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An estimation of the prevalence of genomic disorders using chromosomal microarray data

Multiple genomic disorders result from recurrent deletions or duplications between low-copy repeat (LCR) clusters, mediated by nonallelic homologous recombination (NAHR). These copy number variants (CNVs) often exhibit variable expressivity and/or incomplete penetrance. However, the population preva...

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Autores principales: Gillentine, M.A., Lupo, P.J., Stankiewicz, P., Schaaf, C.P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019170/
https://www.ncbi.nlm.nih.gov/pubmed/29691480
http://dx.doi.org/10.1038/s10038-018-0451-x
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author Gillentine, M.A.
Lupo, P.J.
Stankiewicz, P.
Schaaf, C.P.
author_facet Gillentine, M.A.
Lupo, P.J.
Stankiewicz, P.
Schaaf, C.P.
author_sort Gillentine, M.A.
collection PubMed
description Multiple genomic disorders result from recurrent deletions or duplications between low-copy repeat (LCR) clusters, mediated by nonallelic homologous recombination (NAHR). These copy number variants (CNVs) often exhibit variable expressivity and/or incomplete penetrance. However, the population prevalence of many genomic disorders has not been estimated accurately. A subset of genomic disorders similarly characterized by CNVs between LCRs have been studied epidemiologically, including Williams-Beuren syndrome (7q11.23), Smith-Magenis syndrome (17p11.2), Velocardiofacial syndrome (22q11.21), Prader-Willi/Angelman syndromes (15q11.2q12), 17q12 deletion syndrome, and Charcot-Marie-Tooth Neuropathy type 1 (CMT1A)/hereditary neuropathy with liability to pressure palsy (HNPP) (PMP22, 17q11.2). We have generated a method to estimate prevalence of highly penetrant genomic disorders by (1) leveraging epidemiological data for genomic disorders with previously reported prevalence estimates, (2) obtaining chromosomal microarray data on genomic disorders from a large medical genetics clinic; and (3) utilizing these in a linear regression model to determine the prevalence of this syndromic copy number change among the general population. Using our algorithm, the prevalence for five clinically relevant recurrent genomic disorders: 1q21.1 microdeletion (1/6,882 live births) and microduplication syndromes (1/6,309), 15q13.3 microdeletion syndrome (1/5,525), and 16p11.2 microdeletion (1/3,021) and microduplication syndromes (1/4,216), were determined. These findings will inform epidemiological strategies for evaluating those conditions, and our method may be useful to evaluate the prevalence of other highly penetrant genomic disorders.
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spelling pubmed-60191702018-10-24 An estimation of the prevalence of genomic disorders using chromosomal microarray data Gillentine, M.A. Lupo, P.J. Stankiewicz, P. Schaaf, C.P. J Hum Genet Article Multiple genomic disorders result from recurrent deletions or duplications between low-copy repeat (LCR) clusters, mediated by nonallelic homologous recombination (NAHR). These copy number variants (CNVs) often exhibit variable expressivity and/or incomplete penetrance. However, the population prevalence of many genomic disorders has not been estimated accurately. A subset of genomic disorders similarly characterized by CNVs between LCRs have been studied epidemiologically, including Williams-Beuren syndrome (7q11.23), Smith-Magenis syndrome (17p11.2), Velocardiofacial syndrome (22q11.21), Prader-Willi/Angelman syndromes (15q11.2q12), 17q12 deletion syndrome, and Charcot-Marie-Tooth Neuropathy type 1 (CMT1A)/hereditary neuropathy with liability to pressure palsy (HNPP) (PMP22, 17q11.2). We have generated a method to estimate prevalence of highly penetrant genomic disorders by (1) leveraging epidemiological data for genomic disorders with previously reported prevalence estimates, (2) obtaining chromosomal microarray data on genomic disorders from a large medical genetics clinic; and (3) utilizing these in a linear regression model to determine the prevalence of this syndromic copy number change among the general population. Using our algorithm, the prevalence for five clinically relevant recurrent genomic disorders: 1q21.1 microdeletion (1/6,882 live births) and microduplication syndromes (1/6,309), 15q13.3 microdeletion syndrome (1/5,525), and 16p11.2 microdeletion (1/3,021) and microduplication syndromes (1/4,216), were determined. These findings will inform epidemiological strategies for evaluating those conditions, and our method may be useful to evaluate the prevalence of other highly penetrant genomic disorders. 2018-04-24 2018-07 /pmc/articles/PMC6019170/ /pubmed/29691480 http://dx.doi.org/10.1038/s10038-018-0451-x Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Gillentine, M.A.
Lupo, P.J.
Stankiewicz, P.
Schaaf, C.P.
An estimation of the prevalence of genomic disorders using chromosomal microarray data
title An estimation of the prevalence of genomic disorders using chromosomal microarray data
title_full An estimation of the prevalence of genomic disorders using chromosomal microarray data
title_fullStr An estimation of the prevalence of genomic disorders using chromosomal microarray data
title_full_unstemmed An estimation of the prevalence of genomic disorders using chromosomal microarray data
title_short An estimation of the prevalence of genomic disorders using chromosomal microarray data
title_sort estimation of the prevalence of genomic disorders using chromosomal microarray data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019170/
https://www.ncbi.nlm.nih.gov/pubmed/29691480
http://dx.doi.org/10.1038/s10038-018-0451-x
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