Literature DB >> 28585232

In vitro-in silico-based analysis of the dose-dependent in vivo oestrogenicity of the soy phytoestrogen genistein in humans.

Rungnapa Boonpawa1, Albertus Spenkelink1, Ans Punt1, Ivonne M C M Rietjens1.   

Abstract

BACKGROUND AND
PURPOSE: The in vivo oestrogenicity of genistein and its glycoside genistin is still under debate. The present study aimed to develop a physiologically based kinetic (PBK) model that provides insight in dose-dependent plasma concentrations of genistein aglycone and its metabolites and enables prediction of in vivo oestrogenic effective dose levels of genistein and genistin in humans. EXPERIMENTAL APPROACH: A PBK model for genistein and genistin in humans was developed based on in vitro metabolic parameters. The model obtained was used to translate in vitro oestrogenic concentration-response curves of genistein to in vivo oestrogenic dose-response curves for intake of genistein and genistin. KEY
RESULTS: The model predicted that genistein-7-O-glucuronide was the major circulating metabolite and that levels of the free aglycone were generally low [0.5-17% of total plasma genistein at oral doses from 0.01 to 50 mg (kg·bw)-1 ]. The predicted in vivo benchmark dose for 5% response values for oestrogenicity varied between 0.06 and 4.39 mg kg-1 genistein. For genistin, these values were 1.3-fold higher. These values are in line with reported human data and show that oestrogenic responses can be expected at an Asian dietary and a supplementary intake, while intake resulting from a Western diet may not be effective. CONCLUSIONS AND IMPLICATIONS: The present study shows how plasma concentrations of genistein and its metabolites and oestrogenic dose levels of genistein in humans can be predicted by combining in vitro oestrogenicity with PBK model-based reverse dosimetry, eliminating the need for human intervention studies.
© 2017 The British Pharmacological Society.

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Year:  2017        PMID: 28585232      PMCID: PMC5523000          DOI: 10.1111/bph.13900

Source DB:  PubMed          Journal:  Br J Pharmacol        ISSN: 0007-1188            Impact factor:   8.739


  62 in total

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6.  A Computational Workflow for Probabilistic Quantitative in Vitro to in Vivo Extrapolation.

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