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Interpreting Behavior Genetic Models: Seven Developmental Processes to Understand

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Abstract

Behavior genetic findings figure in debates ranging from urgent public policy matters to perennial questions about the nature of human agency. Despite a common set of methodological tools, behavior genetic studies approach scientific questions with potentially divergent goals. Some studies may be interested in identifying a complete model of how individual differences come to be (e.g., identifying causal pathways among genotypes, environments, and phenotypes across development). Other studies place primary importance on developing models with predictive utility, in which case understanding of underlying causal processes is not necessarily required. Although certainly not mutually exclusive, these two goals often represent tradeoffs in terms of costs and benefits associated with various methodological approaches. In particular, given that most empirical behavior genetic research assumes that variance can be neatly decomposed into independent genetic and environmental components, violations of model assumptions have different consequences for interpretation, depending on the particular goals. Developmental behavior genetic theories postulate complex transactions between genetic variation and environmental experiences over time, meaning assumptions are routinely violated. Here, we consider two primary questions: (1) How might the simultaneous operation of several mechanisms of gene–environment (GE)-interplay affect behavioral genetic model estimates? (2) At what level of GE-interplay does the ‘gloomy prospect’ of unsystematic and non-replicable genetic associations with a phenotype become an unavoidable certainty?

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Notes

  1. Other aims that have been claimed as constitutive of scientific inquiry include having true answers to our questions (Kelly and Glymour 2004), obtaining knowledge (Nagel 1967), advancing empirically adequate theories (van Fraassen 1980, 1986), having understanding (de Regt 2015), and gaining the ability to control nature (Keller 1985). We invite the reader to think about how what we say in this paper matters with respect to these other aims as well, though we will not discuss them explicitly.

  2. Modern behavior genetic models typically rely on structural equation modeling approaches, rather than simple multiplication and subtraction.

  3. In this manuscript, we focus on quantitative G × E, meaning the effect sizes of genes and environments are interdependent, rather than qualitative G × E, meaning different genes may operate across groups.

  4. Caspi et al. (2014) report longitudinal data on the psychometric structure of psychopathology across ages 18–38 years with approximately five waves for 11 disorders. Supplemental Table 1 reports means and standard deviations for each wave. When mean levels of psychopathology increase from one wave to the next, variance in psychopathology also increases (r = 0.78).

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Acknowledgements

The production of this manuscript was supported by a Grant from the John Templeton Foundation (JTF58792).

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Authors and Affiliations

  1. Department of Psychology, University of Illinois at Urbana-Champaign, 603 East Daniel Street, Champaign, IL, 61820, USA

    Daniel A. Briley, Jaime Derringer, R. Chris Fraley & Brent W. Roberts

  2. Department of Philosophy, University of Illinois at Urbana-Champaign, Champaign, IL, USA

    Jonathan Livengood

  3. Department of Psychology and Population Research Center, University of Texas at Austin, Austin, TX, USA

    Elliot M. Tucker-Drob

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  1. Daniel A. Briley
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Daniel A. Briley, Jonathan Livengood, Jaime Derringer, Elliot M. Tucker-Drob, R. Chris Fraley, and Brent W. Roberts declare that they have no conflict of interest.

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Briley, D.A., Livengood, J., Derringer, J. et al. Interpreting Behavior Genetic Models: Seven Developmental Processes to Understand. Behav Genet 49, 196–210 (2019). https://doi.org/10.1007/s10519-018-9939-6

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  • DOI: https://doi.org/10.1007/s10519-018-9939-6

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