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评估将 CNV 监测纳入遗传性视网膜疾病基因面板下一代测序检测中。

Assessment of the incorporation of CNV surveillance into gene panel next-generation sequencing testing for inherited retinal diseases.

机构信息

Manchester Centre for Genomic Medicine, Manchester Academic Health Sciences Centre, Manchester University NHS Foundation Trust, St Mary's Hospital, Manchester, UK.

Division of Evolution and Genomic Sciences, Neuroscience and Mental Health Domain, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

出版信息

J Med Genet. 2018 Feb;55(2):114-121. doi: 10.1136/jmedgenet-2017-104791. Epub 2017 Oct 26.

Abstract

BACKGROUND

Diagnostic use of gene panel next-generation sequencing (NGS) techniques is commonplace for individuals with inherited retinal dystrophies (IRDs), a highly genetically heterogeneous group of disorders. However, these techniques have often failed to capture the complete spectrum of genomic variation causing IRD, including CNVs. This study assessed the applicability of introducing CNV surveillance into first-tier diagnostic gene panel NGS services for IRD.

METHODS

Three read-depth algorithms were applied to gene panel NGS data sets for 550 referred individuals, and informatics strategies used for quality assurance and CNV filtering. CNV events were confirmed and reported to referring clinicians through an accredited diagnostic laboratory.

RESULTS

We confirmed the presence of 33 deletions and 11 duplications, determining these findings to contribute to the confirmed or provisional molecular diagnosis of IRD for 25 individuals. We show that at least 7% of individuals referred for diagnostic testing for IRD have a CNV within genes relevant to their clinical diagnosis, and determined a positive predictive value of 79% for the employed CNV filtering techniques.

CONCLUSION

Incorporation of CNV analysis increases diagnostic yield of gene panel NGS diagnostic tests for IRD, increases clarity in diagnostic reporting and expands the spectrum of known disease-causing mutations.

摘要

背景

遗传性视网膜疾病(IRDs)是一组高度遗传异质性的疾病,基因面板下一代测序(NGS)技术在其诊断中被广泛应用。然而,这些技术通常无法捕捉到导致 IRD 的完整基因组变异谱,包括 CNV。本研究评估了将 CNV 监测引入遗传性视网膜疾病一线基因面板 NGS 诊断服务的适用性。

方法

将三种读深算法应用于 550 名转诊个体的基因面板 NGS 数据集,并使用信息学策略进行质量保证和 CNV 过滤。通过认可的诊断实验室,对 CNV 事件进行确认并报告给转诊临床医生。

结果

我们确认了 33 个缺失和 11 个重复,这些发现确定了 25 个人的 IRD 确诊或暂定分子诊断。我们表明,至少 7%的因 IRD 接受诊断测试的个体在与临床诊断相关的基因中存在 CNV,并且所采用的 CNV 过滤技术的阳性预测值为 79%。

结论

CNV 分析的加入提高了遗传性视网膜疾病基因面板 NGS 诊断测试的诊断效果,增加了诊断报告的清晰度,并扩展了已知致病突变的范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eba0/5800348/cb8a7316e14c/jmedgenet-2017-104791f01.jpg

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