Sleep Profiler Biomarkers for
Characterization of Neurodegenerative Disorders

Initiated in 2018 with support from the National Institute of Aging, Advanced Brain Monitoring formed an international research consortium to assist in the validation of sleep biomarkers for use in phenotyping specific neurodegenerative disorders.

Our recent manuscripts describe the discovery of a new biomarker called non-REM hypertonia (NRH). We evaluated NRH in its relationship to REM sleep without atonia and studied how NRH relates to sleep spindle activity and autonomic dysregulation. A strong association between sleep and wake EEG slowing attributed to neurodegeneration was also discovered.

We cross-validated the automated staging accuracy in patients with isolated REM sleep behavior disorder and investigated whether a biomarker developed to detect ICU delirium, called atypical N3 sleep, was able to assess altered mental status in patients with Lewy body dementia.

The association between supine sleep and neurodegenerative disorders we first reported in 2019 was confirmed in independent cohorts with Lewy body Disease, Alzheimer's disease, and Mild Cognitive Impairment. A proposed mechanism of action, as well as a strong relationship between supine sleep and disease duration and motor impairment in Parkinson’s patients further supports our initial finding.

In community-based surveys we conducted, 87% of older adults want to know if they are at-risk for a neurodegenerative disorder, with 86% agreeing it would help them plan for the future. These surveys also identified what physicians should and should not do to assist their patients in matters relating to neurodegenerative disorders.

After validating each of nine sleep biomarkers, we applied artificial intelligence to derive neurodegenerative disorder risk probabilities for the categories normal, Lewy body disorder, Alzheimer’s disorder, or prodromal synucleinopathy and cross validated the risk and severity predictions in a range of at-risk patient populations.

The 20-min video below summarizes the accuracy and reliability of the neurodegenerative disorder risk and severity assessment and changes that occur in at-risk patients. The 40-minute video provides an in-depth description of our sleep biomarkers and findings associated with each.

20-minute Video: Phenotyping Neurodegenerative Disorder Risk and Severity Using Sleep EEG Biomarkers

40-minute Video Presentation Summarizing Our Biomarker Studies
Links to the studies discussed in the video:
  1. Proof-of-concept for characterization of neurodegenerative disorders using two non-REM biomarkers
  2. Sleep Biomarker Phenotyping of Neurodegenerative Disorders Using Artificial Intelligence – A Pilot Study
  3. Non-REM sleep with hypertonia in Parkinsonian Spectrum Disorders: A pilot investigation
  4. Autonomic dysregulation during sleep in Parkinsonian Spectrum disorders – a proof-of-concept
  5. The accuracy and reliability of sleep staging and sleep biomarkers in patients with Non-REM sleep with hypertonia in isolated REM sleep behavior disorder
  6. Sleep Biomarkerphenotyping of neurodegenerative disorders using artificial intelligence
  7. Atypical N3 sleep: A biomarker for altered mental status in Lewy body disease?
  8. Head position during sleep: Potential implications for patients with neurodegenerative disorders
  9. Comparison of sleep and wake EEG biomarkers in mild cognitive impairment and Alzheimer’s disease dementia
  10. Sleep and sleep position: potential implications for patients with neurodegenerative disease
  11. Collapsibility of the internal jugular veins in the lateral decubitus body position: A potential protective role of the cerebral venous outflow against neurodegeneration
  12. A community-based survey of personal perspective regarding prodromal sleep screening for neurodegenerative disorders
  13. Potential role of physicians in addressing the needs of those at-risk of a neurodegenerative disorder – A pilot study
  14. Effects of deep sedation on sleep in critically ill medical patients on mechanical ventilation
  15. Investigation of sleep metrics in the characterization of neurodegenerative disease
  16. The accuracy, night-to-night variability, and stability of frontopolar sleep EEG biomarkers
  17. Comparison of EMG power during sleep from the submental and frontalis muscles