Article

The Relationships Between Poor Sleep Efficiency and Mild Cognitive Impairment in Parkinson Disease

Journal of Geriatric Psychiatry and Neurology 2014, Vol. 27(2) 77-84 ª The Author(s) 2013 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0891988713509135 jgpn.sagepub.com

David G. Gunn, DPsych1, Sharon L. Naismith, MPsych, DPsych1, Zoe Terpening, BPsych, Msc, DCN1, and Simon J. G. Lewis, MRCP, MD1

Abstract Background: Mild cognitive impairment (MCI) and sleep disturbances are common features in Parkinson disease (PD). This study sought to investigate whether patients with MCI in PD (PD-MCI) have more pronounced sleep disturbance compared to those without PD-MCI and whether phenotypic presentations differ according to the PD-MCI subtypes. Methods: A total of 95 patients with idiopathic PD (53 meeting criteria for PD-MCI and 42 who were not cognitively impaired) and 22 controls underwent neurological and neuropsychological examination. They wore actigraphy watches for 2 weeks, from which measures of nocturnal sleep efficiency were calculated. Results: Patients with PD-MCI has significantly poorer sleep efficiency compared to those without PD-MCI. This effect was particularly apparent in those with multiple-domain PD-MCI, compared to those with single-domain PD-MCI. Furthermore, patients in the PD-MCI group had significantly more nontremor features. Conclusions: These data suggest that PD-MCI is associated with greater sleep disturbance and nontremor features of PD. This is further evidence for the potential role that sleep disturbance plays in the heterogeneity of PD. Keywords Parkinson disease, mild cognitive impairment, sleep, cognition, actigraphy

Introduction Parkinson disease (PD) is a progressive neurodegenerative condition, characterized historically by its cardinal features of tremor, bradykinesia, rigidity, and postural instability. Sleep–wake disturbance is a significant nonmotor feature affecting approximately two-thirds of all the patients.1 Sleep-related symptoms present in a variety of ways including insomnia,2 excessive daytime sleepiness (EDS),3 rapid eye movement (REM) sleep behavior disorder (RBD),4-6 and sleep disordered breathing.7,8 Healthy sleep is believed to be important in the consolidation of memory9,10 and efficient executive functioning.11,12 In PD, sleep–wake disturbances have been specifically linked to neuropsychological deficits in executive functioning,13 processing speed, working memory, verbal fluency, and memory consolidation14 and have been more generally associated with the development of cognitive decline and dementia.3,5,6,15-20 Cognitive impairment is also recognized as an important feature of PD and is a significant predictor of quality of life21 and nursing home placement.22 The pattern of cognitive impairment reflects the distribution of underlying neuronal dysfunction and typically manifests as dysfunction in the domains of memory, processing speed, and executive function.23

There is an increasing appreciation that such cognitive deficits may represent a predementia state known as mild cognitive impairment (MCI),24 with those meeting criteria for MCI in PD (PD-MCI) considered to be at greater risk of developing dementia.25,26 As a diagnostic entity, PD-MCI is defined as an intermediate stage between normal cognitive function and dementia, whereby an individual has deficits in at least 1 cognitive domain but without dysfunction in the activities of daily living. Diagnostic criteria have been proposed,24,27-29 wherein MCI is characterized by a deficit of at least 1.5 standard deviations below the expected age and education corrected mean in the cognitive domain assessed.

1

Parkinson’s Disease Research Clinic, Aging Brain Centre, Brain & Mind Research Institute, The University of Sydney, Sydney, New South Wales, Australia

Received 10/05/2012. Received revised 9/18/2013. Accepted 9/18/2013. Corresponding Author: Simon J. G. Lewis, Parkinson’s Disease Research Clinic, Brain & Mind Research Institute, The University of Sydney, 94 Mallet St, Camperdown, Sydney, New South Wales, Australia. Email: [email protected]

