De novo and recessive forms of congenital heart disease have distinct genetic and phenotypic landscapes

Explainable artificial intelligence for stroke risk stratification in atrial fibrillation

Current risk stratification tools can limit the optimal implementation of new and emerging therapies for patients with heart rhythm disorders. For example, stroke prevention treatments have outpaced means for stroke risk stratification for patients with atrial fibrillation (AF). Artificial intelligence (AI) techniques have shown promise for improving various tasks in cardiovascular medicine. Here, we explain key concepts in AI that are central to using these technologies for better risk stratification, highlighting one approach particularly well suited to the task of portable, personalized risk stratification-probabilistic graphical models (PGMs). Probabilistic graphical models can empower physicians to ask and answer a variety of clinical questions, which we demonstrate using a preliminary model of AF-related stroke risk among 1.6 million patients within the University of Utah Health System. This example also highlights the ability of PGMs to combine social determinants of health and other non-traditional variables with standard clinical and demographic ones to improve personalized risk predictions and address risk factor interactions. When combined with electronic health data, these computational technologies hold great promise to empower personalized, explainable, and equitable risk assessment.

Molecular genetics of congenital heart disease

Congenital heart disease (CHD) is the most prevalent human birth defect and remains a leading cause of mortality in childhood. Although advancements in surgical and medical interventions have significantly reduced mortality rates among infants with critical CHDs, many survivors experience substantial cardiac and extracardiac comorbidities that affect their quality of life. The etiology of CHD is multifactorial, involving both genetic and environmental factors, yet a definitive cause remains unidentified in many cases. Recent advancements in genetic testing technologies have improved our ability to identify the genetic causes of CHD. This review presents an updated summary of the established genetic contributions to CHD, including chromosomal aberrations and mutations in genes associated with transcription factors, cardiac structural proteins, chromatin modifiers, cilia-related proteins, and cell signaling pathways. Furthermore, we discuss recent findings that support the roles of non-coding mutations and complex inheritance in the etiology of CHD.

Recessive genetic contribution to congenital heart disease in 5,424 probands

Variants with large effect contribute to congenital heart disease (CHD). To date, recessive genotypes (RGs) have commonly been implicated through anecdotal ascertainment of consanguineous families and candidate gene-based analysis; the recessive contribution to the broad range of CHD phenotypes has been limited. We analyzed whole exome sequences of 5,424 CHD probands. Rare damaging RGs were estimated to contribute to at least 2.2% of CHD, with greater enrichment among laterality phenotypes (5.4%) versus other subsets (1.4%). Among 108 curated human recessive CHD genes, there were 66 RGs, with 54 in 11 genes with >1 RG, 12 genes with 1 RG, and 85 genes with zero. RGs were more prevalent among offspring of consanguineous union (4.7%, 32/675) than among nonconsanguineous probands (0.7%, 34/4749). Founder variants in GDF1 and PLD1 accounted for 74% of the contribution of RGs among 410 Ashkenazi Jewish probands. We identified genome-wide significant enrichment of RGs in C1orf127, encoding a likely secreted protein expressed in embryonic mouse notochord and associated with laterality defects. Single-cell transcriptomes from gastrulation-stage mouse embryos revealed enrichment of RGs in genes highly expressed in the cardiomyocyte lineage, including contractility-related genes MYH6, UNC45B, MYO18B, and MYBPC3 in probands with left-sided CHD, consistent with abnormal contractile function contributing to these malformations. Genes with significant RG burden account for 1.3% of probands, more than half the inferred total. These results reveal the recessive contribution to CHD, and indicate that many genes remain to be discovered, with each likely accounting for a very small fraction of the total.

Epigene functional diversity: isoform usage, disordered domain content, and variable binding partners

BACKGROUND

Epigenes are defined as proteins that perform post-translational modification of histones or DNA, reading of post-translational modifications, form complexes with epigenetic factors or changing the general structure of chromatin. This specialized group of proteins is responsible for controlling the organization of genomic DNA in a cell-type specific fashion, controlling normal development in a spatial and temporal fashion. Moreover, mutations in epigenes have been implicated as causal in germline pediatric disorders and as driver mutations in cancer. Despite their importance to human disease, to date, there has not been a systematic analysis of the sources of functional diversity for epigenes at large. Epigenes' unique functions that require the assembly of pools within the nucleus suggest that their structure and amino acid composition would have been enriched for features that enable efficient assembly of chromatin and DNA for transcription, splicing, and post-translational modifications.

RESULTS

In this study, we assess the functional diversity stemming from gene structure, isoforms, protein domains, and multiprotein complex formation that drive the functions of established epigenes. We found that there are specific structural features that enable epigenes to perform their variable roles depending on the cellular and environmental context. First, epigenes are significantly larger and have more exons compared with non-epigenes which contributes to increased isoform diversity. Second epigenes participate in more multimeric complexes than non-epigenes. Thirdly, given their proposed importance in membraneless organelles, we show epigenes are enriched for substantially larger intrinsically disordered regions (IDRs). Additionally, we assessed the specificity of their expression profiles and showed epigenes are more ubiquitously expressed consistent with their enrichment in pediatric syndromes with intellectual disability, multiorgan dysfunction, and developmental delay. Finally, in the L1000 dataset, we identify drugs that can potentially be used to modulate expression of these genes.

CONCLUSIONS

Here we identify significant differences in isoform usage, disordered domain content, and variable binding partners between human epigenes and non-epigenes using various functional genomics datasets from Ensembl, ENCODE, GTEx, HPO, LINCS L1000, and BrainSpan. Our results contribute new knowledge to the growing field focused on developing targeted therapies for diseases caused by epigene mutations, such as chromatinopathies and cancers.

AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios

BACKGROUND

Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.

METHODS

Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not. We also sought to identify context-specific risk relationships among inter-related variables in FGR. Performance was assessed as area under the receiver-operating characteristics curve (AUC).

RESULTS

Feature selection identified the 16 most informative variables, which yielded a PGM with good overall performance in the validation cohort (AUC 0.83, 95% CI 0.79-0.87), including among "N of 1" unique scenarios (AUC 0.81, 0.72-0.90). Using the PGM, we identified FGR scenarios with a risk of perinatal morbidity no different from that of the cohort background (e.g. female fetus, estimated fetal weight (EFW) 3-9th percentile, no preexisting diabetes, no progesterone use; RR 0.9, 95% CI 0.7-1.1) alongside others that conferred a nearly 10-fold higher risk (female fetus, EFW 3-9th percentile, maternal preexisting diabetes, progesterone use; RR 9.8, 7.5-11.6). This led to the recognition of a PGM-identified latent interaction of fetal sex with preexisting diabetes, wherein the typical protective effect of female fetal sex was reversed in the presence of maternal diabetes.

CONCLUSIONS

PGMs are able to capture and quantify context-specific risk relationships in FGR and identify latent variable interactions that are associated with large differences in risk. FGR scenarios that are separated by nearly 10-fold perinatal morbidity risk would be managed similarly under current FGR clinical guidelines, highlighting the need for more precise approaches to risk estimation in FGR.

AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios

Background

Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.

Methods

Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not. We also sought to identify context-specific risk relationships among inter-related variables in FGR. Performance was assessed as area under the receiver-operating characteristics curve (AUC).

