The anserine to carnosine ratio: an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study

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Standard

The anserine to carnosine ratio : an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study. / Cuparencu, Catalina; Rinnan, Åsmund; Silvestre, Marta P; Poppitt, Sally D; Raben, Anne; Dragsted, Lars Ove.

I: European Journal of Nutrition, 03.04.2020.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Cuparencu, C, Rinnan, Å, Silvestre, MP, Poppitt, SD, Raben, A & Dragsted, LO 2020, 'The anserine to carnosine ratio: an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study', European Journal of Nutrition. https://doi.org/10.1007/s00394-020-02230-3

APA

Cuparencu, C., Rinnan, Å., Silvestre, M. P., Poppitt, S. D., Raben, A., & Dragsted, L. O. (2020). The anserine to carnosine ratio: an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study. European Journal of Nutrition. https://doi.org/10.1007/s00394-020-02230-3

Vancouver

Cuparencu C, Rinnan Å, Silvestre MP, Poppitt SD, Raben A, Dragsted LO. The anserine to carnosine ratio: an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study. European Journal of Nutrition. 2020 apr 3. https://doi.org/10.1007/s00394-020-02230-3

Author

Cuparencu, Catalina ; Rinnan, Åsmund ; Silvestre, Marta P ; Poppitt, Sally D ; Raben, Anne ; Dragsted, Lars Ove. / The anserine to carnosine ratio : an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study. I: European Journal of Nutrition. 2020.

Bibtex

@article{563930a762e64204a2a37c502beba942,
title = "The anserine to carnosine ratio: an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study",
abstract = "Background: Biomarkers of meat intake hold promise in clarifying the health effects of meat consumption, yet the differentiation between red and white meat remains a challenge. We measure meat intake objectively in a free-living population by applying a newly developed, three-step strategy for biomarker-based assessment of dietary intakes aimed to indicate if (1) any meat was consumed, (2) what type it was and (3) the quantity consumed.Methods: Twenty-four hour urine samples collected in a four-way crossover RCT and in a cross-sectional analysis of a longitudinal lifestyle intervention (the PREVIEW Study) were analyzed by untargeted LC–MS metabolomics. In the RCT, healthy volunteers consumed three test meals (beef, pork and chicken) and a control; in PREVIEW, overweight participants followed a diet with high or moderate protein levels. PLS-DA modeling of all possible combinations between six previously reported, partially validated, meat biomarkers was used to classify meat intake using samples from the RCT to predict consumption in PREVIEW.Results: Anserine best separated omnivores from vegetarians (AUROC 0.94–0.97), while the anserine to carnosine ratio best distinguished the consumption of red from white meat (AUROC 0.94). Carnosine showed a trend for dose–response between non-consumers, low consumers and high consumers for all meat categories, while in combination with other biomarkers the difference was significant.Conclusion: It is possible to evaluate red meat intake by using combinations of existing biomarkers of white and general meat intake. Our results are novel and can be applied to assess qualitatively recent meat intake in nutritional studies. Further work to improve quantitation by biomarkers is needed.",
keywords = "Dietary assessment, Biomarkers, Red meat, Anserine, Carnosine, Metabolomics",
author = "Catalina Cuparencu and {\AA}smund Rinnan and Silvestre, {Marta P} and Poppitt, {Sally D} and Anne Raben and Dragsted, {Lars Ove}",
note = "CURIS 2020 NEXS 116",
year = "2020",
month = "4",
day = "3",
doi = "10.1007/s00394-020-02230-3",
language = "English",
journal = "European Journal of Nutrition",
issn = "1436-6207",
publisher = "Springer Medizin",

}

RIS

TY - JOUR

T1 - The anserine to carnosine ratio

T2 - an excellent discriminator between white and red meats consumed by free-living overweight participants of the PREVIEW study

AU - Cuparencu, Catalina

AU - Rinnan, Åsmund

AU - Silvestre, Marta P

AU - Poppitt, Sally D

AU - Raben, Anne

AU - Dragsted, Lars Ove

N1 - CURIS 2020 NEXS 116

PY - 2020/4/3

Y1 - 2020/4/3

N2 - Background: Biomarkers of meat intake hold promise in clarifying the health effects of meat consumption, yet the differentiation between red and white meat remains a challenge. We measure meat intake objectively in a free-living population by applying a newly developed, three-step strategy for biomarker-based assessment of dietary intakes aimed to indicate if (1) any meat was consumed, (2) what type it was and (3) the quantity consumed.Methods: Twenty-four hour urine samples collected in a four-way crossover RCT and in a cross-sectional analysis of a longitudinal lifestyle intervention (the PREVIEW Study) were analyzed by untargeted LC–MS metabolomics. In the RCT, healthy volunteers consumed three test meals (beef, pork and chicken) and a control; in PREVIEW, overweight participants followed a diet with high or moderate protein levels. PLS-DA modeling of all possible combinations between six previously reported, partially validated, meat biomarkers was used to classify meat intake using samples from the RCT to predict consumption in PREVIEW.Results: Anserine best separated omnivores from vegetarians (AUROC 0.94–0.97), while the anserine to carnosine ratio best distinguished the consumption of red from white meat (AUROC 0.94). Carnosine showed a trend for dose–response between non-consumers, low consumers and high consumers for all meat categories, while in combination with other biomarkers the difference was significant.Conclusion: It is possible to evaluate red meat intake by using combinations of existing biomarkers of white and general meat intake. Our results are novel and can be applied to assess qualitatively recent meat intake in nutritional studies. Further work to improve quantitation by biomarkers is needed.

AB - Background: Biomarkers of meat intake hold promise in clarifying the health effects of meat consumption, yet the differentiation between red and white meat remains a challenge. We measure meat intake objectively in a free-living population by applying a newly developed, three-step strategy for biomarker-based assessment of dietary intakes aimed to indicate if (1) any meat was consumed, (2) what type it was and (3) the quantity consumed.Methods: Twenty-four hour urine samples collected in a four-way crossover RCT and in a cross-sectional analysis of a longitudinal lifestyle intervention (the PREVIEW Study) were analyzed by untargeted LC–MS metabolomics. In the RCT, healthy volunteers consumed three test meals (beef, pork and chicken) and a control; in PREVIEW, overweight participants followed a diet with high or moderate protein levels. PLS-DA modeling of all possible combinations between six previously reported, partially validated, meat biomarkers was used to classify meat intake using samples from the RCT to predict consumption in PREVIEW.Results: Anserine best separated omnivores from vegetarians (AUROC 0.94–0.97), while the anserine to carnosine ratio best distinguished the consumption of red from white meat (AUROC 0.94). Carnosine showed a trend for dose–response between non-consumers, low consumers and high consumers for all meat categories, while in combination with other biomarkers the difference was significant.Conclusion: It is possible to evaluate red meat intake by using combinations of existing biomarkers of white and general meat intake. Our results are novel and can be applied to assess qualitatively recent meat intake in nutritional studies. Further work to improve quantitation by biomarkers is needed.

KW - Dietary assessment

KW - Biomarkers

KW - Red meat

KW - Anserine

KW - Carnosine

KW - Metabolomics

U2 - 10.1007/s00394-020-02230-3

DO - 10.1007/s00394-020-02230-3

M3 - Journal article

C2 - 32246262

JO - European Journal of Nutrition

JF - European Journal of Nutrition

SN - 1436-6207

ER -

ID: 239563127