Literature DB >> 23452466

Identification of biomarkers for intake of protein from meat, dairy products and grains: a controlled dietary intervention study.

Wieke Altorf-van der Kuil1, Elizabeth J Brink, Martine Boetje, Els Siebelink, Sabina Bijlsma, Marielle F Engberink, Pieter van 't Veer, Daniel Tomé, Stephan J L Bakker, Marleen A van Baak, Johanna M Geleijnse.   

Abstract

In the present controlled, randomised, multiple cross-over dietary intervention study, we aimed to identify potential biomarkers for dietary protein from dairy products, meat and grain, which could be useful to estimate intake of these protein types in epidemiological studies. After 9 d run-in, thirty men and seventeen women (22 (SD 4) years) received three high-protein diets (aimed at approximately 18% of energy (en%)) in random order for 1 week each, with approximately 14 en% originating from either meat, dairy products or grain. We used a two-step approach to identify biomarkers in urine and plasma. With principal component discriminant analysis, we identified amino acids (AA) from the plasma or urinary AA profile that were distinctive between diets. Subsequently, after pooling total study data, we applied mixed models to estimate the predictive value of those AA for intake of protein types. A very good prediction could be made for the intake of meat protein by a regression model that included urinary carnosine, 1-methylhistidine and 3-methylhistidine (98% of variation in intake explained). Furthermore, for dietary grain protein, a model that included seven AA (plasma lysine, valine, threonine, α-aminobutyric acid, proline, ornithine and arginine) made a good prediction (75% of variation explained). We could not identify biomarkers for dairy protein intake. In conclusion, specific combinations of urinary and plasma AA may be potentially useful biomarkers for meat and grain protein intake, respectively. These findings need to be cross-validated in other dietary intervention studies.

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Year:  2013        PMID: 23452466     DOI: 10.1017/S0007114512005788

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  18 in total

1.  Postprandial Responses on Serum Metabolome to Milk and Yogurt Intake in Young and Older Men.

Authors:  Jinyoung Kim; Carola Blaser; Reto Portmann; René Badertscher; Corinne Marmonier; Adeline Blot; Jérémie David; Helena Stoffers; Ueli von Ah; Ueli Bütikofer; Guy Vergères; Dominique Dardevet; Sergio Polakof
Journal:  Front Nutr       Date:  2022-05-04

2.  A Newly Developed Indicator of Overeating Saturated Fat Based on Serum Fatty Acids and Amino Acids and Its Association With Incidence of Type 2 Diabetes: Evidence From Two Randomized Controlled Feeding Trials and a Prospective Study.

Authors:  Wei Wei; Tianqi Zi; Ruiming Yang; Jiaxu Xu; Yunyan Chen; XiTao Jiang; Xia Chu; Xue Yang; Wenbo Jiang
Journal:  Front Nutr       Date:  2022-06-14

3.  Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children.

Authors:  Sergey A Krupenko; Shelley A Cole; Ruixue Hou; Karin Haack; Sandra Laston; Nitesh R Mehta; Anthony G Comuzzie; Nancy F Butte; V Saroja Voruganti
Journal:  Am J Clin Nutr       Date:  2022-08-04       Impact factor: 8.472

4.  Urinary metabolic signatures of human adiposity.

Authors:  Paul Elliott; Joram M Posma; Queenie Chan; Isabel Garcia-Perez; Anisha Wijeyesekera; Magda Bictash; Timothy M D Ebbels; Hirotsugu Ueshima; Liancheng Zhao; Linda van Horn; Martha Daviglus; Jeremiah Stamler; Elaine Holmes; Jeremy K Nicholson
Journal:  Sci Transl Med       Date:  2015-04-29       Impact factor: 17.956

5.  Identification of Urinary Polyphenol Metabolite Patterns Associated with Polyphenol-Rich Food Intake in Adults from Four European Countries.

Authors:  Hwayoung Noh; Heinz Freisling; Nada Assi; Raul Zamora-Ros; David Achaintre; Aurélie Affret; Francesca Mancini; Marie-Christine Boutron-Ruault; Anna Flögel; Heiner Boeing; Tilman Kühn; Ruth Schübel; Antonia Trichopoulou; Androniki Naska; Maria Kritikou; Domenico Palli; Valeria Pala; Rosario Tumino; Fulvio Ricceri; Maria Santucci de Magistris; Amanda Cross; Nadia Slimani; Augustin Scalbert; Pietro Ferrari
Journal:  Nutrients       Date:  2017-07-25       Impact factor: 5.717

6.  Increased plasma proline concentrations are associated with sarcopenia in the elderly.

Authors:  Kenji Toyoshima; Marie Nakamura; Yusuke Adachi; Akira Imaizumi; Tomomi Hakamada; Yasuko Abe; Eiji Kaneko; Soiciro Takahashi; Kentaro Shimokado
Journal:  PLoS One       Date:  2017-09-21       Impact factor: 3.240

7.  Effect of Cod Residual Protein Supplementation on Markers of Glucose Regulation in Lean Adults: A Randomized Double-Blind Study.

Authors:  Iselin Vildmyren; Alfred Halstensen; Adrian McCann; Øivind Midttun; Per Magne Ueland; Åge Oterhals; Oddrun Anita Gudbrandsen
Journal:  Nutrients       Date:  2020-05-16       Impact factor: 5.717

Review 8.  Biomarkers of cereal food intake.

Authors:  Rikard Landberg; Kati Hanhineva; Kieran Tuohy; Mar Garcia-Aloy; Izabela Biskup; Rafael Llorach; Xiaofei Yin; Lorraine Brennan; Marjukka Kolehmainen
Journal:  Genes Nutr       Date:  2019-10-12       Impact factor: 5.523

Review 9.  Biomarkers of meat and seafood intake: an extensive literature review.

Authors:  Cătălina Cuparencu; Giulia Praticó; Lieselot Y Hemeryck; Pedapati S C Sri Harsha; Stefania Noerman; Caroline Rombouts; Muyao Xi; Lynn Vanhaecke; Kati Hanhineva; Lorraine Brennan; Lars O Dragsted
Journal:  Genes Nutr       Date:  2019-12-30       Impact factor: 5.523

Review 10.  A Scoping Review: Metabolomics Signatures Associated with Animal and Plant Protein Intake and Their Potential Relation with Cardiometabolic Risk.

Authors:  Gaïa Lépine; Hélène Fouillet; Didier Rémond; Jean-François Huneau; François Mariotti; Sergio Polakof
Journal:  Adv Nutr       Date:  2021-12-01       Impact factor: 11.567

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