Aston E, Whitby H, Maxwell T, Glaus N, Cowley B, Lowry D, Zhu X L, Issa B, South S T, Brothman A R
University of Utah CGH Microarray Laboratory, Department of Pediatrics, Salt Lake City, UT 84132, USA.
J Med Genet. 2008 May;45(5):268-74. doi: 10.1136/jmg.2007.055319. Epub 2008 Jan 4.
The University of Utah Comparative Genomic Hybridization Microarray Laboratory was one of the first US laboratories to offer comparative genomic hybridisation (CGH) microarray testing using a commercial platform in a clinical setting. Results for 1076 patients (1598 chips) are presented.
The Spectral Genomics/PerkinElmer Constitutional Chip (targeted array), SpectralChip 2600 (whole genome array) and a "Combo" chip (both arrays run simultaneously) were the tests offered. Abnormal results were confirmed by an alternative method, most often fluorescence in situ hybridisation.
In 669 cases with known normal cytogenetics, an abnormal detection rate of 10.8% was observed, (5.3%, 12.2% and 14.1% for the Constitutional Chip, SpectralChip 2600 and Combo assay, respectively). Known copy number variants and single clone abnormalities are not included in these rates. Single clone abnormalities are reported separately. For 1076 total cases, we report an average abnormal rate of 16.9% (8.7%, 23.7% and 18.6% for the three assays). This rate includes characterisation of some abnormalities previously identified by cytogenetics.
CGH microarray provides a likely aetiology for the clinical phenotype in many cytogenetically normal cases, and a whole genome array generally identifies copy number changes more effectively than a targeted chip alone.
犹他大学比较基因组杂交微阵列实验室是美国首批在临床环境中使用商业平台提供比较基因组杂交（CGH）微阵列检测的实验室之一。本文展示了1076例患者（1598张芯片）的检测结果。
提供的检测包括Spectral Genomics/PerkinElmer结构芯片（靶向阵列）、SpectralChip 2600（全基因组阵列）以及“组合”芯片（同时运行两种阵列）。异常结果通过另一种方法进行确认，最常用的是荧光原位杂交。
在669例已知细胞遗传学正常的病例中，异常检测率为10.8%（结构芯片、SpectralChip 2600和组合检测的异常率分别为5.3%、12.2%和14.1%）。这些比率不包括已知的拷贝数变异和单克隆异常。单克隆异常单独报告。对于1076例总病例，我们报告的平均异常率为16.9%（三种检测的异常率分别为8.7%、23.7%和18.6%）。该比率包括对一些先前通过细胞遗传学鉴定的异常的特征描述。
CGH微阵列在许多细胞遗传学正常的病例中为临床表型提供了可能的病因，并且全基因组阵列通常比单独的靶向芯片更有效地识别拷贝数变化。
