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  • Review Article
  • Published:

Genomic frontiers in congenital heart disease

Nature Reviews Cardiology volume 19, pages 26–42 (2022)Cite this article

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Abstract

The application of next-generation sequencing to study congenital heart disease (CHD) is increasingly providing new insights into the causes and mechanisms of this prevalent birth anomaly. Whole-exome sequencing analysis identifies damaging gene variants altering single or contiguous nucleotides that are assigned pathogenicity based on statistical analyses of families and cohorts with CHD, high expression in the developing heart and depletion of damaging protein-coding variants in the general population. Gene classes fulfilling these criteria are enriched in patients with CHD and extracardiac abnormalities, evidencing shared pathways in organogenesis. Developmental single-cell transcriptomic data demonstrate the expression of CHD-associated genes in particular cell lineages, and emerging insights indicate that genetic variants perturb multicellular interactions that are crucial for cardiogenesis. Whole-genome sequencing analyses extend these observations, identifying non-coding variants that influence the expression of genes associated with CHD and contribute to the estimated ~55% of unexplained cases of CHD. These approaches combined with the assessment of common and mosaic genetic variants have provided a more complete knowledge of the causes and mechanisms of CHD. Such advances provide knowledge to inform the clinical care of patients with CHD or other birth defects and deepen our understanding of the complexity of human development. In this Review, we highlight known and candidate CHD-associated human genes and discuss how the integration of advances in developmental biology research can provide new insights into the genetic contributions to CHD.

Key points

  • A genetic risk contributes substantially to congenital heart disease (CHD), and variants in >400 genes are estimated to cause human CHD.

  • Analyses of large cohorts of patients with CHD have empowered the identification of novel genes associated with human CHD.

  • Non-coding variants contribute to CHD, in part by altering the activity of cardiac developmental enhancers.

  • Despite the genetic insights gained so far, a definitive cause is not identified in half of the cases of CHD.

  • Integration of genomic data with developmental biology promises to increase our understanding of the pathogenesis of CHD.

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Fig. 1: Common types of congenital heart disease.
Fig. 2: Human heart development.
Fig. 3: Definitive and candidate genes for congenital heart disease: genes with LOF variants.
Fig. 4: Definitive and candidate genes for congenital heart disease: genes with damaging missense variants.
Fig. 5: Relationship between extracardiac features, genotypes and functions of CHD-associated genes.
Fig. 6: Cardiac lineage-specific and temporal expression of definitive and candidate genes for CHD.

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References

  1. Reller, M. D., Strickland, M. J., Riehle-Colarusso, T., Mahle, W. T. & Correa, A. Prevalence of congenital heart defects in metropolitan Atlanta, 1998-2005. J. Pediatr. 153, 807–813 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Hoffman, J. I. E. & Kaplan, S. The incidence of congenital heart disease. J. Am. Coll. Cardiol. 39, 1890–1900 (2002).

    Article  PubMed  Google Scholar 

  3. Leirgul, E. et al. Birth prevalence of congenital heart defects in Norway 1994-2009–A nationwide study. Am. Heart J. 168, 956–964 (2014).

    Article  PubMed  Google Scholar 

  4. Liu, Y. et al. Global birth prevalence of congenital heart defects 1970-2017: updated systematic review and meta-analysis of 260 studies. Int. J. Epidemiol. 48, 455–463 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Bakker, M. K. et al. Prenatal diagnosis and prevalence of critical congenital heart defects: an international retrospective cohort study. BMJ Open 9, e028139 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Mccracken, C. et al. Mortality following pediatric congenital heart surgery: an analysis of the causes of death derived from the national death index. J. Am. Heart Assoc. 7, e010624 (2014).

    Article  Google Scholar 

  7. Egbe, A. et al. Prevalence of congenital anomalies in newborns with congenital heart disease diagnosis. Ann. Pediatr. Cardiol. 7, 86–91 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Hartman, R. J. et al. The contribution of chromosomal abnormalities to congenital heart defects: a population-based study. Pediatr. Cardiol. 32, 1147–1157 (2011).

    Article  PubMed  Google Scholar 

  9. de la Chapelle, A., Herva, R., Koivisto, M. & Aula, P. A deletion in chromosome 22 can cause DiGeorge syndrome. Hum. Genet. 57, 253–256 (1981).

    Article  PubMed  Google Scholar 

  10. Greenberg, F., Elder, F. F. B., Haffner, P., Northrup, H. & Ledbetter, D. H. Cytogenetic findings in a prospective series of patients with DiGeorge anomaly. Am. J. Hum. Genet. 43, 605–611 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Jalali, G. R. et al. Detailed analysis of 22q11.2 with a high density MLPA probe set. Hum. Mutat. 29, 433–440 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Thienpont, B. et al. Submicroscopic chromosomal imbalances detected by array-CGH are a frequent cause of congenital heart defects in selected patients. Eur. Heart J. 28, 2778–2784 (2007).

    Article  CAS  PubMed  Google Scholar 

  13. Agergaard, P., Olesen, C., Østergaard, J. R., Christiansen, M. & Sørensen, K. M. The prevalence of chromosome 22q11.2 deletions in 2,478 children with cardiovascular malformations. A population-based study. Am. J. Med. Genet. Part. A 158A, 498–508 (2012).

