Human variability in hepatic and renal elimination: implications for risk assessment

Current practice and recommendations for advancing how human variability and susceptibility are considered in chemical risk assessment

A key element of risk assessment is accounting for the full range of variability in response to environmental exposures. Default dose-response methods typically assume a 10-fold difference in response to chemical exposures between average (healthy) and susceptible humans, despite evidence of wider variability. Experts and authoritative bodies support using advanced techniques to better account for human variability due to factors such as in utero or early life exposure and exposure to multiple environmental, social, and economic stressors.This review describes: 1) sources of human variability and susceptibility in dose-response assessment, 2) existing US frameworks for addressing response variability in risk assessment; 3) key scientific inadequacies necessitating updated methods; 4) improved approaches and opportunities for better use of science; and 5) specific and quantitative recommendations to address evidence and policy needs.Current default adjustment factors do not sufficiently capture human variability in dose-response and thus are inadequate to protect the entire population. Susceptible groups are not appropriately protected under current regulatory guidelines. Emerging tools and data sources that better account for human variability and susceptibility include probabilistic methods, genetically diverse in vivo and in vitro models, and the use of human data to capture underlying risk and/or assess combined effects from chemical and non-chemical stressors.We recommend using updated methods and data to improve consideration of human variability and susceptibility in risk assessment, including the use of increased default human variability factors and separate adjustment factors for capturing age/life stage of development and exposure to multiple chemical and non-chemical stressors. Updated methods would result in greater transparency and protection for susceptible groups, including children, infants, people who are pregnant or nursing, people with disabilities, and those burdened by additional environmental exposures and/or social factors such as poverty and racism.

Estimation of toluene exposure in air from BMA (S-benzylmercapturic acid) urinary measures using a reverse dosimetry approach based on physiologically pharmacokinetic modeling

This study aimed to use a reverse dosimetry PBPK modeling approach to estimate toluene atmospheric exposure from urinary measurements of S-benzylmercapturic acid (BMA) in a small group of individuals and to evaluate the uncertainty associated to urinary spot-sampling compared to 24-h collected urine samples. Each exposure assessment technique was developed namely to estimate toluene air exposure from BMA measurements in 24-h urine samples (24-h-BMA) and from distributions of daily urinary BMA spot measurements (DUBSM). Model physiological parameters were described based upon age, weight, size and sex. Monte Carlo simulations with the PBPK model allowed converting DUBSM distribution (and 24-h-BMA) into toluene air levels. For the approach relying on DUBSM distribution, the ratio between the 95% probability of predicted toluene concentration and its 50% probability in each individual varied between 1.2 and 1.4, while that based on 24-h-BMA varied between 1.0 and 1.1. This suggests more variability in estimated exposure from spot measurements. Thus, estimating toluene exposure based on DUBSM distribution generated about 20% more uncertainty. Toluene levels estimated (0.0078-0.0138 ppm) are well below Health Canada's maximum chronic air guidelines. PBPK modeling and reverse dosimetry may be combined to interpret urinary metabolites data of VOCs and assess related uncertainties.

Role of the Hyaluronan Receptor, Stabilin-2/HARE, in Health and Disease

Stabilin-2/HARE is the primary clearance receptor for circulating hyaluronan (HA), a polysaccharide found in the extracellular matrix (ECM) of metazoans. HA has many biological functions including joint lubrication, ocular turgor pressure, skin elasticity and hydration, cell motility, and intercellular signaling, among many others. The regulatory system for HA content in the tissues, lymphatics, and circulatory systems is due, in part, to Stabilin-2/HARE. The activity of this receptor was discovered about 40 years ago (early 1980s), cloned in the mid-1990s, and has been characterized since then. Here, we discuss the overall domain organization of this receptor and how it correlates to ligand binding, cellular signaling, and its role in known physiological disorders such as cancer.

