Computational estimates of daily aggregate exposure to PFOA/PFOS from 2011 to 2017 using a basic intake model.

BACKGROUND: Human exposure to per- and polyfluoroalkyl substances has been modeled to estimate serum concentrations. Given that the production and use of these compounds have decreased in recent years, especially PFOA and PFOS, and that additional concentration data have become available from the US and other industrialized countries over the past decade, aggregate median intakes of these two compounds were estimated using more recent data. METHODS: Summary statistics from secondary sources were collected, averaged, and mapped for indoor and outdoor air, water, dust, and soil for PFOA and PFOS to estimate exposures for adults and children. European dietary intake estimates were used to estimate daily intake from food. RESULTS: In accordance with decreased concentrations in media, daily intake estimates among adults, i.e., 40 ng/day PFOA and 40 ng/day PFOS, are substantially lower than those reported previously, as are children's estimates of 14 ng/day PFOA and 17 ng/day PFOS. Using a first-order pharmacokinetic model, these results compare favorably to the National Health and Nutrition Examination Survey serum concentration measurements. CONCLUSION: Concomitant blood concentrations support this enhanced estimation approach that captures the decline of PFOA/PFOS serum concentration over a decade.

Demonstrating a systems approach for integrating disparate data streams to inform decisions on children's environmental health.

BACKGROUND: The use of systems science methodologies to understand complex environmental and human health relationships is increasing. Requirements for advanced datasets, models, and expertise limit current application of these approaches by many environmental and public health practitioners. METHODS: A conceptual system-of-systems model was applied for children in North Carolina counties that includes example indicators of children's physical environment (home age, Brownfield sites, Superfund sites), social environment (caregiver's income, education, insurance), and health (low birthweight, asthma, blood lead levels). The web-based Toxicological Prioritization Index (ToxPi) tool was used to normalize the data, rank the resulting vulnerability index, and visualize impacts from each indicator in a county. Hierarchical clustering was used to sort the 100 North Carolina counties into groups based on similar ToxPi model results. The ToxPi charts for each county were also superimposed over a map of percentage county population under age 5 to visualize spatial distribution of vulnerability clusters across the state. RESULTS: Data driven clustering for this systems model suggests 5 groups of counties. One group includes 6 counties with the highest vulnerability scores showing strong influences from all three categories of indicators (social environment, physical environment, and health). A second group contains 15 counties with high vulnerability scores driven by strong influences from home age in the physical environment and poverty in the social environment. A third group is driven by data on Superfund sites in the physical environment. CONCLUSIONS: This analysis demonstrated how systems science principles can be used to synthesize holistic insights for decision making using publicly available data and computational tools, focusing on a children's environmental health example. Where more traditional reductionist approaches can elucidate individual relationships between environmental variables and health, the study of collective, system-wide interactions can enable insights into the factors that contribute to regional vulnerabilities and interventions that better address complex real-world conditions.

The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk.

Exposure to chemicals is influenced by associations between the individual's location and activities as well as demographic and physiological characteristics. Currently, many exposure models simulate individuals by drawing distributions from population-level data or use exposure factors for single individuals. The Residential Population Generator (RPGen) binds US surveys of individuals and households and combines the population with physiological characteristics to create a synthetic population. In general, the model must be supported by internal consistency; i.e., values that could have come from a single individual. In addition, intraindividual variation must be representative of the variation present in the modeled population. This is performed by linking individuals and similar households across income, location, family type, and house type. Physiological data are generated by linking census data to National Health and Nutrition Examination Survey data with a model of interindividual variation of parameters used in toxicokinetic modeling. The final modeled population data parameters include characteristics of the individual's community (region, state, urban or rural), residence (size of property, size of home, number of rooms), demographics (age, ethnicity, income, gender), and physiology (body weight, skin surface area, breathing rate, cardiac output, blood volume, and volumes for body compartments and organs). RPGen output is used to support user-developed chemical exposure models that estimate intraindividual exposure in a desired population. By creating profiles and characteristics that determine exposure, synthetic populations produced by RPGen increases the ability of modelers to identify subgroups potentially vulnerable to chemical exposures. To demonstrate application, RPGen is used to estimate exposure to Toluene in an exposure modeling case example.

Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework.

A critical review of the current state of knowledge of chemical emissions from indoor sources, partitioning among indoor compartments, and the ensuing indoor exposure leads to a proposal for a modular mechanistic framework for predicting human exposure to semivolatile organic compounds (SVOCs). Mechanistically consistent source emission categories include solid, soft, frequent contact, applied, sprayed, and high temperature sources. Environmental compartments are the gas phase, airborne particles, settled dust, indoor surfaces, and clothing. Identified research needs are the development of dynamic emission models for several of the source emission categories and of estimation strategies for critical model parameters. The modular structure of the framework facilitates subsequent inclusion of new knowledge, other chemical classes of indoor pollutants, and additional mechanistic processes relevant to human exposure indoors. The framework may serve as the foundation for developing an open-source community model to better support collaborative research and improve access for application by stakeholders. Combining exposure estimates derived using this framework with toxicity data for different end points and toxicokinetic mechanisms will accelerate chemical risk prioritization, advance effective chemical management decisions, and protect public health.

A comprehensive framework for evaluating the environmental health and safety implications of engineered nanomaterials.

Engineered nanomaterials (ENM) are a growing aspect of the global economy, and their safe and sustainable development, use, and eventual disposal requires the capability to forecast and avoid potential problems. This review provides a framework to evaluate the health and safety implications of ENM releases into the environment, including purposeful releases such as for antimicrobial sprays or nano-enabled pesticides, and inadvertent releases as a consequence of other intended applications. Considerations encompass product life cycles, environmental media, exposed populations, and possible adverse outcomes. This framework is presented as a series of compartmental flow diagrams that serve as a basis to help derive future quantitative predictive models, guide research, and support development of tools for making risk-based decisions. After use, ENM are not expected to remain in their original form due to reactivity and/or propensity for hetero-agglomeration in environmental media. Therefore, emphasis is placed on characterizing ENM as they occur in environmental or biological matrices. In addition, predicting the activity of ENM in the environment is difficult due to the multiple dynamic interactions between the physical/chemical aspects of ENM and similarly complex environmental conditions. Others have proposed the use of simple predictive functional assays as an intermediate step to address the challenge of using physical/chemical properties to predict environmental fate and behavior of ENM. The nodes and interactions of the framework presented here reflect phase transitions that could be targets for development of such assays to estimate kinetic reaction rates and simplify model predictions. Application, refinement, and demonstration of this framework, along with an associated knowledgebase that includes targeted functional assay data, will allow better de novo predictions of potential exposures and adverse outcomes.

Uses of NHANES Biomarker Data for Chemical Risk Assessment: Trends, Challenges, and Opportunities.

BACKGROUND: Each year, the U.S. NHANES measures hundreds of chemical biomarkers in samples from thousands of study participants. These biomarker measurements are used to establish population reference ranges, track exposure trends, identify population subsets with elevated exposures, and prioritize research needs. There is now interest in further utilizing the NHANES data to inform chemical risk assessments. OBJECTIVES: This article highlights a) the extent to which U.S. NHANES chemical biomarker data have been evaluated, b) groups of chemicals that have been studied, c) data analysis approaches and challenges, and d) opportunities for using these data to inform risk assessments. METHODS: A literature search (1999-2013) was performed to identify publications in which U.S. NHANES data were reported. Manual curation identified only the subset of publications that clearly utilized chemical biomarker data. This subset was evaluated for chemical groupings, data analysis approaches, and overall trends. RESULTS: A small percentage of the sampled NHANES-related publications reported on chemical biomarkers (8% yearly average). Of 11 chemical groups, metals/metalloids were most frequently evaluated (49%), followed by pesticides (9%) and environmental phenols (7%). Studies of multiple chemical groups were also common (8%). Publications linking chemical biomarkers to health metrics have increased dramatically in recent years. New studies are addressing challenges related to NHANES data interpretation in health risk contexts. CONCLUSIONS: This article demonstrates growing use of NHANES chemical biomarker data in studies that can impact risk assessments. Best practices for analysis and interpretation must be defined and adopted to allow the full potential of NHANES to be realized.