    Article  PubMed  Google Scholar 

  14. Peyvandi, S. et al. 22q11.2 deletions in patients with conotruncal defects: data from 1,610 consecutive cases. Pediatr. Cardiol. 34, 1687–1694 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Pierpont, M. E. et al. Genetic basis for congenital heart defects: current knowledge: a scientific statement from the American Heart Association Congenital Cardiac Defects Committee, Council on Cardiovascular Disease in the Young: endorsed by the American Academy of Pediatrics. Circulation 115, 3015–3038 (2007).

    Article  PubMed  Google Scholar 

  16. Fahed, A. C., Gelb, B. D., Seidman, J. G. & Seidman, C. E. Genetics of congenital heart disease: the glass half empty. Circ. Res. 112, 707–720 (2013).

    Article  CAS  PubMed  Google Scholar 

  17. Jin, S. C. et al. Contribution of rare inherited and de novo variants in 2,871 congenital heart disease probands. Nat. Genet. 49, 1593–1601 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Homsy, J. et al. De novo mutations in congenital heart disease with neurodevelopmental and other congenital anomalies. Science 350, 1262–1266 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Sifrim, A. et al. Distinct genetic architectures for syndromic and nonsyndromic congenital heart defects identified by exome sequencing. Nat. Genet. 48, 1060–1065 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. International Society of Ultrasound in Obstetrics & Gynecology. Cardiac screening examination of the fetus: guidelines for performing the ‘basic’ and ‘extended basic’ cardiac scan. Ultrasound Obstet. Gynecol. 27, 107–113 (2006).

    Article  Google Scholar 

  21. Meilhac, S. M. & Buckingham, M. E. The deployment of cell lineages that form the mammalian heart. Nat. Rev. Cardiol. 15, 705–724 (2018).

    Article  PubMed  Google Scholar 

  22. Kathiriya, I. S., Nora, E. P. & Bruneau, B. G. Investigating the transcriptional control of cardiovascular development. Circ. Res. 116, 700–714 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Günthel, M., Barnett, P. & Christoffels, V. M. Development, proliferation, and growth of the mammalian heart. Mol. Ther. 26, 1599–1609 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cui, M., Wang, Z., Bassel-Duby, R. & Olson, E. N. Genetic and epigenetic regulation of cardiomyocytes in development, regeneration and disease. Development 145, dev171983 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  25. van Weerd, J. H. & Christoffels, V. M. The formation and function of the cardiac conduction system. Development 143, 197–210 (2016).

    Article  PubMed  Google Scholar 

  26. Jain, R. & Epstein, J. A. Competent for commitment: you’ve got to have heart! Genes. Dev. 32, 4–13 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Mjaatvedt, C. H. et al. The outflow tract of the heart is recruited from a novel heart-forming field. Dev. Biol. 238, 97–109 (2001).

    Article  CAS  PubMed  Google Scholar 

  28. Cai, C.-L. et al. Isl1 identifies a cardiac progenitor population that proliferates prior to differentiation and contributes a majority of cells to the heart. Dev. Cell 5, 877–889 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Hutson, M. R. & Kirby, M. L. Model systems for the study of heart development and disease. Cardiac neural crest and conotruncal malformations. Semin. Cell Dev. Biol. 18, 101–110 (2007).

    Article  CAS  PubMed  Google Scholar 

  30. Lin, C.-J., Lin, C.-Y., Chen, C.-H., Zhou, B. & Chang, C.-P. Partitioning the heart: mechanisms of cardiac septation and valve development. Development 139, 3277–3299 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Christoffels, V. M. et al. Chamber formation and morphogenesis in the developing mammalian heart. Dev. Biol. 223, 266–278 (2000).

    Article  CAS  PubMed  Google Scholar 

  32. Schultheiss, T. M., Burch, J. B. & Lassar, A. B. A role for bone morphogenetic proteins in the induction of cardiac myogenesis. Genes Dev. 11, 451–462 (1997).

    Article  CAS  PubMed  Google Scholar 

  33. Alsan, B. H. & Schultheiss, T. M. Regulation of avian cardiogenesis by Fgf8 signaling. Development 129, 1935–1943 (2002).

    Article  CAS  PubMed  Google Scholar 

  34. Schultheiss, T. M., Xydas, S. & Lassar, A. B. Induction of avian cardiac myogenesis by anterior endoderm. Development 121, 4203–4214 (1995).

    Article  CAS  PubMed  Google Scholar 

  35. Itoh, N., Ohta, H., Nakayama, Y. & Konishi, M. Roles of FGF signals in heart development, health, and disease. Front. Cell Dev. Biol. 4, 110 (2016).

    PubMed  PubMed Central  Google Scholar 

  36. Marques, S. R. & Yelon, D. Differential requirement for BMP signaling in atrial and ventricular lineages establishes cardiac chamber proportionality. Dev. Biol. 328, 472–482 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Targoff, K. L., Schell, T. & Yelon, D. Nkx genes regulate heart tube extension and exert differential effects on ventricular and atrial cell number. Dev. Biol. 322, 314–321 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Nelson, D. O., Jin, D. X., Downs, K. M., Kamp, T. J. & Lyons, G. E. Irx4 identifies a chamber-specific cell population that contributes to ventricular myocardium development. Dev. Dyn. 243, 381–392 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Lee, J. H., Protze, S. I., Laksman, Z., Backx, P. H. & Keller, G. M. Human pluripotent stem cell-derived atrial and ventricular cardiomyocytes develop from distinct mesoderm populations. Cell Stem Cell 21, 179–194.e4 (2017).

    Article  CAS  PubMed  Google Scholar 

  40. Cheng, Z. et al. Two novel mutations of the IRX4 gene in patients with congenital heart disease. Hum. Genet. 130, 657–662 (2011).

