Exposure reconstruction for reducing uncertainty in risk assessment: example using MTBE biomarkers and a simple pharmacokinetic model

Adverse health risks from environmental agents are generally related to average (long-term) exposures. Because a given individual's contact with a pollutant is highly variable and dependent on activity patterns, local sources and exposure pathways, simple ‘snapshot’ measurements of surrounding environmental media may not accurately assign the exposure level. Furthermore, susceptibility to adverse effects from contaminants is considered highly variable in the population so that even similar environmental exposure levels may result in differential health outcomes in different individuals. The use of biomarker measurements coupled to knowledge of rates of uptake, metabolism and elimination has been suggested as a remedy for reducing this type of uncertainty. To demonstrate the utility of such an approach, we invoke results from a series of controlled human exposure tests and classical first-order rate kinetic calculations to estimate how well spot measurements of methyl tertiary butyl ether and the primary metabolite, tertiary butyl alcohol, can be expected to predict different hypothetical scenarios of previous exposures. We found that blood and breath biomarker measurements give similar results and that the biological damping effect of the metabolite production gives more stable estimates of previous exposure. We also explore the value of a potential urinary biomarker, 2-hydroxyisobutyrate suggested in the literature. We find that individual biomarker measurements are a valuable tool in reconstruction of previous exposures and that a simple pharmacokinetic model can identify the time frames over which an exogenous chemical and the related chemical biomarker are useful. These techniques could be applied to broader ranges of environmental contaminants to assess cumulative exposure risks if ADME (Absorption, Distribution, Metabolization and Excretion) is understood and systemic biomarkers can be measured.     

Exposure reconstruction for reducing uncertainty in risk assessment: example using MTBE biomarkers and a simple pharmacokinetic model

Adverse health risks from environmental agents are generally related to average (long-term) exposures. Because a given individual's contact with a pollutant is highly variable and dependent on activity patterns, local sources and exposure pathways, simple 'snapshot' measurements of surrounding environmental media may not accurately assign the exposure level. Furthermore, susceptibility to adverse effects from contaminants is considered highly variable in the population so that even similar environmental exposure levels may result in differential health outcomes in different individuals. The use of biomarker measurements coupled to knowledge of rates of uptake, metabolism and elimination has been suggested as a remedy for reducing this type of uncertainty. To demonstrate the utility of such an approach, we invoke results from a series of controlled human exposure tests and classical first-order rate kinetic calculations to estimate how well spot measurements of methyl tertiary butyl ether and the primary metabolite, tertiary butyl alcohol, can be expected to predict different hypothetical scenarios of previous exposures. We found that blood and breath biomarker measurements give similar results and that the biological damping effect of the metabolite production gives more stable estimates of previous exposure. We also explore the value of a potential urinary biomarker, 2-hydroxyisobutyrate suggested in the literature. We find that individual biomarker measurements are a valuable tool in reconstruction of previous exposures and that a simple pharmacokinetic model can identify the time frames over which an exogenous chemical and the related chemical biomarker are useful. These techniques could be applied to broader ranges of environmental contaminants to assess cumulative exposure risks if ADME (Absorption, Distribution, Metabolization and Excretion) is understood and systemic biomarkers can be measured.     

Review of Information Resources to Support Human Exposure Assessment Models

Efforts to model human exposures to chemicals are growing more sophisticated and encompass increasingly complex exposure scenarios. The scope of such analyses has increased, growing from assessments of single exposure pathways to complex evaluations of aggregate or cumulative chemical exposures occurring within a variety of settings and scenarios. In addition, quantitative modeling techniques have evolved from simple deterministic analyses using single point estimates for each necessary input parameter to more detailed probabilistic analyses that can accommodate distributions of input parameters and assessment results. As part of an overall effort to guide development of a comprehensive framework for modeling human exposures to chemicals, available information resources needed to derive input parameters for human exposure assessment models were compiled and critically reviewed. Ongoing research in the area of exposure assessment parameters was also identified. The results of these efforts are summarized and other relevant information that will be needed to apply the available data in a comprehensive exposure model is discussed. Critical data gaps in the available information are also identified. Exposure assessment modeling and associated research would benefit from the collection of additional data as well as by enhancing the accessibility of existing and evolving information resources.     

