McNamara Aoife E, Walton Janette, Flynn Albert, Nugent Anne P, McNulty Breige A, Brennan Lorraine
School of Agriculture and Food Science, UCD Institute of Food and Health, University College Dublin, Dublin, Ireland.
UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
Front Nutr. 2021 Jan 14;7:577720. doi: 10.3389/fnut.2020.577720. eCollection 2020.
Dietary and food intake biomarkers offer the potential of improving the accuracy of dietary assessment. An extensive range of putative intake biomarkers of commonly consumed foods have been identified to date. As the field of food intake biomarkers progresses toward solving the complexities of dietary habits, combining biomarkers associated with single foods or food groups may be required. The objective of this work was to examine the ability of a multi-biomarker panel to classify individuals into categories of fruit intake. Biomarker data was measured using H NMR spectroscopy in two studies: (1) An intervention study where varying amounts of fruit was consumed and (2) the National Adult Nutrition Survey (NANS). Using data from an intervention study a biomarker panel (Proline betaine, Hippurate, and Xylose) was constructed from three urinary biomarker concentrations. Biomarker cut-off values for three categories of fruit intake were developed. The biomarker sum cut-offs were ≤ 4.766, 4.766-5.976, >5.976 μM/mOsm/kg for <100, 101-160, and >160 g fruit intake. The ability of the biomarker sum to classify individuals into categories of fruit intake was examined in the cross-sectional study (NANS) ( = 565). Examination of results in the cross-sectional study revealed excellent agreement with self-reported intake: a similar number of participants were ranked into each category of fruit intake. The work illustrates the potential of multi-biomarker panels and paves the way forward for further development in the field. The use of such panels may be key to distinguishing foods and adding specificity to the predictions of food intake.
膳食和食物摄入生物标志物具有提高膳食评估准确性的潜力。迄今为止,已确定了广泛的常见食用食物的假定摄入生物标志物。随着食物摄入生物标志物领域朝着解决饮食习惯复杂性的方向发展,可能需要将与单一食物或食物组相关的生物标志物结合起来。这项工作的目的是检验多生物标志物组合将个体分类为水果摄入量类别的能力。在两项研究中使用核磁共振波谱法测量生物标志物数据:(1)一项干预研究,其中食用了不同量的水果;(2)全国成人营养调查(NANS)。利用干预研究的数据,根据三种尿液生物标志物浓度构建了一个生物标志物组合(脯氨酸甜菜碱、马尿酸盐和木糖)。确定了水果摄入量三类别的生物标志物临界值。水果摄入量<100、101 - 160和>160克时,生物标志物总和临界值分别为≤4.766、4.766 - 5.976、>5.976 μM/mOsm/kg。在横断面研究(NANS)(n = 565)中检验了生物标志物总和将个体分类为水果摄入量类别的能力。横断面研究结果显示与自我报告的摄入量高度一致:每个水果摄入量类别中的参与者数量相似。这项工作说明了多生物标志物组合的潜力,并为该领域的进一步发展铺平了道路。使用这样的组合可能是区分食物并提高食物摄入量预测特异性的关键。