PXDN Biomarker Study: Transcriptomic Data for Coronary Artery Calcification

Yi Lu's research dataset contains transcriptomic data from two cohorts (GSE58150 and GSE211752) used to identify metabolic reprogramming features and biomarkers for coronary artery calcification. The discovery cohort included 8 CAC and 8 control samples, while the validation cohort comprised 6 CAC and 6 control samples. The study identified 138 upregulated and 104 downregulated genes, with PXDN highlighted as a promising circulating biomarker.

Use Cases

• Train biomarker prediction models based on differential gene expression profiles
• Analyze metabolic pathway alterations based on gene set enrichment analysis results
• Validate diagnostic performance of candidate biomarkers like PXDN using ROC curve data
• Study gene regulatory networks based on transcription factor and miRNA interactions identified
• Investigate immune-related pathway activation associated with CAC

Strengths

• Includes a validation cohort (GSE211752) with 6 CAC and 6 control samples for biomarker confirmation
• Identified a specific biomarker (PXDN) with strong diagnostic performance (AUC 0.95 in discovery cohort)
• Functional enrichment analysis indicated concrete alterations in amino acid and vitamin metabolism
• Analysis includes in vivo validation in a CAC mouse model

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Dataset size is 601.1 KB, indicating a limited scope

Provenance

Source

figshare

Collection Method

Transcriptomic datasets (GSE58150 and GSE211752) were analyzed after excluding poor-quality samples.

Freshness

Last updated 2026-04-10 06:02:13