Rory B. Conolly

Endocrine disrupting chemicals in fish: Developing exposure indicators and predictive models of effects based on mechanism of action

Knowledge of possible toxic mechanisms (or modes) of action (MOA) of chemicals can provide valuable insights as to appropriate methods for assessing exposure and effects, thereby reducing uncertainties related to extrapolation across species, endpoints and chemical structure. However, MOA-based testing seldom has been used for assessing the ecological risk of chemicals. This is in part because past regulatory mandates have focused more on adverse effects of chemicals (reductions in survival, growth or reproduction) than the pathways through which these effects are elicited. A recent departure from this involves endocrine-disrupting chemicals (EDCs), where there is a need to understand both MOA and adverse outcomes. To achieve this understanding, advances in predictive approaches are required whereby mechanistic changes caused by chemicals at the molecular level can be translated into apical responses meaningful to ecological risk assessment. In this paper we provide an overview and illustrative results from a large, integrated project that assesses the effects of EDCs on two small fish models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio). For this work a systems-based approach is being used to delineate toxicity pathways for 12 model EDCs with different known or hypothesized toxic MOA. The studies employ a combination of state-of-the-art genomic (transcriptomic, proteomic, metabolomic), bioinformatic and modeling approaches, in conjunction with whole animal testing, to develop response linkages across biological levels of organization. This understanding forms the basis for predictive approaches for species, endpoint and chemical extrapolation. Although our project is focused specifically on EDCs in fish, we believe that the basic conceptual approach has utility for systematically assessing exposure and effects of chemicals with other MOA across a variety of biological systems.

Modeling interindividual variation in physiological factors used in PBPK models of humans.

Modeling interindividual variation in internal doses in humans using PBPK models requires data on the variation in physiological parameters across the population of interest. These data should also reflect the correlations between the values of the various parameters in a person. In this project, we develop a source of data for human physiological parameters where (1) the parameter values for an individual are correlated with one another, and (2) values of parameters capture interindividual variation in populations of a specific gender, race, and age range. The parameters investigated in this project include: (1) volumes of selected organs and tissues; (2) blood flows for the organs and tissues; and (3) the total cardiac output under resting conditions and average daily inhalation rate. These parameters are expressed as records of correlated values for the approximately 30,000 individuals evaluated in the NHANES III survey. A computer program, Physiological Parameters for PBPK Modeling (P3M), is developed that allows records to be retrieved randomly from the database with specification of constraints on age, sex, and ethnicity. P3M is publicly available. The database and accompanying software provide a convenient tool for parameterizating models of interindividual variation in human pharmacokinetics.

Arsenic-Induced Carcinogenesis—Oxidative Stress as a Possible Mode of Action and Future Research Needs for More Biologically Based Risk Assessment

Exposure to inorganic arsenic (iAs) induces cancer in human lungs, urinary bladder, skin, kidney, and liver, with the majority of deaths from lung and bladder cancer. To date, cancer risk assessments for iAs have not relied on mechanistic data, as we have lacked sufficient understanding of arsenics pharmacokinetics and mode(s) of carcinogenic action (MOA). Furthermore, while there are vast amounts of toxicological data on iAs, relatively little of it has been collected using experimental designs that efficiently support development of biologically based dose-response (BBDR) models and subsequently risk assessment. This review outlines an efficient approach to the development of a BBDR model for iAs that would reduce uncertainties in its cancer risk assessment. This BBDR-based approach is illustrated by using oxidative stress as the carcinogenic MOA for iAs but would be generically applicable to other MOAs. Six major research needs that will facilitate BBDR model development for arsenic-induced cancer are (1) MOA research, which is needed to reduce the uncertainty in risk assessment; (2) development and integration of the pharmacodynamic component (MOA) of the BBDR model; (3) dose-response and extrapolation model selection; (4) the determination of internal human speciated arsenical concentrations to improve physiologically based pharmacokinetic (PBPK) models; (5) animal models of arsenic carcinogenesis; and (6) the determination of the low dose human relationship for death from cancer, particularly in lungs and urinary bladder. The major parts of the BBDR model are arsenic exposure, a physiologically based pharmacokinetic model, reactive species, antioxidant defenses, oxidative stress, cytotoxicity, growth factors, transcription factors, DNA damage, chromosome damage, cell proliferation, mutation accumulation, and cancer. The BBDR model will need to be developed concurrently with data collection so that model uncertainties can be identified and addressed through an iterative process of targeted additional research.

