Curation and expansion of human phenotype ontology for defined groups of inborn errors of immunity

M. Haimel, J. Pazmandi, R. Jiménez Heredia, J. Dmytrus, S. Köstel Bal, S. Zoghi, P. van Daele, T. A. Briggs, C. Wouters, B. Bader-Meunier, F. A. Aeschlimann, R. Caorsi, D. Eleftheriou , E. Hoppenreijs, E. Salzer, S. Bakhtiar, B. Derfalvi, F. Saettini , M. A. A. Kusters, R. ElfekyJ. Trück, J. G. Rivière, M. van der Burg, M. Gattorno, M. G. Seidel, S. Burns, K. Warnatz, F. Hauck, P. Brogan, K. C. Gilmour, C. Schuetz, A. Simon, C. Bock, S. Hambleton, E. de Vries, P. N. Robinson, M. van Gijn*, K. Boztug*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Background
Accurate, detailed, and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype Ontology (HPO), extensively used in rare disease research, provides a rich collection of vocabulary with standardized phenotypic descriptions in a hierarchical structure. However, to date, the use of HPO has not yet been widely implemented in the field of inborn errors of immunity (IEIs), mainly due to a lack of comprehensive IEI-related terms.

Objectives
We sought to systematically review available terms in HPO for the depiction of IEIs, to expand HPO, yielding more comprehensive sets of terms, and to reannotate IEIs with HPO terms to provide accurate, standardized phenotypic descriptions.

Methods
We initiated a collaboration involving expert clinicians, geneticists, researchers working on IEIs, and bioinformaticians. Multiple branches of the HPO tree were restructured and extended on the basis of expert review. Our ontology-guided machine learning coupled with a 2-tier expert review was applied to reannotate defined subgroups of IEIs.

Results
We revised and expanded 4 main branches of the HPO tree. Here, we reannotated 73 diseases from 4 International Union of Immunological Societies–defined IEI disease subgroups with HPO terms. We achieved a 4.7-fold increase in the number of phenotypic terms per disease. Given the new HPO annotations, we demonstrated improved ability to computationally match selected IEI cases to their known diagnosis, and improved phenotype-driven disease classification.

Conclusions
Our targeted expansion and reannotation presents enhanced precision of disease annotation, will enable superior HPO-based IEI characterization, and hence benefit both IEI diagnostic and research activities.
Original languageEnglish
JournalJournal of Allergy and Clinical Immunology
DOIs
Publication statusAccepted/In press - 2021

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