Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Nestlé Institute of Health Sciences, Lausanne, Switzerland.
Mech Ageing Dev. 2017 Jul;165(Pt B):171-179. doi: 10.1016/j.mad.2016.12.009. Epub 2016 Dec 23.
Systems biology approaches have been increasingly employed in clinical studies to enhance our understanding of the role of genetics, environmental factors and their interactions on nutritional, health and disease status. Amongst the new omics technologies, metabonomics has emerged as a robust platform to capture metabolic and nutritional requirements by enabling, in a minimally invasive fashion, the monitoring of a wide range of biochemical compounds. Their variations reflect comprehensively the various molecular regulatory processes, which are tightly controlled and under the influence of genetics, diet, gut microbiota and other environmental factors. They are providing key insights into complex metabolic phenomena as well as into differences and specificities at individual and population level. The aim of this review is to evaluate promising metabolic insights towards understanding metabolism of a long and healthy life from pre-clinical and clinical metabonomics studies. We will also discuss analytical approaches to enable data integration, with an emphasis on the longitudinal component. Herein, we will illustrate current examples, challenges and perspectives in the applications of metabonomics monitoring and modelling approaches in the context of healthy ageing research.
系统生物学方法已越来越多地应用于临床研究，以增强我们对遗传、环境因素及其相互作用对营养、健康和疾病状况的影响的理解。在新的组学技术中，代谢组学已成为一种强大的平台，可以通过以微创的方式监测广泛的生化化合物，来捕捉代谢和营养需求。它们的变化全面反映了各种分子调控过程，这些过程受到遗传、饮食、肠道微生物群和其他环境因素的严格控制和影响。它们为复杂的代谢现象以及个体和群体水平的差异和特异性提供了关键的见解。本综述的目的是评估有前途的代谢见解，以从临床前和临床代谢组学研究中了解长寿和健康的代谢。我们还将讨论分析方法，以实现数据集成，重点是纵向部分。本文将举例说明代谢组学监测和建模方法在健康老龄化研究中的应用的当前实例、挑战和观点。
