The groundbreaking new method predicting the onset of dementia years in advance

Jun 07, 2024
The new approach "bridges a critical gap in dementia diagnosis, offering a non-invasive biomarker that could transform early detection and treatment, ultimately improving patient outcomes." Source: Getty Images.

Diagnosing dementia accurately has long been a challenging task, from distinguishing the normal effects of ageing to navigating the various underlying causes and the subjective nature of symptoms.

In addition, early warning signs can go unnoticed with the person affected unaware of any changes in their cognition.

However, researchers have now developed a new method that can predict the onset of dementia with over 80 per cent accuracy up to nine years before diagnosis, providing a more accurate way to predict dementia than memory tests or measurements of brain shrinkage that are currently administered.

Researchers developed the predictive test by analysing functional MRI (fMRI) scans to detect changes in the brain’s ‘default mode network’ (DMN). The DMN connects regions of the brain to perform specific cognitive functions and is the first neural network to be affected by Alzheimer’s disease.

Study co-author, Associate Professor Adeel Razi from Monash University’s School of Psychological Sciences and the Turner Institute for Brain and Mental Health, said the new test is a “game changer” as health practitioners can now offer therapies earlier.

“Our new method for predicting who will develop dementia well in advance will be a game changer, enabling the development of therapies earlier in the disease process,” Associate Professor Razi said.

“By leveraging large datasets and advanced fMRI techniques, we can now identify individuals at high risk for dementia years before symptoms appear, paving the way for proactive and personalised healthcare strategies.

“This innovative approach bridges a critical gap in dementia diagnosis, offering a non-invasive biomarker that could transform early detection and treatment, ultimately improving patient outcomes.”

Led by Professor Charles Marshall from Queen Mary University of London, researchers in the study assigned each patient a probability of dementia based on their brain connectivity patterns. They compared these predictions to medical records from the UK Biobank and found the model accurately predicted dementia onset up to nine years before diagnosis, with over 80 per cent accuracy.

The study also explored whether changes in the DMN were linked to known dementia risk factors. They discovered that genetic risk for Alzheimer’s disease correlated strongly with DMN connectivity changes, suggesting specificity to Alzheimer’s. Additionally, social isolation was identified as a potential risk factor, impacting DMN connectivity and potentially increasing dementia risk.

Professor Marshall is hopeful “that the measure of brain function that we have developed will allow us to be much more precise about whether someone is actually going to develop dementia, and how soon, so that we can identify whether they might benefit from future treatments.”

-with AAP.

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