Genetic polymorphisms in assessing interindividual variability in delivered dose

The risk associated with organophosphorus nerve agents: from their discovery to their unavoidable threat, current medical countermeasures and perspectives

The first organophosphorus nerve agent was discovered accidently during the development of pesticides, shortly after the first use of chemical weapons (chlorine, phosgene) on the battlefield during World War I. Despite the Chemical Weapons Convention banning these substances, they have still been employed in wars, terrorist attacks or political assassinations. Characterised by their high lethality, they target the nervous system by inhibiting the acetylcholinesterase (AChE) enzyme, preventing neurotransmission, which, if not treated rapidly, inevitably leads to serious injury or the death of the person intoxicated. The limited efficacy of current antidotes, known as AChE reactivators, pushes research towards new treatments. Numerous paths have been explored, from modifying the original pyridinium oximes to developing hybrid reactivators seeking a better affinity for the inhibited AChE. Another crucial approach resides in molecules more prone to cross the blood-brain barrier: uncharged compounds, bio-conjugated reactivators or innovative formulations. Our aim is to raise awareness on the threat and toxicity of organophosphorus nerve agents and to present the main synthetic efforts deployed since the first AChE reactivator, to tackle the task of efficiently treating victims of these chemical warfare agents.

PBPK modeling of impact of nonalcoholic fatty liver disease on toxicokinetics of perchloroethylene in mice

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD), a major cause of chronic liver disease in the Western countries with increasing prevalence worldwide, may substantially affect chemical toxicokinetics and thereby modulate chemical toxicity.

OBJECTIVES

This study aims to use physiologically-based pharmacokinetic (PBPK) modeling to characterize the impact of NAFLD on toxicokinetics of perchloroethylene (perc).

METHODS

Quantitative measures of physiological and biochemical changes associated with the presence of NAFLD induced by high-fat or methionine/choline-deficient diets in C57B1/6 J mice are incorporated into a previously developed PBPK model for perc and its oxidative and conjugative metabolites. Impacts on liver fat and volume, as well as blood:air and liver:air partition coefficients, are incorporated into the model. Hierarchical Bayesian population analysis using Markov chain Monte Carlo simulation is conducted to characterize uncertainty, as well as disease-induced variability in toxicokinetics.

RESULTS

NAFLD has a major effect on toxicokinetics of perc, with greater oxidative and lower conjugative metabolism as compared to healthy mice. The NAFLD-updated PBPK model accurately predicts in vivo metabolism of perc through oxidative and conjugative pathways in all tissues across disease states and strains, but underestimated parent compound concentrations in blood and liver of NAFLD mice.

CONCLUSIONS

We demonstrate the application of PBPK modeling to predict the effects of pre-existing disease conditions as a variability factor in perc metabolism. These results suggest that non-genetic factors such as diet and pre-existing disease can be as influential as genetic factors in altering toxicokinetics of perc, and thus are likely contribute substantially to population variation in its adverse effects.

Pharmacogenomic Effect of Cytochrome P450 2C9 Polymorphisms in Different Populations

Presently, warfarin sodium or coumadin is the therapeutic drug of choice for maintenance anticoagualtion therapy. One of several factors underlying the variability in warfarin dose response in the patients receiving this oral anticoagulant is a genetic predisposition, especially the CYP2C9 polymorphisms. The pharmacogenomic effect of CYP2C9 polymorphisms is assessed in different racial populations. A retrospective review was performed with an electronic search engine on this topic to get the data for further meta-analysis. A significant correlation between population ethnicity and gene frequencies was detected in this study. A significant low frequency of CYP2C9 variants among the Asian can be demonstrated. The clinical correlation between CYP2C9 polymorphism and warfarin metabolism was also assessed. Four available case-control reports were selected for this meta-analysis. CYP2C9 variants are strongly associated with low-dose warfarin requirement. In summary, the CYP2C9 variants strongly affect the warfarin dose requirement. This phenomenon is ethnically dependent. Due to the high variant frequency among whites in the West, the investigation for CYP2C9 might be useful for this population, not the Asians, whose variant frequency is very low.

Human health effects of dichloromethane: key findings and scientific issues

BACKGROUND

The U.S. EPA's Integrated Risk Information System (IRIS) completed an updated toxicological review of dichloromethane in November 2011.

OBJECTIVES

In this commentary we summarize key results and issues of this review, including exposure sources, identification of potential health effects, and updated physiologically based pharmacokinetic (PBPK) modeling.

METHODS

We performed a comprehensive review of primary research studies and evaluation of PBPK models.

DISCUSSION

Hepatotoxicity was observed in oral and inhalation exposure studies in several studies in animals; neurological effects were also identified as a potential area of concern. Dichloromethane was classified as likely to be carcinogenic in humans based primarily on evidence of carcinogenicity at two sites (liver and lung) in male and female B6C3F1 mice (inhalation exposure) and at one site (liver) in male B6C3F1 mice (drinking-water exposure). Recent epidemiologic studies of dichloromethane (seven studies of hematopoietic cancers published since 2000) provide additional data raising concerns about associations with non-Hodgkin lymphoma and multiple myeloma. Although there are gaps in the database for dichloromethane genotoxicity (i.e., DNA adduct formation and gene mutations in target tissues in vivo), the positive DNA damage assays correlated with tissue and/or species availability of functional glutathione S-transferase (GST) metabolic activity, the key activation pathway for dichloromethane-induced cancer. Innovations in the IRIS assessment include estimation of cancer risk specifically for a presumed sensitive genotype (GST-theta-1+/+), and PBPK modeling accounting for human physiological distributions based on the expected distribution for all individuals 6 months to 80 years of age.

