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 i s 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.
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