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The MCI can encompass a single deficit in the domain of memory (amnestic MCI [A-MCI]) or deficits in selected domains other than memory including executive functions, language, attention, processing speed, and visuospatial skills (nonamnestic MCI [NA-MCI]). Furthermore, deficits may be restricted to one domain (single-domain MCI [S-MCI]) or may be apparent across several domains (multipledomain MCI [M-MCI]).28 It has been postulated that the existence of these distinct subtypes of PD-MCI may represent specific neurodegenerative patterns or the coexistence of other pathologies (eg, vascular dementia and Alzheimer disease),30 which could therefore impact on therapeutic options. Unlike other dementias such as Alzheimer disease, the NA-MCI subtype is the most common MCI subtype observed in PD.31 It has been suggested that the cognitive impairment and sleep–wake disturbances in PD may relate to dysfunction in common underlying neural substrates.32 Therefore, further elucidation of the relationship between sleep and cognition in PD is of considerable clinical relevance. Sleep–wake symptoms are commonly present early in the disease,19 may even predate the development of physical symptoms,4,33,34 and are associated with an increased risk of PD-MCI35 and dementia.36,37 As such, the occurrence of sleep–wake disturbance may represent a potential prodromal stage during which targeted intervention could help reduce the risk of cognitive decline and Parkinson disease dementia.38,39 To date, no known studies have examined the relationship between an objective actigraphic measure of sleep disturbance and the presence of PD-MCI. Therefore, this study sought to investigate the relationship between actigraphically defined sleep efficiency and the presence of PD-MCI. In addition, we sought to explore whether poor sleep efficiency was associated with any particular subgroup of PD-MCI or particular disease phenotype.

Methods Participants A total of 95 patients (58 males, 37 females) were recruited from the Brain & Mind Research Institute PD Research Clinic, University of Sydney. Exclusion criteria included dementia diagnosis, neurologic disease other than PD (eg, epilepsy), psychosis, prior stroke or head injury (with loss of consciousness >30 minutes), diagnosis of obstructive sleep apnoea, and inadequate English for neuropsychological assessment. All patients satisfied UKPDS Brain Bank criteria and were deemed unlikely on Movement Disorder Society (MDS) guidelines to have dementia40 or major depression according to Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition; DSM-IV)41 criteria by consensus rating of a neurologist (SJGL) and a neuropsychologist (SLN). Data from a subset of the current study’s participants have been reported by our research group previously.14,42 In all, 34 patients were on levodopa monotherapy, 9 were on dopamine agonist monotherapy, and 52 were on levodopa plus an adjuvant agent (eg, dopamine agonist,

catechol-O-methyltransferase inhibitor, and monoamine oxidase inhibitor). In all, 22 patients were taking antidepressants, and 13 were taking benzodiazepines. A further 22 (11 men and 11 women) age-matched volunteers were recruited as healthy control participants after being screened for neurological and psychiatric disease. Permission for the study was obtained from the University of Sydney Human Research Ethics Committee, and all patients gave written informed consent.

Clinical Assessment All neurological and neuropsychological assessments were conducted within 1 session to confirm study eligibility. Patients were in their ‘‘on’’ state when assessed on the Movement Disorder Society Unified Parkinson Disease Rating Scale (MDSUPDRS).40 For each patient, a ‘‘tremor score’’ and a ‘‘nontremor’’ score were calculated from the physical examination (UPDRS III) using an approach similar to that reported elsewhere.43-46 The tremor score was derived from the sum of items 50 to 59 on the UPDRS divided by 10 (the number of items included), whereas the nontremor score was derived from the sum of items 29 to 43, 45, and 47 on the UPDRS divided by 17 (the number of items included). Levodopa dose equivalents (mg/d) were calculated for dopaminergic medication.47 Disease stage was rated on the Hoehn and Yahr scale,48 and disease duration was calculated from time (years) since disease diagnosis. To allow some comparison of the rate of disease progression between patients with differing disease durations assessed at only a single time point, a variable was calculated by dividing the total UPDRS score for sections I to III by the disease duration (years). Participants were asked to complete the REM Sleep Behavior Disorder Screening Questionnaire (RSBDSQ; range 0-13)49 whereby a cutscore of 6 or greater has a high predictive capacity to detect RBD.50 To determine the depressive symptom severity, patients completed the Beck Depression Inventory II (BDI-II; range 0-63).51 Question 6 of the clinician-rated Nonmotor Symptom Scale (NMSS; range 0-12)52 was used to assess PD patients’ severity and frequency of symptoms of Restless Legs Syndrome (RLS). The Scales for Outcomes in PD (SCOPA)53 sleep scale was administered as a subjective measure of nocturnal sleep disturbance (SCOPA night; range 015) and general daytime sleepiness (SCOPA day; range 0-18). A neuropsychologist administered a standardized battery of tests, and these scores were corrected to appropriate normative data. Processing speed was assessed using part A of the Trail Making Test (age- and education-adjusted z score).54 Attention and working memory were assessed using the age-scaled score (ASS) of the Digit Span subtest of the Wechsler Adult Intelligence Scale III.55 The ASSs from the Logical Memory subtest of the Wechsler Memory Scale III were used to assess the encoding (Logical Memory I ASS) and consolidation (Logical Memory % Retention ASS) of verbal material.56 Phonemic and semantic fluency were assessed by the Controlled Oral Word Association Test (letters F, A, S, and animal category, respectively; age- and education-adjusted z score).57 Mental flexibility/set shifting was examined using part B of the Trail Making Test (age- and education-adjusted z score).54 For descriptive

