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<p>Research has shown that impaired copper metabolism is a key factor in the onset and progression of ischemic stroke (IS). This study aimed to identify biomarkers associated with copper metabolism-related genes (CMRGs) in IS patients, potentially aiding the development of targeted therapies. Data were sourced from publicly available databases. Biomarkers were identified through differential expression analysis, weighted gene co-expression network analysis (WGCNA), Mendelian randomization (MR), least absolute shrinkage and selection operator (LASSO), and gene expression analyses. The diagnostic performance of these biomarkers was assessed employing receiver operating characteristic (ROC) analysis. A nomogram was then developed and evaluated based on these biomarkers. Subsequently, functional enrichment, immune infiltration, drug prediction, and molecular docking analyses were performed to explore the potential molecular mechanisms underlying IS. In our study, CXCL16, ST3GAL4, and ACTA2 were identified as biomarkers for IS, all showing significantly higher expression in IS samples. The area under the curve (AUC) values for all biomarkers exceeded 0.80, indicating excellent diagnostic potential. A nomogram was developed and validated, with the calibration curve confirming its effective ability to predict IS risk (<i>P</i> = 0.412 in the Hosmer–Lemeshow test). All biomarkers were significantly co-enriched in the "lysosome" pathway. Furthermore, 16 immune cell types with differential infiltration were identified, with all biomarkers positively correlating with neutrophils and negatively correlating with activated B cells. Additionally, 89 drugs targeting these biomarkers were identified, like benzene, Idose, and probucol. Molecular docking analysis revealed favorable binding energy between drugs and biomarkers, such as a binding energy of − 7.7&#xa0;kcal/mol between ACTA2 and probucol. CXCL16, ST3GAL4, and ACTA2 were identified as biomarkers for IS, offering valuable insights for the development of targeted therapies.</p>

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Identification of Biomarkers Associated With Copper Metabolism in Ischemic Stroke Through Bulk RNA Sequencing and Mendelian Randomization Analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月21日

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  • Ruizhe Yang,
  • Xin Zhou,
  • Zhiheng Zhao,
  • Jie Xu,
  • Zhang Yang

摘要

Research has shown that impaired copper metabolism is a key factor in the onset and progression of ischemic stroke (IS). This study aimed to identify biomarkers associated with copper metabolism-related genes (CMRGs) in IS patients, potentially aiding the development of targeted therapies. Data were sourced from publicly available databases. Biomarkers were identified through differential expression analysis, weighted gene co-expression network analysis (WGCNA), Mendelian randomization (MR), least absolute shrinkage and selection operator (LASSO), and gene expression analyses. The diagnostic performance of these biomarkers was assessed employing receiver operating characteristic (ROC) analysis. A nomogram was then developed and evaluated based on these biomarkers. Subsequently, functional enrichment, immune infiltration, drug prediction, and molecular docking analyses were performed to explore the potential molecular mechanisms underlying IS. In our study, CXCL16, ST3GAL4, and ACTA2 were identified as biomarkers for IS, all showing significantly higher expression in IS samples. The area under the curve (AUC) values for all biomarkers exceeded 0.80, indicating excellent diagnostic potential. A nomogram was developed and validated, with the calibration curve confirming its effective ability to predict IS risk (P = 0.412 in the Hosmer–Lemeshow test). All biomarkers were significantly co-enriched in the "lysosome" pathway. Furthermore, 16 immune cell types with differential infiltration were identified, with all biomarkers positively correlating with neutrophils and negatively correlating with activated B cells. Additionally, 89 drugs targeting these biomarkers were identified, like benzene, Idose, and probucol. Molecular docking analysis revealed favorable binding energy between drugs and biomarkers, such as a binding energy of − 7.7 kcal/mol between ACTA2 and probucol. CXCL16, ST3GAL4, and ACTA2 were identified as biomarkers for IS, offering valuable insights for the development of targeted therapies.