Results

Feature selection identified the 16 most informative variables, which yielded a PGM with good overall performance in the validation cohort (AUC 0.83, 95% CI 0.79-0.87), including among "N of 1" unique scenarios (AUC 0.81, 0.72-0.90). Using the PGM, we identified FGR scenarios with a risk of perinatal morbidity no different from that of the cohort background (e.g. female fetus, estimated fetal weight (EFW) 3-9th percentile, no preexisting diabetes, no progesterone use; RR 0.9, 95% CI 0.7-1.1) alongside others that conferred a nearly 10-fold higher risk (female fetus, EFW 3-9th percentile, maternal preexisting diabetes, progesterone use; RR 9.8, 7.5-11.6). This led to the recognition of a PGM-identified latent interaction of fetal sex with preexisting diabetes, wherein the typical protective effect of female fetal sex was reversed in the presence of maternal diabetes.

Conclusions

PGMs are able to capture and quantify context-specific risk relationships in FGR and identify latent variable interactions that are associated with large differences in risk. FGR scenarios that are separated by nearly 10-fold perinatal morbidity risk would be managed similarly under current FGR clinical guidelines, highlighting the need for more precise approaches to risk estimation in FGR.

Genome Sequencing is Critical for Forecasting Outcomes Following Congenital Cardiac Surgery

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we used artificial intelligence (AI) technologies to explore the predictive value of genome sequencing in forecasting clinical outcomes following surgery for congenital heart defects (CHD). We report results for a cohort of 2,253 CHD patients from the Pediatric Cardiac Genomics Consortium with a broad range of complex heart defects, pre- and post-operative clinical variables and exome sequencing. Damaging genotypes in chromatin-modifying and cilia-related genes were associated with an elevated risk of adverse post-operative outcomes, including mortality, cardiac arrest and prolonged mechanical ventilation. The impact of damaging genotypes was further amplified in the context of specific CHD phenotypes, surgical complexity and extra-cardiac anomalies. The absence of a damaging genotype in chromatin-modifying and cilia-related genes was also informative, reducing the risk for adverse postoperative outcomes. Thus, genome sequencing enriches the ability to forecast outcomes following congenital cardiac surgery.

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.

ENU-based dominant genetic screen identifies contractile and neuronal gene mutations in congenital heart disease

BACKGROUND

Congenital heart disease (CHD) is the most prevalent congenital anomaly, but its underlying causes are still not fully understood. It is believed that multiple rare genetic mutations may contribute to the development of CHD.

METHODS

In this study, we aimed to identify novel genetic risk factors for CHD using an ENU-based dominant genetic screen in mice. We analyzed fetuses with malformed hearts and compared them to control littermates by whole exome or whole genome sequencing (WES/WGS). The differences in mutation rates between observed and expected values were tested using the Poisson and Binomial distribution. Additionally, we compared WES data from human CHD probands obtained from the Pediatric Cardiac Genomics Consortium with control subjects from the 1000 Genomes Project using Fisher's exact test to evaluate the burden of rare inherited damaging mutations in patients.

RESULTS

By screening 10,285 fetuses, we identified 1109 cases with various heart defects, with ventricular septal defects and bicuspid aortic valves being the most common types. WES/WGS analysis of 598 cases and 532 control littermates revealed a higher number of ENU-induced damaging mutations in cases compared to controls. GO term and KEGG pathway enrichment analysis showed that pathways related to cardiac contraction and neuronal development and functions were enriched in cases. Further analysis of 1457 human CHD probands and 2675 control subjects also revealed an enrichment of genes associated with muscle and nervous system development in patients. By combining the mice and human data, we identified a list of 101 candidate digenic genesets, from which each geneset was co-mutated in at least one mouse and two human probands with CHD but not in control mouse and control human subjects.

CONCLUSIONS

Our findings suggest that gene mutations affecting early hemodynamic perturbations in the developing heart may play a significant role as a genetic risk factor for CHD. Further validation of the candidate gene set identified in this study could enhance our understanding of the complex genetics underlying CHD and potentially lead to the development of new diagnostic and therapeutic approaches.

The Role of Cilia and the Complex Genetics of Congenital Heart Disease

Congenital heart disease (CHD) can affect up to 1% of live births, and despite abundant evidence of a genetic etiology, the genetic landscape of CHD is still not well understood. A large-scale mouse chemical mutagenesis screen for mutations causing CHD yielded a preponderance of cilia-related genes, pointing to a central role for cilia in CHD pathogenesis. The genes uncovered by the screen included genes that regulate ciliogenesis and cilia-transduced cell signaling as well as many that mediate endocytic trafficking, a cell process critical for both ciliogenesis and cell signaling. The clinical relevance of these findings is supported by whole-exome sequencing analysis of CHD patients that showed enrichment for pathogenic variants in ciliome genes. Surprisingly, among the ciliome CHD genes recovered were many that encoded direct protein-protein interactors. Assembly of the CHD genes into a protein-protein interaction network yielded a tight interactome that suggested this protein-protein interaction may have functional importance and that its disruption could contribute to the pathogenesis of CHD. In light of these and other findings, we propose that an interactome enriched for ciliome genes may provide the genomic context for the complex genetics of CHD and its often-observed incomplete penetrance and variable expressivity.

Understanding the Genetic and Non-genetic Interconnections in the Aetiology of Isolated Congenital Heart Disease: An Updated Review: Part 1

PURPOSE OF REVIEW

Congenital heart disease (CHD) is the most frequently occurring birth defect. Majority of the earlier reviews focussed on the association of genetic factors with CHD. A few epidemiological studies provide convincing evidence for environmental factors in the causation of CHD. Although the multifactorial theory of gene-environment interaction is the prevailing explanation, explicit understanding of the biological mechanism(s) involved, remains obscure. Nonetheless, integration of all the information into one platform would enable us to better understand the collective risk implicated in CHD development.

RECENT FINDINGS

Great strides in novel genomic technologies namely, massive parallel sequencing, whole exome sequencing, multiomics studies supported by system-biology have greatly improved our understanding of the aetiology of CHD. Molecular genetic studies reveal that cardiac specific gene variants in transcription factors or signalling molecules, or structural proteins could cause CHD. Additionally, non-hereditary contributors such as exposure to teratogens, maternal nutrition, parental age and lifestyle factors also contribute to induce CHD. Moreover, DNA methylation and non-coding RNA are also correlated with CHD. Here, we inform that a complex combination of genetic, environmental and epigenetic factors interact to interfere with morphogenetic processes of cardiac development leading to CHD. It is important, not only to identify individual genetic and non-inherited risk factors but also to recognize which factors interact mutually, causing cardiac defects.

The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young

BACKGROUND

Sudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing.

METHODS

The SDY Case Registry is a National Institutes of Health/Centers for Disease Control and Prevention surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases < 20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015 to 2019. The cohort included 211 children (median age 0.33 year; range 0-20 years), determined to have died suddenly and unexpectedly and from whom DNA biospecimens for DNA extractions and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex- and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy, and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, pathogenic and likely pathogenic genetic variation was identified using a Bayesian-based artificial intelligence (AI) tool.

RESULTS

The SDY cohort was 43% European, 29% African, 3% Asian, 16% Hispanic, and 9% with mixed ancestries and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy, or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, potentially damaging variants in epilepsy, cardiomyopathy, and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death.

CONCLUSIONS

While damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.

