Department of Pediatric Endocrinology and Genetic Metabolism, Shanghai Institute for Pediatric Research, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200092, China.
Clin Chem. 2020 Mar 1;66(3):455-462. doi: 10.1093/clinchem/hvz033.
Capture sequencing (CS) is widely applied to detect small genetic variations such as single nucleotide variants or indels. Algorithms based on depth comparison are becoming available for detecting copy number variation (CNV) from CS data. However, a systematic evaluation with a large sample size has not been conducted to evaluate the efficacy of CS-based CNV detection in clinical diagnosis.
We retrospectively studied 3010 samples referred to our diagnostic laboratory for CS testing. We used 68 chromosomal microarray analysis-positive samples (true set [TS]) and 1520 reference samples to build a robust CS-CNV pipeline. The pipeline was used to detect candidate clinically relevant CNVs in 1422 undiagnosed samples (undiagnosed set [UDS]). The candidate CNVs were confirmed by an alternative method.
The CS-CNV pipeline detected 78 of 79 clinically relevant CNVs in TS samples, with analytical sensitivity of 98.7% and positive predictive value of 49.4%. Candidate clinically relevant CNVs were identified in 106 UDS samples. CNVs were confirmed in 96 patients (90.6%). The diagnostic yield was 6.8%. The molecular etiology includes aneuploid (n = 7), microdeletion/microduplication syndrome (n = 40), and Mendelian disorders (n = 49).
These findings demonstrate the high yield of CS-based CNV. With further improvement of our CS-CNV pipeline, the method may have clinical utility for simultaneous evaluation of CNVs and small variations in samples referred for pre- or postnatal analysis.
捕获测序（CS）广泛应用于检测小的遗传变异，如单核苷酸变异或插入缺失。基于深度比较的算法可用于从 CS 数据中检测拷贝数变异（CNV）。然而，尚未进行大规模的系统评估来评估基于 CS 的 CNV 检测在临床诊断中的效果。
我们回顾性研究了 3010 个送往我们诊断实验室进行 CS 检测的样本。我们使用 68 个染色体微阵列分析阳性样本（真实集 [TS]）和 1520 个参考样本构建了一个稳健的 CS-CNV 管道。该管道用于在 1422 个未确诊样本（未确诊集 [UDS]）中检测候选临床相关 CNV。候选 CNV 通过替代方法进行确认。
CS-CNV 管道在 TS 样本中检测到 78 个临床相关 CNV，分析灵敏度为 98.7%，阳性预测值为 49.4%。在 106 个 UDS 样本中鉴定出候选临床相关 CNV。在 96 名患者（90.6%）中确认了 CNV。诊断率为 6.8%。分子病因包括非整倍体（n=7）、微缺失/微重复综合征（n=40）和孟德尔疾病（n=49）。
这些发现表明基于 CS 的 CNV 具有高的检出率。随着我们的 CS-CNV 管道的进一步改进，该方法可能具有临床实用性，可用于同时评估样本中的 CNV 和小变异。
