Skip to main content
Contact Info
Marvin Martens
Maastricht University

OpenTox 2022 Virtual Conference

Molecular Adverse Outcome Pathways: towards the implementation of transcriptomics data in risk assessments

Adverse Outcome Pathways (AOPs) are designed to provide mechanistic insights into toxicological processes after exposure to a stressor and facilitate the replacement of animal studies with in vitro testing systems. Starting with a Molecular Initiating Event (MIE) and ending with an Adverse Outcome, the sequence of Key Events (KEs) span across biological levels, but the majority of KEs in AOP-Wiki describe molecular and cellular processes. That suggests that established transcriptome-wide studies can be used to validate or measure a multitude of KEs simultaneously and be a goldmine of useful information about cellular responses.

Currently, in toxicology, omics technologies are used primarily for hypothesis generation and are not widely applied in risk assessments of chemicals because of their complexity and lack of consensus on aspects such as standardization, analysis, and interpretation.

To study this, we performed case studies on liver steatosis and mitochondrial complex I inhibition, for which mAOPs were developed and public transcriptomics datasets were selected. Upon extension of the mAOP networks in Cytoscape, we mapped and analysed transcriptomics data, and calculated an enrichment score for individual KEs. Further interpretation of the data was done through the visualisation of the data on the specific molecular pathways.

mAOPs were developed and KEs were linked to the appropriate molecular pathways, allowing detailed exploration of molecular processes with the selected transcriptomics datasets. This has shown us that we can verify the activation of specific MIEs and KEs, and assess progression across the AOP in the steatosis case study. Unexpectedly, the mitochondrial complex I inhibition case study showed only enriched MIE activation at low dose exposure of rotenone, and not with the higher dose.

These case studies have shown that transcriptomics data can be used for identifying potential activation of KEs. However, it is also clear that data is sparse and the process of linking molecular pathways and KEs has its challenges. While proven valuable, pathways linked to KEs appear to show inconsistent levels of activation and should be looked into and refined. More case studies are required to optimize the approaches used for the development and use of mAOPs with transcriptomics datasets.