Generalized Concentration Addition Model Predicts Glucocorticoid Activity Bioassay Responses to Environmentally Detected Receptor-Ligand Mixtures

Prediction and assessment of xenoestrogens mixture effects using the in vitro ERα-CALUX assay

Introduction: Many natural or synthetic compounds used in foods, dietary supplements, and food contact materials (FCMs) are suspected endocrine disruptors (EDs). Currently, scientific evidence to predict the impacts on biological systems of ED mixtures is lacking. In this study, three classes of substances were considered: i) phytoestrogens, ii) plant protection products (PPP) and iii) substances related to FCMs. Fourteen compounds were selected based on their potential endocrine activity and their presence in food and FCMs. Methods: These compounds were evaluated using an in vitro gene expression assay, the ERα-CALUX, to characterize their responses on the estrogen receptor alpha. Cells were exposed to fixed ratio mixtures and non-equipotent mixtures of full and partial agonists. The concentration-response curves measured for the three classes of compounds were characterized by variable geometric parameters in terms of maximum response (efficacy), sensitivity (slope) and potency (median effective concentration EC50). To account for these variations, a generic response addition (GRA) model was derived from mass action kinetics. Results: Although GRA does not allow us to clearly separate the concentration addition (CA) and independent action (IA) models, it was possible to determine in a statistically robust way whether the combined action of the chemicals in the mixture acted by interaction (synergy and antagonism) or by additive behavior. This distinction is crucial for assessing the risks associated with exposure to xenoestrogens. A benchmark dose approach was used to compare the response of phytoestrogen blends in the presence and absence of the hormone estradiol (E2). At the same time, 12 mixtures of 2-5 constituents including phytoestrogens, phthalates and PPPs in proportions close to those found in food products were tested. In 95% of cases, the response pattern observed showed a joint and independent effect of the chemicals on ER. Discussion: Overall, these results validate a risk assessment approach based on an additive effects model modulated by intrinsic toxicity factors. Here, the CA and IA approaches cannot be distinguished solely based on the shape of the concentration response curves. However, the optimized GRA model is more robust than CA when the efficacy, potency, and sensitivity of individual chemical agonists show large variations.

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa

In the United States and globally, contaminant exposure in unregulated private-well point-of-use tapwater (TW) is a recognized public-health data gap and an obstacle to both risk-management and homeowner decision making. To help address the lack of data on broad contaminant exposures in private-well TW from hydrologically-vulnerable (alluvial, karst) aquifers in agriculturally-intensive landscapes, samples were collected in 2018-2019 from 47 northeast Iowa farms and analyzed for 35 inorganics, 437 unique organics, 5 in vitro bioassays, and 11 microbial assays. Twenty-six inorganics and 51 organics, dominated by pesticides and related transformation products (35 herbicide-, 5 insecticide-, and 2 fungicide-related), were observed in TW. Heterotrophic bacteria detections were near ubiquitous (94 % of the samples), with detection of total coliform bacteria in 28 % of the samples and growth on at least one putative-pathogen selective media across all TW samples. Health-based hazard index screening levels were exceeded frequently in private-well TW and attributed primarily to inorganics (nitrate, uranium). Results support incorporation of residential treatment systems to protect against contaminant exposure and the need for increased monitoring of rural private-well homes. Continued assessment of unmonitored and unregulated private-supply TW is needed to model contaminant exposures and human-health risks.

A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals

A 2019 retrospective study analyzed wristband personal samplers from fourteen different communities across three different continents for over 1530 organic chemicals. Investigators identified fourteen chemicals (G14) detected in over 50% of personal samplers. The G14 represent a group of chemicals that individuals are commonly exposed to, and are mainly associated with consumer products including plasticizers, fragrances, flame retardants, and pesticides. The high frequency of exposure to these chemicals raises questions of their potential adverse human health effects. Additionally, the possibility of exposure to mixtures of these chemicals is likely due to their co-occurrence; thus, the potential for mixtures to induce differential bioactivity warrants further investigation. This study describes a novel approach to broadly evaluate the hazards of personal chemical exposures by coupling data from personal sampling devices with high-throughput bioactivity screenings using in vitro and non-mammalian in vivo models. To account for species and sensitivity differences, screening was conducted using primary normal human bronchial epithelial (NHBE) cells and early life-stage zebrafish. Mixtures of the G14 and most potent G14 chemicals were created to assess potential mixture effects. Chemical bioactivity was dependent on the model system, with five and eleven chemicals deemed bioactive in NHBE and zebrafish, respectively, supporting the use of a multi-system approach for bioactivity testing and highlighting sensitivity differences between the models. In both NHBE and zebrafish, mixture effects were observed when screening mixtures of the most potent chemicals. Observations of BMC-based mixtures in NHBE (NHBE BMC Mix) and zebrafish (ZF BMC Mix) suggested antagonistic effects. In this study, consumer product-related chemicals were prioritized for bioactivity screening using personal exposure data. High-throughput high-content screening was utilized to assess the chemical bioactivity and mixture effects of the most potent chemicals.

