错义突变
癫痫
基因型
队列
外显子组测序
复合杂合度
外显子组
医学
遗传学
生物
等位基因
基因
儿科
突变
内科学
精神科
作者
Dongfang Zou,Xiaoyan Li,Xinguo Lu,Huaili Wang,Wang Song,Mengwen Zhang,Xiao‐Rong Liu,Bing-Mei Li,Jianxiang Liao,Jianmin Zhong,Heng Meng,Bin Li
标识
DOI:10.1016/j.seizure.2023.03.003
摘要
Purpose The FAT1 gene encodes FAT atypical cadherin 1, which is essential for foetal development, including brain development. This study aimed to investigate the relationship between FAT1 variants and epilepsy. Methods Trio-based whole-exome sequencing was performed on a cohort of 313 patients with epilepsy. Additional cases with FAT1 variants were collected from the China Epilepsy Gene V.1.0 Matching Platform. Results Four pairs of compound heterozygous missense FAT1 variants were identified in four unrelated patients with partial (focal) epilepsy and/or febrile seizures, but without intellectual disability/developmental abnormalities. These variants presented no/very low frequencies in the gnomAD database, and the aggregate frequencies in this cohort were significantly higher than those in controls. Two additional compound heterozygous missense variants were identified in two unrelated cases using the gene-matching platform. All patients experienced infrequent (yearly/monthly) complex partial seizures or secondary generalised tonic-clonic seizures. They responded well toantiseizure medication, but seizures relapsed in three cases when antiseizure medication were decreased or withdrawn after being seizure-free for three to six years, which correlated with the expression stage of FAT1. Genotype-phenotype analysis showed that epilepsy-associated FAT1 variants were missense, whereas non-epilepsy-associated variants were mainly truncated. The relationship between FAT1 and epilepsy was evaluated to be "Strong" by the Clinical Validity Framework of ClinGen. Conclusions FAT1 is a potential causative gene of partial epilepsy and febrile seizures. Gene expression stage was suggested to be one of the considerations in determining the duration ofantiseizure medication. Genotype-phenotype correlation helps to explain the mechanisms underlying phenotypic variation.
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