Safeguarding Female Reproductive Health against Endocrine Disrupting Chemicals-The FREIA Project.

Currently available test methods are not well-suited for the identification of chemicals that disturb hormonal processes involved in female reproductive development and function. This renders women's reproductive health at increasing risk globally, which, coupled with increasing incidence rates of reproductive disorders, is of great concern. A woman's reproductive health is largely established during embryonic and fetal development and subsequently matures during puberty. The endocrine system influences development, maturation, and function of the female reproductive system, thereby making appropriate hormone levels imperative for correct functioning of reproductive processes. It is concerning that the effects of human-made chemicals on the endocrine system and female reproductive health are poorly addressed in regulatory chemical safety assessment, partly because adequate test methods are lacking. Our EU-funded project FREIA aims to address this need by increasing understanding of how endocrine disrupting chemicals (EDCs) can impact female reproductive health. We will use this information to provide better test methods that enable fit-for-purpose chemical regulation and then share our knowledge, promote a sustainable society, and improve the reproductive health of women globally.

Removing Critical Gaps in Chemical Test Methods by Developing New Assays for the Identification of Thyroid Hormone System-Disrupting Chemicals-The ATHENA Project.

The test methods that currently exist for the identification of thyroid hormone system-disrupting chemicals are woefully inadequate. There are currently no internationally validated in vitro assays, and test methods that can capture the consequences of diminished or enhanced thyroid hormone action on the developing brain are missing entirely. These gaps put the public at risk and risk assessors in a difficult position. Decisions about the status of chemicals as thyroid hormone system disruptors currently are based on inadequate toxicity data. The ATHENA project (Assays for the identification of Thyroid Hormone axis-disrupting chemicals: Elaborating Novel Assessment strategies) has been conceived to address these gaps. The project will develop new test methods for the disruption of thyroid hormone transport across biological barriers such as the blood-brain and blood-placenta barriers. It will also devise methods for the disruption of the downstream effects on the brain. ATHENA will deliver a testing strategy based on those elements of the thyroid hormone system that, when disrupted, could have the greatest impact on diminished or enhanced thyroid hormone action and therefore should be targeted through effective testing. To further enhance the impact of the ATHENA test method developments, the project will develop concepts for better international collaboration and development in the area of thyroid hormone system disruptor identification and regulation.

Raspberry ketone in food supplements--High intake, few toxicity data--A cause for safety concern?

Raspberry ketone (4-(4-hydroxyphenyl)-2-butanone) is marketed on the Internet as a food supplement. The recommended intake is between 100 and 1400 mg per day. The substance is naturally occurring in raspberries (up to 4.3 mg/kg) and is used as a flavouring substance. Toxicological studies on raspberry ketone are limited to acute and subchronic studies in rats. When the lowest recommended daily dose of raspberry ketone (100 mg) as a food supplement is consumed, it is 56 times the established threshold of toxicological concern (TTC) of 1800 µg/day for Class 1 substances. The margin of safety (MOS) based on a NOAEL of 280 mg/kg bw/day for lower weight gain in rats is 165 at 100 mg and 12 at 1400 mg. The recommended doses are a concern taking into account the TTC and MOS. Investigations of raspberry ketone in quantitative structure-activity relationship (QSAR) models indicated potential cardiotoxic effects and potential effects on reproduction/development. Taking into account the high intake via supplements, the compound's toxic potential should be clarified with further experimental studies. In UK the pure compound is regarded as novel food requiring authorisation prior to marketing but raspberry ketone is not withdrawn from Internet sites from this country.

Orthogonal assay and QSAR modelling of Tox21 PPARγ antagonist in vitro high-throughput screening assay.

Disruption of signalling mediated by the nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ) is associated with risk of cancer, metabolic diseases, and endocrine disruption. The purpose of this study was to identify environmental chemicals acting as PPARγ antagonists. Data from the Tox21 PPARγ antagonism assay were replicated using a reporter system in HEK293 cells. Two quantitative structure-activity relationship (QSAR) models were developed, and five REACH-registered substances predicted positive were tested in vitro. Reporter assay results were consistent with Tox21 data since all conflicting results could be explained by assay interference. QSAR models showed good predictive performance, and follow-up experiments revealed two PPARγ antagonists out of three non-interfering chemicals. In conclusion, the developed QSAR models and follow-up experiments are important steps in the discovery of potential endocrine- and metabolism-disrupting chemicals.

New approach methods to improve human health risk assessment of thyroid hormone system disruption-a PARC project.

