Cardiotoxicity Hazard and Risk Characterization of ToxCast Chemicals Using Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes from Multiple Donors

Heart disease remains a significant human health burden worldwide with a significant fraction of morbidity attributable to environmental exposures. However, the extent to which the thousands of chemicals in commerce and the environment may contribute to heart disease morbidity is largely unknown, because in contrast to pharmaceuticals, environmental chemicals are seldom tested for potential cardiotoxicity. Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes have become an informative in vitro model for cardiotoxicity testing of drugs with the availability of cells from multiple individuals allowing in vitro testing of population variability. In this study, we hypothesized that a panel of iPSC-derived cardiomyocytes from healthy human donors can be used to screen for the potential cardiotoxicity hazard and risk of environmental chemicals. We conducted concentration-response testing of 1029 chemicals (drugs, pesticides, flame retardants, polycyclic aromatic hydrocarbons (PAHs), plasticizers, industrial chemicals, food/flavor/fragrance agents, etc.) in iPSC-derived cardiomyocytes from 5 donors. We used kinetic calcium flux and high-content imaging to derive quantitative measures as inputs into Bayesian population concentration-response modeling of the effects of each chemical. We found that many environmental chemicals pose a hazard to human cardiomyocytes in vitro with more than half of all chemicals eliciting positive or negative chronotropic or arrhythmogenic effects. However, most of the tested environmental chemicals for which human exposure and high-throughput toxicokinetics data were available had wide margins of exposure and, thus, do not appear to pose a significant human health risk in a general population. Still, relatively narrow margins of exposure (<100) were estimated for some perfuoroalkyl substances and phthalates, raising concerns that cumulative exposures may pose a cardiotoxicity risk. Collectively, this study demonstrated the value of using a population-based human in vitro model for rapid, high-throughput hazard and risk characterization of chemicals for which little to no cardiotoxicity data are available from guideline studies in animals.

Environmental impacts of Hurricane Florence flooding in eastern North Carolina: temporal analysis of contaminant distribution and potential human health risks

BACKGROUND

Hurricane Florence made landfall in North Carolina in September 2018 causing extensive flooding. Several potential point sources of hazardous substances and Superfund sites sustained water damage and contaminants may have been released into the environment.

OBJECTIVE

This study conducted temporal analysis of contaminant distribution and potential human health risks from Hurricane Florence-associated flooding.

METHODS

Soil samples were collected from 12 sites across four counties in North Carolina in September 2018, January and May 2019. Chemical analyses were performed for organics by gas chromatography-mass spectrometry. Metals were analyzed using inductively coupled plasma mass spectrometry. Hazard index and cancer risk were calculated using EPA Regional Screening Level Soil Screening Levels for residential soils.

RESULTS

PAH and metals detected downstream from the coal ash storage pond that leaked were detected and were indicative of a pyrogenic source of contamination. PAH at these sites were of human health concern because cancer risk values exceeded 1 × 10^-6 threshold. Other contaminants measured across sampling sites, or corresponding hazard index and cancer risk, did not exhibit spatial or temporal differences or were of concern.

SIGNIFICANCE

This work shows the importance of rapid exposure assessment following natural disasters. It also establishes baseline levels of contaminants for future comparisons.

Spatial and temporal distribution of surface water contaminants in the Houston Ship Channel after the Intercontinental Terminal Company Fire

BACKGROUND

The fire at the Intercontinental Terminals Company (ITC, Deer Park, La Porte, TX, USA) from March 17 to 20, 2019 resulted in substantial releases of chemical contaminants to the environment, including the surface waters of the Houston Ship Channel.

OBJECTIVE

To characterize spatial and temporal trends, as well as potential human health risks, from these releases.

METHODS

Out of 433 substances with available data, seven were selected for analysis: benzene, toluene, ethylbenzene, xylenes, oil and grease, suspended solids, and total petroleum hydrocarbons. Spatial and temporal concentration trends were characterized, and hazard quotients and cancer risks were calculated to estimate the potential for human health impacts from these contaminants.

RESULTS

Temporal analysis showed presence of these chemical contaminants in water immediately after the event; their concentrations dissipated substantially within 4 weeks. The spatial distribution of contaminants indicated the highest concentrations in the waterways within about 1 km of the ITC. The greatest potential human health risks stemmed from presence of benzene.

SIGNIFICANCE

A short-term but substantial spike in the concentrations of a number of hazardous contaminants occurred near the incident, with concentrations returning to apparent baseline levels within 1 month likely due to a combination of volatization, dilution and degradation.

Risk Characterization of Environmental Samples Using In Vitro Bioactivity and Polycyclic Aromatic Hydrocarbon Concentrations Data

Methods to assess environmental exposure to hazardous chemicals have primarily focused on quantification of individual chemicals, although chemicals often occur in mixtures, presenting challenges to the traditional risk characterization framework. Sampling sites in a defined geographic region provide an opportunity to characterize chemical contaminants, with spatial interpolation as a tool to provide estimates for non-sampled sites. At the same time, the use of in vitro bioactivity measurements has been shown to be informative for rapid risk-based decisions. In this study, we measured in vitro bioactivity in 39 surface soil samples collected immediately after flooding associated with Hurricane Harvey in Texas in a residential area known to be inundated with polycyclic aromatic hydrocarbon (PAH) contaminants. Bioactivity data were from a number of functional and toxicity assays in 5 human cell types, such as induced pluripotent stem cell-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, as well as human umbilical vein endothelial cells. Data on concentrations of PAH in these samples were also available and the combination of data sources offered a unique opportunity to assess the joint spatial variation of PAH components and bioactivity. We found significant evidence of spatial correlation of a subset of PAH contaminants and of cell-based phenotypes. In addition, we show that the cell-based bioactivity data can be used to predict environmental concentrations for several PAH contaminants, as well as overall PAH summaries and cancer risk. This study's impact lies in its demonstration that cell-based profiling can be used for rapid hazard screening of environmental samples by anchoring the bioassays to concentrations of PAH. This work sets the stage for identification of the areas of concern and direct quantitative risk characterization based on bioactivity data, thereby providing an important supplement to traditional individual chemical analyses by shedding light on constituents that may be missed from targeted chemical monitoring.

Quantitative Characterization of Population-Wide Tissue- and Metabolite-Specific Variability in Perchloroethylene Toxicokinetics in Male Mice

Quantification of interindividual variability is a continuing challenge in risk assessment, particularly for compounds with complex metabolism and multi-organ toxicity. Toxicokinetic variability for perchloroethylene (perc) was previously characterized across 3 mouse strains and in 1 mouse strain with various degrees of liver steatosis. To further characterize the role of genetic variability in toxicokinetics of perc, we applied Bayesian population physiologically based pharmacokinetic (PBPK) modeling to the data on perc and metabolites in blood/plasma and tissues of male mice from 45 inbred strains from the Collaborative Cross (CC) mouse population. After identifying the most influential PBPK parameters based on global sensitivity analysis, we fit the model with a hierarchical Bayesian population analysis using Markov chain Monte Carlo simulation. We found that the data from 3 commonly used strains were not representative of the full range of variability in perc and metabolite blood/plasma and tissue concentrations across the CC population. Using interstrain variability as a surrogate for human interindividual variability, we calculated dose-dependent, chemical-, and tissue-specific toxicokinetic variability factors (TKVFs) as candidate science-based replacements for the default uncertainty factor for human toxicokinetic variability of 100.5. We found that toxicokinetic variability factors for glutathione conjugation metabolites of perc showed the greatest variability, often exceeding the default, whereas those for oxidative metabolites and perc itself were generally less than the default. Overall, we demonstrate how a combination of a population-based mouse model such as the CC with Bayesian population PBPK modeling can reduce uncertainty in human toxicokinetic variability and increase accuracy and precision in quantitative risk assessment.

A Bayesian Method for Population-wide Cardiotoxicity Hazard and Risk Characterization Using an In Vitro Human Model

Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes are an established model for testing potential chemical hazards. Interindividual variability in toxicodynamic sensitivity has also been demonstrated in vitro; however, quantitative characterization of the population-wide variability has not been fully explored. We sought to develop a method to address this gap by combining a population-based iPSC-derived cardiomyocyte model with Bayesian concentration-response modeling. A total of 136 compounds, including 54 pharmaceuticals and 82 environmental chemicals, were tested in iPSC-derived cardiomyocytes from 43 nondiseased humans. Hierarchical Bayesian population concentration-response modeling was conducted for 5 phenotypes reflecting cardiomyocyte function or viability. Toxicodynamic variability was quantified through the derivation of chemical- and phenotype-specific variability factors. Toxicokinetic modeling was used for probabilistic in vitro-to-in vivo extrapolation to derive population-wide margins of safety for pharmaceuticals and margins of exposure for environmental chemicals. Pharmaceuticals were found to be active across all phenotypes. Over half of tested environmental chemicals showed activity in at least one phenotype, most commonly positive chronotropy. Toxicodynamic variability factor estimates for the functional phenotypes were greater than those for cell viability, usually exceeding the generally assumed default of approximately 3. Population variability-based margins of safety for pharmaceuticals were correctly predicted to be relatively narrow, including some below 10; however, margins of exposure for environmental chemicals, based on population exposure estimates, generally exceeded 1000, suggesting they pose little risk at current general population exposures even to sensitive subpopulations. Overall, this study demonstrates how a high-throughput, human population-based, in vitro-in silico model can be used to characterize toxicodynamic population variability in cardiotoxic risk.

