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Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses

A meta‐analysis on seven large case series (>1000 cases) of chromosome microarray analysis (CMA) on products of conceptions (POC) evaluated the diagnostic yields of genomic disorders and syndromic pathogenic copy number variants (pCNVs) from a collection of 35,130 POC cases. CMA detected chromoso...

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Autores principales: Peng, Gang, Zhou, Qinghua, Chai, Hongyan, Wen, Jiadi, Zhao, Hongyu, Taylor, Hugh S., Jiang, Yong‐Hui, Li, Peining
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422064/
https://www.ncbi.nlm.nih.gov/pubmed/37013615
http://dx.doi.org/10.1002/mgg3.2181
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author Peng, Gang
Zhou, Qinghua
Chai, Hongyan
Wen, Jiadi
Zhao, Hongyu
Taylor, Hugh S.
Jiang, Yong‐Hui
Li, Peining
author_facet Peng, Gang
Zhou, Qinghua
Chai, Hongyan
Wen, Jiadi
Zhao, Hongyu
Taylor, Hugh S.
Jiang, Yong‐Hui
Li, Peining
author_sort Peng, Gang
collection PubMed
description A meta‐analysis on seven large case series (>1000 cases) of chromosome microarray analysis (CMA) on products of conceptions (POC) evaluated the diagnostic yields of genomic disorders and syndromic pathogenic copy number variants (pCNVs) from a collection of 35,130 POC cases. CMA detected chromosomal abnormalities and pCNVs in approximately 50% and 2.5% of cases, respectively. The genomic disorders and syndromic pCNVs accounted for 31% of the detected pCNVs, and their incidences in POC ranged from 1/750 to 1/12,000. The newborn incidences of these genomic disorders and syndromic pCNVs were estimated in a range of 1/4000 to 1/50,000 live births from population genetic studies and diagnostic yields of a large case series of 32,587 pediatric patients. The risk of spontaneous abortion (SAB) for DiGeorge syndrome (DGS), Wolf–Hirschhorn syndrome (WHS), and William–Beuren syndrome (WBS) was 42%, 33%, and 21%, respectively. The estimated overall risk of SAB for major genomic disorders and syndromic pCNVs was approximately 38%, which was significantly lower than the 94% overall risk of SAB for chromosomal abnormalities. Further classification on levels of risk of SAB to high (>75%), intermediate (51%–75%), and low (26%–50%) for known chromosomal abnormalities, genomic disorders, and syndromic pCNVs could provide evidence‐based interpretation in prenatal diagnosis and genetic counseling.
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spelling pubmed-104220642023-08-13 Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses Peng, Gang Zhou, Qinghua Chai, Hongyan Wen, Jiadi Zhao, Hongyu Taylor, Hugh S. Jiang, Yong‐Hui Li, Peining Mol Genet Genomic Med Original Articles A meta‐analysis on seven large case series (>1000 cases) of chromosome microarray analysis (CMA) on products of conceptions (POC) evaluated the diagnostic yields of genomic disorders and syndromic pathogenic copy number variants (pCNVs) from a collection of 35,130 POC cases. CMA detected chromosomal abnormalities and pCNVs in approximately 50% and 2.5% of cases, respectively. The genomic disorders and syndromic pCNVs accounted for 31% of the detected pCNVs, and their incidences in POC ranged from 1/750 to 1/12,000. The newborn incidences of these genomic disorders and syndromic pCNVs were estimated in a range of 1/4000 to 1/50,000 live births from population genetic studies and diagnostic yields of a large case series of 32,587 pediatric patients. The risk of spontaneous abortion (SAB) for DiGeorge syndrome (DGS), Wolf–Hirschhorn syndrome (WHS), and William–Beuren syndrome (WBS) was 42%, 33%, and 21%, respectively. The estimated overall risk of SAB for major genomic disorders and syndromic pCNVs was approximately 38%, which was significantly lower than the 94% overall risk of SAB for chromosomal abnormalities. Further classification on levels of risk of SAB to high (>75%), intermediate (51%–75%), and low (26%–50%) for known chromosomal abnormalities, genomic disorders, and syndromic pCNVs could provide evidence‐based interpretation in prenatal diagnosis and genetic counseling. John Wiley and Sons Inc. 2023-04-04 /pmc/articles/PMC10422064/ /pubmed/37013615 http://dx.doi.org/10.1002/mgg3.2181 Text en © 2023 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Peng, Gang
Zhou, Qinghua
Chai, Hongyan
Wen, Jiadi
Zhao, Hongyu
Taylor, Hugh S.
Jiang, Yong‐Hui
Li, Peining
Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
title Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
title_full Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
title_fullStr Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
title_full_unstemmed Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
title_short Estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
title_sort estimation on risk of spontaneous abortions by genomic disorders from a meta‐analysis of microarray results on large case series of pregnancy losses
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422064/
https://www.ncbi.nlm.nih.gov/pubmed/37013615
http://dx.doi.org/10.1002/mgg3.2181
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