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Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction

Abstract

The QRS interval, from the beginning of the Q wave to the end of the S wave on an electrocardiogram, reflects ventricular depolarization and conduction time and is a risk factor for mortality, sudden death and heart failure. We performed a genome-wide association meta-analysis in 40,407 individuals of European descent from 14 studies, with further genotyping in 7,170 additional Europeans, and we identified 22 loci associated with QRS duration (P < 5 × 10−8). These loci map in or near genes in pathways with established roles in ventricular conduction such as sodium channels, transcription factors and calcium-handling proteins, but also point to previously unidentified biologic processes, such as kinase inhibitors and genes related to tumorigenesis. We demonstrate that SCN10A, a candidate gene at the most significantly associated locus in this study, is expressed in the mouse ventricular conduction system, and treatment with a selective SCN10A blocker prolongs QRS duration. These findings extend our current knowledge of ventricular depolarization and conduction.

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Figure 1: Manhattan plot.
Figure 2: Association plots for select loci.
Figure 3: Pleiotropic associations of PR, QRS and QT loci.
Figure 4: Expression and function of Scn10a in the mouse heart.

References

  1. 1

    Desai, A.D. et al. Prognostic significance of quantitative QRS duration. Am. J. Med. 119, 600–606 (2006).

    Article  Google Scholar 

  2. 2

    Elhendy, A., Hammill, S.C., Mahoney, D.W. & Pellikka, P.A. Relation of QRS duration on the surface 12-lead electrocardiogram with mortality in patients with known or suspected coronary artery disease. Am. J. Cardiol. 96, 1082–1088 (2005).

    Article  Google Scholar 

  3. 3

    Oikarinen, L. et al. QRS duration and QT interval predict mortality in hypertensive patients with left ventricular hypertrophy: the Losartan Intervention for Endpoint Reduction in Hypertension Study. Hypertension 43, 1029–1034 (2004).

    CAS  Article  Google Scholar 

  4. 4

    Dhingra, R. et al. Electrocardiographic QRS duration and the risk of congestive heart failure: the Framingham Heart Study. Hypertension 47, 861–867 (2006).

    CAS  Article  Google Scholar 

  5. 5

    Busjahn, A. et al. QT interval is linked to 2 long-QT syndrome loci in normal subjects. Circulation 99, 3161–3164 (1999).

    CAS  Article  Google Scholar 

  6. 6

    Hanson, B. et al. Genetic factors in the electrocardiogram and heart rate of twins reared apart and together. Am. J. Cardiol. 63, 606–609 (1989).

    CAS  Article  Google Scholar 

  7. 7

    Bezzina, C.R. et al. Common sodium channel promoter haplotype in Asian subjects underlies variability in cardiac conduction. Circulation 113, 338–344 (2006).

    CAS  Article  Google Scholar 

  8. 8

    Chambers, J.C. et al. Genetic variation in SCN10A influences cardiac conduction. Nat. Genet. 42, 149–152 (2010).

    CAS  Article  Google Scholar 

  9. 9

    Holm, H. et al. Several common variants modulate heart rate, PR interval and QRS duration. Nat. Genet. 42, 117–122 (2010).

    CAS  Article  Google Scholar 

  10. 10

    Dubois, P.C. et al. Multiple common variants for celiac disease influencing immune gene expression. Nat. Genet. 42, 295–302 (2010).

    CAS  Article  Google Scholar 

  11. 11

    Newton-Cheh, C. et al. Common variants at ten loci influence QT interval duration in the QTGEN Study. Nat. Genet. 41, 399–406 (2009).

    CAS  Article  Google Scholar 

  12. 12

    Pfeufer, A. et al. Common variants at ten loci modulate the QT interval duration in the QTSCD Study. Nat. Genet. 41, 407–414 (2009).

    CAS  Article  Google Scholar 

  13. 13

    Pfeufer, A. et al. Genome-wide association study of PR interval. Nat. Genet. 42, 153–159 (2010).

    CAS  Article  Google Scholar 

  14. 14

    Calvano, S.E. et al. A network-based analysis of systemic inflammation in humans. Nature 437, 1032–1037 (2005).

