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Chromosomal microarray analysis in the investigation of prenatally diagnosed congenital heart disease
Journal Pre-proof Chromosomal Microarray Analysis in the Investigation of Prenatally Diagnosed Congenital Heart Disease Hiba J. Mustafa, MD, Katherine M. Jacobs, MD, Katelyn M. Tessier, MS, Shanti L. Narasimhan, MD, Alena N. Tofte, Allison R. Mccarter, Sarah N. CROSS, MD PII:
S2589-9333(19)30118-1
DOI:
https://doi.org/10.1016/j.ajogmf.2019.100078
Reference:
AJOGMF 100078
To appear in:
American Journal of Obstetrics & Gynecology MFM
Received Date: 29 August 2019 Revised Date:
4 December 2019
Accepted Date: 16 December 2019
Please cite this article as: Mustafa HJ, Jacobs KM, Tessier KM, Narasimhan SL, Tofte AN, Mccarter AR, CROSS SN, Chromosomal Microarray Analysis in the Investigation of Prenatally Diagnosed Congenital Heart Disease, American Journal of Obstetrics & Gynecology MFM (2020), doi: https://doi.org/10.1016/ j.ajogmf.2019.100078. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Published by Elsevier Inc.
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TITLE PAGE
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Chromosomal Microarray Analysis in the Investigation of Prenatally Diagnosed
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Congenital Heart Disease
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Corresponding author: Hiba J. MUSTAFA, MD
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Fellow, Department of Obstetrics, Gynecology & Women’s Health, University of
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Minnesota, [email protected], (832) 475-4061
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Co-authors:
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1. Katherine M. JACOBS, MD Assistant Professor, Department of Obstetrics, Gynecology & Women’s Health, University of Minnesota 2. Katelyn M. TESSIER, MS Research Fellow, Biostatistics Core, Masonic Cancer Center, University of Minnesota 3. Shanti L. NARASIMHAN, MD Associate Professor, Department of Pediatric Cardiology, University of Minnesota 4. Alena N. TOFTE Medical Student, University of Minnesota 5. Allison R. MCCARTER Medical Student, University of Minnesota 6. Sarah N. CROSS, MD
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Assistant Professor, Department of Obstetrics, Gynecology & Women’s Health,
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University of Minnesota
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Conflicts of interest: The authors report no conflict of interests.
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Presentation: The study received an invitation for oral presentation at the 39th annual
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Society of Maternal Fetal Medicine Pregnancy Meeting 2019, Las Vegas, NV
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Word count: Abstract: 313 words, main text: 2384 words
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Chromosomal Microarray Analysis in the Investigation of Prenatally Diagnosed
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Congenital Heart Disease
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CONDENSATION AND SHORT VERSION OF TITLE
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Condensation: Chromosomal microarray is a reliable, high yield diagnostic test in
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prenatal congenital heart disease.
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Short title: Chromosomal microarray in fetuses with congenital heart disease
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AJOG AT A GLANCE
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Why was this study conducted: To investigate the diagnostic yield of chromosomal
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microarray analysis in prenatally diagnosed congenital heart disease.
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Key findings: In the context of prenatal diagnostic testing for fetal CHD, chromosomal
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microarray analysis identified additional, clinically significant cytogenic information
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compared to conventional karyotyping.
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What does this add to what is known: Improved prenatal counseling of genetic
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association with congenital heart disease, especially when combined with extracardiac
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anomalies.
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Keywords: Congenital heart disease, chromosomal abnormalities, copy number
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variants, microarray, pregnancy, translocation
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ABSTRACT
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Objective: Chromosomal microarray analysis has emerged as a primary diagnostic tool
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in prenatally diagnosed congenital heart disease and other structural anomalies in
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clinical practice. Our study aimed to investigate the diagnostic yield of microarray
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analysis as a first tier test for chromosomal abnormalities in fetuses with both isolated
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and non-isolated congenital heart disease and to identify the association of different
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pathogenic chromosomal abnormalities with different subgroups of congenital heart
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disease.
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Design: Retrospective data from 217 pregnancies diagnosed with congenital heart
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disease between 2011 and 2016 were reviewed. All pregnancies were investigated
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using microarray analysis during the study period. Classification of chromosomal
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abnormalities was done based on American College of Medical Genetics and Genomics
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guidelines into 1) pathogenic chromosomal abnormalities including numerical
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chromosomal abnormalities (aneuploidy and partial aneuploidy), and pathogenic copy
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number variants (22q11.2 deletion and other microdeletions/microduplications), 2)
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variants of uncertain significance, and 3) normal findings.
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Results: Our study found a detection rate for pathogenic chromosomal abnormalities
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(numerical and pathogenic copy number variants) of 36.9% (n=80) in pregnancies
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prenatally diagnosed with congenital heart disease who underwent invasive testing with
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chromosomal microarray. Detection rate for numerical abnormalities was 29.5% (n=64)
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and for pathogenic copy number variants was 7.4% (n=16) of which 4.2% were 22q11.2
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deletion and 3.2% were other pathogenic CNVs, most of which theoretically could have
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been missed by utilizing conventional karyotype alone. Pathogenic CNVs were most
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common in conotruncal defects (19.6%, 11/56) including 42.9% in cases of IAA, 23.8%
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in cases of TOF, 13.3% in cases of d-TGA, and 8.3% in cases of DORV. Of these
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changes, 81.8% were 22q11.2 deletion and 18.2% were other
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microdeletions/microduplications. Following conotruncal defects, pathogenic CNVs were
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most common in RVOT and LVOT groups (8% and 2.2%, respectively) in which none
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were 22q11.2 deletion. Pathogenic chromosomal abnormalities (numerical and
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pathogenic CNVs) detected by CMA were significantly more common in the non-
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isolated congenital heart disease group (64.5%, n=49) compared to the isolated group
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(22%, n=31) (P<0.001).
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Conclusion: In pregnancies diagnosed with congenital heart disease and undergoing
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diagnostic genetic testing, our study showed that chromosomal microarray analysis has
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an added value in the detection of pathogenic chromosomal abnormalities compared to
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conventional karyotype, particularly in cases of pathogenic copy number variants. This
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yield is influenced not only by the type of congenital heart disease, but also by the
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presence of extracardiac anomalies.
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MAIN TEXT
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Introduction: Congenital heart disease (CHD) is a structural abnormality of the heart
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and great vessels that is present at birth. 1 It is the most common type of birth defects
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occurring in about 4-13 per 1000 live births and in 10% of still births. 2-4 The underlying
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causes of CHD are multifactorial, although it has long been thought to have both genetic
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and environmental contributions. 5-8 G-banded karyotype coupled with fluorescence in
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situ hybridization (FISH) has been the predominant strategy applied for detecting
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chromosomal abnormalities in fetuses with CHD in clinical practice. However, G-banded
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karyotype is time-consuming, limited by low-resolution (400-500 bands), and can
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identify chromosomal aberrations > 5-10 Mb, while FISH is hampered by limited
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coverage on the whole genome. 9 Chromosomal microarray analysis (CMA) can be
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used to perform karyotyping via array comparative genomic hybridization (array CGH)
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or single-nucleotide polymorphism (SNP). 10 CMA improves resolution over
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conventional G-banded karyotype in detecting chromosomal abnormalities. 11 Recent
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studies investigating prenatal cases of CHD by CMA have shown a detection rate for
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pathogenic chromosomal abnormalities that ranged from 10.9 to 35.5%, and a detection
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rate of 6.6 to 12% for pathogenic copy number variants. 12-15 The potential advantages
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of CMA over conventional karyotyping in prenatal diagnosis include higher resolution,
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avoidance of culturing amniocytes or chorionic villi, automation, and faster turnaround
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times. In addition, since it does not require dividing cells, it is useful in cases of fetal
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demise. 16-18 In 2016, the American College of Obstetricians and Gynecologists
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recommended CMA for patients with a fetus with one or more major structural
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abnormalities identified on ultrasound examination who is undergoing invasive prenatal
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diagnosis. 19 Based on that recommendation, we aimed to investigate the diagnostic
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yield of CMA in prenatal detection of chromosomal abnormalities in fetal CHD, both in
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isolated and non-isolated types.
