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Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates

BACKGROUND: Newborn screening (NBS) has been implemented for neonatal inborn disorders using various technology platforms, but false-positive and false-negative results are still common. In addition, target diseases of NBS are limited by suitable biomarkers. Here we sought to assess the feasibility...

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Autores principales: Huang, Xinwen, Wu, Dingwen, Zhu, Lin, Wang, Wenjun, Yang, Rulai, Yang, Jianbin, He, Qunyan, Zhu, Bingquan, You, Ying, Xiao, Rui, Zhao, Zhengyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862216/
https://www.ncbi.nlm.nih.gov/pubmed/35193651
http://dx.doi.org/10.1186/s13023-022-02231-x
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author Huang, Xinwen
Wu, Dingwen
Zhu, Lin
Wang, Wenjun
Yang, Rulai
Yang, Jianbin
He, Qunyan
Zhu, Bingquan
You, Ying
Xiao, Rui
Zhao, Zhengyan
author_facet Huang, Xinwen
Wu, Dingwen
Zhu, Lin
Wang, Wenjun
Yang, Rulai
Yang, Jianbin
He, Qunyan
Zhu, Bingquan
You, Ying
Xiao, Rui
Zhao, Zhengyan
author_sort Huang, Xinwen
collection PubMed
description BACKGROUND: Newborn screening (NBS) has been implemented for neonatal inborn disorders using various technology platforms, but false-positive and false-negative results are still common. In addition, target diseases of NBS are limited by suitable biomarkers. Here we sought to assess the feasibility of further improving the screening using next-generation sequencing technology. METHODS: We designed a newborn genetic sequencing (NBGS) panel based on multiplex PCR and next generation sequencing to analyze 134 genes of 74 inborn disorders, that were validated in 287 samples with previously known mutations. A retrospective cohort of 4986 newborns was analyzed and compared with the biochemical results to evaluate the performance of this panel. RESULTS: The accuracy of the panel was 99.65% with all samples, and 154 mutations from 287 samples were 100% detected. In 4986 newborns, a total of 113 newborns were detected with biallelic or hemizygous mutations, of which 36 newborns were positive for the same disorder by both NBGS and conventional NBS (C-NBS) and 77 individuals were NBGS positive/C-NBS negative. Importantly, 4 of the 77 newborns were diagnosed currently including 1 newborn with methylmalonic acidemia, 1 newborn with primary systemic carnitine deficiency and 2 newborns with Wilson’s disease. A total of 1326 newborns were found to be carriers with an overall carrier rate of 26.6%. CONCLUSION: Analysis based on next generation sequencing could effectively identify neonates affected with more congenital disorders. Combined with C-NBS, this approach may improve the early and accurate identification of neonates with inborn disorders. Our study lays the foundation for prospective studies and for implementing NGS-based analysis in NBS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-022-02231-x.
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spelling pubmed-88622162022-02-23 Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates Huang, Xinwen Wu, Dingwen Zhu, Lin Wang, Wenjun Yang, Rulai Yang, Jianbin He, Qunyan Zhu, Bingquan You, Ying Xiao, Rui Zhao, Zhengyan Orphanet J Rare Dis Research BACKGROUND: Newborn screening (NBS) has been implemented for neonatal inborn disorders using various technology platforms, but false-positive and false-negative results are still common. In addition, target diseases of NBS are limited by suitable biomarkers. Here we sought to assess the feasibility of further improving the screening using next-generation sequencing technology. METHODS: We designed a newborn genetic sequencing (NBGS) panel based on multiplex PCR and next generation sequencing to analyze 134 genes of 74 inborn disorders, that were validated in 287 samples with previously known mutations. A retrospective cohort of 4986 newborns was analyzed and compared with the biochemical results to evaluate the performance of this panel. RESULTS: The accuracy of the panel was 99.65% with all samples, and 154 mutations from 287 samples were 100% detected. In 4986 newborns, a total of 113 newborns were detected with biallelic or hemizygous mutations, of which 36 newborns were positive for the same disorder by both NBGS and conventional NBS (C-NBS) and 77 individuals were NBGS positive/C-NBS negative. Importantly, 4 of the 77 newborns were diagnosed currently including 1 newborn with methylmalonic acidemia, 1 newborn with primary systemic carnitine deficiency and 2 newborns with Wilson’s disease. A total of 1326 newborns were found to be carriers with an overall carrier rate of 26.6%. CONCLUSION: Analysis based on next generation sequencing could effectively identify neonates affected with more congenital disorders. Combined with C-NBS, this approach may improve the early and accurate identification of neonates with inborn disorders. Our study lays the foundation for prospective studies and for implementing NGS-based analysis in NBS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-022-02231-x. BioMed Central 2022-02-21 /pmc/articles/PMC8862216/ /pubmed/35193651 http://dx.doi.org/10.1186/s13023-022-02231-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Huang, Xinwen
Wu, Dingwen
Zhu, Lin
Wang, Wenjun
Yang, Rulai
Yang, Jianbin
He, Qunyan
Zhu, Bingquan
You, Ying
Xiao, Rui
Zhao, Zhengyan
Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates
title Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates
title_full Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates
title_fullStr Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates
title_full_unstemmed Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates
title_short Application of a next-generation sequencing (NGS) panel in newborn screening efficiently identifies inborn disorders of neonates
title_sort application of a next-generation sequencing (ngs) panel in newborn screening efficiently identifies inborn disorders of neonates
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8862216/
https://www.ncbi.nlm.nih.gov/pubmed/35193651
http://dx.doi.org/10.1186/s13023-022-02231-x
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