In a sense, all genetics research can be viewed as G×E research because genetic effects are necessarily expressed in some environmental context (and vice versa). However, this is not a useful frame of reference because a complete understanding of the etiology of psychiatric phenotypes requires elucidation of causes that are ultimately genetic or environmental or interactive in nature. An important albeit underappreciated limitation of traditional heritability studies (i.e., twin studies) is that they are not able to estimate G×E effects. The potential consequences are serious because the existence of G×E will bias parameter estimates for genetic and environmental effects, as described in more detail below.

Regarding methodology, both molecular G×E and quantitative G×E studies are possible. The term “quantitative genetic” distinguishes studies of latent variables (e.g., A-C-E models using twins) from molecular genetic studies in which participants’ genotypes are measured. Quantitative genetic studies are also referred to as “behavioral genetic” studies, and we use the term “modified heritability” studies to make it clear to readers that such studies are (1) more similar to heritability (traditional twin) studies than they are to molecular genetic studies and (2) distinct from typical heritability studies, which cannot estimate G×E. In general, quantitative G×E studies are more suited to determining the relative magnitude of genetic, environmental, and G×E contributions to phenotypes, whereas molecular G×E studies can identify specific genetic and environmental risk factors. Finally, the study of G×Es has emerged out of both the genetic and environmental traditions of research.

Visual depiction of G×Es, in line or bar graphs, helps to explain the concept of G×E. As demonstrated in Fig. 9.1, phenotype is always depicted on the y-axis. In this example, the phenotype is depression. Either the genetic variable or the environmental variable can be depicted on the x-axis. Here, the environmental variable (maltreatment) is depicted on the x-axis. Genotype is represented as lines G1, G2, and G3, corresponding to minor allele homozygote, heterozygote, and major allele homozygote genotypes. The existence of an interaction is indicated by the fact that the lines are not parallel. The presence of an environmental main effect is indicated by the fact that the trend lines for all genotypes have positive slopes (thus the overall effect of environment has a consistent direction). However, the slope of lines is different for each genotype, indicating that the effect of the environment depends on genotype, which is the definition of an interaction. It is also necessarily the case that the inverse is true: the effect of genotype depends on the environment. The form of an interaction—which can be observed in a graph—can be important conceptually and statistically, as discussed later—so we describe possible forms of interactions here. In addition to the G×E in Fig. 9.1, which is referred to as a “crossover interaction” because the lines in the graph cross, there are also “spreading,” “diathesis–stress,” “other,” and “pure crossover” forms of interactions, as depicted in cells A1, B1, C1, and D1, respectively, in Fig. 9.2. This terminology can be confusing, however, as illustrated by comparing the interactions in the left column with those in the right column. For each row in Fig. 9.2, a single interaction is depicted, but the form of the interaction can appear different depending on the arbitrary choice of which variable—genotype or environment—is placed on the x-axis. The form of interactions A1, B1, and C1 is different from their counterparts: A2, B2, and C2. In contrast, the form of a pure crossover interaction will be the same irrespective of which variable (genetic or environmental) is placed on the x-axis, as illustrated in D1/D2 (though the angle and location at which lines cross depends on the specific interaction). Figure 9.2 illustrates the fact that precise descriptions of interaction are necessary to accurately convey the nature of G×E effects. For example, it is critical to know if risk and protective environments reverse depending on genotype (e.g., A1/A2 and D1/D2) and if risk genotype depends on environment (e.g., D1/D2).

Figure 9.2 also illustrates that not all interactions are created equal, so true replications of reported findings require interactions of the same form, as opposed to the mere presence of an interaction. This is the same as requiring that the direction of effect be constant in main effect studies, because results are certainly not replicated if effects are opposite to those originally reported. Though it is beyond the scope of this chapter, additional complexity exists regarding the form of interactions. Importantly, properties of scale used to quantify variables can also influence the form of interactions and have been extensively discussed (Aiken, West, & Reno, 1991; Eaves, 2006).

As pointed out by Moffit et al. (2006), it important to clarify what G×E is not. It is not merely the combined effects of genetic and environmental effects. G×E is also distinct from gene–environment correlation (rGE), a phenomenon discussed later in this section. Finally, G×E is not epigenetics. Though the definition of epigenetics is evolving (Bird, 2007), there is widespread agreement that it pertains to DNA modifications that do not alter DNA sequence. Oftentimes these modifications (1) alter gene expression and (2) are brought about by environmental influences, and herein lies the confusion that has led some to conclude that epigenetics is a plausible “mechanism” for G×E (Bagot & Meaney, 2010; Meaney, 2010) when in fact it is much more closely aligned with environmental effects (Dick, 2011). The critical distinction between a phenomenon caused by both genes and the environment (and shared biological mechanisms underpinning the two) and G×E is that G×E implies variation in response to the environment due to variation in genotypes. Processes mistakenly described as G×E in the literature often fail to recognize this distinction. The bottom line is that G×E is not merely the combination of genetic and environmental effects but rather the existence of a dependency of genetic effect on the environment, and vice versa.

G×E research is best understood via comparison with genetics research, which has been driven primarily by two factors: (1) genotyping technology and (2) theory. Before molecular genetic data (i.e., genotypes) were available, collective genetic effects were estimated in “heritability studies.” These were typically twin studies in which phenotypic correlations between monozygotic twins were compared to phenotypic correlations between dizygotic twins (Plomin, DeFries, & McClearn, 1990) (see Fig. 9.3) in order to yield estimates of genetic and environmental contributions to phenotypic variance. Heritability studies established that collective genetic influences are ubiquitous in behavioral and psychiatric phenotypes (Plomin et al., 1990).

Gene-environment correlation (rGE) means exactly that: a correlation between genetic and environmental variables. Typically cited mechanisms for the development of rGE invoke the effect of genotype (Plomin et al., 1977), but it is also possible that rGE could result from the environment, particularly over a longer time scale and through the course of evolution. For example, skin pigmentation (which is partially genetically determined) varies based on latitude (an environmental variable) thus inducing a correlation between certain environments and certain alleles in human populations.

Regarding classification, there are three commonly described types of rGE: “passive,” “reactive,” and “active” (Plomin et al., 1977). Plomin makes the point that these terms are not mutually exclusive and that any combination of rGE effects may occur in a given example. Passive rGE occurs when children are given certain genotypes, which are linked to certain environments. For example, athletic parents may provide both alleles and environments that are conducive to athletic performance (e.g., playing catch, encouraging participation in sports). Reactive rGE occurs when children’s genotypes bring about certain environments. For example, coaches may recognize children’s (genetically influenced) athletic abilities and provide situations conducive to further athletic development (e.g., more playing time, offers to be on competitive teams). Finally, active rGE involves children’s own seeking of environments, based on their genotypes. For example, athletic children may be more inclined to practice sports and may try out for sports teams more often. All of these examples involve genetic and environmental effects that act in the same direction (here, to increase athletic performance), but this is not a requirement for rGE. Rather, all that is necessary for rGE to exist is a systematic relationship between genetic and environmental variables, the effects of which can act in the same or opposite direction.

A major question facing researchers pertains to the form of G×Es that affect psychiatric phenotypes. Are G×Es crossover in form? Are they non-crossover? Do all forms exist? Currently no one knows the answer to these questions, but there are both empirical and conceptual clues as to what we might expect. In plant species and nonhuman animals, interactions are well documented and common. Importantly, this includes crossover interactions, which are commonly found in experimental settings and nature if a wide distribution of environments is studied (Ceccarelli, 1996). Thus the argument that crossover interactions are “biologically implausible” is simply inconsistent with known biology. In the cG×E literature, all forms of interactions have been reported, including many crossover interactions. However (as described below) such interactions have yet to be conclusively validated in replication studies and meta-analyses, so observed evidence from the cG×E literature should not be treated as fact. Nevertheless, this empirical evidence from humans, animals, and plants suggests that we are likely to observe all forms of interactions impacting psychiatric phenotypes.

Conceptually, there are arguments in favor of both crossover and non-crossover interactions. Regarding non-crossover interactions, it stands to reason that these almost certainly exist if one considers “reaction to the environment” phenotypes. For example, anxiety in response to a stressor would be an example of a “reaction to the environment” phenotype as would sadness in response to the loss of a relationship. Both of these examples could conceivably contribute to risk of depression. If such “reaction to the environment” phenotypes are influenced by genes, then G×Es necessarily exist because this implies that genes influence one’s reaction to the environment. As genetic influences on behavior are ubiquitous, it stands to reason that “reaction to the environment” phenotypes would also be influenced by genes, and consequently we can infer the existence of non-crossover G×Es (e.g., some people will experience more sadness in response to the loss of a relationship than others and some people will be more anxious in response to stressors than others).

In contrast, some have questioned the likelihood of certain crossover interactions. They wonder if it could ever be the case that the loss of a relationship would decrease depression (in individuals with certain genotypes). Likewise, they question whether childhood maltreatment could ever be expected to bring about positive impacts on psychiatric health—such positive effects are a necessary consequence of pure crossover interactions. Extreme examples such as these seem to defy common sense and they may not exist. However, as some have proposed, there may be genetic differences in susceptibility to environmental influences (the so-called dandelion-orchid or differential susceptibility hypothesis) (Bakermans-Kranenburg & van IJzendoorn, 2006). The “differential susceptibility” hypothesis differentiates itself from the diathesis–stress hypothesis by stating that some individuals will be more susceptible to both positive and negative influences, whereas other individuals will be relatively impervious to the impacts of the environment. In contrast, the diathesis–stress hypothesis may be rigidly construed as only pertaining to negative influences.

Finally, evolutionary considerations are relevant for both the form and the magnitude of interactions. Simply put, any genotype that leads to a net negative impact on fitness (successful reproduction of an organism) will be removed from the gene pool over time by the forces of natural selection. Moreover, there is a well-established inverse relationship between the magnitude (effect size, essentially) of the negative effect of an allele and the length of time that it will remain in the gene pool: more deleterious alleles will be removed more quickly. Thus, the expectation is that alleles with negative effects will tend to have small effect sizes. Notably, this prediction is overwhelmingly consistent with what has been observed across all of human genetics: alleles for traits related to fitness tend to have tiny effect sizes (e.g., odds ratios <1.2). As it pertains to G×Es, evolutionary theory suggests that effect sizes for interactions involving a net negative effect of a particular allele (as in diathesis–stress interactions) will be tiny. However, this by no means precludes the possibility of diathesis–stress interactions (just as it does not preclude the existence of genetic effects); it merely suggests that effect sizes for individual diathesis–stress interactions will be tiny.

In contrast, pure crossover interactions offer the possibility of G×Es with large effect sizes with no net negative effect of any particular allele. Thus, large crossover G×Es are consistent with evolutionary theory and offer hope that single loci may make substantial contributions to psychiatric phenotypes. This exciting possibility is important and substantiates claims that the search for G×Es is important, but it should also be tempered by knowledge that this mechanism may be unlikely (Keller & Miller, 2006). In sum, the range and distribution of forms of G×Es impacting psychiatric phenotypes is not known, yet we can be relatively confident that large diathesis–stress G×Es will not be identified (because they would also have large genetic effects and evolutionary forces would remove such alleles from the gene pool). It remains to be seen whether crossover interactions with large effect sizes will be identified.