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Materials and Methods:
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This was a retrospective cohort study at a single tertiary care center. All the
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pregnancies with CHD that underwent invasive diagnostic testing between 2011 and
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2016 were included in our study. A total of 336 fetuses diagnosed with CHD were
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identified through the fetal ECHO database during that time period of which 217
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pregnancies underwent invasive diagnostic testing via amniocentesis following the
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identification of prenatal CHDs on ultrasound. Details of maternal characteristics,
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obstetrical outcomes, as well as delivery and postnatal outcomes up to 2 years of age
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were obtained for those 217 pregnancies. Prenatal invasive diagnostic testing was done
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via amniocentesis between 18 and 23 weeks gestation. SNP microarray was used in all
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the diagnostic cases in our study.
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Our collected data included all pregnancy outcomes, whether had livebirth, fetal demise,
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underwent termination, or decided to have comfort care. The CHD cohort was classified
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using a method described by Botto et al. 20 into nine groups which consisted of: septal
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defects including atrial septal defects (ASD) and ventricular septal defects (VSD);
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conotruncal defects including truncus arteriosus, interrupted aortic arch (IAA),
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transposition of the great arteries (d-TGA), double outlet right ventricle (DORV), and
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tetralogy of fallot (TOF); left ventricular outflow tract (LVOT) defects including
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hypoplastic left heart syndrome (HLHS), coarctation of aorta (CoA), and aortic stenosis;
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right ventricular outflow tract (RVOT) including pulmonary stenosis, pulmonary atresia,
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tricuspid atresia, and Ebstein’s anomaly; atrioventricular septal defects (AVSD);
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heterotaxy; total anomalous pulmonary venous return (TAPVR); double inlet left
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ventricle (DILV) or complex heart defect; and cardiac tumor.
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The total number of CHD cases were then divided into two groups: isolated CHD which
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included pregnancies with no extracardiac defects and non-isolated CHD which
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included pregnancies with single or multiple extracardiac structural defects.
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Extracardiac structural defects were divided into eight groups which consisted of:
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central nervous system (CNS); face; neck; chest; genitourinary (GU); gastrointestinal
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(GI); abdominal wall; and skeletal. According to the American College of Medical
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Genetics and Genomics, chromosomal microarray analysis results are classified into
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numerical chromosome abnormalities and copy number variants (CNV). 21 Numerical
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abnormalities include aneuploidy and partial aneuploidy. CNVs are divided into:
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pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, and
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benign. For the purposes of this study, our microarray analysis results were classified
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into three groups: 1) pathogenic abnormalities including: numerical abnormalities
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include aneuploidy and partial aneuploidy, and these were assumed to be detectable by
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karyotype, and pathogenic CNVs (22q11.2 deletion, and others); 2) VUS, and 3) normal
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results which included likely benign results as well. Detected CNVs were evaluated
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based on a scientific literature review and the following public databases: The Centre for
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Applied Genomics (TCAG) Database of Genomic Variants
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(http://projects.tcag.ca/variation/), University of California Santa Cruz (UCSC) Genome
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Browser: (http://genome.ucsc.edu/), National Center of Biotechnology Information
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(NCBI) Database of Genomic Structural Variation: (http://www.ncbi.nlm.nih.gov/dbvar/).
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For our analysis, variables of interest were summarized using counts and frequencies
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for categorical variables and mean and standard deviation or median and range for
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continuous variables by chromosomal abnormalities. To investigate the association
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between variables of interest and chromosomal abnormalities, Chi-square tests or
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Fisher’s exact tests were used for categorical variables, when appropriate, and
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Student’s t-tests or Wilcoxon rank-sum tests for continuous variables, when appropriate.
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Structural extra cardiac anomalies were summarized using counts and frequencies for
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everyone tested, those with total pathogenic chromosomal abnormalities, and those
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with numerical abnormalities and with pathogenic CNVs. Additionally, total pathogenic
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chromosomal abnormalities were compared for those with isolated and non-isolated
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CHD. All reported p-values are two-sided, and a level of 0.05 was considered
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statistically significant. All statistical analyses were performed in R (v 3.4.2).
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Results:
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Of the 336 pregnancies diagnosed with CHD, a total of 217 underwent invasive
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diagnostic testing. Subjects’ characteristics and pregnancy outcomes are shown in
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Table 1. Microarray analysis results (Figure 1) were normal in 55.7% (n=121), VUS in
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7.4% (n=16), and pathogenic abnormalities in 36.9% (n=80).
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Pathogenic abnormalities included numerical abnormalities in 29.5% (n=64) and
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pathogenic CNVs in 7.4% (n=16) (Figure 1). Detected aneuploidy consisted of trisomy
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21 (n=28), trisomy 18 (n=12), trisomy 13 (n=6), monosomy X (n=5), and 13 other
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aneuploidies (Figure 1). Pathogenic CNVs consisted of 4.2% (n=9) 22q11.2 deletion
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and 3.2% (n=7) were other microdeletions/microduplications. CHD was initially divided
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into isolated and non-isolated CHD (i.e. pregnancies with extracardiac anomalies),
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where 65% had isolated CHD and 35% had non-isolated. CMA detection rate for
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pathogenic abnormalities was 22% (31/141) in the isolated CHD group compared to
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64.5% (49/76) in the non-isolated CHD group (P< 0.001, Table 2). Numerical
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abnormalities were noted in 23 fetuses (16.3%) in the isolated group compared to 41
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fetuses (53.9%) in the non-isolated group (P<0.001, Table 2).
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The detection rate for pathogenic CNVs in the isolated CHD group was 5.7%, 8/141
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(87.5% were 22q11.2 deletion and 12.5% were other microdeletions/microduplications),
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and 10.5%, 8/76 in the non-isolated CHD group (50% were 22q11.2 deletion, and 50%
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were other deletions/duplications). The difference in the pathogenic CNVs detection rate
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was not statistically significant between both groups (Table 2).
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CHD was then divided into nine groups as explained in the methods section. These
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groups were: conotruncal defects (25.8%), LVOT (20.7%), septal defects (18%), AVSD
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(16.6%), RVOT (11.5%), heterotaxy and DILV (each were 2.8%), followed by TAPVR
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and cardiac tumors (each were 0.9%) (Table 3). CHD types in pregnancies that did not
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undergo diagnostic genetic testing can be seen in supplemental Figure 1.
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Table 3 shows the detection rate of various chromosomal abnormalities in each of those
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nine groups. Total pathogenic chromosomal abnormalities detection rate was highest in
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AVSD (66.7%), followed by conotruncal (39.3%), RVOT and LVOT (24%, and 20%
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respectively). Pathogenic CNVs were most common in conotruncal defects (19.6%,
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11/56) including 42.9% in cases of IAA, 23.8% in cases of TOF, 13.3% in cases of d-
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TGA, and 8.3% in cases of DORV. Of these changes, 81.8% were 22q11.2 deletion and
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18.2% were other microdeletions/microduplications. Following conotruncal defects,
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pathogenic CNVs were most common in RVOT and LVOT groups (8% and 2.2%,
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respectively) in which none were 22q11.2 deletion (Table 3). We emphasize in our
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results on the detection rate for pathogenic CNVs as it is the number that theoretically
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could have been missed by conventional karyotype. 8-11, 22 No pathogenic CNVs were
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detected in the AVSD group as all cases were noted to be aneuploidy, and none were
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also detected in the last four CHD groups (heterotaxy, DILV, TAPVR, and cardiac
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tumors), however these groups had considerable small sample size (Table 3). For
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detailed detection rate for each of the nine groups based on presence and absence of
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extracardiac anomalies please see supplementary material (Supplemental Table 1). We
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also investigated CMA yield in CHD cases with extracardiac anomalies (Table 4). In our
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cohort, 43 (19.8%) pregnancies had single extracardiac anomaly, and 33 (15.2%) had
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multiple anomalies. Pathogenic changes were most commonly associated with face
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anomalies (20.9%, 9/43), followed by gastrointestinal (11.6%, 5/43), and skeletal
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anomalies (9.3%, 4/43). Similar rates of pathogenic changes were seen between
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pregnancies with single extracardiac anomaly and those with multiple ones (66.7% and
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62.8%, respectively).
