Wang Conghui, Shi Panlai, Liang Hongbin, Cram David S, Leigh Donald A, Kong Xiangdong
Genetic and Prenatal Diagnosis Center, Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Genetics and Precision Medicine Centre, The First People's Hospital of Kunming, Kunming, Yunnan, China.
Genet Med Open. 2024 Jan 29;2:101816. doi: 10.1016/j.gimo.2024.101816. eCollection 2024.
Patients with genetic diseases often seek testing to reach a firm diagnosis. Based on clinical phenotypes, exome sequencing for small-nucleotide variations or array-based methods for copy-number variations (CNVs) are commonly offered to identify the underlying causative genetic variants. In this study, we investigated whether data from a standard ES test could be used to additionally identify pathogenic CNVs and increase diagnostic yield.
Prospectively, 134 patients presenting with a skin condition suspected of being genetic in origin were offered the next-generation variant exon screening (ngVES) test. Sequencing data were analyzed for both single-nucleotide variants and CNVs using established algorithms.
The positive detection rate for skin diseases using ngVES was 66% (88/134) with the most common diagnoses being neurofibromatosis type1 ( = 48) and tuberous sclerosis type2 ( = 12). The diagnostic increased yield from 58% to 66% was the result of additional detection of pathogenic CNVs. Each of the 9 CNVs were verified by independent genetic tests.
The advances in the ngVES bioinformatics pipeline are proofs of concept, which improved identification of genetic variants associated with skin disease. Simultaneous single-nucleotide variants/INDEL and CNV detection by this approach demonstrates ngVES potential as a first-tier screen for any suspected genetic disease.
患有遗传疾病的患者常常寻求检测以获得确切诊断。基于临床表型，通常会提供外显子组测序以检测单核苷酸变异，或采用基于阵列的方法检测拷贝数变异（CNV），以识别潜在的致病基因变异。在本研究中，我们调查了标准外显子组测序（ES）测试数据是否可用于额外识别致病性CNV并提高诊断率。
前瞻性地为134例疑似遗传性皮肤病患者提供下一代变异外显子筛查（ngVES）测试。使用既定算法对测序数据进行单核苷酸变异和CNV分析。
使用ngVES检测皮肤病的阳性率为66%（88/134），最常见的诊断是1型神经纤维瘤病（n = 48）和2型结节性硬化症（n = 12）。诊断率从58%提高到66%是额外检测到致病性CNV的结果。9个CNV均通过独立基因检测得到验证。
ngVES生物信息学流程的进展是概念验证，其改善了与皮肤病相关的基因变异识别。通过该方法同时检测单核苷酸变异/插入缺失和CNV证明了ngVES作为任何疑似遗传疾病一线筛查方法的潜力。