    Article  PubMed  Google Scholar 

  41. de Soysa, T. Y. et al. Single-cell analysis of cardiogenesis reveals basis for organ-level developmental defects. Nature 572, 120–124 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Chen, Y. H., Ishii, M., Sun, J., Sucov, H. M. & Maxson, R. E. Msx1 and Msx2 regulate survival of secondary heart field precursors and post-migratory proliferation of cardiac neural crest in the outflow tract. Dev. Biol. 308, 421–437 (2007).

    Article  CAS  PubMed  Google Scholar 

  43. Sharma, A. et al. GATA6 mutations in hiPSCs inform mechanisms for maldevelopment of the heart, pancreas, and diaphragm. eLife 9, e53278 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Uribe, V. et al. Arid3b is essential for second heart field cell deployment and heart patterning. Development 141, 4168–4181 (2014).

    Article  CAS  PubMed  Google Scholar 

  45. Creemers, E. E., Sutherland, L. B., McAnally, J., Richardson, J. A. & Olson, E. N. Myocardin is a direct transcriptional target of Mef2, Tead and Foxo proteins during cardiovascular development. Development 133, 4245–4256 (2006).

    Article  CAS  PubMed  Google Scholar 

  46. Felker, A. et al. Continuous addition of progenitors forms the cardiac ventricle in zebrafish. Nat. Commun. 9, 2001 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Sánchez-Iranzo, H. et al. Tbx5a lineage tracing shows cardiomyocyte plasticity during zebrafish heart regeneration. Nat. Commun. 9, 428 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Jiang, X. et al. Normal fate and altered function of the cardiac neural crest cell lineage in retinoic acid receptor mutant embryos. Mech. Dev. 117, 115–122 (2002).

    Article  CAS  PubMed  Google Scholar 

  49. El Robrini, N. et al. Cardiac outflow morphogenesis depends on effects of retinoic acid signaling on multiple cell lineages. Dev. Dyn. 245, 388–401 (2016).

    Article  CAS  PubMed  Google Scholar 

  50. Inman, K. E. et al. Foxc2 is required for proper cardiac neural crest cell migration, outflow tract septation, and ventricle expansion. Dev. Dyn. 247, 1286–1296 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Kodo, K. et al. Regulation of Sema3c and the interaction between cardiac neural crest and second heart field during outflow tract development. Sci. Rep. 7, 6771 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Ribeiro, I. et al. Tbx2 and Tbx3 regulate the dynamics of cell proliferation during heart remodeling. PLoS ONE 2, e398 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Niessen, K. & Karsan, A. Notch signaling in cardiac development. Circ. Res. 102, 1169–1181 (2008).

    Article  CAS  PubMed  Google Scholar 

  54. Dor, Y. et al. A novel role for VEGF in endocardial cushion formation and its potential contribution to congenital heart defects. Development 128, 1531–1538 (2001).

    Article  CAS  PubMed  Google Scholar 

  55. Bischoff, J. Endothelial-to-mesenchymal transition. Circulation Res. 124, 1163–1165 (2019).

    Article  CAS  PubMed  Google Scholar 

  56. Singh, N. et al. Histone deacetylase 3 regulates smooth muscle differentiation in neural crest cells and development of the cardiac outflow tract. Circ. Res. 109, 1240–1249 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Marguerie, A. et al. Congenital heart defects in Fgfr2-IIIb and Fgf10 mutant mice. Cardiovasc. Res. 71, 50–60 (2006).

    Article  CAS  PubMed  Google Scholar 

  58. Peng, T. et al. Coordination of heart and lung co-development by a multipotent cardiopulmonary progenitor. Nature 500, 589–592 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Liu, X. et al. Single-Cell RNA-seq of the developing cardiac outflow tract reveals convergent development of the vascular smooth muscle cells. Cell Rep. 28, 1346–1361.e4 (2019).

    Article  CAS  PubMed  Google Scholar 

  60. Montague, T. G., Gagnon, J. A. & Schier, A. F. Conserved regulation of nodal-mediated left-right patterning in zebrafish and mouse. Development 145, dev171090 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Weninger, W. J. et al. Cited2 is required both for heart morphogenesis and establishment of the left-right axis in mouse development. Development 132, 1337–1348 (2005).

    Article  CAS  PubMed  Google Scholar 

  62. Sutherland, M. J., Wang, S., Quinn, M. E., Haaning, A. & Ware, S. M. Zic3 is required in the migrating primitive streak for node morphogenesis and left-right patterning. Hum. Mol. Genet. 22, 1913–1923 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Levin, M., Johnson, R. L., Stern, C. D., Kuehn, M. & Tabin, C. A molecular pathway determining left-right asymmetry in chick embryogenesis. Cell 82, 803–814 (1995).

    Article  CAS  PubMed  Google Scholar 

  64. Meno, C. et al. Diffusion of nodal signaling activity in the absence of the feedback inhibitor Lefty2. Dev. Cell 1, 127–138 (2001).

    Article  CAS  PubMed  Google Scholar 

  65. Meno, C. et al. lefty-1 is required for left-right determination as a regulator of lefty-2 and nodal. Cell 94, 287–297 (1998).

    Article  CAS  PubMed  Google Scholar 

  66. Goldmuntz, E. et al. Frequency of 22q11 deletions in patients with conotruncal defects. J. Am. Coll. Cardiol. 32, 492–498 (1998).

