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Interpretation of copy number alterations identified through clinical microarray-comparative genomic hybridization

机译:通过临床微阵列比较基因组杂交鉴定的拷贝数变化的解释

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摘要

Array-comparative genomic hybridization (array-CGH) has become the first-tier technology for the clinical assessment of copy number alterations (CNAs) associated with features such as developmental delay, congenital malformations, autism, or dysmorphic features. It is a near certainty that at least 1 CNA will be identified in each array-CGH assay and the challenge then becomes differentiating between benign CNA and those copy number changes that are dosage sensitive and relate to the abnormal phenotype in question. With advances In array-CGH platform coverage, it is no longer a question of CNA identification, but rather of CNA interpretation. However, there is no single methodology employed by laboratories to conduct this process, and unfortunately all too often the end results provide no clear answer to the ordering physician or their patients. Recent approaches for interpretation of CNA have advanced to suggesting the use of first-generation computational models based on structural and functional genomic features to predict a pathologic or benign value for array-CGH findings. Although such estimation procedures can be helpful, they are currently limited to a single phenotype (mental retardation) and can at best only provide an educated guess as to the true clinical significance of these alterations.
机译:阵列比较基因组杂交(array-CGH)已成为临床评估与发育延迟,先天性畸形,自闭症或畸形特征等特征相关的拷贝数变化(CNA)的第一线技术。几乎可以肯定的是,在每个阵列-CGH分析中将至少鉴定出1个CNA,然后挑战就可以区分良性CNA和那些剂量敏感且与所讨论的异常表型有关的拷贝数变化。随着阵列CGH平台覆盖范围的发展,不再是CNA识别的问题,而是CNA解释的问题。但是,实验室没有采用单一的方法来执行此过程,不幸的是,最终结果常常无法为订购医生或其患者提供明确的答案。用于解释CNA的最新方法已发展为建议使用基于结构和功能基因组特征的第一代计算模型来预测阵列CGH发现的病理或良性价值。尽管这样的估计程序可能会有所帮助,但它们目前仅限于单个表型(智力低下),充其量只能就这些改变的真实临床意义提供有根据的猜测。

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