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Obstetrical outcomes for the whole cohort and postnatal outcomes for the livebirths
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(78.8%, n=171) were obtained (Supplemental Table 2). Postnatal confirmation data of
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the prenatally diagnosed CHDs and extracardiac anomalies were collected. There were
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no critical CHDs missed on prenatal imaging. Extracardiac anomalies undiagnosed on
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prenatal imaging comprised of 4% (n=9) of cases. Outcome data were compared
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between pregnancies that had pathogenic chromosomal abnormalities and those that
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did not. The pathogenic changes group was more significantly associated with
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polyhydramnios (P=0.03), single/multiple structural extracardiac anomalies (P<0.001),
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and with gestational age at delivery of less than 37 weeks (P=0.01) while there were no
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significant differences in the postnatal outcomes between groups (Supplemental Table
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2). Details on pathogenic CNVs and VUS can be found in supplemental material
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(Supplemental Table 3).
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Comment:
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Principle findings: We performed a retrospective study on a large cohort to assess the
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diagnostic yield of SNP array for identifying chromosomal abnormalities in fetuses with
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CHD in clinical practice. Based on the results, we described the frequency and
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distribution of chromosomal abnormalities for different types of CHDs and compared the
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frequency of chromosomal abnormalities between fetuses with isolated CHD and non-
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isolated CHD. We report a detection rate of 36.9% for pathogenic chromosomal
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abnormalities (numerical and pathogenic CNVs). Our study shows an added detection
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rate for CMA over karyotype of 7.4% for pathogenic copy number variants in fetuses
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with CHD (4.2% for 22q11.2 deletion and 3.2% for other pathogenic CNVs) (Figure 1).
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In 22q11.2 deletion syndrome, conotruncal cardiac defects occur in almost 80% of
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patients with the most common are IAA, truncus arteriosus, and TOF.42-44 Although
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traditionally FISH has been used for prenatal 22q11.2 deletion syndrome testing,
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atypical and small deletions can still be missed in 5-15% of cases. 35,36 Hence,
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according to our study results FISH alone could have presumably missed more than
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50% of pathogenic CNVs. After dividing the cohort into isolated and non-isolated CHD,
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the detection rate for pathogenic copy number variants in the setting of isolated cardiac
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anomalies was 5.7%, and in the setting of non-isolated cardiac anomalies was 10.5%
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(Table 2). Pathogenic CNVs were most common in the conotruncal defects group with
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incremental yield of 19.6%. Given that conventional karyotype can reliably detect
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chromosomal abnormalities of >10 Mb, 23 then the theoretical incremental yield of
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pathogenic CNVs <10 Mb in our study would be 7.4% which was identical to VUS
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detection rate in our study. VUS detection rate in fetuses without anomalies has been
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reported to range between 0.9- 2.5%, 9,29 while in fetuses with structural anomalies
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including CDH this rate is higher (7.4% in our study). Patients should be educated and
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counseled about the chances of VUS detection, and the complexities associated with
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interpreting the results when offering CMA testing.
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Clinical implications: It is important to obtain the most accurate and detailed genetic
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information in the prenatal setting for both patients and care providers given the
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implications it can have on both prenatal and immediate postnatal management and
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prognosis, for which several recent studies have investigated prenatal cases of CHD by
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CMA using different array types. 12-15 Our results are in agreement with those previous
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reports that showed a detection rate for pathogenic chromosomal abnormalities ranging
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from 10.9% to 35.5%, 25-28 and for pathogenic CNVs ranging from 6.6% to 12%. 12-15
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Compared to the study by Shafer et al, 29 the incremental yield in cases of Tetralogy of
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Fallot in our study was higher (23.8% versus 13.3%), while the incidence in cases of
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HLHS and VSD were lower in our study. The reasons for this discordance could be that
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the sample sizes and the proportion of isolated CHD were different between the two
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studies. Furthermore, of the 45 cases of LVOT defects, 20% had pathogenic
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chromosomal abnormalities compared to the detection rate of 13.3% in other studies. 12
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Our study had two cases of fetal cardiac tumors in which one of them the mother had a
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personal history of tuberous sclerosis (TS). The newborn was confirmed to have both
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clinical and genetic criteria for TS. Primary cardiac tumors are rare, with prevalence of
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0.25% in infants and children.37,38 The vast majority of primary cardiac tumors are
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benign, with the most common being rhabdomyoma. Cardiac rhabdomyoma may be the
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initial manifestation of TS.39,40 TS is an autosomal dominant condition for which prenatal
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genetic testing can be offered along to the CMA, however, prenatal genetic testing for
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TS was not performed in both cases in our study. It has been reported that the
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incidence of chromosomal abnormalities will be higher when CHD is accompanied with
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additional structural anomalies, 14,29,30 which was also observed in our study. Cases of
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CHD combined with facial malformation resulted in a high incidence of chromosomal
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abnormalities when compared with CHD plus other types of structural anomalies.
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Although the diagnostic utility of CMA is greater than karyotype, the cost of CMA is
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substantially more. However, in multiple cost effective analysis studies, CMA alone
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appeared to be the preferred strategy for sonographically-detected anomalies, although
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karyotype alone and CMA following a normal karyotype are also acceptable strategies.
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If a structural abnormality is strongly suggestive of a particular aneuploidy in the fetus
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(eg, atrioventricular heart defect, which is characteristic of trisomy 21), karyotype with
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reflex to microarray analysis may be offered.41 Performing both karyotype and CMA
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simultaneously did not appear to improve diagnosis and has been shown in prior reports
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to be associated with higher costs. 31–34.
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Strengths and weaknesses: Strengths of our study include: large sample size of our
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cohort which enabled us to obtain the CMA yield for different types of CHDs and to
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investigate the possible differences between the groups of fetuses with isolated and
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non-isolated CHD which can improve prenatal counseling when offering invasive
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diagnostic testing. Ultrasound imaging and laboratory testing were done at one site
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which provide consistency among the definition of particular ultrasound anomalies and
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genetic abnormalities. Postnatal confirmation for prenatally detected ultrasound
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anomalies was obtained in our study.
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We acknowledge the limitations to our study including the retrospective, single center
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design. Although the sample size was large, the distribution of different types of CHDs
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varied greatly. It is in our practice to offer parental genetic testing for detected CNVs.
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However, information regarding parental testing was not collected in our study.
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Conclusion with future research implications: This study aimed to understand the
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specific detection rates for chromosome aberrations after microarray analysis for
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fetuses with different types of CHD.
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We have demonstrated a significantly increased detection of pathogenic chromosomal
283
abnormalities after applying microarray analysis in all indications for prenatal testing for
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CHD, particularly in cases of pathogenic CNVs. This is especially true in situations
285
when an ultrasound examination reveals extracardiac fetal anomalies. Our detection
286
rate for pathogenic CNVs was 7.4%, a theoretical incremental yield over testing with
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standard karyotype. Our study supports the opinion of the American College of
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Obstetrics and Gynecology to endorse the use of microarray testing in the presence of
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fetal anatomic anomalies. 19
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ACKNOWLEDGMENT: Research reported in this publication was supported by NIH
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grant P30 CA77598 utilizing the Biostatistics and Bioinformatics Core shared resource
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of the Masonic Cancer Center, University of Minnesota and by the National Center for
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Advancing Translational Sciences of the National Institutes of Health Award Number
295
UL1TR002494. The content is solely the responsibility of the authors and does not
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necessarily represent the official views of the National Institutes of Health.
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Bergström, S. et al. Trends in Congenital Heart Defects in Infants With Down
Syndrome. Pediatrics 138, e20160123 (2016). 19.
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(Accessed: 3rd November 2018)
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20.
Botto, L. D. et al. Seeking causes: Classifying and evaluating congenital heart
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defects in etiologic studies. Birth Defects Research Part A: Clinical and Molecular
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Teratology 79, 714–727 (2007).
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21.
Richards, S. et al. Standards and Guidelines for the Interpretation of Sequence
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Variants: A Joint Consensus Recommendation of the American College of Medical
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Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17,
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405–424 (2015).
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22. Fiorentino, F. et al. Introducing array comparative genomic hybridization into routine
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prenatal diagnosis practice: a prospective study on over 1000 consecutive clinical
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cases: INTRODUCING ARRAY-CGH INTO ROUTINE PRENATAL DIAGNOSIS
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PRACTICE. Prenat. Diagn. 31, 1270–1282 (2011).
