Linking Bisphenol S to Adverse Outcome Pathways Using a Combined Text Mining and Systems Biology Approach

Abstract

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. https://doi.org/10.1289/EHP4200

Exposure to New Emerging Bisphenols Among Young Children in Switzerland

“…Adverse outcome pathways (AOP)-based thinking has been proposed as a driver for generating new experimental data for BPA [ 74 ]. AOPs have been proposed recently for BPS [ 78 ] and BPF [ 79 ]. Similarly, applying exposure-based, pathway-oriented approaches (e.g., aggregate exposure pathways, AEPs) [ 80 , 81 ] can support a better characterization of the source-to-outcome continuum by exploring the linkages between exposure sources and pathways with internal exposure information (i.e., biomonitoring data), which can be then linked to AOPs.…”

In silico toxicology: From structure–activity relationships towards deep learning and adverse outcome pathways

“…Therefore, an AOP can be used for all compounds where mechanistic evidence is available. AOPs can either be generated manually by literature review or mechanistic studies or by automated data mining . As mentioned earlier, high throughput screening data is a valuable tool to advance in silico toxicology.…”

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

“…Frequent itemset mining has also been used to decipher relevant information by integrating multiple data sources from HTS studies to establish predictive toxicological models ( Oki et al , 2016 ). A new informatics tool based on artificial intelligence, AOP-helpFinder, has been developed to identify reliable associations between events and a chemical of interest ( Carvaillo et al , 2019 ; Rugard et al , 2020 ). Yet, additional automated tools are required to screen even larger number of texts and datasets with a higher efficiency and relevance.…”