Abstract

The objective of this study is to report the results of the genetic analysis in a large and well-characterized population with pediatric-onset epilepsies and to identify those who could benefit from precision medicine treatments. In this retrospective observational study, we consecutively recruited patients with pediatric-onset epilepsy observed at a tertiary neurological center over a time span of 7 years, collecting clinical and laboratory findings. Following in-depth diagnostic process to exclude possible structural and metabolic causes of the disease, patients with a suspected genetically determined etiology underwent next-generation sequencing (NGS) screening with panels for the analysis of target genes causative of epilepsy. We detected likely pathogenic or pathogenic variants (classes IV and V) in 24% of the 562 patients who underwent genetic investigations. By the evaluation of patients' data, we observed that some features (onset of epilepsy before one year old, presence of neurological deficits, psychomotor delay/cognitive disability, and malformative aspects at brain MRI) were significantly associated with class IV or V variants. Moreover, statistical analysis showed that the diagnostic yield resulted higher for patients affected by Progressive Myoclonic Epilepsy (PME) and with early onset developmental and epileptic encephalopathies (DEE), compared with focal epilepsies, genetic generalized epilepsies, DEE with onset at/after 1 y.o., and unclassified epileptic syndromes. According to the results of the genetic screening, up to 33% of patients carrying class IV or V variants resulted potentially eligible for precision medicine treatments. The large-scale application of NGS multigene panels of analysis is a useful tool for the molecular diagnosis of patients with pediatric-onset epilepsies, allowing the identification of those who could benefit from a personalized therapeutic approach. The analysis of patients with pediatric-onset epilepsy using advanced technologies for the screening of all the implicated genes allows the identification of the cause of diseases in an ever-increasing number of cases. Understanding the pathogenic mechanisms could, in some cases, guide the selection and optimization of appropriate treatment approaches for patients.

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