Abstract
Mosaicism due to somatic mutations can cause multiple diseases including cancer, developmental and overgrowth syndromes, neurodevelopmental disorders, autoinflammatory diseases, and atrial fibrillation. With the increased use of next generation sequencing technology, multiple tools have been developed to identify low-frequency variants, specifically from matched tumor-normal tissues in cancer studies. To investigate whether mosaic variants are implicated in congenital heart disease (CHD), we developed a pipeline using the cancer somatic variant caller MuTect to identify mosaic variants in whole-exome sequencing (WES) data from a cohort of parent/affected child trios (n = 715) and a cohort of healthy individuals (n = 416). This is a novel application of the somatic variant caller designed for cancer to WES trio data. We identified two cases with mosaic KMT2D mutations that are likely pathogenic for CHD, but conclude that, overall, mosaicism detectable in peripheral blood or saliva does not account for a significant portion of CHD etiology.
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Acknowledgements
The authors are grateful to the patients and families who participated in this research and team members who supported subject recruitment and sequencing D.Awad, C. Breton, K. Celia, C. Duarte, D. Etwaru, N.Rishman, M. Daspakova, J. Kline, R. Korsin, A. Lanz, E. Marquez, D. Queen, A. Rodriguez, J. Rose, J.K. Sond, D. Warburton, A. Wilpers and R. Yee [Columbia Medical School]; B. McDonough, A. Monafo, J. Stryker [Harvard Medical School]; N. Cross [Yale School of Medicince]; S. M. Edman, J.L. Garbarini, J.E. Tusi, S.H. Woyciechowski (Children’s Hospital of Philadelphia); J. Ellashek and N. Tran (Children’s Hospital of Los Angeles); K. Flack, L. Panesar, N. Taylor (University College London); D. Gruber and N. Stellato (Steve and Alexandra Cohen Children’s Medical Center of New York); D. Guevara, A. Julian, M. MacNeal, C. Mintz (Icahn School of Medicine at Mount Sinai); and E. Taillie (University of Rochester School of Medicine and Dentistry]). We also thank the Simons Foundation for Autism Research for the contribution of control exome trios.
Funding
Funding was provided by the National Heart, Blood and Lung Institute from the following grants: U01-HL098147, U01-HL098123, U01-HL098162, U01-HL098153, U01-HL098163, and U01-HL098188.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Boards listed and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Institutional IRBs: Boston Children’s Hospital, Brigham and Women’s Hospital, Great Ormond Street Hospital, Children’s Hospital of Los Angeles, Children’s Hospital of Philadelphia, Columbia University Medical Center, Icahn School of Medicine at Mount Sinai, Rochester School of Medicine and Dentistry, Steven and Alexandra Cohen Children’s Medical Center of New York, and Yale School of Medicine.
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Informed consent was obtained from all individual participants or their parent/guardian included in this study.
Data availability
The PCGC datasets analyzed during the current study are available from dbGAP (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000571.v1.p1). Approved researchers can obtain the SSC population dataset used as controls in this study by applying at SFARI Base (https://base.sfari.org/).
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Online Resource Figure 1:
Depth of coverage (DOC) distribution for cases (red), original control bams (blue) and down sampled (ds) control bams (green). The mean DOC is 60x for both cases and down sampled controls allowing us to compare the number of mosaic variants in each cohort (PDF 433 kb)
Online ResourceFigure 2:
Distribution of the fraction of WES capture intervals with depth > = 15 (DIR 15 fraction) for WES cases (red), original control bams (blue) and down sampled (ds) control bams (green) (PDF 381 kb)
Online Resource Figure 3:
Schematic illustrating how MuTect somatic variant caller was used with WES trio data to identify de novo variants in the child. For each trio we ran MuTect twice, designating the child as ‘tumor’ and each parent as ‘normal.’ The intersection of variants is the set of de novo variants in the child that are then filtered for mosaic variants (PDF 222 kb)
Online Resource Figure 4: A)
Comparison of alternate allele depth in child versus total depth in child for variants that confirmed as mosaic and homozygous reference based on ddPCR results. Red squares represent confirmed mosaic variants. Blue diamonds represent homozygous loci. Dashed lines represent new filtering parameters to increase the positive predictive value. B) Comparison of minimum parental read depth compared to total depth in child (PDF 418 kb)
Online Resource Figure 5:
Counts of variant types of CHD cases (blue) and controls (red) (PDF 276 kb)
Online Resource Table
1: Phenotypic data for samples in PCGC cases and SSC controls (XLSX 106 kb)
Online Resource Table
2: Filtering parameters for mosaic variants (PDF 60 kb)
Online Resource Table
3: Confirmation results from digital droplet PCR for mosaic variants (PDF 48 kb)
Online Resource Table
4: Mosaic variants identified in cases and controls with CADD annotations (XLSX 74 kb)
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Manheimer, K.B., Richter, F., Edelmann, L.J. et al. Robust identification of mosaic variants in congenital heart disease. Hum Genet 137, 183–193 (2018). https://doi.org/10.1007/s00439-018-1871-6
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DOI: https://doi.org/10.1007/s00439-018-1871-6