Dietary Biomarkers

The current dietary assessment instruments such as food frequency questionnaires, dietary records, recalls etc. are flawed by their lack of objectivity. 

This may result in too vague relationships of dietary intakes with health outcomes. Development and implementation of objective tools for dietary assessment is therefore important for the nutrition research area.

This could solve two purposes:

• To test compliance, i.e. whether a volunteer consumed what was planned and agreed according to the study design. This is important for nutritional trials, since identifying non-compliance allows for handling of statistics in a proper way.
• To assess if volunteers in nutrition studies report their food intake accurately. This is an issue in all studies, both observational and experimental. Forgetfulness, lack of knowledge about foods, and biased dietary recordings are probably the most important factors affecting accuracy of subjective assessments.

In the Dietary Biomarkers group, we are working on practical solutions to overcome current challenges and bring biomarkers of food intake into use for compliance testing and for quantitative assessment of food intakes. 

Ideally, each food consumed would leave a traceable set of unique biomarkers of intake. A good biomarker of intake for a food is a substance originating only from the food in question and not from other foods or other exposures.

The biomarker should be quantifiable in a biological sample, e.g. blood, urine, feces, hair etc. A biomarker analysis would then give the straight answer whether the food component was consumed or not and preferably also how much was consumed.

Of course, biomarkers have limitations, e.g. fast excretion, stability issues, or inter-individually variable metabolism, so the time and frequency of intake and of biological sampling are important characteristics to consider.

Dragsted LO, Gao Q, Scalbert A, Vergères G, Kolehmainen M, Manach C, Brennan L, Afman LA, Wishart DS, Andres-Lacueva C, Garcia-Aloy M, Verhagen H, Feskens EJM, Praticò G (2018) Validation of food intake biomarkers - critical assessment of candidate biomarkers. Genes Nutr. (online) 13:14; https://doi.org/10.1186/s12263-018-0603-9

Gao Q, Prático G, Scalbert A, Vergéres G, Kolehmainen M, Manach C, Brennan L, Afman LA, Wishart DS, Andres-Lacueva C, Garcia-Aloy M, Verhagen H, Dragsted LO (2017) A scheme for a flexible classification of dietary and health biomarkers. Genes Nutr. 12:34. doi: 10.1186/s12263-017-0587-x

Andersen, M.B.; Rinnan, A.; Manach, C.; Poulsen, S.K.; Pujos-Guillot, E.; Larsen, T.M.; Astrup, A.; Dragsted, L.O. (2014) Untargeted metabolomics as a screening tool for estimating compliance to a dietary pattern. J. Proteome Res. (13:3) 1405-1418 dx.doi.org/10.1021/pr400964s.

Gürdeniz G, Uusitupa M, Hermansen K, Savolainen MJ, Schwab U, Kolehmainen M, Brader L, Cloetens L, Herzig K-H, Hukkanen J, Rosqvist F, Ulven SM, Gunnarsdóttir I, Thorsdottir I, Oresic M, Poutanen KS, Riserus  U, Åkesson B, Dragsted LO (2022) Analysis of the SYSDIET Healthy Nordic Diet randomized trial based on metabolic profiling reveals beneficial effects on glucose metabolism and blood lipids. Clin Nutr. 41 441-451. https://doi.org/10.1016/j.clnu.2021.12.031

Cuparencu C, Rinnan Å, Silvestre MP, Poppitt SD, Raben A, Dragsted LO (2021) The anserine to carnosine ratio – an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study. Eur. J. Nutr. (60, 1) 179-192. https://doi.org/10.1007/s00394-020-02230-3

Publications

Trius-Soler M, Praticó G, Gürdeniz G, Garcia-Aloy M, Canali R, Fausta N, Brouwer-Bolsma EM, Andrés-Lacueva C, Dragsted LO (2023) Biomarkers for alcoholic beverages and moderate alcohol intake: a systematic literature review. Genes Nutr. https://doi.org/10.1186/s12263-023-00728-z

Trimigno A, Khakimov B, Rasmussen MA, Dragsted LO, Larsen TM, Astrup A, Engelsen S (2023) Human blood plasma biomarkers of diet and weight loss among  centrally obese subjects in a New Nordic Diet intervention. Frontiers Nutr. (accepted) ID 1198531.

