Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology.

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Assessment of Transcriptomic and Apical Responses of Daphnia magna Exposed to a Polyethylene Microplastic in a 21-d Chronic Study.

There is global concern regarding the fate and effects of microplastics in the environment, particularly in aquatic systems. In the present study, ethylene acrylic acid copolymer particles were evaluated in a chronic toxicity study with the aquatic invertebrate Daphnia magna. The study design included a natural particle control treatment (silica) to differentiate any potential physical effects of a particle from the intrinsic toxicity of the test material. In addition to the standard endpoints of survival, growth, and reproduction, the transcriptomic profiles of control and ethylene acrylic acid copolymer-exposed D. magna were evaluated at the termination of the 21-d toxicity study. No significant effects on D. magna growth, survival, or reproduction were observed in comparison with both particle and untreated control groups. Significant transcriptomic alterations were induced at the highest treatment level of 2.3 × 1012 particles of the ethylene acrylic acid copolymer/L in key pathways linked to central metabolism and energy reserves, oxidative stress, and ovulation and molting, indicating a global transcriptomic response pattern. To put the results in perspective is challenging at this time, because, to date, microplastic environmental monitoring approaches have not been equipped to detect particles in the nanosize range. However, our results indicate that ethylene acrylic acid copolymer microplastics in the upper nanosize range are not expected to adversely affect D. magna growth, survival, or reproductive outcomes at concentrations of up to 1012 particles/L. Environ Toxicol Chem 2020;39:1578-1589. © 2020 SETAC.

Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment.

An important goal in toxicology is the development of new ways to increase the speed, accuracy, and applicability of chemical hazard and risk assessment approaches. A promising route is the integration of in vitro assays with biological pathway information. We examined how the adverse outcome pathway (AOP) framework can be used to develop pathway-based quantitative models useful for regulatory chemical safety assessment. By using AOPs as initial conceptual models and the AOP knowledge base as a source of data on key event relationships, different methods can be applied to develop computational quantitative AOP models (qAOPs) relevant for decision making. A qAOP model may not necessarily have the same structure as the AOP it is based on. Useful AOP modeling methods range from statistical, Bayesian networks, regression, and ordinary differential equations to individual-based models and should be chosen according to the questions being asked and the data available. We discuss the need for toxicokinetic models to provide linkages between exposure and qAOPs, to extrapolate from in vitro to in vivo, and to extrapolate across species. Finally, we identify best practices for modeling and model building and the necessity for transparent and comprehensive documentation to gain confidence in the use of qAOP models and ultimately their use in regulatory applications. Environ Toxicol Chem 2019;38:1850-1865. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Introducing WikiPathways as a Data-Source to Support Adverse Outcome Pathways for Regulatory Risk Assessment of Chemicals and Nanomaterials.

A paradigm shift is taking place in risk assessment to replace animal models, reduce the number of economic resources, and refine the methodologies to test the growing number of chemicals and nanomaterials. Therefore, approaches such as transcriptomics, proteomics, and metabolomics have become valuable tools in toxicological research, and are finding their way into regulatory toxicity. One promising framework to bridge the gap between the molecular-level measurements and risk assessment is the concept of adverse outcome pathways (AOPs). These pathways comprise mechanistic knowledge and connect biological events from a molecular level toward an adverse effect outcome after exposure to a chemical. However, the implementation of omics-based approaches in the AOPs and their acceptance by the risk assessment community is still a challenge. Because the existing modules in the main repository for AOPs, the AOP Knowledge Base (AOP-KB), do not currently allow the integration of omics technologies, additional tools are required for omics-based data analysis and visualization. Here we show how WikiPathways can serve as a supportive tool to make omics data interoperable with the AOP-Wiki, part of the AOP-KB. Manual matching of key events (KEs) indicated that 67% could be linked with molecular pathways. Automatic connection through linkage of identifiers between the databases showed that only 30% of AOP-Wiki chemicals were found on WikiPathways. More loose linkage through gene names in KE and Key Event Relationships descriptions gave an overlap of 70 and 71%, respectively. This shows many opportunities to create more direct connections, for example with extended ontology annotations, improving its interoperability. This interoperability allows the needed integration of omics data linked to the molecular pathways with AOPs. A new AOP Portal on WikiPathways is presented to allow the community of AOP developers to collaborate and populate the molecular pathways that underlie the KEs of AOP-Wiki. We conclude that the integration of WikiPathways and AOP-Wiki will improve risk assessment because omics data will be linked directly to KEs and therefore allow the comprehensive understanding and description of AOPs. To make this assessment reproducible and valid, major changes are needed in both WikiPathways and AOP-Wiki.