High-throughput screening tools facilitate calculation of a combined exposure-bioactivity index for chemicals with endocrine activity

High-throughput and computational tools provide a new opportunity to calculate combined bioactivity of exposure to diverse chemicals acting through a common mechanism. We used high throughput in vitro bioactivity data and exposure predictions from the U.S. EPA's Toxicity and Exposure Forecaster (ToxCast and ExpoCast) to estimate combined estrogen receptor (ER) agonist activity of non-pharmaceutical chemical exposures for the general U.S. population. High-throughput toxicokinetic (HTTK) data provide conversion factors that relate bioactive concentrations measured in vitro (µM), to predicted population geometric mean exposure rates (mg/kg/day). These data were available for 22 chemicals with ER agonist activity and were estimated for other ER bioactive chemicals based on the geometric mean of HTTK values across chemicals. For each chemical, ER bioactivity across ToxCast assays was compared to predicted population geometric mean exposure at different levels of in vitro potency and model certainty. Dose additivity was assumed in calculating a Combined Exposure-Bioactivity Index (CEBI), the sum of exposure/bioactivity ratios. Combined estrogen bioactivity was also calculated in terms of the percent maximum bioactivity of chemical mixtures in human plasma using a concentration-addition model. Estimated CEBIs vary greatly depending on assumptions used for exposure and bioactivity. In general, CEBI values were <1 when using median of the estimated general population chemical intake rates, while CEBI were ≥1 when using the upper 95th confidence bound for those same intake rates for all chemicals. Concentration-addition model predictions of mixture bioactivity yield comparable results. Based on current in vitro bioactivity data, HTTK methods, and exposure models, combined exposure scenarios sufficient to influence estrogen bioactivity in the general population cannot be ruled out. Future improvements in screening methods and computational models could reduce uncertainty and better inform the potential combined effects of estrogenic chemicals.

Methods for evaluating variability in human health dose-response characterization

The Reference Dose (RfD) and Reference Concentration (RfC) are human health reference values (RfVs) representing exposure concentrations at or below which there is presumed to be little risk of adverse effects in the general human population. The 2009 National Research Council report Science and Decisions recommended redefining RfVs as "a risk-specific dose (for example, the dose associated with a 1 in 100,000 risk of a particular end point)." Distributions representing variability in human response to environmental contaminant exposures are critical for deriving risk-specific doses. Existing distributions estimating the extent of human toxicokinetic and toxicodynamic variability are based largely on controlled human exposure studies of pharmaceuticals. New data and methods have been developed that are designed to improve estimation of the quantitative variability in human response to environmental chemical exposures. Categories of research with potential to provide new database useful for developing updated human variability distributions include controlled human experiments, human epidemiology, animal models of genetic variability, in vitro estimates of toxicodynamic variability, and in vitro-based models of toxicokinetic variability. In vitro approaches, with further development including studies of different cell types and endpoints, and approaches to incorporate non-genetic sources of variability, appear to provide the greatest opportunity for substantial near-term advances.

Reverse dosimetry modeling of toluene exposure concentrations based on biomonitoring levels from the Canadian health measures survey

Biomonitoring might provide useful estimates of population exposure to environmental chemicals. However, data uncertainties stemming from interindividual variability are common in large population biomonitoring surveys. Physiologically based pharmacokinetic (PBPK) models might be used to account for age- and gender-related variability in internal dose. The objective of this study was to reconstruct air concentrations consistent with blood toluene measures reported in the third Canadian Health Measures Survey using reverse dosimetry PBPK modeling techniques. Population distributions of model's physiological parameters were described based upon age, weight, and size for four subpopulations (12-19, 20-39, 40-59, and 60-79 years old). Monte Carlo simulations applied to PBPK modeling allowed converting the distributions of venous blood measures of toluene obtained from CHMS into related air levels. Based upon blood levels observed at the 50^th, 90^th and 95^th percentiles, corresponding air toluene concentrations were estimated for teenagers aged 12-19 years as being, respectively, 0.009, 0.04 and 0.06 ppm. Similarly, values were computed for adults aged 20-39 years (0.007, 0.036, and 0.06 ppm), 40-59 years (0.007, 0.036 and 0.06 ppm) and 60-79 years (0.006, 0.022 and 0.04 ppm). These estimations are well below Health Canada's maximum recommended chronic air guidelines for toluene. In conclusion, PBPK modeling and reverse dosimetry may be combined to help interpret biomonitoring data for chemical exposure in large population surveys and estimate the associated toxicological health risk.