Human Genetics of Defects of Situs

Defects of situs are associated with complex sets of congenital heart defects in which the normal concordance of asymmetric thoracic and abdominal organs is disturbed. The cellular and molecular mechanisms underlying the formation of the embryonic left-right axis have been investigated extensively in the past decade. This has led to the identification of mutations in at least 33 different genes in humans with heterotaxy and situs defects. Those mutations affect a broad range of molecular components, from transcription factors, signaling molecules, and chromatin modifiers to ciliary proteins. A substantial overlap of these genes is observed with genes associated with other congenital heart diseases such as tetralogy of Fallot and double-outlet right ventricle, d-transposition of the great arteries, and atrioventricular septal defects. In this chapter, we present the broad genetic heterogeneity of situs defects including recent human genomics efforts.

Establishment of Cardiac Laterality

Formation of the vertebrate heart with its complex arterial and venous connections is critically dependent on patterning of the left-right axis during early embryonic development. Abnormalities in left-right patterning can lead to a variety of complex life-threatening congenital heart defects. A highly conserved pathway responsible for left-right axis specification has been uncovered. This pathway involves initial asymmetric activation of a nodal signaling cascade at the embryonic node, followed by its propagation to the left lateral plate mesoderm and activation of left-sided expression of the Pitx2 transcription factor specifying visceral organ asymmetry. Intriguingly, recent work suggests that cardiac laterality is encoded by intrinsic cell and tissue chirality independent of Nodal signaling. Thus, Nodal signaling may be superimposed on this intrinsic chirality, providing additional instructive cues to pattern cardiac situs. The impact of intrinsic chirality and the perturbation of left-right patterning on myofiber organization and cardiac function warrants further investigation. We summarize recent insights gained from studies in animal models and also some human clinical studies in a brief overview of the complex processes regulating cardiac asymmetry and their impact on cardiac function and the pathogenesis of congenital heart defects.

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.

Integrated omics analysis of coronary artery calcifications and myocardial infarction: the Framingham Heart Study

Gene function can be described using various measures. We integrated association studies of three types of omics data to provide insights into the pathophysiology of subclinical coronary disease and myocardial infarction (MI). Using multivariable regression models, we associated: (1) single nucleotide polymorphism, (2) DNA methylation, and (3) gene expression with coronary artery calcification (CAC) scores and MI. Among 3106 participants of the Framingham Heart Study, 65 (2.1%) had prevalent MI and 60 (1.9%) had incident MI, median CAC value was 67.8 [IQR 10.8, 274.9], and 1403 (45.2%) had CAC scores > 0 (prevalent CAC). Prevalent CAC was associated with AHRR (linked to smoking) and EXOC3 (affecting platelet function and promoting hemostasis). CAC score was associated with VWA1 (extracellular matrix protein associated with cartilage structure in endomysium). For prevalent MI we identified FYTTD1 (down-regulated in familial hypercholesterolemia) and PINK1 (linked to cardiac tissue homeostasis and ischemia-reperfusion injury). Incident MI was associated with IRX3 (enhancing browning of white adipose tissue) and STXBP3 (controlling trafficking of glucose transporter type 4 to plasma). Using an integrative trans-omics approach, we identified both putatively novel and known candidate genes associated with CAC and MI. Replication of findings is warranted.

Mutations in genes related to myocyte contraction and ventricular septum development in non-syndromic tetralogy of Fallot

Objective

Eighty percent of patients with a diagnosis of tetralogy of Fallot (TOF) do not have a known genetic etiology or syndrome. We sought to identify key molecular pathways and biological processes that are enriched in non-syndromic TOF, the most common form of cyanotic congenital heart disease, rather than single driver genes to elucidate the pathogenesis of this disease.

Methods

We undertook exome sequencing of 362 probands with non-syndromic TOF and their parents within the Pediatric Cardiac Genomics Consortium (PCGC). We identified rare (minor allele frequency <1 × 10-4), de novo variants to ascertain pathways and processes affected in this population to better understand TOF pathogenesis. Pathways and biological processes enriched in the PCGC TOF cohort were compared to 317 controls without heart defects (and their parents) from the Simons Foundation Autism Research Initiative (SFARI).

Results

A total of 120 variants in 117 genes were identified as most likely to be deleterious, with CHD7, CLUH, UNC13C, and WASHC5 identified in two probands each. Gene ontology analyses of these variants using multiple bioinformatic tools demonstrated significant enrichment in processes including cell cycle progression, chromatin remodeling, myocyte contraction and calcium transport, and development of the ventricular septum and ventricle. There was also a significant enrichment of target genes of SOX9, which is critical in second heart field development and whose loss results in membranous ventricular septal defects related to disruption of the proximal outlet septum. None of these processes was significantly enriched in the SFARI control cohort.

Conclusion

Innate molecular defects in cardiac progenitor cells and genes related to their viability and contractile function appear central to non-syndromic TOF pathogenesis. Future research utilizing our results is likely to have significant implications in stratification of TOF patients and delivery of personalized clinical care.

Genetic and clinical variables act synergistically to impact neurodevelopmental outcomes in children with single ventricle heart disease

BACKGROUND

Recent large-scale sequencing efforts have shed light on the genetic contribution to the etiology of congenital heart defects (CHD); however, the relative impact of genetics on clinical outcomes remains less understood. Outcomes analyses using genetics are complicated by the intrinsic severity of the CHD lesion and interactions with conditionally dependent clinical variables.

METHODS

Bayesian Networks were applied to describe the intertwined relationships between clinical variables, demography, and genetics in a cohort of children with single ventricle CHD.

RESULTS

As isolated variables, a damaging genetic variant in a gene related to abnormal heart morphology and prolonged ventilator support following stage I palliative surgery increase the probability of having a low Mental Developmental Index (MDI) score at 14 months of age by 1.9- and 5.8-fold, respectively. However, in combination, these variables act synergistically to further increase the probability of a low MDI score by 10-fold. The absence of a damaging variant in a known syndromic CHD gene and a shorter post-operative ventilator support increase the probability of a normal MDI score 1.7- and 2.4-fold, respectively, but in combination increase the probability of a good outcome by 59-fold.

CONCLUSIONS

Our analyses suggest a modest genetic contribution to neurodevelopmental outcomes as isolated variables, similar to known clinical predictors. By contrast, genetic, demographic, and clinical variables interact synergistically to markedly impact clinical outcomes. These findings underscore the importance of capturing and quantifying the impact of damaging genomic variants in the context of multiple, conditionally dependent variables, such as pre- and post-operative factors, and demography.

Genetic Contributions to Biliary Atresia: A Developmental Cholangiopathy

Biliary atresia (BA) is the most prevalent serious liver disease of infancy and childhood, and the principal indication for liver transplantation in pediatrics. BA is best considered as an idiopathic panbiliary cholangiopathy characterized by obstruction of bile flow and consequent cholestasis presenting during fetal and perinatal periods. While several etiologies have been proposed, each has significant drawbacks that have limited understanding of disease progression and the development of effective treatments. Recently, modern genetic analyses have uncovered gene variants contributing to BA, thereby shifting the paradigm for explaining the BA phenotype from an acquired etiology (e.g., virus, toxin) to one that results from genetically altered cholangiocyte development and function. Herein we review recently reported genetic contributions to BA, highlighting the enhanced representation of variants in biological pathways involving ciliary function, cytoskeletal structure, and inflammation. Finally, we blend these findings as a new framework for understanding the resultant BA phenotype as a developmental cholangiopathy.

