结构和非编码变异增加了罕见疾病临床全基因组测序的诊断产量
Alistair T Pagnamenta1,2, Carme Camps1,2, Edoardo Giacopuzzi1,2,3
1Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK.
Genome medicine
|November 10, 2023
概括
全基因组测序 (WGS) 可以改善罕见疾病的诊断. 包括非编码区域在内的全面WGS分析显著增加了诊断产量,并确定了新的疾病基因.
科学领域:
- 基因组学就是基因组学.
- 罕见疾病 罕见疾病
- 临床诊断 临床诊断 临床诊断
背景情况:
- 全基因组测序 (WGS) 是用于罕见疾病诊断的宝贵工具.
- 目前WGS的诊断产量通常是有限的 (25-30%) 由于分析的重点是基因组或编码区域.
- 这凸显了对更全面的基因组分析方法的需求.
研究的目的:
- 评估综合WGS分析在罕见病患者队列中的诊断产量.
- 评估结构,拼接部位和非编码变异对诊断的贡献.
- 识别新型基因并扩大与罕见疾病相关的已知基因的表型谱.
主要方法:
- 全基因组测序 (WGS) 对122名无关罕见病患者及其亲属 (300个基因组) 进行.
- 患者使用基因面板或数组进行了预先选.
- 一个包含新算法 (SVRare,ALTSPLICE,GREEN-DB) 的生物信息管道被用于全面的变异分析,包括结构变异,拼接位置和非编码变异.
主要成果:
- 诊断产量为35% (43/122例),当考虑新型候选基因时,增加到39% (47/122例).
- 结构性,拼接部位和深层内在变异占解决病例的43% (20/47).
- 确定了五种新型基因,并扩大了RMND1的表型谱;临床诊断和治疗受到显著影响.
结论:
- 对整个基因组的全面分析,包括结构,拼接部位和内基因变异,对于最大限度地提高WGS的诊断产量至关重要.
- WGS可以显著地帮助识别罕见疾病的因果病因,缩短诊断旅程.
- 基因组测序是临床环境中强大的一线遗传测试.
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