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23. Di Gregorio, E. et al. Large cryptic genomic rearrangements with apparently normal karyotypes detected by array-CGH. Mol. Cytogenet. 7, 82 (2014). 24.
Zyblewski, S. C. et al. Chromosomal Anomalies Influence Parental Treatment
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Decisions in Relation to Prenatally Diagnosed Congenital Heart Disease. Pediatr.
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Cardiol. 30, 1105–1111 (2009).
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25.
Mone, F. et al. Prenatal detection of structural cardiac defects and presence of
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associated anomalies: a retrospective observational study of 1262 fetal
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echocardiograms. Prenatal Diagnosis 35, 577–582 (2015).
365
26.
Glessner, J. T. et al. Increased Frequency of De Novo Copy Number Variants in
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Congenital Heart Disease by Integrative Analysis of Single Nucleotide Polymorphism
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Array and Exome Sequence Data. Circulation Research 115, 884–896 (2014).
368 369 370
27.
Breckpot, J. et al. Array Comparative Genomic Hybridization as a Diagnostic
Tool for Syndromic Heart Defects. The Journal of Pediatrics 156, 810-817.e4 (2010). 28.
Microdeletions and Microduplications in Patients with Congenital Heart Disease
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and Multiple Congenital Anomalies - Goldmuntz - 2011 - Congenital Heart Disease -
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Wiley Online Library. Available at: https://onlinelibrary-wiley-
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com.ezp3.lib.umn.edu/doi/full/10.1111/j.1747-0803.2011.00582.x. (Accessed: 3rd
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November 2018)
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29.
Shaffer, L. G. et al. Detection rates of clinically significant genomic alterations by
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microarray analysis for specific anomalies detected by ultrasound: Microarray
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experience with abnormal ultrasound anomalies. Prenatal Diagnosis 32, 986–995
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(2012).
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30.
Donnelly, J. C. et al. Association of Copy Number Variants With Specific
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Ultrasonographically Detected Fetal Anomalies: Obstetrics & Gynecology 124, 83–90
381
(2014).
382 383 384
31.
Harper, L. M., Sutton, A. L. M., Longman, R. E. & Odibo, A. O. An Economic Analysis of Prenatal Cytogenetic Technologies for Sonographically-Detected Fetal Anomalies. Am. J. Med. Genet. A. 0, 1192–1197 (2014).
385 386 387
32. Geddes, G. C., Basel, D., Frommelt, P., Kinney, A. & Earing, M. Genetic Testing Protocol Reduces Costs and Increases Rate of Genetic Diagnosis in Infants with Congenital Heart Disease. Pediatr. Cardiol. 38, 1465–1470 (2017).
388 389
33. Dugoff, L., Norton, M. E. & Kuller, J. A. The use of chromosomal microarray for prenatal diagnosis. Am. J. Obstet. Gynecol. 215, B2–B9 (2016).
390 391
34. Armengol, L. et al. Clinical utility of chromosomal microarray analysis in invasive prenatal diagnosis. Hum. Genet. 131, 513–523 (2012).
392 393
35. Driscoll, D. A. Prenatal diagnosis of the 22q11.2 deletion syndrome. Genetics IN Medicine 3,
5 (2001).
394 395 396
36. Geddes, G. C., Basel, D., Frommelt, P., Kinney, A. & Earing, M. Genetic Testing Protocol Reduces Costs and Increases Rate of Genetic Diagnosis in Infants with Congenital Heart Disease. Pediatr Cardiol 38, 1465–1470 (2017).
397 398
37. Yuan, S.-M. Fetal Primary Cardiac Tumors During Perinatal Period. Pediatr Neonatol 58, 205–210 (2017).
399 400
38. Isaacs, H. Fetal and neonatal cardiac tumors. Pediatr Cardiol 25, 252–273 (2004).
401 402 403
39. Gupta, N., Singh, N., Sarangi, S., Dalmia, S. & Mittal, S. Fetal cardiac rhabdomyoma with maternal tuberous sclerosis complicating pregnancy. Arch. Gynecol. Obstet. 278, 169–170 (2008).
404 405
40. Jóźwiak, S. & Kotulska, K. Are all prenatally diagnosed multiple cardiac rhabdomyomas a sign of tuberous sclerosis? Prenat. Diagn. 26, 867–869 (2006).
406 407
41. Practice Bulletin No. 162 Summary: Prenatal Diagnostic Testing for Genetic Disorders. Obstet Gynecol 127, 976–978 (2016).
408 409 410 411
42. Goldmuntz, E. et al. Evaluation of potential modifiers of the cardiac phenotype in the 22q11.2 deletion syndrome. Birth Defects Res. Part A Clin. Mol. Teratol. 85, 125– 129 (2009).
19 | Page 412 413 414
43. McDonald-McGinn, D. M. & Sullivan, K. E. Chromosome 22q11.2 deletion syndrome (DiGeorge syndrome/velocardiofacial syndrome). Medicine (Baltimore) 90, 1– 18 (2011).
415 416 417
44. Ryan, A. K. et al. Spectrum of clinical features associated with interstitial chromosome 22q11 deletions: a European collaborative study. J. Med. Genet. 34, 798– 804 (1997).
418 419 420 421 422 423
20 | Page 424
TABLES
425
Table 1. Summary of subject characteristics. (N=217) Age
< 35 years
158 (72.8)
≥ 35 years Ethnicity, n (%)
Insurance, n (%)
BMI (kg/cm2 ), n (%)
Parity, n (%)
59 (27.2)
White
166 (78.7)
Black
23 (10.9)
Latina
12 (5.7)
Asian
10 (4.7)
Medicaid
36 (45)
Private
44 (55)
Underweight
2 (3.6)
Normal
24 (43.6)
Overweight
13 (23.6)
Obese
16 (29.1)
Nulliparous
27 (33.8)
Multiparous
53 (66.2)
GA at initial diagnosis of cardiac anomaly Mean (SD)
22 (1.8)
Median (range)
20 (18, 23)
Pregnancy outcomes, n (%) Live birth
171 (78.8)
Fetal demise
17 (7.8)
Termination
20 (9.2)
Comfort care
5 (2.3)
Delivered at external institution
4 (1.8)
426 427 428
Table 2. Comparison of types of chromosomal abnormalities for those with and without structural extra cardiac anomalies. Isolated CHD P Value1 Non-isolated CHD (N=76) (N=141) Total pathogenic abnormalities, n (%)
49 (64.5)
31 (22.0)
<0.001
21 | Page Numerical abnormalities, n (%)
41 (53.9)
23 (16.3)
T21
12 (29.2)
16 (69.5)
T18
12 (29.2)
0 (0.0)
T13
6 (14.6)
0 (0.0)
45X
3 (7.3)
2 (8.6)
Other
8 (19.5)
5 (21.7)
8 (10.5)
8 (5.7)
22q11.2 deletion
4 (50.0)
5 (87.5)
Other
4 (50.0)
3 (12.5)
Pathogenic CNV, n (%)
429 430 431
1
432
Table 3. Types of congenital heart disease and associated chromosomal abnormalities
<0.001
0.3
Chi-square tests were performed to test the association between extra cardiac anomalies and types of chromosomal abnormalities.
