Gut Microbiota and Metabolomic Profiles for 39 Myasthenia Gravis Patients and Controls

29 myasthenia gravis patients and 10 healthy controls had their gut microbiota and fecal metabolome profiled using 16S rRNA sequencing and UHPLC-Q-TOF MS metabolomics. The study identified 232 discriminative microbial taxa and 567 altered metabolites, including short-chain fatty acids and bile acids. Author Yunan Shan uploaded the findings to figshare in April 2026 under a CC-BY-4.0 license.

Use Cases

• Train a Random Forest classifier for disease diagnosis based on the 567 altered metabolite features.
• Analyze Spearman correlations between microbial taxa (e.g., Ruminococcus) and metabolites (e.g., butanoic acid) to explore functional relationships.
• Investigate pathway implications for cholinergic synapse or bile secretion using KEGG analysis results.
• Validate the depletion of specific commensals like Faecalibacterium prausnitzii in autoimmune gut dysbiosis models.

Strengths

• Integrated multi-omics data from 16S rRNA sequencing and untargeted metabolomics on the same cohort.
• Reported a Random Forest metabolite model with an AUC of 1.0 for distinguishing patients from controls.
• Analysis includes statistical thresholds (VIP > 1.0, P < 0.05, FDR q < 0.05) and correlation tests with clinical severity scores.

Limitations

• The dataset is small in scale (284.1 KB), containing results from only 39 total subjects.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect geographic or demographic bias inherent to the single-study cohort.

Provenance

Source

Yunan Shan

Collection Method

16S rRNA sequencing and UHPLC-Q-TOF MS metabolomics performed on fecal samples.

Freshness

Last updated 2026-04-23 05:35:53; freshness should be verified.