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用于囊性纤维化新生儿筛查的定制下一代测序检测方法的验证

Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening.

作者信息

Sicko Robert J, Stevens Colleen F, Hughes Erin E, Leisner Melissa, Ling Helen, Saavedra-Matiz Carlos A, Caggana Michele, Kay Denise M

机构信息

New York State Newborn Screening Program, Division of Genetics, Wadsworth Center, New York State Department of Health, Albany, NY 12208, USA.

Applied Genomics Technologies Cluster, Wadsworth Center, New York State Department of Health, Albany, NY 12208, USA.

出版信息

Int J Neonatal Screen. 2021 Nov 2;7(4):73. doi: 10.3390/ijns7040073.

Abstract

Newborn screening (NBS) for Cystic Fibrosis (CF) is associated with improved outcomes. All US states screen for CF; however, CF NBS algorithms have high false positive (FP) rates. In New York State (NYS), the positive predictive value of CF NBS improved from 3.7% to 25.2% following the implementation of a three-tier IRT-DNA-SEQ approach using commercially available tests. Here we describe a modification of the NYS CF NBS algorithm via transition to a new custom next-generation sequencing (NGS) platform for more comprehensive cystic fibrosis transmembrane conductance regulator () gene analysis. After full gene sequencing, a tiered strategy is used to first analyze only a specific panel of 338 clinically relevant variants (second-tier), followed by unblinding of all sequence variants and bioinformatic assessment of deletions/duplications in a subset of samples requiring third-tier analysis. We demonstrate the analytical and clinical validity of the assay and the feasibility of use in the NBS setting. The custom assay has streamlined our molecular workflow, increased throughput, and allows for bioinformatic customization of second-tier variant panel content. NBS aims to identify those infants with the highest disease risk. Technological molecular improvements can be applied to NBS algorithms to reduce the burden of FP referrals without loss of sensitivity.

摘要

新生儿囊性纤维化(CF)筛查与改善预后相关。美国所有州都对CF进行筛查;然而,CF新生儿筛查算法的假阳性(FP)率很高。在纽约州(NYS),采用市售检测方法实施三层IRT-DNA-SEQ方法后,CF新生儿筛查的阳性预测值从3.7%提高到了25.2%。在此,我们描述了通过过渡到新的定制下一代测序(NGS)平台对NYS CF新生儿筛查算法进行的修改,以实现更全面的囊性纤维化跨膜传导调节因子()基因分析。在进行全基因测序后,采用分层策略,首先仅分析338个临床相关变异的特定面板(第二层),然后对所有序列变异进行解盲,并对需要第三层分析的一部分样本中的缺失/重复进行生物信息学评估。我们证明了该检测方法的分析和临床有效性以及在新生儿筛查环境中使用的可行性。定制检测简化了我们的分子工作流程,提高了通量,并允许对第二层变异面板内容进行生物信息学定制。新生儿筛查旨在识别那些疾病风险最高的婴儿。技术分子改进可应用于新生儿筛查算法,以减轻假阳性转诊的负担,同时不损失敏感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b54/8628990/ff21197ed3e4/IJNS-07-00073-g001.jpg

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