Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment

IF 4.9 Q1 CLINICAL NEUROLOGY Alzheimer''s and Dementia: Translational Research and Clinical Interventions Pub Date : 2024-10-10 DOI:10.1002/trc2.70008

Takuya Ataka, Noriyuki Kimura, Naoki Kaneko, Teruaki Masuda, Yosuke Takeuchi, Kenichi Yabuuchi, Takeshi Mizukami, Tsukasa Takeuchi, Temmei Ito, Hideaki Tasai, Takehiko Miyagawa, Shunya Hanai, Shinichi Iwamoto, Etsuro Matsubara

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Abstract

INTRODUCTION

Previous studies have examined the predictive accuracy of plasma amyloid beta (Aβ) biomarkers in clinical cohorts. However, their accuracy for predicting amyloid-positive patients in community-based cohorts is unclear. This study aimed to determine the predictive accuracy of Aβ precursor protein 669-711/Aβ1-42, Aβ1-40/1-42 and their composite biomarkers for brain amyloid deposition or the clinical progression in community-dwelling older adults with mild cognitive impairment (MCI).

METHODS

This prospective cohort study was conducted from August 2015 to September 2019. Subsequently, the participants underwent follow-up cognitive assessments up to 8 years after the start of the study. Blood samples were collected from older adults aged ≥ 65 years with MCI at baseline. Plasma Aβ biomarkers were analyzed using immunoprecipitation-mass spectrometry. The accuracy of plasma biomarkers for brain amyloid status was evaluated using receiver operating characteristic curve analysis. Relationships between comorbidities and plasma Aβ markers were examined using multiple linear regression analysis. Associations of plasma biomarkers with clinical conversion to Alzheimer's disease (AD) dementia were evaluated using Kaplan‒Meier curves.

RESULTS

The participants included 107 patients (57 [53.3%] females, median age: 76.0 [72.0–80.0] years). Plasma biomarkers correlated with cortical amyloid uptake (ρ = 0.667–0.754). The composite biomarker had the best area under the curve (0.943, 95% confidence interval [CI]: 0.901 to 0.985) for predicting amyloid positivity. Apolipoprotein ε4 status showed significant correlations with increased plasma amyloid biomarker levels. Participants with high composite biomarker levels at baseline had a greater risk of conversion to AD dementia (hazard ratio 10.74, 95% CI: 3.51 to 32.84, P < 0.001). The higher composite biomarker was associated with a faster rate of cognitive decline (ρ = −0.575, P < 0.001).

DISCUSSION

Plasma Aβ composite biomarker may serve as a surrogate measure for amyloid deposition and a predictor of disease progression in a community-based cohort.

Highlights

Plasma amyloid beta (Aβ) biomarkers correlated with 11C-Pittsburgh compound B uptake, mainly in the frontal/parietotemporal cortices and posterior cingulate gyrus.
The amyloid composite biomarker can predict amyloid positron emission tomography positivity with a high area under the curve of 0.943 in a community-based mild cognitive impairment cohort.
The higher amyloid composite biomarker at baseline was significantly associated with worsening Mini-Mental State Examination score and a high risk for developing Alzheimer's disease (AD) dementia over 8 years.
The amyloid composite biomarker can predict clinical progression to AD dementia with a high area under the curve of 0.860.
Apolipoprotein E ε4 status influenced the plasma Aβ biomarker levels.

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血浆淀粉样β生物标志物可预测轻度认知障碍患者的淀粉样蛋白阳性率和纵向临床进展