Total Chromosomal Abnormalities Number Tested n=217
Pathogenic Abnormalities
Numerical
Pathogenic CNV (n)
VUS
n=64
n=16
n=16
n
22q11.2 deletion
n=80 CHD type
n (%)
n
DR(%)
Other
DR(%)
n
n=7
n=9 1. Isolated septal defects
39 (18.0)
18
46.2
16
0
2
5.1
3
2. Conotruncal defects
56 (25.8)
22
39.3
11
9
2
19.6
4
Truncus arteriosus
1 (0.5)
0
0.0
0
0
0
0.0
0
IAA
7 (3.2)
6
85.7
3
3
0
42.9
0
d-TGA
15 (6.9)
2
11.8
0
0
2
13.3
0
DORV
12 (5.5)
6
50.0
5
1
0
8.3
2
TOF
21 (9.7)
8
38.1
3
5
0
23.8
2
3. LVOT
45 (20.7)
9
20.0
8
0
1
2.2
2
HLHS
24 (11.1)
4
16.7
3
0
1
4.2
2
CoA
20 (9.2)
5
26.3
5
0
0
0.0
0
Aortic stenosis
1 (0.5)
0
0.0
0
0
0
0.0
0
4. RVOT
25 (11.5)
6
24.0
4
0
2
8.0
2
22 | Page Pulmonary stenosis
3 (1.4)
0
0.0
0
0
0
0.0
0
Pulmonary atresia
9 (4.1)
3
30.0
1
0
2
22.2
1
Tricuspid atresia
11 (5.1)
2
18.2
2
0
0
0.0
1
Ebsteins' anomaly
2 (0.9)
1
50.0
1
0
0
0.0
0
5. AVSD
36 (16.6)
24
66.7
24
0
0
0.0
3
6. Heterotaxy
6 (2.8)
0
0.0
0
0
0
0.0
1
7. TAPVR
2 (0.9)
0
0.0
0
0
0
0.0
0
8. DILV, complex heart defect
6 (2.8)
0
0.0
0
0
0
9. Cardiac tumors
2 (0.9)
1 0.0
1
50.0
1
0
0
0.0
0
VSD: ventricular septal defect, ASD: atrial septal defect, IAA: interrupted aortic arch, d-TGA: transposition of great arteries, DORV: double outlet right ventricle,TOF: tetralogy of fallot, LVOT: left ventricular outflow tract, HLHS: hypoplastic left heart syndrome, CoA: coarctation of aorta, RVOT: right ventricular outflow tract, AVSD: atrioventricular septal defect, TAPVR: total anomalous pulmonary venous return, DILV: double inlet left ventricle, DR:detection rate
433 434
Table 4. Summary of pathogenic chromosomal abnormalities and extracardiac structural anomalies Number Tested N=217
Total Pathogenic Abnormalities
Numerical
Pathogenic CNV
N=64
N=16
N=80
CHD With Single Extra Cardiac Anomaly
N= 43
N= 27
DR(%)
N= 21
N= 6
DR(%)
CNS
4
3
75.0
3
0
0.0
Face
9
9
100.0
8
1
11.1
Neck
1
1
100.0
1
0
0.0
Chest
4
1
25.0
1
0
0.0
GU
3
1
33.3
1
0
0.0
GI
9
5
55.6
3
2
22.2
Abdominal wall
4
3
75.0
1
2
50.0
Skeletal
9
4
44.4
3
1
11.1
2
6.1
n CHD With Multiple Extra Cardiac Anomalies
33
22
66.7
20
PNC: pathogenic copy number variants, CNS: central nervous system, GU: genitourinary, GI: gastrointestinal
435
23 | Page 436 437 438 439 440
FIGURE LEGEND Figure 1. Flow diagram of chromosomal microarray results in the cohort
S2589-9333(19)30118-1
DOI:
https://doi.org/10.1016/j.ajogmf.2019.100078
Reference:
AJOGMF 100078
To appear in:
American Journal of Obstetrics & Gynecology MFM
Received Date: 29 August 2019 Revised Date:
4 December 2019
Accepted Date: 16 December 2019
Please cite this article as: Mustafa HJ, Jacobs KM, Tessier KM, Narasimhan SL, Tofte AN, Mccarter AR, CROSS SN, Chromosomal Microarray Analysis in the Investigation of Prenatally Diagnosed Congenital Heart Disease, American Journal of Obstetrics & Gynecology MFM (2020), doi: https://doi.org/10.1016/ j.ajogmf.2019.100078. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Published by Elsevier Inc.
1
TITLE PAGE
2
Chromosomal Microarray Analysis in the Investigation of Prenatally Diagnosed
3
Congenital Heart Disease
4
Corresponding author: Hiba J. MUSTAFA, MD
5
Fellow, Department of Obstetrics, Gynecology & Women’s Health, University of
6
Minnesota, [email protected], (832) 475-4061
7
Co-authors:
8
9 10
11
12
13
14
15
16
17
18
19
1. Katherine M. JACOBS, MD Assistant Professor, Department of Obstetrics, Gynecology & Women’s Health, University of Minnesota 2. Katelyn M. TESSIER, MS Research Fellow, Biostatistics Core, Masonic Cancer Center, University of Minnesota 3. Shanti L. NARASIMHAN, MD Associate Professor, Department of Pediatric Cardiology, University of Minnesota 4. Alena N. TOFTE Medical Student, University of Minnesota 5. Allison R. MCCARTER Medical Student, University of Minnesota 6. Sarah N. CROSS, MD
20
Assistant Professor, Department of Obstetrics, Gynecology & Women’s Health,
21
University of Minnesota
22
Conflicts of interest: The authors report no conflict of interests.
23
Presentation: The study received an invitation for oral presentation at the 39th annual
24
Society of Maternal Fetal Medicine Pregnancy Meeting 2019, Las Vegas, NV
25
Word count: Abstract: 313 words, main text: 2384 words
26
1 | Page 1
Chromosomal Microarray Analysis in the Investigation of Prenatally Diagnosed
2
Congenital Heart Disease
3
CONDENSATION AND SHORT VERSION OF TITLE
4 5
Condensation: Chromosomal microarray is a reliable, high yield diagnostic test in
6
prenatal congenital heart disease.
7 8
Short title: Chromosomal microarray in fetuses with congenital heart disease
9
AJOG AT A GLANCE
10 11
Why was this study conducted: To investigate the diagnostic yield of chromosomal
12
microarray analysis in prenatally diagnosed congenital heart disease.
13
Key findings: In the context of prenatal diagnostic testing for fetal CHD, chromosomal
14
microarray analysis identified additional, clinically significant cytogenic information
15
compared to conventional karyotyping.
16
What does this add to what is known: Improved prenatal counseling of genetic
17
association with congenital heart disease, especially when combined with extracardiac
18
anomalies.
19 20
Keywords: Congenital heart disease, chromosomal abnormalities, copy number
21
variants, microarray, pregnancy, translocation
22
2 | Page 23
ABSTRACT
24
Objective: Chromosomal microarray analysis has emerged as a primary diagnostic tool
25
in prenatally diagnosed congenital heart disease and other structural anomalies in
26
clinical practice. Our study aimed to investigate the diagnostic yield of microarray
27
analysis as a first tier test for chromosomal abnormalities in fetuses with both isolated
28
and non-isolated congenital heart disease and to identify the association of different
29
pathogenic chromosomal abnormalities with different subgroups of congenital heart
30
disease.
31
Design: Retrospective data from 217 pregnancies diagnosed with congenital heart
32
disease between 2011 and 2016 were reviewed. All pregnancies were investigated
33
using microarray analysis during the study period. Classification of chromosomal
34
abnormalities was done based on American College of Medical Genetics and Genomics
35
guidelines into 1) pathogenic chromosomal abnormalities including numerical
36
chromosomal abnormalities (aneuploidy and partial aneuploidy), and pathogenic copy
37
number variants (22q11.2 deletion and other microdeletions/microduplications), 2)
38
variants of uncertain significance, and 3) normal findings.
39
Results: Our study found a detection rate for pathogenic chromosomal abnormalities
40
(numerical and pathogenic copy number variants) of 36.9% (n=80) in pregnancies
41
prenatally diagnosed with congenital heart disease who underwent invasive testing with
42
chromosomal microarray. Detection rate for numerical abnormalities was 29.5% (n=64)
43
and for pathogenic copy number variants was 7.4% (n=16) of which 4.2% were 22q11.2
44
deletion and 3.2% were other pathogenic CNVs, most of which theoretically could have
45
been missed by utilizing conventional karyotype alone. Pathogenic CNVs were most
3 | Page 46
common in conotruncal defects (19.6%, 11/56) including 42.9% in cases of IAA, 23.8%
47
in cases of TOF, 13.3% in cases of d-TGA, and 8.3% in cases of DORV. Of these
48
changes, 81.8% were 22q11.2 deletion and 18.2% were other
49
microdeletions/microduplications. Following conotruncal defects, pathogenic CNVs were
50
most common in RVOT and LVOT groups (8% and 2.2%, respectively) in which none
51
were 22q11.2 deletion. Pathogenic chromosomal abnormalities (numerical and
52
pathogenic CNVs) detected by CMA were significantly more common in the non-
53
isolated congenital heart disease group (64.5%, n=49) compared to the isolated group
54
(22%, n=31) (P<0.001).
