A Data Fusion Pipeline for Generating and Enriching Adverse Outcome Pathway Descriptions. (15th November 2017)

• Record Type: Journal Article
• Authors: Nymark, Penny; Rieswijk, Linda; Ehrhart, Friederike; Jeliazkova, Nina; Tsiliki, Georgia; Sarimveis, Haralambos; Evelo, Chris T; Hongisto, Vesa; Kohonen, Pekka; Willighagen, Egon; Grafström, Roland C
• Is Part Of: Toxicological sciences. Volume 162:Number 1(2018)
• Page Start: 264
• Page End: 275
• Publication Date: 2017-11-15
• Subjects: Adverse Outcome Pathways -- pathway analysis -- pulmonary fibrosis -- predictive toxicology -- bioinformatics -- alternatives to animal testing; Toxicology -- Periodicals; Toxicology -- Periodicals; Toxicology; Periodicals; 615.9
• DOI: 10.1093/toxsci/kfx252
• Languages: English
• ISSNs: 1096-6080

Abstract

Abstract: 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 nonanimal-based hazard and risk assessment methods. We devised a 6-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.