GenomeMixer and TRUST: Novel bioinformatics tools to improve reliability of Non-Invasive Prenatal Testing (NIPT) for fetal aneuploidies.

Aneuploidy detection Confidence intervals Fetal fraction Non-invasive prenatal testing Semi-supervised method

Journal

Computational and structural biotechnology journal
ISSN: 2001-0370
Titre abrégé: Comput Struct Biotechnol J
Pays: Netherlands
ID NLM: 101585369

Informations de publication

Date de publication:
2022
Historique:
received: 22 09 2021
revised: 27 01 2022
accepted: 17 02 2022
entrez: 4 3 2022
pubmed: 5 3 2022
medline: 5 3 2022
Statut: epublish

Résumé

Non-invasive prenatal testing (NIPT) screens for common fetal chromosomal abnormalities through analysis of circulating cell-free DNA in maternal blood by massive parallel sequencing. NIPT reliability relies on both the estimation of the fetal fraction (ff) and on the sequencing depth (sd) but how these parameters are linked is unknown. Several bioinformatics tools have been developed to determine the ff but there is no universal ff threshold applicable across diagnostics laboratories. Thus, we developed two tools allowing the implementation of a strategy for NIPT results validation in clinical practice: GenomeMixer, a semi-supervised approach to create synthetic sequences and to estimate confidence intervals for NIPT validation and TRUST to estimate the reliability of NIPT results based on confidence intervals found in this study. We retrospectively validated these new tools on 2 cohorts for a total of 1439 samples with 31 confirmed aneuploidies. Through the analysis of the interrelationship between ff, sd and chromosomal aberration detection, we demonstrate that these parameters are profoundly connected and cannot be considered independently. Our tools take in account this critical relationship to improve NIPT reliability and facilitate cross laboratory standardization of this screening test.

Identifiants

pubmed: 35242293
doi: 10.1016/j.csbj.2022.02.014
pii: S2001-0370(22)00054-X
pmc: PMC8881690
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1028-1035

Informations de copyright

© 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

Déclaration de conflit d'intérêts

The authors declare that they have no competing interests

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Auteurs

David Pratella (D)

Université Côte d'Azur, Center of Modeling, Simulation and Interactions, Nice, France.

Véronique Duboc (V)

Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Inserm U1081, CNRS UMR7284, IRCAN, Nice, France.

Marco Milanesio (M)

Université Côte d'Azur, Center of Modeling, Simulation and Interactions, Nice, France.
Université Côte d'Azur, Inria, Epione Project-Team, Sophia-Antipolis, France.

John Boudjarane (J)

Département de génétique médicale, Centre Hospitalier Universitaire la Timone, Marseille, France.

Stéphane Descombes (S)

Université Côte d'Azur, Center of Modeling, Simulation and Interactions, Nice, France.

Véronique Paquis-Flucklinger (V)

Université Côte d'Azur, Center of Modeling, Simulation and Interactions, Nice, France.
Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Inserm U1081, CNRS UMR7284, IRCAN, Nice, France.

Silvia Bottini (S)

Université Côte d'Azur, Center of Modeling, Simulation and Interactions, Nice, France.

Classifications MeSH