Skip to main content

Advertisement

Log in

Divergence of an association between depressive symptoms and a dopamine polygenic score in Caucasians and Asians

  • Original Paper
  • Published:
European Archives of Psychiatry and Clinical Neuroscience Aims and scope Submit manuscript

Abstract

A recent study reported a negative association between a putatively functional dopamine (DA) polygenic score, indexing higher levels of DA signaling, and depressive symptoms. We attempted to replicate this association using data from the Duke Neurogenetics Study. Our replication attempt was made in a subsample of 520 non-Hispanic Caucasian volunteers (277 women, mean age 19.78 ± 1.24 years). The DA polygenic score was based on the following five loci: rs27072 (SLC6A3/DAT1), rs4532 (DRD1), rs1800497 (DRD2/ANKK1), rs6280 (DRD3), and rs4680 (COMT). Because the discovery sample in the original study consisted mostly of Asian participants, we also conducted a post hoc analysis in a smaller subsample of Asian volunteers (N = 316, 179 women, mean age 19.61 ± 1.32 years). In the primary sample of non-Hispanic Caucasians, a linear regression analysis controlling for sex, age, socioeconomic status (SES), body mass index, genetic ancestry, and both early and recent life stress, revealed that higher DA polygenic scores were associated with higher self-reported symptoms of depression. This was in contrast to the original association of higher DA polygenic scores and lower depressive symptoms. However, the direction of the association in our Asian subsample was consistent with this original finding. Our results also suggested that compared to the Asian subsample, the non-Hispanic Caucasian subsample was characterized by higher SES, lower early and recent life stress, and lower depressive symptoms. These differences may have contributed to the observed divergence in associations. Collectively, the current findings add to evidence that specific genetic associations may differ between populations and further encourage explicit modeling of race/ethnicity in examining the polygenic nature of depressive symptoms and depression.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Grace AA (2016) Dysregulation of the dopamine system in the pathophysiology of schizophrenia and depression. Nat Rev Neurosci 17:524

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Belujon P, Grace AA (2017) Dopamine system dysregulation in major depressive disorders. Int J Neuropsychopharmacol 20:1036–1046

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Howard DM, Adams MJ, Shirali M et al (2018) Genome-wide association study of depression phenotypes in UK biobank identifies variants in excitatory synaptic pathways. Nat Commun 9:1470

    PubMed  PubMed Central  Google Scholar 

  4. Wray NR, Ripke S, Mattheisen M et al (2018) Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet 50:668–681

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Pearson-Fuhrhop KM, Dunn EC, Mortero S et al (2014) Dopamine genetic risk score predicts depressive symptoms in healthy adults and adults with depression. PLoS One 9:e93772

    PubMed  PubMed Central  Google Scholar 

  6. Wise R (2004) Dopamine, learning and motivation. Nat Rev Neurosci 5:483–494

    CAS  PubMed  Google Scholar 

  7. Wise R (2008) Dopamine and reward: the anhedonia hypothesis 30 years on. Neurotox Res 14:169–183

    PubMed  PubMed Central  Google Scholar 

  8. Lecrubier Y, Sheehan DV, Weiller E et al (1997) The mini international neuropsychiatric interview (mini). A short diagnostic structured interview: reliability and validity according to the CIDI. Eur Psychiatry 12:224–231

    Google Scholar 

  9. First MB, Gibbon M, Spitzer RL et al (1997) Structured clinical interview for DSM-IV axis II personality disorders, (SCID-II). American Psychiatric Press, Washington, DC

    Google Scholar 

  10. Adler NE, Epel ES, Castellazzo G et al (2000) Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy, white women. Health Psychol 19:586

    CAS  PubMed  Google Scholar 

  11. Purcell S, Neale B, Todd-Brown K et al (2007) Plink: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81:559–575

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Radloff LS (1977) The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas 1:385–401

    Google Scholar 

  13. Bernstein DP, Stein JA, Newcomb MD et al (2003) Development and validation of a brief screening version of the childhood trauma questionnaire. Child Abuse Negl 27:169–190

    PubMed  Google Scholar 

  14. Clements K, Turpin G (1996) The life events scale for students: validation for use with british samples. Pers Individ Differ 20:747–751

