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Am J Clin Nutr. 2011 Oct;94(4):981-91. doi: 10.3945/ajcn.111.017921. Epub 2011 Aug 24.

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

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1
Institute of Biological Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom.

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.

PMID:
21865330
DOI:
10.3945/ajcn.111.017921
[Indexed for MEDLINE]
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