Toward an integration of cognitive and genetic models of risk for depression

Abstract

There is growing interest in integrating cognitive and genetic models of depression risk. We review two ways in which these models can be meaningfully integrated. First, information-processing biases may represent intermediate phenotypes for specific genetic influences. These genetic influences may represent main effects on specific cognitive processes or may moderate the impact of environmental influences on information-processing biases. Second, cognitive and genetic influences may combine to increase reactivity to environmental stressors, increasing risk for depression in a gene × cognition × environment model of risk. There is now growing support for both of these ways of integrating cognitive and genetic models of depression risk. Specifically, there is support for genetic influences on information-processing biases, particularly the link between 5-HTTLPR and attentional biases, from both genetic association and gene × environment (G × E) studies. There is also initial support for gene × cognition × environment models of risk in which specific genetic influences contribute to increased reactivity to environmental influences. We review this research and discuss important areas of future research, particularly the need for larger samples that allow for a broader examination of genetic and epigenetic influences as well as the combined influence of variability across a number of genes.

Sensitivity in detecting facial displays of emotion: Impact of maternal depression and oxytocin receptor genotype

“…As previously discussed, not all children of depressed mothers develop depression themselves and not all should be expected to exhibit information-processing biases. Therefore, researchers have highlighted the importance of identifying specific genetic influences on information-processing biases (e.g., Gibb, Beevers, & McGeary, 2013), which may help to identify which children of depressed mothers are at greatest risk for developing information processing biases (cf. Gibb et al, 2009, 2011).…”

Why are anxiety and depressive symptoms comorbid in youth? A multi-wave, longitudinal examination of competing etiological models

“…While reliable and valid measures were used, a multi-method approach is a logical next step when investigating these questions. For instance, computer-based tasks have been shown to provide objective information concerning cognitive vulnerability (Beevers, 2005; Gibb, Beevers, & McGeary, 2013), and semi-structured interviews may provide better insight into the nature of stressors (Rudolph, Hammen, Burge, Lindberg, Herzberg, & Daley, 2000), depressive symptoms (Ingram & Siegle, 2002), and anxiety symptoms (Velting, Setzer, & Albano, 2004). Second, the present study utilized a community sample to make inferences on comorbid clinical conditions.…”

Association between serotonin Cumulative Genetic Score and the Behavioral Approach System (BAS): Moderation by early life environment

“…Another possibility is that CGS accounts for aspects of genetic background, whereas a single polymorphism cannot. The associations of a single candidate polymorphism may be obscured when there are multiple other variants contributing to a phenotype, but modeling them concurrently might allow a stronger and more reliable estimate of genetic influence (Gibb, Beevers & McGeary, 2012). …”