Autonomic dysregulation during sleep in Parkinsonian spectrum disorders - A proof of concept

Cho, Yeilim; Levendowski, Daniel J.; Walsh, Christine M.; Tsuang, Debby; Lee-Iannotti, Joyce K.; Berka, Chris; Mazeika, Gandis; Salat, David; Hamilton, Joanne M.; Boeve, Bradley F.; Neylan, Thomas C.; St Louis, Erik K.

doi:10.1016/j.parkreldis.2023.105905

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Hypoxia conditioning has a long history of efficient application in chronic obstructive pulmonary disease (COPD), where, among other benefits, it improves ventilation [88]. Furthermore, in COPD patients, hypoxia interventions improved autonomic cardiovascular dysfunctions (e.g., baroreflex sensitivity) [89], which are also common features in PD [90].…”

Section: Increasing the Resilience To Hypoxia In Pdmentioning

confidence: 99%

Hypoxia Sensing and Responses in Parkinson’s Disease

Burtscher,

Duderstadt,

Gatterer

et al. 2024

IJMS

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Parkinson’s disease (PD) is associated with various deficits in sensing and responding to reductions in oxygen availability (hypoxia). Here we summarize the evidence pointing to a central role of hypoxia in PD, discuss the relation of hypoxia and oxygen dependence with pathological hallmarks of PD, including mitochondrial dysfunction, dopaminergic vulnerability, and alpha-synuclein-related pathology, and highlight the link with cellular and systemic oxygen sensing. We describe cases suggesting that hypoxia may trigger Parkinsonian symptoms but also emphasize that the endogenous systems that protect from hypoxia can be harnessed to protect from PD. Finally, we provide examples of preclinical and clinical research substantiating this potential.

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Section: Increasing the Resilience To Hypoxia In Pdmentioning

confidence: 99%

Hypoxia Sensing and Responses in Parkinson’s Disease

Burtscher,

Duderstadt,

Gatterer

et al. 2024

IJMS

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EEG-based headset sleep wearable devices

Markov,

Elgendi,

Menon

2024

npj Biosensing

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The rise of wearable technology has led to EEG-based sleep monitoring devices that use electrodes placed on the forehead, ear, or neck. These devices offer promising applications in clinical and healthy populations by comparing sleep patterns, monitoring intervention responses, and examining the relationship between sleep and lifestyle factors. Despite their potential, challenges like validation against polysomnography, regulatory hurdles, data privacy, and usability hinder clinical adoption. This review explores these devices, their applications, and integration challenges in clinical practice.

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Concordance and Test-Retest Consistency of Sleep Biomarker-Based Neurodegenerative Disorder Profiling

Levendowski,

Tsuang,

Chahine

et al. 2024

Preprint

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Biomarkers that aid in early detection of neurodegeneration are needed to enable early symptomatic treatment and enable identification of people who may benefit from neuroprotective interventions. Increasing evidence suggests that sleep biomarkers may be useful, given the bi-directional relationship between sleep and neurodegeneration and the prominence of sleep disturbances and altered sleep architectural characteristics in several neurodegenerative disorders. This study aimed to demonstrate that sleep can accurately characterize specific neurodegenerative disorders (NDD). A four-class machine-learning algorithm was trained using age and nine sleep biomarkers from patients with clinically-diagnosed manifest and prodromal NDDs, including Alzheimer’s disease dementia (AD = 27), Lewy body dementia (LBD = 18), and isolated REM sleep behavior disorder (iRBD = 15), as well as a control group (CG = 58). The algorithm was validated in a total of 381 recordings, which included the training data set plus an additional AD = 10, iRBD = 18, Parkinson disease without dementia (PD = 29), mild cognitive impairment (MCI = 78) and CG = 128. Test-retest consistency was then assessed in LBD = 10, AD = 9, and CG = 46. The agreement between the NDD profiles and their respective clinical diagnoses exceeded 75% for the AD, LBD, and CG, and improved when NDD participants classified Likely Normal with NDD indications consistent with their clinical diagnosis were considered. Profiles for iRBD, PD and MCI participants were consistent with the heterogeneity of disease severities, with the majority of overt disagreements explained by normal sleep characterization in 27% of iRBD, 21% of PD, and 26% of MCI participants. For test-retest assignments, the same or similar NDD profiles were obtained for 88% of LBD, 86% in AD, and 98% of CG participants. The potential utility for NDD subtyping based on sleep biomarkers demonstrates promise and requires further prospective development and validation in larger NDD cohorts.

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Autonomic dysregulation during sleep in Parkinsonian spectrum disorders - A proof of concept

Cited by 3 publications

References 11 publications

Hypoxia Sensing and Responses in Parkinson’s Disease

Hypoxia Sensing and Responses in Parkinson’s Disease

EEG-based headset sleep wearable devices

Concordance and Test-Retest Consistency of Sleep Biomarker-Based Neurodegenerative Disorder Profiling

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