Targeted exome sequencing strategy (<scp>NeoEXOME</scp>) for Chinese newborns using a pilot study with 3423 neonates

Cao, Ziyang; He, Xiaoyan; Wang, Dongjuan; Gu, Maosheng; Suo, Feng; Qiang, Rong; Zhang, Ruixue; Song, Chengrong; Wang, Xiaohua; Zhu, Bo; Cao, Donghua; Yu, Haihua; Qu, Yiping; Shen, Guosong; Wu, Jian; Wang, Pengpeng; Wang, Jinxia; Zhang, Hongyang; Yan, Zijun; Yu, Guangjun; Zou, Lin

doi:10.1002/mgg3.2357

Cited by 2 publications

(1 citation statement)

References 34 publications

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“…Besides, the NGS technology has also been used to evaluate explore panels of genes and identify complex mechanisms of some pathogenesis, such as congenital hypothyroidism with dyshormonogenesis [ 24 ], and to help in the diagnosis of rare pediatric diseases [ 25 ]. Currently, the use of NGS technology for newborn genome screening is gradually gaining concerns in China [ 26 ]. This study covered a wide range of diseases, encompassing 13 major categories of genetic disorders, 542 disease subtypes, and the screening of 601 genes in newborn genome screening.…”

Section: Discussionmentioning

confidence: 99%

Next-generation sequencing based newborn screening and comparative analysis with MS/MS

Shen,

Li,

Zhang

et al. 2024

BMC Pediatr

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Background Newborn screening (NBS), such as tandem mass spectrometry (MS/MS), may yield false positive/negative results. Next-generation sequencing (NGS) has the potential to provide increased data output, efficiencies, and applications. This study aimed to analyze the types and distribution of pathogenic gene mutations in newborns in Huzhou, Zhejiang province, China and explore the applicability of NGS and MS/MS in NBS. Methods Blood spot samples from 1263 newborns were collected. NGS was employed to screen for pathogenic variants in 542 disease-causing genes, and detected variants were validated using Sanger sequencing. Simultaneously, 26 inherited metabolic diseases (IMD) were screened using MS/MS. Positive or suspicious samples identified through MS/MS were cross-referenced with the results of NGS. Results Among all newborns, 328 had no gene mutations detected. NGS revealed at least one gene mutation in 935 newborns, with a mutation rate of 74.0%. The top 5 genes were FLG, GJB2, UGT1A1, USH2A, and DUOX2. According to American College of Medical Genetics guidelines, gene mutations in 260 cases were classified as pathogenic or likely pathogenic mutation, with a positive rate of 20.6%. The top 5 genes were UGT1A1, FLG, GJB2, MEFV, and G6PD. MS/MS identified 18 positive or suspicious samples for IMD and 1245 negative samples. Verification of these cases by NGS results showed no pathogenic mutations, resulting in a false positive rate of 1.4% (18/1263). Conclusion NBS using NGS technology broadened the range of diseases screened, and enhanced the accuracy of diagnoses in comparison to MS/MS for screening IMD. Combining NGS and biochemical screening would improve the efficiency of current NBS.

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Section: Discussionmentioning

confidence: 99%

Next-generation sequencing based newborn screening and comparative analysis with MS/MS

Shen,

Li,

Zhang

et al. 2024

BMC Pediatr

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Data-driven prioritization of genetic disorders for global genomic newborn screening programs

Minten,

Gold,

Bick

et al. 2024

Preprint

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Over 30 international research studies and commercial laboratories are exploring the use of genomic sequencing to screen apparently healthy newborns for genetic disorders. These programs have individualized processes for determining which genes and genetic disorders are queried and reported in newborns. We compared lists of genes from 26 research and commercial newborn screening programs and found substantial heterogeneity among the genes included. A total of 1,750 genes were included in at least one newborn genome sequencing program, but only 74 genes were included on >80% of gene lists, 16 of which are not associated with conditions on the Recommended Uniform Screening Panel. We used a linear regression model to explore factors related to the inclusion of individual genes across programs, finding that a high evidence base as well as treatment efficacy were two of the most important factors for inclusion. We applied a machine learning model to predict how suitable a gene is for newborn sequencing. As knowledge about and treatments for genetic disorders expand, this model provides a dynamic tool to reassess genes for newborn screening implementation. This study highlights the complex landscape of gene list curation among genomic newborn screening programs and proposes an empirical path forward for determining the genes and disorders of highest priority for newborn screening programs.

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Targeted exome sequencing strategy (NeoEXOME) for Chinese newborns using a pilot study with 3423 neonates

Cited by 2 publications

References 34 publications

Next-generation sequencing based newborn screening and comparative analysis with MS/MS

Next-generation sequencing based newborn screening and comparative analysis with MS/MS

Data-driven prioritization of genetic disorders for global genomic newborn screening programs

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