Assessing the contribution of rare variants to congenital heart disease through a large-scale case-control exome study

Several studies have demonstrated the value of large-scale human exome and genome data analysis, to maximise gene discovery in rare diseases. Using this approach, we have analysed the exomes of 4,747 cases and 52,881 controls, to identify single genes and digenic interactions which confer a substantial risk of congenital heart disease (CHD). We identified both rare loss-of-function and missense coding variants in ten genes which reached genome-wide significance (Bonferroni adjusted P < 0.05) and an additional four genes with a significant association at a false discovery rate ( FDR) threshold of 5%. We highlight distinct genetic contributions to syndromic and non-syndromic CHD at both single gene and digenic level, by independently analysing probands from these two groups. In addition, by integrative analysis of exome data with single-cell transcriptomics data from human embryonic hearts, we identified cardiac-specific cells as well as putative biological processes underlying the pathogenesis of CHD. In summary, our findings strengthen the association of known CHD genes, and have identified additional novel disease genes and digenic interactions contributing to the aetiology of CHD. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was partly funded by PROCEED project ERA PerMED joint Translational Call Initiative (DLR Funding reference number: 01KU1919) and the German Center for Cardiovascular Research (DZHK). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: EGAD00001002200: https://ega-archive.org/datasets/EGAD00001002200 EGAD00001000796: https://ega-archive.org/datasets/EGAD00001000796 EGAD00001000797: https://ega-archive.org/datasets/EGAD00001000797 EGAD00001000800: https://ega-archive.org/datasets/EGAD00001000800 EGAS00001000544: https://ega-archive.org/studies/EGAS00001000544 EGAS00001000775: https://web2.ega-archive.org/studies/EGAS00001000775 UK Biobank exome (Application number 44165): https://www.ukbiobank.ac.uk/enable-your-research/about-our-data/genetic-data I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes