生物标志物 生物标志物
Alberto Jaramillo-Jimenez1,2,3,4, Yorguin Jose Mantilla-Ramos2,4,5, Diego Tovar1,6
1Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 24, 2025
概括
休息状态EEG分析揭示了神经退行性疾病中明显的模式. 莱维体痴呆症显示脑电波减慢和非周期性活动增加,而阿尔茨海默病则表现出较轻微的异常.
科学领域:
- 神经科学是一个神经科学.
- 生物标志物 生物标志物
- 电脑电图 (电脑电图) 是一种脑电图.
背景情况:
- 静止状态EEG (rsEEG) 的α节律变化是神经退行性疾病 (NDD) 的潜在生物标志物.
- 在光谱分析中,rsEEG的非周期性成分经常被忽视.
- 多中心研究面临着批量效应的挑战,需要协调以进行可靠的分析.
研究的目的:
- 在各种NDD中区分rsEEG振荡和无周期变化.
- 通过协调,减轻多中心rsEEG数据中的批量效应.
- 为了识别特定的EEG签名对于像Lewy体痴呆症 (LBD) 和阿尔茨海默病 (AD) 这样的疾病.
主要方法:
- 来自12个地点的1750名受试者的rsEEG数据使用reComBat.com进行了预处理和协调.
- 振荡和非周期性参数从协调后方功率频谱中使用specparam提取.
- 分析了群体差异,使用引导对对对比,排列测试和后勤回归.
主要成果:
- 协调有效地减少了rsEEG后置功率频谱中的批量效应.
- 与其他组相比,莱维体痴呆症 (LBD) 的特点是更的无周期性参数和较低的振荡中心频率.
- 与健康对照组 (HC) 和帕金森病 (PD) 相比,阿尔茨海默氏病 (AD) 的振荡阿尔法功率降低.
结论:
- 数据协调有效地减轻了rsEEG光谱分析中的批量效应.
- LBD表现出显著的振荡减速和增加的非周期性活动.
- 阿尔茨海默病呈现出振荡和非周期性异常,尽管与LBD相比,效果大小较小.
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