缓慢发展的神经系统疾病阿尔茨海默病(AD)没有公认的病因。生物信息学调查验证了AD发展的铜代谢指标。GEO贡献了AD相关数据集GSE1297和GSE5281。差异表达分析和WGCNA证实了生物标志物候选基因。使用单样品基因组富集分析对AD和对照样品中的每种免疫细胞类型进行评分。接收机工作特性(ROC)分析,短时间序列表达式矿工(STEM)分组,对照和AD样品之间的表达分析发现影响AD进展的铜代谢指标。我们测试临床样本和细胞功能以确保研究的正确性。通过starBase预测靶向生物标记的miRNA和lncRNA。信任网站预期生物标志物靶向转录因子。最后,Cytoscape构建了TF/miRNA-mRNA和lncRNA-miRNA网络。DGIdb数据库预测了生物标志物靶向药物。我们鉴定了57个差异表达的铜代谢相关基因(DE-CMRGs)。接下来,确定了14个影响AD进展的铜代谢指标:CCK,ATP6V1E1,SYT1,LDHA,PAM,HPRT1,SCG5,ATP6V1D,GOT1,NFKBIA,SPHK1,MITF,BRCA1和CD38。然后用两种miRNA(hsa-miR-34a-5p和34c-5p)建立TF/miRNA-mRNA调控网络,六个TF(NFKB1、RELA、MYC,HIF1A,JUN,和SP1),和四种生物标志物。DGIdb数据库包含171种针对10种铜代谢相关生物标志物(BRCA1,MITF,NFKBIA,CD38,CCK2,HPRT1,SPHK1,LDHA,SCG5和SYT1)。铜代谢生物标志物CCK,ATP6V1E1,SYT1,LDHA,PAM,HPRT1,SCG5,ATP6V1D,GOT1,NFKBIA,SPHK1,MITF,BRCA1和CD38改变AD进展,为疾病病理生理学和新型AD诊断和治疗奠定基础。
The slow-developing neurological disorder Alzheimer\'s disease (AD) has no recognized etiology. A bioinformatics investigation verified copper metabolism indicators for AD development. GEO contributed AD-related datasets GSE1297 and GSE5281. Differential expression analysis and WGCNA confirmed biomarker candidate genes. Each immune cell type in AD and control samples was scored using single sample gene set enrichment analysis. Receiver Operating Characteristic (ROC) analysis, short Time-series Expression Miner (STEM) grouping, and expression analysis between control and AD samples discovered copper metabolism indicators that impacted AD progression. We test clinical samples and cellular function to ensure study correctness. Biomarker-targeting miRNAs and lncRNAs were predicted by starBase. Trust website anticipated biomarker-targeting transcription factors. In the end, Cytoscape constructed the TF/miRNA-mRNA and lncRNA-miRNA networks. The DGIdb database predicted biomarker-targeted drugs. We identified 57 differentially expressed copper metabolism-related genes (DE-CMRGs). Next, fourteen copper metabolism indicators impacting AD progression were identified: CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38. A TF/miRNA-mRNA regulation network was then established with two miRNAs (hsa-miR-34a-5p and 34c-5p), six TFs (NFKB1, RELA, MYC, HIF1A, JUN, and SP1), and four biomarkers. The DGIdb database contained 171 drugs targeting ten copper metabolism-relevant biomarkers (BRCA1, MITF, NFKBIA, CD38, CCK2, HPRT1, SPHK1, LDHA, SCG5, and SYT1). Copper metabolism biomarkers CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38 alter AD progression, laying the groundwork for disease pathophysiology and novel AD diagnostic and treatment.