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Cited by 318Intergenerational and Educational Inequality StudiesGenetic Associations and EpidemiologyCognitive Abilities and Testing

The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.

Genetic analysis of social-class mobility in five longitudinal studies

Open access
Belsky, Daniel W., Domingue, Benjamin W., Wedow, Robbee, Arseneault, Louise, Boardman, Jason D., Caspi, Avshalom, Conley, Dalton, Fletcher, Jason M., Freese, Jeremy, Herd, Pamela, Moffitt, Terrie E., Poulton, Richie, Sicinski, Kamil, Wertz, Jasmin, Harris, Kathleen Mullan·2018·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.1801238115PMC PMC6077729
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Abstract

Significance: Genome-wide association study (GWAS) discoveries about educational attainment have raised questions about the meaning of the genetics of success. These discoveries could offer clues about biological mechanisms or, because children inherit genetics and social class from parents, education-linked genetics could be spurious correlates of socially transmitted advantages. To distinguish between these hypotheses, we studied social mobility in five cohorts from three countries. We found that people with more education-linked genetics were more successful compared with parents and siblings. We also found mothers’ education-linked genetics predicted their children’s attainment over and above the children’s own genetics, indicating an environmentally mediated genetic effect. Findings reject pure social-transmission explanations of education GWAS discoveries. Instead, genetics influences attainment directly through social mobility and indirectly through family environments.

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Figures

Fig. 1. Cohorts included in analysis of social mobility. Sample sizes reflect participants of European descent with available genetic and attainment data.
Fig. 1. Cohorts included in analysis of social mobility. Sample sizes reflect participants of European descent with available genetic and attainment data.CC BY-NC-ND · PubMed Central
Fig. 2. Effect-size estimates for education polygenic score associations with social attainment and mobility in five cohorts. The figure graphs effect-size estimates (Pearson’s r) for education polygenic score associations with social attainment and mobility. Polygenic score associations with attainment are graphed in navy blue. Polygenic score associations with social mobility are graphed in light blue. Error bars show 95% CIs for effect-size estimates. Mobility effect sizes were estimated from analysis of attainment with covariate adjustment for social origins. Model details are in SI Appendix, 1.7. Result details are in SI Appendix, Table S2.
Fig. 2. Effect-size estimates for education polygenic score associations with social attainment and mobility in five cohorts. The figure graphs effect-size estimates (Pearson’s r) for education polygenic score associations with social attainment and mobility. Polygenic score associations with attainment are graphed in navy blue. Polygenic score associations with social mobility are graphed in light blue. Error bars show 95% CIs for effect-size estimates. Mobility effect sizes were estimated from analysis of attainment with covariate adjustment for social origins. Model details are in SI Appendix, 1.7. Result details are in SI Appendix, Table S2.CC BY-NC-ND · PubMed Central
Fig. 3. Sibling-difference effect-size estimates for education polygenic score associations with social attainment and mobility in three cohorts with sibling data. The figure graphs effect-size estimates (comparable to the Pearson’s r reported for full-sample analysis) for education polygenic score associations with social attainment and mobility from analyses of siblings in the E-Risk, Add Health, and WLS cohorts. Polygenic score associations with attainment in the samples of siblings are graphed in navy blue. Polygenic score associations estimated in sibling-difference models are graphed in light blue. Error bars show 95% CIs for effect-size estimates. Sibling-difference effect sizes were estimated from family fixed-effects regression models. Model details are in SI Appendix, 1.7. Results details are in SI Appendix, Table S3.
Fig. 3. Sibling-difference effect-size estimates for education polygenic score associations with social attainment and mobility in three cohorts with sibling data. The figure graphs effect-size estimates (comparable to the Pearson’s r reported for full-sample analysis) for education polygenic score associations with social attainment and mobility from analyses of siblings in the E-Risk, Add Health, and WLS cohorts. Polygenic score associations with attainment in the samples of siblings are graphed in navy blue. Polygenic score associations estimated in sibling-difference models are graphed in light blue. Error bars show 95% CIs for effect-size estimates. Sibling-difference effect sizes were estimated from family fixed-effects regression models. Model details are in SI Appendix, 1.7. Results details are in SI Appendix, Table S3.CC BY-NC-ND · PubMed Central
Fig. 4. Education polygenic score associations with social attainment for Add Health Study, WLS, Dunedin Study, and HRS participants with low-, middle-, and high-socioeconomic status (SES) social origins. The figure plots polygenic score associations with socioeconomic attainment for Add Health Study (A), Dunedin Study (B), WLS (C), and HRS (D) participants who grew up in low-, middle-, and high-SES households. For the figure, low- middle-, and high-SES households were defined as the bottom quartile, middle 50%, and top quartile of the social origins score distributions for the Add Health Study, WLS, and HRS. For the Dunedin Study, low SES was defined as a childhood NZSEI of two or lower (20% of the sample), middle SES was defined as childhood NZSEI of three to four (63% of the sample), and high SES was defined as childhood NZSEI of five or six (17% of the sample). Attainment is graphed in terms of socioeconomic index scores for the Add Health Study, Dunedin Study, and WLS and in terms of household wealth in the HRS. Add Health Study and WLS socioeconomic index scores were calculated from Hauser and Warren (34) occupational income and occupational education scores. Dunedin Study socioeconomic index scores were calculated similarly, according to the Statistics New Zealand NZSEI (38). HRS household wealth was measured from structured interviews about assets. All measures were z-transformed to have mean = 0, SD = 1 for analysis. The individual graphs show binned scatterplots in which each plotted point reflects average x and y coordinates for a bin of 50 participants for the Add Health Study, WLS, and HRS and for a bin of 10 participants for the Dunedin Study. The red regression lines are plotted from the raw data. The box-and-whisker plots at the bottom of the graphs show the distribution of the education polygenic score for each childhood SES category. The blue diamond in the middle of the box shows the median; the box shows the interquartile range; and the whiskers show upper and lower bounds defined by the 25th percentile minus 1.5× the interquartile range and the 75th percentile plus 1.5× the interquartile range, respectively. The vertical line intersecting the x axis shows the cohort average polygenic score. The figure illustrates three findings observed consistently across cohorts: (i) participants who grew up in higher-SES households tended to have higher socioeconomic attainment independent of their genetics compared with peers who grew up in lower-SES households; (ii) participants’ polygenic scores were correlated with their social origins such that those who grew up in higher-SES households tended to have higher polygenic scores compared with peers who grew up in lower-SES households; (iii) participants with higher polygenic scores tended to achieve higher levels of attainment across strata of social origins, including those born into low-SES families.
Fig. 4. Education polygenic score associations with social attainment for Add Health Study, WLS, Dunedin Study, and HRS participants with low-, middle-, and high-socioeconomic status (SES) social origins. The figure plots polygenic score associations with socioeconomic attainment for Add Health Study (A), Dunedin Study (B), WLS (C), and HRS (D) participants who grew up in low-, middle-, and high-SES households. For the figure, low- middle-, and high-SES households were defined as the bottom quartile, middle 50%, and top quartile of the social origins score distributions for the Add Health Study, WLS, and HRS. For the Dunedin Study, low SES was defined as a childhood NZSEI of two or lower (20% of the sample), middle SES was defined as childhood NZSEI of three to four (63% of the sample), and high SES was defined as childhood NZSEI of five or six (17% of the sample). Attainment is graphed in terms of socioeconomic index scores for the Add Health Study, Dunedin Study, and WLS and in terms of household wealth in the HRS. Add Health Study and WLS socioeconomic index scores were calculated from Hauser and Warren (34) occupational income and occupational education scores. Dunedin Study socioeconomic index scores were calculated similarly, according to the Statistics New Zealand NZSEI (38). HRS household wealth was measured from structured interviews about assets. All measures were z-transformed to have mean = 0, SD = 1 for analysis. The individual graphs show binned scatterplots in which each plotted point reflects average x and y coordinates for a bin of 50 participants for the Add Health Study, WLS, and HRS and for a bin of 10 participants for the Dunedin Study. The red regression lines are plotted from the raw data. The box-and-whisker plots at the bottom of the graphs show the distribution of the education polygenic score for each childhood SES category. The blue diamond in the middle of the box shows the median; the box shows the interquartile range; and the whiskers show upper and lower bounds defined by the 25th percentile minus 1.5× the interquartile range and the 75th percentile plus 1.5× the interquartile range, respectively. The vertical line intersecting the x axis shows the cohort average polygenic score. The figure illustrates three findings observed consistently across cohorts: (i) participants who grew up in higher-SES households tended to have higher socioeconomic attainment independent of their genetics compared with peers who grew up in lower-SES households; (ii) participants’ polygenic scores were correlated with their social origins such that those who grew up in higher-SES households tended to have higher polygenic scores compared with peers who grew up in lower-SES households; (iii) participants with higher polygenic scores tended to achieve higher levels of attainment across strata of social origins, including those born into low-SES families.CC BY-NC-ND · PubMed Central

