Voltage-gated sodium channel epilepsies in a tertiary care center: Phenotypic spectrum with correlation to predicted functional effects.

Developmental and epileptic encephalopathies Dravet Syndrome Epilepsy Gain-of-function Loss-of-function Sodium channel

Journal

Epilepsy & behavior : E&B
ISSN: 1525-5069
Titre abrégé: Epilepsy Behav
Pays: United States
ID NLM: 100892858

Informations de publication

Date de publication:
03 Jul 2024
Historique:
received: 29 02 2024
revised: 27 06 2024
accepted: 29 06 2024
medline: 5 7 2024
pubmed: 5 7 2024
entrez: 4 7 2024
Statut: aheadofprint

Résumé

Variants in sodium channel genes (SCN) are strongly associated with epilepsy phenotypes. Our aim in this study to evaluate the genotype and phenotype correlation of patients with SCN variants in our tertiary care center. In this retrospective study, patients with SCN variants and epilepsy who were followed up at our clinic between 2018 and 2022 were evaluated. Our study discussed the demographics of the patients, the seizure types, the age of seizure onset, the SCN variants, the domains and the functions of the variants, the magnetic resonance imaging findings, the motor, cognitive, and psychiatric comorbidities, and the response to anti-seizure medication. Genetic testing was conducted using a next-generation sequencing gene panel (epilepsy panel) or a whole-exome sequencing. For evaluating variant function, we used a prediction tool (https://funnc.shinyapps.io/shinyappweb/ site). To assess protein domains, we used the PER viewer (http://per.broadinstitute.org/). Twenty-three patients with SCN variants and epilepsy have been identified. Sixteen patients had variants in the SCN1A, six patients had variants in the SCN2A, and one patient had a variant in the SCN3A. Two novel SCN1A variants and two novel SCN2A variants were identified. The analysis revealed 14/23 missense, 6/23 nonsense, 2/23 frameshift, and 1/23 splice site variants in the SCN. There are seven variants predicted to be gain-of-function and 13 predicted to be loss-of-function. Among 23 patients; 11 had Dravet Syndrome, 6 had early infantile developmental and epileptic encephalopathy, three had genetic epilepsy with febrile seizures plus spectrum disorder, one had self-limited familial neonatal-infantile epilepsy, one had self-limited infantile epilepsy and one had infantile childhood development epileptic encephalopathy. Our cohort consists of mainly SCN1 variants, most of them were predicted to be loss of function. Dravet syndrome was the most common phenotype. The prediction tool used in our study demonstrated overall compatibility with clinical findings. Due to the diverse clinical manifestations of variant functions, it may assist in guiding medication selection and predicting outcomes. We believe that such a tool will help the clinician in both prognosis prediction and solving therapeutic challenges in this group where refractory seizures are common.

Sections du résumé

BACKGROUND BACKGROUND
Variants in sodium channel genes (SCN) are strongly associated with epilepsy phenotypes. Our aim in this study to evaluate the genotype and phenotype correlation of patients with SCN variants in our tertiary care center.
METHODS METHODS
In this retrospective study, patients with SCN variants and epilepsy who were followed up at our clinic between 2018 and 2022 were evaluated. Our study discussed the demographics of the patients, the seizure types, the age of seizure onset, the SCN variants, the domains and the functions of the variants, the magnetic resonance imaging findings, the motor, cognitive, and psychiatric comorbidities, and the response to anti-seizure medication. Genetic testing was conducted using a next-generation sequencing gene panel (epilepsy panel) or a whole-exome sequencing. For evaluating variant function, we used a prediction tool (https://funnc.shinyapps.io/shinyappweb/ site). To assess protein domains, we used the PER viewer (http://per.broadinstitute.org/).
RESULTS RESULTS
Twenty-three patients with SCN variants and epilepsy have been identified. Sixteen patients had variants in the SCN1A, six patients had variants in the SCN2A, and one patient had a variant in the SCN3A. Two novel SCN1A variants and two novel SCN2A variants were identified. The analysis revealed 14/23 missense, 6/23 nonsense, 2/23 frameshift, and 1/23 splice site variants in the SCN. There are seven variants predicted to be gain-of-function and 13 predicted to be loss-of-function. Among 23 patients; 11 had Dravet Syndrome, 6 had early infantile developmental and epileptic encephalopathy, three had genetic epilepsy with febrile seizures plus spectrum disorder, one had self-limited familial neonatal-infantile epilepsy, one had self-limited infantile epilepsy and one had infantile childhood development epileptic encephalopathy.
CONCLUSION CONCLUSIONS
Our cohort consists of mainly SCN1 variants, most of them were predicted to be loss of function. Dravet syndrome was the most common phenotype. The prediction tool used in our study demonstrated overall compatibility with clinical findings. Due to the diverse clinical manifestations of variant functions, it may assist in guiding medication selection and predicting outcomes. We believe that such a tool will help the clinician in both prognosis prediction and solving therapeutic challenges in this group where refractory seizures are common.

Identifiants

pubmed: 38964184
pii: S1525-5050(24)00311-1
doi: 10.1016/j.yebeh.2024.109930
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

109930

Informations de copyright

Copyright © 2024 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Fulya Kurekci (F)

Department of Pediatrics, Division of Pediatric Neurology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye. Electronic address: fulya.kurekci@istanbul.edu.tr.

Mehmet Akif Kilic (M)

Department of Pediatrics, Division of Pediatric Neurology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Sinan Akbas (S)

Department of Medical Genetics, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Rıdvan Avci (R)

Department of Pediatrics, Division of Pediatric Neurology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Ceyda Oney (C)

Department of Pediatrics, Division of Pediatric Neurology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Ayca Dilruba Aslanger (A)

Department of Medical Genetics, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Hulya Maras Genc (H)

Department of Pediatrics, Division of Pediatric Neurology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Nur Aydinli (N)

Department of Pediatrics, Division of Pediatric Neurology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Edibe Pembegul Yildiz (E)

Department of Pediatrics, Division of Pediatric Neurology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkiye.

Classifications MeSH