Genomic comparisons between hepatocarcinogenic and non-hepatocarcinogenic organophosphate insecticides in the mouse liver.

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.

Arsenic toxicokinetic modeling and risk analysis: Progress, needs and applications.

Arsenic (As) poses unique challenges in PBTK model development and risk analysis applications. Arsenic metabolism is complex, adequate information to attribute specific metabolites to particular adverse effects in humans is sparse, and measurement of relevant metabolites in biological media can be difficult. Multiple As PBTK models have been published and used or adapted for use in various exposure and risk analysis applications. These applications illustrate the broad utility of PBTK models for exposure and dose-response analysis, particularly for arsenic where multi-pathway, multi-route exposures and multiple toxic effects are of concern. Arsenic PBTK models have been used together with exposure reconstruction and dose-response functions to estimate risk of specific adverse health effects due to drinking water exposure and consumption of specific foodstuffs (e.g. rice, seafood), as well as to derive safe exposure levels and develop consumption advisories. Future refinements to arsenic PBTK models can enhance the confidence in such analyses. Improved estimates for methylation biotransformation parameters based on in vitro to in vivo extrapolation (IVIVE) methods and estimation of interindividual variability in key model parameters for specific toxicologically relevant metabolites are two important areas for consideration.

Comparison of in vivo derived and scaled in vitro metabolic rate constants for several volatile organic compounds (VOCs).

Metabolic rate parameters estimation using in vitro data is necessary due to numbers of chemicals for which data are needed, trend towards minimizing laboratory animal use, and limited opportunity to collect data in human subjects. We evaluated how well metabolic rate parameters derived from in vitro data predict overall in vivo metabolism for a set of environmental chemicals for which well validated and established methods exist. We compared values of VmaxC derived from in vivo vapor uptake studies with estimates of VmaxC scaled up from in vitro hepatic microsomal metabolism studies for VOCs for which data were available in male F344 rats. For 6 of 7 VOCs, differences between the in vivo and scaled up in vitro VmaxC estimates were less than 2.6-fold. For bromodichloromethane (BDCM), the in vivo derived VmaxC was approximately 4.4-fold higher than the in vitro derived and scaled up VmaxC. The more rapid rate of BDCM metabolism estimated based in vivo studies suggests other factors such as extrahepatic metabolism, binding or other non-specific losses making a significant contribution to overall clearance. Systematic and reliable utilization of scaled up in vitro biotransformation rate parameters in PBPK models will require development of methods to predict cases in which extrahepatic metabolism and binding as well as other factors are likely to be significant contributors.

The Impact of Scaling Factor Variability on Risk-Relevant Pharmacokinetic Outcomes in Children: A Case Study Using Bromodichloromethane (BDCM).

Biotransformation rates extrapolated from in vitro data are used increasingly in human physiologically based pharmacokinetic (PBPK) models. This practice requires use of scaling factors, including microsomal content (mg of microsomal protein/g liver, MPPGL), enzyme specific content, and liver mass as a fraction of body weight (FVL). Previous analyses indicated that scaling factor variability impacts pharmacokinetic (PK) outcomes used in adult population dose-response studies. This analysis was extended to pediatric populations because large inter-individual differences in enzyme ontogeny likely would further contribute to scaling factor variability. An adult bromodichloromethane (BDCM) model (Kenyon, E. M., Eklund, C., Leavens, T. L., and Pegram, R. A. (2016a). Development and application of a human PBPK model for bromodichloromethane (BDCM) to investigate impacts of multi-route exposure. J. Appl. Toxicol. 36, 1095-1111) was re-parameterized for neonates, infants, and toddlers. Monte Carlo analysis was used to assess the impact of pediatric scaling factor variation on model-derived PK outcomes compared with adult findings. BDCM dose metrics were estimated following a single 0.05-liter drink of water or a 20-min bath, under typical (5 µg/l) and plausible higher (20 µg/l) BDCM concentrations. MPPGL, CYP2E1, and FVL values reflected the distribution of reported pediatric population values. The impact of scaling factor variability on PK outcome variation was different for each exposure scenario, but similar for each BDCM water concentration. The higher CYP2E1 expression variability during early childhood was reflected in greater variability in predicted PK outcomes in younger age groups, particularly for the oral exposure route. Sensitivity analysis confirmed the most influential parameter for this variability was CYP2E1, particularly in neonates. These findings demonstrate the importance of age-dependent scaling factor variation used for in vitro to in vivo extrapolation of biotransformation rates.

