabolic information enhances the use of this approach in minimally invasive longitudinal studies.
我们回顾了基于核磁共振的代谢组学和代谢谱分析方法在毒理学评估、生物标志物发现以及毒理机制研究方面的主要贡献。代谢组学方法（定义为对生物系统对病理生理刺激或基因修饰的多参数代谢反应进行定量测量）最初是为协助基于核磁共振的毒理学研究的解释而开发的。然而，近年来，它与植物生物学中开发的代谢组学和其他代谢谱分析方法进行了广泛融合，并且在生物医学和环境领域有了更广泛的覆盖。具体而言，代谢组学涉及使用光谱技术以及统计和数学工具，以阐明与通常来自生物流体或组织样本的光谱数据集中与时间相关的代谢波动直接相关的主要模式和趋势。时间多变量代谢特征可用于发现毒性效应的生物标志物，作为一般毒性筛选辅助手段，或提供新的机制信息。这种方法与蛋白质组学和基因组学互补，适用于广泛的问题，包括疾病诊断、异源生物毒性评估、功能基因组学和营养研究。使用生物流体作为全生物体代谢信息的来源，增强了这种方法在微创纵向研究中的应用。