    CAS  Article  Google Scholar 

  15. 15

    Huang, W., Sherman, B.T. & Lempicki, R.A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

    CAS  Article  Google Scholar 

  16. 16

    Zhang, B., Schmoyer, D., Kirov, S. & Snoddy, J. GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies. BMC Bioinformatics 5, 16 (2004).

    Article  Google Scholar 

  17. 17

    Pallante, B.A. et al. Contactin-2 expression in the cardiac Purkinje fiber network. Circ. Arrhythm. Electrophysiol. 3, 186–194 (2010).

    CAS  Article  Google Scholar 

  18. 18

    Jarvis, M.F. et al. A-803467, a potent and selective Nav1.8 sodium channel blocker, attenuates neuropathic and inflammatory pain in the rat. Proc. Natl. Acad. Sci. USA 104, 8520–8525 (2007).

    CAS  Article  Google Scholar 

  19. 19

    Desplantez, T., Dupont, E., Severs, N.J. & Weingart, R. Gap junction channels and cardiac impulse propagation. J. Membr. Biol. 218, 13–28 (2007).

    CAS  Article  Google Scholar 

  20. 20

    Abriel, H. Cardiac sodium channel Na(v)1.5 and interacting proteins: physiology and pathophysiology. J. Mol. Cell. Cardiol. 48, 2–11 (2010).

    CAS  Article  Google Scholar 

  21. 21

    Remme, C.A., Wilde, A.A. & Bezzina, C.R. Cardiac sodium channel overlap syndromes: different faces of SCN5A mutations. Trends Cardiovasc. Med. 18, 78–87 (2008).

    CAS  Article  Google Scholar 

  22. 22

    Akopian, A.N. et al. The tetrodotoxin-resistant sodium channel SNS has a specialized function in pain pathways. Nat. Neurosci. 2, 541–548 (1999).

    CAS  Article  Google Scholar 

  23. 23

    Saimi, Y. & Kung, C. Calmodulin as an ion channel subunit. Annu. Rev. Physiol. 64, 289–311 (2002).

    CAS  Article  Google Scholar 

  24. 24

    Potet, F. et al. Functional interactions between distinct sodium channel cytoplasmic domains through the action of calmodulin. J. Biol. Chem. 284, 8846–8854 (2009).

    CAS  Article  Google Scholar 

  25. 25

    Wolf, C.M. & Berul, C.I. Inherited conduction system abnormalities—one group of diseases, many genes. J. Cardiovasc. Electrophysiol. 17, 446–455 (2006).

    Article  Google Scholar 

  26. 26

    Zhu, Y. et al. Tbx5-dependent pathway regulating diastolic function in congenital heart disease. Proc. Natl. Acad. Sci. USA 105, 5519–5524 (2008).

    CAS  Article  Google Scholar 

  27. 27

    Lebrec, J.J., Stijnen, T. & van Houwelingen, H.C. Dealing with heterogeneity between cohorts in genomewide SNP association studies. Stat. Appl. Genet. Mol. Biol. 9 article 8 (2010).

  28. 28

    Wei, L., Hanna, A.D., Beard, N.A. & Dulhunty, A.F. Unique isoform-specific properties of calsequestrin in the heart and skeletal muscle. Cell Calcium 45, 474–484 (2009).

    CAS  Article  Google Scholar 

  29. 29

    Terentyev, D. et al. Abnormal interactions of calsequestrin with the ryanodine receptor calcium release channel complex linked to exercise-induced sudden cardiac death. Circ. Res. 98, 1151–1158 (2006).

    CAS  Article  Google Scholar 

  30. 30

    Priori, S.G. et al. Clinical and molecular characterization of patients with catecholaminergic polymorphic ventricular tachycardia. Circulation 106, 69–74 (2002).

    CAS  Article  Google Scholar 

  31. 31

    Postma, A.V. et al. Absence of calsequestrin 2 causes severe forms of catecholaminergic polymorphic ventricular tachycardia. Circ. Res. 91, e21–e26 (2002).

    CAS  Article  Google Scholar 

  32. 32

    Wang, Y. & Goldhaber, J.I. Return of calcium: manipulating intracellular calcium to prevent cardiac pathologies. Proc. Natl. Acad. Sci. USA 101, 5697–5698 (2004).

