Can we identify novel biomarkers for early detection of Alzheimer’s disease?
Can we identify novel biomarkers for early detection of Alzheimer’s disease (AD) by targeting the brain-draining lymph nodes?
Alzheimer’s disease (AD) affects >55 million people globally, placing a heavy socioeconomic burden on all countries. The majority of clinical trials for the treatment of AD have reported minimal benefits. One of the major reasons was that the recruited patients were at late disease stage with irreversible damage to the brain. They have also shown that better therapeutic outcomes can be achieved in earlier AD stage.
Scientists have identified antibodies uniquely present in people diagnosed with AD; however, these antibodies were discovered at the later stages of AD, and are less useful for early detection. We believe that specific antibodies are produced during preclinical AD, and the identification and detection of these antibodies could help determine if a person will develop AD and allow for early treatment to stop disease progression.
Recently lymphatic vessels were discovered that drain fluid, waste products and immune cells from the brain to lymph nodes in the neck. Within the lymph node the activation of specialized immune cells leads to the production of a variety of antibodies. In this project, we will screen for antibodies that are uniquely produced in the lymph nodes of pre-symptomatic AD mice (vs. non-AD mice). As these antibodies will eventually distribute into the blood, sensitive assays will subsequently be developed to detect the antibodies in the blood.
The project will demonstrate the feasibility of detecting preclinical AD before the onset of symptoms using a blood test that can be trialled and validated in humans in the future. Once this approach is approved for clinical use, clinicians will be able to determine if a person is at risk of developing AD based on blood test results. If one is at risk, early intervention can be initiated to prevent or even cure AD, and a better therapeutic outcome and quality of life is expected.
Research team
Supervisor
Research group
Collaborators
Associate Professor Natalie Trevaskis
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