Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease

Current and future diagnostics of congenital heart disease (CHD)

Congenital heart defects (CHD) are one of the most common anomalies found among live births and represent a complex multifactorial condition. Given that more than 90 % of cases survive due to improved early treatment options (e.g., catheter intervention, surgical procedure, and improved intensive care), genotype-informed patient follow-up should consider lifelong treatment considering different types of comorbidities. Unfortunately, a thorough genetic workup is only offered to a minority of CHD patients. However, a comprehensive understanding of the genetic underpinnings combined with in-depth phenotyping would strengthen our knowledge regarding the impact of environmental (e.g., pre-gestational diabetes) and genetic causes ranging from aneuploidies to single variants and more complex inheritance patterns on early heart development. Therefore, comprehensive genetic analysis in these patients is an essential way of predicting the prognosis and recurrence risk in families and ultimately improving patients' quality of life due to better therapeutic options. In this review, we examine the different types of variants and genes of different molecular genetics techniques to assess the diagnostic yield in different CHD sub-phenotypes. Given the complex inheritance pattern observed in CHD, we also consider possible future methods and frameworks to improve diagnostics and allow for better genotype-phenotype correlation in this patient group. Predicting recurrence risk and prognosis in CHD patients will ultimately allow for better treatment and lifelong therapeutic outcomes for CHD patients.

Notch3 is an asymmetric gene and a modifier of heart looping defects in Nodal mouse mutants

The TGFβ secreted factor NODAL is a major left determinant required for the asymmetric morphogenesis of visceral organs, including the heart. Yet, when this signaling is absent, shape asymmetry, for example of the embryonic heart loop, is not fully abrogated, indicating that there are other factors regulating left-right patterning. Here, we used a tailored transcriptomic approach to screen for genes asymmetrically expressed in the field of heart progenitors. We thus identify Notch3 as a novel left-enriched gene and validate, by quantitative in situ hybridization, its transient asymmetry in the lateral plate mesoderm and node crown, overlapping with Nodal. In mutant embryos, we analyzed the regulatory hierarchy and demonstrate that Nodal in the lateral plate mesoderm amplifies Notch3 asymmetric expression. The function of Notch3 was uncovered in an allelic series of mutants. In single neonate mutants, we observe that Notch3 is required with partial penetrance for ventricle thickness, septation and aortic valve, in addition to its known role in coronary arteries. In compound mutants, we reveal that Notch3 acts as a genetic modifier of heart looping direction and shape defects in Nodal mutants. Whereas Notch3 was previously mainly associated with the CADASIL syndrome, our observations in the mouse and a human cohort support a novel role in congenital heart defects and laterality defects.

Sequencing in over 50,000 cases identifies coding and structural variation underlying atrial fibrillation risk

Atrial fibrillation (AF) is a prevalent and morbid abnormality of the heart rhythm with a strong genetic component. Here, we meta-analyzed genome and exome sequencing data from 36 studies that included 52,416 AF cases and 277,762 controls. In burden tests of rare coding variation, we identified novel associations between AF and the genes MYBPC3, LMNA, PKP2, FAM189A2 and KDM5B. We further identified associations between AF and rare structural variants owing to deletions in CTNNA3 and duplications of GATA4. We broadly replicated our findings in independent samples from MyCode, deCODE and UK Biobank. Finally, we found that CRISPR knockout of KDM5B in stem-cell-derived atrial cardiomyocytes led to a shortening of the action potential duration and widespread transcriptomic dysregulation of genes relevant to atrial homeostasis and conduction. Our results highlight the contribution of rare coding and structural variants to AF, including genetic links between AF and cardiomyopathies, and expand our understanding of the rare variant architecture for this common arrhythmia.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Rare homozygous cilia gene variants identified in consanguineous congenital heart disease patients

Congenital heart defects (CHD) appear in almost one percent of live births. Asian countries have the highest birth prevalence of CHD in the world. Recessive genotypes may represent a CHD risk factor in Asian populations with a high degree of consanguineous marriages. Genetic analysis of consanguineous families may represent a relatively unexplored source for investigating CHD etiology. To obtain insight into the contribution of recessive genotypes in CHD we analysed a cohort of forty-nine Pakistani CHD probands, originating from consanguineous unions. The majority (82%) of patient's malformations were septal defects. We identified protein altering, rare homozygous variants (RHVs) in the patient's coding genome by whole exome sequencing. The patients had a median of seven damaging RHVs each, and our analysis revealed a total of 758 RHVs in 693 different genes. By prioritizing these genes based on variant severity, loss-of-function intolerance and specific expression in the developing heart, we identified a set of 23 candidate disease genes. These candidate genes were significantly enriched for genes known to cause heart defects in recessive mouse models (P < 2.4e-06). In addition, we found a significant enrichment of cilia genes in both the initial set of 693 genes (P < 5.4e-04) and the 23 candidate disease genes (P < 5.2e-04). Functional investigation of ADCY6 in cell- and zebrafish-models verified its role in heart development. Our results confirm a significant role for cilia genes in recessive forms of CHD and suggest important functions of cilia genes in cardiac septation.

