The prevalence of genetic diagnoses in fetuses with severe
congenital heart defects

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Abstract

Purpose

Congenital heart defects (CHD) are associated with genetic syndromes. Rapid aneuploidy testing and chromosome microarray analysis (CMA) are standard care in fetal CHD. Many genetic syndromes remain undetected with these tests. This cohort study aims to estimate the frequency of causal genetic variants, in particular structural chromosome abnormalities and sequence variants, in fetuses with severe CHD at mid-gestation, to aid prenatal counselling.

Methods

Fetuses with severe CHD were extracted from the PRECOR registry (2012–2016). We evaluated pre- and postnatal genetic testing results retrospectively to estimate the frequency of genetic diagnoses in general, as well as for specific CHDs.

Results

919 fetuses with severe CHD were identified. After exclusion of 211 cases with aneuploidy, a genetic diagnosis was found in 15.7% (111/708). These comprised copy number variants in 9.9% (70/708). In 4.5% (41/708) sequence variants were found that would have remained undetected with CMA. Interrupted aortic arch, pulmonary atresia with ventricular septal defect and atrioventricular septal defect were most commonly associated with a genetic diagnosis.

Conclusion

In case of normal CMA results, parents should be offered exome sequencing sequentially, if time allows for it, especially if the CHD is accompanied by other structural malformations due to the large variety in genetic syndromes.

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Most cited references 18

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The contribution of chromosomal abnormalities to congenital heart defects: a population-based study.

Mikyong Shin, Gregory S A Rasmussen, Adolfo Correa … (2011)

We aimed to assess the frequency of chromosomal abnormalities among infants with congenital heart defects (CHDs) in an analysis of population-based surveillance data. We reviewed data from the Metropolitan Atlanta Congenital Defects Program, a population-based birth-defects surveillance system, to assess the frequency of chromosomal abnormalities among live-born infants and fetal deaths with CHDs delivered from January 1, 1994, to December 31, 2005. Among 4430 infants with CHDs, 547 (12.3%) had a chromosomal abnormality. CHDs most likely to be associated with a chromosomal abnormality were interrupted aortic arch (type B and not otherwise specified; 69.2%), atrioventricular septal defect (67.2%), and double-outlet right ventricle (33.3%). The most common chromosomal abnormalities observed were trisomy 21 (52.8%), trisomy 18 (12.8%), 22q11.2 deletion (12.2%), and trisomy 13 (5.7%). In conclusion, in our study, approximately 1 in 8 infants with a CHD had a chromosomal abnormality. Clinicians should have a low threshold at which to obtain testing for chromosomal abnormalities in infants with CHDs, especially those with certain types of CHDs. Use of new technologies that have become recently available (e.g., chromosomal microarray) may increase the identified contribution of chromosomal abnormalities even further.

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Additional value of prenatal genomic array testing in fetuses with isolated structural ultrasound abnormalities and a normal karyotype: a systematic review of the literature.

M C de Wit, M I Srebniak, L C P Govaerts … (2014)

To establish the prevalence of submicroscopic genetic copy number variants (CNVs) in fetuses with a structural ultrasound anomaly (restricted to one anatomical system) and a normal karyotype. The aim was to determine the diagnostic and prognostic value of genomic array testing in these pregnancies.

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The Congenital Heart Disease Genetic Network Study: Cohort description

Thanh Hoang, Elizabeth Goldmuntz, Amy E Roberts … (2018)