Current test strategies to identify thyroid hormone (TH) system disruptors are inadequate for conducting robust chemical risk assessment required for regulation. The tests rely heavily on histopathological changes in rodent thyroid glands or measuring changes in systemic TH levels, but they lack specific new approach methodologies (NAMs) that can adequately detect TH-mediated effects. Such alternative test methods are needed to infer a causal relationship between molecular initiating events and adverse outcomes such as perturbed brain development. Although some NAMs that are relevant for TH system disruption are available-and are currently in the process of regulatory validation-there is still a need to develop more extensive alternative test batteries to cover the range of potential key events along the causal pathway between initial chemical disruption and adverse outcomes in humans. This project, funded under the Partnership for the Assessment of Risk from Chemicals (PARC) initiative, aims to facilitate the development of NAMs that are specific for TH system disruption by characterizing in vivo mechanisms of action that can be targeted by in embryo/in vitro/in silico/in chemico testing strategies. We will develop and improve human-relevant in vitro test systems to capture effects on important areas of the TH system. Furthermore, we will elaborate on important species differences in TH system disruption by incorporating non-mammalian vertebrate test species alongside classical laboratory rat species and human-derived in vitro assays.

QSAR model for human pregnane X receptor (PXR) binding: screening of environmental chemicals and correlations with genotoxicity, endocrine disruption and teratogenicity.

The pregnane X receptor (PXR) has a key role in regulating the metabolism and transport of structurally diverse endogenous and exogenous compounds. Activation of PXR has the potential to initiate adverse effects, causing drug-drug interactions, and perturbing normal physiological functions. Therefore, identification of PXR ligands would be valuable information for pharmaceutical and toxicological research. In the present study, we developed a quantitative structure-activity relationship (QSAR) model for the identification of PXR ligands using data based on a human PXR binding assay. A total of 631 molecules, representing a variety of chemical structures, constituted the training set of the model. Cross-validation of the model showed a sensitivity of 82%, a specificity of 85%, and a concordance of 84%. The developed model provided knowledge about molecular descriptors that may influence the binding of molecules to PXR. The model was used to screen a large inventory of environmental chemicals, of which 47% was found to be within domain of the model. Approximately 35% of the chemicals within domain were predicted to be PXR ligands. The predicted PXR ligands were found to be overrepresented among chemicals predicted to cause adverse effects, such as genotoxicity, teratogenicity, estrogen receptor activation and androgen receptor antagonism compared to chemicals not causing these effects. The developed model may be useful as a tool for predicting potential PXR ligands and for providing mechanistic information of toxic effects of chemicals.

Identification of cytochrome P450 2D6 and 2C9 substrates and inhibitors by QSAR analysis.

This paper presents four new QSAR models for CYP2C9 and CYP2D6 substrate recognition and inhibitor identification based on human clinical data. The models were used to screen a large data set of environmental chemicals for CYP activity, and to analyze the frequency of CYP activity among these compounds. A large fraction of these chemicals were found to be CYP active, and thus potentially capable of affecting human physiology. 20% of the compounds within applicability domain of the models were predicted to be CYP2C9 substrates, and 17% to be inhibitors. The corresponding numbers for CYP2D6 were 9% and 21%. Where the majority of CYP2C9 active compounds were predicted to be both a substrate and an inhibitor at the same time, the CYP2D6 active compounds were primarily predicted to be only inhibitors. It was demonstrated that the models could identify compound classes with a high occurrence of specific CYP activity. An overrepresentation was seen for poly-aromatic hydrocarbons (group of procarcinogens) among CYP2C9 active and mutagenic compounds compared to CYP2C9 inactive and mutagenic compounds. The mutagenicity was predicted with a QSAR model based on Ames in vitro test data.

Organophosphate ester flame retardants have antiandrogenic potential and affect other endocrine related endpoints in vitro and in silico.

Organophosphate ester flame retardants (OPFRs) are used to prevent ignition and spreading of fire. They are present in various human matrices suggesting adult, fetal, and neonate exposure. Endocrine related effects have been observed in vivo, but information at the molecular level is lacking for some OPFRs. Also, a better understanding of potential contribution from chemical substructures is needed. The aim of this study was to screen OPFRs for endocrine disruptive potential in vitro and in silico. We selected eleven substances to represent some OPFRs with 1) little information on endocrine activity and others to represent 2) varied chemical substructures. We used in vitro assays for androgen receptor (AR), aryl hydrocarbon receptor (AhR), and Nrf2 activity, effects on steroidogenesis, and transthyretin (TTR) binding, as well as in silico models covering estrogen, thyroid, and CYP3A4 induction related endpoints. Ten OPFRs affected AR and AhR activity, seven affected TTR binding, and five affected 17ß-estradiol levels. Several substances had IC50-values below 10 µM and exhibited efficacious effects. These included TPHP, CDP, TMPP, TIPPP, and EHDPP for AR antagonism, suggesting that the degree of arylation and the size of the substance can play a role for the activity. Chlorinated OPFRs had low/no effect on TTR binding. No clear trend was observed for AhR and steroidogenesis, but all arylated OPFRs were predicted to have alert for estrogen receptor binding in an in silico model with metabolism simulator included. Collectively, our data suggest that OPFRs have endocrine disruptive potential warranting further studies to enable human risk assessment.