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purposes, the National Adult Reading Test58 was administered to estimate premorbid intellectual level, and the Mini-Mental State Examination59 was administered as a global measure of cognition.

Participants were excluded if they returned an actigraphy with a period of missing data (ie, taking the actigraphy watch off) greater than 12 hours.

Statistical Analysis Mild Cognitive Impairment Classification Diagnoses were established by consensus ratings (DG, SLN, and SJGL). As described previously, scores on neuropsychological tests were converted to z scores using appropriate normative data.55-57,60 An individual was classified as being either positive or negative for PD-MCI (PD-MCIþ or PDMCI, respectively) if they demonstrated impairment (1.5 standard deviations decrement relative to predicted intelligence quotient [IQ]) on at least 1 domain of the neuropsychological testing.24 In addition, patients were classified as A-MCI or NA-MCI and S-MCI or M-MCI, where M-MCI was defined as impairment in at least 2 separate cognitive domains.28 In order to be classified as A-MCI, participants must have demonstrated memory storage deficits (ie, deficits in delayed recall that were not considered to be due to poor encoding of the material in the first instance).

Actigraphic Assessment Measurement of sleep–wake disturbance was conducted according to the previously established protocols.42,61 Following clinical assessment, participants were required to complete a sleep diary and wear a wrist actiwatch (Minimitter Actiwatch Spectrum, Andover, Massachusetts) on their less severe disease side arm for 14 consecutive days. Actigraphy rest intervals were calculated using Actiware 5.0 software (Minimitter-Respronics Inc, Bend, Oregon) in conjunction with manual scoring. One rest interval per 24-hour period was scored (total rest time). This allowed for the derivation of wake after sleep onset (WASO), total sleep time (ie, total rest time  wake after sleep onset), average variability in sleep onset and offset over the 14 trial days, average nap time, and the number of days that they reported via the sleep diary as having had a nap. The primary measure of sleep disturbance was sleep efficiency, which reflected the percentage of total time spent ‘‘asleep’’ during the rest interval, that is [(total rest time  wake after sleep onset)/ total rest time]  100. Another measure of sleep disturbance was the average number of arousals across the 2-week assessment period (wake bouts). During the rest interval, these were scored as the total number of continuous blocks in an interval (1 or more epochs), where the epochs of each block were scored as ‘‘wake.’’ Each epoch was set to 30 seconds. The wake threshold value (ie, the number of activity counts used to define wake) was set to medium sensitivity of 40.0 activity counts per epoch. Selfreported sleep diaries were utilized to aid nap scoring; however, when there were any discrepancies between objective and subjective sleep–wake behaviors, actigraphy was considered to be more reliable as naps tend to be underreported in the elderly population.62 Therefore, activity patterns resembling sleep that were not reported in the sleep diary were scored as nap intervals.