引言以前的研究已经检验了血浆淀粉样蛋白 beta（Aβ）生物标志物在临床队列中的预测准确性。然而，这些生物标志物预测社区队列中淀粉样蛋白阳性患者的准确性尚不明确。本研究旨在确定 Aβ 前体蛋白 669-711/Aβ1-42、Aβ1-40/1-42 及其复合生物标记物对轻度认知障碍（MCI）社区老年人脑淀粉样蛋白沉积或临床进展的预测准确性。方法这项前瞻性队列研究于 2015 年 8 月至 2019 年 9 月进行。随后，参与者在研究开始后接受了长达 8 年的随访认知评估。基线研究收集了年龄≥ 65 岁、患有 MCI 的老年人的血液样本。采用免疫沉淀质谱法分析血浆 Aβ 生物标志物。使用接收器操作特征曲线分析评估了血浆生物标志物对脑淀粉样蛋白状态的准确性。采用多元线性回归分析法研究了合并症与血浆Aβ标记物之间的关系。使用 Kaplan-Meier 曲线评估了血浆生物标志物与阿尔茨海默病（AD）痴呆临床转化之间的关系。结果参与者包括 107 名患者（57 [53.3%] 名女性，中位年龄：76.0 [72.0-80.0] 岁）。血浆生物标志物与皮质淀粉样蛋白摄取量相关（ρ = 0.667-0.754）。复合生物标志物在预测淀粉样蛋白阳性方面具有最佳曲线下面积（0.943，95% 置信区间 [CI]：0.901 至 0.985）。载脂蛋白ε4状态与血浆淀粉样蛋白生物标志物水平的升高有显著相关性。基线复合生物标志物水平高的参与者转化为AD痴呆的风险更大（危险比10.74，95% CI：3.51至32.84，P <0.001）。复合生物标志物越高，认知能力下降的速度越快（ρ = -0.575，P <0.001）。讨论血浆淀粉样蛋白β复合生物标志物可作为淀粉样蛋白沉积的替代指标，也是社区队列中疾病进展的预测指标。亮点血浆淀粉样蛋白β（Aβ）生物标志物与11C-匹兹堡化合物B摄取相关，主要是在额叶/颞叶旁皮层和扣带回后部。在以社区为基础的轻度认知障碍队列中，淀粉样蛋白复合生物标志物可以预测淀粉样蛋白正电子发射断层扫描阳性率，其曲线下面积高达 0.943。基线时较高的淀粉样蛋白复合生物标志物与迷你精神状态检查评分的恶化和8年内罹患阿尔茨海默病（AD）痴呆症的高风险显著相关。淀粉样蛋白复合生物标志物可以预测阿尔茨海默病痴呆症的临床进展，其曲线下面积高达0.860。载脂蛋白E ε4状态影响血浆Aβ生物标志物水平。

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来源期刊

Alzheimer''s and Dementia: Translational Research and Clinical Interventions Medicine-Psychiatry and Mental Health

CiteScore

10.10

自引率

2.10%

发文量

134

审稿时长

10 weeks

期刊介绍： Alzheimer''s & Dementia: Translational Research & Clinical Interventions (TRCI) is a peer-reviewed, open access,journal from the Alzheimer''s Association®. The journal seeks to bridge the full scope of explorations between basic research on drug discovery and clinical studies, validating putative therapies for aging-related chronic brain conditions that affect cognition, motor functions, and other behavioral or clinical symptoms associated with all forms dementia and Alzheimer''s disease. The journal will publish findings from diverse domains of research and disciplines to accelerate the conversion of abstract facts into practical knowledge: specifically, to translate what is learned at the bench into bedside applications. The journal seeks to publish articles that go beyond a singular emphasis on either basic drug discovery research or clinical research. Rather, an important theme of articles will be the linkages between and among the various discrete steps in the complex continuum of therapy development. For rapid communication among a multidisciplinary research audience involving the range of therapeutic interventions, TRCI will consider only original contributions that include feature length research articles, systematic reviews, meta-analyses, brief reports, narrative reviews, commentaries, letters, perspectives, and research news that would advance wide range of interventions to ameliorate symptoms or alter the progression of chronic neurocognitive disorders such as dementia and Alzheimer''s disease. The journal will publish on topics related to medicine, geriatrics, neuroscience, neurophysiology, neurology, psychiatry, clinical psychology, bioinformatics, pharmaco-genetics, regulatory issues, health economics, pharmacoeconomics, and public health policy as these apply to preclinical and clinical research on therapeutics.