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Endocrine Disrupting effects observed in the environment

An Evaluation of Models to Predict the Activity of Environmental Estrogens Candice M. Johnson and Rominder Suri, Ph.D.,P.E. NSF Water and Environmental Technology (WET) Center, Department of Civil and Environmental Engineering, Temple University, Philadelphia Pennsylvania 19122.

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Endocrine Disrupting effects observed in the environment

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  1. An Evaluation of Models to Predict the Activity of Environmental EstrogensCandice M. Johnson and Rominder Suri, Ph.D.,P.E.NSF Water and Environmental Technology (WET) Center, Department of Civil and Environmental Engineering, Temple University, Philadelphia Pennsylvania 19122

  2. Endocrine Disrupting effects observed in the environment • Imposex condition in snails • Masculanization/Feminization of fish • Altered sex ratio Normal female Masculanized female http://www.asnailsodyssey.com/LEARNABOUT/WHELK/whelImpo.php Normal male • Increased risk of cancer in humans?

  3. Routes of entry for endocrine disruptors in the environment Manufacturing products products Human Use Agriculture Pretreatment Water treatment plant Surface Water Biota Effluent

  4. Endocrine disrupting activity is related to wastewater treatment Relative distance from water treatment plant

  5. Removal of EDCs End-of-Pipe Technologies • Ozonation, Ultrasound, Adsorbents Source Control Strategies • Risk assessment & hazard characterization • Development of policy and laws • Research and development of safer products • Replacement of endocrine active ingredients

  6. Methods for detecting potential endocrine disruptors • Chemical Analysis - target analysis - low limits of detection - rapid analysis methods - high throughput - no indication of biological activity • Biological Analysis (Bioassays) - detects the activity of mixtures and unknowns • detects interactions, measures net biological activity • does not indicate the identity or concentrations of specific contaminants

  7. Approaches to testing EDCs • Chemical-by- chemical approach • May be too simplistic and may underestimate the risks of chemicals • Test mixture toxicity on a case by case basis • Chemical mixtures vary with respect to constituents and to concentrations of those constituents, Provides site specific data • Band-Aid but not a cure to the characterization of chemical mixtures (LeBlanc & Olmstead, 2004) • Component-based approach (estimating the total toxicity from information on identified components) • A step towards a generalized understanding and assessment of mixture toxicity

  8. Effect Directed Analysis (EDA) scheme Unknown Environmental Samples extraction and pre-concentration Bioassay Screening Antagonistic activity? LC-MS or GC-MS analysis of target compounds -- Correlation and quantification of casual factors (confirmation) Mathematical models are used to estimate the biological effects from the concentration of target compounds

  9. Additive models Concentration addition (CA) model Independent action (IA) model (probabilistic model) RP = Relative Potential Cn = Concentration of Component n in the mixture IEQ = Induction equivalents in terms of a standard Emix = Predicted effect of the mixture Emax = Maximum effect Fi,(ci)= activating effects determined from the regression of the concentration response relationships

  10. CA versus IA Concentration Addition (CA) • Applied to chemicals with a similar mode of action • EC50 of a mixture can be predicted based on the EC50 values of the individual components Independent action (IA) • Applied to chemicals with diverse modes of action • Mixture effects predicted from precise effects of each individual component and at the concentration found in the mixture. This information is not readily available • Assumes strictly independent events, may not be relevant in biological systems due to converging signalling pathways and inter-linked subsystems

  11. Objective: To assess the ability of additive models to predict estrogenic activity Approach • Extract hormones from wastewater influent and effluent samples • Measure the estrogenic activity of the extracts using the Yeast Estrogen Screen (YES) Assay • Quantify the concentrations of suspected estrogens using LC-MS/MS • Estimate the estrogenicity of the extracts using additive models

  12. Assessment of additive models Table 1: Concentrations of hormones detected in wastewater extracts *LOD 17β-estradiol = 0.15 ngL-1 Table 2: Total estrogenic activity of the wastewater extracts measured in the YES

  13. Assessment of additive models Predicted and observed concentration response curves in the YES Antagonistic- like activity is evident in both the wastewater influent and effluent samples

  14. Assessment of additive models in ‘clean’ water Predictions based on simulated samples do not suggest that the mixture should be interactive Clear contribution from the wastewater matrix Comparison of predicted and observed mixture responses for 17β-estradiol, estriol, estrone, and 17α-dihydroequilin in simulated sample

  15. Assessment of additive models for estimating estrogenicity and androgenicity 11% No Confirmation 26% Successful use of CA 5% Cytotoxicity 58% Biological Interaction with unknown mixture components

  16. Conclusions and Recommendations • Incomplete degradation of estrogen hormones during wastewater treatment - 24 - > 99% removal of steroid hormones from this wastewater treatment plant. Similar results were reported by Chimchirian et al., 2007 • Residual estrogenicity after water treatment may lead to endocrine disrupting effects in fish • Suggested no effect concentration for 17β-estradiol is 2ngL-1 (Caldwell et al., 2012) • Estrogenicity of effluent in our study is 7ngL-1 EEQ • No synergism or antagonism between estrogen hormones in “clean” water

  17. Conclusions and Recommendations • Other unknown components in the wastewater matrix may cause antagonistic responses • Additive models are applicable to “clean” water but may be limited in their use with complex mixtures • More advanced models that can capture interactions or antagonistic effects are needed

  18. Cn- concentration of nth mixture component γ - interaction index RP - relative potential IEQ - Induction equivalent concentrations * p<0.01 (These predictions are significantly different from the observed values) a – concentration ratio of BPA to testosterone b – concentration ratio of DBP to testosterone TEQ – Testosterone equivalents Johnson, C.M., et al., Environmental Science and Technology. 2013

  19. Thank you!Questions?

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