Early detection of Alzheimers disease (AD) is a necessity as prognosis is poor upon symptom onset. Although previous work diagnosing AD from protein-based biomarkers has been encouraging, cerebrospinal (CSF) biomarker measurement of AD proteins requires invasive lumbar puncture, whereas assessment of direct accumulation requires radioactive substance exposure in positron emission tomography (PET) imaging. Functional magnetic resonance imaging (fMRI)-based neuromarkers, offers an alternative, especially those built by capitalizing on variance distributed across the entire human connectome. In this study, we employed connectome-based predictive modeling (CPM) to build a model of functional connections that would predict CSF p-tau/Aβ42 (PATH-fc model) in individuals diagnosed with Mild Cognitive Impairment (MCI) and AD dementia. fMRI, CSF-based biomarker data, and longitudinal data from neuropsychological testing from the Alzheimers Disease NeuroImaging Initiative (ADNI) were utilized to build the PATH-fc model. Our results provide support for successful in-sample fit of the PATH-fc model in predicting AD pathology in MCI and AD dementia individuals. The PATH-fc model, distributed across all ten canonical networks, additionally predicted cognitive decline on composite measures of global cognition and executive functioning. Our highly distributed pathology-based model of functional connectivity disruptions had a striking overlap with the spatial affinities of amyloid and tau pathology, and included the default mode network as the hub of such network-based disruptions in AD. Future work validating this model in other external datasets, and to midlife adults and older adults with no known diagnosis, will critically extend this neuromarker development work using fMRI.

中文翻译：

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阿尔茨海默氏病病理的全脑功能连接模型

由于症状发作后预后较差，因此必须及早发现阿尔茨海默氏病（AD）。尽管以前基于蛋白质的生物标志物诊断AD的工作令人鼓舞，但脑脊液（CSF）生物标志物对AD蛋白的测量需要侵入性腰椎穿刺，而直接积累的评估则需要在正电子发射断层扫描（PET）成像中暴露放射性物质。基于功能磁共振成像（fMRI）的神经标记物提供了一种替代方法，尤其是那些利用了在整个人类连接体中分布的变异而构建的标记物。在这项研究中，我们采用基于连接组的预测模型（CPM）建立了功能连接模型，该模型可以在诊断为轻度认知障碍（MCI）和AD痴呆的个体中预测CSF p-tau /Aβ42（PATH-fc模型）。功能磁共振成像 利用基于CSF的生物标记数据以及来自阿尔茨海默氏病神经成像倡议组织（ADNI）的神经心理学测试得到的纵向数据来构建PATH-fc模型。我们的结果为成功预测PATH-fc模型的样本适合度，从而预测MCI和AD痴呆患者的AD病理提供了支持。分布在所有十个规范网络中的PATH-fc模型还预测了全球认知和执行功能综合指标的认知下降。我们高度分散的基于病理学的功能连接中断模型与淀粉样蛋白和tau病理学的空间亲和力有着惊人的重叠，并且包括默认模式网络作为AD中此类基于网络的中断的枢纽。未来的工作将在其他外部数据集中验证该模型，