Metabolomic profiling of urine: response to a randomised, controlled feeding study of select fruits and vegetables, and application to an observational study
Open accessAbstract
Metabolomic profiles were used to characterise the effects of consuming a high-phytochemical diet compared with a diet devoid of fruits and vegetables (F&V) in a randomised trial and cross-sectional study. In the trial, 8 h fasting urine from healthy men (n 5) and women (n 5) was collected after a 2-week randomised, controlled trial of two diet periods: a diet rich in cruciferous vegetables, citrus and soya (F&V), and a fruit- and vegetable-free (basal) diet. Among the ions found to differentiate the diets, 176 were putatively annotated with compound identifications, with forty-six supported by MS/MS fragment evidence. Metabolites more abundant in the F&V diet included markers of the dietary intervention (e.g. crucifers, citrus and soya), fatty acids and niacin metabolites. Ions more abundant in the basal diet included riboflavin, several acylcarnitines and amino acid metabolites. In the cross-sectional study, we compared the participants based on the tertiles of crucifers, citrus and soya from 3 d food records (n 36) and FFQ (n 57); intake was separately divided into the tertiles of total fruit and vegetable intake for FFQ. As a group, ions individually differential between the experimental diets differentiated the observational study participants. However, only four ions were significant individually, differentiating the third v. first tertile of crucifer, citrus and soya intake based on 3 d food records. One of these ions was putatively annotated: proline betaine, a marker of citrus consumption. There were no ions significantly distinguishing tertiles by FFQ. The metabolomic assessment of controlled dietary interventions provides a more accurate and stronger characterisation of the diet than observational data.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Using food-frequency questionnaires may directly identify biomarkers of habitual dietary exposure, but their lower accuracy and smaller number of documented foods may limit their usefulness for discovery studies.
“The use of food-frequency questionnaires may directly lead to the identification of biomarkers of habitual dietary exposure, but the lower accuracy and lower number of foods documented may limit their value for such discovery studies (105).”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [105]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692 · see citing works
Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., Fan, T. W.-M., Fiehn, O., Goodacre, R., Griffin, J. L., et al. (2007) · Metabolomics · doi:10.1007/s11306-007-0082-2 · Cited by 5,368 · see citing works
Willett, W. C. (1998) · doi:10.1093/acprof:oso/9780195122978.001.0001 · Cited by 4,541 · see citing works
Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Gentleman, R. C., Carey, V. J., Huber, W. K., Irizarry, R. A., & Dudoit, S. (2005) · Statistics in the health sciences · doi:10.1007/0-387-29362-0 · Cited by 3,470 · see citing works
Mass spectrometry‐based metabolomics
Dettmer, K., Aronov, P. A., & Hammock, B. D. (2006) · Mass Spectrometry Reviews · doi:10.1002/mas.20108 · Cited by 2,261 · see citing works
HMDB: a knowledgebase for the human metabolome
Wishart, D. S., Knox, C., Guo, A. C., Eisner, R., Young, N., Gautam, B., Hau, D., Psychogios, N., Dong, E., Bouatra, S., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn810 · Cited by 1,874 · see citing works
Liquid chromatography–mass spectrometry based global metabolite profiling: A review
Theodoridis, G. A., Gika, H., Want, E. J., & Wilson, I. D. (2011) · Analytica Chimica Acta · doi:10.1016/j.aca.2011.09.042 · Cited by 519 · see citing works
