Converting Alzheimer s disease map into a heavyweight ontology: a formal network to integrate data

TL;DR

This paper presents the conversion of the detailed Alzheimer s disease map into a formal ontology, enhancing data integration, consistency, and expandability for better understanding and hypothesis generation in AD research.

Contribution

It introduces ADMO, an upper-level ontology for AD, and demonstrates converting AlzPathway into a formal ontology to improve data consistency and integration.

Findings

Enables handling of redundancy and naming issues.

Facilitates pathway and process classification.

Supports integration with other resources like Reactome.

Abstract

Alzheimer s disease (AD) pathophysiology is still imperfectly understood and current paradigms have not led to curative outcome. Omics technologies offer great promises for improving our understanding and generating new hypotheses. However, integration and interpretation of such data pose major challenges, calling for adequate knowledge models. AlzPathway is a disease map that gives a detailed and broad account of AD pathophysiology. However, AlzPathway lacks formalism, which can lead to ambiguity and misinterpretation. Ontologies are an adequate framework to overcome this limitation, through their axiomatic definitions and logical reasoning properties. We introduce the AD Map Ontology (ADMO) an ontological upper model based on systems biology terms. We then propose to convert AlzPathway into an ontology and to integrate it into ADMO. We demonstrate that it allows one to deal with issues related to redundancy, naming, consistency, process classification and pathway relationships. Further, it opens opportunities to expand the model using elements from other resources, such as generic pathways from Reactome or clinical features contained in the ADO (AD Ontology). A version of the ontology will be made freely available to the community on Bioportal at the time of the confer-ence.