From the Cover: Genomic Effects of Androstenedione and Sex-Specific Liver Cancer Susceptibility in Mice.

Current strategies for predicting carcinogenic mode of action for nongenotoxic chemicals are based on identification of early key events in toxicity pathways. The goal of this study was to evaluate short-term key event indicators resulting from exposure to androstenedione (A4), an androgen receptor agonist and known liver carcinogen in mice. Liver cancer is more prevalent in men compared with women, but androgen-related pathways underlying this sex difference have not been clearly identified. Short-term hepatic effects of A4 were compared with reference agonists of the estrogen receptor (ethinyl estradiol, EE) and glucocorticoid receptor (prednisone, PRED). Male B6C3F1 mice were exposed for 7 or 28 days to A4, EE, or PRED. EE increased and PRED suppressed hepatocyte proliferation, while A4 had no detectable effects. In a microarray analysis, EE and PRED altered >3000 and >670 genes, respectively, in a dose-dependent manner, whereas A4 did not significantly alter any genes. Gene expression was subsequently examined in archival liver samples from male and female B6C3F1 mice exposed to A4 for 90 days. A4 altered more genes in females than males and did not alter expression of genes linked to activation of the mitogenic xenobiotic receptors AhR, CAR, and PPARα in either sex. A gene expression biomarker was used to show that in female mice, the high dose of A4 activated the growth hormone-regulated transcription factor STAT5b, which controls sexually dimorphic gene expression in the liver. These findings suggest that A4 induces subtle age-related effects on STAT5b signaling that may contribute to the higher risk of liver cancer in males compared with females.

The impact of variation in scaling factors on the estimation of internal dose metrics: a case study using bromodichloromethane (BDCM).

A rate for hepatic metabolism (Vmax) determined in vitro must be scaled for in vivo use in a physiologically based pharmacokinetic (PBPK) model. This requires the use of scaling factors such as mg of microsomal protein per gram of liver (MPPGL) and liver mass (FVL). Variation in MPPGL and FVL impacts variation in Vmax, and hence PBPK model-derived estimates of internal dose used in dose response analysis. The impacts of adult human variation in MPPGL and FVL on estimates of internal dose were assessed using a human PBPK model for bromodichloromethane (BDCM), a water disinfection byproduct, for multiple internal dose metrics for two exposure scenarios (single 0.25 liter drink of water or 10 min shower) under plausible (5 µg/L) and high level (20 µg/L) water concentrations. For both concentrations, all internal dose metrics were changed less than 5% for the showering scenario (combined inhalation and dermal exposure). In contrast, a 27-fold variation in area under the curve (AUC) for BDCM in venous blood was observed at both oral exposure concentrations, whereas total amount of BDCM metabolized in liver was relatively unchanged. This analysis demonstrates that variability in the scaling factors used for in vitro to in vivo extrapolation (IVIVE) for metabolic rate parameters can have a significant route-dependent impact on estimates of internal dose under environmentally relevant exposure scenarios. This indicates the need to evaluate both uncertainty and variability for scaling factors used for IVIVE.

Dose and Effect Thresholds for Early Key Events in a PPARα-Mediated Mode of Action.

Current strategies for predicting adverse health outcomes of environmental chemicals are centered on early key events in toxicity pathways. However, quantitative relationships between early molecular changes in a given pathway and later health effects are often poorly defined. The goal of this study was to evaluate short-term key event indicators using qualitative and quantitative methods in an established pathway of mouse liver tumorigenesis mediated by peroxisome proliferator-activated receptor alpha (PPARα). Male B6C3F1 mice were exposed for 7 days to di (2-ethylhexyl) phthalate (DEHP), di-n-octyl phthalate (DNOP), and n-butyl benzyl phthalate (BBP), which vary in PPARα activity and liver tumorigenicity. Each phthalate increased expression of select PPARα target genes at 7 days, while only DEHP significantly increased liver cell proliferation labeling index (LI). Transcriptional benchmark dose (BMDT) estimates for dose-related genomic markers stratified phthalates according to hypothetical tumorigenic potencies, unlike BMDs for non-genomic endpoints (relative liver weights or proliferation). The 7-day BMDT values for Acot1 as a surrogate measure for PPARα activation were 29, 370, and 676 mg/kg/day for DEHP, DNOP, and BBP, respectively, distinguishing DEHP (liver tumor BMD of 35 mg/kg/day) from non-tumorigenic DNOP and BBP. Effect thresholds were generated using linear regression of DEHP effects at 7 days and 2-year tumor incidence values to anchor early response molecular indicators and a later phenotypic outcome. Thresholds varied widely by marker, from 2-fold (Pdk4 and proliferation LI) to 30-fold (Acot1) induction to reach hypothetical tumorigenic expression levels. These findings highlight key issues in defining thresholds for biological adversity based on molecular changes.

Development and application of a human PBPK model for bromodichloromethane to investigate the impacts of multi-route exposure.

As a result of its presence in water as a volatile disinfection byproduct, bromodichloromethane (BDCM), which is mutagenic, poses a potential health risk from exposure via oral, dermal and inhalation routes. We developed a refined human physiologically based pharmacokinetic (PBPK) model for BDCM (including new chemical-specific human parameters) to evaluate the impact of BDCM exposure during showering and bathing on important measures of internal dose compared with oral exposure. The refined model adequately predicted data from the published literature for oral, dermal and bathing/showering exposures. A liter equivalency approach (L-eq) was used to estimate BDCM concentration in a liter of water consumed by the oral route that would be required to produce the same internal dose of BDCM resulting from a 20-min bath or a 10-min shower in water containing 10 µg l(-1) BDCM. The oral liter equivalent concentrations for the bathing scenario were 605, 803 and 5 µg l(-1) BDCM for maximum venous blood concentration (Cmax), the area under the curve (AUCv) and the amount metabolized in the liver per hour (MBDCM), respectively. For a 10-min showering exposure, the oral L-eq concentrations were 282, 312 and 2.1 µg l(-1) for Cmax, AUC and MBDCM, respectively. These results demonstrate large contributions of dermal and inhalation exposure routes to the internal dose of parent chemical reaching the systemic circulation, which could be transformed to mutagenic metabolites in extrahepatic target tissues. Thus, consideration of the contribution of multiple routes of exposure when evaluating risks from water-borne BDCM is needed, and this refined human model will facilitate improved assessment of internal doses from real-world exposures. Published 2015. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Identifiability of PBPK models with applications to dimethylarsinic acid exposure.

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology.

Interspecies extrapolation.

Interspecies extrapolation encompasses two related but distinct topic areas that are germane to quantitative extrapolation and hence computational toxicology-dose scaling and parameter scaling. Dose scaling is the process of converting a dose determined in an experimental animal to a toxicologically equivalent dose in humans using simple allometric assumptions and equations. In a hierarchy of quantitative extrapolation approaches, this option is used when minimal information is available for a chemical of interest. Parameter scaling refers to cross-species extrapolation of specific biological processes describing rates associated with pharmacokinetic (PK) or pharmacodynamic (PD) events on the basis of allometric relationships. These parameters are used in biologically based models of various types that are designed for not only cross-species extrapolation but also for exposure route (e.g., inhalation to oral) and exposure scenario (duration) extrapolation. This area also encompasses in vivo scale-up of physiological rates determined in various experimental systems. Results from in vitro metabolism studies are generally most useful for interspecies extrapolation purposes when integrated into a physiologically based pharmacokinetic (PBPK) modeling framework. This is because PBPK models allow consideration and quantitative evaluation of other physiological factors, such as binding to plasma proteins and blood flow to the liver, which may be as or more influential than metabolism in determining relevant dose metrics for risk assessment.

Genome-wide analysis of DNA methylation and gene expression changes in the mouse lung following subchronic arsenate exposure.

Alterations in DNA methylation have been proposed as a mechanism for the complex toxicological effects of arsenic. In this study, whole-genome DNA methylation and gene expression changes were evaluated in lungs from female mice exposed for 90 days to 50 ppm arsenate (As) in drinking water. DNA methylation changes were measured using reduced representation bisulfite deep sequencing. Differential methylation was observed in approximately 700 and 1900 start and transcribed regions, respectively. The start regions showed bias toward decreased methylation. No bias was observed in the transcribed region. A comparison of absolute methylation levels in the control animals with treatment-related changes in methylation showed that baseline methylation levels play a role in determining which genes are methylated. Genes with low absolute methylation levels in the start region showed a trend toward increased As-related methylation and decreased expression. Genes with high levels of methylation in the transcribed region showed a trend toward decreased As-related methylation, but no change in expression. No overall correlation between treatment-related changes in methylation and expression was identified. Among genes showing differential methylation in the start region and differential expression, only 57% showed an inverse correlation. The results suggest that differential methylation following As treatment may only play a permissive role in regulating expression. Despite the low correlation, the subset of 17 genes that showed an inverse relationship between As-related methylation and expression included a substantial number that has been demonstrated to play a functional role in cancer-related processes and other effects consistent with arsenic exposure.