Data analyses were conducted using IBM SPSS Statistics 20. Between-group comparisons used independent samples t tests. One-way analysis of covariance (ANCOVA) was used to control for confounding variables. Nominal data were assessed using chi-square (w2) tests. All analyses were 2 tailed with a ¼ .05.

Results In all, 55% (52 of 95) of the sample met criteria for PD-MCI based on at least 1 domain of cognitive functioning. Of these, 33% (17 of 52) met criteria for A-MCI, while 67% (35 of 52) met criteria for NA-MCI. Of PD-MCI-positive patients, 56% (29 of 52) had S-MCI and 44% (23 of 52) had M-MCI. A total of 5 participants from the PD group were excluded prior to analysis due to taking the actigraphy watch off for greater than a 12-hour period during the 14 trial days. Only 26 participants partially completed their sleep diaries, while the remainder of the sample completed the diaries fully.

Comparisons Between the Patients With PD and the Controls Table 1 shows that there was no difference at a group level between the patients with PD and the healthy controls with regard to age, sex, years of education, predicted IQ score, MMSE score, self-reported nighttime sleep disturbance (SCOPA night), Digit Span, Logical Memory I or % Retention, verbal fluency (letters and animals), wake bouts, total sleep time, sleep onset or offset variability, and average nap time. In contrast, the PD group reported significantly higher levels of RBD symptoms (RSBDSQ total score, t ¼ 7.7, P < .001) and restless legs symptoms (NMSS restless legs total, t ¼ 4.1, P < .001), greater depressive symptoms (BDI-II, t ¼ 4.8, P ¼ .002) as well as daytime sleepiness (SCOPA day, t ¼ 3.3, P < .001). As expected, the PD group scored significantly worse of cognitive measures of processing speed (Trail Making Test part A, t ¼ 2.0, P ¼ .044) and cognitively flexibility (Trail Making Test part B, t ¼ 4.2, P < .001) compared to controls. With respect to actigraphic assessment, the PD group had a significantly worse sleep efficiency (t ¼ 3.1, P ¼ .003) and a greater amount of WASO (t ¼ 3.1, P ¼ .003). The PD group also reported a significantly greater number of days on which they napped compared to the control group (t ¼ 2.1, P ¼ .035).

Comparisons Between PD-MCI-Positive and PD-MCI-negative Patients As shown in Table 1, the PD-MCI-positive group scored significantly poorer on neuropsychological measures of processing speed (Trail Making Test part A, t ¼ 4.7, P < .001), attention

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Table 1. Demographic, Neuropsychological, and Sleep Disturbance Data.a Mean (SD)

Mean (SD)

Entire Sample (n ¼ 95) Controls (n ¼ 22) Age, years Sex, males:females Education, years NART, predicted IQ Hoehn and Yahr, stage Disease duration, years UPDRS motor score Disease progression score Levodopa dose equivalent, mg Tremor score Nontremor score Mini-Mental State Examination RSBDSQ total score NMSS restless legs total Beck Depression Inventory II SCOPA day SCOPA night Neuropsychological data Trails A, z score Digit Span, ASS Logical Memory I, ASS Logical Memory % retention, ASS Letter fluency (FAS), z score Semantic fluency (animals), z score Trails B, z score Actigraphy variables Sleep efficiency, % Wake bouts, n Total sleep time, min WASO, min Sleep onset variability, min Sleep offset variability, min Average daily nap time, min Days with a nap, sleep diary

t

PD-MCIþ (n ¼ 52) PD MCI (n ¼ 43)

65.3 (8.7) 11:11 13.8 (2.9) 112.1 (10.4) – – – – – – – 28.4 (1.5) 1.7 (1.5) 0.2 (0.9) 3.9 (4.3) 2.3 (2.3) 4.3 (4.8)

0.4 1.1 1.0 0.0 – – – – – – – 0.6 7.7c 4.1c 4.8c 3.3c 0.6

65.3 (7.2) 33:19 13.6 (3.3) 111.3 (12.2) 2.1 (0.7) 5.9 (6.2) 26.6 (13.9) 14.6 (13.2) 615.5 (504.2) 0.4 (0.5) 1.4 (0.6) 28.4 (1.7) 5.7 (3.7) 1.7 (3.0) 10.0 (6.2) 4.5 (3.3) 5.2 (4.4)

