Skip to main content
SpringerLink
Log in

The Food Exposome

  • Chapter
  • First Online:
Unraveling the Exposome

Abstract

Estimating the food exposome, that is, the totality of dietary exposures, represents a substantial challenge because of the wide nature of foods consumed and the variability of the amount and frequency of intake according to food preference, season, and other individual characteristics. Classical approaches to estimating dietary intake have used dietary assessment instruments such as questionnaires and food composition tables. However, these are subject to a number of biases and errors, including misreporting and recall bias. The use of dietary biomarkers provides a more objective approach to assess exposures to dietary compounds and their food sources. Approximately 150 dietary biomarkers have been measured so far in cohort or biomonitoring studies and many new candidate biomarkers are now regularly proposed following the rapid development of mass spectrometry techniques and metabolomics. Several 100 food-derived compounds can be simultaneously measured as part of the human exposome in very small human biospecimens collected in large populations. These approaches and their implementation in dietary-wide association studies are reviewed. This could significantly advance nutritional epidemiology and its utility in linking dietary exposures with disease outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Achaintre D, Bulete A, Cren-Olive C, Li L, Rinaldi S, Scalbert A (2016) Differential isotope labeling of 38 dietary polyphenols and their quantification in urine by liquid chromatography electrospray ionization tandem mass spectrometry. Anal Chem 88(5):2637–2644

    Article  CAS  Google Scholar 

  • Al-Delaimy WK, van Kappel AL, Ferrari P, Slimani N, Steghens JP, Bingham S, Johansson I, Wallstrom P, Overvad K, Tjonneland A, Key TJ, Welch AA, Bueno-de-Mesquita HB, Peeters PH, Boeing H, Linseisen J, Clavel-Chapelon F, Guibout C, Navarro C, Quiros JR, Palli D, Celentano E, Trichopoulou A, Benetou V, Kaaks R, Riboli E (2004) Plasma levels of six carotenoids in nine European countries: report from the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 7(6):713–722

    Article  Google Scholar 

  • Al-Delaimy WK, Ferrari P, Slimani N, Pala V, Johansson I, Nilsson S, Mattisson I, Wirfalt E, Galasso R, Palli D, Vineis P, Tumino R, Dorronsoro M, Pera G, Ocke MC, Bueno-de-Mesquita HB, Overvad K, Chirlaque MAD, Trichopoulou A, Naska A, Tjonneland A, Olsen A, Lund E, Alsaker EHR, Barricarte A, Kesse E, Boutron-Ruault MC, Clavel-Chapelon F, Key TJ, Spencer E, Bingham S, Welch AA, Sanchez-Perez MJ, Nagel G, Linseisen J, Quiros JR, Peeters PHM, van Gils CH, Boeing H, van Kappel AL, Steghens JP, Riboli E (2005) Plasma carotenoids as biomarkers of intake of fruits and vegetables: individual-level correlations in the European Prospective Investigation into Cancer and Nutrition (EPIC). Eur J Clin Nutr 59(12):1387–1396

    Article  CAS  Google Scholar 

  • Allen NE, Grace PB, Ginn A, Travis RC, Roddam AW, Appleby PN, Key T (2008) Phytanic acid: measurement of plasma concentrations by gas-liquid chromatography-mass spectrometry analysis and associations with diet and other plasma fatty acids. Br J Nutr 99(3):653–659

    Article  CAS  Google Scholar 

  • Arab L (2003) Biomarkers of fat and fatty acid intake. J Nutr 133(3):925S–932S

    Article  CAS  Google Scholar 

  • Aune D, Chan DSM, Vieira AR, Rosenblatt DAN, Vieira R, Greenwood DC, Norat T (2012) Dietary compared with blood concentrations of carotenoids and breast cancer risk: a systematic review and meta-analysis of prospective studies. Am J Clin Nutr 96(2):356–373. https://doi.org/10.3945/ajcn.112.034165

    Article  CAS  Google Scholar 

  • Axel C, Zannini E, Arendt EK, Waters DM, Czerny M (2014) Quantification of cyclic dipeptides from cultures of Lactobacillus brevis R2Delta by HRGC/MS using stable isotope dilution assay. Anal Bioanal Chem 406(9–10):2433–2444. https://doi.org/10.1007/s00216-014-7620-3

    Article  CAS  Google Scholar 

  • Bailey LB, Stover PJ, McNulty H, Fenech MF, Gregory JF 3rd, Mills JL, Pfeiffer CM, Fazili Z, Zhang M, Ueland PM, Molloy AM, Caudill MA, Shane B, Berry RJ, Bailey RL, Hausman DB, Raghavan R, Raiten DJ (2015) Biomarkers of nutrition for development-folate review. J Nutr 145(7):1636S–1680S. https://doi.org/10.3945/jn.114.206599

    Article  CAS  Google Scholar 

  • Baldrick FR, Woodside JV, Elborn JS, Young IS, McKinley MC (2011) Biomarkers of fruit and vegetable intake in human intervention studies: a systematic review. Crit Rev Food Sci Nutr 51(9):795–815. https://doi.org/10.1080/10408398.2010.482217

    Article  CAS  Google Scholar 

  • Bingham SA (2002) Biomarkers in nutritional epidemiology. Public Health Nutr 5(6A):821–827

    Article  Google Scholar 

  • Biskup I, Kyro C, Marklund M, Olsen A, van Dam RM, Tjonneland A, Overvad K, Lindahl B, Johansson I, Landberg R (2016) Plasma alkylresorcinols, biomarkers of whole-grain wheat and rye intake, and risk of type 2 diabetes in Scandinavian men and women. Am J Clin Nutr 104(1):88–96. https://doi.org/10.3945/ajcn.116.133496