Heart Muscle Microphysiological System for Cardiac Liability Prediction of Repurposed COVID-19 Therapeutics

Despite global efforts, it took 7 months between the proclamation of global SARS-CoV-2 pandemic and the first FDA-approved treatment for COVID-19. During this timeframe, clinicians focused their efforts on repurposing drugs, such as hydroxychloroquine (HCQ) or azithromycin (AZM) to treat hospitalized COVID-19 patients. While clinical trials are time-consuming, the exponential increase in hospitalizations compelled the FDA to grant an emergency use authorization for HCQ and AZM as treatment for COVID-19, although there was limited evidence of their combined efficacy and safety. The authorization was revoked 4 months later, giving rise to controversial political and scientific debates illustrating important challenges such as premature authorization of potentially ineffective or unsafe therapeutics, while diverting resources from screening of effective drugs. Here we report on a preclinical drug screening platform, a cardiac microphysiological system (MPS), to rapidly identify clinically relevant cardiac liabilities associated with HCQ and AZM. The cardiac MPS is a microfabricated fluidic system in which cardiomyocytes derived from human induced pluripotent stem cells self-arrange into a uniaxially beating tissue. The drug response was measured using outputs that correlate with clinical measurements such as action potential duration (proxy for clinical QT interval) and drug-biomarker pairing. The cardiac MPS predicted clinical arrhythmias associated with QT prolongation and rhythm instabilities in tissues treated with HCQ. We found no change in QT interval upon acute exposure to AZM, while still observing a significant increase in arrhythmic events. These results suggest that this MPS can not only predict arrhythmias, but it can also identify arrhythmias even when QT prolongation is absent. When exposed to HCQ and AZM polytherapy, this MPS faithfully reflected clinical findings, in that the combination of drugs synergistically increased QT interval when compared to single drug exposure, while not worsening the overall frequency of arrhythmic events. The high content cardiac MPS can rapidly evaluate the cardiac safety of potential therapeutics, ultimately accelerating patients' access to safe and effective treatments.

The DEN and CCl4 -Induced Mouse Model of Fibrosis and Inflammation-Associated Hepatocellular Carcinoma

Human hepatocellular carcinoma (HCC) develops most often as a complication of fibrosis or cirrhosis. Although most human studies of HCC provide crucial insights into the molecular signatures of HCC, they seldom address its etiology. Mouse models provide essential tools for investigating the pathogenesis of HCC, but the majority of rodent cancer models do not feature liver fibrosis. Detailed here is a protocol for an experimental mouse model of HCC that arises in association with advanced liver fibrosis. The disease model is induced by a single injection of N-nitrosodiethylamine (DEN) at 2 weeks of age followed by repeated administration of carbon tetrachloride (CCl₄ ) from 8 weeks of age for up to 14 consecutive weeks. A dramatic potentiation of liver tumor incidence is observed following administration of DEN and CCl₄ , with 100% of mice developing liver tumors at 5 months of age. This model has been employed for studying the molecular mechanisms of fibrogenesis and HCC development, as well as for cancer hazard/chemotherapy testing of drug candidates. © 2021 Wiley Periodicals LLC. Basic Protocol: The DEN and CCl₄ -induced mouse model of fibrosis and inflammation-associated hepatocellular carcinoma.

Data Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility Spectrometry-Mass Spectrometry

Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) is a post-ionization separation technique that can be used for rapid multidimensional analyses of complex samples. IMS-MS offers untargeted analysis, including ion-specific conformational data derived as collisional cross section (CCS) values. Here, we combine nitrogen gas drift tube CCS (^DTCCS_N2) and Kendrick mass defect (KMD) analyses based on CH2 and H functional units to enable compositional analyses of petroleum substances. First, polycyclic aromatic compound standards were analyzed by IMS-MS to demonstrate how CCS assists the identification of isomeric species in homologous series. Next, we used case studies of a gasoline standard previously characterized for paraffin, isoparaffin, aromatic, naphthene, and olefinic (PIANO) compounds, and a crude oil sample to demonstrate the application of the KMD analyses and CCS filtering. Finally, we propose a workflow that enables confident molecular formula assignment to the IMS-MS-derived features in petroleum samples. Collectively, this work demonstrates how rapid untargeted IMS-MS analysis and the proposed data processing workflow can be used to provide confident compositional characterization of hydrocarbon-containing substances.

Quantitative in Vitro-to-in Vivo Extrapolation for Mixtures: A Case Study of Superfund Priority List Pesticides

In vitro cell-based toxicity testing methods generate large amounts of data informative for risk-based evaluations. To allow extrapolation of the quantitative outputs from cell-based tests to the equivalent exposure levels in humans, reverse toxicokinetic (RTK) modeling is used to conduct in vitro-to-in vivo extrapolation (IVIVE) from in vitro effective concentrations to in vivo oral dose equivalents. IVIVE modeling approaches for individual chemicals are well-established; however, the potential implications of chemical-to-chemical interactions in mixture settings on IVIVE remains largely unexplored. We hypothesized that chemical co-exposures could modulate both protein binding efficiency and hepatocyte clearance of the chemicals in a mixture, which would in turn affect the quantitative IVIVE toxicokinetic parameters. To test this hypothesis, we used 20 pesticides from the Agency for Toxic Substances and Disease Registry (ATSDR) Substance Priority List, both individually and as equimolar mixtures, and investigated the concentration-dependent effects of chemical interactions on in vitro toxicokinetic parameters. Plasma protein binding efficiency was determined by using ultracentrifugation, and hepatocyte clearance was estimated in suspensions of cryopreserved primary human hepatocytes. We found that for single chemicals, the protein binding efficiencies were similar at different test concentrations. In a mixture, however, both protein binding efficiency and hepatocyte clearance were affected. When IVIVE was conducted using mixture-derived toxicokinetic data, more conservative estimates of Activity-to-Exposure Ratios (AERs) were produced as compared to using data from single chemical experiments. Because humans are exposed to mixtures of chemicals, this study is significant as it demonstrates the importance of incorporating mixture-derived parameters into IVIVE for in vitro bioactivity data in order to accurately prioritize risks and facilitate science-based decision-making.

Species differences between mouse and human PPARα in modulating the hepatocarcinogenic effects of perinatal exposure to a high-affinity human PPARα agonist in mice

Evidence suggests that species differences exist between rodents and humans in their biological responses to ligand activation of PPARα. Moreover, neonatal/postnatal rodents may be more sensitive to the effects of activating PPARα. Thus, the present studies examined the effects of chronic ligand activation of PPARα initiated during early neonatal development and continued into adulthood on hepatocarcinogenesis in mice. Wild-type, Ppara-null, or PPARA-humanized mice were administered a potent, high affinity human PPARα agonist GW7647, and cohorts of mice were examined over time. Activation of PPARα with GW7647 increased expression of known PPARα target genes in liver and was associated with hepatomegaly, increased hepatic cytotoxicity and necrosis, increased expression of hepatic MYC, and a high incidence of hepatocarcinogenesis in wild-type mice. These effects did not occur or were largely diminished in Ppara-null and PPARA-humanized mice, although background levels of hepatocarcinogenesis were also noted in both Ppara-null and PPARA-humanized mice. More fatty change (steatosis) was also observed in both Ppara-null and PPARA-humanized mice independent of GW7647 administration. Results from these studies indicate that the mouse PPARα is required to mediate hepatocarcinogenesis induced by GW7647 in mice and that activation of the human PPARα with GW7647 in PPARA-humanized mice are diminished compared to wild-type mice. Ppara-null and PPARA-humanized mice are valuable tools for examining species differences in the mechanisms of PPARα-induced hepatocarcinogenesis, but background levels of liver cancer observed in aged Ppara-null and PPARA-humanized mice must be considered when interpreting results from studies that use these models. These results also demonstrate that early life exposure to a potent human PPARα agonist does not enhance sensitivity to hepatocarcinogenesis.

Diminished hepatocarcinogenesis by a potent, high affinity human PPARα agonist in PPARA-humanized mice

Ppara-null and PPARA-humanized mice are refractory to hepatocarcinogenesis caused by the peroxisome proliferator-activated receptor-α (PPARα) agonist Wy-14,643. However, the duration of these earlier studies was limited to approximately one year of treatment, and the ligand used has higher affinity for the mouse PPARα compared to the human PPARα. Thus, the present study examined the effect of long-term administration of a potent, high affinity human PPARα agonist (GW7647) on hepatocarcinogenesis in wild-type, Ppara-null, or PPARA-humanized mice. In wild-type mice, GW7647 caused hepatic expression of known PPARα target genes, hepatomegaly, hepatic MYC expression, hepatic cytotoxicity, and a high incidence of hepatocarcinogenesis. By contrast, these effects were essentially absent in Ppara-null mice or diminished in PPARA-humanized mice, although hepatocarcinogenesis was observed in both genotypes. Enhanced fatty change (steatosis) was also observed in both Ppara-null and PPARA-humanized mice independent of GW7647. PPARA-humanized mice administered GW7647 also exhibited increased necrosis after five weeks of treatment. Results from these studies demonstrate that the mouse PPARα is required for hepatocarcinogenesis induced by GW7647 administered throughout adulthood. Results also indicate that a species difference exists between rodent and human PPARα in the response to ligand activation of PPARα. The hepatocarcinogenesis observed in control and treated Ppara-null mice is likely mediated in part by increased hepatic fatty change, whereas the hepatocarcinogenesis observed in PPARA-humanized mice may also be due to enhanced fatty change and cytotoxicity that could be influenced by minimal activity of the human PPARα in this mouse line on downstream mouse PPARα target genes. The Ppara-null and PPARA-humanized mouse models are valuable tools for examining the mechanisms of PPARα-induced hepatocarcinogenesis but the background level of liver cancer must be controlled for in the design and interpretation of studies that use these mice.

