Gaskill Stacey J, Bruce Erica D
Department of Environmental Science, Baylor University, One Bear Place #97266, Waco, TX, USA.
Department of Environmental Science, Institute of Biomedical Studies, The Institute of Ecological, Earth, and Environmental Science, Baylor University, One Bear Place #97266, Waco, TX, USA.
Risk Anal. 2016 May;36(5):968-91. doi: 10.1111/risa.12475. Epub 2015 Sep 10.
Polycyclic aromatic hydrocarbons (PAHs) have been labeled contaminants of concern due to their carcinogenic potential, insufficient toxicological data, environmental ubiquity, and inconsistencies in the composition of environmental mixtures. The Environmental Protection Agency is reevaluating current methods for assessing the toxicity of PAHs, including the assumption of toxic additivity in mixtures. This study was aimed at testing mixture interactions through in vitro cell culture experimentation, and modeling the toxicity using quantitative structure-activity relationships (QSAR). Clone-9 rat liver cells were used to analyze cellular proliferation, viability, and genotoxicity of 15 PAHs in single doses and binary mixtures. Tests revealed that many mixtures have nonadditive toxicity, but display varying mixture effects depending on the mixture composition. Many mixtures displayed antagonism, similar to other published studies. QSARs were then developed using the genetic function approximation algorithm to predict toxic activity both in single PAH congeners and in binary mixtures. Effective concentrations inhibiting 50% of the cell populations were modeled, with R(2) = 0.90, 0.99, and 0.84, respectively. The QSAR mixture algorithms were then adjusted to account for the observed mixture interactions as well as the mixture composition (ratios) to assess the feasibility of QSARs for mixtures. Based on these results, toxic addition is improbable and therefore environmental PAH mixtures are likely to see nonadditive responses when complex interactions occur between components. Furthermore, QSAR may be a useful tool to help bridge these data gaps surrounding the assessment of human health risks that are associated with PAH exposures.
多环芳烃(PAHs)因其致癌潜力、毒理学数据不足、在环境中普遍存在以及环境混合物成分不一致等问题,已被列为受关注的污染物。美国环境保护局正在重新评估当前评估PAHs毒性的方法,包括混合物中毒性相加的假设。本研究旨在通过体外细胞培养实验测试混合物的相互作用,并使用定量构效关系(QSAR)对毒性进行建模。使用克隆-9大鼠肝细胞分析15种PAHs单剂量及二元混合物的细胞增殖、活力和遗传毒性。测试表明,许多混合物具有非相加毒性,但根据混合物组成表现出不同的混合效应。许多混合物表现出拮抗作用,与其他已发表的研究相似。然后使用遗传函数近似算法开发QSAR,以预测单个PAH同系物和二元混合物中的毒性活性。对抑制50%细胞群体的有效浓度进行了建模,R(2)分别为0.90、0.99和0.84。然后对QSAR混合物算法进行调整,以考虑观察到的混合物相互作用以及混合物组成(比例),从而评估QSAR用于混合物的可行性。基于这些结果,毒性相加不太可能发生,因此当环境PAH混合物各成分之间发生复杂相互作用时,可能会出现非相加反应。此外,QSAR可能是一个有用的工具,有助于填补围绕与PAH暴露相关的人类健康风险评估的这些数据空白。