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Physiologically-based toxicokinetic modeling of zearalenone and its metabolites: application to the Jersey girl study.

Mukherjee D, Royce SG, Alexander JA, Buckley B, Isukapalli SS, Bandera EV, Zarbl H, Georgopoulos PG - PLoS ONE (2014)

Bottom Line: Zearalenone (ZEA), a fungal mycotoxin, and its metabolite zeranol (ZAL) are known estrogen agonists in mammals, and are found as contaminants in food.Zeranol, which is more potent than ZEA and comparable in potency to estradiol, is also added as a growth additive in beef in the US and Canada.Metabolic events such as dehydrogenation and glucuronidation of the chemicals, which have direct effects on the accumulation and elimination of the toxic compounds, have been quantified.

View Article: PubMed Central - PubMed

Affiliation: Environmental and Occupational Health Sciences Institute, Rutgers University, Piscataway, New Jersey, United States of America; Department of Environmental and Occupational Medicine, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America; Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, New Jersey, United States of America.

ABSTRACT
Zearalenone (ZEA), a fungal mycotoxin, and its metabolite zeranol (ZAL) are known estrogen agonists in mammals, and are found as contaminants in food. Zeranol, which is more potent than ZEA and comparable in potency to estradiol, is also added as a growth additive in beef in the US and Canada. This article presents the development and application of a Physiologically-Based Toxicokinetic (PBTK) model for ZEA and ZAL and their primary metabolites, zearalenol, zearalanone, and their conjugated glucuronides, for rats and for human subjects. The PBTK modeling study explicitly simulates critical metabolic pathways in the gastrointestinal and hepatic systems. Metabolic events such as dehydrogenation and glucuronidation of the chemicals, which have direct effects on the accumulation and elimination of the toxic compounds, have been quantified. The PBTK model considers urinary and fecal excretion and biliary recirculation and compares the predicted biomarkers of blood, urinary and fecal concentrations with published in vivo measurements in rats and human subjects. Additionally, the toxicokinetic model has been coupled with a novel probabilistic dietary exposure model and applied to the Jersey Girl Study (JGS), which involved measurement of mycoestrogens as urinary biomarkers, in a cohort of young girls in New Jersey, USA. A probabilistic exposure characterization for the study population has been conducted and the predicted urinary concentrations have been compared to measurements considering inter-individual physiological and dietary variability. The in vivo measurements from the JGS fall within the high and low predicted distributions of biomarker values corresponding to dietary exposure estimates calculated by the probabilistic modeling system. The work described here is the first of its kind to present a comprehensive framework developing estimates of potential exposures to mycotoxins and linking them with biologically relevant doses and biomarker measurements, including a systematic characterization of uncertainties in exposure and dose estimation for a vulnerable population.

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Sensitivity analysis of model.Calculated sensitivity indices for PBPK model implementation in (a) rats and (b) human subjects based on oral dosage. Both models were tested with an oral bolus dose of 8 mg/kg BW of ZEA and ZEA amounts in tissues after 12 hours were used to calculate the sensitivity indices. The size of dots shown in the figures represents the relative sensitivity of each parameter compared to all other aspects of the model.).
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pone-0113632-g013: Sensitivity analysis of model.Calculated sensitivity indices for PBPK model implementation in (a) rats and (b) human subjects based on oral dosage. Both models were tested with an oral bolus dose of 8 mg/kg BW of ZEA and ZEA amounts in tissues after 12 hours were used to calculate the sensitivity indices. The size of dots shown in the figures represents the relative sensitivity of each parameter compared to all other aspects of the model.).