In Vitro Bioavailability of the Hydrocarbon Fractions of Dimethyl Sulfoxide Extracts of Petroleum Substances

Determining the in vitro bioavailable concentration is a critical, yet unmet need to refine in vitro-to-in vivo extrapolation for unknown or variable composition, complex reaction product or biological material (UVCB) substances. UVCBs such as petroleum substances are commonly subjected to dimethyl sulfoxide (DMSO) extraction in order to retrieve the bioactive polycyclic aromatic compound (PAC) portion for in vitro testing. In addition to DMSO extraction, protein binding in cell culture media and dilution can all influence in vitro bioavailable concentrations of aliphatic and aromatic compounds in petroleum substances. However, these in vitro factors have not been fully characterized. In this study, we aimed to fill in these data gaps by characterizing the effects of these processes using both a defined mixture of analytical standards containing aliphatic and aromatic hydrocarbons, as well as 4 refined petroleum products as prototypical examples of UVCBs. Each substance was extracted with DMSO, and the protein binding in cell culture media was measured by using solid-phase microextraction. Semiquantitative analysis for aliphatic and aromatic compounds was achieved via gas chromatography-mass spectrometry. Our results showed that DMSO selectively extracted PACs from test substances, and that chemical profiles of PACs across molecular classes remained consistent after extraction. With respect to protein binding, chemical profiles were retained at a lower dilution (higher concentration), but a greater dilution factor (ie, lower concentration) resulted in higher protein binding in cell medium, which in turn altered the ultimate chemical profile of bioavailable PACs. Overall, this case study demonstrates that extraction procedures, protein binding in cell culture media, and dilution factors prior to in vitro testing can all contribute to determining the final bioavailable concentrations of bioactive constituents of UVCBs in vitro. Thus, in vitro-to-in vivo extrapolation for UVCBs may require greater attention to the concentration-dependent and compound-specific differences in recovery and bioavailability.

Tissue-Engineered Bone Tumor as a Reproducible Human in Vitro Model for Studies of Anticancer Drugs

Studies of anticancer therapies in traditional cell culture models can demonstrate efficacy of direct-acting compounds but lack the 3-dimensional arrangement of the tumor cells and their tissue-specific microenvironments, both of which are important modulators of treatment effects in vivo. Bone cells reside in complex environments that regulate their fate and function. A bioengineered human bone-tumor model has been shown to provide a microphysiological niche for studies of cancer cell behavior. Here, we demonstrate successful transfer between 2 laboratories and utility of this model in efficacy studies using well-established chemotherapeutic agents. The bioengineered human bone-tumor model consisted of Ewing sarcoma (RD-ES) cancer cell aggregates infused into tissue-engineered bone that was grown from human mesenchymal stem cell-derived differentiated into osteoblasts within mineralized bone scaffolds. The tumor model was maintained in culture for over 5 weeks and subjected to clinically relevant doses of linsitinib, doxorubicin, cisplatin, methotrexate, vincristine, dexamethasone, or MAP (methotrexate, doxorubicin, and cisplatin combination). Drug administration cycles were designed to mimic clinical treatment regimens. The bioengineered tumors were evaluated days to weeks after the cessation of treatment to monitor the potential for relapse, using bioengineered bone and ES cell monolayers as controls. Drug binding to the scaffolds and media proteins and gene expression were also evaluated. We show that a bioengineered human bone tumor can be used as a microphysiological model for preclinical studies of anticancer drugs. We found that anticancer efficacy was achieved at concentrations approximating the human Cmax, in contrast to traditional ES cell monolayers. These studies show that the bone-tumor model can be successfully transferred between laboratories and has predictive power in preclinical studies. The effects of drugs on the bone tumors and healthy bone were studied in parallel, in support of the utility of this model for identification of new therapeutic targets.

Curated Data In - Trustworthy In Silico Models Out: The Impact of Data Quality on the Reliability of Artificial Intelligence Models as Alternatives to Animal Testing

New Approach Methodologies (NAMs) that employ artificial intelligence (AI) for predicting adverse effects of chemicals have generated optimistic expectations as alternatives to animal testing. However, the major underappreciated challenge in developing robust and predictive AI models is the impact of the quality of the input data on the model accuracy. Indeed, poor data reproducibility and quality have been frequently cited as factors contributing to the crisis in biomedical research, as well as similar shortcomings in the fields of toxicology and chemistry. In this article, we review the most recent efforts to improve confidence in the robustness of toxicological data and investigate the impact that data curation has on the confidence in model predictions. We also present two case studies demonstrating the effect of data curation on the performance of AI models for predicting skin sensitisation and skin irritation. We show that, whereas models generated with uncurated data had a 7-24% higher correct classification rate (CCR), the perceived performance was, in fact, inflated owing to the high number of duplicates in the training set. We assert that data curation is a critical step in building computational models, to help ensure that reliable predictions of chemical toxicity are achieved through use of the models.

Testing the efficacy of broad-acting sorbents for environmental mixtures using isothermal analysis, mammalian cells, and H. vulgaris

The hazards associated with frequent exposure to polycyclic aromatic hydrocarbons (PAHs), pesticides, Aroclors, plasticizers, and mycotoxins are well established. Adsorption strategies have been proposed for the remediation of soil and water, although few have focused on the mitigation of mixtures. This study tested a hypothesis that broad-acting sorbents can be developed for diverse chemical mixtures. Adsorption of common and hazardous chemicals was characterized using isothermal analysis from Langmuir and Freundlich equations. The most effective sorbents included medical-grade activated carbon (AC), parent montmorillonite clay, acid-processed montmorillonite (APM), and nutrient-amended montmorillonite clays. Next, we tested the ability of broad-acting sorbents to prevent cytotoxicity of class-specific mixtures using 3 mammalian in vitro models (HLF, ESD3, and 3T3 cell lines) and the hydra assay. AC showed the highest efficacy for mitigating pesticides, plasticizers, PAHs, and mycotoxins. Clays, such as APM, were effective against pesticides, Aroclors, and mycotoxins, while amended clays were most effective against plasticizers. Finally, a sorbent mixture was shown to be broadly active. These results are supported by the high correlation coefficients for the Langmuir model with high capacity, affinity, and free energy, as well as the significant protection of cells and hydra (p < 0.05). The protection percentages in 3T3 cells and hydra showed the highest correlation as suggested by both Pearson and Spearman with r = 0.84 and rho = 0.73, respectively (p < 0.0001). Collectively, these studies showed that broad-acting sorbents may be effective in preventing toxic effects of chemical mixtures and provided information on the most effective sorbents based on adsorption isotherms, and in vitro and aquatic organism test methods.

A Comparative Analysis of Analytical Techniques for Rapid Oil Spill Identification

The complex chemical composition of crude oils presents many challenges for rapid chemical characterization in the case of a spill. A number of approaches are currently used to "fingerprint" petroleum-derived samples. Gas chromatography coupled with mass spectrometry (GC-MS) is the most common, albeit not very rapid, technique; however, with GC-MS alone, it is difficult to resolve the complex substances in crude oils. The present study examined the potential application of ion mobility spectrometry-mass spectrometry (IMS-MS) coupled with chem-informatic analyses as an alternative high-throughput method for the chemical characterization of crude oils. We analyzed 19 crude oil samples from on- and offshore locations in the Gulf of Mexico region in the United States using both GC-MS (biomarkers, gasoline range hydrocarbons, and n-alkanes) and IMS-MS (untargeted analysis). Hierarchical clustering, principal component analysis, and nearest neighbor-based classification were used to examine sample similarity and geographical groupings. We found that direct-injection IMS-MS performed either equally or better than GC-MS in the classification of the origins of crude oils. In addition, IMS-MS greatly increased the sample analysis throughput (minutes vs hours per sample). Finally, a tabletop science-to-practice exercise, utilizing both the GC-MS and IMS-MS data, was conducted with emergency response experts from regulatory agencies and the oil industry. This activity showed that the stakeholders found the IMS-MS data to be highly informative for rapid chemical fingerprinting of complex substances in general and specifically advantageous for accurate and confident source-grouping of crude oils. Collectively, the present study shows the utility of IMS-MS as a technique for rapid fingerprinting of complex samples and demonstrates its advantages over traditional GC-MS-based analyses when used for decision-making in emergency situations. Environ Toxicol Chem 2021;40:1034-1049. © 2020 SETAC.

Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes as an in vitro model in toxicology: strengths and weaknesses for hazard identification and risk characterization

INTRODUCTION

Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes is one of the most widely used cell-based models that resulted from the discovery of how non-embryonic stem cells can be differentiated into multiple cell types. In just one decade, iPSC-derived cardiomyocytes went from a research lab to widespread use in biomedical research and preclinical safety evaluation for drugs and other chemicals.

AREAS COVERED

This manuscript reviews data on toxicology applications of human iPSC-derived cardiomyocytes. We detail the outcome of a systematic literature search on their use (i) in hazard assessment for cardiotoxicity liabilities, (ii) for risk characterization, (iii) as models for population variability, and (iv) in studies of personalized medicine and disease.

EXPERT OPINION

iPSC-derived cardiomyocytes are useful to increase the accuracy, precision, and efficiency of cardiotoxicity hazard identification for both drugs and non-pharmaceuticals, with recent efforts beginning to demonstrate their utility for risk characterization. Notable limitations include the needs to improve the maturation of cells in culture, to better understand their potential use identifying structural cardiotoxicity, and for additional case studies involving population-wide and disease-specific risk characterization. Ultimately, the greatest future benefits are likely for non-pharmaceutical chemicals, filling a critical gap where no routine testing for cardiotoxicity is currently performed.

Relationships between constituents of energy drinks and beating parameters in human induced pluripotent stem cell (iPSC)-Derived cardiomyocytes

Consumption of energy drinks has been associated with adverse cardiovascular effects; however, little is known about the ingredients that may contribute to these effects. We therefore characterized the chemical profiles and in vitro effects of energy drinks and their ingredients on human induced pluripotent stem cell (iPSC)-derived cardiomyocytes, and identified the putative active ingredients using a multivariate prediction model. Energy drinks from 17 widely-available over-the-counter brands were evaluated in this study. The concentrations of six common ingredients (caffeine, taurine, riboflavin, pantothenic acid, adenine, and L-methionine) were quantified by coupling liquid chromatography with a triple quadrupole mass spectrometer for the acquisition of LC-MS/MS spectra. In addition, untargeted analyses for each beverage were performed with a platform combining LC, ion mobility spectrometry and mass spectrometry (LC-IMS-MS) measurements. Approximately 300 features were observed across samples in the untargeted studies, and of these ~100 were identified. In vitro effects of energy drinks and some of their ingredients were then tested in iPSC-derived cardiomyocytes. Data on the beat rate (positive and negative chronotropy), ion channel function (QT prolongation), and cytotoxicity were collected in a dilution series. We found that some of the energy drinks elicited adverse effects on the cardiomyocytes with the most common being an increase in the beat rate, while QT prolongation was also observed at the lowest concentrations. Finally, concentration addition modeling using quantitative data from the 6 common ingredients and multivariate prediction modeling was used to determine potential ingredients responsible for the adverse effects on the cardiomyocytes. These analyses suggested theophylline, adenine, and azelate as possibly contributing to the in vitro effects of energy drinks on QT prolongation in cardiomyocytes.

Risk Characterization and Probabilistic Concentration-Response Modeling of Complex Environmental Mixtures Using New Approach Methodologies (NAMs) Data from Organotypic in Vitro Human Stem Cell Assays

BACKGROUND

Risk assessment of chemical mixtures or complex substances remains a major methodological challenge due to lack of available hazard or exposure data. Therefore, risk assessors usually infer hazard or risk from data on the subset of constituents with available toxicity values.

OBJECTIVES

We evaluated the validity of the widely used traditional mixtures risk assessment paradigms, Independent Action (IA) and Concentration Addition (CA), with new approach methodologies (NAMs) data from human cell-based in vitro assays.

METHODS

A diverse set of 42 chemicals was tested both individually and as mixtures for functional and cytotoxic effects in vitro. A panel of induced pluripotent stem cell (iPSCs)-derived models (hepatocytes, cardiomyocytes, endothelial, and neurons) and one primary cell type (HUVEC) were used. Bayesian concentration-response modeling of individual chemicals or their mixtures was performed for a total of 47 phenotypes to derive point-of-departure (POD) values. Probabilistic IA or CA was conducted to estimate the mixture effects based on the bioactivity profiles from the individual chemicals and compared with mixture bioactivity.

RESULTS

All mixtures showed significant bioactivity, even though some were constructed using individual chemical concentrations considered "low" or "safe." Even though CA is much more accurate as a predictor of mixture effects in comparison with IA, with CA-based POD typically within an order of magnitude of the actual mixture, in some cases, the bioactivity of the mixtures appeared to be much greater than that of their components under either additivity assumption.

DISCUSSION

These results suggest that CA is a preferred first approximation for predicting mixture toxicity when data for all constituents are available. However, because the accuracy of additivity assumptions varies greatly across phenotypes, we posit that mixtures and complex substances need to be directly tested for their hazard potential. NAMs provide a practical solution that rapidly yields highly informative data for mixtures risk assessment. https://doi.org/10.1289/EHP7600.

Rapid Characterization of Emerging Per- and Polyfluoroalkyl Substances in Aqueous Film-Forming Foams Using Ion Mobility Spectrometry-Mass Spectrometry

Aqueous film-forming foams (AFFF) are mixtures formulated with numerous hydrocarbon- and fluoro-containing surfactants. AFFF use leads to environmental releases of unknown per- and polyfluoroalkyl substances (PFAS). AFFF composition is seldom disclosed, and their use elicits concerns from both regulatory agencies and the public because PFAS are persistent in the environment and potentially associated with adverse health effects. In this study, we demonstrate the use of coupled liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) to rapidly characterize both known and unknown PFAS in AFFF. Ten AFFF formulations from seven brands were analyzed using LC-IMS-MS in both negative and positive ion modes. Untargeted analysis of the formulations was followed by feature identification of PFAS-like features utilizing database matching, mass defect and homologous series evaluation, and MS/MS fragmentation experiments. Across the tested AFFF formulations, we identified 33 homologous series; only ten of these homologous series have been previously reported. Among tested AFFF, the FireStopper (n = 85) contained the greatest number of PFAS-like features and Phos-Check contained zero. This work demonstrates that LC-IMS-MS-enabled untargeted analysis of complex formulations, followed by feature identification using data-processing algorithms, can be used for rapid exposure characterization of known and putative PFAS during fire suppression-related contamination events.

Human in vitro vascularized micro-organ and micro-tumor models are reproducible organ-on-a-chip platforms for studies of anticancer drugs

Angiogenesis is a complex process that is required for development and tissue regeneration and it may be affected by many pathological conditions. Chemicals and drugs can impact formation and maintenance of the vascular networks; these effects may be both desirable (e.g., anti-cancer drugs) or unwanted (e.g., side effects of drugs). A number of in vivo and in vitro models exist for studies of angiogenesis and endothelial cell function, including organ-on-a-chip microphysiological systems. An arrayed organ-on-a-chip platform on a 96-well plate footprint that incorporates perfused microvessels, with and without tumors, was recently developed and it was shown that survival of the surrounding tissue was dependent on delivery of nutrients through the vessels. Here we describe a technology transfer of this complex microphysiological model between laboratories and demonstrate that reproducibility and robustness of these tissue chip-enabled experiments depend primarily on the source of the endothelial cells. The model was highly reproducible between laboratories and was used to demonstrate the advantages of the perfusable vascular networks for drug safety evaluation. As a proof-of-concept, we tested Fluorouracil (1-1,000 μM), Vincristine (1-1,000 nM), and Sorafenib (0.1-100 μM), in the perfusable and non-perfusable micro-organs, and in a colon cancer-containing micro-tumor model. Tissue chip experiments were compared to the traditional monolayer cultures of endothelial or tumor cells. These studies showed that human in vitro vascularized micro-organ and micro-tumor models are reproducible organ-on-a-chip platforms for studies of anticancer drugs. The data from the 3D models confirmed advantages of the physiological environment as compared to 2D cell cultures. We demonstrated how these models can be translated into practice by verifying that the endothelial cell source and passage are critical elements for establishing a perfusable model.

Grouping of UVCB substances with new approach methodologies (NAMs) data

One of the most challenging areas in regulatory science is assessment of the substances known as UVCB (unknown or variable composition, complex reaction products and biological materials). Because the inherent complexity and variability of UVCBs present considerable challenges for establishing sufficient substance similarity based on chemical characteristics or other data, we hypothesized that new approach methodologies (NAMs), including in vitro test-derived biological activity signatures to characterize substance similarity, could be used to support grouping of UVCBs. We tested 141 petroleum substances as representative UVCBs in a compendium of 15 human cell types representing a variety of tissues. Petroleum substances were assayed in dilution series to derive point of departure estimates for each cell type and phenotype. Extensive quality control measures were taken to ensure that only high-confidence in vitro data were used to determine whether current groupings of these petroleum substances, based largely on the manufacturing process and physico-chemical properties, are justifiable. We found that bioactivity data-based groupings of petroleum substances were generally consistent with the manufacturing class-based categories. We also showed that these data, especially bioactivity from human induced pluripotent stem cell (iPSC)-derived and primary cells, can be used to rank substances in a manner highly concordant with their expected in vivo hazard potential based on their chemical compositional profile. Overall, this study demonstrates that NAMs can be used to inform groupings of UVCBs, to assist in identification of representative substances in each group for testing when needed, and to fill data gaps by read-across.

