Guella Ilaria, McKenzie Marna B, Evans Daniel M, Buerki Sarah E, Toyota Eric B, Van Allen Margot I, Suri Mohnish, Elmslie Frances, Simon Marleen E H, van Gassen Koen L I, Héron Delphine, Keren Boris, Nava Caroline, Connolly Mary B, Demos Michelle, Farrer Matthew J
Centre for Applied Neurogenetics, University of British Columbia, Vancouver, BC V5R 6H8, Canada.
Department of Neuropediatrics, Development, and Rehabilitation, University Children's Hospital, Inselspital, 3010 Berne, Switzerland.
Am J Hum Genet. 2017 Aug 3;101(2):300-310. doi: 10.1016/j.ajhg.2017.07.004.
Massively parallel sequencing has revealed many de novo mutations in the etiology of developmental and epileptic encephalopathies (EEs), highlighting their genetic heterogeneity. Additional candidate genes have been prioritized in silico by their co-expression in the brain. Here, we evaluate rare coding variability in 20 candidates nominated with the use of a reference gene set of 51 established EE-associated genes. Variants within the 20 candidate genes were extracted from exome-sequencing data of 42 subjects with EE and no previous genetic diagnosis. We identified 7 rare non-synonymous variants in 7 of 20 genes and performed Sanger sequence validation in affected probands and parental samples. De novo variants were found only in SLC1A2 (aka EAAT2 or GLT1) (c.244G>A [p.Gly82Arg]) and YWHAG (aka 14-3-3γ) (c.394C>T [p.Arg132Cys]), highlighting the potential cause of EE in 5% (2/42) of subjects. Seven additional subjects with de novo variants in SLC1A2 (n = 1) and YWHAG (n = 6) were subsequently identified through online tools. We identified a highly significant enrichment of de novo variants in YWHAG, establishing their role in early-onset epilepsy, and we provide additional support for the prior assignment of SLC1A2. Hence, in silico modeling of brain co-expression is an efficient method for nominating EE-associated genes to further elucidate the disorder's etiology and genotype-phenotype correlations.
大规模平行测序揭示了发育性和癫痫性脑病(EEs)病因中的许多新生突变,突出了它们的遗传异质性。通过在大脑中的共表达,其他候选基因已在计算机上被优先排序。在这里,我们评估了使用51个已确定的与EE相关基因的参考基因集提名的20个候选基因中的罕见编码变异。从42名患有EE且先前未进行基因诊断的受试者的外显子测序数据中提取了20个候选基因内的变异。我们在20个基因中的7个中鉴定出7个罕见的非同义变异,并在受影响的先证者及其父母样本中进行了桑格序列验证。仅在溶质载体家族1成员2(SLC1A2,又名EAAT2或GLT1)(c.244G>A [p.Gly82Arg])和14-3-3γ蛋白(YWHAG,又名14-3-3γ)(c.394C>T [p.Arg132Cys])中发现了新生变异,这突出了5%(2/42)的受试者中EE的潜在病因。随后通过在线工具又鉴定出另外7名在SLC1A2(n = 1)和YWHAG(n = 6)中有新生变异的受试者。我们在YWHAG中发现了新生变异的高度显著富集,确立了它们在早发性癫痫中的作用,并为先前对SLC1A2的认定提供了额外支持。因此,大脑共表达的计算机模拟是一种提名与EE相关基因的有效方法,以进一步阐明该疾病的病因和基因型-表型相关性。