Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry

Abstract

Delay discounting (DD), the tendency to discount the value of delayed versus current rewards, is elevated in a constellation of diseases and behavioral conditions. We performed a genome-wide association study of DD using 23,127 research participants of European ancestry. The most significantly associated single-nucleotide polymorphism was rs6528024 (P = 2.40 × 10−8), which is located in an intron of the gene GPM6B. We also showed that 12% of the variance in DD was accounted for by genotype and that the genetic signature of DD overlapped with attention-deficit/hyperactivity disorder, schizophrenia, major depression, smoking, personality, cognition and body weight.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Results of genome-wide association study (GWAS) on DD.
Fig. 2: Genetic correlations (rg, SE) between DD and several traits.

Change history

  • 08 January 2019

    The author list was in the wrong order in the HTML version of the original article and in the HTML version of the original correction notice. This has been corrected to show the 23andMe Research Team as the fourth author and Abraham A. Palmer as the last author in both places.

  • 11 May 2018

    In the version of this article initially published, the consortium authorship was not presented correctly. The 23andMe Research Team was listed as the last author, rather than the fourth, and a line directing readers to the Supplementary Note for a list of members did appear but was not directly associated with the consortium name. Also, the Supplementary Note description stated that both member names and affiliations were included; in fact, only names are given. Finally, the URL for S-PrediXcan was given in the Methods as https://github.com/hakyimlab/S-PrediXcan; the correct URL is https://github.com/hakyimlab/MetaXcan. The errors have been corrected in the HTML and PDF versions of the article.

References

  1. 1.

    Bari, A. & Robbins, T. W. Prog. Neurobiol. 108, 44–79 (2013).

    Article  Google Scholar 

  2. 2.

    Hamilton, K. R. et al. Personal. Disord. 6, 182–198 (2015).

    Article  Google Scholar 

  3. 3.

    Jackson, J. N. S. & MacKillop, J. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 1, 316–325 (2016).

    Article  Google Scholar 

  4. 4.

    Amlung, M., Vedelago, L., Acker, J., Balodis, I. & MacKillop, J. Addiction 112, 51–62 (2017).

    Article  Google Scholar 

  5. 5.

    McClelland, J. et al. Neurosci. Biobehav. Rev. 71, 506–528 (2016).

    Article  Google Scholar 

  6. 6.

    Insel, T. et al. Am. J. Psychiatry 167, 748–751 (2010).

    Article  Google Scholar 

  7. 7.

    Kirby, K. N., Petry, N. M. & Bickel, W. K. J. Exp. Psychol. Gen. 128, 78–87 (1999).

    CAS  Article  Google Scholar 

  8. 8.

    Anokhin, A. P., Grant, J. D., Mulligan, R. C. & Heath, A. C. Biol. Psychiatry 77, 887–894 (2015).

    Article  Google Scholar 

  9. 9.

    Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. Am. J. Hum. Genet. 88, 76–82 (2011).

    CAS  Article  Google Scholar 

  10. 10.

    Fjorback, A. W., Müller, H. K. & Wiborg, O. J. Mol. Neurosci. 37, 191–200 (2009).

    CAS  Article  Google Scholar 

  11. 11.

    Dere, E. et al. Behav. Brain Res. 277, 254–263 (2015).

    CAS  Article  Google Scholar 

  12. 12.

    Darna, M. et al. Behav. Brain Res. 293, 134–142 (2015).

    CAS  Article  Google Scholar 

  13. 13.

    Dalley, J. W. & Roiser, J. P. Neuroscience 215, 42–58 (2012).

    CAS  Article  Google Scholar 

  14. 14.

    Schweighofer, N. et al. J. Neurosci. 28, 4528–4532 (2008).

    CAS  Article  Google Scholar 

  15. 15.

    Fuchsova, B., Alvarez Juliá, A., Rizavi, H. S., Frasch, A. C. & Pandey, G. N. Neuroscience 299, 1–17 (2015).

    CAS  Article  Google Scholar 

  16. 16.

    MacKillop, J. J. Exp. Anal. Behav. 99, 14–31 (2013).

    Article  Google Scholar 

  17. 17.

    Gamazon, E. R. et al. Nat. Genet. 47, 1091–1098 (2015).

    CAS  Article  Google Scholar 

  18. 18.

    Bulik-Sullivan, B. et al. Nat. Genet. 47, 1236–1241 (2015).

    CAS  Article  Google Scholar 

  19. 19.

    Patros, C. H. G. et al. Clin. Psychol. Rev. 43, 162–174 (2016).

    Article  Google Scholar 

  20. 20.

    Gottesman, I. I. & Gould, T. D. Am. J. Psychiatry 160, 636–645 (2003).

    Article  Google Scholar 

  21. 21.

    Durand, E. Y., Do, C. B., Mountain, J. L. & Macpherson, J. M. Preprint at bioRxi v https://doi.org/10.1101/010512 (2014).

  22. 22.

    Eriksson, N. et al. PLoS. Genet. 6, e1000993 (2010).

    Article  Google Scholar 

  23. 23.

    Hyde, C. L. et al. Nat. Genet. 48, 1031–1036 (2016).

    CAS  Article  Google Scholar 

  24. 24.

    Lo, M.-T. et al. Nat. Genet. 49, 152–156 (2017).