Aging and susceptibility to toluene in rats: a pharmacokinetic, biomarker, and physiological approach.

Aging adults are a growing segment of the U.S. population and are likely to exhibit increased susceptibility to many environmental toxicants. However, there is little information on the susceptibility of the aged to toxicants. The toxicity of toluene has been well characterized in young adult rodents but there is little information in the aged. Three approaches were used: (1) pharmacokinetic (PK), (2) cardiac biomarkers, and (3) whole-animal physiology to assess whether aging increases susceptibility to toluene in the Brown Norway (BN) rat. Three life stages, young adult, middle aged, and aged (4, 12, and 24 mo, respectively), were administered toluene orally at doses of 0, 0.3, 0.65, or 1 g/kg and subjected to the following: terminated at 45 min or 4 h post dosing, and blood and brain toluene concentration were measured; terminated at 4 h post dosing, and biomarkers of cardiac function were measured; or monitor heart rate (HR), core temperature (Tc), and motor activity (MA) by radiotelemetry before and after dosing. Brain toluene concentration was significantly elevated in aged rats at 4 h after dosing with either 0.3 or 1 g/kg. Blood toluene concentrations were unaffected by age. There were various interactions between aging and toluene-induced effects on cardiac biomarkers. Most notably, toluene exposure led to reductions in mRNA markers for oxidative stress in aged but not younger animals. Toluene also produced a reduction in cardiac endothelin-1 in aged rats. Higher doses of toluene led to tachycardia, hypothermia, and a transient elevation in MA. Aged rats were less sensitive to the tachycardic effects of toluene but showed a prolonged hypothermic response. Elevated brain levels of toluene in aged rats may be attributed to their suppressed cardiovascular and respiratory responses. The expression of several cardiac biochemical markers of toluene exposure in the aged may also reflect differential susceptibility to this toxicant.

Neurobehavioral effects of acute exposure to four solvents: meta-analyses.

Meta- and reanalyses of the available data for the neurobehavioral effects of acute inhalation exposure to toluene were reported by Benignus et al. The present study was designed to test the generality of the toluene results in as many other solvents as possible by further meta- and reanalyses. Sufficient data for meta-analyses were found for only four solvents; toluene, trichloroethylene, perchloroethylene, and 1,1,1-trichloroethane. The results for these solvents showed that rats were less affected by each of the solvents when they were tested in highly motivating situations, for example, rewarded for rapid or correct responding or escape from electrical shock, compared with less motivating circumstances. The four solvents did not differ significantly in potency on any outcome measure when dose was expressed as molar brain concentration. When tested in tasks with low-motivational contingencies, the dose-effect curves of humans (reaction times) and rats (electrophysiological responses to visual stimuli) were not significantly different. However, on an exploratory follow-up analysis, humans were less sensitive than rats. No human data were found to test whether species differed under strong motivation. Dose-equivalence curves were derived for extrapolating to human effects from rat data.

Acute perchloroethylene exposure alters rat visual-evoked potentials in relation to brain concentrations.

These experiments sought to establish a dose-effect relationship between the concentration of perchloroethylene (PCE) in brain tissue and concurrent changes in visual function. A physiologically based pharmacokinetic (PBPK) model was implemented to predict concentrations of PCE in the brains of adult Long-Evans rats following inhalation exposure. The model was evaluated for performance against tissue concentrations from exposed rats (n = 40) and data from the published scientific literature. Visual function was assessed using steady-state pattern-elicited visual-evoked potentials (VEPs) recorded from rats during exposure to air or PCE in two experiments (total n = 84) with concentrations of PCE ranging from 250 to 4000 ppm. VEP waveforms were submitted to a spectral analysis in which the major response component, F2, occurring at twice the visual stimulation rate, was reduced in amplitude by PCE exposure. The F2 amplitudes were transformed to an effect-magnitude scale ranging from 0 (no effect) to 1 (maximum possible effect), and a logistical function was fit to the transformed values as a function of estimated concurrent brain PCE concentrations. The resultant function described a dose-response relationship between brain PCE concentration and changes in visual function with an ED(10) value of approximately 0.684 mg/l and an ED(50) value of approximately 46.5 mg/l. The results confirmed that visual function was disrupted by acute exposure to PCE, and the PBPK model and logistic model together could be used to make quantitative estimates of the magnitude of deficit to be expected for any given inhalation exposure scenario.

