Modeling Core Behavioral, Neuroendocrine and Molecular Features of Depression

University Of Pittsburgh At Pittsburgh, Pittsburgh PA

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Abstract

DESCRIPTION (provided by applicant): Although depression is a leading cause of disability worldwide and clinically-effective antidepressants were discovered over 50 years ago, the cellular and molecular pathology of depression remains mostly uncharacterized. As a result, very few new drug classes have emerged and a large proportion of depressed subjects do not get adequate relief. Yet, this is surprising since altered mood regulation, the core feature of depression, is subserved by identified neural networks including the amygdala, is precipitated by environmental factors such as chronic stress, includes neuroendocrine dysfunctions, and is modulated by known risk factors (female sex, altered serotonin transporter [SERT] and prior depressive episodes). Thus, to develop a plausible animal model that recapitulates these known features of the illness would be invaluable in facilitating the identification of relevant biological and molecular disturbances in depression. Unpredictable chronic mild stress (UCMS) in rodents mimics in a naturalistic way both the role of psycho- social stress in eliciting emotion-related behavioral changes that are reminiscent of symptoms of depression, and the timeframe of therapeutic response to antidepressant treatment. We now show that UCMS in mice also recapitulates the increased vulnerability to altered mood states associated with female sex or low SERT, and that UCMS induces changes in gene expression in the amygdala that are phylogenetically conserved with the molecular signature of human depression. Thus, with the long-term goal of investigating causal mechanisms of depression, this proposal will first characterize UCMS as an integrated rodent model of human depression by assessing the contribution of known risk factors (female sex, low SERT and prior depressive episodes) to the behavioral (Aim 1), neuroendocrine (Aim 2) and molecular (Aim 3) correlates of UCMS. Second, this model will be used, in combination with our identified biosignature of depression in the human amygdala, to identify shared downstream biological pathways that may support the pathophysiology of depression. Consistent with NIMH goals, this R21 proposal investigates an integrated rodent model of depression to better understand the contribution of genetic, neurobiological, behavioral and environmental factors to the development and trajectory of mental disorders. Importantly, this proposal also benefits from a research team actively investigating human postmortem pathology. For instance, our identification of a molecular signature of human depression that is conserved in rodent UCMS will allow direct validation of the rodent molecular findings at modeling mechanisms that are relevant to human depression. Specifically, a biological feature that is i) temporally correlated with changes in emotion-related behaviors in mice, ii) modulated by risk factors known to affect vulnerability to depression in humans, and iii) supported by equivalent molecular changes as in human depression, will represent first a robust and valid candidate system for future investigation of mechanisms leading to altered mood states in depression, and, second, a potential new drug target. PUBLIC HEALTH RELEVANCE: This research proposal investigates an integrated rodent model of depression in order to better understand the contribution of genetic, neurobiological, behavioral and environmental factors to the development and trajectory of the human illness. Specifically, we will investigate biological events that are temporally correlated with changes in emotion-related behaviors in mice, modulated by risk factors known to affect vulnerability to depression in humans, and supported by equivalent molecular changes as in human depression. Results from these studies will identify first robust and valid candidate neurobiological brain systems for future investigations of mechanisms leading to depression, and, second, potential new drug targets.