Pioneering Research on Alzheimer’s Disease: Recognizing Early Signs with Activity Trackers

Pioneering Research on Alzheimer’s Disease: Recognizing Early Signs with Activity Trackers
Alzheimer’s disease, a progressive neurodegenerative disorder, is a major public health concern affecting millions of people worldwide. This pioneering research focuses on utilizing activity trackers to identify early signs of Alzheimer’s disease, providing a potential breakthrough in early detection and intervention. By monitoring key indicators such as sleep patterns, physical activity, and daily routines, researchers aim to recognize subtle changes associated with the onset of Alzheimer’s disease. Understanding these early signs is crucial for developing effective treatments and improving the quality of life for individuals affected by this devastating condition.
Unlocking Early Indicators of Alzheimer’s Disease Using Activity Trackers
Cutting-edge exploration into the early detection of Alzheimer’s disease through the use of activity trackers is revolutionizing the field of neurodegenerative research. By harnessing the power of wearable technology, scientists are uncovering subtle behavioral changes that may signal the onset of Alzheimer’s disease, offering a new avenue for early intervention and treatment. This innovative approach aims to identify key biomarkers and patterns in daily activities that could provide valuable insights into the progression of Alzheimer’s disease, ultimately leading to improved diagnostic methods and personalized care strategies.

Alzheimer’s Disease Prevalence and Early Detection

Researchers estimate that about 22% of all adults aged 50 and above around the world have some stage of Alzheimer’s disease. With this number expected to increase, researchers are focused on finding new ways to recognize early warning signs of this type of dementia. Although there is currently no cure for Alzheimer’s disease, medications are available for the earliest stages of the disease to help slow down its progression. One of the latest studies on Alzheimer’s disease early detection research comes from the Johns Hopkins Bloomberg School of Public Health. In a new study published in the journal SLEEP, scientists found that monitoring a person’s daily activity patterns through a wrist-worn device may spot early warning signs of Alzheimer’s disease.

Scientists from the Johns Hopkins Bloomberg School of Public Health found that monitoring a person’s daily activity patterns through a wrist-worn device may spot early warning signs of this type of dementia. The study aims to contribute to the development of new methods for early detection of Alzheimer’s disease, which is crucial for providing timely medical intervention and support to individuals at risk. By understanding the prevalence of Alzheimer’s disease and the importance of early detection, researchers can work towards developing effective strategies for managing and treating the disease.

Daily Activity Patterns and Health

Each day, most people have a set pattern or routine of certain behaviors, including activity. For example, some people may be more active in the morning while others move more in the evening. This is known as a person’s daily activity pattern. Past studies have linked a consistently highly active daily activity pattern with a healthier cardiometabolic profile, which may help lower a person’s cardiovascular disease risk. Researchers have also linked a regular daily activity pattern to better cognition, mental health, and improved health in older adults. A study published in May 2018 reported that daily activity patterns of older men may be predictive biomarkers for changes in clinically relevant outcomes for mortality, as well as changes in sleep and cognition. And research published in October 2019 found that a more fragmented daily activity pattern was associated with an increased mortality risk in older adults.

Understanding the relationship between daily activity patterns and health can provide valuable insights into the early detection and management of various health conditions, including Alzheimer’s disease. By analyzing daily activity patterns, researchers can identify potential biomarkers and risk factors associated with cognitive decline and dementia. This knowledge can contribute to the development of innovative approaches for monitoring and assessing individuals at risk, ultimately leading to improved health outcomes and quality of life for older adults.

What is an Actigraph?

For this study, researchers studied the data produced by a wristwatch-like device called an actigraph that was worn by 82 cognitively healthy older adults who were part of the long-running Baltimore Longitudinal Study of Aging. “For decades now, sleep researchers have used wrist-worn actigraphs to study sleep in older adults,” Dr. Adam Spira, professor in the Department of Mental Health at the Johns Hopkins Bloomberg School of Public Health and lead author of this study, explained to Medical News Today. “The technology — typically an accelerometer — is similar to that used in commercially available fitness trackers that many people use,” he noted. “Because of growing evidence that sleep disturbances may contribute to the risk of Alzheimer’s disease, my colleagues and I applied for a grant from the National Institute on Aging (NIA) to study links between poor sleep and Alzheimer’s disease, including through the use of wrist actigraphs,” Dr. Spira added. “We received that grant and this work is a direct result.”