    Article  CAS  Google Scholar 

  • Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L (1986) A data-based approach to diet questionnaire design and testing. Am J Epidemiol 124(3):453–469

    Article  CAS  Google Scholar 

  • Bradman A, Kogut K, Eisen EA, Jewell NP, Quiros-Alcala L, Castorina R, Chevrier J, Holland NT, Barr DB, Kavanagh-Baird G, Eskenazi B (2013) Variability of organophosphorous pesticide metabolite levels in spot and 24-hr urine samples collected from young children during 1 week. Environ Health Perspect 121(1):118–124

    Article  Google Scholar 

  • Brantsaeter AL, Haugen M, Thomassen Y, Ellingsen DG, Ydersbond TA, Hagve TA, Alexander J, Meltzer HM (2010) Exploration of biomarkers for total fish intake in pregnant Norwegian women. Public Health Nutr 13(1):54–62. https://doi.org/10.1017/s1368980009005904

    Article  Google Scholar 

  • Brevik A, Veierød MB, Drevon CA, Andersen LF (2005) Evaluation of the odd fatty acids 15:0 and 17:0 in serum and adipose tissue as markers of intake of milk and dairy fat. Eur J Clin Nutr 59(12):1417–1422

    Article  CAS  Google Scholar 

  • Chadeau-Hyam M, Ebbels TMD, Brown IJ, Chan Q, Stemler J, Huang CC, Daviglus ML, Ueshima H, Zhao LC, Holmes E, Nicholson JK, Elliott P, De Iorio M (2010) Metabolic profiling and the metabolome-wide association study: significance level for biomarker identification. J Proteome Res 9(9):4620–4627

    Article  CAS  Google Scholar 

  • Chajes V, Biessy C, Byrnes G, Deharveng G, Saadatian-Elahi M, Jenab M, Peeters PHM, Ocke M, Bueno-de-Mesquita HB, Johansson I, Hallmans G, Manjer J, Wirfalt E, Jakszyn P, Gonzalez CA, Huerta J-M, Martinez C, Amiano P, Rodriguez Suarez L, Ardanaz E, Tjonneland A, Halkjaer J, Overvad K, Jakobsen MU, Berrino F, Pala V, Palli D, Tumino R, Vineis P, de Magistris MS, Spencer EA, Crowe FL, Bingham S, Khaw K-T, Linseisen J, Rohrmann S, Boeing H, Noeethlings U, Olsen KS, Skeie G, Lund E, Trichopoulou A, Zilis D, Oustoglou E, Clavel-Chapelon F, Riboli E, Slimani N (2011a) Ecological-level associations between highly processed food intakes and plasma phospholipid elaidic acid concentrations: results from a cross-sectional study within the European prospective investigation into cancer and nutrition (EPIC). Nutr Cancer 63(8):1235–1250. https://doi.org/10.1080/01635581.2011.617530

    Article  CAS  Google Scholar 

  • Chajes V, Jenab M, Romieu I, Ferrari P, Dahm CC, Overvad K, Egeberg R, Tjonneland A, Clavel-Chapelon F, Boutron-Ruault M-C, Engel P, Teucher B, Kaaks R, Floegel A, Boeing H, Trichopoulou A, Dilis V, Karapetyan T, Mattiello A, Tumino R, Grioni S, Palli D, Vineis P, Bueno-de-Mesquita HB, Numans ME, Peeters PHM, Lund E, Navarro C, Ramon Quiros J, Sanchez-Cantalejo E, Barricarte Gurrea A, Dorronsoro M, Regner S, Sonestedt E, Wirfaelt E, Khaw K-T, Wareham N, Allen NE, Crowe FL, Rinaldi S, Slimani N, Carneiro F, Riboli E, Gonzalez CA (2011b) Plasma phospholipid fatty acid concentrations and risk of gastric adenocarcinomas in the European Prospective Investigation into Cancer and Nutrition (EPIC-EURGAST). Am J Clin Nutr 94(5):1304–1313. https://doi.org/10.3945/ajcn.110.005892

    Article  CAS  Google Scholar 

  • Cheung W, Keski-Rahkonen P, Assi N, Ferrari P, Freisling H, Rinaldi S, Slimani N, Zamora-Ros R, Rundle M, Frost G, Gibbons H, Carr E, Brennan L, Cross AJ, Pala V, Panico S, Sacerdote C, Palli D, Tumino R, Kühn T, Kaaks R, Boeing H, Floegel A, Mancini F, Boutron-Ruault M-C, Baglietto L, Trichopoulou A, Naska A, Orfanos P, Scalbert A (2017) A metabolomic study of biomarkers of meat and fish intake. Am J Clin Nutr 105(3):600–608. https://doi.org/10.3945/ajcn.116.146639

    Article  CAS  Google Scholar 

  • Chung H, Nettleton JA, Lemaitre RN, Barr RG, Tsai MY, Tracy RP, Siscovick DS (2008) Frequency and type of seafood consumed influence plasma (n-3) fatty acid concentrations. J Nutr 138(12):2422–2427

    Article  CAS  Google Scholar 

  • Crews H, Alink G, Andersen R, Braesco V, Holst B, Maiani G, Ovesen L, Scotter M, Solfrizzo M, van den Berg R, Verhagen H, Williamson G (2001a) A critical assessment of some biomarker approaches linked with dietary intake. Br J Nutr 86(Suppl 1):S5–S35

    Article  CAS  Google Scholar 

  • Crews HM, Olivier L, Wilson LA (2001b) Urinary biomarkers for assessing dietary exposure to caffeine. Food Addit Contam 18(12):1075–1087. https://doi.org/10.1080/02652030110056630