Machine Learning in Identifying Marker Genes for Congenital Heart Diseases of Different Cardiac Cell Types

Congenital heart disease (CHD) represents a spectrum of inborn heart defects influenced by genetic and environmental factors. This study advances the field by analyzing gene expression profiles in 21,034 cardiac fibroblasts, 73,296 cardiomyocytes, and 35,673 endothelial cells, utilizing single-cell level analysis and machine learning techniques. Six CHD conditions: dilated cardiomyopathy (DCM), donor hearts (used as healthy controls), hypertrophic cardiomyopathy (HCM), heart failure with hypoplastic left heart syndrome (HF_HLHS), Neonatal Hypoplastic Left Heart Syndrome (Neo_HLHS), and Tetralogy of Fallot (TOF), were investigated for each cardiac cell type. Each cell sample was represented by 29,266 gene features. These features were first analyzed by six feature-ranking algorithms, resulting in several feature lists. Then, these lists were fed into incremental feature selection, containing two classification algorithms, to extract essential gene features and classification rules and build efficient classifiers. The identified essential genes can be potential CHD markers in different cardiac cell types. For instance, the LASSO identified key genes specific to various heart cell types in CHD subtypes. FOXO3 was found to be up-regulated in cardiac fibroblasts for both Dilated and hypertrophic cardiomyopathy. In cardiomyocytes, distinct genes such as TMTC1, ART3, ARHGAP24, SHROOM3, and XIST were linked to dilated cardiomyopathy, Neo-Hypoplastic Left Heart Syndrome, hypertrophic cardiomyopathy, HF-Hypoplastic Left Heart Syndrome, and Tetralogy of Fallot, respectively. Endothelial cell analysis further revealed COL25A1, NFIB, and KLF7 as significant genes for dilated cardiomyopathy, hypertrophic cardiomyopathy, and Tetralogy of Fallot. LightGBM, Catboost, MCFS, RF, and XGBoost further delineated key genes for specific CHD subtypes, demonstrating the efficacy of machine learning in identifying CHD-specific genes. Additionally, this study developed quantitative rules for representing the gene expression patterns related to CHDs. This research underscores the potential of machine learning in unraveling the molecular complexities of CHD and establishes a foundation for future mechanism-based studies.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Discovery of BMP10 as a new gene underpinning congenital heart defects

OBJECTIVE

Aggregating evidence convincingly establishes the predominant genetic basis underlying congenital heart defects (CHD), though the heritable determinants contributing to CHD in the majority of cases remain elusive. In the current investigation, BMP10 was selected as a prime candidate gene for human CHD mainly due to cardiovascular developmental abnormalities in Bmp10-knockout animals. The objective of this retrospective study was to identify a new BMP10 mutation responsible for CHD and characterize the functional effect of the identified CHD-causing BMP10 mutation.

METHODS

Sequencing assay of BMP10 was fulfilled in a cohort of 276 probands with various CHD and a total of 288 non-CHD volunteers. The available family members from the proband harboring an identified BMP10 mutation were also BMP10-genotyped. The effect of the identified CHD-causative BMP10 mutation on the transactivation of TBX20 and NKX2.5 by BMP10 was quantitatively analyzed in maintained HeLa cells utilizing a dual-luciferase reporter assay system.

RESULTS

A novel heterozygous BMP10 mutation, NM_014482.3:c.247G>T;p.(Glu83*), was identified in one proband with patent ductus arteriosus (PDA), which was confirmed to co-segregate with the PDA phenotype in the mutation carrier's family. The nonsense mutation was not observed in 288 non-CHD volunteers. Functional analysis unveiled that Glu83*-mutant BMP10 had no transactivation on its two representative target genes TBX20 and NKX2.5, which were both reported to cause CHD.

CONCLUSION

These findings provide strong evidence indicating that genetically compromised BMP10 predisposes human beings to CHD, which sheds light on the new molecular mechanism that underlies CHD and allows for antenatal genetic counseling and individualized precise management of CHD.

Human Genetics of Congenital Heart Defects

Congenital heart diseases (or congenital heart defects/disorders; CHDs) are structural abnormalities of the heart and/or great vessels that are present at birth. CHDs include an extensive range of defects that may be minor and require no intervention or may be life-limiting and require complex surgery shortly after birth. This chapter reviews the current knowledge on the genetic causes of CHD.

The implication of chromosomal abnormalities in the surgical outcomes of Chinese pediatric patients with congenital heart disease

Background

Copy number variations (CNVs) have been shown to be overrepresented in children with congenital heart disease (CHD). Genetic evaluation of CHD is currently underperformed in China. We sought to determine the occurrence of CNVs in CNV regions with disease-causing potential among a large cohort of Chinese pediatric CHD patients and investigate whether these CNVs could be the important critical modifiers of surgical intervention.

