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Interactions between polygenic scores and environments: Methodological and conceptual challenges

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

    (University of Texas at Austin)

Abstract

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 cohort 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 finally offer 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.

Suggested Citation

  • Domingue, Benjamin & Trejo, Sam & Armstrong-Carter, Emma & Tucker-Drob, Elliot M., 2020. "Interactions between polygenic scores and environments: Methodological and conceptual challenges," SocArXiv u7sh4, Center for Open Science.
    • Handle: RePEc:osf:socarx:u7sh4
    DOI: 10.31219/osf.io/u7sh4
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    Cited by:

    1. von Stumm, Sophie & Nancarrow, Allie F., 2024. "New methods, persistent issues, and one solution: Gene-environment interaction studies of childhood cognitive development," Intelligence, Elsevier, vol. 105(C).
    2. Samuel Baker & Pietro Biroli & Hans van Kippersluis & Stephanie von Hinke, 2022. "Beyond Barker: Infant Mortality at Birth and Ischaemic Heart Disease in Older Age," Working Papers 2022-015, Human Capital and Economic Opportunity Working Group.
    3. Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Cornelius Rietveld & Kevin Thom, 2022. "The Economics and Econometrics of Gene-Environment Interplay," Tinbergen Institute Discussion Papers 22-019/V, Tinbergen Institute.
    4. Trejo, Sam, 2020. "Exploring Genetic Influences on Birth Weight," SocArXiv 7j59q_v1, Center for Open Science.
    5. Gueltzow, Maria & Lahtinen, Hannu & Bijlsma, Maarten J. & Myrskylä, Mikko & Martikainen, Pekka, 2024. "Genetic propensity to depression and the role of partnership status," Social Science & Medicine, Elsevier, vol. 351(C).
    6. Das, Aniruddha, 2021. "The relational genomics of cognitive function: A longitudinal study," Social Science & Medicine, Elsevier, vol. 270(C).
    7. Pereira, Rita & Biroli, Pietro & von hinke, stephanie & Van Kippersluis, Hans & Galama, Titus & Rietveld, Niels & Thom, Kevin, 2022. "Gene-Environment Interplay in the Social Sciences," OSF Preprints d96z3_v1, Center for Open Science.
    8. Rita Dias Pereira & Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Cornelius A. Rietveld & Kevin Thom, 2022. "Gene-Environment Interplay in the Social Sciences," Papers 2203.02198, arXiv.org, revised Aug 2022.
    9. Trejo, Sam, 2020. "Exploring Genetic Influences on Birth Weight," SocArXiv 7j59q, Center for Open Science.

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