Evaluation of Genomic Variants in Non-syndromic Congenital Heart Disease in Turkish Pediatric Group

Sinem Kocagil; Büşra Özkan; Sabri Aynacı; Tuğçem Akın; Ezgi Susam; Ebru Erzurumluoğlu Gökalp; Beyhan Durak Aras; Birsen Uçar; Sevilhan Artan; Oğuz Çilingir

doi:10.12996/gmj.2025.4414

ABSTRACT

Objective

Congenital heart disease (CHD) is the most common congenital malformation in the population, and so far, all the known genetic factors could explain only 20-25% of the cases.

Material and Methods

In this study, microarray analysis was performed, and next-generation sequencing of Myosin Heavy Chain 6 (MYH6), NK2 Homeobox 5 (NKX2-5), GATA Binding Protein 4 (GATA4), Notch Receptor 1 (NOTCH1), and T-Box Transcription Factor 1 (TBX1) genes, which are known to be involved in the etiology of non-syndromic CHD, was performed in 40 patients with isolated cardiac defects between the ages of 0-18 and 40 age-matched controls.

Results

In microarray analysis, 9 novel copy-number variations (CNVs) that were not reported in population databases, and included OMIM genes were detected in 1.5% (6/40) of the patients. Even though the detected CNVs had not been previously associated with CHDs and were classified as Variant of Uncertain Significance (VUS), overall CNV count burden in the patient group was significantly higher than in the control group. Also, there were no pathogenic/likely pathogenic sequence variants in MYH6, NKX2-5, GATA4, NOTCH1, and TBX1 genes. The c.700C>T [p.(Arg234Cys)] and c.5949C>G [p.(Asn1983Lys)] in the NOTCH1 gene were classified as VUS and have not been detected in the control group.

Conclusion

Although microarray technologies and candidate gene sequencing are useful diagnostic tools, routine genetic testing of sporadic non-syndromic CHD patients is controversial. We believe that still remains a challenge to interpret the variants detected in multifactorial CHD with complex etiology, and further studies are needed.

Keywords:

Next-generation sequencing, microarray analysis, congenital heart disease

INTRODUCTION

Congenital heart disease (CHD) is the most common congenital malformation in the population with an estimated frequency of 1-2%. Every year approximately 1.35 million new patients are born with the condition, and it still remains one of the most important causes of childhood mortality and morbidity in well-developed countries (1).

Most of the patients, approximately 75-80%, have isolated cardiac defects without any extra-cardiac malformation or global developmental delay, intellectual disability. The rest manifest the cardiac defects as a part of a syndrome such as aneuploidies, monogenic, or microdeletion/duplication syndromes (2).

Large-scale epidemiological studies revealed that a genetic or environmental cause can be identified in approximately 20-30% of CHDs (3). Among the genetic causes, chromosomal aneuploidies and gross structural chromosome aberrations that could be detected by conventional cytogenetic analyses are responsible for 20-25%; submicroscopic chromosomal rearrangements such as 22q11.2 deletion syndrome and Williams syndrome are responsible for 10-12%; and monogenic syndromes such as Kabuki syndrome and Noonan syndrome are responsible for 3-5% (4). It becomes even more compelling in the context of the non-syndromic CHD group. Positive family history increases the risk of recurrence depending on the type of defect (3.4 to 79.1 times) in siblings, and monozygotic twin studies show a higher concordance than the rest of the population (5, 6). Also, consanguinity of the parents has been shown to increase the risk (7). Non-syndromic cardiac defects are mostly diagnosed as sporadic multifactorial malformations resulting from complex genetic mechanisms or environmental factors. To further define the genetic contributions to the causes, developmental steps in the embryonic and fetal period are studied in particular, and several genes coding transcription factors, cardiac structural proteins, or molecules responsible for the signal transduction pathways are evaluated (8).

In recent studies, it is estimated that copy-number variations (CNV), which involve the loss and gain of genomic material more than 1 kb, is responsible for approximately 3-10% of the non-syndromic CHD patients. Similarly, next-generation sequencing (NGS) of the candidate genes revealed that sequence variants are responsible for 2% (9). Many genes have so far been identified as responsible for the non-syndromic CHDs, such as Myosin Heavy Chain 6 (MYH6), NK2 Homeobox 5 (NKX2-5), GATA Binding Protein 4 (GATA4), Notch Receptor 1 (NOTCH1), and T-Box Transcription Factor 1 (TBX1) (10-12).

