Assessing author willingness to enter study information into structured data templates as part of the manuscript submission process: A pilot study.

Background: Environmental health and other researchers can benefit from automated or semi-automated summaries of data within published studies as summarizing study methods and results is time and resource intensive. Automated summaries can be designed to identify and extract details of interest pertaining to the study design, population, testing agent/intervention, or outcome (etc.). Much of the data reported across existing publications lack unified structure, standardization and machine-readable formats or may be presented in complex tables which serve as barriers that impede the development of automated data extraction methodologies.As full automation of data extraction seems unlikely soon, encouraging investigators to submit structured summaries of methods and results in standardized formats with meta-data tagging of content may be of value during the publication process. This would produce machine-readable content to facilitate automated data extraction, establish sharable data repositories, help make research data FAIR, and could improve reporting quality. Objectives: A pilot study was conducted to assess the feasibility of asking participants to summarize study methods and results using a structured, web-based data extraction model as a potential workflow that could be implemented during the manuscript submission process. Methods: Eight participants entered study details and data into the Health Assessment Workplace Collaborative (HAWC). Participants were surveyed after the extraction exercise to ascertain 1) whether this extraction exercise will impact their conducting and reporting of future research, 2) the ease of data extraction, including which fields were easiest and relatively more problematic to extract and 3) the amount of time taken to perform data extractions and other related tasks. Investigators then presented participants the potential benefits of providing structured data in the format they were extracting. After this, participants were surveyed about 1) their willingness to provide structured data during the publication process and 2) whether they felt the potential application of structured data entry approaches and their implementation during the journal submission process should continue to be further explored. Conclusions: Routine provision of structured data that summarizes key information from research studies could reduce the amount of effort required for reusing that data in the future, such as in systematic reviews or agency scientific assessments. Our pilot study suggests that directly asking authors to provide that data, via structured templates, may be a viable approach to achieving this: participants were willing to do so, and the overall process was not prohibitively arduous. We also found some support for the hypothesis that use of study templates may have halo benefits in improving the conduct and completeness of reporting of future research. While limitations in the generalizability of our findings mean that the conditions of success of templates cannot be assumed, further research into how such templates might be designed and implemented does seem to have enough chance of success that it ought to be undertaken.

Systematic Evidence Map for Over One Hundred and Fifty Per- and Polyfluoroalkyl Substances (PFAS).

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are a large class of synthetic (man-made) chemicals widely used in consumer products and industrial processes. Thousands of distinct PFAS exist in commerce. The 2019 U.S. Environmental Protection Agency (U.S. EPA) Per- and Polyfluoroalkyl Substances (PFAS) Action Plan outlines a multiprogram national research plan to address the challenge of PFAS. One component of this strategy involves the use of systematic evidence map (SEM) approaches to characterize the evidence base for hundreds of PFAS. OBJECTIVE: SEM methods were used to summarize available epidemiological and animal bioassay evidence for a set of ∼150 PFAS that were prioritized in 2019 by the U.S. EPA's Center for Computational Toxicology and Exposure (CCTE) for in vitro toxicity and toxicokinetic assay testing. METHODS: Systematic review methods were used to identify and screen literature using manual review and machine-learning software. The Populations, Exposures, Comparators, and Outcomes (PECO) criteria were kept broad to identify mammalian animal bioassay and epidemiological studies that could inform human hazard identification. A variety of supplemental content was also tracked, including information on in vitro model systems; exposure measurement-only studies in humans; and absorption, distribution, metabolism, and excretion (ADME). Animal bioassay and epidemiology studies meeting PECO criteria were summarized with respect to study design, and health system(s) were assessed. Because animal bioassay studies with ≥21-d exposure duration (or reproductive/developmental study design) were most useful to CCTE analyses, these studies underwent study evaluation and detailed data extraction. All data extraction is publicly available online as interactive visuals with downloadable metadata. RESULTS: More than 40,000 studies were identified from scientific databases. Screening processes identified 44 animal and 148 epidemiology studies from the peer-reviewed literature and 95 animal and 50 epidemiology studies from gray literature that met PECO criteria. Epidemiological evidence (available for 15 PFAS) mostly assessed the reproductive, endocrine, developmental, metabolic, cardiovascular, and immune systems. Animal evidence (available for 40 PFAS) commonly assessed effects in the reproductive, developmental, urinary, immunological, and hepatic systems. Overall, 45 PFAS had evidence across animal and epidemiology data streams. DISCUSSION: Many of the ∼150 PFAS were data poor. Epidemiological and animal evidence were lacking for most of the PFAS included in our search. By disseminating this information, we hope to facilitate additional assessment work by providing the initial scoping literature survey and identifying key research needs. Future research on data-poor PFAS will help support a more complete understanding of the potential health effects from PFAS exposures. https://doi.org/10.1289/EHP10343.

Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks.

The workshop titled "Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks" was co-organized by the Evidence-based Toxicology Collaboration and the European Food Safety Authority (EFSA) and hosted by EFSA at its headquarters in Parma, Italy on October 2 and 3, 2019. The goal was to explore integration of systematic review with mechanistic evidence evaluation. Participants were invited to work on concrete products to advance the exploration of how evidence-based approaches can support the development and application of adverse outcome pathways (AOP) in chemical risk assessment. The workshop discussions were centered around three related themes: 1) assessing certainty in AOPs, 2) literature-based AOP development, and 3) integrating certainty in AOPs and non-animal evidence into decision frameworks. Several challenges, mostly related to methodology, were identified and largely determined the workshop recommendations. The workshop recommendations included the comparison and potential alignment of processes used to develop AOP and systematic review methodology, including the translation of vocabulary of evidence-based methods to AOP and vice versa, the development and improvement of evidence mapping and text mining methods and tools, as well as a call for a fundamental change in chemical risk and uncertainty assessment methodology if to be conducted based on AOPs and new approach methodologies (NAM). The usefulness of evidence-based approaches for mechanism-based chemical risk assessments was stressed, particularly the potential contribution of the rigor and transparency inherent to such approaches in building stakeholders' trust for implementation of NAM evidence and AOPs into chemical risk assessment.

Health Effects of Naphthalene Exposure: A Systematic Evidence Map and Analysis of Potential Considerations for Dose-Response Evaluation.

BACKGROUND: Naphthalene is a polycyclic aromatic hydrocarbon that has been associated with health effects, including cancer. As the state of the science on naphthalene toxicity continues to evolve, updated toxicity reference value(s) may be required to support human health risk assessment. OBJECTIVES: We present a systematic evidence map of studies that could be used to derive toxicity reference value(s) for naphthalene. METHODS: Human and animal health effect studies and physiologically based pharmacokinetic (PBPK) models were identified from a literature search based on populations, exposures, comparators, and outcomes (PECO) criteria. Human and animal studies meeting PECO criteria were refined to a smaller subset considered most informative for deriving chronic reference value(s), which are preferred for assessing risk to the general public. This subset was evaluated for risk of bias and sensitivity, and the suitability of each study for dose-response analysis was qualitatively assessed. Lowest observed adverse effect levels (LOAELs) were extracted and summarized. Other potentially relevant studies (e.g., mechanistic and toxicokinetic studies) were tracked as supplemental information but not evaluated further. Existing reference values for naphthalene are also summarized. RESULTS: We identified 26 epidemiology studies and 16 animal studies that were considered most informative for further analysis. Eleven PBPK models were identified. The available epidemiology studies generally had significant risk of bias and/or sensitivity concerns and were mostly found to have low suitability for dose-response analysis due to the nature of the exposure measurements. The animal studies had fewer risk of bias and sensitivity concerns and were mostly found to be suitable for dose-response analysis. CONCLUSION: Although both epidemiological and animal studies of naphthalene provide weight of evidence for hazard identification, the available animal studies appear more suitable for reference value derivation. PBPK models and mechanistic and toxicokinetic data can be applied to extrapolate these animal data to humans, considering mode of action and interspecies metabolic differences. https://doi.org/10.1289/EHP7381.

Applying evidence-based methods to the development and use of adverse outcome pathways

The workshop "Application of evidence-based methods to construct mechanistic frameworks for the development and use of non-animal toxicity tests" was organized by the Evidence-based Toxicology Collaboration and hosted by the Grading of Recommendations Assessment, Development and Evaluation Working Group on June 12, 2019. The purpose of the workshop was to bring together international regulatory bodies, risk assessors, academic scientists, and industry to explore how systematic review methods and the adverse outcome pathway framework could be combined to develop and use mechanistic test methods for predicting the toxicity of chemical substances in an evidence-based manner. The meeting covered the history of biological frameworks, the way adverse outcome pathways are currently developed, the basic principles of systematic methodology, including systematic reviews and evidence maps, and assessment of cer­tainty in models, and adverse outcome pathways in particular. Specific topics were discussed via case studies in small break-out groups. The group concluded that adverse outcome pathways provide an important framework to support mechanism-based assessment in environmental health. The process of their development has a few challenges that could be addressed with systematic methods and automation tools. Addressing these challenges will increase the transparency of the evidence behind adverse outcome pathways and the consistency with which they are defined; this in turn will increase their value for supporting public health decisions. It was suggested to explore the details of applying systematic methods to adverse outcome pathway development in a series of case studies and workshops.

