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Educational Tracking and the Polygenic Prediction of Education

By on March 18, 2024 in Articles

Hannu Lahtinen, Pekka Martikainen, Kaarina Korhonen, Tim Morris, Mikko Myrskylä

Sociological Science March 18, 2024
10.15195/v11.a8

Abstract

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Educational systems that separate students into curriculum tracks later may place less emphasis on socioeconomic family background and allow individuals’ personal skills and interests more time to manifest. We tested whether postponing tracking from age 11 to 16 results in stronger genetic prediction of education across a population, exploiting the natural experiment of the Finnish comprehensive school reform between 1972 and 1977. The association between polygenic score of education and achieved education strengthened after the reform by one-third among men and those from low-educated families. We observed no evidence for reform effect among women or those from high-educated families. The first cohort experiencing the new system had the strongest increases. From the perspective of genetic prediction, the school reform promoted equality of opportunity and optimal allocation of human capital. The results also suggest that turbulent circumstances, including puberty or ongoing restructuring of institutional practices, may strengthen genetic associations in education.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Hannu Lahtinen: Population Research Unit, University of Helsinki; Max Planck – University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
E-mail: hannu.lahtinen@helsinki.fi

Pekka Martikainen: Population Research Unit, University of Helsinki; Max Planck Institute for Demographic Research, Rostock, Germany; Max Planck – University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
E-mail: pekka.martikainen@helsinki.fi

Kaarina Korhonen: Population Research Unit, University of Helsinki; Max Planck – University of Helsinki Center for Social Inequalities in Population Health, Helsinki, Finland
E-mail: kaarina.korhonen@helsinki.fi

Tim Morris: Centre for Longitudinal Studies, Social Research Institute, University College London
E-mail: t.t.morris@ucl.ac.uk

Mikko Myrskylä: Max Planck Institute for Demographic Research, Rostock, Germany; University of Helsinki, Helsinki, Finland; Max Planck – University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland
E-mail: myrskyla@demogr.mpg.de

Acknowledgements: Special thanks for Aysu Okbay for providing education GWAS summary results excluding overlapping samples. We also thank the Finnish National Agency for Education for providing municipal-specific school-reform implementation years. The genetic samples used for the research were obtained from the THL Biobank (study number: THLBB2020_8), and we thank all study participants for their generous participation in the THL Biobank.

Supplemental Material

Replication Package: Instructions for data access and code to reproduce the analysis can be found at https://github.com/halahti/SocSci23

  • Citation: Lahtinen, Hannu, Pekka Martikainen, Kaarina Korhonen, Tim Morris, and Mikko Myrskylä. 2024. “Educational tracking and the polygenic prediction of education.” Sociological Science 11: 186-213.
  • Received: September 19, 2023
  • Accepted: October 31, 2023
  • Editors: Arnout van de Rijt, Nan Dirk de Graaf
  • DOI: 10.15195/v11.a8


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Interactions between Polygenic Scores and Environments: Methodological and Conceptual Challenges

By on September 21, 2020 in Articles

Benjamin W. Domingue, Sam Trejo, Emma Armstrong-Carter, Elliot M. Tucker-Drob

Sociological Science September 21, 2020
10.15195/v7.a19

Abstract
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Interest in the study of gene–environment interaction has recently grown due to the sudden availability of molecular genetic data—in particular, polygenic scores—in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key challenges, provide new perspectives on the study of gene–environment interactions, and end by offering some practical guidance for conducting research in this area. Given the sudden availability of well-powered polygenic scores, we anticipate a substantial increase in research testing for interaction between such scores and environments. The issues we discuss, if not properly addressed, may impact the enduring scientific value of gene–environment interaction studies.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Benjamin W. Domingue: Graduate School of Education, Stanford University
E-mail: bdomingu@stanford.edu

Sam Trejo: La Follette School of Public Affairs & Department of Sociology, University of Wisconsin–Madison
E-mail: sam.trejo@wisc.edu

Emma Armstrong-Carter: Graduate School of Education, Stanford University
E-mail: emmaac@stanford.edu

Elliot M. Tucker-Drob: Department of Psychology and Population Research Center, University of Texas at Austin
E-mail: tuckerdrob@utexas.edu

Acknowledgments: This work has been supported by the Russell Sage Foundation and the Ford Foundation (grant 96-17-04). S.T. was supported by the National Science Foundation (grant DGE-1656518) and the Institute of Education Sciences (grant R305B140009). E.M.T.-D. was supported by the National Institutes of Health (grants R01AG054628, R01MH120219, and R01HD083613) and by the Jacobs Foundation. Any opinions expressed are those of the authors alone and should not be construed as representing the opinions of any foundation. The authors would like to thank Jason Boardman and Jason Fletcher for comments on an early draft of this article.

