Pediatric Cardiac Genomics Consortium Research Articles

Genomic rare variant mechanisms for congenital cardiac laterality defect: A digenic model approach.

Laterality defects are defined by perturbations in the usual left-right asymmetry of organs. Due to low known genetic etiology of congenital heart disease (CHD) cases (less than 40%), we used a digenic model approach for the identification of contributing variants in known laterality defect genes (N = 115) in the exome/genome sequencing (ES/GS) data from individuals with clinically diagnosed laterality defects. The unsolved ES/GS data were analyzed from three CHD cohorts: Baylor College of Medicine-Genomics Research to Elucidate the Genetics of Rare Diseases (BCM-GREGoR; N = 247 proband ES), Gabriella Miller Kids First Pediatric Research program (Kids First; N = 158 trio GS), and Pediatric Cardiac Genomics Consortium (PCGC; N = 163 trio ES), and trans-heterozygous digenic variants were identified in 2.8% (inherited digenic variants in 0.4%), 8.2%, and 13.5% cases respectively, which was significantly higher as compared to 602 control trios provided by the 1000 Genomes Project (p = 0.001, 1.4e-07, and 8.9e-13, respectively). Trans-heterozygous digenic variants were also identified in 0.4%, and 1.4% cases with non-laterality CHD in Kids First and PCGC datasets, respectively, which was not statistically significant as compared to control trios ( p = 1, and 0.059, respectively). Altogether, in laterality cohorts, 23% of digenic pairs were in the same structural complex of motile cilia. Out of 39 unique digenic pairs in laterality CHD, 29 are more likely to be potential digenic hits as predicted by DiGePred tool. These findings provide further evidence that digenic epistatic interaction can contribute to the complex genetics of laterality defects.

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.

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

BackgroundCongenital 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.MethodsIn 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.ResultsBy 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.ConclusionsOur 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.

Abstract We088: Spatiotemporal analysis of cardiac progenitor cells reveals migratory characteristics during epithelial-mesenchymal transition

Introduction: Congenital heart defects (CHD) are one of the most common types of birth defects, with a rising prevalence in mild types. The most frequent CHDs include anomalies in the cardiac outflow tract (OFT), which mainly derives from multipotent cardiac progenitor cells termed second heart field (SHF). Hence, dysregulation of highly synchronized, chronological sequence of proliferation and differentiation of SHF cells could lead to severe CHDs. As the SHF contributes entirely to the OFT, mutations in the SHF-related genes lead to major arterial pole defects which account for one third of CHDs in newborn children. Investigating how these genes regulate cell-cell behavior and communication is of vital importance. Hypothesis and Methods: In this study, we employed a multidimensional approach to assess the hypothesis that the dynamic behavior of SHFs is regulated by key genes implicated in CHD pathogenesis. Leveraging single-cell RNA sequencing (RNA-seq) data obtained from experimentally dissected mouse OFT, we delineated distinct epithelial-to-mesenchymal transition states within SHF cell populations. Additionally, we developed a quantitative metric to assess SHF cell’s migratory level and integrated it with spatial transcriptomic analyses to map the developmental trajectory of SHFs. Results and Conclusion: Through spatiotemporal analysis, we identified a panel of key genes associated with SHF migration, shedding light on the molecular mechanisms underlying OFT development during early embryonic stages. Furthermore, we leveraged the data from The Pediatric Cardiac Genomics Consortium (PCGC) study (phs001194.v3.p2) which comprises a large cohort of CHD patients (13716 participants) and a proportion of 21.68% identified with OFT obstruction in its sub-study. In conclusion, using these datasets and quantitative metric being developed, we validated the SHF-derived genes in the PCGC participants and revealed specific expression patterns of these genes associated with OFT-specific CHDs. These results would benefit the understanding of the genetic regulation of SHF proliferation and differentiation, which is crucial for early detection and precise surgical intervention in CHD patients.

Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure

Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.

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

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. 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). 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. 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.

