基础科学和病原发生学
Ricky Lali1, Shihong Mao2, Basilio Cieza3
1Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 25, 2025
概括
这项研究引入了第一个罕见变异多基因风险评分,用于晚发性阿尔茨海默病 (LOAD),证明了其在预测不同人群中LOAD风险方面的有效性. 新的评分,rvPRS-AD,利用罕见的遗传变异来改善风险分层.
科学领域:
- 遗传学 是一个遗传学.
- 神经科学是一个神经科学.
- 计算生物学 计算生物学
背景情况:
- 晚发性阿尔茨海默氏病 (LOAD) 构成了全球重大健康挑战,预计到2050年,这种病例将增加三倍.
- 遗传因素对LOAD变异的贡献超过60%,但使用常见变异的传统风险评分在不同人群中具有有限的预测能力.
- 对于LOAD的多基因框架中的罕见破坏性变异的预测潜力以前没有被评估.
研究的目的:
- 开发第一个罕见变异多基因LOAD风险评分 (rvPRS-AD).
- 评估rvPRS-AD.的跨祖先预测能力.
- 评估rvPRS-AD与常见变异预测因子和APOEε4状态的独立性.
主要方法:
- 使用完整基因组适应的RV-EXCALIBER方法开发的rvPRS-AD用于罕见变异基因负载测试.
- 利用欧洲LOAD病例和gnomAD控制数据来识别风险转移基因.
- 在西班牙裔参与者中构建了rvPRS-AD,通过对每个基因的罕见破坏性变异的负担进行加权.
主要成果:
- 确定ABCA7是与LOAD最强烈相关的基因 (OR = 1.40,p=1×10−4).
- rvPRS-AD显示出显著的跨祖先预测能力,在西班牙裔中增加了38%的LOAD几率 (1-SD增加).
- 该得分仍然独立于APOEε4状态的预测性,并确定了极端风险的个体 (概率增加≥2倍).
结论:
- rvPRS-AD是第一个利用罕见变异在多基因框架中用于LOAD风险预测的遗传仪器.
- 这种方法可以在祖先多样化的群体中提供更好的预测.
- rvPRS-AD提供了一个新的工具,用于独立于常见变异的LOAD风险分层.
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