Almanza-Aguilera Enrique, Urpi-Sarda Mireia, Llorach Rafael, Vázquez-Fresno Rosa, Garcia-Aloy Mar, Carmona Francesc, Sanchez Alex, Madrid-Gambin Francisco, Estruch Ramon, Corella Dolores, Andres-Lacueva Cristina
Biomarkers and Nutrimetabolomics Laboratory, Nutrition, Food Science and Gastronomy Department, XaRTA, INSA, Campus Torribera, Faculty of Pharmacy and Food Science, University of Barcelona, Barcelona 08028, Spain.
Biomarkers and Nutrimetabolomics Laboratory, Nutrition, Food Science and Gastronomy Department, XaRTA, INSA, Campus Torribera, Faculty of Pharmacy and Food Science, University of Barcelona, Barcelona 08028, Spain; CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid 28028, Spain.
J Nutr Biochem. 2017 Oct;48:36-43. doi: 10.1016/j.jnutbio.2017.06.001. Epub 2017 Jun 7.
The study of biomarkers of dietary patterns including the Mediterranean diet (MedDiet) is scarce and could improve the assessment of these patterns. Moreover, it could provide a better understanding of health benefits of dietary patterns in nutritional epidemiology. We aimed to determine a robust and accurate biomarker associated with a high adherence to a MedDiet pattern that included dietary assessment and its biological effect. In this cross-sectional study, we included 56 and 63 individuals with high (H-MDA) and low (L-MDA) MedDiet adherence categories, respectively, all from the Prevención con Dieta Mediterránea trial. A H-NMR-based untargeted metabolomics approach was applied to urine samples. Multivariate statistical analyses were conducted to determine the metabolite differences between groups. A stepwise logistic regression and receiver operating characteristic curves were used to build and evaluate the prediction model for H-MDA. Thirty-four metabolites were identified as discriminant between H-MDA and L-MDA. The fingerprint associated with H-MDA included higher excretion of proline betaine and phenylacetylglutamine, among others, and decreased amounts of metabolites related to glucose metabolism. Three microbial metabolites - phenylacetylglutamine, p-cresol and 4-hydroxyphenylacetate - were included in the prediction model of H-MDA (95% specificity, 95% sensitivity and 97% area under the curve). The model composed of microbial metabolites was the biomarker that defined high adherence to a Mediterranean dietary pattern. The overall metabolite profiling identified reflects the metabolic modulation produced by H-MDA. The proposed biomarker may be a better tool for assessing and aiding nutritional epidemiology in future associations between H-MDA and the prevention or amelioration of chronic diseases.
对包括地中海饮食(MedDiet)在内的饮食模式生物标志物的研究较为匮乏,而此类研究有助于改进对这些饮食模式的评估。此外,它还能让人更好地理解营养流行病学中饮食模式对健康的益处。我们旨在确定一种与高度遵循地中海饮食模式相关的可靠且准确的生物标志物,该研究涵盖饮食评估及其生物学效应。在这项横断面研究中,我们分别纳入了56名和63名高度(H-MDA)和低度(L-MDA)遵循地中海饮食模式的个体,他们均来自地中海饮食预防试验。对尿液样本采用了基于核磁共振氢谱(1H-NMR)的非靶向代谢组学方法。进行多变量统计分析以确定组间代谢物差异。采用逐步逻辑回归和受试者工作特征曲线来构建和评估H-MDA的预测模型。34种代谢物被确定为H-MDA和L-MDA之间的判别指标。与H-MDA相关的指纹图谱包括较高的脯氨酸甜菜碱和苯乙酰谷氨酰胺排泄量等,以及与葡萄糖代谢相关的代谢物含量降低。三种微生物代谢物——苯乙酰谷氨酰胺、对甲酚和4-羟基苯乙酸——被纳入H-MDA的预测模型(特异性95%、敏感性95%和曲线下面积97%)。由微生物代谢物组成的模型就是定义高度遵循地中海饮食模式的生物标志物。所确定的整体代谢物谱反映了H-MDA产生的代谢调节作用。所提出的生物标志物可能是未来评估H-MDA与慢性病预防或改善之间关联时,用于评估和辅助营养流行病学的更好工具。