Abstract P1008: Characterizing Complex Tandem Repeat Variants And Their Contribution To Congenital Heart Disease

Congenital heart disease (CHD) is a major cause of childhood mortality and lifelong morbidity in children and adults. CHD has a strong genetic basis, with exome and short read whole genome sequencing (srWGS) identifying genetic contributions to CHD risk in around 45% of affected individuals, while the remaining 55% have not had a specific genetic risk identified. Variation in tandem repeats (TRs), defined as repeated sequences of base pairs, has been implicated in several diseases and can affect gene expression. TR polymorphism in coding or regulatory regions of CHD related genes can alter function and expression, thereby modifying risk of CHD in patients. Identifying variants in TRs has been a challenge due to multiple variants at each site, as well as difficulty resolving long expansions with short read sequencing technologies. New bioinformatic tools have enabled identification of high-confidence short-TR (STR) variants in srWGS. Additionally, long read whole genome sequencing (lrWGS), with read lengths of 10-20 kilobases, enables genotyping of longer TRs that are missed by srWGS. We hypothesized that patients with CHD will have a higher burden of de novo and transmitted TRs near known CHD genes. We identified de novo and transmitted STR variants near known CHD genes in srWGS data from 1900 CHD proband and their parents in the Pediatric Cardiac Genomics Consortium (PCGC), and 1611 non-CHD probands and their parents. Transmitted STR variants in CHD probands were enriched in 5’-UTR, introns, and promoters of CHD genes compared to non-CHD probands. We identified large de novo repeats near known CHD genes such as NOTCH2 and RBFOX2 . Additionally we used Pacbio HiFi lrWGS on 150 PCGC probands without an established etiology for CHD. Combining these analyses, we identified 3,243 repeat regions with low read depth in srWGS, and therefore unable to be resolved accurately, near known CHD genes and from lrWGS we assess length polymorphisms using Tandem Repeat Finder. TRs that harbor large variation in length were identified within intronic regions of CHD genes including FLT4 , NFATC1 , and PKD1 . We suggest that polymorphic repeat regions provide new candidate variants or altering gene transcription or splicing and thereby contribute to CHD.

Expanding the phenome and variome of the ROBO-SLIT pathway in congenital heart defects: toward improving the genetic testing yield of CHD

BackgroundRecent studies have shown the implication of the ROBO-SLIT pathway in heart development. Within this study, we aimed to further assess the implication of the ROBO and SLIT genes mainly in bicuspid aortic valve (BAV) and other human congenital heart defects (CHD).MethodsWe have analyzed a cohort of singleton exome sequencing data comprising 40 adult BAV patients, 20 pediatric BAV patients generated by the Pediatric Cardiac Genomics Consortium, 10 pediatric cases with tetralogy of Fallot (ToF), and one case with coarctation of the aorta. A gene-centered analysis of data was performed. To further advance the interpretation of the variants, we intended to combine more than 5 prediction tools comprising the assessment of protein structure and stability.ResultsA total of 24 variants were identified. Only 4 adult BAV patients (10%) had missense variants in the ROBO and SLIT genes. In contrast, 19 pediatric cases carried variants in ROBO or SLIT genes (61%). Three BAV patients with a severe phenotype were digenic. Segregation analysis was possible for two BAV patients. For the homozygous ROBO4: p.(Arg776Cys) variant, family segregation was consistent with an autosomal recessive pattern of inheritance. The ROBO4: c.3001 + 3G > A variant segregates with the affected family members. Interestingly, these variants were also found in two unrelated patients with ToF highlighting that the same variant in the ROBO4 gene may underlie different cardiac phenotypes affecting the outflow tract development.ConclusionOur results further reinforce the implication of the ROBO4 gene not only in BAV but also in ToF hence the importance of its inclusion in clinical genetic testing. The remaining ROBO and SLIT genes may be screened in patients with negative or inconclusive genetic tests.

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

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. 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. 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. 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.

Prevalence of Genetic Diagnoses in a Cohort With Valvar Pulmonary Stenosis.