    Article  CAS  PubMed  Google Scholar 

  67. Corsten-Janssen, N. et al. The cardiac phenotype in patients with a CHD7 mutation. Circ. Cardiovasc. Genet. 6, 248–254 (2013).

    Article  CAS  PubMed  Google Scholar 

  68. Layman, W. S., Hurd, E. A. & Martin, D. M. Chromodomain proteins in development: lessons from CHARGE syndrome. Clin. Genet. 78, 11–20 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Rozas, M. F., Benavides, F., León, L. & Repetto, G. M. Association between phenotype and deletion size in 22q11.2 microdeletion syndrome: systematic review and meta-analysis. Orphanet. J. Rare Dis. 14, 195 (2019).

    Google Scholar 

  70. Zhao, Y. et al. Complete sequence of the 22q11.2 allele in 1,053 subjects with 22q11.2 deletion syndrome reveals modifiers of conotruncal heart defects. Am. J. Hum. Genet. 106, 26–40 (2020).

    Article  CAS  PubMed  Google Scholar 

  71. Greenway, S. C. et al. De novo copy number variants identify new genes and loci in isolated sporadic tetralogy of Fallot. Nat. Genet. 41, 931–935 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Mefford, H. C. et al. Recurrent rearrangements of chromosome 1q21.1 and variable pediatric phenotypes. N. Engl. J. Med. 359, 1685–1699 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Page, D. J. et al. Whole exome sequencing reveals the major genetic contributors to nonsyndromic tetralogy of Fallot. Circ. Res. 124, 553–563 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Reuter, M. S. et al. Haploinsufficiency of vascular endothelial growth factor related signaling genes is associated with tetralogy of Fallot. Genet. Med. 21, 1001–1007 (2019).

    Article  PubMed  Google Scholar 

  75. De Luca, A. et al. New mutations in ZFPM2/FOG2 gene in tetralogy of Fallot and double outlet right ventricle. Clin. Genet. 80, 184–190 (2011).

    Article  PubMed  Google Scholar 

  76. Yang, Y. Q. et al. GATA4 loss-of-function mutations underlie familial tetralogy of Fallot. Hum. Mutat. 34, 1662–1671 (2013).

    Article  CAS  PubMed  Google Scholar 

  77. Kodo, K. et al. GATA6 mutations cause human cardiac outflow tract defects by disrupting semaphorin-plexin signaling. Proc. Natl Acad. Sci. USA 106, 13933–13938 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Burns, T., Yang, Y., Hiriart, E. & Wessels, A. The dorsal mesenchymal protrusion and the pathogenesis of atrioventricular septal defects. J. Cardiovasc. Dev. Dis. 3, 29 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Lana-Elola, E. et al. Genetic dissection of Down syndrome-associated congenital heart defects using a new mouse mapping panel. eLife 5, e11614 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Calabrò, R. & Limongelli, G. Complete atrioventricular canal. Orphanet J. Rare Dis. 1, 8 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Freeman, S. B. et al. Population-based study of congenital heart defects in Down syndrome. Am. J. Med. Genet. 80, 213–217 (1998).

    Article  CAS  PubMed  Google Scholar 

  82. Bergström, S. et al. Trends in congenital heart defects in infants with Down syndrome. Pediatrics 138, e20160123 (2016).

    Article  PubMed  Google Scholar 

  83. Pelleri, M. C. et al. Genotype-phenotype correlation for congenital heart disease in Down syndrome through analysis of partial trisomy 21 cases. Genomics 109, 391–400 (2017).

    Article  CAS  PubMed  Google Scholar 

  84. Ang, Y.-S. et al. Disease model of GATA4 mutation reveals transcription factor cooperativity in human cardiogenesis. Cell 167, 1734–1749.e22 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Garg, V. et al. GATA4 mutations cause human congenital heart defects and reveal an interaction with TBX5. Nature 424, 443–447 (2003).

    Article  CAS  PubMed  Google Scholar 

  86. Durocher, D., Charron, F., Warren, R., Schwartz, R. J. & Nemer, M. The cardiac transcription factors nkx2-5 and GATA-4 are mutual cofactors. EMBO J. 16, 5687–5696 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. McBride, K. L. et al. Inheritance analysis of congenital left ventricular outflow tract obstruction malformations: segregation, multiplex relative risk, and heritability. Am. J. Med. Genet. 134A, 180–186 (2005).

    Article  PubMed  Google Scholar 

  88. Silberbach, M. et al. Cardiovascular health in Turner syndrome: a scientific statement from the American Heart Association. Circulation. Genomic Precis. Med. 11, e000048 (2018).

    Article  Google Scholar 

  89. Lara, D. A., Ethen, M. K., Canfield, M. A., Nembhard, W. N. & Morris, S. A. A population-based analysis of mortality in patients with Turner syndrome and hypoplastic left heart syndrome using the Texas Birth Defects Registry. Congenit. Heart Dis. 12, 105–112 (2017).

    Article  PubMed  Google Scholar 

  90. Prakash, S. K. et al. Autosomal and X chromosome structural variants are associated with congenital heart defects in Turner syndrome: the NHLBI GenTAC registry. Am. J. Med. Genet. A 170, 3157–3164 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Grossfeld, P. D. et al. The 11q terminal deletion disorder: a prospective study of 110 cases. Am. J. Med. Genet. 129A, 51–61 (2004).

    Article  PubMed  Google Scholar 

  92. Miao, Y. et al. Intrinsic endocardial defects contribute to hypoplastic left heart syndrome. Cell Stem Cell 27, 574–589.e8 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Shi, L. M. et al. GATA5 loss-of-function mutations associated with congenital bicuspid aortic valve. Int. J. Mol. Med. 33, 1219–1226 (2014).

