Benchmark dose profiles for joint‐action continuous data in quantitative risk assessment

Benchmark analysis is a widely used tool in biomedical and environmental risk assessment. Therein, estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a prespecified benchmark response (BMR) is well understood for the case of an adverse response to a single stimulus. For cases where two agents are studied in tandem, however, the benchmark approach is far less developed. This paper demonstrates how the benchmark modeling paradigm can be expanded from the single‐agent setting to joint‐action, two‐agent studies. Focus is on continuous response outcomes. Extending the single‐exposure setting, representations of risk are based on a joint‐action dose–response model involving both agents. Based on such a model, the concept of a benchmark profile—a two‐dimensional analog of the single‐dose BMD at which both agents achieve the specified BMR—is defined for use in quantitative risk characterization and assessment.     

Endocrine disrupting chemicals and other substances of concern in food contact materials: an updated review of exposure, effect and risk assessment

Food contact materials (FCM) are an underestimated source of chemical food contaminants and a potentially relevant route of human exposure to endocrine disrupting chemicals (EDCs). Quantifying the exposure of the general population to substances from FCM relies on estimates of food consumption and leaching into food. Recent studies using polycarbonate plastics show that food simulants do not always predict worst-case leaching of bisphenol A, a common FCM substance. Also, exposure of children to FCM substances is not always realistically predicted using the common conventions and thus possibly misjudged. Further, the exposure of the whole population to substances leaching into dry foods is underestimated. Consumers are exposed to low levels of substances from FCM across their entire lives. Effects of these compounds currently are assessed with a focus on mutagenicity and genotoxicity. This approach however neglects integrating recent new toxicological findings, like endocrine disruption, mixture toxicity, and developmental toxicity. According to these new toxicology paradigms women of childbearing age and during pregnancy are a new sensitive population group requiring more attention. Furthermore, in overweight and obese persons a change in the metabolism of xenobiotics is observed, possibly implying that this group of consumers is insufficiently protected by current risk assessment practice. Innovations in FCM risk assessment should therefore include routine testing for EDCs and an assessment of the whole migrate toxicity of a food packaging, taking into account all sensitive population groups. In this article I focus on recent issues of interest concerning either exposure to or effects of FCM-related substances. Further, I review the use of benzophenones and organotins, two groups of known or suspected EDCs, in FCM authorized in the US and EU.     

Benchmark Dose Profiles for Joint‐Action Quantal Data in Quantitative Risk Assessment

Summary Benchmark analysis is a widely used tool in public health risk analysis. Therein, estimation of minimum exposure levels, called Benchmark Doses (BMDs), that induce a prespecified Benchmark Response (BMR) is well understood for the case of an adverse response to a single stimulus. For cases where two agents are studied in tandem, however, the benchmark approach is far less developed. This article demonstrates how the benchmark modeling paradigm can be expanded from the single‐dose setting to joint‐action, two‐agent studies. Focus is on response outcomes expressed as proportions. Extending the single‐exposure setting, representations of risk are based on a joint‐action dose–response model involving both agents. Based on such a model, the concept of a benchmark profile (BMP) – a two‐dimensional analog of the single‐dose BMD at which both agents achieve the specified BMR – is defined for use in quantitative risk characterization and assessment. The resulting, joint, low‐dose guidelines can improve public health planning and risk regulation when dealing with low‐level exposures to combinations of hazardous agents.     

Risk Assessment: Replacing Default Options with Specific Science

The history of approaches to evaluating the hazards and risks of chemicals is briefly reviewed. The role of default options (generic approaches based on general knowledge in the absence of specific knowledge to the contrary) is discussed as a part of the risk assessment paradigm advanced by the National Academy of Science/National Research Council in 1983 and 1994. Examples are given of the impact of acquiring specific science to replace default options. An argument is made for developing specific science that would reduce uncertainty in risk assessments. Research on specific science would be guided by identified sources of uncertainty in the risk assessment process. The importance of using a research strategy that builds on human data is emphasized for validating new molecular and cellular biological assessment methods. The paper closes with a discussion of the tension between a hazard-based approach versus quantitative risk assessment in guiding risk management decisions. The former requires limited data, is qualitative, and easy to communicate, while the latter requires substantial data and is difficult to communicate. However, quantitative risk assessment provides a more rational basis for decisions on the allocation of both public and private resources for actions that will effectively minimize overall health risks to the public.     

