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Identification of genomic loci associated with resting heart rate and shared genetic predictors with all-cause mortality


Resting heart rate is a heritable trait correlated with life span. Little is known about the genetic contribution to resting heart rate and its relationship with mortality. We performed a genome-wide association discovery and replication analysis starting with 19.9 million genetic variants and studying up to 265,046 individuals to identify 64 loci associated with resting heart rate (P < 5 × 10−8); 46 of these were novel. We then used the genetic variants identified to study the association between resting heart rate and all-cause mortality. We observed that a genetically predicted resting heart rate increase of 5 beats per minute was associated with a 20% increase in mortality risk (hazard ratio 1.20, 95% confidence interval 1.11–1.28, P = 8.20 × 10−7) translating to a reduction in life expectancy of 2.9 years for males and 2.6 years for females. Our findings provide evidence for shared genetic predictors of resting heart rate and all-cause mortality.

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Figure 1: Genome-wide −log10(P) plot and effects for significant loci.
Figure 2: Biological insights.


  1. 1

    Schmidt-Nielsen, K. Animal Physiology: Adaptation and Environment (Cambridge University Press, 1975).

  2. 2

    Levine, H.J. Rest heart rate and life expectancy. J. Am. Coll. Cardiol. 30, 1104–1106 (1997).

    CAS  Article  Google Scholar 

  3. 3

    Dyer, A.R. et al. Heart rate as a prognostic factor for coronary heart disease and mortality: findings in three Chicago epidemiologic studies. Am. J. Epidemiol. 112, 736–749 (1980).

    CAS  Article  Google Scholar 

  4. 4

    Kannel, W.B., Kannel, C., Paffenbarger, R.S. Jr. & Cupples, L.A. Heart rate and cardiovascular mortality: the Framingham Study. Am. Heart J. 113, 1489–1494 (1987).

    CAS  Article  Google Scholar 

  5. 5

    Gillum, R.F., Makuc, D.M. & Feldman, J.J. Pulse rate, coronary heart disease, and death: the NHANES I epidemiologic follow-up Study. Am. Heart J. 121, 172–177 (1991).

    CAS  Article  Google Scholar 

  6. 6

    Greenland, P. et al. Resting heart rate is a risk factor for cardiovascular and noncardiovascular mortality: the Chicago Heart Association Detection Project in Industry. Am. J. Epidemiol. 149, 853–862 (1999).

    CAS  Article  Google Scholar 

  7. 7

    Kristal-Boneh, E., Silber, H., Harari, G. & Froom, P. The association of resting heart rate with cardiovascular, cancer and all-cause mortality. Eight year follow-up of 3527 male Israeli employees (the CORDIS Study). Eur. Heart J. 21, 116–124 (2000).

    CAS  Article  Google Scholar 

  8. 8

    Reunanen, A. et al. Heart rate and mortality. J. Intern. Med. 247, 231–239 (2000).

    CAS  Article  Google Scholar 

  9. 9

    Kolloch, R. et al. Impact of resting heart rate on outcomes in hypertensive patients with coronary artery disease: findings from the International Verapamil-SR/trandolapril Study (INVEST). Eur. Heart J. 29, 1327–1334 (2008).

    Article  Google Scholar 

  10. 10

    Diaz, A., Bourassa, M.G., Guertin, M.C. & Tardif, J.C. Long-term prognostic value of resting heart rate in patients with suspected or proven coronary artery disease. Eur. Heart J. 26, 967–974 (2005).

    Article  Google Scholar 

  11. 11

    Böhm, M. et al. Heart rate as a risk factor in chronic heart failure (SHIFT): the association between heart rate and outcomes in a randomised placebo-controlled trial. Lancet 376, 886–894 (2010).

    Article  Google Scholar 

  12. 12

    Grassi, G. et al. Heart rate as marker of sympathetic activity. J. Hypertens. 16, 1635–1639 (1998).

    CAS  Article  Google Scholar 

  13. 13

    Böhm, M., Reil, J.C., Deedwania, P., Kim, J.B. & Borer, J.S. Resting heart rate: risk indicator and emerging risk factor in cardiovascular disease. Am. J. Med. 128, 219–228 (2015).

    Article  Google Scholar 

  14. 14

    Aladin, A.I. et al. The association of resting heart rate and incident hypertension: the Henry Ford Hospital Exercise Testing (FIT) Project. Am. J. Hypertens. 29, 251–257 (2016).

    Article  Google Scholar 

  15. 15

    Jiang, X. et al. Metabolic syndrome is associated with and predicted by resting heart rate: a cross-sectional and longitudinal study. Heart 101, 44–49 (2015).

    CAS  Article  Google Scholar 

  16. 16

    Caetano, J. & Delgado Alves, J. Heart rate and cardiovascular protection. Eur. J. Intern. Med. 26, 217–222 (2015).

    Article  Google Scholar 

  17. 17

    Bangalore, S. et al. β-blocker use and clinical outcomes in stable outpatients with and without coronary artery disease. J. Am. Med. Assoc. 308, 1340–1349 (2012).

    CAS  Article  Google Scholar 

  18. 18

    Messerli, F.H., Grossman, E. & Goldbourt, U. Are β-blockers efficacious as first-line therapy for hypertension in the elderly? A systematic review. J. Am. Med. Assoc. 279, 1903–1907 (1998).

