Abstract
We explore how risk-taking in the card game contract bridge, and in a financial gamble, correlate with variation in the dopamine receptor D4 gene (DRD4) among serious tournament bridge players. In bridge risk-taking, we find significant interactions between genetic predisposition and skill. Among men with the 7-repeat allele of DRD4, namely 7R + men, those with more bridge skill take more good risks and fewer bad risks, while the opposite is found for less-expert 7R + men. Conversely, skill does not predict risk-taking among men without the 7R + allele. Consistent with some prior studies, we also find that 7R + men take more risk in the financial gamble. We find no relationship between 7R + and either risk measure among our female subjects. Our results suggest that the dopamine system plays an important role in individual differences in risk-taking among men, and is the first to distinguish between advantageous and disadvantageous risk-taking.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
See Appendix 1 for more information on DRD4 as well as the genotyping.
Obviously, further elaboration is required if these positive expected value risks are correlated with one another.
Some of these studies also look at other genes.
Out of these 237 participants, 209 completed both risk measures and indicated their masterpoints, age and gender, and 175 of these were successfully genotyped. As described in the results section, our analysis only considers these 175 subjects for whom we have all information.
300+ masterpoints, with an additional requirement that some fraction of them be won in regional or national championships, qualifies one to be a Life Master in competitive bridge. 79% of our participants have 300+ masterpoints.
Our bridge quiz and answers are available by request, and are also posted online by the reference to this paper at http://www.hks.harvard.edu/fs/rzeckhau/biblio.htm
For certain hands, participants were also asked to indicate which bid they liked least. This data is not included in our analysis, as it is unclear how dislike translates into a risk preference.
All subsequent analysis considers these 175 participants only.
This difference becomes stronger when including subjects with missing demographic information (chi2 test, p = 0.025)
In a regression with all the data, there is a significant three-way interaction between 7R+, being female and masterpoints, for both good and bad risk. This suggests that the effect of 7R + and masterpoints is dramatically different in men and women.
To get the net predicted effect for any particular player we must multiply the interaction coefficient by his log10(masterpoints + 1) and add to the main effect coefficient.
This result is only slightly surprising. Positing that 7R + men take more risk, they could only have achieved significant success (masterpoints) if they were highly skilled at distinguishing between good and bad risks.
The lack of statistical significance among women is not surprising given the very low number of 7R + women.
Similarly, following Johnson et al. (1993), perhaps less skilled 7R + men are more biased in their probability assessments than skilled 7R + men are, and as one gains more experience, either skills are honed or the worst risk takers are weeded out.
References
Alger, A. (1997). Buffet on bridge. Forbes, 159(11), June 2, 206–208.
Apicella, C. L., Dreber, A., Campbell, B., Gray, P. B., Hoffman, M., & Little, A. C. (2008). Testosterone and financial risk preferences. Evolution and Human Behavior, 29(6), 384–390.
Apicella, C. L., Cesarini, D., Johannesson, M., Dawes, C. T., Lichtenstein, P., Wallace, B., et al. (2010). No association between oxytocin receptor (OXTR) gene polymorphisms and experimentally elicited social preferences. PLoS ONE, 5(6), e11153. doi:10.1371/journal.pone.0011153.
Barnea, A., Cronqvist, H., & Siegel, S. (2010). Nature or nurture: What determines investor behavior? Journal of Financial Economics, 98, 583–604.
Barsky, R. B., Juster, F. T., Kimball, M. S., & Shapiro, M. D. (1997). Preference parameters and behavioral heterogeneity: An experimental approach in the Health and Retirement Study. Quarterly Journal of Economics, 112(2), 537–579.
Bazerman, M., & Chugh, D. (2005). Bounded awareness: Focusing failures in negotiation. In L. Thompson (Ed.), Frontiers of Social Psychology: Negotiation. New York: Psychological Press.
Benjamin, D. J., Chabris, C. F., Glaeser, E., Gudnason, W., Harris, T. B., Laibson, D., et al. (2008). Genoeconomics. In M. Weinstein, J. W. Vaupel, & K. W. Wachter (Eds.), Biosocial Surveys. Committee on Population, Division of Behavioral and Social Sciences and Education. Washington: The National Academies Press.
Byrnes, J. P., Miller, D. C., & Schafer, W. D. (1999). Gender differences in risk taking: A meta-analysis. Psychological Bulletin, 125(3), 367–383.
Calvet, L.E. & Sodini, P. (2010). Twin Picks: Disentangling the determinants of risk-taking in household portfolios. NBER Working Paper.
