Li-Jun Zuo; Shu-Yang Yu; Fang Wang; Yang Hu; Ying-Shan Piao; Yang Du; Teng-Hong Lian; Rui-Dan Wang; Qiu-Jin Yu; Ya-Jie Wang; Xiao-Min Wang; Piu Chan; Sheng-Di Chen; Yongjun Wang; Wei Zhang

doi:10.3988/jcn.2016.12.2.172

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Zuo, Yu, Wang, Hu, Piao, Du, Lian, Wang, Yu, Wang, Wang, Chan, Chen, Wang, and Zhang: Parkinson's Disease with Fatigue: Clinical Characteristics and Potential Mechanisms Relevant to α-Synuclein Oligomer

Original Article

Journal of Clinical Neurology 2016; 12(2): 172-180.

Published online: 4 February 2016

DOI: https://doi.org/10.3988/jcn.2016.12.2.172

Parkinson's Disease with Fatigue: Clinical Characteristics and Potential Mechanisms Relevant to α-Synuclein Oligomer

Li-Jun Zuo^a, Shu-Yang Yu^b, Fang Wang^a, Yang Hu^b, Ying-Shan Piao^b, Yang Du^a, Teng-Hong Lian^a, Rui-Dan Wang^a, Qiu-Jin Yu^a, Ya-Jie Wang^c, Xiao-Min Wang^d, Piu Chan^e,^f, Sheng-Di Chen^g, Yongjun Wang^a,^h, Wei Zhang^b,^e,^h,ⁱ

^aDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

^bDepartment of Geriatrics, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

^cCore Laboratory for Clinical Medical Research, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

^dDepartment of Physiology, Capital Medical University, Beijing, China.

^eCenter of Parkinson's Disease, Beijing Institute for Brain Disorders, Beijing, China.

^fDepartment of Neurobiology, Beijing Xuanwu Hospital, Capital Medical University, Beijing, China.

^gDepartment of Neurology, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.

^hChina National Clinical Research Center for Neurological Diseases, Beijing, China.

ⁱBeijing Key Laboratory on Parkinson's Disease, Beijing, China.

Correspondence: Wei Zhang, MD, PhD. Department of Geriatrics, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China. Tel +86-13911996107, Fax +86-10-67098429, ttyyzw@163.com

Received 11 June 2015 Revised 1 October 2015 Accepted 2 October 2015

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background and Purpose

The aim of this study was to identify the clinical characteristics and potential mechanisms relevant to pathological proteins in Parkinson's disease (PD) patients who experience fatigue.

Methods

PD patients (n=102) were evaluated using a fatigue severity scale and scales for motor and nonmotor symptoms. The levels of three pathological proteins—α-synuclein oligomer, β-amyloid (Aβ)_1-42, and tau—were measured in 102 cerebrospinal fluid (CSF) samples from these PD patients. Linear regression analyses were performed between fatigue score and the CSF levels of the above-listed pathological proteins in PD patients.

Results

The frequency of fatigue in the PD patients was 62.75%. The fatigue group had worse motor symptoms and anxiety, depression, and autonomic dysfunction. The CSF level of α-synuclein oligomer was higher and that of Aβ_1-42 was lower in the fatigue group than in the non-fatigue group. In multiple linear regression analyses, fatigue severity was significantly and positively correlated with the α-synuclein oligomer level in the CSF of PD patients, after adjusting for confounders.

Conclusions

PD patients experience a high frequency of fatigue. PD patients with fatigue have worse motor and part nonmotor symptoms. Fatigue in PD patients is associated with an increased α-synuclein oligomer level in the CSF.

