Abstract
Congenital heart defects (CHDs) have a neonatal incidence of 0.8–1% (refs. 1,2). Despite abundant examples of monogenic CHD in humans and mice, CHD has a low absolute sibling recurrence risk (∼2.7%)3, suggesting a considerable role for de novo mutations (DNMs) and/or incomplete penetrance4,5. De novo protein-truncating variants (PTVs) have been shown to be enriched among the 10% of 'syndromic' patients with extra-cardiac manifestations6,7. We exome sequenced 1,891 probands, including both syndromic CHD (S-CHD, n = 610) and nonsyndromic CHD (NS-CHD, n = 1,281). In S-CHD, we confirmed a significant enrichment of de novo PTVs but not inherited PTVs in known CHD-associated genes, consistent with recent findings8. Conversely, in NS-CHD we observed significant enrichment of PTVs inherited from unaffected parents in CHD-associated genes. We identified three genome-wide significant S-CHD disorders caused by DNMs in CHD4, CDK13 and PRKD1. Our study finds evidence for distinct genetic architectures underlying the low sibling recurrence risk in S-CHD and NS-CHD.
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Acknowledgements
We thank the patients and their families for their participation and patience. The authors thank J. Lord for proofreading this manuscript and the Exome Aggregation Consortium for making their data available. The Deciphering Developmental Disorders study presents independent research commissioned by the Health Innovation Challenge Fund (grant HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the UK Department of Health, and the Wellcome Trust Sanger Institute (grant WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of the Wellcome Trust or the UK Department of Health. The research team acknowledges the support of the National Institutes for Health Research through the Comprehensive Clinical Research Network. The authors wish to thank the Sanger Human Genome Informatics team, the DNA pipelines team and the Core Sequencing team for their support in generating and processing the data. We would like to thank the Pediatric Cardiac Genomics Consortium (PCGC) and dbGAP for making the data publicly available. This study was supported by the German Center for Cardiovascular Research (DZHK) partner sites Berlin, Kiel and Competence Network for Congenital Heart Defects, National Register for Congenital Heart Defects. Participants in the INTERVAL randomized controlled trial were recruited with the active collaboration of NHS Blood and Transplant England, which has supported field work and other elements of the trial. DNA extraction and genotyping was funded by the National Institute of Health Research (NIHR), the NIHR BioResource and the NIHR Cambridge Biomedical Research Centre. The academic coordinating center for INTERVAL was supported by core funding from the NIHR Blood and Transplant Research Unit in Donor Health and Genomics, UK Medical Research Council (G0800270), British Heart Foundation (SP/09/002), and NIHR Research Cambridge Biomedical Research Centre. J.D.B., K.S. and A.K. are funded by British Heart Foundation Programme Grant RG/13/10/30376. A.W. is funded by a British Heart Foundation Clinical Fellowship FS/14/51/30879. D.R.F. is funded through an MRC Human Genetics Unit program grant to the University of Edinburgh. S.H.A.T., S.O.O. and R.M.A.-S. were supported by funding from King Abdullah International Medical Research Center (grant number RC12/037). J.B. was supported by the Klinisch Onderzoeksfonds UZ; B.T. was supported by the CHAMELEO Marie Curie Career Integration Grant; J.J.L. and M.G. Eddy Merckx Research grant. K.D. was funded by the GOA/2012/015 grant. A.K.M., D.M. and S.M. were supported by the Heart and Stroke Foundation of Ontario, Canadian Institutes of Health Research.
