Abstracts

Rationale: Recent data underline that genetic testing in childhood epilepsy can allow an accurate prognosis, impact management and likely limits the diagnostic odyssey and further unnecessary testing. This is especially true in children with early onset, drug-resistant epilepsy with neurodevelopmental disorders (Symonds JD & McTague, EJPN. 24:15-23 (2020)). Genetic testing in epilepsy most commonly involves a gene panel analysis, which is cost-effective and relatively rapid. Conversely, whole exome sequencing (WES) targets all coding genes, which is more likely to result in a higher number of variants of unknown significance (VUS) (Sands TT & Choi H, Curr Neurol Neurosci Rep. 17(5):45 (2017)).

To understand the possible pathogenicity of a VUS, one should ideally perform in vivo analysis. However, this takes time and preclinical research in a certified laboratory. To overcome this problem, there are computational tools for variant interpretation (e.g. Tian Y, et al. Sci Rep.9(1):12752 (2019)).

Methods: As part of the ERN EpiCARE network, the University Hospitals Leuven include the genetic basis in children with epilepsy in a standardized registry. Subsequent computational VUS analyses were performed by two online, computational tools (MutationTaster and InterVar) (Li Q & Wang K. Am J Hum Genet. 100(2):267–80 (2017); Schwarz JM, et al. Nature methods. 11 p. 361–2 (2017)). InterVar generates an automated interpretation of any VUS by using 18 criteria, validated by the American College of Medical Genetics and Genomics and MutationTaster is able to further analyze non-synonymous single nucleotide variants, InDels and non-coding variants (Oates S, et al. NPJ genomic Med. 3:13 (2018)).

Results: We have performed a focused analysis of 496 patients, seen in the outpatient clinic between January 2020 and January 2021. In those with genetic testing, 20% patients had a clear pathogenic mutation and almost 50% had a VUS. In total, 144 VUS were analyzed and without computational analysis we reached a diagnostic yield of 23.6%. After computational analysis, this yield increased to 31.3% due to the classification of 11 VUS as (likely) pathogenic. One of our patients is an 11-year-old boy with drug-resistant, generalized epilepsy and developmental disability. Three distinct VUS were detected by WES (table 1). Our in silico predictions showed that the IGLON5 and CACNA1H variants are likely benign and also present in a healthy control population, in clear contrast to the SLC7A3 variant. This latter variant follows a X-linked recessive inheritance pattern that explains why female carriers in this family are not affected.

Conclusions: Computational analysis led to a significant increase of the diagnostic yield. This yield is higher compared to recent reports (yield: 15-29%; e.g. Lindy AS, et al. Epilepsia. 59(5):1062–71 (2018)).

While future functional studies remain necessary to proof the pathogenicity of a certain VUS, segregation analyses and in silico predictions suggest SLC7A3 as the likely culprit gene for the epileptic phenotype in our case report.

Funding: Please list any funding that was received in support of this abstract.: None.