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Record W4411924938 · doi:10.1186/s12929-025-01145-7

The endocannabinoidome–gut microbiome–brain axis as a novel therapeutic target for autism spectrum disorder

2025· review· en· W4411924938 on OpenAlexafffund
Antonella Campanale, Dario Siniscalco, Vincenzo Di Marzo

Bibliographic record

VenueJournal of Biomedical Science · 2025
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité LavalNutrition InternationalInstitut universitaire de cardiologie et de pneumologie de QuébecMcGill UniversityMcGill University Health Centre
FundersMcGill University Health Centre
KeywordsPalmitoylethanolamideEndocannabinoid systemGut–brain axisNeuroscienceMonoacylglycerol lipaseCannabinoid receptor type 2Autism spectrum disorderMedicineCannabinoid receptorReceptorPharmacologyPsychologyAutismBiologyBioinformaticsMicrobiomeInternal medicinePsychiatryAgonist

Abstract

fetched live from OpenAlex

INTRODUCTION: Autism spectrum disorder (ASD) is characterized by disruption of the gut-brain axis, which leads to behavioral, psychiatric, metabolic and gastrointestinal symptoms. Effective ASD treatments are limited. Research highlights the roles of the endocannabinoidome (eCBome) and gut microbiome (GM), both crucial for brain and gut function. This review summarizes research on therapeutic targets within the eCBome-GM-brain axis for ASD and related comorbidities. DISCUSSION: Evidence suggests that reduced levels of eCBome mediators, like oleoylethanolamide and anandamide, and altered cannabinoid type 1 and type 2 (CB1 and CB2) receptors activity may contribute to ASD symptoms, making them promising targets. Modulating the eCBome-GM-brain axis with inhibitors of fatty acid amide hydrolase (FAAH), transient receptor potential vanilloid 1, and monoacylglycerol lipase (MAGL) may improve repetitive, stereotypical, and sensory behaviors, and alleviate sociability impairments, depression and anxiety. However, inhibition of FAAH and MAGL may also induce ADHD-like behaviors, which can be reversed by CB1 inverse agonists. Targeting metabotropic glutamate receptor 5 to increase levels of the eCBome mediator 2-arachidonoylglycerol (2-AG) may benefit ASD-related behaviors. eCBome mediators such as 2-AG, 1/2-palmitoylglycerol and palmitoylethanolamide may also help manage ASD- and GI-related symptoms, and systemic inflammation. Other potential therapeutic targets that deserve further investigation are eCBome-related receptors G-protein-coupled receptor 55 and peroxisome proliferator-activated receptors-alpha and -gamma, and the cyclooxygenase-2/prostaglandin E2 pathway, which may address hyperactivity and repetitive behaviors. Additionally, mucin-degrading genera like Akkermansia and Ruminococcus may improve ASD-related GI symptoms such as hypersensitivity and inflammation. Selective antibiotics against specific Clostridium strains may improve irritability and aggression. In ASD with ADHD and OCD, treatments may involve modulating the CB1 and CB2 receptor, and bacterial families like Ruminococcaceae and Lachnospiraceae. Lastly, modulating the abundance of anti-inflammatory genera like Prevotella and Anaeroplasma, and taxa associated with gut health such as Roseburia may also offer therapeutic value. CONCLUSION: The eCBome-GM-brain axis is a promising target for ASD treatment, meriting further clinical and preclinical research.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.021
GPT teacher head0.378
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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