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Janssen Daalen JM, van den Bergh R, Prins EM, Moghadam MSC, van den Heuvel R, Veen J, Mathur S, Meijerink H, Mirelman A, Darweesh SKL, Evers LJW, Bloem BR. Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art. NPJ Digit Med 2024; 7:186. [PMID: 38992186 PMCID: PMC11239921 DOI: 10.1038/s41746-024-01144-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 05/22/2024] [Indexed: 07/13/2024] Open
Abstract
Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.
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Affiliation(s)
- Jules M Janssen Daalen
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands.
| | - Robin van den Bergh
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Eva M Prins
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Mahshid Sadat Chenarani Moghadam
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Rudie van den Heuvel
- HAN University of Applied Sciences, School of Engineering and Automotive, Health Concept Lab, Arnhem, The Netherlands
| | - Jeroen Veen
- HAN University of Applied Sciences, School of Engineering and Automotive, Health Concept Lab, Arnhem, The Netherlands
| | | | - Hannie Meijerink
- ParkinsonNL, Parkinson Patient Association, Bunnik, The Netherlands
| | - Anat Mirelman
- Tel Aviv University, Sagol School of Neuroscience, Department of Neurology, Faculty of Medicine, Laboratory for Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility (CMCM), Tel Aviv, Israel
| | - Sirwan K L Darweesh
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
| | - Luc J W Evers
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands
- Radboud University, Institute for Computing and Information Sciences, Nijmegen, The Netherlands
| | - Bastiaan R Bloem
- Radboud university medical center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, The Netherlands.
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Leclair-Visonneau L, Feemster JC, Bibi N, Gossard TR, Jagielski JT, Strainis EP, Carvalho DZ, Timm PC, Bliwise DL, Boeve BF, Silber MH, McCarter SJ, St. Louis EK. Contemporary diagnostic visual and automated polysomnographic REM sleep without atonia thresholds in isolated REM sleep behavior disorder. J Clin Sleep Med 2024; 20:279-291. [PMID: 37823585 PMCID: PMC10835777 DOI: 10.5664/jcsm.10862] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 10/06/2023] [Accepted: 10/06/2023] [Indexed: 10/13/2023]
Abstract
STUDY OBJECTIVES Accurate diagnosis of isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is crucial due to its injury potential and neurological prognosis. We aimed to analyze visual and automated REM sleep without atonia (RSWA) diagnostic thresholds applicable in varying clinical presentations in a contemporary cohort of patients with iRBD using submentalis (SM) and individual bilateral flexor digitorum superficialis (FDS) and anterior tibialis electromyography limb recordings during polysomnography. METHODS We analyzed RSWA in 20 patients with iRBD and 20 age-, REM-, apnea-hypopnea index-matched controls between 2017 and 2022 for phasic burst durations, density of phasic, tonic, and "any" muscle activity (number of 3-second mini-epochs containing phasic or tonic muscle activity divided by the total number of REM sleep 3-second mini-epochs), and automated Ferri REM atonia index (RAI). Group RSWA metrics were comparatively analyzed. Receiver operating characteristic curves determined optimized area under the curve (AUC) and maximized specificity and sensitivity diagnostic iRBD RSWA thresholds. RESULTS All mean RSWA metrics were higher in patients with iRBD than in controls (P < .05), except for selected anterior tibialis measures. Optimized, maximal specificity AUC diagnostic cutoffs for coprimary outcomes were: SM "any" 6.5%, 14.0% (AUC = 92.5%) and combined SM+FDS "any" 15.1%, 27.4% (AUC = 95.8%), while SM burst durations were 0.72, and 0.72 seconds (AUC 90.2%) and FDS RAI = 0.930, 0.888 (AUC 92.8%). CONCLUSIONS This study provides evidence for current quantitative RSWA diagnostic thresholds in chin and individual 4 limb muscles applicable in different iRBD clinical settings and confirms the key value of SM or SM+FDS to assure accurate iRBD diagnosis. Evolving iRBD recognition underscores the necessity of continuous assessment with future large, prospective, well-harmonized, multicenter polysomnographic analyses. CITATION Leclair-Visonneau L, Feemster JC, Bibi N, et al. Contemporary diagnostic visual and automated polysomnographic REM sleep without atonia thresholds in isolated REM sleep behavior disorder. J Clin Sleep Med. 2024;20(2):279-291.