A strategy for establishing mode of action of chemical carcinogens as a guide for approaches to risk assessments

The current standard approach for assessing carcinogenic potential is to conduct a near lifetime rodent pathology study with the high dose set to the maximum tolerated dose (MTD) of the test chemical. The linearized multistage model is then used as the default approach to estimate the potential human cancer risk at environmental elvels of the chemical. There is an increasing appreciation in the scientific and regulatory communities that chemical carcinogens differ dramatically in potency, exhibit a high degree of tissue and species specificity, and act through different modes of action. This paper advocates a decision tree strategy for classifying carcinogens that are acting primarily through genotoxic, cytotoxic, or mitogenic pathways. A primary concern is whether the chemical has direct genotoxic potential resulting from DNA reactivity or clastogenicity of the compound or its metabolite(s). Knowledge of the exposure-response curve for cytotoxicity is important because initiation and promotion events may occur secondary to a variety of associated activities such as regenerative cell proliferation. Mitogens indice direct stimulation of growth and may provide a selective growth advantage to spontaneously initiated precancerous cells. Of particular concern is the situation where pathological changes induced during the course of the treatment at high doses near the MTD are absent at lower, environmentally relevant, doses. If the tumor response is coincident with the preceding toxic response, it may not be justified to use the high-dose data in extrapolating to expected responses at low environmental exposures where no induced tissue abnormalities occur. Suggestions are presented for appropriate risk assessment approaches for different modes of action. Examples discussed are formaldehyde, a weakly genotoxic rodent nasal carcinogen; chloroform, a nongenotoxic-cytotoxic rodent liver and kidney carcinogen; and phenobarbital, a nongenotoxic-mitogenic rodent liver carcinogen.

Physiologically based pharmacokinetic and pharmacodynamic model for the inhibition of acetylcholinesterase by diisopropylfluorophosphate

Organophosphate (OP) exposure can be lethal at high doses while lower doses may impair performance of critical tasks. The ability to predict such effects for realistic exposure scenarios would expedite OP risk assessment. To this end, a physiologically based model for diisopropylfluorophosphate (DFP) pharmacokinetics and acetylcholinesterase (AChE) inhibition was developed in mammals. DFP tissue:blood partition coefficients, rates of DFP hydrolysis by esterases, and DFP-esterase bimolecular inhibition rate constants were determined in rat tissue homogenates. Other model parameters were scaled for rats and mice using standard allometric relationships. These DFP-specific parameter values were used with the model to simulate expected in vivo pharmacokinetic data from mice and rats. Literature data were used for model validation. DFP concentrations in mouse plasma and brain were successfully simulated after a single iv injection (B. R. Martin, 1985, Toxicol. Appl. Pharmacol. 77, 275–284). AChE inhibition and AChE resynthesis data from this study were also simulated. Effects of repeated, subcutaneous DFP dosing on AChE activity in rat plasma and brain (H. Michalek, A. Meneguz, and G. M. Bisso, 1982, Arch. Toxicol., Suppl. 5, 116–119; M. E. Traina and L. A. Serpietri, 1984, Biochem. Pharmacol. 33, 645–653) were also simulated well, but the return of brain AChE activity to basal levels after cessation of repeated dosing was not as well described. The initial model structure returned brain AChE activity to the original level, while in the laboratory studies brain AChE never returned to basal levels, even at 35 days after the last dose. These data suggest modulation of AChE synthesis with prolonged DFP exposure. This study demonstrated the possibility of using a model based on mammalian physiology and biochemistry to simulate in vivo data on DFP pharmacokinetics and AChE inhibition. Scaling of the model between rats and mice was also successful. The approach holds promise for predictive simulation of organophosphate-mediated AChE inhibition in humans.

