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Effect-based aggregate exposure pathways for tracking mixture potency across the source-to-target site continuum.

Edmond Sanganyado1

  • 1Toxicology Centre, University of Saskatchewan, Saskatoon, SK, S7N 5B3, Canada; School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK S7N 5CN, Canada.

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Summary

This study introduces an effect-based aggregate exposure pathway (AEP) framework using bioanalytical equivalence quotients to link environmental exposures to biological effects. The framework enhances mechanistic mixture risk assessment in the exposome era.

Keywords:
Adverse outcome pathwayAggregate exposure pathwayEnvironmental riskExposomeMixture toxicity

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Area of Science:

  • Environmental Science
  • Toxicology
  • Risk Assessment

Background:

  • Environmental exposures involve complex mixtures and pathways, hindering mechanistic links to biological effects.
  • The aggregate exposure pathway (AEP) framework aims to organize exposure data but faces interoperability challenges.
  • Current methods struggle to quantify mixture activity across diverse exposure states.

Purpose of the Study:

  • To propose an effect-based aggregate exposure pathway (AEP) framework for mechanistic mixture risk assessment.
  • To utilize bioanalytical equivalence quotients for tracking mixture activity across exposure states.
  • To evaluate the framework's utility using a hypothetical contaminated river system.

Main Methods:

  • Constructed two interconnected AEPs with eleven key exposure states for a hypothetical contaminated river.
  • Employed a weight-of-evidence assessment to evaluate linkages between exposure states.
  • Utilized bioanalytical equivalence quotients as potency metrics for mixture activity.

Main Results:

  • Linkages between exposure states were strongest at the source and in environmental media, weakening for internal exposures.
  • Translational relationships showed stronger empirical support in environmental media than in biological matrices.
  • Identified data gaps in extracting complex mixtures and quantifying bioanalytical equivalence quotients in complex matrices.

Conclusions:

  • The proposed effect-based AEP framework offers a quantitative and scalable approach for mixture risk assessment.
  • The framework highlights limitations in current analytical methods for complex environmental and biological samples.
  • This approach advances mechanistic understanding of chemical mixture effects in the exposome era.