[Diversity and functional prediction of gut microbiota in children with autism spectrum disorder]

Resilience of human gut microbiomes in autism spectrum disorder: measured using stiffness network analysis

Autism spectrum disorder (ASD) affects an estimated 1%-2% of children worldwide, but its specific etiology remains unclear. In recent years, the gut microbiome's role in ASD pathogenesis has garnered increasing attention. However, the exact relationship between microbiota and ASD-such as which microbial species significantly impact disease onset and progression-remains unresolved, and effective methods to measure microbial interactions are still lacking. In this study, we introduce an innovative stiffness network analysis (SNA) method to quantify changes in microbial network structure and identify disease-specific microbial bacteria theoretically. The SNA method was applied to reanalyze eight ASD gut microbiome data sets, encompassing 898 ASD samples and 467 healthy control (HC) samples from 16S-rRNA sequencing data. Key findings include the following: (i) an "allies" biomarker subgroup consisting of Bacteroides plebeius, Sutterella, Lachnospira, and Prevotella copri was identified; (ii) a profile monitoring score of 0.72 for the biomarker subgroup, indicating significant relationship changes between HC and ASD states, and (iii) a P/N ratio of biomarker subgroup in ASD-associated gut bacteria that was three times higher than that of HC microbiomes. Additionally, we discuss the non-monotonic relationship alterations within microbial sub-communities in the ASD gut microbiome.IMPORTANCEIt is crucial to assess alterations in network structure in different biological states in order to promote health. The stiffness network allows for the exploration of species interactions and the measurement of resilience in complex microbial networks. The objective of this study was to develop a stiffness network analysis (SNA) method for evaluating the contribution of microbial bacteria in differentiating disease samples from healthy control samples by examining changes in network stiffness parameters. Furthermore, the SNA method was employed on both simulated and real autism spectrum disorder gut microbiome data sets to identify potential microbial biomarker subgroups, with a particular focus on the relationship alterations within microbial networks.

[Association between the structure of intestinal flora and inflammatory response in children with sepsis: a prospective cohort study]

OBJECTIVES

To investigate the structural characteristics of intestinal flora in children with sepsis and its association with inflammatory response.

METHODS

A prospective cohort study was conducted. The children with sepsis who were admitted from December 2021 to January 2023 were enrolled as the sepsis group, and the children with non-sepsis who were admitted during the same period were enrolled as the non-sepsis group. The two groups were compared in terms of the distribution characteristics of intestinal flora, peripheral white blood cell count (WBC), C reactive protein (CRP), and cytokines, and the correlation of the relative abundance of fecal flora with WBC, CRP, and cytokines was analyzed.

RESULTS

At the genus level, compared with the non-sepsis group, the sepsis group had significantly lower relative abundance of Akkermansia, Ruminococcus, and Alistipes and significantly higher relative abundance of Enterococcus, Streptococcus, and Staphylococcus (P<0.05). At the phylum level, Proteobacteria was the dominant phylum (37.46%) in the group of children with a score of ≤70 from the Pediatric Critical Illness Score (PICS), and Firmicutes was the dominant phylum in the group of children with a score of 71-80 or 81-90 from the PICS (72.20% and 43.88%, respectively). At the genus level, among the 18 specimens, 5 had a relative abundance of >50% for a single flora. Compared with the non-sepsis group, the sepsis group had significant higher levels of WBC, CRP, interleukin-6 (IL-6), interleukin-10 (IL-10), and tumor necrosis factor-α (P<0.05). The Spearman's rank correlation analysis showed that at the genus level, the relative abundance of Ruminococcus, Alistipes, and Parasutterella in the sepsis group was negatively correlated with the levels of WBC, CRP, and IL-6 (P<0.05); the relative abundance of Enterococcus was positively correlated with the CRP level (P<0.01); the relative abundance of Streptococcus and Staphylococcus was positively correlated with the levels of CRP and IL-6 (P<0.05); the relative abundance of Streptococcus was positively correlated with WBC (P<0.05).

CONCLUSIONS

Intestinal flora disturbance is observed in children with sepsis, and its characteristics vary with the severity of the disease. The structural changes of intestinal flora are correlated with inflammatory response in children with sepsis.

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.