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Lookup NU author(s): Dr David Lewis-Smith
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023Background: 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.
Author(s): Carmody LC, Gargano MA, Toro S, Vasilevsky NA, Adam MP, Blau H, Chan LE, Gomez-Andres D, Horvath R, Kraus ML, Ladewig MS, Lewis-Smith D, Lochmuller H, Matentzoglu NA, Munoz-Torres MC, Schuetz C, Seitz B, Similuk MN, Sparks TN, Strauss T, Swietlik EM, Thompson R, Zhang XA, Mungall CJ, Haendel MA, Robinson PN
Publication type: Article
Publication status: Published
Journal: Med
Year: 2023
Volume: 4
Issue: 12
Pages: 913-927.E3
Print publication date: 08/12/2023
Online publication date: 13/11/2023
Acceptance date: 14/10/2023
Date deposited: 27/11/2023
ISSN (print): 2666-6359
ISSN (electronic): 2666-6340
Publisher: Cell Press
URL: https://doi.org/10.1016/j.medj.2023.10.003
DOI: 10.1016/j.medj.2023.10.003
Data Access Statement: This study did not generate original data. This paper does not report original code. Ontology and annotation files are available at the project’s two GitHub repositories as shown in the key resources table. Versioned releases are available on the Releases page of the main MAxO repository. Any additional information required to reanalyze the data reported in this paper is available from lead contact upon request.
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