Over the past decade, with the development of massive parallel sequencing techniques and microarray technologies, it has become possible to elucidate the monogenic pathogenic variants contributing to specific phenotypes and identify candidate genes. Therefore, this study aimed to perform microarray analysis and NGS on previously implicated genes in Turkish pediatric cases of non-syndromic CHD.

MATERIALS AND METHODS

Study Group

A group of 40 patients was included in the study. All patients were diagnosed by echocardiography at Pediatric Cardiology clinics and then evaluated at Medical Genetics clinics for syndromic traits and pedigree analysis. Inclusion criteria for the patients were not to have extra-cardiac anomaly or global developmental delay or intellectual disability. All 40 age-matched (8±4.6) control samples, consisting of 18 females and 22 males, were examined by echocardiography before being included in the study. The control group was included in the microarray analysis to assess the contrast in size and CNV count burden between two groups. Written informed consent was obtained from legal representatives before collecting blood samples in accordance with the Declaration of Helsinki. The study was approved by the Non-interventional Clinical Research Ethics Committee of Eskişehir Osmangazi University (decision number: 17, date: 30.12.2024).

Microarray Method

DNA was extracted from peripheral blood samples of all cases using the A.B.T. DNA Purification Kit (TM), according to the manufacturer’s recommendations. For microarray analysis, the Agilent Comparative Genomic Hybridization + Single Nucleotide Polymorphism Microarray Kit (4x180K) was used. DNA digestion, labeling, purification, and hybridization procedures were performed according to the manufacturer’s instructions, and after post-hybridization washes, the scanning process was performed.

Next-Generation Sequencing

Peripheral blood samples were collected from all patients, and by the Magna Pure Compact LC (Roche Applied) extraction kit gDNA was isolated according to the manufacturer’s recommendations. Amplification of all exons and exon/intron boundaries of NKX2-5, TBX1, NOTCH1, MYH6, and GATA4 genes in each pool of 51 amplicons was done by TaqDNA polymerase using a Thermal Cycler (Thermo Fisher Scientific Inc.). Library preparation was done with NEXTERA XT Index Kit V2, and sequence analysis on a micro flow cell was performed with the MiSeq instrument (Illumina, Inc.).

Analysis of Sequence Variants

Sequence alignment to the reference genome and the quality filter were performed by MiSeq Reporter v2.3 software. Single nucleotide variants, small insertion variants, and deletion variants were filtered. Coverage depth and quality scores were controlled using the integrative genomics viewer database. The variant classification according to the American College of Medical Genetics (ACMG) criteria was done using the platforms such as Varsome and Franklin (13). Non-synonymous variants that were not reported in population databases (GnomAD) or had a minor allele frequency of <0.01 were noted as rare variants. The functional impact of missense variants was assessed using in silico prediction tools: MutationTaster (http://www.mutationtaster.org/), Prediction of Effects of Human nsSNPs (http://genetics.bwh.harvard.edu/pph2/), Scale-Invariant Feature Transform (http://sift.jcvi.org/), and Human Splicing Finder (http://www.umd.be/HSF/). The dbSNP (https://www.ncbi.nlm.nih.gov/snp/) and ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/) databases were used for literature review.

Analysis of Copy-Number Variations

Feature Extraction 3.0.2.11 and Agilent Cytogenomics 3.0.2.11 software were used for data extraction and analysis, respectively. Conservative log2 ratio thresholds were taken as 0.3 and -0.3, respectively. Genomic regions with at least 5 probes were included for analysis. DECIPHER database v11.12 (https://www.deciphergenomics.org/), the Database of Genomic Variant (http://dgv.tcag.ca/dgv/app/home), and PubMed were used as resources to assess the variants detected. Franklin Genoox database (https://franklin.genoox.com/clinical-db/home), and ClinGen CNV Interpretation Calculator (https://cnvcalc.clinicalgenome.org/cnvcalc/) were used to classify the variants according to ACMG/ClinGen Technical Standards for CNVs (14).

Statistical Analysis

Data analysis was performed with IBM SPSS 21.0. Relationships between means of a continuous variable were evaluated by independent-sample t-test analysis.

RESULTS

In this study, a total of 40 patients were included: 14 males and 26 females. The mean age of the patients was noted as 6±5.1. According to the diagnostic criteria, 13 septal defects (32.5%), 12 left ventricle outflow defects (30%), 7 conotruncal anomalies (17.5%), 4 complex cardiac anomalies (10%), 2 right ventricle outflow defects (5%), 1 atrioventricular canal defect (2.5%), 1 pulmonary venous return anomaly (2.5%) were detected. The cardiac anomalies of the patients are given in Table 1. The incidence of consanguinity among the parents of the patients was 7.5% (3/40).

