ANTI-COMPULSIVE ACTION OF ESCITALOPRAM IN DEER MICE PARALLELS DECREASED PLASMA LIPOPOLYSACCHARIDE AND INCREASED FRONTAL-CORTICAL AND STRIATAL TRYPTOPHAN, BUT NOT SEROTONIN CONCENTRATIONS
Bibliographic record
Abstract
Abstract Background Obsessive-compulsive disorder (OCD) is associated with cortico-striatal hyperactivation which is likely promulgated by hyposerotonergia. Selective serotonin reuptake inhibitors (SSRIs), e.g., escitalopram (ESC), are the first line pharmacotherapy for OCD, but treatment resistance remains a clinical dilemma. In fact, the mechanism of action of SSRIs in OCD remains unclear. Serotonin must be synthesised from dietary absorbed tryptophan (TRP) and reduced TRP availability may thus impact central serotonin concentrations. Systemic inflammation promotes TRP breakdown via the kynurenine, instead of the serotonin pathway. Lipopolysaccharide (LPS) is an inflammatory endotoxin that is associated with gut microbiota dysbiosis and compromised gut wall integrity. Considering the suboptimal response of OCD to current serotonergic therapies, as well as the paucity of data highlighting TRP and serotonin related gut-immune-brain interactions in OCD, continued investigation is needed. For this, pre- clinical animal model systems, are useful. Subpopulations of deer mice (Peromyscus maniculatus bairdii) that are housed in captivity spontaneously develop compulsive-like behaviours, e.g., persistent large nesting behaviour (LNB). We have previously shown LNB to associate with gut microbiota perturbations, compared to normal (NNB) behavioural controls (5). Since the neurobiological underpinnings of LNB have not yet been elucidated, we explored the potential associations between LNB, plasma LPS and central TRP and serotonin concentrations, before and after chronic exposure to ESC. Aims and Objectives The aim of this work was to investigate the potential associations between LNB, plasma LPS, and frontal cortical and striatal TRP and serotonin concentrations, before and after chronic exposure to ESC. In so doing, we also aimed to shed light on the anti-compulsive mechanism of action of ESC in this model. Methods Twenty-four (24) NNB and 24 LNB expressing mice were used (age 12 weeks; total n = 48; equal distribution between sexes, Ethical Approval Nr. NWU-00523-20-A5). Twelve (12) animals of each cohort were exposed to either normal water or escitalopram (50 mg/kg/day) for 28-days, with nesting expression analysed before and after said exposure. After the last nesting assessment, mice were euthanised and the trunk blood, frontal cortices and striata collected. LPS concentrations were determined in plasma by means of ELISA, while brain tissues were analysed for TRP and serotonin via LC/MS. Results We show that LNB, compared to NNB, associates with reduced frontal-cortical, but not striatal TRP and serotonin concentrations (p <0.01 for both) and that ESC significantly attenuates the expression of LNB, without affecting NNB (p <0.01). Importantly, the anti-compulsive action of ESC was associated with significantly increased frontal cortical and striatal TRP (p <0.05 for both), but not serotonin concentrations which paralleled a robust reduction in plasma LPS (p <0.001). Discussion We show that the anti-compulsive action of ESC in deer mice associates with TRP-specific, but not serotonergic mechanisms, which are likely related to its modulation of gut-microbiota associated systemic inflammation. The present data contribute to our understanding of LNB in deer mice and extend the current knowledge of how SSRIs may elicit their therapeutic actions by modulating gut-immune-brain interaction.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".