CERAPP: Collaborative Estrogen Receptor Activity Prediction Project.

BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. OBJECTIVES: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. METHODS: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. RESULTS: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. CONCLUSION: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points. CITATION: Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. 2016. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect 124:1023-1033; http://dx.doi.org/10.1289/ehp.1510267.

The ChemScreen project to design a pragmatic alternative approach to predict reproductive toxicity of chemicals.

There is a great need for rapid testing strategies for reproductive toxicity testing, avoiding animal use. The EU Framework program 7 project ChemScreen aimed to fill this gap in a pragmatic manner preferably using validated existing tools and place them in an innovative alternative testing strategy. In our approach we combined knowledge on critical processes affected by reproductive toxicants with knowledge on the mechanistic basis of such effects. We used in silico methods for prescreening chemicals for relevant toxic effects aiming at reduced testing needs. For those chemicals that need testing we have set up an in vitro screening panel that includes mechanistic high throughput methods and lower throughput assays that measure more integrative endpoints. In silico pharmacokinetic modules were developed for rapid exposure predictions via diverse exposure routes. These modules to match in vitro and in vivo exposure levels greatly improved predictivity of the in vitro tests. As a further step, we have generated examples how to predict reproductive toxicity of chemicals using available data. We have executed formal validations of panel constituents and also used more innovative manners to validate the test panel using mechanistic approaches. We are actively engaged in promoting regulatory acceptance of the tools developed as an essential step towards practical application, including case studies for read-across purposes. With this approach, a significant saving in animal use and associated costs seems very feasible.

Are structural analogues to bisphenol a safe alternatives?

BACKGROUND: Bisphenol A (BPA) is a chemical with widespread human exposure suspected of causing low-dose effects. Thus, a need for developing alternatives to BPA exists. Structural analogues of BPA have already been detected in foods and humans. Due to the structural analogy of the alternatives, there is a risk of effects similar to BPA. OBJECTIVES: The aim was to elucidate and compare the hazards of bisphenol B (BPB), bisphenol E (BPE), bisphenol F (BPF), bisphenol S (BPS) and 4-cumylphenol (HPP) to BPA. METHODS: In vitro studies on steroidogenesis, receptor activity, and biomarkers of effect, as well as Quantitative Structure-Activity Relationship (QSAR) modeling. RESULTS: All test compounds caused the same qualitative effects on estrogen receptor and androgen receptor activities, and most of the alternatives exhibited potencies within the same range as BPA. Hormone profiles for the compounds indicated a specific mechanism of action on steroidogenesis which generally lead to decreased androgen, and increased estrogen and progestagen levels. Differential effects on corticosteroid synthesis were observed suggesting a compound-specific mechanism. Overall, BPS was less estrogenic and antiandrogenic than BPA, but BPS showed the largest efficacy on 17α-hydroxyprogesterone (17α-OH progesterone). Finally, there were indications of DNA damage, carcinogenicity, oxidative stress, effects on metabolism, and skin sensitization of one or more of the test compounds. CONCLUSIONS: Interference with the endocrine system was the predominant effect of the test compounds. A substitution of BPA with these structural analogues should be carried out with caution.

Screening of 397 chemicals and development of a quantitative structure--activity relationship model for androgen receptor antagonism.

We have screened 397 chemicals for human androgen receptor (AR) antagonism by a sensitive reporter gene assay to generate data for the development of a quantitative structure-activity relationship (QSAR) model. A total of 523 chemicals comprising data on 292 chemicals from our laboratory and data on 231 chemicals from the literature constituted the training set for the model. The chemicals were selected with the purpose of representing a wide range of chemical structures (e.g., organochlorines and polycyclic aromatic hydrocarbons) and various functions (e.g., natural hormones, pesticides, plastizicers, plastic additives, brominated flame retardants, and roast mutagens). In addition, the intention was to obtain an equal number of positive and negative chemicals. Among our own data for the training set, 45.7% exhibited inhibitory activity against the transcriptional activity induced by the synthetic androgen R1881. The MultiCASE expert system was used to construct a QSAR model for AR antagonizing potential. A "5 Times, 2-Fold 50% Cross Validation" of the model showed a sensitivity of 64%, a specificity of 84%, and a concordance of 76%. Data for 102 chemicals were generated for an external validation of the model resulting in a sensitivity of 57%, a specificity of 98%, and a concordance of 92% of the model. The model was run on a set of 176103 chemicals, and 47% were within the domain of the model. Approximately 8% of chemicals was predicted active for AR antagonism. We conclude that the predictability of the global QSAR model for this end point is good. This most comprehensive QSAR model may become a valuable tool for screening large numbers of chemicals for AR antagonism.