Mentions: Model predictions of human biomarker levels for zearalenone and zeranol are affected by (a) variability in model parameter values estimated for human populations and (b) uncertainties in dietary exposure estimation. Parameter estimation for human populations cannot be conducted directly as done for other mammals and therefore parameters are generally obtained through in vitro-in vivo extrapolation of measurements from in vitro cultures (discussed in detail in the “Parameter estimation” & the “Extension of the PBTK model to human subjects” sections). The model utilizes in vitro and in vivo data available in the scientific literature regarding chemical kinetics of zearalenone and its metabolites. However, there is still wide variability within these data related to species tested, in vitro cultures used, and chemicals evaluated. This causes variability in model estimates, which could be potentially improved by performing improved measurements of these compounds and their metabolites using human tissue samples in vitro. Consequently, a key step towards developing better models is to identify important parameters that most substantially affect the final results, and subsequently design future studies for obtaining improved estimates of those key parameters. Results of sensitivity analyses conducted on the parameters of the PBPK models that were developed for the rats and the human subjects in this work, are presented in Fig. 13. Fig. 13 shows the sensitivity indices as black dots with the relative size of the dots signifying a proportionally greater or lesser relative sensitivity. Sensitivity indices have been calculated according to the following equation:(18)where is the sensitivity index for parameter based on output variable Vj. Here, and are respectively, the original value and changed value of the ith parameter. and are the corresponding changes in the jth output variable due to the change in parameter value. The calculated sensitivity indices are then normalized based on their maximum value. Fig. 13(a) shows that the PBPK model results for rats are highly sensitive in general to kinetic parameters and which control metabolism of ZEA in the liver. ZEA concentrations in the tissues are sensitive to the corresponding partition coefficient () for that tissue, except which affects whole body distribution of ZEA. The model is also especially sensitive to the parameters for gut elimination () and that for slow absorption in the gut lumen (). This is expected since, for oral dosage, gut absorption, elimination, and hepatic metabolism are key processes controlling ZEA concentration in tissues. Key parameters for urinary biomarker levels include the hepatic metabolic parameters (, ), filtration parameter (), and the partition coefficients of liver and kidney (, ). The PBPK model implementation for human subjects (Fig. 13(b)) shows a similar high sensitivity for the tissue partition coefficients corresponding to the respective tissue concentration. Additionally, higher sensitivity is observed for the kidney filtration parameter and kidney partition coefficient, especially for urinary biomarker levels. Overall, it can be stated that the liver and kidney appear to be key controlling compartments affecting the whole-body distribution, metabolism and biomarker levels in both rats and humans. Better estimation of parameters pertaining to key compartmental processes is important in addressing observed large uncertainties associated with model predictions. A better characterization of these parameters in the future, will also help capture inter-individual variations in whole body distribution and metabolism of the compounds of concern.


Physiologically-based toxicokinetic modeling of zearalenone and its metabolites: application to the Jersey girl study.

Mukherjee D, Royce SG, Alexander JA, Buckley B, Isukapalli SS, Bandera EV, Zarbl H, Georgopoulos PG - PLoS ONE (2014)

Sensitivity analysis of model.Calculated sensitivity indices for PBPK model implementation in (a) rats and (b) human subjects based on oral dosage. Both models were tested with an oral bolus dose of 8 mg/kg BW of ZEA and ZEA amounts in tissues after 12 hours were used to calculate the sensitivity indices. The size of dots shown in the figures represents the relative sensitivity of each parameter compared to all other aspects of the model.).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4256163&req=5

