Identification of biomarkers for intake of protein from meat, dairy products and grains: a controlled dietary intervention study
Identification of biomarkers for intake of protein from meat, dairy products and grains: a controlled dietary intervention study
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DOI：
10.1017/s0007114512005788
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发表时间：
2013-09-14
影响因子：
3.6
通讯作者：
Geleijnse, Johanna M.
中科院分区：
文献类型：
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作者：
Altorf-van der Kuil, Wieke;Brink, Elizabeth J.;Geleijnse, Johanna M.
在目前的对照，随机，多交叉饮食干预研究中，我们的目的是确定乳制品，肉类和谷物中膳食蛋白质的潜在生物标志物，这可能有助于在流行病学研究中估计这些蛋白质类型的摄入量。经过9天的磨合，30名男性和17名女性（22（SD 4）岁）接受了三种高蛋白饮食（旨在约18%的能量（en%）），随机顺序为1周，约14 en%来自肉类，乳制品或谷物。我们使用两步法来鉴定尿液和血浆中的生物标志物。主成分判别分析，我们确定了氨基酸（AA）从血浆或尿液中的AA档案之间的饮食是独特的。随后，在汇总总研究数据后，我们应用混合模型来估计这些AA对蛋白质类型摄入量的预测值。通过包括尿肌肽、1-甲基组氨酸和3-甲基组氨酸的回归模型，可以很好地预测肉类蛋白质的摄入量（解释了98%的摄入量变化）。此外，对于膳食谷物蛋白质，包括7个AA（血浆赖氨酸、缬氨酸、苏氨酸、α-氨基丁酸、脯氨酸、鸟氨酸和精氨酸）的模型做出了良好的预测（解释了75%的变化）。我们无法确定乳制品蛋白质摄入量的生物标志物。总之，尿和血浆AA的特定组合可能分别是肉类和谷物蛋白质摄入的潜在有用的生物标志物。这些发现需要在其他饮食干预研究中进行交叉验证。
In the present controlled, randomised, multiple cross-over dietary intervention study, we aimed to identify potential biomarkers for dietary protein from dairy products, meat and grain, which could be useful to estimate intake of these protein types in epidemiological studies. After 9 d run-in, thirty men and seventeen women (22 (SD 4) years) received three high-protein diets (aimed at approximately 18% of energy (en%)) in random order for 1 week each, with approximately 14 en% originating from either meat, dairy products or grain. We used a two-step approach to identify biomarkers in urine and plasma. With principal component discriminant analysis, we identified amino acids (AA) from the plasma or urinary AA profile that were distinctive between diets. Subsequently, after pooling total study data, we applied mixed models to estimate the predictive value of those AA for intake of protein types. A very good prediction could be made for the intake of meat protein by a regression model that included urinary carnosine, 1-methylhistidine and 3-methylhistidine (98% of variation in intake explained). Furthermore, for dietary grain protein, a model that included seven AA (plasma lysine, valine, threonine, alpha-aminobutyric acid, proline, ornithine and arginine) made a good prediction (75% of variation explained). We could not identify biomarkers for dairy protein intake. In conclusion, specific combinations of urinary and plasma AA may be potentially useful biomarkers for meat and grain protein intake, respectively. These findings need to be cross-validated in other dietary intervention studies.