Chromatin regulators in the TBX1 network confer risk for conotruncal heart defects in 22q11.2DS

Congenital heart disease (CHD) affecting the conotruncal region of the heart, occurs in 40-50% of patients with 22q11.2 deletion syndrome (22q11.2DS). This syndrome is a rare disorder with relative genetic homogeneity that can facilitate identification of genetic modifiers. Haploinsufficiency of TBX1, encoding a T-box transcription factor, is one of the main genes responsible for the etiology of the syndrome. We suggest that genetic modifiers of conotruncal defects in patients with 22q11.2DS may be in the TBX1 gene network. To identify genetic modifiers, we analyzed rare, predicted damaging variants in whole genome sequence of 456 cases with conotruncal defects and 537 controls, with 22q11.2DS. We then performed gene set approaches and identified chromatin regulatory genes as modifiers. Chromatin genes with recurrent damaging variants include EP400, KAT6A, KMT2C, KMT2D, NSD1, CHD7 and PHF21A. In total, we identified 37 chromatin regulatory genes, that may increase risk for conotruncal heart defects in 8.5% of 22q11.2DS cases. Many of these genes were identified as risk factors for sporadic CHD in the general population. These genes are co-expressed in cardiac progenitor cells with TBX1, suggesting that they may be in the same genetic network. The genes KAT6A, KMT2C, CHD7 and EZH2, have been previously shown to genetically interact with TBX1 in mouse models. Our findings indicate that disturbance of chromatin regulatory genes impact the TBX1 gene network serving as genetic modifiers of 22q11.2DS and sporadic CHD, suggesting that there are some shared mechanisms involving the TBX1 gene network in the etiology of CHD.

Congenital heart defects caused by FOXJ1

FOXJ1 is expressed in ciliated cells of the airways, testis, oviduct, central nervous system and the embryonic left-right organizer. Ablation or targeted mutation of Foxj1 in mice, zebrafish and frogs results in loss of ciliary motility and/or reduced length and number of motile cilia, affecting the establishment of the left-right axis. In humans, heterozygous pathogenic variants in FOXJ1 cause ciliopathy leading to situs inversus, obstructive hydrocephalus and chronic airway disease. Here, we report a novel truncating FOXJ1 variant (c.784_799dup; p.Glu267Glyfs*12) identified by clinical exome sequencing from a patient with isolated congenital heart defects (CHD) which included atrial and ventricular septal defects, double outlet right ventricle (DORV) and transposition of the great arteries. Functional experiments show that FOXJ1 c.784_799dup; p.Glu267Glyfs*12, unlike FOXJ1, fails to induce ectopic cilia in frog epidermis in vivo or to activate the ADGB promoter, a downstream target of FOXJ1 in cilia, in transactivation assays in vitro. Variant analysis of patients with heterotaxy or heterotaxy-related CHD indicates that pathogenic variants in FOXJ1 are an infrequent cause of heterotaxy. Finally, we characterize embryonic-stage CHD in Foxj1 loss-of-function mice, demonstrating randomized heart looping. Abnormal heart looping includes reversed looping (dextrocardia), ventral looping and no looping/single ventricle hearts. Complex CHDs revealed by histological analysis include atrioventricular septal defects, DORV, single ventricle defects as well as abnormal position of the great arteries. These results indicate that pathogenic variants in FOXJ1 can cause isolated CHD.

Insights into the genetic architecture of congenital heart disease from animal modeling

Congenital heart disease (CHD) is observed in up to 1% of live births and is one of the leading causes of mortality from birth defects. While hundreds of genes have been implicated in the genetic etiology of CHD, their role in CHD pathogenesis is still poorly understood. This is largely a reflection of the sporadic nature of CHD, as well as its variable expressivity and incomplete penetrance. We reviewed the monogenic causes and evidence for oligogenic etiology of CHD, as well as the role of de novo mutations, common variants, and genetic modifiers. For further mechanistic insight, we leveraged single-cell data across species to investigate the cellular expression characteristics of genes implicated in CHD in developing human and mouse embryonic hearts. Understanding the genetic etiology of CHD may enable the application of precision medicine and prenatal diagnosis, thereby facilitating early intervention to improve outcomes for patients with CHD.

Evidence-Based Assessment of Congenital Heart Disease Genes to Enable Returning Results in a Genomic Study

BACKGROUND

Congenital heart disease (CHD) is the most common major congenital anomaly and causes significant morbidity and mortality. Epidemiologic evidence supports a role of genetics in the development of CHD. Genetic diagnoses can inform prognosis and clinical management. However, genetic testing is not standardized among individuals with CHD. We sought to develop a list of validated CHD genes using established methods and to evaluate the process of returning genetic results to research participants in a large genomic study.

METHODS

Two-hundred ninety-five candidate CHD genes were evaluated using a ClinGen framework. Sequence and copy number variants involving genes in the CHD gene list were analyzed in Pediatric Cardiac Genomics Consortium participants. Pathogenic/likely pathogenic results were confirmed on a new sample in a clinical laboratory improvement amendments-certified laboratory and disclosed to eligible participants. Adult probands and parents of probands who received results were asked to complete a post-disclosure survey.

RESULTS

A total of 99 genes had a strong or definitive clinical validity classification. Diagnostic yields for copy number variants and exome sequencing were 1.8% and 3.8%, respectively. Thirty-one probands completed clinical laboratory improvement amendments-confirmation and received results. Participants who completed postdisclosure surveys reported high personal utility and no decision regret after receiving genetic results.

CONCLUSIONS

The application of ClinGen criteria to CHD candidate genes yielded a list that can be used to interpret clinical genetic testing for CHD. Applying this gene list to one of the largest research cohorts of CHD participants provides a lower bound for the yield of genetic testing in CHD.

The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young

Background

Sudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing.

Methods

The SDY Case Registry is a National Institutes of Health/Centers for Disease Control surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases <20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015-2019. The cohort included 211 children (mean age 1 year; range 0-20 years), determined to have died suddenly and unexpectedly and in whom DNA biospecimens and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex-and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, genetic variation predicted to be damaging was identified using a Bayesian-based artificial intelligence (AI) tool.

Results

The SDY cohort was 42% European, 30% African, 17% Hispanic, and 11% with mixed ancestries, and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, damaging variants in epilepsy, cardiomyopathy and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death.

Conclusions

While damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort, and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.

Recent advances in CRISPR-based genome editing technology and its applications in cardiovascular research

The rapid development of genome editing technology has brought major breakthroughs in the fields of life science and medicine. In recent years, the clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing toolbox has been greatly expanded, not only with emerging CRISPR-associated protein (Cas) nucleases, but also novel applications through combination with diverse effectors. Recently, transposon-associated programmable RNA-guided genome editing systems have been uncovered, adding myriads of potential new tools to the genome editing toolbox. CRISPR-based genome editing technology has also revolutionized cardiovascular research. Here we first summarize the advances involving newly identified Cas orthologs, engineered variants and novel genome editing systems, and then discuss the applications of the CRISPR-Cas systems in precise genome editing, such as base editing and prime editing. We also highlight recent progress in cardiovascular research using CRISPR-based genome editing technologies, including the generation of genetically modified in vitro and animal models of cardiovascular diseases (CVD) as well as the applications in treating different types of CVD. Finally, the current limitations and future prospects of genome editing technologies are discussed.

