Literature DB >> 28675625

Comment on "Noninvasive prenatal screening at low fetal fraction: comparing whole-genome sequencing and single-nucleotide polymorphism methods".

Allison Ryan1, Kimberly A Martin2.   

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Year:  2017        PMID: 28675625      PMCID: PMC5575504          DOI: 10.1002/pd.5072

Source DB:  PubMed          Journal:  Prenat Diagn        ISSN: 0197-3851            Impact factor:   3.050


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This correspondence is in reference to the article entitled, ‘Noninvasive Prenatal Screening at Low Fetal Fraction: Comparing Whole‐Genome Sequencing and Single‐Nucleotide Polymorphism Methods’ by Artieri, et al., which was recently published in Prenatal Diagnosis.1 The objective of the publication was to compare the performance of two non‐invasive prenatal testing (NIPT) methods, whole‐genome sequencing (WGS) and single nucleotide polymorphism (SNP)‐based analysis of cell‐free DNA, for the detection of fetal trisomies, specifically at low fetal fractions. The authors make strong clinical claims about the inferior performance of SNP‐based NIPT compared with the WGS method that are invalidated by two significant methodological flaws – (1) the WGS model does not address inherent biological and measurement variations, and (2) the model for the SNP‐based method disregards the method's ability to establish linkage between SNPs. Compounding these issues, neither simulation model was validated by showing that it produces realistic sequencing data. To point one, the approach used for the WGS model was based on a theoretical Poisson distribution and did not incorporate any sources of variance other than random sampling of the number of reads. It is, however, widely accepted that WGS‐generated NIPT data are affected by several additional sources of variance,2 both biological and laboratory‐process driven, which lead to reduced performance at low fetal fraction.3, 4 These include variability in fetal DNA concentration, pre‐sequencing DNA amplification, and GC content. In the described simulation approach, any underestimate of WGS process variance would result in the trisomy classification limit being set artificially low, leading directly to improved apparent sensitivity. Furthermore, it is standard practice that simulation‐based analyses be supported by evidence that the simulation produces realistic data – in the absence of such validation, there is no justification for using the simulation to make claims about clinical performance. To point two, the modeling of the SNP‐based classification method was incomplete. The authors' implementation of the SNP‐based classification method incorrectly assumes that each SNP's fetal genotype is inherited independently from adjacent loci, ignoring the information available using linkage. In contrast, Natera's SNP‐based method incorporates the effect of chromosome recombinations and homolog inheritance (i.e. linkage) that are critical to accurately detecting trisomies. As it is missing this critical component, the SNP‐based classifier implemented by the authors cannot be used to predict performance limitations of a fully implemented method. Finally, high sensitivity of the SNP‐based NIPT method was analytically validated using plasma from affected pregnancies.5, 6 Additionally, SNP‐based methods have the unique ability to detect triploidy,7 vanishing twins and molar pregnancies, which further increases their overall ability to detect aneuploidy. The article by Artieri, et al. does not provide sound justification for its claims regarding poor sensitivity of the SNP method, nor has Counsyl published validation data demonstrating clinical sensitivity of their own WGS‐based test.1
  8 in total

1.  Prenatal detection of fetal triploidy from cell-free DNA testing in maternal blood.

Authors:  Kypros H Nicolaides; Argyro Syngelaki; Maria del Mar Gil; Maria Soledad Quezada; Yana Zinevich
Journal:  Fetal Diagn Ther       Date:  2013-10-10       Impact factor: 2.587

2.  Noninvasive prenatal screening at low fetal fraction: comparing whole-genome sequencing and single-nucleotide polymorphism methods.