    Google Scholar 

  15. Avinun R, Nevo A, Knodt AR et al (2017) Reward-related ventral striatum activity buffers against the experience of depressive symptoms associated with sleep disturbances. J Neurosci 37:9724–9729

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Nikolova YS, Bogdan R, Brigidi BD et al (2012) Ventral striatum reactivity to reward and recent life stress interact to predict positive affect. Biol Psychiatry 72:157–163

    PubMed  Google Scholar 

  17. Johnston E, Johnson S, McLeod P et al (2004) The relation of body mass index to depressive symptoms. Can J Public Health 95:179–183

    PubMed  PubMed Central  Google Scholar 

  18. Do CB, Tung JY, Dorfman E et al (2011) Web-based genome-wide association study identifies two novel loci and a substantial genetic component for parkinson’s disease. PLoS Genet 7:e1002141

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Eriksson N, Macpherson JM, Tung JY et al (2010) Web-based, participant-driven studies yield novel genetic associations for common traits. PLoS Genet 6:e1000993

    PubMed  PubMed Central  Google Scholar 

  20. Tung JY, Do CB, Hinds DA et al (2011) Efficient replication of over 180 genetic associations with self-reported medical data. PLoS One 6:e23473

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Muthén LK, Muthén BO (2007) Mplus user’s guide. Muthén & Muthén, Los Angeles

    Google Scholar 

  22. Avinun R, Nevo A, Knodt AR et al (2018) Replication in imaging genetics: the case of threat-related amygdala reactivity. Biol Psychiatry 84:148–159

    PubMed  Google Scholar 

  23. van Aert RC, van Assen MA (2018) Examining reproducibility in psychology: a hybrid method for combining a statistically significant original study and a replication. Behav Res Methods 50:1515–1539

    PubMed  Google Scholar 

  24. Savitz J, Hodgkinson CA, Martin-Soelch C et al (2013) DRD2/ANKK1 Taq1A polymorphism (rs1800497) has opposing effects on d2/3 receptor binding in healthy controls and patients with major depressive disorder. Int J Neuropsychopharmacol 16:2095–2101

    CAS  PubMed  Google Scholar 

  25. Karrer TM, Josef AK, Mata R et al (2017) Reduced dopamine receptors and transporters but not synthesis capacity in normal aging adults: a meta-analysis. Neurobiol Aging 57:36–46

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Nikolaidis A, Gray JR (2009) ADHD and the DRD4 exon III 7-repeat polymorphism: an international meta-analysis. Soc Cogn Affect Neurosci 5:188–193

    PubMed  PubMed Central  Google Scholar 

  27. Cerasa A, Gioia MC, Labate A et al (2008) Impact of catechol-o-methyltransferase Val108/158 met genotype on hippocampal and prefrontal gray matter volume. Neuroreport 19:405–408

    CAS  PubMed  Google Scholar 

  28. Wang Y, Li J, Chen C et al (2013) Comt rs4680 met is not always the ‘smart allele’: Val allele is associated with better working memory and larger hippocampal volume in healthy chinese. Genes Brain Behav 12:323–329

    CAS  PubMed  Google Scholar 

  29. Klengel T, Binder EB (2015) Epigenetics of stress-related psychiatric disorders and gene × environment interactions. Neuron 86:1343–1357

    CAS  PubMed  Google Scholar 

  30. Belujon P, Grace AA (2015) Regulation of dopamine system responsivity and its adaptive and pathological response to stress. Proc R Soc B Biol Sci 282:20142516

    Google Scholar 

  31. Kim HS, Sherman DK, Mojaverian T et al (2011) Gene–culture interaction: oxytocin receptor polymorphism (OXTR) and emotion regulation. Soc Psychol Pers Sci 2:665–672

    Google Scholar 

  32. Avinun R, Davidov M, Mankuta D et al (2018) Predicting the use of corporal punishment: child aggression, parent religiosity, and the BDNF gene. Aggress Behav 44:165–175

    PubMed  Google Scholar 

  33. GTEx Consortium (2013) The genotype-tissue expression (GTEX) project. Nat Genet 45:580

    Google Scholar 

  34. Boyle EA, Li YI, Pritchard JK (2017) An expanded view of complex traits: from polygenic to omnigenic. Cell 169:1177–1186

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Ray LA, Bujarski S, Chin PF et al (2011) Pharmacogenetics of naltrexone in Asian Americans: a randomized placebo-controlled laboratory study. Neuropsychopharmacology 37:445

