在欧洲人口中预测与年龄相关的阿尔茨海默病风险的多基因危险评分:开发和验证
Bayram Cevdet Akdeniz1,2, Shahram Bahrami1, Espen Hagen1
1Centre for Precision Psychiatry, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
medRxiv : the preprint server for health sciences
|August 6, 2025
概括
针对阿尔茨海默病 (AD) 的新型多基因危险评分 (PHS) 模型显示,对欧洲人口发病年龄的预测准确度有所提高. 这种增强的模型有助于针对AD风险的早期干预策略.
科学领域:
- 遗传学 是一个遗传学.
- 神经科学是一个神经科学.
- 生物统计学 生物统计学
背景情况:
- 多基因危险评分 (PHS) 模型预测与年龄相关的疾病风险.
- 阿尔茨海默病 (AD) 是一种复杂的疾病,早期预测至关重要.
- 现有的模型在准确预测AD发病年龄方面存在局限性.
研究的目的:
- 开发和评估一个改进的PHS模型来预测阿尔茨海默病发病年龄.
- 结合大量的遗传变异来提高预测准确度.
- 将新模型的性能与欧洲人口中现有的替代方案进行比较.
主要方法:
- 开发PHS模型 (EADB720) 使用720个遗传变异,包括APOE等位基因.
- 使用了欧洲阿尔茨海默氏症和痴呆症生物库 (EADB) 样本 (n=42,120).
- 在独立数据集 (HUSK,DemGene,ADNI) 中用于模型开发和验证的Elastic Net规范化的Cox回归.
主要成果:
- EADB720模型显示,在欧洲人群中,阿尔茨海默病发病年龄的预测准确度显著提高.
- 在风险分层方面实现了5.10至13.15之间的高赔率比率 (OR80/20).
- 在 ε3/3 个体中显示出更好的风险分层,并在独立数据集中成功验证了OR80/20 到10.00.00.
结论:
- EADB720 PHS模型显著提高了欧洲人口中与年龄相关的AD风险预测的准确性 (p<0.03).
- 准确预测AD发病年龄对于及时的临床干预和新药的实施至关重要.
- 这种改进的模型对管理阿尔茨海默病具有重大临床意义.
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