Diagnostic Yield of Epilepsy-Genes Sequencing and Chromosomal Microarray in Pediatric Epilepsy

Kelly C Burk; Maki Kaneko; Catherine Quindipan; My H Vu; Maritza Feliz Cepin; Jonathan D Santoro; Michele Van Hirtum-Das; Deborah Holder; Gordana Raca

doi:10.1016/j.pediatrneurol.2023.10.014

Diagnostic Yield of Epilepsy-Genes Sequencing and Chromosomal Microarray in Pediatric Epilepsy

Pediatr Neurol. 2024 Jan:150:50-56. doi: 10.1016/j.pediatrneurol.2023.10.014. Epub 2023 Oct 27.

Authors

Kelly C Burk¹, Maki Kaneko², Catherine Quindipan², My H Vu³, Maritza Feliz Cepin⁴, Jonathan D Santoro⁵, Michele Van Hirtum-Das⁵, Deborah Holder⁵, Gordana Raca⁶

Affiliations

¹ Department of Neurology, Keck School of Medicine of the University of Southern California, Los Angeles, California.
² Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Center for Personalized Medicine, Los Angeles, California.
³ Biostatistics Core, The Saban Research Institute, Children's Hospital Los Angeles, Los Angeles, California.
⁴ Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles.
⁵ Department of Neurology, Keck School of Medicine of the University of Southern California, Los Angeles, California; Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles.
⁶ Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Center for Personalized Medicine, Los Angeles, California. Electronic address: graca@chla.usc.edu.

PMID: 37979304
DOI: 10.1016/j.pediatrneurol.2023.10.014

Abstract

Background: Around 40% of individuals with epilepsy have an underlying identifiable genetic etiology. Common methods for epilepsy genetic testing are chromosomal microarray (CMA) and epilepsy-genes sequencing (EGS). Historically, CMA was the first-line test for patients with epilepsy, but recent studies have shown that EGS has a superior diagnostic yield. To further optimize testing algorithms for epilepsy, we compared these tests' diagnostic yields and explored how they are influenced by age of onset and phenotype complexity.

Methods: Genetic test results from a cohort of patients with epilepsy were used to determine the diagnostic yield of CMA (n = 366) versus EGS (n = 370) for genetic epilepsy etiologies. Further analysis examined the probability of diagnostic results based on age of seizure onset and patients' phenotype complexity.

Results: For patients who underwent CMA, causative variants were found in 28 of 366 cases (7.7%), and 60 of 366 patients (16.4%) had at least one variant of uncertain significance (VUS). For EGS, 65 of 370 (17.6%) cases had causative variants, whereas 155 of 370 (41.9%) had at least one VUS. EGS had a significantly higher diagnostic yield than CMA (odds ratio [OR] = 2.63, P < 0.001). This difference in diagnostic yield was further pronounced among patients with infantile seizure onset (OR = 4.69, P < 0.001) and patients with additional neurological findings (OR = 2.99, P < 0.001).

Conclusion: To minimize the time and resources required to reach a diagnosis, clinicians and insurers alike should consider using EGS as an initial diagnostic tool.

Keywords: Epilepsy; Genetic testing; Molecular diagnostics; Precision medicine.

MeSH terms

Child
Epilepsy* / diagnosis
Epilepsy* / genetics
Genetic Testing / methods
Humans
Microarray Analysis
Phenotype
Seizures / genetics