    Article  CAS  Google Scholar 

  • Curl CL, Beresford SA, Fenske RA, Fitzpatrick AL, Lu C, Nettleton JA, Kaufman JD (2015) Estimating pesticide exposure from dietary intake and organic food choices: the Multi-Ethnic Study of Atherosclerosis (MESA). Environ Health Perspect 123(5):475–483. https://doi.org/10.1289/ehp.1408197

    Article  CAS  Google Scholar 

  • Dahl H, Carlsson AV, Hillgren K, Helander A (2011) Urinary ethyl glucuronide and ethyl sulfate testing for detection of recent drinking in an outpatient treatment program for alcohol and drug dependence. Alcohol Alcohol 46(3):278–282. https://doi.org/10.1093/alcalc/agr009

    Article  CAS  Google Scholar 

  • Davis MA, Gilbert-Diamond D, Karagas MR, Li Z, Moore JH, Williams SM, Frost HR (2014) A dietary-wide association study (DWAS) of environmental metal exposure in US children and adults. PLoS One 9(9):e104768. https://doi.org/10.1371/journal.pone.0104768

    Article  CAS  Google Scholar 

  • de Batlle J, Matejcic M, Chajes V, Moreno-Macias H, Amadou A, Slimani N, Cox DG, Clavel-Chapelon F, Fagherazzi G, Romieu I (2016) Determinants of folate and vitamin B12 plasma levels in the French E3N-EPIC cohort. Eur J Nutr 57(2):751–760. https://doi.org/10.1007/s00394-016-1365-z

    Article  CAS  Google Scholar 

  • de Nijs M, Mengelers MJB, Boon PE, Heyndrickx E, Hoogenboom LAP, Lopez P, Mol HGJ (2016) Strategies for estimating human exposure to mycotoxins via food. World Mycotoxin J 9(5):831–845. https://doi.org/10.3920/WMJ2016.2045

    Article  Google Scholar 

  • Dehghan M, Akhtar-Danesh N, McMillan CR, Thabane L (2007) Is plasma vitamin C an appropriate biomarker of vitamin C intake? A systematic review and meta-analysis. Nutr J 6:41. https://doi.org/10.1186/1475-2891-6-41

    Article  CAS  Google Scholar 

  • Dragsted LO (2010) Biomarkers of meat intake and the application of nutrigenomics. Meat Sci 84(2):301–307

    Article  CAS  Google Scholar 

  • Edmands WM, Ferrari P, Rothwell JA, Rinaldi S, Slimani N, Barupal DK, Biessy C, Jenab M, Clavel-Chapelon F, Fagherazzi G, Boutron-Ruault MC, Katzke VA, Kuhn T, Boeing H, Trichopoulou A, Lagiou P, Trichopoulos D, Palli D, Grioni S, Tumino R, Vineis P, Mattiello A, Romieu I, Scalbert A (2015) Polyphenol metabolome in human urine and its association with intake of polyphenol-rich foods across European countries. Am J Clin Nutr 102(4):905–913. https://doi.org/10.3945/ajcn.114.101881

    Article  CAS  Google Scholar 

  • Edmands WMB, Beckonert OP, Stella C, Campbell A, Lake BG, Lindon JC, Holmes E, Gooderham NJ (2011) Identification of human urinary biomarkers of cruciferous vegetable consumption by metabonomic profiling. J Proteome Res 10(10):4513–4521. https://doi.org/10.1021/pr200326k

    Article  CAS  Google Scholar 

  • Edmands WMB, Petrick L, Barupal DK, Scalbert A, Rappaport SM (2017) compMS2Miner: an automatable metabolite identification, visualization and data-sharing R package for high-resolution LC-MS datasets. Anal Chem 89(7):3919–3928

    Article  CAS  Google Scholar 

  • Forouhi NG, Imamura F, Sharp SJ, Koulman A, Schulze MB, Zheng J, Ye Z, Sluijs I, Guevara M, Huerta JM, Kroger J, Wang LY, Summerhill K, Griffin JL, Feskens EJ, Affret A, Amiano P, Boeing H, Dow C, Fagherazzi G, Franks PW, Gonzalez C, Kaaks R, Key TJ, Khaw KT, Kuhn T, Mortensen LM, Nilsson PM, Overvad K, Pala V, Palli D, Panico S, Quiros JR, Rodriguez-Barranco M, Rolandsson O, Sacerdote C, Scalbert A, Slimani N, Spijkerman AM, Tjonneland A, Tormo MJ, Tumino R, van der AD, van der Schouw YT, Langenberg C, Riboli E, Wareham NJ (2016) Association of plasma phospholipid n-3 and n-6 polyunsaturated fatty acids with Type 2 diabetes: the EPIC-InterAct case-cohort study. PLoS Med 13(7):e1002094. https://doi.org/10.1371/journal.pmed.1002094

    Article  Google Scholar 

  • Garcia-Aloy M, Llorach R, Urpi-Sarda M, Tulipani S, Estruch R, Martinez-Gonzalez MA, Corella D, Fito M, Ros E, Salas-Salvado J, Andres-Lacueva C (2014) Novel multimetabolite prediction of walnut consumption by a urinary biomarker model in a free-living population: the PREDIMED study. J Proteome Res 13(7):3476–3483

    Article  CAS  Google Scholar 

  • Garcia-Perez I, Posma JM, Gibson R, Chambers ES, Hansen TH, Vestergaard H, Hansen T, Beckmann M, Pedersen O, Elliott P, Stamler J, Nicholson JK, Draper J, Mathers JC, Holmes E, Frost G (2017) Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial. Lancet Diabetes Endocrinol 5(3):184–195. https://doi.org/10.1016/s2213-8587(16)30419-3

