Mascarenhas Rumika, Merrikh Daria, Khanbabaei Maryam, Kaur Navprabhjot, Ghaderi Navid, Maroilley Tatiana, Liu Yiping, Soule Tyler, Appendino Juan Pablo, Jacobs Julia, Wiebe Samuel, Hader Walter, Pfeffer Gerald, Tarailo-Graovac Maja, Klein Karl Martin
Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada.
Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.
Epilepsia. 2025 Apr;66(4):1234-1249. doi: 10.1111/epi.18251. Epub 2025 Jan 3.
Somatic variants causing epilepsy are challenging to detect, as they are only present in a subset of brain cells (e.g., mosaic), resulting in low variant allele frequencies. Traditional methods relying on surgically resected brain tissue are limited to patients undergoing brain surgery. We developed an improved protocol to detect somatic variants using DNA from stereoelectroencephalographic (SEEG) depth electrodes, enabling access to a larger patient cohort and diverse brain regions. This protocol mitigates issues of contamination and low yields by purifying neuronal nuclei using fluorescence-activated nuclei sorting (FANS).
SEEG depth electrodes were collected upon extraction from 41 brain regions across 17 patients undergoing SEEG. Nuclei were isolated separately from depth electrodes in the affected brain regions (seizure onset zone) and the unaffected brain regions. Neuronal nuclei were isolated using FANS, and DNA was amplified using primary template amplification. Short tandem repeat (STR) analysis and postsequencing allelic imbalance assessment were used to evaluate sample integrity. High-quality amplified DNA samples from affected brain regions, patient-matched unaffected brain regions, and genomic DNA were subjected to whole exome sequencing (WES). A bioinformatic workflow was developed to reduce false positives and to accurately detect somatic variants in the affected brain region.
Based on DNA yield and STR analysis, 14 SEEG-derived neuronal DNA samples (seven affected and seven unaffected) across seven patients underwent WES. From the variants prioritized using our bioinformatic workflow, we chose four candidate variants in MTOR, CSDE1, KLLN, and NLE1 across four patients based on pathogenicity scores and association with phenotype. All four variants were validated using digital droplet polymerase chain reaction.
Our approach enhances the reliability and applicability of SEEG-derived DNA for epilepsy, offering insights into its molecular basis, facilitating epileptogenic zone identification, and advancing precision medicine.
导致癫痫的体细胞变异难以检测，因为它们仅存在于一部分脑细胞中（例如，嵌合体），导致变异等位基因频率较低。依赖手术切除脑组织的传统方法仅限于接受脑部手术的患者。我们开发了一种改进方案，利用立体脑电图（SEEG）深度电极的DNA检测体细胞变异，从而能够纳入更多患者并获取不同的脑区。该方案通过使用荧光激活核分选（FANS）纯化神经元核，减轻了污染和产量低的问题。
从17例接受SEEG的患者的41个脑区提取SEEG深度电极。分别从受影响脑区（癫痫发作起始区）和未受影响脑区的深度电极中分离细胞核。使用FANS分离神经元核，并使用初级模板扩增法扩增DNA。使用短串联重复序列（STR）分析和测序后等位基因不平衡评估来评估样本完整性。对来自受影响脑区、患者匹配的未受影响脑区的高质量扩增DNA样本以及基因组DNA进行全外显子组测序（WES）。开发了一种生物信息学工作流程，以减少假阳性并准确检测受影响脑区的体细胞变异。
基于DNA产量和STR分析，对7例患者的14个源自SEEG的神经元DNA样本（7个受影响和7个未受影响）进行了WES。根据致病性评分和与表型的关联，我们从使用我们的生物信息学工作流程确定优先级的变异中，选择了4例患者中MTOR、CSDE1、KLLN和NLE1中的4个候选变异。所有4个变异均使用数字液滴聚合酶链反应进行了验证。
我们的方法提高了源自SEEG的DNA用于癫痫研究的可靠性和适用性，为其分子基础提供了见解，有助于癫痫灶的识别，并推动精准医学的发展。