CONCLUSION

The 2011 IRIS assessment of dichloromethane provides insights into the toxicity of a commonly used solvent.

Considerations for Using Genetic and Epigenetic Information in Occupational Health Risk Assessment and Standard Setting

Risk assessment forms the basis for both occupational health decision-making and the development of occupational exposure limits (OELs). Although genetic and epigenetic data have not been widely used in risk assessment and ultimately, standard setting, it is possible to envision such uses. A growing body of literature demonstrates that genetic and epigenetic factors condition biological responses to occupational and environmental hazards or serve as targets of them. This presentation addresses the considerations for using genetic and epigenetic information in risk assessments, provides guidance on using this information within the classic risk assessment paradigm, and describes a framework to organize thinking about such uses. The framework is a 4 × 4 matrix involving the risk assessment functions (hazard identification, dose-response modeling, exposure assessment, and risk characterization) on one axis and inherited and acquired genetic and epigenetic data on the other axis. The cells in the matrix identify how genetic and epigenetic data can be used for each risk assessment function. Generally, genetic and epigenetic data might be used as endpoints in hazard identification, as indicators of exposure, as effect modifiers in exposure assessment and dose-response modeling, as descriptors of mode of action, and to characterize toxicity pathways. Vast amounts of genetic and epigenetic data may be generated by high-throughput technologies. These data can be useful for assessing variability and reducing uncertainty in extrapolations, and they may serve as the foundation upon which identification of biological perturbations would lead to a new paradigm of toxicity pathway-based risk assessments.

Assessing human variability in kinetics for exposures to multiple environmental chemicals: a physiologically based pharmacokinetic modeling case study with dichloromethane, benzene, toluene, ethylbenzene, and m-xylene

The objective of this study was to compare the magnitude of interindividual variability in internal dose for inhalation exposure to single versus multiple chemicals. Physiologically based pharmacokinetic models for adults (AD), neonates (NEO), toddlers (TODD), and pregnant women (PW) were used to simulate inhalation exposure to "low" (RfC-like) or "high" (AEGL-like) air concentrations of benzene (Bz) or dichloromethane (DCM), along with various levels of toluene alone or toluene with ethylbenzene and xylene. Monte Carlo simulations were performed and distributions of relevant internal dose metrics of either Bz or DCM were computed. Area under the blood concentration of parent compound versus time curve (AUC)-based variability in AD, TODD, and PW rose for Bz when concomitant "low" exposure to mixtures of increasing complexities occurred (coefficient of variation (CV) = 16-24%, vs. 12-15% for Bz alone), but remained unchanged considering DCM. Conversely, AUC-based CV in NEO fell (15 to 5% for Bz; 12 to 6% for DCM). Comparable trends were observed considering production of metabolites (AMET), except for NEO's CYP2E1-mediated metabolites of Bz, where an increased CV was observed (20 to 71%). For "high" exposure scenarios, Cmax-based variability of Bz and DCM remained unchanged in AD and PW, but decreased in NEO (CV= 11-16% to 2-6%) and TODD (CV= 12-13% to 7-9%). Conversely, AMET-based variability for both substrates rose in every subpopulation. This study analyzed for the first time the impact of multiple exposures on interindividual variability in toxicokinetics. Evidence indicates that this impact depends upon chemical concentrations and biochemical properties, as well as the subpopulation and internal dose metrics considered.

Considerations for Using Genetic and Epigenetic Information in Occupational Health Risk Assessment and Standard Setting

Risk assessment forms the basis for both occupational health decision-making and the development of occupational exposure limits (OELs). Although genetic and epigenetic data have not been widely used in risk assessment and ultimately, standard setting, it is possible to envision such uses. A growing body of literature demonstrates that genetic and epigenetic factors condition biological responses to occupational and environmental hazards or serve as targets of them. This presentation addresses the considerations for using genetic and epigenetic information in risk assessments, provides guidance on using this information within the classic risk assessment paradigm, and describes a framework to organize thinking about such uses. The framework is a 4 × 4 matrix involving the risk assessment functions (hazard identification, dose-response modeling, exposure assessment, and risk characterization) on one axis and inherited and acquired genetic and epigenetic data on the other axis. The cells in the matrix identify how genetic and epigenetic data can be used for each risk assessment function. Generally, genetic and epigenetic data might be used as endpoints in hazard identification, as indicators of exposure, as effect modifiers in exposure assessment and dose-response modeling, as descriptors of mode of action, and to characterize toxicity pathways. Vast amounts of genetic and epigenetic data may be generated by high-throughput technologies. These data can be useful for assessing variability and reducing uncertainty in extrapolations, and they may serve as the foundation upon which identification of biological perturbations would lead to a new paradigm of toxicity pathway-based risk assessments.

Dispelling urban myths about default uncertainty factors in chemical risk assessment--sufficient protection against mixture effects?

Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an incentive to generate better data and recommend adopting a pragmatic, but scientifically better founded approach to mixture risk assessment.

Genetic Polymorphisms of Cytochrome P450 Enzymes and the Effect on Interindividual, Pharmacokinetic Variability in Extensive Metabolizers

Genetic polymorphisms of cytochrome P450 (CYP) enzymes are one of the factors that contribute to the pharmacokinetic (PK) variability of drugs. PK variability is observed in the bimodal distribution between extensive metabolizers (EMs) and poor metabolizers (PMs). PK variability may also exist between individuals genotyped as homozygous EMs and heterozygous EMs. This may carry implications for drug dosing and drug response (e.g., risk of therapeutic failure or drug toxicity). Studies have reported significant PK differences between homozygous and heterozygous EMs. Some literature suggests that this distinction may be of clinical relevance. Due to study design limitations and data that are either sparse or conflicting, generalizations regarding the potential impact of the CYP genotype, within EMs, are difficult. Optimally designed clinical trials are needed. This review evaluates the potential impact of CYP genetic polymorphisms on interindividual PK variability of drugs within an EM population.

