An ontological foundation for ocular phenotypes and rare eye diseases

Abstract

Background: The optical accessibility of the eye and technological advances in ophthalmic diagnostics have put ophthalmology at the forefront of data-driven medicine. The focus of this study is rare eye disorders, a group of conditions whose clinical heterogeneity and geographic dispersion make data-driven, evidence-based practice particularly challenging. Inter-institutional collaboration and information sharing is crucial but the lack of standardised terminology poses an important barrier. Ontologies are computational tools that include sets of vocabulary terms arranged in hierarchical structures. They can be used to provide robust terminology standards and to enhance data interoperability. Here, we discuss the development of the ophthalmology-related component of two well-established biomedical ontologies, the Human Phenotype Ontology (HPO; includes signs, symptoms and investigation findings) and the Orphanet Rare Disease Ontology (ORDO; includes rare disease nomenclature/nosology).

Methods: A variety of approaches were used including automated matching to existing resources and extensive manual curation. To achieve the latter, a study group including clinicians, patient representatives and ontology developers from 17 countries was formed. A broad range of terms was discussed and validated during a dedicated workshop attended by 60 members of the group.

Results: A comprehensive, structured and well-defined set of terms has been agreed on including 1106 terms relating to ocular phenotypes (HPO) and 1202 terms relating to rare eye disease nomenclature (ORDO). These terms and their relevant annotations can be accessed in http://www.human-phenotype-ontology.org/ and http://www.orpha.net/ ; comments, corrections, suggestions and requests for new terms can be made through these websites. This is an ongoing, community-driven endeavour and both HPO and ORDO are regularly updated.

Conclusions: To our knowledge, this is the first effort of such scale to provide terminology standards for the rare eye disease community. We hope that this work will not only improve coding and standardise information exchange in clinical care and research, but also it will catalyse the transition to an evidence-based precision ophthalmology paradigm.

Keywords: Evidence-based precision medicine; Human phenotype ontology; Orphanet rare disease ontology; Rare eye disease.

Fig. 1

Example of hierarchical (tree) structure of data in the Human Phenotype Ontology (HPO). Ophthalmic findings in a child with PHACE syndrome (posterior fossa anomalies, hemangioma, arterial lesions, cardiac abnormalities/coarctation of the aorta, eye anomalies) are shown. Ontologies consist of several distinct elements including terms (nodes in the figure) and relationships (arrows in the figure). Each term can be associated with annotated textual information known as metadata; these may include modifiers (blue squares), definitions and alternative/secondary identifiers. Modifiers can be assigned to each term and may relate to severity (mild, moderate etc.), temporal pattern (acute, episodic, etc.), age of onset (childhood onset, adult onset etc), progression (progressive, nonprogressive, etc.), laterality (right, bilateral etc) and spatial pattern (central, generalized, etc.). The user can specify if a specific phenotype (HPO term) is present or absent in an individual. When a phenotype/term is selected as present (e.g. terms corresponding to the five circles with thickened margins) then, by definition, all terms above this term (coloured circles; colours only used to enhance visualisation) have to be present; this is because each term is connected with its parent terms by an “is a” relationship. Therefore, the higher in the ontology a term is located, the more general it is and the lesser its information content (defined as the negative logarithm of its probability) will be