Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
J Med Genet. 2024 Jun 20;61(7):621-625. doi: 10.1136/jmg-2023-109559.
Reanalysis of exome/genome data improves diagnostic yield. However, the value of reanalysis of clinical array comparative genomic hybridisation (aCGH) data has never been investigated. Case-by-case reanalysis can be challenging in busy diagnostic laboratories.
We harmonised historical postnatal clinical aCGH results from ~16 000 patients tested via our diagnostic laboratory over ~7 years with current clinical guidance. This led to identification of 37 009 copy number losses (CNLs) including 33 857 benign, 2173 of uncertain significance and 979 pathogenic. We found benign CNLs to be significantly less likely to encompass haploinsufficient genes compared with the pathogenic or CNLs of uncertain significance in our database. Based on this observation, we developed a reanalysis pipeline using up-to-date disease association data and haploinsufficiency scores and shortlisted 207 CNLs of uncertain significance encompassing at least one autosomal dominant disease-gene associated with haploinsufficiency or loss-of-function mechanism. Clinical scientist reviews led to reclassification of 15 CNLs of uncertain significance as pathogenic or likely pathogenic. This was ~0.7% of the starting cohort of 2173 CNLs of uncertain significance and 7.2% of 207 shortlisted CNLs. The reclassified CNLs included first cases of CNV-mediated disease for some genes where all previously described cases involved only point variants. Interestingly, some CNLs could not be reclassified because the phenotypes of patients with CNLs seemed distinct from the known clinical features resulting from point variants, thus raising questions about accepted underlying disease mechanisms.
Reanalysis of clinical aCGH data increases diagnostic yield.
外显子/基因组数据的重新分析可提高诊断率。然而,临床阵列比较基因组杂交(aCGH)数据的重新分析价值从未被研究过。在繁忙的诊断实验室中,逐个案例进行重新分析可能具有挑战性。
我们将我们诊断实验室在大约 7 年的时间内测试的约 16000 名患者的历史产后临床 aCGH 结果与当前临床指南进行了协调。这导致确定了 37009 个拷贝数缺失(CNL),包括 33857 个良性、2173 个意义不确定和 979 个致病性。我们发现良性 CNL 包含的单基因功能不全基因明显少于我们数据库中的致病性或意义不确定的 CNL。基于这一观察结果,我们使用最新的疾病关联数据和单基因功能不全评分开发了一个重新分析管道,并将至少包含一个与单基因功能不全或功能丧失机制相关的常染色体显性疾病基因的 207 个意义不确定的 CNL 列入候选名单。临床科学家的审查导致 15 个意义不确定的 CNL 被重新分类为致病性或可能致病性。这约占起始队列中 2173 个意义不确定的 CNL 的 0.7%,占 207 个入围的意义不确定的 CNL 的 7.2%。重新分类的 CNL 包括一些基因的 CNV 介导疾病的首例病例,而所有以前描述的病例仅涉及点突变。有趣的是,一些 CNL 无法重新分类,因为 CNL 患者的表型与已知的由点突变引起的临床特征明显不同,这引发了对公认的潜在疾病机制的质疑。
临床 aCGH 数据的重新分析可提高诊断率。