Use of a Physiologically Based Pharmacokinetic Model to Identify Exposures Consistent With Human Biomonitoring Data for Chloroform

Biomonitoring data provide evidence of human exposure to environmental chemicals by quantifying the chemical or its metabolite in a biological matrix. To better understand the correlation between biomonitoring data and environmental exposure, physiologically based pharmacokinetic (PBPK) modeling can be of use. The objective of this study was to use a combined PBPK model with an exposure model for showering to estimate the intake concentrations of chloroform based on measured blood and exhaled breath concentrations of chloroform. First, the predictive ability of the combined model was evaluated with three published studies describing exhaled breath and blood concentrations in people exposed to chloroform under controlled showering events. Following that, a plausible exposure regimen was defined combining inhalation, ingestion, and dermal exposures associated with residential use of water containing typical concentrations of chloroform to simulate blood and exhaled breath concentrations of chloroform. Simulation results showed that inhalation and dermal exposure could contribute substantially to total chloroform exposure. Next, sensitivity analysis and Monte Carlo analysis were performed to investigate the sources of variability in model output. The variability in exposure conditions (e.g., shower duration) was shown to contribute more than the variability in pharmacokinetics (e.g., body weight) to the predicted variability in blood and exhaled breath concentrations of chloroform. Lastly, the model was used in a reverse dosimetry approach to estimate distributions of exposure consistent with concentrations of chloroform measured in human blood and exhaled breath.

Apoptosis and cancer risk assessment.

Apoptosis is one form of physiological or active cell death. The balance between cell proliferation and cell death or apoptosis not only effects organ growth but also has a profound impact on the net increase and growth of initiated cells and preneoplastic and tumor cell populations. With respect to cancer development apoptosis is becoming widely recognized as being an innate tissue defense against carcinogens by inhibiting survival and controlling growth of precancerous cell populations and tumors at different stages of carcinogenesis. Experimental data on cell birth and cell death rates help identify the mode of action of a chemical and can be incorporated into biologically based cancer models. This article describes the quantitation and regulation of apoptosis in rodent liver and how loss of regulation can have a role in hepatocarcinogenesis. A biologically-based mouse liver cancer model is presented and utilized to describe how treatment related growth effects affect the process of carcinogenesis. Advantages and limitations of biologically based cancer models in cancer research and risk assessment are discussed.

Correlation of regional formaldehyde flux predictions with the distribution of formaldehyde-induced squamous metaplasia in F344 rat nasal passages.

Squamous epithelium lines the nasal vestibule of the rat, rhesus monkey, and human. Respiratory, transitional, and olfactory epithelia line most areas posterior to the nasal vestibule. Inhaled formaldehyde gas induces squamous metaplasia posterior to the nasal vestibule and does not induce lesions in the nasal vestibule in rats and rhesus monkeys, indicating that squamous epithelium is resistant to irritant effects of formaldehyde and that squamous metaplasia may be an adaptive response. If squamous metaplasia is determined by formaldehyde dosimetry rather than by tissue-specific factors, squamous epithelium may be protective by absorbing less formaldehyde than other epithelial types. In a previous study, a three-dimensional, anatomically accurate computational fluid dynamics (CFD) model of the anterior F344 rat nasal passages was used to simulate inspiratory airflow and inhaled formaldehyde transport. The present study consisted of two related parts. First, the rat CFD model was used to test the hypothesis that the distribution of formaldehyde-induced squamous metaplasia is related to the location of high-flux regions posterior to squamous epithelium. Regional formaldehyde flux into nonsquamous epithelium predicted by the CFD model correlated with regional incidence of formaldehyde-induced squamous metaplasia on the airway perimeter of one cross-sectional level of the noses of F344 rats exposed to 10 and 15 ppm formaldehyde gas for 6 months. Formaldehyde flux into nonsquamous epithelium was estimated to vary by an order of magnitude depending on the degree of formaldehyde absorption by squamous epithelium. These results indicate that the degree to which squamous epithelium absorbs formaldehyde strongly affects the rate and extent of the progression of squamous metaplasia with continued exposure to formaldehyde. In the second part of this study, the CFD model was used to predict squamous metaplasia progression. Data needs for verification of this model prediction are considered. These results indicate that information on the permeability of squamous epithelium in rats, monkeys, and humans is important for accurate prediction of uptake in regions posterior to the nasal vestibule.

Issues in the design and interpretation of chronic toxicity and carcinogenicity studies in rodents: approaches to dose selection.

