Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA.
J Hum Genet. 2019 May;64(5):437-443. doi: 10.1038/s10038-019-0573-9. Epub 2019 Feb 14.
Standard clinical interpretation of DNA copy number variants (CNVs) identified by cytogenomic microarray involves examining protein-coding genes within the region and comparison to other CNVs. Emerging basic research suggests that CNVs can also exert a pathogenic effect through disruption of DNA structural elements such as topologically associated domains (TADs). To begin to integrate these discoveries with current practice, we developed ClinTAD, a free browser-based tool to assist with interpretation of CNVs in the context of TADs ( www.clintad.com ). We used ClinTAD to examine 209 randomly selected single-nucleotide polymorphism microarray cases with a total of 236 CNVs. We compared 118 CNVs classified as variants of uncertain clinical significance (VUS), where additional insight into pathogenicity of these CNVs would be of greatest utility, to 118 CNVs classified as benign. We found that a higher proportion of VUS had at least two genes in a nearby TAD related to a phenotype seen in the patient based on Human Phenotype Ontology (HPO) annotation. We present example cases demonstrating scenarios where ClinTAD may either increase or decrease clinical suspicion of pathogenicity for VUS, depending on disruption of TAD boundaries and HPO phenotype match. ClinTAD is an easy-to-use tool, based on emerging research in chromatin architecture, that can help inform CNV interpretation.
通过比较基因组微阵列识别的 DNA 拷贝数变异 (CNV) 的标准临床解释包括检查该区域内的编码蛋白基因,并与其他 CNV 进行比较。新兴的基础研究表明,CNV 还可以通过破坏 DNA 结构元件(如拓扑相关域 (TAD))来发挥致病作用。为了将这些发现与当前的实践相结合,我们开发了 ClinTAD,这是一种免费的基于浏览器的工具,用于在 TAD 背景下协助解释 CNV(www.clintad.com)。我们使用 ClinTAD 检查了 209 个随机选择的单核苷酸多态性微阵列病例,共发现 236 个 CNV。我们将 118 个分类为不确定临床意义的变异 (VUS) 的 CNV 与 118 个分类为良性的 CNV 进行了比较。我们发现,更多的 VUS 具有至少两个基因位于附近的 TAD 中,这些基因与基于人类表型本体论 (HPO) 注释的患者表型相关。我们展示了一些示例病例,展示了 ClinTAD 可能会根据 TAD 边界和 HPO 表型匹配增加或降低对 VUS 致病性的临床怀疑的情况。ClinTAD 是一种基于染色质结构新兴研究的易于使用的工具,可以帮助解释 CNV。