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Network-Based Assessment of Environmental Neurotoxicants Using High-Throughput Transcriptomics in Zebrafish Embryos

  • Pu Xia
  • , Pingping Wang
  • , Shengnan Liu
  • , Ying Peng
  • , Xiao Gou
  • , Haoyue Tan
  • , Jing Guo
  • , Wei Shi
  • , John K. Colbourne
  • , John P. Giesy
  • , Xiaowei Zhang*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Omics-based evaluation of neurotoxicants is challenged by limited ability to translate molecular signals into phenotypic effects. We developed an Adverse Outcome Pathway (AOP) network-based framework to interpret concentration-dependent transcriptomics in zebrafish embryos in relation to behavioral outcomes. An annotation of key events (KEs) to zebrafish molecular pathways was curated to enable mapping of zebrafish transcriptomics to the AOP network. Concentration-dependent transcriptomics of 24 environmental chemicals identified concentration-responsive KEs (CRKEs) that differentiated neurotoxic from non-neurotoxic compounds. Transcriptomic points of departure (tPOD) were significantly correlated with behavioral apical POD (aPOD) (R2 = 0.539, P < 0.01), indicating the potential for predicting tPOD from transcriptomics. Time- and concentration-dependent transcriptomics of five model chemicals identified 12 time-responsive KEs (TRKEs) across four developmental stages. Partial least-squares regression integrating neurotoxicity-relevant CRKEs and TRKEs showed the best performance to estimate aPOD (slope = 0.70, R2 = 0.64, RMSE = 0.9, P = 1.30 × 10–5). External validation using published fish transcriptomics data showed that estimated aPOD values from 8 of 14 chemicals were within 1 order of magnitude of measured aPOD. The findings support AOP network-guided omics analysis as a promising approach for quantitative neurotoxicity assessment, contributing to the use of omics into new approach methodologies (NAMs).
Original languageEnglish
Pages (from-to)8326–8338
Number of pages13
JournalEnvironmental Science and Technology
Volume60
Issue number11
Early online date30 Jan 2026
DOIs
Publication statusPublished - 24 Mar 2026

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