The actigraph is a valuable tool for monitoring and analyzing daily activity patterns, sleep quality, and other behavioral factors that may be associated with the risk of Alzheimer’s disease and cognitive decline. By leveraging advanced technologies such as actigraphs, researchers can gain deeper insights into the early warning signs and risk factors for Alzheimer’s disease, paving the way for more effective interventions and preventive strategies.

Beta-Amyloid Presence Linked to Different Daily Activity Pattern

Of the 82 study participants with an average age of 76, some had detectable amounts of the protein beta-amyloid in the brain. Amyloid plaques are considered one of the hallmarks of Alzheimer’s disease. When analyzing the data collected by the actigraph devices, the researchers reported significant differences between the 25 “amyloid-positive” and 57 “amyloid-negative” participant groups in average activity during certain times in the afternoon, as well as differences in the variability of activity throughout the days during a broader time window. The scientists discovered those in the “amyloid-positive” group had higher average activity during the early afternoon (1:00 p.m. to 3:30 p.m.) and fewer day-to-day activity changes from 1:30 to 4:00 p.m. and 7:30 to 10:30 p.m. “Our results are noteworthy because they showed, in people who were cognitively normal, that those with detectable beta-amyloid in their brains had different patterns of activity at particular times of day from those without beta-amyloid,” Dr. Spira said. “This is a novel finding.”

The presence of beta-amyloid in the brain is closely linked to changes in daily activity patterns, which may serve as a potential biomarker for early detection of Alzheimer’s disease. By identifying these associations, researchers can develop targeted interventions and monitoring strategies to assess individuals at risk and provide timely support and medical care to those affected by the disease.

Can Mainstream Activity Trackers Help Predict Cognitive Decline?

While in this study researchers used a scientific-based wristwatch-type device, would people one day be able to detect early warning signs of Alzheimer’s disease through mainstream fitness and activity trackers like Fitbit, Garmin, and the Apple Watch? At this point, Dr. Spira said people should not try to interpret data from their own devices as a sign of whether or not they have amyloid in their brains. “Whether these methods could be used in the future for early detection of Alzheimer’s disease depends on whether further studies support our findings or identify other ‘digital signatures’ of Alzheimer’s disease that can be detected using wearable devices,” he explained. “If they do, it is conceivable that one day, wearable devices will be used to help identify people at elevated risk for neurological disorders like Alzheimer’s disease. We’re not there yet, though,” Dr. Spira cautioned.

The potential use of mainstream activity trackers for predicting cognitive decline and early signs of Alzheimer’s disease presents an intriguing area for future research and technological advancements. By exploring the capabilities of wearable devices, researchers can develop innovative approaches for monitoring and assessing neurological disorders, ultimately leading to improved diagnostic tools and interventions for individuals at risk of cognitive decline.

Potential Framework for ‘Sundowning’

After reviewing this study, Dr. Clifford Segil, a neurologist at Providence Saint John’s Health Center in Santa Monica, CA, not involved in the research, admitted to MNT that he was confused by the study, as Alzheimer’s dementia is a memory loss disorder and not a movement disorder. “The data supports that the older adults in this study who were amyloid-positive moved better during the early afternoon and had less movement variability in the late afternoon and evening,” Dr. Segil explained. “I think the authors are trying to provide a framework to look at ‘sundowning,’ which is a phenomenon when patients with Alzheimer’s Dementia become more agitated at night. I am assuming an agitated old adult would have higher movement variability than a non-agitated older adult.” – Dr. Clifford Segil “I don’t think a wearable recording ‘wrist actigraphy’ will be used clinically in the diagnosis of a memory loss disorder like Alzheimer’s dementia in the future,” he continued. “Decreased activity as people age is normal and more worrisome for other medical comorbidities like heart disease, neuropathies, or other medical problems more than dementia. I would love to see this methodology applied to the diagnosis of a neurological movement disorder, Parkinson’s disease,” said Dr. Segil.

The study’s findings may provide a potential framework for understanding the phenomenon of “sundowning” in patients with Alzheimer’s dementia. By examining the relationship between daily activity patterns and behavioral changes, researchers can gain valuable insights into the management and care of individuals affected by Alzheimer’s disease, ultimately leading to improved support and interventions for patients and their caregivers.

RESULT

Alzheimer’s Disease is a debilitating condition that gradually impairs memory, thinking, and behavior. It is characterized by the accumulation of abnormal protein deposits in the brain, leading to the death of nerve cells and the shrinking of brain tissue. As the disease progresses, individuals may experience difficulty with daily tasks, communication, and even recognizing loved ones. Currently, there is no cure for Alzheimer’s Disease, but early diagnosis and appropriate care can help manage symptoms and improve the quality of life for affected individuals.