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<p>Alzheimer’s disease (AD) is a complex neurodegenerative disorder. Recent studies have demonstrated that the dysregulated metabolism of metal ions, particularly copper and iron imbalance in the brains of AD patients,&#xa0; is closely associated with the pathogenesis of Alzheimer’s disease. Based on GEO database and GeneCards database, this study screened and identified 1191 AD-related differentially expressed genes (DEGs), as well as 671 and 682 genes highly associated with copper and iron metabolism. The intersection analysis yielded 26 differentially expressed copper- and iron-related genes (DECIGs). GO and KEGG enrichment analysis indicated that most of them were involved in cellular energy metabolism. PPI network analysis identified 12 hub genes, five of which had AUC values greater than 0.8, indicating strong diagnostic potential. qRT-PCR validation revealed that three hub genes (<i>GOT1</i>, <i>LDHA</i>, and <i>UQCRFS1</i>) showed significant differences in the expression levels between the AD and the control group. The multigene diagnostic model based on the three genes exhibited considerable diagnostic value.</p> Graphical Abstract <p>Twenty-six differentially expressed copper- and iron-related genes were screened based on the GEO and Genecards database. Twelve hub genes were selected by PPI network analysis. Three genes as AD potential biomarkers were identified by ROC diagnostic curves and qRT-PCR validation.</p> <p></p>

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Identification of Copper and Iron Metabolism Related Biomarkers in Alzheimer’s Disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月18日

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  • Dandan Huang,
  • Shasha Huang,
  • Yunhan Gao,
  • Wei Xu

摘要

Alzheimer’s disease (AD) is a complex neurodegenerative disorder. Recent studies have demonstrated that the dysregulated metabolism of metal ions, particularly copper and iron imbalance in the brains of AD patients,  is closely associated with the pathogenesis of Alzheimer’s disease. Based on GEO database and GeneCards database, this study screened and identified 1191 AD-related differentially expressed genes (DEGs), as well as 671 and 682 genes highly associated with copper and iron metabolism. The intersection analysis yielded 26 differentially expressed copper- and iron-related genes (DECIGs). GO and KEGG enrichment analysis indicated that most of them were involved in cellular energy metabolism. PPI network analysis identified 12 hub genes, five of which had AUC values greater than 0.8, indicating strong diagnostic potential. qRT-PCR validation revealed that three hub genes (GOT1, LDHA, and UQCRFS1) showed significant differences in the expression levels between the AD and the control group. The multigene diagnostic model based on the three genes exhibited considerable diagnostic value.

Graphical Abstract

Twenty-six differentially expressed copper- and iron-related genes were screened based on the GEO and Genecards database. Twelve hub genes were selected by PPI network analysis. Three genes as AD potential biomarkers were identified by ROC diagnostic curves and qRT-PCR validation.