Estimates of penetrance for recurrent pathogenic copy-number variations
Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We s...
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| Published in | Genetics in medicine Vol. 15; no. 6; pp. 478 - 481 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Elsevier Inc
01.06.2013
Nature Publishing Group US Elsevier Limited Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1098-3600 1530-0366 1530-0366 |
| DOI | 10.1038/gim.2012.164 |
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| Abstract | Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci.
We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications.
Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions.
This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session.
Genet Med 2013:15(6):478–481 |
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| AbstractList | Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci.
We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications.
Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions.
This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session. Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci.PURPOSEAlthough an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci.We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications.METHODSWe conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications.Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions.RESULTSEstimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions.This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session.CONCLUSIONThis model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session. Purpose:Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci.Methods:We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications.Results:Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions.Conclusion:This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session.Genet Med 2013:15(6):478–481 Purpose: Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci. Methods: We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations ( n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications. Results: Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions. Conclusion: This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session. Genet Med 2013:15(6):478–481 Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci. We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be ~5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications. Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions. This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session. Genet Med 2013:15(6):478–481 Purpose: Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of these copy-number variations remains mostly unknown. This poses challenges for counseling, both for recurrence risks and prenatal diagnosis. We sought to provide empiric estimates for penetrance for some of these recurrent, disease-susceptibility loci. Methods: We conducted a Bayesian analysis, based on the copy-number variation frequencies in control populations (n = 22,246) and in our database of >48,000 postnatal microarray-based comparative genomic hybridization samples. The background risk for congenital anomalies/developmental delay/intellectual disability was assumed to be approximately 5%. Copy-number variations studied were 1q21.1 proximal duplications, 1q21.1 distal deletions and duplications, 15q11.2 deletions, 16p13.11 deletions, 16p12.1 deletions, 16p11.2 proximal and distal deletions and duplications, 17q12 deletions and duplications, and 22q11.21 duplications. Results: Estimates for the risk of an abnormal phenotype ranged from 10.4% for 15q11.2 deletions to 62.4% for distal 16p11.2 deletions. Conclusion: This model can be used to provide more precise estimates for the chance of an abnormal phenotype for many copy-number variations encountered in the prenatal setting. By providing the penetrance, additional, critical information can be given to prospective parents in the genetic counseling session. |
| Author | Cuckle, Howard Eichler, Evan E. Shaffer, Lisa G. Coe, Bradley P. Rosenfeld, Jill A. |
| Author_xml | – sequence: 1 givenname: Jill A. surname: Rosenfeld fullname: Rosenfeld, Jill A. organization: Signature Genomic Laboratories, PerkinElmer, Inc. Spokane, Washington, USA – sequence: 2 givenname: Bradley P. surname: Coe fullname: Coe, Bradley P. organization: Department of Genome Sciences, University of Washington, Seattle, Washington, USA – sequence: 3 givenname: Evan E. surname: Eichler fullname: Eichler, Evan E. organization: Department of Genome Sciences, University of Washington, Seattle, Washington, USA – sequence: 4 givenname: Howard surname: Cuckle fullname: Cuckle, Howard organization: Department of Obstetrics and Gynecology, Columbia University Medical Center, New York, New York, USA – sequence: 5 givenname: Lisa G. surname: Shaffer fullname: Shaffer, Lisa G. email: lshaffer@pawprintgenetics.com organization: Signature Genomic Laboratories, PerkinElmer, Inc. Spokane, Washington, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23258348$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
