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Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro.

Hadrup N, Taxvig C, Pedersen M, Nellemann C, Hass U, Vinggaard AM - PLoS ONE (2013)

Bottom Line: Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data.In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects.In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals.

View Article: PubMed Central - PubMed

Affiliation: Division of Toxicology and Risk Assessment, National Food Institute, Technical University of Denmark, Søborg, Denmark.

ABSTRACT
Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals.

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The effect of Mixture 1 on steroid hormone levels in H295R cells.Cells were incubated with Mixture 1 at concentrations ranging from 0.04 to 30 µM for 48 h. Hormones levels were measured by LC-MS/MS, except for estradiol that was measured by DELFIA. The figure shows the results of progesterone, 17-OH-progesterone, cortisol, dehydroepiandrosterone, androstenedione, estrone, testosterone and estradiol arranged according to appropriate steps in steroidogenesis. Data are mean ± SD expressed as per-cent of the control level. A p-value of less than 0.05 was considered significant, and in case of significance a sigmoidal curve fit (black line) was applied with a 95% confidence band (black dotted lines). Enzymes involved in steroidogenesis are illustrated by colour shaded boxes at appropriate steps. Abbreviations are as follows: CYP: Cytochrome P450, HSD: Hydroxysteroid dehydrogenase.
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pone-0070490-g001: The effect of Mixture 1 on steroid hormone levels in H295R cells.Cells were incubated with Mixture 1 at concentrations ranging from 0.04 to 30 µM for 48 h. Hormones levels were measured by LC-MS/MS, except for estradiol that was measured by DELFIA. The figure shows the results of progesterone, 17-OH-progesterone, cortisol, dehydroepiandrosterone, androstenedione, estrone, testosterone and estradiol arranged according to appropriate steps in steroidogenesis. Data are mean ± SD expressed as per-cent of the control level. A p-value of less than 0.05 was considered significant, and in case of significance a sigmoidal curve fit (black line) was applied with a 95% confidence band (black dotted lines). Enzymes involved in steroidogenesis are illustrated by colour shaded boxes at appropriate steps. Abbreviations are as follows: CYP: Cytochrome P450, HSD: Hydroxysteroid dehydrogenase.

Mentions: By LC-MS/MS the following was found for Mixture 1 (Fig. 1): Progesterone levels were increased with an EC50 value of 16 µM and a measured maximal effect level of 1200% of control. It should be noted that the curve did not seem to have reached its maximal effect level, thus the value is a tentative Emax value, 17α-OH progesterone was unchanged. Cortisol was decreased with an EC50 value of 1.5 µM and a measured maximal effect level of 18% of control; dehydroepiandrosterone was decreased with an EC50 value of 0.43 µM and a measured maximal effect level at 17% of control. Androstenedione was decreased with an EC50 value of 1.5 µM and a measured maximal effect level of 9% of control. Testosterone was also decreased with an EC50 value of 2.4 µM and a measured maximal effect level of 16% of control (Fig. 1). Estrone was unchanged. Estradiol was measured by DELFIA as it was not detected by LC-MS/MS. Mixture 1 had no effect on the estradiol level (Fig. 1).


Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro.

Hadrup N, Taxvig C, Pedersen M, Nellemann C, Hass U, Vinggaard AM - PLoS ONE (2013)

The effect of Mixture 1 on steroid hormone levels in H295R cells.Cells were incubated with Mixture 1 at concentrations ranging from 0.04 to 30 µM for 48 h. Hormones levels were measured by LC-MS/MS, except for estradiol that was measured by DELFIA. The figure shows the results of progesterone, 17-OH-progesterone, cortisol, dehydroepiandrosterone, androstenedione, estrone, testosterone and estradiol arranged according to appropriate steps in steroidogenesis. Data are mean ± SD expressed as per-cent of the control level. A p-value of less than 0.05 was considered significant, and in case of significance a sigmoidal curve fit (black line) was applied with a 95% confidence band (black dotted lines). Enzymes involved in steroidogenesis are illustrated by colour shaded boxes at appropriate steps. Abbreviations are as follows: CYP: Cytochrome P450, HSD: Hydroxysteroid dehydrogenase.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3750043&req=5

pone-0070490-g001: The effect of Mixture 1 on steroid hormone levels in H295R cells.Cells were incubated with Mixture 1 at concentrations ranging from 0.04 to 30 µM for 48 h. Hormones levels were measured by LC-MS/MS, except for estradiol that was measured by DELFIA. The figure shows the results of progesterone, 17-OH-progesterone, cortisol, dehydroepiandrosterone, androstenedione, estrone, testosterone and estradiol arranged according to appropriate steps in steroidogenesis. Data are mean ± SD expressed as per-cent of the control level. A p-value of less than 0.05 was considered significant, and in case of significance a sigmoidal curve fit (black line) was applied with a 95% confidence band (black dotted lines). Enzymes involved in steroidogenesis are illustrated by colour shaded boxes at appropriate steps. Abbreviations are as follows: CYP: Cytochrome P450, HSD: Hydroxysteroid dehydrogenase.
Mentions: By LC-MS/MS the following was found for Mixture 1 (Fig. 1): Progesterone levels were increased with an EC50 value of 16 µM and a measured maximal effect level of 1200% of control. It should be noted that the curve did not seem to have reached its maximal effect level, thus the value is a tentative Emax value, 17α-OH progesterone was unchanged. Cortisol was decreased with an EC50 value of 1.5 µM and a measured maximal effect level of 18% of control; dehydroepiandrosterone was decreased with an EC50 value of 0.43 µM and a measured maximal effect level at 17% of control. Androstenedione was decreased with an EC50 value of 1.5 µM and a measured maximal effect level of 9% of control. Testosterone was also decreased with an EC50 value of 2.4 µM and a measured maximal effect level of 16% of control (Fig. 1). Estrone was unchanged. Estradiol was measured by DELFIA as it was not detected by LC-MS/MS. Mixture 1 had no effect on the estradiol level (Fig. 1).

Bottom Line: Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data.In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects.In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals.

View Article: PubMed Central - PubMed

Affiliation: Division of Toxicology and Risk Assessment, National Food Institute, Technical University of Denmark, Søborg, Denmark.

ABSTRACT
Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals.

Show MeSH
Related in: MedlinePlus