    Article  Google Scholar 

  • Gregory JF, Quinlivan EP (2002) In vivo kinetics of folate metabolism. Annu Rev Nutr 22:199–220. https://doi.org/10.1046/annurev.nutr.22.120701.083554

    Article  CAS  Google Scholar 

  • Guertin KA, Moore SC, Sampson JN, Huang W-Y, Xiao Q, Stolzenberg-Solomon RZ, Sinha R, Cross AJ (2014) Metabolomics in nutritional epidemiology: identifying metabolites associated with diet and quantifying their potential to uncover diet-disease relations in populations. Am J Clin Nutr 100:208–217. https://doi.org/10.3945/ajcn.113.078758

    Article  CAS  Google Scholar 

  • Guertin KA, Loftfield E, Boca SM, Sampson JN, Moore SC, Xiao Q, Huang W-Y, Xiong X, Freedman ND, Cross AJ, Sinha R (2015) Serum biomarkers of habitual coffee consumption may provide insight into the mechanism underlying the association between coffee consumption and colorectal cancer. Am J Clin Nutr 101:1000–1011. https://doi.org/10.3945/ajcn.114.096099

    Article  CAS  Google Scholar 

  • Gurdeniz G, Jensen MG, Meier S, Bech L, Lund E, Dragsted LO (2016) Detecting beer intake by unique metabolite patterns. J Proteome Res 15(12):4544–4556. https://doi.org/10.1021/acs.jproteome.6b00635

    Article  CAS  Google Scholar 

  • Hedrick VE, Dietrich AM, Estabrooks PA, Savla J, Serrano E, Davy BM (2012) Dietary biomarkers: advances, limitations and future directions. Nutr J 11:109. https://doi.org/10.1186/1475-2891-11-109

    Article  Google Scholar 

  • Heinzmann SS, Brown IJ, Chan Q, Bictash M, Dumas M-E, Kochhar S, Stamler J, Holmes E, Elliott P, Nicholson JK (2010) Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption. Am J Clin Nutr 92(2):436–443

    Article  CAS  Google Scholar 

  • Hodson L, Skeaff CM, Fielding BA (2008) Fatty acid composition of adipose tissue and blood in humans and its use as a biomarker of dietary intake. Prog Lipid Res 47(5):348–380

    Article  CAS  Google Scholar 

  • Hunter D (1998) Biochemical indicators of dietary intake. In: Willett WC (ed) Nutritional epidemiology, 2nd edn. Oxford University Press, Oxford, pp 174–243

    Google Scholar 

  • Illner A-K, Freisling H, Boeing H, Huybrechts I, Crispim S, Slimani N (2012) Review and evaluation of innovative technologies for measuring diet in nutritional epidemiology. Int J Epidemiol 41(4):1187–1203. https://doi.org/10.1093/ije/dys105

    Article  Google Scholar 

  • Isaksson A, Walther L, Hansson T, Andersson A, Alling C (2011) Phosphatidylethanol in blood (B-PEth): a marker for alcohol use and abuse. Drug Test Anal 3(4):195–200. https://doi.org/10.1002/dta.278

    Article  CAS  Google Scholar 

  • Jenab M, Slimani N, Bictash M, Ferrari P, Bingham SA (2009) Biomarkers in nutritional epidemiology: applications, needs and new horizons. Hum Genet 125(5–6):507–525

    Article  Google Scholar 

  • Kaaks R, Riboli E, Vanstaveren W (1995) Calibration of dietary intake measurements in prospective cohort studies. Am J Epidemiol 142(5):548–556

    Article  CAS  Google Scholar 

  • Kaaks R, Riboli E, Sinha R (1997) Biochemical markers of dietary intake. IARC Sci Publ 142:103–126

    Google Scholar 

  • Kaaks RJ (1997) Biochemical markers as additional measurements in studies of the accuracy of dietary questionnaire measurements: conceptual issues. Am J Clin Nutr 65(4 Suppl):1232S–1239S

    Article  CAS  Google Scholar 

  • Keski-Rahkonen P, Rothwell JA, Scalbert A (2017) Metabolomic techniques to discover food biomarkers. In: Schoeller DA, Westerterp-Plantenga M (eds) Advances for in the assessment of dietary intake. CRC Press, Boca Raton

    Google Scholar 

  • Khakimov B, Poulsen SK, Savorani F, Acar E, Gurdeniz G, Larsen TM, Astrup A, Dragsted LO, Engelsen SB (2016) New Nordic diet versus average Danish diet: a randomized controlled trial revealed healthy long-term effects of the new Nordic Diet by GC-MS blood plasma metabolomics. J Proteome Res 15(6):1939–1954

    Article  CAS  Google Scholar 

  • Kirkpatrick SI, Subar AF, Douglass D, Zimmerman TP, Thompson FE, Kahle LL, George SM, Dodd KW, Potischman N (2014) Performance of the Automated Self-Administered 24-hour Recall relative to a measure of true intakes and to an interviewer-administered 24-h recall. Am J Clin Nutr 100(1):233–240

    Article  CAS  Google Scholar 

  • Kristal AR, Peters U, Potter JD (2005) Is it time to abandon the food frequency questionnaire? Cancer Epidemiol Biomark Prev 14(12):2826–2828. https://doi.org/10.1158/1055-9965.epi-12-ed1

