New approach methodologies (NAMs), especially omics-based high-throughput bioassays have been developed rapidly, providing rich mechanistic information such as molecular initiation events (MIEs) and (sub)cellular key events (KEs) in adverse outcome pathways (AOPs). However, how to apply the knowledge of MIEs/KEs to predict adverse outcomes (AOs) induced by chemicals represents a new challenge for computational toxicology. Here, an integrated method named ScoreAOP was developed and evaluated to predict chemicals’ developmental toxicity for zebrafish embryos by integrating four related AOPs and dose-dependent reduced zebrafish transcriptome (RZT). The rules of ScoreAOP included 1) sensitivity of responsive KEs demonstrated by point of departure of KEs (PODKE), 2) evidence reliability and 3) distance between KEs and AOs. Moreover, eleven chemicals with different modes of action (MoAs) were tested to evaluate ScoreAOP. Results showed that eight of the eleven chemicals caused developmental toxicity at tested concentration in apical tests. All the tested chemicals’ developmental defects were predicted using ScoreAOP, whereas eight out of the eleven chemicals predicted by ScoreMIE which was developed to score MIEs disturbed by chemicals based on in vitro bioassays data. Finally, in terms of mechanism explanation, ScoreAOP clustered chemicals with different MoAs while ScoreMIE failed, and ScoreAOP revealed the activation of aryl hydrocarbon receptor (AhR) plays a significant role in dysfunction of cardiovascular system, resulting in zebrafish developmental defects and mortality. In conclusion, ScoreAOP represents a promising approach to apply mechanism information obtained from omics to predict AOs induced by chemicals.

Short-chain chlorinated paraffins (SCCPs) have attracted attention because of their toxicological potential in humans and wildlife at environmentally relevant doses. However, limited information is available regarding mechanistic differences across species in terms of the biological pathways that are impacted by SCCP exposure. Here, a concentration-dependent reduced human transcriptome (RHT) approach was conducted to evaluate 15 SCCPs in HepG2 cells and compared with our previous results using a reduced zebrafish transcriptome (RZT) approach in zebrafish embryos (ZFEs). Generally, SCCPs induced a broader suite of biological pathways in ZFEs than HepG2 cells, and all of the 15 SCCPs were more potent in HepG2 cells compared to ZFEs. Despite these general differences, the transcriptional potency of SCCPs in both model systems showed a significant linear relationship (p = 0.0017, r2 = 0.57), and the average ratios of transcriptional potency for each SCCP in RZT to that in RHT were ∼100,000. C10H14Cl8 was the most potent SCCP, while C10H17Cl5 was the least potent in both ZFEs and HepG2 cells. An adverse outcome pathway network-based analysis demonstrated model-specific responses, such as xenobiotic metabolism that may be mediated by different nuclear receptor-mediated pathways between HepG2 cells (e.g., CAR and AhR activation) and ZFEs (e.g., PXR activation). Moreover, induced transcriptional changes in ZFEs associated with pathways and molecular initiating events (e.g., activation of nicotinic acetylcholine receptor) suggest that SCCPs may disrupt neural development processes. The cross-model comparison of concentration-dependent transcriptomics represents a promising approach to assess and prioritize SCCPs.