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. Highlights

Prediction and Characterization of CYP3A4-mediated Metabolisms of Azole Fungicides: an Application of the Fused-grid Template* system

“…Imidazole and triazole fungicides are used as clinical medicines and pesticides. These chemicals influence sterol biosyntheses [1][2][3] and also retinoic acid metabolisms 4,5) , which may be associated with the adverse outcomes [6][7][8] . These fungicides showed broadened biological half-lives in experimental animals and humans.…”

Quantitative adverse outcome pathway (qAOP) models for toxicity prediction

“…Likewise, Doering et al (2018) investigated the activation of the aryl hydrocarbon receptor leading to early life stage mortality and validated the resulting qAOP model with empirical evidence. An integration of in silico, in vitro and in vivo data was employed to model the teratogenicity of single and mixture azole fungicides by Battistoni et al (2019). At the same time, not all quantified AOPs accounted for both dose-and time-scales.…”

“…The qAOPs of Muller et al (2015), Hassan et al (2017), andForan et al (2019) were quantified using purely mathematical equations. Battistoni et al (2019) developed a multistage dose-response model applying a Bayesian statistical analysis. Besides empirical dose-response, systems biology models were used as a quantitative approach by Battistoni et al (2019) and Zgheib et al (2019).…”

The use of adverse outcome pathways in the safety evaluation of food additives

“…the adverse outcome). This would require the development and use of quantitative, not only qualitative, AOPs for systemic toxic endpoints, as described recently by Perkins et al (2019), Zgheib et al (2019), and Battistoni et al (2019). Moreover, points-of-departure derived from in vitro bioassays reflecting KEs in an AOP cannot directly be converted into health-based reference values.…”