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Research Article

Genetic analysis of social-class mobility in five longitudinal studies

View ORCID ProfileDaniel W. Belsky, View ORCID ProfileBenjamin W. Domingue, View ORCID ProfileRobbee Wedow, Louise Arseneault, Jason D. Boardman, Avshalom Caspi, View ORCID ProfileDalton Conley, View ORCID ProfileJason M. Fletcher, Jeremy Freese, Pamela Herd, Terrie E. Moffitt, Richie Poulton, Kamil Sicinski, Jasmin Wertz, and Kathleen Mullan Harris
  1. aDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC 27710;
  2. bSocial Science Research Institute, Duke University, Durham, NC 27708;
  3. cGraduate School of Education, Stanford University, Stanford, CA 94305;
  4. dInstitute of Behavioral Science and Department of Sociology, University of Colorado, Boulder, CO 80309;
  5. eSocial, Genetic, and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, SE5 8AF London, United Kingdom;
  6. fDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708;
  7. gDepartment of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC 27708;
  8. hCenter for Genomic and Computational Biology, Duke University, Durham, NC 27708;
  9. iDepartment of Sociology, Princeton University, Princeton, NJ 08544;
  10. jLa Follette School of Public Policy, University of Wisconsin–Madison, Madison, WI 53706;
  11. kCenter for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI 53706;
  12. lDepartment of Sociology, Stanford University, Stanford, CA 94305;
  13. mDunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, 9016 Dunedin, New Zealand;
  14. nDepartment of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516;
  15. oCarolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516

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PNAS July 31, 2018 115 (31) E7275-E7284; first published July 9, 2018; https://doi.org/10.1073/pnas.1801238115
Daniel W. Belsky
aDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC 27710;
bSocial Science Research Institute, Duke University, Durham, NC 27708;
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  • ORCID record for Daniel W. Belsky
  • For correspondence: dbelsky@duke.edu kathie_harris@unc.edu
Benjamin W. Domingue
cGraduate School of Education, Stanford University, Stanford, CA 94305;
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  • ORCID record for Benjamin W. Domingue
Robbee Wedow
dInstitute of Behavioral Science and Department of Sociology, University of Colorado, Boulder, CO 80309;
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  • ORCID record for Robbee Wedow
Louise Arseneault
eSocial, Genetic, and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, SE5 8AF London, United Kingdom;
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Jason D. Boardman
dInstitute of Behavioral Science and Department of Sociology, University of Colorado, Boulder, CO 80309;
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Avshalom Caspi
eSocial, Genetic, and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, SE5 8AF London, United Kingdom;
fDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708;
gDepartment of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC 27708;
hCenter for Genomic and Computational Biology, Duke University, Durham, NC 27708;
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Dalton Conley
iDepartment of Sociology, Princeton University, Princeton, NJ 08544;
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  • ORCID record for Dalton Conley
Jason M. Fletcher
jLa Follette School of Public Policy, University of Wisconsin–Madison, Madison, WI 53706;
kCenter for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI 53706;
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Jeremy Freese
lDepartment of Sociology, Stanford University, Stanford, CA 94305;
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Pamela Herd
jLa Follette School of Public Policy, University of Wisconsin–Madison, Madison, WI 53706;
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Terrie E. Moffitt
eSocial, Genetic, and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, SE5 8AF London, United Kingdom;
fDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708;
gDepartment of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC 27708;
hCenter for Genomic and Computational Biology, Duke University, Durham, NC 27708;
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Richie Poulton
mDunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, 9016 Dunedin, New Zealand;
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Kamil Sicinski
kCenter for Demography of Health and Aging, University of Wisconsin–Madison, Madison, WI 53706;
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Jasmin Wertz
fDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27708;
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Kathleen Mullan Harris
nDepartment of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516;
oCarolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516
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  • For correspondence: dbelsky@duke.edu kathie_harris@unc.edu
  1. Contributed by Kathleen Mullan Harris, May 10, 2018 (sent for review January 26, 2018; reviewed by Christopher S. Jencks and Elliot M. Tucker-Drob)

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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.

Abstract

A summary genetic measure, called a “polygenic score,” derived from a genome-wide association study (GWAS) of education can modestly predict a person’s educational and economic success. This prediction could signal a biological mechanism: Education-linked genetics could encode characteristics that help people get ahead in life. Alternatively, prediction could reflect social history: People from well-off families might stay well-off for social reasons, and these families might also look alike genetically. A key test to distinguish biological mechanism from social history is if people with higher education polygenic scores tend to climb the social ladder beyond their parents’ position. Upward mobility would indicate education-linked genetics encodes characteristics that foster success. We tested if education-linked polygenic scores predicted social mobility in >20,000 individuals in five longitudinal studies in the United States, Britain, and New Zealand. Participants with higher polygenic scores achieved more education and career success and accumulated more wealth. However, they also tended to come from better-off families. In the key test, participants with higher polygenic scores tended to be upwardly mobile compared with their parents. Moreover, in sibling-difference analysis, the sibling with the higher polygenic score was more upwardly mobile. Thus, education GWAS discoveries are not mere correlates of privilege; they influence social mobility within a life. Additional analyses revealed that a mother’s polygenic score predicted her child’s attainment over and above the child’s own polygenic score, suggesting parents’ genetics can also affect their children’s attainment through environmental pathways. Education GWAS discoveries affect socioeconomic attainment through influence on individuals’ family-of-origin environments and their social mobility.

  • genetics
  • social class
  • social mobility
  • sociogenomics
  • polygenic score

Footnotes

  • ↵1D.W.B. and B.W.D. contributed equally to this work.

  • ↵2To whom correspondence may be addressed. Email: dbelsky{at}duke.edu or kathie_harris{at}unc.edu.
  • Author contributions: D.W.B., B.W.D., J.D.B., A.C., D.C., J.M.F., J.F., T.E.M., J.W., and K.M.H. designed research; D.W.B., B.W.D., R.W., L.A., A.C., J.F., P.H., T.E.M., R.P., K.S., and K.M.H. performed research; D.W.B. and B.W.D. analyzed data; and D.W.B., B.W.D., A.C., T.E.M., and K.M.H. wrote the paper.

  • Reviewers: C.S.J., Harvard University; and E.M.T.-D., University of Texas at Austin.

  • The authors declare no conflict of interest.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1801238115/-/DCSupplemental.

  • Copyright © 2018 the Author(s). Published by PNAS.

This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

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Genetic analysis of social-class mobility in five longitudinal studies
Daniel W. Belsky, Benjamin W. Domingue, Robbee Wedow, Louise Arseneault, Jason D. Boardman, Avshalom Caspi, Dalton Conley, Jason M. Fletcher, Jeremy Freese, Pamela Herd, Terrie E. Moffitt, Richie Poulton, Kamil Sicinski, Jasmin Wertz, Kathleen Mullan Harris
Proceedings of the National Academy of Sciences Jul 2018, 115 (31) E7275-E7284; DOI: 10.1073/pnas.1801238115

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Genetic analysis of social-class mobility in five longitudinal studies
Daniel W. Belsky, Benjamin W. Domingue, Robbee Wedow, Louise Arseneault, Jason D. Boardman, Avshalom Caspi, Dalton Conley, Jason M. Fletcher, Jeremy Freese, Pamela Herd, Terrie E. Moffitt, Richie Poulton, Kamil Sicinski, Jasmin Wertz, Kathleen Mullan Harris
Proceedings of the National Academy of Sciences Jul 2018, 115 (31) E7275-E7284; DOI: 10.1073/pnas.1801238115
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