Get your first bottle FREE by taking a short quiz

Poor spatial navigation: a potential early predictor of Alzheimer’s disease decades before memory loss

Poor spatial navigation: a potential early predictor of Alzheimer’s disease decades before memory loss

A recent study conducted by UCL suggests that poor spatial navigation could serve as an early indicator of Alzheimer’s disease, potentially decades before the onset of memory loss symptoms.1

 

This research discusses the possibility of developing a diagnostic support tool for identifying individuals at risk of Alzheimer’s in the future.

 

Utilizing virtual reality technology, researchers evaluated the spatial navigation skills of 100 asymptomatic adults aged 43-66, significantly younger than the estimated age of dementia onset.

 

The study revealed that individuals with a higher risk of developing Alzheimer’s disease displayed impaired spatial navigation abilities, impacting attention, memory, perception, and decision-making.

 

Intriguingly, this impairment was observed before any other cognitive decline, particularly memory issues.

 

The study also revealed strong gender differences in performance, with men exhibiting impairment in spatial navigation while women did not.

 

These findings suggest that spatial navigation deficits could manifest years or even decades before the appearance of other Alzheimer’s symptoms, according to experts.

 

Early Detection and Diagnostic Advances

 

Dr. Coco Newton, the lead author from UCL Institute of Cognitive Neuroscience, conducted the research while at the University of Cambridge.

 

She noted that their findings suggested that changes in navigation behavior could serve as the earliest indication of Alzheimer’s disease continuum, marking the transition when people move from being unimpaired to displaying symptomatic manifestations.

 

Participants in the study, all part of the PREVENT-Dementia prospective cohort study, shared a common risk of Alzheimer’s disease. This was either through genetic predisposition, family history, or lifestyle factors like low physical activity levels.

 

Led by Professor Dennis Chan, the study utilized a test devised by Dr. Andrea Castegnaro and Professor Neil Burgess. Participants wore VR headsets and navigated through a virtual environment as part of the assessment.

 

Dr. Newton highlighted the plans to translate these findings into a diagnostic clinical decision support tool for the NHS, aiming to revolutionize dementia diagnosis and provide timely interventions.

 

In her words, “We are now taking these findings forward to develop a diagnostic clinical decision support tool for the NHS in the coming years, which is a completely new way of approaching diagnostics and will hopefully help people to get a more timely and accurate diagnosis.”

 

The Future of Alzheimer’s Research and Treatment

 

She further explained the significance of these developments, particularly in light of the emergence of anti-amyloid treatments for Alzheimer’s disease, which are most effective during the early stages.

 

Additionally, it highlights the importance of studying the differing vulnerabilities of men and women to Alzheimer’s and integrating gender considerations into diagnosis and treatment strategies.

 

The research was conducted in collaboration with the University of Cambridge and was funded by the Alzheimer’s Society along with an MSD research grant. Dr. Richard Oakley, the associate director of research and innovation at Alzheimer’s Society, emphasized the importance of early and accurate diagnosis for individuals to access appropriate support, plan for the future, and receive suitable treatment.

 

He highlighted the alarming statistic that one in three people born today will eventually develop dementia.

 

Dr. Oakley pointed out that while early symptoms of dementia can be subtle and difficult to detect, issues with navigation are believed to be among the initial signs of Alzheimer’s disease.

 

He noted that more efforts were needed to develop this technology, expressing optimism about the potential of this research to detect disease-specific changes early on, ultimately improving the lives of individuals living with dementia.

 

References

  1. Newton C, Pope M, Rua C, et al. (in press). Entorhinal-based path integration selectively predicts midlife risk of Alzheimer’s disease. Alzheimers Dement. 2024. doi:10.1002/atz.13733
share the article