The process to classify the pattern where the cells in the brain are lost or damaged in Alzheimer's using MRIs are capable of predicting cognitive impairment in Parkinson's disease, reveals new study.
Researchers from the Perelman School of Medicine at the University of Pennsylvania also found that higher baseline Alzheimer's patterns of atrophy predicted long-term cognitive decline in cognitively normal Parkinson's patients.
"On the basis of a simple neuroimaging study, we can now predict which patients with Parkinson's disease will experience long-term cognitive decline or develop dementia in the future," said the study's lead author, Daniel Weintraub, MD, associate professor of Geriatric Psychiatry with Penn's Perelman School of Medicine and the Philadelphia Veterans Affairs Medical Center.
This research raises the possibility that both Alzheimer's disease and Parkinson's disease pathology contribute to cognitive decline in Parkinson's disease.
As biomarkers for Alzheimer's and Parkinson's disease continue to emerge, the researchers suggest at least an overlap in regions undergoing neurodegeneration with cognitive decline, and point to the Spatial Pattern of Abnormalities for Recognition of Alzheimer's disease (SPARE-AD) classification system to detect brain atrophy in Parkinson's disease, to detect patients at imminent risk of cognitive decline before clinically identifiable symptoms emerge.
The Penn research team applied a pattern classification individual-based score, the SPARE-AD score, to a cross-sectional cohort of 84 Parkinson's patients including patients with dementia, mild cognitive impairment and no dementia.
In the cross-sectional analyses, the SPARE-AD score correlated to cognitive impairment across all groups. From this group, 59 Parkinson's patients without dementia were followed for an additional two years.
Researchers determined that a higher baseline SPARE-AD score predicted worsening cognitive performance over time, even in those patients with normal cognition at baseline.
The study has been published online in Brain.