    Article  Google Scholar 

  • Kyro C, Olsen A, Landberg R, Skeie G, Loft S, Aman P, Leenders M, Dik VK, Siersema PD, Pischon T, Christensen J, Overvad K, Boutron-Ruault M-C, Fagherazzi G, Cottet V, Kuehn T, Chang-Claude J, Boeing H, Trichopoulou A, Bamia C, Trichopoulos D, Palli D, Krogh V, Tumino R, Vineis P, Panico S, Peeters PH, Weiderpass E, Bakken T, Asli LA, Argueelles M, Jakszyn P, Sanchez M-J, Amiano P, Huerta JM, Barricarte A, Ljuslinder I, Palmqvist R, Khaw K-T, Wareham N, Key TJ, Travis RC, Ferrari P, Freisling H, Jenab M, Gunter MJ, Murphy N, Riboli E, Tjonneland A, Bueno-de-Mesquita HB (2014) Plasma alkylresorcinols, biomarkers of whole-grain wheat and rye intake, and incidence of colorectal cancer. J Natl Cancer Inst 106(1):djt352. https://doi.org/10.1093/jnci/djt352

    Article  CAS  Google Scholar 

  • Landberg R, Aman P, Friberg LE, Vessby B, Adlercreutz H, Kamal-Eldin A (2009) Dose response of whole-grain biomarkers: alkylresorcinols in human plasma and their metabolites in urine in relation to intake. Am J Clin Nutr 89(1):290–296

    Article  CAS  Google Scholar 

  • Leech RM, Worsley A, Timperio A, McNaughton SA (2015) Understanding meal patterns: definitions, methodology and impact on nutrient intake and diet quality. Nutr Res Rev 28(1):1–21. https://doi.org/10.1017/S0954422414000262

    Article  Google Scholar 

  • Levine M, Conry-Cantilena C, Wang Y, Welch RW, Washko PW, Dhariwal KR, Park JB, Lazarev A, Graumlich JF, King J, Cantilena LR (1996) Vitamin C pharmacokinetics in healthy volunteers: evidence for a recommended dietary allowance. Proc Natl Acad Sci U S A 93(8):3704–3709

    Article  CAS  Google Scholar 

  • Lloyd AJ, Beckmann M, Fave G, Mathers JC, Draper J (2011) Proline betaine and its biotransformation products in fasting urine samples are potential biomarkers of habitual citrus fruit consumption. Br J Nutr 106(6):812–824. https://doi.org/10.1017/s0007114511001164

    Article  CAS  Google Scholar 

  • Lu QY, Hung JC, Heber D, Go VLW, Reuter VE, Cordon-Cardo C, Scher HI, Marshall JR, Zhang ZF (2001) Inverse associations between plasma lycopene and other carotenoids and prostate cancer. Cancer Epidemiol Biomark Prev 10(7):749–756

    CAS  Google Scholar 

  • MacDonald L, Thumser AE, Sharp P (2002) Decreased expression of the vitamin C transporter SVCT1 by ascorbic acid in a human intestinal epithelial cell line. Br J Nutr 87(2):97–100

    Article  CAS  Google Scholar 

  • Mendonça N, Mathers JC, Adamson AJ, Martin-Ruiz C, Seal CJ, Jagger C, Hill TR (2016) Intakes of folate and vitamin B12 and biomarkers of status in the very old: the Newcastle 85+ Study. Nutrients 8(10):pii: E604. https://doi.org/10.3390/nu8100604

    Article  CAS  Google Scholar 

  • Mennen L, Sapinho D, Ito H, Galan P, Hercberg S, Scalbert A (2006) Urinary flavonoids and phenolic acids as biomarkers of intake for polyphenol-rich foods. Br J Nutr 96:191–198

    Article  CAS  Google Scholar 

  • Merritt MA, Tzoulaki I, Tworoger SS, De Vivo I, Hankinson SE, Fernandes J, Tsilidis KK, Weiderpass E, Tjonneland A, Petersen KE, Dahm CC, Overvad K, Dossus L, Boutron-Ruault MC, Fagherazzi G, Fortner RT, Kaaks R, Aleksandrova K, Boeing H, Trichopoulou A, Bamia C, Trichopoulos D, Palli D, Grioni S, Tumino R, Sacerdote C, Mattiello A, Bueno-de-Mesquita HB, Onland-Moret NC, Peeters PH, Gram IT, Skeie G, Quiros JR, Duell EJ, Sanchez MJ, Salmeron D, Barricarte A, Chamosa S, Ericson U, Sonestedt E, Nilsson LM, Idahl A, Khaw KT, Wareham N, Travis RC, Rinaldi S, Romieu I, Patel CJ, Riboli E, Gunter MJ (2015) Investigation of dietary factors and endometrial cancer risk using a nutrient-wide association study approach in the EPIC and Nurses’ Health Study (NHS) and NHSII. Cancer Epidemiol Biomark Prev 24(2):466–471

    Article  CAS  Google Scholar 

  • Mondul AM, Moore SC, Weinstein SJ, Karoly ED, Sampson JN, Albanes D (2015) Metabolomic analysis of prostate cancer risk in a prospective cohort: the alpha-tocolpherol, beta-carotene cancer prevention (ATBC) study. Int J Cancer 137(9):2124–2132. https://doi.org/10.1002/ijc.29576

    Article  CAS  Google Scholar 

  • Murphy N, Achaintre D, Zamora-Ros R, Jenab M, Boutron-Ruault MC, Carbonnel F, Savoye I, Kaaks R, Kühn T, Boeing H, Aleksandrova K, Tjønneland A, Kyrø C, Overvad K, Quirós JR, Sánchez MJ, Altzibar JM, María Huerta J, Barricarte A, Khaw KT, Bradbury KE, Perez-Cornago A, Trichopoulou A, Karakatsani A, Peppa E, Palli D, Grioni S, Tumino R, Sacerdote C, Panico S, Bueno-de-Mesquita B, Peeters PH, Rutegård M, Johansson I, Freisling H, Noh H, Cross AJ, Vineis P, Tsilidis K, Gunter MJ, Scalbert A (2018) A prospective evaluation of plasma polyphenol levels and colon cancer risk. Int J Cancer: in press. https://https://doi:10.1002/ijc.31563

