Development of Resting-State fMRI as a Biomarker for Alzheimers Disease

描述（由申请人提供）：在首次描述100多年后，阿尔茨海默病（AD）仍然严格按照临床标准进行诊断，这些标准对疾病的早期阶段不敏感，并且不能充分区分AD和非AD痴呆。当将临床诊断与尸检确认的诊断进行比较时，即使是最有经验的临床医生也有15-20%的时间是错误的。这种诊断不准确性被认为是相当糟糕的非专业设置，其中AD的初步诊断是最常见的。随着实验疗法的进步以及随之而来的有效治疗可能具有严重副作用的提醒，对准确，非侵入性AD生物标志物的需求比以往任何时候都更加迫切。这种生物标志物在几个方面都很有用。在临床环境中，它将允许更多的诊断确定性，试图区分AD从其他痴呆症。具有足够灵敏度的准确生物标志物也应该有助于预测哪些轻度认知障碍（MCI）患者将继续发展AD，同样重要的是，哪些不会。最后，在最早阶段检测疾病并跟踪临床状态的AD生物标志物将通过促进剂量反应研究并实现更快速和客观的疗效评估来加速药物开发。尽管付出了相当大的努力，但该领域尚未开发出能够满足这些迫切需求的生物标志物。本申请将研究一种相对新颖的功能性MRI（fMRI）形式，作为AD的候选成像生物标志物。静息状态功能磁共振成像提供了一种测量特定大脑网络内功能连接的方法，并在初步研究中显示出作为AD生物标志物的前景。目前这种方法的局限性在于，它尚未被证明在单个受试者水平上是可靠的可解释的，其在MCI中的预测价值仍然不确定，并且尚未进行纵向检查。本申请利用多中心纵向研究的优势，将尝试解决这些局限性。这项研究将涉及从斯坦福大学和加州大学旧金山分校弗朗西斯科的四个大型队列的受试者：健康老龄化，MCI，AD和非AD痴呆的静息状态fMRI数据的采集。将在基线时对受试者进行扫描并进行纵向随访。受试者子集将每隔1年再次接受扫描。本研究的目的是：a）增强静息态功能连接测量在区分AD与健康老龄化和非AD痴呆中的灵敏度和特异性，B）评估静息态功能磁共振成像在预测MCI患者在研究的五年过程中随后转化为AD中的效用，以及c）评估静息态功能磁共振成像在跟踪疾病进展中的效用。

DESCRIPTION (provided by applicant): More than 100 years after it was first described, Alzheimer's disease (AD) is still diagnosed strictly on clinical criteria that are not sensitive to the early stages of disease and do not adequately distinguish AD from non-AD dementias. When comparing a clinical diagnosis to an autopsy-confirmed diagnosis, even the most seasoned clinicians are wrong 15-20% of the time. This diagnostic inaccuracy is assumed to be considerably worse in non-specialty settings where the initial diagnosis of AD is most often made. With advances in experimental therapeutics and the concomitant reminder that potent treatments may have serious side effects, the need for an accurate, non-invasive AD biomarker is more pressing than ever. Such a biomarker would be useful on several fronts. In the clinical setting it would allow for more diagnostic certainty in trying to distinguish AD from other dementias. An accurate biomarker with sufficient sensitivity should also help predict which patients with mild cognitive impairment (MCI) will go on to develop AD and, just as importantly, which will not. Lastly, an AD biomarker that detects disease in the earliest stages and tracks with clinical status would accelerate drug development by facilitating dose-response studies and enabling more rapid and objective assessment of efficacy. Despite considerable efforts, the field has yet to develop a biomarker that can meet these pressing needs. The current application will examine a relatively novel form of functional MRI (fMRI) as a candidate imaging biomarker in AD. Resting-state fMRI provides a measure of functional connectivity within specific brain networks and has shown promise in preliminary studies as an AD biomarker. The limitations of this approach currently are that it has not yet proven to be reliably interpretable at the single-subject level, its predictive value in MCI remains uncertain, and it has not been examined longitudinally. The current application, drawing on the strengths of a multi-site, longitudinal study, will attempt to address these limitations. The study will involve the acquisition of resting-state fMRI data from Stanford University and the University of California, San Francisco in four large cohorts of subjects: healthy aging, MCI, AD, and non-AD dementia. Subjects will be scanned at baseline and followed longitudinally. A subset of subjects will be scanned again at a 1-year interval. The aims of the study will be a) to enhance the sensitivity and specificity of resting-state functional connectivity measures in distinguishing AD from both healthy aging and non-AD dementia, b) to assess the utility of resting-state fMRI in predicting which patients with MCI subsequently convert to AD over the five-year course of the study and c) to assess the utility of resting-state fMRI in tracking disease progression over time.