A geospatial modeling approach to quantifying risk of exposure to environmental chemical mixtures via a common molecular initiating event
Year: 2021
Type: conference-abstract
Abstract: BACKGROUND AND AIM: The exposome, a measure of all chemical exposures experienced through a lifetime, plays an important role in human health outcomes. Thus, identifying and quantifying lifetime exposure to chemicals present in the environment is important for risk assessment. Linking health outcomes to environmental chemicals exposures is challenging, as real-world exposures involve multiple chemicals and unresolved spatial and temporal distributions. To address these challenges, we propose a geospatially resolved biological target-based risk assessment for exposure to chemical mixtures. This approach models the geospatial distribution of environmental chemicals based on common activation of toxicological adverse outcome pathways (AOPs) as indicated by Tox21 high throughput assays. METHODS: We exemplify this with a USA-wide proof-of-concept that quantifies the predicted geospatial likelihood of thyroid peroxidase (TPO) inhibition. This enzyme is necessary for producing the thyroid hormone T3 and T4, and inhibition has been associated with decreased cognitive function. First, environmental chemicals were identified that both 1) inhibit TPO based on Tox21 data, and 2) were measured by the USGS and EPA in environmental samples (surface water). Next, the geospatial chemical distributions were modeled with combined land-use regression and Gaussian process models. The individual chemical exposure surfaces can be combined into an aggregate risk surface using an unweighted approach or weighted by chemical potency from the toxicological assay concentration-response data. RESULTS:Maps of the aggregate risk surface will identify regions where thyroid peroxidase inhibition is more likely based on combined environmental chemical exposures and chemical potency. CONCLUSIONS:This work will help advance risk assessment methods by providing a method for assessing the geospatial risk of exposure to environmental chemical mixtures and identifying regions with a higher cumulative risk of activating the selected molecular pathways, which may lead to adverse health outcomes. KEYWORDS: Mixtures, External exposome, Exposure assessment-general, risk assessment, Spatial statistics, big data
Source: ISEE Conference Abstracts
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3193956672