    Article  CAS  Google Scholar 

  • Neveu V, Moussy A, Rouaix H, Wedekind R, Pon A, Knox C, Wishart DS, Scalbert A (2017) Exposome-explorer: a manually-curated database on biomarkers of exposure to dietary and environmental factors. Nucleic Acids Res 45(D1):D979–D984. https://doi.org/10.1093/nar/gkw980

    Article  CAS  Google Scholar 

  • Ovesen L, Boeing H, EFCOSUM Group (2002) The use of biomarkers in multicentric studies with particular consideration of iodine, sodium, iron, folate and vitamin D. Eur J Clin Nutr 56(Suppl 2):S12–S17. https://doi.org/10.1038/sj.ejcn.1601424

    Article  CAS  Google Scholar 

  • Pallister T, Haller T, Thorand B, Altmaier E, Cassidy A, Martin T, Jennings A, Mohney RP, Gieger C, MacGregor A, Kastenmüller G, Metspalu A, Spector TD, Menni C (2016a) Metabolites of milk intake: a metabolomic approach in UK twins with findings replicated in two European cohorts. Eur J Nutr 56(7):2379–2391. https://doi.org/10.1007/s00394-016-1278-x

    Article  CAS  Google Scholar 

  • Pallister T, Jennings A, Mohney RP, Yarand D, Mangino M, Cassidy A, MacGregor A, Spector TD, Menni C (2016b) Characterizing blood metabolomics profiles associated with self-reported food intakes in female twins. PLoS One 11(6):e0158568

    Article  Google Scholar 

  • Patel CJ, Bhattacharya J, Butte AJ (2010) An environment-wide association study (EWAS) on type 2 diabetes mellitus. PLoS One 5(5):e10746

    Article  Google Scholar 

  • Personne V, Partouche H, Souberbielle JC (2013) Vitamin D insufficiency and deficiency: epidemiology, measurement, prevention and treatment. Presse Med 42(10):1334–1342. https://doi.org/10.1016/j.lpm.2013.06.013

    Article  Google Scholar 

  • Playdon MC, Sampson JN, Cross AJ, Sinha R, Guertin KA, Moy KA, Rothman N, Irwin ML, Mayne ST, Stolzenberg-Solomon R, Moore SC (2016) Comparing metabolite profiles of habitual diet in serum and urine. Am J Clin Nutr 104(3):776–789. https://doi.org/10.3945/ajcn.116.135301

    Article  CAS  Google Scholar 

  • Pujos-Guillot E, Hubert J, Martin J-F, Lyan B, Quintana M, Claude S, Chabanas B, Rothwell JA, Bennetau-Pelissero C, Scalbert A, Comte B, Hercberg S, Morand C, Galan P, Manach C (2013) Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study. J Proteome Res 12(4):1645–1659. https://doi.org/10.1021/pr300997c

    Article  CAS  Google Scholar 

  • Quifer-Rada P, Martinez-Huelamo M, Chiva-Blanch G, Jauregui O, Estruch R, Lamuela-Raventos RM (2014) Urinary isoxanthohumol is a specific and accurate biomarker of beer consumption. J Nutr 144(4):484–488. https://doi.org/10.3945/jn.113.185199

    Article  CAS  Google Scholar 

  • Rappaport SM, Barupal DK, Wishart D, Vineis P, Scalbert A (2014) The blood exposome and its role in discovering causes of disease. Environ Health Perspect 122(8):769–774. https://doi.org/10.1289/ehp.1308015

    Article  CAS  Google Scholar 

  • Reboul E, Richelle M, Perrot E, Desmoulins-Malezet C, Pirisi V, Borel P (2006) Bioaccessibility of carotenoids and vitamin E from their main dietary sources. J Agric Food Chem 54(23):8749–8755. https://doi.org/10.1021/jf061818s

    Article  CAS  Google Scholar 

  • Regueiro J, Vallverdu-Queralt A, Simal-Gandara J, Estruch R, Lamuela-Raventos RM (2014) Urinary tartaric acid as a potential biomarker for the dietary assessment of moderate wine consumption: a randomised controlled trial. Br J Nutr 111(9):1680–1685. https://doi.org/10.1017/s0007114513004108

    Article  CAS  Google Scholar 

  • Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC (1992) Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol 135(10):1114–1126

    Article  CAS  Google Scholar 

  • Ross AB, Svelander C, Undeland I, Pinto R, Sandberg AS (2015) Herring and beef meals lead to differences in plasma 2-aminoadipic acid, beta-alanine, 4-hydroxyproline, cetoleic acid, and docosahexaenoic acid concentrations in overweight men. J Nutr 145(11):2456–2463

    Article  CAS  Google Scholar 

  • Rothwell J, Madrid-Gambin F, Garcia-Aloy M, Gao Q, Andres-Lacueva C, Logue C, Gallagher AM, Mack C, Kulling S, Dragsted L, Scalbert A (2018) Biomarkers of intake for coffee, tea and sweetened beverages. Genes Nutr, In Revision

    Google Scholar 

  • Rothwell JA, Fillâtre Y, Martin J-F, Lyan B, Pujos-Guillot E, Fezeu L, Hercberg S, Comte B, Galan P, Touvier M, Manach C (2014) New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects. PLoS One 9(4):e93474. https://doi.org/10.1371/journal.pone.0093474

