Wearable tech that monitors body activity might help detect early signs of Alzheimer’s disease, new study shows

Actigraphs are now being used to detect the early stages of Alzheimer’s disease, a progressive condition diagnosed in around six million adults in the United States.

This disease worsens over time, but early and accurate detection can facilitate access to treatment and support.

According to a new study by researchers from the Johns Hopkins Bloomberg School of Public Health, monitoring daily activity using a wrist-worn device might aid in detecting early signs of Alzheimer’s disease.

It was published online in the journal SLEEP on February 21st.

The study involved the analysis of data from wristwatch-like devices called actigraphs worn by 82 older adults participating in a long-term study about aging.

Among these adults, some exhibited a buildup of a protein called amyloid beta in their brains, a known marker for Alzheimer’s disease.

Using a special technique for data analysis, the researchers observed differences in activity levels between those with amyloid buildup and those without.

Adam Spira, a professor at Johns Hopkins Bloomberg School of Public Health, emphasizes the need for further studies to confirm these findings.

Interestingly, similar differences have been observed in two different studies.

“We need to replicate these findings in larger studies, but it is intriguing that we’ve observed a similar distinction between amyloid-positive and amyloid-negative older adults in two independent studies,” he said.

The results of this new study align with findings from an earlier, smaller study led by Spira

This suggests that actigraphs might one day help detect Alzheimer’s disease before it significantly impacts thinking and memory.

The previous study gathered information from participants involved in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4) and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies.

In their latest research, Spira and his team examined 82 community-dwelling individuals, with an average age of around 76.

Each participant underwent a PET scan to measure amyloid levels in their brains and wore an actigraph continuously for a week.

Utilizing a specialized statistical method known as FOSR (function-on-scalar regression), the researchers uncovered that the 25 participants with amyloid buildup exhibited higher activity levels during the early afternoon, specifically from 1:00 to 3:30 p.m., and demonstrated reduced variability in activity between 1:30 to 4:00 p.m. and 7:30 to 10:30 p.m.

While some of these differences were less pronounced in other analyses, the heightened afternoon activity and decreased variability echoed previous findings by the researchers.

Alzheimer’s disease is the primary cause of dementia. It is characterized by the accumulation of amyloid plaques and tangles in the brain, a process that can begin many years before the disease is clinically diagnosed.

Currently, the only approved treatments for Alzheimer’s disease focus on slowing its progression by targeting amyloid beta and reducing plaque formation.

Researchers believe these treatments may be more effective if administered earlier, ideally before the onset of dementia symptoms.

Sleep and waking patterns have been examined as potential early indicators of Alzheimer’s disease.

Individuals with Alzheimer’s often exhibit irregular sleep patterns, and previous research indicates that amyloid accumulation may influence sleep patterns in the early stages of the disease.

Moreover, there is evidence suggesting that sleep deprivation may contribute to increased amyloid buildup, thus establishing a potential cycle.

These findings imply that in the future, older adults may utilize to monitor their sleep and activity patterns.

Should someone display unusual activity patterns, they could consult with their doctor regarding Alzheimer’s screening.

The participants in the study were part of the Baltimore Longitudinal Study of Aging, which is conducted by the National Institute on Aging (NIA), a division of the National Institutes of Health (NIH). Some members of the NIA team also contributed to this study.

Standard statistical methods, without utilizing FOSR, did not reveal significant differences in activity or sleep patterns. This suggests that these conventional methods may not be as effective in detecting amyloid buildup.

In a previous actigraphy study, researchers employed FOSR-based analyses with a different group of 59 participants.

The researchers found that individuals with amyloid buildup exhibited increased activity levels in the afternoon and reduced variation in activity during that time compared to those without amyloid buildup.

The exact reason why amyloid buildup influences activity patterns at specific times of the day remains uncertain.

However, the researchers speculate that it might be linked to a common phenomenon in Alzheimer’s known as “sundowning,” where individuals experience increased agitation in the afternoon and early evening.

“It’s possible that the heightened afternoon activity we observed is indicative of ‘preclinical sundowning,'” remarked Spira, noting that it’s premature for older adults to be concerned if their fitness trackers indicate increased activity in the afternoon.

More research utilizing actigraphs is necessary to comprehend how activity patterns evolve with Alzheimer’s disease and whether they correlate with changes in cognitive function and memory over time.

Spira and his team aim to conduct additional studies similar to this one, including longer-term investigations, to ascertain whether changes in activity patterns are indeed linked to amyloid buildup and cognitive decline.

The study titled “Evaluating a Novel 24-Hour Rest/Activity Rhythm Marker of Preclinical β-Amyloid Deposition” was co-authored by Adam Spira and others, indicating a collaborative effort among various researchers in the field.

For further information on the plaques, tangles, causes, symptoms, and pathology of Alzheimer’s disease, you can watch this informative video: