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基于代谢组学的早期疾病诊断方法。

Metabolomics-based methods for early disease diagnostics.

作者信息

Gowda G A Nagana, Zhang Shucha, Gu Haiwei, Asiago Vincent, Shanaiah Narasimhamurthy, Raftery Daniel

机构信息

Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN 47907, USA.

出版信息

Expert Rev Mol Diagn. 2008 Sep;8(5):617-33. doi: 10.1586/14737159.8.5.617.

Abstract

The emerging field of metabolomics, in which a large number of small-molecule metabolites from body fluids or tissues are detected quantitatively in a single step, promises immense potential for early diagnosis, therapy monitoring and for understanding the pathogenesis of many diseases. Metabolomics methods are mostly focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry (MS). Analysis of the data from these high-resolution methods using advanced chemometric approaches provides a powerful platform for translational and clinical research and diagnostic applications. In this review, the current trends and recent advances in NMR- and MS-based metabolomics are described with a focus on the development of advanced NMR and MS methods, improved multivariate statistical data analysis and recent applications in the area of cancer, diabetes, inborn errors of metabolism and cardiovascular diseases.

摘要

代谢组学这一新兴领域能够在一步操作中对来自体液或组织的大量小分子代谢物进行定量检测,在疾病的早期诊断、治疗监测以及理解多种疾病的发病机制方面具有巨大潜力。代谢组学方法主要集中于核磁共振波谱(NMR)和质谱(MS)等信息丰富的分析技术。使用先进的化学计量学方法对这些高分辨率方法得到的数据进行分析,为转化研究、临床研究及诊断应用提供了一个强大的平台。在这篇综述中,我们描述了基于NMR和MS的代谢组学的当前趋势和最新进展,重点介绍了先进的NMR和MS方法的发展、改进的多变量统计数据分析以及在癌症、糖尿病、先天性代谢缺陷和心血管疾病领域的最新应用。

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