Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.
J Nutr. 2021 Jan 4;151(1):40-49. doi: 10.1093/jn/nxaa338.
High diet quality is associated with a lower risk of chronic diseases. Metabolomics can be used to identify objective biomarkers of diet quality.
We used metabolomics to identify serum metabolites associated with 4 diet indices and the components within these indices in 2 samples from African Americans and European Americans.
We studied cross-sectional associations between known metabolites and Healthy Eating Index (HEI)-2015, Alternative Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension Trial (DASH) diet, alternate Mediterranean diet (aMED), and their components using untargeted metabolomics in 2 samples (n1 = 1,806, n2 = 2,056) of the Atherosclerosis Risk in Communities study (aged 45-64 y at baseline). Dietary intakes were assessed using an FFQ. We used multivariable linear regression models to examine associations between diet indices and serum metabolites in each sample, adjusting for participant characteristics. Metabolites significantly associated with diet indices were meta-analyzed across 2 samples. C-statistics were calculated to examine if these candidate biomarkers improved prediction of individuals in the highest compared with lowest quintile of diet scores beyond participant characteristics.
Seventeen unique metabolites (HEI: n = 6; AHEI: n = 5; DASH: n = 14; aMED: n = 2) were significantly associated with higher diet scores after Bonferroni correction in sample 1 and sample 2. Six of 17 significant metabolites [glycerate, N-methylproline, stachydrine, threonate, pyridoxate, 3-(4-hydroxyphenyl)lactate)] were associated with ≥1 dietary pattern. Candidate biomarkers of HEI, AHEI, and DASH distinguished individuals with highest compared with lowest quintile of diet scores beyond participant characteristics in samples 1 and 2 (P value for difference in C-statistics <0.02 for all 3 diet indices). Candidate biomarkers of aMED did not improve C-statistics beyond participant characteristics (P value = 0.930).
A considerable overlap of metabolites associated with HEI, AHEI, DASH, and aMED reflects the similar food components and similar metabolic pathways involved in the metabolism of healthy diets in African Americans and European Americans.
高饮食质量与慢性病风险降低有关。代谢组学可用于识别饮食质量的客观生物标志物。
我们使用代谢组学方法在来自非裔美国人和欧洲裔美国人的两个样本中,确定与 4 种饮食指数以及这些指数内成分相关的血清代谢物。
我们在社区动脉粥样硬化风险研究(基线时年龄为 45-64 岁)的两个样本(n1=1806,n2=2056)中,使用非靶向代谢组学研究了已知代谢物与健康饮食指数(HEI-2015)、替代健康饮食指数(AHEI-2010)、停止高血压的饮食方法(DASH)饮食、替代地中海饮食(aMED)及其成分之间的横断面关联。使用 FFQ 评估饮食摄入量。我们使用多变量线性回归模型,在每个样本中调整参与者特征后,检查饮食指数与血清代谢物之间的关联。对与饮食指数显著相关的代谢物进行荟萃分析,以检验这些候选生物标志物是否可以改善个体在饮食评分最高与最低五分位数之间的预测。
在样本 1 和样本 2 中,经过 Bonferroni 校正后,有 17 种独特的代谢物(HEI:n=6;AHEI:n=5;DASH:n=14;aMED:n=2)与较高的饮食评分显著相关。17 种显著代谢物中有 6 种[甘油酸、N-甲基脯氨酸、莨菪亭、苏氨酸、吡哆醇、3-(4-羟苯基)-乳酸]与≥1 种饮食模式相关。在样本 1 和样本 2 中,HEI、AHEI 和 DASH 的候选生物标志物可以区分饮食评分最高五分位数与最低五分位数的个体,且这些差异在所有 3 种饮食指数中均有统计学意义(所有 3 种饮食指数 P 值均<0.02)。候选生物标志物 aMED 并不能改善参与者特征以外的 C 统计量(P 值=0.930)。
与 HEI、AHEI、DASH 和 aMED 相关的代谢物存在相当大的重叠,这反映了非裔美国人和欧洲裔美国人健康饮食中涉及的类似食物成分和类似代谢途径。