Genetic Analysis Strategy for Diagnosing Congenital Heart Disease

Abstract

Introduction

Congenital heart defects (CHD) affect approximately 10–12 per 1,000 newborns globally, and they can be divided into simple cardiac defects or severe and complex ones. Its etiology derives from environmental and genetic causes, with 20–30% of cases being genetic conditions ranging from alterations such as aneuploidies, monogenic defects, and copy number variations (CNVs). Even with the severity of this condition, many patients remain with an uncertain diagnosis. This study aimed to evaluate patients with CHD who are still undiagnosed but have already undergone genetic testing and evaluation and provide a guideline that can be followed in third-world countries to make CHD diagnostics faster and easier.

Method

DNA was extracted from all patients included; first the samples were analyzed with the P311 multiplex ligation-dependent probe amplification (MLPA) kit specific to CHD, and the patients that remain undiagnostic were analyzed with the P245 MLPA kit for microdeletions.

Results

CNVs were identified in 36% of the patients, representing a high detection rate.

Conclusion

The patient selection and prior clinical evaluation may explain our high detection rate, as much as the karyotype and fluorescent in situ hybridization normal results used for screening, combined with using two MLPA kits for detection.

Introduction

Congenital heart defects (CHD) are the most prevalent congenital malformations, affecting 1% of all live births and requiring surgical intervention in the first year of life [1, 2]. According to a Canadian study, 13.1 per 1,000 live births and 6 per 1,000 adults present some anomaly in the heart or large vessels. Despite these expressive numbers, the research group states that most patients with heart diseases are still underdiagnosed [3]. This condition can be divided into simple defects that have a more favorable prognosis, including atrial septal defect (such as interatrial communication [IAC]), ventricular septal defects (such as interventricular communication [IVC]), patent ductus arteriosus (PDA), pulmonary stenosis, and patent foramen ovale. Other cases are severe and complex, such as tetralogy of fallot (TOF), univentricular heart, and hypoplastic left heart syndrome. These alterations require multiple surgical corrections and have an uncertain prognosis in the long term [4].

CHD is a complex and multifactorial condition with an uncertain etiology that can have an environmental or genetic cause, with the last being 20–30% of the cases. The first genetic abnormalities associated with CHD were aneuploidies (8–10%), especially Down, Edwards, and Patau Syndrome, followed by monogenic defects (3–5%) and copy number variations (CNVs) (3–25%) [5]. Conventional cytogenetics techniques are the gold standard method to detect aneuploidies, and the fluorescent in situ hybridization (FISH) is a resourceful method for the detection of the most common microdeletion syndromes associated with CHD, such as 22q11.2 microdeletion, William’s syndrome (7q11 deletion), and 8p23.1 deletion syndrome, as examples [6–8]. When a karyotype analysis is performed after a clinical evaluation of the CHD, it can discard approximately 10% of the cases due to aneuploidies diagnostics, in the case of a normal result, performing a FISH analysis for the investigation of 22q11.2 microdeletion syndrome can diagnose the patients in a range between 48.5%, 64%, and 79% overall, respectively, according to the literature, due to the high incidence of CHD in this syndrome [9–12]. Diniz et al. [11] have already suggested using different cytogenetics techniques depending on the individuality of each case studied, to diagnose patients with CHD.

In Brazil, the unified health system (UHS) offers every Brazilian citizen full, universal, and free access to health services. Considered one of the largest and best public health systems in the world, it was only in 2014 that the UHS instituted financial incentives for applying molecular methodologies to diagnose patients suspected of having a genetic condition (Ordinance No. 981, of May 21, 2014: https://bvsms.saude.gov.br/bvs/saudelegis/gm/2014/prt0981_21_05_2014.html). However, this system does not routinely provide molecular genetic tests due to higher costs. Thus, research studies are essential to help diagnose patients who need molecular investigation [13]. Studies have been performed to correlate CNVs with CHD [14], mainly using multiplex ligation-dependent probe amplification (MLPA), an affordable, fast, and easy molecular cytogenetic technique for screening CNVs in patients with CHD, malformations, and other clinical conditions [14, 15]. Therefore, this study aimed to evaluate patients with cases of congenital heart defects that are still undiagnosed but have already undergone genetic testing and evaluation and provide guidelines that can be followed in third-world countries to make CHD diagnostics faster and easier.

Methods

This study evaluated patients with congenital heart disease, with or without extracardiac malformations, from the Hospital da Criança Santo Antônio (HCSA), Porto Alegre, RS, Brazil. The Clinical Genetics Service conducted genetic testing at the cytogenetics laboratory at the Federal University of Health Sciences of Porto Alegre (UFCSPA). The inclusion criteria for the patients were an evaluation by the clinical geneticist and cardiologist to characterize the CHD, which could be isolated or with other extracardiac malformations; the patient also needed to have undergone karyotyping and FISH for 22q11.23 microdeletion syndrome with the LSI TUPLE1 probe (Vysis, Abbott Molecular, USA), and obtained normal results.