Results of Next-generation Sequencing

Patients with non-syndromic congenital heart defects were included in the study; previously defined structural cardiac protein-coding and transcription factor genes were sequenced by NGS methods. Mean coverage was 152x for 98.10% of the targeted amplicons of the NOTCH1 gene, 134x for 98.40% of the targeted amplicons of the MYH6 gene, 171x for 99.30% of the targeted amplicons of the GATA4 gene, 117x for 99.70% of the targeted amplicons of the NKX2-5 gene and 105x for 99.10% of the targeted amplicons of the TBX1 gene. There were no pathogenic or likely pathogenic variants detected in this study, but in 5% (2/40) of patients, variants of uncertain significance (VUS) that might be clinically significant were detected. The detected VUS variants and clinical findings of the variant carriers are summarized in Table 2.

The c.700C>T, [p.(Arg234Cys)] variant in the NOTCH1 gene has been detected in case 34, who was a 9-month-old female patient. She was born to healthy, non-consanguineous parents. There was no prenatal exposure to teratogens during the pregnancy, nor was there a family history of CHD. She was diagnosed with secundum ASD and pulmonary stenosis at 6 months of age. The variant was classified as VUS according to the ACMG criteria. Segregation analysis revealed the variant occurred de novo.

c.5949C>G [p.(Asn1983Lys)] variant in the NOTCH1 gene has been detected in case 40, who was a 14-year-old male patient. He was born to healthy, non-consanguineous parents. There was no prenatal exposure to teratogens during the pregnancy or family history of CHD. He was diagnosed with bicuspid aortic valve and aortic stenosis after the birth. This variant was a novel change that was not previously reported in databases, and the allele frequency was not available at the GnomAD database. The variant was classified as VUS according to the ACMG criteria. Segregation analysis revealed, the variant occurred de novo.

Results of Microarray Analysis

There were a total of 62 CNVs detected in the patient group and 27 CNVs in the control group. Among the 62 CNVs, five were detected in both control and study groups. Among the patient and control groups, CNV detection rates were 82% (33/40) and 22.5% (9/40), respectively (odds ratio: 16.2381 95% confidence interval: 5.3905 to 48.9145, p<0.0001). The burden of CNV counts (total CNVs/total individuals) was significantly higher (p<0.001) in the patient group compared to the control group, Among the CNVs detected in patients, 45.1% (28/62) were copy-number losses and 54.8% (34/62) were copy-number gains. 14.51% (38/62) of the CNVs were previously reported in DGV more than once, therefore classified as ‘‘benign’’. Also, 12.9% (8/62) of CNVs did not have any genes included in the region. Pathogenic or likely pathogenic variants were not detected in our study, but we have identified VUS CNVs in 15% (6/40) of the patient group. 14.5% (9/62) were are summarized in Table 3.

Case 13 was a 1-year-4-month-old female patient who was diagnosed with perimembranous VSD. She had a 55.749 kb gain at the region 6p25.3 and a 272.22 kb gain at the region 17q25.3. Neither of the aberrations has been previously reported in CHD. Gain of the 6p25.3 region included the FOXCUT and FOXC1 genes. The FOXC1 gene was reported to be haploinsufficient and was previously associated with Anterior segment dysgenesis 3, multiple types (OMIM #301631) and Axenfeld-Rieger syndrome, type 3 (OMIM #602482). The FOXCUT gene encodes a long noncoding RNA, which was suggested to be a regulator of the FOXC1 transcript and involved in the proliferation and migration processes of tumor cells. Gain of the related region was not reported in the DECIPHER database. The 17q25.3 (79,638,223-79,910,442) region included 17 OMIM genes (CCDC137, HGS, MRPL12, SLC25A10, GCGR, MCRIP1, P4HB, ARHGDIA, ALYREF, ANAPC11, PCYT2, NPB, SIRT7, MAFG, PYCR1, NOTUM, ARL16). GCGR, P4HB, ARHGDIA, and PYCR1 were morbid genes in the region, but they have not been previously associated with congenital heart defects. This gain was not reported in the DECIPHER database.

Case 23 was a 7-year-5-month-old male patient who was diagnosed with aortic coarctation and bicuspid aortic valve. He had a 358,299 kb gain at 3q13.31 and an 81.09 kb gain at the 8q24.11 region. The gain at the 3q13.31 region includes the OMIM gene, TUSC7. In the DECIPHER database, a patient (DECIPHER ID: 384018) who has autism was reported with a gain of a similar region, but it was classified as likely benign and had been maternally inherited. Gain at the 8q24.11 region includes the EXT1 gene, which encodes the exostosin-1 protein. Loss of the EXT1 gene causes multiple exostoses type 1, but gain of the gene is not associated with any CHD.