Keywords: Parkinson's disease, fatigue, motor symptoms, nonmotor symptoms, α-synuclein oligomer, cerebrospinal fluid

INTRODUCTION

Parkinson's disease (PD) is a progressive neurodegenerative disorder with typical motor symptoms and various nonmotor symptoms, including neuropsychiatric symptoms, autonomic dysfunctions, abnormal sense, sleep disorders, and fatigue. According to the International Classification of Diseases (ICD)-10, the signs and symptoms of fatigue include asthenia, debility, general physical deterioration, lethargy, and tiredness.1 Currently there is less attention paid to fatigue than to other nonmotor symptoms of PD. The PaRkinson And non Motor symptOms study found that fatigue was present in 58.1% of 1072 PD patients, ranging from 37.7% in the early stage to 81.6% in the advanced stage.2 Importantly, about 50% of PD patients reportedly consider fatigue to be one of the most disabling nonmotor symptoms.3 Fatigue dramatically compromises the activities of daily living and the quality of life for PD patients.4 5

While the epidemiology of PD with fatigue has been investigated, how fatigue is related to demographic information, motor symptoms, and other nonmotor symptoms of PD is still uncertain, with uncertain inclusion criteria having been applied. Exploring these issues may identify the most important clinical characteristics and underlying factors of fatigue, thereby yielding potential therapeutic targets for PD with fatigue.

While fatigue is very common in PD patients and impacts their quality of life, little is known about the underlying mechanisms. The presence of any correlations between fatigue and pathological proteins in the cerebrospinal fluid (CSF) is still unclear. α-synuclein oligomer is the main component of Lewy bodies—the pathological hallmark of PD—in both neuronal bodies and neurites. β-Amyloid (Aβ)_1-42 is the core component of neuroinflammatory plaques in the extracellular space, and phosphorylated tau (P-tau) is the main component of neurofibrillary tangles in the brains of Alzheimer's disease (AD) patients. Pathological changes associated with AD are also found in PD brains;6 for example, PD patients without dementia have a large Aβ_1-42 burden in the brain.7 8 9 Moreover, increasing attention is being paid to Aβ_1-42 and tau burdens in both early and late PD.10 11 These data imply that PD may be a complex clinicopathological entity. Past studies have revealed relationships between the above-mentioned pathological proteins and motor symptoms of PD. For example, it has been reported that decreased CSF levels of α-synuclein and total tau (T-tau) are associated with an increased severity of motor symptoms in PD patients.11 α-synuclein is also related to nonmotor symptoms such as olfactory dysfunction.12 Our previous work has demonstrated that an increased CSF α-synuclein oligomer level is associated with rapid-eye-movement-sleep behavior disorder (RBD).13 Moreover, tau and Aβ are all involved in PD with dementia.14 However, the relationships between fatigue and the above-mentioned pathological proteins—α-synuclein oligomer, Aβ_1-42, T-tau, and P-tau—are uncertain.

In this study we investigated the clinical characteristics and potential mechanisms relevant to pathological proteins in PD patients with fatigue, with the aim of identifying clues for the early identification of and effective clinical interventions for PD with fatigue.

METHODS

Subjects

Patients with PD. In total, 102 PD patients were recruited from the neurodegenerative outpatient clinics in the Department of Geriatrics and Neurology, Beijing Tiantan Hospital, Capital Medical University. Demographic information including sex, age, and education level, and disease duration as well as levodopa equivalent daily doses was recorded (Table 1). Among the 102 PD patients, 51 cases (50.0%) were male and 51 (50.0%) were female with ages ranging from 30 to 85 years (60.4±10.4 years, mean±SD). The disease duration varied from 1 month to 22 years, with a median of 2.1 years [interquartile range (IQR): 4.3 years]. The demographic characteristics are listed in Table 1. Patients were diagnosed with PD according to criteria of Parkinson's UK Brain Bank.15 PD patients with any type of dementia (according to criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) and systemic diseases including hypertension, anemia, hepatosis, heart failure, pulmonary disorders, chronic liver/renal failure, severe hypothyroidism, and diabetes were excluded. PD patients with an Epworth Sleepiness Scale score of >616 or an Apathy Scale score of ≥14 were excluded.17

Control subjects. In total, 31 age-matched controls from Beijing Tiantan Hospital were selected based on the following criteria: 1) no essential tremor, PD, secondary parkinsonism, or Parkinson-plus syndrome; 2) no systemic diseases affecting sleep or fatigue, such as hypertension, anemia, hepatosis, heart failure, pulmonary disorders, chronic liver/renal failure, severe hypothyroidism, diabetes, or epilepsy history; 3) no dysarthria or mental illness that affect expression; 4) no obvious apathy, cognitive impairment, or psychiatric symptoms; and 5) no alcohol or drug abuse. Six control subjects whose CSF levels of α-synuclein oligomer were below 0.078 ng/mL were excluded.

