Adverse Outcome Pathways

Research Article

A data fusion pipeline for generating and enriching Adverse Outcome Pathway descriptions

Penny Nymark1,2, Linda Rieswijk3,4, Friederike Ehrhart3, Nina Jeliazkova5, Georgia Tsiliki6.7, Haralambos Sarimveis6, Chris Evelo3, Vesa Hongisto2, Pekka Kohonen1,2, Egon Willighagen3 Roland Grafström1,2

1Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden, 2Department of Toxicology, Misvik Biology, Turku, Finland, 3Department of Bioinformatics, NUTRIM, Maastricht University, Maastricht, The Netherlands, 4Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, United States, 5IdeaConsult Ltd., Sofia, Bulgaria, 6School of Chemical Engineering, National Technical University of Athens, Athens, Greece, 7Institute for the Management of Information Systems, ATHENA Research and Innovation Centre, Athens, Greece.

PLOS Published: 17 November 2017
DOI: 10.1093/toxsci/kfx252


Increasing amounts of systems toxicology data, including omics results, are becoming publically available and accessible in databases. Data-driven and informatics-tool supported pipeline schemas for fitting such data into Adverse Outcome Pathway (AOP) descriptions could potentially aid the development of non-animal based hazard and risk assessment methods. We devised a six-step workflow that integrated diverse types of toxicology data into a novel AOP scheme for pulmonary fibrosis.

Mining of literature references and diverse data sources covering previous pathway descriptions and molecular results were coupled in a stepwise manner with informatics tools applications that enabled gene linkage and pathway identification in molecular interaction maps.

Ultimately, a network of functional elements coupled 64 pulmonary fibrosis-associated genes into a novel, open-source AOP-linked molecular pathway, now available for commenting and improvements in WikiPathways (WP3624).

Applying in silico-based knowledge extraction and modeling, the pipeline enabled screening and fusion of many different complex data types, including the integration of omics results.

Overall, the taken, stepwise approach should be generally useful to construct novel AOP descriptions as well as to enrich developing AOP descriptions in progress.

A data fusion pipeline is accessible at