A team of researchers at Queen Mary University of London has created a new technique that can predict dementia with over 80% accuracy, and it can do so up to nine years before an official diagnosis is made. This new method offers a more precise way to predict dementia compared to the commonly used memory tests or measurements of brain shrinkage.using dementia.
Professor Charles Marshall and his team created a test that predicts Alzheimer’s disease by studying functional MRI (fMRI) scans to identify changes in the brain’s ‘default mode network’ (DMN). The DMN connects different brain regions to perform specific cognitive functions and is the first neural network to be impacted by Alzheimer’s.
The researchers analyzed fMRI scans from more than 1,100 volunteers in the UK Biobank, a biomedical database and research resource with genetic and health data from half a million UK participants. They used this data to estimate the effective connectivity between ten brain regions to detect Alzheimer’s disease. rnrnThe default mode network in the brain was the focus of the study. The researchers used the effective connectivity pattern of each patient to calculate their probability of developing dementia. They then compared these predictions to the patients’ medical records from the UK Biobank. The results indicated that the model was able to accurately predict the onset of dementia up to nine years before an official diagnosis, with over 80% accuracy. Additionally, in cases where the volunteers had developed dementia, the model was able to identify this as well.Charles Marshall, a Professor and Honorary Consultant Neurologist, headed the team of researchers. They found that the DMN could accurately predict the time it would take for a dementia diagnosis to be made, with a margin of error of two years. The study also revealed that genetic risk factors for Alzheimer’s disease were strongly linked to changes in DMN connectivity, suggesting that these changes are specific to Alzheimer’s disease. Additionally, social isolation was found to increase the risk of dementia by affecting connectivity in the DMN.The Centre for Preventive Neurology at Queen Mary’s Wolfson Institute of Population Health is focused on predicting who will develop dementia in the future. This is crucial for developing treatments to prevent the irreversible loss of brain cells that lead to dementia symptoms. While there has been progress in detecting the proteins in the brain that can cause Alzheimer’s disease, many individuals can live for years with these proteins without showing signs of dementia. The Centre hopes that the brain function measure they have created will provide a more accurate prediction of who will develop dementia.By developing a better understanding of who might develop dementia and when, we hope to be able to determine who could benefit from potential future treatments,” Samuel Ereira, lead author and Academic Foundation Programme Doctor at the Centre for Preventive Neurology, Wolfson Institute of Population Health, explained. “Through the use of these analysis techniques on large datasets, we can pinpoint those at a high risk of dementia and also uncover the environmental factors that may have contributed to their high risk. There is significant potential for applying these methods to various brain networks and populations, which can help us gain a deeper insight into the interactions between the environment, neurobiology, and illness in different contexts.Dementia and other neurodegenerative diseases could potentially be detected early using fMRI, a non-invasive medical imaging tool. It only takes about 6 minutes to collect the necessary data on an MRI scanner, making it possible to integrate into existing diagnostic pathways, especially where MRI is already being used.”
