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).

  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).

  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).

  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).

  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).

  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).

  8. 8

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

  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).

  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).

  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).

  12. 12

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

  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).

  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).

  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).

  16. 16

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

  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).

  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).

  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).

  20. 20

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

  21. 21

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

  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).

  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).

  24. 24

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

  25. 25

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

  26. 26

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

  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).

  28. 28

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

  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).

  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).

  31. 31

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

  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).

  36. 36

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

  37. 37

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

  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).

  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).

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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.

Correspondence to Pim van der Harst.

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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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