Then, after being included in this study, patients were tested with the SALSA MLPA Probemix P311 Congenital Heart Disease kit (MRC-Holland, Amsterdam, The Netherlands) and the ones that continued undiagnosed also underwent testing with the SALSA MLPA Probemix P245 Microdeletion Syndromes-1A kit (MRC-Holland). Genomic DNA extraction was performed using the laboratory’s standard protocol, and DNA was quantified and evaluated using a BioSpec-nano (Shimadzu, San Jose, CA, USA). The MLPA assay was performed according to the manufacturer’s protocol. MLPA products were run on SeqStudio Genetic Analyzer (Thermo Fisher Scientific) and analyzed with Coffalyser software (MRC-Holland), which normalized the signals from all the probes. The samples were compared with reference samples, and two normal controls were used [16].

Results

A total of 36 patients were first evaluated regarding their CHD, the majority of patients were between 3 and 5 years old (75% of the sample), followed by 2 or fewer years (17%) and only 8% were between 6 and 11 years old. Severe CHD was observed in 35% of patients, TOF being the main abnormality shown. The remaining 65% presented with simpler defects, the most prevalent being IVC (37%), followed by IAC (27%), PDA (21%), and patent foramen ovale (18%). In the MLPA analysis using the SALSA MLPA Probemix P311 Congenital Heart Disease kit, deletions and duplications were identified in 22% of the patients. The remaining samples were analyzed using the SALSA MLPA Probemix P245 Microdeletion Syndromes-1A kit, where abnormalities were found in 18%, totaling a 36% detection rate in this sample group. All these clinical findings and the molecular alterations are shown in Table 1.

Table 1.

Clinical and genetic findings

Patient	CHD	MLPA Kit P311	MLPA Kit P245
1	PS	rsa 22q11.21(CDC45, GP1BB, DGCR8)x3	–
2	HLHS + IVC	rsa (P311)x2	rsa 7q11.23(ELN)x1
3	PDA	rsa (P311)x2	rsa (P245)x2
4	TOF+ FOA + IVC	rsa (P311)x2	rsa (P245)x2
5	IAC+ ASD + PDA	rsa 8p23.1(GATA4)x1	–
6	FOA + IVC + PS	rsa (P311)x2	rsa (P245)x2
7	IVC	rsa 8p23.1(GATA4)x3	–
8	TOF + IAC	rsa 8p23.1(GATA4)x1	–
9	TOF	rsa (P311)x2	rsa (P245)x2
10	HLHS	rsa (P311)x2	rsa (P245)x2
11	TOF	rsa (P311)x2	rsa 1p36.33(TNFRSFA)x1, 16p13.3(CREBBP)x1, 22q11.21(GP1BB)x1, 22q13.33(SHANK3)x1
12	FOA + IVC + PDA	rsa (P311)x2	rsa (P245)x2
13	FOA + IVC + PDA	rsa (P311)x2	rsa (P245)x2
14	DAA	rsa (P311)x2	rsa (P245)x2
15	IVC + IAC	rsa (P311)x2	rsa (P245)x2
16	IVC + PDA + IAC + FOA	rsa 14q13.3(NKX2)x3	–
17	IAC + IVC	rsa (P311)x2	rsa 17p13.3(PAFAH1B1)x3
18	IVC + IAC + FOA	rsa 8p23.1(GATA4)x1	–
19	PDA + PS	rsa (P311)x2	rsa (P245)x2
20	TOF + IAC + FOA + IVC	rsa (P311)x2	rsa (P245)x2
21	PS + PDA + IAC + FOA	rsa (P311)x2	rsa (P245)x2
22	IAC	rsa (P311)x2	rsa (P245)x2
23	IVC	rsa (P311)x2	rsa 17q11.2(NF1)x1
24	IVC + IAC	rsa (P311)x2	rsa 5p15.33(TERT)x1
25	TOF + FOA + IVC	rsa (P311)x2	rsa (P245)x2
26	TOF	rsa (P311)x2	rsa (P245)x2
27	PS	rsa (P311)x2	rsa (P245)x2
28	IVC	rsa 8p23.1(GATA4)x1	–
29	TOF + FOA	rsa (P311)x2	rsa (P245)x2
30	TOF + IVC + FOA	rsa (P311)x2	rsa (P245)x2
31	TOF + IVC	rsa (P311)x2	rsa (P245)x2
32	IAC + IVC + PDA	rsa (P311)x2	rsa (P245)x2
33	IVC + FOA + PS	rsa (P311)x2	rsa (P245)x2
34	IVC + PDA	rsa (P311)x2	rsa (P245)x2
35	TOF	rsa 8p23.1(GATA4)x1	–
36	NMC	rsa (P311)x2	rsa (P245)x2

MLPA nomenclature according to the International System for Human Cytogenomic Nomenclature (ISCN), 2024 version [17]. NMC, noncompaction cardiomyopathy; DAA, double aortic arch; ASD, atrial septal defect; PS, pulmonary stenosis; FOA, patent foramen ovale; HLHS, hypoplastic left heart syndrome.

