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. 2025 Oct 6:iyaf215.
doi: 10.1093/genetics/iyaf215. Online ahead of print.

Mondo: Integrating Disease Terminology Across Communities

Nicole A Vasilevsky  1 Sabrina Toro  2 Nicolas Matentzoglu  3 Joseph E Flack  4 Kathleen R Mullen  5 Harshad Hegde  6 Sarah Gehrke  7 Patricia L Whetzel  7 Yousif Shwetar  8 Nomi L Harris  9 Mee S Ngu  7 Gioconda L Alyea  10 Megan S Kane  11 Paola Roncaglia  12 Eric Sid  13 Courtney L Thaxton  7 Valerie Wood  14 Roshini S Abraham  15 Maria Isabel Achatz  16 Pamela Ajuyah  17 Joanna S Amberger  18 Lawrence Babb  19 Jasmine Baker  20 James P Balhoff  21 Jonathan S Berg  7 Amol Bhalla  22 Xavier Bofill-De Ros  23 Ian R Braun  1 Eleanor C Broeren  19 Blake K Byer  2 Alicia B Byrne  24 Tiffany J Callahan  25 Leigh C Carmody  26 Lauren E Chan  27 Amanda R Clause  28 Julie S Cohen  29 Marcello DeLuca  30 Natalie T Deuitch  31 May Flowers  32 Jamie Fraser  33 Toyofumi Fujiwara  34 Vanessa Gitau  19 Jennifer L Goldstein  35 Dylan Gration  36 Tudor Groza  37 Benjamin M Gyori  38 William Hankey  2 Jason A Hilton  39 Daniel S Himmelstein  40 Stephanie S Hong  41 Charles T Hoyt  42 Robert Huether  43 Eric Hurwitz  2 Julius O B Jacobsen  44 Atsuo Kikuchi  45 Sebastian Köhler  46 Daniel R Korn  2 David Lagorce  47 Bryan J Laraway  7 Jane Y Li  48 Adriana J Malheiro  49 James McLaughlin  50 Birgit H M Meldal  51 Shruthi Mohan  52 Sierra A T Moxon  53 Monica C Munoz-Torres  54 Tristan H Nelson  55 Frank W Nicholas  56 David Ochoa  57 Daniel Olson  58 Tudor I Oprea  59 Tomiko T Oskotsky  60 David Osumi-Sutherland  61 Kelley Paris  19 Helen E Parkinson  62 Zoë M Pendlington  63 Xiao P Peng  64 Amy Pizzino  65 Sharon E Plon  66 Bradford C Powell  7 Julie C Ratliff  67 Heidi L Rehm  68 Lyubov Remennik  69 Erin R Riggs  55 Sean Roberts  70 Peter N Robinson  71 Justyne E Ross  72 Kevin Schaper  7 Brian M Schilder  73 Johanna L Schmidt  65 Elliott W Sharp  74 Morgan N Similuk  75 Damian Smedley  44 Tam P Sneddon  76 Rachel Sparks  77 Ray Stefancsik  78 Gregory S Stupp  79 Shilpa Sundar  5 Terue Takatsuki  80 Imke Tammen  81 Kezang C Tshering  82 Deepak R Unni  83 Eloise Valasek  84 Adeline Vanderver  65 Alex H Wagner  85 Ryan F Webb  17 Danielle Welter  86 Doron Yaya-Stupp  87 Andreas Zankl  88 Xingmin Aaron Zhang  89 Julie A McMurry  2 Christopher G Chute  90 Ada Hamosh  91 Christopher J Mungall  92 Melissa A Haendel  2
Affiliations

Mondo: Integrating Disease Terminology Across Communities

Nicole A Vasilevsky et al. Genetics. .

Abstract

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities ⁠- including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology-a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene-disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

Keywords: biomedical informatics; community-driven ontology; disease classification; disease integration; disease ontology; disease terminology; rare disease.

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