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Research works printed but not linked: 2

  1. J Lee, , Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment. Nat Genet, in press.
  2. WB Elley, JC Irving, Revised socioeconomic index for New-Zealand. N Z J Educ Stud 11, 25–36 (1976).

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Metadata

Authors
Belsky, D. W., Domingue, B. W., Wedow, R., Arseneault, L., Boardman, J. D., Caspi, A., Conley, D., Fletcher, J. M., Freese, J., Herd, P., Moffitt, T. E., Poulton, R., Sicinski, K., Wertz, J., & Harris, K. M.
Affiliations
  • Duke University (US)
  • Stanford University (US)
  • University of Colorado Boulder (US)
  • King's College London (GB)
  • Princeton University (US)
  • University of Wisconsin–Madison (US)
  • Department of Sociology, Stanford University, Stanford, CA 94305;
  • University of Otago (NZ)
  • University of North Carolina at Chapel Hill (US)
Corresponding author
  • Belsky, Daniel W.
  • Harris, Kathleen Mullan
ORCID
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2018-07-09
Volume
115
Issue
31
Pages
E7275-E7284
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.1801238115
PMC
PMC6077729
OpenAlex
W2848694795
Cited by
315
References
72
Citations by year
2026: 21 · 2025: 26 · 2024: 36 · 2023: 35 · 2022: 42 · 2021: 47 · 2020: 34 · 2019: 65 · 2018: 8
FWCI
87.42
Type
journal article
Language
en
Update notices
correction (2018-11-05)
Open access
Licence
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Research Portal (King's College London) (submittedVersion, cc-by-nc-nd)
Funders
  • Office of Extramural Research, National Institutes of Health (R01HD077482, P01HD31921, R01HD073342, R01HD060726, R01AG032282)
  • UK Medical Research Council (G1002190, MR/P005918/1)
  • Jacobs Foundation (Jacobs Prize, Early Career Fellowship)
  • Russel Sage Foundation (961704)
  • National Science Foundation (DGE1144083)
Topics
  • Social Sciences › Sociology and Political Science › Intergenerational and Educational Inequality Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
Keywords
social mobility, educational attainment, polygenic risk score, upward mobility, socioeconomic attainment, wealth accumulation, parental socioeconomic status, family environment
MeSH terms
Educational Status, Genetic Testing, Humans, Longitudinal Studies, Occupations, Social Class, Social Mobility, Siblings, Genome-Wide Association Study

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