Poor spatial navigation could predict Alzheimer’s before symptom onset

by | 4th Mar 2024 | News

Around 900,000 people in the UK are affected by the progressive neurodegenerative disease

Researchers from University College London (UCL), in collaboration with the University of Cambridge, have revealed that impaired spatial navigation could determine the risk of Alzheimer’s disease (AD) before the onset of symptoms.

Published in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, researchers used virtual reality (VR) to test the spatial navigation of 100 asymptomatic adults from the PREVENT-Dementia study.

Affecting around 900.000 people in the UK, AD is a neurodegenerative disorder that progressively destroys memory, thinking skills and the ability to carry out simple day-to-day tasks.

Researchers recruited adults aged between 43 and 66 years who had a hereditary or physiological risk of AD related to either the APOE-ε4 allele gene, a family history of AD or lifestyle risk factors, including low levels of physical activity, who were around 25 years younger than their estimated age of dementia onset.

Funded by the Alzheimer’s Society and Merck & Co (known as MSD outside the US and Canada), participants in the study were asked to complete a test within a virtual environment while wearing VR headsets.

The study revealed that those who were at greater risk of developing AD were selectively impaired on the VR navigation task without a corresponding impairment on other cognitive tests and regardless of risk factors, suggesting that spatial navigation impairments may develop years before the onset of any other symptoms.

Researchers also revealed a strong difference in how participants performed in the context of gender, with the impairment being observed only in men and not women.

Author of the study, Dr Coco Newton from the UCL Institute of Cognitive Neuroscience, said: “This type of navigation behaviour change might represent the very earliest diagnostic signal in the AD continuum.

“We are now taking these findings forward to develop a diagnostic clinical decision support tool for the NHS in the coming years” to “help people to get a more timely and accurate diagnosis”.

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