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Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening
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 implementatio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628990/ https://www.ncbi.nlm.nih.gov/pubmed/34842611 http://dx.doi.org/10.3390/ijns7040073 |
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author | Sicko, Robert J. Stevens, Colleen F. Hughes, Erin E. Leisner, Melissa Ling, Helen Saavedra-Matiz, Carlos A. Caggana, Michele Kay, Denise M. |
author_facet | Sicko, Robert J. Stevens, Colleen F. Hughes, Erin E. Leisner, Melissa Ling, Helen Saavedra-Matiz, Carlos A. Caggana, Michele Kay, Denise M. |
author_sort | Sicko, Robert J. |
collection | PubMed |
description | 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 (CFTR) gene analysis. After full gene sequencing, a tiered strategy is used to first analyze only a specific panel of 338 clinically relevant CFTR 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. |
format | Online Article Text |
id | pubmed-8628990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86289902021-11-30 Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening Sicko, Robert J. Stevens, Colleen F. Hughes, Erin E. Leisner, Melissa Ling, Helen Saavedra-Matiz, Carlos A. Caggana, Michele Kay, Denise M. Int J Neonatal Screen Article 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 (CFTR) gene analysis. After full gene sequencing, a tiered strategy is used to first analyze only a specific panel of 338 clinically relevant CFTR 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. MDPI 2021-11-02 /pmc/articles/PMC8628990/ /pubmed/34842611 http://dx.doi.org/10.3390/ijns7040073 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sicko, Robert J. Stevens, Colleen F. Hughes, Erin E. Leisner, Melissa Ling, Helen Saavedra-Matiz, Carlos A. Caggana, Michele Kay, Denise M. Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening |
title | Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening |
title_full | Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening |
title_fullStr | Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening |
title_full_unstemmed | Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening |
title_short | Validation of a Custom Next-Generation Sequencing Assay for Cystic Fibrosis Newborn Screening |
title_sort | validation of a custom next-generation sequencing assay for cystic fibrosis newborn screening |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628990/ https://www.ncbi.nlm.nih.gov/pubmed/34842611 http://dx.doi.org/10.3390/ijns7040073 |
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