Search

Short-term biomarkers of toxicity have an increasingly important role in the screening and prioritization of new chemicals. In this study, we examined early indicators of liver toxicity for three reference organophosphate (OP) chemicals, which are among the most widely used insecticides in the world. The OP methidathion was previously shown to increase the incidence of liver toxicity, including hepatocellular tumors, in male mice. To provide insights into the adverse outcome pathway (AOP) that underlies these tumors, effects of methidathion in the male mouse liver were examined after 7 and 28 day exposures and compared to those of two other OPs that either do not increase (fenthion) or possibly suppress liver cancer (parathion) in mice. None of the chemicals caused increases in liver weight/body weight or histopathological changes in the liver. Parathion decreased liver cell proliferation after 7 and 28 days while the other chemicals had no effects. There was no evidence for hepatotoxicity in any of the treatment groups. Full-genome microarray analysis of the livers from the 7 and 28 day treatments demonstrated that methidathion and fenthion regulated a large number of overlapping genes, while parathion regulated a unique set of genes. Examination of cytochrome P450 enzyme activities and use of predictive gene expression biomarkers found no consistent evidence for activation of AhR, CAR, PXR, or PPARα. Parathion suppressed the male-specific gene expression pattern through STAT5b, similar to genetic and dietary conditions that decrease liver tumor incidence in mice. Overall, these findings indicate that methidathion causes liver cancer by a mechanism that does not involve common mechanisms of liver cancer induction.

Haber's rule as commonly interpreted in inhalation toxicology, can be stated as exposure concentration times duration equals a constant biological effect, or C × t = k . In other words, identical products of concentration and duration lead to the same effect. The goals of this paper are to develop a biological and pharmacokinetic modeling approach for chloroform, and to evaluate Haber's rule for different ages by taking into account the physiological changes due to growth and aging in rats. Three-dimensional dose–response surfaces for liver toxicity were generated for each age group of interest: adolescent, adult, and senescent rats. The three-dimensional surfaces were then characterized with a generalized description of Haber's rule for each age group. The simulations suggest that adolescent rats need higher exposure levels in order to achieve similar levels of liver damage compared to adults or senescent rats, if the comparison is made using the same exposure length. In summary, a pharmacokinetic modeling approach with a biological framework including the chemical's mode of action, was used to relate concentration, exposure duration and effect. Major advantages of this approach include: the potential ability to extrapolate to humans, the inclusion of aging in the simulations, and the ability to summarize the results using a generalized form of Haber's rule.

Mixture risk assessment is often hampered by the lack of dose–response information on the mixture being assessed, forcing reliance on component formulas such as dose addition. We present a four-step approach for evaluating chemical mixture data for consistency with dose addition for use in supporting a component based mixture risk assessment. Following the concepts in the U.S. EPA mixture risk guidance (U.S. EPA, 2000a,b), toxicological interaction for a defined mixture (all components known) is departure from a clearly articulated definition of component additivity. For the common approach of dose additivity, the EPA guidance identifies three desirable characteristics, foremost of which is that the component chemicals are toxicologically similar. The other two characteristics are empirical: the mixture components have toxic potencies that are fixed proportions of each other (throughout the dose range of interest), and the mixture dose term in the dose additive prediction formula, which we call the combined prediction model (CPM), can be represented by a linear combination of the component doses. A consequent property of the proportional toxic potencies is that the component chemicals must share a common dose–response model, where only the dose coefficients depend on the chemical components. A further consequence is that the mixture data must be described by the same mathematical function (“mixture model”) as the components, but with a distinct coefficient for the total mixture dose. The mixture response is predicted from the component dose–response curves by using the dose additive CPM and the prediction is then compared with the observed mixture results. The four steps are to evaluate: (1) toxic proportionality by determining how well the CPM matches the single chemical models regarding mean and variance; (2) fit of the mixture model to the mixture data; (3) agreement between the mixture data and the CPM prediction; and (4) consistency between the CPM and the mixture model. Because there are four evaluations instead of one, some involving many parameters or dose groups, there are more opportunities to reject statistical hypotheses about dose addition, thus statistical adjustment for multiple comparisons is necessary. These four steps contribute different pieces of information about the consistency of the component and mixture data with the two empirical characteristics of dose additivity. We examine this four-step approach in how it can show empirical support for dose addition as a predictor for an untested mixture in a screening level risk assessment. The decision whether to apply dose addition should be based on all four of those evidentiary pieces as well as toxicological understanding of these chemicals and should include interpretations of the numerical and toxicological issues that arise during the evaluation. This approach is demonstrated with neurotoxicity data on carbamate mixtures.

Evidence to explain the enhanced hepatotoxicity of carbon tetrachloride (CCl4) following methanol exposure by inhalation is presented. Hepatic microsomes prepared from male F344 rats exposed to methanol at concentrations up to 10,000 ppm showed increased p-nitrophenol hydroxylase activity but no increase in pentoxyresorufin-O-dealkylase or ethoxyresorufin-O-deethylase activities. Hepatic antioxidant levels, glutathione levels and glutathione-S-transferase activity in methanol-treated animals were not different from controls. In vitro metabolism of CCl4 was also increased in microsomes from methanol-treated animals. Pretreatment with allyl sulfone, a specific chemical inhibitor of cytochrome P450 2E1, abolished the difference in microsomal metabolism between exposed and control animals. This study shows that methanol exposure induces cytochrome P450 2E1, which appears to be the principal toxicokinetic mechanism responsible for the increased metabolism and thus the increased hepatotoxicity of CCl4.

It is now well-recognized that human environmental exposures are not to single chemicals. Rather, humans are exposed, either concurrently or sequentially, to multiple chemicals. Challenges that chemical mixtures pose for risk assessment and toxicology are presented. Challenge areas include increasing the peer-reviewed publication of human studies, improving access to peer-reviewed data and examining multiple target organs. Two difficult challenges are development of a common, consistent language and the use of appropriate and innovative experimental designs and analyses. The challenge of elucidation of mechanism(s) offers a rational basis for extrapolation across dose levels, exposure durations and exposure routes as well as to other species and to other similar chemicals. Of particular importance is focusing effort on those areas of investigation where answers have the greatest potential for reducing uncertainty in risk assessments for chemical mixtures and on those chemical mixtures and multiple chemical exposures that have the greatest potential impact on human health. A particularly fruitful area for future investigation is determination of the likelihood of nonadditive interactions in humans exposed to multiple chemicals at environmental exposure levels.

Exposure of rabbits for 12 weeks to 300 ppm carbon disulfide (CS2) for 6 h/day, 5 days/week, or to 25 mg/day of thiourea or 2% cholesterol in the diet, or to any combination thereof caused a significant reduction in the concentration of serum thyroxine (T4). The reduction of the concentration of serum T4 in rabbits by the treatments was completely offset by the inclusion of 0.1 mg/day of sodium levothyroxine in the diet. Ingestion of feed containing 2% cholesterol significantly increased the degree of atherosclerosis present in the aortic arch and significantly increased the oil red O positive lipid present in the heart and the aorta, with the aortic arch being the most severely affected. The response of the aorta and the heart to the 2% cholesterol diet was not significantly modified by concurrent exposure to CS2 by inhalation or by treatment with thiourea, a metabolite of CS2. We found no evidence that the development of cardiovascular lesions induced by a 2% cholesterol diet in rabbits was mediated by a mechanism involving a component of hypothyroidism.