通过外体数据再分析检测到的致病性隐秘变异显著增加了乔伯特综合征的诊断产量
Fulvio D'Abrusco1, Valentina Serpieri1, Cecilia Maria Taccagni1
1Department of Molecular Medicine, University of Pavia, Pavia, Italy.
European journal of human genetics : EJHG
|October 11, 2024
概括
重新分析外基因组测序数据,在朱伯特综合征 (JS) 患者中发现了神秘的遗传变异. 这种方法使诊断产量增加了24%,揭示了之前错过的纤毛病基因突变.
科学领域:
- 遗传学 是一个遗传学.
- 神经科学是一个神经科学.
- 分子生物学分子生物学
背景情况:
- 朱伯特综合征 (JS) 是一种复杂的神经发育障碍,由各种基因突变引起.
- 目前的诊断方法,包括外基因组测序 (ES),让大量的JS患者未被诊断出来.
- 确定JS的遗传基础对于诊断,预后和潜在的治疗策略至关重要.
研究的目的:
- 通过重新分析现有的外基因组测序数据,提高乔伯特综合征的诊断产量.
- 为了揭示神秘的遗传变异,如副本数变异 (CNVs) 和内部拼接变化,这些在初步分析中错过了.
- 确定这些神秘变体在未被诊断的JS病例中的频率和影响.
主要方法:
- 从最初缺乏明确诊断的JS患者的原始外因子测序 (ES) 数据的有针对性的再分析.
- 系统地搜索影响拼接的副本数变异 (CNVs) 和内部变异.
- 使用实时PCR,染色体微阵列,RT-PCR和小基因分析等技术验证已识别的变异.
- 扩展对隐秘变体的搜索到对外体测序负JS个体的队列.
主要成果:
- 在54% (14/26) 的患者中,鉴定出了神秘的"第二次击中"变体,这些患者具有明显的异性致病性编码变体.
- 在7% (3/44) 的患者中,通过外体序列测序发现了双性隐形变异,这些患者最初呈阴性.
- 聚焦的再分析策略实现了24% (17/70名患者) 的整体诊断收益.
- 副本数变异和内基拼接变异被证实是JS的显著突变机制.
结论:
- 重新分析外基因组测序数据是提高乔伯特综合征诊断产量的高效策略.
- 密码变体,特别是CNV和拼接缺陷,是未被诊断的JS的常见原因.
- 这种方法显著改善了诊断,特别是对于基因异构变异的患者,如KIAA0586,CC2D2A和CPLANE1.
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