Analysis of Faecal Microbiota and Small ncRNAs in Autism: Detection of miRNAs and piRNAs with Possible Implications in Host-Gut Microbiota Cross-Talk

PIWI-Interacting RNAs: A Pivotal Regulator in Neurological Development and Disease

PIWI-interacting RNAs (piRNAs), a class of small non-coding RNAs (sncRNAs) with 24-32 nucleotides (nt), were initially identified in the reproductive system. Unlike microRNAs (miRNAs) or small interfering RNAs (siRNAs), piRNAs normally guide P-element-induced wimpy testis protein (PIWI) families to slice extensively complementary transposon transcripts without the seed pairing. Numerous studies have shown that piRNAs are abundantly expressed in the brain, and many of them are aberrantly regulated in central neural system (CNS) disorders. However, the role of piRNAs in the related developmental and pathological processes is unclear. The elucidation of piRNAs/PIWI would greatly improve the understanding of CNS development and ultimately lead to novel strategies to treat neural diseases. In this review, we summarized the relevant structure, properties, and databases of piRNAs and their functional roles in neural development and degenerative disorders. We hope that future studies of these piRNAs will facilitate the development of RNA-based therapeutics for CNS disorders.

The potential of short-chain fatty acid epigenetic regulation in chronic low-grade inflammation and obesity

Obesity and chronic low-grade inflammation, often occurring together, significantly contribute to severe metabolic and inflammatory conditions like type 2 diabetes (T2D), cardiovascular disease (CVD), and cancer. A key player is elevated levels of gut dysbiosis-associated lipopolysaccharide (LPS), which disrupts metabolic and immune signaling leading to metabolic endotoxemia, while short-chain fatty acids (SCFAs) beneficially regulate these processes during homeostasis. SCFAs not only safeguard the gut barrier but also exert metabolic and immunomodulatory effects via G protein-coupled receptor binding and epigenetic regulation. SCFAs are emerging as potential agents to counteract dysbiosis-induced epigenetic changes, specifically targeting metabolic and inflammatory genes through DNA methylation, histone acetylation, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). To assess whether SCFAs can effectively interrupt the detrimental cascade of obesity and inflammation, this review aims to provide a comprehensive overview of the current evidence for their clinical application. The review emphasizes factors influencing SCFA production, the intricate connections between metabolism, the immune system, and the gut microbiome, and the epigenetic mechanisms regulated by SCFAs that impact metabolism and the immune system.

A comparison between children and adolescents with autism spectrum disorders and healthy controls in biomedical factors, trace elements, and microbiota biomarkers: a meta-analysis

Introduction

Autism spectrum disorder (ASD) is a multifaceted developmental condition that commonly appears during early childhood. The etiology of ASD remains multifactorial and not yet fully understood. The identification of biomarkers may provide insights into the underlying mechanisms and pathophysiology of the disorder. The present study aimed to explore the causes of ASD by investigating the key biomedical markers, trace elements, and microbiota factors between children with autism spectrum disorder (ASD) and control subjects.

Methods

Medline, PubMed, ProQuest, EMBASE, Cochrane Library, PsycINFO, Web of Science, and EMBSCO databases have been searched for publications from 2012 to 2023 with no language restrictions using the population, intervention, control, and outcome (PICO) approach. Keywords including "autism spectrum disorder," "oxytocin," "GABA," "Serotonin," "CRP," "IL-6," "Fe," "Zn," "Cu," and "gut microbiota" were used for the search. The Joanna Briggs Institute (JBI) critical appraisal checklist was used to assess the article quality, and a random model was used to assess the mean difference and standardized difference between ASD and the control group in all biomedical markers, trace elements, and microbiota factors.

