Autism & Developmental Medicine Institute, Geisinger, Danville, PA, USA.
Michigan Medical Genetics Laboratories (MMGL), University of Michigan, Ann Arbor, MI, USA.
Hum Mutat. 2018 Nov;39(11):1650-1659. doi: 10.1002/humu.23610.
Conflict resolution in genomic variant interpretation is a critical step toward improving patient care. Evaluating interpretation discrepancies in copy number variants (CNVs) typically involves assessing overlapping genomic content with focus on genes/regions that may be subject to dosage sensitivity (haploinsufficiency (HI) and/or triplosensitivity (TS)). CNVs containing dosage sensitive genes/regions are generally interpreted as "likely pathogenic" (LP) or "pathogenic" (P), and CNVs involving the same known dosage sensitive gene(s) should receive the same clinical interpretation. We compared the Clinical Genome Resource (ClinGen) Dosage Map, a publicly available resource documenting known HI and TS genes/regions, against germline, clinical CNV interpretations within the ClinVar database. We identified 251 CNVs overlapping known dosage sensitive genes/regions but not classified as LP or P; these were sent back to their original submitting laboratories for re-evaluation. Of 246 CNVs re-evaluated, an updated clinical classification was warranted in 157 cases (63.8%); no change was made to the current classification in 79 cases (32.1%); and 10 cases (4.1%) resulted in other types of updates to ClinVar records. This effort will add curated interpretation data into the public domain and allow laboratories to focus attention on more complex discrepancies.
基因组变异解释中的冲突解决是改善患者护理的关键步骤。评估拷贝数变异 (CNV) 的解释差异通常涉及评估重叠的基因组内容,重点是可能存在剂量敏感性的基因/区域(杂合不足 (HI) 和/或三倍体敏感性 (TS))。包含剂量敏感基因/区域的 CNV 通常被解释为“可能致病性” (LP) 或“致病性” (P),涉及相同已知剂量敏感基因的 CNV 应获得相同的临床解释。我们比较了临床基因组资源 (ClinGen) 剂量图,这是一个公开的资源,记录了已知的 HI 和 TS 基因/区域,与 ClinVar 数据库中的种系、临床 CNV 解释进行了比较。我们确定了 251 个与已知剂量敏感基因/区域重叠但未分类为 LP 或 P 的 CNV;这些 CNV 被送回其原始提交实验室进行重新评估。在重新评估的 246 个 CNV 中,157 个案例(63.8%)需要更新临床分类;79 个案例(32.1%)没有改变当前分类;10 个案例(4.1%)导致 ClinVar 记录的其他类型更新。这项工作将把经过策展的解释数据添加到公共领域,并允许实验室将注意力集中在更复杂的差异上。