    CAS  Article  Google Scholar 

  33. 33

    Vasan, R.S. et al. Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data. J. Am. Med. Assoc. 302, 168–178 (2009).

    CAS  Article  Google Scholar 

  34. 34

    Eijgelsheim, M. et al. Genome-wide association analysis identifies multiple loci related with resting heart rate. Hum. Mol. Genet. 19, 3885–3895 (2010).

    CAS  Article  Google Scholar 

  35. 35

    Braz, J.C. et al. PKC-alpha regulates cardiac contractility and propensity toward heart failure. Nat. Med. 10, 248–254 (2004).

    CAS  Article  Google Scholar 

  36. 36

    Baillat, G. et al. Molecular cloning and characterization of phocein, a protein found from the Golgi complex to dendritic spines. Mol. Biol. Cell 12, 663–673 (2001).

    CAS  Article  Google Scholar 

  37. 37

    Meurs, K.M. et al. Genome-wide association identifies a deletion in the 3′ untranslated region of Striatin in a canine model of arrhythmogenic right ventricular cardiomyopathy. Hum. Genet. 128, 315–324. (2010).

  38. 38

    Boogerd, K.J. et al. Msx1 and Msx2 are functional interacting partners of T-box factors in the regulation of Connexin43. Cardiovasc. Res. 78, 485–493 (2008).

    CAS  Article  Google Scholar 

  39. 39

    Hoogaars, W.M. et al. The transcriptional repressor Tbx3 delineates the developing central conduction system of the heart. Cardiovasc. Res. 62, 489–499 (2004).

    CAS  Article  Google Scholar 

  40. 40

    Singh, R. et al. Tbx20 interacts with smads to confine tbx2 expression to the atrioventricular canal. Circ. Res. 105, 442–452 (2009).

    CAS  Article  Google Scholar 

  41. 41

    Posch, M.G. et al. A gain-of-function TBX20 mutation causes congenital atrial septal defects, patent foramen ovale and cardiac valve defects. J. Med. Genet. 47, 230–235 (2009).

    Article  Google Scholar 

  42. 42

    Bakker, M.L. et al. Transcription factor Tbx3 is required for the specification of the atrioventricular conduction system. Circ. Res. 102, 1340–1349 (2008).

    CAS  Article  Google Scholar 

  43. 43

    Riley, P., Anson-Cartwright, L. & Cross, J.C. The Hand1 bHLH transcription factor is essential for placentation and cardiac morphogenesis. Nat. Genet. 18, 271–275 (1998).

    CAS  Article  Google Scholar 

  44. 44

    Reamon-Buettner, S.M. et al. A functional genetic study identifies HAND1 mutations in septation defects of the human heart. Hum. Mol. Genet. 18, 3567–3578 (2009).

    CAS  Article  Google Scholar 

  45. 45

    Breckenridge, R.A. et al. Overexpression of the transcription factor Hand1 causes predisposition towards arrhythmia in mice. J. Mol. Cell. Cardiol. 47, 133–141 (2009).

    CAS  Article  Google Scholar 

  46. 46

    Rentschler, S. et al. Neuregulin-1 promotes formation of the murine cardiac conduction system. Proc. Natl. Acad. Sci. USA 99, 10464–10469 (2002).

    CAS  Article  Google Scholar 

  47. 47

    Hofer, A. et al. C-erbB2/neu transfection induces gap junctional communication incompetence in glial cells. J. Neurosci. 16, 4311–4321 (1996).

    CAS  Article  Google Scholar 

  48. 48

    Besson, A. & Yong, V.W. Involvement of p21(Waf1/Cip1) in protein kinase C alpha-induced cell cycle progression. Mol. Cell. Biol. 20, 4580–4590 (2000).

    CAS  Article  Google Scholar 

  49. 49

    Wilkinson, L. et al. CRIM1 regulates the rate of processing and delivery of bone morphogenetic proteins to the cell surface. J. Biol. Chem. 278, 34181–34188 (2003).

    CAS  Article  Google Scholar 

  50. 50

    Kolle, G., Georgas, K., Holmes, G.P., Little, M.H. & Yamada, T. CRIM1, a novel gene encoding a cysteine-rich repeat protein, is developmentally regulated and implicated in vertebrate CNS development and organogenesis. Mech. Dev. 90, 181–193 (2000).

