The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods
Open accessAbstract
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.
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“Direct flow injection-MS has also been used (82,114), which offers the advantage of high-throughput analysis, as would be required for large-scale epidemiologic studies.”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [82]
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Cites
Fruit and vegetable intake and risk of major chronic disease
Hung, H.-C., Joshipura, K. J., Jiang, R., Hu, F. B., Hunter, D., Smith-Warner, S. A., Colditz, G. A., Rosner, B., Spiegelman, D., & Willett, W. C. (2004) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djh296 · Cited by 1,327
Hooper, L., Kroon, P. A., Rimm, E. B., Cohn, J. S., Harvey, I., Le Cornu, K. A., Ryder, J. J., Hall, W. L., & Cassidy, A. (2008) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/88.1.38 · Cited by 1,097
Human metabolic phenotype diversity and its association with diet and blood pressure
Holmes, E., Loo, R. L., Stamler, J., Bictash, M., Yap, I. K. S., Chan, Q., Ebbels, T., De Iorio, M., Brown, I. J., Veselkov, K. A., et al. (2008) · Nature · doi:10.1038/nature06882 · Cited by 1,054
Carr, A. C., & Frei, B. (1999) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/69.6.1086 · Cited by 940
Bingham, S. A., Gill, C., Welch, A., Day, K., Cassidy, A., Khaw, K. T., Sneyd, M. J., Key, T. J. A., Roe, L., & Day, N. E. (1994) · British Journal of Nutrition · doi:10.1079/bjn19940064 · Cited by 749
Bingham, S. (1997) · International Journal of Epidemiology · doi:10.1093/ije/26.suppl_1.s137 · Cited by 634
Scalbert, A., Brennan, L., Fiehn, O., Hankemeier, T., Kristal, B. S., van Ommen, B., Pujos-Guillot, E., Verheij, E., Wishart, D., & Wopereis, S. (2009) · Metabolomics · doi:10.1007/s11306-009-0168-0 · Cited by 565
Heidemann, C., Schulze, M. B., Franco, O. H., van Dam, R. M., Mantzoros, C. S., & Hu, F. B. (2008) · Circulation · doi:10.1161/circulationaha.108.771881 · Cited by 509
Spencer, J., Mohsen, M. M. A. E., Minihane, A., & Mathers, J. (2007) · British Journal of Nutrition · doi:10.1017/s0007114507798938 · Cited by 481
Self-citationRiihinen, K., Kamal‐Eldin, A., & Törrönen, A. (2004) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf049450r · Cited by 466
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The food metabolome: a window over dietary exposure
Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S. (2014) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.076133 · Cited by 519
Self-citationUse of Metabolomics in Improving Assessment of Dietary Intake
Guasch‐Ferré, M., Bhupathiraju, S. N., & Hu, F. B. (2017) · Clinical Chemistry · doi:10.1373/clinchem.2017.272344 · Cited by 327
Biomarkers of Nutrition and Health: New Tools for New Approaches
Picó, C., Serra, F., Rodríguez, A. M., Keijer, J., & Palou, A. (2019) · Nutrients · doi:10.3390/nu11051092 · Cited by 287
García‐Pérez, I., Posma, J. M., Gibson, R., Chambers, E. S., Hansen, T. H., Vestergaard, H., Hansen, T. F., Beckmann, M., Pedersen, O. B., Elliott, P., et al. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(16)30419-3 · Cited by 251
Self-citationBenefits of the Mediterranean diet: Epidemiological and molecular aspects
Serra‐Majem, L., Román‐Viñas, B., Sánchez‐Villegas, A., Guasch‐Ferré, M., Corella, D., & Vecchia, C. L. (2019) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2019.06.001 · Cited by 259
Metadata
- Authors
- Lloyd, A. J., Favé, G., Beckmann, M., Lin, W., Tailliart, K., Xie, L., Mathers, J. C., & Draper, J.
- Affiliations
- Aberystwyth University (GB)
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2011-10
- Volume
- 94
- Issue
- 4
- Pages
- 981-991
- ISSN
- 0002-9165 (ISSN-L)
- OpenAlex
- W2096891019
- Cited by
- 130
- References
- 48
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 3 · 2022: 2 · 2021: 4 · 2020: 16 · 2019: 13 · 2018: 12 · 2017: 15 · 2016: 13 · 2015: 7 · 2014: 13 · 2013: 19 · 2012: 9
- FWCI
- 5.33
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion)
- PubMed (publishedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Keywords
- urinary metabolites, salmon consumption, trimethylamine N-oxide, 1-methylhistidine, broccoli, raspberry, biomarker discovery
- MeSH terms
- Animals, Diet, Food, Humans, Kinetics, Gas Chromatography-Mass Spectrometry, ROC Curve, Biomarkers, Multivariate Analysis, Urinalysis, Postprandial Period, Spectrometry, Mass, Electrospray Ionization, Metabolomics, Metabolome, Data Mining
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