An international research team, led by Queen Mary University of London, has made a groundbreaking discovery in the field of dementia prediction. Their new method can accurately predict dementia up to nine years before diagnosis, with over 80% accuracy. This development offers a more precise alternative to traditional memory tests and brain shrinkage measurements commonly used for diagnosing dementia.
Published in Nature Mental Health, the researchers utilized functional MRI (fMRI) scans to analyze changes in the brain’s ‘default mode network’ (DMN). The DMN is a neural network crucial for cognitive functions and is typically the first to be impacted by Alzheimer’s disease.
Associate Professor Adeel Razi from Monash University’s School of Psychological Sciences and the Turner Institute for Brain and Mental Health highlighted the significance of this new predictive method. Razi emphasized that previous attempts to treat Alzheimer’s disease have often failed due to focusing on advanced disease stages where brain cell damage is irreversible.
Razi stated, ‘Our innovative approach to predicting dementia well in advance has the potential to revolutionize the field, allowing for the development of therapies at earlier disease stages. By leveraging extensive datasets and advanced fMRI techniques, we can now identify individuals at high risk for dementia years before symptoms manifest, opening doors to proactive and personalized healthcare strategies.’
The study, spearheaded by Professor Charles Marshall from Queen Mary University of London, involved analyzing fMRI scans from more than 1,100 volunteers in the UK Biobank database. This resource contains genetic and health data from half a million UK participants. The researchers assessed the effective connectivity between ten brain regions forming the default mode network to estimate each patient’s probability of developing dementia.
By comparing connectivity patterns to distinguish between those indicative of dementia and healthy controls, the researchers were able to assign each patient a probability value for dementia development. This novel biomarker could significantly enhance early detection and treatment of dementia, ultimately leading to improved patient outcomes.
