Zamani Jafar, Vahid Amirali, Avelar-Pereira Bárbara, Gozdas Elveda, Hosseini S M Hadi
Computational Brain Research and Intervention (C-Brain) Lab, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, California, USA.
Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Alzheimers Dement. 2025 Feb;21(2):e14499. doi: 10.1002/alz.14499. Epub 2025 Jan 8.
Amyloid beta (Aβ) plaques and hyperphosphorylated tau in the entorhinal regions are key Alzheimer's disease (AD) markers, but the spatial Aβ pathways influencing tau pathology remain unclear.
We applied predictive modeling to identify Aβ standardized uptake value ratio (SUVR) spatial patterns that predict entorhinal tau levels, future hippocampal volume, and Preclinical Alzheimer's Cognitive Composite (PACC) scores at 5-year follow-up. The model was trained on Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 237), incorporating amyloid-PET (positron emission tomography), tau-PET, magnetic resonance imaging (MRI), and cognitive data, and validated on Harvard Aging Brain Study (HABS) (N = 276).
The model accurately predicted entorhinal tau levels (r = 0.48, p < 0.0001), future hippocampal volume (r = 0.24, p = 0.002), and PACC scores (r = 0.35, p < 0.0001) based on regional Aβ.
Aβ in the rostral middle frontal, medial orbitofrontal, and striatal regions predict entorhinal tau levels, future hippocampal volume, and PACC scores, indicating their potential as early biomarkers in AD prediction models.
Positron emission tomography (PET) imaging reveals amyloid beta (Aβ) patterns predicting entorhinal tau levels in preclinical Alzheimer's disease (AD). Aβ in medial orbitofrontal, rostral middle frontal, and nucleus accumbens best predicts tau. Aβ distribution in these regions predicts future hippocampal neurodegeneration and cognitive decline. Model validated with Alzheimer's Disease Neuroimaging Initiative (ADNI) and Harvard Aging Brain Study (HABS) data sets, showing robustness and reproducibility. Findings suggest early Aβ patterns can aid in diagnosing AD and guide anti-Aβ therapies.
内嗅区的β淀粉样蛋白（Aβ）斑块和过度磷酸化的tau蛋白是阿尔茨海默病（AD）的关键标志物，但影响tau蛋白病变的Aβ空间通路仍不清楚。
我们应用预测模型来识别Aβ标准化摄取值比率（SUVR）的空间模式，该模式可预测5年随访时的内嗅区tau蛋白水平、未来海马体积和临床前阿尔茨海默病认知综合评分（PACC）。该模型在阿尔茨海默病神经影像学倡议（ADNI）（N = 237）上进行训练，纳入了淀粉样蛋白正电子发射断层扫描（PET）、tau蛋白PET、磁共振成像（MRI）和认知数据，并在哈佛衰老大脑研究（HABS）（N = 276）上进行验证。
该模型基于区域Aβ准确预测了内嗅区tau蛋白水平（r = 0.48，p < 0.0001）、未来海马体积（r = 0.24，p = 0.002）和PACC评分（r = 0.35，p < 0.0001）。
额中回前部、眶额内侧和纹状体区域的Aβ可预测内嗅区tau蛋白水平、未来海马体积和PACC评分，表明它们在AD预测模型中作为早期生物标志物的潜力。
正电子发射断层扫描（PET）成像揭示了在临床前阿尔茨海默病（AD）中预测内嗅区tau蛋白水平的β淀粉样蛋白（Aβ）模式。眶额内侧、额中回前部和伏隔核中的Aβ最能预测tau蛋白。这些区域的Aβ分布可预测未来海马神经变性和认知衰退。该模型通过阿尔茨海默病神经影像学倡议（ADNI）和哈佛衰老大脑研究（HABS）数据集进行验证，显示出稳健性和可重复性。研究结果表明，早期Aβ模式有助于AD的诊断并指导抗Aβ治疗。