Carpenter, J., Garcia, J. R., & Lum, J. K. (2011). Dopamine receptor genes predict risk preferences, time preferences, and related economic choices. Journal of Risk and Uncertainty. doi:10.1007/s11166-011-9115-3.
Cesarini, D., Dawes, C. T., Fowler, J. H., Johannesson, M., Lichtenstein, P., & Wallace, B. (2008). Heritability of cooperative behavior in the trust game. Proceedings of the National Academy of Sciences, 105, 3721–3726.
Cesarini, D., Dawes, C. T., Johannesson, M., Lichtenstein, P., & Wallace, B. (2009). Genetic variation in preferences for giving and risk-taking. Quarterly Journal of Economics, 124(2), 809–842.
Cesarini, D., Johannesson, M., Lichtenstein, P., Sandewall, Ö., & Wallace, B. (2010). Financial risk-taking behavior is genetically transmitted. Journal of Finance, 65(5), 1725–1754.
Charness, G., & Gneezy, U. (2010). Portfolio choice and risk attitudes: An experiment. Economic Inquiry, 48(1), 133–146.
Chugh, D., & Bazerman, M. H. (2007). Bounded awareness: What you fail to see can hurt you. Mind and Society, 6(1), 1–18.
Cohan, W. D. (2009). A Tale of Hubris and Wretched Excess on Wall Street. New York: Doubleday.
Congdon, E., Lesch, K. P., & Canli, T. (2008). Analysis of DRD4 and DAT polymorphisms and behavioral inhibition in healthy adults: Implications for impulsivity. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 147B, 27–32.
Crisan, L. G., Pana, S., Vulturar, R., Heilman, R. M., Szekely, R., Druga, B., et al. (2009). Genetic contributions of the serotonin transporter to social learning of fear and economic decision making. Social Cognitive and Affective Neuroscience, 4(4), 399–408.
Croson, R., & Gneezy, U. (2009). Gender differences in preferences. Journal of Economic Literature, 47(2), 1–27.
Ding, Y. C., Chi, H. C., Grady, D. L., Morishima, A., Kidd, J. R., Kidd, K. K., et al. (2002). Evidence of positive selection acting at the human dopamine receptor D4 gene locus. Proceedings of the National Academy of Sciences, 99, 309–14.
Dohmen, T. J., Falk, A., Huffman, D., Sunde, U., Schupp, J., Wagner, G. G. Forthcoming. Individual risk attitudes: New evidence from a large, representative, experimentally-validated survey. Journal of the European Economic Association.
Donkers, B., Melenberg, B., & Van Soest, A. (2001). Estimating risk attitudes using lotteries: A large sample approach. Journal of Risk and Uncertainty, 22(2), 165–95.
Dreber, A., Apicella, C. L., Eisenberg, D. T. A., Garcia, J. R., Zamore, R. S., Lum, J. K., et al. (2009). The 7R polymorphism in the dopamine receptor D-4 gene (DRD4) is associated with financial risk taking in men. Evolution and Human Behavior, 30(2), 85–92.
Ebstein, R. P., Novick, O., Umansky, R., Priel, B., Osher, Y., Blaine, D., et al. (1996). Dopamine D4 receptor (D4DR) exon III polymorphism associated with the human personality trait of novelty seeking. Nature Genetics, 12, 78–80.
Eisenberg, D. T., Campbell, B., Gray, P. B., & Sorenson, M. D. (2008). Dopamine receptor genetic polymorphisms and body composition in undernourished pastoralists: An exploration of nutrition indices among nomadic and recently settled Ariaal men of northern Kenya. BMC Evolutionary Biology, 8, 173.
Eisenberg, D. T., Mackillop, J., Modi, M., Beauchemin, J., Dang, D., Lisman, S. A., et al. (2007). Examining impulsivity as an endophenotype using a behavioral approach: A DRD2 TaqI A and DRD4 48-bp VNTR association study. Behavioral and Brain Functions, 3, 2. doi:10.1186/1744-9081-3-2.
Eisenegger, C., Knoch, D., Ebstein, R. P., Gianotti, L. R., Sandor, P. S., & Fehr, E. (2010). Dopamine receptor D4 polymorphism predicts the effect of L-DOPA on gambling behavior. Biological Psychiatry, 67(8), 702–6.
Feigelson, H. S., Rodriguez, C., Robertson, A. S., Jacobs, E. J., Calle, E. E., Reid, Y. A., et al. (2001). Determinants of DNA yield and quality from buccal cell samples collected with mouthwash. Cancer Epidemiology, Biomarkers & Prevention, 10, 1005–8.
Garcia, J. R., MacKillop, J., Aller, E. L., Merriwether, A. M., Wilson, D. S., & Lum, J. K. (2010). Associations between dopamine D4 receptor gene variation with both infidelity and sexual promiscuity. PLoS ONE, 5(11), e14162. doi:10.1371/journal.pone.0014162.
