AOP4EUpest: mapping of pesticides in adverse outcome pathways using a text mining tool

Florence Jornod (1, 2) , Marylène Rugard (1, 2) , Luc Tamisier (3) , Xavier Coumoul (1, 2) , Helle R Andersen (4) , Robert Barouki (1, 2) , Karine Audouze (1, 2)

1 T3S - UMR_S 1124 - Toxicité environnementale, cibles thérapeutiques, signalisation cellulaire
2 UPCité - Université Paris Cité
3 SPPIN - UMR 8003 - Saints-Pères Paris Institute for Neurosciences
4 SDU - University of Southern Denmark

Motivation: Exposure to pesticides may lead to adverse health effects in human populations, in particular vulnerable groups. The main long-term health concerns are neurodevelopmental disorders, carcinogenicity as well as endocrine disruption possibly leading to reproductive and metabolic disorders. Adverse outcome pathways (AOP) consist in linear representations of mechanistic perturbations at different levels of the biological organization. Although AOPs are chemical-agnostic, they can provide a better understanding of the Mode of Action of pesticides and can support a rational identification of effect markers. Results: With the increasing amount of scientific literature and the development of biological databases, investigation of putative links between pesticides, from various chemical groups and AOPs using the biological events present in the AOP-Wiki database is now feasible. To identify co-occurrence between a specific pesticide and a biological event in scientific abstracts from the PubMed database, we used an updated version of the artificial intelligencebased AOP-helpFinder tool. This allowed us to decipher multiple links between the studied substances and molecular initiating events, key events and adverse outcomes. These results were collected, structured and presented in a web application named AOP4EUpest that can support regulatory assessment of the prioritized pesticides and trigger new epidemiological and experimental studies.

Domaines: Bio-Informatique, Biologie Systémique [q-bio.QM]; Toxicologie

Florence Jornod, Marylène Rugard, Luc Tamisier, Xavier Coumoul, Helle R Andersen, et al.. AOP4EUpest: mapping of pesticides in adverse outcome pathways using a text mining tool. Bioinformatics, 2022, 36 (15), pp.4379 - 4381. ⟨10.1093/bioinformatics/btaa545⟩. ⟨hal-03741270⟩