Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors

Assessing Internal Consistency of the Autism Spectrum Disorder Gastrointestinal and Related Behaviors Inventory and the Frequency and Socio-Emotional Correlates of Gastrointestinal Difficulties in Children With the Autism Spectrum Disorder: A Cross-Sectional Study

Gastrointestinal (GI) difficulties are common in children diagnosed with autism spectrum disorder (ASD). However, these difficulties can frequently remain unrecognized. Therefore, we aimed to translate a newly developed instrument, The Autism Spectrum Disorder Gastrointestinal and Related Behaviors Inventory in Children (ASD-GIRBI), to assess its reliability and to explore the frequency of various gastrointestinal difficulties and related behaviors, as well as to explore the association of GI difficulties with the measures of social functioning and emotional and behavioral difficulties in children with ASD. A total of 98 children and adolescents (aged 4-18 [M age = 10.67 ± 3.705], 82.7% male), previously diagnosed with ASD at the Institute of Mental Health in Belgrade, Serbia, took part in this research. Their parents filled out the following questionnaires: ASD-GIRBI (an assessment of gastrointestinal and related symptoms), Stanford Social Dimensions Scale (SSDS) (a measure of social functioning) and Strengths and Difficulties Questionnaire (SDQ) (a measure of emotional and behavioral problems). Our results indicate that the ASD-GIRBI is a reliable instrument for GI difficulties assessment (Cronbach's α = 0.841) with the total score successfully discriminating between the participants with and without a GI disorder diagnosis (p = 0.040). Any gastrointestinal symptom was present in 54.1% of the participants, most commonly flatulence, diarrhea, and constipation. The severity of gastrointestinal difficulties correlated to emotional problems (r = 0.261, p < 0.01), conduct problems (r = 0.219, p < 0.05), hyperactivity (r = 0.381, p < 0.01), peer problems (r = 0.266, p < 0.01), total difficulties (r = 0.454, p < 0.01) and total difficulties impact (r = 0.321, p < 0.01). Our data emphasize the potential importance of GI difficulties for various areas of functioning of individuals with ASD.

Functional foods acting on gut microbiota-related wellness: The multi-unit in vitro colon model to assess gut ecological and functional modulation

The aim of this study was to investigate the effect of a functional probiotic cheese (FPC) on gut microbiota (GM), after simulated digestion performed by a multi-unit in vitro colon model (MICODE). Squacquerone-like cheese was produced using the starter Streptococcus thermophilus (control, CTRL), and supplemented with the probiotic Lacticaseibacillus rhamnosus, which was either subjected to high pressure homogenization (LrH) or not (Lr). Samples were stratified by cheese type, storage time, and colonic fermentation phase. Samples were then digested with MICODE and digests were characterized for ecological and functional profiles. The lactobacilli detected in Lr and LrH cheeses (9.0 log CFU/g) were represented by the probiotic strain L. rhamnosus and remained unchanged after storage at 4 °C. Lactobacilli levels in CTRLs increased from 1.5 log CFU/g to 2.0 log CFU/g after six days at 4 °C, while total coliforms remained below 1.5 log CFU/g in all samples. Real-time qPCR indicated a positive GM response after FPC simulated digestion, highlighting an abundance of bifidobacteria, lactobacilli and Clostridium group IV in LrH samples. Metataxonomy revealed higher levels of Firmicutes and Proteobacteria (p ≤ 0.05) after simulated digestion, as well as Megasphaera, Escherichia, Prevotella and Dorea. Moreover, an increase of short and medium chain fatty acids were detected by metabolomics. Overexpression of inferred KEGG metabolic pathways showed mainly fatty acids, novobiocin and amino acid metabolism. Understanding how functional foods can modify the GM may lead to the development of targeted microbiome-based therapies and the exploitation of these foods for the benefit of human health.

Contributions of Artificial Intelligence to Analysis of Gut Microbiota in Autism Spectrum Disorder: A Systematic Review

BACKGROUND

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder whose etiology is not known today, but everything indicates that it is multifactorial. For example, genetic and epigenetic factors seem to be involved in the etiology of ASD. In recent years, there has been an increase in studies on the implications of gut microbiota (GM) on the behavior of children with ASD given that dysbiosis in GM may trigger the onset, development and progression of ASD through the microbiota-gut-brain axis. At the same time, significant progress has occurred in the development of artificial intelligence (AI).

METHODS

The aim of the present study was to perform a systematic review of articles using AI to analyze GM in individuals with ASD. In line with the PRISMA model, 12 articles using AI to analyze GM in ASD were selected.

RESULTS

Outcomes reveal that the majority of relevant studies on this topic have been conducted in China (33.3%) and Italy (25%), followed by the Netherlands (16.6%), Mexico (16.6%) and South Korea (8.3%).

CONCLUSIONS

The bacteria Bifidobacterium is the most relevant biomarker with regard to ASD. Although AI provides a very promising approach to data analysis, caution is needed to avoid the over-interpretation of preliminary findings. A first step must be taken to analyze GM in a representative general population and ASD samples in order to obtain a GM standard according to age, sex and country. Thus, more work is required to bridge the gap between AI in mental health research and clinical care in ASD.

Propionic acid affects the synaptic architecture of rat hippocampus and prefrontal cortex

It is well documented that propionic acid (PPA) produces behavioral, morphological, molecular and immune responses in rats that are characteristic of autism spectrum disorder in humans. However, whether PPA affects the ultrastructure and synaptic architecture of regions of autistic brain has not been adequately addressed. Earlier we show that single intraperitoneal (IP) injection of PPA (175 mg/kg) produces superficial changes in the spatial memory and learning of adolescent male Wistar rats. However, in neurons, synapses and glial cells of hippocampal CA1 area and medial prefrontal cortex transient (mainly) or enduring alterations were detected. In this study, we used electron microscopic morphometric analysis to test the effect of PPA on different structural parameters of axodendritic synapses of the hippocampus and prefrontal cortex. The animals were treated with a single IP injection of PPA (175 mg/kg). The length and width of synaptic active zone, the area of presynaptic and postsynaptic mitochondria, the distance between presynaptic mitochondria and the synapse active zone, the distance between postsynaptic mitochondria and postsynaptic density and the depth and opening diameter of neuronal porosome complex were evaluated. Our results show that synaptic mitochondria of the hippocampus and prefrontal cortex are the most vulnerable to PPA treatment: in both regions, the area of postsynaptic mitochondria were increased. In general, our results show that even small dose of PPA, which produces only superficial effects on spatial memory and learning is able to alter the synapse architecture in brain regions involved in cognition and autism pathogenesis. Therefore, the microbiome may be involved in the control of neurotransmission in these regions.