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A.W., J.B., S.H.A.T., B.T., H.A.-K., S. Banka, U.M.M.B., J.B., F. Berger, S. Bhattacharya., F. Bu'Lock, N.C., C.C., H.C., I.D., J.D., A.F., M.G., E.H., K.H., T.H., A.-K.K., H.-H.K., K.L., A.K.L., J.J.L., A.K.M., K.M., C.M., R.N.-E., S.O.O., W.H.O., S.-M.P., M.J.P., T.P., L.R., D.J.R., J.S., K.S., B.S., C.T., O.T., H.W., D.W., M.W., S.M., P.E.F.D., B.K., J.G., R.M.A.-S., S.K., C.F.W., H.V.F., K.D., D.R.F. and J.D.B. recruited the patients. M-P.H., A.W., J.B., H.A.-K., S. Banka, U.M.M.B., J.B., F. Berger, S. Bhattacharya, F. Bu'Lock, N.C., C.C., H.C., I.D., A.F., M.G., E.H., T.H., A.-K.K., H.-H.K., K.L., A.K.L., J.J.L., A.K.M., K.P.M., K.M., R.N.-E., S.O.O., S.-M.P., M.J.P., L.R., K.S., B.S., C.T., O.T., H.W., D.W., M.W., S.M., P.E.F.D., B.K., J.G., R.M.A.-S., S.K., C.F.W., H.V.F., K.D., D.R.F. and J.D.B. participated in initial phenotyping or classification of patients. A.W., J.B., S.H.A.T., B.T., K.H., A.K., D.M., K.P.M., T.P. and K.S. performed sample preparation. M.-P.H., S.H.A.T., E.P., D.R. and K.H. performed validation experiments. A.S., M.-P.H., S.H.A.T., S.M., P.E.F.D., B.K., J.G., R.M.A.-S., S.K., C.F.W., H.V.F., J.C.B., K.D., D.R.F., J.D.B. and M.E.H. designed the study. A.S., M.-P.H., A.W., J.B., S.H.A.T., J.M., T.W.F., T.S., G.J.S., I.-G.C., A.D., M.O.P., J.C.B. and M.E.H. designed and developed the analysis strategy. A.S., M.-P.H., A.W., J.B., S.H.A.T., B.T., J.M., T.W.F., T.S., G.J.S., C.F.W., H.V.F., J.C.B., K.D., D.R.F., J.D.B. and M.E.H. interpreted the results. A.S., M.-P.H., A.W., J.D.B. and M.E.H. wrote the manuscript. M.E.H. supervised the project.
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M.E.H. is a cofounder of and holds shares in Congenica Ltd., a genetics diagnostic company.
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A list of members and affiliations appears in the Supplementary Note.
A list of members and affiliations appears in the Supplementary Note.
A list of members and affiliations appears in the Supplementary Note.
Integrated supplementary information
Supplementary Figure 1 Principal component analysis based on a selected set of polymorphic SNPs.
Transparent colored areas represent reference samples of different Hapmap3 populations (African, Asian, European, South-East Asian) as an indicator of ethnic ancestry. Black dots represent samples in the A) cases or B) controls. Dashed lines represent the thresholds used to classify a sample as being of European ancestry (PC1 >= 0.01 and PC2 >= 0.04)
Supplementary Figure 2 Probands with de novo CHD4 mutations.
A) Clinical synopsis of the observed phenotypes across patients carrying CHD4 mutations. Columns represent single probands, shades of cells represent the number of probands sharing a phenotype in the given phenotypic categories. Photographs of affected probands are shown for which consent could be obtained for publication. B) Protein plot showing CHD4 protein domains and the distribution of de novo mutations.
Supplementary Figure 3 Probands with de novo PRKD1 mutations.
A) Clinical synopsis of the observed phenotypes across patients carrying PRKD1 mutations. Columns represent single probands, shades of cells represent the number of probands sharing a phenotype in the given phenotypic categories. Photographs of affected probands are shown for which consent could be obtained for publication. B) Protein plot showing PRKD1 protein domains and the distribution of de novo mutations. Two probands share identical missense mutations (Gly592Arg).
Supplementary Figure 4 High-confidence interactions found in the STRING PPI database in top-ranking set of CHD-associated genes.
Edges in the graph represent high confidence (STRING score > 0.9) protein-protein interactions between top ranking genes (FDR < 50%) in the integrated de novo and inherited variant analysis. Known CHD-associated genes are colored blue, other nodes are scaled according to their association FDR. The size of nodes is scaled by its degree.
Supplementary Figure 5 Saturation analysis for detecting haploinsufficient S-CHD-associated genes.
A box plot showing the distribution of statistical power to detect a significant enrichment of PTV mutations across 19252 genes in the genome, for different numbers of trios studied, from 500 trios to 10,000 trios. Line within the box shows the median, box corresponds to the first and third quartiles (the 25th and 75th percentiles) and whiskers correspond to most extreme values within 1.5 times the interquartile range from the box.
Supplementary Figure 6 Distribution of pairwise discordance between any sample pair in the cohort.
Samples with the lowest median coverage in sample-pairs with a discordance below 20% were excluded from further analysis.
Supplementary Figure 7 Comparison of candidate de novo mutations called by DeNovoGear between publicly available data sets of the DDD study and the study by Zaidi et al.
Allelic balance distributions are shown for transitions (ts) and transversions (tv) in both datasets. An overrepresentation of transversion events is found in the Zaidi et al. dataset at low allelic balances, primarily made up of G>T transversions.
Supplementary Figure 8 Principal component analysis of common SNPs for syndromic CHD probands and non-syndromic CHD probands.
