Effects of glutathione transferase theta polymorphism on the risk estimates of dichloromethane to humans.

The carcinogenic potential of dichloromethane (DCM) has been linked to its metabolism to formaldehyde by glutathione-S-transferase theta 1 (GSTT1). GSTT1 is polymorphic in humans. The frequency of the GSTT1 homozygous null genotype ranges from 10 to 60% in different ethnic and racial populations around the world. We investigated how varying GSTT1 genotype frequencies would impact cancer risk estimates for DCM by the application of Monte Carlo simulation methods in combination with physiologically based pharmacokinetic (PBPK) models. The PBPK model was used to estimate the DNA-protein cross links (DPX) caused by metabolism of DCM based on an earlier model. Cancer potency of DCM was obtained by the application of the estimated DPX amounts to the results of a carcinogenicity study by National Toxicology Program in B6C3F(1) mice. Human risks were estimated based on the carcinogenic potency of DCM to mice and PBPK-predicted amounts of DPX formed in humans. The Monte Carlo simulations were used to provide distributions of risk estimates for a sample of 1000 PBPK runs, each run representing a collection of biochemical and physiological parameters for a single person (with and without polymorphism included in the model). Our results show that average and median risk estimates were 23-30% higher when GSTT1 polymorphism was not included at inhalation DCM doses of 1000, 100, 10, and 1 ppm. This increase in risk was significantly reduced when it was based on the 95th percentile measure for all the doses. The specific effect of this polymorphism on population risk was further investigated by varying the probability that an individual may have a nonfunctional form of the enzyme at a constant dose level of 10 ppm of DCM. Higher values of this probability resulted in a corresponding decrease in risk. Again, this drop in population risk was not as significant when the 95th percentile measure was used.

Characterizing dose-response: I: Critical assessment of the benchmark dose concept.

We present a critical assessment of the benchmark dose (BMD) method introduced by Crump as an alternative method for setting a characteristic dose level for toxicant risk assessment. The no-observed-adverse-effect-level (NOAEL) method has been criticized because it does not use all of the data and because the characteristic dose level obtained depends on the dose levels and the statistical precision (sample sizes) of the study design. Defining the BMD in terms of a confidence bound on a point estimate results in a characteristic dose that also varies with the statistical precision and still depends on the study dose levels. Indiscriminate choice of benchmark response level may result in a BMD that reflects little about the dose-response behavior available from using all of the data. Another concern is that the definition of the BMD for the quantal response case is different for the continuous response case. Specifically, defining the BMD for continuous data using a ratio of increased effect divided by the background response results in an arbitrary dependence on the natural background for the endpoint being studied, making comparison among endpoints less meaningful and standards more arbitrary. We define a modified benchmark dose as a point estimate using the ratio of increased effect divided by the full adverse response range which enables consistent placement of the benchmark response level and provides a BMD with a more consistent relationship to the dose-response curve shape.

Genetic susceptibility: significance in risk assessment.

Polymorphisms in metabolism and DNA-repair genes can increase the risks of cancer associated with exposure to chemical and physical agents in the environment. These types of gene-environment interactions may alter our view of dose-response patterns and how to characterize risk in an exposed population. Depending upon the action of the different forms of these genes, differing patterns of dose-response may be seen in a study population and these patterns can effect our interpretation of the degree of hazard as well as the risk in the general population. This short report describes some of the key issues associated with how variation in genetic make-up can result in different dose-response patterns for cancer following exposure to environmental agents.

Statistical research needs in mechanistic modelling for carcinogenic risk assessment.

If the broad spectrum of mechanistic research conducted on an environmental carcinogen is to be used in quantifying cancer risks, statisticians must play a key role. Statistical methods are critically needed for a scientifically valid analysis of a complicated series of linked experimental findings. This will require a greater understanding of the underlying biology than is common in statistical consulting, aiding in the development of complicated mechanistically based mathematical descriptions of mean response and in the creation of statistical methods for the estimation of model parameters (e.g. likelihoods) able to use both the underlying model and much of the available data.

Workshop overview. National Toxicology Program Studies: principles of dose selection and applications to mechanistic based risk assessment.

A workshop entitled "NTP Studies: Principles of Dose Selection and Applications to Mechanistic Based Risk Assessment" was held at the 34th Annual Meeting of the Society of Toxicology in Baltimore, Maryland. The purpose of the workshop was to provide an overview of factors currently considered important in the selection of doses for NTP studies, to describe some of the confounding factors that can result from the indiscriminate use of bioassay data in quantitative risk assessment, and to suggest ways in which information from mechanistic studies or studies of biomarkers of exposure or effect might be used to better advantage in risk assessment.

Implications for risk assessment of suggested nongenotoxic mechanisms of chemical carcinogenesis.

