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How do patterns of energy production in a specialized region of the brain connect to Alzheimer’s-related brain changes?
Elouise Koops, Ph.D.
Massachusetts General Hospital
Boston, MA - United States
Background
Studies suggest that brain changes associated with Alzheimer’s can occur decades before clinical symptoms (such as changes in memory, thinking and reasoning) appear. Researchers are working to find approaches to early detection of Alzheimer’s, long before the onset of symptoms.
A small, specialized region of the brain called the locus coeruleus is known to be especially vulnerable to nerve cell death in the early stages of Alzheimer’s. Additionally, in individuals with Alzheimer’s, the locus coeruleus progressively decreases in volume. These findings suggest that changes in the locus coeruleus may predict future Alzheimer’s-related brain and behavioral changes. However, due to the deep location within the brain and the small size of the locus coeruleus, measuring changes in living humans has been challenging.
Research Plan
Dr. Koops and colleagues believe that tracking energy production (metabolism) in the locus coeruleus may be one way to overcome this challenge. Dr. Koop’s team has pioneered the development of a sophisticated computer technique that may be used with brain scan methods (positron emission tomography, PET) to study Alzheimer’s-related changes in metabolic patterns in the locus coeruleus.
The researchers will use brain scan data from two large-scale, long-term datasets: the Harvard Aging Brain Study (HABS) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Using this data, they will study variability in locus coeruleus metabolism and its association with Alzheimer’s risk. They will investigate if metabolic changes within this brain region predict disease progression and are associated with Alzheimer’s-related brain changes.
Impact
If successful, the results of this project may help identify individuals at risk of developing Alzheimer’s before the onset of clinical symptoms. Early identification may also help determine who may benefit the most from interventions.
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