Induction of the Estrogenic Marker Calbindn-D₉k by Octamethylcyclotetrasiloxane

Interrupting the hormonal balance of an organism by interfering with hormones and their target receptors gives rise to various problems such as developmental disorders. Collectively, these reagents are known as endocrine disruptors (EDs). Cyclic volatile methyl siloxanes (cVMSs) are a group of silicone polymers that including octamethylcyclotetrasiloxane (D4). In the present study, we examined the estrogenicity of D4 through in vitro and in vivo assays that employed calcium-binding protein 9K (calbindin-D9k; CaBP-9K) as a biomarker. For in vitro investigation, GH3 rat pituitary cells were exposed to vehicle, 17β-estradiol (E2), or D4 with/without ICI 182 780 (ICI). CaBP-9K and progesterone receptor (PR) both were up-regulated by E2 and D4 which were completely blocked by ICI. Transcription of estrogen receptor α (ER α) was decreased by E2 and D4 but increased by ICI. D4 was also administered to immature female rats for an uterotrophic (UT) assay and detection of CaBP-9K. Ethinyl estradiol (EE) or D4 was administered subcutaneously with or without ICI. Although uterine weight was not significant altered by D4, an effect thought to be due to cytochrome P450 (CYP), it induced CaBP-9K and PR gene expression. Based on these results we reveal that D4 has estrogenic potential proven under in vitro and in vivo experimental conditions.

Ethnic differences in adverse drug reactions to asthma medications: a systematic review

BACKGROUND

Information on ethnic diversity of adverse drug reactions (ADRs) to asthma medications is rare despite evidence suggesting higher risk for African Americans when using β2-adrenergic receptor agonists. The objectives are to investigate how ethnic background was involved in ADR assessment and to examine the relationship between ethnic background and ADRs to asthma medications.

METHODS

MEDLINE was searched until March 2014. All types of studies reporting ADRs to asthma medications involving more than one ethnic group were included. Extracted information includes study designs, ethnic backgrounds, intervention, and types and severities of ADRs.

RESULTS

Among the selected 15 randomised clinical trials, six pooled analyses of randomized clinical trials, and five prospective observational studies, only six studies compared ADRs across different ethnic groups. The majority of the comparisons were either statistically insignificant or inconclusive.

CONCLUSIONS

Ethnicity was largely overlooked. Most studies neglected to report ADRs by ethnicity. Lack of consistency in defining ethnicities complicated further pooled analyses. Despite the higher prevalence of asthma among specific ethnic minority groups, few studies disaggregated information by ethnic background, and reports of ADRs to asthma medications in different ethnic groups were rare. We suggest that the inclusion of ADR analysis by different ethnic backgrounds is desirable.

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.

Sources of variability in biomarker concentrations

Human biomonitoring has become a primary tool for chemical exposure characterization in a wide variety of contexts: population monitoring and characterization at a national level, assessment and description of cohort exposures, and individual exposure assessments in the context of epidemiological research into potential adverse health effects of chemical exposures. The accurate use of biomonitoring as an exposure characterization tool requires understanding of factors, apart from external exposure level, that influence variation in biomarker concentrations. This review provides an overview of factors that might influence inter- and intraindividual variation in biomarker concentrations apart from external exposure magnitude. These factors include characteristics of the specific chemical of interest, characteristics of the likely route(s) and frequency of exposure, and physiological characteristics of the biomonitoring matrix (typically, blood or urine). Intraindividual variation in biomarker concentrations may be markedly affected by the relationship between the elimination half-life and the intervals between exposure events, as well as by variation in characteristics of the biomonitored media such as blood lipid content or urinary flow rate. Variation across individuals may occur due to differences in time of sampling relative to exposure events, physiological differences influencing urinary flow or creatinine excretion rates or blood characteristics, and interindividual differences in metabolic rate or other factors influencing the absorption or excretion rate of a compound. Awareness of these factors can assist researchers in improving the design and interpretation of biomonitoring studies.

