Federal Department of Economic Affairs, Education, and Research, Agroscope, Bern, Switzerland.
Service of Endocrinology, Diabetes, and Metabolism, Lausanne University Hospital, Lausanne, Switzerland.
J Nutr. 2020 May 1;150(5):1058-1067. doi: 10.1093/jn/nxaa029.
The use of biomarkers of food intake (BFIs) in blood and urine has shown great promise for assessing dietary intake and complementing traditional dietary assessment tools whose use is prone to misreporting.
Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake of milk and cheese and to explore the metabolic response to the ingestion of these foods.
A randomized controlled crossover study was conducted in healthy adults [5 women, 6 men; age: 23.6 ± 5.0 y; BMI (kg/m2): 22.1 ± 1.7]. After a single isocaloric intake of milk (600 mL), cheese (100 g), or soy-based drink (600 mL), serum and urine samples were collected postprandially up to 6 h and after fasting after 24 h. Untargeted metabolomics was conducted using LC-MS. Discriminant metabolites were selected in serum by multivariate statistical analysis, and their mass distribution and postprandial kinetics were compared.
Serum metabolites discriminant for cheese intake had a significantly lower mass distribution than metabolites characterizing milk intake (P = 4.1 × 10-4). Candidate BFIs for milk or cheese included saccharides, a hydroxy acid, amino acids, amino acid derivatives, and dipeptides. Two serum oligosaccharides, blood group H disaccharide (BGH) and Lewis A trisaccharide (LeA), specifically reflected milk intake but with high interindividual variability. The 2 oligosaccharides showed related but opposing trends: subjects showing an increase in either oligosaccharide did not show any increase in the other oligosaccharide. This result was confirmed in urine.
New candidate BFIs for milk or cheese could be identified in healthy adults, most of which were related to protein metabolism. The increase in serum of LeA and BGH after cow-milk intake in adults calls for further investigations considering the beneficial health effects on newborns of such oligosaccharides in maternal milk. The trial is registered at clinicaltrials.gov as NCT02705560.
血液和尿液中的食物摄入生物标志物(BFIs)在评估饮食摄入方面显示出巨大的潜力,并补充了传统的饮食评估工具,这些工具容易出现错误报告。
应用非靶向 LC-MS 代谢组学来鉴定用于评估牛奶和奶酪摄入量的候选 BFIs,并探索摄入这些食物后的代谢反应。
在健康成年人中进行了一项随机对照交叉研究[5 名女性,6 名男性;年龄:23.6±5.0 岁;BMI(kg/m2):22.1±1.7]。在单次摄入等热量的牛奶(600 mL)、奶酪(100 g)或基于大豆的饮料(600 mL)后,在 6 小时内采集餐后和 24 小时后空腹的血清和尿液样本。使用 LC-MS 进行非靶向代谢组学分析。通过多变量统计分析在血清中选择具有判别力的代谢物,并比较其质量分布和餐后动力学。
用于鉴定奶酪摄入量的血清代谢物的质量分布明显低于用于鉴定牛奶摄入量的代谢物(P=4.1×10-4)。牛奶或奶酪的候选 BFIs 包括糖、羟基酸、氨基酸、氨基酸衍生物和二肽。两种血清低聚糖,即血型 H 二糖(BGH)和 Lewis A 三糖(LeA),特异性地反映了牛奶的摄入,但个体间的变异性很高。这两种低聚糖表现出相关但相反的趋势:在任一低聚糖增加的受试者中,另一种低聚糖没有增加。这一结果在尿液中得到了证实。
在健康成年人中可以鉴定出用于牛奶或奶酪的新候选 BFIs,其中大多数与蛋白质代谢有关。成年人摄入牛奶后血清中 LeA 和 BGH 的增加,呼吁进一步研究母乳中这些低聚糖对新生儿的有益健康影响。该试验在 clinicaltrials.gov 上注册为 NCT02705560。