Genetic heterogeneity in familial forms of genetic generalized epilepsy: from mono- to oligogenism.

IF 3.8 3区 医学 Q2 GENETICS & HEREDITY Human Genomics Pub Date : 2024-11-21 DOI:10.1186/s40246-024-00659-9
Maha Dahawi, Jean-Madeleine de Sainte Agathe, Mohamed S Elmagzoub, Elhami A Ahmed, Julien Buratti, Thomas Courtin, Eric Noé, Julie Bogoin, Bruno Copin, Fatima A Elmugadam, Wasma A Abdelgadir, Ahmed K M A Ahmed, Mohamed A Daldoum, Rayan Mamoon Ibrahim Altayeb, Mohamed Bashir, Leena Mohamed Khalid, Sahar Gamil, Sara Baldassari, Liena Elsayed, Boris Keren, Gregory Nuel, Ammar E Ahmed, Eric Leguern
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Abstract

Genetic generalized epilepsy (GGE) including childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy (JME), and GGE with tonic-clonic seizures (TCS) (GGE-TCS), is genetically influenced with a two- to four- fold increased risk in the first-degree relatives of patients. Since large families with GGE are very rare, international studies have focused on sporadic GGE patients using whole exome sequencing, suggesting that GGE are highly genetically heterogeneous and rather involve rare or ultra-rare variants. Moreover, a polygenic mode of inheritance is suspected in most cases. We performed SNP microarrays and whole exome sequencing in 20 families from Sudan, focusing on those with at least four affected members. Standard genetic filters and Endeavour algorithm for functional prioritization of genes selected likely susceptibility variants in FAT1, DCHS1 or ASTN2 genes. FAT1 and DCHS1 are adhesion transmembrane proteins interacting during brain development, while ASTN2 is involved in dendrite development. Our approach on familial forms of GGE is complementary to large-scale collaborative consortia studies of sporadic cases. Our study reinforces the hypothesis that GGE is genetically heterogeneous, even in a relatively limited geographic area, and mainly oligogenic, as supported by the low familial penetrance of GGE and by the Bayesian algorithm that we developed in a large pedigree with JME. Since populations with founder effect and endogamy are appropriate to study autosomal recessive pathologies, they would be also adapted to decipher genetic components of complex diseases, using the reported bayesian model.

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遗传性全身性癫痫家族形式的遗传异质性:从单基因到寡基因。
遗传性全身性癫痫(GGE),包括儿童失神癫痫、青少年失神癫痫、青少年肌阵挛性癫痫(JME)和伴强直阵挛发作(TCS)的全身性癫痫(GGE-TCS),受遗传因素影响,患者一级亲属患病风险增加两到四倍。由于 GGE 的大家庭非常罕见,因此国际研究重点关注使用全外显子组测序的散发性 GGE 患者,结果表明 GGE 具有高度遗传异质性,涉及罕见或超罕见变异。此外,大多数病例被怀疑具有多基因遗传模式。我们对来自苏丹的 20 个家庭进行了 SNP 微阵列和全外显子测序,重点研究了至少有四名患病成员的家庭。通过标准遗传过滤器和 Endeavour 算法对基因进行功能优先排序,筛选出 FAT1、DCHS1 或 ASTN2 基因中可能存在的易感变异。FAT1 和 DCHS1 是大脑发育过程中相互作用的粘附跨膜蛋白,而 ASTN2 则参与树突的发育。我们对家族性 GGE 的研究方法与对散发性病例的大规模合作研究是相辅相成的。我们的研究加强了这样的假设:即使在相对有限的地理区域内,GGE 也具有遗传异质性,而且主要是寡基因遗传,这一点得到了 GGE 家族低渗透性和我们在一个大型 JME 血统中开发的贝叶斯算法的支持。由于具有创始效应和内生性的人群适合研究常染色体隐性遗传病,因此也适合利用所报告的贝叶斯模型来破译复杂疾病的遗传成分。
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来源期刊
Human Genomics
Human Genomics GENETICS & HEREDITY-
CiteScore
6.00
自引率
2.20%
发文量
55
审稿时长
11 weeks
期刊介绍: Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics. Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.
期刊最新文献
Integration of single-cell sequencing and drug sensitivity profiling reveals an 11-gene prognostic model for liver cancer. SCAN: a nanopore-based, cost effective decision-supporting tool for mass screening of aneuploidies. Advancing understanding of human variability through toxicokinetic modeling, in vitro-in vivo extrapolation, and new approach methodologies. Genetic heterogeneity in familial forms of genetic generalized epilepsy: from mono- to oligogenism. Analysis of public perceptions on the use of artificial intelligence in genomic medicine.
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