In vitro effects-based method and water quality screening model for use in pre- and post-distribution treated waters

Recent urban public water supply contamination events emphasize the importance of screening treated drinking water quality after distribution. In vitro bioassays, when run concurrently with analytical chemistry methods, are effective tools to evaluating the efficacy of water treatment processes and water quality. We tested 49 water samples representing the Chicago Department of Water Management service areas for estrogen, (anti)androgen, glucocorticoid receptor-activating contaminants and cytotoxicity. We present a tiered screening approach suitable to samples with anticipated low-level activity and initially tested all extracts for statistically identifiable endocrine activity; performing a secondary dilution-response analysis to determine sample EC₅₀ and biological equivalency values (BioEq). Estrogenic activity was detected in untreated Lake Michigan intake water samples using mammalian (5/49; median: 0.21 ng E2Eq/L) and yeast cell (5/49; 1.78 ng E2Eq/L) bioassays. A highly sensitive (anti)androgenic activity bioassay was applied for the first time to water quality screening and androgenic activity was detected in untreated intake and treated pre-distribution samples (4/49; 0.93 ng DHTEq/L). No activity was identified above method detection limits in the yeast androgenic, mammalian anti-androgenic, and both glucocorticoid bioassays. Known estrogen receptor agonists were detected using HPLC/MS-MS (estrone: 0.72-1.4 ng/L; 17α-estradiol: 1.3-1.5 ng/L; 17β-estradiol: 1.4 ng/L; equol: 8.8 ng/L), however occurrence did not correlate with estrogenic bioassay results. Many studies have applied bioassays to water quality monitoring using only relatively small samples sets often collected from surface and/or wastewater effluent. However, to realistically adapt these tools to treated water quality monitoring, water quality managers must have the capacity to screen potentially hundreds of samples in short timeframes. Therefore, we provided a tiered screening model that increased sample screening speed, without sacrificing statistical stringency, and detected estrogenic and androgenic activity only in pre-distribution Chicago area samples.

Bioanalytical equivalents and relative potencies for predicting the biological effects of mixtures

Bioanalytical equivalents (BEQs) of mixtures and environmental samples are widely used to reflect the potential threat of pollutants in the environment and can be obtained by bioassays or using chemical analysis combined with relative potencies (REPs). In this study, the relationships between bioassay-detected BEQs (Bio-BEQs) and chemically analyzed BEQs (Chem-BEQs) were studied. BEQs and REPs are correlated with effect level and the concentration-response curves of the reference standard and sample. Thus, effect level (e.g., EC₁₀, EC₂₅ and EC₅₀) should be addressed for the BEQ values obtained from bioassays or chemical analyses. The previous prerequisites for REPs application (i.e., curves that are parallel and have the same maximum response) are redundant, and the use of REPs for the calculation of BEQs or in risk assessment should instead be based on the same effect level. For a complex mixture with many components, all active components can be regarded as dilutions of a standard compound for inducing a specific effect. Relative toxicity estimates based on EC₅₀ ignore the contribution of weak-active components with maximum response below EC₅₀ of the reference standard, especially in complex mixtures or environmental samples. REPs based on an effect level EC₁₀ that can be clearly discriminated from background response are recommended for BEQ calculation. As an example, the aryl hydrocarbon receptor (AhR)-mediated activity of US EPA priority polycyclic aromatic hydrocarbons (PAHs) in RTL-W1 cells was used to assess the reliability of REPs for mixture toxicity prediction based on the effect level EC₁₀.

