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. 2015 Apr;77(2):344-350.
doi: 10.1111/jomf.12164.

Gene-Environment Interplay: Where We Are, Where We Are Going

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Free PMC article

Gene-Environment Interplay: Where We Are, Where We Are Going

Jessica E Salvatore et al. J Marriage Fam. .
Free PMC article

Abstract

The idea that both genetic and environmental influences contribute to behavioral outcomes is widely accepted. However, the practice of examining candidate Gene × Environment interaction (cGxE) is controversial. In this article, we summarize some of the key issues involved in cGxE research and provide recommendations for work in this area. Highlighted challenges include the selection of the gene, the development of the cGxE hypothesis, and the coding of the genotype. To address these challenges and gain confidence in cGxE findings, we recommend using empirical data to select and code genes/variants, using theory to develop cGxE hypotheses and a rigorous and transparent approach to hypothesis testing. Family researchers have much to offer to the study of Gene × Environment research in view of their process-oriented theories that are grounded in decades of nuanced measurement of the environment; implementing these best practices will help deliver on that promise.

Keywords: developmental psychology; family research; measurement; methods; research methodologies.

Figures

Figure 1
Figure 1
An Illustration of the Difficulty in Determining Whether a Genetic Variant Confers Differential Susceptibility, Using the Hypothetical Example of Internalizing Symptoms as a Function of Interparental Conflict and a Single Nucleotide Polymorphism. Note. In the low-risk sample (far right of the x-axis), the range of interparental conflict is restricted relative to the high-risk sample. Accordingly, in a low-risk sample we observe a fan-shaped interaction effect, which is consistent with a diathesis–stress model of cGxE. In a high-risk sample, where there is potentially a greater range of interparental conflict, we observe a crossover interaction effect, which is consistent with a differential susceptibility model of cGxE.

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