For more than three decades chronic studies in rodents have been the benchmark for assessing the potential long-term toxicity, and particularly the carcinogenicity, of chemicals. With doses typically administered for about 2 years (18 months to lifetime), the rodent bioassay has been an integral component of testing protocols for food additives, pesticides, pharmaceuticals, industrial chemicals, and all manner of byproducts and environmental contaminants. Over time, the data from these studies have been used to address an increasing diversity of questions related to the assessment of human health risks, adding complexity to study design and interpretation. An earlier ILSI RSI working group developed a set of principles for the selection of doses for chronic rodent studies (). The present report builds on that work, examining some of the issues that arise and offering new perspectives and approaches for putting the principles into practice. Dose selection is considered both from the prospective viewpoint of the choosing of dose levels for a study and from the retrospective interpretation of study results in light of the doses used. A main theme of this report is that the purposes and objectives of chronic rodent studies vary and should be clearly defined in advance. Dose placement, then, should be optimized to achieve study objectives. For practical reasons, most chronic studies today must be designed to address multiple objectives, often requiring trade-offs and innovative approaches in study design. A systematic approach to dose selection should begin with recognition that the design of chronic studies occurs in the context of a careful assessment of the accumulated scientific information on the test substance, the relevant risk management questions, priorities and mandates, and the practical limitations and constraints on available resources. A stepwise process is described. The aim is to increase insofar as possible the utility of an expensive and time-consuming experiment. The kinds of data that are most commonly needed for dose selection and for understanding the dose-related results of chronic rodent studies, particularly carcinogenicity studies, are discussed as “design/interpretation factors.” They comprise both the inherent characteristics of the test substance and indicators of biological damage, perturbation or stress among the experimental animals. They may be primary toxicity endpoints, predictors or indicators of appropriate dose selection, or indicators of conditions to be avoided in dose selection. The application and interpretation of design/interpretation factors is conditioned by the study objectives–what is considered desirable will depend on the strategy for choice of doses that is being followed. The challenge is to select doses that accommodate all of the issues raised by the relevant design/interpretation factors. Three case studies are presented here that illustrate the interplay between study objectives and the design and selection of doses for chronic rodent studies. These examples also highlight issues associated with multiple plausible modes of action, multiple pathways for biotransformation of the chemical, extraneous high-dose effects, the use of modeling in dose selection, and the implications of human exposure levels. Finally, looking to the future, the report explores seven potential paradigm shifts for risk assessment that will significantly impact the design and interpretation of toxicity and carcinogenicity studies.

Benchmark dose Risk Assessment for formaldehyde using airflow modeling and a single-compartment, DNA-protein cross-link dosimetry model to estimate human equivalent doses

Formaldehyde induced squamous-cell carcinomas in the nasal passages of F344 rats in two inhalation bioassays at exposure levels of 6 ppm and above. Increases in rates of cell proliferation were measured by T. M. Monticello and colleagues at exposure levels of 0.7 ppm and above in the same tissues from which tumors arose. A risk assessment for formaldehyde was conducted at the CIIT Centers for Health Research, in collaboration with investigators from Toxicological Excellence in Risk Assessment (TERA) and the U.S. Environmental Protection Agency (U.S. EPA) in 1999. Two methods for dose-response assessment were used: a full biologically based modeling approach and a statistically oriented analysis by benchmark dose (BMD) method. This article presents the later approach, the purpose of which is to combine BMD and pharmacokinetic modeling to estimate human cancer risks from formaldehyde exposure. BMD analysis was used to identify points of departure (exposure levels) for low-dose extrapolation in rats for both tumor and the cell proliferation endpoints. The benchmark concentrations for induced cell proliferation were lower than for tumors. These concentrations were extrapolated to humans using two mechanistic models. One model used computational fluid dynamics (CFD) alone to determine rates of delivery of inhaled formaldehyde to the nasal lining. The second model combined the CFD method with a pharmacokinetic model to predict tissue dose with formaldehyde-induced DNA-protein cross-links (DPX) as a dose metric. Both extrapolation methods gave similar results, and the predicted cancer risk in humans at low exposure levels was found to be similar to that from a risk assessment conducted by the U.S. EPA in 1991. Use of the mechanistically based extrapolation models lends greater certainty to these risk estimates than previous approaches and also identifies the uncertainty in the measured dose-response relationship for cell proliferation at low exposure levels, the dose-response relationship for DPX in monkeys, and the choice between linear and nonlinear methods of extrapolation as key remaining sources of uncertainty.