The controls were also patients, but their diseases were not related to and did not influence the results of this investigation, such as peripheral neuropathy and headache caused by high intracranial pressure.

Assessment of fatigue

The Fatigue Severity Scale (FSS) satisfies the criteria of a "recommended" fatigue scale in PD (both for screening and severity rating) because it has been shown to have good psychometric properties (including for discriminating between fatigued and non-fatigued patients) in PD patients and has also been used in previous studies.18 It is a self-administered nine-item fatigue rating scale that encompasses several aspects of fatigue and their impact on the daily functioning of patients. Patients were asked to rate how each item described their fatigue level from 1 ("strongly disagree") to 7 ("strongly agree"). The total FSS score was obtained by dividing the sum of all item scores by 9. When it was used with a cutoff of 4 points, the sensitivity and specificity were 75.5% and 74.5%, respectively. Patients with total FSS scores of >4 points and ≤4 points were classified into the fatigue and non-fatigue groups, respectively.19

This study was approved by the review board of Beijing Tiantan Hospital. Written informed consent was obtained from all participants.

Clinical assessments of motor and nonmotor symptoms

The severity of PD was assessed based on the Hoehn and Yahr (H-Y) stage. Motor symptoms were evaluated by Unified Parkinson's Disease Rating Scale (UPDRS) III, in which items 20 and 21 were for tremor, item 22 was for rigidity, items 23–26 and 31 were for bradykinesia, and items 27–30 were for postural and gait abnormalities. The score for each motor symptom was calculated by summing up the score for the relevant items in UPDRS III. Nonmotor symptoms were evaluated using the following scales: Hamilton Depression Scale (HAMD) (24 items for depression), Hamilton Anxiety Scale (HAMA) (14 items for anxiety), Scale for Outcomes in Parkinson's Disease for Autonomic Symptoms (SCOPA-AUT) for autonomic dysfunctions, Mini Mental State Examination for cognitive decline, and Restless Legs Syndrome Rating Scale for restless legs symptoms.

Collection of CSF samples

Antiparkinsonian drugs were withheld for 12–14 hours prior to sampling the CSF. Three milliliters of CSF were obtained using a lumbar puncture between 7 a.m. and 10 a.m. under a fasting condition, and placed in a polypropylene tube. Approximate 0.5 mL volumes of CSF were aliquoted into separate Nunc cryotubes and kept frozen at -80℃ until used in assays. The use of a separate aliquot for each measure avoided freeze-thawing and the associated potential degradation of proteins. We analyzed the validity of the measurements of the CSF levels of α-synuclein oligomer, which showed acceptable intrarun and interrun precisions, with coefficients of variation of 8.5% and 9.8%, respectively.

We took the following actions in order to avoid blood contamination resulting in misleading measurements of the CSF α-synuclein oligomer level: 1) we performed the lumbar puncture very carefully to avoid injury; 2) we examined the CSF sample of each PD patient or control subject, and excluded samples if they were red or turbid, or red blood cells were evident; and 3) all CSF samples were centrifuged at 3,000 rpm for 10 minutes to remove cells and debris. Since the limit of detection (analytical sensitivity) for α-synuclein oligomer was 0.078 ng/mL, six control subjects with CSF α-synuclein oligomer levels below 0.078 ng/mL were excluded. Eventually, totals of 102 PD patients and 25 control subjects were recruited into this study.

