Abstract
Objective:The clinical features of epilepsy determine how it is defined, which in turn guides management. Therefore, consideration of the fundamental clinical entities that comprise an epilepsy is essential in the study of causes, trajectories, and treatment responses. The Human Phenotype Ontology (HPO) is used widely in clinical and research genetics for concise communication and modeling of clinical features, allowing extracted data to be harmonized using logical inference. We sought to redesign the HPO seizure subontology to improve its consistency with current epileptological concepts, supporting the use of large clinical data sets in high-throughput clinical and research genomics.Methods:We created a new HPO seizure subontology based on the 2017 International League Against Epilepsy (ILAE) Operational Classification of Seizure Types, and integrated concepts of status epilepticus, febrile, reflex, and neonatal seizures at different levels of detail. We compared the HPO seizure subontology prior to, and following, our revision, according to the information that could be inferred about the seizures of 791 individuals from three independent cohorts: 2 previously published and 150 newly recruited individuals. Each cohort’s data were provided in a different format and harmonized using the two versions of the HPO.Results:The new seizure subontology increased the number of descriptive concepts for seizures 5-fold. The number of seizure descriptors that could be annotated to the cohort increased by 40% and the total amount of information about individuals’ seizures increased by 38%. The most important qualitative difference was the relationship of focal to bilateral tonic-clonic seizure to generalized-onset and focal-onset seizures.
Highlights
Information about the clinical features of research participants is essential for diagnostic interpretation of genetic findings and discovery research in epilepsy genetics.[1,2] To fully exploit these data, information must be harmonized to allow reliable comparison of individuals to diagnostic criteria, or to each other.[3]
We describe the revision of the seizure domain within the Human Phenotype Ontology (HPO) to align it with contemporary classification concepts, and the resulting effect on precise seizure description in 791 individuals
We demonstrate how seizure data can be encoded in HPO terms, automatically classifying each seizure according to multiple conceptually broader descriptors, and how it can harmonize data provided in different formats
Summary
The Human Phenotype Ontology (HPO) formally models the relationships between clinical concepts to facilitate concise communication, harmonization, and algorithmic inference. Our new HPO seizure subontology increases the amount of information that can be encoded and made available for automated reasoning, making clinical data tractable in big data sets
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