How can biologically-based modeling of arsenic kinetics and dynamics inform the risk assessment process? - A workshop review.

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic metabolizing enzymes can lead to differences in target tissue dosimetry for key metabolites causative in toxic and carcinogenic response. This type of variation can be quantitatively incorporated into pharmacokinetic (PK) models and used together with population-based modeling approaches to evaluate the impact of genetic variation in methylation capacity on dose of key metabolites to target tissue. The PK model is an essential bridge to the pharmacodynamic (PD) models. A particular benefit of PD modeling for arsenic is that alternative models can be constructed for multiple proposed modes of action for arsenicals. Genomics data will prove useful for identifying the key pathways involved in particular responses and aid in determining other types of data needed for quantitative modeling. These models, when linked with PK models, can be used to better understand and explain dose- and time-response behaviors. This in turn assists in prioritizing modes of action with respect to their risk assessment relevance and future research. This type of integrated modeling approach can form the basis for a highly informative mode-of-action directed risk assessment for inorganic arsenic (iAs). This paper will address both practical and theoretical aspects of integrating PK and PD data in a modeling framework, including practical barriers to its application.

A physiologically based pharmacokinetic model for intravenous and ingested dimethylarsinic acid in mice.

A physiologically based pharmacokinetic (PBPK) model for the organoarsenical dimethylarsinic acid (DMA(V)) was developed in mice. The model was calibrated using tissue time course data from multiple tissues in mice administered DMA(V) intravenously. The final model structure was based on diffusion limitation kinetics. In general, PBPK models use the assumption of blood flow-limited transport into tissues. This assumption has historically worked for small lipophilic organic solvents. However, the conditions under which flow-limited kinetics occurs and how to distinguish when flow-limited versus diffusion-limited transport is more appropriate, have been rarely evaluated. One important goal of this modeling effort was to systematically evaluate descriptions of flow-limited compared with diffusion-limited tissue distribution for DMA(V), using the relatively extensive pharmacokinetic data available in mice. The diffusion-limited model consistently provided an improved fit over flow-limited simulations when compared with tissue time course iv experimental data. After model calibration, an independent data set obtained by oral gavage of DMA(V), was used to further test model structure. Sensitivity analysis of the two PBPK model structures showed the importance of early time course data collection, and the impact of diffusion for kidney time course data description. In summary, this modeling effort suggests the importance of availability of organ specific time course data sets necessary for the discernment of PBPK modeling structure, motivated by knowledge of biology, and providing necessary feedback between experimental design and biological modelers.

Modeling the toxicokinetics of inhaled toluene in rats: influence of physical activity and feeding status.

Toluene is found in petroleum-based fuels and used as a solvent in consumer products and industrial applications. The critical effects following inhalation exposure involve the brain and nervous system in both humans and experimental animals, whether exposure duration is acute or chronic. The goals of this physiologically based pharmacokinetic (PBPK) model development effort were twofold: (1) to evaluate and explain the influence of feeding status and activity level on toluene pharmacokinetics utilizing our own data from toluene-exposed Long Evans (LE) rats, and (2) to evaluate the ability of the model to simulate data from the published literature and explain differing toluene kinetics. Compartments in the model were lung, slowly and rapidly perfused tissue groups, fat, liver, gut, and brain; tissue transport was blood-flow limited and metabolism occurred in the liver. Chemical-specific parameters and initial organ volumes and blood flow rates were obtained from the literature. Sensitivity analysis revealed that the single most influential parameter for our experimental conditions was alveolar ventilation; other moderately influential parameters (depending upon concentration) included cardiac output, rate of metabolism, and blood flow to fat. Based on both literature review and sensitivity analysis, other parameters (e.g., partition coefficients and metabolic rate parameters) were either well defined (multiple consistent experimental results with low variability) or relatively noninfluential (e.g. organ volumes). Rats that were weight-maintained compared to free-fed rats in our studies could be modeled with a single set of parameters because feeding status did not have a significant impact on toluene pharmacokinetics. Heart rate (HR) measurements in rats performing a lever-pressing task indicated that the HR increased in proportion to task intensity. For rats acclimated to eating in the lab during the day, both sedentary rats and rats performing the lever-pressing task required different alveolar ventilation rates to successfully predict the data. Model evaluation using data from diverse sources together with statistical evaluation of the resulting fits revealed that the model appropriately predicted blood and brain toluene concentrations with some minor exceptions. These results (1) emphasize the importance of experimental conditions and physiological status in explaining differing kinetic data, and (2) demonstrate the need to consider simulation conditions when estimating internal dose metrics for toxicity studies in which kinetic data were not collected.