Case 26 was a 4-year, 3-month-old male patient who was a diagnosed with d-TGA. He had a 166,784 kb gain at 4q32.1. The region includes three OMIM genes (ASIC5, TDO2 and CTSO) but they have not been reported as morbid genes. Gain of a similar region was reported in DECIPHER database, previously in a patient with intellectual disability (DECIPHER ID: 345189) but not reported in a patient who was diagnosed with CHD.

Case 28, was a 14-year-3-month-old male patient who has been diagnosed with TOF. He had a 638.515kb gain at Xq21.31. The region included the PCDH11X OMIM gene. The PCDH11X gene belongs to the protocadherin gene family and has not been associated with any phenotype to date. It was reported to be expressed mainly in brain, and ovary tissues. In addition to that, it is implicated in cell-cell communication and dendritic synaptic plasticity, and is suggested as a candidate gene for dyslexia. Gain of a similar region was reported previously in the DECIPHER database in a patient with intellectual disability and obesity (DECIPHER ID: 258856) who did not have any cardiac findings.

Case 35 was a 17-year-old female patient, who was diagnosed with a bicuspid aortic valve. She had 169.936 kb loss at 19p13.3. The region included three OMIM genes (TLE2, TLE6 and ZNF77). The TLE2 gene has not been previously associated with any phenotype but is known to act as a corepressor in the negative regulation of the canonical Wnt signaling pathway (15).
TLE6 gene is associated with preimplantation embryonic lethality, autosomal recessive (OMIM #612399). It regulates spermatogonia proliferation and cell cycle progression, but is not associated with the pathogenesis of congenital heart defects. ZNF77 gene has not been previously associated with any phenotype and is predicted to enable DNA-binding transcription repressor activity.

In Case 36, a 10-year-3-month-old male patient diagnosed with a bicuspid aortic valve, a 98.904 kilobases gain at 6q27 and a 95.998 gain at the 13q21.32 regions were detected. gain at the 6q27 region includes SMOC2 gene. This gene Dentin dysplasia, type I, characterized by microdontia and misshapen teeth, and with autosomal recessive (OMIM #125400), but not with any CHD. The gain at the 13q21.32 region included the PCDH19 gene. This gene is associated with developmental and epileptic encephalopathy type 9, X-linked (OMIM #300088), but not with any CHD.

DISCUSSION

Congenital heart defects are the most common birth defects all around the world. It remains one of the most important reasons for childhood mortality and morbidity (16). Given the multifactorial nature of the condition, it is challenging to identify the genetic etiology, thereby making it difficult to provide proper genetic counseling to patients. However, thanks to advances in molecular technologies, information on the molecular pathology of the disease has begun to emerge (17).

This study aimed to perform microarray analysis and NGS of NKX2-5, MYH6, GATA4, NOTCH1 and TBX1 genes in the Turkish pediatric group with non-syndromic CHD. Microarray analysis is the most important tool for identifying CNVs in routine practice. Among other genetic conditions, it has emerged as a useful tool for the diagnosis of both isolated and syndromic CHDs (18). More recently, in addition to common pathogenic microdeletion syndromes that include extracardiac abnormalities such as 22q11.2 deletion, CNVs that include dosage-sensitive genes important for cardiogenesis, or include regulatory elements, have been identified in isolated CHDs. It is known that CNVs are the underlying mechanism of 3-25% of syndromic CHDs while they account for 3-10% of the non-syndromic CHDs.

In our study, we did not detect any pathogenic or likely pathogenic CNVs, but we have identified CNVs in 15% (6/40) of the patient group. Previous studies described in Table 4 show that pathogenic/likely pathogenic CNVs are detected in the patient cohorts, including both syndromic and non-syndromic CHDs (20-24). Since our patient group included only non-syndromic CHDs and there was no positive family history, we assumed that there were no pathogenic/likely pathogenic CNVs detected.

Besides gene content and pathogenicity classification, researchers also suggest that the total number and size of the CNVs are higher in CHD patients than in control groups. Several studies indicate that the overall CNV count burden is likely higher in CHD patients compared to the control group. Similar to previous studies in the literature, CNV counts were detected significantly higher in the patient group compared to the control group in our study (25, 26).

