The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Leigh C Carmody - , Jackson Laboratory (Author)
  • Michael A Gargano - , Jackson Laboratory (Author)
  • Sabrina Toro - , University of Colorado Anschutz Medical Campus (Author)
  • Nicole A Vasilevsky - , Critical Path Institute (Author)
  • Margaret P Adam - , Washington University St. Louis (Author)
  • Hannah Blau - , Jackson Laboratory (Author)
  • Lauren E Chan - , Oregon State University (Author)
  • David Gomez-Andres - , Vall d'Hebron University Hospital (Author)
  • Rita Horvath - , University of Cambridge (Author)
  • Megan L Kraus - , University of Colorado Anschutz Medical Campus (Author)
  • Markus S Ladewig - , Klinikum Saarbrücken (Author)
  • David Lewis-Smith - , Newcastle University (Author)
  • Hanns Lochmüller - , Ottawa Hospital Research Institute (Author)
  • Nicolas A Matentzoglu - , Semanticly (Author)
  • Monica C Munoz-Torres - , University of Colorado Anschutz Medical Campus (Author)
  • Catharina Schuetz - , Department of Paediatrics, Technische Universität Dresden (Author)
  • Berthold Seitz - , University Hospital of Saarland (Author)
  • Morgan N Similuk - , National Institutes of Health (NIH) (Author)
  • Teresa N Sparks - , University of California at Irvine (Author)
  • Timmy Strauss - , Department of Paediatrics, Technische Universität Dresden (Author)
  • Emilia M Swietlik - , University of Cambridge (Author)
  • Rachel Thompson - , Children's Hospital of Eastern Ontario (CHEO) (Author)
  • Xingmin Aaron Zhang - , Jackson Laboratory (Author)
  • Christopher J Mungall - , Lawrence Berkeley National Laboratory (Author)
  • Melissa A Haendel - , University of Colorado Anschutz Medical Campus (Author)
  • Peter N Robinson - , Jackson Laboratory (Author)

Abstract

BACKGROUND: Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical procedures, therapies, and interventions.

METHODS: MAxO incorporates logical structures that link MAxO terms to numerous other ontologies within the OBO Foundry. Term development involves a blend of manual and semi-automated processes. Additionally, we have generated annotations detailing diagnostic modalities for specific phenotypic abnormalities defined by the Human Phenotype Ontology (HPO). We introduce a web application, POET, that facilitates MAxO annotations for specific medical actions for diseases using the Mondo Disease Ontology.

FINDINGS: MAxO encompasses 1,757 terms spanning a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. These terms annotate phenotypic features associated with specific disease (using HPO and Mondo). Presently, there are over 16,000 MAxO diagnostic annotations that target HPO terms. Through POET, we have created 413 MAxO annotations specifying treatments for 189 rare diseases.

CONCLUSIONS: MAxO offers a computational representation of treatments and other actions taken for the clinical management of patients. Its development is closely coupled to Mondo and HPO, broadening the scope of our computational modeling of diseases and phenotypic features. We invite the community to contribute disease annotations using POET (https://poet.jax.org/). MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO).

FUNDING: NHGRI 1U24HG011449-01A1 and NHGRI 5RM1HG010860-04.

Details

Original languageEnglish
Pages (from-to)913-927.e3
Number of pages19
JournalMED
Volume4
Issue number12
Early online date9 Nov 2023
Publication statusPublished - 8 Dec 2023
Peer-reviewedYes

External IDs

Scopus 85176350085
ORCID /0009-0003-6519-0482/work/147674510

Keywords

Sustainable Development Goals

Keywords

  • Biological Ontologies, Computer Simulation, Humans, Rare Diseases, Software

Library keywords