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PreprintCited by 12Genomics and Rare DiseasesGenetic Associations and EpidemiologyCancer Genomics and Diagnostics

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DeMAG predicts the effects of variants in clinically actionable genes by integrating structural and evolutionary epistatic features

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Luppino, Federica, Adzhubei, Ivan A., Cassa, Christopher A., Toth-Petroczy, Agnes·2022·Nature Communications
DOI 10.1101/2022.06.15.496230PMC PMC10115847

Preprint — published as 10.1038/s41467-023-37661-z · Paper page

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Abstract

Despite an increasing use of genomic sequencing in clinical practice, interpretation of rare genetic variants remains challenging even in well-studied disease genes, resulting in many patients with Variants of Uncertain Significance (VUSs). Computational Variant Effect Predictors (VEPs) are currently used to provide valuable evidence in variant classifications, but they often misclassify benign variants, contributing to potential misdiagnoses. Here, we developed Deciphering Mutations in Actionable Genes (DeMAG), a supervised classifier for interpreting missense variants in actionable disease genes with improved performance over existing VEPs (20% decrease of false positive rate). Our tool has balanced specificity (82%) and sensitivity (94%) on clinical data, and the lowest misclassification rate on putatively benign variants among evaluated tools. DeMAG takes advantage of a novel epistatic feature, the ‘ partners score’, which is based on evolutionary and structural partnerships of residues as estimated by evolutionary information and AlphaFold2 structural models. The ‘partners score’ as a general framework of epistatic interactions, can integrate not only clinical but functional information. We anticipate that our tool ( demag.org ) will facilitate the interpretation of variants and improve clinical decision-making.

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Metadata

Authors
Luppino, F., Adzhubei, I. A., Cassa, C. A., & Toth-Petroczy, A.
Affiliations
  • Center for Systems Biology Dresden (DE)
  • Brigham and Women's Hospital (US)
Corresponding author
Cassa, Christopher A.
ORCID
Venue
Nature Communications
Publisher
openRxiv
Published
2022-06-17
Volume
14
Issue
1
Pages
2230-2230
ISSN
2041-1723 (ISSN-L)
DOI
10.1101/2022.06.15.496230
PMC
PMC10115847
OpenAlex
W4366405805
Cited by
12
References
1
Citations by year
2026: 3 · 2025: 5 · 2024: 4
FWCI
1.99
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • U.S. Department of Health and Human Services (R01-HG010372)
  • Max-Planck-Gesellschaft
  • Tartu Ülikool
  • National Institutes of Health
  • National Human Genome Research Institute (R01HG010372)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Keywords
variant effect prediction, missense mutations, variants of uncertain significance, epistasis, protein structure, evolutionary conservation, variant interpretation
MeSH terms
Genetic Testing, Humans, United States, Genetic Variation, Mutation, Missense, Genomics

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