DESCRIPTION (provided by applicant): Alzheimer's disease (AD) is a major public health issue facing the world's aging population; however, to date, there is no rapid and cost effective means for early diagnosis that is widely accessible. It has been suggested that a blood-based screening will become the first-step in the AD diagnostic process, although no such test currently exists. In our prior work through the Texas Alzheimer's Research & Care Consortium (TARCC), we created a serum-based screening algorithm that correctly classified 94% of those with and without AD. We then followed that work-up by creating a blood-based algorithm in the TARCC that worked across both serum and plasma that, when applied to the ADNI plasma samples, correctly classified 89% of those with and without AD in the entirely independent cohort. The long-term goal of this project is the validation of the our blood-based screening instrument for AD. The specific aims of the current project are as follows: Specific Aim 1: To test the reliability and validity of our previously created blood-based screening algorithm, and Specific Aim 2: To validate our blood-based algorithms against other diagnostic modalities (i.e., neuropathological findings and CSF analyses). Multiplex serum- and plasma-based biomarker assays (using electrochemiluminescence) will be conducted on 1,100 samples from the TARCC and Mayo Clinic Jacksonville biobanks. The establishment of a blood-based screening instrument for AD will significantly change the field of geriatric medicine. Such a tool would fit into the existing medical infrastructure as a frontline population-based screening device where positive findings can be followed-up with clinical, imaging or CSF assessments. This overall approach will increase accessibility to standard care far beyond what can be offered by other methodologies. This approach will also provide a more rapid and cost-efficient means for screening into AD clinical trials.
|Effective start/end date||15/04/12 → 31/03/15|
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.