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Low-pass genome sequencing versus chromosomal microarray analysis: implementation in prenatal diagnosis.
Wang, Huilin; Dong, Zirui; Zhang, Rui; Chau, Matthew Hoi Kin; Yang, Zhenjun; Tsang, Kathy Yin Ching; Wong, Hoi Kin; Gui, Baoheng; Meng, Zhuo; Xiao, Kelin; Zhu, Xiaofan; Wang, Yanfang; Chen, Shaoyun; Leung, Tak Yeung; Cheung, Sau Wai; Kwok, Yvonne K; Morton, Cynthia C; Zhu, Yuanfang; Choy, Kwong Wai.
Afiliação
  • Wang H; Maternal-Fetal Medicine Institute, Bao'an Maternity and Child Health Hospital Affiliated to Jinan University School of Medicine, Key Laboratory of Birth Defects Research, Birth Defects Prevention Research and Transformation Team, Shenzhen, China.
  • Dong Z; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Zhang R; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Chau MHK; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Yang Z; Maternal-Fetal Medicine Institute, Bao'an Maternity and Child Health Hospital Affiliated to Jinan University School of Medicine, Key Laboratory of Birth Defects Research, Birth Defects Prevention Research and Transformation Team, Shenzhen, China.
  • Tsang KYC; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Wong HK; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Gui B; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Meng Z; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Xiao K; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Zhu X; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Wang Y; Maternal-Fetal Medicine Institute, Bao'an Maternity and Child Health Hospital Affiliated to Jinan University School of Medicine, Key Laboratory of Birth Defects Research, Birth Defects Prevention Research and Transformation Team, Shenzhen, China.
  • Chen S; Maternal-Fetal Medicine Institute, Bao'an Maternity and Child Health Hospital Affiliated to Jinan University School of Medicine, Key Laboratory of Birth Defects Research, Birth Defects Prevention Research and Transformation Team, Shenzhen, China.
  • Leung TY; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Cheung SW; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
  • Kwok YK; Maternal-Fetal Medicine Institute, Bao'an Maternity and Child Health Hospital Affiliated to Jinan University School of Medicine, Key Laboratory of Birth Defects Research, Birth Defects Prevention Research and Transformation Team, Shenzhen, China.
  • Morton CC; Maternal-Fetal Medicine Institute, Bao'an Maternity and Child Health Hospital Affiliated to Jinan University School of Medicine, Key Laboratory of Birth Defects Research, Birth Defects Prevention Research and Transformation Team, Shenzhen, China.
  • Zhu Y; Department of Obstetrics & Gynaecology, The Chinese University of Hong Kong, Hong Kong, China.
  • Choy KW; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China.
Genet Med ; 22(3): 500-510, 2020 03.
Article em En | MEDLINE | ID: mdl-31447483
PURPOSE: Emerging studies suggest that low-pass genome sequencing (GS) provides additional diagnostic yield of clinically significant copy-number variants (CNVs) compared with chromosomal microarray analysis (CMA). However, a prospective back-to-back comparison evaluating accuracy, efficacy, and incremental yield of low-pass GS compared with CMA is warranted. METHODS: A total of 1023 women undergoing prenatal diagnosis were enrolled. Each sample was subjected to low-pass GS and CMA for CNV analysis in parallel. CNVs were classified according to guidelines of the American College of Medical Genetics and Genomics. RESULTS: Low-pass GS not only identified all 124 numerical disorders or pathogenic or likely pathogenic (P/LP) CNVs detected by CMA in 121 cases (11.8%, 121/1023), but also defined 17 additional and clinically relevant P/LP CNVs in 17 cases (1.7%, 17/1023). In addition, low-pass GS significantly reduced the technical repeat rate from 4.6% (47/1023) for CMA to 0.5% (5/1023) and required less DNA (50 ng) as input. CONCLUSION: In the context of prenatal diagnosis, low-pass GS identified additional and clinically significant information with enhanced resolution and increased sensitivity of detecting mosaicism as compared with the CMA platform used. This study provides strong evidence for applying low-pass GS as an alternative prenatal diagnostic test.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diagnóstico Pré-Natal / Aberrações Cromossômicas / Cromossomos / Análise em Microsséries Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Genet Med Assunto da revista: GENETICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diagnóstico Pré-Natal / Aberrações Cromossômicas / Cromossomos / Análise em Microsséries Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Limite: Female / Humans / Pregnancy Idioma: En Revista: Genet Med Assunto da revista: GENETICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China