A key goal of Major Depressive Disorder (MDD) research is to understand how changes in gene expression contribute to the development of disease. While numerous individual transcriptional changes have been identi- fied in both human MDD and animal models of depression, there is a fundamental gap in our understanding of how single gene alterations interact to mediate the disease state. Intriguingly, more transcriptional alterations are observed in the brains of animals that undergo stressful stimuli but do not develop depression-like behav- ior, however, the network-level transcriptional alterations associated with resilience have not been explored. The overall objective of this proposal is to characterize gene networks associated with resilience in the Chronic Social Defeat Stress (CSDS) model of depression in mice. My central hypothesis is that network-level changes in gene expression drive resilience to CSDS, and that manipulation of resilient-specific networks by modulating individual network regulators will modify resilience in animal models of stress. The rationale for this research is that the resilient phenotype in CSDS is associated with many antidepressant-like changes, so elucidation of these alterations in a network context, as well as identification of regulators of these changes, will enhance our understanding of changes in gene expression following stress and identify novel targets for antidepressant therapeutics. My hypothesis will be tested by two Specific Aims.
Aim 1 characterizes the transcriptional net- works associated with resilience to CSDS. In this Aim, I will use bioinformatics to contextualize networks of gene expression that exist across several brain regions in resilient, but not susceptible, mice in terms of both structure and function. Additionally, I will compare these networks to networks from post-mortem MDD patients to determine their disease relevance.
Aim 2 determines whether induction of gene co-expression networks regulates depression-like behavior. In this Aim, I will test the effect of overexpressing or knocking down module regulators in specific brain regions in vivo on depression-like behavior in CSDS and sub-threshold variable stress. Further, I will use RNA expression assays to determine the mechanisms by which regulator genes alter the expression of other genes in their module and therefore affect behavior. To achieve these goals, I will re- ceive training from my primary sponsor, Dr. Eric Nestler, and my co-sponsor Dr. Bin Zhang. Dr. Nestler is an expert in molecular psychiatry and has published extensively on the molecular mechanisms of depression. Dr. Zhang is a leader in genomics and was one of the primary developers of Weighted Gene Co-Expression Net- work Analysis. Working closely with them, as well as participating in targeted coursework and career develop- ment activities, I will receive in-depth training in genomics, bioinformatics, molecular neuroscience, and mouse behavior that will help me to successfully perform the experiments outlined in this proposal as well as achieve my long-term and career goals.
Major Depressive Disorder is a significant public health concern that causes considerable morbidity and mor- tality worldwide, yet the mechanisms underlying depression remain poorly understood. This study aims to characterize networks of neural gene expression associated with resilience in an animal model of depression, identifying genes responsible for mitigating depression-like behavior. This research is relevant to the NIH's mission of improving health and understanding mental disorders because it is expected to further clarify the molecular mechanisms underlying depression and identify novel targets for antidepressant therapeutics.
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