In vitro cardiotoxicity assessment of environmental chemicals using an organotypic human induced pluripotent stem cell-derived model.

An important target area for addressing data gaps through in vitro screening is the detection of potential cardiotoxicants. Despite the fact that current conservative estimates relate at least 23% of all cardiovascular disease cases to environmental exposures, the identities of the causative agents remain largely uncharacterized. Here, we evaluate the feasibility of a combinatorial in vitro/in silico screening approach for functional and mechanistic cardiotoxicity profiling of environmental hazards using a library of 69 representative environmental chemicals and drugs. Human induced pluripotent stem cell-derived cardiomyocytes were exposed in concentration-response for 30min or 24h and effects on cardiomyocyte beating and cellular and mitochondrial toxicity were assessed by kinetic measurements of intracellular Ca2+ flux and high-content imaging using the nuclear dye Hoechst 33342, the cell viability marker Calcein AM, and the mitochondrial depolarization probe JC-10. More than half of the tested chemicals exhibited effects on cardiomyocyte beating after 30min of exposure. In contrast, after 24h, effects on cell beating without concomitant cytotoxicity were observed in about one third of the compounds. Concentration-response data for in vitro bioactivity phenotypes visualized using the Toxicological Prioritization Index (ToxPi) showed chemical class-specific clustering of environmental chemicals, including pesticides, flame retardants, and polycyclic aromatic hydrocarbons. For environmental chemicals with human exposure predictions, the activity-to-exposure ratios between modeled blood concentrations and in vitro bioactivity were between one and five orders of magnitude. These findings not only demonstrate that some ubiquitous environmental pollutants might have the potential at high exposure levels to alter cardiomyocyte function, but also indicate similarities in the mechanism of these effects both within and among chemicals and classes.

Assessment of beating parameters in human induced pluripotent stem cells enables quantitative in vitro screening for cardiotoxicity.

Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes show promise for screening during early drug development. Here, we tested a hypothesis that in vitro assessment of multiple cardiomyocyte physiological parameters enables predictive and mechanistically-interpretable evaluation of cardiotoxicity in a high-throughput format. Human iPSC-derived cardiomyocytes were exposed for 30 min or 24 h to 131 drugs, positive (107) and negative (24) for in vivo cardiotoxicity, in up to 6 concentrations (3 nM to 30 uM) in 384-well plates. Fast kinetic imaging was used to monitor changes in cardiomyocyte function using intracellular Ca(2+) flux readouts synchronous with beating, and cell viability. A number of physiological parameters of cardiomyocyte beating, such as beat rate, peak shape (amplitude, width, raise, decay, etc.) and regularity were collected using automated data analysis. Concentration-response profiles were evaluated using logistic modeling to derive a benchmark concentration (BMC) point-of-departure value, based on one standard deviation departure from the estimated baseline in vehicle (0.3% dimethyl sulfoxide)-treated cells. BMC values were used for cardiotoxicity classification and ranking of compounds. Beat rate and several peak shape parameters were found to be good predictors, while cell viability had poor classification accuracy. In addition, we applied the Toxicological Prioritization Index (ToxPi) approach to integrate and display data across many collected parameters, to derive "cardiosafety" ranking of tested compounds. Multi-parameter screening of beating profiles allows for cardiotoxicity risk assessment and identification of specific patterns defining mechanism-specific effects. These data and analysis methods may be used widely for compound screening and early safety evaluation in drug development.

A scoping review of the health and toxicological activity of bisphenol A (BPA) structural analogues and functional alternatives.

