Johnson G E, Soeteman-Hernández L G, Gollapudi B B, Bodger O G, Dearfield K L, Heflich R H, Hixon J G, Lovell D P, MacGregor J T, Pottenger L H, Thompson C M, Abraham L, Thybaud V, Tanir J Y, Zeiger E, van Benthem J, White P A
Institute of Life Science, College of Medicine, Swansea University, Swansea, Wales, United Kingdom.
Environ Mol Mutagen. 2014 Oct;55(8):609-23. doi: 10.1002/em.21870. Epub 2014 May 6.
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.
传统上，遗传毒理学数据一直用于危害的定性评估，而非定量评估。作为我们早期分析甲磺酸乙酯（EMS）和甲磺酸甲酯（MMS）剂量反应数据报告的延续（Gollapudi等人，2013年），在此我们展示了对1-乙基-1-亚硝基脲（ENU）和1-甲基-1-亚硝基脲（MNU）剂量反应数据的分析，以及确定遗传毒性起始点（PoD）指标的其他方法。我们之前描述了确定遗传毒性终点的未观察到遗传毒性效应水平（NOGEL）、断点剂量（BPD；先前称为Td）和基准剂量（BMD10）的方法。在本研究中，我们采用这些方法以及一种新方法来确定非线性斜率转变剂量（STD），并采用替代方法来确定BPD和BMD，以分析一系列体外和体内终点的9个ENU数据集和22个MNU数据集。对于大多数基因突变和染色体损伤研究，NOGEL、BMDL10和BMDL1SD PoD指标可以很容易地计算出来；然而，由于数据限制和基础统计方法的约束，BPD和STD并不总是能够得出。BMDL10值通常低于其他PoD，并且BMDL10值的分布产生了最低的PoD中位数。我们的观察结果表明，在本研究中调查的方法中，BMD方法是定量描述遗传毒理学数据的首选PoD。一旦通过这种方法计算出遗传毒理学PoD，它们就可以用于得出参考剂量和暴露边际值，这可能有助于评估人类风险和监管决策。
