Altered Serotonin Regulation in Genetic and Post-Stroke Models of Anxiety and Depression
Bibliographic record
Abstract
Major depression is a complex disease involving genetic and environmental factors. Previous studies suggest that functional genetic polymorphisms that alter the serotonin (5-HT) system in combination with psychosocial stress can synergistically increase the strength of these associations. In addition, depression is associated with several neurological disorders involving neuronal injury, including stroke (i.e. post-stroke depression, PSD). Both forms of depression are treated with 5-HT-selective antidepressants like fluoxetine, but remission rates do not exceed 50%. Evidence showed that alterations affecting the 5-HT system, directly or indirectly, lead to anxiety or depression phenotypes and may elucidate determinants of response to antidepressants. To better understand common and unique alterations in both genetic- and injury-related depression, I have generated and investigated two novel mouse models that exemplify a serotonin-related genetic risk (Flx-Freud-1 mice) and an injury model (ischemic lesion), to identify similarities and differences in their behavioral phenotypes, and in response to fluoxetine treatment. In the Flx-Freud-1 mouse model, 5-HT neuron-specific adult knockout of Freud-1, a key repressor of the 5-HT1A receptor gene, led to overexpression of 5-HT1A autoreceptors thought to negatively regulate the 5-HT system. These mice showed increased 5-HT1A autoreceptor responses, reduced 5-HT levels and a robust anxiety and depression phenotype that was resistant to chronic fluoxetine treatment. These behaviors were dependent on increased 5-HT1A autoreceptors since they were not seen in mice lacking 5-HT1A autoreceptors in adult Freud-1 knockout background. Instead an opposite anti-depressed phenotype emerged, suggesting that Freud-1 might have additional functions in 5-HT cells. In the PSD model, the vasoconstrictor endothelin-1 was injected to induce transient ischemia in the left medial prefrontal cortex, iv part of the circuitry thought to be damaged in PSD in humans. This stroke resulted in a persistent anxiety, depression and cognitive impairment. Chronic fluoxetine treatment alone or combined with voluntary exercise was effective to reverse the behavioral and cognitive phenotypes in this PSD mouse model.The results of genetic and SSRI treated stroke models show that changes in 5-HT system contribute to widespread dysregulation of the neuronal circuitry implicated in depression, anxiety. Genetic alteration of the 5-HT system conferred fluoxetine-resistance, while cortical stroke which indirectly altered the 5-HT system remained responsive to fluoxetine. Following unilateral stroke, there was increased activity of the contralateral hemisphere, including the prefrontal cortex and limbic areas involved in anxiety and depression, and activation of the 5-HT system. Effective treatment with chronic fluoxetine alone or combined with exercise significantly reduced and balanced the contralesional neuronal activation in affected regions that correlated with improvements in phenotypes. In conclusion, this work implicates genetic changes that directly alter the 5-HT system in resistance to chronic fluoxetine treatment. Therefore, the Flx-Freud-1-induced 5-HT1A autoreceptor overexpression mouse model may provide a useful pre-clinical model of antidepressant resistance. In contrast, in the PSD model, in which expression of 5-HT1A autoreceptors remained intact, chronic fluoxetine treatment reversed depression and anxiety phenotypes. This model may provide insight into changes in neuronal activity that allows antidepressants to mediate behavioral and cognitive improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".