Over the past 10 years, the increasingly important role played by next-generation sequencing panels in the genetic diagnosis of epilepsy has led to a growing list of gene variants and a plethora of new scientific data. To date, however, there is still no consensus on what constitutes the "ideal panel design," or on the most rational criteria for selecting the best candidates for gene-panel analysis, even though both might optimize the cost-benefit ratio and the diagnostic efficiency of customized gene panels. Even though more and more laboratories are adopting whole-exome sequencing as a first-tier diagnostic approach, interpreting, "in silico," a set of epilepsy-related genes remains difficult. In the light of these considerations, we performed a systematic review of the targeted gene panels for epilepsy already reported in the available scientific literature, with a view to identifying the best criteria for selecting patients for gene-panel analysis, and the best way to design an "ideal," gold-standard panel that includes all genes with an established role in epilepsy pathogenesis, as well as those that might help to guide decisions regarding specific medical interventions and treatments. Our analyses suggest that the usefulness and diagnostic power of customized gene panels for epilepsy may be greatest when these panels are confined to rationally selected, relatively small, pools of genes, and applied in more carefully selected epilepsy patients (those with complex forms of epilepsy). A panel containing 64 genes, which includes the 45 genes harboring a significant number of pathogenic variants identified in previous literature, the 32 clinically actionable genes, and the 21 ILAE (International League Against Epilepsy) recommended genes, may represent an "ideal" core set likely able to provide the highest diagnostic efficiency and cost-effectiveness and facilitate gene prioritization when testing patients with whole-exome/whole-genome sequencing.
Keywords: CLAGs; Epilepsy; Genotype-phenotype correlations; Ideal gene panel.