Impact of Genetic Testing Using Gene Panels, Exomes, and Genome Sequencing in Romanian Children with Epilepsy.

Epilepsy is a prevalent neurological condition, having a wide range of phenotypic traits, which complicate the diagnosis process. Next-generation sequencing (NGS) techniques have improved the diagnostics for unexplained epilepsies. Our goal was to evaluate the utility and impact of genetic testing in the clinical management of pediatric epilepsies. In addition, we aimed to identify clinical factors that could predict a genetic diagnosis. This was a retrospective study of 140 pediatric patients with epilepsy with or without other neurological conditions that underwent NGS testing (multigene panel, WES = whole exome sequencing and/or WGS = whole genome sequencing). A comparison between genetically diagnosed versus non-diagnosed children was performed based on different clinical features. Univariate and multivariate logistic regression analysis was performed to identify clinical predictors of a positive genetic diagnosis. Most children underwent gene panel testing, while 30 had exome sequencing and 3 had genome sequencing. The overall diagnostic yield of genetic testing was 28.6% (40/140) for more than 28 genes. The most frequently identified genes with causative variants were (n = 4), (n = 3), (n = 3), (n = 2), (n = 2), (n = 2), and (n = 2). Significant predictors from the logistic regression model were a younger age at seizure onset ( = 0.015), the presence of intellectual disability ( = 0.021), and facial dysmorphism ( = 0.049). A genetic diagnosis led to an impact on the choice or duration of medication in 85% (34/40) of the children, as well as the recommendation for screening of comorbidities or multidisciplinary referrals in 45% (18/40) of children. Epilepsy is a highly heterogeneous disorder, both genetically and phenotypically. Less than one third of patients had a genetic diagnosis identified using panels, exomes, and/or genomes. An early onset and syndromic features (including global developmental delay) were more likely to receive a diagnosis and benefit from optimized disease management.