Use of study-specific MOE-like estimates to prioritize health effects from chemical exposure for analysis in human health assessments.

There are unique challenges in estimating dose-response with chemicals that are associated with multiple health outcomes and numerous studies. Some studies are more suitable than others for quantitative dose-response analyses. For such chemicals, an efficient method of screening studies and endpoints to identify suitable studies and potentially important health effects for dose-response modeling is valuable. Using inorganic arsenic as a test case, we developed a tiered approach that involves estimating study-specific margin of exposure (MOE)-like unitless ratios for two hypothetical scenarios. These study-specific unitless ratios are derived by dividing the exposure estimated to result in a 20% increase in relative risk over the background exposure (RRE20) by the background exposure, as estimated in two different ways. In our case study illustration, separate study-specific ratios are derived using estimates of United States population background exposure (RRB-US) and the mean study population reference group background exposure (RRB-SP). Systematic review methods were used to identify and evaluate epidemiologic studies, which were categorized based on study design (case-control, cohort, cross-sectional), various study quality criteria specific to dose-response analysis (number of dose groups, exposure ascertainment, exposure uncertainty), and availability of necessary dose-response data. Both case-control and cohort studies were included in the RRB analysis. The RRE20 estimates were derived by modeling effective counts of cases and controls estimated from study-reported adjusted odds ratios and relative risks. Using a broad (but not necessarily comprehensive) set of epidemiologic studies of multiple health outcomes selected for the purposes of illustrating the RRB approach, this test case analysis would suggest that diseases of the circulatory system, bladder cancer, and lung cancer may be arsenic health outcomes that warrant further analysis. This is suggested by the number of datasets from adequate dose-response studies demonstrating an effect with RRBs close to 1 (i.e., RRE20 values close to estimated background arsenic exposure levels).

A Physiologically Based Pharmacokinetic Model for Naphthalene With Inhalation and Skin Routes of Exposure.

Naphthalene, a volatile organic compound present in moth repellants and petroleum-based fuels, has been shown to induce toxicity in mice and rats during chronic inhalation exposures. Although simpler default methods exist for extrapolating toxicity points of departure from animals to humans, using a physiologically based pharmacokinetic (PBPK) model to perform such extrapolations is generally preferred. Confidence in PBPK models increases when they have been validated using both animal and human in vivo pharmacokinetic (PK) data. A published inhalation PBPK model for naphthalene was previously shown to predict rodent PK data well, so we sought to evaluate this model using human PK data. The most reliable human data available come from a controlled skin exposure study, but the inhalation PBPK model does not include a skin exposure route; therefore, we extended the model by incorporating compartments representing the stratum corneum and the viable epidermis and parameters that determine absorption and rate of transport through the skin. The human data revealed measurable blood concentrations of naphthalene present in the subjects prior to skin exposure, so we also introduced a continuous dose-rate parameter to account for these baseline blood concentration levels. We calibrated the three new parameters in the modified PBPK model using data from the controlled skin exposure study but did not modify values for any other parameters. Model predictions then fell within a factor of 2 of most (96%) of the human PK observations, demonstrating that this model can accurately predict internal doses of naphthalene and is thus a viable tool for use in human health risk assessment.

Model averaging methods for the evaluation of dose-response model uncertainty when assessing the suitability of studies for estimating risk.

This paper describes the use of multiple models and model averaging for considering dose-response uncertainties when extrapolating low-dose risk from studies of populations with high levels of exposure. The model averaging approach we applied builds upon innovative methods developed by the U.S. Food and Drug Administration (FDA), principally through the relaxing of model constraints. The relaxing of model constraints allowed us to evaluate model uncertainty using a broader set of model forms and, within the context of model averaging, did not result in the extreme supralinearity that is the primary concern associated with the application of individual unconstrained models. A study of the relationship between inorganic arsenic exposure to a Taiwanese population and potential carcinogenic effects is used to illustrate the approach. We adjusted the reported number of cases from two published prospective cohort studies of bladder and lung cancer in a Taiwanese population to account for potential covariates and less-than-lifetime exposure (for estimating effects on lifetime cancer incidence), used bootstrap methods to estimate the uncertainty surrounding the µg/kg-day inorganic arsenic dose from drinking water and dietary intakes, and fit multiple models weighted by Bayesian Information Criterion to the adjusted incidence and dose data to generate dose-specific mean, 2.5th and 97.5th percentile risk estimates. Widely divergent results from adequate model fits for a broad set of constrained and unconstrained models applied individually and in a model averaging framework suggest that substantial model uncertainty exists in risk extrapolation from estimated doses in the Taiwanese studies to lower doses more relevant to countries like the U.S. that have proportionally lower arsenic intake levels.

