4.8 Article

The Human Phenotype Ontology in 2021

Journal

NUCLEIC ACIDS RESEARCH
Volume 49, Issue D1, Pages D1207-D1217

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkaa1043

Keywords

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Funding

  1. Monarch R24 [2R24OD011883-05A1]
  2. NHGRI Phenomics [1RM1HG010860]
  3. NHGRI/NCI Forums in Phenomics [5U13CA221044]
  4. Solve-RD [779257]
  5. HIPBI [643578]
  6. DFG [Gr 970/9-1]
  7. E-Rare-3
  8. HCQ4Surfdefect
  9. Cost CA [16125 ENTeR-chIL]
  10. NIH

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The Human Phenotype Ontology (HPO) serves as a global standard for phenotype exchange, with recent major extensions in neurology, nephrology, immunology, pulmonology, and other fields. Efforts have been made to improve computational definitions of phenotypic abnormalities across HPO and multiple phenotype ontologies for animal disease models, benefiting software accuracy and cross-species phenotype matching. Recent initiatives include translating HPO into indigenous languages and advancing its use in electronic health record systems.
The Human Phenotype Ontology (HPO, https://hpo. jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

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