Temporal and spatial analysis of per and polyfluoroalkyl substances in surface waters of Houston ship channel following a large-scale industrial fire incident

Firefighting foams contain per- and polyfluoroalkyl substances (PFAS) - a class of compounds widely used as surfactants. PFAS are persistent organic pollutants that have been reported in waterways and drinking water systems across the United States. These substances are of interest to both regulatory agencies and the general public because of their persistence in the environment and association with adverse health effects. PFAS can be released in large quantities during industrial incidents because they are present in most firefighting foams used to suppress chemical fires; however, little is known about persistence of PFAS in public waterways after such events. In response to large-scale fires at Intercontinental Terminal Company (ITC) in Houston, Texas in March 2019, almost 5 million liters of class B firefighting foams were used. Much of this material flowed into the Houston Ship Channel and Galveston Bay (HSC/GB) and concerns were raised about the levels of PFAS in these water bodies that have commercial and recreational uses. To evaluate the impact of the ITC incident response on PFAS levels in HSC/GB, we collected 52 surface water samples from 12 locations over a 6-month period after the incident. Samples were analyzed using liquid chromatography-mass spectrometry to evaluate 27 PFAS, including perfluorocarboxylic acids, perfluorosulfonates and fluorotelomers. Among PFAS that were evaluated, 6:2 FTS and PFOS were detected at highest concentrations. Temporal and spatial profiles of PFAS were established; we found a major peak in the level of many PFAS in the days and weeks after the incident and a gradual decline over several months with patterns consistent with the tide- and wave-associated water movements. This work documents the impact of a large-scale industrial fire, on the environmental levels of PFAS, establishes a baseline concentration of PFAS in HSC/GB, and highlights the critical need for development of PFAS water quality standards.

Hepatic lipocalin 2 promotes liver fibrosis and portal hypertension

Advanced fibrosis and portal hypertension influence short-term mortality. Lipocalin 2 (LCN2) regulates infection response and increases in liver injury. We explored the role of intrahepatic LCN2 in human alcoholic hepatitis (AH) with advanced fibrosis and portal hypertension and in experimental mouse fibrosis. We found hepatic LCN2 expression and serum LCN2 level markedly increased and correlated with disease severity and portal hypertension in patients with AH. In control human livers, LCN2 expressed exclusively in mononuclear cells, while its expression was markedly induced in AH livers, not only in mononuclear cells but also notably in hepatocytes. Lcn2-/- mice were protected from liver fibrosis caused by either ethanol or CCl4 exposure. Microarray analysis revealed downregulation of matrisome, cell cycle and immune related gene sets in Lcn2-/- mice exposed to CCl4, along with decrease in Timp1 and Edn1 expression. Hepatic expression of COL1A1, TIMP1 and key EDN1 system components were elevated in AH patients and correlated with hepatic LCN2 expression. In vitro, recombinant LCN2 induced COL1A1 expression. Overexpression of LCN2 increased HIF1A that in turn mediated EDN1 upregulation. LCN2 contributes to liver fibrosis and portal hypertension in AH and could represent a new therapeutic target.

The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring county-level vulnerability using visualization, statistical modeling, and machine learning

BACKGROUND

While the COVID-19 pandemic presents a global challenge, the U.S. response places substantial responsibility for both decision-making and communication on local health authorities, necessitating tools to support decision-making at the community level.

OBJECTIVES

We created a Pandemic Vulnerability Index (PVI) to support counties and municipalities by integrating baseline data on relevant community vulnerabilities with dynamic data on local infection rates and interventions. The PVI visually synthesizes county-level vulnerability indicators, enabling their comparison in regional, state, and nationwide contexts.

METHODS

We describe the data streams used and how these are combined to calculate the PVI, detail the supporting epidemiological modeling and machine-learning forecasts, and outline the deployment of an interactive web Dashboard. Finally, we describe the practical application of the PVI for real-world decision-making.

RESULTS

Considering an outlook horizon from 1 to 28 days, the overall PVI scores are significantly associated with key vulnerability-related outcome metrics of cumulative deaths, population adjusted cumulative deaths, and the proportion of deaths from cases. The modeling results indicate the most significant predictors of case counts are population size, proportion of black residents, and mean PM2.5. The machine learning forecast results were strongly predictive of observed cases and deaths up to 14 days ahead. The modeling reinforces an integrated concept of vulnerability that accounts for both dynamic and static data streams and highlights the drivers of inequities in COVID-19 cases and deaths. These results also indicate that local areas with a highly ranked PVI should take near-term action to mitigate vulnerability.

DISCUSSION

The COVID-19 PVI Dashboard monitors multiple data streams to communicate county-level trends and vulnerabilities and facilitates decision-making and communication among government officials, scientists, community leaders, and the public to enable effective and coordinated action to combat the pandemic.

Histopathological and Molecular Signatures of a Mouse Model of Acute-on-Chronic Alcoholic Liver Injury Demonstrate Concordance With Human Alcoholic Hepatitis

Human alcoholic hepatitis (AH) carries a high mortality rate. AH is an acute-on-chronic form of liver injury characterized by hepatic steatosis, ballooned hepatocytes, neutrophil infiltration, and pericellular fibrosis. We aimed to study the pathogenesis of AH in an animal model which combines chronic hepatic fibrosis with intragastric alcohol administration. Adult male C57BL6/J mice were treated with CCl4 (0.2 ml/kg, 2×weekly by intraperitoneal injections for 6 weeks) to induce chronic liver fibrosis. Then, ethyl alcohol (up to 25 g/kg/day for 3 weeks) was administered continuously to mice via a gastric feeding tube, with or without one-half dose of CCl4. Liver and serum markers and liver transcriptome were evaluated to characterize acute-on-chronic-alcoholic liver disease in our model. CCl4 or alcohol treatment alone induced liver fibrosis or steatohepatitis, respectively, findings that were consistent with expected pathology. Combined treatment resulted in a marked exacerbation of liver injury, as evident by the development of inflammation, steatosis, and pericellular fibrosis, pathological features of human AH. E. coli and Candida were also detected in livers of mice cotreated with CCl4 and alcohol, indicating pathogen translocation from gut to liver, similar to human AH. Importantly, liver transcriptomic changes specific to combined treatment group demonstrated close concordance with pathways perturbed in patients with severe AH. Overall, mice treated with CCl4 and alcohol displayed key molecular and pathological characteristics of human AH-pericellular fibrosis, increased hepatic bacterial load, and dysregulation of the same molecular pathways. This model may be useful for developing therapeutics for AH.

Cardiovascular Effects of Polychlorinated Biphenyls and Their Major Metabolites

BACKGROUND

Xenobiotic metabolism is complex, and accounting for bioactivation and detoxification processes of chemicals remains among the most challenging aspects for decision making with in vitro new approach methods data.

OBJECTIVES

Considering the physiological relevance of human organotypic culture models and their utility for high-throughput screening, we hypothesized that multidimensional chemical-biological profiling of chemicals and their major metabolites is a sensible alternative for the toxicological characterization of parent molecules vs. metabolites in vitro.

METHODS

In this study, we tested 25 polychlorinated biphenyls (PCBs) [PCB 3, 11, 52, 126, 136, and 153 and their relevant metabolites (hydroxylated, methoxylated, sulfated, and quinone)] in concentration-response (10 nM-100μM) for effects in human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (CMs) and endothelial cells (ECs) (iPSC-derived and HUVECs). Functional phenotypic end points included effects on beating parameters and intracellular Ca2+ flux in CMs and inhibition of tubulogenesis in ECs. High-content imaging was used to evaluate cytotoxicity, mitochondrial integrity, and oxidative stress.

RESULTS

Data integration of a total of 19 physicochemical descriptors and 36 in vitro phenotypes revealed that chlorination status and metabolite class are strong predictors of the in vitro cardiovascular effects of PCBs. Oxidation of PCBs, especially to di-hydroxylated and quinone metabolites, was associated with the most pronounced effects, whereas sulfation and methoxylation of PCBs resulted in diminished bioactivity.

DISCUSSION

Risk characterization analysis showed that although in vitro derived effective concentrations exceeded the levels measured in the general population, risks cannot be ruled out due to the potential for population variability in susceptibility and the need to fill data gaps using read-across approaches. This study demonstrated a strategy for how in vitro data can be used to characterize human health risks from PCBs and their metabolites. https://doi.org/10.1289/EHP7030.

