Gut Microbiota and Metabolomic Profiles in Myasthenia Gravis Patients and Controls

A 2026 study by Yunan Shan profiles fecal samples from 29 myasthenia gravis patients and 10 healthy controls using 16S rRNA sequencing and untargeted metabolomics. The dataset includes results on 232 discriminative microbial taxa and 567 altered metabolites, identifying potential diagnostic biomarkers. It was published on figshare under a CC-BY-4.0 license.

Use Cases

• Training a biomarker classification model based on the 567 altered metabolites identified.
• Analyzing correlations between microbial taxa like Faecalibacterium prausnitzii and clinical severity scores.
• Investigating metabolic pathway disturbances (e.g., bile secretion, sphingolipid signaling) in autoimmune disorders.
• Validating the reported Random Forest metabolite model that achieved an AUC of 1.0 for patient classification.

Strengths

• Includes data from a controlled study with 29 patients and 10 healthy controls.
• Reports specific findings on 232 discriminative microbial taxa and 567 altered metabolites.
• Integrates two profiling techniques: 16S rRNA sequencing and UHPLC-Q-TOF MS metabolomics.

Limitations

• The dataset is very small at 27.2 KB, suggesting it may contain summary results rather than raw sequence or spectral data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Sample size is limited to 39 total participants, which may affect statistical generalizability.

Provenance

Source

Yunan Shan via figshare.

Collection Method

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

Freshness

Last updated 2026-04-23 05:35:50.