A Quantitative Source-to-Outcome Case Study To Demonstrate the Integration of Human Health and Ecological End Points Using the Aggregate Exposure Pathway and Adverse Outcome Pathway Frameworks

The GeoTox Package: Open-source software for connecting spatiotemporal exposure to individual and population-level risk

Background

Comprehensive environmental risk characterization, encompassing physical, chemical, social, ecological, and lifestyle stressors, necessitates innovative approaches to handle the escalating complexity. This is especially true when considering individual and population-level diversity, where the myriad combinations of real-world exposures magnify the combinatoric challenges. The GeoTox framework offers a tractable solution by integrating geospatial exposure data from source-to-outcome in a series of modular, interconnected steps.

Results

Here, we introduce the GeoTox open-source R software package for characterizing the risk of perturbing molecular targets involved in adverse human health outcomes based on exposure to spatially-referenced stressor mixtures. We demonstrate its usage in building computational workflows that incorporate individual and population-level diversity. Our results demonstrate the applicability of GeoTox for individual and population-level risk assessment, highlighting its capacity to capture the complex interplay of environmental stressors on human health.

Conclusions

The GeoTox package represents a significant advancement in environmental risk characterization, providing modular software to facilitate the application and further development of the GeoTox framework for quantifying the relationship between environmental exposures and health outcomes. By integrating geospatial methods with cutting-edge exposure and toxicological frameworks, GeoTox offers a robust tool for assessing individual and population-level risks from environmental stressors. GeoTox is freely available at https://niehs.github.io/GeoTox/.

Quantitative relationships of FAM50B and PTCHD3 methylation with reduced intelligence quotients in school aged children exposed to lead: Evidence from epidemiological and in vitro studies

At present, the application of DNA methylation (DNAm) biomarkers in environmental health risk assessment (EHRA) is more challenging due to the unclearly quantitative relationship between them. We aimed to explore the role of FAM50B and PTCHD3 at the level of signaling pathways, and establish the quantitative relationship between them and children's intelligence quotients (IQs). DNAm of target regions was measured in multiple cell models and was compared with the human population data. Then the dose-response relationships of lead exposure with neurotoxicity and DNAm were established by benchmark dose (BMD) model, followed by potential signaling pathway screening. Results showed that there was a quantitative linear relationship between children's IQs and FAM50B/PTCHD3 DNAm (DNAm between 51.40 % - 78.78 % and 31.41 % - 74.19 % for FAM50B and PTCHD3, respectively), and this relationship was more significant when children's IQs > 90. The receiver operating characteristic (ROC) and calibration curves showed that FAM50B/PTCHD3 DNAm had a satisfying accuracy and consistency in predicting children's IQs, which was confirmed by sensitivity analysis of gender and CpG site grouping data. In cell experiments, there was also a quantitative linear relationship between FAM50B DNAm and reactive oxygen species (ROS) production, which was mediated by PI3K-AKT signaling pathway. In addition, the lead BMD of ROS was close to that of FAM50B DNAm, suggesting that FAM50B DNAm was a suitable biomarker for the risk assessments of adverse outcomes induced by lead. Taken collectively, these results suggest that FAM50B/PTCHD3 can be applied to EHRA and the prevention/intervention of adverse effects of lead on children's IQs.

Daily Exposure to Environmental Volatile Organic Compounds Triggers Oxidative Damage: Evidence from a Large-Scale Survey in China

Volatile organic compounds (VOCs) are ubiquitous environmental pollutants and have been implicated in adverse health outcomes. In this study, concentrations of 11 VOC metabolites (mVOCs) and three oxidative stress biomarkers (8-oxo-7,8-dihydro-2'-deoxyguanosine, 8-oxo-7,8-dihydro-guanosine, and dityrosine) were determined in 205 urine samples collected from 12 cities across mainland China. Urinary ∑11mVOC concentrations ranged from 498 to 1660 ng/mL, with a geometric mean (GM) value of 1070 ng/mL. The factorial analysis revealed that cooking, solvents, and vehicle emissions were the three primary sources of VOC exposure. A significant regional variation was clearly found in ∑11mVOC concentrations across four regions in China, with high urine VOC concentrations found in North and South China (GM: 1450 and 1340 ng/mL). The multiple linear regression model revealed that most mVOCs were significantly positively correlated with three oxidative stress markers (β range: 0.06-0.22). Mixture effect regression showed that isoprene, crotonaldehyde, acrolein, and benzene were the strongest contributors to oxidative stress. Approximately 80% of the participants have HQ values greater than 1.0 for 1,3-butadiene and benzene, suggesting that their exposure doses were close to potential adverse health effects. Our findings provide comprehensive information on human exposure and potential health risks of VOCs in China.

