An Approach for the Quantitative Consideration of Genetic Polymorphism Data in Chemical Risk Assessment: Examples with Warfarin and Parathion

Abstract

In recent years, a great deal of research has been conducted to identify genetic polymorphisms. One focus has been to characterize variability in metabolic enzyme systems that could impact internal doses of pharmaceuticals or environmental pollutants. Methods are needed for using this metabolic information to estimate the resulting variability in tissue doses associated with chemical exposure. We demonstrate here the use of physiologically based pharmacokinetic (PBPK) modeling in combination with Monte Carlo analysis to incorporate information on polymorphisms into the analysis of toxicokinetic variability. Warfarin and parathion were used as case studies to demonstrate this approach. Our results suggest that polymorphisms in the PON1 gene, that give rise to allelic variants of paraoxonase, which is involved in the metabolism of paraoxon (a metabolite of parathion), make only a minor contribution to the overall variability in paraoxon tissue dose, while polymorphisms in the CYP2C9 gene, which gives rise to allelic variants of the major metabolic enzyme for warfarin, account for a significant portion of the overall variability in (S)-warfarin tissue dose. These analyses were used to estimate chemical-specific adjustment factors (CSAFs) for the human variability in toxicokinetics for both parathion and warfarin. Implications of alternatives in the calculation of CSAFs are explored. Key decision points for applying the PBPK-Monte Carlo approach to evaluate toxicokinetic variability for other chemicals are also discussed.

Genetic Susceptibility and the Setting of Occupational Health Standards

“…Using genetic data may improve understanding of the risks of various levels of exposure. Also, many commentators have identified the importance of using mechanistic data in risk assessments (18,35,37,42), and genetic data are part of the mechanistic information that can be used. Genetic information has also been useful in extrapolating from animals to humans (15,30,53).…”

“…Many (if not all) genes that code for enzymes that metabolize occupationally relevant toxicants are polymorphic (18). A good example of the utility of genotype data in risk assessments is dichloromethane (DCM), a substance widely used in industry for degreasing metal.…”

“…The researchers found that the unit risk was reduced by a factor of more than 100 from previously published risk assessments. The question of the degree to which polymorphisms increase human variability in toxic response, while widely discussed, still is not well characterized (18,22).…”

“…Curran Not all genetic polymorphisms make significant contributions to the variability of the tissue dose of a toxicant. For example, Gentry et al (18) showed that polymorphisms in the PON1 gene that gave risk to allelic variants of paraoxonase, which is involved in the metabolism of paraoxon (a metabolite of the insecticide parathion), make only a minimal contribution to the variability of paraoxon tissue dose. In contrast, polymorphisms in the CYP2C9 gene, which give rise to allelic variants of the major metabolic enzyme for the rodenticide warfarin, account for a significant portion of the overall (s)-warfarin tissue dose.…”

Preclinical Pharmacology of the MDM2 Antagonist Nutlin-3a

“…PBPK model has also been used for special population-such as pediatrics [126][127][128][129][130][131][132][133][134], elderly patients [135,136], pregnant [137][138][139] and lactating [140,141] individuals, and for patients with organ impairments [142]. It has been applied to predict human drug-drug interaction [130,[143][144][145][146][147][148][149][150][151], inter-individual variability [120], and the effect of genetics [152][153][154]. In addition to small molecules, the applications of the PBPK model have also been extended to large molecules [155][156][157][158][159][160][161][162][163] and nano-particles [164][165][166][167].…”