    Article  CAS  Google Scholar 

  • Rothwell JR, Urpi-Sarda M, Boto-Ordonez M, Knox C, Llorach R, Eisner R, Cruz J, Neveu V, Wishart D, Manach C, Andres-Lacueva C, Scalbert A (2012) Phenol-Explorer 2.0: a major update of the Phenol-Explorer database integrating data on polyphenol metabolism and pharmacokinetics in humans and experimental animals. Database 2012:bas031

    Article  Google Scholar 

  • Sanz ML, Villamiel M, Martınez-Castro I (2004) Inositols and carbohydrates in different fresh fruit juices. Food Chem 87(3):325–328. https://doi.org/10.1016/j.foodchem.2003.12.001

    Article  CAS  Google Scholar 

  • Saraff V, Shaw N (2016) Sunshine and vitamin D. Arch Dis Child 101(2):190–192. https://doi.org/10.1136/archdischild-2014-307214

    Article  Google Scholar 

  • Scalbert A, Brennan L, Manach C, Andres-Lacueva C, Dragsted LO, Draper J, Rappaport SM, van der Hooft JJJ, Wishart DS (2014) The food metabolome—a window over dietary exposure. Am J Clin Nutr 99:1286–1308

    Article  CAS  Google Scholar 

  • Scalbert A, Rothwell JA, Keski-Rahkonen P, Neveu V (2017) The food metabolome and dietary biomarkers. In: Schoeller DA, Westerterp-Plantenga M (eds) Advances in the assessment of dietary intake. CRC Press, Boca Raton

    Google Scholar 

  • Scheline R (1978) Mammalian metabolism of plant xenobiotics. Academic Press, New York

    Google Scholar 

  • Schoeller DA, Westerterp-Plantenga M (eds) (2017) Advances in the assessment of dietary intake. CRC Press, Boca Raton

    Google Scholar 

  • Schroeder H, de la Torre R, Estruch R, Corella D, Angel Martinez-Gonzalez M, Salas-Salvado J, Ros E, Aros F, Flores G, Civit E, Farre M, Fiol M, Vila J, Fernandez-Crehuet J, Ruiz-Gutierrez V, Lapetra J, Saez G, Covas M-I, Investigators PS (2009) Alcohol consumption is associated with high concentrations of urinary hydroxytyrosol. Am J Clin Nutr 90(5):1329–1335

    Article  Google Scholar 

  • Slimani N, Freisling H, Illner AK, Huybrechts I (2015) Methods to determine dietary intake. In: Lovegrove JA, Hodson L, Sharma S, Lanham-New SA (eds) Nutrition research methodologies. Wiley, Hoboken

    Google Scholar 

  • Soininen P, Kangas AJ, Würtz P, Suna T, Ala-Korpela M (2015) Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. Circ Cardiovasc Genet 8(1):192–206. https://doi.org/10.1161/circgenetics.114.000216

    Article  CAS  Google Scholar 

  • Steingrimsdottir L, Ovesen L, Moreiras O, Jacob S (2002) Selection of relevant dietary indicators for health. Eur J Clin Nutr 56(Suppl 2):S8–S11. https://doi.org/10.1038/sj.ejcn.1601423

    Article  Google Scholar 

  • Sun Q, Bertrand KA, Franke AA, Rosner B, Curhan GC, Willett WC (2017) Reproducibility of urinary biomarkers in multiple 24-h urine samples. Am J Clin Nutr 105(1):159–168. https://doi.org/10.3945/ajcn.116.139758

    Article  CAS  Google Scholar 

  • The_Joint_FAO/WHO_Expert_Committee_on_Food_Additives_(JECFA) (2017) Chemical risks and JECFA. Food and Agriculature Organisation (FAO), http://www.fao.org/food/food-safety-quality/scientific-advice/jecfa/en/. Accessed 15 Feb 2017

  • Thompson FE, Subar AF (2013) Dietary assessment methodology. In: Coulston AM, Boushey CJ, Ferruzzi MG (eds) Nutrition in the prevention and treatment of disease, 3rd edn. Elsevier, San Diego, CA, pp 5–46

    Chapter  Google Scholar 

  • Troche JR, Mayne ST, Freedman ND, Shebl FM, Guertin KA, Cross AJ, Abnet CC (2016) Alcohol consumption-related metabolites in relation to colorectal cancer and adenoma: two case-control studies using serum biomarkers. PLoS One 11:e0150962. https://doi.org/10.1371/journal.pone.0150962

    Article  CAS  Google Scholar 

  • Turner PC, Hopton RP, Lecluse Y, White KL, Fisher J, Lebailly P (2010) Determinants of urinary deoxynivalenol and de-epoxy deoxynivalenol in male farmers from Normandy, France. J Agric Food Chem 58(8):5206–5212. https://doi.org/10.1021/jf100892v

    Article  CAS  Google Scholar 

  • Tzoulaki I, Patel CJ, Okamura T, Chan Q, Brown IJ, Miura K, Ueshima H, Zhao L, Van Horn L, Daviglus ML, Stamler J, Butte AJ, Ioannidis JPA, Elliott P (2012) A nutrient-wide association study on blood pressure. Circulation 126(21):2456–2464. https://doi.org/10.1161/circulationaha.112.114058

    Article  CAS  Google Scholar 

  • University_of_Alberta (2016) FooDB—the food component database. http://www.foodb.ca/. Accessed 11 Dec 2016

  • van der Hooft JJ, Wandy J, Barrett MP, Burgess KE, Rogers S (2016) Topic modeling for untargeted substructure exploration in metabolomics. Proc Natl Acad Sci U S A 113(48):13738–13743. https://doi.org/10.1073/pnas.1608041113

