Metabolite Profiles from 67 Carotid Artery Plaques for Stroke Risk Biomarker Discovery

A non-targeted metabolomics analysis of 67 carotid artery plaque samples (40 stable, 27 unstable) collected for a study published in 2026. The dataset contains metabolite signatures used to identify 98 differentially abundant metabolites and potential biomarkers for unstable plaques. It was created by Jia-Qi Ma and is shared under a CC-BY-4.0 license.

Use Cases

• Training classification models to predict plaque stability based on metabolite profiles.
• Identifying key metabolic pathways (e.g., cGMP-PKG signaling) associated with unstable plaques.
• Screening for potential metabolic biomarkers to improve stroke risk prediction.

Strengths

• Includes data from 67 clinical samples with clear classification into stable (40) and unstable (27) plaques.
• Analysis identified 98 significantly differentially abundant metabolites and 43 linked to specific pathways.
• Four distinct machine learning algorithms (RF, SVM, LASSO, LR) were applied for feature analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• The dataset is very small (13.3 KB), indicating limited scope and likely summary-level results.

Provenance

Source

figshare

Collection Method

Non-targeted metabolomics analysis of clinical plaque samples.

Freshness

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