Identifying Age-Related Proteomic Changes That Predict Future Onset of Amyloid Beta Aggregation in Late-Onset Alzheimer’s Disease

Aging is the single greatest risk factor for late-onset Alzheimer’s disease. The risk for Alzheimer’s disease increases dramatically after the age of 65 and continues to rise with age. Therefore, we need to understand how brain aging causes Alzheimer’s disease to know how to prevent it. A protein called amyloid beta can clump together into plaques and these plaques also dramatically increase with age. These amyloid beta plaques are one of the first changes to occur in the brains of people developing Alzheimer’s disease. However, why amyloid beta clumps together in plaques in some people but not others is not known.  If we can figure out why aging causes amyloid beta to clump together, we could predict who will go on to get Alzheimer’s at the earliest stages and may be able to prevent the disease.  

This grant proposal aims to measure thousands of proteins in the fluid that surrounds the brain and use advanced artificial intelligence machine learning to look at these protein stages before any amyloid beta aggregation in the brain occurs.  We can detect this state by looking at changes in the blood amyloid beta biomarkers and refer to it as “pre-amyloidosis”. By doing this, we will determine what protein pathways are associated with future amyloid beta plaques so we can understand why these amyloid plaques form. Through these analyses, we aim to discover new age-associated pathways that may cause Alzheimer’s disease.  These identified pathways may provide targets to develop new treatments for preventing amyloid beta aggregation that may prevent Alzheimer’s disease.