Genetic architecture in neonatal intensive care unit patients with congenital heart defects: a retrospective study from the China Neonatal Genomes Project

BACKGROUND

Congenital heart defects (CHDs) are the most common type of birth defects. The genetic aetiology of CHD is complex and incompletely understood. The overall distribution of genetic causes in patients with CHD from neonatal intensive care units (NICUs) needs to be studied.

METHODS

CHD cases were extracted from the China Neonatal Genomes Project (2016-2021). Next-generation sequencing results and medical records were retrospectively evaluated to note the frequency of genetic diagnosis and the respective patient outcomes.

RESULTS

In total, 1795 patients were included. The human phenotype ontology term of atrial septal defect, patent ductus arteriosus and ventricular septal defect account for a large portion of the CHD subtype. Co-occurring extracardiac anomalies were observed in 35.1% of patients. 269 of the cases received genetic diagnoses that could explain the phenotype of CHDs, including 172 copy number variations and 97 pathogenic variants. The detection rate of trio-whole-exome sequencing was higher than clinical exome sequencing (21.8% vs 14.5%, p<0.05). Further follow-up analysis showed the genetic diagnostic rate was higher in the deceased group than in the surviving group (29.0% vs 11.9%, p<0.05).

CONCLUSION

This is the largest cohort study to explore the genetic spectrum of patients with CHD in the NICU in China. Our findings may benefit future work on improving genetic screening and counselling for NICU patients with CHD.

Variable phenotypes and penetrance between and within different zebrafish ciliary transition zone mutants

Meckel syndrome, nephronophthisis, Joubert syndrome and Bardet-Biedl syndrome are caused by mutations in proteins that localize to the ciliary transition zone (TZ). The phenotypically distinct syndromes suggest that these TZ proteins have differing functions. However, mutations in a single TZ gene can result in multiple syndromes, suggesting that the phenotype is influenced by modifier genes. We performed a comprehensive analysis of ten zebrafish TZ mutants, including mks1, tmem216, tmem67, rpgrip1l, cc2d2a, b9d2, cep290, tctn1, nphp1 and nphp4, as well as mutants in ift88 and ift172. Our data indicate that variations in phenotypes exist between different TZ mutants, supporting different tissue-specific functions of these TZ genes. Further, we observed phenotypic variations within progeny of a single TZ mutant, reminiscent of multiple disease syndromes being associated with mutations in one gene. In some mutants, the dynamics of the phenotype became complex with transitory phenotypes that are corrected over time. We also demonstrated that multiple-guide-derived CRISPR/Cas9 F0 'crispant' embryos recapitulate zygotic null phenotypes, and rapidly identified ciliary phenotypes in 11 cilia-associated gene candidates (ankfn1, ccdc65, cfap57, fhad1, nme7, pacrg, saxo2, c1orf194, ttc26, zmynd12 and cfap52).

Statistical models of the genetic etiology of congenital heart disease

Congenital heart disease (CHD) is a collection of anatomically and clinically heterogeneous structure anomalies of heart at birth. Finding genetic causes of CHD can not only shed light on developmental biology of heart, but also provide basis for improving clinical care and interventions. The optimal study design and analytical approaches to identify genetic causes depend on the underlying genetic architecture. A few well-known syndromes with CHD as core conditions, such as Noonan and CHARGE, have known monogenic causes. The genetic causes of most of CHD patients, however, are unknown and likely to be complex. In this review, we highlight recent studies that assume a complex genetic architecture of CHD with two main approaches. One is genomic sequencing studies aiming for identifying rare or de novo risk variants with large genetic effect. The other is genome-wide association studies optimized for common variants with moderate genetic effect.

Hedgehog signaling activates a mammalian heterochronic gene regulatory network controlling differentiation timing across lineages

Many developmental signaling pathways have been implicated in lineage-specific differentiation; however, mechanisms that explicitly control differentiation timing remain poorly defined in mammals. We report that murine Hedgehog signaling is a heterochronic pathway that determines the timing of progenitor differentiation. Hedgehog activity was necessary to prevent premature differentiation of second heart field (SHF) cardiac progenitors in mouse embryos, and the Hedgehog transcription factor GLI1 was sufficient to delay differentiation of cardiac progenitors in vitro. GLI1 directly activated a de novo progenitor-specific network in vitro, akin to that of SHF progenitors in vivo, which prevented the onset of the cardiac differentiation program. A Hedgehog signaling-dependent active-to-repressive GLI transition functioned as a differentiation timer, restricting the progenitor network to the SHF. GLI1 expression was associated with progenitor status across germ layers, and it delayed the differentiation of neural progenitors in vitro, suggesting a broad role for Hedgehog signaling as a heterochronic pathway.

Clustering of Genetic Anomalies of Cilia Outer Dynein Arm and Central Apparatus in Patients with Transposition of the Great Arteries

Transposition of the great arteries (TGA) is a congenital heart defect with a complex pathogenesis that has not been fully elucidated. In this study, we performed whole-exome sequencing (WES) in isolated TGA-diagnosed patients and analyzed genes of motile and non-motile cilia ciliogenesis and ciliary trafficking, as well as genes previously associated with this heart malformation. Deleterious missense and splicing variants of genes DNAH9, DNAH11, and ODAD4 of cilia outer dynein arm and central apparatus, HYDIN, were found in our TGA patients. Remarkable, there is a clustering of deleterious genetic variants in cilia genes, suggesting it could be an oligogenic disease. Our data evidence the genetic diversity and etiological complexity of TGA and point out that population allele determination and genetic aggregation studies are required to improve genetic counseling.

DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features

BACKGROUND

Pathogenic mutations in genes that control chromatin function have been implicated in rare genetic syndromes. These chromatin modifiers exhibit extraordinary diversity in the scale of the epigenetic changes they affect, from single basepair modifications by DNMT1 to whole genome structural changes by PRM1/2. Patterns of DNA methylation are related to a diverse set of epigenetic features across this full range of epigenetic scale, making DNA methylation valuable for mapping regions of general epigenetic dysregulation. However, existing methods are unable to accurately identify regions of differential methylation across this full range of epigenetic scale directly from DNA methylation data.

RESULTS

To address this, we developed DMRscaler, a novel method that uses an iterative windowing procedure to capture regions of differential DNA methylation (DMRs) ranging in size from single basepairs to whole chromosomes. We benchmarked DMRscaler against several DMR callers in simulated and natural data comparing XX and XY peripheral blood samples. DMRscaler was the only method that accurately called DMRs ranging in size from 100 bp to 1 Mb (pearson's r = 0.94) and up to 152 Mb on the X-chromosome. We then analyzed methylation data from rare-disease cohorts that harbor chromatin modifier gene mutations in NSD1, EZH2, and KAT6A where DMRscaler identified novel DMRs spanning gene clusters involved in development.

CONCLUSION

Taken together, our results show DMRscaler is uniquely able to capture the size of DMR features across the full range of epigenetic scale and identify novel, co-regulated regions that drive epigenetic dysregulation in human disease.