Epigenetic Applications in Adverse Outcome Pathways and Environmental Risk Evaluation.

BACKGROUND: The epigenome may be an important interface between environmental chemical exposures and human health. However, the links between epigenetic modifications and health outcomes are often correlative and do not distinguish between cause and effect or common-cause relationships. The Adverse Outcome Pathway (AOP) framework has the potential to demonstrate, by way of an inference- and science-based analysis, the causal relationship between chemical exposures, epigenome, and adverse health outcomes. OBJECTIVE: The objective of this work is to discuss the epigenome as a modifier of exposure effects and risk, perspectives for integrating toxicoepigenetic data into an AOP framework, tools for the exploration of epigenetic toxicity, and integration of AOP-guided epigenetic information into science and risk-assessment processes. DISCUSSION: Organizing epigenetic information into the topology of a qualitative AOP network may help describe how a system will respond to epigenetic modifications caused by environmental chemical exposures. However, understanding the biological plausibility, linking epigenetic effects to short- and long-term health outcomes, and including epigenetic studies in the risk assessment process is met by substantive challenges. These obstacles include understanding the complex range of epigenetic modifications and their combinatorial effects, the large number of environmental chemicals to be tested, and the lack of data that quantitatively evaluate the epigenetic effects of environmental exposure. CONCLUSION: We anticipate that epigenetic information organized into AOP frameworks can be consistently used to support biological plausibility and to identify data gaps that will accelerate the pace at which epigenetic information is applied in chemical evaluation and risk-assessment paradigms. https://doi.org/10.1289/EHP2322.

Using In Vitro High-Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards.

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high-throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline-based meta-regression can be used to integrate data across multiple assay replicates to generate a concentration-response curve. We used this analysis to calculate an in vitro point of departure of 0.751 µM and risk-specific in vitro concentrations of 0.29 µM and 0.28 µM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta-regression, may allow risk assessors to identify points of departure and risk-specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.

Arsenite activates NFκB through induction of C-reactive protein.

C-reactive protein (CRP) is an acute phase protein in humans. Elevated levels of CRP are produced in response to inflammatory cytokines and are associated with atherosclerosis, hypertension, cardiovascular disease and insulin resistance. Exposure to inorganic arsenic, a common environmental toxicant, also produces cardiovascular disorders, namely atherosclerosis and is associated with insulin-resistance. Inorganic arsenic has been shown to contribute to cardiac toxicities through production of reactive oxygen species (ROS) that result in the activation of NFκB. In this study we show that exposure of the hepatic cell line, HepG2, to environmentally relevant levels of arsenite (0.13 to 2 µM) results in elevated CRP expression and secretion. ROS analysis of the samples showed that a minimal amount of ROS are produced by HepG2 cells in response to these concentrations of arsenic. In addition, treatment of FvB mice with 100 ppb sodium arsenite in the drinking water for 6 months starting at weaning age resulted in dramatically higher levels of CRP in both the liver and inner medullary region of the kidney. Further, mouse Inner Medullary Collecting Duct cells (mIMCD-4), a mouse kidney cell line, were stimulated with 10 ng/ml CRP which resulted in activation of NFκB. Pretreatment with 10 nM Y27632, a known Rho-kinase inhibitor, prior to CRP exposure attenuated NFκB activation. These data suggest that arsenic causes the expression and secretion of CRP and that CRP activates NFκB through activation of the Rho-kinase pathway, thereby providing a novel pathway by which arsenic can contribute to metabolic syndrome and cardiovascular disease.

Influence of arsenate and arsenite on signal transduction pathways: an update.

Arsenic has been a recognized contaminant and toxicant, as well as a medicinal compound throughout human history. Populations throughout the world are exposed to arsenic and these exposures have been associated with a number of human cancers. Not much is known about the role of arsenic as a human carcinogen and more recently its role in non-cancerous diseases, such as cardiovascular disease, hypertension and diabetes mellitus have been uncovered. The health effects associated with arsenic are numerous and the association between arsenic exposure and human disease has intensified the search for molecular mechanisms that describe the biological activity of arsenic in humans and leads to the aforementioned disease states. Arsenic poses a human health risk due in part to the regulation of cellular signal transduction pathways and over the last few decades, some cellular mechanisms that account for arsenic toxicity, as well as, signal transduction pathways have been discovered. However, given the ubiquitous nature of arsenic in the environment, making sense of all the data remains a challenge. This review will focus on our knowledge of signal transduction pathways that are regulated by arsenic.