PreprintCited by 4Bioinformatics and Genomic NetworksGenomics and Rare DiseasesBiomedical Text Mining and Ontologies

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Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

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Preprint — published as 10.1093/database/baae031

Abstract

Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of ∼800 disease reactions constituting ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactome’s pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.

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Metadata

Authors
Orlic-Milacic, M., Rothfels, K., Matthews, L., Wright, A., Jassal, B., Shamovsky, V., Trinh, Q., Gillespie, M., Sevilla, C., Tiwari, K., Ragueneau, E., Gong, C., Stephan, R., May, B., Haw, R., Weiser, J., Beavers, D., Conley, P., Hermjakob, H., Stein, L. D., D’Eustachio, P., & Wu, G.
Affiliations
  • Ontario Institute for Cancer Research (CA)
  • New York University (US)
  • European Bioinformatics Institute (GB)
  • Oregon Health & Science University (US)
Corresponding author
Orlic-Milacic, Marija
Venue
Database
Publisher
openRxiv
Published
2023-10-22
Volume
2024
ISSN
1758-0463 (ISSN-L)
OpenAlex
W4396685747
Cited by
4
References
1
Citations by year
2025: 4
FWCI
0.54
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Database (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion)
Funders
  • European Bioinformatics Institute
  • European Commission (223411)
  • University of Toronto
  • National Institutes of Health (P41HG003751 U01CA239069 U54GM114833)
  • National Human Genome Research Institute (U41HG003751, 1U24HG012198 U41HG003751, P41HG003751, U24HG011851, U24HG012198)
  • National Cancer Institute (U01CA239069)
  • National Institute of General Medical Sciences (U54GM114833)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
Keywords
disease reaction, disease pathways, Reactome, molecular phenotypes, pathogenic variants, variants of uncertain significance, gain-of-function mutations, loss-of-function mutations, variant pathogenicity prediction, biological pathway databases

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