A method discovered to predict Alzheimer’s disease nine years in advance

Researchers have discovered a way to predict dementia with 80 percent accuracy nine years before diagnosis, Neuroscience News reports.

The approach outperformed traditional memory tests and measured brain shrinkage. The study used data from more than 1,100 volunteers and highlights potential applications for early intervention.

In this analysis, researchers from Queen Mary University of London used functional NRI (fMRI) images to analyse changes in the brain’s ‘default mode network’ (DMN), which is affected in the early stages of Alzheimer’s disease.

The “default mode network” is a brain network that connects different parts of the brain to perform specific cognitive functions, and it is also the first neural network affected by Alzheimer’s disease.

More details and findings

Researchers at Queen Mary University of London used fMRI scans of more than 1,100 volunteers from UK Biobank, an extensive biomedical database and research resource containing genetic and health information on half a million UK participants, to estimate effective connectivity between the 10 brain regions that make up the default mode network.

“Predicting who will develop dementia in the future is crucial for finding effective treatments,” said Charles Marshall, lead author of the research team, referring to the future results of the study. “These treatments could prevent the irreversible destruction of brain cells that leads to dementia symptoms.” “We hope that this test will give us a more accurate picture of if and when someone will actually develop dementia, so that we can determine if they could benefit from future treatments,” he continued.

The researchers also found that social isolation increases the risk of dementia, likely through its effects on connectivity in the brain’s default mode network.