生物标志物 生物标志物
Julie K Wisch1, Nicole S McKay2, Matthew D Zammit3
1Washington University in St. Louis School of Medicine, St. Louis, MO, USA.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 26, 2025
概括
采样代局部近似 (SILA) 算法准确估计自自体主导性阿尔茨海默病 (ADAD) 中的粉样蛋白阳性以来的时间. 这项阿尔茨海默病 (AD) 研究使得更好的疾病阶段和AD形式之间的比较成为可能.
科学领域:
- 神经学 神经学
- 生物医学成像技术 生物医学成像技术
- 阿尔茨海默氏症疾病研究研究
背景情况:
- 阿尔茨海默氏病 (AD) 病理在几十年内进展,需要准确的治疗时间的分期.
- 自体主导AD (ADAD) 允许通过估计的症状发作年数 (EYO) 预测症状发作,但这种方法缺乏广泛的适用性.
- 对ADAD的验证,广泛适用的时间过程对于了解疾病进展和干预策略至关重要.
研究的目的:
- 验证采样代局部近似 (SILA) 算法,使用具有已知的疾病时间进程的队列.
- 建立一种可靠的方法,以使用纵向PET数据来估计自自体主导AD (ADAD) 的粉样蛋白阳性 (A时间) 的时间.
主要方法:
- 在长度ADAD队列 (N=316) 中使用PET数据评估A时间.
- 对比新阳性个体的粉样蛋白阳性 (A+) 的SILA预测年龄与A+的观察年龄.
- 利用线性回归和通用添加模型来比较A时间和EYO与症状发作和认知表现相关.
主要成果:
- SILA在预测粉样蛋白阳性时的年龄方面显示了1.15年的平均平均误差.
- 在A+时的SILA估计年龄解释了症状发作时估计年龄差异的39% (β=0.918,p<0.0001).
- A时间解释了19%的认知变异,而EYO解释了43%,表明认知和疾病进展标志物之间存在非线性关联.
结论:
- 该SILA算法提供了一个有效的时间估计从ADAD中粉样蛋白的阳性.
- 这种验证可以直接比较ADAD分期与其他AD形式,克服EYO的局限性.
- 在临床前阿尔茨海默氏症持续时间上存在显著的异质性,不仅仅是粉样蛋白状况,这突显了阿尔茨海默氏症进展的复杂性.
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