Meta-analysis of the autism gut microbiome identifies factors influencing study discrepancies and machine learning classification

Chavira, Aries; Wang, Eric Hou-Jen; Mills, Robert H.

doi:10.1101/2022.03.18.484910

Cited by 8 publications

(6 citation statements)

References 77 publications

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“…Only one study reported decreased levels of Actinobacteria. In a recent meta‐analysis by Chavira et al, higher levels of Actinobacteria in children with ASD was one of the most coherent results 64 . It was speculated whether this could indicate that the gut microbiota of children with ASD is underdeveloped, as Actinobacteria is more abundant in younger children.…”

Section: Discussionmentioning

confidence: 99%

“…In a recent meta-analysis by Chavira et al, higher levels of Actinobacteria in children with ASD was one of the most coherent results. 64 It was speculated whether this could indicate that the gut microbiota of children with ASD is underdeveloped, as Actinobacteria is more abundant in younger children. Three trials that included an intervention had interesting results regarding changes in behavioral symptoms among children with ASD.…”

Section: Discussionmentioning

confidence: 99%

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Systematic review: Autism spectrum disorder and the gut microbiota

Korteniemi,

Karlsson,

Aatsinki

2023

Acta Psychiatr Scand

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ObjectiveAutism spectrum disorders (ASD) are a varying group of disorders characterized by deficiency in social interaction and restrictive patterns of behavior and interests. While there are several studies focusing on the neuropsychiatric pathogenesis of ASD, its etiology remains unclear. The role of gut‐brain‐axis in ASD has been studied increasingly and a correlation between symptoms and the composition of gut microbiota has been documented in various works. Despite this, the significance of individual microbes and their function is still widely unknown. This work aims to elucidate the current knowledge of the interrelations between ASD and the gut microbiota in children based on scientific evidence.MethodsThis is a systematic review done by a literature search focusing on the main findings concerning the gut microbiota composition, interventions targeting the gut microbiota, and possible mechanisms explaining the results in children aged between 2 and 18 years of age.ResultsMost studies in this review found significant differences between microbial communities, while there was notable variation in results regarding diversity indices or taxonomic level abundance. The most consistent results regarding taxa differences in ASD children's gut microbiota were higher levels of Proteobacteria, Actinobacteria and Sutterella compared to controls.ConclusionThese results show that the gut microbiota of children with ASD is altered compared to one of neurotypically developed children. More research is needed to discover whether some of these features could be used as potential biomarkers for ASD and how the gut microbiota could be targeted in therapeutical interventions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Systematic review: Autism spectrum disorder and the gut microbiota

Korteniemi,

Karlsson,

Aatsinki

2023

Acta Psychiatr Scand

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“…All meta-analyses used a fivefold cross-validation approach for machine learning classification on taxonomic annotation data, but the number and type of classifiers differed between the studies. In Chavira et al 53 , they examined how taxonomic resolution impact predictive accuracy concluding that the higher the taxonomic resolution is, the better the models’ performance is. Additionally, Pietrucci et al 54 looked at the importance of the control groups for ASD classification using three different classifiers.…”

Section: Discussionmentioning

confidence: 99%

A robust microbiome signature for autism spectrum disorder across different studies using machine learning

Peralta-Marzal,

Rojas-Velazquez,

Rigters

et al. 2024

Sci Rep

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Autism spectrum disorder (ASD) is a highly complex neurodevelopmental disorder characterized by deficits in sociability and repetitive behaviour, however there is a great heterogeneity within other comorbidities that accompany ASD. Recently, gut microbiome has been pointed out as a plausible contributing factor for ASD development as individuals diagnosed with ASD often suffer from intestinal problems and show a differentiated intestinal microbial composition. Nevertheless, gut microbiome studies in ASD rarely agree on the specific bacterial taxa involved in this disorder. Regarding the potential role of gut microbiome in ASD pathophysiology, our aim is to investigate whether there is a set of bacterial taxa relevant for ASD classification by using a sibling-controlled dataset. Additionally, we aim to validate these results across two independent cohorts as several confounding factors, such as lifestyle, influence both ASD and gut microbiome studies. A machine learning approach, recursive ensemble feature selection (REFS), was applied to 16S rRNA gene sequencing data from 117 subjects (60 ASD cases and 57 siblings) identifying 26 bacterial taxa that discriminate ASD cases from controls. The average area under the curve (AUC) of this specific set of bacteria in the sibling-controlled dataset was 81.6%. Moreover, we applied the selected bacterial taxa in a tenfold cross-validation scheme using two independent cohorts (a total of 223 samples—125 ASD cases and 98 controls). We obtained average AUCs of 74.8% and 74%, respectively. Analysis of the gut microbiome using REFS identified a set of bacterial taxa that can be used to predict the ASD status of children in three distinct cohorts with AUC over 80% for the best-performing classifiers. Our results indicate that the gut microbiome has a strong association with ASD and should not be disregarded as a potential target for therapeutic interventions. Furthermore, our work can contribute to use the proposed approach for identifying microbiome signatures across other 16S rRNA gene sequencing datasets.

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“…He showed that building machine learning models for diagnosing ASD from stools worked particularly well when models were built from data in China, which could suggest that there are geographical differences that play a role in autism. Their meta-analysis on reprocessed 16S ribosomal RNA gene amplicon (16S) sequencing data suggests that the gut microbiome can be altered in ASD patients [ 15 ].…”

Section: Industry Presentationsmentioning

confidence: 99%