Methods

CNVs screenings were performed in 1,762 Chinese children who underwent at least one cardiac surgery. CNV status at over 200 CNV locus with disease-causing potential was analyzed with a high-throughput ligation-dependent probe amplification (HLPA) assay.

Results

We found 378 out of 1,762 samples (21.45%) to have at least one CNV and 2.38% of them were carrying multiple CNVs. The detection rates of ppCNVs (pathogenic and likely pathogenic CNVs) were 9.19% (162/1,762), significantly higher than that of the healthy Han Chinese individuals from The Database of Genomic Variants archive (9.19% vs. 3.63%; P = 0.0012). CHD cases with ppCNVs had a significantly higher proportion of complex surgeries compared to CHD patients with no ppCNVs (62.35% vs. 37.63%, P < 0.001). Duration of cardiopulmonary bypass and aortic cross clamp procedures were significantly longer in CHD cases with ppCNVs (all P < 0.05), while no group differences were identified for complications of surgery and one-month mortality after surgery. The detection rate of ppCNVs in the atrioventricular septal defect (AVSD) subgroup was significantly higher than that in other subgroups (23.10% vs. 9.70%, P = 0.002).

Conclusions

CNV burden is an important contributor to Chinese children with CHD. Our study demonstrated the robustness and diagnostic efficiency of HLPA method in the genetic screening of CNVs in CHD patients.

Structural genomic variants in thoracic aortic disease

PURPOSE OF REVIEW

Structural genomic variants have emerged as a relevant cause for several disorders, including intellectual disability, neuropsychiatric disorders, cancer and congenital heart disease. In this review, we will discuss the current knowledge about the involvement of structural genomic variants and, in particular, copy number variants in the development of thoracic aortic and aortic valve disease.

RECENT FINDINGS

There is a growing interest in the identification of structural variants in aortopathy. Copy number variants identified in thoracic aortic aneurysms and dissections, bicuspid aortic valve related aortopathy, Williams-Beuren syndrome and Turner syndrome are discussed in detail. Most recently, the first inversion disrupting FBN1 has been reported as a cause for Marfan syndrome.

SUMMARY

During the past 15 years, the knowledge on the role of copy number variants as a cause for aortopathy has grown significantly, which is partially due to the development of novel technologies including next-generation sequencing. Although copy number variants are now often investigated on a routine basis in diagnostic laboratories, more complex structural variants such as inversions, which require the use of whole genome sequencing, are still relatively new to the field of thoracic aortic and aortic valve disease.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Systems analysis of de novo mutations in congenital heart diseases identified a protein network in the hypoplastic left heart syndrome

Despite a strong genetic component, only a few genes have been identified in congenital heart diseases (CHDs). We introduced systems analyses to uncover the hidden organization on biological networks of mutations in CHDs and leveraged network analysis to integrate the protein interactome, patient exomes, and single-cell transcriptomes of the developing heart. We identified a CHD network regulating heart development and observed that a sub-network also regulates fetal brain development, thereby providing mechanistic insights into the clinical comorbidities between CHDs and neurodevelopmental conditions. At a small scale, we experimentally verified uncharacterized cardiac functions of several proteins. At a global scale, our study revealed developmental dynamics of the network and observed its association with the hypoplastic left heart syndrome (HLHS), which was further supported by the dysregulation of the network in HLHS endothelial cells. Overall, our work identified previously uncharacterized CHD factors and provided a generalizable framework applicable to studying many other complex diseases. A record of this paper's Transparent Peer Review process is included in the supplemental information.

Network assisted analysis of de novo variants using protein-protein interaction information identified 46 candidate genes for congenital heart disease

De novo variants (DNVs) with deleterious effects have proved informative in identifying risk genes for early-onset diseases such as congenital heart disease (CHD). A number of statistical methods have been proposed for family-based studies or case/control studies to identify risk genes by screening genes with more DNVs than expected by chance in Whole Exome Sequencing (WES) studies. However, the statistical power is still limited for cohorts with thousands of subjects. Under the hypothesis that connected genes in protein-protein interaction (PPI) networks are more likely to share similar disease association status, we developed a Markov Random Field model that can leverage information from publicly available PPI databases to increase power in identifying risk genes. We identified 46 candidate genes with at least 1 DNV in the CHD study cohort, including 18 known human CHD genes and 35 highly expressed genes in mouse developing heart. Our results may shed new insight on the shared protein functionality among risk genes for CHD.

The topologic information in a pathway may be informative to identify functionally interrelated genes and help improve statistical power in DNV studies. Under the hypothesis that connected genes in PPI networks are more likely to share similar disease association status, we developed a novel statistical model that can leverage information from publicly available PPI databases. Through simulation studies under multiple settings, we proved our method can increase statistical power in identifying additional risk genes compared to methods without using the PPI network information. We then applied our method to a real example for CHD DNV data, and then visualized the subnetwork of candidate genes to find potential functional gene clusters for CHD.

Correction: Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease

[This corrects the article DOI: 10.1371/journal.pgen.1009679.].