Polygenic risk scores of endo-phenotypes identify the effect of genetic background in congenital heart disease

Congenital heart disease (CHD) is a rare structural defect that occurs in ∼1% of live births. Studies on CHD genetic architecture have identified pathogenic single-gene mutations in less than 30% of cases. Single-gene mutations often show incomplete penetrance and variable expressivity. Therefore, we hypothesize that genetic background may play a role in modulating disease expression. Polygenic risk scores (PRSs) aggregate effects of common genetic variants to investigate whether, cumulatively, these variants are associated with disease penetrance or severity. However, the major limitations in this field have been in generating sufficient sample sizes for these studies. Here we used CHD-phenotype matched genome-wide association study (GWAS) summary statistics from the UK Biobank (UKBB) as our base study and whole-genome sequencing data from the CHD cohort (n1 = 711 trios, n2 = 362 European trios) of the Gabriella Miller Kids First dataset as our target study to develop PRSs for CHD. PRSs estimated using a GWAS for heart valve problems and heart murmur explain 2.5% of the variance in case-control status of CHD (all SNVs, p = 7.90 × 10-3; fetal cardiac SNVs, p = 8.00 × 10-3) and 1.8% of the variance in severity of CHD (fetal cardiac SNVs, p = 6.20 × 10-3; all SNVs, p = 0.015). These results show that common variants captured in CHD phenotype-matched GWASs have a modest but significant contribution to phenotypic expression of CHD. Further exploration of the cumulative effect of common variants is necessary for understanding the complex genetic etiology of CHD and other rare diseases.

Molecular genetic mechanisms of congenital heart disease

Congenital heart disease (CHD) affects ~1% of all live births, but a definitive etiology is identified in only ~50%. The causes include chromosomal aneuploidies and copy-number variations, pathogenic variation in single genes, and exposure to environmental factors. High-throughput sequencing of large CHD patient cohorts and continued expansion of the complex molecular regulation of cardiac morphogenesis has uncovered numerous disease-causing genes, but the previously held monogenic model for CHD etiology does not sufficiently explain the heterogeneity and incomplete penetrance of CHD phenotypes. Here, we provide a summary of well-known genetic contributors to CHD and discuss emerging concepts supporting complex genetic mechanisms that may provide explanations for cases that currently lack a molecular diagnosis.

[Exploring the association between de novo mutations and non-syndromic cleft lip with or without palate based on whole exome sequencing of case-parent trios]

OBJECTIVE

To explore the association between de novo mutations (DNM) and non-syndromic cleft lip with or without palate (NSCL/P) using case-parent trio design.

METHODS

Whole-exome sequencing was conducted for twenty-two NSCL/P trios and Genome Analysis ToolKit (GATK) was used to identify DNM by comparing the alleles of the cases and their parents. Information of predictable functions was annotated to the locus with SnpEff. Enrichment analysis for DNM was conducted to test the difference between the actual number and the expected number of DNM, and to explore whether there were genes with more DNM than expected. NSCL/P-related genes indicated by previous studies with solid evidence were selected by literature reviewing. Protein-protein interactions analysis was conducted among the genes with protein-altering DNM and NSCL/P-related genes. R package "denovolyzeR" was used for the enrichment analysis (Bonferroni correction: P=0.05/n, n is the number of genes in the whole genome range). Protein-protein interactions among genes with DNM and genes with solid evidence on the risk factors of NSCL/P were predicted depending on the information provided by STRING database.

RESULTS

A total of 339 908 SNPs were qualified for the subsequent analysis after quality control. The number of high confident DNM identified by GATK was 345. Among those DNM, forty-four DNM were missense mutations, one DNM was nonsense mutation, two DNM were splicing site mutations, twenty DNM were synonymous mutations and others were located in intron or intergenic regions. The results of enrichment analysis showed that the number of protein-altering DNM on the exome regions was larger than expected (P < 0.05), and five genes (KRTCAP2, HMCN2, ANKRD36C, ADGRL2 and DIPK2A) had more DNM than expected (P < 0.05/(2×19 618)). Protein-protein interaction analysis was conducted among forty-six genes with protein-altering DNM and thirteen genes associated with NSCL/P selected by literature reviewing. Six pairs of interactions occurred between the genes with DNM and known NSCL/P-related genes. The score measuring the confidence level of the predicted interaction between RGPD4 and SUMO1 was 0.868, which was higher than the scores for other pairs of genes.

CONCLUSION

Our study provided novel insights into the development of NSCL/P and demonstrated that functional analyses of genes carrying DNM were warranted to understand the genetic architecture of complex diseases.

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.

A change of heart: new roles for cilia in cardiac development and disease

Although cardiac abnormalities have been observed in a growing class of human disorders caused by defective primary cilia, the function of cilia in the heart remains an underexplored area. The primary function of cilia in the heart was long thought to be restricted to left-right axis patterning during embryogenesis. However, new findings have revealed broad roles for cilia in congenital heart disease, valvulogenesis, myocardial fibrosis and regeneration, and mechanosensation. In this Review, we describe advances in our understanding of the mechanisms by which cilia function contributes to cardiac left-right axis development and discuss the latest findings that highlight a broader role for cilia in cardiac development. Specifically, we examine the growing line of evidence connecting cilia function to the pathogenesis of congenital heart disease. Furthermore, we also highlight research from the past 10 years demonstrating the role of cilia function in common cardiac valve disorders, including mitral valve prolapse and aortic valve disease, and describe findings that implicate cardiac cilia in mechanosensation potentially linking haemodynamic and contractile forces with genetic regulation of cardiac development and function. Finally, given the presence of cilia on cardiac fibroblasts, we also explore the potential role of cilia in fibrotic growth and summarize the evidence implicating cardiac cilia in heart regeneration.

Causal and Candidate Gene Variants in a Large Cohort of Women With Primary Ovarian Insufficiency

CONTEXT

A genetic etiology likely accounts for the majority of unexplained primary ovarian insufficiency (POI).

OBJECTIVE

We hypothesized that heterozygous rare variants and variants in enhanced categories are associated with POI.

DESIGN

The study was an observational study.

SETTING

Subjects were recruited at academic institutions.

PATIENTS

Subjects from Boston (n = 98), the National Institutes of Health and Washington University (n = 98), Pittsburgh (n = 20), Italy (n = 43), and France (n = 32) were diagnosed with POI (amenorrhea with an elevated follicle-stimulating hormone level). Controls were recruited for health in old age or were from the 1000 Genomes Project (total n = 233).

INTERVENTION

We performed whole exome sequencing (WES), and data were analyzed using a rare variant scoring method and a Bayes factor-based framework for identifying genes harboring pathogenic variants. We performed functional studies on identified genes that were not previously implicated in POI in a D. melanogaster model.

MAIN OUTCOME

Genes with rare pathogenic variants and gene sets with increased burden of deleterious variants were identified.

RESULTS

Candidate heterozygous variants were identified in known genes and genes with functional evidence. Gene sets with increased burden of deleterious alleles included the categories transcription and translation, DNA damage and repair, meiosis and cell division. Variants were found in novel genes from the enhanced categories. Functional evidence supported 7 new risk genes for POI (USP36, VCP, WDR33, PIWIL3, NPM2, LLGL1, and BOD1L1).

CONCLUSIONS

Candidate causative variants were identified through WES in women with POI. Aggregating clinical data and genetic risk with a categorical approach may expand the genetic architecture of heterozygous rare gene variants causing risk for POI.

