Metabolomic Signatures of Unstable Carotid Plaques from 67 Patient Samples

Jia-Qi Ma published metabolomics data from 67 carotid artery plaque samples (40 stable, 27 unstable) on figshare in May 2026. The dataset contains results from a non-targeted metabolomics analysis identifying 98 differentially abundant metabolites. Four machine learning algorithms were used to construct feature analysis models and screen for potential metabolic biomarkers associated with unstable plaques.

Use Cases

• Train a biomarker classifier for unstable plaques based on the 98 differentially abundant metabolites.
• Validate machine learning models for feature selection using the described RF, SVM, LASSO, and LR algorithms.
• Investigate metabolic pathway associations, such as the cGMP-PKG signaling pathway, mentioned in the KEGG enrichment results.
• Explore relationships between specific metabolites and pathways using the described network diagram of 43 metabolites.

Strengths

• Data is derived from 67 clinical samples, providing a basis for comparative analysis.
• The analysis identified 98 specific metabolites significantly associated with unstable plaques.
• Results include pathway enrichment analysis linking metabolites to specific biological processes.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 20.5 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Non-targeted metabolomics analysis performed on carotid artery plaque tissue samples.

Freshness

Last updated 2026-05-12 04:20:10; freshness should be verified.