Balech B, Brennan L, Carrillo de Santa Pau E, Cavalieri D, Coort S, D’Elia D, Dragsted LO, Eftimov T, Evelo CT, Ferk P, Finglas P, Gori A, Hancock J, Kalaš M, Seljak BK, Lachat C, Leskošek B, Pasolli E, Pesole G, Presser K, Sandionigi A, Santamaria M, Şener DD, Traka M, Vergères G, Zimmermann K, Bouwman J (2022) The future of food and nutrition in ELIXIR F1000Research 11(ELIXIR):978 (online for open peer review: https://doi.org/10.12688/f1000research.51747.1)

Gürdeniz G, Uusitupa M, Hermansen K, Savolainen MJ, Schwab U, Kolehmainen M, Brader L, Cloetens L, Herzig K-H, Hukkanen J, Rosqvist F, Ulven SM, Gunnarsdóttir I, Thorsdottir I, Oresic M, Poutanen KS, Riserus  U, Åkesson B, Dragsted LO (2022) Analysis of the SYSDIET Healthy Nordic Diet randomized trial based on metabolic profiling reveals beneficial effects on glucose metabolism and blood lipids. Clin Nutr. 41 441-451. https://doi.org/10.1016/j.clnu.2021.12.031

Xi M, La Barbera G, Eriksen JN, Prahm AP, Arrigoni E, Jeppesen PB, Dragsted LO (2021) Discovery of urinary biomarkers of spinach consumption using untargeted LC-MS metabolomics in a human intervention trial. Mol. Nutr. Food Res. (online) https://doi.org/10.1002/mnfr.202100260.

Xi M, Berendsen AAM, Ernst M, Hu T, Vazquez-Manjarrez N, Feskens EJM, Dragsted LO, La Barbera G (2021) Combined urinary biomarkers to assess coffee intake using untargeted metabolomics: discovery in three pilot human intervention studies and validation in cross-sectional studies. J. Agric. Food Chem. (69,25) 7230-7242 https://doi.org/10.1021/acs.jafc.1c01155.

Xi M, Dragsted LO, Tullin M, Ernst M, Zaharudin N, La Barbera G (2021) Discovery of Urinary Biomarkers of Seaweed Intake Using Untargeted LC–MS Metabolomics in a Three-Way Cross-Over Human Study. Metabolites 11, 1 https://dx.doi.org/10.3390/metabo11010011  

Zhou X, Ulaszewska MM, De Gobba C, Rinnan Å, Poulsen MW, Chen J, Mattivi F, Hedegaard RV, Skibsted LH, Dragsted LO (2021) New advanced glycation end products observed in rat urine by untargeted metabolomics after feeding with heat-treated skimmed milk powder. Mol. Nutr. Food Res. (online). e2001049. https://doi.org/10.1002/mnfr.202001049.

Vázquez-Manjarrez N, Ulaszewska M, García-Aloy M, Mattivi F, Praticò G, Dragsted LO, Manach C (2020) Biomarkers of intake for banana and tropical fruits. Genes Nutr. (15) 1-11. https://doi.org/10.1186/s12263-020-00670-4  

Trimigno A, Khakimov B, Savorani F, Poulsen SK, Astrup A, Dragsted LO, Engelsen SB (2020) Human urine 1H NMR metabolomics reveals alterations of the protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet. Nutrients. (79-80) 110867 https://doi.org/10.1016/j.nut.2020.110867  

Dragsted LO (2020) The metabolic nature of individuality. Nature Food (1; June 2020) 327-329. https://doi.org/10.1038/s43016-020-0104-z

Zhou X; Ulaszewska MM; Cuparencu C; De Gobba C; Vazquez Manjarrez N; Gurdeniz G; Chen J; Mattivi F; Dragsted LO (2020) Urine metabolome profiling reveals imprints of food heating processes after dietary intervention with differently cooked potatoes. J. Agric. Food Chem. (68, 22)6122-6131. https://doi.org/10.1021/acs.jafc.0c01136

Cuparencu C, Rinnan Å, Silvestre MP, Poppitt SD, Raben A, Dragsted LO (2021) The anserine to carnosine ratio – an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study. Eur. J. Nutr. (60, 1) 179-192. https://doi.org/10.1007/s00394-020-02230-3

Meslier V, Laiola M, Roager HM, De Filippis F, Roume H, Quinquis B, Giacco R, Mennella I, Ferracane R, Pons N, Pasolli E, Rivellese AA, Dragsted LO, Vitaglione P, Ehrlich DS, Ercolini D (2020) Mediterranean diet intervention in overweight and obese subjects leads to multiple beneficial shifts in gut microbiome and metabolome independently from energy intake. Gut (69, 7) 1258-68. https://doi.org/10.1136/gutjnl-2019-320438

