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| Funder | NATIONAL INSTITUTE OF MENTAL HEALTH |
|---|---|
| Recipient Organization | University of California, San Diego |
| Country | United States |
| Start Date | Jul 01, 2024 |
| End Date | Jun 30, 2026 |
| Duration | 729 days |
| Number of Grantees | 2 |
| Roles | Co-Investigator; Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10799340 |
Project Summary Major depressive disorder (MDD) is a common and burdensome psychiatric disorder. Unfortunately, current depression treatments suffer from numerous weaknesses, including treatment-resistance in a large proportion of patients. Several factors likely contribute to the limitations of current MDD pharmacotherapies, including the
heterogeneous nature of depression symptoms and the fact that most conventional treatments were discovered serendipitously rather than by targeting the underlying mechanisms of the disorder. One reason why targeted treatments have not been developed for MDD is the lack of translation between the depression-
relevant behaviors quantifiable in humans relative to those used to model MDD. Unfortunately, many behavioral models used to test new medications for MDD are often based on phenomena will limited relevance to those seen in humans, meaning that treatments targeting those behaviors often have limited clinical efficacy.
As an alternative to those existing models, specific tests quantify impairments exhibited by people with depression that are also available for testing in rodents. Here, we propose an approach that leverages the clinical sensitivities of behavioral and electroencephalographic (EEG) assessments to better evaluate the
putative impact of depression-relevant manipulations. Given the heterogeneous origins of MDD, Aim 1 will test whether three distinct manipulations known to induce depression-relevant behaviors (chronic corticosterone treatment, a short-active winter-like photoperiod, and acute treatment with the acetylcholinesterase inhibitor physostigmine) are capable of inducing depression-relevant states in mice,
using cross-species behavioral readouts affected in people with MDD, the probabilistic reversal learning and progressive ratio breakpoint tasks. Because depression can also alter neurological processes independent of its behavioral impacts, Aim 2 will test whether the same three manipulations have effects on specific
behavioral-associated neural processes that are known to be impacted in MDD that can be directly tested in rodents (Reward Positivity and parietal alpha power). Finally, to test the ability of these models to detect novel treatment efficacy, Aim 3 will determine the impact on these models of classical psychedelic
drugs such as psilocybin (currently undergoing human trials for MDD) that produce long-lasting symptom reductions after acute administration. To disentangle the potential therapeutic-like effects of psychedelics from their intoxicating properties, the psychedelics will be tested at doses equivalent to high and low (micro)doses in
humans. Overall, we will develop translational depression-relevant models that target specific domains of performance impacted in people and assessable in mice, potentially enabling the discovery and development of new, mechanistically-targeted treatments for MDD. Given our use of psychedelics in current clinical trials
and use of these EEG-linked tasks in clinical populations, these data will enable targeted assessment in patient populations in future studies.
University of California, San Diego
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