Oxidative stress induced in the workers of natural gas refineries, no role for GSTM1 and GSTT1 polymorphisms

Oxidative stress has an important role in the pathophysiology of many occupational diseases. In this controlled exposure study, the intensity of oxidative stress biomarkers was assessed in the workers of natural sweet and sour gas refineries (SwGR and SoGR, respectively) and compared with controls. In addition, the role of gluthatione S-transferase M1 (GSTM1)-null and GSTT1-null polymorphisms on the intensity of oxidative stress and liver function tests (LFTs) was investigated. Blood samples were taken and measured for lipid peroxidation (LPO) level, total antioxidant capacity (TAC) and total thiol molecules (TTMs). GSTM1- and GSTT1-null genotypes were determined using polymerase chain reaction. LPO was significantly ( p < 0.05) higher in the workers of SoGR. TAC was significantly lower in SwGR subjects ( p < 0.001). TTMs were significantly lower in SoGR and SwGR subjects. Among LFTs, activities of aspartate aminotransferase and alanine aminotransferase but not alkaline phosphatase were elevated significantly ( p < 0.001) in SoGR subjects. Multivariate linear regression revealed no association between studied polymorphisms, oxidative stress biomarkers, and LFTs. These results indicate that working in the SoGR and SwGR can lead to oxidative stress and abnormal LFTs. Continuous monitoring of natural gas workers for probable ongoing problems is therefore suggested.

Modeling the Human Kinetic Adjustment Factor for Inhaled Volatile Organic Chemicals: Whole Population Approach versus Distinct Subpopulation Approach

The objective of this study was to evaluate the impact of whole- and sub-population-related variabilities on the determination of the human kinetic adjustment factor (HKAF) used in risk assessment of inhaled volatile organic chemicals (VOCs). Monte Carlo simulations were applied to a steady-state algorithm to generate population distributions for blood concentrations (CAss) and rates of metabolism (RAMs) for inhalation exposures to benzene (BZ) and 1,4-dioxane (1,4-D). The simulated population consisted of various proportions of adults, elderly, children, neonates and pregnant women as per the Canadian demography. Subgroup-specific input parameters were obtained from the literature and P3M software. Under the “whole population” approach, the HKAF was computed as the ratio of the entire population's upper percentile value (99th, 95th) of dose metrics to the median value in either the entire population or the adult population. Under the “distinct subpopulation” approach, the upper percentile values in each subpopulation were considered, and the greatest resulting HKAF was retained. CAss-based HKAFs that considered the Canadian demography varied between 1.2 (BZ) and 2.8 (1,4-D). The “distinct subpopulation” CAss-based HKAF varied between 1.6 (BZ) and 8.5 (1,4-D). RAM-based HKAFs always remained below 1.6. Overall, this study evaluated for the first time the impact of underlying assumptions with respect to the interindividual variability considered (whole population or each subpopulation taken separately) when determining the HKAF.

Risk factors of vitamin K antagonist overcoagulation

OBJECTIVES

The aims of this prospective study were to identify, in vitamin K antagonist (VKA)-treated patients, factors associated with INR values: (i) greater than 6.0. and (ii) ranging from 4.0 to 6.0 complicated with bleeding. We also assessed VKA-related morbidity in these patients.

METHODS

During a 6-month period, 3090 consecutive patients were referred to our Department of Internal Medicine, including 412 VKA-treated patients. At admission, the medical records of VKA-treated patients were reviewed for type, duration and indication of VKA therapy, previous medical history of VKA-related hemorrhage, comorbidities and concomitant medications.

RESULTS

Forty of the 412 VKA-treated patients (9.7%) exhibited oral anticoagulant related overcoagulation. VKA overcoagulation was associated with high morbidity, leading to major bleeding in 27.5% of cases; moreover, 12.5% of these patients died, death being mainly due to major bleeding. Under multivariate analysis, significant factors for VKA-related overcoagulation were as follows: previous medical history of VKA therapy-related hemorrhage (P=0.00001) and INR levels over therapeutic range (P=0.0006), chronic liver disease (P=0.03), therapy with amiodarone (P=0.009); in contrast, statin therapy was found to be a protective factor of VKA overcoagulation (P=0.008).

CONCLUSIONS

The knowledge of predictive factors of VKA-related overcoagulation seems of utmost importance to improve patients' management. Our study underlines the fact that the potential of drug interaction should be taken into account when choosing amiodarone for patients receiving VKAs. Interestingly, long-term (>6 month) statin therapy may be a protective factor of VKA overcoagulation. Our findings, therefore, suggest that there may be no need to switch long-term users of VKA and statin to a safer alternative therapy.

Physiologically based pharmacokinetic model use in risk assessment--Why being published is not enough

A panel of experts in physiologically based pharmacokinetic (PBPK) modeling and relevant quantitative methods was convened to describe and discuss model evaluation criteria, issues, and choices that arise in model application and computational tools for improving model quality for use in human health risk assessments (HHRAs). Although publication of a PBPK model in a peer-reviewed journal is a mark of good science, subsequent evaluation of published models and the supporting computer code is necessary for their consideration for use in HHRAs. Standardized model evaluation criteria and a thorough and efficient review process can reduce the number of review and revision iterations and hence the time needed to prepare a model for application. Efficient and consistent review also allows for rapid identification of needed model modifications to address HHRA-specific issues. This manuscript reports on the workshop where a process and criteria that were created for PBPK model review were discussed along with other issues related to model review and application in HHRA. Other issues include (1) model code availability, portability, and validity; (2) probabilistic (e.g., population-based) PBPK models and critical choices in parameter values to fully characterize population variability; and (3) approaches to integrating PBPK model outputs with other HHRA tools, including benchmark dose modeling. Two specific case study examples are provided to illustrate challenges that were encountered during the review and application process. By considering the frequent challenges encountered in the review and application of PBPK models during the model development phase, scientists may be better able to prepare their models for use in HHRAs.

