2024 Alzheimer's Association Research Grant (AARG)

Stratifying ARIA risk with cerebral amyloid angiopathy biomarkers

Can brain scans help predict risk of treatment side effects?

Andreas Charidimou, M.D., Ph.D.
Boston University
Boston, MA - United States

Background

Individuals with Alzheimer’s disease are at high risk for another disease called cerebral amyloid angiopathy (CAA). In CAA, brain changes can lead to stiffening of the vessels and problems with blood circulation. Recent studies have also found that having CAA is a risk factor for developing a negative side effect of certain Alzheimer’s-related treatments, the side effect is known as amyloid-related imaging abnormalities (or ARIA), which can lead to changes in mental state, seizures, tremor, headache, brain blood vessel damage and brain bleeding.

Current research is limited in measures to help evaluate whether someone is at higher risk of ARIA. Dr. Antreas Charidimou and colleagues plan to identify biological markers (biomarkers) of CAA using a brain scanning technique called magnetic resonance imaging (MRI), which might help predict who is most at risk for developing ARIA from Alzheimer’s treatments.

Research Plan

Dr. Charidimou and colleagues will leverage the Boston University Alzheimer’s Disease Research Center (BU ADRC) for access to clinical and brain imaging data from individuals with Alzheimer’s. The team will assess structural brain MRIs from 400 participants and compare that to demographic information, clinical data, and details of their diagnosis. They will look for various indicators of small vessel disease and signs of CAA, such as microbleeds.

The team will also study brain samples from 400 study participants who had Alzheimer’s to calculate the presence and severity of CAA. They plan to determine what portion of people with Alzheimer’s might have undiagnosed CAA.

Ultimately, the research team intend to update and adapt MRI-based criteria for CAA diagnosis, potentially with additional MRI biomarkers.

Impact

Results from this study could help update clinical criteria for CAA, which could help predict risk of ARIA. This may help to better select people who could be low-risk candidates for certain Alzheimer’s treatments.