Uncovering novel endocannabinoidome-gut microbiome-brain axis-based therapeutic targets in a Fragile X Syndrome mouse model
Bibliographic record
Abstract
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition associated with increased risk of psychiatric, gastrointestinal, and metabolic comorbidities. Recent studies highlight the bidirectional role of the gut microbiome (GM) and endocannabinoidome (eCBome)-axis in the gut-brain axis, suggesting its therapeutic potential for ASD and comorbidities. METHODS: ) mouse model, known as a genetic model of ASD, to identify therapeutic targets. Fecal GM composition was analysed by 16S rDNA sequencing, brain eCBome profile by HPLC-MS/MS and qRT-PCR, and fecal short chain fatty acids by GC-FID. RESULTS: compared to wild-type mice. GM analyses revealed potential gut dysbiosis, increased permeability, and inflammation. Specifically, elevated Akkermansia and Eubacterium siraeum-linked to gut barrier dysfunction-and Ruminococcus and Clostridium, associated with ASD severity, were identified. Concurrently, decreased levels of the gut health biomarker Roseburia and the taxa Helicobacter and Anaeroplasma were observed. Brain region-specific eCBome alterations underscored neuroinflammation. In the HPC, reduced anti-inflammatory dihomogamma-linolenic acid (DGLA) was accompanied by elevated pro-inflammatory 12-hydroxy-heptadecatrienoic acid, a mediator of microglial activation. In the PFC, decreased DGLA, 1/2-linoleoylglycerol, and N-linoleoyl-ethanolamine suggested neuroinflammation; elevated prostaglandin D2, a marker of autophagy impairment, underscores further mechanisms of dysfunction. Upregulation of cannabinoid type 2 and PPAR-γ receptor genes in the PFC suggested a compensatory response to neuroinflammation. Correlations between eCBome and GM alterations highlighted potential links between gut dysbiosis, systemic inflammation, and neurodevelopmental atypicalities. CONCLUSIONS: ASD mouse model harbors significant eCBome-GM-brain axis alterations. This study highlights specific GM taxa and eCBome components as potential therapeutic targets for clinical validation in Fragile X Syndrome and ASD.
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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 | 0.000 |
| 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 | 0.000 |
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".