Developing Parameters for Uncommon Exposures

Common exposure scenarios form the basis for exposure assessments included in human health risk assessments. The quantitative parameters that are used to calculate the receptor's dose associated with these common exposure scenarios are readily available. When humans have uncommon exposures, these often are excluded from the dose calculations because of the lack of parameters or parameters are estimated, which can increase the uncertainty in calculated dose. This study evaluates a third option of performing laboratory experiments to estimate parameters for uncommon exposures. Two exposures, the handling and hand-washing of contaminated work clothes and the drinking of water with sufficient free-phase hydrocarbons to form a visible sheen, were simulated in a laboratory. Parameters were developed for each exposure such that doses could be calculated. Parameters developed include a mass of oily contaminants on skin after washing contaminated clothes and the mass of a visible oily sheen on an aqueous surface. These results demonstrate that developing parameters for uncommon exposure scenarios is a practical alternative to eliminating or estimating exposures and these experiments can be done in compliance with human subject protocols.     

Distributions Selected for Use in Probabilistic Human Health Risk Assessments in Oregon

In 1995, Oregon enacted amendments to its state Cleanup Law that emphasize risk-based remedial action decisions and allow a responsible party to conduct probabilistic human health risk assessments. This change required selection and/or development of probability density functions for exposure factors frequently used in human health risk assessments. Methods used to obtain distributions for body weight, soil, water, vegetable/fruit, fish, and animal product ingestion, soil adherence, daily inhalation rate, various event and exposure frequencies, and exposure duration are described. Primary data sources were U.S. Environmental Protection Agency guidance and peer-reviewed scientific literature. These distributions of exposure factors may be used, in conjunction with a probabilistic age- and gender-based model, to calculate prospective exposures and risks. A brief overview of this model, which handles temporal parameters (age, exposure frequency, exposure duration) in a manner substantially different from that typically used in deterministic assessments, is also provided. Oregon's development of an age/ gender-based exposure model, and its selection of exposure factor value distributions for that model, represents one of the first attempts to develop practical approaches to using probabilistic techniques in a hazardous waste regulatory program.     

A modeling procedure to predict cancer risks associated with inhalable oil dust from Kuwait oil lakes

A model was constructed to estimate cancer risks associated with PM₁₀‐bound polycydic aromatic hydrocarbons (PAHs) from Kuwait oil lakes. The design of the risk model was based on a conceptual “chain of events”; leading from levels of PAH compounds in oil lakes, erosion of oil dust and input into the atmosphere, to contaminant concentration in air, to actual human exposure in residential areas. Uncertainties in the “chain of events”; model were addressed using Monte Carlo techniques. To identify the exposure duration of concern [duration beyond which risk becomes unacceptable (i.e. Risk > 10^‐6)], four exposure durations were tested 10, 20, 40, 70 years. 40 years was identified to be the exposure duration of concern based on the 95th percen‐tile of the risk distribution. As a result, the acceptability of risk was specified in terms of a single constraint on the 95^th percentile of the risk distribution evaluated after 40 years of exposure: 0 < Risk (40 y)₀.₉₅ ≤ 10^‐6. Based on this constraint, it was estimated that a removal rate of 217, 793.27 m³/year to be an adequate action for risk management. The northern oil lakes were identified as the lakes of most concern when inhalation exposures are considered.     

