The link between autism spectrum disorder and gut microbiota: A scoping review
Notice bibliographique
Résumé
Gut dysfunction and microbial dysbiosis comorbidities are of particular interest in recent autism research, as gastrointestinal distress is present in up to 90% of autism spectrum disorder cases and therefore may play a key role in the pathogenesis of this disorder. This scoping review aims to integrate the results of studies conducted in the past 6 years examining the association between gut microbiota and autism spectrum disorder, specifically with regard to the characterization of autism spectrum disorder microbiota and potential therapeutic interventions. Studies related to the gastrointestinal microbiome of subjects with autism spectrum disorder were identified through PubMed, SCOPUS, PsycInfo, and Google Scholar databases. Studies were screened and selected based on defined inclusion and exclusion criteria; 19 studies were included. Research continues to report differences between microbiota of individuals with autism spectrum disorder and controls; however, the types and abundances of bacteria present remain inconsistent. Promising treatment interventions for autism spectrum disorder, including special diets, dietary supplementation, and of particular interest, microbiota transfer therapy, are also being explored. Research regarding the link between gut microbiota and autism spectrum disorder renders exciting results; however, it is still in its infancy of investigation. Rigorous methodologies are required to support and strengthen the reliability of existing results, and to further our understanding of the pathogenesis of autism spectrum disorder. Lay abstract Gastrointestinal distress and gut microbial imbalances are commonly found in children with autism spectrum disorder, and therefore may play a key role in the development of the disorder. This scoping review aimed to examine the extent, range and nature of research conducted in the past 6 years that focused on furthering our understanding of autism spectrum disorder and its association with gut microbiota. A literature review was performed with predetermined key words. Studies were screened and selected based on defined inclusion and exclusion criteria. A total of 19 studies were included for final analysis. While there are continuous reports of differences in gut microbiota between autism spectrum disorder and neurotypical individuals, knowledge about the consistency in the presence and abundance of bacterial species, as well as metabolites, remains deficient. Treatments such as special diets, vitamin, prebiotic, probiotic, and microbiota transfer therapy show promising therapeutic potential, yet are in their infancy of investigation. Overall, further research with rigorous methodologies is required to support and strengthen the reliability of existing findings. Future research should aim to increase sample sizes, eliminate biases, and subgroup autism spectrum disorder groups to help accommodate for inter-individual variation. As increasing evidence of a unique autism spectrum disorder microbiome and metabolome is acquired, autism spectrum disorder-specific biomarkers can be identified. These biomarkers have great implications in terms of elucidating the molecular mechanisms of autism spectrum disorder, preventing the onset of autism spectrum disorder, and improving treatments for individuals with autism spectrum disorder.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,005 |
| Bibliométrie | 0,020 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».