Genetic predictors of educational attainment and intelligence test performance predict voter turnout.
Journal
Nature human behaviour
ISSN: 2397-3374
Titre abrégé: Nat Hum Behav
Pays: England
ID NLM: 101697750
Informations de publication
Date de publication:
02 2021
02 2021
Historique:
received:
30
08
2019
accepted:
17
08
2020
pubmed:
11
11
2020
medline:
6
3
2021
entrez:
10
11
2020
Statut:
ppublish
Résumé
Although the genetic influence on voter turnout is substantial (typically 40-50%), the underlying mechanisms remain unclear. Across the social sciences, research suggests that 'resources for politics' (as indexed notably by educational attainment and intelligence test performance) constitute a central cluster of factors that predict electoral participation. Educational attainment and intelligence test performance are heritable. This suggests that the genotypes that enhance these phenotypes could positively predict turnout. To test this, we conduct a genome-wide complex trait analysis of individual-level turnout. We use two samples from the Danish iPSYCH case-cohort study, including a nationally representative sample as well as a sample of individuals who are particularly vulnerable to political alienation due to psychiatric conditions (n = 13,884 and n = 33,062, respectively). Using validated individual-level turnout data from the administrative records at the polling station, genetic correlations and Mendelian randomization, we show that there is a substantial genetic overlap between voter turnout and both educational attainment and intelligence test performance.
Identifiants
pubmed: 33168953
doi: 10.1038/s41562-020-00952-2
pii: 10.1038/s41562-020-00952-2
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
281-291Références
Gerber, A. S., Green, D. P. & Shachar, R. Voting may be habit‐forming: evidence from a randomized field experiment. Am. J. Polit. Sci. 47, 540–550 (2003).
doi: 10.1111/1540-5907.00038
Green, D. P. & Shachar, R. Habit formation and political behaviour: evidence of consuetude in voter turnout. Br. J. Polit. Sci. 30, 561–573 (2000).
doi: 10.1017/S0007123400000247
Plutzer, E. Becoming a habitual voter: inertia, resources, and growth in young adulthood. Am. Polit. Sci. Rev. 96, 41–56 (2002).
doi: 10.1017/S0003055402004227
Wolfinger, R. E. & Rosenstone, S. J. Who Votes? 22 (Yale Univ. Press, 1980).
Dawes, C. et al. The relationship between genes, psychological traits, and political participation. Am. J. Polit. Sci. 58, 888–903 (2014).
doi: 10.1111/ajps.12100
Dawes, C. T., Settle, J. E., Loewen, P. J., McGue, M. & Iacono, W. G. Genes, psychological traits and civic engagement. Philos. Trans. R. Soc. Lond. B 370, 20150015 (2015).
doi: 10.1098/rstb.2015.0015
Fowler, J. H., Baker, L. A. & Dawes, C. T. Genetic variation in political participation. Am. Polit. Sci. Rev. 102, 233–248 (2008).
doi: 10.1017/S0003055408080209
Klemmensen, R. et al. The genetics of political participation, civic duty, and political efficacy across cultures: Denmark and the United States. J. Theor. Polit. 24, 409–427 (2012).
doi: 10.1177/0951629812438984
Loewen, P. J. & Dawes, C. T. The heritability of duty and voter turnout. Polit. Psychol. 33, 363–373 (2012).
doi: 10.1111/j.1467-9221.2012.00881.x
Weinschenk, A. C., Dawes, C. T., Kandler, C., Bell, E. & Riemann, R. New evidence on the link between genes, psychological traits, and political engagement. Polit. Life Sci. 38, 1–13 (2019).
doi: 10.1017/pls.2019.3
Mondak, J. J. Personality and the Foundations of Political Behavior (Cambridge Univ. Press, 2010).
Mondak, J. J., Hibbing, M. V., Canache, D., Seligson, M. A. & Anderson, M. R. Personality and civic engagement: an integrative framework for the study of trait effects on political behavior. Am. Polit. Sci. Rev. 104, 85–110 (2010).
doi: 10.1017/S0003055409990359
Charney, E. Behavior genetics and postgenomics. Behav. Brain Sci. 35, 331–358 (2012).
pubmed: 23095378
doi: 10.1017/S0140525X11002226
Charney, E. & English, W. Genopolitics and the science of genetics. Am. Polit. Sci. Rev. 107, 382–395 (2013).
doi: 10.1017/S0003055413000099
Frey, B. S. Why do high income people participate more in politics? Publ. Choice 11, 101–105 (1971).
doi: 10.1007/BF01726215
Tollison, R. D. & Willett, T. D. Some simple economics of voting and not voting. Publ. Choice 6, 59–71 (1973).
doi: 10.1007/BF01718807
Verba, S., Schlozman, K. L. & Brady, H. E. Voice and Equality: Civic Voluntarism in American Politics 4 (Harvard Univ. Press, 1995).