Valvar pulmonary stenosis (vPS) accounts for 8% to 12% of congenital heart disease cases. Multiple genetic syndromes are associated with vPS, most commonly Noonan syndrome, but the cause is unknown in most cases. We analyzed genomic data from a large cohort with vPS to determine the prevalence of genetic diagnosis. The Pediatric Cardiac Genomics Consortium database was queried to identify probands with vPS without complex congenital heart disease or aneuploidy and with existing whole exome or genome sequencing. A custom analysis workflow was used to identify likely pathogenic or pathogenic variants in disease-associated genes. Demographic and phenotypic characteristics were compared between groups with and without molecular diagnoses. Data from 119 probands (105 trios) were included. A molecular diagnosis was identified in 22 (18%); 17 (14%) had Noonan syndrome or a related disorder. Extracardiac and neurodevelopmental comorbidities were seen in 67/119 (56%) of probands. Molecular diagnosis was more common in those with extracardiac and neurodevelopmental phenotypes than those without (18/67 versus 4/52, P=0.0086). Clinicians should have high suspicion for a genetic diagnosis in individuals with vPS, particularly if additional phenotypes are present. Our results suggest that clinicians should consider offering sequencing of at least the known congenital heart disease and RASopathy genes to all individuals with vPS, regardless of whether that individual has extracardiac or neurodevelopmental phenotypes present.

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

The genetic architecture of sporadic congenital heart disease (CHD) is characterized by enrichment in damaging de novo variants in chromatin-modifying genes. To test the hypothesis that gene pathways contributing to de novo forms of CHD are distinct from those for recessive forms, we analyze 2391 whole-exome trios from the Pediatric Cardiac Genomics Consortium. We deploy a permutation-based gene-burden analysis to identify damaging recessive and compound heterozygous genotypes and disease genes, controlling for confounding effects, such as background mutation rate and ancestry. Cilia-related genes are significantly enriched for damaging rare recessive genotypes, but comparatively depleted for de novo variants. The opposite trend is observed for chromatin-modifying genes. Other cardiac developmental gene classes have less stratification by mode of inheritance than cilia and chromatin-modifying gene classes. Our analyses reveal dominant and recessive CHD are associated with distinct gene functions, with cilia-related genes providing a reservoir of rare segregating variation leading to CHD.

Association of Rare Recurrent Copy Number Variants With Congenital Heart Defects Based on Next-Generation Sequencing Data From Family Trios.

Congenital heart defects (CHDs) are a common birth defect, affecting approximately 1% of newborn children in the United States. As previously reported, a significant number of CHDs are potentially attributed to altered copy number variants (CNVs). However, as many genomic variants are rare, a large-scale CNV triad study is necessary to characterize the genetic architecture of CHD. We used whole-exome sequencing (WES) data generated by the Pediatric Cardiac Genomics Consortium (PCGC), including a discovery dataset of 2,103 individuals from 760 nuclear family trios and an independent replication set of 4,808 individuals from 1,712 trios. The candidate targets uncovered were further validated through different platforms, including the Omni single-nucleotide polymorphism (SNP) array chip in 1,860 individuals and the whole-genome sequencing (WGS) data in 33 trios. The genes harboring CNVs of interest were then investigated for expression alternations based on cardiac tissue RNA-Seq data. We identified multiple CNVs in the WES data that associated with specific sub-phenotypes of CHD in approximately 2,400 families, including 98 de novo CNV regions. We identified five CNV loci harboring LIMS1, GCC2, RANBP2, TTC3, and MAP3K7CL, respectively, where those genes are highly expressed in human heart and/or mouse embryo heart at 15 days. Five novel CNV loci were uncovered, demonstrating altered expression of the respective candidate genes involved. To our knowledge, this is the largest trio-based WES study of CHD and, in addition to uncovering novel CHD targets, presents an extensive resource with the potential to provide important insights to the architecture and impact of CNVs in CHD.

ORE identifies extreme expression effects enriched for rare variants.

Non-coding rare variants (RVs) may contribute to Mendelian disorders but have been challenging to study due to small sample sizes, genetic heterogeneity and uncertainty about relevant non-coding features. Previous studies identified RVs associated with expression outliers, but varying outlier definitions were employed and no comprehensive open-source software was developed. We developed Outlier-RV Enrichment (ORE) to identify biologically-meaningful non-coding RVs. We implemented ORE combining whole-genome sequencing and cardiac RNAseq from congenital heart defect patients from the Pediatric Cardiac Genomics Consortium and deceased adults from Genotype-Tissue Expression. Use of rank-based outliers maximized sensitivity while a most extreme outlier approach maximized specificity. Rarer variants had stronger associations, suggesting they are under negative selective pressure and providing a basis for investigating their contribution to Mendelian disorders. ORE, source code, and documentation are available at https://pypi.python.org/pypi/ore under the MIT license. Supplementary data are available at Bioinformatics online.

Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors.

Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome-wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared with XHMM, and a significant enrichment of 15q11.2 deletions compared with controls. In addition, MEM identified eight cases of uniparental disomy, sample switches, and DNA contamination. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools.

The Congenital Heart Disease Genetic Network Study: Cohort description.

The Pediatric Cardiac Genomics Consortium (PCGC) designed the Congenital Heart Disease Genetic Network Study to provide phenotype and genotype data for a large congenital heart defects (CHDs) cohort. This article describes the PCGC cohort, overall and by major types of CHDs (e.g., conotruncal defects) and subtypes of conotrucal heart defects (e.g., tetralogy of Fallot) and left ventricular outflow tract obstructions (e.g., hypoplastic left heart syndrome). Cases with CHDs were recruited through ten sites, 2010–2014. Information on cases (N = 9,727) and their parents was collected through interviews and medical record abstraction. Four case characteristics, eleven parental characteristics, and thirteen parent-reported neurodevelopment outcomes were summarized using counts and frequencies and compared across CHD types and subtypes. Eleven percent of cases had a genetic diagnosis. Among cases without a genetic diagnosis, the majority had conotruncal heart defects (40%) or left ventricular outflow tract obstruction (21%). Across CHD types, there were significant differences (p<0.05) in the distribution of all four case characteristics (e.g., sex), four parental characteristics (e.g., maternal pregestational diabetes), and five neurodevelopmental outcomes (e.g., learning disabilities). Several characteristics (e.g., sex) were also significantly different across CHD subtypes. The PCGC cohort is one of the largest CHD cohorts available for the study of genetic determinants of risk and outcomes. The majority of cases do not have a genetic diagnosis. This description of the PCGC cohort, including differences across CHD types and subtypes, provides a reference work for investigators who are interested in collaborating with or using publically available resources from the PCGC.

Genome-Wide Association Studies and Meta-Analyses for Congenital Heart Defects.

Maternal and inherited (ie, case) genetic factors likely contribute to the pathogenesis of congenital heart defects, but it is unclear whether individual common variants confer a large risk. To evaluate the relationship between individual common maternal/inherited genotypes and risk for heart defects, we conducted genome-wide association studies in 5 cohorts. Three cohorts were recruited at the Children's Hospital of Philadelphia: 670 conotruncal heart defect (CTD) case-parent trios, 317 left ventricular obstructive tract defect (LVOTD) case-parent trios, and 406 CTD cases (n=406) and 2976 pediatric controls. Two cohorts were recruited through the Pediatric Cardiac Genomics Consortium: 355 CTD trios and 192 LVOTD trios. We also conducted meta-analyses using the genome-wide association study results from the CTD cohorts, the LVOTD cohorts, and from the combined CTD and LVOTD cohorts. In the individual genome-wide association studies, several genome-wide significant associations (P≤5×10-8) were observed. In our meta-analyses, 1 genome-wide significant association was detected: the case genotype for rs72820264, an intragenetic single-nucleotide polymorphism associated with LVOTDs (P=2.1×10-8). We identified 1 novel candidate region associated with LVOTDs and report on several additional regions with suggestive evidence for association with CTD and LVOTD. These studies were constrained by the relatively small samples sizes and thus have limited power to detect small to moderate associations. Approaches that minimize the multiple testing burden (eg, gene or pathway based) may, therefore, be required to uncover common variants contributing to the risk of these relatively rare conditions.

