Exhaustive non-synonymous variants functionality prediction enables high resolution characterization of the neurofibromin architecture
| Autor: | Shay Ben-Shachar, Deeann Wallis, Ofer Isakov, D. Gareth Evans |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Nonsynonymous substitution Untranslated region OR Odds Ratio Research paper DRF Distributed Random Forest LOVD Leiden Open Variation Database 030105 genetics & heredity mRNA Messanger Ribonucleic acid ExAC Exome Aggregation Consortium Databases Genetic Missense mutation Genetic variant gnomAD Genome Aggregation Database Neurofibromatosis type I Neurofibromin 1 biology Variant prioritization ROC Receiver Operating Characteristic Functional annotation General Medicine Exons Prognosis FPR False Positive Rate SNV Single Nucleotide Variant XRT eXtremely Randomized Trees CI Confidence Intervals GLM Generalized Linera Model GRD GAP Related Domain congenital hereditary and neonatal diseases and abnormalities Neurofibromatosis 1 NF1 Neurofibromatosis Type 1 CALM Café Au Lait Macules GBM Gradient Boosting Machine Computational biology Models Biological Polymorphism Single Nucleotide General Biochemistry Genetics and Molecular Biology Domain (software engineering) 03 medical and health sciences Machine learning medicine Humans Genetic Predisposition to Disease Codon AUC Area Under the Curve Gene Genetic Association Studies UTR Untranslated Regions Computational Biology Genetic Variation Molecular Sequence Annotation medicine.disease 030104 developmental biology ROC Curve biology.protein Leiden Open Variation Database |
| Zdroj: | Isakov, O, Wallis, D, Evans, D G & Ben-shachar, S 2018, ' Exhaustive non-synonymous variants functionality prediction enables high resolution characterization of the neurofibromin architecture ', EBioMedicine, vol. 36 . https://doi.org/10.1016/j.ebiom.2018.09.039 EBioMedicine |
| DOI: | 10.1016/j.ebiom.2018.09.039 |
| Popis: | Background Neurofibromatosis type I (NF1) is caused by heterozygous loss-of-function variants in the NF1 gene encoding neurofibromin which serves as a tumor suppressor that inhibits RAS signaling and regulates cell proliferation and differentiation. While, the only well-established functional domain in the NF1 protein is the GAP-related domain (GRD), most of the identified non-truncating disease-causing variants are located outside of this domain, supporting the existence of other important disease-associated domains. Identifying these domains may reveal novel functions of NF1. Methods By implementing inferential statistics combined with machine-learning methods, we developed a novel NF1-specific functional prediction model that focuses on nonsynonymous single nucleotide variants (SNVs). The model enables annotating all possible NF1 nonsynonymous variants, thus mapping the range of pathogenic non-truncating variants at the codon level across the NF1 gene. Findings The generated model demonstrates high absolute prediction value for missense and splice-site variations (area under the ROC curve of 0.96) outperforming 14 other established models. By reviewing the entire dataset of nonsynonymous variants, two novel domains (Armadillo type fold 1 and 2) were identified as being associated with pathogenicity (OR 1.86; CI 1.04 to 3.34 and OR 2.08; CI 1.08 to 4.04, respectively; P |
| Databáze: | OpenAIRE |
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