A NOVEL FMRI BIOMARKER OF INCIPIENT ALZHEIMER?S DISEASE

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 阿尔茨海默病（AD）是痴呆症的最常见原因，影响多达1/10的65岁以上的人和1/3的85岁以上的人。 流行病学研究估计，目前美国AD的患病率约为400万人，预计到2050年这一数字将达到1300万人。 目前批准的治疗仅提供适度的症状益处，但设计用于预防疾病发作或进展的几种药物正在进行临床试验。 随着预防性或治愈性治疗的潜力即将出现，并且了解到这种治疗在疾病的最早阶段开始时将是最有效的，研究已经转向早期，理想的是临床前检测AD。 尽管大力开发AD的体内诊断测定法，但研究人员一直无法在血清或脑脊液分析中鉴定具有足够灵敏度和特异性的生物标志物，以使其值得用作临床诊断测试。 许多研究小组已经研究了MRI在检测早期AD和预测哪些高危患者将发展为AD中的功能和结构方面的潜在作用。 然而，迄今为止，这些成像方法在个体患者水平上也缺乏足够的灵敏度和特异性。 我们改进了一种新的功能性磁共振成像技术？功能连接性MRI（fcMRI）？检测一个特定的静息状态网络（RSN），该网络包含了在AD早期阶段受影响的几个大脑区域。 所述方法包括向个体受试者分配定量分数，所述定量分数反映其RSN与RSN的标准模板匹配的程度。 我们开发这种方法的目的是使其具有临床相关性和广泛适用性（即从大学教学医院到社区医院）。 为此，它是自动化的，不需要投射刺激或记录行为反应，也不需要高场MRI扫描仪。 我们的初步数据表明，这种方法有可能在疾病的最早阶段将健康的老年对照与个体AD患者区分开来。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Alzheimer's Disease (AD) is the most common cause of dementia affecting as many as 1 in 10 people over age 65 and 1 in 3 people over age 85. Epidemiological studies estimate the prevalence of AD in the United States to be approximately 4 million people currently and this number is expected to reach 13 million by the year 2050. Currently approved therapy only provides modest symptomatic benefit, but several drugs designed to prevent the onset or progression of disease are undergoing clinical trials. With the potential for preventive or curative therapy on the horizon and an understanding that such treatments will be most effective when begun at the earliest stages of the illness, research has turned to the early, and ideally pre-clinical, detection of AD. Despite intensive efforts to develop an in vivo diagnostic assay for AD, researchers have been unable to identify biomarkers in either serum or cerebrospinal fluid analyses with sufficient sensitivity and specificity to merit their use as a clinical diagnostic test. A number of groups have examined the potential role of MRI, both functional and structural, in detecting early AD and predicting which at-risk patients will develop AD. To date, however, these imaging approaches have also lacked sufficient sensitivity and specificity at the individual patient level. We have modified a novel functional MRI technique?functional connectivity MRI (fcMRI)?to detect a specific resting-state network (RSN) that incorporates several brain regions affected in the earliest stages of AD. The method includes assigning a quantitative score to individual subjects reflecting the degree to which their RSN matches a standard template of the RSN. We have developed this method with the goal of making it both clinically relevant and broadly applicable (i.e beyond university teaching hospitals to community hospitals). To this end, it is automated, does not require projection of stimuli or recording of behavioral responses, and does not require a high field MRI scanner. Our preliminary data suggests that this approach has the potential to distinguish healthy elderly controls from individual AD patients at the earliest stage of the disease.