Results

From 76,217 records, 43 studies met the inclusion and exclusion criteria and were included in this meta-analysis. The pooled analyses showed that children with ASD had significantly lower levels of oxytocin (mean differences, MD = -45.691, 95% confidence interval, CI: -61.667, -29.717), iron (MD = -3.203, 95% CI: -4.891, -1.514), and zinc (MD = -6.707, 95% CI: -12.691, -0.722), lower relative abundance of Bifidobacterium (MD = -1.321, 95% CI: -2.403, -0.238) and Parabacteroides (MD = -0.081, 95% CI: -0.148, -0.013), higher levels of c-reactive protein, CRP (MD = 0.401, 95% CI: 0.036, 0.772), and GABA (MD = 0.115, 95% CI: 0.045, 0.186), and higher relative abundance of Bacteroides (MD = 1.386, 95% CI: 0.717, 2.055) and Clostridium (MD = 0.281, 95% CI: 0.035, 0.526) when compared with controls. The results of the overall analyses were stable after performing the sensitivity analyses. Additionally, no substantial publication bias was observed among the studies.

Interpretation

Children with ASD have significantly higher levels of CRP and GABA, lower levels of oxytocin, iron, and zinc, lower relative abundance of Bifidobacterium and Parabacteroides, and higher relative abundance of Faecalibacterium, Bacteroides, and Clostridium when compared with controls. These results suggest that these indicators may be a potential biomarker panel for the diagnosis or determining therapeutic targets of ASD. Furthermore, large, sample-based, and randomized controlled trials are needed to confirm these results.

Microbiota in Autism Spectrum Disorder: A Systematic Review

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by several core symptoms: restricted interests, communication difficulties, and impaired social interactions. Many ASD children experience gastrointestinal functional disorders, impacting their well-being. Emerging evidence suggests that a gut microbiota imbalance may exacerbate core and gastrointestinal symptoms. Our review assesses the gut microbiota in children with ASD and interventions targeting microbiota modulation. The analysis of forty-four studies (meta-analyses, reviews, original research) reveals insights into the gut microbiota-ASD relationship. While specific microbiota alterations are mixed, some trends emerge. ASD children exhibit increased Firmicutes (36-81%) and Pseudomonadota (78%) and decreased Bacteroidetes (56%). The Bacteroidetes to Firmicutes ratio tends to be lower (56%) compared to children without ASD, which correlates with behavioral and gastrointestinal abnormalities. Probiotics, particularly Lactobacillus, Bifidobacterium, and Streptococcus strains, show promise in alleviating behavioral and gastrointestinal symptoms (66%). Microbiota transfer therapy (MTT) seems to have lasting benefits for the microbiota and symptoms in one longitudinal study. Prebiotics can potentially help with gastrointestinal and behavioral issues, needing further research for conclusive efficacy due to different interventions being used. This review highlights the gut microbiota-ASD interplay, offering potential therapeutic avenues for the gut-brain axis. However, study heterogeneity, small sample sizes, and methodological variations emphasize the need for comprehensive, standardized research. Future investigations may unveil complex mechanisms linking the gut microbiota to ASD, ultimately enhancing the quality of life for affected individuals.

Genus-Level Analysis of Gut Microbiota in Children with Autism Spectrum Disorder: A Mini Review

Autism is a global health problem, probably due to a combination of genetic and environmental factors. There is emerging data that the gut microbiome of autistic children differs from the one of typically developing children and it is important to know which bacterial genera may be related to autism. We searched different databases using specific keywords and inclusion criteria and identified the top ten bacterial genera from the selected articles that were significantly different between the studied patients and control subjects studied. A total of 34 studies that met the inclusion criteria were identified. The genera Bacteroides, Bifidobacterium, Clostridium, Coprococcus, Faecalibacterium, Lachnospira, Prevotella, Ruminococcus, Streptococcus, and Blautia exhibited the most substantial data indicating that their fluctuations in the gastrointestinal tract could be linked to the etiology of autism. It is probable that autism symptoms are influenced by both increased levels of harmful bacteria and decreased levels of beneficial bacteria. Interestingly, these genera demonstrated varying patterns of increased or decreased levels across different articles. To validate and eliminate the sources of this fluctuation, further research is needed. Consequently, future investigations on the causes of autism should prioritize the examination of the bacterial genera discussed in this publication.