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Affiliation(s)
- Laurène Leclair-Visonneau
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
- Department of Clinical Neurophysiology, CHU de Nantes, Nantes, France
- Nantes Université, INSERM, TENS, The Enteric Nervous System in Gut and Brain Diseases, Nantes, France
| | - John C. Feemster
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Noor Bibi
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Thomas R. Gossard
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Jack T. Jagielski
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Emma P. Strainis
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Diego Z. Carvalho
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Paul C. Timm
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Donald L. Bliwise
- Emory Sleep Center and Department of Neurology, Emory University, Atlanta, Georgia
| | - Bradley F. Boeve
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Michael H. Silber
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Stuart J. McCarter
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
| | - Erik K. St. Louis
- Mayo Sleep Behavior and Neurophysiology Research Laboratory, Rochester, Minnesota
- Mayo Center for Sleep Medicine, Rochester, Minnesota
- Department of Neurology, Mayo Clinic and Foundation, Rochester, Minnesota
- Department of Medicine, Mayo Clinic and Foundation, Rochester, Minnesota
- Department of Clinical and Translational Science, Mayo Clinic Health System Southwest Wisconsin, La Crosse, Wisconsin
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Memon AA, George EB, Nazir T, Sunkara Y, Catiul C, Amara AW. Heart rate variability during sleep in synucleinopathies: a review. Front Neurol 2024; 14:1323454. [PMID: 38239321 PMCID: PMC10794570 DOI: 10.3389/fneur.2023.1323454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 12/11/2023] [Indexed: 01/22/2024] Open
Abstract
Synucleinopathies are a group of neurodegenerative diseases characterized by abnormal accumulations of insoluble alpha-synuclein in neurons or glial cells. These consist of Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Moreover, idiopathic REM sleep behavior disorder (iRBD) is often the first manifestation of synucleinopathies, demonstrating a pathophysiological continuum. While these disorders vary in prevalence, symptom patterns, and severity, they can all include autonomic nervous system (ANS) dysfunction, which significantly reduces quality of life and worsens prognosis. Consequently, identifying abnormalities of the ANS can provide opportunities for improving quality of life through symptomatic treatments that are tailored to the individual's symptoms. An exciting development is using heart rate variability (HRV) as a non-invasive research tool for analyzing how the ANS regulates physiological processes. HRV during sleep, however, may provide a more accurate and reliable measure of ANS activity than during wakefulness, as during awake time, ANS activity is influenced by a variety of factors, including physical activity, stress, and emotions, which may mask or confound the underlying patterns of ANS activity. This review aims to provide an overview of the current knowledge regarding sleep-related HRV in synucleinopathies and to discuss contributing mechanisms. Evidence suggests that iRBD, PD, and MSA are associated with nocturnal ANS dysfunction. Further, comparative studies indicate that the presence of RBD could exacerbate this abnormality. In contrast, no studies have been conducted in patients with DLB. Overall, this review provides new insight into the complex interplay between the ANS and synucleinopathies and underscores the need for further research in this area to develop effective therapies to improve sleep and overall quality of life in patients with synucleinopathies.
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Affiliation(s)
- Adeel A. Memon
- Department of Neurology, West Virginia University Rockefeller Neuroscience Institute, Morgantown, WV, United States
| | - Ethan B. George
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Talha Nazir
- NeuroCare.AI, Neuroscience Academy, Dallas, TX, United States
| | - Yatharth Sunkara
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Corina Catiul
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Amy W. Amara
- Department of Neurology, University of Colorado, Anschutz Medical Campus, Aurora, CO, United States
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Cho Y, Levendowski DJ, Walsh CM, Tsuang D, Lee-Iannotti JK, Berka C, Mazeika G, Salat D, Hamilton JM, Boeve BF, Neylan TC, St Louis EK. Autonomic dysregulation during sleep in Parkinsonian spectrum disorders - A proof of concept. Parkinsonism Relat Disord 2023; 117:105905. [PMID: 37939637 PMCID: PMC10842052 DOI: 10.1016/j.parkreldis.2023.105905] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 10/09/2023] [Accepted: 10/22/2023] [Indexed: 11/10/2023]
Abstract
INTRODUCTION Autonomic dysfunction is common in α-synucleinopathies such as Lewy Body dementias (LBD), Parkinson's disease (PD), and isolated REM Sleep Behavior Disorder (iRBD). We analyzed pulse-rate changes during sleep to index autonomic nervous system (ANS) dysfunction in patients with α-synucleinopathies vs. non-synucleinopathy groups expected to have normal ANS function. METHODS Patients with LBD (n = 16), PD (PD, n = 14) or iRBD (n = 12) were compared to the non-synucleinopathy groups Alzheimers disease dementia (ADem, n = 26), mild cognitive impairment (MCI, n = 34) or controls (CG, n = 54). Sleep Profiler was used to derive a sleep autonomic activation index (AAI), i.e., ≥6 beat-per-minute increase/decrease, pulse rate coefficient of variation (PR-CV), and automated sleep staging with sleep-spindles and non-REM hypertonia (NRH). Analysis included statistical group comparisons and receiver operating characteristics curves to determine optimal classification of groups. RESULTS AAI and PR-CV were moderately correlated across all recordings (rs = 0.58, P < 0.0001), except in the LBD and PD groups. AAI but not PR-CV differentiated the LBD, PD and iRBD from non-Parkinsonian groups. AAI was decreased in LBD and PD patients compared to the CG (p < 0.003) and MCI (p < 0.03). AAI decreased based on age and its receiver operating characteristic area under the curve ranged from 0.63 to 0.75. AAI had a weak negative correlation to NRH (rs ≤ -0.26) but not sleep-spindles. CONCLUSION Synucleinopathy-related ANS dysfunction can reasonably discriminate prodromal and manifest PD/LBD diseased groups from non-synucleinopathies. Further studies incorporating AAI into a multivariate classifier of neurodegenerative disorders based on sleep characteristics acquired in the patient's home are planned.