    Article  CAS  PubMed  Google Scholar 

  94. Bonachea, E. M. et al. Rare GATA5 sequence variants identified in individuals with bicuspid aortic valve. Pediatr. Res. 76, 211–216 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Verma, S. K. et al. Rbfox2 function in RNA metabolism is impaired in hypoplastic left heart syndrome patient hearts. Sci. Rep. 6, 30896 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Theis, J. L. et al. Recessive MYH6 mutations in hypoplastic left heart with reduced ejection fraction. Circ. Cardiovasc. Genet. 8, 564–571 (2015).

    Article  CAS  PubMed  Google Scholar 

  97. Wald, R. M. et al. Outcome after prenatal diagnosis of tricuspid atresia: a multicenter experience. Am. Heart J. 153, 772–778 (2007).

    Article  PubMed  Google Scholar 

  98. Svensson, E. C. et al. A syndrome of tricuspid atresia in mice with a targeted mutation of the gene encoding Fog-2. Nat. Genet. 25, 353–356 (2000).

    Article  CAS  PubMed  Google Scholar 

  99. Prendiville, T. W. et al. Cardiovascular disease in Noonan syndrome. Arch. Dis. Child. 99, 629–634 (2014).

    Article  PubMed  Google Scholar 

  100. Gelb, B. D. & Tartaglia, M. Noonan syndrome and related disorders: dysregulated RAS-mitogen activated protein kinase signal transduction. Hum. Mol. Genet. 15, R220–R226 (2006).

    Article  CAS  PubMed  Google Scholar 

  101. Roberts, A. et al. The cardiofaciocutaneous syndrome. J. Med. Genet. 43, 833–842 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Danyel, M., Kortüm, F., Dathe, K., Kutsche, K. & Horn, D. Autosomal dominant Robinow syndrome associated with a novel DVL3 splice mutation. Am. J. Med. Genet. Part. A 176, 992–996 (2018).

    Article  CAS  PubMed  Google Scholar 

  103. Atalay, S. et al. Congenital heart disease and Robinow syndrome. Clin. Dysmorphol. 2, 208–210 (1993).

    Article  CAS  PubMed  Google Scholar 

  104. Afzal, A. R. et al. Recessive Robinow syndrome, allelic to dominant brachydactyly type B, is caused by mutation of ROR2. Nat. Genet. 25, 419–422 (2000).

    Article  CAS  PubMed  Google Scholar 

  105. Person, A. D. et al. WNT5A mutations in patients with autosomal dominant Robinow syndrome. Dev. Dyn. 239, 327–337 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. White, J. et al. DVL1 frameshift mutations clustering in the penultimate exon cause autosomal-dominant Robinow syndrome. Am. J. Hum. Genet. 96, 612–622 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Penton, A. L., Leonard, L. D. & Spinner, N. B. Notch signaling in human development and disease. Semin. Cell Dev. Biol. 23, 450–457 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. McElhinney, D. B. et al. Analysis of cardiovascular phenotype and genotype-phenotype correlation in individuals with a JAG1 mutation and/or Alagille syndrome. Circulation 106, 2567–2574 (2002).

    Article  PubMed  Google Scholar 

  109. Liu, X. et al. Exome-based case-control analysis highlights the pathogenic role of ciliary genes in transposition of the great arteries. Circ. Res. 126, 811–821 (2020).

    Article  CAS  PubMed  Google Scholar 

  110. Li, A. H. et al. Genetic architecture of laterality defects revealed by whole exome sequencing. Eur. J. Hum. Genet. 27, 563–573 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Mohapatra, B. et al. Identification and functional characterization of NODAL rare variants in heterotaxy and isolated cardiovascular malformations. Hum. Mol. Genet. 18, 861–871 (2009).

    Article  CAS  PubMed  Google Scholar 

  112. Ware, S. M. et al. Identification and functional analysis of ZIC3 mutations in heterotaxy and related congenital heart defects. Am. J. Hum. Genet. 74, 93–105 (2004).

    Article  CAS  PubMed  Google Scholar 

  113. Lahaye, S. et al. Utilization of whole exome sequencing to identify causative mutations in familial congenital heart disease. Circ. Cardiovasc. Genet. 9, 320–329 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Hoang, T. T. et al. The congenital heart disease genetic network study: cohort description. PLoS ONE 13, e0191319 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  115. Preuss, C. et al. Family based whole exome sequencing reveals the multifaceted role of Notch signaling in congenital heart disease. PLoS Genet. 12, e1006335 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  116. Zaidi, S. et al. De novo mutations in histone-modifying genes in congenital heart disease. Nature 498, 220–223 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Watkins, W. S. et al. De novo and recessive forms of congenital heart disease have distinct genetic and phenotypic landscapes. Nat. Commun. 10, 4722 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  118. Morton, S. U. et al. Association of damaging variants in genes with increased cancer risk among patients with congenital heart disease. JAMA Cardiol. 6, 457–462 (2020).

    Article  Google Scholar 

  119. Tan, H. L. et al. Nonsynonymous variants in the SMAD6 gene predispose to congenital cardiovascular malformation. Hum. Mutat. 33, 720–727 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Krebs, L. T. et al. Notch signaling regulates left-right asymmetry determination by inducing Nodal expression. Genes Dev. 17, 1207–1212 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Galvin, K. M. et al. A role for Smad6 in development and homeostasis of the cardiovascular system. Nat. Genet. 24, 171–174 (2000).

