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Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens

BACKGROUND: Noninvasive prenatal screening (NIPS) of common aneuploidies using cell-free DNA from maternal plasma is part of routine prenatal care and is widely used in both high-risk and low-risk patient populations. High specificity is needed for clinically acceptable positive predictive values. M...

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Autores principales: Kaseniit, Kristjan Eerik, Hogan, Gregory J, D’Auria, Kevin M, Haverty, Carrie, Muzzey, Dale
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194617/
https://www.ncbi.nlm.nih.gov/pubmed/30340588
http://dx.doi.org/10.1186/s12920-018-0410-6
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author Kaseniit, Kristjan Eerik
Hogan, Gregory J
D’Auria, Kevin M
Haverty, Carrie
Muzzey, Dale
author_facet Kaseniit, Kristjan Eerik
Hogan, Gregory J
D’Auria, Kevin M
Haverty, Carrie
Muzzey, Dale
author_sort Kaseniit, Kristjan Eerik
collection PubMed
description BACKGROUND: Noninvasive prenatal screening (NIPS) of common aneuploidies using cell-free DNA from maternal plasma is part of routine prenatal care and is widely used in both high-risk and low-risk patient populations. High specificity is needed for clinically acceptable positive predictive values. Maternal copy-number variants (mCNVs) have been reported as a source of false-positive aneuploidy results that compromises specificity. METHODS: We surveyed the mCNV landscape in 87,255 patients undergoing NIPS. We evaluated both previously reported and novel algorithmic strategies for mitigating the effects of mCNVs on the screen’s specificity. Further, we analyzed the frequency, length, and positional distribution of CNVs in our large dataset to investigate the curation of novel fetal microdeletions, which can be identified by NIPS but are challenging to interpret clinically. RESULTS: mCNVs are common, with 65% of expecting mothers harboring an autosomal CNV spanning more than 200 kb, underscoring the need for robust NIPS analysis strategies. By analyzing empirical and simulated data, we found that general, outlier-robust strategies reduce the rate of mCNV-caused false positives but not as appreciably as algorithms specifically designed to account for mCNVs. We demonstrate that large-scale tabulation of CNVs identified via routine NIPS could be clinically useful: together with the gene density of a putative microdeletion region, we show that the region’s relative tolerance to duplications versus deletions may aid the interpretation of microdeletion pathogenicity. CONCLUSIONS: Our study thoroughly investigates a common source of NIPS false positives and demonstrates how to bypass its corrupting effects. Our findings offer insight into the interpretation of NIPS results and inform the design of NIPS algorithms suitable for use in screening in the general obstetric population. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12920-018-0410-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-61946172018-10-25 Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens Kaseniit, Kristjan Eerik Hogan, Gregory J D’Auria, Kevin M Haverty, Carrie Muzzey, Dale BMC Med Genomics Research Article BACKGROUND: Noninvasive prenatal screening (NIPS) of common aneuploidies using cell-free DNA from maternal plasma is part of routine prenatal care and is widely used in both high-risk and low-risk patient populations. High specificity is needed for clinically acceptable positive predictive values. Maternal copy-number variants (mCNVs) have been reported as a source of false-positive aneuploidy results that compromises specificity. METHODS: We surveyed the mCNV landscape in 87,255 patients undergoing NIPS. We evaluated both previously reported and novel algorithmic strategies for mitigating the effects of mCNVs on the screen’s specificity. Further, we analyzed the frequency, length, and positional distribution of CNVs in our large dataset to investigate the curation of novel fetal microdeletions, which can be identified by NIPS but are challenging to interpret clinically. RESULTS: mCNVs are common, with 65% of expecting mothers harboring an autosomal CNV spanning more than 200 kb, underscoring the need for robust NIPS analysis strategies. By analyzing empirical and simulated data, we found that general, outlier-robust strategies reduce the rate of mCNV-caused false positives but not as appreciably as algorithms specifically designed to account for mCNVs. We demonstrate that large-scale tabulation of CNVs identified via routine NIPS could be clinically useful: together with the gene density of a putative microdeletion region, we show that the region’s relative tolerance to duplications versus deletions may aid the interpretation of microdeletion pathogenicity. CONCLUSIONS: Our study thoroughly investigates a common source of NIPS false positives and demonstrates how to bypass its corrupting effects. Our findings offer insight into the interpretation of NIPS results and inform the design of NIPS algorithms suitable for use in screening in the general obstetric population. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12920-018-0410-6) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-19 /pmc/articles/PMC6194617/ /pubmed/30340588 http://dx.doi.org/10.1186/s12920-018-0410-6 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Kaseniit, Kristjan Eerik
Hogan, Gregory J
D’Auria, Kevin M
Haverty, Carrie
Muzzey, Dale
Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens
title Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens
title_full Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens
title_fullStr Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens
title_full_unstemmed Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens
title_short Strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens
title_sort strategies to minimize false positives and interpret novel microdeletions based on maternal copy-number variants in 87,000 noninvasive prenatal screens
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6194617/
https://www.ncbi.nlm.nih.gov/pubmed/30340588
http://dx.doi.org/10.1186/s12920-018-0410-6
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