Brennan Lorraine, Hu Frank B, Sun Qi
Conway Institute, Institute of Food and Health, School of Agriculture and Food Science, UCD, Belfield, Dublin 4, Ireland.
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Metabolites. 2021 Oct 19;11(10):709. doi: 10.3390/metabo11100709.
Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a "black box" approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.
传统上,营养流行病学是在人群层面研究饮食与人类健康和疾病之间的关系。通常,所关注的暴露因素是食物摄入量。近年来,营养流行病学已从“黑箱”方法转向系统方法,基因组学、代谢组学和蛋白质组学为饮食与健康之间的相互作用提供了新的见解。在此背景下,代谢组学正在成为营养流行病学中的关键工具。本综述探讨了代谢组学在营养流行病学中的应用。特别是,它研究了食物摄入生物标志物在解决自我报告饮食摄入数据局限性方面所起的作用,以及利用代谢物测量评估饮食对代谢途径和生理过程影响的潜力。然而,为了充分实现代谢组学在营养流行病学中的潜力,需要应对诸如强大的生物标志物验证以及新代谢物鉴定的新方法等关键挑战。传统流行病学方法与代谢组学之间的协同作用将有助于将营养流行病学证据转化为有效的精准营养。