Brady, H. E., Verba, S. & Schlozman, K. L. Beyond SES: a resource model of political participation. Am. Polit. Sci. Rev. 89, 271–294 (1995).
doi: 10.2307/2082425
Hansen, K. M. Electoral turnouts: strong social norms of voting. in Oxford Handbook of Danish Politics (eds Christiansen, P. M. et al.) 76–87 (Oxford Univ. Press, 2020).
Bouchard, T. J. & McGue, M. Familial studies of intelligence: a review. Science 212, 1055–1059 (1981).
pubmed: 7195071
doi: 10.1126/science.7195071
Hill, W. D. et al. A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence. Mol. Psychiatry 24, 169–181 (2018).
pubmed: 29326435
pmcid: 6344370
doi: 10.1038/s41380-017-0001-5
Plomin R., DeFries, J. C., Knopik, V. S. & Neiderhiser, J. M. Behavioral Genetics 6th edn (Worth Publishers, 2013).
Rowe, D. C., Jacobson, K. C. & Van den Oord, E. J. Genetic and environmental influences on vocabulary IQ: parental education level as moderator. Child Dev. 70, 1151–1162 (1999).
pubmed: 10546338
doi: 10.1111/1467-8624.00084
Krapohl, E. et al. The high heritability of educational achievement reflects many genetically influenced traits, not just intelligence. Proc. Natl Acad. Sci. USA 111, 15273–15278 (2014).
pubmed: 25288728
doi: 10.1073/pnas.1408777111
Converse, P. E. In The Human Meaning of Social Change (eds Campbell, A. & Converse, P. E.) 263–337 (Russell Sage, 1972).
Dinesen, P. T. et al. Estimating the impact of education on political participation: evidence from monozygotic twins in the United States, Denmark and Sweden. Polit. Behav. 38, 579–601 (2016).
doi: 10.1007/s11109-015-9328-2
Verba, S. & Nie, N. H. Participation in America: Social Equality and Political Democracy (Harper & Row, 1972).
Persson, M. Education and political participation. Br. J. Polit. Sci. 45, 689–703 (2015).
doi: 10.1017/S0007123413000409
Nie, N. H., Junn, J. & Stehlik-Barry, K. Education and Democratic Citizenship in America (Univ. Chicago Press, 1996).
Gerber, A. S. et al. Personality traits and participation in political processes. J. Polit. 73, 692–706 (2011).
doi: 10.1017/S0022381611000399
Richardson, M., Abraham, C. & Bond, R. Psychological correlates of university students’ academic performance: a systematic review and meta-analysis. Psychol. Bull. 138, 353–387 (2012).
pubmed: 22352812
doi: 10.1037/a0026838
Moffitt, T. E. et al. A gradient of childhood self-control predicts health, wealth, and public safety. Proc. Natl Acad. Sci. USA 108, 2693–2698 (2011).
pubmed: 21262822
doi: 10.1073/pnas.1010076108
Mõttus, R., Realo, A., Vainik, U., Allik, J. & Esko, T. Educational attainment and personality are genetically intertwined. Psychol. Sci. 28, 1631–1639 (2017).
pubmed: 28910230
doi: 10.1177/0956797617719083
Belsky, D. W. et al. Genetic analysis of social-class mobility in five longitudinal studies. Proc. Natl Acad. Sci. USA 115, E7275–E7284 (2018).
pubmed: 29987013
doi: 10.1073/pnas.1801238115
Belsky, D. W. et al. The genetics of success: how single-nucleotide polymorphisms associated with educational attainment relate to life-course development. Psychol. Sci. 27, 957–972 (2016).
pubmed: 27251486
pmcid: 4946990
doi: 10.1177/0956797616643070
Barth, D., Papageorge, N. W. & Thom, K. Genetic endowments and wealth inequality. J. Polit. Econ. 128, 1474–1522 (2020).