Recent progress in antithrombotic therapy for atrial fibrillation

Atrial fibrillation (AF) is becoming a major health care burden as elderly populations increase. The increased risk of stroke and thromboembolisms in patients with AF is well documented and anti-coagulation with adjusted-dose warfarin is highly effective in reducing stroke risk, being superior to antiplatelet agents. Despite recognition of the epidemiological problem and the sound evidence base for thromboprophylaxis, as well as major guidelines recommending treatment, anticoagulation use is still suboptimal, given the dis-utility and limitations associated with warfarin. Recent developments in thromboprophylaxis for AF include efforts for better risk stratification for predictions of thromboembolic risk. Constant efforts are underway to develop newer, less cumbersome, alternatives to warfarin with similar (or better) efficacy. This review article provides an overview of the recent progress made, the potential challenges involved and the future of these therapeutic approaches.

Fibrate/Statin initiation in warfarin users and gastrointestinal bleeding risk

PURPOSE

To evaluate whether initiation of a fibrate or statin increases the risk of hospitalization for gastrointestinal bleeding in warfarin users.

METHODS

We used Medicaid claims data (1999-2003) to perform an observational case-control study nested within person-time exposed to warfarin in those > or =18 years (n=353,489). Gastrointestinal bleeding cases were matched to 50 controls based on index date and state.

RESULTS

Chronic warfarin users had an increased odds ratio of gastrointestinal bleeding upon initiation of gemfibrozil (1.88; 95% confidence interval [CI], 1.00-3.54] for the first prescription; 1.75; 95% CI, 0.77-3.95 for the second prescription); simvastatin (1.46; 95% CI, 1.03-2.07 for the first prescription; 1.60; 95% CI, 1.07-2.39 for the second prescription); or atorvastatin (1.39; 95% CI, 1.07-1.81 for the first prescription; 1.05; 95% CI, 0.73-1.52 for the second prescription). In contrast, no increased risk was found with pravastatin initiation (0.75; 95% CI, 0.39-1.46 for the first prescription; 0.90; 95% CI, 0.43-1.91 for the second prescription).

CONCLUSIONS

Initiation of a fibrate or statin that inhibits CYP3A4 enzymes, including atorvastatin, was associated with an increased risk of hospitalization for gastrointestinal bleeding. Initiation of pravastatin, which is mainly excreted unchanged, was not associated with an increased risk.

U-shaped dose-response curves: implications for risk characterization of essential elements and other chemicals

The existing risk assessment and management model is a general framework that can incorporate the assessment of numerous types of chemicals, such as essential elements. The general nature of the framework, however, often precludes precise statements of risk and only gives assurances of accuracy by way of a judicious use of conservative assumptions. A mode-of-action framework may provide approaches that are both more precise and accurate, and that may be used for characterizing both risk and benefit of essential elements, but such a framework needs to address the differing severity of adverse effects. Current dose-response data gaps often hinder the evaluation of the risk and benefit of several essential elements; however, new modeling methods, such as categorical regression, need to be further explored. Finally, the essentiality of certain elements provides evidence that two thresholds likely exist in an individual for adverse effect, one at low doses for undernutrition, and another at high doses for toxicity, for the element of concern. This evidence may aid in the estimation of such thresholds in populations.

Reconstructing population exposures to environmental chemicals from biomarkers: challenges and opportunities

A conceptual/computational framework for exposure reconstruction from biomarker data combined with auxiliary exposure-related data is presented, evaluated with example applications, and examined in the context of future needs and opportunities. This framework employs physiologically based toxicokinetic (PBTK) modeling in conjunction with numerical "inversion" techniques. To quantify the value of different types of exposure data "accompanying" biomarker data, a study was conducted focusing on reconstructing exposures to chlorpyrifos, from measurements of its metabolite levels in urine. The study employed biomarker data as well as supporting exposure-related information from the National Human Exposure Assessment Survey (NHEXAS), Maryland, while the MENTOR-3P system (Modeling ENvironment for TOtal Risk with Physiologically based Pharmacokinetic modeling for Populations) was used for PBTK modeling. Recently proposed, simple numerical reconstruction methods were applied in this study, in conjunction with PBTK models. Two types of reconstructions were studied using (a) just the available biomarker and supporting exposure data and (b) synthetic data developed via augmenting available observations. Reconstruction using only available data resulted in a wide range of variation in estimated exposures. Reconstruction using synthetic data facilitated evaluation of numerical inversion methods and characterization of the value of additional information, such as study-specific data that can be collected in conjunction with the biomarker data. Although the NHEXAS data set provides a significant amount of supporting exposure-related information, especially when compared to national studies such as the National Health and Nutrition Examination Survey (NHANES), this information is still not adequate for detailed reconstruction of exposures under several conditions, as demonstrated here. The analysis presented here provides a starting point for introducing improved designs for future biomonitoring studies, from the perspective of exposure reconstruction; identifies specific limitations in existing exposure reconstruction methods that can be applied to population biomarker data; and suggests potential approaches for addressing exposure reconstruction from such data.

