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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: nambalavanan@peds.uab.edu

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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References

1. Payne, AR, Chang, SW, Koenig, SN, Zinn, AR, Garg, V. Submicroscopic chromosomal copy number variations identified in children with hypoplastic left heart syndrome. Pediatr Cardiol 2012; 33: 757763.Google Scholar
2. Osoegawa, K, Iovannisci, DM, Lin, B, et al. Identification of novel candidate gene loci and increased sex chromosome aneuploidy among infants with conotruncal heart defects. Am J Med Genet A 2014; 164A: 397406.Google Scholar
3. Reller, MD, Strickland, MJ, Riehle-Colarusso, T, Mahle, WT, Correa, A. Prevalence of congenital heart defects in metropolitan Atlanta, 1998–2005. J Pediatr 2008; 153: 807813.Google Scholar
4. Yang, Q, Chen, H, Correa, A, Devine, O, Mathews, TJ, Honein, MA. Racial differences in infant mortality attributable to birth defects in the United States, 1989–2002. Birth Defects Res A Clin Mol Teratol 2006; 76: 706713.Google Scholar
5. Bittel, DC, Butler, MG, Kibiryeva, N, et al. Gene expression in cardiac tissues from infants with idiopathic conotruncal defects. BMC Med Genomics 2011; 4: 1.Google Scholar
6. Erdogan, F, Larsen, LA, Zhang, L, et al. High frequency of submicroscopic genomic aberrations detected by tiling path array comparative genome hybridisation in patients with isolated congenital heart disease. J Med Genet 2008; 45: 704709.CrossRefGoogle ScholarPubMed
7. Richards, AA, Garg, V. Genetics of congenital heart disease. Curr Cardiol Rev 2010; 6: 9197.Google Scholar
8. Breckpot, J, Thienpont, B, Peeters, H, et al. Array comparative genomic hybridization as a diagnostic tool for syndromic heart defects. J Pediatr 2010; 156: 810817, 817.e1–817.e4.CrossRefGoogle ScholarPubMed
9. Menten, B, Maas, N, Thienpont, B, et al. Emerging patterns of cryptic chromosomal imbalance in patients with idiopathic mental retardation and multiple congenital anomalies: a new series of 140 patients and review of published reports. J Med Genet 2006; 43: 625633.Google Scholar
10. Reddy, UM, Page, GP, Saade, GR, et al. Karyotype versus microarray testing for genetic abnormalities after stillbirth. N Engl J Med 2012; 367: 21852193.Google Scholar
11. Bachman, KK, Deward, SJ, Chrysostomou, C, Munoz, R, Madan-Khetarpal, S. Array CGH as a first-tier test for neonates with congenital heart disease. Cardiol Young 2013; 18.Google Scholar
12. Warburton, D, Ronemus, M, Kline, J, et al. The contribution of de novo and rare inherited copy number changes to congenital heart disease in an unselected sample of children with conotruncal defects or hypoplastic left heart disease. Hum Genet 2014; 133: 1127.Google Scholar
13. Carey, AS, Liang, L, Edwards, J, et al. Effect of copy number variants on outcomes for infants with single ventricle heart defects. Circ Cardiovasc Genet 2013; 6: 444451.Google Scholar
14. Kearney, HM, Thorland, EC, Brown, KK, Quintero-Rivera, F, South, ST, Committee WGotACoMGLQA. American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants. Genet Med 2011; 13: 680685.Google Scholar
15. Stennard, FA, Harvey, RP. T-box transcription factors and their roles in regulatory hierarchies in the developing heart. Development 2005; 132: 48974910.CrossRefGoogle ScholarPubMed
16. Wang, E, Sun, S, Qiao, B, et al. Identification of functional mutations in GATA4 in patients with congenital heart disease. PLoS One 2013; 8: e62138.Google Scholar
17. Cowan, J, Tariq, M, Ware, SM. Genetic and functional analyses of ZIC3 variants in congenital heart disease. Hum Mutat 2014; 35: 6675.Google Scholar
18. McElhinney, DB, Geiger, E, Blinder, J, Benson, DW, Goldmuntz, E. NKX2.5 mutations in patients with congenital heart disease. J Am Coll Cardiol 2003; 42: 16501655.Google Scholar
19. Maitra, M, Koenig, SN, Srivastava, D, Garg, V. Identification of GATA6 sequence variants in patients with congenital heart defects. Pediatr Res 2010; 68: 281285.Google Scholar
20. Kosaki, K, Bassi, MT, Kosaki, R, et al. Characterization and mutation analysis of human LEFTY A and LEFTY B, homologues of murine genes implicated in left-right axis development. Am J Hum Genet 1999; 64: 712721.CrossRefGoogle ScholarPubMed
21. Ghosh, P, Bhaumik, P, Ghosh, S, et al. Polymorphic haplotypes of CRELD1 differentially predispose Down syndrome and euploids individuals to atrioventricular septal defect. Am J Med Genet A 2012; 158A: 28432848.Google Scholar
22. Mohapatra, B, Casey, B, Li, H, et al. Identification and functional characterization of NODAL rare variants in heterotaxy and isolated cardiovascular malformations. Hum Mol Genet 2009; 18: 861871.Google Scholar
23. Kirk, EP, Sunde, M, Costa, MW, et al. Mutations in cardiac T-box factor gene TBX20 are associated with diverse cardiac pathologies, including defects of septation and valvulogenesis and cardiomyopathy. Am J Hum Genet 2007; 81: 280291.Google Scholar
24. Miller, DT, Adam, MP, Aradhya, S, et al. Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet 2010; 86: 749764.Google Scholar
25. Kent, WJ, Sugnet, CW, Furey, TS, et al. The human genome browser at UCSC. Genome Res 2002; 12: 9961006.Google Scholar
26. Bandaru, V, Sunkara, S, Wallace, SS, Bond, JP. A novel human DNA glycosylase that removes oxidative DNA damage and is homologous to Escherichia coli endonuclease VIII. DNA Repair (Amst) 2002; 1: 517529.Google Scholar
27. Soemedi, R, Wilson, IJ, Bentham, J, et al. Contribution of global rare copy-number variants to the risk of sporadic congenital heart disease. Am J Hum Genet 2012; 91: 489501.Google Scholar
28. Greenway, SC, Pereira, AC, Lin, JC, et al. De novo copy number variants identify new genes and loci in isolated sporadic tetralogy of Fallot. Nat Genet 2009; 41: 931935.Google Scholar
29. Richards, AA, Santos, LJ, Nichols, HA, et al. Cryptic chromosomal abnormalities identified in children with congenital heart disease. Pediatr Res 2008; 64: 358363.Google Scholar
30. Thienpont, B, Mertens, L, de Ravel, T, et al. Submicroscopic chromosomal imbalances detected by array-CGH are a frequent cause of congenital heart defects in selected patients. Eur Heart J 2007; 28: 27782784.Google Scholar
31. Hitz, MP, Lemieux-Perreault, LP, Marshall, C, et al. Rare copy number variants contribute to congenital left-sided heart disease. PLoS Genet 2012; 8: e1002903.Google Scholar
32. Yang, Y, Muzny, DM, Reid, JG, et al. Clinical whole-exome sequencing for the diagnosis of Mendelian disorders. N Engl J Med 2013; 369: 15021511.CrossRefGoogle ScholarPubMed