Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson’s disease

Gitte Julie Christensen; Jacob Kempfner; Marielle Zoetmulder; Helle L Leonthin; Lars Arvastson; Søren Christensen; Helge B D Sorensen; Poul Jennum

doi:10.1016/j.clinph.2013.08.013

Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson’s disease

Gitte Julie Christensen, Jacob Kempfner, Marielle Zoetmulder, Helle L Leonthin, Lars Arvastson, Søren Christensen, Helge B D Sorensen, Poul Jennum

39 Citations (Scopus)

Abstract

Objective: To determine whether sleep spindles (SS) are potentially a biomarker for Parkinson's disease (PD). Methods: Fifteen PD patients with REM sleep behavior disorder (PD. +. RBD), 15 PD patients without RBD (PD. RBD), 15 idiopathic RBD (iRBD) patients and 15 age-matched controls underwent polysomnography (PSG). SS were scored in an extract of data from control subjects. An automatic SS detector using a Matching Pursuit (MP) algorithm and a Support Vector Machine (SVM) was developed and applied to the PSG recordings. The SS densities in N1, N2, N3, all NREM combined and REM sleep were obtained and evaluated across the groups. Results: The SS detector achieved a sensitivity of 84.7% and a specificity of 84.5%. At a significance level of α=. 1%, the iRBD and PD. +. RBD patients had a significantly lower SS density than the control group in N2, N3 and all NREM stages combined. At a significance level of α=. 5%, PD. RBD had a significantly lower SS density in N2 and all NREM stages combined. Conclusions: The lower SS density suggests involvement in pre-thalamic fibers involved in SS generation. SS density is a potential early PD biomarker. Significance: It is likely that an automatic SS detector could be a supportive diagnostic tool in the evaluation of iRBD and PD patients.

Original language	English
Journal	Clinical Neurophysiology
Volume	125
Issue number	3
Pages (from-to)	512-519
Number of pages	8
ISSN	1388-2457
DOIs	https://doi.org/10.1016/j.clinph.2013.08.013
Publication status	Published - Mar 2014

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title = "Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson{\textquoteright}s disease",

abstract = "Objective: To determine whether sleep spindles (SS) are potentially a biomarker for Parkinson's disease (PD). Methods: Fifteen PD patients with REM sleep behavior disorder (PD. +. RBD), 15 PD patients without RBD (PD. RBD), 15 idiopathic RBD (iRBD) patients and 15 age-matched controls underwent polysomnography (PSG). SS were scored in an extract of data from control subjects. An automatic SS detector using a Matching Pursuit (MP) algorithm and a Support Vector Machine (SVM) was developed and applied to the PSG recordings. The SS densities in N1, N2, N3, all NREM combined and REM sleep were obtained and evaluated across the groups. Results: The SS detector achieved a sensitivity of 84.7% and a specificity of 84.5%. At a significance level of α=. 1%, the iRBD and PD. +. RBD patients had a significantly lower SS density than the control group in N2, N3 and all NREM stages combined. At a significance level of α=. 5%, PD. RBD had a significantly lower SS density in N2 and all NREM stages combined. Conclusions: The lower SS density suggests involvement in pre-thalamic fibers involved in SS generation. SS density is a potential early PD biomarker. Significance: It is likely that an automatic SS detector could be a supportive diagnostic tool in the evaluation of iRBD and PD patients.",

author = "Christensen, {Gitte Julie} and Jacob Kempfner and Marielle Zoetmulder and Leonthin, {Helle L} and Lars Arvastson and S{\o}ren Christensen and Sorensen, {Helge B D} and Poul Jennum",

year = "2014",

month = mar,

doi = "10.1016/j.clinph.2013.08.013",

language = "English",

volume = "125",

pages = "512--519",

journal = "Clinical Neurophysiology",

issn = "1388-2457",

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TY - JOUR

T1 - Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson’s disease

AU - Christensen, Gitte Julie

AU - Kempfner, Jacob

AU - Zoetmulder, Marielle

AU - Leonthin, Helle L

AU - Arvastson, Lars

AU - Christensen, Søren

AU - Sorensen, Helge B D

AU - Jennum, Poul

PY - 2014/3

Y1 - 2014/3

N2 - Objective: To determine whether sleep spindles (SS) are potentially a biomarker for Parkinson's disease (PD). Methods: Fifteen PD patients with REM sleep behavior disorder (PD. +. RBD), 15 PD patients without RBD (PD. RBD), 15 idiopathic RBD (iRBD) patients and 15 age-matched controls underwent polysomnography (PSG). SS were scored in an extract of data from control subjects. An automatic SS detector using a Matching Pursuit (MP) algorithm and a Support Vector Machine (SVM) was developed and applied to the PSG recordings. The SS densities in N1, N2, N3, all NREM combined and REM sleep were obtained and evaluated across the groups. Results: The SS detector achieved a sensitivity of 84.7% and a specificity of 84.5%. At a significance level of α=. 1%, the iRBD and PD. +. RBD patients had a significantly lower SS density than the control group in N2, N3 and all NREM stages combined. At a significance level of α=. 5%, PD. RBD had a significantly lower SS density in N2 and all NREM stages combined. Conclusions: The lower SS density suggests involvement in pre-thalamic fibers involved in SS generation. SS density is a potential early PD biomarker. Significance: It is likely that an automatic SS detector could be a supportive diagnostic tool in the evaluation of iRBD and PD patients.

AB - Objective: To determine whether sleep spindles (SS) are potentially a biomarker for Parkinson's disease (PD). Methods: Fifteen PD patients with REM sleep behavior disorder (PD. +. RBD), 15 PD patients without RBD (PD. RBD), 15 idiopathic RBD (iRBD) patients and 15 age-matched controls underwent polysomnography (PSG). SS were scored in an extract of data from control subjects. An automatic SS detector using a Matching Pursuit (MP) algorithm and a Support Vector Machine (SVM) was developed and applied to the PSG recordings. The SS densities in N1, N2, N3, all NREM combined and REM sleep were obtained and evaluated across the groups. Results: The SS detector achieved a sensitivity of 84.7% and a specificity of 84.5%. At a significance level of α=. 1%, the iRBD and PD. +. RBD patients had a significantly lower SS density than the control group in N2, N3 and all NREM stages combined. At a significance level of α=. 5%, PD. RBD had a significantly lower SS density in N2 and all NREM stages combined. Conclusions: The lower SS density suggests involvement in pre-thalamic fibers involved in SS generation. SS density is a potential early PD biomarker. Significance: It is likely that an automatic SS detector could be a supportive diagnostic tool in the evaluation of iRBD and PD patients.

U2 - 10.1016/j.clinph.2013.08.013

DO - 10.1016/j.clinph.2013.08.013

M3 - Journal article

C2 - 24125856

SN - 1388-2457

VL - 125

SP - 512

EP - 519

JO - Clinical Neurophysiology

JF - Clinical Neurophysiology

IS - 3

ER -

Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson’s disease

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