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Nonivasive prenatal diagnosis of single-gene disorders using droplet digital PCR

View ORCID ProfileJoan Camunas-Soler, Hojae Lee, Louanne Hudgins, Susan R. Hintz, Yair J. Blumenfeld, Yasser Y. El-Sayed, Stephen R. Quake
doi: https://doi.org/10.1101/179804
Joan Camunas-Soler
1Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
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  • ORCID record for Joan Camunas-Soler
Hojae Lee
1Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
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Louanne Hudgins
2Division of Medical Genetics, Department of Pediatrics, Stanford University, Stanford, CA 94305, USA.
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Susan R. Hintz
3Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.
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Yair J. Blumenfeld
4Division of Maternal-Fetal Medicine and Obstetrics, Department of Obstetrics and Gynecology, Stanford University, Stanford, CA 94305, USA.
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Yasser Y. El-Sayed
4Division of Maternal-Fetal Medicine and Obstetrics, Department of Obstetrics and Gynecology, Stanford University, Stanford, CA 94305, USA.
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Stephen R. Quake
1Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
5Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
6Chan Zuckerberg Biohub, San Francisco, CA 94518, USA.
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Abstract

Background Prenatal diagnosis in pregnancies at risk of single-gene disorders is currently performed using invasive methods such as chorionic villus sampling and amniocentesis. This is in contrast with screening for common aneuploidies, for which noninvasive methods with a single maternal blood sample have become standard clinical practice.

Methods We developed a protocol for noninvasive prenatal diagnosis of inherited single gene disorders using droplet digital PCR (ddPCR) from circulating cell-free DNA (cfDNA) in maternal plasma. First, the amount of cfDNA and fetal fraction are determined using a panel of Taqman assays targeting high-variability SNPs. Second, the ratio of healthy and diseased alleles in maternal plasma are quantified using Taqman assays targeting the mutations carried by the parents. Two validation approaches of the mutation assay are presented.

Results We collected blood samples from 9 pregnancies at risk for different single gene disorders including common conditions and rare metabolic disorders. We measured cases at risk of hemophilia, ornithine transcarbamylase deficiency, cystic fibrosis, β-thalassemia, mevalonate kinase deficiency, acetylcholine receptor deficiency and DFNB1 nonsyndromic hearing loss. We correctly differentiated affected and unaffected pregnancies (2 affected, 7 unaffected), confirmed by neonatal testing. We successfully measured an affected pregnancy as early as week 11, and with a fetal fraction as low as 3.7±0.3%.

Conclusion Our method detects single nucleotide mutations of autosomal recessive diseases as early as the first trimester of pregnancy. This is of importance for metabolic disorders where early diagnosis can affect management of the disease and reduce complications and anxiety related to invasive testing.

Footnotes

  • Abbreviations:

    ddPCR
    droplet digital PCR
    cfDNA
    cell-free DNA
    SNP
    single nucleotide polymorphism
    NIPT
    noninvasive prenatal testing
    CVS
    Chorionic villi sampling
    gDNA
    genomic DNA
    MAF
    minor allele fraction
    OTC
    Ornithine Transcarbamylase Deficiency
    MKD
    Mevalonate Kinase Deficiency
    AChR
    Acetylcholine receptor

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted August 23, 2017.
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Nonivasive prenatal diagnosis of single-gene disorders using droplet digital PCR
Joan Camunas-Soler, Hojae Lee, Louanne Hudgins, Susan R. Hintz, Yair J. Blumenfeld, Yasser Y. El-Sayed, Stephen R. Quake
bioRxiv 179804; doi: https://doi.org/10.1101/179804
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Nonivasive prenatal diagnosis of single-gene disorders using droplet digital PCR
Joan Camunas-Soler, Hojae Lee, Louanne Hudgins, Susan R. Hintz, Yair J. Blumenfeld, Yasser Y. El-Sayed, Stephen R. Quake
bioRxiv 179804; doi: https://doi.org/10.1101/179804

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