Experimental validation of a statistical model for evaluating the past or future magnetic field exposures of a population living near power lines

This study was designed to provide an experimental validation for a statistical model predicting past or future exposures to magnetic fields (MF) from power lines. The model estimates exposure, combining the distribution of ambient MF in the absence of power lines with the distribution of past or future MF produced by power lines. In the study, validation is carried out by comparing exposures predicted by the model with the actual measurements obtained from a large-scale epidemiological study. The comparison was made for a group of 220 women living near a 735 kV power line. Knowing that the individual arithmetic means of MF exposures follow a log-normal distribution, the Pearson correlation between the log-transformed measured means and the calculated ones was determined and found to be 0.77. Predicted values of MF exposures were slightly lower than measured values. The calculated geometric mean of the group was 0.33 microT, compared to 0.38 microT for the measured geometric mean. The present study shows good agreement between the measured MF exposure of an individual inside a house near a 735 kV line and the MF exposure calculated using a statistical model.     

Setting Guidelines for Electromagnetic Exposures and Research Needs

Current limits for exposures to nonionizing electromagnetic fields (EMF) are set, based on relatively short-term exposures. Long-term exposures to weak EMF are not addressed in the current guidelines. Nevertheless, a large and growing amount of evidence indicates that long-term exposure to weak fields can affect biological systems and might have effects on human health. If they do, the public health issues could be important because of the very large fraction of the population worldwide that is exposed. We also discuss research that needs to be done to clarify questions about the effects of weak fields. In addition to the current short-term exposure guidelines, we propose an approach to how weak field exposure guidelines for long-term exposures might be set, in which the responsibility for limiting exposure is divided between the manufacturer, system operator, and individual being exposed. Bioelectromagnetics. © 2020 Bioelectromagnetics Society     

Role of biomarkers in monitoring exposures to chemicals: present position, future prospects

Biomarkers are becoming increasingly important in toxicology and human health. Many research groups are carrying out studies to develop biomarkers of exposure to chemicals and apply these for human monitoring. There is considerable interest in the use and application of biomarkers to identify the nature and amounts of chemical exposures in occupational and environmental situations. Major research goals are to develop and validate biomarkers that reflect specific exposures and permit the prediction of the risk of disease in individuals and groups. One important objective is to prevent human cancer. This review presents a commentary and consensus views about the major developments on biomarkers for monitoring human exposure to chemicals. A particular emphasis is on monitoring exposures to carcinogens. Significant developments in the areas of new and existing biomarkers, analytical methodologies, validation studies and field trials together with auditing and quality assessment of data are discussed. New developments in the relatively young field of toxicogenomics possibly leading to the identification of individual susceptibility to both cancer and non-cancer endpoints are also considered. The construction and development of reliable databases that integrate information from genomic and proteomic research programmes should offer a promising future for the application of these technologies in the prediction of risks and prevention of diseases related to chemical exposures. Currently adducts of chemicals with macromolecules are important and useful biomarkers especially for certain individual chemicals where there are incidences of occupational exposure. For monitoring exposure to genotoxic compounds protein adducts, such as those formed with haemoglobin, are considered effective biomarkers for determining individual exposure doses of reactive chemicals. For other organic chemicals, the excreted urinary metabolites can also give a useful and complementary indication of exposure for acute exposures. These methods have revealed 'backgrounds' in people not knowingly exposed to chemicals and the sources and significance of these need to be determined, particularly in the context of their contribution to background health risks.     

Role of biomarkers in monitoring exposures to chemicals: present position,future prospects

Biomarkers are becoming increasingly important in toxicology and human health. Many research groups are carrying out studies to develop biomarkers of exposure to chemicals and apply these for human monitoring. There is considerable interest in the use and application of biomarkers to identify the nature and amounts of chemical exposures in occupational and environmental situations. Major research goals are to develop and validate biomarkers that reflect specific exposures and permit the prediction of the risk of disease in individuals and groups. One important objective is to prevent human cancer. This review presents a commentary and consensus views about the major developments on biomarkers for monitoring human exposure to chemicals. A particular emphasis is on monitoring exposures to carcinogens. Significant developments in the areas of new and existing biomarkers, analytical methodologies, validation studies and field trials together with auditing and quality assessment of data are discussed. New developments in the relatively young field of toxicogenomics possibly leading to the identification of individual susceptibility to both cancer and non-cancer endpoints are also considered. The construction and development of reliable databases that integrate information from genomic and proteomic research programmes should offer a promising future for the application of these technologies in the prediction of risks and prevention of diseases related to chemical exposures. Currently adducts of chemicals with macromolecules are important and useful biomarkers especially for certain individual chemicals where there are incidences of occupational exposure. For monitoring exposure to genotoxic compounds protein adducts, such as those formed with haemoglobin, are considered effective biomarkers for determining individual exposure doses of reactive chemicals. For other organic chemicals, the excreted urinary metabolites can also give a useful and complementary indication of exposure for acute exposures. These methods have revealed ‘backgrounds’ in people not knowingly exposed to chemicals and the sources and significance of these need to be determined, particularly in the context of their contribution to background health risks.     