    Article  CAS  PubMed  Google Scholar 

  122. McKean, D. M. et al. Loss of RNA expression and allele-specific expression associated with congenital heart disease. Nat. Commun. 7, 12824 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Duchon, A. & Herault, Y. DYRK1A, a dosage-sensitive gene involved in neurodevelopmental disorders, is a target for drug development in down syndrome. Front. Behav. Neurosci. 10, 104 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  124. Helsmoortel, C. et al. A SWI/SNF-related autism syndrome caused by de novo mutations in ADNP. Nat. Genet. 46, 380–384 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Sirmaci, A. et al. Mutations in ANKRD11 cause KBG syndrome, characterized by intellectual disability, skeletal malformations, and macrodontia. Am. J. Hum. Genet. 89, 289–294 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Bostwick, B. L. et al. Phenotypic and molecular characterisation of CDK13-related congenital heart defects, dysmorphic facial features and intellectual developmental disorders. Genome Med. 9, 73 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  127. Wang, X. et al. Phenotypic expansion in DDX3X – a common cause of intellectual disability in females. Ann. Clin. Transl. Neurol. 5, 1277–1285 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  128. Fischbach, G. D. & Lord, C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron 68, 192–195 (2010).

    Article  CAS  PubMed  Google Scholar 

  129. Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Yokouchi-Konishi, T. et al. Recurrent congenital heart diseases among neonates born to mothers with congenital heart diseases. Pediatr. Cardiol. 40, 865–870 (2019).

    Article  PubMed  Google Scholar 

  132. Ellesøe, S. G. et al. Familial co-occurrence of congenital heart defects follows distinct patterns. Eur. Heart J. 39, 1015–1022 (2018).

    Article  PubMed  Google Scholar 

  133. Gill, H. K., Splitt, M., Sharland, G. K. & Simpson, J. M. Patterns of recurrence of congenital heart disease: an analysis of 6,640 consecutive pregnancies evaluated by detailed fetal echocardiography. J. Am. Coll. Cardiol. 42, 923–929 (2003).

    Article  PubMed  Google Scholar 

  134. Øyen, N. et al. Recurrence of congenital heart defects in families. Circulation 120, 295–301 (2009).

    Article  PubMed  Google Scholar 

  135. Burn, J. et al. Recurrence risks in offspring of adults with major heart defects: results from first cohort of British collaborative study. Lancet 351, 311–316 (1998).

    Article  CAS  PubMed  Google Scholar 

  136. Cordell, H. J. et al. Genome-wide association study identifies loci on 12q24 and 13q32 associated with Tetralogy of Fallot. Hum. Mol. Genet. 22, 1473–1481 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Hanchard, N. A. et al. A genome-wide association study of congenital cardiovascular left-sided lesions shows association with a locus on chromosome 20. Hum. Mol. Genet. 25, 2331–2341 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Hu, Z. et al. A genome-wide association study identifies two risk loci for congenital heart malformations in Han Chinese populations. Nat. Genet. 45, 818–821 (2013).

    Article  CAS  PubMed  Google Scholar 

  139. Lin, Y. et al. Association analysis identifies new risk loci for congenital heart disease in Chinese populations. Nat. Commun. 6, 8082 (2015).

    Article  CAS  PubMed  Google Scholar 

  140. Cordell, H. J. et al. Genome-wide association study of multiple congenital heart disease phenotypes identifies a susceptibility locus for atrial septal defect at chromosome 4p16. Nat. Genet. 45, 822–824 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Wang, D. et al. A genetic variant in FIGN gene reduces the risk of congenital heart disease in Han Chinese populations. Pediatr. Cardiol. 38, 1169–1174 (2017).

    Article  PubMed  Google Scholar 

  142. Guo, T. et al. Genome-wide association study to find modifiers for tetralogy of Fallot in the 22q11.2 deletion syndrome identifies variants in the GPR98 locus on 5q14.3. Circ. Cardiovasc. Genet. 10, e001690 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Huang, A. Y. et al. MosaicHunter: accurate detection of postzygotic single-nucleotide mosaicism through next-generation sequencing of unpaired, trio, and paired samples. Nucleic Acids Res. 45, e76 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Manheimer, K. B. et al. Robust identification of mosaic variants in congenital heart disease. Hum. Genet. 137, 183–193 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Hsieh, A. et al. EM-mosaic detects mosaic point mutations that contribute to congenital heart disease. Genome Med. 12, 42 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. King, D. A. et al. Detection of structural mosaicism from targeted and whole-genome sequencing data. Genome Res. 27, 1704–1714 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Wei, W. et al. Frequency and signature of somatic variants in 1461 human brain exomes. Genet. Med. 21, 904–912 (2019).

    Article  CAS  PubMed  Google Scholar 

  148. Belkadi, A. et al. Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc. Natl Acad. Sci. USA 112, 5473–5478 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Noll, A. C. et al. Clinical detection of deletion structural variants in whole-genome sequences. NPJ Genomic Med. 1, 16026 (2016).

    Article  Google Scholar 

  150. Bjornsson, T. et al. A rare missense mutation in MYH6 associates with non-syndromic coarctation of the aorta. Eur. Heart J. 39, 3243–3249 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  151. Wright, C. F. et al. Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet 385, 1305–1314 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  152. Turner, T. N. & Eichler, E. E. The role of de novo noncoding regulatory mutations in neurodevelopmental disorders. Trends Neurosci. 42, 115–127 (2019).

