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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.

SUBMITTER: Gibb BE

PROVIDER: S-EPMC3509244 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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

Gibb Brandon E BE Beevers Christopher G CG McGeary John E JE

Cognition & emotion 20120824 2

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 ...[more]

PMID: 22920216

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Project description:PURPOSE:To evaluate the performance of a cognitive and emotional test battery in a representative sample of depressed outpatients to inform likelihood of remission over 8 weeks of treatment with each of three common antidepressant medications. PATIENTS AND METHODS:Outpatients 18-65 years old with nonpsychotic major depressive disorder (17 sites) were randomized to escitalopram, sertraline or venlafaxine-XR (extended release). Participants scored ?12 on the baseline 16-item Quick Inventory of Depressive Symptomatology - Self-Report and completed 8 weeks of treatment. The baseline test battery measured cognitive and emotional status. Exploratory multivariate logistic regression models predicting remission (16-item Quick Inventory of Depressive Symptomatology - Self-Report score ?5 at 8 weeks) were developed independently for each medication in subgroups stratified by age, sex, or cognitive and emotional test performance. The model with the highest cross-validated accuracy determined the participant proportion in each arm for whom remission could be predicted with an accuracy ?10% above chance. The proportion for whom a prediction could be made with very high certainty (positive predictive value and negative predictive value exceeding 80%) was calculated by incrementally increasing test battery thresholds to predict remission/non-remission. RESULTS:The test battery, individually developed for each medication, improved identification of remitting and non-remitting participants by ?10% beyond chance for 243 of 467 participants. The overall remission rates were escitalopram: 40.8%, sertraline: 30.3%, and venlafaxine-XR: 31.1%. Within this subset for whom prediction exceeded chance, test battery thresholds established a negative predictive value of ?80%, which identified 40.9% of participants not remitting on escitalopram, 77.1% of participants not remitting on sertraline, and 38.7% of participants not remitting on venlafaxine-XR (all including 20% false negatives). CONCLUSION:The test battery identified about 50% of each medication group as being ?10% more or less likely to remit than by chance, and identified about 38% of individuals who did not remit with ?80% certainty. Clinicians might choose to avoid this specific medication in these particular patients.

Dataset Information

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

Publications

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

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