Ethnic differences in warfarin maintenance dose requirement and its relationship with genetics

Warfarin is a highly efficacious drug, but management of warfarin is difficult, in part because of the large interindividual maintenance dose differences. Warfarin dose requirements differ by race and it has been suggested that some of these differences are owing to genetic diversity. For example, persons of African descent have lower allele frequencies of the CYP2C9*2 and *3 and VKORC1 1173T allele, which have been associated with lower warfarin dose requirements in Caucasians. Since there is currently debate whether genetic information should be used in clinical practice to determine the starting dose for a warfarin initiator, it is of great importance to determine whether everyone will benefit from this knowledge.

Genetic polymorphism in paraoxonase 1 (PON1): Population distribution of PON1 activity

Paraoxonase-1 (PON1) is a serum esterase that hydrolyzes the activated oxon form of several organophosphates. The central role of PON1 in detoxification of organophosphate (OP) pesticides was demonstrated in knockout mouse studies, suggesting that human variability in PON1 needs to be considered in health risk assessments involving exposure to these pesticides. The current analysis focused on two genetic loci in which polymorphisms demonstrated to affect PON1 activity. Detailed kinetic studies and population studies found that the *192Q (wild type) allele is more active toward some substrates (such as sarin, soman, and diazoxon) and less active toward others (such as paraoxon or chlorpyrifos) relative to the variant *192R allele. Another allele that affects activity is *55M; PON1 enzyme quantity, rather than specific activity or substrate preference, is altered. The *192R variant occurs commonly with a frequency of 25-64% across the populations analyzed. The *55M allele is less common, occurring in 5-40% of individuals depending upon the ethnic group studied. These activity and allele frequency data were incorporated into Monte Carlo simulations in which the frequency of both variant alleles was simultaneously modeled in Caucasian, African American, and Japanese populations. The resulting Monte Carlo activity distributions were bimodal for the substrate paraoxon with approximately fourfold differences between low- and high-activity modal medians. Differences in activity between total population median and 1st percentile were five- to sixfold. When sarin metabolic variability was simulated, the population distributions were unimodal. However, there was an even greater degree of interindividual variability (median to 1st percentile difference >20-fold). These results show that the combined effects of two PON1 allelic variants yielded a population distribution that is associated with a considerable degree of interindividual variability in enzyme activity. This indicates that assessments involving PON1 substrates need to evaluate polymorphism-related variability in enzyme activity to display the distribution of internal doses and adverse responses. This may best be achieved via physiologically based pharmacokinetic (PBPK) models that input PON1 activity distributions, such as those generated in this analysis, to simulate the range of oxon internal doses possible across the population.

Genetic Polymorphism in Glutathione Transferases (GST): Population distribution of GSTM1, T1, and P1 conjugating activity

Glutathione transferases (GST) catalyze the conjugation of glutathione (GSH) with electrophiles, many of which may otherwise interact with protein or DNA. In select cases such as halogenated solvents, GST-mediated conjugation may lead to a more toxic or mutagenic metabolite. Polymorphisms that exert substantial effects on GST function were noted in human populations for several isozymes. This analysis focuses on three well-characterized isozymes, GSTM1, T1, and P1, in which polymorphisms were extensively studied with respect to DNA adducts and cancer in molecular epidemiologic studies. The current review and analysis focused upon how polymorphisms in these GST contributed to population variability in GST function. The first step in developing this review was to characterize the influence of genotype on phenotype (enzyme function) and the frequency of the polymorphisms across major population groups for all three GST. This information was then incorporated into Monte Carlo simulations to develop population distributions of enzyme function. These simulations were run separately for GSTM1, T1, and P1, and also for the combination of these isozymes, to assess the possibility of overlapping substrate specificity. Monte Carlo simulations indicated large interindividual variability for GSTM1 and T1 due to the presence of the null (zero activity) genotype, which is common in all populations studied. Even for GSTM1 or T1 non-null individuals, there was considerable interindividual variability with a bimodal distribution of enzyme activity evident. GSTP1 polymorphisms are associated with somewhat less variability due to the absence of null genotypes. However, in all cases simulated, the estimated variability is sufficiently large to warrant consideration of GST function distributions in assessments involving GST-mediated activation or detoxification of xenobiotics. Ideally, such assessments would involve physiologically based toxicokinetic (PBTK) modeling to assess population variability in internal dose.

The influence of genetic polymorphisms on population variability in six xenobiotic-metabolizing enzymes

This review provides variability statistics for polymorphic enzymes that are involved in the metabolism of xenobiotics. Six enzymes were evaluated: cytochrome P-450 (CYP) 2D6, CYP2E1, aldehyde dehydrogenase-2 (ALDH2), paraoxonase (PON1), glutathione transferases (GSTM1, GSTT1, and GSTP1), and N-acetyltransferases (NAT1 and NAT2). The polymorphisms were characterized with respect to (1) number and type of variants, (2) effects of polymorphisms on enzyme function, and (3) frequency of genotypes within specified human populations. This information was incorporated into Monte Carlo simulations to predict the population distribution and describe interindividual variability in enzyme activity. The results were assessed in terms of (1) role of these enzymes in toxicant activation and clearance, (2) molecular epidemiology evidence of health risk, and (3) comparing enzyme variability to that commonly assumed for pharmacokinetics. Overall, the Monte Carlo simulations indicated a large degree of interindividual variability in enzyme function, in some cases characterized by multimodal distributions. This study illustrates that polymorphic metabolizing systems are potentially important sources of pharmacokinetic variability, but there are a number of other factors including blood flow to liver and compensating pathways for clearance that affect how a specific polymorphism will alter internal dose and toxicity. This is best evaluated with the aid of physiologically based pharmacokinetic (PBPK) modeling. The population distribution of enzyme activity presented in this series of articles serves as inputs to such PBPK modeling analyses.