55
Conclusion: In pregnancies diagnosed with congenital heart disease and undergoing
56
diagnostic genetic testing, our study showed that chromosomal microarray analysis has
57
an added value in the detection of pathogenic chromosomal abnormalities compared to
58
conventional karyotype, particularly in cases of pathogenic copy number variants. This
59
yield is influenced not only by the type of congenital heart disease, but also by the
60
presence of extracardiac anomalies.
61
4 | Page 62
MAIN TEXT
63
Introduction: Congenital heart disease (CHD) is a structural abnormality of the heart
64
and great vessels that is present at birth. 1 It is the most common type of birth defects
65
occurring in about 4-13 per 1000 live births and in 10% of still births. 2-4 The underlying
66
causes of CHD are multifactorial, although it has long been thought to have both genetic
67
and environmental contributions. 5-8 G-banded karyotype coupled with fluorescence in
68
situ hybridization (FISH) has been the predominant strategy applied for detecting
69
chromosomal abnormalities in fetuses with CHD in clinical practice. However, G-banded
70
karyotype is time-consuming, limited by low-resolution (400-500 bands), and can
71
identify chromosomal aberrations > 5-10 Mb, while FISH is hampered by limited
72
coverage on the whole genome. 9 Chromosomal microarray analysis (CMA) can be
73
used to perform karyotyping via array comparative genomic hybridization (array CGH)
74
or single-nucleotide polymorphism (SNP). 10 CMA improves resolution over
75
conventional G-banded karyotype in detecting chromosomal abnormalities. 11 Recent
76
studies investigating prenatal cases of CHD by CMA have shown a detection rate for
77
pathogenic chromosomal abnormalities that ranged from 10.9 to 35.5%, and a detection
78
rate of 6.6 to 12% for pathogenic copy number variants. 12-15 The potential advantages
79
of CMA over conventional karyotyping in prenatal diagnosis include higher resolution,
80
avoidance of culturing amniocytes or chorionic villi, automation, and faster turnaround
81
times. In addition, since it does not require dividing cells, it is useful in cases of fetal
82
demise. 16-18 In 2016, the American College of Obstetricians and Gynecologists
83
recommended CMA for patients with a fetus with one or more major structural
84
abnormalities identified on ultrasound examination who is undergoing invasive prenatal
5 | Page 85
diagnosis. 19 Based on that recommendation, we aimed to investigate the diagnostic
86
yield of CMA in prenatal detection of chromosomal abnormalities in fetal CHD, both in
87
isolated and non-isolated types.
88
Materials and Methods:
89
This was a retrospective cohort study at a single tertiary care center. All the
90
pregnancies with CHD that underwent invasive diagnostic testing between 2011 and
91
2016 were included in our study. A total of 336 fetuses diagnosed with CHD were
92
identified through the fetal ECHO database during that time period of which 217
93
pregnancies underwent invasive diagnostic testing via amniocentesis following the
94
identification of prenatal CHDs on ultrasound. Details of maternal characteristics,
95
obstetrical outcomes, as well as delivery and postnatal outcomes up to 2 years of age
96
were obtained for those 217 pregnancies. Prenatal invasive diagnostic testing was done
97
via amniocentesis between 18 and 23 weeks gestation. SNP microarray was used in all
98
the diagnostic cases in our study.
99
Our collected data included all pregnancy outcomes, whether had livebirth, fetal demise,
100
underwent termination, or decided to have comfort care. The CHD cohort was classified
101
using a method described by Botto et al. 20 into nine groups which consisted of: septal
102
defects including atrial septal defects (ASD) and ventricular septal defects (VSD);
103
conotruncal defects including truncus arteriosus, interrupted aortic arch (IAA),
104
transposition of the great arteries (d-TGA), double outlet right ventricle (DORV), and
105
tetralogy of fallot (TOF); left ventricular outflow tract (LVOT) defects including
106
hypoplastic left heart syndrome (HLHS), coarctation of aorta (CoA), and aortic stenosis;
107
right ventricular outflow tract (RVOT) including pulmonary stenosis, pulmonary atresia,
6 | Page 108
tricuspid atresia, and Ebstein’s anomaly; atrioventricular septal defects (AVSD);
109
heterotaxy; total anomalous pulmonary venous return (TAPVR); double inlet left
110
ventricle (DILV) or complex heart defect; and cardiac tumor.
111
The total number of CHD cases were then divided into two groups: isolated CHD which
112
included pregnancies with no extracardiac defects and non-isolated CHD which
113
included pregnancies with single or multiple extracardiac structural defects.
114
Extracardiac structural defects were divided into eight groups which consisted of:
115
central nervous system (CNS); face; neck; chest; genitourinary (GU); gastrointestinal
116
(GI); abdominal wall; and skeletal. According to the American College of Medical
117
Genetics and Genomics, chromosomal microarray analysis results are classified into
118
numerical chromosome abnormalities and copy number variants (CNV). 21 Numerical
119
abnormalities include aneuploidy and partial aneuploidy. CNVs are divided into:
120
pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, and
121
benign. For the purposes of this study, our microarray analysis results were classified
122
into three groups: 1) pathogenic abnormalities including: numerical abnormalities
123
include aneuploidy and partial aneuploidy, and these were assumed to be detectable by
124
karyotype, and pathogenic CNVs (22q11.2 deletion, and others); 2) VUS, and 3) normal
125
results which included likely benign results as well. Detected CNVs were evaluated
126
based on a scientific literature review and the following public databases: The Centre for
127
Applied Genomics (TCAG) Database of Genomic Variants
128
(http://projects.tcag.ca/variation/), University of California Santa Cruz (UCSC) Genome
129
Browser: (http://genome.ucsc.edu/), National Center of Biotechnology Information
130
(NCBI) Database of Genomic Structural Variation: (http://www.ncbi.nlm.nih.gov/dbvar/).
7 | Page 131
For our analysis, variables of interest were summarized using counts and frequencies
132
for categorical variables and mean and standard deviation or median and range for
133
continuous variables by chromosomal abnormalities. To investigate the association
134
between variables of interest and chromosomal abnormalities, Chi-square tests or
135
Fisher’s exact tests were used for categorical variables, when appropriate, and
136
Student’s t-tests or Wilcoxon rank-sum tests for continuous variables, when appropriate.
137
Structural extra cardiac anomalies were summarized using counts and frequencies for
138
everyone tested, those with total pathogenic chromosomal abnormalities, and those
139
with numerical abnormalities and with pathogenic CNVs. Additionally, total pathogenic
140
chromosomal abnormalities were compared for those with isolated and non-isolated
141
CHD. All reported p-values are two-sided, and a level of 0.05 was considered
142
statistically significant. All statistical analyses were performed in R (v 3.4.2).
143 144
Results:
145
Of the 336 pregnancies diagnosed with CHD, a total of 217 underwent invasive
146
diagnostic testing. Subjects’ characteristics and pregnancy outcomes are shown in
147
Table 1. Microarray analysis results (Figure 1) were normal in 55.7% (n=121), VUS in
148
7.4% (n=16), and pathogenic abnormalities in 36.9% (n=80).
149
Pathogenic abnormalities included numerical abnormalities in 29.5% (n=64) and
150
pathogenic CNVs in 7.4% (n=16) (Figure 1). Detected aneuploidy consisted of trisomy
151
21 (n=28), trisomy 18 (n=12), trisomy 13 (n=6), monosomy X (n=5), and 13 other
152
aneuploidies (Figure 1). Pathogenic CNVs consisted of 4.2% (n=9) 22q11.2 deletion
153
and 3.2% (n=7) were other microdeletions/microduplications. CHD was initially divided
8 | Page 154
into isolated and non-isolated CHD (i.e. pregnancies with extracardiac anomalies),
155
where 65% had isolated CHD and 35% had non-isolated. CMA detection rate for
156
pathogenic abnormalities was 22% (31/141) in the isolated CHD group compared to
157
64.5% (49/76) in the non-isolated CHD group (P< 0.001, Table 2). Numerical
158
abnormalities were noted in 23 fetuses (16.3%) in the isolated group compared to 41
159
fetuses (53.9%) in the non-isolated group (P<0.001, Table 2).
