Integrative metagenomic and metabolomic analysis reveals a gut microbiota-metabolite-immune axis in pediatric...

This study aimed to delineate the alterations in the gut microbiome and host amino acid metabolism in children with comorbid allergic rhinitis and functional constipation (ARFC), and to explore their links with clinical allergy markers.

We performed shotgun metagenomic sequencing and amino acid-targeted metabolomics on fecal samples from 19 children with ARFC and 16 age-matched healthy controls (HC). Microbial community structure, differentially abundant taxa, and metabolic profiles were analyzed. Integrative analyzes, including correlation networks and machine learning modeling, were employed to investigate microbiota-metabolite-host interactions.

Significant beta-diversity distinction was found between ARFC and HC gut microbiota (PCoA R²=0.228, P = 0.001). ARFC children exhibited enrichment of mucin-degrading Bacteroidota (e.g., Bacteroides, Phocaeicola) and depletion of beneficial Bacillota (e.g., Bifidobacterium, Blautia). Metabolomics identified 50 differentially abundant metabolites, with widespread downregulation of immunomodulatory amino acids including L-glutamine and γ-aminobutyric acid (GABA). Enriched pathways involved mTOR and FoxO signaling, and neurotransmitter synapses. Integration revealed significant correlations between specific microbial genera (e.g., Bacteroides, Proteus) and metabolites (e.g., kynurenine), and between gut species (e.g., Bacteroides thetaiotaomicron) and serum IgE levels. A machine learning model integrating key microbial and metabolic features, evaluated under a rigorous leave-one-out cross-validation framework, demonstrated robust discriminative performance in this cohort (AUC = 0.946).

This multi-omics study unveils a distinct "gut dysbiosis-metabolite dysregulation-immune dysfunction" axis in ARFC children. The synergistic shift towards a mucolytic, pro-inflammatory microbiota alongside deficient immunomodulatory metabolite production, which correlates with clinical allergy markers, provides a novel mechanistic framework for this comorbidity and highlights potential diagnostic biomarkers for future validation.