    CAS  Article  Google Scholar 

  51. 51

    Pardali, K., Kowanetz, M., Heldin, C.H. & Moustakas, A. Smad pathway-specific transcriptional regulation of the cell cycle inhibitor p21(WAF1/Cip1). J. Cell. Physiol. 204, 260–272 (2005).

    CAS  Article  Google Scholar 

  52. 52

    Laederich, M.B. et al. The leucine-rich repeat protein LRIG1 is a negative regulator of ErbB family receptor tyrosine kinases. J. Biol. Chem. 279, 47050–47056 (2004).

    CAS  Article  Google Scholar 

  53. 53

    Minakuchi, M. et al. Identification and characterization of SEB, a novel protein that binds to the acute undifferentiated leukemia-associated protein SET. Eur. J. Biochem. 268, 1340–1351 (2001).

    CAS  Article  Google Scholar 

  54. 54

    Zhao, J. & Zhong, C.J. A review on research progress of transketolase. Neurosci. Bull. 25, 94–99 (2009).

    Article  Google Scholar 

  55. 55

    Fedi, P. et al. Isolation and biochemical characterization of the human Dkk-1 homologue, a novel inhibitor of mammalian Wnt signaling. J. Biol. Chem. 274, 19465–19472 (1999).

    CAS  Article  Google Scholar 

  56. 56

    Ai, Z., Fischer, A., Spray, D.C., Brown, A.M. & Fishman, G.I. Wnt-1 regulation of connexin43 in cardiac myocytes. J. Clin. Invest. 105, 161–171 (2000).

    CAS  Article  Google Scholar 

  57. 57

    Korol, O., Gupta, R.W. & Mercola, M. A novel activity of the Dickkopf-1 amino terminal domain promotes axial and heart development independently of canonical Wnt inhibition. Dev. Biol. 324, 131–138 (2008).

    CAS  Article  Google Scholar 

  58. 58

    Tsai, I.C. et al. A Wnt-CKIvarepsilon-Rap1 pathway regulates gastrulation by modulating SIPA1L1, a Rap GTPase activating protein. Dev. Cell 12, 335–347 (2007).

    CAS  Article  Google Scholar 

  59. 59

    Chen, W.M. & Abecasis, G.R. Family-based association tests for genomewide association scans. Am. J. Hum. Genet. 81, 913–926 (2007).

    CAS  Article  Google Scholar 

  60. 60

    Devlin, B., Roeder, K. & Wasserman, L. Genomic control, a new approach to genetic-based association studies. Theor. Popul. Biol. 60, 155–166 (2001).

    CAS  Article  Google Scholar 

  61. 61

    de Bakker, P.I. et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum. Mol. Genet. 17, R122–R128 (2008).

    CAS  Article  Google Scholar 

  62. 62

    Pe'er, I., Yelensky, R., Altshuler, D. & Daly, M.J. Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet. Epidemiol. 32, 381–385 (2008).

    Article  Google Scholar 

  63. 63

    Johnson, A.D. et al. SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24, 2938–2939 (2008).

    CAS  Article  Google Scholar 

  64. 64

    Sreejit, P., Kumar, S. & Verma, R.S. An improved protocol for primary culture of cardiomyocyte from neonatal mice. In Vitro Cell. Dev. Biol. Anim. 44, 45–50 (2008).

    CAS  Article  Google Scholar 

  65. 65

    Livak, K.J. & Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 25, 402–408 (2001).

    CAS  Article  Google Scholar 

  66. 66

    Lee, P. et al. Conditional lineage ablation to model human diseases. Proc. Natl. Acad. Sci. USA 95, 11371–11376 (1998).

    CAS  Article  Google Scholar 

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Acknowledgements

Acknowledgments are available in the Supplementary Note.

Author information

Affiliations

Authors

Contributions

Study concept and design: N.S., A.A., D.E.A., P.I.W.d.B., E.B., H.C., A.C., C.M.v.D., M.E., S.B.F., G.I.F., A.R.F., J.F., V.G., P.v.d.H., S.R.H., A.A.H., A.H., A.I., S.K., H.K.K., C.N.-C., B.A.O., A. Pfeufer, P.P.P., B.M.P., J.I.R., I.R., H.S., E.Z.S., B.H.C.S., A.G.U., A.V.S., U.V., H.V., T.J.W., J.F.W., A.F.W., N.J.S., Y.J.

