Mayo Clinic scientists have developed a groundbreaking method to predict Alzheimer’s risk up to decades before symptoms appear, using a blend of brain scans and genetics. Published in The Lancet Neurology, the study employs data from the Mayo Clinic Study of Aging, tracking thousands of participants over time. Led by Dr. Clifford Jack Jr., the team analyzed brain scans, genetic data, and medical records from over 5,800 adults to construct a predictive model.
This model calculates both a person’s 10-year and lifetime risk of cognitive decline, which could significantly alter the detection and treatment strategies for Alzheimer’s in the future. The study highlights the role of two key proteins, amyloid and tau, which accumulate in the brain years before symptoms develop, disrupting communication between neurons and ultimately leading to memory loss and cognitive impairments.
By using specialized brain imaging, researchers were able to measure amyloid buildup, providing a quantifiable scale of biological severity ranging from 0 to 100. The findings suggest that early risk assessment could enable individuals and their doctors to make critical decisions about therapy initiation and lifestyle changes to potentially delay symptom onset, drawing parallels to how cholesterol levels predict heart attack risk.
Additional factors like age, sex, and the presence of the APOE ε4 gene were integrated into the model to enhance its predictive accuracy. While the study has its limitations, including its focus on older white adults and the necessity of costly specialized brain scans, researchers are optimistic about future advancements, such as simpler blood tests for amyloid or other biomarkers, that could make risk assessment more accessible.