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Published on: August 28, 2019
New Insights into the Visual Toxicity of Organophosphate Esters: An Integrated Quantitative Adverse Outcome Pathway
Ning Gao1, Lanpeng Yang2, Lingyan Zhu1
1Key Laboratory of Pollution Process and Environmental Criteria of Ministry of Education and Tianjin Key Laboratory of Environmental Technology for Complex Trans-Media Pollution, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
Abstract:
Organophosphate esters (OPEs) have been documented to adversely affect visual function, potentially impacting wildlife survival and human health, thereby necessitating a comprehensive risk assessment. Despite the quantitative adverse outcome pathway (qAOP) holding promise for addressing this concern mechanistically, unclear mode of action and inadequate quantitative understanding across biological levels currently impede its development. Herein, we employed an integrated strategy, combining multiomics analyses, targeted bioassays, and modular model-fitting, to develop and validate a qAOP framework for visual toxicity of OPEs, exemplified by tris(2-butoxyethyl) phosphate, triphenyl phosphate, and tris(1,3-dichloro-2-propyl) phosphate. Our results revealed that these OPEs induce visual dysfunction in zebrafish larvae primarily via oxidative stress, then cascade to damaging photoreceptors and retinal structures, ultimately resulting in the disruption of visual behaviors (i.e., decreased optokinetic response, phototaxis, and visual motor response). The qAOP, validated through cross-chemical extrapolation, enabled the prediction for vision-related effects of OPEs within a certain domain. Integrating toxicokinetic modeling could compensate for the uncertainty in qAOP predictions, since adjusting for internal concentrations as inputs significantly enhanced the accuracy and applicability of the predictions. This work contributes to a better understanding of visual toxicity by OPEs and presents a promising paradigm for quantitative risk assessment based on the qAOP framework.
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