The adverse outcome pathway (AOP) framework was developed to organize knowledge about the sequence of causally connected key events (KEs) that link molecular-level perturbations that can arise from chemical exposure to a higher-level adverse outcome (AO). As the number of suspected synthetic contributors to human disease grows, AOPs provide a structured approach to elucidate the underlying mechanisms. However, common AOP development methods depend on manual curation, which is labor intensive and time consuming. As such, there are relatively few (< 600) AOPs already developed (compared to 350,000 chemicals in commerce). To help speed up AOP development, we created a workflow for identification of putative AOPs, focused on Parkinson disease as an AO and using insecticides as prototypical stressors. Our method bridges diverse databases (e.g., The Human Proteome Atlas, Bgee) to integrate and structure these data into cause-effect chains that predict AOPs. Insecticide-gene interactions extracted from the Comparative Toxicogenomics Database represent the first KE (molecular initiating event), while Gene Ontology, Reactome, and Monarch terms were statistically linked as the KEs. This pipeline yielded over 20,000 candidate AOPs, ranked by weight of evidence to prioritize toxicity mechanisms for further study. We also integrated known genetic variants implicated in Parkinson disease from DISGENET to inform possible gene-environment interaction. Our findings highlighted a potential role for insecticides in the neuronal apoptotic process and the canonical Wnt/β-catenin pathway via the PRKN gene (a crucial gene in Parkinson disease). The proposed computational pipeline can be extended to other chemicals and adverse outcomes of interest.

Co-authors: Chenyu Shen, Ksenia Groh, Marissa B. Kosnik