Acquisition of data: A.A., D.E.A., L.H.v.d.B., R.A.d.B., E.B., M.J.C., A.C., J.M.C., A.F.D., M.D., C.M.v.D., R.S.N.F., A.R.F., L.F., S.G., H.J.M.G., T.B.H., P.v.d.H., C.H., G.v.H., A.I., W.H.L.K., N.K., J.A.K., A.K., L.L., M.L., F.-Y.L., I.M.L., G.t.M., P.B.M., G.N., C.N.-C., B.A.O., R.A.O., S. Perz, A. Pfeufer, A. Petersmann, O.P., B.M.P., J.Q., F.R., J.I.R., I.R., N.J.S., C.S., M.P.S.S., M.F.S., E.Z.S., B.H.C.S., A.T., A.G.U., D.J.v.V., C.B.V., R.K.W., C.W., J.F.W., J.C.M.W., D.L., T.D.S.

Statistical analysis and interpretation of data: A.A., D.E.A., T.A., P.I.W.d.B., N.S., E.B., A.C., L.A.C., M.E., K.E., G.I.F., A.R.F., L.F., J.F., C.F., S.A.G., W.H.v.G., S.G., V.G., P.v.d.H., C.H., S.R.H., A.I., T.J., W.H.L.K., X.L., K.D.M., I.M.L., M.M., I.M.N., S. Padmanabhan, A. Pfeufer, O.P., B.M.P., K.R., H.S., A.T., A.V.S., S.H.W., Y.A.W., N.J.S.

Drafting of the manuscript: N.S., A.A., D.E.A, F.W.A., P.I.W.d.B., M.D., C.M.v.D,. M.E., G.I.F., J.F., S.A.G., V.G., C.H., A.I., Y.J., S.K., J.W.M., I.M.N., O.P., N.J.S., H.S., C.N.-C., P.v.d.H.

Critical revision of the manuscript: A.A., D.E.A., T.A., F.W.A., J.C.B., R.A.d.B., E.B., H.C., M.J.C., A.C., J.M.C., L.A.C., A.F.D., M.D., C.M.v.D., M.E., K.E., S.B.F., G.I.F., A.R.F., J.F., W.H.v.G., V.G., T.B.H., P.v.d.H., C.H., S.R.H., G.v.H., A.A.H., A.H., A.I., Y.J., T.J., S.K., W.H.L.K., N.K., J.A.K., A.K., H.K.K., L.L., D.L., M.L., J.W.M., I.M.L., T.M., M.M., P.B.M., G.N., C.N.-C., I.M.N., C.J.O., B.A.O., S. Padmanabhan, S. Perz, A. Pfeufer, A. Petersmann, O.P., B.M.P., F.R., J.I.R., I.R., M.P.S.S., M.F.S., D.S.S., H.S., B.H.C.S., E.Z.S., A.T., A.G.U., D.J.v.V., U.V., H.V., T.J.W., H.-E.W., A.V.S., S.H.W., J.F.W., J.C.M.W., A.F.W.

Obtained funding: L.H.v.d.B., E.B., H.C., M.J.C., A.C., J.M.C., A.F.D., C.M.v.D., S.B.F., G.I.F., W.H.v.G., H.J.M.G., V.G., P.v.d.H., A.H., Y.J., S.K., H.K.K., L.L., P.B.M., G.N., C.N.-C., C.J.O., B.A.O., R.A.O., P.P.P., B.M.P., J.I.R., I.R., N.J.S., N.S., T.D.S., A.G.U., D.J.v.V., U.V., H.V., T.J.W., R.K.W., H.-E.W., C.W., J.F.W., A.F.W., D.L.

Corresponding authors

Correspondence to Nona Sotoodehnia or Stefan Kääb or Dan E Arking.

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Competing interests

A.C. is a paid member of the Scientific Advisory Board of Affymetrix, a role that is managed by the Committee on Conflict of Interest of the Johns Hopkins University School of Medicine.

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Sotoodehnia, N., Isaacs, A., de Bakker, P. et al. Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction. Nat Genet 42, 1068–1076 (2010). https://doi.org/10.1038/ng.716

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