Cuparencu C, Pratico G, Hemeryck LY, Sri Harsha PSC, Noerman S, Rombouts C, Xi M, Vanhaecke L, Hanhineva K, Brennan,L, Dragsted LO (2019) Biomarkers of meat and seafood intake: an extensive literature review. Genes and Nutrition 14;35 https://doi.org/10.1186/s12263-019-0656-4

Xi M, Dragsted LO (2019) Biomarkers of seaweed intake. Genes Nutr. 14:24. https://doi.org/10.1186/s12263-019-0648-4  

Pekmez CT, Bjørnshave A, Práticó G, Hermansen K, Dragsted LO (2019) Premeal protein intake alters postprandial plasma metabolome in subjects with metabolic syndrome. Eur. J. Nutr. (59,5) 1181-94 https://doi.org/10.1007/s00394-019-02039-9   

Vazquez-Manjarrez N, Weinert CH, Ulaszewska MM, Mack CI, Micheau P, Pétéra M, Durand S, Pujot-Guillot E, Egert B, Mattivi F, Bub A, Dragsted LO, Kulling SE, Manach C (2019) Discovery and Validation of Banana Intake Biomarkers Using  Untargeted Metabolomics in Human Intervention and Cross-sectional Studies. J. Nutr. (149,10) 1701-13 https://doi.org/10.1093/jn/nxz125  

Maruvada P, Lampe J, Wishart DS, Barupal D, Chester DN, Dodd D, Djoumbou-Feunang Y, Dorrestein PC, Dragsted LO, Draper D, Duffy LC, Dwyer JT, Emenaker NJ, Fiehn O, Gerszten RE, Hu F, Karp RW, Klurfeld DM, Laughlin MR, Little AR, Lynch CJ, Moore SC, Nicastro HL, O’Brien DM, Ordóvas JM, Osganian SK, Playdon M, Prentice R, Raftery D, Reisdorph N, Roche HM, Ross SA, Sang S, Scalbert A, Srinivas PR, Zeisel SH (2019) Perspective: Dietary Biomarkers of Intake and Exposure: Exploration with Omics Approaches. Adv. Nutr. (11, 2) 200-211. https://doi.org/5544358[pii];10.1093/advances/nmz075

Cuparencu C, Rinnan Å & Dragsted LO (2019) Combined markers to assess meat intake - human metabolomic studies of discovery and validation. Mol. Nutr. Food Res. (63)17  e1900106. https://doi.org/10.1002/mnfr.201900106

Zhou X, Gao Q, Pratico G, Chen J & Dragsted LO (2019) Biomarkers of tuber intake. Genes Nutr. 14:9. https://doi.org/10.1186/s12263-019-0631-0

Acar E, Gurdeniz G, Khakimov B, Savorani F, Korndal SK, Larsen TM, Engelsen SB, Astrup A, Dragsted LO (2019) Biomarkers of Individual Foods, and Separation of Diets Using Untargeted LC-MS Based Plasma Metabolomics in a Randomized Controlled Trial. Mol. Nutr. Food Res. 63(1): e1800215 https://doi.org/10.1002/mnfr.201800215

Praticò G, Gao Q, Manach C & Dragsted LO (2018) Biomarkers of food intake for Allium vegetables. Genes Nutr. 13:34. DOI: 10.1186/s12263-018-0624-4

Ulaszewska M, Vázquez Manjarrez N, Garcia-Aloy M, Llorach R, Mattivi F, Dragsted LO, Pratico G. & Manach C (2018) Food intake biomarkers for apple, pear, and stone fruit Genes Nutr. 13:29. DOI: 10.1186/s12263-018-0620-8

Rothwell JA, Madrid-Gamblin F, Garcia-Aloy M, Andres-Lacueva C, Logue C, Gallagher AM, Mack C, Kulling SE, Gao QW, Praticó G, Dragsted LO, Scalbert A, (2018) Biomarkers of intake for coffee, tea and sweetened beverages. Genes & Nutr. 13:15; doi: 10.1186/s12263-018-0607-5. DOI: 10.1186/s12263-018-0607-5

Dragsted LO, Gao Q, Scalbert A, Vergères G, Kolehmainen M, Manach C, Brennan L, Afman LA, Wishart DS, Andres-Lacueva C, Garcia-Aloy M, Verhagen H, Feskens EJM, Praticò G (2018) Validation of food intake biomarkers - critical assessment of candidate biomarkers. Genes Nutr. (online) 13:14; https://doi.org/10.1186/s12263-018-0603-9