GATA4 was the most affected gene, located on chromosome 8p23.1 and part of the 8p23.1 microdeletion syndrome, presenting 3 deletions in exon 1, 2 deletions in exon 6, and 1 duplication in exon 1. Patient number 1 presented with duplication in the CDC45, GP1BB, and DGCR8 genes on chromosome 22q11.21; patient number 16 had duplication in the 5 exons of the NKX2 gene on chromosome 14q13.3. Using P245 MLPA kit, patient 2 presented a deletion of the ELN gene on chromosome 7q11.23, patient 11 had a deletion in the TNFRSF4 gene on chromosome 1p36.33, CREBBP gene on chromosome 16p13.3, GP1BB gene on chromosome 22q11.21, and SHANK3 genes on chromosome 22q13.33; patient 17 had duplication in PAFAH1B1 on chromosome 17p13.3; patient 23 presented NF1 deletion on chromosome 17q11.2; and lastly patient 24 had a TERT gene deletion on chromosome 5p15.33. The MLPA results are in online supplementary Figure S1 (for all online suppl. material, see https://doi.org/10.1159/000547412).

In this cohort of 36 patients with CHD, some genotype-phenotype correlations were observed. Notably, CNVs involving the 8p23.1 region, encompassing the GATA4 gene, were detected in 6 patients (patients 5, 7, 8, 18, 28, and 35). These patients predominantly presented with septal defects, such as atrial septal defect, IAC, and IVC, as well as PDA and TOF. Overall, the most recurrent and consistent genetic findings were GATA4 alterations at 8p23.1, associated with septal defects and conotruncal malformations, and 22q11.2 deletions, linked to conotruncal anomalies.

Discussion

CHD is still the most common birth defect, with high mortality and morbidity, and even so, the etiology of most patients remains unclear [3]. This congenital alteration can be caused by genetic factors in 20% of the cases, most commonly due to aneuploidies, monogenic defects, and/or CNVs [5]. Even with the high prevalence, mortality, and morbidity of this condition, some patients remain with CHD of uncertain origin because of the challenges in diagnosing these patients due to the lack of well-established guidelines. In Brazil, for example, the “guidelines for comprehensive care for people with rare diseases in the UHS,” which cover congenital malformations, including CHDs, only determine that genetic counseling should be carried out for multiple anomalies. Furthermore, they only describe “laboratory tests for the investigation of congenital anomalies” but do not specify or indicate which tests or even the correlation between them [18]. Rachamadugu et al. [19], from the Johns Hopkins Genomics, implemented a guideline for syndromic and non-syndromic CHD diagnostics. However, this guideline is more oriented and outlined, but most of the suggested exams are not disposable in third-world countries’ laboratories or healthcare systems.

Glaeser et al. [20] reported in their study the difference in prices for a molecular test between the USA and Brazil. Although there are tests that will provide abundant results in less time, when compared to FISH or MLPA, for example, the financial unfeasibility of countries like Brazil prevents many patients from being diagnosed. Thus, in this study, we suggest a guideline to diagnose syndromic CHD cases in third-world countries with limited resources. Through our analysis strategy, this study was able to identify CNVs in 36% of the patients, whereas 22% were detected using SALSA MLPA Probemix P311 Congenital Heart Disease kit and 18% using the SALSA MLPA Probemix P245 Microdeletion Syndromes-1A kit, this diagnostics rate is considered high, as most studies published in the literature normally detect CNVs in 3.1% [15], 3.4% [16], 4.76% [21], and 15.2% of the patients, using MLPA technique [22].

With the proposed methodology, CNVs were detected in 13 different genes, with GATA4 being the most observed (6 affected patients). In addition, deletions were more common than duplications in this sample, and most of the altered genes were transcription factors associated with and highly expressed in cardiac development. The haploinsufficiency of transcription factors has been described to result in cardiac malformations. This is explained because all transcription factors act together to regulate cardiac septum development [23]. This explains why transcription factor genes, such as NKX2 and GATA4, or even the CREBBP that regulates a variety of transcription factor activities, are commonly seen as altered in patients with CHD.

