Kim Oh Yoen, Lee Jong Ho, Sweeney Gary
Department of Food Science & Nutrition, College of Human Ecology, Dong-A University, Busan, Korea.
Expert Rev Cardiovasc Ther. 2013 Jan;11(1):61-8. doi: 10.1586/erc.12.121.
There have been considerable improvements in therapeutics for chronic diseases. However, the maximum benefit of these or other options are hard to achieve in practice, due in part to the difficulties associated with determining optimal targets for such interventions. Recent developments have suggested that understanding changes in metabolite profiles will confer a high degree of predictive accuracy in terms of understanding the fundamental mechanisms resulting in perturbations of the metabolic state. Metabolomics involves the establishment of relationships between phenotype and a metabolic signature, which are key aspects of biological function. These approaches have been applied to the identification of serum/plasma metabolic markers involved in obesity, diabetes and vascular disease using animal models or in humans. Different kinds of metabolite profiling techniques using nuclear magnetic resonance spectroscopy, mass spectrometry, ultraperformance liquid chromatography and so on are currently employed to generate global metabolic profiles. Scientific information derived from these techniques can be applied to provide accurate and clinically useful prognostic/diagnostic capability for the management of major chronic diseases. One current consideration limiting the widespread use of metabolomic profiling is the analysis of its cost-effectiveness. In summary, it is hoped that the information derived from metabolite profiling will make it possible to suggest individualized therapies that more effectively treat disease.
慢性病的治疗方法已有了显著改进。然而,这些疗法或其他选择的最大益处很难在实践中实现,部分原因在于确定此类干预的最佳靶点存在困难。最近的进展表明,了解代谢物谱的变化将在理解导致代谢状态紊乱的基本机制方面具有高度的预测准确性。代谢组学涉及建立表型与代谢特征之间的关系,而这是生物学功能的关键方面。这些方法已被应用于使用动物模型或在人体中鉴定与肥胖、糖尿病和血管疾病相关的血清/血浆代谢标志物。目前采用了不同种类的代谢物谱分析技术,如核磁共振光谱法、质谱分析法、超高效液相色谱法等,以生成整体代谢谱。从这些技术中获得的科学信息可用于为主要慢性病的管理提供准确且临床有用的预后/诊断能力。目前限制代谢组学分析广泛应用的一个考虑因素是对其成本效益的分析。总之,希望从代谢物谱分析中获得的信息能够提出更有效治疗疾病的个体化疗法。