ArticleFrontiers in bioinformatics2026
Characteristics of predicated pathogenic missense variants in human genes for Mendelian disorders.
Article in Frontiers in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Missense variants represent a major class of genetic variation and contribute substantially to the cause of Mendelian disorders. However, the genetic and protein properties governing their pathogenicity remain incompletely characterized. Existing variant pathogenicity databases, such as ClinVar, are enriched for variants in well-studied genes and therefore may not provide a representative view of pathogenic missense variants across the genome. Meanwhile, recent advances in computational pathogenicity prediction have significantly improved their predictive accuracy, enabling large-scale genome-wide analysis. In this study, we investigated the genetic and protein properties associated with the predicted pathogenicity of missense variants in Mendelian disease genes. Methods: We collected all possible missense variants in Mendelian genes curated from the Online Mendelian Inheritance in Man (OMIM). Each variant was annotated with pathogenicity predictions from gMVP and a range of properties, including evolutionary conservation, physicochemical substitution characteristics, and functional and structural genetic and protein features. Using multiple linear regression models, we investigated the relationships between the various properties and the predicted pathogenicity of the missense variants. Interaction effects among those properties were also examined. We first validated the quality of gMVP by comparing the effects of each property in the linear regression, fitting to either gMVP pathogenicity predictions or ClinVar pathogenicity labels, on the ClinVar dataset. Then, we extended the analyses to the entire missense dataset to fit gMVP pathogenicity scores. In addition, gene set and robustness analyses were further performed to validate the study findings. Results: In 655,859 missense variants from ClinVar, 7.1% were labeled as pathogenic/likely pathogenic compared with 6.4% predicted as pathogenic using a gMVP threshold of 0.9. Regression analyses revealed a high degree of concordance between ClinVar and gMVP pathogenicity annotations, with most predictors showing associations in the same direction and of similar magnitude. The genome-wide dataset includes 23,339,549 missense variants in 4,709 Mendelian disease genes, with 31.8% predicted to be pathogenic using a default gMVP threshold of 0.75. Evolutionary conservation, solvent accessibility, and intrinsic disorder were strongly associated with gMVP pathogenicity scores. Other features, including functional annotations and amino acid biochemical properties, also contributed to the predicted pathogenicity with moderate effect sizes. Feature interactions support an integrative model in which conservation and local protein structure jointly influence the variant impact. GO-stratified and other gene-set analyses indicated that these associations were broadly conserved across gene functional contexts and inheritance patterns. Conclusion: gMVP-predicted pathogenic missense variants are consistently enriched in conserved and structured protein core regions, regardless of gene function and inheritance pattern. These findings highlight the importance of incorporating genetic and protein annotations into variant interpretation frameworks.
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