Department of Nutritional Sciences, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, London SE1 9NH, U.K.
Department of Twin Research & Genetic Epidemiology, School of Life Course and Population Sciences, Faculty of Life Sciences and Medicine, King's College London, London SE1 7EH, U.K.
J Agric Food Chem. 2024 Jun 12;72(23):13439-13450. doi: 10.1021/acs.jafc.4c00959. Epub 2024 Jun 3.
The objective assessment of habitual (poly)phenol-rich diets in nutritional epidemiology studies remains challenging. This study developed and evaluated the metabolic signature of a (poly)phenol-rich dietary score (PPS) using a targeted metabolomics method comprising 105 representative (poly)phenol metabolites, analyzed in 24 h of urine samples collected from healthy volunteers. The metabolites that were significantly associated with PPS after adjusting for energy intake were selected to establish a metabolic signature using a combination of linear regression followed by ridge regression to estimate penalized weights for each metabolite. A metabolic signature comprising 51 metabolites was significantly associated with adherence to PPS in 24 h urine samples, as well as with (poly)phenol intake estimated from food frequency questionnaires and diaries. Internal and external data sets were used for validation, and plasma, spot urine, and 24 h urine samples were compared. The metabolic signature proposed here has the potential to accurately reflect adherence to (poly)phenol-rich diets, and may be used as an objective tool for the assessment of (poly)phenol intake.
在营养流行病学研究中,对习惯性(多)酚类化合物丰富的饮食进行客观评估仍然具有挑战性。本研究采用靶向代谢组学方法开发和评估了(多)酚类化合物丰富的饮食评分(PPS)的代谢特征,该方法包括分析健康志愿者 24 小时尿液样本中的 105 种代表性(多)酚类代谢物。在调整能量摄入后,选择与 PPS 显著相关的代谢物,使用线性回归和岭回归相结合的方法,为每个代谢物估计惩罚权重,从而建立代谢特征。由 51 种代谢物组成的代谢特征与 24 小时尿液样本中 PPS 的依从性以及通过食物频率问卷和日记估计的(多)酚类化合物摄入量显著相关。该代谢特征还使用内部和外部数据集进行了验证,并比较了血浆、随机尿和 24 小时尿样。本研究提出的代谢特征具有准确反映(多)酚类化合物丰富饮食依从性的潜力,可作为评估(多)酚类化合物摄入量的客观工具。