Nongenotoxic carcinogens are chemicals that induce neoplasia without it or its metabolites reacting directly with DNA. Chemicals classified as nongenotoxic carcinogens have been assumed to act as tumor promoters and exhibit threshold tumor dose-responses. This is in contrast to genotoxic carcinogens that are DNA reactive, act as tumor initiators, and are assumed to exhibit proportional responses at low doses. In this perspective, we examine the basic tenets and utility of this classification for evaluating human cancer risk. Two classes of so-called nongenotoxic chemical carcinogens selected for review include cytotoxic agents that induce regenerative hyperplasia (trihalomethanes and inducers of alpha 2-microglobulin nephropathy) and agents that act via receptor-mediated mechanisms (peroxisome proliferators and dioxin). Major conclusions of this review include: a) many chemicals considered to be nongenotoxic carcinogens actually possess certain genotoxic activities, and limiting evaluations of carcinogenicity to their nongenotoxic effects can be misleading; b) some nongenotoxic activities may cause oxidative DNA damage and thereby initiate carcinogenesis; c) although cell replication is involved in tumor development, cytotoxicity and mitogenesis do not reliably predict carcinogenesis; d) a threshold tumor response is not an inevitable result of a receptor-mediated mechanism. There are insufficient data on the chemicals reviewed here to justify treating their carcinogenic effects in animals as irrelevant for evaluating human risk. Research findings that characterize the multiple mechanisms of chemical carcinogenesis should be used quantitatively to clarify human dose-response relationships, leading to improved scientifically based public health decisions. Excessive reliance on oversimplified classification schemes that do not consider all potential contributing effects of a toxicant can obscure the actual causal relationships between exposure and cancer outcome.

The importance of biological realism in dioxin risk assessment models.

Mechanistic mathematical models of hepatocarcinogenesis in the female rat were constructed to investigate possible relationships among the Ah, estrogen, and EGF receptors in TCDD hepatocarcinogenicity. Each model generates dose-response curves for the expression of biomarker liver proteins CYP1A1, CYP1A2, and residual plasma membrane EGF receptor consequent to exposure to TCDD. The shapes of the response curves were strongly dependent on the assumed mechanisms of constitutive expression of these proteins. Assuming a constant level of the hepatic Ah receptor, a sigmoidal dose-response of hepatic CYP1A1 to total liver TCDD was computed. However, inclusion of induction of the Ah receptor by TCDD in a physiologically realistic dosimetric model produced a linear low-dose response of CYP1A1. This behavior was computed to arise from the net effect of sublinear response of CYP1A1 mRNA to the concentration of the Ah-TCDD complex and supralinear response of the protein concentration to the mRNA level, illustrating the importance of biological realism in dose-response modeling. The dosimetric model also computed effects of TCDD on the hepatic estradiol concentration and consequent effects on the binding capacity of the EGF receptor and suggests plausible mechanisms for tumor promotion by TCDD. Setting circulating estradiol levels in the model to values typical of the male rat indicated possible sources of the differences in the responses of the EGF receptor and in development of tumors in the two sexes.

Use of animal studies in risk assessment for immunotoxicology.

We have previously reported on the design and content of a screening battery involving a 'tier' approach for detecting potential immunosuppressive compounds in mice. This battery has been used to examine a variety of compounds, and the database generated from these studies, which consists of over 50 compounds, has been collected and analyzed in an attempt to improve the accuracy and efficiency of screening chemicals for immunosuppression and to identify better those tests that predict experimentally-induced, immune-mediated diseases. Specifically, these analyses attempted to develop an improved testing configuration for the accurate prediction of immunotoxic agents and to provide insight into the qualitative and quantitative relationships between a number of immune and host resistance assays commonly employed to examine potential immunotoxic chemicals in experimental animals. While a number of limitations existed in the analyses, several conclusions were drawn from the results which will be discussed.

The use of animal tests in risk assessment for immunotoxicology.

The design and content of a screening battery using a 'tier' approach for detecting potential immunotoxic compounds in mice has been described (M. I. Luster et al., Fundamental and Applied Toxicology 1988, 10, 2-19). The database generated from these studies, which consists of over 50 selected compounds, has been analysed in an attempt to improve future testing strategies and provide information to aid in developing future quantitative risk assessment for immunotoxicity. In a recent study it was shown that as few as two or three immune parameters were needed to predict immunotoxicants in mice (M. I. Luster et al., Fundamental and Applied Toxicology 1992, 18, 200-210). The analyses described here focus on the use of this database to develop statistical models that examine the qualitative and quantitative relationship(s) between the immune function and host resistance tests. The conclusions derived from these analyses are as follows: (1) A good correlation exists between changes in the immune tests and altered host resistance, in that there were no instances where host resistance was altered without affecting one or more immune test(s). However, in some instances immune changes occurred without corresponding changes in host resistance. (2) No single immune test could be identified that was fully predictive for altered host resistance, although most assays were relatively good indicators (i.e. 70%). Several others, such as proliferative response to lipopolysaccharide and leucocyte counts, were found to be relatively poor indicators for host resistance changes. (3) The ability to resist infectious agent challenge is dependent on the degrees of immunosuppression and the quantity of infectious agent administered. (4) Logistic and standard regression modelling using one extensive chemical data set from the immunosuppressive agent, cyclophosphamide, indicated that most immune function-host resistance relationships followed linear rather than linear-quadratic (threshold-like) models. For most of the relationships this could not be confirmed using a large chemical data set and, thus, a more mechanistically based approach for modelling will need to be developed.