Data-driven asthma endotypes defined from blood biomarker and gene expression data.

The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels.

Intake to production ratio: a measure of exposure intimacy for manufactured chemicals.

BACKGROUND: Limited data are available to assess human exposure to thousands of chemicals currently in commerce. Information that relates human intake of a chemical to its production and use can help inform understanding of mechanisms and pathways that control exposure and support efforts to protect public health. OBJECTIVES: We introduce the intake-to-production ratio (IPR) as an economy-wide quantitative indicator of the extent to which chemical production results in human exposure. METHODS: The IPR was evaluated as the ratio of two terms: aggregate rate of chemical uptake in a human population (inferred from urinary excretion data) divided by the rate that chemical is produced in or imported into that population's economy. We used biomonitoring data from the U.S. Centers for Disease Control and Prevention along with chemical manufacturing data reported by the U.S. Environmental Protection Agency, as well as other published data, to estimate the IPR for nine chemicals in the United States. Results are reported in units of parts per million, where 1 ppm indicates 1 g of chemical uptake for every million grams of economy-wide use. RESULTS: Estimated IPR values for the studied compounds span many orders of magnitude from a low of 0.6 ppm for bisphenol A to a high of > 180,000 ppm for methyl paraben. Intermediate results were obtained for five phthalates and two chlorinated aromatic compounds: 120 ppm for butyl benzyl phthalate, 670 ppm for di(2-ethylhexyl) phthalate, 760 ppm for di(n-butyl) phthalate, 1,040 ppm for para-dichlorobenzene, 6,800 ppm for di(isobutyl) phthalate, 7,700 ppm for diethyl phthalate, and 8,000-24,000 ppm (range) for triclosan. CONCLUSION: The IPR is well suited as an aggregate metric of exposure intensity for characterizing population-level exposure to synthesized chemicals, particularly those that move fairly rapidly from manufacture to human intake and have relatively stable production and intake rates.

Incorporating exposure information into the toxicological prioritization index decision support framework.

The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to potential for endocrine disruption. However, exposure information is required along with hazard information to prioritize chemicals for further testing. The goal of this analysis is to demonstrate the utility of the ToxPi framework for incorporating exposure information to rank chemicals and improve understanding of key exposure surrogates. The ToxPi tool was applied to common exposure surrogates (i.e., fate parameters, manufacturing volume, and occurrence measurements) and the relationship between resulting rankings and higher-tiered exposure estimates was investigated. As information more directly relevant to human exposure potential is incorporated, relative rank of chemicals changes. Binned ToxPi results are shown to be consistent with chemical priorities based on crude measures of population-level exposure for a limited set of chemicals. However, these bins are not predictive of higher tiered estimates of exposure such as those developed for pesticide registration. Although rankings based on exposure surrogates are used in a variety of contexts, analysis of the relevance of these tools is challenging. The ToxPi framework can be used to gain insight into the factors driving these rankings and aid identification of key exposure metrics. Additional exposure data is required to build confidence in exposure-based chemical prioritization.

Aggregating data for computational toxicology applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System.

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases.

Providing the missing link: the exposure science ontology ExO.

Environmental health information resources lack exposure data required to translate molecular insights, elucidate environmental contributions to diseases, and assess human health and ecological risks. We report development of an Exposure Ontology, ExO, designed to address this information gap by facilitating centralization and integration of exposure data. Major concepts were defined and the ontology drafted and evaluated by a working group of exposure scientists and other ontology and database experts. The resulting major concepts forming the basis for the ontology are "exposure stressor", "exposure receptor", "exposure event", and "exposure outcome". Although design of the first version of ExO focused on human exposure to chemicals, we anticipate expansion by the scientific community to address exposures of human and ecological receptors to the full suite of environmental stressors. Like other widely used ontologies, ExO is intended to link exposure science and diverse environmental health disciplines including toxicology, epidemiology, disease surveillance, and epigenetics.