Bellew, M., Coram, M., Fitzgibbon, M., Igra, M., Randolph, T. R., Wang, P., May, D., Eng, J. K., Fang, R., Lin, C., et al. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl276 · Cited by 265 · see citing works
The complex links between dietary phytochemicals and human health deciphered by metabolomics
Manach, C., Hubert, J., Llorach, R., & Scalbert, A. (2009) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.200800516 · Cited by 218 · see citing works
Lloyd, A. J., Beckmann, M., Favé, G., Mathers, J. C., & Draper, J. (2011) · British Journal Of Nutrition · doi:10.1017/s0007114511001164 · Cited by 152 · see citing works
Influence of acute phytochemical intake on human urinary metabolomic profiles
Walsh, M. C., Brennan, L., Pujos‐Guillot, E., Sébédio, J., Scalbert, A., Fagan, A., Higgins, D. G., & Gibney, M. J. (2007) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/86.5.1687 · Cited by 142 · see citing works
Mechanisms of action of isothiocyanates in cancer chemoprevention: an update
Navarro, S. L., Li, F., & Lampe, J. W. (2011) · Food & Function · doi:10.1039/c1fo10114e · Cited by 129 · see citing works
Edmands, W. M. B., Beckonert, O. P., Stella, C., Campbell, A., Lake, B. G., Lindon, J. C., Holmes, E., & Gooderham, N. J. (2011) · Journal of Proteome Research · doi:10.1021/pr200326k · Cited by 119 · see citing works
Biomarkers of oxidative damage to DNA and repair
Loft, S. H., Danielsen, P. H., Mikkelsen, L., Risom, L., Forchhammer, L., & Möller, P. (2008) · Biochemical Society Transactions · doi:10.1042/bst0361071 · Cited by 109 · see citing works
Dietary determinants of plasma enterolactone.
Horner, N. K., Kristal, A. R., Prunty, J., Skor, H. E., Potter, J. D., & Lampe, J. W. (2002) · PubMed · Cited by 99 · see citing works
A statistical method for chromatographic alignment of LC-MS data
Wang, P., Tang, H., Fitzgibbon, M., McIntosh, M. W., Coram, M., Zhang, H., Yi, E. C., & Aebersold, R. H. (2006) · Biostatistics · doi:10.1093/biostatistics/kxl015 · Cited by 65 · see citing works
Brass, E. P., & Hiatt, W. R. (1998) · Journal of the American College of Nutrition · doi:10.1080/07315724.1998.10718750 · Cited by 63 · see citing works
Influence of acute phytochemical intake on human urinary metabolomic profiles
Walsh, M. C., Brennan, L., Pujos‐Guillot, E., et al. (2007) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/86.6.1687 · Cited by 59 · see citing works
Investigating Neoplastic Progression of Ulcerative Colitis with Label-Free Comparative Proteomics
May, D., Pan, S., Crispin, D. A., Lai, K., Bronner, M. P., Hogan, J. M., Hockenbery, D. M., McIntosh, M. W., Brentnall, T. A., & Chen, R. (2010) · Journal of Proteome Research · doi:10.1021/pr100574p · Cited by 47 · see citing works
Session 2: Personalised nutrition Metabolomic applications in nutritional research
Brennan, L. (2008) · Proceedings of the Nutrition Society · doi:10.1017/s0029665108008719 · Cited by 44 · see citing works
Navarro, S. L., Saracino, M. R., Makar, K. W., Thomas, S., Li, L., Zheng, Y., Levy, L., Schwarz, Y., Bigler, J., Potter, J. D., et al. (2011) · Lifestyle Genomics · doi:10.1159/000327782 · Cited by 39 · see citing works
Saracino, M. R., Bigler, J., Schwarz, Y., Chang, J.-L., Li, S., Li, L., White, E., Potter, J. D., & Lampe, J. W. (2009) · Journal of Nutrition · doi:10.3945/jn.108.097279 · Cited by 34 · see citing works
Chang, J.-L., Bigler, J., Schwarz, Y., Li, S. S., Li, L., King, I. B., Potter, J. D., & Lampe, J. W. (2007) · Journal of Nutrition · doi:10.1093/jn/137.4.890 · Cited by 28 · see citing works
Li, Q., Wacholder, S., Hunter, D. J., Hoover, R. N., Chanock, S. J., Thomas, G. D., & Yu, K. F. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20396 · Cited by 25 · see citing works
