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Chunk #31 — Discussion — Limitations

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Predicting alcohol consumption in adolescence from alcohol-specific and general externalizing genetic risk factors, key environmental exposures and their interaction.
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Fourth, despite its flexibility, our regression model does not allow us to unconfound the effects of gene– environment interaction and gene–environment correlation. We know, for example, that the two exposures that had the most robust evidence for interaction – alcohol availability and peer group deviance – both have heritable components (Gillespie et al. 2007; Kendler et al. 2007). Perhaps the observed interaction with GR-ExtD and GR-AUD in the prediction of alcohol consumption results in part or entirely from genetic correlations between these variables. However, the pattern of our findings argues strongly against such an interpretation. For example, the genetic influences on both alcohol availability and peer deviance are considerably stronger at ages 18–21 than at ages 12–14 (Gillespie et al. 2007; Kendler et al. 2007). If our evidence for gene–environment interaction resulted from genetic effects on these variables, we would expect stronger evidence for interactions at ages 18–21 than at ages 12–14. However, the observed pattern is exactly the opposite.