Informing selection of nanomaterial concentrations for ToxCast in vitro testing based on occupational exposure potential.

BACKGROUND: Little justification is generally provided for selection of in vitro assay testing concentrations for engineered nanomaterials (ENMs). Selection of concentration levels for hazard evaluation based on real-world exposure scenarios is desirable. OBJECTIVES: Our goal was to use estimates of lung deposition after occupational exposure to nanomaterials to recommend in vitro testing concentrations for the U.S. Environmental Protection Agency's ToxCast™ program. Here, we provide testing concentrations for carbon nanotubes (CNTs) and titanium dioxide (TiO2) and silver (Ag) nanoparticles (NPs). METHODS: We reviewed published ENM concentrations measured in air in manufacturing and R&D (research and development) laboratories to identify input levels for estimating ENM mass retained in the human lung using the multiple-path particle dosimetry (MPPD) model. Model input parameters were individually varied to estimate alveolar mass retained for different particle sizes (5-1,000 nm), aerosol concentrations (0.1 and 1 mg/m3), aspect ratios (2, 4, 10, and 167), and exposure durations (24 hr and a working lifetime). The calculated lung surface concentrations were then converted to in vitro solution concentrations. RESULTS: Modeled alveolar mass retained after 24 hr is most affected by activity level and aerosol concentration. Alveolar retention for Ag and TiO2 NPs and CNTs for a working-lifetime (45 years) exposure duration is similar to high-end concentrations (~ 30-400 µg/mL) typical of in vitro testing reported in the literature. CONCLUSIONS: Analyses performed are generally applicable for providing ENM testing concentrations for in vitro hazard screening studies, although further research is needed to improve the approach. Understanding the relationship between potential real-world exposures and in vitro test concentrations will facilitate interpretation of toxicological results.

Estimating toxicity-related biological pathway altering doses for high-throughput chemical risk assessment.

We describe a framework for estimating the human dose at which a chemical significantly alters a biological pathway in vivo, making use of in vitro assay data and an in vitro-derived pharmacokinetic model, coupled with estimates of population variability and uncertainty. The quantity we calculate, the biological pathway altering dose (BPAD), is analogous to current risk assessment metrics in that it combines dose-response data with analysis of uncertainty and population variability to arrive at conservative exposure limits. The analogy is closest when perturbation of a pathway is a key event in the mode of action (MOA) leading to a specified adverse outcome. Because BPADs are derived from relatively inexpensive, high-throughput screening (HTS) in vitro data, this approach can be applied to high-throughput risk assessments (HTRA) for thousands of data-poor environmental chemicals. We envisage the first step of HTRA to be an assessment of in vitro concentration-response relationships across biologically important pathways to derive biological pathway altering concentrations (BPAC). Pharmacokinetic (PK) modeling is then used to estimate the in vivo doses required to achieve the BPACs in the blood at steady state. Uncertainty and variability are incorporated in both the BPAC and the PK parameters and then combined to yield a probability distribution for the dose required to perturb the critical pathway. We finally define the BPADL as the lower confidence bound of this pathway-altering dose. This perspective outlines a framework for using HTRA to estimate BPAD values; provides examples of the use of this approach, including a comparison of BPAD values with published dose-response data from in vivo studies; and discusses challenges and alternative formulations.

Biologically relevant exposure science for 21st century toxicity testing.