Application of generalized concentration addition to predict mixture effects of glucocorticoid receptor ligands

Environmental exposures often occur in complex mixtures and at low concentrations. Generalized concentration addition (GCA) is a method used to estimate the joint effect of receptor ligands that vary in efficacy. GCA models have been successfully applied to mixtures of aryl hydrocarbon receptor (AhR) and peroxisome proliferator-activated receptor gamma (PPARγ) ligands, each of which can be modeled as a receptor with a single binding site. Here, we evaluated whether GCA could be applied to homodimer nuclear receptors, which have two binding sites, to predict the combined effect of full glucocorticoid receptor (GR) agonists with partial agonists. We measured transcriptional activation of GR using a cell-based bioassay. Individual concentration-response curves for dexamethasone (full agonist), prednisolone (full agonist), and medroxyprogesterone 17-acetate (partial agonist) were generated and applied in three additivity models, GCA, effect summation (ES), and relative potency factor (RPF), to generate response surfaces. GCA and RPF yielded adequate predictions of the experimental data for two full agonists. However, GCA fit experimental data significantly better than ES and RPF for all other binary mixtures. This work extends the application of GCA to homodimer nuclear receptors and improves prediction accuracy of mixture effects of GR agonists.

Predictive Analysis Using Chemical-Gene Interaction Networks Consistent with Observed Endocrine Activity and Mutagenicity of U.S. Streams

In a recent U.S. Geological Survey/U.S. Environmental Protection Agency study assessing more than 700 organic compounds in 38 streams, in vitro assays indicated generally low estrogen, androgen, and glucocorticoid receptor activities, with 13 surface waters with 17β-estradiol-equivalent (E2Eq) activities greater than a 1-ng/L estimated effects-based trigger value for estrogenic effects in male fish. Among the 36 samples assayed for mutagenicity in the Salmonella bioassay (reported here), 25% had low mutagenic activity and 75% were not mutagenic. Endocrine and mutagenic activities of the water samples were well correlated with each other and with the total number and cumulative concentrations of detected chemical contaminants. To test the predictive utility of knowledge-base-leveraging approaches, site-specific predicted chemical-gene (pCGA) and predicted analogous pathway-linked (pPLA) association networks identified in the Comparative Toxicogenomics Database were compared with observed endocrine/mutagenic bioactivities. We evaluated pCGA/pPLA patterns among sites by cluster analysis and principal component analysis and grouped the pPLA into broad mode-of-action classes. Measured E2eq and mutagenic activities correlated well with predicted pathways. The pPLA analysis also revealed correlations with signaling, metabolic, and regulatory groups, suggesting that other effects pathways may be associated with chemical contaminants in these waters and indicating the need for broader bioassay coverage to assess potential adverse impacts.

Adverse Maternal, Fetal, and Postnatal Effects of Hexafluoropropylene Oxide Dimer Acid (GenX) from Oral Gestational Exposure in Sprague-Dawley Rats

BACKGROUND

Hexafluoropropylene oxide dimer acid [(HFPO-DA), GenX] is a member of the per- and polyfluoroalkyl substances (PFAS) chemical class, and elevated levels of HFPO-DA have been detected in surface water, air, and treated drinking water in the United States and Europe.

OBJECTIVES

We aimed to characterize the potential maternal and postnatal toxicities of oral HFPO-DA in rats during sexual differentiation. Given that some PFAS activate peroxisome proliferator-activated receptors (PPARs), we sought to assess whether HFPO-DA affects androgen-dependent development or interferes with estrogen, androgen, or glucocorticoid receptor activity.

METHODS

Steroid receptor activity was assessed with a suite of in vitro transactivation assays, and Sprague-Dawley rats were used to assess maternal, fetal, and postnatal effects of HFPO-DA exposure. Dams were dosed daily via oral gavage during male reproductive development (gestation days 14-18). We evaluated fetal testes, maternal and fetal livers, maternal serum clinical chemistry, and reproductive development of F1 animals.

RESULTS

HFPO-DA exposure resulted in negligible in vitro receptor activity and did not impact testosterone production or expression of genes key to male reproductive development in the fetal testis; however, in vivo exposure during gestation resulted in higher maternal liver weights ([Formula: see text]), lower maternal serum thyroid hormone and lipid profiles ([Formula: see text]), and up-regulated gene expression related to PPAR signaling pathways in maternal and fetal livers ([Formula: see text]). Further, the pilot postnatal study indicated lower female body weight and lower weights of male reproductive tissues in F1 animals.

CONCLUSIONS

HFPO-DA exposure produced multiple effects that were similar to prior toxicity evaluations on PFAS, such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), but seen as the result of higher oral doses. The mean dam serum concentration from the lowest dose group was 4-fold greater than the maximum serum concentration detected in a worker in an HFPO-DA manufacturing facility. Research is needed to examine the mechanisms and downstream events linked to the adverse effects of PFAS as are mixture-based studies evaluating multiple PFAS. https://doi.org/10.1289/EHP4372.