Warfarin with fluoroquinolones, sulfonamides, or azole antifungals: interactions and the risk of hospitalization for gastrointestinal bleeding

The aim of this study was to determine whether a potential pharmacokinetic interaction between warfarin and orally administered anti-infectives increases the risk of hospitalization for gastrointestinal (GI) bleeding in warfarin users. We conducted a nested case-control and case-crossover study using US Medicaid data. Logistic regression was used to determine the association between GI bleeding and prior use of ciprofloxacin, levofloxacin, gatifloxacin, co-trimoxazole, or fluconazole vs. no exposure and also vs. use of cephalexin, which would not be expected to interact with warfarin. All of the anti-infectives examined were associated with elevated odds ratios (ORs) when compared to no exposure to these drugs. With cephalexin data as the reference, the ORs for co-trimoxazole (OR: 1.68 (95% confidence interval (CI): 1.21-2.33) in the prior 6-10 days) and fluconazole (OR: 2.09 (95% CI: 1.34-3.26) in the prior 11-15 days) were significantly elevated. Warfarin users who had received an anti-infective agent showed a substantially increased risk of GI bleeding. However, a drug-drug interaction with warfarin was evident only for co-trimoxazole and fluconazole.

Background, approaches and recent trends for setting health-based occupational exposure limits: a minireview

The setting of occupational exposure limits (OELs) are founded in occupational medicine and the predictive toxicological testing, resulting in exposure-response relationships. For compounds where a No-Observed-Adverse-Effect-Level (NOAEL) can be established, health-based OELs are set by dividing the NOAEL of the critical effect by an overall uncertainty factor. Possibly, the approach may also be used for carcinogens if the mechanism is epigenetic or the genetic effect is secondary to effect from reactions with proteins such as topoisomerase inhibitors, and mitotic and meiotic spindle poisons. Additionally, the NOAEL approach may also be used for compounds with weak genotoxic effect, playing no or only a minor role in the development of tumours. No health-based OEL can be set for direct-acting genotoxic compounds where the life-time risks may be estimated from the low-dose linear non-threshold extrapolation, allowing a politically based exposure level to be set. OELs are set by several agencies in the US and Europe, but also in-house in major chemical and pharmaceutical companies. The benchmark dose approach may in the future be used where it has advantage over the NOAEL approach. Also, more attention should be devoted to sensitive groups, toxicological mechanisms and interactions as most workplace exposures are mixtures.

Warfarin therapy: in need of improvement after all these years

BACKGROUND

Warfarin therapy has been used clinically for over 60 years, yet continues to be problematic because of its narrow therapeutic index and large inter-individual variability in patient response. As a result, warfarin is a leading cause of serious medication-related adverse events, and its efficacy is also suboptimal.

OBJECTIVE

To review factors that are responsible for variable response to warfarin, including clinical, environmental, and genetic factors, and to explore some possible approaches to improving warfarin therapy.

RESULTS

Recent efforts have focused on developing dosing algorithms that included genetic information to try to improve warfarin dosing. These dosing algorithms hold promise, but have not been fully validated or tested in rigorous clinical trials. Perhaps equally importantly, adherence to warfarin is a major problem that should be addressed with innovative and cost-effective interventions.

CONCLUSION

Additional research is needed to further test whether interventions can be used to improve warfarin dosing and outcomes.

Warfarin and cytochrome P450 2C9 genotype: possible ethnic variation in warfarin sensitivity

INTRODUCTION

Warfarin is a widely prescribed, efficacious oral anticoagulant. S-warfarin, the more active form, is metabolized by the cytochrome P450 (CYP)2C9 enzyme. The aim was to evaluate the influence of two CYP2C9 functional polymorphisms (*2 and *3) on warfarin dose in African-Americans, an unstudied population and Caucasians, and also to assess the effect of these polymorphisms on anticoagulation response after accounting for nongenetic factors and genetic factors that might also impact the dose-response relationship of warfarin.

PATIENTS AND METHODS

A prospective cohort of 362 patients with a target international normalized ratio of between 2.0 and 3.0 were genotyped. Warfarin sensitivity stratified by genotype was investigated using univariate and multivariate analyses.

RESULTS

The maintenance dose of warfarin was significantly related to genotype (p < 0.01) (variant carriers: 31.25 mg/week; wild-type: 37.5 mg/week), even after adjustment for possible confounding factors (p = 0.046). However, the effect of genotype was restricted to Caucasians, in whom variant carriers had a significantly lower maintenance dose compared with wild-type homozygotes (unadjusted: p < 0.01; adjusted: p = 0.02). There was a greater risk of over-anticoagulation among Caucasian variant carriers, although this was only observed prior to reaching maintenance dose. For African-American variant carriers, there was no difference in warfarin response based on CYP2C9 genotype.

DISCUSSION

CYP2C9 *2 and *3 variants provide predictive information in anticoagulation response. However, these variants may not be useful in African-Americans or as a marker of long-term over-anticoagulation once a stable dose is reached.

Evaluation of physiologically based pharmacokinetic models for use in risk assessment

Physiologically based pharmacokinetic (PBPK) models are sophisticated dosimetry models that offer great flexibility in modeling exposure scenarios for which there are limited data. This is particularly of relevance to assessing human exposure to environmental toxicants, which often requires a number of extrapolations across species, route, or dose levels. The continued development of PBPK models ensures that regulatory agencies will increasingly experience the need to evaluate available models for their application in risk assessment. To date, there are few published criteria or well-defined standards for evaluating these models. Herein, important considerations for evaluating such models are described. The evaluation of PBPK models intended for risk assessment applications should include a consideration of: model purpose, model structure, mathematical representation, parameter estimation, computer implementation, predictive capacity and statistical analyses. Model purpose and structure require qualitative checks on the biological plausibility of a model. Mathematical representation, parameter estimation, computer implementation involve an assessment of the coding of the model, as well as the selection and justification of the physical, physicochemical and biochemical parameters chosen to represent a biological organism. Finally, the predictive capacity and sensitivity, variability and uncertainty of the model are analysed so that the applicability of a model for risk assessment can be determined. Published in 2007 by John Wiley & Sons, Ltd.

