Discovery and validation of urinary exposure markers for different plant foods by untargeted metabolomics

• Published in: Analytical and bioanalytical chemistry Vol. 406; no. 7; pp. 1829 - 1844
• Main Authors: Andersen, Maj-Britt Schmidt, Kristensen, Mette, Manach, Claudine, Pujos-Guillot, Estelle, Poulsen, Sanne Kellebjerg, Larsen, Thomas Meinert, Astrup, Arne, Dragsted, Lars
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2014; Springer; Springer Nature B.V; Springer Verlag
• Subjects: Adolescent; Adult; Aged; Analysis; Analytical Chemistry; beets; Biochemistry; Biomarkers - urine; Brassica; cabbage; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; chocolate; Chromatography, Liquid; Citrus; data collection; Diet - classification; Diet Records; eating habits; Exposure; Feeding Behavior; Female; Food; Food groups; Food habits; Food Science; Foods; Fragaria; green beans; Health aspects; Humans; Intakes; Intervention; Investigations; Juglans; Laboratory Medicine; Life Sciences; Male; Markers; Mass Spectrometry; Meals; Metabolism; Metabolites; metabolome; metabolomics; Metabolomics - methods; Middle Aged; Monitoring/Environmental Analysis; Nutrition research; Paper in Forefront; Phaseolus vulgaris; Plants (organisms); Plants, Edible - classification; Plants, Edible - metabolism; quantitative analysis; Reproducibility of Results; Sensitivity analysis; Sensitivity and Specificity; strawberries; t-test; Urine; walnuts; Young Adult; Belgium; Germany; Urine; UPLC-MS; Food exposure markers; Humans; Untargeted metabolomics; Dietary intervention study
• ISSN: 1618-2642; 1618-2650; 1618-2650
• DOI: 10.1007/s00216-013-7498-5

While metabolomics is increasingly used to investigate the food metabolome and identify new markers of food exposure, limited attention has been given to the validation of such markers. The main objectives of the present study were to (1) discover potential food exposure markers (PEMs) for a range of plant foods in a study setting with a mixed dietary background and (2) validate PEMs found in a previous meal study. Three-day weighed dietary records and 24-h urine samples were collected three times during a 6-month parallel intervention study from 107 subjects randomized to two distinct dietary patterns. An untargeted UPLC-qTOF-MS metabolomics analysis was performed on the urine samples, and all features detected underwent strict data analyses, including an iterative paired t test and sensitivity and specificity analyses for foods. A total of 22 unique PEMs were identified that covered 7 out of 40 investigated food groups (strawberry, cabbages, beetroot, walnut, citrus, green beans and chocolate). The PEMs reflected foods with a distinct composition rather than foods eaten more frequently or in larger amounts. We found that 23 % of the PEMs found in a previous meal study were also valid in the present intervention study. The study demonstrates that it is possible to discover and validate PEMs for several foods and food classes in an intervention study with a mixed dietary background, despite the large variability in such a dataset. Final validation of PEMs for intake of foods should be performed by quantitative analysis. Figure Examples of two urinary exposure markers for cabbage (left) and beetroot (right) found in the study from an untargeted LC‐MS metabolomics analysis of urine samples and self‐reported food intake data