Nat Med::血液转录组测序可提高罕见病的诊断率

2019-08-16 佚名 生物通

斯坦福大学的研究人员近日发现,整合血液样本的转录组数据有助于提高罕见病患者的诊断率,并确定新的疾病相关基因。

斯坦福大学的研究人员近日发现,整合血液样本的转录组数据有助于提高罕见病患者的诊断率,并确定新的疾病相关基因。

全球大约有3.5亿人患有罕见病,这些疾病主要是由单个基因的突变引起的。即使是采用最成功的方法——全外显子组测序,目前的诊断率也只达到50%。

斯坦福大学的研究人员近日发现,整合血液样本的转录组数据有助于提高罕见病患者的诊断率,并确定新的疾病相关基因。这项成果于本周一发表在《Nature Medicine》杂志上。

斯坦福大学医学院的Stephen Montgomery及其同事采集了近百名罕见病患者的血液样本,并开展RNA测序(RNA-seq)分析。这些患者尚未确诊,属于16种不同的疾病类别。结果显示,这种方法的诊断率为7.5%,表明RNA测序有助于罕见病的诊断。

“这项工作证明了对外周血样本开展RNA-seq的作用,这是临床实践中最容易获得的标本,”研究人员在文中写道。

在这项研究中,Montgomery领导的团队采集了143名个体的全血样本,并收集了RNA-seq以及全外显子组(WES)或全基因组(WGS)数据。其中,94人身患罕见病,另外49人是未患病的家庭成员。

然后,他们将患者的RNA-seq数据与49名对照的数据进行比较,同时还与1,594名外部对照的数据进行比较,这些对照来自三个队列:抑郁基因和网络(DGN)、乌普萨拉老年人血管系统的前瞻性研究(PIVUS)项目以及基因型-组织表达(GTEx)联盟。

研究人员首次证实,许多已知的罕见病基因确实在血液中表达。对于每个罕见病样本,他们发现平均有343个基因存在异常表达。在根据功能丧失耐受性、等位基因特异性表达及其他参数进行过滤后,他们进一步缩小了候选基因列表。平均而言,每个病例的异常表达基因被缩小到不足10个。

与此同时,研究人员还鉴定出540个剪接异常的基因。根据表型以及其他标准对基因进行过滤,他们将每个病例的候选基因数量降至10个左右。他们还发现,对每个病例而言,平均有94个等位基因特异性表达事件与疾病存在关联。

将表达、剪接和等位基因特异性表达这三种信号相结合,研究人员确定了6个病例的致病基因(总共80个独立病例),诊断率达到7.5%。此外,对于30个具有候选基因信息的病例,他们确定了5个病例的候选基因,比例为16.7%。不过,他们仍然无法找到69个病例的相关候选基因。

研究人员指出,这些研究结果强调了RNA-seq的数据可以帮助确定致病基因。例如,他们在一对兄弟的MECR基因中发现了双等位基因的杂合致病变异,这两兄弟表现出运动方面的发育迟缓,并逐步发展为痉挛、共济失调步态和运动技能的丧失。

同样地,对于一名散发性脊髓性肌萎缩的患者,他们在ASAH1基因中发现了剪接变异。对于另一名发育倒退并伴有震颤和癫痫发作的患者,他们发现KCTD7基因的同义突变导致剪接点的产生。

研究人员认为,这表明RNA-seq有助于罕见病的诊断。“我们预计,结合多组学信息将在未来进一步改善罕见病的诊断,”他们在文中写道。

原始出处:Frésard L1, Smail C2, Ferraro NM2, e al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med. 2019 Jun;25(6):911-919.

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    2019-12-07 mjldent
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    2019-09-01 liye789132251
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    2019-08-18 syscxl
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