Molecular and clinical spectrum of epilepsy-dyskinesia syndromes: a cross-sectional study of 609 patients

运动障碍 癫痫 医学 运动障碍 队列 表型 遗传学 生物 神经科学 基因 内科学 帕金森病 疾病
作者
Vicente Quiroz,Julian E. Alecu,Umar Zubair,Katerina Bernardi,Zainab Zaman,Joshua Rong,Amy Tam,Avaneesh Kunta,Habibah P Agianda,Nicole Battaglia,Hendrik Schmidt,Dario Resch,Noah Wyman,Lindsey M. Vogt,Wafa Bani Uraba,Leonie Becker,Kavitha Kothur,Deepak Gill,Bernardita Suárez,J. Jofre
出处
期刊:Brain [Oxford University Press]
卷期号:149 (2): 563-578 被引量:8
标识
DOI:10.1093/brain/awaf297
摘要

Epilepsy-dyskinesia syndromes (EDS) are a complex group of neurogenetic disorders characterized by the co-occurrence of epilepsy and movement disorders. Despite their increasing clinical recognition, the molecular and clinical spectrum of EDS remains poorly understood. While numerous genetic aetiologies have been implicated, systematic characterization across diverse populations is lacking. This study aimed to delineate the molecular and clinical landscape of EDS in a large, multinational cohort, focusing on movement disorder phenomenologies, genotype-phenotype correlations, and treatment responses. We conducted a multicentre, cross-sectional study involving 609 patients with childhood-onset movement disorders associated with pathogenic variants in 105 predefined genes. Clinical data were collected from over 30 centres across 25 countries using a standardized survey, capturing movement disorder phenomenologies, seizure types, developmental trajectories, motor function and treatment outcomes. We classified EDS-associated genes into biologically meaningful groups by performing unsupervised clustering, which integrated protein-protein interactions and functional data. Genotype-phenotype correlations were assessed using a one-versus-remainder approach to quantify differential enrichment of clinical manifestations and treatment responses. Pathogenic variants were identified in 74 of the 105 predefined genes, with 12 genes accounting for two-thirds of cases. The most frequently reported genes were MECP2, ATP1A3, and GNAO1. Data-driven gene cluster analysis identified 12 functional groups, mapping EDS to relevant biological pathways and informing genotype-phenotype analyses. Dystonia (34.2%), stereotypies (24.6%) and ataxia (16.2%) were the most prevalent movement disorders, with gene- and pathway-specific movement disorder signatures extending beyond previously known associations. Notably, most patients exhibited mixed movement disorders, highlighting the phenotypic complexity of EDS. Epilepsy was diagnosed in only 66.8% of cases, suggesting that some EDS primarily manifest as movement disorders. Developmental trajectories varied by genetic aetiology. Pharmacological responses demonstrated gene- and pathway-specific treatment effects, confirming established therapeutic associations (e.g. PRRT2 variants responding to carbamazepine) and identifying previously unrecognized effects, such as exacerbation of motor symptoms with levodopa/carbidopa in GNAO1 and MECP2 variants. This study provides a detailed characterization of EDS, identifying distinct genetic, phenotypic and therapeutic patterns. The findings underscore the need for early recognition of movement disorders within epilepsy cohorts, offer immediate insights to improve anticipatory guidance and clinical management of EDS, and advocate for personalized treatment strategies. By laying the groundwork for longitudinal studies to refine genotype-phenotype correlations and establish a natural history, this work paves the way for interventional clinical trials and precision medicine approaches.
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