CELSR1 Risk Alleles in Familial Bicuspid Aortic Valve and Hypoplastic Left Heart Syndrome

BACKGROUND

Whole-genome sequencing in families enables deciphering of congenital heart disease causes. A shared genetic basis for familial bicuspid aortic valve (BAV) and hypoplastic left heart syndrome (HLHS) was postulated.

METHODS

Whole-genome sequencing was performed in affected members of 6 multiplex BAV families, an HLHS cohort of 197 probands and 546 relatives, and 813 controls. Data were filtered for rare, predicted-damaging variants that cosegregated with familial BAV and disrupted genes associated with congenital heart disease in humans and mice. Candidate genes were further prioritized by rare variant burden testing in HLHS cases versus controls. Modifier variants in HLHS proband-parent trios were sought to account for the severe developmental phenotype.

RESULTS

In 5 BAV families, missense variants in 6 ontologically diverse genes for structural (SPTBN1, PAXIP1, and FBLN1) and signaling (CELSR1, PLXND1, and NOS3) proteins fulfilled filtering metrics. CELSR1, encoding cadherin epidermal growth factor laminin G seven-pass G-type receptor, was identified as a candidate gene in 2 families and was the only gene demonstrating rare variant enrichment in HLHS probands (P=0.003575). HLHS-associated CELSR1 variants included 16 missense, one splice site, and 3 noncoding variants predicted to disrupt canonical transcription factor binding sites, most of which were inherited from a parent without congenital heart disease. Filtering whole-genome sequencing data for rare, predicted-damaging variants inherited from the other parent revealed 2 cases of CELSR1 compound heterozygosity, one case of CELSR1-CELSR3 synergistic heterozygosity, and 4 cases of CELSR1-MYO15A digenic heterozygosity.

CONCLUSIONS

CELSR1 is a susceptibility gene for familial BAV and HLHS, further implicating planar cell polarity pathway perturbation in congenital heart disease.

Extensive identification of genes involved in congenital and structural heart disorders and cardiomyopathy

Clinical presentation of congenital heart disease is heterogeneous, making identification of the disease-causing genes and their genetic pathways and mechanisms of action challenging. By using in vivo electrocardiography, transthoracic echocardiography and microcomputed tomography imaging to screen 3,894 single-gene-null mouse lines for structural and functional cardiac abnormalities, here we identify 705 lines with cardiac arrhythmia, myocardial hypertrophy and/or ventricular dilation. Among these 705 genes, 486 have not been previously associated with cardiac dysfunction in humans, and some of them represent variants of unknown relevance (VUR). Mice with mutations in Casz1, Dnajc18, Pde4dip, Rnf38 or Tmem161b genes show developmental cardiac structural abnormalities, with their human orthologs being categorized as VUR. Using UK Biobank data, we validate the importance of the DNAJC18 gene for cardiac homeostasis by showing that its loss of function is associated with altered left ventricular systolic function. Our results identify hundreds of previously unappreciated genes with potential function in congenital heart disease and suggest causal function of five VUR in congenital heart disease.

Whole genome sequencing in transposition of the great arteries and associations with clinically relevant heart, brain and laterality genes

BACKGROUND

The most common cyanotic congenital heart disease (CHD) requiring management as a neonate is transposition of great arteries (TGA). Clinically, up to 50% of TGA patients develop some form of neurodevelopmental disability (NDD), thought to have a significant genetic component. A "ciliopathy" and links with laterality disorders have been proposed. This first report of whole genome sequencing in TGA, sought to identify clinically relevant variants contributing to heart, brain and laterality defects.

METHODS

Initial whole genome sequencing analyses on 100 TGA patients focussed on established disease genes related to CHD (n = 107), NDD (n = 659) and heterotaxy (n = 74). Single variant as well as copy number variant analyses were conducted. Variant pathogenicity was assessed using the American College of Medical Genetics and Genomics-Association for Molecular Pathology guidelines.

RESULTS

Fifty-five putatively damaging variants were identified in established disease genes associated with CHD, NDD and heterotaxy; however, no clinically relevant variants could be attributed to disease. Notably, case-control analyses identified significantly more predicted-damaging, silent and total variants in TGA cases than healthy controls in established CHD genes (P < .001), NDD genes (P < .001) as well as across the three gene panels (P < .001).

CONCLUSION

We present compelling evidence that the majority of TGA is not caused by monogenic rare variants and is most likely oligogenic and/or polygenic in nature, highlighting the complex genetic architecture and multifactorial influences on this CHD sub-type and its long-term sequelae. Assessment of variant burden in key heart, brain and/or laterality genes may be required to unravel the genetic contributions to TGA and related disabilities.

Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries

RATIONALE

Dextro-transposition of the great arteries (D-TGA) is a severe congenital heart defect which affects approximately 1 in 4,000 live births. While there are several reports of D-TGA patients with rare variants in individual genes, the majority of D-TGA cases remain genetically elusive. Familial recurrence patterns and the observation that most cases with D-TGA are sporadic suggest a polygenic inheritance for the disorder, yet this remains unexplored.

OBJECTIVE

We sought to study the role of common single nucleotide polymorphisms (SNPs) in risk for D-TGA.

METHODS AND RESULTS

We conducted a genome-wide association study in an international set of 1,237 patients with D-TGA and identified a genome-wide significant susceptibility locus on chromosome 3p14.3, which was subsequently replicated in an independent case-control set (rs56219800, meta-analysis P=8.6x10-10, OR=0.69 per C allele). SNP-based heritability analysis showed that 25% of variance in susceptibility to D-TGA may be explained by common variants. A genome-wide polygenic risk score derived from the discovery set was significantly associated to D-TGA in the replication set (P=4x10-5). The genome-wide significant locus (3p14.3) co-localizes with a putative regulatory element that interacts with the promoter of WNT5A, which encodes the Wnt Family Member 5A protein known for its role in cardiac development in mice. We show that this element drives reporter gene activity in the developing heart of mice and zebrafish and is bound by the developmental transcription factor TBX20. We further demonstrate that TBX20 attenuates Wnt5a expression levels in the developing mouse heart.

CONCLUSIONS

This work provides support for a polygenic architecture in D-TGA and identifies a susceptibility locus on chromosome 3p14.3 near WNT5A. Genomic and functional data support a causal role of WNT5A at the locus.

Genomic enhancers in cardiac development and disease

The Human Genome Project marked a major milestone in the scientific community as it unravelled the ~3 billion bases that are central to crucial aspects of human life. Despite this achievement, it only scratched the surface of understanding how each nucleotide matters, both individually and as part of a larger unit. Beyond the coding genome, which comprises only ~2% of the whole genome, scientists have realized that large portions of the genome, not known to code for any protein, were crucial for regulating the coding genes. These large portions of the genome comprise the 'non-coding genome'. The history of gene regulation mediated by proteins that bind to the regulatory non-coding genome dates back many decades to the 1960s. However, the original definition of 'enhancers' was first used in the early 1980s. In this Review, we summarize benchmark studies that have mapped the role of cardiac enhancers in disease and development. We highlight instances in which enhancer-localized genetic variants explain the missing link to cardiac pathogenesis. Finally, we inspire readers to consider the next phase of exploring enhancer-based gene therapy for cardiovascular disease.

