Microglial Activation, Tau Pathology, and Neurodegeneration Biomarkers Predict Longitudinal Cognitive Decline in Alzheimer's Disease Continuum.
Microglial Activation, Tau Pathology, and Neurodegeneration Biomarkers Predict Longitudinal Cognitive Decline in Alzheimer's Disease Continuum.
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小胶质细胞激活、Tau病理和神经变性生物标记物可预测阿尔茨海默病患者的纵向认知功能下降。
DOI：
10.3389/fnagi.2022.848180
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发表时间：
2022
影响因子：
4.8
通讯作者：
中科院分区：
文献类型：
--
作者：
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然难以捉摸。 Tau 病理学、神经炎症和神经变性是主要的候选预测因子。我们的目的是确定脑脊液 (CSF) 和血浆中生物标志物的这三个方面，以利用阿尔茨海默病神经影像计划 (ADNI) 队列预测纵向认知状态。共有 430 名受试者，其中 96 名认知正常 (CN) β 淀粉样蛋白 (Aβ) 阴性，54 名 CN 伴有 Aβ 阳性，195 名轻度认知障碍 (MCI) 伴有 Aβ 阳性，85 名 AD 淀粉样蛋白阳性（Aβ 阳性通过 CSF Aβ42/Aβ40 < 0.138 鉴定为 Aβ 阳性）。通过脑脊液和血浆Aβ42/Aβ40比值评估Aβ负荷；通过脑脊液和血浆磷酸化 tau (p-tau181) 评估 tau 病理学；通过脑脊液可溶性 TREM2 (sTREM2) 和颗粒体蛋白前体 (PGRN) 测量小胶质细胞活化；通过脑脊液和血浆 t-tau 蛋白以及结构磁共振成像 (MRI) 测量神经退行性变；在接下来的 8 年里，每年都会使用阿尔茨海默氏病评估量表认知 13 项目量表 (ADAS13) 和简易精神状态检查 (MMSE) 对认知进行检查。应用线性混合效应模型（LME）来评估生物标志物与纵向认知衰退之间的相关性，以及它们对纵向认知衰退预测的影响大小。与 CN 相比，MCI 和 AD 中的基线 CSF Aβ42/Aβ40 比率降低，而 CSF p-tau181 和 t-tau 增加。与 CN 相比，基线 CSF sTREM2 和 PGRN 在 MCI 和 AD 方面没有表现出任何差异。 MCI 和 AD 组的基线脑体积（包括海马、内嗅、中颞叶和全脑）减少。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×时间存在显着的交互作用，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，而脑容量在预测认知能力下降方面表现出更强的效果。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能力下降。血浆 p-tau181 可作为 AD 纵向认知衰退预测的相对无创可靠的生物标志物。
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.
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影响因子：
5.3
作者：
Janelidze S;Zetterberg H;Mattsson N;Palmqvist S;Vanderstichele H;Lindberg O;van Westen D;Stomrud E;Minthon L;Blennow K;Swedish BioFINDER study group;Hansson O
通讯作者：
Hansson O
DOI：
10.1186/s13195-021-00772-0
发表时间：
2021-02-05
期刊：
Alzheimer's research & therapy
影响因子：
--
作者：
Coomans EM;Schoonhoven DN;Tuncel H;Verfaillie SCJ;Wolters EE;Boellaard R;Ossenkoppele R;den Braber A;Scheper W;Schober P;Sweeney SP;Ryan JM;Schuit RC;Windhorst AD;Barkhof F;Scheltens P;Golla SSV;Hillebrand A;Gouw AA;van Berckel BNM
通讯作者：
van Berckel BNM
DOI：
10.3233/jad-132489
发表时间：
2014
期刊：
Journal of Alzheimer's disease : JAD
影响因子：
--
作者：
Korecka M;Waligorska T;Figurski M;Toledo JB;Arnold SE;Grossman M;Trojanowski JQ;Shaw LM
通讯作者：
Shaw LM
DOI：
10.1186/s13195-022-00990-0
发表时间：
2022-03-29
期刊：
Alzheimer's research & therapy
影响因子：
--
作者：
Pichet Binette A;Palmqvist S;Bali D;Farrar G;Buckley CJ;Wolk DA;Zetterberg H;Blennow K;Janelidze S;Hansson O
通讯作者：
Hansson O
DOI：
10.1016/j.jalz.2018.01.010
发表时间：
2018-11
期刊：
Alzheimer's & dementia : the journal of the Alzheimer's Association
影响因子：
--
作者：
Hansson O;Seibyl J;Stomrud E;Zetterberg H;Trojanowski JQ;Bittner T;Lifke V;Corradini V;Eichenlaub U;Batrla R;Buck K;Zink K;Rabe C;Blennow K;Shaw LM;Swedish BioFINDER study group;Alzheimer's Disease Neuroimaging Initiative
通讯作者：
Alzheimer's Disease Neuroimaging Initiative