Abstract
New microbiome sequencing technologies provide novel information about the potential interactions among intestinal microorganisms and the host in some neuropathologies as autism spectrum disorders (ASD). The microbiota–gut–brain axis is an emerging aspect in the generation of autistic behaviors; evidence from animal models suggests that intestinal microbial shifts may produce changes fitting the clinical picture of autism. The aim of the present study was to evaluate the fecal metagenomic profiles in children with ASD and compare them with healthy participants. This comparison allows us to ascertain how mental regression (an important variable in ASD) could influence the intestinal microbiota profile. For this reason, a subclassification in children with ASD by mental regression (AMR) and no mental regression (ANMR) phenotype was performed. The present report was a descriptive observational study. Forty-eight children aged 2–6 years with ASD were included: 30 with ANMR and 18 with AMR. In addition, a control group of 57 normally developing children was selected and matched to the ASD group by sex and age. Fecal samples were analyzed with a metagenomic approach using a next-generation sequencing platform. Several differences between children with ASD, compared with the healthy group, were detected. Namely, Actinobacteria and Proteobacteria at phylum level, as well as, Actinobacteria, Bacilli, Erysipelotrichi, and Gammaproteobacteria at class level were found at higher proportions in children with ASD. Additionally, Proteobacteria levels showed to be augmented exclusively in AMR children. Preliminary results, using a principal component analysis, showed differential patterns in children with ASD, ANMR and AMR, compared to healthy group, both for intestinal microbiota and food patterns. In this study, we report, higher levels of Actinobacteria, Proteobacteria and Bacilli, aside from Erysipelotrichi, and Gammaproteobacteria in children with ASD compared to healthy group. Furthermore, AMR children exhibited higher levels of Proteobacteria. Further analysis using these preliminary results and mixing metagenomic and other “omic” technologies are needed in larger cohorts of children with ASD to confirm these intestinal microbiota changes.
Highlights
The advent of new sequencing technologies has stimulated the beginning of new research to ascertain the connections between the microbial communities that reside in our gut and some physiological and pathological conditions
The major findings were that fecal samples from children with autism spectrum disorders (ASD) exhibited several differences compared to a healthy group, especially in Actinobacteria and Proteobacteria, as these two phyla were significantly higher in children with ASD
XVII were solely higher in children with ANMR, whereas Proteobacteria, Thermoactinomycetaceae and Enterococcus abundances were exclusively higher in children with ASD by mental regression (AMR)
Summary
The advent of new sequencing technologies has stimulated the beginning of new research to ascertain the connections between the microbial communities that reside in our gut and some physiological and pathological conditions. The microbiota, defined as the full collection of microbes (bacteria, fungi, viruses, among others) that naturally exist within a particular biological niche, is estimated to contain 500–1000 species [1,2,3], and has an important impact on human health. The gut microbiota may play a key role in many essential processes in health and disease via the activity of the gut-brain axis, possibly contributing to autism spectrum disorders (ASD), Alzheimer’s disease, Parkinson’s disease, depression, and anxiety disorders, among others [4]. ASD is a severe neurodevelopmental disorder that impairs child’s ability to communicate and interact with others. Children with neurodevelopmental disorders, including ASD, are regularly affected by gastrointestinal problems and dysbiosis of the gut microbiota [5]. In the case of Spain, the estimated prevalence is 1.55% in preschoolers and 1.00% in school-age children, and male-to-female ratio was around 4:1 [7]
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