Atkinson, C., Newton, K. M., Stanczyk, F. Z., Westerlind, K. C., Li, L., & Lampe, J. W. (2008) · Cancer Causes & Control · doi:10.1007/s10552-008-9172-3 · Cited by 25 · see citing works
Lodge, J. K. (2009) · Proceedings of The Nutrition Society · doi:10.1017/s0029665109991704 · Cited by 25 · see citing works
Corso, G., D’Apolito, O., Garofalo, D., Paglia, G., & Russo, A. D. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2011.05.009 · Cited by 16 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [26]Rebouche CJ Carnitine. Modern Nutrition in Health and Disease 2006 10th ed. Philadelphia Lippincott, Williams & Wilkins
Cited by
Sorted by citations
The Nrf2 regulatory network provides an interface between redox and intermediary metabolism
Hayes, J. D., & Dinkova‐Kostova, A. T. (2014) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2014.02.002 · Cited by 2,158 · see citing works
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 · see citing works
Livestock metabolomics and the livestock metabolome: A systematic review
Goldansaz, S. A., Guo, A. C., Sajed, T., Steele, M. A., Plastow, G. S., & Wishart, D. S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177675 · Cited by 379 · see citing works
Nrf2 affects the efficiency of mitochondrial fatty acid oxidation
Ludtmann, M. H. R., Angelova, P. R., Zhang, Y., Abramov, A. Y., & Dinkova‐Kostova, A. T. (2013) · Biochemical Journal · doi:10.1042/bj20130863 · Cited by 241 · see citing works
Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies
Ulaszewska, M., Weinert, C. H., Trimigno, A., Portmann, R., Andrés‐Lacueva, C., Badertscher, R., Brennan, L., Brunius, C. F., Bub, A., Capozzi, F., et al. (2018) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201800384 · Cited by 238 · see citing works
Physiological conditions can be reflected in human urine proteome and metabolome
Wu, J., & Gao, Y. (2015) · Expert Review of Proteomics · doi:10.1586/14789450.2015.1094380 · Cited by 197 · see citing works
Nair, M. K., Augustine, L. F., & Konapur, A. (2016) · Frontiers in Public Health · doi:10.3389/fpubh.2015.00277 · Cited by 176 · see citing works
Comparing metabolite profiles of habitual diet in serum and urine
Playdon, M. C., Sampson, J. N., Cross, A. J., Sinha, R. R., Guertin, K. A., Moy, K. A., Rothman, N., Irwin, M. L., Mayne, S. T., Stolzenberg‐Solomon, R. Z., et al. (2016) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.116.135301 · Cited by 175 · see citing works
Untargeted Metabolomics as a Screening Tool for Estimating Compliance to a Dietary Pattern
Andersen, M.-B. S., Rinnan, Å., Manach, C., Poulsen, S. K., Pujos‐Guillot, E., Larsen, T. M., Astrup, A. V., & Dragsted, L. O. (2014) · Journal of Proteome Research · doi:10.1021/pr400964s · Cited by 133 · see citing works
Metabolomics as a tool in nutritional research
Gibbons, H., O’Gorman, A., & Brennan, L. (2014) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000140 · Cited by 108 · see citing works
Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review
Rafiq, T., Azab, S. M., Teo, K. K., Thabane, L., Anand, S. S., Morrison, K. M., de Souza, R. J., & Britz‐McKibbin, P. (2021) · Advances in Nutrition · doi:10.1093/advances/nmab054 · Cited by 105 · see citing works
Metabolomics and microbiomes as potential tools to evaluate the effects of the Mediterranean diet
Jin, Q., Black, A., Kales, S. N., Vattem, D., Ruiz-Canela, M., & Sotos-Prieto, M. (2019) · Nutrients · doi:10.3390/nu11010207 · Cited by 100 · see citing works
The metabolic signature associated with the Western dietary pattern: a cross-sectional study
Bouchard‐Mercier, A., Rudkowska, I., Lemieux, S., Couture, P., & Vohl, M. (2013) · Nutrition Journal · doi:10.1186/1475-2891-12-158 · Cited by 97 · see citing works