  • Citation: Domingue, Benjamin W., Sam Trejo, Emma Armstrong-Carter, and Elliot M. Tucker-Drob. 2020. “Interactions between Polygenic Scores and Environments: Methodological and Conceptual Challenges.” Sociological Science 7: 465-486.
  • Received: June 5, 2020
  • Accepted: August 24, 2020
  • Editors: Olav Sorenson
  • DOI: 10.15195/v7.a19


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Schools as Moderators of Genetic Associations with Life Course Attainments: Evidence from the WLS and Add Health

By on August 2, 2018 in Articles

Sam Trejo, Daniel W Belsky, Jason D. Boardman, Jeremy Freese, Kathleen Mullan Harris, Pam Herd, Kamil Sicinski, Benjamin W. Domingue

Sociological Science, August 2, 2018
10.15195/v5.a22

Abstract
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Genetic variants identified in genome-wide association studies of educational attainment have been linked with a range of positive life course development outcomes. However, it remains unclear whether school environments may moderate these genetic associations. We analyze data from two biosocial surveys that contain both genetic data and follow students from secondary school through mid- to late life. We test if the magnitudes of the associations with educational and occupational attainments varied across the secondary schools that participants attended or with characteristics of those schools. Although we find little evidence that genetic associations with educational and occupational attainment varied across schools or with school characteristics, genetic associations with any postsecondary education and college completion were moderated by school-level socioeconomic status. Along similar lines, we observe substantial between-school variation in the average level of educational attainment students achieved for a fixed genotype. These findings emphasize the importance of social context in the interpretation of genetic associations. Specifically, our results suggest that though existing measures of individual genetic endowment have a linear relationship with years of schooling that is relatively consistent across school environments, school context is crucial in connecting an individual’s genotype to his or her likelihood of crossing meaningful educational thresholds.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Sam Trejo: Graduate School of Education, Stanford University
E-mail: samtrejo@stanford.edu.

Daniel W. Belsky: Duke University School of Medicine and Social Science Research Institute
E-mail: dbelsky@duke.edu

Jason D. Boardman: Institute of Behavioral Science and Sociology Department, University of Colorado Boulder
E-mail: boardman@colorado.edu

Jeremy Freese: Department of Sociology, Stanford University
E-mail: jfreese@stanford.edu

Kathleen Mullan Harris: Department of Sociology and Carolina Population Center, University of North Carolina at Chapel Hill
E-mail: kathie_harris@unc.edu

Pam Herd: Department of Sociology and La Folette School of Public Affairs, University of Wisconsin–Madison
E-mail: pherd@lafollette.wisc.edu

Kamil Sicinski: Center for Demography of Health and Aging, University of Wisconsin–Madison.
E-mail: ksicinsk@ssc.wisc.edu

Benjamin W. Domingue: Graduate School of Education, Stanford University
E-mail: bdomingue@stanford.edu

Acknowledgements: This work has been supported (in part) by award 96-17-04 from the Russell Sage Foundation and the Ford Foundation, the National Science Foundation Graduate Research Fellowship Program under grant DGE-1656518 (Trejo), the Institute of Education Sciences under grant R305B140009 (Trejo), and a Jacobs Foundation Early Career Research Fellowship (Belsky). This research uses Add Health GWAS data funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development grant R01 HD073342 to Kathleen Mullan Harris and the Eunice Kennedy Shriver National Institute of Child Health and Human Development and National Institutes of Health grant R01 HD060726 to Harris, Boardman, and McQueen. Add Health is a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill; it is funded by grant P01 HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development with cooperative funding from 23 other federal agencies and foundations. The Wisconsin Longitudinal Study is directed by Pamela Herd, and the work conducted herein was supported by the National Institute on Aging (R01 AG041868-01A1 and P30 AG017266). This research benefitted from GWAS results made available by the Social Science Genetic Association Consortium. Any opinions expressed are those of the author(s) alone and should not be construed as representing the opinions of each foundation.

Supplemental Material

  • Citation: Trejo, Sam, Daniel W. Belsky, Jason D. Boardman, Jeremy Freese, Kathleen Mullan Harris, Pam Herd, Kamil Sicinski, and Benjamin W. Domingue. 2018. “Schools as Moderators of Genetic Associations with Life Course Attainments: Evidence from the WLS and Add Health.” Sociological Science 5: 513-540.
  • Received: March 20, 2018
  • Accepted: April 16, 2018
  • Editors: Kim Weeden
  • DOI: 10.15195/v5.a22


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