Monitoring daily activity patterns using a wrist-worn device may detect early warning signs of Alzheimer’s disease, according to a new study led by researchers at the Johns Hopkins Bloomberg School of Public Health.
The researchers analyzed movement data from wristwatch-like devices called actigraphs worn by 82 cognitively healthy older adults who were participants in a long-running study of aging. Some of the participants had detectable brain amyloid buildup as measured by PET scan. Buildup of the protein amyloid beta in the brain is a key feature of Alzheimer’s disease.
Using a sensitive statistical technique, the researchers found significant differences between this “amyloid-positive” group and “amyloid-negative” participants in mean activity in certain afternoon periods and differences in variability of activity across days in a broader range of time windows.
The new study was published online February 21 in the journal SLEEP.
For their new study, researchers investigated the potential of actigraph-based monitoring in 82 community-dwelling individuals whose average age was about 76. Each participant had a PET scan to measure brain amyloid and wore an actigraph 24 hours per day for one week. Using a sensitive statistical technique called FOSR (function-on-scalar regression), the researchers found that the 25 amyloid-positive participants, compared to the 57 amyloid-negative participants, had higher mean activity during the early afternoon, 1:00 to 3:30 p.m., and less day-to-day variability in activity from 1:30 to 4:00 p.m. and 7:30 to 10:30 p.m.
In more conservative analyses, some of these time windows with differences were no longer statistically significant.
The individuals in the new study were participants in a long-running study, the Baltimore Longitudinal Study of Aging, which is conducted by the Intramural Research Program of the National Institute on Aging (NIA), part of the National Institutes of Health (NIH). Several members of the NIA team were co-authors of the study.
Standard, non-FOSR statistical methods did not detect any significant differences in activity or sleep patterns, suggesting the methods may be less sensitive to amyloid deposition.
Johns Hopkins Bloomberg School of Public Health release on Newswise
