Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world

Abstract

This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations, and expected payoff. Using substance use and abuse as our driving example, we then turn to the importance of etiological psychological theory in guiding genetic, environmental, and developmental research, as well as the utility of refined phenotypic measures, such as endophenotypes, in the pursuit of etiological understanding and focused tests of genetic and environmental associations. Phenotypic measurement has received considerable attention and is informed by psychometrics, while the environment remains relatively poorly measured and is often confounded with genetic effects (i.e., gene-environment correlation). Genetically-informed designs which—thanks to ever cheaper genotyping—are no longer are limited to twin and adoption studies, are required to understand environmental influences. Finally, we outline the vast amount of individual differences in structural genomic variation, most of which remains to be leveraged in genetic association tests. While the genetic data can be burdensomely massive (tens of millions of variants per person), we argue that improved understanding of genomic structure and function will provide investigators with new tools to test specific a priori hypotheses derived from etiological psychological theory, much like current candidate gene research, but with less confusion and more payoff than candidate gene research has to date.

Assessing the utility of intermediate phenotypes for genetic mapping of psychiatric disease

“…[88] : "An endophenotype is a heritable, biologically based, objectively quantifiable measure that is associated with a psychiatric phenotype because both share a common genetic influence. Endophenotypes hold promise for gene finding because they are believed to (a) be more proximal to the effects of genes; (b) tap one of many facets of a disorder and thus be more etiologically homogeneous than the associated disorder; (c) be more highly heritable than the disorder, thus likely to produce larger effect sizes and boost GWAS power; or, (d) because the endophenotype deals with an etiologically homogenous facet of the disorder, be associated with fewer genes each of which may be expected to have larger individual effect sizes.…”

Examining gene–environment interactions in comorbid depressive and disruptive behavior disorders using a Bayesian approach

“…However, the simulated interaction effect was above zero less than 80% of the time, a level comparable to what we observed in our results, indicating power may have affected the ability to detect interactive effects. This is not surprising given the general difficulty in detecting interaction effects in psychological research due to limited sample sizes, small effect sizes, and measurement factors (Vrieze et al, 2012). Interaction effects for CRHNA5 and FKBP5 were sampled above zero at rates similar to the simulation study.…”

“…This approach, combined with an optimized genetic selection strategy (Vrieze, Iacono, & McGue, 2012), revealed genetic variants involved in stress regulation ( FKBP5 , SERT x OPMR ), social bonding ( OXTR ), and nicotine responsivity ( CHRNA5 ) in predicting comorbid status.…”

“…A decade after the 2003 study, experts disagree about the nature of these interactions, and meta-analyses efforts to summarize findings support very different conclusions (Caspi, Hariri, Holmes, Uher, & Moffitt, 2010; Caspi et al, 2003; Karg K, 2011; Risch et al, 2009). The state of the literature has prompted researchers to evaluate the limitations of existing GxE research findings and methods and to recommend new strategies for selecting genetic variants (Vrieze et al, 2012). A recommended strategy that may optimize analysis for GxE interactions capitalizes on both genome wide association studies (GWAS) and candidate gene approaches by filtering the set of single nucleotide polymorphisms (SNPs) that have indicated promise in past empirical work (Vrieze et al, 2012).…”

“…The state of the literature has prompted researchers to evaluate the limitations of existing GxE research findings and methods and to recommend new strategies for selecting genetic variants (Vrieze et al, 2012). A recommended strategy that may optimize analysis for GxE interactions capitalizes on both genome wide association studies (GWAS) and candidate gene approaches by filtering the set of single nucleotide polymorphisms (SNPs) that have indicated promise in past empirical work (Vrieze et al, 2012). Using genetic variants that have been identified in the literature, rather than those based on hypothesized biological mechanisms, may open additional avenues of exploration unconstrained by knowledge of the putative mechanism of action.…”