Determining Indicators of Exposure and Effects for Endocrine Disrupting Chemicals (EDCs): An Introduction

Endocrine disruptors are characterized by their influence on animal endocrine systems resulting in reproductive, developmental, neurological, and immune dysfunction. The purpose of this overview is to provide the reader with a sense of the activities within the U.S. Environmental Protection Agency (USEPA), in particular NHEERL, that address the many facets of research on endocrine disrupting chemicals (EDCs) and to highlight the approach being taken at the different organizational levels within the USEPA, including screening, testing and evaluating endocrine disrupting chemicals. As a part of this endeavor, the USEPA continues to evaluate the current research activities in order to better understand and refine the process of risk characterization of EDCs. Thus, the participants in this session were asked to review their research within the framework of a better identification of EDC effects, better characterization of those compounds that have endocrine disrupting activity and how to incorporate this information into the risk assessment paradigm. Specifically, the goals of the ensuing papers were to compare individual vs. population indicators of endocrine disrupting effects, examine comparable and multiple mechanisms of toxicity, and describe the use of effects as indicators to identify toxicants and their sources. Mammalian and fish reproductive endpoints served as models to emphasize commonalities between human and wildlife risks.     

Zebrafish (Danio rerio) as a model organism for investigating endocrine disruption

Endocrine-disrupting compounds (EDCs) are widespread in the aquatic environment and can cause alterations in development, physiological homeostasis and health of vertebrates. Zebrafish, Danio rerio, has been suggested as a model species to identify targets as well as modes of EDC action. In fact, zebrafish has been found useful in EDC screening, in EDC effects assessment and in studying targets and mechanisms of EDC action. Since many of the environmental EDCs interfere with the sex steroid system of vertebrates, most EDC studies with zebrafish addressed disruption of sexual differentiation and reproduction. However, other targets of EDCs action must not be overlooked. For using a species as a toxicological model, a good knowledge of the biological traits of this species is a pre-requisite for the rational design of test protocols and endpoints as well as for the interpretation and extrapolation of the toxicological findings. Due to the genomic resources available for zebrafish and the long experience with zebrafish in toxicity testing, it is easily possible to establish molecular endpoints for EDC effects assessment. Additionally, the zebrafish model offers a number of technical advantages including ease and cost of maintenance, rapid development, high fecundity, optical transparency of embryos supporting phenotypic screening, existence of many mutant strains, or amenability for both forward and reverse genetics. To date, the zebrafish has been mainly used to identify molecular targets of EDC action and to determine effect thresholds, while the potential of this model species to study immediate and delayed physiological consequences of molecular interactions has been instrumentalized only partly. One factor that may limit the exploitation of this potential is the still rather fragmentary knowledge of basic biological and endocrine traits of zebrafish. Information on species-specific features in endocrine processes and biological properties, however, need to be considered in establishing EDC test protocols using zebrafish, in extrapolating findings from zebrafish to other vertebrate species, and in understanding how EDC-induced gene expression changes translate into disease.     

Pathway-Related Factors: The Potential for Human Data to Improve the Scientific Basis of Risk Assessment

The default uncertainty factors used for risk assessment are applied either to allow for different aspects of extrapolation of the dose-response curve or to allow for database deficiencies. Replacement of toxicokinetic or toxicodynamics defaults by chemical-specific data allows the calculation of a chemical-specific “data-derived factor”, which is the product of chemical-specific values and default uncertainty factors. Such chemical-specific composite values will improve the scientific basis of the risk assessment of that chemical, but the necessary chemical-specific data are rarely available. Categorical defaults related to pathways of elimination and mechanisms of toxicity could be used when the overall fate or mechanism is known, but there are no chemical-specific data sufficient to allow replacement of the default, and the development of an overall data-derived factor. The development of pathway-related categorical defaults is being undertaken using data on selected probe substrates for which adequate data are available. The concept and difficulties of this approach are illustrated using data for CYP1A2.     

Quantitative risk assessment for multivariate continuous outcomes with application to neurotoxicology: the bivariate case

The neurotoxic effects of chemical agents are often investigated in controlled studies on rodents, with multiple binary and continuous endpoints routinely collected. One goal is to conduct quantitative risk assessment to determine safe dose levels. Such studies face two major challenges for continuous outcomes. First, characterizing risk and defining a benchmark dose are difficult. Usually associated with an adverse binary event, risk is clearly definable in quantal settings as presence or absence of an event; finding a similar probability scale for continuous outcomes is less clear. Often, an adverse event is defined for continuous outcomes as any value below a specified cutoff level in a distribution assumed normal or log normal. Second, while continuous outcomes are traditionally analyzed separately for such studies, recent literature advocates also using multiple outcomes to assess risk. We propose a method for modeling and quantitative risk assessment for bivariate continuous outcomes that address both difficulties by extending existing percentile regression methods. The model is likelihood based; it allows separate dose-response models for each outcome while accounting for the bivariate correlation and overall characterization of risk. The approach to estimation of a benchmark dose is analogous to that for quantal data without the need to specify arbitrary cutoff values. We illustrate our methods with data from a neurotoxicity study of triethyl tin exposure in rats.     

Endocrine disruption in aquatic systems: up‐scaling research to address ecological consequences

Endocrine‐disrupting chemicals (EDCs) can alter biological function in organisms at environmentally relevant concentrations and are a significant threat to aquatic biodiversity, but there is little understanding of exposure consequences for populations, communities and ecosystems. The pervasive nature of EDCs within aquatic environments and their multiple sub‐lethal effects make assessments of their impact especially important but also highly challenging. Herein, we review the data on EDC effects in aquatic systems focusing on studies assessing populations and ecosystems, and including how biotic and abiotic processes may affect, and be affected by, responses to EDCs. Recent research indicates a significant influence of behavioural responses (e.g. enhancing feeding rates), transgenerational effects and trophic cascades in the ecological consequences of EDC exposure. In addition, interactions between EDCs and other chemical, physical and biological factors generate uncertainty in our understanding of the ecological effects of EDCs within aquatic ecosystems. We illustrate how effect thresholds for EDCs generated from individual‐based experimental bioassays of the types commonly applied using chemical test guidelines [e.g. Organisation for Economic Co‐operation and Development (OECD)] may not necessarily reflect the hazards associated with endocrine disruption. We argue that improved risk assessment for EDCs in aquatic ecosystems urgently requires more ecologically oriented research as well as field‐based assessments at population‐, community‐ and food‐web levels.     

Comprehensive Realism's Weight-of-Evidence Based Distributional Dose-Response Characterization

Challenges to low-dose linearity and other default assumptions in cancer risk assessment and the limitations associated with NOAELs, LOAELs, and constant uncertainty factor values in the evaluation of noncancer health effects have stimulated the continued evolution of risk assessment methodologies. The increasing need for more realistic estimates of the dose-response relationship, better uncertainty characterization, and greater utilization of cost-benefit analyses have also contributed to this evolution. “Comprehensive Realism” is an emerging quantitative weight-of-evidence based risk assessment methodology for both cancer and noncancer health effects which utilizes probability distributions and decision analysis techniques to reflect more of the relevant human exposure data, more of the available and pertinent human and animal dose-response data, and the current state of knowledge about the relative plausibility of alternative dose-response analyses. A tree (like a decision tree and a probability tree) is used to decompose the dose-response assessment into component factors, to provide a structure for explicitly considering multiple alternatives for each factor, and to explicitly incorporate the current state of knowledge about the relative plausibility of these alternatives. Groundbreaking work has demonstrated the feasibility of weight-of-evidence based distributional characterizations, and provided initial examples. Computer software implementations are also available.     

Likelihood models for clustered binary and continuous outcomes: application to developmental toxicology

In developmental toxicology, methods based on dose response modeling and quantitative risk assessment are being actively pursued. Among live fetuses, the presence of malformations and reduction in fetal weight are of primary interest, but ordinarily, the dose-response relationships are characterized in each of the outcomes separately while appropriately accounting for clustering within litters. Jointly modeling the outcomes, allowing different relationships with dose while incorporating the correlation between the fetuses and the outcomes, may be more appropriate. We propose a likelihood-based model that is an extension of a correlated probit model to incorporate continuous outcomes. Our model maintains a marginal dose-response interpretation for the individual outcomes while taking into account both the correlations between outcomes on an individual fetus and those due to clustering. The joint risk of malformation and low birth weight can then be estimated directly. This approach is particularly well suited to estimating safe dose levels as part of quantitative risk assessment.     

Quantitative Risk Assessment in Epidemiological Studies Investigating Threshold Effects

In this paper a method for quantitative risk assessment in epidemiological studies investigating threshold effects is proposed. The simple logistic regression model is used to describe the association between a binary response variable and a continuous risk factor. By defining acceptable levels for the absolute risk and the risk gradient the corresponding benchmark values of the risk factor can be calculated by means of nonlinear functions of the logistic regression coefficients. Standard errors and confidence intervals of the benchmark values are derived by means of the multivariate delta method. The proposed approach is compared with the threshold model of Ulm (1991) for assessing threshold values in epidemiological studies.     

Assessment of reproductive risks

In the regulatory process, the hazards posed by potentially toxic agents to the female and male reproductive systems and to developing young are evaluated by risk assessment procedures. In this paper, toxicity testing and the regulatory process are discussed, with emphasis on risk assessment. The suggested testing protocols of the Pesticide Assessment Guidelines (U.S. EPA) are presented as an example of testing that might be done to produce toxicity data for an agent. Protocols and end points that are utilized in testing for reproductive effects are described. Included are acute, subchronic, chronic, and short-term tests. The four components of reproductive risk assessment (hazard identification, dose-response assessment, exposure assessment, and risk characterization) are examined. Effects of dibromochloropropane on rabbit testicular parameters are used to demonstrate approaches that could be taken in doing a reproductive risk assessment. Research needs for screening methods, adequate dose-response testing, toxicokinetics, end point development, and extrapolation methods are identified. Finally, this paper discusses selected areas in which changes in reproductive risk assessment are anticipated, as well as the mechanism for influencing the nature and extent of those changes.     

