Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods

Abstract

Background: The lack of robust biological markers of dietary exposure hinders the quantitative understanding of causal relations between diet and health. Objective: We aimed to develop an efficient procedure to discover metabolites in urine that may have future potential as biomarkers of acute exposure to foods of high public health importance. Design: Twenty-four participants were provided with a test breakfast in which the cereal component of a standardized breakfast was replaced by 1 of 4 foods of high public health importance; 1.5-, 3-, and 4.5-h postprandial urine samples were collected. Flow infusion electrospray-ionization mass spectrometry followed by supervised multivariate data analysis was used to discover signals resulting from consumption of each test food. Results: Fasted-state urine samples provided a universal comparator for food biomarker lead discovery in postprandial urine. The filtering of data features associated with consumption of the common components of the standardized breakfast improved discrimination models and readily identified metabolites that showed consumption of specific test foods. A combination of trimethylamine-N-oxide and 1-methylhistidine was associated with salmon consumption. Novel ascorbate derivatives were discovered in urine after consumption of either broccoli or raspberries. Sulphonated caffeic acid and sulphonated methyl-epicatechin concentrations increased dramatically after consumption of raspberries. Conclusions: This biomarker lead discovery strategy can identify urinary metabolites associated with acute exposure to individual foods. Future studies are required to validate the specificity and utility of potential biomarkers in an epidemiologic context. Am J Clin Nutr 2011;94:981-91.

Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples

“…Non-targeted metabolite fingerprinting, using either NMR (17,19,21,28,29,31,33,35) or MS (20,(25)(26)(27) , and metabolite profiling using liquid chromatography MS (18,(22)(23)(24)28,30,32,34) have been used successfully for biomarker-lead discovery using urine samples from various study designs (Table 1). In acute food intervention studies (20,(22)(23)(24)(25)32) , participants were exposed to specific foods in known amounts and either postprandial urines sampled before the next meal or overnight or 24 h urines were collected. In other studies, participants were established on a specific diet for several days/weeks (17,19,21,28,33,35) or longer term (> 1 month) (18,31,34) before urine sampling.…”

“…In these studies, the analysis of diet diary or FFQ information allowed classification of individuals in terms of their frequency of consumption of specific diet constituents. In the present paper, we illustrate these approaches for biomarker discovery with particular reference to two studies carried out by the authors (20,(25)(26)(27) . The presence of substantial inter-and intra-individual variability in human metabolite profiles (36) provides a challenge for both biofluid sampling and subsequent data normalisation in metabolomics studies seeking information on habitual diet.…”

“…no alcohol and the consumption of a standardised evening meal in the evening before a clinic visit to provide a fasting urine sample. It was anticipated that the latter would provide a 'normalised' background against which differences in urine chemistry resulting from either previous habitual dietary intake prior to clinic visit or acute food intake during the test day would be detectable (12,14,20,25) . With effective protocols in place for volunteer management and urine sampling there was now an opportunity to determine whether changes in urine chemistry could reflect dietary exposure (11) .…”

“…In an acute feeding 'proof of principle' study, urine samples were analysed from individuals participating in the MEtabolomics to characterise Dietary Exposure (MEDE) research programme (20) . As part of the MEDE project (11) , twenty-four healthy participants consumed a 'test' breakfast, in which the cereal component of a standardised breakfast was replaced by one of four foods of high public health importance, followed by the collection of postprandial urine samples for metabolome analysis (20,25) . Once candidate food biomarkers had been identified (25,26) there was then the opportunity to validate their potential usefulness to monitor habitual diet in the independent GrainMark study (http://www.ncl.ac.uk/afrd/ research/project/2287) (27) .…”

Metabolomics as a tool in the identification of dietary biomarkers

“…As this was a less controlled intervention that included a wider selection of foods with varied amounts of intake and different preparation methods, it highlights the need for the validation of biomarkers in different subjects and study settings (27) . A number of red meat and fish biomarkers have been identified using this intervention approach (7,28,29) . Most recently, metabolomics has been applied to compare the different effects of meat and fish on the plasma metabolome (30) .…”