Microbiome-Specific Statistical Modeling Identifies Interplay Between Gastrointestinal Microbiome and Neurobehavioral Outcomes in Patients With Autism: A Case Control Study

Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with unclear mechanisms of pathogenesis. Gastrointestinal microbiome alterations were found to correlate with ASD core symptoms, but its specific role in ASD pathogenesis has not been determined. In this study, we used a case-control strategy that simultaneously compared the ASD gastrointestinal microbiome with that from age-sex matched controls and first-degree relative controls, using a statistical framework accounting for confounders such as age. Enterobacteriaceae (including Escherichia/Shigella) and Phyllobacterium were significantly enriched in the ASD group, with their relative abundances all following a pattern of ASD > first degree relative control > healthy control, consistent with our hypothesis of living environment and shared microbial and immunological exposures as key drivers of ASD gastrointestinal microbiome dysbiosis. Using multivariable omnibus testing, we identified clinical factors including ADOS scores, dietary habits, and gastrointestinal symptoms that covary with overall microbiome structure within the ASD cohort. A microbiome-specific multivariate modeling approach (MaAsLin2) demonstrated microbial taxa, such as Lachnoclostridium and Tyzzerella, are significantly associated with ASD core symptoms measured by ADOS. Finally, we identified alterations in predicted biological functions, including tryptophan and tyrosine biosynthesis/metabolism potentially relevant to the pathophysiology of the gut-brain-axis. Overall, our results identified gastrointestinal microbiome signature changes in patients with ASD, highlighted associations between gastrointestinal microbiome and clinical characteristics related to the gut-brain axis and identified contributors to the heterogeneity of gastrointestinal microbiome within the ASD population.

Abelmoschus Manihot ameliorates the levels of circulating metabolites in diabetic nephropathy by modulating gut microbiota in non‐obese diabetes mice

“…In the current study, specific bacterial genera altered significantly after HKC administration, and showed a significant correlation with changes in metabolite levels and disease indicators, suggesting that they may be associated with the mechanism of effects of HKC in treatment of DN. Among the differential intestinal bacteria, Phyllobacterium has been reported to be associated with the diseases in humans, such as liver cirrhosis and non‐liver cirrhosis‐induced HCC, and significantly enriched in the autism spectrum disorders patients and the cholestatic infants (Guo et al, 2018 ; Huang et al, 2021 ; Zheng, Wang, et al, 2020 ). Similarly, a recent study has demonstrated that Weissella confusa was higher in KK‐Ay mice with T2D (Liu et al, 2021 ) while other studies have shown that Weissella decreased after treatment with some effective medications in an animal model of T2D (Hu et al, 2019 ; Zheng, Chen, et al, 2020 ).…”

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

“…A total of 12 met the inclusion criteria described above and were included in this analysis. We identified one dataset deposited in the Sequence Read Archive (SRA) with its respective metadata, that was not yet published but published during manuscript preparation 39 . Lastly, we utilized open-source data generated from the American Gut Project (AGP) to cultivate an additional dataset of ASD children and controls.…”

Overall Rebalancing of Gut Microbiota Is Key to Autism Intervention

“…Most children show some abnormal behavior symptoms only at about 18–24 months, while other specific functional characteristics may only be found at an older age ( Borghi and Vignoli, 2019 ). Current studies indicate that there are multiple subtypes of ASD, potentially caused by different routes of pathophysiology and each with diverse comorbid psychiatric and medical conditions (e.g., gastrointestinal symptoms, allergies, sleep disorders) ( Huang et al, 2021 ). However, this heterogeneity is not addressed by the conventional DSM5-based behavioral diagnostic criteria.…”