Parameterizing Potential Exposure to Sulfur Mustard (HD) Using Mixed Model Regression

The possible threat posed by terrorists using chemical warfare agents (CWAs) against civilian targets is a major concern, reflecting the fact that CWAs are highly toxic to unprotected populations, with releases as vapors or aerosols likely to produce mass casualties on a highly localized basis within minutes or hours after an incident. A conceptual site model is developed and mixed model regression is used to estimate concentration values for the vesicant sulfur mustard (HD) based on the output from computational fluid dynamics (CFD) simulation following wind tunnel experimentation. The analysis provides a first-approximation of the spatial and temporal distribution of potential exposures within a set of 50 m × 50 m × 2 m grids across a 1000 m width by 300 m height by 2250 m length domain in a geographic information system (GIS) environment. The HD concentration values are calculated as log-averaged mean and the 95% confidence intervals for each grid at 1.9 d and 6.0 d after initial release. The technique offers a statistically valid means for rapidly generating unbiased first-approximations of concentration values subsequent to an initial release as an alternative to extensive monitoring or multiple runs of CFD models to parameterize potential exposure to HD spatially and temporally.     

Development of Factors for Estimating Swimmers' Exposures to Chemicals in Swimming Pools

The U.S. Environmental Protection Agency (USEPA) has developed a model to estimate chemical-specific exposures to swimmers following pool treatments. This model is called SWIMODEL. The model was first introduced in 1996, and the USEPA has made refinements to the model over the last decade. One of the most significant parameters in this model is the duration of exposure. Unfortunately, there was no reliable source of data for these exposure durations, so highly conservative estimates were used in the earlier version of SWIMODEL. In order to address this data deficiency, a telephone survey of competitive swimming coaches was conducted to provide data for the refinement of the SWIMODEL. The survey collected data on practice durations and other factors that are potentially relevant to swimmer exposures. Two different surveys were developed. The first survey was designed for coaches of amateur swim club teams, and the second survey was for collegiate coaches. The survey found that the average practice durations for youth, adult Masters, and collegiate teams were 9.1, 6.4, and 17.0 hours/week, respectively. The use of these data to estimate acute, chronic, and lifetime exposures is discussed. The data developed in this study were used to update the exposure duration and frequency estimates in SWIMODEL for competitive swimmers based on survey responses. The survey was also used to determine the percentage of competitive swimmers that wear eye goggles and other protective gear, and to supplement other measurements of the incidental water ingestion of competitive swimmers.     

Effects of 2G and 3G mobile phones on human alpha rhythms: Resting EEG in adolescents,young adults,and the elderly

The present study was conducted to determine whether adolescents and/or the elderly are more sensitive to mobile phone (MP)‐related bioeffects than young adults, and to determine this for both 2nd generation (2G) GSM, and 3rd generation (3G) W‐CDMA exposures. To test this, resting alpha activity (8–12 Hz band of the electroencephalogram) was assessed because numerous studies have now reported it to be enhanced by MP exposure. Forty‐one 13–15 year olds, forty‐two 19–40 year olds, and twenty 55–70 year olds were tested using a double‐blind crossover design, where each participant received Sham, 2G and 3G exposures, separated by at least 4 days. Alpha activity, during exposure relative to baseline, was recorded and compared between conditions. Consistent with previous research, the young adults' alpha was greater in the 2G compared to Sham condition, however, no effect was seen in the adolescent or the elderly groups, and no effect of 3G exposures was found in any group. The results provide further support for an effect of 2G exposures on resting alpha activity in young adults, but fail to support a similar enhancement in adolescents or the elderly, or in any age group as a function of 3G exposure. Bioelectromagnetics 31:434–444, 2010. © 2010 Wiley‐Liss, Inc.     

