A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry

Jianfeng Wu, Yindan Su, Yanxi Chen, Wenjie Zhu, E. Reiman, R. Caselli, Kewei Chen, P. Thompson, Junwen Wang, Yalin Wang
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Abstract

BACKGROUND Alzheimer's disease (AD) is the most common type of age-related dementia, affecting 6.2 million people aged 65 or older according to CDC data. It is commonly agreed that discovering an effective AD diagnosis biomarker could have enormous public health benefits, potentially preventing or delaying up to 40% of dementia cases. Tau neurofibrillary tangles are the primary driver of downstream neurodegeneration and subsequent cognitive impairment in AD, resulting in structural deformations such as hippocampal atrophy that can be observed in magnetic resonance imaging (MRI) scans. OBJECTIVE To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline. METHODS Using data obtained from different institutions, we develop a surface-based federated Chow test model to study the synergistic effects of APOE, a previously reported significant risk factor of AD, and tau on hippocampal surface morphometry. RESULTS We illustrate that the APOE-specific morphometry features correlate with AD progression and better predict future AD conversion than other MRI biomarkers. For example, a strong association between atrophy and abnormal tau was identified in hippocampal subregion cornu ammonis 1 (CA1 subfield) and subiculum in e4 homozygote cohort. CONCLUSION Our model allows for identifying MRI biomarkers for AD and cognitive decline prediction and may uncover a corner of the neural mechanism of the influence of APOE and tau deposition on hippocampal morphology.
结合APOE状态、Tau沉积测量和海马表面形态测量的基于表面的联邦Chow测试模型
背景:根据疾病预防控制中心的数据,阿尔茨海默病(AD)是最常见的与年龄相关的痴呆症,影响了620万65岁或以上的人。人们普遍认为,发现一种有效的阿尔茨海默病诊断生物标志物可能会带来巨大的公共卫生效益,有可能预防或延缓高达40%的痴呆症病例。Tau神经原纤维缠结是阿尔茨海默病下游神经变性和随后认知障碍的主要驱动因素,导致结构变形,如海马萎缩,可以在磁共振成像(MRI)扫描中观察到。目的建立基于表面的模型,检测APOE亚组之间tau沉积模式和海马萎缩的差异,并利用提取的表面特征预测认知能力下降。方法利用从不同机构获得的数据,我们建立了一个基于表面的联合Chow测试模型,研究APOE(先前报道的AD的重要危险因素)和tau对海马表面形态的协同作用。研究结果表明,apoe特异性形态学特征与AD进展相关,比其他MRI生物标志物更能预测未来AD的转化。例如,在e4纯合子队列中,在海马角氨基亚区1 (CA1亚区)和耻骨下发现了萎缩与异常tau之间的强烈关联。结论我们的模型可以识别AD和认知能力下降预测的MRI生物标志物,并可能揭示APOE和tau沉积影响海马形态的神经机制的一个角落。
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