Gibbons, H., Michielsen, C. C. J. R., Rundle, M., Frost, G. S., McNulty, B. A., Nugent, A. P., Walton, J., Flynn, A., Gibney, M. J., & Brennan, L. (2017) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201700037 · Cited by 89 · see citing works
Coras, R., Murillo‐Saich, J., & Gumá, M. (2020) · Cells · doi:10.3390/cells9040827 · Cited by 85 · see citing works
Recent Advances in the Application of Metabolomics for Nutrition and Health
González-Peña, D., & Brennan, L. (2019) · Annual Review of Food Science and Technology · doi:10.1146/annurev-food-032818-121715 · Cited by 83 · see citing works
Armah, C. N., Τράκα, Μ., Dainty, J. R., Defernez, M., Janssens, A. I. W. A., Leung, W., Doleman, J. F., Potter, J. F., & Mithen, R. F. (2013) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.065235 · Cited by 77 · see citing works
Piccolo, B. D., Comerford, K. B., Karakas, S. E., Knotts, T. A., Fiehn, O., & Adams, S. H. (2015) · Journal of Nutrition · doi:10.3945/jn.114.203943 · Cited by 74 · see citing works
A metabolomics approach to the identification of biomarkers of sugar-sweetened beverage intake
Gibbons, H., McNulty, B. A., Nugent, A. P., Walton, J., Flynn, A., Gibney, M. J., & Brennan, L. (2015) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.095604 · Cited by 67 · see citing works
Metabolomics as a tool in the identification of dietary biomarkers
Gibbons, H., & Brennan, L. (2016) · Proceedings of The Nutrition Society · doi:10.1017/s002966511600032x · Cited by 67 · see citing works
Zhao, X., Zeisel, S. H., & Zhang, S. (2015) · Electrophoresis · doi:10.1002/elps.201500055 · Cited by 63 · see citing works
Loo, R. L., Zou, X., Appel, L. J., Nicholson, J. K., & Holmes, E. C. (2018) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqx072 · Cited by 63 · see citing works
Zhang, T., & Watson, D. G. (2015) · The Analyst · doi:10.1039/c4an02294g · Cited by 47 · see citing works
Ulaszewska, M., Trôst, K., Stanstrup, J., Tuohy, K. M., Franceschi, P., Chong, M. F., George, T. W., Minihane, A. M., Lovegrove, J. A., & Mattivi, F. (2016) · Metabolomics · doi:10.1007/s11306-015-0935-z · Cited by 45 · see citing works
Urinary biomarkers of dietary intake: a review
Clarke, E. D., Rollo, M. E., Pezdirc, K., Collins, C. E., & Haslam, R. L. (2019) · Nutrition Reviews · doi:10.1093/nutrit/nuz048 · Cited by 44 · see citing works
Bub, A., Kriebel, A., Dörr, C., Bandt, S., Rist, M. J., Röth, A., Hummel, E., Kulling, S. E., Hoffmann, I., & Watzl, B. (2016) · JMIR Research Protocols · doi:10.2196/resprot.5792 · Cited by 37 · see citing works
A Metabolomics Approach to the Identification of Urinary Biomarkers of Pea Intake
Harsha, P. S. C. S., Wahab, R. A., Cuparencu, C., Dragsted, L. O., & Brennan, L. (2018) · Nutrients · doi:10.3390/nu10121911 · Cited by 34 · see citing works
Gurley, B. J., Yates, C. R., & Markowitz, J. S. (2018) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1131 · Cited by 33 · see citing works
Urpí-Sardà, M., Almanza‐Aguilera, E., Tulipani, S., Tinahones, F. J., Salas‐Salvadó, J., & Andrés‐Lacueva, C. (2015) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-015-0440-y · Cited by 27 · see citing works
Dietary Assessment and Metabolomic Methodologies in Human Feeding Studies: A Scoping Review
Clarke, E. D., Ferguson, J. J. A., Stanford, J., & Collins, C. E. (2023) · Advances in Nutrition · doi:10.1016/j.advnut.2023.08.010 · Cited by 27 · see citing works
Hotea, I., Sîrbu, C. B., Plotuna, A.-M., Tîrziu, E., Badea, C., Berbecea, A. A., Dragomirescu, M., & Radulov, I. (2023) · Metabolites · doi:10.3390/metabo13070800 · Cited by 26 · see citing works
Which is the urine sample material of choice for metabolomics-driven biomarker studies?
