AOP4EUpest: Mapping of pesticides into Adverse Outcome Pathways using a text mining tool.

About the AOP-helpFinder 2 method:

Motivation:Exposure to pesticides may lead to adverse effects for vulnerable groups or high exposure population groups. According to the literature and biomonitoring studies, the main health concerns are neurodevelopment, genotoxic, carcinogenic and disturbances of the endocrine systems that may lead to reproductive and metabolism disorders. Mode of action (MoA) of pesticides are not completely defined. The concept of adverse outcome pathways (AOP) propose a linear representation of mechanistic perturbations at different levels of the biological organization. Even if AOPs are chemical-agnostic, they may help to have a better understanding of the MoA of pesticides when considering them as stressors.

Results: With the increasing amount of scientific literature and the development of biological databases, investigation of putative linkage 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 PubChem database, we used an updated version of the AOP-helpFinder tool, that is based on artificial intelligence. As results, multiple linkages were deciphered between the studied substances and molecular initiating events (MIEs), key events (KEs) and adverse outcomes (AOs).These results can support regulatory assessment for prioritized pesticides, and trigger new epidemiological and experimental studies.

About the AOP-helpFinder 1 method:

Linking Bisphenol S to Adverse Outcome Pathways Using a Combined Text Mining and Systems Biology Approach (Carvaillo et al.)

Background: Available toxicity data can be optimally interpreted if they are integrated using computational approaches such as systems biology modeling. Such approaches are particularly warranted in cases where regulatory decisions have to be made rapidly.
Objectives: The study aims at developing and applying a new integrative computational strategy to identify associations between bisphenol S (BPS), a substitute for bisphenol A (BPA), and components of adverse outcome pathways (AOPs).
Methods: The proposed approach combines a text mining (TM) procedure and integrative systems biology to comprehensively analyze the scientific literature to enrich AOPs related to environmental stressors. First, to identify relevant associations between BPS and different AOP components, a list of abstracts was screened using the developed text-mining tool AOP-helpFinder, which calculates scores based on the graph theory to prioritize the findings. Then, to fill gaps between BPS, biological events, and adverse outcomes (AOs), a systems biology approach was used to integrate information from the AOP-Wiki and ToxCast databases, followed by manual curation of the relevant publications.
Results: Links between BPS and 48 AOP key events (KEs) were identified and scored via 31 references. The main outcomes were related to reproductive health, endocrine disruption, impairments of metabolism, and obesity. We then explicitly analyzed co-mention of the terms BPS and obesity by data integration and manual curation of the full text of the publications. Several molecular and cellular pathways were identified, which allowed the proposal of a biological explanation for the association between BPS and obesity.
Conclusions: By analyzing dispersed information from the literature and databases, our novel approach can identify links between stressors and AOP KEs. The findings associating BPS and obesity illustrate the use of computational tools in predictive toxicology and highlight the relevance of the approach to decision makers assessing substituents to toxic chemicals.