    Article  CAS  PubMed  Google Scholar 

  153. Montefiori, L. E. et al. A promoter interaction map for cardiovascular disease genetics. eLife 7, e35788 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  154. Hoelscher, S. C. et al. MicroRNAs: pleiotropic players in congenital heart disease and regeneration. J. Thorac. Dis. 9, S64–S81 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  155. Melnikov, A. et al. Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nat. Biotechnol. 30, 271–277 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Akerberg, B. N. et al. A reference map of murine cardiac transcription factor chromatin occupancy identifies dynamic and conserved enhancers. Nat. Commun. 10, 4907 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  157. Vanoudenhove, J., Yankee, T. N., Wilderman, A. & Cotney, J. Epigenomic and transcriptomic dynamics during human heart organogenesis. Circ. Res. 127, E184–E209 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Thorsson, T. et al. Chromosomal imbalances in patients with congenital cardiac defects: a meta-analysis reveals novel potential critical regions involved in heart development. Congenit. Heart Dis. 10, 193–208 (2015).

    Article  PubMed  Google Scholar 

  159. Smemo, S. et al. Regulatory variation in a TBX5 enhancer leads to isolated congenital heart disease. Hum. Mol. Genet. 21, 3255–3263 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Richter, F. et al. Genomic analyses implicate noncoding de novo variants in congenital heart disease. Nat. Genet. 52, 769–777 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Audano, P. A. et al. Characterizing the major structural variant alleles of the human genome. Cell 176, 663–675.e19 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Sudmant, P. H. et al. An integrated map of structural variation in 2,504 human genomes. Nature 526, 75–81 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Collins, R. L. et al. A structural variation reference for medical and population genetics. Nature 581, 444–451 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Turner, T. N. et al. Genomic patterns of de novo mutation in simplex autism. Cell 171, 710–722.e12 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Udaka, T. et al. An Alu retrotransposition-mediated deletion of CHD7 in a patient with CHARGE syndrome. Am. J. Med. Genet. A 143, 721–726 (2007).

    Article  Google Scholar 

  166. Rajagopalan, R. et al. Genome sequencing increases diagnostic yield in clinically diagnosed Alagille syndrome patients with previously negative test results. Genet. Med. 23, 323–330 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  167. Legoff, L., D’Cruz, S. C., Tevosian, S., Primig, M. & Smagulova, F. Transgenerational inheritance of environmentally induced epigenetic alterations during mammalian development. Cells 8, 1559 (2019).

    Article  CAS  PubMed Central  Google Scholar 

  168. Barua, S. & Junaid, M. A. Lifestyle, pregnancy and epigenetic effects. Epigenomics 7, 85–102 (2015).

    Article  CAS  PubMed  Google Scholar 

  169. Strande, N. T. et al. Evaluating the clinical validity of gene-disease associations: an evidence-based framework developed by the clinical genome resource. Am. J. Hum. Genet. 100, 895–906 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17, 405–423 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  171. Pijuan-Sala, B. et al. A single-cell molecular map of mouse gastrulation and early organogenesis. Nature 566, 490–495 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Litvinˇuková, M. et al. Cells of the adult human heart. Nature 588, 466–472 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  173. Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  174. Cui, Y. et al. Single-cell transcriptome analysis maps the developmental track of the human heart. Cell Rep. 26, 1934–1950.e5 (2019).

    Article  CAS  PubMed  Google Scholar 

  175. Lescroart, F. et al. Defining the earliest step of cardiovascular lineage segregation by single-cell RNA-seq. Science 359, 1177–1181 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. DeLaughter, D. M. et al. Single-cell resolution of temporal gene expression during heart development. Dev. Cell 39, 480–490 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Ulirsch, J. C. et al. The genetic landscape of Diamond-Blackfan anemia. Am. J. Hum. Genet. 103, 930–947 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  178. Robertson, C., Tran, D. D. & George, S. C. Concise review: maturation phases of human pluripotent stem cell-derived cardiomyocytes. Stem Cell 31, 829–837 (2013).

    Article  CAS  Google Scholar 

  179. Takahashi, K. et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131, 861–872 (2007).

    Article  CAS  PubMed  Google Scholar 

  180. Zhang, J. et al. Functional cardiac fibroblasts derived from human pluripotent stem cells via second heart field progenitors. Nat. Commun. 10, 2238 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  181. Kreitzer, F. R. et al. A robust method to derive functional neural crest cells from human pluripotent stem cells. Am. J. Stem Cell 2, 119–131 (2013).

    CAS  Google Scholar 

  182. Neri, T. et al. Human pre-valvular endocardial cells derived from pluripotent stem cells recapitulate cardiac pathophysiological valvulogenesis. Nat. Commun. 10, 1929 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  183. Kathiriya, I. S. et al. Modeling human TBX5 haploinsufficiency predicts regulatory networks for congenital heart disease. Dev. Cell 56, 292–309.e9 (2021).

    Article  CAS  PubMed  Google Scholar 

  184. Hamdan, F. F. et al. High rate of recurrent de novo mutations in developmental and epileptic encephalopathies. Am. J. Hum. Genet. 101, 664–685 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Pierpont, M. E. et al. Genetic basis for congenital heart disease: revisited: a scientific statement from the American Heart Association. Circulation 138, e653–e711 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  186. Philippakis, A. A. et al. The matchmaker exchange: a platform for rare disease gene discovery. Hum. Mutat. 36, 915–921 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  187. MacArthur, D. G. et al. Guidelines for investigating causality of sequence variants in human disease. Nature 508, 469–476 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Yu, Y. et al. Functional mutant GATA4 identification and potential application in preimplantation diagnosis of congenital heart diseases. Gene 641, 349–354 (2018).