Rapid hazard characterization of environmental chemicals using a compendium of human cell lines from different organs

The lack of adequate toxicity data for the vast majority of chemicals in the environment has spurred the development of new approach methodologies (NAMs). This study aimed to develop a practical high-throughput in vitro model for rapidly evaluating potential hazards of chemicals using a small number of human cells. Forty-two compounds were tested using human induced pluripotent stem cell (iPSC)-derived cells (hepatocytes, neurons, cardiomyocytes and endothelial cells), and a primary endothelial cell line. Both functional and cytotoxicity endpoints were evaluated using high-content imaging. Concentration-response was used to derive points-of-departure (POD). PODs were integrated with ToxPi and used as surrogate NAM-based PODs for risk characterization. We found chemical class-specific similarity among the chemicals tested; metal salts exhibited the highest overall bioactivity. We also observed cell type-specific patterns among classes of chemicals, indicating the ability of the proposed in vitro model to recognize effects on different cell types. Compared to available NAM datasets, such as ToxCast/Tox21 and chemical structure-based descriptors, we found that the data from the five-cell-type model was as good or even better in assigning compounds to chemical classes. Additionally, the PODs from this model performed well as a conservative surrogate for regulatory in vivo PODs and were less likely to underestimate in vivo potency and potential risk compared to other NAM-based PODs. In summary, we demonstrate the potential of this in vitro screening model to inform rapid risk-based decision-making through ranking, clustering, and assessment of both hazard and risks of diverse environmental chemicals.

PBPK modeling of impact of nonalcoholic fatty liver disease on toxicokinetics of perchloroethylene in mice

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD), a major cause of chronic liver disease in the Western countries with increasing prevalence worldwide, may substantially affect chemical toxicokinetics and thereby modulate chemical toxicity.

OBJECTIVES

This study aims to use physiologically-based pharmacokinetic (PBPK) modeling to characterize the impact of NAFLD on toxicokinetics of perchloroethylene (perc).

METHODS

Quantitative measures of physiological and biochemical changes associated with the presence of NAFLD induced by high-fat or methionine/choline-deficient diets in C57B1/6 J mice are incorporated into a previously developed PBPK model for perc and its oxidative and conjugative metabolites. Impacts on liver fat and volume, as well as blood:air and liver:air partition coefficients, are incorporated into the model. Hierarchical Bayesian population analysis using Markov chain Monte Carlo simulation is conducted to characterize uncertainty, as well as disease-induced variability in toxicokinetics.

RESULTS

NAFLD has a major effect on toxicokinetics of perc, with greater oxidative and lower conjugative metabolism as compared to healthy mice. The NAFLD-updated PBPK model accurately predicts in vivo metabolism of perc through oxidative and conjugative pathways in all tissues across disease states and strains, but underestimated parent compound concentrations in blood and liver of NAFLD mice.

CONCLUSIONS

We demonstrate the application of PBPK modeling to predict the effects of pre-existing disease conditions as a variability factor in perc metabolism. These results suggest that non-genetic factors such as diet and pre-existing disease can be as influential as genetic factors in altering toxicokinetics of perc, and thus are likely contribute substantially to population variation in its adverse effects.

Characterization of the variability in the extent of nonalcoholic fatty liver induced by a high-fat diet in the genetically diverse Collaborative Cross mouse model

Interindividual variability and sexual dimorphisms in the development of nonalcoholic fatty liver disease (NAFLD) are still poorly understood. In the present study, male and female strains of Collaborative Cross (CC) mice were fed a high-fat and high-sucrose (HF/HS) diet or a control diet for 12 weeks to investigate interindividual- and sex-specific variations in the development of NAFLD. The severity of liver steatosis varied between sexes and individual strains and was accompanied by an elevation of serum markers of insulin resistance, including increases in total cholesterol, low-density lipoproteins, high-density lipoproteins, phospholipids, and glucose. The development of NAFLD was associated with overexpression of the critical fatty acid uptake and de novo lipogenesis genes Pparg, Mogat1, Cd36, Acaab1, Fabp2, and Gdf15 in male and female mice. The expression of Pparg, Mogat1, and Cd36 was positively correlated with liver triglycerides in male mice, and Mogat1 and Cd36 expression were positively correlated with liver triglycerides in female mice. Our results indicate the value of CC mice in combination with HF/HS diet-induced alterations as an approach to study the susceptibility and interindividual variabilities in the pathogenesis of nonalcoholic fatty liver and early nonalcoholic steatohepatitis at the population level, uncovering of susceptible and resistant cohorts, and identifying sex-specific molecular determinants of disease susceptibility.

Epithelial splicing regulatory protein 2-mediated alternative splicing reprograms hepatocytes in severe alcoholic hepatitis

Severe alcoholic hepatitis (SAH) is a deadly liver disease without an effective medical therapy. Although SAH mortality is known to correlate with hepatic accumulation of immature liver cells, why this occurs and how it causes death are unclear. Here, we demonstrate that expression of epithelial splicing regulatory protein 2 (ESRP2), an RNA-splicing factor that maintains the nonproliferative, mature phenotype of adult hepatocytes, was suppressed in both human SAH and various mouse models of SAH in parallel with the severity of alcohol consumption and liver damage. Inflammatory cytokines released by excessive alcohol ingestion reprogrammed adult hepatocytes into proliferative, fetal-like cells by suppressing ESRP2. Sustained loss of ESRP2 permitted reemergence of a fetal RNA-splicing program that attenuates the Hippo signaling pathway and thus allows fetal transcriptional regulators to accumulate in adult liver. We further showed that depleting ESRP2 in mice exacerbated alcohol-induced steatohepatitis, enabling surviving hepatocytes to shed adult hepatocyte functions and become more regenerative, but threatening overall survival by populating the liver with functionally immature hepatocytes. Our findings revealed a mechanism that explains why liver failure develops in patients with the clinical syndrome of SAH, suggesting that recovery from SAH might be improved by limiting adult-to-fetal reprogramming in hepatocytes.

Predicting tubular reabsorption with a human kidney proximal tubule tissue-on-a-chip and physiologically-based modeling

Kidney is a major route of xenobiotic excretion, but the accuracy of preclinical data for predicting in vivo clearance is limited by species differences and non-physiologic 2D culture conditions. Microphysiological systems can potentially increase predictive accuracy due to their more realistic 3D environment and incorporation of dynamic flow. We used a renal proximal tubule microphysiological device to predict renal reabsorption of five compounds: creatinine (negative control), perfluorooctanoic acid (positive control), cisplatin, gentamicin, and cadmium. We perfused compound-containing media to determine renal uptake/reabsorption, adjusted for non-specific binding. A physiologically-based parallel tube model was used to model reabsorption kinetics and make predictions of overall in vivo renal clearance. For all compounds tested, the kidney tubule chip combined with physiologically-based modeling reproduces qualitatively and quantitatively in vivo tubular reabsorption and clearance. However, because the in vitro device lacks filtration and tubular secretion components, additional information on protein binding and the importance of secretory transport is needed in order to make accurate predictions. These and other limitations, such as the presence of non-physiological compounds such as antibiotics and bovine serum albumin in media and the need to better characterize degree of expression of important transporters, highlight some of the challenges with using microphysiological devices to predict in vivo pharmacokinetics.

Biology-inspired microphysiological systems to advance patient benefit and animal welfare in drug development

The first microfluidic microphysiological systems (MPS) entered the academic scene more than 15 years ago and were considered an enabling technology to human (patho)biology in vitro and, therefore, provide alternative approaches to laboratory animals in pharmaceutical drug development and academic research. Nowadays, the field generates more than a thousand scientific publications per year. Despite the MPS hype in academia and by platform providers, which says this technology is about to reshape the entire in vitro culture landscape in basic and applied research, MPS approaches have neither been widely adopted by the pharmaceutical industry yet nor reached regulated drug authorization processes at all. Here, 46 leading experts from all stakeholders - academia, MPS supplier industry, pharmaceutical and consumer products industries, and leading regulatory agencies - worldwide have analyzed existing challenges and hurdles along the MPS-based assay life cycle in a second workshop of this kind in June 2019. They identified that the level of qualification of MPS-based assays for a given context of use and a communication gap between stakeholders are the major challenges for industrial adoption by end-users. Finally, a regulatory acceptance dilemma exists against that background. This t4 report elaborates on these findings in detail and summarizes solutions how to overcome the roadblocks. It provides recommendations and a roadmap towards regulatory accepted MPS-based models and assays for patients' benefit and further laboratory animal reduction in drug development. Finally, experts highlighted the potential of MPS-based human disease models to feedback into laboratory animal replacement in basic life science research.

An integrative method for identification and prioritization of constituents of concern in produced water from onshore oil and gas extraction

In the United States, onshore oil and gas extraction operations generate an estimated 900 billion gallons of produced water annually, making it the largest waste stream associated with upstream development of petroleum hydrocarbons. Management and disposal practices of produced water vary from deep well injection to reuse of produced water in agricultural settings. However, there is relatively little information with regard to the chemical or toxicological characteristics of produced water. A comprehensive literature review was performed, screening nearly 16,000 published articles, and identifying 129 papers that included data on chemicals detected in produced water. Searches for information on the potential ecotoxicological or mammalian toxicity of these chemicals revealed that the majority (56%) of these compounds have not been a subject of safety evaluation or mechanistic toxicology studies and 86% lack data to be used to complete a risk assessment, which underscores the lack of toxicological information for the majority of chemical constituents in produced water. The objective of this study was to develop a framework to identify potential constituents of concern in produced water, based on available and predicted toxicological hazard data, to prioritize these chemicals for monitoring, treatment, and research. In order to integrate available evidence to address gaps in toxicological hazard on the chemicals in produced water, we have catalogued available information from ecological toxicity studies, toxicity screening databases, and predicted toxicity values. A Toxicological Priority Index (ToxPi) approach was applied to integrate these various data sources. This research will inform stakeholders and decision-makers on the potential hazards in produced water. In addition, this work presents a method to prioritize compounds that, based on hazard and potential exposure, may be considered during various produced water reuse strategies to reduce possible human health risks and environmental impacts.

Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation

Gene transcription profiles across tissues are largely defined by the activity of regulatory elements, most of which correspond to regions of accessible chromatin. Regulatory element activity is in turn modulated by genetic variation, resulting in variable transcription rates across individuals. The interplay of these factors, however, is poorly understood. Here we characterize expression and chromatin state dynamics across three tissues-liver, lung, and kidney-in 47 strains of the Collaborative Cross (CC) mouse population, examining the regulation of these dynamics by expression quantitative trait loci (eQTL) and chromatin QTL (cQTL). QTL whose allelic effects were consistent across tissues were detected for 1,101 genes and 133 chromatin regions. Also detected were eQTL and cQTL whose allelic effects differed across tissues, including local-eQTL for Pik3c2g detected in all three tissues but with distinct allelic effects. Leveraging overlapping measurements of gene expression and chromatin accessibility on the same mice from multiple tissues, we used mediation analysis to identify chromatin and gene expression intermediates of eQTL effects. Based on QTL and mediation analyses over multiple tissues, we propose a causal model for the distal genetic regulation of Akr1e1, a gene involved in glycogen metabolism, through the zinc finger transcription factor Zfp985 and chromatin intermediates. This analysis demonstrates the complexity of transcriptional and chromatin dynamics and their regulation over multiple tissues, as well as the value of the CC and related genetic resource populations for identifying specific regulatory mechanisms within cells and tissues.

Modulation of Tetrachloroethylene-Associated Kidney Effects by Nonalcoholic Fatty Liver or Steatohepatitis in Male C57BL/6J Mice

Accounting for genetic and other (eg, underlying disease states) factors that may lead to inter-individual variability in susceptibility to xenobiotic-induced injury is a challenge in human health assessments. A previous study demonstrated that nonalcoholic fatty liver disease (NAFLD), one of the common underlying disease states, enhances tetrachloroethylene (PERC)-associated hepatotoxicity in mice. Interestingly, NAFLD resulted in a decrease in metabolism of PERC to nephrotoxic glutathione conjugates; we therefore hypothesized that NAFLD would protect against PERC-associated nephrotoxicity. Male C57BL/6J mice were fed a low-fat (LFD), high-fat (31% fat, HFD), or high-fat methionine/choline/folate-deficient (31% fat, MCD) diets. After 8 weeks mice were administered either a single dose of PERC (300 mg/kg i.g.) and euthanized at 1-36 h post dose, or five daily doses of PERC (300 mg/kg/d i.g.) and euthanized 4 h after last dose. Relative to LFD-fed mice, HFD- or MCD-fed mice exhibited decreased PERC concentrations and increased trichloroacetate (TCA) in kidneys. S-(1,2,2-trichlorovinyl)glutathione (TCVG), S-(1,2,2-trichlorovinyl)-l-cysteine (TCVC), and N-acetyl-S-(1,2,2,-trichlorovinyl)-l-cysteine (NAcTCVC) were also significantly lower in kidney and urine of HFD- or MCD-fed mice compared with LFD-fed mice. Despite differences in levels of nephrotoxic PERC metabolites in kidney, LFD- and MCD-fed mice demonstrated similar degree of nephrotoxicity. However, HFD-fed mice were less sensitive to PERC-induced nephrotoxicity. Thus, whereas both MCD- and HFD-induced fatty liver reduced the delivered dose of nephrotoxic PERC metabolites to the kidney, only HFD was protective against PERC-induced nephrotoxicity, possibly due to greater toxicodynamic sensitivity induced by methyl and choline deficiency. These results therefore demonstrate that pre-existing disease conditions can lead to a complex interplay of toxicokinetic and toxicodynamic changes that modulate susceptibility to the toxicity of xenobiotics.

A Novel Mouse Model of Acute-on-Chronic Cholestatic Alcoholic Liver Disease: A Systems Biology Comparison With Human Alcoholic Hepatitis

BACKGROUND

Alcohol-related liver disease is the main cause of liver-related mortality worldwide. The development of novel targeted therapies for patients with advanced forms (i.e., alcoholic hepatitis, AH) is hampered by the lack of suitable animal models. Here, we developed a novel mouse model of acute-on-chronic alcohol liver injury with cholestasis and fibrosis and performed an extensive molecular comparative analysis with human AH.

METHODS

For the mouse model of acute-on-chronic liver injury, we used 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC, 0.05% w/w) diet for 8 weeks to establish cholestatic liver fibrosis. After 1-week washout period, male mice were fed intragastrically for 4 weeks with up to 24 g/kg of ethyl alcohol in a high-fat diet. This animal model was phenotyped using histopathology, clinical chemistry, microbiome, and gene expression approaches. Data were compared to the phenotypes of human alcohol-related liver disease, including AH.

RESULTS

Mice with cholestatic liver fibrosis and subsequent alcohol exposure (DDC + EtOH) exhibited exacerbated liver fibrosis with a pericellular pattern, increased neutrophil infiltration, and ductular proliferation, all characteristics of human AH. DDC administration had no effect on urine alcohol concentration or liver steatosis. Importantly, DDC- and alcohol-treated mice showed a transcriptomic signature that resembled that of patients with AH. Finally, we show that mice in the DDC + EtOH group had an increased gut barrier dysfunction, mimicking an important pathophysiological mechanism of human AH.

CONCLUSIONS

We developed a novel mouse model of acute-on-chronic cholestatic alcoholic liver injury that has considerable translational potential and can be used to test novel therapeutic modalities for AH.

Baseline data for distribution of contaminants by natural disasters: results from a residential Houston neighborhood during Hurricane Harvey flooding

Hurricane Harvey made landfall in Texas August 25, 2017, bringing massive rains and flooding that impacted soils in a residential neighborhood in East Houston. Trace elements, organochlorine pesticides, polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ether fire retardants (PBDEs) and polychlorinated biphenyls (PCBs) were determined in 24 soil samples. The highest concentrations found in soils were total PAHs, which ranged from 1,310 μg/kg to 85,700 μg/kg with a mean of 12,600 μg/kg. Analysis of specific PAH ratios indicate the source of the PAHs were dominated by pyrogenic rather than petrogenic sources. Chlordanes were detectable in the area where the likely local source is for ant control. The trace metal concentrations were below any environmental health concern concentrations but As, Cd, Hg, Pb, Se, Ag, Zn were enriched over the crustal abundance. While Hurricane Harvey was responsible for the redistribution of many contaminants, the large volume of rain and floodwater likely transported contaminants from the land areas and into the Houston Ship Channel and Galveston Bay. The findings from this study will serve as baseline data for determining the mobilization of contaminants caused by natural disasters.

Population-based toxicity screening in human induced pluripotent stem cell-derived cardiomyocytes

The potential for cardiotoxicity is carefully evaluated for pharmaceuticals, as it is a major safety liability. However, environmental chemicals are seldom tested for their cardiotoxic potential. Moreover, there is a large variability in both baseline and drug-induced cardiovascular risk in humans, but data are lacking on the degree to which susceptibility to chemically-induced cardiotoxicity may also vary. Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes have become an important in vitro model for drug screening. Thus, we hypothesized that a population-based model of iPSC-derived cardiomyocytes from a diverse set of individuals can be used to assess potential hazard and inter-individual variability in chemical effects on these cells. We conducted concentration-response screening of 134 chemicals (pharmaceuticals, industrial and environmental chemicals and food constituents) in iPSC-derived cardiomyocytes from 43 individuals, comprising both sexes and diverse ancestry. We measured kinetic calcium flux and conducted high-content imaging following chemical exposure, and utilized a panel of functional and cytotoxicity parameters in concentration-response for each chemical and donor. We show reproducible inter-individual variability in both baseline and chemical-induced effects on iPSC-derived cardiomyocytes. Further, chemical-specific variability in potency and degree of population variability were quantified. This study shows the feasibility of using an organotypic population-based human in vitro model to quantitatively assess chemicals for which little cardiotoxicity information is available. Ultimately, these results advance in vitro toxicity testing methodologies by providing an innovative tool for population-based cardiotoxicity screening, contributing to the paradigm shift from traditional animal models of toxicity to in vitro toxicity testing methods.

Grouping of complex substances using analytical chemistry data: A framework for quantitative evaluation and visualization

A detailed characterization of the chemical composition of complex substances, such as products of petroleum refining and environmental mixtures, is greatly needed in exposure assessment and manufacturing. The inherent complexity and variability in the composition of complex substances obfuscate the choices for their detailed analytical characterization. Yet, in lieu of exact chemical composition of complex substances, evaluation of the degree of similarity is a sensible path toward decision-making in environmental health regulations. Grouping of similar complex substances is a challenge that can be addressed via advanced analytical methods and streamlined data analysis and visualization techniques. Here, we propose a framework with unsupervised and supervised analyses to optimally group complex substances based on their analytical features. We test two data sets of complex oil-derived substances. The first data set is from gas chromatography-mass spectrometry (GC-MS) analysis of 20 Standard Reference Materials representing crude oils and oil refining products. The second data set consists of 15 samples of various gas oils analyzed using three analytical techniques: GC-MS, GC×GC-flame ionization detection (FID), and ion mobility spectrometry-mass spectrometry (IM-MS). We use hierarchical clustering using Pearson correlation as a similarity metric for the unsupervised analysis and build classification models using the Random Forest algorithm for the supervised analysis. We present a quantitative comparative assessment of clustering results via Fowlkes-Mallows index, and classification results via model accuracies in predicting the group of an unknown complex substance. We demonstrate the effect of (i) different grouping methodologies, (ii) data set size, and (iii) dimensionality reduction on the grouping quality, and (iv) different analytical techniques on the characterization of the complex substances. While the complexity and variability in chemical composition are an inherent feature of complex substances, we demonstrate how the choices of the data analysis and visualization methods can impact the communication of their characteristics to delineate sufficient similarity.

Gene Expression and DNA Methylation Alterations in the Glycine N-Methyltransferase Gene in Diet-Induced Nonalcoholic Fatty Liver Disease-Associated Carcinogenesis

Nonalcoholic fatty liver disease (NAFLD) is becoming a major etiological risk factor for hepatocellular carcinoma (HCC) in the United States and other Western countries. In this study, we investigated the role of gene-specific promoter cytosine DNA methylation and gene expression alterations in the development of NAFLD-associated HCC in mice using (1) a diet-induced animal model of NAFLD, (2) a Stelic Animal Model of nonalcoholic steatohepatitis-derived HCC, and (3) a choline- and folate-deficient (CFD) diet (CFD model). We found that the development of NAFLD and its progression to HCC was characterized by down-regulation of glycine N-methyltransferase (Gnmt) and this was mediated by progressive Gnmt promoter cytosine DNA hypermethylation. Using a panel of genetically diverse inbred mice, we observed that Gnmt down-regulation was an early event in the pathogenesis of NAFLD and correlated with the extent of the NAFLD-like liver injury. Reduced GNMT expression was also found in human HCC tissue and liver cancer cell lines. In in vitro experiments, we demonstrated that one of the consequences of GNMT inhibition was an increase in genome methylation facilitated by an elevated level of S-adenosyl-L-methionine. Overall, our findings suggest that reduced Gnmt expression caused by promoter hypermethylation is one of the key molecular events in the development of NAFLD-derived HCC and that assessing Gnmt methylation level may be useful for disease stratification.

Metabolism and Toxicity of Trichloroethylene and Tetrachloroethylene in Cytochrome P450 2E1 Knockout and Humanized Transgenic Mice

Trichloroethylene (TCE) and tetrachloroethylene (PCE) are structurally similar olefins that can cause liver and kidney toxicity. Adverse effects of these chemicals are associated with metabolism to oxidative and glutathione conjugation moieties. It is thought that CYP2E1 is crucial to the oxidative metabolism of TCE and PCE, and may also play a role in formation of nephrotoxic metabolites; however, inter-species and inter-individual differences in contribution of CYP2E1 to metabolism and toxicity are not well understood. Therefore, the role of CYP2E1 in metabolism and toxic effects of TCE and PCE was investigated using male and female wild-type [129S1/SvlmJ], Cyp2e1(-/-), and humanized Cyp2e1 [hCYP2E1] mice. To fill in existing gaps in our knowledge, we conducted a toxicokinetic study of TCE (600 mg/kg, single dose, i.g.) and a subacute study of PCE (500 mg/kg/day, 5 days, i.g.) in 3 strains. Liver and kidney tissues were subject to profiling of oxidative and glutathione conjugation metabolites of TCE and PCE, as well as toxicity endpoints. The amounts of trichloroacetic acid formed in the liver was hCYP2E1≈ 129S1/SvlmJ > Cyp2e1(-/-) for both TCE and PCE; levels in males were about 2-fold higher than in females. Interestingly, 2- to 3-fold higher levels of conjugation metabolites were observed in TCE-treated Cyp2e1(-/-) mice. PCE induced lipid accumulation only in liver of 129S1/SvlmJ mice. In the kidney, PCE exposure resulted in acute proximal tubule injury in both sexes in all strains (hCYP2E1 ≈ 129S1/SvlmJ > Cyp2e1(-/-)). In conclusion, our results demonstrate that CYP2E1 is an important, but not exclusive actor in the oxidative metabolism and toxicity of TCE and PCE.

Defective HNF4alpha-dependent gene expression as a driver of hepatocellular failure in alcoholic hepatitis

Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we show that development of AH is characterized by defective activity of liver-enriched transcription factors (LETFs). TGFβ1 is a key upstream transcriptome regulator in AH and induces the use of HNF4α P2 promoter in hepatocytes, which results in defective metabolic and synthetic functions. Gene polymorphisms in LETFs including HNF4α are not associated with the development of AH. In contrast, epigenetic studies show that AH livers have profound changes in DNA methylation state and chromatin remodeling, affecting HNF4α-dependent gene expression. We conclude that targeting TGFβ1 and epigenetic drivers that modulate HNF4α-dependent gene expression could be beneficial to improve hepatocellular function in patients with AH.

Comparative analysis of Rapid Equilibrium Dialysis (RED) and solid phase micro-extraction (SPME) methods for In Vitro-In Vivo extrapolation of environmental chemicals

In vitro to in vivo extrapolation (IVIVE) is a critical component of the efforts to prioritize and assess environmental chemicals using high-throughput in vitro assays. The plasma unbound fraction (F_ub) is a key toxicokinetic parameter in IVIVE, and is usually measured via the Rapid Equilibrium Dialysis (RED) assay widely used for pharmaceuticals. However, pharmaceuticals have a narrower range of physicochemical properties than environmental chemicals. Motivated by the observation that high LogK_OW compounds appeared to have disproportionately low F_ub measurements using RED, we added a protein-free control in order to verify equilibration to 100% unbound in the absence of proteins. We found that many high LogK_OW non-pharmaceuticals fail to equilibrate in RED in protein-free controls, and thus had apparent values of F_ub = 0 in plasma. In these cases, Solid Phase Microextraction (SPME) as an alternative method provided an accurate, though more time-consuming, alternative to accurately determine F_ub. We propose an updated IVIVE workflow that adds a protein-free control to the RED protocol, with the use of alternative approaches, such as SPME, in cases where compounds fail to adequately equilibrate. These refinements will provide additional confidence in the use of IVIVE as part of high-throughput screening programs of chemicals.

Using Collaborative Cross Mouse Population to Fill Data Gaps in Risk Assessment: A Case Study of Population-Based Analysis of Toxicokinetics and Kidney Toxicodynamics of Tetrachloroethylene

BACKGROUND

Interindividual variability in susceptibility remains poorly characterized for environmental chemicals such as tetrachloroethylene (PERC). Development of population-based experimental models provide a potential approach to fill this critical need in human health risk assessment.

OBJECTIVES

In this study, we aimed to better characterize the contribution of glutathione (GSH) conjugation to kidney toxicity of PERC and the degree of associated interindividual toxicokinetic (TK) and toxicodynamic (TD) variability by using the Collaborative Cross (CC) mouse population.

METHODS

Male mice from 45 strains were intragastrically dosed with PERC ([Formula: see text]) or vehicle (5% Alkamuls EL-620 in saline), and time-course samples were collected for up to 24 h. Population variability in TK of S-(1,2,2-trichlorovinyl)GSH (TCVG), S-(1,2,2-trichlorovinyl)-L-cysteine (TCVC), and N-acetyl-S-(1,2,2-trichlorovinyl)-L-cysteine (NAcTCVC) was quantified in serum, liver, and kidney, and analyzed using a toxicokinetic model. Effects of PERC on kidney weight, fatty acid metabolism-associated genes [ Acot1 (Acyl-CoA thioesterase 1), Fabp1 (fatty acid-binding protein 1), and Ehhadh (enoyl-coenzyme A, hydratase/3-hydroxyacyl coenzyme A dehydrogenase)], and a marker of proximal tubular injury [KIM-1 (kidney injury molecule-1)/Hepatitis A virus cellular receptor 1 ( Havcr1)] were evaluated. Finally, quantitative data on interstrain variability in both formation of GSH conjugation metabolites of PERC and its kidney effects was used to calculate adjustment factors for the interindividual variability in both TK and TD.

RESULTS

Mice treated with PERC had significantly lower kidney weight, higher kidney-to-body weight (BW) ratio, and higher expression of fatty acid metabolism-associated genes ( Acot1, Fabp1, and Ehhadh) and a marker of proximal tubular injury (KIM-1/ Havcr1). Liver levels of TCVG were significantly correlated with KIM-1/ Havcr1 in kidney, consistent with kidney injury being associated with GSH conjugation. We found that the default uncertainty factor for human variability may be marginally adequate to protect 95%, but not more, of the population for kidney toxicity mediated by PERC.

DISCUSSION

Overall, this study demonstrates the utility of the CC mouse population in characterizing metabolism-toxicity interactions and quantifying interindividual variability. Further refinement of the characterization of interindividual variability can be accomplished by incorporating these data into in silico population models both for TK (such as a physiologically based pharmacokinetic model), as well as for toxicodynamic responses. https://doi.org/10.1289/EHP5105.