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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Multimodal Analysis of SCN1A Missense Variants Improves Interpretation of Clinically Relevant Variants in Dravet Syndrome

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Autor(es):
Gonsales, Marina C. [1] ; Montenegro, Maria Augusta [2] ; Preto, Paula [2] ; Guerreiro, Marilisa M. [2] ; Coan, Ana Carolina [2] ; Quast, Monica Paiva [3] ; Carvalho, Benilton S. [3] ; Lopes-Cendes, Iscia [1]
Número total de Autores: 8
Afiliação do(s) autor(es):
[1] Univ Estadual Campinas, Dept Med Genet & Genom Med, Brazilian Inst Neurosci & Neurotecnol, Sch Med Sci, Campinas, SP - Brazil
[2] Univ Estadual Campinas, Brazilian Inst Neurosci & Neurotecnol, Dept Neurol, Sch Med Sci, Campinas, SP - Brazil
[3] Univ Estadual Campinas, Brazilian Inst Neurosci & Neurotecnol, Inst Math Stat & Sci Comp, Dept Stat, Campinas, SP - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: FRONTIERS IN NEUROLOGY; v. 10, MAR 28 2019.
Citações Web of Science: 0
Resumo

Objective: We aimed to improve the classification of SCN1A missense variants in patients with Dravet syndrome (DS) by combining and modifying the current variants classification criteria to minimize inconclusive test results. Methods: We established a score classification workflow based on evidence of pathogenicity to adapt the classification of DS-related SCN1A missense variants. In addition, we compiled the variants reported in the literature and our cohort and assessed the proposed pathogenic classification criteria. We combined information regarding previously established pathogenic amino acid changes, mode of inheritance, population-specific allele frequencies, localization within protein domains, and deleterious effect prediction analysis. Results: Our meta-analysis showed that 46% (506/1,101) of DS-associated SCN1A variants are missense. We applied the score classification workflow and 56.5% (286/506) of the variants had their classification changed from VUS: 17.8% (90/506) into ``pathogenic{''} and 38.7% (196/506) as ``likely pathogenic.{''} Conclusion: Our results indicate that using multimodal analysis seems to be the best approach to interpret the pathogenic impact of SCN1A missense changes for the molecular diagnosis of patients with DS. By applying the proposed workflow, most DS related SCN1A variants had their classification improved. (AU)

Processo FAPESP: 13/07559-3 - Instituto Brasileiro de Neurociência e Neurotecnologia - BRAINN
Beneficiário:Fernando Cendes
Linha de fomento: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
Processo FAPESP: 13/18775-9 - Uso do zebrafish como modelo animal para o estudo de epilepsias genéticas
Beneficiário:Marina Coelho Gonsales
Linha de fomento: Bolsas no Brasil - Pós-Doutorado