High-throughput screening tools facilitate calculation of a combined exposure-bioactivity index for chemicals with endocrine activity.

High-throughput and computational tools provide a new opportunity to calculate combined bioactivity of exposure to diverse chemicals acting through a common mechanism. We used high throughput in vitro bioactivity data and exposure predictions from the U.S. EPA's Toxicity and Exposure Forecaster (ToxCast and ExpoCast) to estimate combined estrogen receptor (ER) agonist activity of non-pharmaceutical chemical exposures for the general U.S. population. High-throughput toxicokinetic (HTTK) data provide conversion factors that relate bioactive concentrations measured in vitro (µM), to predicted population geometric mean exposure rates (mg/kg/day). These data were available for 22 chemicals with ER agonist activity and were estimated for other ER bioactive chemicals based on the geometric mean of HTTK values across chemicals. For each chemical, ER bioactivity across ToxCast assays was compared to predicted population geometric mean exposure at different levels of in vitro potency and model certainty. Dose additivity was assumed in calculating a Combined Exposure-Bioactivity Index (CEBI), the sum of exposure/bioactivity ratios. Combined estrogen bioactivity was also calculated in terms of the percent maximum bioactivity of chemical mixtures in human plasma using a concentration-addition model. Estimated CEBIs vary greatly depending on assumptions used for exposure and bioactivity. In general, CEBI values were <1 when using median of the estimated general population chemical intake rates, while CEBI were ≥1 when using the upper 95th confidence bound for those same intake rates for all chemicals. Concentration-addition model predictions of mixture bioactivity yield comparable results. Based on current in vitro bioactivity data, HTTK methods, and exposure models, combined exposure scenarios sufficient to influence estrogen bioactivity in the general population cannot be ruled out. Future improvements in screening methods and computational models could reduce uncertainty and better inform the potential combined effects of estrogenic chemicals.

Prediction of Estrogenic Bioactivity of Environmental Chemical Metabolites.

The US Environmental Protection Agency's (EPA) Endocrine Disruptor Screening Program (EDSP) is using in vitro data generated from ToxCast/Tox21 high-throughput screening assays to assess the endocrine activity of environmental chemicals. Considering that in vitro assays may have limited metabolic capacity, inactive chemicals that are biotransformed into metabolites with endocrine bioactivity may be missed for further screening and testing. Therefore, there is a value in developing novel approaches to account for metabolism and endocrine activity of both parent chemicals and their associated metabolites. We used commercially available software to predict metabolites of 50 parent compounds, out of which 38 chemicals are known to have estrogenic metabolites, and 12 compounds and their metabolites are negative for estrogenic activity. Three ER QSAR models were used to determine potential estrogen bioactivity of the parent compounds and predicted metabolites, the outputs of the models were averaged, and the chemicals were then ranked based on the total estrogenicity of the parent chemical and metabolites. The metabolite prediction software correctly identified known estrogenic metabolites for 26 out of 27 parent chemicals with associated metabolite data, and 39 out of 46 estrogenic metabolites were predicted as potential biotransformation products derived from the parent chemical. The QSAR models estimated stronger estrogenic activity for the majority of the known estrogenic metabolites compared to their parent chemicals. Finally, the three models identified a similar set of parent compounds as top ranked chemicals based on the estrogenicity of putative metabolites. This proposed in silico approach is an inexpensive and rapid strategy for the detection of chemicals with estrogenic metabolites and may reduce potential false negative results from in vitro assays.

Halogenated bisphenol-A analogs act as obesogens in zebrafish larvae (Danio rerio).

Obesity has increased dramatically over the past decades, reaching epidemic proportions. The reasons are likely multifactorial. One of the suggested causes is the accelerated exposure to obesity-inducing chemicals (obesogens). However, out of the tens of thousands of industrial chemicals humans are exposed to, very few have been tested for their obesogenic potential, mostly due to the limited availability of appropriate in vivo screening models. In this study, we investigated whether two commonly used flame retardants, the halogenated bisphenol-A (BPA) analogs tetrabromobisphenol-A (TBBPA) and tetrachlorobisphenol-A (TCBPA), could act as obesogens using zebrafish larvae as an in vivo animal model. The effect of embryonic exposure to these chemicals on lipid accumulation was analyzed by Oil Red-O staining, and correlated to their capacity to activate human and zebrafish peroxisome proliferator-activated receptor gamma (PPARγ) in zebrafish and in reporter cell lines. Then, the metabolic fate of TBBPA and TCBPA in zebrafish larvae was analyzed by high-performance liquid chromatography (HPLC) . TBBPA and TCBPA were readily taken up by the fish embryo and both compounds were biotransformed to sulfate-conjugated metabolites. Both halogenated-BPAs, as well as TBBPA-sulfate induced lipid accumulation in zebrafish larvae. TBBPA and TCBPA also induced late-onset weight gain in juvenile zebrafish. These effects correlated to their capacity to act as zebrafish PPARγ agonists. Screening of chemicals for inherent obesogenic capacities through the zebrafish lipid accumulation model could facilitate prioritizing chemicals for further investigations in rodents, and ultimately, help protect humans from exposure to environmental obesogens.