High visibility efforts in toxicity testing and computational toxicology including the recent National Research Council of the National Academies (NRC) report, Toxicity Testing in the 21st Century: A Vision and Strategy (NRC, 2007a), raise important research questions and opportunities for the field of exposure science. The authors of the National Academies report (NRC, 2007a) emphasize that population-based data and human exposure information are required at each step of their vision for toxicity testing and that these data will continue to play a critical role in both guiding development and use of the toxicity information. In fact, state-of-the-art exposure science is essential for translation of toxicity data to assess potential for risk to individuals and populations and to inform public health decisions. As we move forward to implement the NRC vision, a transformational change in exposure science is required. Application of a fresh perspective and novel techniques to capture critical determinants at biologically motivated resolution for translation from controlled in vitro systems to the open multifactorial system of real-world human-environment interaction will be critical. Development of an exposure ontology and knowledge base will facilitate extension of network analysis to the individual and population for translating toxicity information and assessing health risk. Such a sea change in exposure science is required to incorporate consideration of lifestage, genetic susceptibility, and interaction of nonchemical stressors for holistic assessment of risk factors associated with complex environmental disease. A new generation of scientific tools has emerged to rapidly measure signals from cells, tissues, and organisms following exposure to chemicals. Investment in 21st century exposure science is now required to fully realize the potential of the NRC vision for toxicity testing.

Predicting residential exposure to phthalate plasticizer emitted from vinyl flooring: a mechanistic analysis.

A two-room model is developed to estimate the emission rate of di-2-ethylhexyl phthalate (DEHP) from vinyl flooring and the evolving gas-phase and adsorbed surface concentrations in a realistic indoor environment. Because the DEHP emission rate measured in a test chamber may be quite different from the emission rate from the same material in the indoor environment the model provides a convenient means to predict emissions and transport in a more realistic setting. Adsorption isotherms for phthalates and plasticizers on interior surfaces, such as carpet, wood, dust, and human skin, are derived from previous field and laboratory studies. Log-linear relationships between equilibrium parameters and chemical vapor pressure are obtained. The predicted indoor air DEHP concentration at steady state is 0.15 microg/m3. Room 1 reaches steady state within about one year, while the adjacent room reaches steady state about three months later. Ventilation rate has a strong influence on DEHP emission rate while total suspended particle concentration has a substantial impact on gas-phase concentration. Exposure to DEHP via inhalation, dermal absorption, and oral ingestion of dust is evaluated. The model clarifies the mechanisms that govern the release of DEHP from vinyl flooring and the subsequent interactions with interior surfaces, airborne particles, dust, and human skin. Although further model development, parameter identification, and model validation are needed, our preliminary model provides a mechanistic framework that elucidates exposure pathways for phthalate plasticizers, and can most likely be adapted to predict emissions and transport of other semivolatile organic compounds, such as brominated flame retardants and biocides, in a residential environment.

Comparing surface residue transfer efficiencies to hands using polar and nonpolar fluorescent tracers.

Transfer of chemicals from contaminated surfaces such as foliage, floors, and furniture is a potentially significant source of both occupational exposure and children's residential exposure. Increased understanding of relevant factors influencing transfers from contaminated surfaces to skin and resulting dermal-loading will reduce uncertainty in exposure assessment. In a previously reported study, a fluorescence imaging system was developed, tested, and used to measure transfer of riboflavin residues from surfaces to hands. Parameters evaluated included surface type, surface loading, contact motion, pressure, duration, and skin condition. Results of the initial study indicated that contact duration and pressure were not significant for the range of values tested, but that there are potentially significant differences in transfer efficiencies of different compounds. In the study reported here, experimental methods were refined and additional transfer data were collected. A second fluorescent tracer, Uvitex OB, with very different physicochemical properties than riboflavin, was also evaluated to better characterize the range of transfers that may be expected for a variety of compounds. Fluorescent tracers were applied individually to surfaces and transfers to skin were measured after repeated hand contacts with the surface. Additional trials were conducted to compare transfer of tracers and co-applied pesticide residues. Results of this study indicate that dermal loadings of both tracers increase through the seventh brief contact. Dermal loading of Uvitex tends to increase at a higher rate than dermal loadings of riboflavin. Measurement of co-applied tracer and pesticide suggest results for these two tracers may provide reasonable bounding estimates of pesticide transfer.