Converting Alzheimer's Disease Map into a Heavyweight Ontology: A Formal Network to Integrate Data

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 ADMO is freely available at http://bioportal.bioontology.org/ontologies/ADMO.

[1]  Sebastian Schaffert,et al.  IkeWiki: A Semantic Wiki for Collaborative Knowledge Management , 2006, 15th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE'06).

[2]  Cathy H. Wu,et al.  UniProt: the Universal Protein knowledgebase , 2004, Nucleic Acids Res..

[3]  A. Rector,et al.  Relations in biomedical ontologies , 2005, Genome Biology.

[4]  Yukiko Matsuoka,et al.  Using process diagrams for the graphical representation of biological networks , 2005, Nature Biotechnology.

[5]  Martin Hofmann-Apitius,et al.  ADO: A disease ontology representing the domain knowledge specific to Alzheimer's disease , 2014, Alzheimer's & Dementia.

[6]  Todd E. Golde,et al.  Anti-Aβ Therapeutics in Alzheimer's Disease: The Need for a Paradigm Shift , 2011, Neuron.

[7]  Tom C. Freeman,et al.  The mEPN scheme: an intuitive and flexible graphical system for rendering biological pathways , 2010, BMC Systems Biology.

[8]  Alzheimer’s Association 2018 Alzheimer's disease facts and figures , 2018, Alzheimer's & Dementia.

[9]  Hiroshi Tanaka,et al.  AlzPathway, an Updated Map of Curated Signaling Pathways: Towards Deciphering Alzheimer's Disease Pathogenesis. , 2016, Methods in molecular biology.

[10]  Samik Ghosh,et al.  Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map , 2013, Molecular Neurobiology.

[11]  Sebastian Schaffert,et al.  A SEMANTIC WIKI FOR COLLABORATIVE KNOWLEDGE FORMATION , 2006 .

[12]  Minoru Kanehisa,et al.  KEGG: new perspectives on genomes, pathways, diseases and drugs , 2016, Nucleic Acids Res..

[13]  Michel Dumontier,et al.  Controlled vocabularies and semantics in systems biology , 2011, Molecular systems biology.

[14]  Nicolas Le Novère,et al.  Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2 , 2015, J. Integr. Bioinform..

[15]  Arthur W Toga,et al.  Global Data Sharing in Alzheimer Disease Research , 2016, Alzheimer disease and associated disorders.

[16]  Chris J. Myers,et al.  SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3 , 2015, J. Integr. Bioinform..

[17]  Henning Hermjakob,et al.  The Reactome pathway knowledgebase , 2013, Nucleic Acids Res..

[18]  Riichiro Mizoguchi Tutorial on ontological engineering , 2009, New Generation Computing.

[19]  Kei-Hoi Cheung,et al.  BioPAX – A community standard for pathway data sharing , 2010, Nature Biotechnology.

[20]  Martin Hofmann-Apitius,et al.  NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease , 2016, Journal of Biomedical Semantics.