    Article  CAS  PubMed  Google Scholar 

  189. Boskovski, M. T. et al. De novo damaging variants, clinical phenotypes and post-operative outcomes in congenital heart disease. Circ. Genomic Precis. Med. 13, e002836 (2020).

    Article  Google Scholar 

  190. Gurvitz, M. et al. Prevalence of cancer in adults with congenital heart disease compared with the general population. Am. J. Cardiol. 118, 1742–1750 (2016).

    Article  PubMed  Google Scholar 

  191. Mandalenakis, Z. et al. Risk of cancer among children and young adults with congenital heart disease compared with healthy controls. JAMA Netw. Open 2, e196762 (2019).

    Article  PubMed  Google Scholar 

  192. Lee, Y. S. et al. The risk of cancer in patients with congenital heart disease: a nationwide population-based cohort study in Taiwan. PLoS ONE 10, 1–13 (2015).

    Google Scholar 

  193. Krupp, D. R. et al. Exonic mosaic mutations contribute risk for autism spectrum disorder. Am. J. Hum. Genet. 101, 369–390 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  194. Mercer-Rosa, L., Pinto, N., Yang, W., Tanel, R. & Goldmuntz, E. 22q11.2 deletion syndrome is associated with perioperative outcome in tetralogy of Fallot. J. Thorac. Cardiovasc. Surg. 146, 868–873 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. O’Byrne, M. L. et al. 22q11.2 deletion syndrome is associated with increased perioperative events and more complicated postoperative course in infants undergoing infant operative correction of truncus arteriosus communis or interrupted aortic arch. J. Thorac. Cardiovasc. Surg. 148, 1597–1605 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  196. Kim, D. S. et al. Burden of potentially pathologic copy number variants is higher in children with isolated congenital heart disease and significantly impairs covariate-adjusted transplant-free survival. J. Thorac. Cardiovasc. Surg. 151, 1147–1151.e4 (2016).

    Article  PubMed  Google Scholar 

  197. Meyer, H. V. et al. Genetic and functional insights into the fractal structure of the heart. Nature 584, 589–594 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Beauséjour Ladouceur, V. et al. Exposure to low-dose ionizing radiation from cardiac procedures in patients with congenital heart disease. Circulation 133, 12–20 (2016).

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors’ work is supported in part by grants from the Harvard Medical School Epigenetics & Gene Dynamics Award, AHA postdoctoral Fellowship, and Boston Children’s Hospital Office of Faculty Development Career Development Fellowship Award (S.U.M.), the John S. LaDue Memorial Fellowship at Harvard Medical School (D.Q.), National Institutes of Health (J.G.S.: UM1 HL098166, HL151257; C.E.S.: UM1 HL0981479, 3U01HL131003), and the Howard Hughes Medical Institute (C.E.S.).

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  1. These authors contributed equally: Sarah U. Morton, Daniel Quiat.

Authors and Affiliations

  1. Division of Newborn Medicine, Department of Medicine, Boston Children’s Hospital, Boston, MA, USA

    Sarah U. Morton

  2. Department of Pediatrics, Harvard Medical School, Boston, MA, USA

    Sarah U. Morton & Daniel Quiat

  3. Department of Genetics, Harvard Medical School, Boston, MA, USA

    Sarah U. Morton, Daniel Quiat, Jonathan G. Seidman & Christine E. Seidman

  4. Department of Cardiology, Boston Children’s Hospital, Boston, MA, USA

    Daniel Quiat

  5. Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    Christine E. Seidman

  6. Howard Hughes Medical Institute, Harvard University, Boston, MA, USA

    Christine E. Seidman

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Related links

American College of Medical Genetics and Genomics: https://www.acmg.net/

ClinGen: https://clinicalgenome.org

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Genome Aggregation Database: https://gnomad.broadinstitute.org/

Online Mendelian Inheritance in Man: https://www.omim.org/

Supplementary information

Glossary

Whole-exome sequencing

(WES). Targeted sequencing of protein-encoding regions, which comprise 1% of the genome. WES can be used to determine single-nucleotide variants, small insertions and deletions, and copy number variants, but is less sensitive than WGS for the detection of structural variants.

Whole-genome sequencing

(WGS). Sequencing of the entire genome (protein coding and non-coding regions) that can be used to determine single-nucleotide variants, small insertions and deletions, and structural variants.

Probability of LOF intolerance

(pLI). A measure of evolutionary constraint estimated by the ratio of observed LOF variant alleles in the gnomAD cohort compared with the expected number of LOF variants on the basis of mutation rate, cohort size and sequence context.

Genome-wide association studies

A statistical genetic analysis approach that associates common genetic variants, often with a minor allele frequency of ≥5%, with quantitative and qualitative traits. Given the number of genomic loci, a commonly accepted significance threshold of P < 5 × 10−8 is used regardless of how many loci are included in the analysis.

Alternative allele fraction

The proportion of total nucleotide reads at a particular genomic position that represent a non-reference allele. For example, in a sequencing library containing ten reads of the reference allele A and ten reads of the alternative allele T, the alternative allele fraction would be 0.5 (10/20).

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Morton, S.U., Quiat, D., Seidman, J.G. et al. Genomic frontiers in congenital heart disease. Nat Rev Cardiol 19, 26–42 (2022). https://doi.org/10.1038/s41569-021-00587-4

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