Liu, X., Yin, P., Shao, Y., Wang, Z., Wang, B., Lehmann, R., & Xu, G. (2020) · Analytica Chimica Acta · doi:10.1016/j.aca.2020.01.028 · Cited by 26 · see citing works
Metabolic profiles from two different breakfast meals characterized by 1H NMR-based metabolomics
Rådjursöga, M., Karlsson, G., Lindqvist, H. M., Pedersen, A., Persson, C., Pinto, R. C., Ellegård, L., & Winkvist, A. (2017) · Food Chemistry · doi:10.1016/j.foodchem.2017.03.142 · Cited by 25 · see citing works
Spaceflight induced changes in the human proteome
Kononikhin, A. S., Starodubtseva, N. L., Pastushkova, L. K., Kashirina, D. N., Fedorchenko, K. Y., Brhozovsky, A. G., Popov, I. A., Larina, I. M., & Николаев, Е. Н. (2016) · Expert Review of Proteomics · doi:10.1080/14789450.2017.1258307 · Cited by 23 · see citing works
An Overview of the Role of Metabolomics in the Identification of Dietary Biomarkers
Brennan, L., Gibbons, H., & O’Gorman, A. (2015) · Current Nutrition Reports · doi:10.1007/s13668-015-0139-1 · Cited by 21 · see citing works
Towards the Fecal Metabolome Derived from Moderate Red Wine Intake
Jiménez-Girón, A., Muñoz‐González, I., Martínlvarez, P., Moreno-Arribas, M. V., & Bartolomé, B. (2014) · Metabolites · doi:10.3390/metabo4041101 · Cited by 21 · see citing works
Lacalle-Bergeron, L., Portolés, T., López, F. J., Sancho, J. V., Ortega‐Azorín, C., Asensio, E. M., Coltell, Ó., & Corella, D. (2020) · Nutrients · doi:10.3390/nu12071916 · Cited by 19 · see citing works
Víctor de la, O., Cruz, E. F., Valdés, A., Cifuentes, A., Walton, J., & Martínez, J. A. (2024) · Nutrition Reviews · doi:10.1093/nutrit/nuae133 · Cited by 15 · see citing works
Sierra, J. A., Escobar, J. S., Corrales-Agudelo, V., Lara-Guzmán, O. J., Velásquez-Mejía, E. P., Henao‐Rojas, J. C., Caro‐Quintero, A., Vaillant, F. E., & Muñoz-Durango, K. (2022) · Food Research International · doi:10.1016/j.foodres.2022.111949 · Cited by 13 · see citing works
Brachem, C., Oluwagbemigun, K., Langenau, J., Weinhold, L., Alexy, U., Schmid, M. C., & Nöthlings, U. (2022) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.202200023 · Cited by 11 · see citing works
Wang, N. C., Bagheri, M., Olszewski, T., Friese, K. A., Smith, H., Robles, M. E., Wang, C., Brooks, A., Bordenstein, S. R., Ferguson, J. F., et al. (2021) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2021.05.013 · Cited by 10 · see citing works
Using metabolomics to evaluate food intake
Manach, C., Brennan, L., & Dragsted, L. O. (2014) · Elsevier eBooks · doi:10.1016/b978-1-78242-084-2.00009-5 · Cited by 10 · see citing works
Ferguson, J. J. A., Clarke, E. D., Stanford, J., Burrows, T. L., Wood, L., & Collins, C. E. (2023) · BMJ Open · doi:10.1136/bmjopen-2023-073658 · Cited by 9 · see citing works
Metabolomic based approach to identify biomarkers of broccoli intake
McNamara, A. E., Yin, X., Collins, C., & Brennan, L. (2023) · Food & Function · doi:10.1039/d2fo03988e · Cited by 9 · see citing works
