Gene expression datasets, clinical validation data, and analytical scripts for HDAC6/XK as novel oxidative stress-related diagnostic biomarkers in acute myocardial infarction

This dataset supports the research article "Identification of HDAC6 and XK as a novel gene signature associated with oxidative stress for early diagnosis of acute myocardial infarction". The data package includes three core components: (1) Processed gene expression data from GEO datasets GSE29111 and GSE97320 (platform: GPL570), including normalized expression matrices, differentially expressed genes (DEGs) lists, and weighted gene co-expression network analysis (WGCNA) module genes; (2) Clinical validation data: raw Ct values of quantitative real-time PCR (RT-qPCR) for HDAC6, XK, and reference gene GAPDH in peripheral blood samples from 10 acute myocardial infarction (AMI) patients and 10 non-AMI controls (matched for age and sex), along with melting curve verification images and sample information sheets; (3) Analytical scripts: R code for differential expression analysis (limma), WGCNA, protein-protein interaction (PPI) network construction, machine learning screening (random forest, LASSO regression, support vector machine), Gene Ontology (GO) enrichment, Gene Set Enrichment Analysis (GSEA), and ROC curve analysis. All data were generated following standardized experimental and analytical protocols, with ethical approval from the Ethics Committee of Gansu Provincial Central Hospital (File No.: (2023) GSFY [30]) and written informed consent obtained from all clinical participants. This dataset is reusable for further exploration of AMI-related molecular mechanisms, validation of diagnostic biomarkers, and development of targeted therapeutic strategies.