First two components of PCA analysis, blue dots represent non-syndromic CHD cases while orange dots represent syndromic CHD cases. Sideplots represent the marginal distributions of the principal components, stratified by syndromic status.
Supplementary Figure 9 Number of cases and variants by sex stratified by syndromic status.
A) Counts by sex and syndromic status of samples included in the burden analysis. B) Mean number of B) de novo and C) inherited PTV variants stratified by sex and syndromic status. Error bars represent 99% confidence intervals on the measured means.
Supplementary Figure 10 Box plots for transition/transversion (Ti/Tv) ratios of rare exomic inherited variants for samples used in the burden analysis.
Samples are stratified by syndromic status. Whiskers represent the highest/lowest value within 1.5 times the interquartile range. Upper and lower hinges represent the 25th and 75th percentiles, respectively.
Supplementary Figure 11 Box plots showing counts of rare inherited synonymous variants for samples used in the burden analysis.
Samples are stratified by syndromic status. Whiskers represent the highest/lowest value within 1.5 times the interquartile range. Upper and lower hinges represent the 25th and 75th percentiles, respectively.
Supplementary Figure 12 Mean number of autosomal de novo synonymous mutations stratified by syndromic status.
Dashed line represents the expected synonymous mutation rate (Samocha et al., 2014). Error bars represent the 99% confidence interval for the measured mean.
Supplementary Figure 13 Quantile–quantile plots for case–control counts using Fisher’s exact test statistics.
QQ-plots considering case/control A) PTV counts or B) missense counts using Fisher’s exact test statistics to test for systematic deviations from the null hypothesis.
Supplementary Figure 14 CDK13 protein structure by homology modeling.
CDK13 protein structure by homology modeling on the known CDK12 structure with co-crystallized ATP-substitute AMP ligand: mutated residues are shown in green, catalyzing Magnesium ion is shown in magenta, Cyclin domain is shown in orange with it’s interacting residue shown in cyan.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–14 (PDF 1835 kb)
Supplementary Note
Supplementary Note and Supplementary Tables 1–6, 13, 14, 19, 24 and 27 (PDF 1884 kb)
Supplementary Table 7
Inherited rare PTVs in Tier 1 monoallelic CHD genes (XLSX 10 kb)
Supplementary Table 8
Results of de novo enrichment analysis in the S-CHD cohort (XLSX 66 kb)
Supplementary Table 9
Results of de novo enrichment analysis in the "unresolved" S-CHD cohort (XLSX 50 kb)
Supplementary Table 10
Clinical description of probands carrying de novo mutations in CDK13 (XLSX 72 kb)
Supplementary Table 11
Clinical description of probands carrying de novo mutations in CHD4 (XLSX 74 kb)
Supplementary Table 12
Clinical description of probands carrying de novo mutations in PRKD1 (XLSX 75 kb)
Supplementary Table 15
Manual review of top-ranking genes from the (TADA) integrated de novo and inherited variant analysis (XLSX 68 kb)
Supplementary Table 16
Results of InnateDB Gene Ontology overrepresentation analysis (XLSX 241 kb)
Supplementary Table 17
Results of InnateDB Pathway overrepresentation analysis (XLSX 65 kb)
Supplementary Table 18
Overview of main analyses and their primary conclusions (XLSX 9 kb)
Supplementary Table 20
Manually curated set of known CHD-genes by tier and inheritance mode (XLSX 14 kb)
Supplementary Table 21
List of de novo variants in S-CHD cases called by DeNovoGear after filtering criteria were applied (XLSX 114 kb)
Supplementary Table 22
List of de novo variants in NS-CHD cases called by DeNovoGear after filtering criteria were applied (XLSX 151 kb)
Supplementary Table 23
List of de novo variants in S-CHD-DX cases (syndromic cases with no de novo variants in known developmental disorder genes) called by DeNovoGear after filtering criteria were applied (XLSX 82 kb)
Supplementary Table 25
1241 rare CNV calls made by CoNVex and passing automatic and manual quality control (XLSX 307 kb)
Supplementary Table 26
31 CNV calls overlapping known CHD-associated genes or top-ranking genes (FDR<10%) from the integrated de novo and inherited variant analysis (XLSX 19 kb)
Supplementary Table 28
Results of the integrated (TADA) de novo and inherited rare variant analysis (XLSX 3978 kb)
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Sifrim, A., Hitz, MP., Wilsdon, A. et al. Distinct genetic architectures for syndromic and nonsyndromic congenital heart defects identified by exome sequencing. Nat Genet 48, 1060–1065 (2016). https://doi.org/10.1038/ng.3627
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DOI: https://doi.org/10.1038/ng.3627
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