Mechanistic Modeling of Salmonellosis

The serious limitation of the available human data contributes to the need for making simplifying assumptions for dose-response modeling which has led to frequent use of a single function, the beta-Poisson function, as a default dose-response model form. This function is a concave, low-dose linear function. Sub-linear or convex curves may be more appropriate for some host-pathogen interactions due to the series of highly regulated innate and acquired defense systems of the healthy human body that protect against most microbial challenges. A systematic investigation of the steps of non-typhoid salmonellosis in humans leads to biological motivations for sub-linear, or non-concave, dose-response curves in microbial risk assessment. Three phenomena were identified that might contribute to sub-linear, or non-concave, dose-response curves: (1) clumping of bacterial cells in microcolonies in a food matrix; (2) quorum sensing, or density-dependency in expression of virulence genes or other metabolic actions; and (3) need, at least in some circumstances, for multiple lesions for progression to symptomatic illness. This investigation suggests that microbial risk assessors should routinely employ a variety of model forms in addition to the commonly used beta-Poisson model to depict more fully the uncertainty of the true dose-response model.     

Statistical Evaluation of Toxicological Experimental Design for Bayesian Model Averaged Benchmark Dose Estimation with Dichotomous Data

A method is presented to statistically evaluate toxicity study design for dose– response assessment aimed at minimizing the uncertainty in resulting Benchmark dose (BMD) estimates. Although the BMD method has been accepted as a valuable tool for risk assessment, the traditional no observed adverse effect level (NOAEL)/lowest observed adverse effective level (LOAEL) approach is still the principal basis for toxicological study design. To develop similar protocols for experimental design for BMD estimation, methods are needed that account for variability in experimental outcomes, and uncertainty in dose–response model selection and model parameter estimates. Based on Bayesian model averaging (BMA) BMD estimation, this study focuses on identifying the study design criteria that can reduce the uncertainty in BMA BMD estimates by using a Monte Carlo pre-posterior analysis on BMA BMD predictions. The results suggest that (1) as more animals are tested there is less uncertainty in BMD estimates; (2) one relatively high dose is needed and other doses can then be appropriately spread over the resulting dose scale; (3) placing different numbers of animals in different dose groups has very limited influence on improving BMD estimation; and (4) when the total number of animals is fixed, using more (but smaller) dose groups is a preferred strategy.     

Chromatographic evaluation of the toxicity in fish of pesticides

Ecotoxicity assessment is essential before placing new chemical substances on the market. An investigation of the use of the chromatographic retention (log k) in biopartitioning micellar chromatography (BMC) as an in vitro approach to evaluate the toxicity in fish of pesticides (acute toxicity levels as pLC(50)) is proposed. A heterogeneous data set of 85 pesticides from six chemical families with available experimental fish toxicity data (ECOTOX database from U.S. Environmental Protection Agency (EPA)) was used. For pesticides exhibiting non-polar narcosis mechanism in fish (non-specific toxicity), more reliable models and precise pLC(50) estimations are obtained from log k (quantitative retention-activity relationships, QRAR) than from log P (quantitative structure-activity relationships, QSAR) or ECOSAR (ECOSAR program from U.S. EPA).     

A new recombinant cell-based bioluminescent assay for sensitive androgen-like compound detection

A public concern is continuously arising about the presence of natural and anthropogenic compounds which affect human health by modulating normal endocrine functions. These substances, defined as endocrine disrupting compounds (EDC) represent an heterogeneous class of molecules either steroidal or not, sharing the ability of interfering with the endocrine system via nuclear receptor signaling pathways. Therefore there is an urgent need for high throughput screening systems able to detect EDCs and evaluate their biological activity. However, little attention has been dedicated to the development of assays for androgen-like compounds. The present work describes the development and optimization of a new rapid and sensitive bioluminescent yeast-based bioassay for androgen-like compounds in a 96-well microplate format. The bioassay is based on recombinant Saccharomyces cerevisiae cells modified to express human androgen receptor (hAR) and containing the sequence androgen response element (ARE) which drives the expression of Photinus pyralis luciferase, used as reporter gene. A recombinant yeast strain constitutively expressing luciferase was used as external control to correct the light signal accordingly to cell viability and sample matrix aspecific effects. The bioassay responds to testosterone as reference androgen in a concentration-dependent manner from 0.05 to 1000 nM allowing an accurate and precise quantitative evaluation in aqueous environmental samples down to 10(-11)mol/L. Other known androgen-like compounds exhibit similar dose-response behavior, thus permitting the use of the bioassay for an overall detection of androgen-like effect in environmental samples.