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Updated: Jul 14, 2026

Evaluating Toxicity of Chemicals using a Zebrafish Vibration Startle Response Screening System
Published on: January 12, 2024
Exposure reconstruction for reducing uncertainty in risk assessment: example using MTBE biomarkers and a simple
1Human Exposure and Atmospheric Sciences Division, National Exposure Research Laboratory Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA. pleil@unc.edu
Abstract:
Adverse health risks from environmental agents are generally related to average (long-term) exposures. Because a given individual's contact with a pollutant is highly variable and dependent on activity patterns, local sources and exposure pathways, simple 'snapshot' measurements of surrounding environmental media may not accurately assign the exposure level. Furthermore, susceptibility to adverse effects from contaminants is considered highly variable in the population so that even similar environmental exposure levels may result in differential health outcomes in different individuals. The use of biomarker measurements coupled to knowledge of rates of uptake, metabolism and elimination has been suggested as a remedy for reducing this type of uncertainty. To demonstrate the utility of such an approach, we invoke results from a series of controlled human exposure tests and classical first-order rate kinetic calculations to estimate how well spot measurements of methyl tertiary butyl ether and the primary metabolite, tertiary butyl alcohol, can be expected to predict different hypothetical scenarios of previous exposures. We found that blood and breath biomarker measurements give similar results and that the biological damping effect of the metabolite production gives more stable estimates of previous exposure. We also explore the value of a potential urinary biomarker, 2-hydroxyisobutyrate suggested in the literature. We find that individual biomarker measurements are a valuable tool in reconstruction of previous exposures and that a simple pharmacokinetic model can identify the time frames over which an exogenous chemical and the related chemical biomarker are useful. These techniques could be applied to broader ranges of environmental contaminants to assess cumulative exposure risks if ADME (Absorption, Distribution, Metabolization and Excretion) is understood and systemic biomarkers can be measured.
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