Revised assessment of cancer risk to dichloromethane II. Application of probabilistic methods to cancer risk determinations

An updated PBPK model of methylene chloride (DCM, dichloromethane) carcinogenicity in mice was recently published using Bayesian statistical methods (Marino et al., 2006). In this work, this model was applied to humans, as recommended by Sweeney et al.(2004). Physiological parameters for input into the MCMC analysis were selected from multiple sources reflecting, in each case, the source that was considered to represent the most current scientific evidence for each parameter. Metabolic data for individual subjects from five human studies were combined into a single data set and population values derived using MCSim. These population values were used for calibration of the human model. The PBPK model using the calibrated metabolic parameters was used to perform a cancer risk assessment for DCM, using the same tumor incidence and exposure concentration data relied upon in the current IRIS entry. Unit risks, i.e., the risk of cancer from exposure to 1 microg/m3 over a lifetime, for DCM were estimated using the calibrated human model. The results indicate skewed distributions for liver and lung tumor risks, alone or in combination, with a mean unit risk (per microg/m3) of 1.05 x 10(-9), considering both liver and lung tumors. Adding the distribution of genetic polymorphisms for metabolism to the ultimate carcinogen, the unit risks range from 0 (which is expected given that approximately 20% of the US population is estimated to be nonconjugators) up to a unit risk of 2.70 x 10(-9) at the 95th percentile. The median, or 50th percentile, is 9.33 x 10(-10), which is approximately a factor of 500 lower than the current EPA unit risk of 4.7 x 10(-7) using a previous PBPK model. These values represent the best estimates to date for DCM cancer risk because all available human data sets were used, and a probabilistic methodology was followed.

Application of Physiologically Based Pharmacokinetic Modeling in Setting Acute Exposure Guideline Levels for Methylene Chloride

Acute exposure guideline levels (AEGLs) are derived to protect the human population from adverse health effects in case of single exposure due to an accidental release of chemicals into the atmosphere. AEGLs are set at three different levels of increasing toxicity for exposure durations ranging from 10 min to 8 h. In the AEGL setting for methylene chloride, specific additional topics had to be addressed. This included a change of relevant toxicity endpoint within the 10-min to 8-h exposure time range from central nervous system depression caused by the parent compound to formation of carboxyhemoglobin (COHb) via biotransformation to carbon monoxide. Additionally, the biotransformation of methylene chloride includes both a saturable step as well as genetic polymorphism of the glutathione transferase involved. Physiologically based pharmacokinetic modeling was considered to be the appropriate tool to address all these topics in an adequate way. Two available PBPK models were combined and extended with additional algorithms for the estimation of the maximum COHb levels. The model was validated and verified with data obtained from volunteer studies. It was concluded that all the mentioned topics could be adequately accounted for by the PBPK model. The AEGL values as calculated with the model were substantiated by experimental data with volunteers and are concluded to be practically applicable.

Workshop Overview: Reassessment of the Cancer Risk of Dichloromethane in Humans

The U.S. Environmental Protection Agency (U.S. EPA) classifies dichloromethane (DCM) as a "probable human carcinogen," based upon its risk assessment conducted in the late 1980s (http://www.epa.gov/iris/subst/0070.htm). Since that time, cancer risk-assessment practices have evolved, leading to improved scientifically based methods for estimating risk and for illuminating as well as reducing residual uncertainties. A new physiologically based pharmacokinetic (PBPK) model has been developed, using data from human volunteers exposed to low DCM levels, that provides new information on the human to human variability in DCM metabolism and elimination (L. M. Sweeney et al., 2004, Toxicol. Lett. 154, 201-216). This information, along with data from other published human studies, has been used to develop a new cancer risk estimation model utilizing probabilistic methodology similar to that employed recently by U.S. EPA for other chemicals (ENVIRON Health Sciences Institute, 2005, Development of population cancer risk estimates for environmental exposure to dichloromethane using a physiologically based pharmacokinetic model. Final Report to Eastman Kodak Company). This article summarizes the deliberations of a scientific peer-review panel convened on 3 and 4 May 2005 at the CIIT Centers for Health Research in Research Triangle Park, North Carolina, to review the "state of the science" for DCM and to critically evaluate the new information for its utility in assessing potential human cancer risks from DCM exposure. The panel (Melvin E Andersen, CIIT Centers for Health Research, Research Triangle Park, NC 27709; A. John Bailer, Miami University, Scripps Gerontology Center, Oxford, OH 45056; Kenneth S. Crump, ENVIRON Health Sciences Institute, Ruston, LA 71270; Clifford R. Elcombe, University of Dundee, Biomedical Research Centre, Dundee DD1 9SY, United Kingdom; Linda S. Erdreich, Exponent, 420 Lexington Avenue, Suite 1740, New York, NY 10170; Jeffery W. Fisher, University of Georgia, Department of Environmental Health Science, Athens, GA 30602; David Gaylor, Gaylor and Associates, LLC, Eureka Springs, AR 72631; F Peter Guengerich, Vanderbilt University, Department of Biochemistry, Nashville, TN 37232; Kenneth Mundt, ENVIRON Health Sciences Institute, Amherst, MA 01004; Lorenz R Rhomberg, Gradient Corporation, Cambridge, MA 021138; Charles Timchalk, Pacific Northwest National Laboratory, Richland, WA 99352), chaired by M.E.A., was composed of experts in xenobiotic metabolism and carcinogenic mechanisms, PBPK modeling, epidemiology, biostatistics, and quantitative risk assessment. Observers included representatives from U.S. EPA, CIIT, and Eastman Kodak Company (Kodak), as well as several consultants to Kodak. The workshop was organized and sponsored by Kodak, which employs DCM as a solvent in the production of imaging materials. Overall, the panel concluded that the new models for DCM risk assessment were scientifically and technically sound and represented an advance over those employed in past assessments.