Acquired Mutations Link Congenital Heart Disease, Neurodevelopmental Disorders

Back to table of contents Previous article Next article Clinical and Research NewsFull AccessAcquired Mutations Link Congenital Heart Disease, Neurodevelopmental DisordersNick ZagorskiNick ZagorskiSearch for more papers by this authorPublished Online:4 Feb 2016https://doi.org/10.1176/appi.pn.2016.1b16AbstractAbout 20 percent of children with severe congenital heart disease have an excess of mutations that are also commonly found in children with developmental problems such as autism.A study published December 4 in Science suggests that neurodevelopmental abnormalities in children with congenital heart disease may arise from the acquisition of harmful de novo gene mutations. These are not inherited but rather spontaneously occur during fetal development. These abnormalities include cognitive, motor, social, and language impairments.Michelle Massi“Finding this strong association between the developing heart and brain was a bit surprising, for while the heart and brain are both complex organs, they do separate early in the development process,” said study coauthor Jonathan Kaltman, M.D., who is the administrator of the National Heart, Lung, and Blood Institute’s (NHLBI) Bench to Bassinet Program, which funded this study.“At the same time, it makes sense clinically, given that there are several inherited disorders such as Down’s syndrome or DiGeorge syndrome, which feature both cardiac and neurological problems.”Investigators from the NHLBI’s Pediatric Cardiac Genomics Consortium used a technique known as exome sequencing to scan all the protein-encoding regions of the genome in over 1,200 affected family trios (a child with congenital heart disease [CHD] and his or her parents) along with 900 control trios without CHD.They uncovered almost 400 potentially harmful de novo mutations that significantly contribute to the risk of co-occurring CHD and neurodevelopmental disorders.While an excess number of these harmful mutations were found in only 2 percent of patients who had isolated CHD, the prevalence rose in children with more complications. The mutations were present in about 10 percent of patients who also had neurodevelopmental disorders or other extracardiac congenital anomalies (such as limb or kidney defects), and 20 percent of patients who had both.When the researchers compared the genetic data from children with CHD and children with neurodevelopmental disorders but no heart problems, they found 85 mutations were present in both groups—more than twice as many as would be expected by random chance.“These findings show enough statistical risk of developing neurodevelopmental disabilities when these particular gene mutations are present that we might consider developing a genetic test for patients with CHD,” Kaltman told Psychiatric News. Such a test could help to identify high-risk children for early interventions that might help to limit developmental delays and improve functioning, he said.In addition to the NHLBI, this study was supported in part by the National Human Genome Research Institute, the Howard Hughes Medical Institute, and Simons Foundation for Autism Research. ■An abstract of “De Novo Mutations in Congenital Heart Disease With Neurodevelopmental and Other Congenital Anomalies” can be accessed here. ISSUES NewArchived

Public Health Science Agenda for Congenital Heart Defects: Report From a Centers for Disease Control and Prevention Experts Meeting

Congenital heart defects (CHDs) are the most common type of birth defect, affecting ≈1% of births per year.[1][1] Although survival has been improving over time, there remain numerous gaps in the understanding of the public health impact of CHDs across the lifespan. Recognizing that there was “a

The Congenital Heart Disease Genetic Network Study

Congenital heart defects (CHD) are the leading cause of infant mortality among birth defects, and later morbidities and premature mortality remain problematic. Although genetic factors contribute significantly to cause CHD, specific genetic lesions are unknown for most patients. The National Heart, Lung, and Blood Institute-funded Pediatric Cardiac Genomics Consortium established the Congenital Heart Disease Genetic Network Study to investigate relationships between genetic factors, clinical features, and outcomes in CHD. The Pediatric Cardiac Genomics Consortium comprises 6 main and 4 satellite sites at which subjects are recruited, and medical data and biospecimens (blood, saliva, cardiovascular tissue) are collected. Core infrastructure includes an administrative/data-coordinating center, biorepository, data hub, and core laboratories (genotyping, whole-exome sequencing, candidate gene evaluation, and variant confirmation). Eligibility includes all forms of CHD. Annual follow-up is obtained for probands <1-year-old. Parents are enrolled whenever available. Enrollment from December 2010 to June 2012 comprised 3772 probands. One or both parents were enrolled for 72% of probands. Proband median age is 5.5 years. The one third enrolled at age <1 year are contacted annually for follow-up information. The distribution of CHD favors more complex lesions. Approximately, 11% of probands have a genetic diagnosis. Adequate DNA is available from 97% and 91% of blood and saliva samples, respectively. Genomic analyses of probands with heterotaxy, atrial septal defects, conotruncal, and left ventricular outflow tract obstructive lesions are underway. The scientific community's use of Pediatric Cardiac Genomics Consortium resources is welcome.