A polygenic score for educational attainment partially predicts voter turnout

Abstract

Twin and adoption studies have shown that individual differences in political participation can be explained, in part, by genetic variation. However, these research designs cannot identify which genes are related to voting or the pathways through which they exert influence, and their conclusions rely on possibly restrictive assumptions. In this study, we use three different US samples and a Swedish sample to test whether genes that have been identified as associated with educational attainment, one of the strongest correlates of political participation, predict self-reported and validated voter turnout. We find that a polygenic score capturing individuals' genetic propensity to acquire education is significantly related to turnout. The strongest associations we observe are in second-order midterm elections in the United States and European Parliament elections in Sweden, which tend to be viewed as less important by voters, parties, and the media and thus present a more information-poor electoral environment for citizens to navigate. A within-family analysis suggests that individuals' education-linked genes directly affect their voting behavior, but, for second-order elections, it also reveals evidence of genetic nurture. Finally, a mediation analysis suggests that educational attainment and cognitive ability combine to account for between 41% and 63% of the relationship between the genetic propensity to acquire education and voter turnout.

Keywords: cognitive ability; education; polygenic score; turnout; voting.

Fig. 1.

Incremental R² for the EA PGS compared to other predictors of voter turnout. The height of each bar represents the increase in the coefficient of determination (R²) when each variable indicated is added as a covariate to a regression of voter turnout on a set of baseline controls that includes gender, birth year, and 10 principal components of the genetic relatedness matrix. Parental income and education are not available for the MTFS parents. The income measure for Add Health and the MTFS twins is personal income before taxes and, for the MTFS parents, household income before taxes. For the WLS sample, the figure reports personal net worth rather than income, since it is a more appropriate measure of financial resources for older individuals in the sample, many of whom are retired. For the STR sample, we use annual register information on gross total wage income and income from business to calculate average income between ages 25 and 65 years.

Fig. 2.

Mediation analysis results for self-reported and validated turnout. The height of each bar represents the estimated effect of the polygenic score on turnout, and the error bars represent 95% confidence intervals. The model with mediators includes years of education and cognitive ability. Both models include controls for gender, birth year, and the first 10 principal components of the genetic relatedness matrix.