A Conceptual Framework for the Interpretation of Biological Markers for Environmental Exposure Assessment

Human exposure to environmental contaminants occurs via air, water, soil, dust, food, and other environmental media. Given this multitude of sources, environmental exposure assessment is moving away from single route exposure assessment to more integrated measures of exposure. Biological markers are frequently advocated as appropriate exposure assessment tools since they provide a measure of internal dose integrated over all routes of exposure. However, contributing sources may be difficult to identify through use of biological markers, and thus, have had limited utility in the regulatory community. To explore the different perspectives on the use and application of biological markers for exposure assessors, epidemiologists, and regulatory personnel, we have developed a biological marker conceptual framework. This framework is developed as a paradigm for the interpretation of biological markers for environmental exposure assessment linking the exposure assessment and the health effects assessment perspectives regarding biological markers. Further, it incorporates issues of source-specific exposures, aggregate exposure assessment, route-specific contributions, and biological variation in response to exposure. This structure provides an approach to explore the current constraints in using biological markers to evaluate source-specific exposures. This framework is discussed in the context of currently available biological markers for lead, carbon monoxide, and toluene. Biological markers represent a complex tool to assess human exposures to environmental contaminants; the biological marker framework presents a structure for their interpretation recognizing that many of the determinants of exposure, bioavailablity, and toxicokinetics are still being evaluated. The conceptual framework presented here provides another tool for the researcher in assessing the utility of biological markers in exposure assessment and epidemiology.     

Effect of exposure to evening light on sleep initiation in the elderly: A longitudinal analysis for repeated measurements in home settings

Epidemiologic data have demonstrated associations of sleep-onset insomnia with a variety of diseases, including depression, dementia, diabetes and cardiovascular diseases. Sleep initiation is controlled by the suprachiasmatic nucleus of the hypothalamus and endogenous melatonin, both of which are influenced by environmental light. Exposure to evening light is hypothesized to cause circadian phase delay and melatonin suppression before bedtime, resulting in circadian misalignment and sleep-onset insomnia; however, whether exposure to evening light disturbs sleep initiation in home settings remains unclear. In this longitudinal analysis of 192 elderly individuals (mean age: 69.9 years), we measured evening light exposure and sleep-onset latency for 4 days using a wrist actigraph incorporating a light meter and an accelerometer. Mixed-effect linear regression analysis for repeated measurements was used to evaluate the effect of evening light exposure on subsequent sleep-onset latency. The median intensity of evening light exposure and the median sleep-onset latency were 27.3?lux (interquartile range, 17.9–43.4) and 17?min (interquartile range, 7–33), respectively. Univariate models showed significant associations between sleep-onset latency and age, gender, daytime physical activity, in-bed time, day length and average intensity of evening and nighttime light exposures. In a multivariate model, log-transformed average intensity of evening light exposure was significantly associated with log-transformed sleep-onset latency independent of the former potential confounding factors (regression coefficient, 0.133; 95% CI, 0.020–0.247; p?=?0.021). Day length and nighttime light exposure were also significantly associated with log-transformed sleep-onset latency (p?=?0.001 and p?<?0.001, respectively). In conclusion, exposure to evening light in home setting prolongs subsequent sleep-onset latency in the elderly.     