A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target

In the real world, individuals are exposed to chemicals from sources that vary over space and time. However, traditional risk assessments based on in vivo animal studies typically use a chemical-by-chemical approach and apical disease endpoints. New approach methodologies (NAMs) in toxicology, such as in vitro high-throughput (HTS) assays generated in Tox21 and ToxCast, can more readily provide mechanistic chemical hazard information for chemicals with no existing data than in vivo methods. In this paper, we establish a workflow to assess the joint action of 41 modeled ambient chemical exposures in the air from the USA-wide National Air Toxics Assessment by integrating human exposures with hazard data from curated HTS (cHTS) assays to identify counties where exposure to the local chemical mixture may perturb a common biological target. We exemplify this proof-of-concept using CYP1A1 mRNA up-regulation. We first estimate internal exposure and then convert the inhaled concentration to a steady state plasma concentration using physiologically based toxicokinetic modeling parameterized with county-specific information on ages and body weights. We then use the estimated blood plasma concentration and the concentration-response curve from the in vitro cHTS assay to determine the chemical-specific effects of the mixture components. Three mixture modeling methods were used to estimate the joint effect from exposure to the chemical mixture on the activity levels, which were geospatially mapped. Finally, a Monte Carlo uncertainty analysis was performed to quantify the influence of each parameter on the combined effects. This workflow demonstrates how NAMs can be used to predict early-stage biological perturbations that can lead to adverse health outcomes that result from exposure to chemical mixtures. As a result, this work will advance mixture risk assessment and other early events in the effects of chemicals.

Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT-NAMs Symposium

New approach methodologies (NAMs) are emerging chemical safety assessment tools consisting of in vitro and in silico (computational) methodologies intended to reduce, refine, or replace (3R) various in vivo animal testing methods traditionally used for risk assessment. Significant progress has been made toward the adoption of NAMs for human health and environmental toxicity assessment. However, additional efforts are needed to expand their development and their use in regulatory decision making. A virtual symposium was held during the 2021 Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) Smoke Science and Product Technology (SSPT) conference (titled "Advancing New Alternative Methods for Tobacco Harm Reduction"), with the goals of introducing the concepts and potential application of NAMs in the evaluation of potentially reduced-risk (PRR) tobacco products. At the symposium, experts from regulatory agencies, research organizations, and NGOs shared insights on the status of available tools, strengths, limitations, and opportunities in the application of NAMs using case examples from safety assessments of chemicals and tobacco products. Following seven presentations providing background and application of NAMs, a discussion was held where the presenters and audience discussed the outlook for extending the NAMs toxicological applications for tobacco products. The symposium, endorsed by the CORESTA In Vitro Tox Subgroup, Biomarker Subgroup, and NextG Tox Task Force, illustrated common ground and interest in science-based engagement across the scientific community and stakeholders in support of tobacco regulatory science. Highlights of the symposium are summarized in this paper.

Aggregate exposure pathways for microplastics (mpAEP): An evidence-based framework to identify research and regulatory needs

Microplastics as emerging contaminants have been detected from peaks to poles. High concerns on the risks of microplastic pollution to humans and ecosystems have therefore been raised in the past decade. While a large number of studies have been conducted to investigate the environmental levels and toxicity of microplastics, the information generated to support risk assessment is fragmented and the coherence between different types of study is largely lacking. Here we introduced the Aggregate Exposure Pathway (AEP), a conceptual framework originally proposed for chemical exposure assessment, to facilitate organization, visualization and evaluation of existing information generated from microplastic research, and to efficiently identify future knowledge and regulatory needs. A putative microplastic AEP network (mpAEP) was developed to demonstrate the concept and model development strategies. Two mpAEP case studies, with polyethylene (PE) as a prototype, were then presented based on existing environmental exposure data collected from the Changjiang Estuary and the East China Sea (Case I), and the Oslo Fjord (Case II), respectively. Weight of evidence (WoE) assessment of the mpAEPs were performed for evaluating the essentiality, theoretical plausibility, empirical evidence and quantitative understanding of the evidence and relationships in the AEPs. Both cases showed moderate/high WoE to support the strength of the models, whereas also displayed clear knowledge gaps, thus providing guidance for future investigations and regulations. The mpAEP framework introduced herein presents a novel strategy for organizing fragmented information from diverse types of microplastic research, enhancing mechanistic understanding of causal relationships and facilitating the development of quantitative prediction models for research and regulation in the future.

Organizing mechanism-related information on chemical interactions using a framework based on the aggregate exposure and adverse outcome pathways

This paper presents a framework for organizing and accessing mechanistic data on chemical interactions. The framework is designed to support the assessment of risks from combined chemical exposures. The framework covers interactions between chemicals that occur over the entire source-to-outcome continuum including interactions that are studied in the fields of chemical transport, environmental fate, exposure assessment, dosimetry, and individual and population-based adverse outcomes. The framework proposes to organize data using a semantic triple of a chemical (subject), has impact (predicate), and a causal event on the source-to-outcome continuum of a second chemical (object). The location of the causal event on the source-to-outcome continuum and the nature of the impact are used as the basis for a taxonomy of interactions. The approach also builds on concepts from the Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP). The framework proposes the linking of AEPs of multiple chemicals and the AOP networks relevant to those chemicals to form AEP-AOP networks that describe chemical interactions that cannot be characterized using AOP networks alone. Such AEP-AOP networks will aid the construction of workflows for both experimental design and the systematic review or evaluation performed in risk assessments. Finally, the framework is used to link the constructs of existing component-based approaches for mixture toxicology to specific categories in the interaction taxonomy.