Multi-omics technology reveals the changes in gut microbiota to stimulate aromatic amino acid metabolism in children with allergic rhinitis and constipation.

BACKGROUND

Comorbid allergic rhinitis and constipation (ARFC) in children are associated with gut microbiota (GM) dysbiosis and metabolic perturbations; however, the underlying mechanistic interplay remains unclear.

OBJECTIVE

This multi-omics study aimed to characterize GM and fecal metabolomic signatures in preschool ARFC children and elucidate microbial-metabolite interactions driving dual symptomatology.

METHODS

Fecal samples from 16 ARFC and 15 healthy control (HC) children underwent high-throughput absolute quantification 16S rRNA sequencing and untargeted metabolomics. Differential taxa and metabolites were identified via LEfSe and OPLS-DA (VIP > 1, false discovery rate (FDR) q < 0.05). Microbial-metabolite networks were reconstructed using genome-scale metabolic modeling and KEGG pathway analysis.

RESULTS

The ARFC group exhibited distinct β-diversity (P = 0.031), marked by elevated Hungatella, Tyzzerella, and Bifidobacterium longum (P < 0.05). Metabolomics revealed upregulated aromatic amino acids (AAAs), neurotransmitters, and bile acids (FDR q < 0.05), with enrichment in tryptophan/tyrosine pathways (P < 0.01). Bioinformatic modeling linked Hungatella to tryptophan hydroxylase (EC:1.14.16.4), driving serotonin synthesis, and Tyzzerella to indoleamine 2,3-dioxygenase (EC:1.13.11.52), promoting kynurenine production. Bifidobacterium longum correlated with phenylalanine hydroxylase (EC:1.14.16.1), enhancing phenylalanine derivatives. A combined GM-metabolite diagnostic model demonstrated robust accuracy (AUC = 0.8).

CONCLUSION

GM dysbiosis in ARFC children activates AAA metabolism, generating neuroactive and pro-inflammatory metabolites that may exacerbate allergic and gastrointestinal symptoms. These findings highlight microbial-metabolite axes as therapeutic targets. Study limitations include cohort size and lack of disease-specific controls, necessitating validation in expanded cohorts.