Abstract
There are many types of biomarkers; the two common ones are biomarkers of exposure and biomarkers of effect. The utility of a biomarker for estimating exposures or predicting risks depends on the strength of the correlation between biomarker concentrations and exposure/effects. In the current study, a combined exposure and physiologically-based pharmacokinetic/pharmacodynamic (PBPK/PD) model of carbaryl was used to demonstrate the use of computational modeling for providing insight into the selection of biomarkers for different purposes. The Cumulative and Aggregate Risk Evaluation System (CARES) was used to generate exposure profiles, including magnitude and timing, for use as inputs to the PBPK/PD model. The PBPK/PD model was then used to predict blood concentrations of carbaryl and urine concentrations of its principal metabolite, 1-naphthol (1-N), as biomarkers of exposure. The PBPK/PD model also predicted acetylcholinesterase (AChE) inhibition in red blood cells (RBC) as a biomarker of effect. The correlations of these simulated biomarker concentrations with intake doses or brain AChE inhibition (as a surrogate of effects) were analyzed using a linear regression model. Results showed that 1-N in urine is a better biomarker of exposure than carbaryl in blood, and that 1-N in urine is correlated with the dose averaged over the last 2 days of the simulation. They also showed that RBC AChE inhibition is an appropriate biomarker of effect. This computational approach can be applied to a wide variety of chemicals to facilitate quantitative analysis of biomarker utility.
Highlights
A biomarker is a substance that can be measured in an accessible biological sample and is correlated to some metric or condition of interest in the body
The physiologically-based pharmacokinetic/pharmacodynamic (PBPK/PD) model for carbaryl describes the disposition of carbaryl and 1-N, the binding of carbaryl to cholinesterases in blood and brain, and the urinary excretion of 1-N
(B) Exposure doses averaged over the past week. (C) Exposure dose averaged over the 24 h prior to sampling. (D) Exposure dose averaged over the past 2 days
Summary
A biomarker is a substance that can be measured in an accessible biological sample and is correlated to some metric or condition of interest in the body. “Biomarkers of exposure” are markers that infer exposures to xenobiotics. They may be the parent chemical itself, a metabolite, or an endogenous substance; at minimum, the marker must exhibit a predictable relationship in response to exposure (USEPA, 2014). In some cases, this predictable relationship is strong enough to reconstruct exposures from measured biomarker concentrations. “Biomarkers of effect” are markers that are either known to be directly associated with specific adverse outcomes (e.g., cholinergic poisoning, Kim et al, 2010; Marsillach et al, 2011), or to be empirically associated with particular systemic effects (e.g., oxidative stress, Peluso et al, 2013; Zhang et al, 2013)
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