Gneezy, U., & Potters, J. (1997). An experiment on risk taking and evaluation periods. Quarterly Journal of Economics, 112(2), 631–645.
Halek, M., & Eisenhauer, J. G. (2001). Demography of risk aversion. The Journal of Risk and Insurance, 68, 1–24.
Hamer, D., & Sirota, L. (2000). Beware the chopsticks gene. Molecular Psychiatry, 5, 11–3.
Hogarth, R. M., & Kunreuther, H. (1995). Decision making under ignorance: Arguing with yourself. Journal of Risk and Uncertainty, 10(1), 15–36.
Israel, S., Lerer, E., Shalev, I., Uzefovsky, F., Riebold, M., Laiba, E., et al. (2009). The oxytocin receptor (OXTR) contributes to prosocial fund allocations in the dictator game and the social value orientations task. PLoS ONE, 4, e5535. doi:10.1371/journal.pone.0005535.
Johnson, E. J., Hershey, J., Meszaros, J., & Kunreuther, H. (1993). Framing, probability distortions, and insurance decisions. Journal of Risk and Uncertainty, 7, 35–51.
Knafo, A., Israel, S., Darvasi, A., Bachner-Melman, R., Uzefovsky, F., Cohen, L., et al. (2007). Individual differences in allocation of funds in the dictator game associated with length of the arginine vasopressin 1a receptor RS3 promoter region and correlation between RS3 length and hippocampal mRNA. Genes, Brain and Behavior, 7(3), 266–275.
Kuhnen, C. M., & Chiao, J. Y. (2009). Genetic determinants of financial risk taking. PLoS ONE, 4, e4362. doi:10.1371/journal.pone.0004362.
Laucht, M., Becker, K., Blomeyer, D., & Schmidt, M. H. (2007). Novelty seeking involved in mediating the association between the dopamine D4 receptor gene exon III polymorphism and heavy drinking in male adolescents: Results from a high-risk community sample. Biological Psychiatry, 61(1), 87–92.
Li, D., Sham, P. C., Owen, M. J., & He, L. (2006). Meta-analysis shows significant association between dopamine system genes and attention deficit hyperactivity disorder (ADHD). Human Molecular Genetics, 15(14), 2276–2284.
McDermott, R., Tingley, D., Cowden, J., Frazzetto, G., & Johnson, D. D. (2009). Monoamine oxidase A gene (MAOA) predicts behavioral aggression following provocation. Proceedings of the National Academy of Sciences, 106, 2118–23.
Munafo, M. R., Yalcin, B., Willis-Owen, S. A., & Flint, J. (2008). Association of the dopamine D4 receptor (DRD4) gene and approach-related personality traits: Meta-analysis and new data. Biological Psychiatry, 63(2), 197–206.
Perez de Castro, I., Ibanez, A., Torres, P., Saiz-Ruiz, J., & Fernandez-Piqueras, J. (1997). Genetic association study between pathological gambling and a functional DNA polymorphism at the D4 receptor gene. Pharmacogenetics, 7(5), 345–348.
Roe, B. E., Tilley, M. R., Gu, H. H., Beversdorf, D. Q., Sadee, W., Haab, T. C., et al. (2009). Financial and psychological risk attitudes associated with two single nucleotide polymorphisms in the nicotine receptor (CHRNA4) Gene. PLoS ONE, 4, e6704. doi:10.1371/journal.pone.0006704.
Roiser, J. P., de Martino, B., Tan, G. C., Kumaran, D., Seymour, B., Wood, N. W., et al. (2009). A genetically mediated bias in decision making driven by failure of amygdala control. Journal of Neuroscience, 29(18), 5985–91.
Schoots, O., & Van Tol, H. H. M. (2003). The human dopamine D4 receptor repeat sequences modulate expression. The Pharmacogenomics Journal, 3(6), 343–348.
Wallace, B., Cesarini, D., Lichtenstein, P., & Johannesson, M. (2007). Heritability of ultimatum game responder behavior. Proceedings of the National Academy of Sciences, 104, 15631–4.
Zhong, S., Chew, S. H., Set, E., Zhang, J., Israel, S., Xue, H., et al. (2009a). The heritability of attitude toward economic risk. Twin Research and Human Genetics, 12(1), 103–107.
Zhong, S., Israel, S., Xue, H., Ebstein, R. P., & Chew, S. H. (2009b). Monoamine Oxidase A gene (MAOA) associated with attitude towards longshot risks. PLoS ONE, 4, e8516. doi:10.1371/journal.pone.0008516.
