The link between autism spectrum disorder and gut microbiota: A scoping review
Bibliographic record
Abstract
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.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".