Background

Humans and wildlife are continuously exposed to chemical mixtures. These mixtures vary in composition but typically contain hundreds of micropollutants at low concentrations. As it is not feasible to measure the toxicity of all possibly occurring mixtures, there is a need to predict mixture toxicity. Two models, Concentration Addition (CA) and Independent Action (IA), have been applied to estimate mixture toxicity. Here, we compared measured with predicted toxicity of nine mixtures designed from 15 environmentally relevant substances in zebrafish embryos to investigate the usability of these models for predicting phenotypic effects in a whole organism short term acute assay.

Results

In total, we compared 177 toxicity values derived from 31 exposure scenarios with their predicted counterparts. Our results show that mixture toxicity was either correctly estimated (86%) by the prediction window, the concentration-effect space that is spanned between both models, or was underestimated with both models (14%). The CA model correctly predicted the measured mixture toxicity in 100% of cases when a prediction deviation factor of 2.5 was allowed. However, prediction accuracy of mixture toxicity prediction was dependent on exposure duration and mixture potency. The CA model showed highest prediction quality for long-term exposure with highly potent mixtures, respectively, whereas IA proved to be more accurate for short-term exposure with less potent mixtures. Obtained mixture concentration–response curves were steep and indicated the occurrence of remarkable combined effects as mixture constituents were applied at concentrations below their respective individual effect threshold in 90% of all investigated cases.

Conclusions

Experimental factors, such as exposure duration or mixture potency, influence the prediction accuracy of both inspected models. The CA model showed highest prediction accuracy even for a set of diverse mixtures and various exposure conditions. However, the prediction window served as the most robust predicator to estimate mixture toxicity. Overall, our results demonstrate the importance of considering mixture toxicity in risk assessment schemes and give guidance for future experiment design regarding mixture toxicity investigations.

中文翻译：

---

斑马鱼胚胎中的混合物毒性分析：时间和浓度分辨的混合物效应预测性研究

背景

人类和野生动植物不断暴露于化学混合物中。这些混合物的成分不同，但通常包含数百种低浓度的微污染物。由于无法测量所有可能存在的混合物的毒性，因此需要预测混合物的毒性。浓度增加（CA）和独立作用（IA）这两种模型已用于估计混合物毒性。在这里，我们比较了从15种与环境有关的物质设计的9种混合物在斑马鱼胚胎中的预测毒性与预期毒性的关系，以研究这些模型在整个生物短期急性试验中预测表型效应的可用性。

结果

总的来说，我们比较了31种暴露情况下的177种毒性值与预期的对应值。我们的结果表明，通过预测窗口可以正确估计混合物毒性（86％），这两个模型之间都存在或两个模型都被低估的浓度效应空间（14％）。当允许预测偏差因子为2.5时，CA模型可正确预测100％的情况下测得的混合物毒性。但是，混合物毒性预测的预测准确性取决于暴露时间和混合物效力。CA模型分别显示了对强效混合物长期暴露的最高预测质量，而IA被证明对强效混合物短期暴露更准确。所获得的混合物浓度-响应曲线陡峭，表明在所有调查病例中有90％的混合物组分以低于其各自效应阈值的浓度施用时，出现了显着的联合效应。

结论

实验因素（例如暴露时间或混合物效力）会影响两个检查模型的预测准确性。即使对于一组不同的混合物和各种暴露条件，CA模型也显示出最高的预测准确性。但是，预测窗口是估计混合物毒性的最可靠的预测器。总体而言，我们的结果证明了在风险评估方案中考虑混合物毒性的重要性，并为混合物毒性研究的未来实验设计提供了指导。