Abstract

Recent studies have identified brain somatic variants as a cause of focal epilepsy. These studies relied on resected tissue from epilepsy surgery, which is not available in most patients. The use of trace tissue adherent to depth electrodes used for stereo electroencephalography (EEG) has been proposed as an alternative but is hampered by the low cell quality and contamination by nonbrain cells. Here, we use our improved depth electrode harvesting technique that purifies neuronal nuclei to achieve molecular diagnosis in a patient with focal cortical dysplasia (FCD). Depth electrode tips were collected, pooled by brain region and seizure onset zone, and nuclei were isolated and sorted using fluorescence-activated nuclei sorting (FANS). Somatic DNA was amplified from neuronal and astrocyte nuclei using primary template amplification followed by exome sequencing of neuronal DNA from the affected pool, unaffected pool, and saliva. The identified variant was validated using droplet digital polymerase chain reaction (PCR). An 11-year-old male with drug-resistant genetic-structural epilepsy due to left anterior insula FCD had seizures from age 3 years. Stereo EEG confirmed seizure onset in the left anterior insula. The two anterior insula electrodes were combined as the affected pool and three frontal electrodes as the unaffected pool. FANS isolated 140 neuronal nuclei from the affected and 245 neuronal nuclei from the unaffected pool. A novel somatic missense MTOR variant (p.Leu489Met, CADD score 23.7) was identified in the affected neuronal sample. Droplet digital PCR confirmed a mosaic gradient (variant allele frequency = .78% in affected neuronal sample; variant was absent in all other samples). Our findings confirm that harvesting neuronal DNA from depth electrodes followed by molecular analysis to identify brain somatic variants is feasible. Our novel method represents a significant improvement compared to the previous method by focusing the analysis on high-quality cells of the cell type of interest.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call