A decision analysis framework for estimating the potential hazards for drinking water resources of chemicals used in hydraulic fracturing fluids.

Despite growing concerns over the potential for hydraulic fracturing to impact drinking water resources, there are limited data available to identify chemicals used in hydraulic fracturing fluids that may pose public health concerns. In an effort to explore these potential hazards, a multi-criteria decision analysis (MCDA) framework was employed to analyze and rank selected subsets of these chemicals by integrating data on toxicity, frequency of use, and physicochemical properties that describe transport in water. Data used in this analysis were obtained from publicly available databases compiled by the United States Environmental Protection Agency (EPA) as part of a larger study on the potential impacts of hydraulic fracturing on drinking water. Starting with nationwide hydraulic fracturing chemical usage data from EPA's analysis of the FracFocus Chemical Disclosure Registry 1.0, MCDAs were performed on chemicals that had either noncancer toxicity values (n=37) or cancer-specific toxicity values (n=10). The noncancer MCDA was then repeated for subsets of chemicals reported in three representative states (Texas, n=31; Pennsylvania, n=18; and North Dakota, n=20). Within each MCDA, chemicals received scores based on relative toxicity, relative frequency of use, and physicochemical properties (mobility in water, volatility, persistence). Results show a relative ranking of these chemicals based on hazard potential, and provide preliminary insight into chemicals that may be more likely than others to impact drinking water resources. Comparison of nationwide versus state-specific analyses indicates regional differences in the chemicals that may be of more concern to drinking water resources, although many chemicals were commonly used and received similar overall hazard rankings. Several chemicals highlighted by these MCDAs have been reported in groundwater near areas of hydraulic fracturing activity. This approach is intended as a preliminary analysis, and represents one possible method for integrating data to explore potential public health impacts.

The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions.

BACKGROUND: The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions. OBJECTIVE: Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures. METHODS: New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling. DISCUSSION: NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams. CONCLUSIONS: While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.

Applying comprehensive environmental assessment to research planning for multiwalled carbon nanotubes: Refinements to inform future stakeholder engagement.

Risk assessments and risk management efforts to protect human health and the environment can benefit from early, coordinated research planning by researchers, risk assessors, and risk managers. However, approaches for engaging these and other stakeholders in research planning have not received much attention in the environmental scientific literature. The Comprehensive Environmental Assessment (CEA) approach under development by the United States Environmental Protection Agency (USEPA) is a means to manage complex information and input from diverse stakeholder perspectives on research planning that will ultimately support environmental and human health decision making. The objectives of this article are to 1) describe the outcomes of applying lessons learned from previous CEA applications to planning research on engineered nanomaterial, multiwalled carbon nanotubes (MWCNTs) and 2) discuss new insights and refinements for future efforts to engage stakeholders in research planning for risk assessment and risk management of environmental issues. Although framed in terms of MWCNTs, this discussion is intended to enhance research planning to support assessments for other environmental issues as well. Key insights for research planning include the potential benefits of 1) ensuring that participants have research, risk assessment, and risk management expertise in addition to diverse disciplinary backgrounds; 2) including an early scoping step before rounds of formal ratings; 3) using a familiar numeric scale (e.g., US dollars) versus ordinal rating scales of "importance"; 4) applying virtual communication tools to supplement face-to-face interaction between participants; and 5) refining criteria to guide development of specific, actionable research questions.

Adverse Outcome Pathways for Regulatory Applications: Examination of Four Case Studies With Different Degrees of Completeness and Scientific Confidence.

Adverse outcome pathways (AOPs) offer a pathway-based toxicological framework to support hazard assessment and regulatory decision-making. However, little has been discussed about the scientific confidence needed, or how complete a pathway should be, before use in a specific regulatory application. Here we review four case studies to explore the degree of scientific confidence and extent of completeness (in terms of causal events) that is required for an AOP to be useful for a specific purpose in a regulatory application: (i) Membrane disruption (Narcosis) leading to respiratory failure (low confidence), (ii) Hepatocellular proliferation leading to cancer (partial pathway, moderate confidence), (iii) Covalent binding to proteins leading to skin sensitization (high confidence), and (iv) Aromatase inhibition leading to reproductive dysfunction in fish (high confidence). Partially complete AOPs with unknown molecular initiating events, such as 'Hepatocellular proliferation leading to cancer', were found to be valuable. We demonstrate that scientific confidence in these pathways can be increased though the use of unconventional information (eg, computational identification of potential initiators). AOPs at all levels of confidence can contribute to specific uses. A significant statistical or quantitative relationship between events and/or the adverse outcome relationships is a common characteristic of AOPs, both incomplete and complete, that have specific regulatory uses. For AOPs to be useful in a regulatory context they must be at least as useful as the tools that regulators currently possess, or the techniques currently employed by regulators.

