Literature DB >> 22566634

The genetic architecture of economic and political preferences.

Daniel J Benjamin1, David Cesarini, Matthijs J H M van der Loos, Christopher T Dawes, Philipp D Koellinger, Patrik K E Magnusson, Christopher F Chabris, Dalton Conley, David Laibson, Magnus Johannesson, Peter M Visscher.   

Abstract

Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.

Mesh:

Year:  2012        PMID: 22566634      PMCID: PMC3361436          DOI: 10.1073/pnas.1120666109

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  43 in total

1.  Genomic control for association studies.

Authors:  B Devlin; K Roeder
Journal:  Biometrics       Date:  1999-12       Impact factor: 2.571

2.  The mystery of missing heritability: Genetic interactions create phantom heritability.

Authors:  Or Zuk; Eliana Hechter; Shamil R Sunyaev; Eric S Lander
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-05       Impact factor: 11.205

3.  Upward bias in odds ratio estimates from genome-wide association studies.

Authors:  Chad Garner
Journal:  Genet Epidemiol       Date:  2007-05       Impact factor: 2.135

4.  The impact of poor health on academic performance: New evidence using genetic markers.

Authors:  Weili Ding; Steven F Lehrer; J Niels Rosenquist; Janet Audrain-McGovern
Journal:  J Health Econ       Date:  2008-12-25       Impact factor: 3.883

5.  Editorial policy on candidate gene association and candidate gene-by-environment interaction studies of complex traits.

Authors:  John K Hewitt
Journal:  Behav Genet       Date:  2011-09-18       Impact factor: 2.805

6.  Common SNPs explain a large proportion of the heritability for human height.

Authors:  Jian Yang; Beben Benyamin; Brian P McEvoy; Scott Gordon; Anjali K Henders; Dale R Nyholt; Pamela A Madden; Andrew C Heath; Nicholas G Martin; Grant W Montgomery; Michael E Goddard; Peter M Visscher
Journal:  Nat Genet       Date:  2010-06-20       Impact factor: 38.330

Review 7.  A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry.

Authors:  Laramie E Duncan; Matthew C Keller
Journal:  Am J Psychiatry       Date:  2011-09-02       Impact factor: 18.112

8.  Genome-wide meta-analyses identify multiple loci associated with smoking behavior.

Authors: 
Journal:  Nat Genet       Date:  2010-04-25       Impact factor: 38.330

9.  Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs.

Authors:  S Hong Lee; Teresa R DeCandia; Stephan Ripke; Jian Yang; Patrick F Sullivan; Michael E Goddard; Matthew C Keller; Peter M Visscher; Naomi R Wray
Journal:  Nat Genet       Date:  2012-02-19       Impact factor: 38.330

10.  Individual laboratory-measured discount rates predict field behavior.

Authors:  Christopher F Chabris; David Laibson; Carrie L Morris; Jonathon P Schuldt; Dmitry Taubinsky
Journal:  J Risk Uncertain       Date:  2008-12-01
View more
  77 in total

1.  Stability and change in risk-taking propensity across the adult life span.

Authors:  Anika K Josef; David Richter; Gregory R Samanez-Larkin; Gert G Wagner; Ralph Hertwig; Rui Mata
Journal:  J Pers Soc Psychol       Date:  2016-01-28

2.  Molecular genetics and subjective well-being.

Authors:  Cornelius A Rietveld; David Cesarini; Daniel J Benjamin; Philipp D Koellinger; Jan-Emmanuel De Neve; Henning Tiemeier; Magnus Johannesson; Patrik K E Magnusson; Nancy L Pedersen; Robert F Krueger; Meike Bartels
Journal:  Proc Natl Acad Sci U S A       Date:  2013-05-24       Impact factor: 11.205

3.  Peer Influence, Genetic Propensity, and Binge Drinking: A Natural Experiment and a Replication.

Authors:  Guang Guo; Yi Li; Hongyu Wang; Tianji Cai; Greg J Duncan
Journal:  AJS       Date:  2015-11

4.  Estimating Telomere Length Heritability in an Unrelated Sample of Adults: Is Heritability of Telomere Length Modified by Life Course Socioeconomic Status?

Authors:  Jessica D Faul; Colter M Mitchell; Jennifer A Smith; Wei Zhao
Journal:  Biodemography Soc Biol       Date:  2016

5.  Genetic influences on political ideologies: twin analyses of 19 measures of political ideologies from five democracies and genome-wide findings from three populations.

Authors:  Peter K Hatemi; Sarah E Medland; Robert Klemmensen; Sven Oskarsson; Levente Littvay; Christopher T Dawes; Brad Verhulst; Rose McDermott; Asbjørn Sonne Nørgaard; Casey A Klofstad; Kaare Christensen; Magnus Johannesson; Patrik K E Magnusson; Lindon J Eaves; Nicholas G Martin
Journal:  Behav Genet       Date:  2014-02-26       Impact factor: 2.805

6.  Cohort of birth modifies the association between FTO genotype and BMI.

Authors:  James Niels Rosenquist; Steven F Lehrer; A James O'Malley; Alan M Zaslavsky; Jordan W Smoller; Nicholas A Christakis
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-29       Impact factor: 11.205

7.  Gene by Social-Environment Interaction for Youth Delinquency and Violence: Thirty-Nine Aggression-related Genes.

Authors:  Hexuan Liu; Yi Li; Guang Guo
Journal:  Soc Forces       Date:  2015

Review 8.  Three gaps and what they may mean for risk preference.

Authors:  Ralph Hertwig; Dirk U Wulff; Rui Mata
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-02-18       Impact factor: 6.237

9.  Gender Interacts with Opioid Receptor Polymorphism A118G and Serotonin Receptor Polymorphism -1438 A/G on Speed-Dating Success.

Authors:  Karen Wu; Chuansheng Chen; Robert K Moyzis; Ellen Greenberger; Zhaoxia Yu
Journal:  Hum Nat       Date:  2016-09

10.  The Promises and Pitfalls of Genoeconomics*

Authors:  Daniel J Benjamin; David Cesarini; Christopher F Chabris; Edward L Glaeser; David I Laibson; Vilmundur Guðnason; Tamara B Harris; Lenore J Launer; Shaun Purcell; Albert Vernon Smith; Magnus Johannesson; Patrik K E Magnusson; Jonathan P Beauchamp; Nicholas A Christakis; Craig S Atwood; Benjamin Hebert; Jeremy Freese; Robert M Hauser; Taissa S Hauser; Alexander Grankvist; Christina M Hultman; Paul Lichtenstein
Journal:  Annu Rev Econom       Date:  2012-06-18
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.