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Design of Knowledge Driven and Data Driven Algorithms for Neurodegenerative Diseases

Background

Parkinson’s disease (PD) is one of the most important neurodegenerative disorders with major impact on quality life, morbidity and mortality and there are still not valid and world-recognized biomarkers for identification of early stages of the disease [1]. Sleep disturbances are common symptoms of PD, and some studies have found that there is a strong relation between a specific sleep disorder (REM sleep behavior disorder - RBD) and Parkinsonism [2, 3]. This relation suggests the idea that sleep disturbances might precede the clinical diagnosis of PD. Therefore, analysis of sleep carried out with polysomnography has the potential to be used for early disease identification. Previous studies have shown that automatic algorithms are able to identify altered eye movements during sleep [4, 5], altered sleep stability [6], and a decrease and change of morphology of spindles [7] in patients suffering from PD and RBD. However, none of these biomarkers can be considered as a stand-alone early PD biomarker [8].

Project objectives:

The aim of the current Ph.D. project is to further investigate objective findings during sleep in RBD patients and early PD patients, to broaden the family of early sleep PD biomarkers. In particular, it is known that PD and RBD patients are characterized by abnormal sleep muscular activity, which is still manually scored by expert technicians. Therefore, the first aim of the PhD project consists in developing an automatic and data-driven algorithm to identify such abnormal patterns, which can therefore be considered an early PD biomarker. Second, the PhD project aims at investigating longitudinal changes in the electroencephalographic sleep structure of RBD and early PD patients. In this way there will be the possibility of analyzing how the sleep electrical activity is changing in the early stages of the disease. These studies are carried out in national and European databases and have the objective of developing algorithms that have high accuracy for future clinical applications.
The early identification of PD has the potential of identifying a group of patients that can be the target of clinical trials, when neuroprotective or disease-modifying treatments will be available.

References

  1. A. J. Lees, J. Hardy, and T. Revesz, Parkinson's disease, Lancet, vol. 373, no. 9680, pp. 2055-2066, 2009.
  2. A. Stefani and B. Högl, Sleep in Parkinson’s disease, Neuropsychopharmacology, 2019
  3. C. H. Schenck, B. F. Boeve, and M. W. Mahowald, Delayed emergence of a parkinsonian disorder or dementia in 81% of older men initially diagnosed with idiopathic rapid eye movement p behavior disorder: a 16-year update on a previously reported series, Sleep Medicine, vol. 14, n. 8, pp. 744-748, 2013
  4. J. A. E. Christensen, R. Frandsen, J. Kempfner, L. Arvastson, S. R. Christensen, P. Jennum, and H. B. Sorensen, Separation of Parkinson's patients in early and mature stages from control subjects using one EOG channel, IEEE Engineering in Medicine and Biology Society Conference Proceedings, vol. 2012, pp. 2941-2944, 2012
  5. J. A. E. Christensen, H. Koch, R. Frandsen, J. Kempfner, L. J. Arvastson, S. R. Christensen, H. B. D. Sorensen, and P. Jennum, Classification of iRBD and Parkinson's disease patients based on eye movements during sleep, IEEE Engineering in Medicine and Biology Society Conference Proceedings, vol. 2013, pp. 441-444, 2013.
  6. J. A. E. Christensen, P. Jennum, H. Koch, R. Frandsen, M. Zoetmulder, L. J. Arvastson, S. R. Christensen, and H. B. D. Sorensen, Sleep stability and transitions in patients with idiopathic REM sleep behavior disorder and patients with Parkinson's disease, Clinical Neurophysiology, vol. 127, no. 1, pp. 537-543, 2016.
  7. J. A. E. Christensen, J. Kempfner, M. Zoetmulder, H. L. Leonthin, L. J. Arvastson, S. R. Christensen, H. B. D. Sorensen, and P. Jennum, Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson’s disease, Clinical Neurophysiology, vol. 125, no. 3, pp. 512-519, 2014
  8. M. Cesari and P. Jennum, Selective Polysomnographic Findings in REM Sleep Behavior Disorder (RBD) and Parkinson’s Disease, Rapid-Eye-Movement Sleep Behavior Disorder. Springer, Cham, pp. 271-279, 2019

Contact

Helge Bjarup Dissing Sørensen
Groupleader, Associate Professor MSK, PhD
DTU Health Tech
+45 45 25 52 44

Contact

Poul Jørgen Jennum
Professor
Rigshospitalet, Glostrup

Contact

Julie Anja Engelhard Christensen
Senior Researcher
Health Technology

Contact

Matteo Cesari
PhD Student
Health Technology
https://www.cachet.dk/research/finalized-phd-projects/design-of-knowledge-driven-and-data-driven-algorithms-for-neurodegenerative-diseases
27 JANUARY 2023