Since the advent of massive parallel sequencing technologies, our understanding of the genetics of CHDs has rapidly expanded (27). Targeted or non-targeted sequencing (whole exome sequencing, whole genome sequencing) technologies have been applied to both syndromic and non-syndromic forms of CHD. Causative variants are mostly identified in familial non-syndromic patients, but due to the multifactorial nature of the CHDs it is not possible to identify a pattern presuming Mendelian inheritance (28, 29).

NKX2-5, GATA4, TBX1, NOTCH1, and MYH6 genes have been identified as strong candidates for non-syndromic CHDs in the past decades (4, 30, 31). In our study, we have detected a total of 103 variants in the five genes by the NGS technique. There were no pathogenic or likely pathogenic variants detected in this study; however, in 5% (2/40) of patients, VUS were detected. Dong et al. (32) have evaluated 73 CHD probands from consanguineous Turkish families with whole exome sequencing and detected causative genetic alterations in 13.7% of the patients. It was assumed that the detection rate of this study was high because of the consanguinity among the parents and the contribution of recessive variants (9.6%), which is lower in contrast to our study (32). Blue et al. (33) reported pathogenic variants at 57 genes that have been previously associated with both syndromic and non-syndromic CHDs in five probands (5/16) with positive family history. It was noted that the high prevalence of the pathogenic variants in the study was due to the inclusion of exceptionally familial cases. Similar to that, Jia et al. (34) evaluated 36 CHD patients from 13 families by targeted NGS analysis of 57 CHD-related genes and detected potentially disease-causing variants in 46% (6/13) of the families. Also, in a study done by Pulignani et al. (35) 68 non-syndromic CHD patients (57 sporadic and 11 familial) were evaluated by next-generation sequencing of 16 candidate genes. They have detected 20 possible disease-causing variants out of 68 patients. We believe that the lower detection rate in our study, compared to previously reported ones, is due to the inclusion of both familial and syndromic cases in other studies. Also, it might differ because of the distinct variant classification criteria that are used and the different number of genes covered in targeted NGS panels.

The NOTCH1 gene is located at the 9q34 region and consists of 34 exons. It encodes a protein that belongs to an essential intracellular signaling receptor family that has important functions such as cell proliferation, cell death, and cell fate decisions during embryogenesis (36). It was reported that during cardiogenesis, activation of the NOTCH1 receptor function in the epithelial-mesenchymal transition of the endocardial cushion development and the formation of the semilunar valves (37). It is well known that truncating variants of the NOTCH1 gene are associated with the development of CHDs, especially BAV and left ventricular outflow tract malformations. The c.700C>T [p.(Arg234Cys)] variant was previously reported (rs567890045), but has not been associated with any phenotype. It is located at codon 234 in the extracellular EGF-like domain of the protein. Since the variant is located adjacent to the O-glycosylation site of 232 amino acids, it was predicted to alter posttranslational modification and intracellular interactions of the protein (38). c.5949C>G [p.(Asn1983Lys)] is a novel variant that was reported in the literature. The variant is present in the ankyrin repeat domain of the protein, and there have been several functional studies indicating that such variants might disrupt the proper folding of the protein.

Study Limitations

Although it was designed as a case-control study, and age-matched controls with normal echocardiography have been included, we believe that one of the limitations of the study that might have influenced the results is the limited number of patients who were involved in our study. Second, in the NGS analysis, only five autosomal dominant candidate genes, which have the strongest association, were included; therefore, future studies with a large number of genes might be more informative.

CONCLUSION

The objective of this study is to identify genetic etiology among pediatric patients with non-syndromic congenital heart defects. We believe that one of the challenges is to interpret the VUS and give proper genetic counselling. To further identify the genetic background of the CHDs, genome-wide analysis done in larger populations, might be more effective than targeted tests.

Ethics

Ethics Committee Approval: The study was approved by the Non-interventional Clinical Research Ethics Committee of Eskişehir Osmangazi University (decision number: 17, date: 30.12.2024).

Informed Consent: Written informed consent was obtained from legal representatives before collecting blood samples in accordance with the Declaration of Helsinki.

Authorship Contributions

Surgical and Medical Practices: T.A., E.S., B.U., S.K., Concept: S.K., B.Ö., S.A., T.A., B.U., O.Ç., Design: E.S., Supervision: E.E.G., B.D.A., Resources: B.Ö., S.A., Material: S.A., Data Collection or Processing: S.K., S.A., Analysis or Interpretation: E.E.G., Literature Search: B.D.A., S.A., Writing: T.A., E.S., Critical Review: O.Ç., B.U.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: This study was supported by Scientific Research Project Commission, Eskisehir Osmangazi University, Project No 2019-2758.

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