The Role of Intracranial Atherosclerosis in the Development of Alzheimer's Disease

理由：痴呆症在美国和世界范围内是一个日益严重的问题。缺乏有效治疗或 阿尔茨海默病（AD）是痴呆症最常见的原因，其预防策略已导致 死亡率上升和医疗费用飙升。颅内动脉粥样硬化性疾病（ICAD）也是高风险的。 流行于老年人，新的证据表明，它可能与AD及其前体，轻度 认知障碍（MCI），但缺乏前瞻性验证。我们建议前瞻性地研究 ICAD及其在认知下降、MCI和痴呆（特别是AD）发展中的进展。 目的：我们将通过MRI确定ICAD的存在和测量，包括其进展和风险指数 基于基线ICAD特征，导致认知能力下降、MCI事件和痴呆事件。我们将 确定ICAD是否增加了局部脑容量损失的预测值，这是AD的已知预测因素。最后， 我们将建立预测ICAD进展的危险因素和斑块特征。 设计/方法：我们将对社区动脉粥样硬化风险（ARIC）研究进行辅助研究， 一项由NIH资助的心血管队列研究，开始时约有16,000名参与者，年龄在45-64岁之间， 自1987年以来。ARIC神经认知研究（ARIC-NCS），在最近的ARIC访问中进行， 2011年至2013年，获得脑MRI和认知评估，以研究血管疾病的横截面相关性。 MCI和痴呆的危险因素和MRI脑改变。MRI还识别和测量了狭窄， ICAD首次使用了一种新的血管壁成像技术。这项技术检测动脉粥样硬化 斑块，即使它们不导致狭窄，并且可能是动脉粥样硬化疾病负担的更好量度。 我们计划在NIH资助的下一次ARIC访问中对1，000名参与者进行重复的脑部MRI检查，该访问将于2010年开始。 2016年，间隔5-8年，以测量ICAD进展、脑容量损失和小血管疾病 (SVD)这是与AD相关的血流障碍的另一个原因。重复的认知评估也是 计划好了我们预计，在本次检查开始时，MCI和痴呆的发病病例分别为335例和266例。 然后，我们将评估ICAD基线与事件认知结果的关联。核磁共振成像可以让 我们可以对AD（或MCI中的AD型）进行特异性诊断，并对其危险因素进行分析。另外我们 将使用随访MRI数据测量管腔狭窄和血管壁厚度的变化，以识别ICAD 进展在分析与ICAD的相关性时，我们将考虑SVD和血管危险因素。是 值得注意的是，大梗塞是痴呆症的一种罕见原因，而不是本研究的主要焦点。 影响：通过我们提出的研究，我们将建立ICAD在发展中的作用， MCI和痴呆，特别是AD的进展。这将是第一次研究自然历史的特征 ICAD进展及其预测认知结果的能力。这些信息可能会导致预防性 在目前无法治疗的疾病中，治疗方案的策略和风险分层。

Rationale: Dementia is a growing problem in the US and worldwide. The lack of effective treatment or preventive strategies for Alzheimer’s Disease (AD), the most common cause of dementia, has led to an increasing mortality rate and soaring medical costs. Intracranial atherosclerotic disease (ICAD) is also highly prevalent in older adults, and new evidence suggests it may be associated with AD and its precursor, mild cognitive impairment (MCI), but prospective validation is lacking. We propose to prospectively study the role of ICAD and its progression in the development of cognitive decline, MCI and dementia, in particular AD. Aims: We will determine if ICAD presence and measures by MRI, including its progression and a risk index based on baseline ICAD features, lead to cognitive decline, incident MCI and incident dementia. We will determine if ICAD adds to the predictive value of regional brain volume loss, a known predictor of AD. Finally, we will establish risk factors and plaque features that predict progression of ICAD. Design/Methods: We will conduct an ancillary study to the Atherosclerosis Risk in Communities (ARIC) Study, an NIH-funded cardiovascular cohort that began with about 16,000 participants, aged 45-64, who have been followed since 1987. The ARIC Neurocognitive Study (ARIC-NCS), conducted at the most recent ARIC visit in 2011-2013, acquired brain MRIs and cognitive evaluations to study cross-sectional associations of vascular risk factors and MRI brain changes with MCI and dementia. MRI also identified and measured stenosis and, for the first time, ICAD using a novel vessel wall imaging technique. This technique detects atherosclerotic plaques even if they do not result in stenosis and may be a better measure of atherosclerotic disease burden. We plan to acquire a repeat brain MRI in 1,000 participants at the next NIH-funded ARIC visit that begins in 2016 after a 5-8 year interval to measure ICAD progression, brain volume loss, and small vessel disease (SVD), another cause of blood flow impairment associated with AD. Repeat cognitive evaluations are also planned. We expect 335 and 266 incident cases of MCI and dementia, respectively, by the start of this exam. We will then evaluate the association of ICAD at baseline with incident cognitive outcomes. The MRI will allow us to make a specific diagnosis of AD (or AD-type in MCI), permitting analysis of its risk factors. In addition, we will use follow-up MRI data to measure changes in luminal stenosis and vessel wall thickness to identify ICAD progression. We will account for SVD and vascular risk factors when analyzing associations with ICAD. It is worth noting that large infarcts are an uncommon cause of dementia and not the primary focus of this study. Implications: Through our proposed study we will establish the role of ICAD in the development and progression of MCI and dementia, in particular AD. This will be the first study characterizing the natural history of ICAD progression and its ability to predict cognitive outcomes. This information could lead to preventive strategies and risk stratification for treatment protocols in an otherwise currently untreatable disease.