Performance of semiconductor sequencing platform for non‐invasive prenatal genetic screening for fetal aneuploidy: results from a multicenter prospective cohort study in a clinical setting

Khattabi, Laïla El; Brun, S.; Guéguen, Paul; Chatron, Nicolas; Guichoux, Erwan; Schutz, Sacha; Nectoux, Juliette; Sorlin, Arthur; Quere, M. P.; Boudjarane, John; Tsatsaris, Vassilis; Mandelbrot, Laurent; Schluth-Bolard, Caroline; Dupont, Jean‐Michel; Rooryck, Caroline; Cormier, Alexandre; Férec, Claude; Pipoli, J.; Letourneur, Franck; Bonnet, Céline; Jonveaux, Philippe; Bardel, Claire; Lagarde, Arnaud; Badens, Catherine; Lévy, Nicolas; Duboc, Véronique; Paquis‐Fluckinger, Véronique; Boureau-Wirth, Amandine; Bannwarth, Sylvie; Arveiler, Benoı̂t; Lacombe, Didier; Goossens, Michel; Vidaud, Michel; Massardier, Jérôme; Saliou, Anne-Hélène; Sanlaville, Damien

doi:10.1002/uog.20112

Cited by 11 publications

(10 citation statements)

References 30 publications

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“…SANEFALCON method was narrower than that in the DEFRAG method, and the assay-based method involving methylated RASSF1A promoters (96,108). However, the DEFRAG assay can only detect FF in male fetuses, while the RASSF1A assay can detect the FF in both male and female fetuses but requires additional PCR steps.…”

Section: Methods For Calculation Ffmentioning

confidence: 94%

Factors Affecting the Fetal Fraction in Noninvasive Prenatal Screening: A Review

Deng

Liu

2022

Front. Pediatr.

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A paradigm shift in noninvasive prenatal screening has been made with the discovery of cell-free fetal DNA in maternal plasma. Noninvasive prenatal screening is primarily used to screen for fetal aneuploidies, and has been used globally. Fetal fraction, an important parameter in the analysis of noninvasive prenatal screening results, is the proportion of fetal cell-free DNA present in the total maternal plasma cell-free DNA. It combines biological factors and bioinformatics algorithms to interpret noninvasive prenatal screening results and is an integral part of quality control. Maternal and fetal factors may influence fetal fraction. To date, there is no broad consensus on the factors that affect fetal fraction. There are many different approaches to evaluate this parameter, each with its advantages and disadvantages. Different fetal fraction calculation methods may be used in different testing platforms or laboratories. This review includes numerous publications that focused on the understanding of the significance, influencing factors, and interpretation of fetal fraction to provide a deeper understanding of this parameter.

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Section: Methods For Calculation Ffmentioning

confidence: 94%

Factors Affecting the Fetal Fraction in Noninvasive Prenatal Screening: A Review

Deng

Liu

2022

Front. Pediatr.

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“…We observed that the distribution of points (samples) is coherent in the two cohorts ( Figure 2A and B ): most of the points are clustered around the centroid of the plot. If cohorts came from two different hospitals, the extraction and sequencing method were identical [ 23 ]. We thus joined the two cohorts for cross comparison ( Figure 2C ).…”

Section: Resultsmentioning

confidence: 99%

“…Shallow whole-genome sequencing of cfDNA was performed using either a Proton or an S5XL sequencer (Thermo Fisher Scientific®, Waltham, MA, USA), starting from 15 ng input of cfDNA. For library building, cfDNA samples were processed either manually or in semiautomated procedure with the Ion Plus fragment library kit and Ion Plus Core Library Module for AB Library Builder TM System respectively (Life Technologies -Thermo Fisher Scientific®, Waltham, MA, USA) using an optimized procedure [ 23 ]. Library concentrations were measured using Ion Library TaqMan™ Quantitation Kit (Thermo Fisher Scientific).…”

Section: Methodsmentioning

confidence: 99%

NiPTUNE: an automated pipeline for noninvasive prenatal testing in an accurate, integrative and flexible framework

Duboc¹,

Pratella

Milanesio

et al. 2021

Briefings in Bioinformatics

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Noninvasive prenatal testing (NIPT) consists of determining fetal aneuploidies by quantifying copy number alteration from the sequencing of cell-free DNA (cfDNA) from maternal blood. Due to the presence of cfDNA of fetal origin in maternal blood, in silico approaches have been developed to accurately predict fetal aneuploidies. Although NIPT is becoming a new standard in prenatal screening of chromosomal abnormalities, there are no integrated pipelines available to allow rapid, accurate and standardized data analysis in any clinical setting. Several tools have been developed, however often optimized only for research purposes or requiring enormous amount of retrospective data, making hard their implementation in a clinical context. Furthermore, no guidelines have been provided on how to accomplish each step of the data analysis to achieve reliable results. Finally, there is no integrated pipeline to perform all steps of NIPT analysis. To address these needs, we tested several tools for performing NIPT data analysis. We provide extensive benchmark of tools performances but also guidelines for running them. We selected the best performing tools that we benchmarked and gathered them in a computational pipeline. NiPTUNE is an open source python package that includes methods for fetal fraction estimation, a novel method for accurate gender prediction, a principal component analysis based strategy for quality control and fetal aneuploidies prediction. NiPTUNE is constituted by seven modules allowing the user to run the entire pipeline or each module independently. Using two cohorts composed by 1439 samples with 31 confirmed aneuploidies, we demonstrated that NiPTUNE is a valuable resource for NIPT analysis.

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“…Non‐invasive prenatal testing (NIPT) methods relying on low‐pass whole‐genome sequencing can be used to test all chromosomes for aneuploidy, as with karyotyping. Within the H+ Consortium, we developed an in‐house NIPT method using whole‐genome semiconductor sequencing. A minimum of 8 million aligned deduplicated reads were necessary for WISECONDOR analysis based on a local reference dataset of 31 euploid samples.…”

Section: Non‐invasive Prenatal Testing (Nipt) Results and Follow‐up Imentioning

confidence: 99%

Detection of rare autosomal trisomies through non‐invasive prenatal testing: benefits for pregnancy management

Chatron

Till

Abel

et al. 2019

Ultrasound in Obstet & Gyne

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Non Invasive Prenatal Testing (NIPT) methods relying on low-pass whole genome sequencing can be used for pangenomic testing as karyotyping. Within the H+ Consortium, we developed an in-house NIPT using whole genome semi-conductor sequencing. A minimum of 8 million aligned deduplicated reads were necessary for WISECONDOR analysis (1) based on a local reference dataset of 31 euploid samples. Patients were informed of potential secondary findings during pre-test counseling. Karyotype techniques were performed using standard procedures either on amniotic fluid (AF) cell culture during pregnancy or on placental tissue obtained after delivery. Centromeric probes were used for interphase FISH techniques. Uniparental disomy (UPD) was tested using methyl PCR after sodium bisulfite treatment and microsatellites analysis. This article is protected by copyright. All rights reserved.

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Performance of semiconductor sequencing platform for non‐invasive prenatal genetic screening for fetal aneuploidy: results from a multicenter prospective cohort study in a clinical setting

Cited by 11 publications

References 30 publications

Factors Affecting the Fetal Fraction in Noninvasive Prenatal Screening: A Review

Factors Affecting the Fetal Fraction in Noninvasive Prenatal Screening: A Review

NiPTUNE: an automated pipeline for noninvasive prenatal testing in an accurate, integrative and flexible framework

Detection of rare autosomal trisomies through non‐invasive prenatal testing: benefits for pregnancy management

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