pone-0113632-g013: Sensitivity analysis of model.Calculated sensitivity indices for PBPK model implementation in (a) rats and (b) human subjects based on oral dosage. Both models were tested with an oral bolus dose of 8 mg/kg BW of ZEA and ZEA amounts in tissues after 12 hours were used to calculate the sensitivity indices. The size of dots shown in the figures represents the relative sensitivity of each parameter compared to all other aspects of the model.).
Mentions: Model predictions of human biomarker levels for zearalenone and zeranol are affected by (a) variability in model parameter values estimated for human populations and (b) uncertainties in dietary exposure estimation. Parameter estimation for human populations cannot be conducted directly as done for other mammals and therefore parameters are generally obtained through in vitro-in vivo extrapolation of measurements from in vitro cultures (discussed in detail in the “Parameter estimation” & the “Extension of the PBTK model to human subjects” sections). The model utilizes in vitro and in vivo data available in the scientific literature regarding chemical kinetics of zearalenone and its metabolites. However, there is still wide variability within these data related to species tested, in vitro cultures used, and chemicals evaluated. This causes variability in model estimates, which could be potentially improved by performing improved measurements of these compounds and their metabolites using human tissue samples in vitro. Consequently, a key step towards developing better models is to identify important parameters that most substantially affect the final results, and subsequently design future studies for obtaining improved estimates of those key parameters. Results of sensitivity analyses conducted on the parameters of the PBPK models that were developed for the rats and the human subjects in this work, are presented in Fig. 13. Fig. 13 shows the sensitivity indices as black dots with the relative size of the dots signifying a proportionally greater or lesser relative sensitivity. Sensitivity indices have been calculated according to the following equation:(18)where is the sensitivity index for parameter based on output variable Vj. Here, and are respectively, the original value and changed value of the ith parameter. and are the corresponding changes in the jth output variable due to the change in parameter value. The calculated sensitivity indices are then normalized based on their maximum value. Fig. 13(a) shows that the PBPK model results for rats are highly sensitive in general to kinetic parameters and which control metabolism of ZEA in the liver. ZEA concentrations in the tissues are sensitive to the corresponding partition coefficient () for that tissue, except which affects whole body distribution of ZEA. The model is also especially sensitive to the parameters for gut elimination () and that for slow absorption in the gut lumen (). This is expected since, for oral dosage, gut absorption, elimination, and hepatic metabolism are key processes controlling ZEA concentration in tissues. Key parameters for urinary biomarker levels include the hepatic metabolic parameters (, ), filtration parameter (), and the partition coefficients of liver and kidney (, ). The PBPK model implementation for human subjects (Fig. 13(b)) shows a similar high sensitivity for the tissue partition coefficients corresponding to the respective tissue concentration. Additionally, higher sensitivity is observed for the kidney filtration parameter and kidney partition coefficient, especially for urinary biomarker levels. Overall, it can be stated that the liver and kidney appear to be key controlling compartments affecting the whole-body distribution, metabolism and biomarker levels in both rats and humans. Better estimation of parameters pertaining to key compartmental processes is important in addressing observed large uncertainties associated with model predictions. A better characterization of these parameters in the future, will also help capture inter-individual variations in whole body distribution and metabolism of the compounds of concern.

Bottom Line: Zearalenone (ZEA), a fungal mycotoxin, and its metabolite zeranol (ZAL) are known estrogen agonists in mammals, and are found as contaminants in food.Zeranol, which is more potent than ZEA and comparable in potency to estradiol, is also added as a growth additive in beef in the US and Canada.Metabolic events such as dehydrogenation and glucuronidation of the chemicals, which have direct effects on the accumulation and elimination of the toxic compounds, have been quantified.

View Article: PubMed Central - PubMed

Affiliation: Environmental and Occupational Health Sciences Institute, Rutgers University, Piscataway, New Jersey, United States of America; Department of Environmental and Occupational Medicine, Rutgers University - Robert Wood Johnson Medical School, Piscataway, New Jersey, United States of America; Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, New Jersey, United States of America.

ABSTRACT
Zearalenone (ZEA), a fungal mycotoxin, and its metabolite zeranol (ZAL) are known estrogen agonists in mammals, and are found as contaminants in food. Zeranol, which is more potent than ZEA and comparable in potency to estradiol, is also added as a growth additive in beef in the US and Canada. This article presents the development and application of a Physiologically-Based Toxicokinetic (PBTK) model for ZEA and ZAL and their primary metabolites, zearalenol, zearalanone, and their conjugated glucuronides, for rats and for human subjects. The PBTK modeling study explicitly simulates critical metabolic pathways in the gastrointestinal and hepatic systems. Metabolic events such as dehydrogenation and glucuronidation of the chemicals, which have direct effects on the accumulation and elimination of the toxic compounds, have been quantified. The PBTK model considers urinary and fecal excretion and biliary recirculation and compares the predicted biomarkers of blood, urinary and fecal concentrations with published in vivo measurements in rats and human subjects. Additionally, the toxicokinetic model has been coupled with a novel probabilistic dietary exposure model and applied to the Jersey Girl Study (JGS), which involved measurement of mycoestrogens as urinary biomarkers, in a cohort of young girls in New Jersey, USA. A probabilistic exposure characterization for the study population has been conducted and the predicted urinary concentrations have been compared to measurements considering inter-individual physiological and dietary variability. The in vivo measurements from the JGS fall within the high and low predicted distributions of biomarker values corresponding to dietary exposure estimates calculated by the probabilistic modeling system. The work described here is the first of its kind to present a comprehensive framework developing estimates of potential exposures to mycotoxins and linking them with biologically relevant doses and biomarker measurements, including a systematic characterization of uncertainties in exposure and dose estimation for a vulnerable population.

Show MeSH
Related in: MedlinePlus