Pratico G, Gao Q, Scalbert A, Vergeres G, Kolehmainen M, Manach C, Brennan L, Sri Harsha PSC, Afman LA, Wishart DS, Vazquez-Fresno R, Lacueva CA, Garcia-Aloy M, Verhagen H, Feskens EJM, Dragsted LO (2018) Guidelines for Biomarker of Food Intake Reviews (BFIRev): how to conduct an extensive literature search for biomarker of food intake discovery. Genes Nutr. 13:3; DOI: 10.1186/s12263-018-0592-8

Sri Harsha PSC, Wahab RA, Cuparencu C, Dragsted LO & Brennan L (2018) A metabolomics approach to the identification of urinary biomarkers of pea intake. Nutrients 10:12. 10.3390/nu10121911 [doi]

Gao Q, Prático G, Scalbert A, Vergéres G, Kolehmainen M, Manach C, Brennan L, Afman LA, Wishart DS, Andres-Lacueva C, Garcia-Aloy M, Verhagen H, Dragsted LO (2017) A scheme for a flexible classification of dietary and health biomarkers. Genes Nutr. 12:34. doi: 10.1186/s12263-017-0587-x

Dragsted LO, Gao Q, Pratico G, Manach C, Wishart D, Scalbert A, Feskens EJM (2017) Dietary and health biomarkers - time for an update. Genes Nutr. 12:24 DOI: 10.1186/s12263-017-0578-y

Brouwer-Brolsma E, Brennan L, Drevon CA, van Kanen H, Manach M, Dragsted LO, Roche HM, Andres-Lacueva C, Bakker SJL, Bouwman J, Capozzi F, De Saeger S, Gundersen TE, Kolehmainen M, Kulling S, Landberg R, Linseisen J, Mattivi F, Mensink RP, Scaccini C, Skurk T, Tetens I, Vergeres G, Wishart D, Scalbert A, Feskens EJM (2017) Combining traditional dietary assessment methods with novel metabolomics techniques: Current efforts by the Food Biomarker Alliance. Proc. Nutr. Soc. (76:4) 619-627.

Dragsted, L.O. (2017) Relying on biomarkers for intake assessment in nutrition Amer. J. Clin. Nutr. 105(1); 8-9

Eriksen, J.N., Madsen, P. Dragsted, L.O., Arrigoni, E. (2017) Optimized, fast-throughput UHPLC-DAD based method for carotenoid quantification in spinach, serum, chylomicrons, and faeces. J. Agric. Food Chem. 65,4 973-980

Monosik, R., Dragsted, L.O. (2016) Versatile UHPLC–MSMS method for simultaneous quantification of various alcohol intake related compounds in human urine and blood. Analytical Methods, 8, 6865 – 6871

Gürdeniz G, Jensen MG, Meier S, Bech L, Lund E, Dragsted LO. (2016) Detecting beer intake by unique m 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; 1939-54.etabolite patterns. J.Proteome Res. 15, 4544−4556.

Cuparencu, C.S., Andersen, M-B.S., Gürdeniz, G., Schou, S.S., Mortensen, M.W., Raben, A., Astrup, A., Dragsted, L.O. (2015) Identification of urinary biomarkers after consumption of sea buckthorn and strawberry, by untargeted LC-MS metabolomics: a meal study in adult men. Metabolomics 12:31 doi: 10.1007/s11306-015-0934-0

Souverein, O., de Vries, J.H.M., Freese, F., Watzl, B., Bub, A., Miller III, E.R., Castenmiller, J.J.M., Pasman, W.J., van het Hof, K.,Chopra, M., Karlsen, A., Dragsted, L.O., Winkels, R., Itsiopoulos, C., Brazionis, L., O’Dea, K., van Loo-Bouwman,C.A., Naber, T.N.J., van der Voet H., Boshuizen, H.C. (2015) Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies. Br. J. Nutr. 113(9); 1396-1409

Marklund, M., Magnusdottir, O.K., Rosqvist, F.,, Cloetens, L., Landberg, R., Kolehmainen, M., Brader, L., Hermansen, K., Poutanen, K.S., Herzig, K-H., Hukkanen, J., Savolainen, M.J., Dragsted, L.O., Schwab, U., Paananen, J., Uusitupa, M., Åkesson, B., Thorsdottir, I., Risérus, U. (2014) A dietary biomarker approach captures compliance and cardiometabolic effects of a healthy nordic diet in individuals with metabolic syndrome J. Nutr. 144(10) 1642-1649

Scalbert A., Brennan L., Manach C., Andres-Lacueva C, Dragsted L.O., Draper J., Rappaport S.M., van der Hooft J.J.J., Wishart D.S. (2014) The Food Metabolome: a window over dietary exposure. Amer. J. Clin. Nutr. 99(6) 1286-1308.

