Data Sheet 1_Multi-omics analyses reveal significant differences in the gut microbiota and

31 children with Kawasaki disease and matched healthy controls provide fecal and blood samples analyzed via shotgun metagenomic sequencing and untargeted metabolomics. The dataset reveals significant reductions in microbial alpha diversity and richness in patients, alongside shifts in specific pathogenic and beneficial species and 49 differentially enriched metabolic pathways. Liangtao Zhao published this foundational resource on figshare in May 2026 under a CC-BY-4.0 license.

Use Cases

• Identify microbial biomarkers for Kawasaki disease based on species-level abundance changes.
• Investigate metabolic pathway dysregulation in pediatric vasculitis based on the 49 differentially enriched pathways.
• Correlate specific fecal and plasma metabolites with disease state based on listed compounds like butyrate, indole, and cholesterol.
• Compare gut microbiome diversity and composition between patient and control groups based on alpha diversity and richness metrics.

Strengths

• Includes multi-omics data from 31 patient-control pairs via shotgun metagenomics and untargeted metabolomics.
• Identifies 49 differentially enriched metabolic pathways and lists specific elevated and reduced microbial species and metabolites.
• Focuses on a pediatric population from Northwest China, a specific demographic and geographic context.

Limitations

• Row and column counts are unknown, limiting suitability assessment for specific analytical tasks.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is relatively small at 4.9 MB, which may limit the complexity of analyses.

Provenance

Source

Liangtao Zhao via figshare.

Collection Method

Fecal and blood samples collected from 31 children with Kawasaki disease and age/sex-matched healthy controls, analyzed with shotgun metagenomic sequencing and untargeted metabolomics.

Freshness

Last updated 2026-05-11 04:26:06.

Geography

Northwest China.