Ahmed, S. A., Manna, P., & Borah, J. C. (2024) · RSC Medicinal Chemistry · doi:10.1039/d4md00425f · Cited by 9 · see citing works
French, C. D., Arnold, C. D., Taha, A. Y., Engle‐Stone, R., Schmidt, R. J., Hertz‐Picciotto, I., & Slupsky, C. M. (2023) · Metabolites · doi:10.3390/metabo13080904 · Cited by 9 · see citing works
Metabolic Phenotyping of Diet and Dietary Intake
Brignardello, J., Holmes, E. C., & García‐Pérez, I. (2017) · Advances in food and nutrition research · doi:10.1016/bs.afnr.2016.12.002 · Cited by 9 · see citing works
Urinary Metabolites of Type 2 Diabetes Rats Fed With Palm Oil Enriched-High Fat Diet
Sim, X., Ibrahim, B., & Gam, L. (2021) · Heliyon · doi:10.1016/j.heliyon.2021.e08075 · Cited by 7 · see citing works
Metabolomic analyses of plasma and liver of mice fed with immature Citrus tumida peel
Toyoda, A., Sato, M., Muto, M., Goto, T., Miyaguchi, Y., & Inoue, E. (2020) · Bioscience Biotechnology and Biochemistry · doi:10.1080/09168451.2020.1719821 · Cited by 7 · see citing works
Sun, J., Charron, C. S., Liu, Z., Novotny, J. A., Harrington, P. D. B., Ross, S. A., Seifried, H. E., & Chen, P. C. (2020) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.0c05184 · Cited by 7 · see citing works
Application of Metabolomics to Assess Effects of Controlled Dietary Interventions
Hanhineva, K. (2015) · Current Nutrition Reports · doi:10.1007/s13668-015-0148-0 · Cited by 5 · see citing works
Levy, J., Silva, A. M., Carli, E. D., Cacau, L. T., de Alvarenga, J. F. R., Fiamoncini, J., Benseñor, I. M., Lotufo, P. A., & Marchioni, D. M. L. (2022) · Journal of Nutrition · doi:10.1093/jn/nxac115 · Cited by 3 · see citing works
Piloted space flight and post-genomic technologies
Larina, I. M., Pastushkova, L. K., Kononikhin, A. S., Николаев, Е. Н., & Orlov, O. I. (2019) · REACH · doi:10.1016/j.reach.2020.100034 · Cited by 3 · see citing works
Andueza, N., Muñoz‐Prieto, D., Romo‐Hualde, A., Cuervo, M., & Navas‐Carretero, S. (2024) · Food Science & Nutrition · doi:10.1002/fsn3.4226 · Cited by 2 · see citing works
Targeting Foodome-Metabolome Interactions: A Combined Modeling Approach
Zhao, S., & Mechanick, J. I. (2015) · The Endocrine Society eBooks · doi:10.1210/mn1.9781936704842.ch11 · Cited by 2 · see citing works
Ferguson, J. J. A., Clarke, E. D., Stanford, J., Gómez‐Martín, M., Jakstas, T., Collins, C. E., Beck, K. L., Collins, C. E., Cuparencu, C., Souza, D. P. D., et al. (2025) · Advances in Nutrition · doi:10.1016/j.advnut.2025.100420 · Cited by 2 · see citing works
Factors to consider in the verification of urine biomarkers
WeiWei, Q. I. N., Huan, Y., & Gao, Y. (2017) · Scientia Sinica Vitae · doi:10.1360/n052017-00157 · Cited by 2 · see citing works
Food Constituent and Food Metabolite Databases
Foroutan, A., & Wishart, D. S. (2020) · Elsevier eBooks · doi:10.1016/b978-0-08-100596-5.22772-8 · Cited by 2 · see citing works
Metabolomics: new analytical methods for metabolome research
Demetrowitsch, T. J., & Schwarz, K. (2014) · Cited by 1 · see citing works