pubmed: 32863431
doi: 10.1086/705415
Sondheimer, R. M. & Green, D. P. Using experiments to estimate the effects of education on voter turnout. Am. J. Polit. Sci. 54, 174–189 (2010).
doi: 10.1111/j.1540-5907.2009.00425.x
Deary, I. J., Batty, G. D. & Gale, C. R. Childhood intelligence predicts voter turnout, voting preferences, and political involvement in adulthood: the 1970 British cohort study. Intelligence 36, 548–555 (2008).
doi: 10.1016/j.intell.2008.09.001
Hillygus, D. S. The missing link: exploring the relationship between higher education and political engagement. Polit. Behav. 27, 25–47 (2005).
doi: 10.1007/s11109-005-3075-8
Sternberg, R. J., Grigorenko, E. L., & Bundy, D. A. The predictive value of IQ. Merrill Palmer Q. 47, 1–41 (2001).
White, E. S. Intelligence and sense of political efficacy in children. J. Polit. 30, 710–731 (1968).
doi: 10.2307/2128802
White, K. R. The relation between socioeconomic status and academic achievement. Psychol. Bull. 91, 461–481 (1982).
doi: 10.1037/0033-2909.91.3.461
Strenze, T. Intelligence and socioeconomic success: a meta-analytic review of longitudinal research. Intelligence 35, 401–426 (2007).
doi: 10.1016/j.intell.2006.09.004
Savage, J. E. et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat. Genet. 50, 912–919 (2018).
pubmed: 29942086
pmcid: 6411041
doi: 10.1038/s41588-018-0152-6
Zheng, J. et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272–279 (2017).
pubmed: 27663502
doi: 10.1093/bioinformatics/btw613
Sniekers, S. et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat. Genet. 49, 1107–1112 (2017).
pubmed: 28530673
pmcid: 5665562
doi: 10.1038/ng.3869
Johnson, W., McGue, M. & Iacono, W. G. Disruptive behavior and school grades: genetic and environmental relations in 11-year-olds. J. Educ. Psychol. 97, 391–405 (2005).
doi: 10.1037/0022-0663.97.3.391
Johnson, W., McGue, M. & Iacono, W. G. Genetic and environmental influences on academic achievement trajectories during adolescence. Dev. Psychol. 42, 514–532 (2006).
pubmed: 16756442
doi: 10.1037/0012-1649.42.3.514
Deary, I. J. & Johnson, W. Intelligence and education: causal perceptions drive analytic processes and therefore conclusions. Int. J. Epidemiol. 39, 1362–1369 (2010).
pubmed: 20504860
doi: 10.1093/ije/dyq072
Davies, G. et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol. Psychiatry 16, 996–1005 (2011).
pubmed: 21826061
pmcid: 3182557
doi: 10.1038/mp.2011.85
Davies, G. et al. Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N = 112 151). Mol. Psychiatry 21, 758–767 (2016).
pubmed: 27046643
pmcid: 4879186
doi: 10.1038/mp.2016.45
Fowler, J. H. & Dawes, C. T. Two genes predict voter turnout. J. Polit. 70, 579–594 (2008).
doi: 10.1017/S0022381608080638
Abdellaoui, A. et al. Genetic correlates of social stratification in Great Britain. Nat. Hum. Behav. 3, 1332–1342 (2019).
pubmed: 31636407
doi: 10.1038/s41562-019-0757-5
Ojeda, C. Depression and political participation. Soc. Sci. Q. 96, 1226–1243 (2015).
pubmed: 26924857
pmcid: 4764256
doi: 10.1111/ssqu.12173
Burden, B. C., Fletcher, J. M., Herd, P., Moynihan, D. P. & Jones, B. M. How different forms of health matter to political participation. J. Polit. 79, 166–178 (2017).
pubmed: 29503463
doi: 10.1086/687536
Cesarini, D., Johannesson, M. & Oskarsson, S. Pre-birth factors, post-birth factors, and voting: evidence from Swedish adoption data. Am. Polit. Sci. Rev. 108, 71–87 (2014).
doi: 10.1017/S0003055413000592
Shultziner, D. Genes and politics: a new explanation and evaluation of twin study results and association studies in political science. Polit. Anal. 21, 350–367 (2013).
