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Computational analysis of 10,860 phenotypic annotations in individuals with SCN2A-related disorders.
- Source :
-
Genetics in medicine : official journal of the American College of Medical Genetics [Genet Med] 2021 Jul; Vol. 23 (7), pp. 1263-1272. Date of Electronic Publication: 2021 Mar 17. - Publication Year :
- 2021
-
Abstract
- Purpose: Pathogenic variants in SCN2A cause a wide range of neurodevelopmental phenotypes. Reports of genotype-phenotype correlations are often anecdotal, and the available phenotypic data have not been systematically analyzed.<br />Methods: We extracted phenotypic information from primary descriptions of SCN2A-related disorders in the literature between 2001 and 2019, which we coded in Human Phenotype Ontology (HPO) terms. With higher-level phenotype terms inferred by the HPO structure, we assessed the frequencies of clinical features and investigated the association of these features with variant classes and locations within the Na <subscript>V</subscript> 1.2 protein.<br />Results: We identified 413 unrelated individuals and derived a total of 10,860 HPO terms with 562 unique terms. Protein-truncating variants were associated with autism and behavioral abnormalities. Missense variants were associated with neonatal onset, epileptic spasms, and seizures, regardless of type. Phenotypic similarity was identified in 8/62 recurrent SCN2A variants. Three independent principal components accounted for 33% of the phenotypic variance, allowing for separation of gain-of-function versus loss-of-function variants with good performance.<br />Conclusion: Our work shows that translating clinical features into a computable format using a standardized language allows for quantitative phenotype analysis, mapping the phenotypic landscape of SCN2A-related disorders in unprecedented detail and revealing genotype-phenotype correlations along a multidimensional spectrum.
Details
- Language :
- English
- ISSN :
- 1530-0366
- Volume :
- 23
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Genetics in medicine : official journal of the American College of Medical Genetics
- Publication Type :
- Academic Journal
- Accession number :
- 33731876
- Full Text :
- https://doi.org/10.1038/s41436-021-01120-1