Derivation of Point of Departure (PoD) Estimates in Genetic Toxicology Studies and Their Potential Applications In Risk Assessment

  • Publication Date :
  • Publication Type : Journal Article
  • Author(s) : Johnson GE, Soeteman‐Hernández LG, Gollapudi BB, Bodger OG, Dearfield KL, Heflich RH, Hixon JG, Lovell DP, MacGregor JT, Pottenger LH, Thompson CM
  • Journal Name : Environmental and Molecular Mutagenesis

Environmental and Molecular Mutagenesis. 2014;55(8):609-623

Abstract: Genetic toxicology data have traditionally been employed for qualitative, rather than quantitative evaluations of hazard. As a continuation of our earlier report that analyzed ethyl methanesulfonate (EMS) and methyl methanesulfonate (MMS) dose–response data (Gollapudi et al., 2013), here we present analyses of 1-ethyl-1-nitrosourea (ENU) and 1-methyl-1-nitrosourea (MNU) dose–response data and additional approaches for the determination of genetic toxicity point-of-departure (PoD) metrics. We previously described methods to determine the no-observed-genotoxic-effect-level (NOGEL), the breakpoint-dose (BPD; previously named Td), and the benchmark dose (BMD10) for genetic toxicity endpoints. In this study we employed those methods, along with a new approach, to determine the non-linear slope-transition-dose (STD), and alternative methods to determine the BPD and BMD, for the analyses of nine ENU and 22 MNU datasets across a range of in vitro and in vivo endpoints. The NOGEL, BMDL10 and BMDL1SD PoD metrics could be readily calculated for most gene mutation and chromosomal damage studies; however, BPDs and STDs could not always be derived due to data limitations and constraints of the underlying statistical methods. The BMDL10 values were often lower than the other PoDs, and the distribution of BMDL10 values produced the lowest median PoD. Our observations indicate that, among the methods investigated in this study, the BMD approach is the preferred PoD for quantitatively describing genetic toxicology data. Once genetic toxicology PoDs are calculated via this approach, they can be used to derive reference doses and margin of exposure values that may be useful for evaluating human risk and regulatory decision making.

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