Detection of pathological proteins

The CSF levels of pathological proteins were determined using an enzyme-linked immunosorbent assay, including those of α-synuclein oligomer, Aβ_1-42, T-tau, and tau phosphorylated at the following positions: threonine 181 (P-tau_181t), threonine 231 (P-tau_231t), serine 396 (P-tau_396s), and serine 199 (P-tau_199s). CSB-E18033h, CSB-E10684h, and CSB-E12011h kits for measuring α-synuclein oligomer, Aβ_1-42, and T-tau, respectively, were obtained from CUSABIO (Wuhan, China), while KHB7031, KHB7041, KHB8051, and KHO0631 kits for measuring P-tau_396s, P-tau_199s, P-tau_231t, and P-tau_181t, respectively, were obtained from Invitrogen (Carlsbad, CA, USA). The levels of α-synuclein oligomer, Aβ_1-42, T-tau, P-tau_181t, P-tau_231t, P-tau_396s, and P-tau_199s were measured using a quantitative sandwich enzyme immunoassay.

Data analyses

Statistical analyses were performed with SPSS Statistics (version 20.0, SPSS Inc., Chicago, IL, USA). Demographic information was compared among the control, fatigue, and non-fatigue groups. Motor and nonmotor symptoms were compared between the fatigue and non-fatigue groups. The CSF levels of pathological proteins were detected and compared among the control, fatigue, and non-fatigue groups. Continuous variables that were normally distributed are reported as mean±SD values, with two-tailed t-tests used for two-group comparisons and ANOVAs used for three-group comparisons. Continuous variables that were not normally distributed are reported as median (IQR) values, with the Kruskal-Wallis test used for both two- and three-group comparisons.

Multiple linear regression analyses were used to investigate the associations between the scores for fatigue severity and the CSF levels of pathological proteins in three models: Model 1, unadjusted; Model 2, adjusted for age, sex, disease duration, and levodopa equivalent daily doses; and Model 3, additionally adjusted for UPDRS III, rigidity, bradykinesia, HAMA, HAMD, and SCOPA-AUTO scores. Probability values of p<0.05 were considered to indicate statistically significant differences.

RESULTS

Frequency of fatigue, demographic information, motor symptoms, and nonmotor symptoms in the fatigue and non-fatigue groups

Fatigue was present in 64 (62.7%) of the 102 PD patients. The median fatigue severity scores in the fatigue and non-fatigue groups were 5.7 (IQR=1.8) and 2.2 (IQR=1.89) points, respectively (Table 2). Ten (15.6%) of the 64 PD patients with fatigue had experienced fatigue before the onset of motor symptoms. The fatigue group showed a more advanced H-Y stage, higher total UPDRS III scores, and higher scores for rigidity and bradykinesia according to UPDRS III relative to the non-fatigue group. The fatigue group also exhibited higher HAMA, HAMD, and SCOPA-AUTO scales than the non-fatigue group, suggesting that the fatigued individuals had worse anxiety, depression, and autonomic dysfunctions. Age, sex, education level, disease duration, and levodopa equivalent daily dose did not differ between the fatigue and non-fatigue groups (Table 2).

Comparisons of pathological protein levels in the CSF among the control, fatigue, and non-fatigue groups

Table 3 compares the CSF levels of α-synuclein oligomer, Aβ_1-42, T-tau, P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s among the control, fatigue, and non-fatigue groups. The level of α-synuclein oligomer in the CSF of the fatigue group was strikingly elevated relative to the control and non-fatigue groups (p<0.017), while the CSF level of Aβ_1-42 in the fatigue group was remarkably decreased relative to the control group (p<0.017).

The levels of P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s in the CSF were higher in both the fatigue and non-fatigue groups than in the control group, while the T-tau level was markedly higher in the fatigue group than in the control group (p<0.017). The CSF levels of P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s did not differ significantly between the fatigue and non-fatigue groups (Table 3).

Correlations between fatigue severity and the CSF levels of pathological proteins in PD patients

Multiple linear regression models were constructed in which the FSS score was set as a dependent variable in order to investigate the associations between the score for the fatigue severity and the CSF levels of pathological proteins (Models 1, 2, and 3).

