Pfundt Rolph, Del Rosario Marisol, Vissers Lisenka E L M, Kwint Michael P, Janssen Irene M, de Leeuw Nicole, Yntema Helger G, Nelen Marcel R, Lugtenberg Dorien, Kamsteeg Erik-Jan, Wieskamp Nienke, Stegmann Alexander P A, Stevens Servi J C, Rodenburg Richard J T, Simons Annet, Mensenkamp Arjen R, Rinne Tuula, Gilissen Christian, Scheffer Hans, Veltman Joris A, Hehir-Kwa Jayne Y
Department of Human Genetics, Donders Institute, Radboud University Medical Center, Nijmegen, The Netherlands.
Department of Clinical Genetics, GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.
Genet Med. 2017 Jun;19(6):667-675. doi: 10.1038/gim.2016.163. Epub 2016 Oct 27.
Copy-number variation is a common source of genomic variation and an important genetic cause of disease. Microarray-based analysis of copy-number variants (CNVs) has become a first-tier diagnostic test for patients with neurodevelopmental disorders, with a diagnostic yield of 10-20%. However, for most other genetic disorders, the role of CNVs is less clear and most diagnostic genetic studies are generally limited to the study of single-nucleotide variants (SNVs) and other small variants. With the introduction of exome and genome sequencing, it is now possible to detect both SNVs and CNVs using an exome- or genome-wide approach with a single test.
We performed exome-based read-depth CNV screening on data from 2,603 patients affected by a range of genetic disorders for which exome sequencing was performed in a diagnostic setting.
In total, 123 clinically relevant CNVs ranging in size from 727 bp to 15.3 Mb were detected, which resulted in 51 conclusive diagnoses and an overall increase in diagnostic yield of ~2% (ranging from 0 to -5.8% per disorder).
This study shows that CNVs play an important role in a broad range of genetic disorders and that detection via exome-based CNV profiling results in an increase in the diagnostic yield without additional testing, bringing us closer to single-test genomics.Genet Med advance online publication 27 October 2016.
拷贝数变异是基因组变异的常见来源,也是疾病的重要遗传原因。基于微阵列的拷贝数变异(CNV)分析已成为神经发育障碍患者的一线诊断检测方法,诊断率为10%-20%。然而,对于大多数其他遗传疾病,CNV的作用尚不清楚,大多数诊断性遗传学研究通常仅限于单核苷酸变异(SNV)和其他小变异的研究。随着外显子组和基因组测序的引入,现在可以通过一次检测,采用全外显子组或全基因组方法同时检测SNV和CNV。
我们对2603例受一系列遗传疾病影响的患者的数据进行了基于外显子组的读深度CNV筛查,这些患者的外显子组测序是在诊断环境中进行的。
总共检测到123个临床相关的CNV,大小从727bp到15.3Mb不等,这导致了51个明确的诊断,诊断率总体提高了约2%(每种疾病的诊断率从0到-5.8%不等)。
本研究表明,CNV在广泛的遗传疾病中起重要作用,通过基于外显子组的CNV分析进行检测可在无需额外检测的情况下提高诊断率,使我们更接近单检测基因组学。《遗传医学》于2016年10月27日在线提前发表。