Melatonin in the unicellular Tetrahymena pyriformis: effects of different lighting conditions

Melatonin content in the cellular fraction and medium of Tetrahymena pyriformis GL cultures was measured at different time points of light and dark exposures. Tetrahymena produced, stored and secreted immunoreactive melatonin, which in displacement and HPLC studies, behaved like synthetic melatonin. There was not a continuous secretion of melatonin produced by the cells. In contrast to this, storage of melatonin was observed, which was more expressed in dark conditions. Prolonged light exposure suppressed melatonin production and secretion alike, however it did not block it completely.     

Repetitive exposures with simian/human immunodeficiency viruses: strategy to study HIV pre-clinical interventions in non-human primates

BACKGROUND: Non-human primate models for human immunodeficiency virus (HIV) infection represent a valuable pre-clinical tool to evaluate interventions (e.g., topical microbicides, vaccines, and chemoprophylaxis) designed to prevent transmission or slow disease progression after infection. Standard transmission models use a single-dose exposure with high, non-physiologic levels of virus to approach 100% infection rates of control animals. These single-exposure models do not represent the circumstances of mucosal HIV transmission in humans and may result in misleading data with regard to intervention efficacy. Therefore, we have developed a repetitive mucosal exposure model using doses of virus that better reflects human exposures. METHODS: The virus used for these evaluations was simian-human immunodeficiency virus [SHIVSF162P3 (R5-using, subtype B HIV-1 envelope)] and the virus dose used (approximately 10(5)-10(6) viral particle equivalents or approximately 10 tissue culture infectious doses per exposure) approximates viral loads observed in the semen during acute HIV-1 infection. Using the repeated mucosal exposure approach, we have evaluated a candidate vaginal microbicide (cellulose acetate phthalate, CAP) given 15 minutes prior to each weekly virus exposure. Pig-tailed macaques were exposed weekly by vaginal inoculations with and without microbicide until systemic viral RNA was detected. RESULTS: Groups of na?ve control monkeys were infected after an average of three to four exposures for the vaginal route of inoculation. Data from the first application of this monkey model to evaluate the topical microbicide CAP suggested that protection from SHIV infection was possible with three of four CAP-treated monkeys remaining uninfected after 12 exposures (P = 0.015). CAP efficacy was markedly improved from 66% in a previous single-dose virus exposure study to 92% in this repeated exposure system. CONCLUSIONS: Our experience with using repetitive virus exposures to study topical microbicides and the findings to date from this study provides a basis to refine monkey models to more closely resemble human exposure during HIV transmission. This model may be highly relevant to pre-clinical evaluation for a variety of therapeutic interventions which is discussed here.     

Quantitative biomechanical workplace exposure measures: Distribution centers

Physical work exposure characteristics assessed in most previous epidemiologic studies have been described mostly in gross categorical terms (e.g. heavy work, lifting and forceful movements, etc.) and have resulted in relatively moderate associations with low back pain risk. We hypothesized that it was necessary to characterize work demands in a much more quantitative fashion so that the precise biomechanically meaningful measures of exposure were available for risk analysis. In this study, we used sophisticated instrumentation to continuously document 390 physical exposures during lifting (in four types of distribution centers) throughout work. This study profiles these exposures and shows how these exposures vary as a function of the type of distribution center and compares the exposures to (previously documented) manufacturing exposures. Static load and load moment measures were found to greatly under-represent true (dynamic) load and load moment exposures to workers. Lift durations averaged 11–12% of the cycle time in distribution environments. This study indicates that distribution workers are commonly exposed to greater extreme loads and move much more rapidly than manufacturing employees. The information provided here can serve as a basis for low back pain risk assessments.     

Guidance for exposure design of human studies addressing health risk evaluations of mobile phones

Conflicting results have recently emerged from human provocation studies that addressed the possible health hazards of radio frequency (RF) field exposure from mobile phones. Different findings may have resulted from exposures that are poorly defined and difficult to compare. The aim of this study was to develop guidelines to facilitate the development of exposure systems for human volunteer studies which lead to reproducible results and which provide maximum relevance with respect to the assessment of the safety of mobile technology. The most important exposure parameters are discussed such as the signal, field distribution, and field strength, as well as the minimum requirements for the setup and dosimetry.