Chen Yi-He, Lin Rong-Rong, Huang Hui-Feng, Xue Yan-Yan, Tao Qing-Qing
Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China.
Department of Neurology, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China.
Front Aging Neurosci. 2022 Jun 30;14:848180. doi: 10.3389/fnagi.2022.848180. eCollection 2022.
Biomarkers used for predicting longitudinal cognitive change in Alzheimer's disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.
A total of 430 subjects including, 96 cognitive normal (CN) with amyloid β (Aβ)-negative, 54 CN with Aβ-positive, 195 mild cognitive impairment (MCI) with Aβ-positive, and 85 AD with amyloid-positive (Aβ-positive are identified by CSF Aβ42/Aβ40 < 0.138). Aβ burden was evaluated by CSF and plasma Aβ42/Aβ40 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline.
Baseline CSF Aβ42/Aβ40 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 × time, plasma p-tau181 × time, CSF sTREM2 × time, and brain volumes × time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline.
Our study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.
用于预测阿尔茨海默病(AD)连续体纵向认知变化的生物标志物仍不明确。tau蛋白病理、神经炎症和神经退行性变是主要的候选预测指标。我们旨在通过阿尔茨海默病神经影像学倡议(ADNI)队列确定脑脊液(CSF)和血浆中这三个方面的生物标志物,以预测纵向认知状态。
共有430名受试者,包括96名淀粉样β蛋白(Aβ)阴性的认知正常(CN)者、54名Aβ阳性的CN者、195名Aβ阳性的轻度认知障碍(MCI)者和85名Aβ阳性的AD患者(CSF Aβ42/Aβ40<0.138确定为Aβ阳性)。通过CSF和血浆Aβ42/Aβ40比值评估Aβ负荷;通过CSF和血浆磷酸化tau蛋白(p-tau181)评估tau蛋白病理;通过CSF可溶性触发受体表达于髓样细胞2(sTREM2)和颗粒蛋白前体(PGRN)测量小胶质细胞活化;通过CSF和血浆总tau蛋白(t-tau)以及结构磁共振成像(MRI)测量神经退行性变;在随后8年中每年使用阿尔茨海默病评估量表认知13项量表(ADAS13)和简易精神状态检查表(MMSE)检查认知情况。应用线性混合效应模型(LME)评估生物标志物与纵向认知下降之间的相关性,以及它们对纵向认知下降预测的效应大小。
与CN相比,MCI和AD患者的基线CSF Aβ42/Aβ40比值降低,而CSF p-tau181和t-tau升高。与CN相比,MCI和AD患者的基线CSF sTREM2和PGRN没有显示出任何差异。MCI和AD组的基线脑体积(包括海马体、内嗅皮质、颞中叶和全脑)减小。对于纵向研究,CSF p-tau181×时间、血浆p-tau181×时间、CSF sTREM2×时间和脑体积×时间存在显著的交互作用,表明CSF、血浆p-tau181、CSF sTREM2和脑体积可以预测纵向认知恶化率。CSF sTREM2、CSF和血浆p-tau181具有相似的中等预测效果,而脑体积在预测认知下降方面显示出更强的效果。
我们的研究报告称,基线CSF sTREM2、CSF和血浆p-tau181以及结构MRI可以预测AD病理阳性受试者的纵向认知下降。血浆p-tau181可作为AD纵向认知下降预测的相对非侵入性可靠生物标志物。