Characterization of the human kinetic adjustment factor for the health risk assessment of environmental contaminants

A default uncertainty factor of 3.16 (√10) is applied to account for interindividual variability in toxicokinetics when performing non-cancer risk assessments. Using relevant human data for specific chemicals, as WHO/IPCS suggests, it is possible to evaluate, and replace when appropriate, this default factor by quantifying chemical-specific adjustment factors for interindividual variability in toxicokinetics (also referred to as the human kinetic adjustment factor, HKAF). The HKAF has been determined based on the distributions of pharmacokinetic parameters (e.g., half-life, area under the curve, maximum blood concentration) in relevant populations. This article focuses on the current state of knowledge of the use of physiologically based algorithms and models in characterizing the HKAF for environmental contaminants. The recent modeling efforts on the computation of HKAF as a function of the characteristics of the population, chemical and its mode of action (dose metrics), as well as exposure scenario of relevance to the assessment are reviewed here. The results of these studies, taken together, suggest the HKAF varies as a function of the sensitive subpopulation and dose metrics of interest, exposure conditions considered (route, duration, and intensity), metabolic pathways involved and theoretical model underlying its computation. The HKAF seldom exceeded the default value of 3.16, except in very young children (i.e., <≈ 3 months) and when the parent compound is the toxic moiety. Overall, from a public health perspective, the current state of knowledge generally suggest that the default uncertainty factor is sufficient to account for human variability in non-cancer risk assessments of environmental contaminants.

Tools and perspectives for assessing chemical mixtures and multiple stressors

The present paper summarizes the most important insights and findings of the EU NoMiracle project with a focus on (1) risk assessment of chemical mixtures, (2) combinations of chemical and natural stressors, and (3) the receptor-oriented approach in cumulative risk assessment. The project aimed at integration of methods for human and ecological risk assessment. A mechanistically based model, considering uptake and toxicity as a processes in time, has demonstrated considerable potential for predicting mixture effects in ecotoxicology, but requires the measurement of toxicity endpoints at different moments in time. Within a novel framework for risk assessment of chemical mixtures, the importance of environmental factors on toxicokinetic processes is highlighted. A new paradigm for applying personal characteristics that determine individual exposure and sensitivity in human risk assessment is suggested. The results are discussed in the light of recent developments in risk assessment of mixtures and multiple stressors.

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.

Novel methods for integrated risk assessment of cumulative stressors--results from the NoMiracle project

This special issue covers the main results of the European Sixth Framework Integrated Research project NoMiracle (Novel Methods for Risk Assessment of Cumulative stressors in Europe). New tools to analyse, characterise and quantify the combined risks to health or the environment from multiple stressors are presented or reviewed. Examples of cumulative stressors are mixtures of chemicals alone or in combination with biological or physical environmental factors such as pathogens and climate extremes. Among the main findings, the scientific work points at the importance of time in dealing with toxicity, and in particular the toxicity of chemical mixtures, the natures of the uncertainties associated with risk assessment and the value of visualisation in identifying and quantifying the most relevant risks. A major conclusion of the project is that researchers and regulators should focus on the receptor rather than on the single stressor or combination of agents. There is also a need for more efforts on mechanistic understanding and for a mechanism-based framework for interpreting mixture/multiple stressor effects. The new tools are available on the internet (http://nomiracle.jrc.ec.europa.eu).

