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Comparative Study
. 2016 Sep;48(9):1060-5.
doi: 10.1038/ng.3627. Epub 2016 Aug 1.

Distinct genetic architectures for syndromic and nonsyndromic congenital heart defects identified by exome sequencing

Alejandro Sifrim  1 , Marc-Phillip Hitz  1   2   3 , Anna Wilsdon  4 , Jeroen Breckpot  5 , Saeed H Al Turki  1   6   7 , Bernard Thienpont  8   9 , Jeremy McRae  1 , Tomas W Fitzgerald  1 , Tarjinder Singh  1 , Ganesh Jawahar Swaminathan  1 , Elena Prigmore  1 , Diana Rajan  1 , Hashim Abdul-Khaliq  10   11 , Siddharth Banka  12   13 , Ulrike M M Bauer  11 , Jamie Bentham  14 , Felix Berger  3   11   15 , Shoumo Bhattacharya  16 , Frances Bu'Lock  17 , Natalie Canham  18 , Irina-Gabriela Colgiu  1 , Catherine Cosgrove  16 , Helen Cox  19 , Ingo Daehnert  11   20 , Allan Daly  1 , John Danesh  1   21   22 , Alan Fryer  23 , Marc Gewillig  24 , Emma Hobson  25 , Kirstin Hoff  2   3 , Tessa Homfray  26 ; INTERVAL Study; Anne-Karin Kahlert  2   3   27 , Ami Ketley  4 , Hans-Heiner Kramer  2   3   11 , Katherine Lachlan  28   29   30 , Anne Katrin Lampe  31 , Jacoba J Louw  24 , Ashok Kumar Manickara  32 , Dorin Manase  32 , Karen P McCarthy  33 , Kay Metcalfe  13 , Carmel Moore  22 , Ruth Newbury-Ecob  34 , Seham Osman Omer  35 , Willem H Ouwehand  1   21   36   37 , Soo-Mi Park  38 , Michael J Parker  39 , Thomas Pickardt  11 , Martin O Pollard  1 , Leema Robert  40 , David J Roberts  21   41   42 , Jennifer Sambrook  22   36 , Kerry Setchfield  4 , Brigitte Stiller  11   43 , Chris Thornborough  17 , Okan Toka  11   44 , Hugh Watkins  16 , Denise Williams  19 , Michael Wright  45 , Seema Mital  32 , Piers E F Daubeney  46   47 , Bernard Keavney  48 , Judith Goodship  49 ; UK10K Consortium; Riyadh Mahdi Abu-Sulaiman  35   50   51 , Sabine Klaassen  3   11   52   53 , Caroline F Wright  1 , Helen V Firth  54 , Jeffrey C Barrett  1 , Koenraad Devriendt  5 , David R FitzPatrick  55 , J David Brook  4 ; Deciphering Developmental Disorders Study; Matthew E Hurles  1
Affiliations
Comparative Study

Distinct genetic architectures for syndromic and nonsyndromic congenital heart defects identified by exome sequencing

Alejandro Sifrim et al. Nat Genet. 2016 Sep.

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%), suggesting a considerable role for de novo mutations (DNMs) and/or incomplete penetrance. De novo protein-truncating variants (PTVs) have been shown to be enriched among the 10% of 'syndromic' patients with extra-cardiac manifestations. 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 findings. 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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Conflict of interest statement

Competing financial interests

M.E.H. is a co-founder of, and holds shares in, Congenica Ltd, a genetics diagnostic company.

Figures

Figure 1
Figure 1. Burden of de novo and inherited variants in NS-CHD compared to S-CHD
(A) Excess of DNMs compared to null mutation model. Excess of DNMs was computed as the ratio of the observed number of DNMs over the expectation given random mutation using a null gene-wise mutation rate model. P-values were computed using a Poisson model parameterized by the cumulative mutation rate across the gene set for the same number of probands (nS-CHD= 518, nNS-CHD= 847). We stratify by variant consequence and within known autosomal dominant CHD genes (n=78), autosomal dominant developmental disorder genes excluding autosomal dominant CHD genes (n=203) and all autosomal protein coding genes excluding autosomal dominant developmental disorder and CHD genes (n=17,404). No data is shown for silent variants in CHD genes for syndromic probands as no variants were detected. Error bars represent the 95% confidence interval. (B) Comparison of exome-wide excess of DNMs across different diseases stratified by variant consequence. (C) Excess of rare inherited variants (nS-CHD= 471, nNS-CHD= 663) compared to 12,031 controls of matched ancestry: Excess of DNMs was computed as the ratio of the observed number of rare inherited variants over the expected numbers as seen in controls. (D) Counts of de novo PTVs in S-CHD probands and rare inherited (INH) PTVs in NS-CHD probands in known monoallelic CHD-associated genes.
Figure 2
Figure 2. Gene-wise enrichment of de novo mutations
Gene-wise DNM enrichment was computed for A) the complete S-CHD cohort (n=518), B) ‘unresolved’ S-CHD trios without a plausible pathogenic DNM in known developmental disorder and CHD-associated genes (n=398). The probability of enrichment was computed given a Poisson distribution with the rate given by the gene-specific mutation rate multiplied by the number of chromosomes considered. This was performed for de novo PTVs and de novo missense variants independently. The de novo missense-enrichment probability was further combined with the probability of non-random clustering of de novo mutations using Fisher’s method and the minimum was taken between the combined and the original p-value. The minimum probability (considering either de novo PTVs or de novo missense mutations) was plotted. The dashed horizontal line represents genome-wide significance (p<1.31x10–6, Bonferronni corrected P-value of 0.05 corrected for 2x19,252 protein coding genes).
Figure 3
Figure 3. Overview of CDK13 mutations in S-CHD cases
A) Phenotype summary of probands carrying missense mutations in CDK13. Colors indicate the number of times a certain phenotype was observed in individuals carrying a de novo mutation in CDK13. Photographs of affected probands are shown for which consent could be obtained for publication. B) clustering of DNMs in Serine-Threonine kinase domain. Density plot displays a sliding window (±10 amino acids) missense variant count in the Non-Finnish European population of the Exome Aggregation Consortium data, showing a marked reduction of missense variants in the kinase domain. C) 3D protein structure of CDK13 by homology modelling adapted from CDK12. Mutated residues are marked in bright green. Catalysing Magnesium ion is highlighted in magenta, and the co-crystallized AMP ligand is portrayed in orange.
Figure 4
Figure 4. Integrated analysis of de novo and inherited variant enrichment using Hierarchical Bayesian modelling
Scatter plots representing Bayes factors (ratio of the evidence given the alternative model of the gene being associated with CHD over the evidence given the null model of the gene not being associated with CHD) for the de novo and inherited components of the model for PTVs and missense variants. The diagonal solid line represents the identity line, where equal signal is obtained from de novo variation compared to inherited variation. Genes at an FDR < 10% are labelled and colors represent different confidence thresholds.
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