Use of (Q)SAR genotoxicity predictions and fuzzy multicriteria decision-making for priority ranking of ethoxyquin transformation products. (January 2022) - Rasinger, J.D.; Frenzel, F.; Braeuning, A.; Bernhard, A.; Ørnsrud, R.; Merel, S.; Berntssen, M.H.G.
Graphical abstract: Highlights: Novel workflow for integration of predictions from multiple (Q)SAR models. Inclusion of chemical occurrence data for augmented in silico hazard ranking. Creation of prioritization index for 47 ethoxyquin transformation products (EQTPs). EQTPs recently detected in fish muscle predicted more genotoxic than known EQTPs. Shortlist for prioritization of EQTPs for future Ames genotoxicity testing created. Abstract: Ethoxyquin (EQ; 6-ethoxy-2, 2, 4-trimethyl-1, 2-dihydroquinoline) has been used as an antioxidant in feed for pets and food-producing animals, including farmed fish such as Atlantic salmon. In Europe, the authorization for use of EQ as a feed additive was suspended, due to knowledge gaps concerning the presence and toxicity of EQ transformation products (TPs). Recent analytical studies focusing on the detection of EQ TPs in farmed Atlantic salmon feed and fillets reported the detection of a total of 27 EQ TPs, comprising both known and previously not described EQ TPs. We devised and applied an in silico workflow to rank these EQ TPs according to their genotoxic potential and their occurrence data in Atlantic salmon feed and fillet. Ames genotoxicity predictions were obtained applying a suite of five (quantitative) structure–activity relationship ((Q)SAR) tools, namely VEGA, TEST, LAZAR, Derek Nexus and Sarah Nexus. (Q)SAR Ames genotoxicity predictions were aggregated using fuzzy analytic hierarchy process (fAHP) multicriteria decision-making (MCDM). A priority ranking of EQ TPs was performed based on combining both fAHP ranked (Q)SAR predictions and analytical occurrence data. The applied workflow prioritized four newly identified EQ TPs for further investigation of genotoxicity. The fAHP-based prioritization strategy described here, can easily be applied to other toxicity endpoints and groups of chemicals for priority ranking of compounds of most concern for subsequent experimental and mechanistic toxicology analyses.