0.2 (1.6) 11.0 (2.6) 10.1 (3.3) 11.0 (3.2) 0.2 (1.4) 0.2 (1.4) 0.4 (1.7)

0.5 (0.8) 10.8 (2.9) 10.1 (2.7) 11.3 (3.3) 0.1 (1.0) 0.7 (1.7) 0.4 (0.6)

2.0b 0.3 1.0 0.4 0.2 1.2 4.2c

0.8 10.2 8.6 10.4 0.0 0.2 1.2

(1.8) (2.5) (3.9) (3.6) (1.2) (1.3) (1.9)

0.5 (0.9) 11.8 (2.5) 10.4 (2.8) 11.6 (2.7) 0.5 (1.6) 0.8 (1.4) 0.4 (0.8)

90.2 (5.1) 32.7 (12.2) 490.8 (64.5) 47.4 (23.7) 65.8 (63.9) 54.0 (40.9) 39.6 (36.9) 5.1 (4.3)

92.5 (2.5) 31.7 (9.0) 482.2 (46.3) 35.9 (12.7) 76.2 (112.2) 65.7 (68.1) 33.4 (56.6) 3.0 (3.6)

3.4c 0.3 0.6 3.1c 0.6 1.0 0.6 2.1b

88.7 34.7 490.6 54.5 69.5 59.2 44.0 5.4

(5.3) (12.8) (65.2) (24.8) (72.6) (51.5) (37.4) (4.2)

92.0 (4.1) 30.1 (11.1) 491.0 (64.4) 38.9 (19.4) 61.5 (52.5) 47.9 (22.5) 34.6 (36.1) 4.7 (4.4)

64.6 (7.8) 58:37 13.9 (3.1) 112 (10.5) 2.0 (0.7) 5.3 (5.5) 23.8 (11.4) 13.8 (12.4) 594.5 (489.4) 0.4 (0.4) 1.2 (0.6) 28.6 (1.5) 5.5 (3.6) 1.5 (2.7) 9.4 (6.6) 4.3 (3.5) 4.9 (4.0)

63.7 (8.5) 25:18 14.1 (2.8) 112.4 (8.6) 1.9 (0.6) 4.8 (4.5) 21.4 (8.7) 13.0 (11.5) 569.1 (475.7) 0.4 (0.3) 1.0 (0.5) 28.9 (1.3) 5.2 (3.5) 1.2 (2.2) 8.7 (7.1) 4.0 (3.6) 4.6 (3.6)

t 1.0 0.3 0.8 0.5 1.4 0.9 2.2b 0.6 0.5 0.4 3.3c 1.4 0.8 0.9 0.9 0.6 0.8 4.7c 3.2c 2.7c 1.9 1.7 3.8c 5.1c 3.4c 1.9 0.3 3.4c 0.6 1.3 1.2 0.7

Abbreviations: PD-MCIþ, positive for mild cognitive impairment in Parkinson disease; PD-MCI, negative for mild cognitive impairment in Parkinson disease; NART, National Adult Reading Test; UPDRS, Unified Parkinson Disease Rating Scale; RSBDSQ, REM Sleep Behavior Disorder Screening Questionnaire; NMSS, Nonmotor Symptom Scale; SCOPA, Scales for Outcomes in Parkinson Disease; ASS, Age-Scaled Score; WASO, wake after sleep onset; IQ, intelligence quotient; SD, standard deviation. a Chi-square analysis was used to assess sex distribution. b P < .05. c P < .01.

