Analysis of missense variants in the human genome reveals widespread gene-specific clustering and improves prediction of pathogenicity

We used a machine learning approach to analyze the within-gene distribution of missense variants observed in hereditary conditions and cancer. When applied to 840 genes from the ClinVar database, this approach detected a significant non-random distribution of pathogenic and benign variants in 387 (4...

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Bibliographic Details
Published in:American journal of human genetics 2022-03, Vol.109 (3), p.457-470
Main Authors: Quinodoz, Mathieu, Peter, Virginie G., Cisarova, Katarina, Royer-Bertrand, Beryl, Stenson, Peter D., Cooper, David N., Unger, Sheila, Superti-Furga, Andrea, Rivolta, Carlo
Format: Article
Language:English
Subjects:
Cluster Analysis
Exome - genetics
functional domains
gain-of-function
Genome, Human - genetics
human genome
Humans
loss-of-function
medical genetics
missense
molecular pathology
mutation
Mutation, Missense - genetics
pathogenicity prediction
variant clustering
Virulence
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Summary:We used a machine learning approach to analyze the within-gene distribution of missense variants observed in hereditary conditions and cancer. When applied to 840 genes from the ClinVar database, this approach detected a significant non-random distribution of pathogenic and benign variants in 387 (46%) and 172 (20%) genes, respectively, revealing that variant clustering is widespread across the human exome. This clustering likely occurs as a consequence of mechanisms shaping pathogenicity at the protein level, as illustrated by the overlap of some clusters with known functional domains. We then took advantage of these findings to develop a pathogenicity predictor, MutScore, that integrates qualitative features of DNA substitutions with the new additional information derived from this positional clustering. Using a random forest approach, MutScore was able to identify pathogenic missense mutations with very high accuracy, outperforming existing predictive tools, especially for variants associated with autosomal-dominant disease and cancer. Thus, the within-gene clustering of pathogenic and benign DNA changes is an important and previously underappreciated feature of the human exome, which can be harnessed to improve the prediction of pathogenicity and disambiguation of DNA variants of uncertain significance. [Display omitted]
ISSN:0002-9297
1537-6605
DOI:10.1016/j.ajhg.2022.01.006