Impact of rapid genomic testing on clinical outcomes of acutely unwell children presenting with severe epilepsy.
Sasaki E., Millington P., Sazonova T., Hanington L., Parrish A., Banos-Pinero B., Lord H., Taylor J., Jeeneea R., Sherlaw-Sturrock C., Parida A., Vogt J., Naik S., Sa M., Kini U.
UNLABELLED: About 30% of epilepsy patients remain unresponsive to standard antiseizure treatment. Increasing evidence suggests that genetic epilepsies may respond better to targeted management. In this study, we therefore evaluate the therapeutic benefits of rapid genetic testing in children with severe epilepsy. METHODS: the clinical data of patients with epilepsy referred for rapid whole-exome sequencing were systematically collected at two large paediatric/neurogenetic centres (Birmingham/Oxford) in the United Kingdom over 3 years (2019-2022), with follow-up at 12 months post-diagnosis. The demographics, diagnostic yield, management by gene function and seizure group (SZ-seizures only or SZ+ seizures with co-morbidities) were explored. RESULTS: among the 106 eligible patients, the age at testing ranged from 0 to 16 years with a median of 7 months. Underserved ethnic groups, e.g., British Asians and Black British, were well-represented. Thirty-nine genes affecting 49 patients were identified, giving an overall diagnostic yield of 46%, which was further enhanced to 51% (31/61) in the SZ+ group. Twenty percent of genes identified affect ion channels and patients were more likely to present early (<6 months old) and respond to a gene-directed treatment (p = 0.004483). Seizures secondary to metabolic disorders responded to bespoke therapy. A fifth (22/106) of tested patients and 45% (22/49) of those diagnosed had their management impacted. At the 12-month follow-up, 9/15 (60%) patients remained seizure-free following gene-targeted management. CONCLUSION: this study demonstrates high diagnostic yield and significant therapeutic benefit from rapid genetic testing in patients with epilepsy. The gene function categories were statistically significant predictors of management change.