Zhong, S., Israel, S., Xue, H., Sham, P. C., Ebstein, R. P., & Chew, S. H. (2009c). A neurochemical approach to valuation sensitivity over gains and losses. Proceedings of the Royal Society B: Biological Sciences, 276(1676), 4181–4188.
Acknowledgments
We thank the study participants at the Fall 2008 North American Bridge Championship in Boston, MA and Mark Aquino, president of the host Eastern Massachusetts Bridge Association, for making this study possible. We thank Rita Spathis and Alexandra Taylor for valuable laboratory assistance, and Nathan Lord for valuable assistance with data collection. We thank Johan Almenberg, Suzanne Cooper, Magnus Johannesson, Dan Levy, Kip Viscusi (the editor), an anonymous referee, and seminar participants at Harvard Kennedy School, Olin Business School, Simon Fraser University, Stockholm University, the 4th Nordic Conference on Behavioral and Experimental Economics, the 2010 Economic Science Association World Meeting and the Workshop on Biological Basis of Behavioral Economics for helpful comments, and the Berkman Center for Internet and Society for funding. DGR is supported by a grant from the John Templeton Foundation, and NW gratefully acknowledges funding from the NSF.
Author information
Authors and Affiliations
Corresponding author
Appendices
Appendix 1
1.1 Background on DRD4
The human DRD4 gene on chromosome 11 contains a 48 bp variable number tandem repeat (VNTR) polymorphism (variation) in exon 3 and consists of 2–11 repeats (Ding et al. 2002), likely involved in modulating expression of the gene (Schoots and Van Tol 2003). There is generally a trimodal distribution of 2, 4 and 7 repeat alleles (2R, 4R and 7R) in most populations (Ding et al. 2002).
1.2 Genotyping
Genotyping was performed at the Laboratory of Evolutionary Anthropology and Health at Binghamton University, New York. Each participant was given a 15 ml centrifuge tube containing approximately 10 ml of Scope® mouthwash (Feigelson et al. 2001). Participants gently swirled the mouthwash from cheek to cheek for 45 sec, to collect buccal cells. Using a sterile straw, participants were instructed to spit the sample back into the same centrifuge tube. Samples were later centrifuged and prepared for DNA extraction using the Maxwell® 16 System (Promega).
Sufficient DNA for DRD4 Polymerase Chain Reaction (PCR) amplification was extracted from 86% (203/237) of the buccal cell samples. Genotyping was only performed for the one candidate gene DRD4. Previous studies have highlighted problems associated with consistent genotyping of the DRD4 VNTR region (Eisenberg et al. 2008), suggesting multiple PCR runs for each sample to control for allelic dropout. Thus, the PCR reaction was modified to reflect the high content of G and C nucleotides, and all samples that were initially scored as homozygotes were reanalyzed two additional times with different starting template concentrations to confirm genotypes. The PCR reaction consisted of 1× Q-Solution (Qiagen), 1× Buffer (Qiagen), 1 μM Primer 1 (5’ GCGACTACGTGGTCTACTCG 3’), 1 μM Primer 2 (5’ AGGACCCTCATGGCCTTG 3’), 200 μM dATP, 200 μM dTTP, 200 μM dCTP, 100 μM dITP, 100 μM dGTP, 0.3 units HotStar Taq (Qiagen), and 1 μl of DNA template, in a total volume of 10 μl. The PCR profile began with 15 min at 95°C for enzyme activation and denaturing of template DNA followed by 40 cycles consisting of 1 min denaturation at 94°C, 1 min annealing at 55°C, 1.5 min extension at 72°C, and finished with a 10 min extension at 72°C. Amplicons were electrophoresed through 1.4–2.0% agarose gels containing ethidium bromide and genotypes were determined by comparison with a 100 bp ladder. Participants were then scored as either 7R + (at least one allele of at least 7-repeats or more) or 7R− (both alleles less than 7-repeats).
Population stratification can be an issue in this type of candidate gene study (see Hamer and Sirota 2000). Population stratification in this case could lead to biased results due to allele frequency similarities amongst subpopulations with homogeneous ancestry. In the sample studied here, an overwhelming majority of participants self-reported Caucasian race, hence we believe these legitimate concerns to be minimal for our particular results.
Appendix 2
Distribution of investment amounts (out of 250) in the risky financial gamble
Rights and permissions
About this article
Cite this article
Dreber, A., Rand, D.G., Wernerfelt, N. et al. Dopamine and risk choices in different domains: Findings among serious tournament bridge players. J Risk Uncertain 43, 19–38 (2011). https://doi.org/10.1007/s11166-011-9119-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11166-011-9119-z