Gut Microbiome and Metabolite Profiles in Children with Allergic Rhinitis and Constipation

Shotgun metagenomic sequencing and amino acid-targeted metabolomics data from fecal samples of 19 children with comorbid allergic rhinitis and functional constipation (ARFC) and 16 healthy controls. The dataset was created by Hui Wu and last updated in May 2026. It includes results from integrative analysis, correlation networks, and a machine learning model.

Use Cases

• Train diagnostic classifiers based on integrated microbial and metabolic features mentioned in the description.
• Analyze correlations between specific microbial genera (e.g., Bacteroides) and immunomodulatory metabolites (e.g., kynurenine).
• Investigate links between gut species (e.g., Bacteroides thetaiotaomicron) and clinical allergy markers like serum IgE.
• Study altered metabolic pathways (e.g., mTOR and FoxO signaling) in pediatric allergic conditions.

Strengths

• Includes multi-omics data from shotgun metagenomics and targeted metabolomics on the same cohort.
• Integrative analysis revealed a machine learning model with an AUC of 0.946 under leave-one-out cross-validation.
• Identified 50 differentially abundant metabolites between patient and control groups.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 11.4 KB, indicating limited primary data or a summary document.

Provenance

Source

figshare

Collection Method

Shotgun metagenomic sequencing and amino acid-targeted metabolomics performed on fecal samples.

Freshness

Last updated 2026-05-26 08:16:48; freshness should be verified.