and working memory (Digit Span, t ¼ 3.2, P ¼ .002), encoding of verbal material (Logical Memory I, t ¼ 2.7, P ¼ .008), semantic fluency (animals, t ¼ 3.8, P < .001), and set shifting (Trail Making Test part B, t ¼ 5.1, P < .001). The groups did not differ significantly on a measure of verbal memory consolidation (Logical Memory % Retention, t ¼ 1.8, P ¼ .078) or a phonemic fluency task (FAS, t ¼ 1.7, P ¼ .091). The PDMCI-positive group had significantly poorer sleep efficiency (t ¼ 3.4, P ¼ .001) and greater WASO (t ¼ 3.4, P < .001) compared to the PD-MCI-negative group. The PD-MCIpositive group also scored significantly higher on the motor section of the UPDRS compared to the PD-MCI-negative group (t ¼ 2.2, P ¼ .028) as well as returning a higher average nontremor score (t ¼ 3.3, P ¼ .001). To determine

whether the difference in sleep efficiency between the PDMCI groups remained once controlling for motor dysfunction, an ANCOVA was conducted using UPDRS motor score as a covariate. This analysis revealed that even after controlling for UPDRS motor score, F1,92 ¼ 0.3, P ¼ .575, there was still a significant difference in sleep efficiency between the PDMCI-positive and PD-MCI-negative groups, F1,92 ¼ 9.6, P ¼ .003. The w2 testing revealed that neither antidepressant (w2 ¼ .36, df ¼ 1, P ¼ .546) nor benzodiazepine (w2 ¼ .79, df ¼ 1, P ¼ .374) use differed between the PD-MCIpositive and the PD-MCI-negative groups. Table 2 presents the demographic and clinical variables for the comparison of the patients with PD who met criteria for NA-MCI and A-MCI. These groups did not differ on

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Table 2. Comparison Between the A-MCI and NA-MCI Groups.a

Table 3. Comparison Between the S-MCI and M-MCI Groups.a

Mean (SD) A-MCI (n ¼ 17)

NA-MCI (n ¼ 35)

Age, years 66.8 (6.0) 64.6 (7.8) Sex, males:females 12:5 21:14 Education, years 12.4 (3.3) 14.2 (3.2) NART, predicted IQ 109.8 (10.7) 112.0 (13.0) Hoehn and Yahr, stage 2.3 (0.8) 2.0 (0.7) Disease duration, years 8.1 (7.4) 4.7 (5.3) UPDRS motor score 28.9 (13.3) 25.5 (14.3) Disease progression score 12.8 (16.1) 15.4 (11.7) Levodopa dose equivalent, mg 803.3 (541.1) 524.3 (466.1) Tremor score 0.5 (0.8) 0.3 (0.3) Nontremor score 1.6 (0.5) 1.3 (0.7) RSBDSQ total score 4.7 (3.3) 6.3 (3.8) NMSS restless legs total 1.1 (2.2) 2.0 (3.3) Beck Depression Inventory II 9.4 (5.2) 10.2 (6.6) SCOPA day 4.1 (3.7) 4.6 (3.2) SCOPA night 5.6 (5.1) 5.1 (4.0) Sleep efficiency, % 87.7 (6.6) 89.2 (4.6) Wake Bouts, n 32.8 (13.5) 35.7 (12.6) Total sleep time, min 503.3 (86.4) 484.6 (52.9) WASO, min 59.6 (29.8) 52.0 (22.0) Sleep onset variability, min 96.0 (104.0) 55.9 (45.8) Sleep offset variability, min 74.1 (66.1) 51.5 (41.2) Average daily nap time, min 47.8 (39.3) 42.1 (37.0) Days with a nap, sleep diary 6.2 (3.7) 5.0 (4.4)

Mean (SD) S-MCI (n ¼ 30)

t 1.0 0.6 2.0 0.6 1.6 1.8 0.8 0.7 1.9 1.0 1.2 1.5 1.1 0.4 0.5 0.4 1.0 0.8 1.0 1.0 1.5 1.3 0.5 0.9

M-MCI (n ¼ 24)

