doi:10.1016/j.yrtph.2004.09.006 
Copyright © 2004 Elsevier Inc. All rights reserved.
Dose–response modeling of in vivo genotoxicity data for use in risk assessment: some approaches illustrated by an analysis of acrylamide
Bruce Allena, 
, 
, Errol Zeigerb, Greg Lawrencec, Marvin Friedmand and Annette Shippc
aEnviron Health Sciences Institute, 101 Corbin Hill Circle, Chapel Hill, NC 27514, USA
bErrol Zeiger Consulting, 800 Indian Springs Road, Chapel Hill, NC, 27514, USA
cEnviron Health Sciences Institute, 602 E. Georgia Avenue, Ruston, LA 71270, USA
dSNF Floerger, 2932 Bayhead Run, Oveido, FL 32765, USA
Received 3 June 2004.
Available online 8 December 2004.
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Abstract
Methods for dose–response modeling of in vivo genotoxicity data are introduced and applied to a case study of acrylamide. Genetic toxicity results are typically summarized as being either positive or negative, with no further consideration of the dose–response patterns that can be estimated from such studies. This analysis explores the use of three modeling approaches: Poisson regression of counts of genetic effects per cell; dynamic modeling of the time-course of micronucleus production and loss as a function of exposure; and categorical regression of sets of genetic toxicity experiments, the results of which are recoded in terms of severities of response. Estimates derived from these models (benchmark doses and predictions of response rates for predetermined doses of interest) are then used to assess the relevance and role of the genetic toxicity results in a risk assessment. With respect to the acrylamide data base, the results suggest that the genetic damage studies do not appear to be consistent or congruent with the thyroid tumor endpoints observed in two long-term bioassays in rats. This suggests that acrylamide’s mechanism of action with respect to production of such tumors may not be genotoxic, and that a cancer risk assessment that applied a linear, no-threshold approach to such endpoints might be inappropriate. Benchmark doses derived from the genetic toxicity data base do not appear to be the critical ones for acrylamide risk assessment. Dose metric and modeling issues associated with the proposed dose–response approach to evaluation of genetic toxicity data are explored, and it is recommended that further advancements of the methodology be developed and employed for optimal use of such data for risk assessment purposes.
Keywords: Acrylamide; Genetic toxicity; Risk assessment; Dose–response; Benchmark dose
Fig. 1. Time-courses of observed and predicted percentages of micronucleated cells following three acrylamide doses. Data are from Cihak and Vontorkova (1990). Experimental observations (circles) are at 24, 48, and 72 h after initial dose, with additional doses at 24 and 48 h after the initial dose. Observations (and corresponding model predictions shown by the solid curves) are for 42.5 (purple), 55 (red), 68 (yellow), and 88 (black) mg/kg doses.
Fig. 2. Time-courses of observed and predicted percentages of micronucleated cells following single acrylamide doses. Data are from Knapp et al. (1988), dark blue circles, at various times after a dose of 136 mg/kg with corresponding model predictions (dark blue solid curve) for that dose. The light blue circles represent the observations from Cihak and Vontorkova (1988) and Adler et al. (1988) following a single dose of 100 mg/kg, with corresponding model predictions shown by the light blue solid curve.
Fig. 3. Time-courses of observed and predicted percentages of micronucleated cells following single acrylamide doses, four dose levels. The observations from Adler et al. (1988) are represented by the colored circles, with corresponding model predictions (solid curves), 24 h after a single dose of acrylamide of 50 (yellow), 75 (red), 100 (purple), and 125 (green) mg/kg.
Fig. 4. Time-courses of observed and predicted percentages of micronucleated cells following two acrylamide doses. Data from Cihak and Vontorkova (1988) show the observed (colored circles) and model predicted (solid curve) percentages of cells with micronuclei following doses of 25 (purple), 50 (red), or 100 (yellow) mg/kg given at time 0 and then again 18 h later.
Fig. 5. Observed and predicted severities of response among the somatic cell genotoxicity studies. (A) The observed and predicted probability of a severity 1 or greater response. The dose metric is daily dose (mg/kg). (B) The observed and predicted probability of a severity 2 or greater response. The dose metric is daily dose (mg/kg).
Fig. 6. Observed and predicted severities of response among the mouse germ cell genotoxicity studies. (A) The observed and predicted probability of a severity 1 or greater response. The dose metric is total dose. (B) The observed and predicted probability of a severity 2 or greater response. The dose metric is total dose.
Fig. 7. Observed and predicted severities of response among the rat germ cell genotoxicity studies. (A) The observed and predicted probability of a severity 1 or greater response. The dose metric is total dose. (B) The observed and predicted probability of a severity 2 or greater response. The dose metric is total dose.
Table 1.
Chromosomal aberration and sister chromatid exchange data and modeling results
Both studies tested male mice. For Backer et al. (1989) the number of effects was estimated from data on the total number of cells examined and the average number of effects per cell.
a Goodness-of-fit was based on the deviance, defined as twice the difference between the saturated log-likelihood and the log-likelihood associated with the fitted model. The deviance was assumed to have a
χ2 distribution with one degree of freedom (four dose groups minus three fitted parameters).
Table 2.
Micronucleus assay data used for analysis
The mean percent presented is the average percentage of polychromatic erythrocytes that had micronuclei, over the total number of animals (N) in each group.
Table 3.
Modeling results for categorical regression analyses
The predicted responses at 2 mg/kg/day for germ cell effects are not given because the dose metric used for categorical regression of those effects was total dose (daily dose in mg/kg multiplied by number of days of dosing). No conversion of total dose estimates to daily dose rates was attempted (see text). The BMD estimates for the somatic cell effects are in units of mg/kg/day; for the germ cell effects they are in units of total mg/kg.
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