- Alzheimer’s and Parkinson’s are neurodegenerative diseases that gradually worsen over time. There is currently a lack of effective treatments for both conditions.
- Early diagnoses using biomarkers may help slow disease progression or offer prevention.
- Individuals with Alzheimer’s and Parkinson’s often experience changes in brain activity patterns during sleep that may be detected using electroencephalography (EEG).
- Certain EEG patterns observed during sleep appear in early stages of Alzheimer’s and Parkinson’s prior to symptom onset, which could serve as biomarkers.
- Scientists in Denmark are developing an easy-to-use wearable in-ear EEG device to monitor sleep patterns at home and enable widespread screening for Alzheimer’s and Parkinson’s.
Estimates from the World Alzheimer Report 2021 indicate that nearly 75% of dementia cases across the globe are undiagnosed. This highlights the need for robust biomarkers for screening and diagnosing individuals with neurodegenerative disorders.
There is currently a lack of effective treatments for neurodegenerative conditions like Alzheimer’s disease and Parkinson’s disease, and early diagnoses may help delay or prevent these conditions.
Individuals with Alzheimer’s or Parkinson’s begin to show sleep disturbances and changes in brain activity levels during sleep from the early stages of these conditions. Thus, brain activity patterns during sleep could be used as biomarkers for neurodegenerative conditions.
Now, researchers in Denmark are developing an easy-to-use wearable electroencephalographyy (EEG) device that resembles in-ear headphones to measure brain activity levels during sleep.
Besides measuring brain waves, the device also allows for the measurement of other sleep-related variables. The device includes an oximeter to measure blood oxygen levels, a thermometer for body temperature, and a microphone to evaluate heart and respiratory rates.
The scientists hope the development of this easy-to-use device will facilitate large-scale screening for Alzheimer’s and Parkinson’s in the general population.
This project is a collaborative effort between researchers at Rigshospitalet, Aarhus University, and T&W Engineering — a health technology company. This project, entitled “Progression Assessment in Neurodegenerative Disorders of Ageing (PANDA),” will be conducted over 4 years.
After developing this in-ear-EEG device with other sleep monitoring sensors, the researchers intend to test this device for its ability to discriminate between individuals with or without Alzheimer’s or Parkinson’s disease in a clinical trial as a part of this project.
Prof. Poul Jørgen Jennum, a clinical neurophysiologist at the University of Copenhagen, and one of the researchers involved in this initiative, notes in a news release:
“We hope that we’ll be able to use the ear-EEG to replace in part the existing and somewhat more troublesome sleep monitoring. We’ll try to make the technology so simple that it can be used at home and over a longer period of time. Ideally, we hope it will be possible to measure your own sleep over a few days, weeks, or even months every year.”
Prof. Jennum adds that the aim of his and his colleagues’ current research on the in-ear EEG device “is to identify changes that may be early signs of serious brain diseases such as Alzheimer’s and Parkinson’s disease and to diagnose patients more easily and earlier than today.”
“This would be a great advantage. Another advantage is that we can examine patients in their everyday lives and monitor changes in sleep patterns and the effect of treatments. This makes the potential ear-EEG technology a good screening tool that can be used at home — just like a blood pressure meter,” the researcher says.
The researchers intend to test this device for its ability to discriminate between individuals with or without Alzheimer’s or Parkinson’s disease as a part of the project.
Changes in brain structure and function during the development of Alzheimer’s and Parkinson’s begin long before symptom onset.
Thus, changes in the structure and function of the brain may be used as biomarkers for these conditions.
The characterization of such biomarkers could facilitate the development of therapies for the prevention of these neurodegenerative conditions in at-risk individuals.
Over the years, studies have shown changes in brain activity, as measured using EEG, in individuals with Alzheimer’s and Parkinson’s. EEG involves the use of electrodes placed on the scalp to record the electrical activity in the brain.
Neurons in the brain produce small electrical impulses to communicate with each other. Electroencephalography measures the collective activity of a population of neurons that appears as brain waves of a specific frequency. These brain waves appear even while an awake organism is not engaged in an activity and during sleeping.
Changes in sleep patterns, including the incidence of sleep disorders, are closely associated with neurodegenerative disorders. These changes in sleep patterns can be observed as alterations in EEG patterns, which can be used as biomarkers.
Studies examining brain activity patterns of awake individuals with Alzheimer’s disease at rest using EEG have shown changes in the rhythms in the cortex, which is involved in cognitive functions, including memory and thinking.
Specifically, these changes in individuals with Alzheimer’s disease include slowing of EEG patterns involving an increase in lower-frequency waves and a decrease in high-frequency waves in the cortex.
Notably, these changes in brain activity patterns are associated with alterations in brain structure and function observed in individuals with Alzheimer’s disease. These changes in EEG patterns are present in the early stages of Alzheimer’s disease, suggesting their suitability as a biomarker for this condition.
Individuals with Alzheimer’s tend to wake up more frequently during the night and stay awake for longer. Individuals with Alzheimer’s also show changes in specific features of EEG brain activity patterns during all phases of sleep.
For instance, studies in individuals with Alzheimer’s disease have shown a slowing of EEG patterns during the rapid-eye-movement phase of sleep, similar to that observed during rest.
These EEG patterns during sleep are associated with memory and learning, and changes in brain activity patterns could underly the deficits in these cognitive domains in Alzheimer’s disease.
Evidence suggests that these changes in EEG patterns during sleeping are a more accurate predictor of cognitive deficits in individuals with Alzheimer’s disease than brain patterns during the wakeful state.
Notably, studies have shown that EEG patterns can accurately distinguish between Alzheimer’s disease and other forms of dementia.
Similarly, individuals with Parkinson’s disease also show sleep disturbances and alterations in sleep phases, such as a reduction of time spent in the REM phase.
Individuals with Parkinson’s disease also show slowing of EEG patterns, and these changes in these brain activity patterns often appear before deficits in motor function.
Studies have also demonstrated that sleep disruptions and changes in sleep EEG patterns in mice models of Parkinson’s disease.
There is a need for inexpensive and easily accessible biomarkers to screen the broader populations for neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease.
This wearable in-ear device could be easily used at home while sleeping, thus allowing multiple, regular measurements of brain activity patterns during sleep.
Moreover, this technology could potentially distinguish and identify different neurodegenerative conditions at an early stage.
Dr. Steven Allder, a consultant neurologist at Re:Cognition Health, not involved in this study, told Medical News Today:
“There is a huge need to accurately identify patients in the early stages of age-related neurodegenerative conditions such as Alzheimer’s and Parkinson’s disease. Each neurodegenerative disease has a very distinct underlying pathophysiology; therefore, it should be possible to detect each disease early. Doing so would be revolutionary.”
Dr. Allder also noted that this EEG-based technique “could have applications far beyond an early diagnosis of these conditions.”
“The EEG signal is a rich source of data, so I would predict [the researchers] will eventually succeed. This is another sign neurology is entering a whole new paradigm of care,” he added.
Read the full article here