    CAS  Article  Google Scholar 

  25. 25.

    Henn, B. M. et al. PLoS ONE 7, e34267 (2012).

    CAS  Article  Google Scholar 

  26. 26.

    Browning, S. R. & Browning, B. L. Am. J. Hum. Genet. 81, 1084–1097 (2007).

    CAS  Article  Google Scholar 

  27. 27.

    Fuchsberger, C., Abecasis, G. R. & Hinds, D. A. Bioinformatics 31, 782–784 (2015).

    CAS  Article  Google Scholar 

  28. 28.

    Zheng, X. et al. Pharmacogenomics J. 14, 192–200 (2014).

    CAS  Article  Google Scholar 

  29. 29.

    Gray, J. C., Amlung, M. T., Palmer, A. A. & MacKillop, J. J. Exp. Anal. Behav. 106, 156–163 (2016).

    Article  Google Scholar 

  30. 30.

    Saunders, J. B., Aasland, O. G., Babor, T. F., de la Fuente, J. R. & Grant, M. Addiction 88, 791–804 (1993).

    CAS  Article  Google Scholar 

  31. 31.

    Aschard, H., Vilhjálmsson, B. J., Joshi, A. D., Price, A. L. & Kraft, P. Am. J. Hum. Genet. 96, 329–339 (2015).

    CAS  Article  Google Scholar 

  32. 32.

    The 1000 Genomes Project Consortium. Nature 467, 1061–1073 (2010).

    Article  Google Scholar 

  33. 33.

    Willer, C. J., Li, Y. & Abecasis, G. R. Bioinformatics 26, 2190–2191 (2010).

    CAS  Article  Google Scholar 

  34. 34.

    Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. Methods. Mol. Biol. 1019, 215–236 (2013).

    CAS  Article  Google Scholar 

  35. 35.

    Bulik-Sullivan, B. K. et al. Nat. Genet. 47, 291–295 (2015).

    CAS  Article  Google Scholar 

  36. 36.

    International HapMap 3 Consortium. et al. Nature 467, 52–58 (2010).

    Article  Google Scholar 

  37. 37.

    Price, A. L., Zaitlen, N. A., Reich, D. & Patterson, N. Nat. Rev. Genet. 11, 459–463 (2010).

    CAS  Article  Google Scholar 

  38. 38.

    Benjamini, Y. & Hochberg, Y. J.R. Stat. Soc. 57, 289–300 (1995).

    Google Scholar 

  39. 39.

    Sanchez-Roige, S. et al. Preprint at bioRxiv https://doi.org/10.1101/147397 (2017).

Download references

Acknowledgements

We thank the research participants and employees of 23andMe for making this work possible. J.M. was partially supported by the Peter Boris Chair in Addictions Research. S.S.-R. was supported by the Frontiers of Innovation Scholars Program (FISP; #3-P3029), the Interdisciplinary Research Fellowship in NeuroAIDS (IRFN; MH081482) and a pilot award from DA037844.

Author information

Affiliations

Authors

Consortia

Contributions

Conceptualization: A.A.P., J.M.; analysis and software: S.S.-R., P.F., L.K.D., J.C.G., A.A.P.; writing: S.S.-R., A.A.P.; review and editing: all authors.

Corresponding author

Correspondence to Abraham A. Palmer.

Ethics declarations

Competing interests

P.F., S.L.E., and members of the 23andMe Research Team are employees of 23andMe Inc. The opinions and assertions expressed herein are those of the authors; specifically, with respect to J.C.G., they do not reflect the official policy or position of the Uniformed Services University or the Department of Defense.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated Supplementary Information

Supplementary Figure 1 Regional association plot focusing on top SNP rs6528025 at 3′ of GPM6B gene on chromosome X at position 13.9 Mb

This plot was generated using LocusZoom1. The -log10(P value) is shown on the left y-axis; position in Mb is on the x-axis. Recombination rates (expressed in centiMorgans cM per Mb; NCBI Build GRCh37; highlighted in blue) are shown on the right y-axis. Pairwise linkage disequilibrium (r2) of each SNP with the top SNP in the region is indicated by its color. Crossed points represent imputed SNPs, circles represent directly genotyped SNPs. The statistical tests used were two-sided; sample size = 23,217.

Supplementary Figure 2 Regional association plot showing the second index SNP rs2665993, located in the EVPL gene on chromosome 17

This plot was generated using LocusZoom1. The -log10(P value) is shown on the left y-axis; position in Mb is on the x-axis. Recombination rates (expressed in centiMorgans cM per Mb; NCBI Build GRCh37; highlighted in blue) are shown on the right y-axis. Pairwise linkage disequilibrium (r2) of each SNP with the top SNP in the region is indicated by its color. Crossed points represent imputed SNPs, circles represent directly genotyped SNPs. The statistical tests used were two-sided; sample size = 23,217.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sanchez-Roige, S., Fontanillas, P., Elson, S.L. et al. Genome-wide association study of delay discounting in 23,217 adult research participants of European ancestry. Nat Neurosci 21, 16–18 (2018). https://doi.org/10.1038/s41593-017-0032-x

Download citation

Further reading

Search

Sign up for the Nature Briefing newsletter for a daily update on COVID-19 science.
Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing