Hosseini Seyedeh Fahimeh, Akbarabadi Parastoo, Noorani Fatemeh, Kezemi Danial, Sadeghsalehi Hamidreza, Fattahpour Mohammadtaghi, Sheybani-Arani MohammadHosein, Noroozi Masoud, Kazemi Ali
Mechanical Engineering Department, Sharif University of Technology, Teymouri Square, Tarasht, Postal Code: 1458889694, Tehran, Iran.
Department of Genetics, Faculty of Biological Science, Tarbiat Modares University, Jalal AleAhmad Street, Nasr Street, Postal Code: 14115111, Tehran, Iran.
Curr Alzheimer Res. 2025 Jun 5. doi: 10.2174/0115672050379856250529113023.
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.
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.
The current study explores the use of BSI and CSF biomarkers for the early detection of Alzheimer's disease.
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.
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.
The application of the BSI is pivotal for monitoring brain volume alterations and their association with CSF biomarkers.
本研究旨在探讨脑脊液（CSF）生物标志物（Aβ1-42、磷酸化Tau181p、总Tau）与阿尔茨海默病（AD）谱系中通过脑移位积分（BSI）测量的脑容量变化之间的关系。我们探索BSI作为AD早期诊断和病情进展监测的一种补充性、非侵入性工具的潜力。
AD是一种以淀粉样斑块和tau缠结为特征的神经退行性疾病，会导致认知能力下降。CSF生物标志物是AD病理学的关键指标，但将它们与BSI等成像指标相结合可以提高早期诊断水平。BSI通过磁共振成像（MRI）量化脑容量变化，为AD谱系中的神经退行性变提供有价值的见解。
本研究探索使用BSI和CSF生物标志物进行阿尔茨海默病的早期检测。
本研究利用了阿尔茨海默病神经成像计划（ADNI）数据库中的数据，包括CSF生物标志物（Aβ1-42、总tau、磷酸化tau181）以及基线和第24个月随访时的BSI测量值。进行Spearman相关性分析以评估生物标志物与脑容量变化之间的关联。使用线性回归模型来检验生物标志物对BSI的预测价值，并控制潜在的混杂因素。
本研究共纳入239名参与者，包括94名认知正常（CN）个体、104名轻度认知障碍（MCI）患者和41名AD患者。在MCI组中，基线时（p=0.013）和24个月时（p=0.018），Aβ1-42与脑桥脑移位积分（BBSI）和脑室脑移位积分（VBSI）均呈显著负相关；在CN组中，基线时（p=0.039）和24个月时（p=0.033），Aβ1-42与VBSI呈显著负相关。在MCI组中，基线时磷酸化tau181与BBSI（p=0.013）和VBSI（p=0.030）呈正相关，24个月时与BBSI呈正相关（p=0.013）。线性回归分析证实，在MCI组中，Aβ-42和磷酸化tau181显著预测BSI测量值（R2=0.141-0.173，p<0.05），而在CN组中，Aβ1-42是VBSI的显著预测指标（R2=0.156-0.166，p<0.01）。在AD组中未发现显著关联。
BSI的应用对于监测脑容量变化及其与CSF生物标志物的关联至关重要。