    CAS  Article  Google Scholar 

  19. 19

    Van Gelder, I.C. et al. Lenient versus strict rate control in patients with atrial fibrillation. N. Engl. J. Med. 362, 1363–1373 (2010).

    CAS  Article  Google Scholar 

  20. 20

    Fox, K. et al. Ivabradine in stable coronary artery disease without clinical heart failure. N. Engl. J. Med. 371, 1091–1099 (2014).

    Article  Google Scholar 

  21. 21

    Swedberg, K. et al. Ivabradine and outcomes in chronic heart failure (SHIFT): a randomised placebo-controlled study. Lancet 376, 875–885 (2010).

    CAS  Article  Google Scholar 

  22. 22

    Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).

    Article  Google Scholar 

  23. 23

    den Hoed, M. et al. Identification of heart rate–associated loci and their effects on cardiac conduction and rhythm disorders. Nat. Genet. 45, 621–631 (2013).

    CAS  Article  Google Scholar 

  24. 24

    Pers, T.H. et al. Biological interpretation of genome-wide association studies using predicted gene functions. Nat. Commun. 6, 5890 (2015).

    CAS  Article  Google Scholar 

  25. 25

    Siva, N. UK gears up to decode 100,000 genomes from NHS patients. Lancet 385, 103–104 (2015).

    Article  Google Scholar 

  26. 26

    Collins, F.S. & Varmus, H. A new initiative on precision medicine. N. Engl. J. Med. 372, 793–795 (2015).

    CAS  Article  Google Scholar 

  27. 27

    Fox, K., Ford, I., Steg, P.G., Tendera, M. & Ferrari, R. Ivabradine for patients with stable coronary artery disease and left-ventricular systolic dysfunction (BEAUTIFUL): a randomised, double-blind, placebo-controlled trial. Lancet 372, 807–816 (2008).

    CAS  Article  Google Scholar 

  28. 28

    Azbel, MYa. Universal biological scaling and mortality. Proc. Natl. Acad. Sci. USA 91, 12453–12457 (1994).

    CAS  Article  Google Scholar 

  29. 29

    Davies, G. et al. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112151). Mol. Psychiatry 21, 758–767 (2016).

    CAS  Article  Google Scholar 

  30. 30

    Lane, J.M. et al. Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UK Biobank. Nat. Commun. 7, 10889 (2016).

    CAS  Article  Google Scholar 

  31. 31

    Xu, C. et al. Estimating genome-wide significance for whole-genome sequencing studies. Genet. Epidemiol. 38, 281–290 (2014).

    Article  Google Scholar 

  32. 32

    Kanai, M., Tanaka, T. & Okada, Y. Empirical estimation of genome-wide significance thresholds based on the 1000 Genomes Project data set. J. Hum. Genet. (2016).

  33. 33

    UK Biobank. Genotype imputation and genetic association studies of UK Biobank. Interim data release, May 2015 (2015).

  34. 34

    UK Biobank. Genotyping and quality control of UK Biobank, a largescale, extensively phenotyped prospective resource. Information for researchers. Interim Data Release, 2015. (2015).

  35. 35

    Purcell, S.M. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

    CAS  Article  Google Scholar 

  36. 36

    Thanassoulis, G. et al. Genetic associations with valvular calcification and aortic stenosis. N. Engl. J. Med. 368, 503–512 (2013).

    CAS  Article  Google Scholar 

  37. 37

    Nelson, C.P. et al. Genetically determined height and coronary artery disease. N. Engl. J. Med. 372, 1608–1618 (2015).

    CAS  Article  Google Scholar 

  38. 38

    Burgess, S. & Thompson, S.G. Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects. Am. J. Epidemiol. 181, 251–260 (2015).

    Article  Google Scholar 

  39. 39

    Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44, 512–525 (2015).

    Article  Google Scholar 

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This research was conducted using the UK Biobank Resource. This project is supported by the Netherlands organization for health research and development (ZonMw grant 90.700.441). S.B. is supported by the Wellcome Trust (grant 100114). P.B.M. acknowledges support from the NIHR Cardiovascular Biomedical Research Unit at Barts and the London School of Medicine and Dentistry, Queen Mary University of London. N.V. is supported by Netherlands Heart Institute and Marie Sklodowska-Curie Global Fellowship (grant 661395).

Author information




Participant recruitment, characterization and data generation: D.A.H., K.S., D.F.G., D.J.v.V., P.v.d.H. Data quality control and analysis: R.N.E., Y.H., D.A.H., K.S., D.F.G., R.N.E., N.V., P.v.d.H. Statistical analysis review: R.N.E., S.B., D.F.G., P.B.M., N.V., P.v.d.H. Central data analysis: R.N.E., Y.H., N.V. Supervision of the project: P.v.d.H. Draft of first version of the manuscript: R.N.E., P.v.d.H. All authors critically reviewed and approved the final version of the manuscript.

Corresponding author

Correspondence to Pim van der Harst.

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The authors declare no competing financial interests.

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Eppinga, R., Hagemeijer, Y., Burgess, S. et al. Identification of genomic loci associated with resting heart rate and shared genetic predictors with all-cause mortality. Nat Genet 48, 1557–1563 (2016).

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