Adverse Outcome Pathway Network-Based Chemical Risk Assessment Using High-Throughput Transcriptomics

The lack of adequate toxicity data for the vast majority of chemicals in the environment has spurred the development of high-throughput transcriptomics (HTT) to support pathway-based screening of chemicals. The main challenge is how to decipher molecular response into adverse effects from omics data. This chapter describes an adverse outcome pathway (AOP) network-based approach for chemical screening using HTT in a compendium of human cells. First, the methodology for conducting HTT, concentration-dependent modeling analysis and AOP network analysis is introduced. Two case studies are presented: (1) cross-species comparison of transcriptomic dose-response of short-chain chlorinated paraffins and (2) high-throughput transcriptomics screening of chemicals with various known modes of action using human cells, which demonstrate the ability of HTT for chemical screening, classification and tiered chemical risk assessment by HTT-based AOP network profiles. In summary, the AOP network-based chemical screening provides a rapid and efficient omics-based approach for ranking, clustering and assessment of chemical hazards.