Concise Review: Stem Cell Models of SCN1A-Related Encephalopathies—Current Perspective and Future Therapies

Genetic variant interpretation for the neurologist - A pragmatic approach in the next-generation sequencing era in childhood epilepsy

Genetic advances over the past decade have enhanced our understanding of the genetic landscape of childhood epilepsy. However a major challenge for clinicians ha been understanding the rationale and systematic approach towards interpretation of the clinical significance of variant(s) detected in their patients. As the clinical paradigm evolves from gene panels to whole exome or whole genome testing including rapid genome sequencing, the number of patients tested and variants identified per patient will only increase. Each step in the process of variant interpretation has limitations and there is no single criterion which enables the clinician to draw reliable conclusions on a causal relationship between the variant and disease without robust clinical phenotyping. Although many automated online analysis software tools are available, these carry a risk of misinterpretation. This guideline provides a pragmatic, real-world approach to variant interpretation for the child neurologist. The focus will be on ascertaining aspects such as variant frequency, subtype, inheritance pattern, structural and functional consequence with regard to genotype-phenotype correlations, while refraining from mere interpretation of the classification provided in a genetic test report. It will not replace the expert advice of colleagues in clinical genetics, however as genomic investigations become a first-line test for epilepsy, it is vital that neurologists and epileptologists are equipped to navigate this landscape.

Identification of five novel SCN1A variants

Background

Epilepsy is characterized by recurrent unprovoked seizures. Mutations in the voltage-gated sodium channel alpha subunit 1 (SCN1A) gene are the main monogenic cause of epilepsy. Type and location of variants make a huge difference in the severity of SCN1A disorder, ranging from the mild phenotype (genetic epilepsy with febrile seizures plus, GEFS+) to the severe phenotype (developmental and epileptic encephalopathies, DEEs). Dravet Syndrome (DS) is an infantile-onset DEE, characterized by drug-resistant epilepsy and temperature sensitivity or febrile seizures. Genetic test results reveal SCN1A variants are positive in 80% DS patients and DS is mainly caused by de novo variants.

Methods

Trio-whole exome sequencing (WES) was used to detect variants which were associated with clinical phenotype of five probands with epilepsy or twitching. Then, Sanger sequencing was performed to validate the five novel SCN1A variants and segregation analysis. After analyzing the location of five SCN1A variants, the pathogenic potential was assessed.

Results

In this study, we identified five novel SCN1A variants (c.4224G > C, c.3744_3752del, c.209del, c.5727_5734delTTTAAAACinsCTTAAAAAG and c.5776delT) as the causative variants. In the five novel SCN1A variants, four were de novo and the remaining one was inherited. All novel variants would be classified as "pathogenic" or "likely pathogenic."

Conclusion

The five novel SCN1A variants will enrich the SCN1A mutations database and provide the corresponding reference data for the further genetic counseling.

The Generation of Human iPSC Lines from Three Individuals with Dravet Syndrome and Characterization of Neural Differentiation Markers in iPSC-Derived Ventral Forebrain Organoid Model

Dravet syndrome (DRVT) is a rare form of neurodevelopmental disorder with a high risk of sudden unexpected death in epilepsy (SUDEP), caused mainly (>80% cases) by mutations in the SCN1A gene, coding the Nav1.1 protein (alfa-subunit of voltage-sensitive sodium channel). Mutations in SCN1A are linked to heterogenous epileptic phenotypes of various types, severity, and patient prognosis. Here we generated iPSC lines from fibroblasts obtained from three individuals affected with DRVT carrying distinct mutations in the SCN1A gene (nonsense mutation p.Ser1516*, missense mutation p.Arg1596His, and splicing mutation c.2589+2dupT). The iPSC lines, generated with the non-integrative approach, retained the distinct SCN1A gene mutation of the donor fibroblasts and were characterized by confirming the expression of the pluripotency markers, the three-germ layer differentiation potential, the absence of exogenous vector expression, and a normal karyotype. The generated iPSC lines were used to establish ventral forebrain organoids, the most affected type of neurons in the pathology of DRVT. The DRVT organoid model will provide an additional resource for deciphering the pathology behind Nav1.1 haploinsufficiency and drug screening to remediate the functional deficits associated with the disease.