生物信息学和实验验证识别用于诊断阿尔茨海默病的生物标志物
Hui Liu1,2, Chenye Li1, Congchen Zhai1,3
1The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Frontiers in aging neuroscience
|August 22, 2025
概括
这项研究确定了四种潜在的阿尔茨海默病 (AD) 生物标志物,并建议c-Myc作为阿尔茨海默病诊断的有希望的血液生物标志物,提高早期检测能力.
科学领域:
- 基因组学和生物信息学
- 神经科学
- 生物标志物发现
背景情况:
- 阿尔茨海默病 (AD) 呈现复杂的机制和逐渐的认知衰退.
- 目前对阿尔茨海默病的诊断方法缺乏简单性和可靠性,
研究的目的:
- 使用生物信息学方法识别阿尔茨海默病的新型诊断生物标志物.
- 为早期诊断阿尔茨海默病提供新的见解.
主要方法:
- 使用GSE63060转录组数据集和应用生物信息学工具,包括WGCNA,PPI网络和机器学习.
- 鉴定了核心基因并分析了上游转录因子c-Myc.
- 使用ELISA和ROC曲线分析验证了c- Myc在AD患者和对照人群的血清样本中的诊断潜力.
主要成果:
- 确定了与阿尔茨海默病相关的四个枢纽基因 (RPL36AL,NDUFA1,NDUFS5,RPS25).
- 在阿尔茨海默病患者和对照组之间发现了c- Myc蛋白度的显著差异 (p < 0. 001).
- c- Myc的诊断潜力为87. 8%,特异性为51.2%,AUC为0. 753.
结论:
- RPL36AL,NDUFA1,NDUFS5和RPS25显示为阿尔茨海默病的潜在生物标志物.
- c-Myc是阿尔茨海默病诊断的有希望的血液生物标志物,具有独立的诊断意义.
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