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Affiliation(s)
- Yeilim Cho
- Mental Illness Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | | | - Christine M Walsh
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Debby Tsuang
- Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | | | - Chris Berka
- Advanced Brain Monitoring, Inc., Carlsbad, CA, USA
| | | | - David Salat
- Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Bradley F Boeve
- Department of Neurology and Center for Sleep Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Thomas C Neylan
- UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Erik K St Louis
- Departments of Neurology and Medicine and Center for Sleep Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
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Figorilli M, Meloni M, Lanza G, Casaglia E, Lecca R, Saibene FL, Congiu P, Puligheddu M. Considering REM Sleep Behavior Disorder in the Management of Parkinson's Disease. Nat Sci Sleep 2023; 15:333-352. [PMID: 37180094 PMCID: PMC10167974 DOI: 10.2147/nss.s266071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 04/25/2023] [Indexed: 05/15/2023] Open
Abstract
Rapid eye movement (REM) sleep behavior disorder (RBD) is the result of the loss of physiological inhibition of muscle tone during REM sleep, characterized by dream-enacting behavior and widely recognized as a prodromal manifestation of alpha-synucleinopathies. Indeed, patients with isolated RBD (iRBD) have an extremely high estimated risk to develop a neurodegenerative disease after a long follow up. Nevertheless, in comparison with PD patients without RBD (PDnoRBD), the occurrence of RBD in the context of PD (PDRBD) seems to identify a unique, more malignant phenotype, characterized by a more severe burden of disease in terms of both motor and non-motor symptoms and increased risk for cognitive decline. However, while some medications (eg, melatonin, clonazepam, etc.) and non-pharmacological options have been found to have some therapeutic benefits on RBD there is no available treatment able to modify the disease course or, at least, slow down the neurodegenerative process underlying phenoconversion. In this scenario, the long prodromal phase may allow an early therapeutic window and, therefore, the identification of multimodal biomarkers of disease onset and progression is becoming increasingly crucial. To date, several clinical (motor, cognitive, olfactory, visual, and autonomic features) neurophysiological, neuroimaging, biological (biofluids or tissue biopsy), and genetic biomarkers have been identified and proposed, also in combination, as possible diagnostic or prognostic markers, along with a potential role for some of them as outcome measures and index of treatment response. In this review, we provide an insight into the present knowledge on both existing and future biomarkers of iRBD and highlight the difference with PDRBD and PDnoRBD, including currently available treatment options.
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Affiliation(s)
- Michela Figorilli
- Sleep Disorder Research Center, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Mario Meloni
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Giuseppe Lanza
- Department of Surgery and Medical-Surgical Specialties, University of Catania, Catania, Italy
- Clinical Neurophysiology Research Unit, Oasi Research Institute-IRCCS, Troina, Italy
| | - Elisa Casaglia
- Sleep Disorder Research Center, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Rosamaria Lecca
- Sleep Disorder Research Center, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | | | - Patrizia Congiu
- Sleep Disorder Research Center, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Monica Puligheddu
- Sleep Disorder Research Center, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
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de Natale ER, Wilson H, Politis M. Predictors of RBD progression and conversion to synucleinopathies. Curr Neurol Neurosci Rep 2022; 22:93-104. [PMID: 35274191 PMCID: PMC9001233 DOI: 10.1007/s11910-022-01171-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/15/2021] [Indexed: 12/17/2022]
Abstract
Purpose of review Rapid eye movement (REM) sleep behaviour disorder (RBD) is considered the expression of the initial neurodegenerative process underlying synucleinopathies and constitutes the most important marker of their prodromal phase. This article reviews recent research from longitudinal research studies in isolated RBD (iRBD) aiming to describe the most promising progression biomarkers of iRBD and to delineate the current knowledge on the level of prediction of future outcome in iRBD patients at diagnosis. Recent findings Longitudinal studies revealed the potential value of a variety of biomarkers, including clinical markers of motor, autonomic, cognitive, and olfactory symptoms, neurophysiological markers such as REM sleep without atonia and electroencephalography, genetic and epigenetic markers, cerebrospinal fluid and serum markers, and neuroimaging markers to track the progression and predict phenoconversion. To-date the most promising neuroimaging biomarker in iRBD to aid the prediction of phenoconversion is striatal presynaptic striatal dopaminergic dysfunction. Summary There is a variety of potential biomarkers for monitoring disease progression and predicting iRBD conversion into synucleinopathies. A combined multimodal biomarker model could offer a more sensitive and specific tool. Further longitudinal studies are warranted to iRBD as a high-risk population for early neuroprotective interventions and disease-modifying therapies.
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Affiliation(s)
| | - Heather Wilson
- Neurodegeneration Imaging Group, University of Exeter Medical School, London, UK
| | - Marios Politis
- Neurodegeneration Imaging Group, University of Exeter Medical School, London, UK.
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