Risk assessment in immunotoxicology. II. Relationships between immune and host resistance tests.

We have reported on the design and content of a screening battery using a "tier" approach for detecting potential immunotoxic compounds in mice (Luster et al., Fundam. Appl. Toxicol., 10, 2-19, 1988). The data base generated from these studies, which consists of over 50 selected compounds, has been collected and analyzed in an attempt to improve future testing strategies and provide information to aid in developing future quantitative risk assessment for immunotoxicity. In a recent study it was shown that as few as two or three immune parameters were needed to predict immunotoxicants in mice (Luster et al., Fundam. Appl. Toxicol., 18, 200-210, 1992). In particular, enumeration of lymphocyte populations and quantitation of the T-dependent antibody response were particularly beneficial. Furthermore, commonly employed apical measures (e.g., leukocyte counts, lymphoid organ weights) were fairly insensitive. The present analyses focus on the use of this data base to develop statistical models that examine the qualitative and quantitative relationship(s) between the immune function and host resistance tests. The conclusion derived from these analyses are: (1) A good correlation exists between changes in the immune tests and altered host resistance in that there were no instances where host resistance was altered without affecting an immune test(s). However, in some instances immune changes occurred without corresponding changes in host resistance. (2) No single immune test could be identified which was fully predictive for altered host resistance, although most assays were relatively good indicators (i.e., > 70%). Several others, such as proliferative response to lipopolysaccharide and leukocyte counts, were found to be relatively poor indicators for host resistance changes. (3) The ability to resist infectious agent challenge is dependent upon the degrees of immunosuppression and the quantity of infectious agent administered. (4) Logistic and standard regression modeling using one extensive chemical data set from the immunosuppressive agent, cyclophosphamide, indicated that most immune function-host resistance relationships followed linear rather than linear-quadratic (threshold-like) models. For most of the relationships this could not be confirmed using a large chemical data set and, thus, a more mechanistically based approach for modeling will need to be developed. (5) Using this limited data set, methods were developed for modeling the precise quantitative relationships between changes in selected immune tests and host resistance tests.

Ligand/receptor binding for 2,3,7,8-TCDD: implications for risk assessment.

There is renewed controversy regarding safe exposure levels for dioxin. At the heart of this controversy is the hypothesis that toxic effects of dioxin are receptor-mediated and therefore a "threshold" should exist below which no toxic effects can occur. Our research focuses on the ability of dioxin to alter protein levels in rodent livers. Established effects of exposure to dioxin are the induction of cytochrome P450-1A1 and P450-1A2 and a reduction in the maximal binding of the epidermal growth factor receptor in rat livers. An initiation-promotion protocol was used to study the effects of dioxin in female Sprague-Dawley rats. Animals were administered a single initiating dose of diethylnitrosamine followed by 16 biweekly gavage doses of 2,3,7,8-TCDD. Steady-state pharmacodynamic models were fit to these data assuming a combination of Hill kinetics and Michaelis-Menten kinetics. Two classes of models were developed which postulate two different mechanisms for the constitutive expression and TCDD-induced alterations in the levels of these proteins. The results are consistent with models which follow proportionate response in the low-dose region (no threshold) and with models which allow for a low-dose threshold. In all cases studied, the best fitting model exhibited no "threshold" for the effects of TCDD on the modulation of these proteins. The finding is consistent with the knowledge that for some receptor-mediated responses, there is a proportional relationship between receptor occupancy and biological response, even at low ligand concentrations.(ABSTRACT TRUNCATED AT 250 WORDS)

Mechanistic modelling and risk assessment.

Risk Assessment in the United States has been rapidly changing over the last few years. The historical methods and endpoints by which risk estimates were derived are gradually being replaced by newer methods and a broader spectrum of endpoints. For carcinogenic risk assessment, there is movement from the routinely used "linearized multistage model" for low dose risk estimation to methodology which is more deeply rooted in carcinogenic mechanisms and which allows the incorporation of additional data into the estimation of risks in a direct, quantitative fashion. There is also a determined effort under way to develop methods for assessing risks from exposure based on other endpoints such as effects on the immune system and the reproductive system. This paper briefly discusses some of the statistical and mathematical issues which will play important roles in determining the utility and precision of these new methods for estimating risks from environmental exposures.