Authors:  Carlo G Artieri; Carrie Haverty; Eric A Evans; James D Goldberg; Imran S Haque; Yuval Yaron; Dale Muzzey
Journal:  Prenat Diagn       Date:  2017-04-26       Impact factor: 3.050

3.  A unified approach to risk assessment for fetal aneuploidies.

Authors:  D Wright; A Wright; K H Nicolaides
Journal:  Ultrasound Obstet Gynecol       Date:  2014-12-01       Impact factor: 7.299

4.  The impact of maternal plasma DNA fetal fraction on next generation sequencing tests for common fetal aneuploidies.

Authors:  Jacob A Canick; Glenn E Palomaki; Edward M Kloza; Geralyn M Lambert-Messerlian; James E Haddow
Journal:  Prenat Diagn       Date:  2013-05-31       Impact factor: 3.050

5.  Single-nucleotide polymorphism-based noninvasive prenatal screening in a high-risk and low-risk cohort.

Authors:  Eugene Pergament; Howard Cuckle; Bernhard Zimmermann; Milena Banjevic; Styrmir Sigurjonsson; Allison Ryan; Megan P Hall; Michael Dodd; Phil Lacroute; Melissa Stosic; Nikhil Chopra; Nathan Hunkapiller; Dennis E Prosen; Sallie McAdoo; Zachary Demko; Asim Siddiqui; Matthew Hill; Matthew Rabinowitz
Journal:  Obstet Gynecol       Date:  2014-08       Impact factor: 7.661

6.  Validation of an Enhanced Version of a Single-Nucleotide Polymorphism-Based Noninvasive Prenatal Test for Detection of Fetal Aneuploidies.

Authors:  Allison Ryan; Nathan Hunkapiller; Milena Banjevic; Naresh Vankayalapati; Nicole Fong; Kristine N Jinnett; Zachary Demko; Bernhard Zimmermann; Styrmir Sigurjonsson; Susan J Gross; Matthew Hill
Journal:  Fetal Diagn Ther       Date:  2016-03-31       Impact factor: 2.587

7.  Noninvasive prenatal diagnosis of fetal trisomy 18 and trisomy 13 by maternal plasma DNA sequencing.

Authors:  Eric Z Chen; Rossa W K Chiu; Hao Sun; Ranjit Akolekar; K C Allen Chan; Tak Y Leung; Peiyong Jiang; Yama W L Zheng; Fiona M F Lun; Lisa Y S Chan; Yongjie Jin; Attie T J I Go; Elizabeth T Lau; William W K To; Wing C Leung; Rebecca Y K Tang; Sidney K C Au-Yeung; Helena Lam; Yu Y Kung; Xiuqing Zhang; John M G van Vugt; Ryoko Minekawa; Mary H Y Tang; Jun Wang; Cees B M Oudejans; Tze K Lau; Kypros H Nicolaides; Y M Dennis Lo
Journal:  PLoS One       Date:  2011-07-06       Impact factor: 3.240

8.  Comment on "Noninvasive prenatal screening at low fetal fraction: comparing whole-genome sequencing and single-nucleotide polymorphism methods".

Authors:  Allison Ryan; Kimberly A Martin
Journal:  Prenat Diagn       Date:  2017-07       Impact factor: 3.050

  8 in total
  3 in total

1.  Chromosomal phase improves aneuploidy detection in non-invasive prenatal testing at low fetal DNA fractions.

Authors:  Giulio Genovese; Curtis J Mello; Po-Ru Loh; Robert E Handsaker; Seva Kashin; Christopher W Whelan; Lucy A Bayer-Zwirello; Steven A McCarroll
Journal:  Sci Rep       Date:  2022-07-14       Impact factor: 4.996

2.  Comment on "Noninvasive prenatal screening at low fetal fraction: comparing whole-genome sequencing and single-nucleotide polymorphism methods".

Authors:  Allison Ryan; Kimberly A Martin
Journal:  Prenat Diagn       Date:  2017-07       Impact factor: 3.050

3.  Identification of a novel COL10A1: c.1952 G>T variant in a family with Schmid metaphyseal chondrodysplasia and development of a noninvasive prenatal testing method.

Authors:  Yanchou Ye; Weihao Li; Guan Wang; Longsheng Zhan; Junwei Lin; Tian Li; Jun Zhang
Journal:  Mol Genet Genomic Med       Date:  2021-08-23       Impact factor: 2.183

  3 in total

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