    Article  CAS  Google Scholar 

  • Verkleij-Hagoort AC, de Vries JHM, Stegers MPG, Lindemans J, Ursem NTC, Steegers-Theunissen RPM (2007) Validation of the assessment of folate and vitamin B-12 intake in women of reproductive age: the method of triads. Eur J Clin Nutr 61(5):610–615

    Article  CAS  Google Scholar 

  • Vioque J, Weinbrenner T, Asensio L, Castello A, Young IS, Fletcher A (2007) Plasma concentrations of carotenoids and vitamin C are better correlated with dietary intake in normal weight than overweight and obese elderly subjects. Br J Nutr 97(5):977–986

    Article  CAS  Google Scholar 

  • Wang Z, Klipfell E, Bennett BJ, Koeth R, Levison BS, DuGar B, Feldstein AE, Britt EB, Xiaoming F, Yoon-Mi C, Yuping W, Schauer P, Smith JD, Hooman A, Wilson Tang WH, DiDonato JA, Lusis AJ, Hazen SL (2011) Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472(7341):57–63

    Article  CAS  Google Scholar 

  • Willett WC (ed) (1998) Nutritional epidemiology, 2nd edn. Oxford University Press, Oxford

    Google Scholar 

  • Wittenbecher C, Muehlenbruch K, Kroeger J, Jacobs S, Kuxhaus O, Gel AF, Fritsche A, Pischon T, Prehn C, Adamski J, Joost H-G, Boeing H, Schulze MB (2015) Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes. Am J Clin Nutr 101(6):1241–1250. https://doi.org/10.3945/ajcn.114.099150

    Article  CAS  Google Scholar 

  • Wurtz P, Cook S, Wang Q, Tiainen M, Tynkkynen T, Kangas AJ, Soininen P, Laitinen J, Viikari J, Kahonen M, Lehtimaki T, Perola M, Blankenberg S, Zeller T, Mannisto S, Salomaa V, Jarvelin MR, Raitakari OT, Ala-Korpela M, Leon DA (2016) Metabolic profiling of alcohol consumption in 9778 young adults. Int J Epidemiol 45(5):1493–1506. https://doi.org/10.1093/ije/dyw175

    Article  Google Scholar 

  • Yao YY, Wang PG, Shao G, Del Toro LVA, Codero J, Giese RW (2016) Nontargeted analysis of the urine nonpolar sulfateome: a pathway to the nonpolar xenobiotic exposome. Rapid Commun Mass Spectrom 30(21):2341–2350. https://doi.org/10.1002/rcm.7726

    Article  CAS  Google Scholar 

  • Zain ME (2011) Impact of mycotoxins on humans and animals. J Saudi Chem Soc 15(2):129–144. https://doi.org/10.1016/j.jscs.2010.06.006

    Article  CAS  Google Scholar 

  • Zamora-Ros R, Urpi-Sarda M, Lamuela-Raventos RM, Estruch R, Martinez-Gonzalez MA, Bullo M, Aros F, Cherubini A, Andres-Lacueva C (2009) Resveratrol metabolites in urine as a biomarker of wine intake in free-living subjects: the PREDIMED Study. Free Radic Biol Med 46(12):1562–1566

    Article  CAS  Google Scholar 

  • Zamora-Ros R, Achaintre D, Rothwell JA, Rinaldi S, Assi N, Ferrari P, Leitzmann M, Boutron-Ruault M-C, Fagherazzi G, Auffret A, Kühn T, Katzke V, Boeing H, Trichopoulou A, Naska A, Vasilopoulou E, Palli D, Grioni S, Mattiello A, Tumino R, Ricceri F, Slimani N, Romieu I, Scalbert A (2016) Urinary excretions of 34 dietary polyphenols and their associations with lifestyle factors in the EPIC cohort study. Sci Rep 6:26905. https://doi.org/10.1038/srep26905

    Article  CAS  Google Scholar 

  • Zheng Y, Yu B, Alexander D, Steffen LM, Boerwinkle E (2014a) Human metabolome associates with dietary intake habits among African Americans in the atherosclerosis risk in communities study. Am J Epidemiol 179(12):1424–1433. https://doi.org/10.1093/aje/kwu073

    Article  Google Scholar 

  • Zheng Y, Yu B, Alexander D, Steffen LM, Nettleton JA, Boerwinkle E (2014b) Metabolomic patterns and alcohol consumption in African Americans in the Atherosclerosis Risk in Communities Study. Am J Clin Nutr 99(6):1470–1478. https://doi.org/10.3945/ajcn.113.074070

    Article  CAS  Google Scholar 

Download references

Conflict of Interest

Authors have no conflict of interest.

Acknowledgments

Support from the FoodBAll project funded by the BIO-NH call under the Joint Programming Initiative, “a Healthy Diet for a Healthy Life” (grant number 529051002), is acknowledged.

Author information

Authors and Affiliations

  1. Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC), Lyon, France

    Augustin Scalbert, Inge Huybrechts & Marc J. Gunter

Authors
  1. Augustin Scalbert
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Inge Huybrechts
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marc J. Gunter
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Augustin Scalbert .

Editor information

Editors and Affiliations

  1. Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK

    Sonia Dagnino

  2. The Johns Hopkins School of Medicine, Agilent Technologies, Baltimore, MD, USA

    Anthony Macherone

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Scalbert, A., Huybrechts, I., Gunter, M.J. (2019). The Food Exposome. In: Dagnino, S., Macherone, A. (eds) Unraveling the Exposome. Springer, Cham. https://doi.org/10.1007/978-3-319-89321-1_8

Download citation

Publish with us

Policies and ethics

Search

Navigation