Exploration of the relationship between gut microbiota and fecal microRNAs in patients with major depressive disorder

Microbiota-gut-brain axis signaling plays a pivotal role in mood disorders. The communication between the host and the gut microbiota may involve complex regulatory networks. Previous evidence showed that host-fecal microRNAs (miRNAs) interactions partly shaped gut microbiota composition. We hypothesized that some miRNAs are correlated with specific bacteria in the fecal samples in patients with major depressive disorder (MDD), and these miRNAs would show enrichment in pathways associated with MDD. MDD patients and healthy controls were recruited to collect fecal samples. We performed 16S ribosome RNA sequence using the Illumina MiSeq sequencers and analysis of 798 fecal miRNAs using the nCounter Human-v2 miRNA Panel in 20 subjects. We calculated the Spearman correlation coefficient for bacteria abundance and miRNA expressions, and analyzed the predicted miRNA pathways by enrichment analysis with false-discovery correction (FDR). A total of 270 genera and 798 miRNAs were detected in the fecal samples. Seven genera (Anaerostipes, Bacteroides, Bifidobacterium, Clostridium, Collinsella, Dialister, and Roseburia) had fold changes greater than one and were present in over 90% of all fecal samples. In particular, Bacteroides and Dialister significantly differed between the MDD and control groups (p-value < 0.05). The correlation coefficients between the seven genera and miRNAs in patients with MDD showed 48 pairs of positive correlations and 36 negative correlations (p-value < 0.01). For miRNA predicted functions, there were 57 predicted pathways with a p-value < 0.001, including MDD-associated pathways, axon guidance, circadian rhythm, dopaminergic synapse, focal adhesion, long-term potentiation, and neurotrophin signaling pathway. In the current pilot study, our findings suggest specific genera highly correlated with the predicted miRNA functions, which might provide clues for the interaction between host factors and gut microbiota via the microbiota-gut-brain axis. Follow-up studies with larger sample sizes and refined experimental design are essential to dissect the roles between gut microbiota and miRNAs for depression.

Leveraging Existing 16SrRNA Microbial Data to Define a Composite Biomarker for Autism Spectrum Disorder

Cumulative studies have utilized high-throughput sequencing of the 16SrRNA gene to characterize the composition and structure of the microbiota in autism spectrum disorder (ASD). However, they do not always obtain consistent results; thus, conducting cross-study comparisons is necessary. This study sought to analyze the alteration of fecal microbiota and the diagnostic capabilities of gut microbiota biomarkers in individuals with ASD using the existing 16SrRNA microbial data and explore heterogeneity among studies. The raw sequence and metadata from 10 studies, including 1,019 samples, were reanalyzed. Results showed no significant difference in alpha diversity of fecal microbiota between ASD and the control group. However, a significant difference in the composition structure of fecal microbiota was observed. Given the large differences in sample selection and technical differences, the separation of fecal microbiota between ASD and controls was not observed. Subgroup analysis was performed on the basis of different country of origin, hypervariable regions, and sequencing platforms, and the dominant genera in ASD and healthy control groups were determined by linear discriminant analysis (LDA) of the effect size (LEfSe) algorithm and Wilcoxon rank-sum test. Machine learning analyses were carried out to determine the diagnostic capabilities of potential microbial biomarkers. A total of 12 genera were identified to distinguish ASD from control, and the AUC of the training set and verification set was 0.757 and 0.761, respectively. Despite cohort heterogeneity, gut microbial dysbiosis of ASD has been proven to be a widespread phenomenon. Therefore, fecal microbial markers are of great significance in diagnosing ASD diseases and possible candidates for further mechanistic study of the role of intestinal microbiota in ASD.

IMPORTANCE This study provides an updated analysis to characterize the gut microbiota in ASD using 16SrRNA gene high-throughput sequencing data from 10 publicly available studies. Our analysis suggests an association between the fecal microbiota and ASD. Sample selection and technical differences between studies may interfere with the species composition analysis of the ASD group and control group. By summarizing the results of 16SrRNA gene sequencing from multiple fecal samples, we can provide evidence to support the use of microbial biomarkers to diagnose the occurrence of ASD. Our study provides a new perspective for further revealing the correlation between gut microbiota and ASD from the perspective of 16SrRNA sequencing in larger samples.