BIOMARKERS FOR EARLY EXPRESSION OF ALZHEIMER'S DISEASE

我们目前对阿尔茨海默病（AD）的研究表明， 许多生物变量（睡眠，脑电图频率，脑电图 光谱能量和运动减慢）可以正确区分85- 90%的AD患者来自对照组和抑郁组。 这些AD患者处于疾病过程的早期阶段， (MMS=23.0 ± 3.0），表明选定的生物 测量可以作为AD早期表达的生物标志物： 特别有用，因为生物标志物主要是枕骨 频率（DOF）（α频率），EEG能量较高 12 Hz以上的频带（使用快速傅立叶 转换）和简单反应时间任务的提升部分。 在本申请中，我们建议测试这些和 相关的生物标志物，以预测AD样下降的样品中， 300人“有风险”的AD。 这个“有风险”的样本将包括 符合NINCDS的有效记忆投诉受试者 可能/很可能AD的标准（或几乎符合这些标准）。 受试者年龄为45岁或以上，无混杂因素 除抑郁症外的医学精神疾病。 在最初的 研究期间（时间1）我们计划收集两个依赖（临床， 认知和功能）和独立（生物标志物）变量。 30个月后，受试者将被召回并随访（时间 2)将再次收集相关度量。 的受试者 由于药物医学、精神病学，时间2状态受到混淆 或依从性问题将从研究中删除， 时间 对于剩余的无混杂因素的受试者， 时间1（T1）和时间2时的认知和功能状态 (T2)将用于将每个受试者分配到三个结果之一 组（AD，非AD（NAD）或不确定）。 然后我们将 检查我们的T1生物标志物正确分类的能力， 随访时受试者的AD/NAD状态。 我们亦会研究 T1生物标志物对受试者的贡献（如有） 根据临床和功能形成的亚组。 我们的目标是 开发AD生物标志物，用于实现更早和更长时间的治疗， AD的准确诊断。 这一领域的发展是 AD治疗/干预研究的重要辅助手段。 我们 我们还将从研究样本中提取白细胞和血浆， 今后对遗传和血浆因子谱的分析 与AD 这将使我们能够询问有关 遗传易感性与早期表达的关系 在未来的研究中。

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.