Role of metabolism in parathion-induced hepatotoxicity and immunotoxicity

The objective of this study was to investigate whether metabolic activation of parathion by cytochrome P-450s (CYPs) was responsible for pesticide-induced hepatotoxicity and immunotoxicity. Initially, to investigate parathion metabolism in vitro, the production of paraoxon and p-nitrophenol, major metabolites of parathion, was determined by high-performance liquid chromatography (HPLC). Subsequently, metabolic fate and CYP enzymes involved in the metabolism of parathion were partially monitored in rat liver microsomes in the presence of the NADPH-generating system. Among others, phenobarbital (PB)-induced microsomes produced the metabolites paraoxon and p-nitrophenol to the greatest extent, indicating the involvement of CYP 2B in parathion metabolism. When female BALB/c mice were treated orally with 1, 4, or 16 mg/kg of parathion in corn oil once, parathion suppressed the antibody response to sheep red blood cells. To further investigate a possible role of metabolic activation by CYP enzymes in parathion-induced toxicity, female BALB/c mice were pretreated intraperitoneally with 40 mg/kg PB for 3 d, followed by a single oral treatment with 16 mg/kg parathion. PB pretreatment produced a decrease in hepatic glutathione content and increases in hepatotoxic paramenters in parathion-treated mice with no changes in the antibody response. In addition, greater p-nitrophenol amounts were produced when mice were pretreated with PB, compared to treatment with parathion alone. These results indicate that parathion-induced hepatotoxicity might be differentiated from immunotoxicity in mice.

Is INR between 2.0 and 3.0 the optimal level for Chinese patients on warfarin therapy for moderate-intensity anticoagulation?

AIM

To examine the optimal range of International Normalized Ratio (INR) for Chinese patients receiving warfarin for moderate-intensity anticoagulation.

METHODS

This was a retrospective cohort study conducted at the ambulatory setting of a 1400-bed public teaching hospital in Hong Kong. The INR measurements and occurrence of serious or life-threatening haemorrhagic and thromboembolic events among patients newly started on warfarin from 1 January 1999 to 30 June 2001 for indications with target INR 2-3 were analysed. The INR-specific incidence of bleeding and thromboembolism were calculated.

RESULTS

A total of 491 patients were included, contributing to 453 patient-years of observation period. Forty-seven of the 491 patients experienced 25 haemorrhagic events (5.5 per 100 patient-years) and 27 thromboembolic events (6.0 per 100 patient-years). The percentage of patient-time spent within therapeutic INR range (2-3), INR <2 and INR >3 were 50, 44 and 6%, respectively. The incidence of either haemorrhagic or thromboembolic events was lowest (< or =4 events per 100 patient-years) at INR values between 1.8 and 2.4.

CONCLUSIONS

An INR of 1.8-2.4 appeared to be associated with the lowest incidence rate of major bleeding or thromboembolic events in a cohort of Hong Kong Chinese patients receiving warfarin therapy for moderate-intensity anticoagulation.

The refinement of uncertainty/safety factors in risk assessment by the incorporation of data on toxicokinetic variability in humans

The derivation of safe levels of exposure in humans for compounds that are assumed to cause threshold toxicity has relied on the application of a 100-fold uncertainty factor to a measure for the threshold, such as the no observed adverse effect level (NOAEL) or the benchmark dose (BMD). This 100-fold safety factor consists of the product of two 10-fold factors allowing for human variability and interspecies differences. The International Programme on Chemical Safety has suggested the subdivision of these 10-fold factors to allow for variability in toxicokinetics and toxicodynamics. This subdivision allows the replacement of the default uncertainty factors with a chemical-specific adjustment factor (CSAF) when suitable data are available. This short review describes potential options to refine safety factors used in risk assessment, with particular emphasis on pathway-related uncertainty factors associated with variability in kinetics. These pathway-related factors were derived from a database that quantified interspecies differences and human variability in phase I metabolism, phase II metabolism, and renal excretion. This approach allows metabolism and pharmacokinetic data in healthy adults and subgroups of the population to be incorporated in the risk-assessment process and constitutes an intermediate approach between simple default factors and chemical-specific adjustment factors.

Assessing biomarker use in risk assessment--a survey of practitioners

Advances in molecular epidemiology and mechanistic toxicology have provided increased opportunities for incorporating biomarkers in the human health risk assessment process. For years, the published literature has lauded the concept of incorporating biomarkers into risk assessments as a means to reduce uncertainty in estimating health risk. For all the potential benefits, one would think that markers of effective dose, markers of early biological effects, and markers of human susceptibility are frequently selected as the basis for quantitative human health risk assessments. For this article, we sought to determine the degree to which this evolution in risk assessment has come to pass. The extent to which biomarkers are being used in current human health risk assessment was determined through an informal survey of leading risk assessment practitioners. Case studies highlighting the evolution of risk assessment methods to include biomarkers are also described. The goal of this review was to enhance the implementation of biomarker technology in risk assessment by (1) highlighting successes in biomarker implementation, (2) identifying key barriers to overcome, and (3) describing evolutions in risk assessment methods.