160
The detection rate for pathogenic CNVs in the isolated CHD group was 5.7%, 8/141
161
(87.5% were 22q11.2 deletion and 12.5% were other microdeletions/microduplications),
162
and 10.5%, 8/76 in the non-isolated CHD group (50% were 22q11.2 deletion, and 50%
163
were other deletions/duplications). The difference in the pathogenic CNVs detection rate
164
was not statistically significant between both groups (Table 2).
165
CHD was then divided into nine groups as explained in the methods section. These
166
groups were: conotruncal defects (25.8%), LVOT (20.7%), septal defects (18%), AVSD
167
(16.6%), RVOT (11.5%), heterotaxy and DILV (each were 2.8%), followed by TAPVR
168
and cardiac tumors (each were 0.9%) (Table 3). CHD types in pregnancies that did not
169
undergo diagnostic genetic testing can be seen in supplemental Figure 1.
170
Table 3 shows the detection rate of various chromosomal abnormalities in each of those
171
nine groups. Total pathogenic chromosomal abnormalities detection rate was highest in
172
AVSD (66.7%), followed by conotruncal (39.3%), RVOT and LVOT (24%, and 20%
173
respectively). Pathogenic CNVs were most common in conotruncal defects (19.6%,
174
11/56) including 42.9% in cases of IAA, 23.8% in cases of TOF, 13.3% in cases of d-
175
TGA, and 8.3% in cases of DORV. Of these changes, 81.8% were 22q11.2 deletion and
176
18.2% were other microdeletions/microduplications. Following conotruncal defects,
9 | Page 177
pathogenic CNVs were most common in RVOT and LVOT groups (8% and 2.2%,
178
respectively) in which none were 22q11.2 deletion (Table 3). We emphasize in our
179
results on the detection rate for pathogenic CNVs as it is the number that theoretically
180
could have been missed by conventional karyotype. 8-11, 22 No pathogenic CNVs were
181
detected in the AVSD group as all cases were noted to be aneuploidy, and none were
182
also detected in the last four CHD groups (heterotaxy, DILV, TAPVR, and cardiac
183
tumors), however these groups had considerable small sample size (Table 3). For
184
detailed detection rate for each of the nine groups based on presence and absence of
185
extracardiac anomalies please see supplementary material (Supplemental Table 1). We
186
also investigated CMA yield in CHD cases with extracardiac anomalies (Table 4). In our
187
cohort, 43 (19.8%) pregnancies had single extracardiac anomaly, and 33 (15.2%) had
188
multiple anomalies. Pathogenic changes were most commonly associated with face
189
anomalies (20.9%, 9/43), followed by gastrointestinal (11.6%, 5/43), and skeletal
190
anomalies (9.3%, 4/43). Similar rates of pathogenic changes were seen between
191
pregnancies with single extracardiac anomaly and those with multiple ones (66.7% and
192
62.8%, respectively).
193
Obstetrical outcomes for the whole cohort and postnatal outcomes for the livebirths
194
(78.8%, n=171) were obtained (Supplemental Table 2). Postnatal confirmation data of
195
the prenatally diagnosed CHDs and extracardiac anomalies were collected. There were
196
no critical CHDs missed on prenatal imaging. Extracardiac anomalies undiagnosed on
197
prenatal imaging comprised of 4% (n=9) of cases. Outcome data were compared
198
between pregnancies that had pathogenic chromosomal abnormalities and those that
199
did not. The pathogenic changes group was more significantly associated with
10 | Page 200
polyhydramnios (P=0.03), single/multiple structural extracardiac anomalies (P<0.001),
201
and with gestational age at delivery of less than 37 weeks (P=0.01) while there were no
202
significant differences in the postnatal outcomes between groups (Supplemental Table
203
2). Details on pathogenic CNVs and VUS can be found in supplemental material
204
(Supplemental Table 3).
205 206
Comment:
207
Principle findings: We performed a retrospective study on a large cohort to assess the
208
diagnostic yield of SNP array for identifying chromosomal abnormalities in fetuses with
209
CHD in clinical practice. Based on the results, we described the frequency and
210
distribution of chromosomal abnormalities for different types of CHDs and compared the
211
frequency of chromosomal abnormalities between fetuses with isolated CHD and non-
212
isolated CHD. We report a detection rate of 36.9% for pathogenic chromosomal
213
abnormalities (numerical and pathogenic CNVs). Our study shows an added detection
214
rate for CMA over karyotype of 7.4% for pathogenic copy number variants in fetuses
215
with CHD (4.2% for 22q11.2 deletion and 3.2% for other pathogenic CNVs) (Figure 1).
216
In 22q11.2 deletion syndrome, conotruncal cardiac defects occur in almost 80% of
217
patients with the most common are IAA, truncus arteriosus, and TOF.42-44 Although
218
traditionally FISH has been used for prenatal 22q11.2 deletion syndrome testing,
219
atypical and small deletions can still be missed in 5-15% of cases. 35,36 Hence,
220
according to our study results FISH alone could have presumably missed more than
221
50% of pathogenic CNVs. After dividing the cohort into isolated and non-isolated CHD,
222
the detection rate for pathogenic copy number variants in the setting of isolated cardiac
11 | Page 223
anomalies was 5.7%, and in the setting of non-isolated cardiac anomalies was 10.5%
224
(Table 2). Pathogenic CNVs were most common in the conotruncal defects group with
225
incremental yield of 19.6%. Given that conventional karyotype can reliably detect
226
chromosomal abnormalities of >10 Mb, 23 then the theoretical incremental yield of
227
pathogenic CNVs <10 Mb in our study would be 7.4% which was identical to VUS
228
detection rate in our study. VUS detection rate in fetuses without anomalies has been
229
reported to range between 0.9- 2.5%, 9,29 while in fetuses with structural anomalies
230
including CDH this rate is higher (7.4% in our study). Patients should be educated and
231
counseled about the chances of VUS detection, and the complexities associated with
232
interpreting the results when offering CMA testing.
233
Clinical implications: It is important to obtain the most accurate and detailed genetic
234
information in the prenatal setting for both patients and care providers given the
235
implications it can have on both prenatal and immediate postnatal management and
236
prognosis, for which several recent studies have investigated prenatal cases of CHD by
237
CMA using different array types. 12-15 Our results are in agreement with those previous
238
reports that showed a detection rate for pathogenic chromosomal abnormalities ranging
239
from 10.9% to 35.5%, 25-28 and for pathogenic CNVs ranging from 6.6% to 12%. 12-15
240
Compared to the study by Shafer et al, 29 the incremental yield in cases of Tetralogy of
241
Fallot in our study was higher (23.8% versus 13.3%), while the incidence in cases of
242
HLHS and VSD were lower in our study. The reasons for this discordance could be that
243
the sample sizes and the proportion of isolated CHD were different between the two
244
studies. Furthermore, of the 45 cases of LVOT defects, 20% had pathogenic
245
chromosomal abnormalities compared to the detection rate of 13.3% in other studies. 12
12 | Page 246
Our study had two cases of fetal cardiac tumors in which one of them the mother had a
247
personal history of tuberous sclerosis (TS). The newborn was confirmed to have both
248
clinical and genetic criteria for TS. Primary cardiac tumors are rare, with prevalence of
249
0.25% in infants and children.37,38 The vast majority of primary cardiac tumors are
250
benign, with the most common being rhabdomyoma. Cardiac rhabdomyoma may be the
251
initial manifestation of TS.39,40 TS is an autosomal dominant condition for which prenatal
252
genetic testing can be offered along to the CMA, however, prenatal genetic testing for
253
TS was not performed in both cases in our study. It has been reported that the
254
incidence of chromosomal abnormalities will be higher when CHD is accompanied with
255
additional structural anomalies, 14,29,30 which was also observed in our study. Cases of
256
CHD combined with facial malformation resulted in a high incidence of chromosomal
257
abnormalities when compared with CHD plus other types of structural anomalies.
258
Although the diagnostic utility of CMA is greater than karyotype, the cost of CMA is
259
substantially more. However, in multiple cost effective analysis studies, CMA alone
260
appeared to be the preferred strategy for sonographically-detected anomalies, although
261
karyotype alone and CMA following a normal karyotype are also acceptable strategies.
