Literature DB >> 31485704

Evaluation of droplet digital PCR for non-invasive prenatal diagnosis of phenylketonuria.

Yousheng Yan1,2,3, Fang Wang1,2, Chuan Zhang3, Xiaohua Jin1,2, Qinhua Zhang3, Xuan Feng3, Shengju Hao3, Huafang Gao4,5, Xu Ma6,7.   

Abstract

This study was carried out to establish a non-invasive prenatal diagnosis method for phenylketonuria (PKU) based on droplet digital PCR (ddPCR) and to evaluate its accuracy by comparison with conventional invasive diagnostic methods. A total of 24 PKU pedigrees that required prenatal diagnosis were studied, in which the genetic mutations in the probands and parents were unambiguous. Prenatal diagnosis of sibling fetuses was performed using traditional invasive prenatal diagnostic methods as a standard. At the same time, cell-free DNA (cfDNA) was extracted from maternal plasma and the fetal genes contained within were typed and quantified using ddPCR method. Invasive prenatal diagnosis determined that 3 of the 24 fetuses were affected, 8 of them were normal, and 13 were heterozygous carriers of pathogenic mutations. Successful non-invasive prenatal diagnosis analysis of PAH gene mutations was performed for 8 of the families using ddPCR method. Non-invasive prenatal diagnosis results were consistent with the results of the invasive prenatal diagnoses and no false positive or false negative results were found. In conclusion, this study is the first to establish non-invasive prenatal diagnosis of PKU based on ddPCR. The method showed high sensitivity and specificity from cfDNA, indicating that ddPCR is a reliable non-invasive prenatal diagnosis tool for PKU diagnosis. Graphical abstract.

Entities:  

Keywords:  Cell-free fetal DNA; Droplet digital PCR; Non-invasive prenatal testing; Phenylketonuria

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Year:  2019        PMID: 31485704     DOI: 10.1007/s00216-019-02087-4

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  1 in total

1.  Development of a droplet digital PCR method for detection of Streptococcus agalactiae.

Authors:  Yi-Fan Zeng; Chu-Mao Chen; Xiao-Yan Li; Jun-Jiang Chen; Yan-Ge Wang; Shi Ouyang; Tian-Xing Ji; Yong Xia; Xu-Guang Guo
Journal:  BMC Microbiol       Date:  2020-06-23       Impact factor: 3.605

  1 in total

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