Metabolome response to glycemic load in a randomized, controlled, crossover feeding trial in humans
Barton, S. (2014) · ResearchWorks at the University of Washington (University of Washington)
Génétique, acides gras oméga-3 et facteurs de risque des maladies cardiovasculaires
Bouchard‐Mercier, A. (2015) · Corpus Université Laval (Université Laval)
Loo, R. L., Zou, X., Appel, L. J., Nicholson, J. K., & Holmes, E. C. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/193359
Urinary Profiling with Liquid Chromatography-Mass Spectrometry
Gam, L. (2022) · Biomarkers in disease · doi:10.1007/978-3-030-81303-1_42-1
BJN volume 110 issue 10 Cover and Back matter
(2013) · British Journal Of Nutrition · doi:10.1017/s000711451300353x
Urinary Profiling with Liquid Chromatography-Mass Spectrometry
Gam, L. (2022) · Biomarkers in disease · doi:10.1007/978-3-031-08014-2_42
Comparative metabolomic analysis of mouse plasma in response to different dietary conditions
Yang, S. H., Kim, Y. J., Lee, H., Seo, W. D., Kwon, E. Y., & Kim, J. K. (2023) · Food Science and Biotechnology · doi:10.1007/s10068-023-01479-8
Wong, N. M. Y., Ting, M., Liu, M. H., & Kim, J. E. (2026) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2026.2652523
- Authors
- May, D. H., Navarro, S. L., Ruczinski, I., Hogan, J., Ogata, Y., Schwarz, Y., Levy, L., Holzman, T., McIntosh, M. W., & Lampe, J. W.
- Affiliations
- Fred Hutch Cancer Center (US)
- Johns Hopkins University (US)
- Corresponding author
- Lampe, Johanna W.
- ORCID
- Venue
- British Journal Of Nutrition
- Publisher
- Cambridge University Press (CUP)
- Published
- 2013-05-09
- Volume
- 110
- Issue
- 10
- Pages
- 1760-1770
- ISSN
- 0007-1145 (ISSN-L)
- 1475-2662
- PMC
- PMC3818452
- OpenAlex
- W2131308179
- Cited by
- 69
- References
- 26
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 6 · 2022: 5 · 2021: 3 · 2020: 7 · 2019: 4 · 2018: 5 · 2017: 6 · 2016: 6 · 2015: 10 · 2014: 8 · 2013: 4
- FWCI
- 4.18
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- British Journal Of Nutrition (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- M.J. Murdock Charitable Trust
- National Institutes of Health
- National Cancer Institute (R56 CA70913, R01CA142695, R25 CA 94880, R25CA094880, R56CA070913, P30CA015704)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Medicine › Biochemistry › Phytochemicals and Antioxidant Activities
- Keywords
- urine metabolomics, dietary intervention, fruit and vegetable intake, cruciferous vegetables, citrus, soybean, proline betaine, dietary biomarkers, fatty acids, acylcarnitines, riboflavin, food frequency questionnaire, 3-day food record
- MeSH terms
- Adult, Carnitine, Citrus, Cross-Sectional Studies, Diet, Fatty Acids, Feeding Behavior, Female, Fruit, Humans, Ions, Male, Niacin, Proline, Surveys and Questionnaires, Riboflavin, Glycine max, Vegetables, Biomarkers, Nutrition Assessment, Diet Records, Brassicaceae, Metabolomics, Metabolome, Young Adult, Phytochemicals
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review