doi: 10.1093/pan/mps035
Rosenstone, S. J. & Wolfinger, R. E. The effect of registration laws on voter turnout. Am. Polit. Sci. Rev. 72, 22–45 (1978).
doi: 10.2307/1953597
Pedersen, C. B. et al. The iPSYCH2012 case–cohort sample: new directions for unravelling genetic and environmental architectures of severe mental disorders. Mol. Psychiatry 23, 6–14 (2018).
pubmed: 28924187
doi: 10.1038/mp.2017.196
Highton, B. Voter identification laws and turnout in the United States. Annu. Rev. Polit. Sci. 20, 149–167 (2017).
doi: 10.1146/annurev-polisci-051215-022822
Mental Disorders Affect One In Four People World Health Report (WHO, 2001); https://www.who.int/whr/2001/media_centre/press_release/en/
Bullenkamp, J. & Voges, B. Voting preferences of outpatients with chronic mental illness in Germany. Psychiatr. Serv. 55, 1440–1442 (2004).
pubmed: 15572576
doi: 10.1176/appi.ps.55.12.1440
Siddique, A. & Lee, A. A survey of voting practices in an acute psychiatric unit. Ir. J. Psychol. Med. 31, 229–231 (2014).
pubmed: 30189507
doi: 10.1017/ipm.2014.53
Couture, J. & Breux, S. The differentiated effects of health on political participation. Eur. J. Publ. Health 27, 599–604 (2017).
Ojeda, C. & Pacheco, J. Health and voting in young adulthood. Br. J. Polit. Sci. 49, 1163–1186 (2017).
doi: 10.1017/S0007123417000151
Sund, R., Lahtinen, H., Wass, H., Mattila, M. & Martikainen, P. How voter turnout varies between different chronic conditions? A population-based register study. J. Epidemiol. Community Health 71, 475–479 (2017).
pubmed: 27965314
doi: 10.1136/jech-2016-208314
Kelly, B. D. & Nash, M. Voter participation among people attending mental health services in Ireland. Ir. J. Med. Sci. 188, 925–929 (2018).
pubmed: 30374802
doi: 10.1007/s11845-018-1921-z
Evans, L. M. et al. Narrow-sense heritability estimation of complex traits using identity-by-descent information. Heredity 121, 616–630 (2018).
pubmed: 29588506
pmcid: 6221881
doi: 10.1038/s41437-018-0067-0
Wray, N. R. et al. Pitfalls of predicting complex traits from SNPs. Nat. Rev. Genet. 14, 507–515 (2013).
pubmed: 23774735
pmcid: 4096801
doi: 10.1038/nrg3457
Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
pubmed: 21167468
pmcid: 21167468
doi: 10.1016/j.ajhg.2010.11.011
Vinkhuyzen, A. A. et al. Common SNPs explain some of the variation in the personality dimensions of neuroticism and extraversion. Transl. Psychiatry 2, e102 (2012).
pubmed: 22832902
pmcid: 3337075
doi: 10.1038/tp.2012.27
Benjamin, D. J. et al. The genetic architecture of economic and political preferences. Proc. Natl Acad. Sci. USA 109, 8026–8031 (2012).
pubmed: 22566634
doi: 10.1073/pnas.1120666109
Tingsten, H. Political Behavior: Studies in Election Statistics (PS King, 1937).
Bhatti, Y., Dahlgaard, J. O., Hansen, J. H. & Hansen, K. M. Core and peripheral voters: predictors of turnout across three types of elections. Polit. Stud. 67, 348–366 (2019).
doi: 10.1177/0032321718766246
Lee, J. J. et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50, 1112–1121 (2018).
pubmed: 30038396
pmcid: 6393768
doi: 10.1038/s41588-018-0147-3
Domingue, B. W. et al. The social genome of friends and schoolmates in the National Longitudinal Study of Adolescent to Adult Health. Proc. Natl Acad. Sci. USA 115, 702–707 (2018).
pubmed: 29317533
doi: 10.1073/pnas.1711803115
Lewis, C. M. & Vassos, E. Prospects for using risk scores in polygenic medicine. Genome Med. 9, 96 (2017).
pubmed: 29132412
pmcid: 5683372
doi: 10.1186/s13073-017-0489-y
Okbay, A. et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature 533, 539–542 (2016).
