The Human Phenotype Ontology in 2021
Overview
Authors
Affiliations
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.
Gnanaolivu R, Oliver G, Jenkinson G, Blake E, Chen W, Chia N BMC Bioinformatics. 2025; 26(1):82.
PMID: 40087567 DOI: 10.1186/s12859-025-06096-2.
Roselli C, Surakka I, S Olesen M, Sveinbjornsson G, Marston N, Choi S Nat Genet. 2025; 57(3):539-547.
PMID: 40050429 DOI: 10.1038/s41588-024-02072-3.
Li X, Rao Y, Li G, He L, Wang Y, He W Sci Rep. 2025; 15(1):7418.
PMID: 40033004 PMC: 11876315. DOI: 10.1038/s41598-025-92030-8.
Genetic variants and phenotypic data curated for the CAGI6 intellectual disability panel challenge.
Aspromonte M, Del Conte A, Polli R, Baldo D, Benedicenti F, Bettella E Hum Genet. 2025; .
PMID: 40019509 DOI: 10.1007/s00439-025-02733-1.
Rare disease gene association discovery in the 100,000 Genomes Project.
Cipriani V, Vestito L, Magavern E, Jacobsen J, Arno G, Behr E Nature. 2025; .
PMID: 40011789 DOI: 10.1038/s41586-025-08623-w.