Recent studies report widespread usage or exposure to a variety of chemicals with structural or functional similarity to bisphenol A (BPA), referred to as BPA analogues or derivatives. These have been detected in foodstuffs, house dust, environmental samples, human urine or blood, and consumer products. Compared to BPA, relatively little is known about potential toxicity of these compounds. This scoping review aimed to summarize the human, animal, and mechanistic toxicity data for 24 BPA analogues of emerging interest to research and regulatory communities. PubMed was searched from March 1, 2015 to January 5, 2019 and combined with the results obtained from literature searches conducted through March 23, 2015, in The National Toxicology Program's Research Report 4 (NTP RR-04), "Biological Activity of Bisphenol A (BPA) Structural Analogues and Functional Alternatives". Study details are presented in interactive displays using Tableau Public. In total, 5748 records were screened for inclusion. One hundred sixty seven studies were included from NTP RR-04 and 175 studies were included from the updated literature search through January 2019. In total, there are 22, 117, and 221 human epidemiological, experimental animal, or in vitro studies included. The most frequently studied BPA analogues are bisphenol S (BPS), bisphenol F (4,4-BPF), and bisphenol AF (BPAF). Notable changes in the literature since 2015 include the growing body of human epidemiological studies and in vivo studies conducted in zebrafish. Numerous new endpoints were also evaluated across all three evidence streams including diabetes, obesity, and oxidative stress. However, few studies have addressed endpoints such as neurodevelopmental outcomes or impacts on the developing mammary or prostate glands, which are known to be susceptible to disruption by BPA. Further, there remains a critical need for better exposure information in order to prioritize experimental studies. Moving forward, researchers should also ensure that full dose responses are performed for all main effects in order to support hazard and risk characterization efforts. The evidence gathered here suggests that hazard and risk characterizations should expand beyond BPA in order to consider BPA structural and functional analogues.

Conditional Toxicity Value (CTV) Predictor: An In Silico Approach for Generating Quantitative Risk Estimates for Chemicals.

BACKGROUND: Human health assessments synthesize human, animal, and mechanistic data to produce toxicity values that are key inputs to risk-based decision making. Traditional assessments are data-, time-, and resource-intensive, and they cannot be developed for most environmental chemicals owing to a lack of appropriate data. OBJECTIVES: As recommended by the National Research Council, we propose a solution for predicting toxicity values for data-poor chemicals through development of quantitative structure-activity relationship (QSAR) models. METHODS: We used a comprehensive database of chemicals with existing regulatory toxicity values from U.S. federal and state agencies to develop quantitative QSAR models. We compared QSAR-based model predictions to those based on high-throughput screening (HTS) assays. RESULTS: QSAR models for noncancer threshold-based values and cancer slope factors had cross-validation-based Q2 of 0.25-0.45, mean model errors of 0.70-1.11 log10 units, and applicability domains covering >80% of environmental chemicals. Toxicity values predicted from QSAR models developed in this study were more accurate and precise than those based on HTS assays or mean-based predictions. A publicly accessible web interface to make predictions for any chemical of interest is available at http://toxvalue.org. CONCLUSIONS: An in silico tool that can predict toxicity values with an uncertainty of an order of magnitude or less can be used to quickly and quantitatively assess risks of environmental chemicals when traditional toxicity data or human health assessments are unavailable. This tool can fill a critical gap in the risk assessment and management of data-poor chemicals. https://doi.org/10.1289/EHP2998.

Standardizing benchmark dose calculations to improve science-based decisions in human health assessments.

BACKGROUND: Benchmark dose (BMD) modeling computes the dose associated with a prespecified response level. While offering advantages over traditional points of departure (PODs), such as no-observed-adverse-effect-levels (NOAELs), BMD methods have lacked consistency and transparency in application, interpretation, and reporting in human health assessments of chemicals. OBJECTIVES: We aimed to apply a standardized process for conducting BMD modeling to reduce inconsistencies in model fitting and selection. METHODS: We evaluated 880 dose-response data sets for 352 environmental chemicals with existing human health assessments. We calculated benchmark doses and their lower limits [10% extra risk, or change in the mean equal to 1 SD (BMD/L10/1SD)] for each chemical in a standardized way with prespecified criteria for model fit acceptance. We identified study design features associated with acceptable model fits. RESULTS: We derived values for 255 (72%) of the chemicals. Batch-calculated BMD/L10/1SD values were significantly and highly correlated (R2 of 0.95 and 0.83, respectively, n = 42) with PODs previously used in human health assessments, with values similar to reported NOAELs. Specifically, the median ratio of BMDs10/1SD:NOAELs was 1.96, and the median ratio of BMDLs10/1SD:NOAELs was 0.89. We also observed a significant trend of increasing model viability with increasing number of dose groups. CONCLUSIONS: BMD/L10/1SD values can be calculated in a standardized way for use in health assessments on a large number of chemicals and critical effects. This facilitates the exploration of health effects across multiple studies of a given chemical or, when chemicals need to be compared, providing greater transparency and efficiency than current approaches.