pubmed: 27225129
pmcid: 4883595
doi: 10.1038/nature17671
Blais, A. & St-Vincent, S. L. Personality traits, political attitudes and the propensity to vote. Eur. J. Polit. Res. 50, 395–417 (2011).
doi: 10.1111/j.1475-6765.2010.01935.x
Denny, K. & Doyle, O. Political interest, cognitive ability and personality: determinants of voter turnout in Britain. Br. J. Polit. Sci. 38, 291–310 (2008).
doi: 10.1017/S000712340800015X
Gallego, A. & Oberski, D. Personality and political participation: the mediation hypothesis. Polit. Behav. 34, 425–451 (2012).
doi: 10.1007/s11109-011-9168-7
Weinschenk, A. Cause you’ve got personality: political participation and the tendency to join civic groups. SAGE Open 3, 1–12 (2013).
doi: 10.1177/2158244013508418
Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
pubmed: 25642630
pmcid: 25642630
doi: 10.1038/ng.3211
Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).
doi: 10.1038/ng.3538
Fowler, J. H. & Schreiber, D. Biology, politics, and the emerging science of human nature. Science 322, 912–914 (2008).
pubmed: 18988845
doi: 10.1126/science.1158188
Kong, A. et al. The nature of nurture: effects of parental genotypes. Science 359, 424–428 (2018).
pubmed: 29371463
doi: 10.1126/science.aan6877
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).
Mortensen, P. B. Response to “Ethical concerns regarding Danish genetic research”. Mol. Psychiatry 24, 1574–1575 (2019).
pubmed: 30413799
doi: 10.1038/s41380-018-0296-x
Schork, A. J. et al. A genome-wide association study of shared risk across psychiatric disorders implicates gene regulation during fetal neurodevelopment. Nat. Neurosci. 22, 353–361 (2019).
pubmed: 30692689
pmcid: 6497521
doi: 10.1038/s41593-018-0320-0
Nørgaard‐Pedersen, B. & Hougaard, D. M. Storage policies and use of the Danish newborn screening Biobank. J. Inherit. Metab. Dis. 30, 530–536 (2007).
pubmed: 17632694
doi: 10.1007/s10545-007-0631-x
De Moor, M. H. et al. Meta-analysis of genome-wide association studies for personality. Mol. Psychiatry 17, 337–349 (2012).
pubmed: 21173776
doi: 10.1038/mp.2010.128
Bhatti, Y., Hansen, K. M. & Wass, H. The relationship between age and turnout: a roller-coaster ride. Elect. Stud. 31, 588–593 (2012).
doi: 10.1016/j.electstud.2012.05.007
Duan, S., Zhang, W., Cox, N. J. & Dolan, M. E. FstSNP-HapMap3: a database of SNPs with high population differentiation for HapMap3. Bioinformation 3, 139–141 (2008).
pubmed: 19238253
pmcid: 2639690
doi: 10.6026/97320630003139
Ge, T., Chen, C. Y., Neale, B. M., Sabuncu, M. R. & Smoller, J. W. Correction: phenome-wide heritability analysis of the UK Biobank. PLoS Genet. 14, e1007228 (2018).
pubmed: 29425192
pmcid: 5806775
doi: 10.1371/journal.pgen.1007228
Abraham, G. & Inouye, M. Fast principal component analysis of large-scale genome-wide data. PLoS ONE 9, e93766 (2014).
pubmed: 24718290
pmcid: 3981753
doi: 10.1371/journal.pone.0093766
Canty A. & Ripley B. D. boot: bootstrap R (S-Plus) functions. R package version 1.3-25 https://cran.r-project.org/web/packages/boot/index.html (2020).
Davison A. C. & Hinkley D. V. Bootstrap Methods and Their Applications (Cambridge Univ. Press, 1997); http://statwww.epfl.ch/davison/BMA/
Lee, S. H., Goddard, M. E., Wray, N. R. & Visscher, P. M. A. Better coefficient of determination for genetic profile analysis. Genet. Epidemiol. 36, 214–224 (2012).
pubmed: 22714935
doi: 10.1002/gepi.21614
Zhu, Z. et al. Causal associations between risk factors and common diseases inferred from GWAS summary data. Nat. Commun. 9, 224 (2018).
pubmed: 5768719
pmcid: 5768719
doi: 10.1038/s41467-017-02317-2