262
If a structural abnormality is strongly suggestive of a particular aneuploidy in the fetus
263
(eg, atrioventricular heart defect, which is characteristic of trisomy 21), karyotype with
264
reflex to microarray analysis may be offered.41 Performing both karyotype and CMA
265
simultaneously did not appear to improve diagnosis and has been shown in prior reports
266
to be associated with higher costs. 31–34.
267
Strengths and weaknesses: Strengths of our study include: large sample size of our
268
cohort which enabled us to obtain the CMA yield for different types of CHDs and to
13 | Page 269
investigate the possible differences between the groups of fetuses with isolated and
270
non-isolated CHD which can improve prenatal counseling when offering invasive
271
diagnostic testing. Ultrasound imaging and laboratory testing were done at one site
272
which provide consistency among the definition of particular ultrasound anomalies and
273
genetic abnormalities. Postnatal confirmation for prenatally detected ultrasound
274
anomalies was obtained in our study.
275
We acknowledge the limitations to our study including the retrospective, single center
276
design. Although the sample size was large, the distribution of different types of CHDs
277
varied greatly. It is in our practice to offer parental genetic testing for detected CNVs.
278
However, information regarding parental testing was not collected in our study.
279
Conclusion with future research implications: This study aimed to understand the
280
specific detection rates for chromosome aberrations after microarray analysis for
281
fetuses with different types of CHD.
282
We have demonstrated a significantly increased detection of pathogenic chromosomal
283
abnormalities after applying microarray analysis in all indications for prenatal testing for
284
CHD, particularly in cases of pathogenic CNVs. This is especially true in situations
285
when an ultrasound examination reveals extracardiac fetal anomalies. Our detection
286
rate for pathogenic CNVs was 7.4%, a theoretical incremental yield over testing with
287
standard karyotype. Our study supports the opinion of the American College of
288
Obstetrics and Gynecology to endorse the use of microarray testing in the presence of
289
fetal anatomic anomalies. 19
290
14 | Page 291
ACKNOWLEDGMENT: Research reported in this publication was supported by NIH
292
grant P30 CA77598 utilizing the Biostatistics and Bioinformatics Core shared resource
293
of the Masonic Cancer Center, University of Minnesota and by the National Center for
294
Advancing Translational Sciences of the National Institutes of Health Award Number
295
UL1TR002494. The content is solely the responsibility of the authors and does not
296
necessarily represent the official views of the National Institutes of Health.
297 298
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20 | Page 424
TABLES
425
Table 1. Summary of subject characteristics. (N=217) Age
< 35 years
158 (72.8)
≥ 35 years Ethnicity, n (%)
Insurance, n (%)
BMI (kg/cm2 ), n (%)
Parity, n (%)
59 (27.2)
White
166 (78.7)
Black
23 (10.9)
Latina
12 (5.7)
Asian
10 (4.7)
Medicaid
36 (45)
Private
44 (55)
Underweight
2 (3.6)
Normal
24 (43.6)
Overweight
13 (23.6)
Obese
16 (29.1)
Nulliparous
27 (33.8)
Multiparous
53 (66.2)
GA at initial diagnosis of cardiac anomaly Mean (SD)
22 (1.8)
Median (range)
20 (18, 23)
Pregnancy outcomes, n (%) Live birth
171 (78.8)
Fetal demise
17 (7.8)
Termination
20 (9.2)
Comfort care
5 (2.3)
Delivered at external institution
4 (1.8)
426 427 428
Table 2. Comparison of types of chromosomal abnormalities for those with and without structural extra cardiac anomalies. Isolated CHD P Value1 Non-isolated CHD (N=76) (N=141) Total pathogenic abnormalities, n (%)
49 (64.5)
31 (22.0)
<0.001
21 | Page Numerical abnormalities, n (%)
41 (53.9)
23 (16.3)
T21
12 (29.2)
16 (69.5)
T18
12 (29.2)
0 (0.0)
T13
6 (14.6)
0 (0.0)
45X
3 (7.3)
2 (8.6)
Other
8 (19.5)
5 (21.7)
8 (10.5)
8 (5.7)
22q11.2 deletion
4 (50.0)
5 (87.5)
Other
4 (50.0)
3 (12.5)
Pathogenic CNV, n (%)
429 430 431
1
432
Table 3. Types of congenital heart disease and associated chromosomal abnormalities
<0.001
0.3
Chi-square tests were performed to test the association between extra cardiac anomalies and types of chromosomal abnormalities.
Total Chromosomal Abnormalities Number Tested n=217
Pathogenic Abnormalities
Numerical
Pathogenic CNV (n)
VUS
n=64
n=16
n=16
n
22q11.2 deletion
n=80 CHD type
n (%)
n
DR(%)
Other
DR(%)
n
n=7
n=9 1. Isolated septal defects
39 (18.0)
18
46.2
16
0
2
5.1
3
2. Conotruncal defects
56 (25.8)
22
39.3
11
9
2
19.6
4
Truncus arteriosus
1 (0.5)
0
0.0
0
0
0
0.0
0
IAA
7 (3.2)
6
85.7
3
3
0
42.9
0
d-TGA
15 (6.9)
2
11.8
0
0
2
13.3
0
DORV
12 (5.5)
6
50.0
5
1
0
8.3
2
TOF
21 (9.7)
8
38.1
3
5
0
23.8
2
3. LVOT
45 (20.7)
9
20.0
8
0
1
2.2
2
HLHS
24 (11.1)
4
16.7
3
0
1
4.2
2
CoA
20 (9.2)
5
26.3
5
0
0
0.0
0
Aortic stenosis
1 (0.5)
0
0.0
0
0
0
0.0
0
4. RVOT
25 (11.5)
6
24.0
4
0
2
8.0
2
22 | Page Pulmonary stenosis
3 (1.4)
0
0.0
0
0
0
0.0
0
Pulmonary atresia
9 (4.1)
3
30.0
1
0
2
22.2
1
Tricuspid atresia
11 (5.1)
2
18.2
2
0
0
0.0
1
Ebsteins' anomaly
2 (0.9)
1
50.0
1
0
0
0.0
0
5. AVSD
36 (16.6)
24
66.7
24
0
0
0.0
3
6. Heterotaxy
6 (2.8)
0
0.0
0
0
0
0.0
1
7. TAPVR
2 (0.9)
0
0.0
0
0
0
0.0
0
8. DILV, complex heart defect
6 (2.8)
0
0.0
0
0
0
9. Cardiac tumors
2 (0.9)
1 0.0
1
50.0
1
0
0
0.0
0
VSD: ventricular septal defect, ASD: atrial septal defect, IAA: interrupted aortic arch, d-TGA: transposition of great arteries, DORV: double outlet right ventricle,TOF: tetralogy of fallot, LVOT: left ventricular outflow tract, HLHS: hypoplastic left heart syndrome, CoA: coarctation of aorta, RVOT: right ventricular outflow tract, AVSD: atrioventricular septal defect, TAPVR: total anomalous pulmonary venous return, DILV: double inlet left ventricle, DR:detection rate
433 434
Table 4. Summary of pathogenic chromosomal abnormalities and extracardiac structural anomalies Number Tested N=217
Total Pathogenic Abnormalities
Numerical
Pathogenic CNV
N=64
N=16
N=80
CHD With Single Extra Cardiac Anomaly
N= 43
N= 27
DR(%)
N= 21
N= 6
DR(%)
CNS
4
3
75.0
3
0
0.0
Face
9
9
100.0
8
1
11.1
Neck
1
1
100.0
1
0
0.0
Chest
4
1
25.0
1
0
0.0
GU
3
1
33.3
1
0
0.0
GI
9
5
55.6
3
2
22.2
Abdominal wall
4
3
75.0
1
2
50.0
Skeletal
9
4
44.4
3
1
11.1
2
6.1
n CHD With Multiple Extra Cardiac Anomalies
33
22
66.7
20
PNC: pathogenic copy number variants, CNS: central nervous system, GU: genitourinary, GI: gastrointestinal
435
23 | Page 436 437 438 439 440
FIGURE LEGEND Figure 1. Flow diagram of chromosomal microarray results in the cohort