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

描述（由申请人提供）：阿尔茨海默病（AD）在首次被描述100多年后，仍然严格按照临床标准诊断，这些标准对疾病的早期阶段不敏感，并且不能充分区分AD与非AD痴呆。当将临床诊断与尸检证实的诊断进行比较时，即使是最有经验的临床医生也有15-20%的错误。这种诊断的不准确性被认为在非专业环境中更为严重，因为在非专业环境中，阿尔茨海默病的初始诊断是最常见的。随着实验性治疗方法的进步以及强力治疗可能产生严重副作用的提醒，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。这样的生物标记物在几个方面都是有用的。在临床环境中，它将允许更多的诊断确定性，试图区分阿尔茨海默病与其他痴呆症。一种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）患者会发展为阿尔茨海默病，同样重要的是，哪些不会。最后，一种能够在早期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和实现更快速、客观的疗效评估来加速药物开发。尽管付出了巨大的努力，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。目前的应用将研究一种相对新颖的功能MRI （fMRI）作为AD的候选成像生物标志物。静息状态fMRI提供了特定大脑网络内功能连接的测量，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，它尚未被证明在单受试者水平上是可靠的，它在MCI中的预测价值仍然不确定，而且它还没有被纵向检验。目前的应用，利用多地点纵向研究的优势，将试图解决这些限制。该研究将包括从斯坦福大学和加州大学旧金山分校获取静息状态功能磁共振成像数据，包括四组受试者：健康衰老、轻度认知障碍、阿尔茨海默病和非阿尔茨海默病痴呆。受试者将在基线处接受扫描并进行纵向随访。一部分受试者将每隔1年再次接受扫描。该研究的目的是：a)增强静息状态功能连接测量在区分AD与健康衰老和非AD痴呆方面的敏感性和特异性；b)评估静息状态fMRI在预测哪些MCI患者随后在研究的五年过程中转化为AD方面的效用；c)评估静息状态fMRI在跟踪疾病进展方面的效用。

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.