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复发性致病性拷贝数变异的外显率估计。

Estimates of penetrance for recurrent pathogenic copy-number variations.

机构信息

Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, Washington, USA.

出版信息

Genet Med. 2013 Jun;15(6):478-81. doi: 10.1038/gim.2012.164. Epub 2012 Dec 20.

Abstract

PURPOSE

Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci.

METHODS

We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications.

RESULTS

Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions.

CONCLUSION

This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session.

摘要

目的

尽管越来越多的拷贝数变异被鉴定为多种儿科疾病的易感基因座,但这些拷贝数变异的外显率大多仍不清楚。这给咨询带来了挑战,包括复发风险和产前诊断。我们试图为其中一些复发性疾病易感基因座的外显率提供经验估计。

方法

我们基于对照人群(n=22246)和我们的>48000 例基于微阵列的比较基因组杂交样本数据库中的拷贝数变异频率进行了贝叶斯分析。先天性异常/发育迟缓/智力残疾的背景风险假定为~5%。研究的拷贝数变异为 1q21.1 近端重复、1q21.1 远端缺失和重复、15q11.2 缺失、16p13.11 缺失、16p12.1 缺失、16p11.2 近端和远端缺失和重复、17q12 缺失和重复,以及 22q11.21 重复。

结果

异常表型风险的估计值范围从 15q11.2 缺失的 10.4%到远端 16p11.2 缺失的 62.4%。

结论

该模型可用于为产前环境中遇到的许多拷贝数变异提供更精确的异常表型发生概率估计。通过提供外显率,可以在遗传咨询会议中为未来的父母提供更多关键信息。

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