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代谢组学:理解药物和疾病分子机制的前沿工具。

Metabolomics: A Tool Ahead for Understanding Molecular Mechanisms of Drugs and Diseases.

作者信息

Shah Neel Jayesh, Sureshkumar Srinivasamurthy, Shewade Deepak Gopal

机构信息

Department of Pharmacology, JIPMER, Pondicherry-6, India.

Department of Clinical Pharmacology, JIPMER, Pondicherry-6, India.

出版信息

Indian J Clin Biochem. 2015 Jul;30(3):247-54. doi: 10.1007/s12291-014-0455-z. Epub 2014 Jul 15.

Abstract

To refer to metabolomics as a new field is injustice to ancient doctors who used ants to diagnose the patients of diabetes having glycosuria. Measuring the levels of molecules in biological fluids believing them to be the representatives of biochemical pathways of carbohydrates, fats, proteins, nucleic acids or xenobiotic metabolism and deciphering meaningful data from it is what can be called as metabolomics, just as high glucose in urine suggests diabetes mellitus. Genomics, epigenetics, proteomics, transcriptomics finally converge to metabolomics, which are the signatures of mechanisms of bodily processes which is why understanding this science can have many applications. Just as a heap of stones does not make a house, having data of metabolite levels does not make it a science. Analyzing this data would help us in constructing biochemical pathways and their interactions. Analyzing the changes caused by a drug in the metabolite levels would help us in deriving the mechanisms by which the drug acts. Comparing metabolite levels in diseased with non-diseased, good-responders with poor-responders to a particular drug can help in identifying new markers of a disease or response to a drug respectively. Also, metabolite levels of an endogenous substrate can tell us the status of a person's metabolizing enzymes and help in drug dose titration. Generating hypothesis by identifying the new molecular markers and testing their utility in clinics seems to be the most promising approach in future. This review narrates the modes of quantifying and identifying metabolome, its proposed applications in diagnosis, monitoring and understanding the diseases and drug responses. We also intend to identify hindrances in using metabolomics in clinical studies or experiments.

摘要

将代谢组学称为一个新领域,这对古代医生是不公平的,他们曾用蚂蚁来诊断患有糖尿的糖尿病患者。测量生物体液中的分子水平,并认为这些分子是碳水化合物、脂肪、蛋白质、核酸或外源性物质代谢生化途径的代表,然后从中解读出有意义的数据,这才是所谓的代谢组学,就像尿中高血糖提示糖尿病一样。基因组学、表观遗传学、蛋白质组学、转录组学最终都汇聚到代谢组学,而代谢组学是身体过程机制的特征,这就是为什么理解这门科学会有许多应用。正如一堆石头建不成一座房子一样,仅有代谢物水平的数据并不意味着它就是一门科学。分析这些数据将有助于我们构建生化途径及其相互作用。分析药物引起的代谢物水平变化将有助于我们推导药物作用的机制。比较患病者与非患病者、对特定药物反应良好者与反应不佳者的代谢物水平,分别有助于识别疾病的新标志物或对药物的反应。此外,内源性底物的代谢物水平可以告诉我们一个人的代谢酶状态,并有助于药物剂量滴定。通过识别新的分子标志物并在临床中测试其效用从而生成假设,这似乎是未来最有前景的方法。这篇综述叙述了代谢组定量和识别的模式、其在疾病诊断、监测以及理解疾病和药物反应方面的应用。我们还打算找出在临床研究或实验中使用代谢组学的障碍。

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