German Federal Institute for Risk Assessment, Dept. Food Safety, Berlin, Germany.
University of Bielefeld, CeBiTec, Bielefeld, Germany.
Toxicology. 2021 Aug;460:152892. doi: 10.1016/j.tox.2021.152892. Epub 2021 Aug 8.
While real-life exposure occurs to complex chemical mixtures, toxicological risk assessment mostly focuses on individual compounds. There is an increasing demand for in vitro tools and strategies for mixture toxicity analysis. Based on a previously established set of hepatotoxicity marker genes, we analyzed mixture effects of non-cytotoxic concentrations of different pesticides in exposure-relevant binary mixtures in human HepaRG hepatocarcinoma cells using targeted transcriptomics. An approach for mixture analysis at the level of a complex endpoint such as a transcript pattern is presented, including mixture design based on relative transcriptomic potencies and similarities. From a mechanistic point of view, goal of the study was to evaluate combinations of chemicals with varying degrees of similarity in order to determine whether differences in mechanisms of action lead to different mixtures effects. Using a model deviation ratio-based approach for assessing mixture effects, it was revealed that most data points are consistent with the assumption of dose addition. A tendency for synergistic effects was only observed at high concentrations of some combinations of the test compounds azoxystrobin, cyproconazole, difenoconazole, propiconazole and thiacloprid, which may not be representative of human real-life exposure. In summary, the findings of our study suggest that, for the pesticide mixtures investigated, risk assessment based on the general assumption of dose addition can be considered sufficiently protective for consumers. The way of data analysis presented in this paper can pave the way for a more comprehensive use of multi-gene expression data in experimental studies related to mixture toxicity.
虽然实际暴露于复杂的化学混合物中，但毒理学风险评估主要侧重于单个化合物。人们对用于混合物毒性分析的体外工具和策略的需求日益增加。基于先前建立的一组肝毒性标记基因，我们使用靶向转录组学分析了人类 HepaRG 肝癌细胞中暴露相关二元混合物中非细胞毒性浓度的不同农药的混合物效应。提出了一种用于复杂终点（如转录模式）混合物分析的方法，包括基于相对转录组效力和相似性的混合物设计。从机制的角度来看，该研究的目标是评估具有不同相似程度的化学品组合，以确定作用机制的差异是否导致不同的混合物效应。使用基于模型偏差比的方法评估混合物效应，结果表明大多数数据点与剂量加和的假设一致。仅在某些测试化合物（肟菌酯、环丙唑醇、烯唑醇、丙环唑和噻虫啉）的高浓度组合中观察到协同作用的趋势，这可能不符合人类实际暴露的情况。总之，本研究的结果表明，对于所研究的农药混合物，基于剂量加和的一般假设进行风险评估可以被认为对消费者具有足够的保护作用。本文中提出的数据分析方法可以为与混合物毒性相关的实验研究中更全面地使用多基因表达数据铺平道路。