The remaining CNVs detected were related to some well-established syndromes, like 22q11.2 microdeletion, 1p36 deletion syndrome, Williams-Beuren, Miller-Dieker, Watson syndrome, or cri du chat [24–28]. All these syndromes contain some cardiac or great vessel abnormality, which explains the finding of these CNVs in a sample of patients with CHD. The studies used to compare the detection rate did not find as many CNVs as in this study. Most of their patients presented with 22q11.2 microdeletion syndrome [15, 16, 21, 22]. Sørensen, et al. [15] also found CNVs on chromosomes 2, 5, 8, and 17; Floriani et al. [16] found a deletion in gene GATA4 in 8p23.1 microdeletion syndrome; Stefekova et al. [22] also found a deletion in the 8p23.1 microdeletion syndrome and a deletion in the 9q34.3 region. The results found in this article reflect the use of other cytogenetics analysis prior to MLPA for eliminating possible aneuploidies and 22q11.2 microdeletion syndrome, which was the most identified syndrome in other studies and that can be diagnosed using the FISH technique; this led to a more heterogeneous result in the MLPA analysis, identifying different syndromes.

The patient selection and prior clinical evaluation may explain our high detection rate, as much as the Karyotype and FISH normal results used for screening, combined with using two MLPA kits for detection. Precise determination of etiology through diagnostics has important implications in genetic counseling and patient treatment. The appropriate usage of genetic techniques and methodologies is important for syndrome detection and diagnostics, and the MLPA technique may be used as a powerful diagnostics tool for the detection of relevant CNVs in CHD patients still undiagnosed [16, 22, 29]. A well-established and oriented guideline that any healthcare professional can follow in any healthcare system to aim for faster and reliable CHD diagnostics is essential to clarify the still complicated etiology involving CHD, more importantly, because most patients with heart diseases are still underdiagnosed [30].

Conclusion

The present study analyzed 36 patients presenting CHD, which had already undergone clinical genetics evaluation and cytogenetics tests, such as karyotype and FISH analyses for 22q11.2 microdeletion syndrome but remained undiagnosed. In this study, we were able to diagnose 36% of the patients included, obtaining a higher detection rate than prior studies. This may be explained by the methodology applied that combined a previous screening performed with karyotype and FISH, which had already eliminated the most common genetic causes of CHD, with two different MLPA kits specific to CHD detection and the most common microdeletion syndromes reported. Considering the lack of guidelines to follow for the diagnosis and detection of CNVs in CHD patients, the high detection rate obtained from our proposed methodology and that not all molecular cytogenetics tests are fully available in every country, we proposed that the analysis strategy applied in this article could be raised into a guideline to the diagnosed of CHD patients. The workflow is represented in Figure 1.

Fig. 1.

Guideline for CHD diagnostic workflow. Workflow on how to implement the suggested guideline for CHD diagnostics. Image was produced by the authors.

The research group highly recommends continuous evaluation of these patients, with clinical assessment and genetics analysis using more advanced technologies such as exome, CGH-array, or even optical genome mapping (OGM) if any of these technologies become available in the future for the public healthcare system in Brazil.

Acknowledgment

The authors would like to thank all the patients and families that agreed to participate in this study.

Statement of Ethics

The ethical approval statement for this study was obtained from the Ethics Committee of the Federal University of Health Sciences of Porto Alegre (UFCSPA), Possessing No. 5.418.036, and from the Research Committee at the dean of research and postgraduate studies at UFCSPA, with Project No. 154/2022, which allows collecting samples and data from patients and medical reports. Written informed consent was obtained from participants prior to the study, and they can be obtained upon reasonable request from the author.

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Funding Sources

This work was funded by the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS; 17/2551-0,001,063-9). This grant was used to purchase the MLPA kits used in this study.

Author Contributions

Concept and design of the article, analysis, and writing – review and editing: Natasha Malgarezi de Moraes and Bruna Lixinski Diniz. Data acquisition: Ana Kalise Böttcher, Natasha Malgarezi de Moraes, and Rafaella Mergener. Clinical case report: Marcela Rodrigues Nunes and Natasha Malgarezi de Moraes. Original draft preparation: Natasha Malgarezi de Moraes, Bruna Lixinski Diniz, Marcela Rodrigues Nunes, Rafaella Mergener, Ana Kalise Böttcher da Silveira, and Paulo Ricardo Gazzola Zen. Supervision: Paulo Ricardo Gazzola Zen.

Funding Statement

This work was funded by the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS; 17/2551-0,001,063-9). This grant was used to purchase the MLPA kits used in this study.

Data Availability Statement

The data supporting this study’s findings are available from the corresponding author upon reasonable request.