Section of Neurology, St. Christopher's Hospital for Children, Drexel University College of Medicine, Philadelphia, Pennsylvania 19134, USA.
Pediatr Neurol. 2010 Dec;43(6):391-4. doi: 10.1016/j.pediatrneurol.2010.06.019.
The technique of chromosomal microarray analysis identifies genetic imbalance. Evaluation of its diagnostic role in pediatrics is still underway. We describe our experience with chromosomal microarrays. We retrospectively reviewed the charts of children in the Sections of Neurology and Clinical Genetics at St. Christopher's Hospital for Children who had undergone microarray analysis between 2006 and 2009. Collected data included age, sex, and the presence of mental retardation, developmental delay, autism, learning disability, hypotonia, dysmorphic features, and epilepsy, and the use of microarray technique. Statistical analysis was performed using SPSS. There were 82 children (mean age ± S.D., 5.7 ± 5 years), including 45 (55%) boys and 37 (45%) girls. All patients exhibited a normal karyotype. Microarray analysis produced abnormal results in 20 (23.5%). Deletions comprised 74% of all abnormalities. Patients with ≥ 4 clinical variables demonstrated a 30.5% incidence of abnormal chromosomal microarray findings, compared with 8.7% of patients with ≤ 3 clinical variables (P = 0.039, χ(2) test). Logistic regression indicated that motor impairment (P = 0.039) and presence of epilepsy (P = 0.024) independently contributed to the model. The likelihood of an abnormal microarray result increased with the number of clinical abnormalities. Microarray analysis will likely become the diagnostic genetic test of choice in children with neurodevelopmental disorders or epilepsy.
染色体微阵列分析技术可识别遗传失衡。评估其在儿科中的诊断作用仍在进行中。我们描述了我们在染色体微阵列方面的经验。我们回顾性地审查了圣克里斯托弗儿童医院神经科和临床遗传学科在 2006 年至 2009 年间进行微阵列分析的儿童的图表。收集的数据包括年龄、性别以及智力障碍、发育迟缓、自闭症、学习障碍、肌张力低下、畸形特征和癫痫的存在，以及微阵列技术的使用。使用 SPSS 进行统计分析。共有 82 名儿童（平均年龄±标准差，5.7±5 岁），包括 45 名（55%）男孩和 37 名（45%）女孩。所有患者均表现出正常核型。微阵列分析产生异常结果 20 例（23.5%）。所有异常中，缺失占 74%。有≥4 个临床变量的患者异常染色体微阵列发现的发生率为 30.5%，而有≤3 个临床变量的患者为 8.7%（P=0.039，X²检验）。逻辑回归表明运动障碍（P=0.039）和癫痫存在（P=0.024）独立影响该模型。异常微阵列结果的可能性随临床异常数量的增加而增加。染色体微阵列分析可能成为神经发育障碍或癫痫儿童的首选诊断性遗传检测。
