Confirmatory and competitive evaluation of alternative gene-environment interaction hypotheses

Authors

  • Jay Belsky,

    Corresponding author
    1. Department of Human Ecology, University of California, Davis, CA, USA
    2. Department of Special Education, King Abdulaziz University, Jedda, Saudi, Arabia, USA
    3. Department of Psychological Sciences, Birkbeck University of London, London, UK
    • Jay Belsky, Department of Human Ecology, Program in Human Development and Family Studies, University of California, Davis, Davis, CA 95616, USA; Email: jbelsky@ucdavis.edu

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  • Michael Pluess,

    1. Institute of Psychiatry, Kings College, London, UK
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  • Keith F. Widaman

    1. Department of Psychology, University of California, Davis, CA, USA
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  • Conflict of interest statement: The authors have declared that they have no competing or potential conflicts of interest.

Abstract

Background

Most gene-environment interaction (GXE) research, though based on clear, vulnerability-oriented hypotheses, is carried out using exploratory rather than hypothesis-informed statistical tests, limiting power and making formal evaluation of competing GXE propositions difficult.

Method

We present and illustrate a new regression technique which affords direct testing of theory-derived predictions, as well as competitive evaluation of alternative diathesis-stress and differential-susceptibility propositions, using data on the moderating effect of DRD4 with regard to the effect of childcare quality on children's social functioning.

Results

Results show that (a) the new approach detects interactions that the traditional one does not; (b) the discerned GXE fit the differential-susceptibility model better than the diathesis-stress one; and (c) a strong rather than weak version of differential susceptibility is empirically supported.

Conclusion

The new method better fits the theoretical ‘glove’ to the empirical ‘hand,’ raising the prospect that some failures to replicate GXE results may derive from standard statistical approaches being less than ideal.

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