BIOMARKERS FOR EARLY EXPRESSION OF ALZHEIMERS DISEASE

我们目前对阿尔茨海默病(AD)的研究表明 一些生物变量(睡眠、脑电频率、脑电 频谱能量和电机减速)可以正确区分85- 90%的AD患者来自对照组和抑郁症受试者。 这些阿尔茨海默病患者处于疾病进程的早期阶段 (MMS=23.0正负3.0)，表示所选生物 措施可作为AD：OF早期表达的生物标志物 特别有用，因为生物标志物是枕骨的主导 频率(DOF)(Alpha频率)，EEG能量较高 12赫兹以上的频段(使用快速傅立叶分析得出 变换)和简单反应时间任务的提升组件。 在此应用程序中，我们建议测试这些和 样本中预测AD样下降的相关生物标志物 300人有患AD的“风险”。这一“危险”样本将包括 符合NINCDS的具有有效记忆主诉的受试者 可能/可能是AD的标准(或几乎符合这些标准)。 受试者的年龄将在45岁或以上，并且没有混淆 除抑郁症外的医学精神障碍。在初级阶段 研究期间(时间1)我们计划收集依赖(临床， 认知和功能)和独立(生物标记物)变量。 30个月后，受试者将被召回并进行随访(时间 2)将再次收集依赖措施。受试者的 时间2的状态由于药物-医学、精神病学而混乱 否则，合规性问题将从这项研究中删除 时间到了。对于剩下的没有混淆的受试者，临床， 时间1(T1)和时间2的认知和功能状态 (T2)将用于将每个受试者分配到以下三个结果之一 组(AD，非AD(NAD)或不确定)。到时候我们会的 检查我们的T1生物标志物正确分类的能力 我们的目标在后续行动中的AD/NAD状态。我们还将检查 T1生物标记物对受试者的贡献(如果有) 以临床和功能为基础形成的分组。我们的目标是 开发AD生物标记物有助于更早和更多地实现 AD的准确诊断。这一领域的发展是一个 AD治疗/干预研究的重要辅助手段。我们 也会储存我们研究样本中的白细胞和血浆 遗传和血浆因子谱一致性的未来分析 使用AD。这将允许我们询问有关 遗传易感性与早期表达的关系 阿尔茨海默病在未来研究中的应用。

Our current study of Alzheimer's Disease (AD) has demonstrated that a number of biological variables (sleep, EEG frequency, EEG spectral energy and motor slowing) can correctly discriminate 85- 90 percent of AD patients from Control and Depressed subjects. These AD patients were in the early stages of the disease process (MMS=23.0 plus or minus 3.0), indicating that selected biological measures may serve as biomarkers for early expression of AD: Of particular usefulness as biomarkers were dominant occipital frequency (DOF) (alpha frequency), EEG energy in higher frequency bands above 12 Hz (derived using fast fourier transforms) and the lift component of a simple reaction time task. In this application we propose to test the ability of these and related biomarkers to predict for AD like decline in a sample of 300 individuals "at risk" for AD. This "at-risk" sample will consist of subjects with a validated memory complaint who meet NINCDS criteria for possible/probably AD (or almost meet these criteria). The subjects will be aged 45 or more and be free of confounding medical psychiatric disorders except depression. During the intial study period (time 1) we plan to collect both dependent (clinical, cognitive and function) and independent (biomarker) variables. After thirty months, subjects will be recalled and follow-up (Time 2) dependent measures will again be collected. Subjects whose Time 2 status is confounded due to pharmaco-medical, psychiatric or compliance problems will be dropped from the study at this time. For the remaining unconfounded subject, the clinical, cognitive and functional status, both at Time 1 (T1) and time 2 (T2) will be used to assign each subject to one of three outcome groups (AD, Not AD (NAD) or Indeterminate). We will then examine the ability of our T1 biomarkers to correctly classify the AD/NAD status of our subject at follow-up. We will also examine T1 biomarkers for their contribution (if any) to subject subgrouping formed on clinical and functional grounds. Our aim is to develop AD biomarkers useful in achieving on earlier and more accurate diagnosis of AD. Developments in this field are an important adjunct to treatment/intervention research in AD. We will also bank leukocytes and plasma from our study sample for future analyses of genetic and plasma factor profiles consitent with AD. This will allow us to ask questions about the relationship between genetic predisposition and early expression of AD in future studies.