Integrated Transcriptomic and Metabolomic Analysis for Acute Ischemic Stroke Biomarkers

A research dataset identifying candidate genes and metabolites associated with acute ischemic stroke (AIS). The study integrated transcriptomic data from the GSE16561 dataset and metabolomic data from a cohort of 20 individuals (10 AIS patients and 10 controls). It was authored by Jiayan Zhang and last updated in April 2026.

Use Cases

• Validate the diagnostic performance of identified key genes (ITGAM, TLR4, MMP9, STAT3, TLR2) based on the study's findings.
• Explore immune infiltration correlations, such as the negative correlation between ITGAM and memory B cells, mentioned in the description.
• Investigate enriched metabolic pathways like steroid hormone biosynthesis, HIF-1, and FoxO signaling pathways.
• Screen candidate drugs, including paregoric and celecoxib, predicted from the molecular network analysis.

Strengths

• Integrated multi-omics approach combining transcriptomic and metabolomic data.
• Includes validation steps via RT-qPCR and diagnostic evaluation for identified genes.
• Clinical cohort details are provided, including patient demographics (age, gender) and stroke subtypes.

Limitations

• Dataset is very small (19.6 KB), suggesting limited raw data or a summary document.
• Column-level documentation is absent; field semantics must be inferred after download.
• The primary data file is a DOCX document, which may not be a standard structured data format for analysis.

Provenance

Source

figshare, authored by Jiayan Zhang.

Collection Method

Analysis of public transcriptomic dataset GSE16561 and metabolomic sequencing of a clinical cohort.

Time Range

Blood samples were obtained from AIS patients within 24 hours of stroke onset.

Freshness

Last updated 2026-04-15 04:21:49; freshness should be verified.

Geography

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