Tissue dosimetry, metabolism and excretion of pentavalent and trivalent dimethylated arsenic in mice after oral administration.

Dimethylarsinic acid (DMA(V)) is a rat bladder carcinogen and the major urinary metabolite of administered inorganic arsenic in most mammals. This study examined the disposition of pentavalent and trivalent dimethylated arsenic in mice after acute oral administration. Adult female mice were administered [(14)C]-DMA(V) (0.6 or 60 mg As/kg) and sacrificed serially over 24 h. Tissues and excreta were collected for analysis of radioactivity. Other mice were administered unlabeled DMA(V) (0.6 or 60 mg As/kg) or dimethylarsinous acid (DMA(III)) (0.6 mg As/kg) and sacrificed at 2 or 24 h. Tissues (2 h) and urine (24 h) were collected and analyzed for arsenicals. Absorption, distribution and excretion of [(14)C]-DMA(V) were rapid, as radioactivity was detected in tissues and urine at 0.25 h. For low dose DMA(V) mice, there was a greater fractional absorption of DMA(V) and significantly greater tissue concentrations of radioactivity at several time points. Radioactivity distributed greatest to the liver (1-2% of dose) and declined to less than 0.05% in all tissues examined at 24 h. Urinary excretion of radioactivity was significantly greater in the 0.6 mg As/kg DMA(V) group. Conversely, fecal excretion of radioactivity was significantly greater in the high dose group. Urinary metabolites of DMA(V) included DMA(III), trimethylarsine oxide (TMAO), dimethylthioarsinic acid and trimethylarsine sulfide. Urinary metabolites of DMA(III) included TMAO, dimethylthioarsinic acid and trimethylarsine sulfide. DMA(V) was also excreted by DMA(III)-treated mice, showing its sensitivity to oxidation. TMAO was detected in tissues of the high dose DMA(V) group. The low acute toxicity of DMA(V) in the mouse appears to be due in part to its minimal retention and rapid elimination.

Development of a human physiologically based pharmacokinetic (PBPK) model for inorganic arsenic and its mono- and di-methylated metabolites.

A physiologically-based pharmacokinetic (PBPK) model was developed to estimate levels of arsenic and its metabolites in human tissues and urine after oral exposure to arsenate (As(V)), arsenite (As(III)) or organoarsenical pesticides. The model consists of interconnected individual PBPK models for inorganic arsenic (As(V) and As(III)), monomethylarsenic acid (MMA(V)), and, dimethylarsenic acid (DMA(V)). Reduction of MMA(V) and DMA(V) to their respective trivalent forms also occurs in the lung, liver, and kidney including excretion in urine. Each submodel was constructed using flow limited compartments describing the mass balance of the chemicals in GI tract (lumen and tissue), lung, liver, kidney, muscle, skin, heart, and brain. The choice of tissues was based on physiochemical properties of the arsenicals (solubility), exposure routes, target tissues, and sites for metabolism. Metabolism of inorganic arsenic in liver was described as a series of reduction and oxidative methylation steps incorporating the inhibitory influence of metabolites on methylation. The inhibitory effects of As(III) on the methylation of MMA(III) to DMA, and MMA(III) on the methylation of As(III) to MMA were modeled as noncompetitive. To avoid the uncertainty inherent in estimation of many parameters from limited human data, a priori independent parameter estimates were derived using data from diverse experimental systems with priority given to data derived using human cells and tissues. This allowed the limited data for human excretion of arsenicals in urine to be used to estimate only parameters that were most sensitive to this type of data. Recently published urinary excretion data, not previously used in model development, are also used to evaluate model predictions.