整合等离子体,MRI和认知生物标志物,以个性化预测认知领域的衰退
Elaheh Moradi1, Robert Dahnke2, Vandad Imani3
1A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio 70150, Finland.
Neurobiology of aging
|July 25, 2025
概括
血生物标志物和MRI在预测没有痴呆症的个体的认知衰退方面表现有前途. 这些标志物,特别是记忆,可以帮助预测阿尔茨海默病的早期进展.
科学领域:
- 神经科学和神经病学 神经科学和神经病学
- 生物标志物发现发现
- 机器学习在医学中的应用
背景情况:
- 血生物标志物与认知表现和阿尔茨海默病 (AD) 的下降有关.
- 早期发现认知衰退对于及时干预至关重要.
- 需要采取非侵入性措施来补充现有的诊断工具.
研究的目的:
- 调查血生物标志物的预测价值与非侵入性措施相结合,在没有痴呆症的个体中研究认知衰退.
- 开发和评估一种多式机器学习方法,用于预测各个认知领域的认知衰退率.
- 评估这些预测因素在预测进展到轻度认知障碍 (MCI) 或痴呆症方面的相关性.
主要方法:
- 开发了一种多式机器学习模型,该模型包含了血生物标记物 (粉样β 42/40比 (Aβ42/40),酸化tau 181 (p-tau181),神经丝光 (NfL),MRI,人口统计,APOE4状态和认知评估.
- 模型旨在预测记忆,执行功能,语言和视觉空间能力的认知衰退率.
- 交叉验证用于评估预测和实际认知衰退率之间的相关性.
主要成果:
- 预测与实际认知衰退率的交叉验证相关性是:0.50 (记忆),0.49 (语言),0.42 (执行功能) 和0.44 (视觉空间能力).
- 磁力共振成像显示出比单独的血生物标志物具有更大的预测重要性.
- 在等离子体生物标志物中,NfL和p-tau181显示出比Aβ42/40.0更高的预测值. 这些生物标志物显著增强了对记忆衰退和痴呆症进展的预测模型.
结论:
- 血生物标志物,特别是当与MRI,人口统计,APOE4状态和认知测量相结合时,显示出预测没有痴呆症的个体内记忆衰退的巨大潜力.
- 多式联络数据的结合在评估痴呆症进展风险方面是有效的,即使在认知上没有受损的个体中也是如此.
- 血生物标志物,特别是AD特定的生物标志物,如p-tau181和NfL,对于预测与记忆相关的衰退和进展最有价值.
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