Age, years 63.6 (7.0) 67.5 (7.1) Sex, males:females 18:11 15:8 Education, years 13.5 (2.9) 13.8 (3.8) NART, predicted IQ 110.6 (12.6) 112.2 (12.0) Hoehn and Yahr, stage 2.1 (0.6) 2.2 (0.9) Disease duration, years 5.0 (5.4) 7.0 (6.9) UPDRS motor score 25.4 (10.4) 28.1 (17.5) Disease progression score 14.3 (10.4) 14.9 (16.3) Levodopa dose equivalent, mg 560.1 (460.5) 685.4 (556.9) Tremor score 0.5 (0.6) 0.4 (0.5) Nontremor score 1.4 (0.7) 1.4 (0.6) RSBDSQ total score 5.5 (3.8) 6.0 (3.5) NMSS restless legs total 1.5 (2.8) 2.0 (3.4) Beck Depression Inventory II 9.4 (7.0) 10.7 (4.9) SCOPA day 4.0 (3.4) 5.0 (3.2) SCOPA night 5.5 (4.8) 4.9 (3.9) Sleep efficiency, % 90.0 (4.4) 87.1 (6.1) Wake Bouts, n 32.5 (12.6) 37.5 (12.8) Total sleep time, min 490.6 (57.1) 490.6 (75.2) WASO, min 48.4 (20.3) 62.1 (28.2) Sleep onset variability, min 84.9 (88.8) 49.9 (38.0) Sleep offset variability, min 69.4 (63.6) 46.2 (25.9) Average daily nap time, min 38.8 (37.3) 50.5 (37.4) Days with a nap, sleep diary 4.9 (4.4) 6.0 (4.1)

t 2.0 0.1 0.3 0.5 0.5 1.2 0.7 0.2 0.9 0.7 0.4 0.5 0.7 0.8 1.1 0.5 2.0b 1.4 0.0 2.0b 1.7 1.8 1.0 0.8

Abbreviations: A-MCI, mild cognitive impairment amnestic subtype; NA-MCI, mild cognitive impairment nonamnestic subtype; NART, National Adult Reading Test; UPDRS, Unified Parkinson Disease Rating Scale; RSBDSQ, REM Sleep Behavior Disorder Screening Questionnaire; NMSS, Nonmotor Symptom Scale; SCOPA, Scales for Outcomes in Parkinson Disease; WASO, wake after sleep onset; IQ, intelligence quotient; SD, standard deviation. a Chi-square analysis was used to assess sex distribution.

Abbreviations: S-MCI, mild cognitive impairment single domain subtype; M-MCI, mild cognitive impairment multiple domain subtype; NART, National Adult Reading Test; UPDRS, Unified Parkinson Disease Rating Scale; RSBDSQ, REM Sleep Behavior Disorder Screening Questionnaire, NMSS, Nonmotor Symptom Scale; SCOPA, Scales for Outcomes in Parkinson Disease; WASO, wake after sleep onset; IQ, intelligence quotient; SD, standard deviation. a Chi-square analysis was used to assess sex distribution. b P < .05.

any demographic, clinical, self-report, or actigraphy sleep variable. Comparisons were also made between those that met criteria for S-MCI and M-MCI (Table 3). The M-MCI group was characterized by a significantly lower sleep efficiency (t ¼ 2.0, P ¼ .046) and a greater WASO (t ¼ 2.0, P ¼ .047) compared to those patients with PD who met criteria for S-MCI. These groups did not differ on any other variable measured.

positive and the PD-MCI-negative groups on age, gender, education, disease stage, disease duration or rate of progression, levodopa dose equivalent, or severity of depressive symptoms. The present findings are in agreement with a previous study of 35 nondemented patients with PD that reported an association between attentional and executive dysfunctional with sleep disturbance,13 an association that has also been demonstrated in healthy individuals.12,63,64 Although the present study only demonstrated differences between patients with PD and controls on measures of sleep efficiency and WASO, an earlier study has shown differences on all actigraphy measures between patients with PD and controls.65 This disparity may reflect the shorter disease duration of the patients included in the present study. Alternatively, the high sleep efficiency observed in the current sample with PD may in part be explained by the overestimation of sleep time as measured by actigraphy due to patients with akinetic-rigid PD who are less able to move in bed. Indeed, actigraphy has been found to overestimate sleep time in individuals with insomnia who attempt to fall asleep by lying motionless in bed.66

Discussion This study is the first to demonstrate the association of an objective measure of sleep efficiency with the presence of PD-MCI. Specifically, those classified with PD-MCI returned poorer actigraphically defined sleep efficiency scores compared to individuals with PD who had no cognitive impairment. Although the total rest time was comparable between the 2 groups, the reduction in sleep efficiency seemed to relate to having more WASO. This observation was not related to differences between the PD-MCI-

