Comparing BMD‐derived genotoxic potency estimations across variants of the transgenic rodent gene mutation assay

Abstract

There is growing interest in quantitative analysis of in vivo genetic toxicity dose‐response data, and use of point‐of‐departure (PoD) metrics such as the benchmark dose (BMD) for human health risk assessment (HHRA). Currently, multiple transgenic rodent (TGR) assay variants, employing different rodent strains and reporter transgenes, are used for the assessment of chemically‐induced genotoxic effects in vivo. However, regulatory issues arise when different PoD values (e.g., lower BMD confidence intervals or BMDLs) are obtained for the same compound across different TGR assay variants. This study therefore employed the BMD approach to examine the ability of different TGR variants to yield comparable genotoxic potency estimates. Review of over 2000 dose‐response datasets identified suitably‐matched dose‐response data for three compounds (ethyl methanesulfonate or EMS, N‐ethyl‐N‐nitrosourea or ENU, and dimethylnitrosamine or DMN) across four commonly‐used murine TGR variants (Muta™Mouse lacZ, Muta™Mouse cII, gpt delta and BigBlue® lacI). Dose‐response analyses provided no conclusive evidence that TGR variant choice significantly influences the derived genotoxic potency estimate. This conclusion was reliant upon taking into account the importance of comparing BMD confidence intervals as opposed to directly comparing PoD values (e.g., comparing BMDLs). Comparisons with earlier works suggested that with respect to potency determination, tissue choice is potentially more important than choice of TGR assay variant. Scoring multiple tissues selected on the basis of supporting toxicokinetic information is therefore recommended. Finally, we used typical within‐group variances to estimate preliminary endpoint‐specific benchmark response (BMR) values across several TGR variants/tissues. We discuss why such values are required for routine use of genetic toxicity PoDs for HHRA. Environ. Mol. Mutagen. 58:632–643, 2017. © 2017 Her Majesty the Queen in Right of Canada. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc.

The 28 + 28 day design is an effective sampling time for analyzing mutant frequencies in rapidly proliferating tissues of MutaMouse animals

“…To ensure consistency of the analyses across the tested substances, the dose–response data were analysed using a five parameter exponential model. BMD-covariate analyses often assume that some model parameters (e.g., c and d for maximum response and log-steepness after axis scaling) are constant across covariate sub-groups (Wills et al 2017 ); this is consistent with the work of (Slob and Setzer 2014 ). The AIC (Akaike Information Criterion) was used for model selection, and post-hoc analyses statistically evaluated the effect of sampling time on any retained parameter.…”

Re: Gi et al. 2018, In vivo positive mutagenicity of 1,4-dioxane and quantitative analysis of its mutagenicity and carcinogenicity in rats, Archives of Toxicology 92:3207–3221

“…This is critically important since it provides a means for determining the precision of the BMD; moreover, it's utility for risk assessment and regulatory decision-making. More specifically, the ratio of the BMDU to the BMDL provides information about the uncertainty of the BMD, which in turn reflects the quality of the underlying dose-response data(Wills et al 2017). Indeed, it has been suggested that the magnitude of uncertainty of the BMD estimate, as indicated by the BMDL to BMDU ratio, should be used as a tool for evaluating the statistical quality of the underlying data(Benford et al 2010), and the utility of a BMDL as a reference PoD for regulatory decision-making(Barlow et al 2006;Benford et al 2010).…”

Transforming early pharmaceutical assessment of genotoxicity: applying statistical learning to a high throughput, multi end point in vitro micronucleus assay

“…aneugens 37 . This is less accepted for a DNA reactive compounds 38 . However, the generation of high content quantitative dose response data, such as that in this assay, could enable safe dose margins or thresholds to be established for compounds using benchmark dose considerations 38 .…”