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BACKGROUND: Known genetic causes of congenital heart disease (CHD) explain METHODS: We tested de novo variants from trio studies of 2649 CHD probands and their parents, as well as rare (allele frequency, − 6 ) variants from 4472 CHD probands in the Pediatric Cardiac Genetics Consortium through a combined computational and in vitro approach. RESULTS: We identified 53 de novo and 74 rare variants in CHD cases that alter splicing and thus are loss of function. Of these, 77 variants are in known dominant, recessive, and candidate CHD genes, including KMT2D and RBFOX2 . In 1 case, we confirmed the variant’s predicted impact on RNA splicing in RNA transcripts from the proband’s cardiac tissue. Two probands were found to have 2 loss-of-function variants for recessive CHD genes HECTD1 and DYNC2H1 . In addition, SpliceAI—a predictive algorithm for altered RNA splicing—has a positive predictive value of ≈93% in our cohort. CONCLUSIONS: Through assessment of RNA splicing, we identified a new loss-of-function variant within a CHD gene in 78 probands, of whom 69 (1.5%; n=4472) did not have a previously established genetic explanation for CHD. Identification of splice-altering variants improves diagnostic classification and genetic diagnoses for CHD. REGISTRATION: URL: https://clinicaltrials.gov ; Unique identifier: NCT01196182.

Background: Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. Methods: We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. Results: Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P =1.49×10 −8 ) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P =1.46×10 − 8 ) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9 . A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P =2.6×10 − 8 ) physically interacts with NCAM1 ( P FDR =1.86×10 − 27 ), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. Conclusions: We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.

Background:Congenital heart disease (CHD) is the most common anomaly at birth, with a prevalence of ≈1%. While infants born to mothers with diabetes or obesity have a 2- to 3-fold increased incidence of CHD, the cause of the increase is unknown. Damaging de novo variants (DNV) in coding regions are more common among patients with CHD, but genome-wide rates of coding and noncoding DNVs associated with these prenatal exposures have not been studied in patients with CHD.Methods:DNV frequencies were determined for 1812 patients with CHD who had whole-genome sequencing and prenatal history data available from the Pediatric Cardiac Genomics Consortium’s CHD GENES study (Genetic Network). The frequency of DNVs was compared between subgroups usingttest or linear model.Results:Among 1812 patients with CHD, the number of DNVs per patient was higher with maternal diabetes (76.5 versus 72.1,ttestP=3.03×10−11), but the difference was no longer significant after including parental ages in a linear model (paternal and maternal correctionP=0.42). No interaction was observed between diabetes risk and parental age (paternal and maternal interactionP=0.80 and 0.68, respectively). No difference was seen in DNV count per patient based on maternal obesity (72.0 versus 72.2 for maternal body mass index 30,ttestP=0.86).Conclusions:After accounting for parental age, the offspring of diabetic or obese mothers have no increase in DNVs compared with other children with CHD. These results emphasize the role for other mechanisms in the cause of CHD associated with these prenatal exposures.Registration:URL:https://clinicaltrials.gov; NCT01196182.

Genetic diseases that affect the cardiovascular system are relatively common and include cardiac channelopathies, cardiomyopathies, aortopathies, hypercholesterolemias, and structural diseases of the heart and great vessels. The rapidly expanding availability of clinical genetic testing leverages decades of research into the genetic origins of these diseases, helping inform diagnosis, clinical management, and prognosis. Although a number of guidelines and statements detail best practices for cardiovascular genetic testing, there is a paucity of pediatric-focused statements addressing the unique challenges in testing in this vulnerable population. In this scientific statement, we seek to coalesce the existing literature around the use of genetic testing for cardiovascular disease in infants, children, and adolescents.