    PubMed  PubMed Central  Google Scholar 

  36. Kato M, Zanardi R, Rossini D et al (2009) 5-HT2A gene variants influence specific and different aspects of antidepressant response in japanese and italian mood disorder patients. Psychiatry Res 167:97–105

    CAS  PubMed  Google Scholar 

  37. Porcelli S, Fabbri C, Serretti A (2012) Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with antidepressant efficacy. Eur Neuropsychopharmacol 22:239–258

    CAS  PubMed  Google Scholar 

  38. Shen H, He MM, Liu H et al (2007) Comparative metabolic capabilities and inhibitory profiles of CYP2D6. 1, CYP2D6. 10, and CYP2D6. 17. Drug Metab Dispos 35:1292–1300

    CAS  PubMed  Google Scholar 

  39. Huang W, Ma JZ, Payne TJ et al (2008) Significant association of DRD1 with nicotine dependence. Hum Genet 123:133–140

    CAS  PubMed  Google Scholar 

  40. Ota VK, Spindola LN, Gadelha A et al (2012) Drd1 rs4532 polymorphism: a potential pharmacogenomic marker for treatment response to antipsychotic drugs. Schizophr Res 142:206–208

    PubMed  Google Scholar 

  41. Ferrari M, Comi C, Marino F et al (2016) Polymorphisms of dopamine receptor genes and risk of visual hallucinations in Parkinson’s patients. Eur J Clin Pharmacol 72:1335–1341

    CAS  PubMed  Google Scholar 

  42. Thompson J, Thomas N, Singleton A et al (1997) D2 dopamine receptor gene (DRD2) taq1 a polymorphism: reduced dopamine d2 receptor binding in the human striatum associated with the a1 allele. Pharmacogenetics 7:479–484

    CAS  PubMed  Google Scholar 

  43. Noble E, Blum K, Ritchie T et al (1991) Allelic association of the d2 dopamine receptor gene with receptor-binding characteristics in alcoholism. Arch Gen Psychiatry 48:648–654

    CAS  PubMed  Google Scholar 

  44. Stice E, Spoor S, Bohon C et al (2008) Relation between obesity and blunted striatal response to food is moderated by TaqIA A1 allele. Science 322:449–452

    CAS  PubMed  Google Scholar 

  45. Jeanneteau F, Funalot B, Jankovic J et al (2006) A functional variant of the dopamine d3 receptor is associated with risk and age-at-onset of essential tremor. Proc Natl Acad Sci USA 103:10753–10758

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Savitz J, Hodgkinson CA, Martin-Soelch C et al (2013) The functional DRD3 ser9gly polymorphism (rs6280) is pleiotropic, affecting reward as well as movement. PLoS One 8:e54108

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Lachman HM, Papolos DF, Saito T et al (1996) Human catechol-o-methyltransferase pharmacogenetics: description of a functional polymorphism and its potential application to neuropsychiatric disorders. Pharmacogenetics 6:243–250

    CAS  PubMed  Google Scholar 

  48. Dreher J-C, Kohn P, Kolachana B et al (2009) Variation in dopamine genes influences responsivity of the human reward system. Proc Natl Acad Sci USA 106:617–622

    CAS  PubMed  Google Scholar 

  49. Pinsonneault JK, Han DD, Burdick KE et al (2011) Dopamine transporter gene variant affecting expression in human brain is associated with bipolar disorder. Neuropsychopharmacology 36:1644–1655

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the Duke Neurogenetics Study participants and the staff of the Laboratory of NeuroGenetics, especially Annchen R. Knodt. The Duke Neurogenetics Study was supported by Duke University as well as US-National Institutes of Health Grants R01DA033369 and R01DA031579. RA and ARH received further support from US-National Institutes of Health Grant R01AG049789.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Reut Avinun.

Ethics declarations

Conflict of interest

The authors declare no competing financial or other interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Avinun, R., Nevo, A., Radtke, S.R. et al. Divergence of an association between depressive symptoms and a dopamine polygenic score in Caucasians and Asians. Eur Arch Psychiatry Clin Neurosci 270, 229–235 (2020). https://doi.org/10.1007/s00406-019-01040-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00406-019-01040-x

Keywords

Navigation