Development of an Ontology for Periodontitis

BackgroundIn the clinical dentists and periodontal researchers’ community, there is an obvious demand for a systems model capable of linking the clinical presentation of periodontitis to underlying molecular knowledge. A computer-readable representation of processes on disease development will give periodontal researchers opportunities to elucidate pathways and mechanisms of periodontitis. An ontology for periodontitis can be a model for integration of large variety of factors relating to a complex disease such as chronic inflammation in different organs accompanied by bone remodeling and immune system disorders, which has recently been referred to as osteoimmunology.MethodsTerms characteristic of descriptions related to the onset and progression of periodontitis were manually extracted from 194 review articles and PubMed abstracts by experts in periodontology. We specified all the relations between the extracted terms and constructed them into an ontology for periodontitis. We also investigated matching between classes of our ontology and that of Gene Ontology Biological Process.ResultsWe developed an ontology for periodontitis called Periodontitis-Ontology (PeriO). The pathological progression of periodontitis is caused by complex, multi-factor interrelationships. PeriO consists of all the required concepts to represent the pathological progression and clinical treatment of periodontitis. The pathological processes were formalized with reference to Basic Formal Ontology and Relation Ontology, which accounts for participants in the processes realized by biological objects such as molecules and cells. We investigated the peculiarity of biological processes observed in pathological progression and medical treatments for the disease in comparison with Gene Ontology Biological Process (GO-BP) annotations. The results indicated that peculiarities of Perio existed in 1) granularity and context dependency of both the conceptualizations, and 2) causality intrinsic to the pathological processes. PeriO defines more specific concepts than GO-BP, and thus can be added as descendants of GO-BP leaf nodes. PeriO defines causal relationships between the process concepts, which are not shown in GO-BP. The difference can be explained by the goal of conceptualization: PeriO focuses on mechanisms of the pathogenic progress, while GO-BP focuses on cataloguing all of the biological processes observed in experiments. The goal of conceptualization in PeriO may reflect the domain knowledge where a consequence in the causal relationships is a primary interest. We believe the peculiarities can be shared among other diseases when comparing processes in disease against GO-BP.ConclusionsThis is the first open biomedical ontology of periodontitis capable of providing a foundation for an ontology-based model of aspects of molecular biology and pathological processes related to periodontitis, as well as its relations with systemic diseases. PeriO is available at http://bio-omix.tmd.ac.jp/periodontitis/.

[1]  Cynthia L. Smith,et al.  Integrating phenotype ontologies across multiple species , 2010, Genome Biology.

[2]  A. Collmer,et al.  Gene Ontology for type III effectors: capturing processes at the host-pathogen interface. , 2009, Trends in microbiology.

[3]  C E Lipscomb,et al.  Medical Subject Headings (MeSH). , 2000, Bulletin of the Medical Library Association.

[4]  Takako Takai-Igarashi,et al.  Development of a Database and Ontology for Pathogenic Pathways in Periodontitis , 2009, Silico Biol..

[5]  Gang Feng,et al.  From disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose ontology for the test of gene-ontology associations , 2009, Bioinform..

[6]  Chul-woo Yang,et al.  Cytokine-Mediated Bone Destruction in Rheumatoid Arthritis , 2014, Journal of immunology research.

[7]  Anna Zhukova,et al.  Modeling sample variables with an Experimental Factor Ontology , 2010, Bioinform..

[8]  J. Potempa,et al.  Role of bacterial proteinases in matrix destruction and modulation of host responses. , 2000, Periodontology 2000.

[9]  J. Beck,et al.  Rethinking periodontal inflammation. , 2008, Journal of periodontology.

[10]  Monte Westerfield,et al.  Linking Human Diseases to Animal Models Using Ontology-Based Phenotype Annotation , 2009, PLoS biology.

[11]  A. Souza-Machado,et al.  Does periodontal infection have an effect on severe asthma in adults? , 2014, Journal of periodontology.

