遗传 ›› 2008, Vol. 30 ›› Issue (4): 389-399.doi: 10.3724/SP.J.1005.2008.00389

• 综述 • 上一篇    下一篇

代谢组学技术及其在临床研究中的应用

李灏; 姜颖; 贺福初   

  1. 北京放射医学研究所, 北京蛋白质组研究中心, 蛋白质组学国家重点实验室, 北京 102206

  • 收稿日期:2007-12-29 修回日期:2008-01-10 出版日期:2008-04-10 发布日期:2008-04-10
  • 通讯作者: 姜颖; 贺福初

Recent development of metabonomics and its applications in clinical research

LI Hao; JIANG Ying; HE Fu-Chu

  

  1. State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China
  • Received:2007-12-29 Revised:2008-01-10 Online:2008-04-10 Published:2008-04-10
  • Contact: JIANG Ying; HE Fu-Chu

摘要:

在后基因组时代, 系统生物学研究成为人们关注的焦点。转录组学、蛋白质组学等功能基因组学研究方法可同时检测药物或其他因素影响下大量基因或蛋白质的表达变化情况, 但这些变化不能与生物学功能的变化建立直接联系。代谢组学方法则可为代谢物含量变化与生物表型变化建立直接相关性。代谢组学研究的目的是定量分析一个生物系统内所有代谢物的含量, 进行全面代谢物分析需要分析化学技术的支撑, 核磁共振和基于质谱的分析技术是代谢组学研究的两种主要技术手段。代谢组学研究可产生大量数据信息, 对这些数据进行分析离不开化学统计学的应用, 比如主成分分析、多维缩放、各种聚类分析技术以及功能差异分析等。文章综述了近年来代谢组学分析技术及数据分析技术的研究进展, 在此基础上, 对代谢组学在临床研究及临床前研究中的应用研究进展进行了综述。对疾病代谢表型图谱的研究有助于人们了解疾病发生、发展以及致死的机制; 在临床条件下, 这些代谢图谱可以作为疾病诊断、预后以及治疗的评判标准。代谢物组成的变化是毒物胁迫对机体造成的最终影响, 利用代谢组技术可以直接反映毒物对机体的影响。质谱技术、核磁共振技术的应用使得药物筛选过程可以快速完成, 并有助于实现个性化用药。此外, 利用代谢组学技术还可以进行已知酶的新活性研究, 也可以研究未知酶。

关键词: 代谢组学, 核磁共振, 质谱, 化学统计学, 临床应用

Abstract:

In the post-genomic era, systems biology is central to the biological sciences. Functional genomics such as transcriptomics and proteomics can simultaneous determine massive gene or protein expression changes following drug treatment or other intervention. However, these changes can’t be coupled directly to changes in biological function. As a result, metabonomics and its many pseudonyms (metabolomics, metabolic profiling, etc.) have exploded onto the scientific scene in the past several years. Metabonomics is a rapidly growing research area and a system approach for comprehensive and quantitative analysis of the global metabolites in a biological matrix. Analytical chemistry approach is necessary for the development of comprehensive metabonomics investigations. Fundamentally, there are two types of metabonomics approaches: mass-spectrometry (MS) based and nuclear magnetic resonance (NMR) methodologies. Metabonomics measurements provide a wealth of data information and interpretation of these data relies mainly on chemometrics approaches to perform large-scale data analysis and data visualization, such as principal and independent component analysis, multidimensional scaling, a variety of clustering techniques, and discriminant function analysis, among many others. In this review, the recent development of analytical and statistical techniques used in metabonomics is summarized. Major applications of metabonomics relevant to clinical and preclinical study are then reviewed. The applications of metabonomics in study of liver diseases, cancers and other diseases have proved useful both as an experimental tool for pathogenesis mechanism re-search and ultimately a tool for diagnosis and monitoring treatment response of these diseases. Next, the applications of metabonomics in preclinical toxicology are discussed and the role that metabonomics might do in pharmaceutical research and development is explained with special reference to the aims and achievements of the Consortium for Metabonomic Toxicology (COMET), and the concept of pharmacometabonomics as a way of predicting an individual’s response to treatment is highlighted. Finally, the role of metabonomics in elucidating the function of the unknown or novel enzyme is mentioned.