de Sainte Agathe Jean-Madeleine, Monin Pauline, Riccardi Florence, Nava Caroline, Arnaud Lionel, Mignot Cyril, Ville Dorothée, Auvin Stéphane, Tardieu Sandrine, Larcher Kathy, Gourfinkel-An Isabelle, Canon Mathilde, Navarro Vincent, Héron Bénédicte, Julia Sophie, Doummar Diane, Jacquemont Marie-Line, Maurey Hélène, Dozières-Puyravel Blandine, Perrin Laurence, Pasquier Laurent, Dubourg Christèle, Odent Sylvie, Bouazzaoui Abdelhakim, Carre Wilfrid, Fradin Mélanie, Demurger Florence, Chatron Nicolas, Sanlaville Damien, Essid Miriam, Portes Vincent des, Panagiotakaki Eleni, Poulat Anne-Lise, Rivier Clotilde, Sarret Catherine, Remerand Ganaëlle, Altuzarra Cecilia, Stoeva Radka, Nguyen Sylvie, Piard Juliette, Boucher Élise, Flurin Vincent, Guerrot Anne-Marie, Joriot Sylvie, Desnous Béatrice, Villeneuve Nathalie, Lépine Anne, Camus Caroline Hachon-Le, Villard Laurent, Faoucher Marie, Milh Mathieu, Lesca Gaëtan, Leguern Éric
Département de Génétique Médicale, APHP, Sorbonne Université, Paris, France.
Inserm, CNRS UMR1127, Institut du Cerveau-Paris Brain Institute-ICM, Sorbonne Université, Paris, France.
Eur J Neurol. 2025 Aug;32(8):e70324. doi: 10.1111/ene.70324.
Epileptic disorders are a heterogeneous group of neurological conditions, with many cases linked to monogenic causes, particularly in developmental and epileptic encephalopathies (DEE). Identifying pathogenic variants aids treatment, prognosis, and family planning. In France, genetic testing is coordinated through the EpiGene network.
We analyzed clinical and genetic data from 2563 epilepsy patients referred to four diagnostic labs (2016-2023). Epilepsy syndromes were classified via pre-test questionnaires, and genotyping used various gene panels, including a 68-gene core panel. Multivariate logistic regression assessed diagnostic rates and genotype-phenotype correlations.
Overall, 27.0% of patients had pathogenic/likely pathogenic variants, mainly within the core panel (24%). SCN1A and KCNQ2 were the most frequently mutated genes. Diagnostic yield varied by syndrome, with Dravet Syndrome Spectrum (DSS) and early-infantile DEE (EIDEE) showing the highest rates (41% and 34%, respectively). Genetic heterogeneity differed across syndromes, from DSS (predominantly SCN1A) to Infantile Epileptic Spasms Syndrome (IESS, 12%), involving ≥ 26 genes. Outside DEE, self-limited neonatal epilepsy (SeLNE) had the highest yield (50%). Earlier seizure onset was associated with a higher likelihood of a positive molecular diagnosis, whereas intellectual disability severity and drug resistance were not independently predictive of diagnostic outcome. Genotype-phenotype correlations highlighted that objective clinical data (e.g., age of onset) can outperform syndrome labels (e.g., EIDEE) in predicting diagnosis.
This large cohort study refines the genetic landscape of epilepsy, informs classification challenges, and enhances genetic testing strategies, ultimately improving patient care and future research directions.
癫痫性疾病是一组异质性神经疾病，许多病例与单基因病因有关，尤其是在发育性和癫痫性脑病（DEE）中。识别致病变异有助于治疗、预后评估和计划生育。在法国，基因检测通过EpiGene网络进行协调。
我们分析了转诊至四个诊断实验室的2563例癫痫患者的临床和基因数据（2016 - 2023年）。通过检测前问卷对癫痫综合征进行分类，基因分型使用了各种基因panel，包括一个68基因的核心panel。多变量逻辑回归评估诊断率和基因型 - 表型相关性。
总体而言，27.0%的患者有致病/可能致病变异，主要在核心panel内（24%）。SCN1A和KCNQ2是最常突变的基因。诊断率因综合征而异，Dravet综合征谱系（DSS）和早发性婴儿DEE（EIDEE）的诊断率最高（分别为41%和34%）。不同综合征的基因异质性不同，从DSS（主要为SCN1A）到婴儿痉挛症综合征（IESS，12%），涉及≥26个基因。在DEE之外，自限性新生儿癫痫（SeLNE）的诊断率最高（50%）。癫痫发作起始越早，分子诊断阳性的可能性越高，而智力残疾严重程度和耐药性并非诊断结果的独立预测因素。基因型 - 表型相关性突出表明，在预测诊断方面，客观临床数据（如发病年龄）比综合征标签（如EIDEE）更具优势。
这项大型队列研究细化了癫痫的遗传图谱，为分类挑战提供了信息，并增强了基因检测策略，最终改善了患者护理和未来研究方向。
