Human Genetics

, Volume 137, Issue 2, pp 183–193 | Cite as

Robust identification of mosaic variants in congenital heart disease

  • Kathryn B. Manheimer
  • Felix Richter
  • Lisa J. Edelmann
  • Sunita L. D’Souza
  • Lisong Shi
  • Yufeng Shen
  • Jason Homsy
  • Marko T. Boskovski
  • Angela C. Tai
  • Joshua Gorham
  • Christopher Yasso
  • Elizabeth Goldmuntz
  • Martina Brueckner
  • Richard P. Lifton
  • Wendy K. Chung
  • Christine E. Seidman
  • J. G. Seidman
  • Bruce D. Gelb
Original Investigation

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.

Notes

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.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

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.

Informed consent

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/).

Supplementary material

439_2018_1871_MOESM1_ESM.pdf (433 kb)
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)
439_2018_1871_MOESM2_ESM.pdf (381 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)
439_2018_1871_MOESM3_ESM.pdf (222 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)
439_2018_1871_MOESM4_ESM.pdf (419 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)
439_2018_1871_MOESM5_ESM.pdf (276 kb)
Online Resource Figure 5: Counts of variant types of CHD cases (blue) and controls (red) (PDF 276 kb)
439_2018_1871_MOESM6_ESM.xlsx (107 kb)
Online Resource Table 1: Phenotypic data for samples in PCGC cases and SSC controls (XLSX 106 kb)
439_2018_1871_MOESM7_ESM.pdf (60 kb)
Online Resource Table 2: Filtering parameters for mosaic variants (PDF 60 kb)
439_2018_1871_MOESM8_ESM.pdf (48 kb)
Online Resource Table 3: Confirmation results from digital droplet PCR for mosaic variants (PDF 48 kb)
439_2018_1871_MOESM9_ESM.xlsx (75 kb)
Online Resource Table 4: Mosaic variants identified in cases and controls with CADD annotations (XLSX 74 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Kathryn B. Manheimer
    • 1
  • Felix Richter
    • 1
  • Lisa J. Edelmann
    • 2
  • Sunita L. D’Souza
    • 3
  • Lisong Shi
    • 2
  • Yufeng Shen
    • 16
    • 17
  • Jason Homsy
    • 5
    • 18
  • Marko T. Boskovski
    • 19
  • Angela C. Tai
    • 5
  • Joshua Gorham
    • 5
  • Christopher Yasso
    • 5
  • Elizabeth Goldmuntz
    • 6
    • 7
  • Martina Brueckner
    • 8
    • 9
  • Richard P. Lifton
    • 8
    • 10
    • 11
    • 12
    • 13
  • Wendy K. Chung
    • 14
    • 15
  • Christine E. Seidman
    • 5
    • 20
    • 21
  • J. G. Seidman
    • 5
  • Bruce D. Gelb
    • 1
    • 2
    • 4
  1. 1.Mindich Child Health and Development InstituteIcahn School of Medicine at Mount SinaiNew YorkUSA
  2. 2.Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkUSA
  3. 3.Department of Cell, Developmental and Regenerative BiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
  4. 4.Department of PediatricsIcahn School of Medicine at Mount SinaiNew YorkUSA
  5. 5.Department of GeneticsHarvard Medical SchoolBostonUSA
  6. 6.Department of Pediatrics, The Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA
  7. 7.Division of Cardiology, The Children’s Hospital of PhiladelphiaThe University of Pennsylvania Perelman School of MedicinePhiladelphiaUSA
  8. 8.Department of GeneticsYale University School of MedicineNew HavenUSA
  9. 9.Department of PediatricsYale University School of MedicineNew HavenUSA
  10. 10.Howard Hughes Medical InstituteYale UniversityNew HavenUSA
  11. 11.Yale Center for Mendelian GenomicsNew HavenUSA
  12. 12.Yale Center for Genome AnalysisYale UniversityNew HavenUSA
  13. 13.Department of Internal MedicineYale University School of MedicineNew HavenUSA
  14. 14.Department of PediatricsColumbia University Medical CenterNew YorkUSA
  15. 15.Department of MedicineColumbia University Medical CenterNew YorkUSA
  16. 16.Department of Systems BiologyColumbia University Medical CenterNew YorkUSA
  17. 17.Department of Biomedical InformaticsColumbia University Medical CenterNew YorkUSA
  18. 18.Cardiovscular Research CenterMassachusetts General HospitalBostonUSA
  19. 19.Division of Cardiac Surgery, The Brigham and Women’s HospitalHarvard Medical SchoolBostonUSA
  20. 20.Department of Medicine (Cardiology)Brigham and Women’s HospitalBostonUSA
  21. 21.The Howard Hughes Medical InstituteChevy ChaseUSA

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