脑和心室边界位移积分测量与脑脊液生物标志物的关联:一项病例对照研究。

IF 1.9
Seyedeh Fahimeh Hosseini, Parastoo Akbarabadi, Fatemeh Noorani, Danial Kezemi, Hamidreza Sadeghsalehi, Mohammadtaghi Fattahpour, MohammadHosein Sheybani-Arani, Masoud Noroozi, Ali Kazemi
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引用次数: 0

摘要

目的:本研究旨在探讨脑脊液(CSF)生物标志物(Aβ1-42, Phospho-Tau181p, Total-Tau)与脑移积分(BSI)测量的阿尔茨海默病(AD)谱中脑容量变化之间的关系。我们探索BSI作为早期诊断和AD进展监测的补充、非侵入性工具的潜力。背景:AD是一种以淀粉样斑块和tau蛋白缠结为特征的神经退行性疾病,可导致认知能力下降。脑脊液生物标志物是阿尔茨海默病病理的关键指标,但它们与BSI等成像指标的结合可以增强早期诊断。BSI通过MRI量化脑容量变化,为阿尔茨海默病谱系的神经变性提供了有价值的见解。目的:本研究探讨BSI和CSF生物标志物在阿尔茨海默病早期检测中的应用。方法:本研究利用来自ADNI数据库的数据,包括脑脊液生物标志物(Aβ1-42, t-tau, p- tau181)和基线和第24个月就诊的BSI测量。采用Spearman相关性来评估生物标志物与脑容量变化之间的关联。线性回归模型用于检验生物标志物对BSI的预测价值,控制潜在的混杂因素。结果:共有239名参与者纳入研究,包括94名认知正常(CN)个体,104名轻度认知障碍(MCI)个体和41名AD患者。a - β1-42与MCI患者基线(p=0.013)和24个月(p=0.018)的BBSI和VBSI呈显著负相关,与CN患者基线(p=0.039)和24个月(p=0.033)的VBSI呈显著负相关。在MCI中,p-tau181与基线时BBSI (p=0.013)和VBSI (p=0.030)呈正相关,与24个月时BBSI呈正相关(p=0.013)。线性回归分析证实,Aβ1-42和p-tau181显著预测MCI患者的BSI指标(R2=0.141-0.173)。结论:BSI的应用对监测脑容量变化及其与脑脊液生物标志物的关联至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association of Brain and Ventricular Boundary Shift Integral Measurements with CSF Biomarkers: A Case-Control Study.

Aims: This study seeks to examine the relationship between cerebrospinal fluid (CSF) biomarkers (Aβ1-42, Phospho-Tau181p, Total-Tau) and brain volumetric changes measured by Brain Shift Integral (BSI) in Alzheimer's disease (AD) spectrum. We explore the potential of BSI as a complementary, non-invasive tool for early diagnosis and progression monitoring of AD.

Background: AD is a neurodegenerative disorder marked by amyloid plaques and tau tangles, leading to cognitive decline. CSF biomarkers are key indicators of AD pathology, but their integration with imaging metrics like BSI could enhance early diagnosis. BSI quantifies brain volume changes via MRI, offering valuable insights into neurodegeneration across the AD spectrum.

Objectives: The current study explores the use of BSI and CSF biomarkers for the early detection of Alzheimer's disease.

Methods: This study utilized data from the ADNI database, including CSF biomarkers (Aβ1-42, t-tau, p-- tau181) and BSI measurements from baseline and month 24 visits. Spearman correlations were performed to assess associations between biomarkers and brain volumetric changes. Linear regression models were used to examine the predictive value of biomarkers on BSI, controlling for potential confounders.

Results: A total of 239 participants were included in the study, comprising 94 cognitively normal (CN) individuals, 104 with mild cognitive impairment (MCI), and 41 with AD. Significant negative correlations were observed between Aβ1-42 and both BBSI and VBSI in MCI at baseline (p=0.013) and 24 months (p=0.018), as well as between Aβ1-42 and VBSI in CN at baseline (p=0.039) and 24 months (p=0.033). In MCI, p-tau181 was positively correlated with BBSI (p=0.013) and VBSI (p=0.030) at baseline and with BBSI at 24 months (p=0.013). Linear regression analysis confirmed that Aβ1-42 and p-tau181 significantly predicted BSI measures in MCI (R2=0.141-0.173, p<0.05), while Aβ1-42 was a significant predictor of VBSI in CN (R2=0.156-0.166, p<0.01). No significant associations were found in AD.

Conclusion: The application of the BSI is pivotal for monitoring brain volume alterations and their association with CSF biomarkers.

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