The Pediatric Cardiac Genomics Consortium (PCGC) designed the Congenital Heart Disease Genetic Network Study to provide phenotype and genotype data for a large congenital heart defects (CHDs) cohort. This article describes the PCGC cohort, overall and by major types of CHDs (e.g., conotruncal defects) and subtypes of conotrucal heart defects (e.g., tetralogy of Fallot) and left ventricular outflow tract obstructions (e.g., hypoplastic left heart syndrome). Cases with CHDs were recruited through ten sites, 2010–2014. Information on cases (N = 9,727) and their parents was collected through interviews and medical record abstraction. Four case characteristics, eleven parental characteristics, and thirteen parent-reported neurodevelopment outcomes were summarized using counts and frequencies and compared across CHD types and subtypes. Eleven percent of cases had a genetic diagnosis. Among cases without a genetic diagnosis, the majority had conotruncal heart defects (40%) or left ventricular outflow tract obstruction (21%). Across CHD types, there were significant differences (p<0.05) in the distribution of all four case characteristics (e.g., sex), four parental characteristics (e.g., maternal pregestational diabetes), and five neurodevelopmental outcomes (e.g., learning disabilities). Several characteristics (e.g., sex) were also significantly different across CHD subtypes. The PCGC cohort is one of the largest CHD cohorts available for the study of genetic determinants of risk and outcomes. The majority of cases do not have a genetic diagnosis. This description of the PCGC cohort, including differences across CHD types and subtypes, provides a reference work for investigators who are interested in collaborating with or using publically available resources from the PCGC.

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Author and article information

Contributors

Amber E. L. van Nisselrooij:

ORCID: http://orcid.org/0000-0003-1752-5834

a.e.l.nisselrooij@lumc.nl

Journal

Journal ID (nlm-ta): Genet Med

Journal ID (iso-abbrev): Genet. Med

Title: Genetics in Medicine

Publisher: Nature Publishing Group US (New York )

ISSN (Print): 1098-3600

ISSN (Electronic): 1530-0366

Publication date (Electronic): 28 April 2020

Publication date PMC-release: 28 April 2020

Publication date (Print): 2020

Volume: 22

Issue: 7

Pages: 1206-1214

Affiliations

[1 ]ISNI 0000000089452978, GRID grid.10419.3d, Department of Obstetrics and Fetal Medicine, , Leiden University Medical Center, ; Leiden, Netherlands

[2 ]ISNI 0000000084992262, GRID grid.7177.6, Amsterdam UMC, University of Amsterdam, Obstetrics, Amsterdam Reproduction and Development Research Institute, ; Amsterdam, Netherlands

[3 ]ISNI 0000000404654431, GRID grid.5650.6, Department of Paediatric Cardiology, , Emma Children’s Hospital, Academic Medical Center, Amsterdam UMC, ; Amsterdam, Netherlands

[4 ]ISNI 0000000089452978, GRID grid.10419.3d, Department of Paediatric Cardiology, , Leiden University Medical Center, ; Leiden, Netherlands

[5 ]ISNI 0000000084992262, GRID grid.7177.6, Department of Clinical Genetics, Amsterdam UMC, , University of Amsterdam, ; Amsterdam, Netherlands

[6 ]ISNI 0000000089452978, GRID grid.10419.3d, Department of Clinical Genetics, , Leiden University Medical Center, ; Leiden, Netherlands

Author information

Amber E. L. van Nisselrooij http://orcid.org/0000-0003-1752-5834

Article

Publisher ID: 791

DOI: 10.1038/s41436-020-0791-8

PMC ID: 7332415

PubMed ID: 32341573

SO-VID: 3c5bb728-3a3e-4cf5-980a-16014ecf756f

License:

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, and provide a link to the Creative Commons license. You do not have permission under this license to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

History

Date received : 7 November 2019

Date revision received : 19 March 2020

Date accepted : 20 March 2020

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: genetic syndrome,congenital heart defects,prenatal counseling,chromosome microarray analysis,exome sequencing

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ScienceOpen disciplines: Genetics

Keywords: genetic syndrome, congenital heart defects, prenatal counseling, chromosome microarray analysis, exome sequencing

The prevalence of genetic diagnoses in fetuses with severe congenital heart defects

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Abstract

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Genome Integrity

Most cited references 18

The contribution of chromosomal abnormalities to congenital heart defects: a population-based study.

Additional value of prenatal genomic array testing in fetuses with isolated structural ultrasound abnormalities and a normal karyotype: a systematic review of the literature.

The Congenital Heart Disease Genetic Network Study: Cohort description

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