Genomic frontiers in congenital heart disease

The application of next-generation sequencing to study congenital heart disease (CHD) is increasingly providing new insights into the causes and mechanisms of this prevalent birth anomaly. Whole-exome sequencing analysis identifies damaging gene variants altering single or contiguous nucleotides that are assigned pathogenicity based on statistical analyses of families and cohorts with CHD, high expression in the developing heart and depletion of damaging protein-coding variants in the general population. Gene classes fulfilling these criteria are enriched in patients with CHD and extracardiac abnormalities, evidencing shared pathways in organogenesis. Developmental single-cell transcriptomic data demonstrate the expression of CHD-associated genes in particular cell lineages, and emerging insights indicate that genetic variants perturb multicellular interactions that are crucial for cardiogenesis. Whole-genome sequencing analyses extend these observations, identifying non-coding variants that influence the expression of genes associated with CHD and contribute to the estimated ~55% of unexplained cases of CHD. These approaches combined with the assessment of common and mosaic genetic variants have provided a more complete knowledge of the causes and mechanisms of CHD. Such advances provide knowledge to inform the clinical care of patients with CHD or other birth defects and deepen our understanding of the complexity of human development. In this Review, we highlight known and candidate CHD-associated human genes and discuss how the integration of advances in developmental biology research can provide new insights into the genetic contributions to CHD.

Sequencing of a Chinese tetralogy of fallot cohort reveals clustering mutations in myogenic heart progenitors

Tetralogy of Fallot (TOF) is the most common cyanotic heart defect, yet the underlying genetic mechanisms remain poorly understood. Here, we performed whole-genome sequencing analysis on 146 nonsyndromic TOF parent-offspring trios of Chinese ethnicity. Comparison of de novo variants and recessive genotypes of this data set with data from a European cohort identified both overlapping and potentially novel gene loci and revealed differential functional enrichment between cohorts. To assess the impact of these mutations on early cardiac development, we integrated single-cell and spatial transcriptomics of early human heart development with our genetic findings. We discovered that the candidate gene expression was enriched in the myogenic progenitors of the cardiac outflow tract. Moreover, subsets of the candidate genes were found in specific gene coexpression modules along the cardiomyocyte differentiation trajectory. These integrative functional analyses help dissect the pathogenesis of TOF, revealing cellular hotspots in early heart development resulting in cardiac malformations.

M-DATA: A statistical approach to jointly analyzing de novo mutations for multiple traits

Recent studies have demonstrated that multiple early-onset diseases have shared risk genes, based on findings from de novo mutations (DNMs). Therefore, we may leverage information from one trait to improve statistical power to identify genes for another trait. However, there are few methods that can jointly analyze DNMs from multiple traits. In this study, we develop a framework called M-DATA (Multi-trait framework for De novo mutation Association Test with Annotations) to increase the statistical power of association analysis by integrating data from multiple correlated traits and their functional annotations. Using the number of DNMs from multiple diseases, we develop a method based on an Expectation-Maximization algorithm to both infer the degree of association between two diseases as well as to estimate the gene association probability for each disease. We apply our method to a case study of jointly analyzing data from congenital heart disease (CHD) and autism. Our method was able to identify 23 genes for CHD from joint analysis, including 12 novel genes, which is substantially more than single-trait analysis, leading to novel insights into CHD disease etiology.

Genetics of congenital heart disease: a narrative review of recent advances and clinical implications

Congenital heart disease (CHD) is the most common human birth defect and remains a leading cause of mortality in childhood. Although advances in clinical management have improved the survival of children with CHD, adult survivors commonly experience cardiac and non-cardiac comorbidities, which affect quality of life and prognosis. Therefore, the elucidation of genetic etiologies of CHD not only has important clinical implications for genetic counseling of patients and families but may also impact clinical outcomes by identifying at-risk patients. Recent advancements in genetic technologies, including massively parallel sequencing, have allowed for the discovery of new genetic etiologies for CHD. Although variant prioritization and interpretation of pathogenicity remain challenges in the field of CHD genomics, advances in single-cell genomics and functional genomics using cellular and animal models of CHD have the potential to provide novel insights into the underlying mechanisms of CHD and its associated morbidities. In this review, we provide an updated summary of the established genetic contributors to CHD and discuss recent advances in our understanding of the genetic architecture of CHD along with current challenges with the interpretation of genetic variation. Furthermore, we highlight the clinical implications of genetic findings to predict and potentially improve clinical outcomes in patients with CHD.

Molecular Genetics and Complex Inheritance of Congenital Heart Disease

Congenital heart disease (CHD) is the most common congenital malformation and the leading cause of mortality therein. Genetic etiologies contribute to an estimated 90% of CHD cases, but so far, a molecular diagnosis remains unsolved in up to 55% of patients. Copy number variations and aneuploidy account for ~23% of cases overall, and high-throughput genomic technologies have revealed additional types of genetic variation in CHD. The first CHD risk genotypes identified through high-throughput sequencing were de novo mutations, many of which occur in chromatin modifying genes. Murine models of cardiogenesis further support the damaging nature of chromatin modifying CHD mutations. Transmitted mutations have also been identified through sequencing of population scale CHD cohorts, and many transmitted mutations are enriched in cilia genes and Notch or VEGF pathway genes. While we have come a long way in identifying the causes of CHD, more work is required to end the diagnostic odyssey for all CHD families. Complex genetic explanations of CHD are emerging but will require increasingly sophisticated analysis strategies applied to very large CHD cohorts before they can come to fruition in providing molecular diagnoses to genetically unsolved patients. In this review, we discuss the genetic architecture of CHD and biological pathways involved in its pathogenesis.

Setd5 is required in cardiopharyngeal mesoderm for heart development and its haploinsufficiency is associated with outflow tract defects in mouse

Congenital heart defects are a feature of several genetic haploinsufficiency syndromes, often involving transcriptional regulators. One property of haploinsufficient genes is their propensity for network interactions at the gene or protein level. In this article we took advantage of an online dataset of high throughput screening of mutations that are embryonic lethal in mice. Our aim was to identify new genes where the loss of function caused cardiovascular phenotypes resembling the 22q11.2 deletion syndrome models, that is, heterozygous and homozygous loss of Tbx1. One gene with a potentially haploinsufficient phenotype was identified, Setd5, thought to be involved in chromatin modification. We found murine Setd5 haploinsufficiency to be associated with double outlet right ventricle and perimembranous ventricular septal defect, although no genetic interaction with Tbx1 was detected. Conditional mutagenesis revealed that Setd5 was required in cardiopharyngeal mesoderm for progression of the heart tube through the ballooning stage to create a four-chambered heart.

Lifespan Perspective on Congenital Heart Disease Research: JACC State-of-the-Art Review

More than 90% of patients with congenital heart disease (CHD) are nowadays surviving to adulthood and adults account for over two-thirds of the contemporary CHD population in Western countries. Although outcomes are improved, surgery does not cure CHD. Decades of longitudinal observational data are currently motivating a paradigm shift toward a lifespan perspective and proactive approach to CHD care. The aim of this review is to operationalize these emerging concepts by presenting new constructs in CHD research. These concepts include long-term trajectories and a life course epidemiology framework. Focusing on a precision health, we propose to integrate our current knowledge on the genome, phenome, and environome across the CHD lifespan. We also summarize the potential of technology, especially machine learning, to facilitate longitudinal research by embracing big data and multicenter lifelong data collection.