[12]  Barry Smith,et al.  CLASSIFYING PROCESSES: AN ESSAY IN APPLIED ONTOLOGY. , 2012, Ratio.

[13]  Robert Stevens,et al.  Gene Ontology Consortium , 2014 .

[14]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[15]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[16]  William Stafford Noble,et al.  Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project , 2007, Nature.

[17]  Andreas Schmidt,et al.  Bioinformatic analysis of proteomics data , 2014, BMC Systems Biology.

[18]  Cornelius Rosse,et al.  The Foundational Model of Anatomy Ontology , 2008, Anatomy Ontologies for Bioinformatics.

[19]  Alexander D. Diehl,et al.  Logical Development of the Cell Ontology , 2011, BMC Bioinformatics.

[20]  Yijin Ren,et al.  Role of notch signaling in osteoimmunology--from the standpoint of osteoclast differentiation. , 2013, European journal of orthodontics.

[21]  Barry Smith,et al.  An improved ontological representation of dendritic cells as a paradigm for all cell types , 2009, BMC Bioinformatics.

[22]  Christoph Steinbeck,et al.  A database for chemical proteomics: ChEBI. , 2012, Methods in molecular biology.

[23]  F. Scannapieco,et al.  Periodontal systemic associations: review of the evidence. , 2013, Journal of clinical periodontology.

[24]  Werner Ceusters,et al.  Foundations for a realist ontology of mental disease , 2010, J. Biomed. Semant..

[25]  R. Gruber Cell biology of osteoimmunology , 2010, Wiener Medizinische Wochenschrift.

[26]  Giorgio Valle,et al.  Muscle Research and Gene Ontology: New standards for improved data integration , 2009, BMC Medical Genomics.

[27]  G. Anastasi,et al.  Immunohistochemical analysis of TGF-β1 and VEGF in gingival and periodontal tissues: a role of these biomarkers in the pathogenesis of scleroderma and periodontal disease. , 2012, International journal of molecular medicine.

[28]  A. Pradeep,et al.  Periodontal Health Condition in Patients With Alzheimer’s Disease , 2014, American journal of Alzheimer's disease and other dementias.

[29]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

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

[31]  Midori A. Harris,et al.  BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btm112 Databases and ontologies OBO-Edit—an ontology editor for biologists , 2007 .

[32]  Robert A. Israel,et al.  International Classification of Diseases (ICD) , 2005 .

[33]  J. Glasner,et al.  Gene Ontology annotation highlights shared and divergent pathogenic strategies of type III effector proteins deployed by the plant pathogen Pseudomonas syringae pv tomato DC3000 and animal pathogenic Escherichia coli strains , 2009, BMC Microbiology.

[34]  S. Schulz,et al.  Survey of current terminologies and ontologies in biology and medicine , 2009 .

[35]  K. Mossman The Wellcome Trust Case Control Consortium, U.K. , 2008 .

[36]  C. Trautwein,et al.  Tumor necrosis factor-α and oral inflammation in patients with Crohn disease. , 2014, Journal of periodontology.

[37]  Alan Ruttenberg,et al.  Computational knowledge integration in biopharmaceutical research , 2003, Briefings Bioinform..

[38]  K. Kornman,et al.  Mapping the pathogenesis of periodontitis: a new look. , 2008, Journal of periodontology.

[39]  Ron Kikinis,et al.  Computational neuroanatomy: ontology-based representation of neural components and connectivity , 2009, BMC Bioinformatics.

[40]  M. Grant What do 'omic technologies have to offer periodontal clinical practice in the future? , 2012, Journal of periodontal research.

[41]  Kazuhiko Ohe,et al.  Browsing Causal Chains in a Disease Ontology , 2012, International Semantic Web Conference.

[42]  B. Loos,et al.  Inflammatory mechanisms linking periodontal diseases to cardiovascular diseases. , 2013, Journal of clinical periodontology.

[43]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[44]  M. Ashburner,et al.  An ontology for cell types , 2005, Genome Biology.