RESUMO
Adverse Outcome Pathways (AOPs) summarize mechanistic understanding of toxicological effects and have, for example, been highlighted as a promising tool to integrate data from novel in vitro and in silico methods into chemical risk assessments. Networks based on AOPs are considered the functional implementation of AOPs, as they are more representative of complex biology. At the same time, there are currently no harmonized approaches to generate AOP networks (AOPNs). Systematic strategies to identify relevant AOPs, and methods to extract and visualize data from the AOP-Wiki, are needed. The aim of this work was to develop a structured search strategy to identify relevant AOPs in the AOP-Wiki, and an automated data-driven workflow to generate AOPNs. The approach was applied on a case study to generate an AOPN focused on the Estrogen, Androgen, Thyroid, and Steroidogenesis (EATS) modalities. A search strategy was developed a priori with search terms based on effect parameters in the ECHA/EFSA Guidance Document on Identification of Endocrine Disruptors. Furthermore, manual curation of the data was performed by screening the contents of each pathway in the AOP-Wiki, excluding irrelevant AOPs. Data were downloaded from the Wiki, and a computational workflow was utilized to automatically process, filter, and format the data for visualization. This study presents an approach to structured searches of AOPs in the AOP-Wiki coupled to an automated data-driven workflow for generating AOPNs. In addition, the case study presented here provides a map of the contents of the AOP-Wiki related to the EATS-modalities, and a basis for further research, for example, on integrating mechanistic data from novel methods and exploring mechanism-based approaches to identify endocrine disruptors (EDs). The computational approach is freely available as an R-script, and currently allows for the (re)-generation and filtering of new AOP networks based on data from the AOP-Wiki and a list of relevant AOPs used for filtering.
RESUMO
Endocrine disruptors (EDs) are chemical substances that interfere with the endocrine system, adversely affecting human health and environment. Legislation with aim to eliminate and ban EDs have been introduced in EU, but the identification of EDs remains challenging and crucial step towards regulation and risk management. A guidance for ED assessment has been recently established for pesticides and biocides in the EU, which heavily relies on traditional toxicological testing in vivo. Most notably lacking mechanistic methods for some ED modalities and not covering many other modalities that might be affected by EDs. In this project, we focus on the ED assessment according to the valid legislation and explore the possibility to employ alternative methods to bolster the mechanistic understanding of the ED effects and eventually decrease the need for in vivo testing. We selected a well-studied industrial chemical perfluorooctanesulfonic acid (PFOS) to be a model compound in a case study for ED assessment where the EU criteria were applied in the frame of human health risk assessment with focus on thyroid disruption and developmental neurotoxicity. A systematic literature review has been conducted for these effects (Scopus, Pubmed, Embase), and relevant studies were selected by title/abstract screening (RAYYAN) and full-text examination. Selected studies were assessed for reliability (SciRAP), and all relevant data were extracted into a database and assessed by Weight of Evidence (WoE) approach. The initial analysis showed potential endocrine adverse effects and endocrine activity, meeting the ED criteria. The use of mechanistic and alternative methods enhanced the outcomes of WoE assessment. Also, the study provides a great hands-on experience with the most up-to-date development in the area of risk assessment and EDs.