More specifically, the team used datasets held for people in the spectrum of late-onset Alzheimer’s and Huntington’s disease that was made available by the Harvard Brain Tissue Resource Center, the Religious Orders Study and the Rush Memory and Aging Project Alzheimer's Disease Neuroimaging Initiative.
The algorithm strongly predicted disease stage and progression to advanced disease
As recently reported in the journal Brain, the algorithm strongly predicted the various stages and neuropathological severity of the disease. When applied to blood samples taken at baseline, it also strongly predicted clinical deterioration and progression to advanced stages of the disease, suggesting its potential as a minimally invasive technique for early screening.
Furthermore, the AI tool identified genes and molecular pathways in both blood and brain tissue that were strong predictors of disease evolution. Between 85 and 90% of the most highly predictive molecular pathways identified in the blood were the same as those identified in the brain, suggesting that the underlying molecular changes are similar between the brain and the peripheral body.
“These pathways support the importance of studying the peripheral-brain axis,” .