Population-based nutrikinetic modelling of phytochemical exposure

E.J.J. van Velzen, J.A. Westerhuis, C.H. Grün, J.P.M. van Duynhoven, D.M. Jacobs, P.H.C. Eilers, T.P. Mulder, M. Foltz, U. Garczarek, R. Kemperman, E.E. Vaughan, A.K. Smilde

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Scopus)

Abstract

The beneficial health effects of fruits and vegetables have been attributed to their polyphenol content. These compounds undergo many bioconversions in the body. Modeling polyphenol exposure of humans upon intake is a prerequisite for understanding the modulating effect of the food matrix and the colonic microbiome. This modeling is not a trivial task and requires a careful integration of measuring techniques, modeling methods and experimental design. Moreover, both at the population level as well as the individual level polyphenol exposure has to be quantified and assessed. We developed a strategy to quantify polyphenol exposure based on the concept of nutrikinetics in combination with population-based modeling. The key idea of the strategy is to derive nutrikinetic model parameters that summarize all information of the polyphenol exposure at both individual and population level. This is illustrated by a placebo-controlled crossover study in which an extract of wine/grapes and black tea solids was administered to twenty subjects. We show that urinary and plasma nutrikinetic time-response curves can be used for phenotyping the gut microbial bioconversion capacity of individuals. Each individual harbours an intrinsic microbiota composition converting similar polyphenols from both test products in the same manner and stable over time. We demonstrate that this is a novel approach for associating the production of two gut-mediated ¿-valerolactones to specific gut phylotypes. The large inter-individual variation in nutrikinetics and ¿-valerolactones production indicated that gut microbial metabolism is an essential factor in polyphenol exposure and related potential health benefits
Original languageEnglish
Pages (from-to)1059-1073
JournalMetabolomics
Volume10
Issue number6
DOIs
Publication statusPublished - 2014

Fingerprint

Phytochemicals
Polyphenols
Population
Bioconversion
Microbiota
Health
Wine
Vitis
Vegetables
Insurance Benefits
Tea
Ports and harbors
Fruits
Metabolism
Design of experiments
Cross-Over Studies
Fruit
Research Design
Placebos
Plasmas

Keywords

  • red wine/grape juice
  • black tea
  • dietary polyphenols
  • phenolic metabolites
  • nutrition research
  • food sources
  • human plasma
  • green tea
  • gut model
  • pharmacokinetics

Cite this

van Velzen, E. J. J., Westerhuis, J. A., Grün, C. H., van Duynhoven, J. P. M., Jacobs, D. M., Eilers, P. H. C., ... Smilde, A. K. (2014). Population-based nutrikinetic modelling of phytochemical exposure. Metabolomics, 10(6), 1059-1073. https://doi.org/10.1007/s11306-014-0645-y
van Velzen, E.J.J. ; Westerhuis, J.A. ; Grün, C.H. ; van Duynhoven, J.P.M. ; Jacobs, D.M. ; Eilers, P.H.C. ; Mulder, T.P. ; Foltz, M. ; Garczarek, U. ; Kemperman, R. ; Vaughan, E.E. ; Smilde, A.K. / Population-based nutrikinetic modelling of phytochemical exposure. In: Metabolomics. 2014 ; Vol. 10, No. 6. pp. 1059-1073.
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van Velzen, EJJ, Westerhuis, JA, Grün, CH, van Duynhoven, JPM, Jacobs, DM, Eilers, PHC, Mulder, TP, Foltz, M, Garczarek, U, Kemperman, R, Vaughan, EE & Smilde, AK 2014, 'Population-based nutrikinetic modelling of phytochemical exposure', Metabolomics, vol. 10, no. 6, pp. 1059-1073. https://doi.org/10.1007/s11306-014-0645-y

Population-based nutrikinetic modelling of phytochemical exposure. / van Velzen, E.J.J.; Westerhuis, J.A.; Grün, C.H.; van Duynhoven, J.P.M.; Jacobs, D.M.; Eilers, P.H.C.; Mulder, T.P.; Foltz, M.; Garczarek, U.; Kemperman, R.; Vaughan, E.E.; Smilde, A.K.

In: Metabolomics, Vol. 10, No. 6, 2014, p. 1059-1073.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Population-based nutrikinetic modelling of phytochemical exposure

AU - van Velzen, E.J.J.

AU - Westerhuis, J.A.

AU - Grün, C.H.

AU - van Duynhoven, J.P.M.

AU - Jacobs, D.M.

AU - Eilers, P.H.C.

AU - Mulder, T.P.

AU - Foltz, M.

AU - Garczarek, U.

AU - Kemperman, R.

AU - Vaughan, E.E.

AU - Smilde, A.K.

PY - 2014

Y1 - 2014

N2 - The beneficial health effects of fruits and vegetables have been attributed to their polyphenol content. These compounds undergo many bioconversions in the body. Modeling polyphenol exposure of humans upon intake is a prerequisite for understanding the modulating effect of the food matrix and the colonic microbiome. This modeling is not a trivial task and requires a careful integration of measuring techniques, modeling methods and experimental design. Moreover, both at the population level as well as the individual level polyphenol exposure has to be quantified and assessed. We developed a strategy to quantify polyphenol exposure based on the concept of nutrikinetics in combination with population-based modeling. The key idea of the strategy is to derive nutrikinetic model parameters that summarize all information of the polyphenol exposure at both individual and population level. This is illustrated by a placebo-controlled crossover study in which an extract of wine/grapes and black tea solids was administered to twenty subjects. We show that urinary and plasma nutrikinetic time-response curves can be used for phenotyping the gut microbial bioconversion capacity of individuals. Each individual harbours an intrinsic microbiota composition converting similar polyphenols from both test products in the same manner and stable over time. We demonstrate that this is a novel approach for associating the production of two gut-mediated ¿-valerolactones to specific gut phylotypes. The large inter-individual variation in nutrikinetics and ¿-valerolactones production indicated that gut microbial metabolism is an essential factor in polyphenol exposure and related potential health benefits

AB - The beneficial health effects of fruits and vegetables have been attributed to their polyphenol content. These compounds undergo many bioconversions in the body. Modeling polyphenol exposure of humans upon intake is a prerequisite for understanding the modulating effect of the food matrix and the colonic microbiome. This modeling is not a trivial task and requires a careful integration of measuring techniques, modeling methods and experimental design. Moreover, both at the population level as well as the individual level polyphenol exposure has to be quantified and assessed. We developed a strategy to quantify polyphenol exposure based on the concept of nutrikinetics in combination with population-based modeling. The key idea of the strategy is to derive nutrikinetic model parameters that summarize all information of the polyphenol exposure at both individual and population level. This is illustrated by a placebo-controlled crossover study in which an extract of wine/grapes and black tea solids was administered to twenty subjects. We show that urinary and plasma nutrikinetic time-response curves can be used for phenotyping the gut microbial bioconversion capacity of individuals. Each individual harbours an intrinsic microbiota composition converting similar polyphenols from both test products in the same manner and stable over time. We demonstrate that this is a novel approach for associating the production of two gut-mediated ¿-valerolactones to specific gut phylotypes. The large inter-individual variation in nutrikinetics and ¿-valerolactones production indicated that gut microbial metabolism is an essential factor in polyphenol exposure and related potential health benefits

KW - red wine/grape juice

KW - black tea

KW - dietary polyphenols

KW - phenolic metabolites

KW - nutrition research

KW - food sources

KW - human plasma

KW - green tea

KW - gut model

KW - pharmacokinetics

U2 - 10.1007/s11306-014-0645-y

DO - 10.1007/s11306-014-0645-y

M3 - Article

VL - 10

SP - 1059

EP - 1073

JO - Metabolomics

JF - Metabolomics

SN - 1573-3882

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van Velzen EJJ, Westerhuis JA, Grün CH, van Duynhoven JPM, Jacobs DM, Eilers PHC et al. Population-based nutrikinetic modelling of phytochemical exposure. Metabolomics. 2014;10(6):1059-1073. https://doi.org/10.1007/s11306-014-0645-y