Quantitative AOP based teratogenicity prediction for mixtures of azole fungicides

Abstract Exposure of embryos to mixtures of environmental chemicals can result in congenital malformations. Mixture experiments can provide an indication of the joint effects of substances, but it is practically infeasible to test all possible combinations. The development of mechanistic approaches and integrated models able to predict the effects of mixtures from the concentrations of their individual components, are crucial to assess mixtures associated risks. Azole fungicides can induce craniofacial defects, both after in utero and in vitro exposure. Results obtained in vitro have shown a significant enhancement of teratogenic effects after co-exposure to azoles in comparison to the single exposures. In this project, we evaluated the hypothesis that those molecules concur to imbalance the retinoic acid pathway in specific responsive embryonic tissues. We developed a quantitative adverse outcome pathway for craniofacial malformations, able to simulate the formation of the physiological retinoic acid gradient in the rat embryo hindbrain and its perturbation after exposure to cyproconazole, flusilazole, triadimefon and to their binary mixtures. The underlying system biology model was calibrated using in vitro data and is reasonably predictive of mixtures’ effects for those azoles, thereby confirming the plausibility of the hypothesized pathogenic pathway. This quantitative AOP could have mechanistic or predictive applications in pesticides risk assessment.