Can data science inform environmental justice and community risk screening for type 2 diabetes?

BACKGROUND: Having the ability to scan the entire country for potential "hotspots" with increased risk of developing chronic diseases due to various environmental, demographic, and genetic susceptibility factors may inform risk management decisions and enable better environmental public health policies. OBJECTIVES: Develop an approach for community-level risk screening focused on identifying potential genetic susceptibility hotpots. METHODS: Our approach combines analyses of phenotype-genotype data, genetic prevalence of single nucleotide polymorphisms, and census/geographic information to estimate census tract-level population attributable risks among various ethnicities and total population for the state of California. RESULTS: We estimate that the rs13266634 single nucleotide polymorphism, a type 2 diabetes susceptibility genotype, has a genetic prevalence of 56.3%, 47.4% and 37.0% in Mexican Mestizo, Caucasian, and Asian populations. Looking at the top quintile for total population attributable risk, 16 California counties have greater than 25% of their population living in hotspots of genetic susceptibility for developing type 2 diabetes due to this single genotypic susceptibility factor. CONCLUSIONS: This study identified counties in California where large portions of the population may bear additional type 2 diabetes risk due to increased genetic prevalence of a susceptibility genotype. This type of screening can easily be extended to include information on environmental contaminants of interest and other related diseases, and potentially enables the rapid identification of potential environmental justice communities. Other potential uses of this approach include problem formulation in support of risk assessments, land use planning, and prioritization of site cleanup and remediation actions.

Systematic Omics Analysis Review (SOAR) tool to support risk assessment.

Environmental health risk assessors are challenged to understand and incorporate new data streams as the field of toxicology continues to adopt new molecular and systems biology technologies. Systematic screening reviews can help risk assessors and assessment teams determine which studies to consider for inclusion in a human health assessment. A tool for systematic reviews should be standardized and transparent in order to consistently determine which studies meet minimum quality criteria prior to performing in-depth analyses of the data. The Systematic Omics Analysis Review (SOAR) tool is focused on assisting risk assessment support teams in performing systematic reviews of transcriptomic studies. SOAR is a spreadsheet tool of 35 objective questions developed by domain experts, focused on transcriptomic microarray studies, and including four main topics: test system, test substance, experimental design, and microarray data. The tool will be used as a guide to identify studies that meet basic published quality criteria, such as those defined by the Minimum Information About a Microarray Experiment standard and the Toxicological Data Reliability Assessment Tool. Seven scientists were recruited to test the tool by using it to independently rate 15 published manuscripts that study chemical exposures with microarrays. Using their feedback, questions were weighted based on importance of the information and a suitability cutoff was set for each of the four topic sections. The final validation resulted in 100% agreement between the users on four separate manuscripts, showing that the SOAR tool may be used to facilitate the standardized and transparent screening of microarray literature for environmental human health risk assessment.

What do the data show? Knowledge map development for comprehensive environmental assessment.

Environmental and human health risk assessments benefit from using data that cross multiple scientific domains. Although individual data points may often be readily understood, the total picture can be difficult to envision. This is especially true with gaps in the data (e.g., with emerging substances such as engineered nanomaterials [ENM]), such that simply presenting only known information can result in a skewed picture. This study describes a method for building knowledge maps (KM) to visually summarize factors relevant to risk assessment in a relatively easy to interpret format. The KMs were created in the context of the comprehensive environmental assessment (CEA) approach for research planning and risk management of environmental contaminants. Recent applications of CEA to emerging substances such as engineered nanomaterials that have numerous data gaps have suggested that a more visually based depiction of information would improve the approach. We developed KM templates as a pilot project, to represent pertinent aspects of conceptual domains, and to highlight gaps in available information for one particular portion of a specific CEA application: the comparison of environmental transport, transformation, and fate of multiwalled carbon nanotubes (MWCNTs) and decabromodiphenyl ether as flame retardants. The results are 3 KM templates representing Physical Properties, Transport, and Transformation. The 3 templates were applied to both substances, resulting in a total of 6 KMs. In addition to presenting the KMs, this paper details the process used to generate them, to aid KM development for other sections of CEA applied to MWCNTs, or to apply the process to new CEA applications.