Qualitative and quantitative experimental models to aid in risk assessment for immunotoxicology.

We have previously reported on the design and content of a screening battery using a "tier" approach for detecting potential immunosuppressive compounds in mice [1]. This battery was composed of various immune function, immunopathology and host resistance tests, the results of which could help establish the potential of chemical and biological agents to cause immunosuppression. The data from these studies, which now encompass over 50 compounds, have been analyzed in an attempt to improve future testing strategies and provide information to aid in the risk assessment process. Specifically, the following two issues will be addressed; what are the likelihood(s) for each of the individual tests and testing configurations to accurately identify immunotoxic compounds? and what are the quantitative and qualitative relationships between the immune tests and host resistance assays?

Risk assessment in immunotoxicology. I. Sensitivity and predictability of immune tests.

We have previously reported on the design and content of a screening battery involving a "tier" approach for detecting potential immunotoxic compounds in mice (Luster et al., 1988, Fundam. Appl. Toxicol. 10, 2-19). This battery has now been utilized to examine a variety of compounds by the NIEHS Immunotoxicology Laboratory, the National Toxicology Program-sponsored laboratories, and by the Cell Biology Department at the Chemical Industry Institute of Toxicology. The database generated from these studies, which consists of over 50 selected compounds, has been collected and analyzed in an attempt to improve future testing strategies and provide information to aid in quantitative risk assessment for immunotoxicity. Studies presented here have established the ability of each of the tests or test combinations in the screening battery to detect immunotoxic compounds. Efforts are currently underway using this database to determine the relationships between these immune tests and susceptibility to challenge with infectious agents or transplantable tumor cells. The present analyses indicated that the performance of only two or three immune tests are sufficient to predict immunotoxic compounds in rodents (greater than 90% concordance). The tests that showed the highest association with immunotoxicity were the splenic antibody plaque forming cell response (78%) and cell surface marker analysis (83%). The relationship between immunotoxicity and carcinogenicity, as well as genotoxicity, was also determined. These analyses suggested that potential immunotoxic compounds are likely to be rodent carcinogens (p = 0.019) although for compounds that are not immunotoxic the carcinogenic status is unclear. There was no relationship observed between immunotoxicity and mutagenicity as determined using in vitro genotoxicity tests. The significance of these observations is discussed in terms of the relationship between immunotoxicity tests and biological/toxicological processes concerned with human health (e.g., infectious disease).

An evaluation of the Rai and Van Ryzin dose-response model in teratology.

The underlying assumptions of the Rai and Van Ryzin dose-response model for reproductive toxicological data are evaluated on the basis of existing experimental data. The model under consideration is unusual in its use of litter size to completely account for extra-binomial variation in the data by associating litter size with reproductive outcome. The experimental data show that controlling litter size is not sufficient to account for the litter-to-litter variability in responses. It is also shown that the two linear components of the Rai and Van Ryzin model are inappropriate. For the component which applies to the dam, the data suggest a strong nonlinearity, supported by rejection of the linear model via statistical hypothesis tests. In the component involving litter size, a relationship with dose is not apparent. The litter size parameters offer considerable potential for bias in estimation; bias which is at least partly masked by the model having good prediction characteristics due to the increased number of parameters. A simulation study is presented to illustrate how the Rai and Van Ryzin model can exaggerate litter size effects on the probability of response when the simulated data arise from a model involving a nonlinear dam component, common to this type of data, and no effect of litter size.

Biologically based models for risk assessment.

The modelling problems associated with the estimation of risks from long-term chemical exposures at low dose levels represent a statistical and mathematical challenge with special relevance to environmental research. Determining an adequate model for estimating the relationship between dose and response is critical to reducing potential bias in the risk estimation process. This paper discusses the various assumptions and models used in carcinogenic risk assessment. The emphasis is on our ability to accurately determine the magnitude of the carcinogenic risk, the shape of the dose-response relationship and the overall variability of the risk estimates.

Variability of safe dose estimates when using complicated models of the carcinogenic process. A case study: methylene chloride.

Advances in understanding carcinogenesis have led to the development of mathematical models that have biologically interpretable parameters. These models utilize more of the available scientific data than the empirical models routinely employed for quantifying carcinogenic risk. They also require consideration of sources of uncertainty in risk estimates that were previously ignored, such as animal-to-animal variability of physiological and pharmacological constants. A numerical technique is proposed for studying the consequences of incorporating the intrapopulation variability of biologically interpretable parameters into the risk assessment process. To demonstrate the technique, the variability of safe dose estimates for exposure to methylene chloride is considered. The results suggest that intrapopulation variability of the model parameters can increase the variability of safe dose estimates an appreciable amount.