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Array comparative genomic hybridisation testing in CHD

Published online by Cambridge University Press:  08 October 2014

Hannah B. Hightower
Affiliation:
Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
Nathaniel H. Robin
Affiliation:
Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
Fady M. Mikhail
Affiliation:
Department of Genetics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
Namasivayam Ambalavanan*
Affiliation:
Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
*
Correspondence to: N. Ambalavanan, MD, Women and Infants Center, University of Alabama at Birmingham, 176F Suite 9380, 619 South 19th Street, Birmingham, AL 35249-7335, United States of America. Tel: +205 934 4680; Fax: +205 934 3100; E-mail: [email protected]

Abstract

Background: CHD is the leading cause of mortality due to birth defects. Array comparative genomic hybridisation (aCGH) detects submicroscopic copy number changes and may improve identification of the genetic basis of CHD. Methods: This is a retrospective analysis of 1252 patients from a regional referral centre who had undergone aCGH. Of the patients, 173 had CHD. A whole-genome custom-designed oligonucleotide array with >44,000 probes was used to detect copy number changes. Results: Of the 1252 patients, 335 (26.76%) had abnormal aCGH results. Of the 173 patients with CHD, 50 (28.9%) had abnormal aCGH results versus 284 (26.3%) of 1079 non-cardiac patients. There were six patients with CHD who had well-described syndromes such as Wolf–Hirschhorn, trisomy 13, DiGeorge, and Williams. Of the patients with CHD, those with left-sided heart disease had the highest proportion (14/31; 45.13%) of abnormal aCGH results, followed by those with conotruncal heart disease (10/29; 34.48%), endocardial cushion defects (13/50; 26%), complex/other heart disease (12/52; 23.08%), and patent ductus arteriosus (1/11; 9.09%). Conclusions: Patients with CHD are at a substantial risk of having microdeletions and microduplications. The incidence of abnormalities on aCGH analysis is higher than identified with karyotype, and identification of copy number changes may help identify the genetic basis of the specific heart defects. However, aCGH may not have a significant diagnostic yield in those with isolated CHD. Further research using larger data sets may help identify candidate genes associated with CHD.

Type
Original Articles
Copyright
© Cambridge University Press 2014 

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