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PreprintCited by 19Genomics and Rare DiseasesGenetic Associations and EpidemiologyBioinformatics and Genomic Networks

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Prevalence of loss-of-function, gain-of-function and dominant-negative mechanisms across genetic disease phenotypes

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Badonyi, Mihaly, Marsh, Joseph A·2025·Nature Communications
DOI 10.1101/2025.03.13.642984PMC PMC12462468

Preprint — published as 10.1038/s41467-025-63234-3 · Paper page

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Abstract

Molecular disease mechanisms caused by mutations in protein-coding regions are diverse, but they can be broadly categorised into loss-of-function (LOF), gain-of-function (GOF), and dominant-negative (DN) effects. Accurately predicting these mechanisms is a pressing clinical need, as therapeutic strategies must align with the underlying disease mechanism. Moreover, computational predictors tend to perform less well at the identification of pathogenic GOF and DN variants. Here, we develop a protein structure-based missense LOF (mLOF) likelihood score that can separate recessive LOF and dominant LOF from alternative disease mechanisms. Using mLOF scores, we estimated the prevalence of molecular mechanisms across 2,837 phenotypes in 1,979 Mendelian disease genes, finding that DN and GOF mechanisms account for 48% of phenotypes in dominant genes. Applying mLOF scores to genes with multiple phenotypes revealed widespread intragenic mechanistic heterogeneity, with 43% of dominant and 49% of mixed-inheritance genes harbouring both LOF and non-LOF mechanisms. Furthermore, we show that combining mLOF scores with phenotype semantic similarity enables the prioritisation of DN mechanisms in mixed-inheritance genes. Our structure-based approach, accessible via a Google Colab notebook, offers a scalable tool for predicting disease mechanisms and advancing personalised medicine.

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Metadata

Authors
Badonyi, M., & Marsh, J. A.
Affiliations
Institute of Genetics and Cancer (GB)
Corresponding author
  • Badonyi, Mihaly
  • Marsh, Joseph A
ORCID
Venue
Nature Communications
Publisher
openRxiv
Published
2025-03-15
Volume
16
Issue
1
Pages
8392-8392
ISSN
2041-1723 (ISSN-L)
DOI
10.1101/2025.03.13.642984
PMC
PMC12462468
OpenAlex
W4414512364
Cited by
19
References
125
Citations by year
2026: 16 · 2025: 3
FWCI
11.17
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • OSF Preprints (OSF Preprints) (submittedVersion)
Funders
  • European Commission (HORIZON2020)
  • Lister Institute of Preventive Medicine
  • Medical Research Council (MC_UU_00035/9)
  • H2020 European Research Council (101001169)
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 › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
loss of function, gain-of-function, dominant-negative mechanism, missense mutations, protein structure-based prediction, Mendelian disease genes, variant prioritization, recessive inheritance
MeSH terms
Loss of Function Mutation, Gain of Function Mutation, Genes, Dominant, Humans, Phenotype, Prevalence, Mutation, Missense, Genetic Diseases, Inborn

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