Turicibacter and Catenibacterium as potential biomarkers in autism spectrum disorders

Abstract

Autism spectrum disorders (ASD) are neurodevelopmental disorders characterized by social, behavioral, and cognitive impairments. Several comorbidities, including gastrointestinal (GI) dysregulations, are frequently reported in ASD children. Although studies in animals have shown the crucial role of the microbiota in key aspects of neurodevelopment, there is currently no consensus on how the alteration of microbial composition affects the pathogenesis of ASD. Moreover, disruption of the gut-brain axis (GBA) has been reported in ASD although with limited studies conducted on the Mediterranean population. In our study, we aimed to investigate gut microbiota composition in Lebanese ASD subjects, their unaffected siblings, and a control group from various regions in Lebanon using the 16 S-rRNA sequencing (NGS). Our study revealed a lower abundance of Turicibacter and a significant enrichment on Proteobacteria in the ASD and siblings' groups compared to the controls, indicating that gut microbiota is probably affected by dietary habits, living conditions together with host genetic factors. The study also showed evidence of changes in the gut microbiome of ASD children compared to their siblings and the unrelated control. Bacteroidetes revealed a lower abundance in the ASD group compared to controls and siblings, conversely, Catenibacterium and Tenericutes revealed an increased abundance in the ASD group. Notably, our study identifies alterations in the abundance of Turicibacter and Catenibacterium in ASD children suggesting a possible link between these bacterial taxa and ASD and contributing to the growing body of evidence linking the microbiome to ASD.

Keywords: Catenibacterium; Turicibacter; Autism spectrum disorders; Gastrointestinal dysregulations; Gut-brain axis; Microbiota.

Fig. 1

Taxonomic composition of community at Phylum level using Stacked Bar plot.

Fig. 2

Taxonomic composition of community at Genus level using Stacked Bar plot.

Fig. 3

Gut microbial diversity in the studied groups. Alpha diversity was assessed at the Phylum level using four frequently employed methods: Observed, ACE, Shannon, and Simpson. The boxplots depict the median and interquartile (IQR) range, with whiskers reaching to the outermost data points within 1.5 times the IQR.

Fig. 4

Gut microbial diversity in the studied groups. Alpha diversity was assessed at the Genus level using four frequently employed methods: Observed, ACE, Shannon, and Simpson. The boxplots depict the median and interquartile (IQR) range, with whiskers reaching to the outermost data points within 1.5 times the IQR.

Fig. 5

Beta diversity index was assessed using the Bray-Curtis method, employing principal coordinate analysis to analyze the relative abundance of OTUs. Axis.1 and Axis.2 explained 23.3% and 20.7% of the variances, respectively. Statistical significance (p < 0.05) was assessed using permutation tests, integral to the PERMANOVA framework.

Fig. 6

Gut microbial markers were measured by LEfSe analytical tool with an LDA cut-off value > 2.0 in autistic, control, and sibling groups.

Fig. 7

Significant features identified by Random Forest. The features are ranked by the mean decrease in classification accuracy when permuted.

Fig. 8

Microbial association analysis to examine the connections between microbial features and experimental metadata for Autism Vs Control groups.