Metabolism, variability and risk assessment

For non-genotoxic carcinogens, "thresholded toxicants", Acceptable/Tolerable Daily Intakes (ADI/TDI) represent a level of exposure "without appreciable health risk" when consumed everyday or weekly for a lifetime and are derived by applying an uncertainty factor of a 100-fold to a no-observed-adverse-effect-levels (NOAEL) or to a benchmark dose. This UF allows for interspecies differences and human variability and has been subdivided to take into account toxicokinetics and toxicodynamics with even values of 10(0.5) (3.16) for the human aspect. Ultimately, such refinements allow for chemical-specific adjustment factors and physiologically based models to replace such uncertainty factors. Intermediate to chemical-specific adjustment factors are pathway-related uncertainty factors which have been derived for phase I, phase II metabolism and renal excretion. Pathway-related uncertainty factors are presented here as derived from the result of meta-analyses of toxicokinetic variability data in humans using therapeutic drugs metabolised by a single pathway in subgroups of the population. Pathway-related lognormal variability was derived for each metabolic route. The resulting pathway-related uncertainty factors showed that the current uncertainty factor for toxicokinetics (3.16) would not cover human variability for genetic polymorphism and age differences (neonates, children, the elderly). Latin hypercube (Monte Carlo) models have also been developed using quantitative metabolism data and pathway-related lognormal variability to predict toxicokinetics variability and uncertainty factors for compounds handled by several metabolic routes. For each compound, model results gave accurate predictions compared to published data and observed differences arose from data limitations, inconsistencies between published studies and assumptions during model design and sampling. Finally, under the 6(th) framework EU project NOMIRACLE (http://viso.jrc.it/nomiracle/), novel methods to improve the risk assessment of chemical mixtures were explored (1) harmonization of the use of uncertainty factors for human and ecological risk assessment using mechanistic descriptors (2) use of toxicokinetics interaction data to derive UFs for chemical mixtures. The use of toxicokinetics data in risk assessment are discussed together with future approaches including sound statistical approaches to optimise predictability of models and recombinant technology/toxicokinetics assays to identify metabolic routes for chemicals and screen mixtures of environmental health importance.

Demographic data in asthma clinical trials: a systematic review with implications for generalizing trial findings and tackling health disparities

The prevalence of asthma, and the morbidity, adverse events, mortality and healthcare utilisation of asthmatic patients vary widely among racial/ethnic and other socio-demographic groups. Debates over the meanings of race and ethnicity and the strategic need to resolve health inequalities have prompted extensive recommendations for reporting and analyzing racial/ethnic and demographic information in clinical trials. We conducted a systematic review to determine the extent to which race/ethnicity, socio-economic status and other demographic variables are analyzed and reported in publications from randomized controlled trials of asthma interventions. Randomized controlled trials of inhaled corticosteroids and long-acting beta-agonists in asthmatic patients were identified by systematically searching 12 electronic bibliographic databases. We identified peer-reviewed papers reporting 87 relevant trials published during 1985-2006, from which we extracted data on patients' race/ethnicity, ancestry, gender, socio-economic variables and geographical attributes. The proportion of the papers reporting the race/ethnicity of their participants was lower than would be expected by chance and has recently declined. None of the papers included race/ethnicity or gender in statistical analyses or reported socio-economic variables, ancestry, or genetic data for their participants, and few discussed the generalizability of their findings. The frequency of reporting race/ethnicity was statistically significantly lower in trials conducted in the UK than in the US, but 23 of the 87 papers did not identify countries. Despite extensive recommendations in the literature, guidance from health agencies on analyzing and reporting demographic data in clinical trials still appears inconsistent and vague. There remains a need to improve guidance on the representation and analysis of minority populations in asthma clinical trials, in order to encourage transparent reporting of population selection, analysis approaches, and trial generalizability. To assist this process, asthma clinical trials should be based on clear hypotheses that link both to existing demographic evidence and to demographic healthcare goals.

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.