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| References | Girirajan, Eichler (bb0010) 2010; 19 Shen, Dies, Holm (bb0040) 2010; 125 Baird, Anderson, Newcombe, Lowry (bb0080) 1988; 42 Walsh, Bracken (bb0090) 2011; 13 Miller, Adam, Aradhya (bb0035) 2010; 86 Girirajan, Rosenfeld, Coe (bb0045) 2012; 367 Ballif, Theisen, Coppinger (bb0050) 2008; 1 Lee, Lin, Lin, Shih, Lin, Su (bb0100) 2012; 119 Duker, Ballif, Bawle (bb0060) 2010; 18 Girirajan, Campbell, Eichler (bb0015) 2011; 45 van Bon, Mefford, Menten (bb0085) 2009; 46 Vassos, Collier, Holden (bb0075) 2010; 19 Mefford, Sharp, Baker (bb0020) 2008; 359 Cooper, Coe, Girirajan (bb0025) 2011; 43 Ballif, Theisen, McDonald-McGinn (bb0055) 2008; 74 Kaminsky, Kaul, Paschall (bb0030) 2011; 13 Shaffer, Dabell, Fisher (bb0105) 2012; 32 Hubert, Van der Veeken (bb0070) 2008; 22 Centers for Disease Control and Prevention (bb0095) 2009; 58 Bejjani, Saleki, Ballif (bb0065) 2005; 134 Mefford, Sharp, Baker (CR3) 2008; 359 Girirajan, Campbell, Eichler (CR2) 2011; 45 Lee, Lin, Lin, Shih, Lin, Su (CR19) 2012; 119 Girirajan, Rosenfeld, Coe (CR8) 2012; 367 Baird, Anderson, Newcombe, Lowry (CR15) 1988; 42 Ballif, Theisen, McDonald-McGinn (CR10) 2008; 74 Hubert, Van der Veeken (CR13) 2008; 22 Duker, Ballif, Bawle (CR11) 2010; 18 Ballif, Theisen, Coppinger (CR9) 2008; 1 Bejjani, Saleki, Ballif (CR12) 2005; 134 Girirajan, Eichler (CR1) 2010; 19 Shaffer, Dabell, Fisher (CR20) 2012; 32 Vassos, Collier, Holden (CR14) 2010; 19 Cooper, Coe, Girirajan (CR4) 2011; 43 Kaminsky, Kaul, Paschall (CR5) 2011; 13 Miller, Adam, Aradhya (CR6) 2010; 86 (CR18) 2009; 58 Walsh, Bracken (CR17) 2011; 13 van Bon, Mefford, Menten (CR16) 2009; 46 Shen, Dies, Holm (CR7) 2010; 125 Girirajan (10.1038/gim.2012.164_bb0010) van Bon (10.1038/gim.2012.164_bb0085) Walsh (10.1038/gim.2012.164_bb0090) Kaminsky (10.1038/gim.2012.164_bb0030) Baird (10.1038/gim.2012.164_bb0080) Centers for Disease Control and Prevention (10.1038/gim.2012.164_bb0095) 2009; 58 Duker (10.1038/gim.2012.164_bb0060) Vassos (10.1038/gim.2012.164_bb0075) Cooper (10.1038/gim.2012.164_bb0025) Ballif (10.1038/gim.2012.164_bb0055) Shaffer (10.1038/gim.2012.164_bb0105) Miller (10.1038/gim.2012.164_bb0035) Shen (10.1038/gim.2012.164_bb0040) Ballif (10.1038/gim.2012.164_bb0050) Lee (10.1038/gim.2012.164_bb0100) Bejjani (10.1038/gim.2012.164_bb0065) Mefford (10.1038/gim.2012.164_bb0020) Girirajan (10.1038/gim.2012.164_bb0045) Hubert (10.1038/gim.2012.164_bb0070) Girirajan (10.1038/gim.2012.164_bb0015) 23552451 - Genet Med. 2013 Apr;15(4):316-7. doi: 10.1038/gim.2013.16. 23552452 - Genet Med. 2013 Apr;15(4):317-8. doi: 10.1038/gim.2013.20. |
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10.1111/j.1471-0528.2012.03279.x – volume: 43 start-page: 838 year: 2011 end-page: 846 ident: CR4 article-title: A copy number variation morbidity map of developmental delay [forthcoming corrigendum in Nat Genet] publication-title: Nat Genet doi: 10.1038/ng.909 – volume: 74 start-page: 469 year: 2008 end-page: 475 ident: CR10 article-title: Identification of a previously unrecognized microdeletion syndrome of 16q11.2q12.2 publication-title: Clin Genet doi: 10.1111/j.1399-0004.2008.01094.x – volume: 42 start-page: 677 year: 1988 end-page: 693 ident: CR15 article-title: Genetic disorders in children and young adults: a population study publication-title: Am J Hum Genet – volume: 58 start-page: 1 year: 2009 end-page: 20 ident: CR18 article-title: Prevalence of autism spectrum disorders—Autism and Developmental Disabilities Monitoring Network, United States, 2006. Surveillance Summaries publication-title: Morb Mortal Wkly Rep – volume: 19 start-page: R176 year: 2010 end-page: R187 ident: CR1 article-title: Phenotypic variability and genetic susceptibility to genomic disorders publication-title: Hum Mol Genet doi: 10.1093/hmg/ddq366 – volume: 134 start-page: 259 year: 2005 end-page: 267 ident: CR12 article-title: Use of targeted array-based CGH for the clinical diagnosis of chromosomal imbalance: is less more publication-title: Am J Med Genet doi: 10.1002/ajmg.a.30621 – volume: 1 start-page: 8 year: 2008 ident: CR9 article-title: Expanding the clinical phenotype of the 3q29 microdeletion syndrome and characterization of the reciprocal microduplication publication-title: Mol Cytogenet doi: 10.1186/1755-8166-1-8 – ident: 10.1038/gim.2012.164_bb0040 – ident: 10.1038/gim.2012.164_bb0045 – ident: 10.1038/gim.2012.164_bb0055 – ident: 10.1038/gim.2012.164_bb0030 – ident: 10.1038/gim.2012.164_bb0050 – ident: 10.1038/gim.2012.164_bb0070 – volume: 58 start-page: 1 year: 2009 ident: 10.1038/gim.2012.164_bb0095 article-title: Prevalence of autism spectrum disorders—Autism and Developmental Disabilities Monitoring Network, United States, 2006. 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| Snippet | Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance of... Purpose: Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the... Purpose:Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the penetrance... Purpose: Although an increasing number of copy-number variations are being identified as susceptibility loci for a variety of pediatric diseases, the... |
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| SubjectTerms | 631/208/726/649/2157 631/208/727/2000 692/699 692/700/1720 Algorithms Bayes Theorem Biomedical and Life Sciences Biomedicine Brief Report Case-Control Studies copy-number variation DNA Copy Number Variations Genetic counseling Genetic Loci Genetic Predisposition to Disease genomic disorder Genotype Human Genetics Humans Laboratory Medicine microarray Models, Genetic Penetrance prenatal diagnosis |
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| Title | Estimates of penetrance for recurrent pathogenic copy-number variations |
| URI | https://dx.doi.org/10.1038/gim.2012.164 https://link.springer.com/article/10.1038/gim.2012.164 https://www.ncbi.nlm.nih.gov/pubmed/23258348 https://www.proquest.com/docview/2887718560 https://www.proquest.com/docview/1365986032 https://www.proquest.com/docview/1547860056 https://pubmed.ncbi.nlm.nih.gov/PMC3664238 http://www.gimjournal.org/article/S1098360021027751/pdf |
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