2024 Alzheimer's Association Research Fellowship to Promote Diversity (AARF-D)
Multimodal AI based Predictor of Alzheimer’s Disease (MAP-AD)
Can a new computer-based technology be used to assess Alzheimer’s risk?
Apoorva Safai, Ph.D.
University of Wisconsin-Madison (Board of Regents University of Wisconsin System)
Madison, WI - United States
Background
Studies have shown that Alzheimer’s, like other chronic diseases, can develop as a result of multiple contributing factors, such as genetics, environment, and lifestyle, rather than a single cause. This also includes social determinants of health, such as education, income, and access to healthcare, that also contribute to one’s lifetime health, including risk of developing Alzheimer’s or other dementia.
Brain scanning techniques are some of the most reliable tools currently available to measure the hallmark brain changes that occur in Alzheimer’s, including the accumulation of amyloid plaques and tau tangles and structural brain changes. However, these methods do not consider the impact of social determinants of health on Alzheimer’s risk.
Research Plan
For their studies, Dr. Apoorva Safai and colleagues will use an advanced computer science technique called machine learning, a form of artificial intelligence, to develop a new screening tool for Alzheimer’s. Their tool, called Multimodal Artificial intelligence-based Prediction of Alzheimer’s disease (MAP-AD), will leverage artificial intelligence to examine the impact of social determinants of health on images that measure the hallmark brain changes in Alzheimer’s. The researchers will examine the association between various social determinants of health with cognitive function and amyloid plaque and tau tangle levels (measured by both brain scanning techniques and blood biomarkers) using data from more than 3,000 individuals with Alzheimer’s. Next, the team will examine the validity of the MAP-AD tool by assessing whether MAP-AD scores can reliably predict Alzheimer’s risk in a separate cohort of individuals.
Impact
If successful, this study may develop a novel screening tool for Alzheimer’s that considers the impact of social determinants of health on Alzheimer’s risk. The findings may also lead to new prevention strategies for those at greatest risk of developing the disease.