Comparing metabolite profiles of habitual diet in serum and urine

Abstract

Background: Diet plays an important role in chronic disease etiology, but some diet-disease associations remain inconclusive because of methodologic limitations in dietary assessment. Metabolomics is a novel method for identifying objective dietary biomarkers, although it is unclear what dietary information is captured from metabolites found in serum compared with urine.

Objective: We compared metabolite profiles of habitual diet measured from serum with those measured from urine.

Design: We first estimated correlations between consumption of 56 foods, beverages, and supplements assessed by a food-frequency questionnaire, with 676 serum and 848 urine metabolites identified by untargeted liquid chromatography mass spectrometry, ultra-high performance liquid chromatography tandem mass spectrometry, and gas chromatography mass spectrometry in a colon adenoma case-control study (n = 125 cases and 128 controls) while adjusting for age, sex, smoking, fasting, case-control status, body mass index, physical activity, education, and caloric intake. We controlled for multiple comparisons with the use of a false discovery rate of <0.1. Next, we created serum and urine multiple-metabolite models to predict food intake with the use of 10-fold crossvalidation least absolute shrinkage and selection operator regression for 80% of the data; predicted values were created in the remaining 20%. Finally, we compared predicted values with estimates obtained from self-reported intake for metabolites measured in serum and urine.

Results: We identified metabolites associated with 46 of 56 dietary items; 417 urine and 105 serum metabolites were correlated with ≥1 food, beverage, or supplement. More metabolites in urine (n = 154) than in serum (n = 39) were associated uniquely with one food. We found previously unreported metabolite associations with leafy green vegetables, sugar-sweetened beverages, citrus, added sugar, red meat, shellfish, desserts, and wine. Prediction of dietary intake from multiple-metabolite profiles was similar between biofluids.

Conclusions: Candidate metabolite biomarkers of habitual diet are identifiable in both serum and urine. Urine samples offer a valid alternative or complement to serum for metabolite biomarkers of diet in large-scale clinical or epidemiologic studies.

Keywords: biomarker; diet; food; metabolite; metabolomics; nutrition assessment; serum; urine.

FIGURE 1

Accuracy of multiple-metabolite profiles for predicting dietary intake amounts in serum compared with urine in the Navy Adenoma Study (n = 253). Data represent the correlation between observed dietary intake and predicted intake based on 10-fold crossvalidated LASSO regression of metabolites at the dietary intake level. Metabolites were adjusted residually for age, sex, smoking history, fasting status, case-control status, BMI, education, physical activity, and daily caloric intake. Residual-adjusted metabolite values were used for the LASSO analysis. Training and validation were conducted in a random 80% of the sample; testing was conducted in the remaining 20%. This process was repeated 10 times with the use of different random data splits. Final estimates averaged correlations between observed and predicted dietary intake levels. Correlations of urine and serum metabolites with food intake differed significantly for apples, butter, and tea (P < 0.05). LASSO, least absolute shrinkage and selection operator.