Hjerpsted, J.B., Ritz, C., Schou, S.S., Tholstrup, T., Dragsted, L.O. (2014) Effect of cheese and butter intake on metabolites in urine using a non-targeted metabolomics approach. Metabolomics (10:6) 1176-1185.

Andersen, M.B., Kristensen, M.; Manach, C.; Pujos-Guillot, E.; Poulsen, S.K.; Larsen, T.M.; Astrup, A.; Dragsted, L.O. (2014) Discovery and validation of urinary exposure markers for different plant foods by untargeted metabolomics. Anal.Bioanal.Chem. (406:7) 1829-1844 DOI 10.1007/s00216-013-7498-5.

Andersen, M.B.; Rinnan, A.; Manach, C.; Poulsen, S.K.; Pujos-Guillot, E.; Larsen, T.M.; Astrup, A.; Dragsted, L.O. (2014) Untargeted metabolomics as a screening tool for estimating compliance to a dietary pattern. J. Proteome Res. (13:3) 1405-1418 dx.doi.org/10.1021/pr400964s.

Knudsen, M.D., Kyrø, C., Olsen, A., Dragsted, L.O., Dkeie, G., Lund, E., Åman, P., Nilsson, L.M., Bueno-de-Mesquita, H.B., Overvad, K., Tjønneland, A., Landberg, R. (2014) Self-reported whole-grain intake and plasma alkylresorcinol concentrations in combination in the relation to incidence of colorectal cancer. Amer. J. Epidemiol. (179:10) 1188-1196  DOI: 10.1093/aje/kwu031

Gürdeniz, G., Rago., D., Bendsen, N.T., Savorani, F., Astrup, A., Dragsted, L.O. (2013) Effect of trans fatty acid intake on LC-MS and NMR plasma profiles PLoS One (8,7) e69589

Rago, D., Kristensen, M., Gürdeniz, G., Marini, F., Poulsen, M., Dragsted, L.O. (2013) A LC-MS metabolomics approach to investigate the effect of raw apple intake in the rat plasma metabolome. Metabolomics (9,6) 1202-1215.

Johansson-Persson, A., Barri, T., Ulmius, M., Önning, G., and Dragsted, L.O. (2013) LC-QTOF/MS metabolomic profiles in human plasma after a 5-week high dietary fiber intake. Analytical and Bioanalytical Chemistry (405:14) 4799-4809 DOI: 10.1007/s00216-013-6874-5

Andersen, M-B.S., Reinbach, H.C., Rinnan, Å., Barri, T., Mithril, C.E., Dragsted, L.O. (2013) Discovery of exposure markers in urine for Brassica-containing meals served with different protein sources by UPLC-qTOF-MS untargeted metabolomics. Metabolomics (9) 984–997. DOI 10.1007/s11306-013-0522-0.

Bondia-Pons, I., Barri, T., Hanhineva, K., Juntunen, K., Dragsted, L.O., Mykkänen, H., Poutanen, K. (2013) UPLC-QTOF/MS Metabolic Profiling Unveils Urinary Changes in Humans after a Whole Grain Rye versus Refined Wheat Bread Intervention. Mol. Nutr. Food Res. (57,3) 412-422.

Rasmussen, L.G., Winning,H., Savorani, F., Toft, H., Larsen, T.M.,  Dragsted, L.O., Astrup, A., and Engelsen,S.B. (2012) Assessment of the effect of high or low protein diet on the human urine metabolome by NMR. Nutrients (4,2) 112-131.

Rasmussen, L.G., Winning, H., Savorani, F., Ritz, C., Engelsen, S.B. , Astrup, A., Larsen, T.M., and Dragsted, L.O. (2011) Assessment of dietary exposure related to dietary GI and fibre intake in a nutritional metabolomic study of human urine. Genes Nutr. (7) 281-293

Rasmussen, L.G., Savorani, F., Larsen, T.M., Dragsted, L.O., Astrup, A., and  Engelsen, S.B. (2011) Standardization of factors that influence human urine. Metabolomics 7:71–83

Kristensen, M., Engelsen S.B., and Dragsted, L.O. (2012) LC-MS metabolomics top-down approach reveals new exposure and effect biomarkers of apple and apple-pectin intake. Metabolomics 8,1 64-73

Winning, H., Roldán-Marín, E., Dragsted, L.O., Viereck, N., Poulsen, M.,Sánchez-Moreno, C., Cano, M.P., Engelsen, S.B. (2009) An exploratory NMR nutri-metabonomic investigation reveals dimethylsulfone as a dietary biomarker for onion intake. Analyst, 134, 2344-2351