Fung Cheuk-Wing, Kwong Anna Ka-Yee, Wong Virginia Chun-Nei
Division of Paediatric Neurology/Developmental Behavioural Paediatrics/Neurohabilitation Department of Paediatrics and Adolescent Medicine Li Ka Shing Faculty of Medicine the University of Hong Kong Hong Kong SAR China.
Epilepsia Open. 2017 May 4;2(2):236-243. doi: 10.1002/epi4.12055. eCollection 2017 Jun.
Epileptic encephalopathy (EE) is a heterogeneous condition associated with deteriorations of cognitive, sensory and/or motor functions as a consequence of epileptic activity. The phenomenon is the most common and severe in infancy and early childhood. Genetic-based diagnosis in EE patients is challenging owing to genetic and phenotypic heterogeneity of numerous monogenic disorders and the fact that thousands of genes are involved in neurodevelopment. Therefore, high-throughput next-generation sequencing (NGS) was used to investigate the genetic causes of non-syndromic cryptogenic neonatal/infantile EE (NIEE).
We have selected a cohort of 31 patients with seizure cryptogenic NIEE and seizure onset before 24 months. All investigations including metabolic work-up, were negative. Using NGS, we distinguished a panel of 430 epilepsy-associated genes by NGS was utilized to identify possible pathogenic variants in the patients. Segregation analysis and multiple silico analysis prediction tools were used for pathogenicity assessment. The identified variants were classified as "pathogenic," "likely pathogenic" and "uncertain significance," according to the American College of Medical Genetics (ACMG) guidelines.
Pathogenic or likely pathogenic variants were identified in six genes ( [1], [2] [2] [1] [1] [2]) in 9 NIEE patients (9/31; 29%). Variants of uncertain significance (VUS) were found in and in 2 NIEE patients (2/31; 6%). Most phenotypes in our cohort matched with those reported cases.
The diagnostic rate (29%) of pathogenic and likely pathogenic variants was comparable to the recent studies of early-onset epileptic encephalopathy, indicating that gene panel analysis through NGS is a powerful tool to investigate cryptogenic NIEE in patients. Six percent of patients had neurometabolic disorders. Some of our diagnosed cases illustrated that successful molecular investigation may allow a better treatment strategy and avoid unnecessary and even invasive investigations. Functional analysis could be performed to further study the pathogenicity of the VUS identified in and .
癫痫性脑病（EE）是一种异质性疾病，因癫痫活动导致认知、感觉和/或运动功能恶化。这种现象在婴儿期和幼儿期最为常见和严重。由于众多单基因疾病的遗传和表型异质性以及数千个基因参与神经发育，对EE患者进行基于基因的诊断具有挑战性。因此，采用高通量下一代测序（NGS）来研究非综合征性隐源性新生儿/婴儿EE（NIEE）的遗传病因。
我们选取了31例癫痫性隐源性NIEE患者，其癫痫发作起始于24个月之前。包括代谢检查在内的所有检查均为阴性。使用NGS，我们通过NGS区分了一组430个癫痫相关基因，以识别患者中可能的致病变异。分离分析和多种计算机分析预测工具用于致病性评估。根据美国医学遗传学学会（ACMG）指南，将鉴定出的变异分为“致病的”、“可能致病的”和“意义不明确的”。
在9例NIEE患者（9/31；29%）中，在6个基因（[1]、[2][2][1][1][2]）中鉴定出致病或可能致病的变异。在2例NIEE患者（2/31；6%）中，在和中发现了意义不明确的变异（VUS）。我们队列中的大多数表型与报道病例相符。
致病和可能致病变异的诊断率（29%）与近期早发性癫痫性脑病的研究相当，表明通过NGS进行基因panel分析是研究患者隐源性NIEE的有力工具。6%的患者患有神经代谢紊乱。我们的一些诊断病例表明，成功的分子研究可能会带来更好的治疗策略，并避免不必要甚至侵入性的检查。可进行功能分析以进一步研究在和中鉴定出的VUS的致病性。
