Abstract
Congenital Diaphragmatic Hernia (CDH) is a common and often lethal birth defect characterized by diaphragmatic structural defects and pulmonary hypoplasia. CDH is isolated in 60% of newborns, but may also be part of a complex phenotype with additional anomalies. We performed whole exome sequencing (WES) on 87 individuals with isolated or complex CDH and on their unaffected parents, to assess the contribution of de novo mutations in the etiology of diaphragmatic and pulmonary defects and to identify new candidate genes. A combined analysis with 39 additional trios with complex CDH, previously published, revealed a significant genome-wide burden of de novo variants compared to background mutation rate and 900 control trios. We identified an increased burden of likely gene-disrupting (LGD, i.e. nonsense, frameshift, and canonical splice site) and predicted deleterious missense (D-mis) variants in complex and isolated CDH patients. Overall, an excess of predicted damaging de novo LGD and D-mis variants relative to the expected frequency contributed to 21% of complex cases and 12% of isolated CDH cases. The burden of de novo variants was higher in genes expressed in the developing mouse diaphragm and heart. Some overlap with genes responsible for congenital heart defects and neurodevelopmental disorders was observed in CDH patients within our cohorts. We propose that de novo variants contribute significantly to the development of CDH.
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Acknowledgements
We thank Barbara R. Pober for her inspiration and her seminal contributions to the project, and the physicians at MassGeneral Hospital for Children and Boston Children’s Hospital for their continued support: T. Buchmiller, C. C. Chen, D. Doody, S. J. Fishman, A. Goldstein, L. Holmes, T. Jaksic, R. Jennings, C. Kelleher, D. Lawlor, C.W. Lillehei, P. Masiakos, D. P. Mooney, K. Papadakis, R. Pieretti, M. Puder, D. P. Ryan, R. C. Shamberger, C. Smithers, J. Vacanti, and C. Weldon. We are also grateful to all of the families at the participating Simons Simplex Collection (SSC) sites, as well as the principal investigators (A. Beaudet, R. Bernier, J. Constantino, E. Cook, E. Fombonne, D. Geschwind, R. Goin-Kochel, E. Hanson, D. Grice, A. Klin, D. Ledbetter, C. Lord, C. Martin, D. Martin, R. Maxim, J. Miles, O. Ousley, K. Pelphrey, B. Peterson, J. Piggot, C. Saulnier, M. State, W. Stone, J. Sutcliffe, C. Walsh, Z. Warren, E. Wijsman).
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Sequencing services were provided through the RS&G Service by the Northwest Genomics Center at the University of Washington, Department of Genome Sciences, under U.S. Federal Government contract number HHSN268201100037C from the National Heart, Lung, and Blood Institute (r223 to M. Longoni). Funding was provided by the National Institute of Child Health and Human Development (NICHD/NIH, http://www.nichd.nih.gov) P01HD068250. Partial funding was provided by the NICHD/NIH grant HD057036, by the Columbia University’s Clinical and Translational Science Award (CTSA), and by the National Center for Advancing Translational Sciences/National Institutes of Health (NCATS-NCRR/NIH, ncats.nih.gov) grant UL1 RR024156. Philanthropic funding was obtained by CHERUBS, the National Greek Orthodox Ladies Philoptochos Society, Inc., and generous donations from The Wheeler foundation, Vanech Family Foundation, Larsen Family, Wilke Family, and many other families. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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439_2017_1774_MOESM1_ESM.xlsx
Supplementary material 1 (XLSX 17 kb) Table S1 Clinical and genetic data for MGH/CHB Cohort. Patients are ordered according to Study ID. If previously published in the Longoni et al. 2014 publication, a conversion matrix to the alternative study ID is provided. Samples necessitating whole genome amplification prior to library construction are indicated. Patient data include self-reported ethnicity, gender, isolated or complex (syndromic) phenotype, side of the diaphragmatic defect, type of the diaphragmatic defect (Bochdalek, Morgagni, eventration, agenesis, or not otherwise specified)
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Supplementary material 2 (DOCX 14 kb) Table S2 WES metrics for MGH/CHB Cohort. Read length, reads per sample, median and mean coverage at each targeted base, and percent of targeted bases with at least 15X reads are indicated for each of the three sequencing batches (Yale, UW1, UW2) along with number of samples per each batch. Mean of samples and standard deviation are reported
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Supplementary material 3 (XLSX 74 kb) Table S3 De novo variants in combined MGH/CHB and DHREAMS cohorts. The complete and annotated list of variants is provided. Proband ID, study cohort and symbols of genes with de novo variants are indicated, as are position of the variants and official nomenclature according to Human Genome Variation Society (HGVS) recommendations
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Supplementary material 4 (XLSX 73 kb) Table S4 Enrichr enrichment terms. The list of genes with de novo variants was associated to functional biological terms in a systematic way for data exploration and interpretation using the integrative web-based application Enrichr. Significant enrichments in three libraries are shown (ChEA for transcription factor regulation, 2016 update; Biocarta for metabolic and signaling pathways, 2016 update; Reactome for curated biological pathways, 2016 update)
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Supplementary material 5 (XLSX 18 kb) Table S5 Annotated nodes in protein–protein interaction analysis (GeNets). Nodes are indicated in alphabetical order. Evidence for their implication in CDH is provided: de novo (genes with de novo variants in human cohorts), human (genetic variants in human cohorts except de novo), mouse (mouse models with diaphragmatic defects), bioinformatics (identified by expanding protein–protein networks to first and second order interactors). Community numbers indicate which interaction subnetwork, if any, the proteins belong to
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Supplementary material 6 (XLSX 14 kb) Table S6 Annotated modules (WGCNA) with significant enrichment for CDH genes. Modules are listed by arbitrary names (pink, yellow, brown, and blue). Total number of genes, number of CDH genes, and number of genes with de novo variants are shown for each module. Hypergeometric enrichment p values indicate whether each module contains more CDH genes than expected by random distribution
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Supplementary material 8 (TIFF 72 kb) Fig. S1 Poisson fit of de novo variant distribution in Boston (MGH/CHB) and DHREAMS cohorts. Number of patients with 0 ~ 7 de novo variants in the MGH/CHB (purple) and DHREAMS (cyan) cohorts are indicated. The superimposed lines indicate the expected distribution
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Supplementary material 9 (TIFF 254 kb) Fig. S2 Correlation between diaphragm and heart expression ranks for genes with de novo variants. The distribution of de novo variants is shown according to gene expression ranks in the developing diaphragm (x-axis) and in the developing heart (y-axis). Lines indicate the top quartile of expression rank. Genes are color coded according to functional consequence of the de novo variants (top left), cohort and patient phenotype (top right), type of LGD variant (bottom left), and functional prediction of missense variants compared to silent variants (bottom right)
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Supplementary material 10 (TIFF 147 kb) Fig. S3 Networks in protein–protein interaction analysis (GeNets). Additional network analysis of proteins with de novo variants: entire set (A), top quartile of expression rank in the developing diaphragm (B) and heart (C). GeNets (http://apps.broadinstitute.org/genets) was used for biological network analysis and visualization, implementing machine learning to identify previously unknown pathway relationships and discover functional modules based on the GeNets Metanetwork v1.0 combining protein–protein interaction information from InWeb3 and Gene Expression Networks from GEO
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Longoni, M., High, F.A., Qi, H. et al. Genome-wide enrichment of damaging de novo variants in patients with isolated and complex congenital diaphragmatic hernia. Hum Genet 136, 679–691 (2017). https://doi.org/10.1007/s00439-017-1774-y
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DOI: https://doi.org/10.1007/s00439-017-1774-y