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We have previously shown an association between selfreported nighttime sleep and mood.14 Although no difference in mood between MCI subtypes was observed in this study, this may reflect the utilization of an objective sleep measure (actigraphy) rather than self-report questionnaires. These questionnaires are likely to have a degree of shared variance across items for similar domains, such as poor sleep and hypersomnolence, which are common to sleep disturbance and depression more generally. It should also be noted that although the PD-MCI subtypes in this study did not differ on their MMSE, the limitations of this instrument for detecting subtle cognitive deficits have been widely recognized.29,67,68 The PD-MCI-positive group was characterized by a significantly higher degree of motor dysfunction which was specifically related to their nontremor score. Despite this motor difference, sleep efficiency remained significantly worse in patients with PD-MCI compared to those without cognitive impairment even after controlling for the UPDRS motor score. Thus, it is possible that this reduction in sleep efficiency may be specifically related to nontremor features such as axial rigidity or bradykinesia, leading to nocturnal awakenings and longer periods of WASO through factors such as physical discomfort. The finding that PD-MCI was associated with a particular motor phenotype is consistent with a number of previous studies that have associated cognitive impairment in patient with PD having a nontremor dominant subgroup.29,44,69-71 This patient phenotype is also more likely to report higher levels of RBD and autonomic dysfunction.15,16,46 Comparison between the subtypes of PD-MCI demonstrated lower sleep efficiency in those patients with PD who meet criteria for M-MCI. This could indicate that as disease pathology progresses and more cognitive domains become impaired, there is an increased likelihood that the neural substrates involved in maintaining the sleep–wake cycle become increasingly compromised. Should this be the case then those patients with PD who meet criteria for M-MCI may represent the most ‘‘at-risk’’ population for whom targeted intervention for sleep disturbance may be warranted to improve cognitive performance. Due to the potential for negative cognitive and affective side effects that can result from pharmacotherapy,72 psychoeducational interventions may prove beneficial.73,74 This actigraphic study did not allow exploration of the contribution of common features such as RBD or obstructive sleep apnoea, which may impact on both sleep efficiency and cognition.75 Indeed, our group has previously shown that self-reported symptoms of nocturnal sleep disturbance and RBD are correlated with a broad range of cognitive impairments.14,35-37 Although the sample employed in the current study included individuals with PD and controls from our earlier reports of the associations between sleep disturbance and cognitive dysfunction in PD,14,42 the present study did not demonstrate the associations between cognition and RBD and EDS in PD that have been shown elsewhere.13,35,36,74 Rather, this study attempted to identify the sleep–wake factors associated with PD-MCI employing actigraphy. Although actigraphy has been suggested to be more reliable over several nights than

polysomnography (PSG),76 future studies with larger patient samples incorporating PSG will be required. It is also worth noting that sleep–wake disturbance per se (eg, manifesting as hypersomnolence) can interfere with performance on cognitive testing and could have potentially contributed to the results of this study. The findings of this study prompt several opportunities for future research. In general, more research on PD-MCI is required in order to identify the relationship between sleep– wake disturbance and MCI subtype, in particular accounting for features of excessive daytime somnolence and RBD. Characterizing these relationships will become especially important as new therapeutic options become available, affording the opportunity for early intervention strategies that may ameliorate cognitive decline. Authors’ Note David G. Gunn was involved in the conception, organization and execution of the research project, the design and execution of the statistical analysis and manuscript preparation; Sharon L. Naismith was involved in the conception and organization of the research project, the design, execution and critique of the statistical analysis and the review and critique of the manuscipt; Zoe Terpening was involved in the conception, organization and execution of the research project, the execution of the statistical analysis and the writing of and critique of the manuscript. Simon J. G. Lewis was involved in the conception, organization and execution of the research project, critique of the statistical analysis, and the writing of and review of the manuscript.

Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Lewis is supported by an NHMRC Practitioner Fellowship and a University of Sydney Rolf Edgar Lake Postdoctoral Fellowship. Naismith is supported by an NHMRC Career Development Award.

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