The multiple linear regression equation was statistically significant for Model 1 (F=16.998, p<0.0001), Model 2 (F=11.576, p=0.002), and Model 3 (F=11.12, p=0.003). Our data indicate that the α-synuclein oligomer level in the CSF was the only factor influencing the FSS score in the PD group [regression coefficient=0.78, p=0.003]. The association remained significant after adjusting for each group of confounders. Among the demographic factors and clinical variables, an increased CSF level of α-synuclein oligomer was associated with the fatigue severity as assessed by the FSS (Table 4).

DISCUSSION

Fatigue was firstly noted by James Parkinson in 1817 in his original description of PD, but it was not investigated further until very recently. The overall frequency of fatigue (defined as an FSS mean score of >4 points) in this study was 62.5%, indicating that fatigue is a very common nonmotor symptom of PD. This frequency of fatigue among our PD patients is higher than those found in a previous study,2 which may be due to differences in disease durations.

According to ICD-10, fatigue includes asthenia, debility, general physical deterioration, lethargy, and tiredness.1 While there is generally considered to be no relationship between fatigue and the severity of motor symptoms,3 the PD patients with fatigue in the present study showed a more advanced H-Y stage and higher total UPDRS III score (Table 2), demonstrating that fatigue worsens with disease progression and severity.20 21 22 Importantly, further analyses of each motor symptom in the PD patients revealed that the scores for rigidity and bradykinesia as evaluated by the corresponding items in UPDRS III were significantly higher in the fatigue group than in the non-fatigue group (Table 2), whereas the scores for tremor and postural and gait abnormalities did not differ between the fatigue and non-fatigue groups. Bradykinesia is caused by the defective preparation of voluntary movement and alteration in movement execution,23 which may contribute to fatigue in PD patients.24 No previous study has investigated the relationship between rigidity and fatigue, and so the present study is the first to reveal that rigidity is related to PD with fatigue. Similar to bradykinesia, rigidity worsens at an annual rate and is an unremitting motor symptom, which together with rigidity25 26 27, may contribute to fatigue in PD. There is no correlation between fatigue and tremor. Recent studies suggest that tremor is usually an episodic phenomenon and does not worsen at a fixed rate,28 suggesting that the pathophysiology underlying tremor differs from those of bradykinesia and rigidity.29 30 In contrast to a previous report, the scores for postural and gait abnormalities are higher in PD patients with fatigue than in those without fatigue.31 The present study found no relationship between postural and gait abnormalities and fatigue, which may be due to the different fatigue scales and cutoff points adopted. Additionally, the early stage of PD is characterized by tremor, rigidity, and bradykinesia, with or without axial involvement, while postural and gait abnormalities usually occur at the late stage. Most of the PD patients included in the present study were in the early stage, which may explain the absence of a correlation between fatigue and postural and gait abnormalities. It may therefore be worthwhile to further investigate the relationship between fatigue and postural and gait abnormalities among patients in the late stage. Each individual motor symptom of PD might not be independently correlated with fatigue, but when multiple symptoms are present they may work together and amplify the effect of each other, significantly contributing to PD with fatigue. In this study, the control, fatigue, and non-fatigue groups showed no significant differences in demographic information (including age, sex, and education level), disease duration, and levodopa equivalent daily dose (Table 1), indicating that fatigue is not related to those factors.32 33 34

Previous studies have explored the relationship between fatigue and other nonmotor symptoms of PD, but no definitive conclusions were drawn. This study found that PD patients in the fatigue group had worse depression, anxiety, and autonomic dysfunctions than those in the non-fatigue group (Table 2). Pavese reported that fatigue in PD patients was related to the serotonin (5-HT) system by using ¹¹C-DASB [N,N-dimethyl-2-(2-amino-4-cyanophenylthio) benzylamine].35 We directly investigated the relationship between fatigue severity and the level of 5-HT in the CSF of PD patients, and found that fatigue severity was negatively and significantly related to the CSF 5-HT level (r=-0.45, p=0.003; unpublished data) (Table 5). Several studies have suggested that serotonergic dysfunction is relevant to the development of fatigue as well as depression and anxiety in PD patients,36 37 implying that these three symptoms may share the same neurobiological mechanisms.37 For example, depression and anxiety may precipitate the occurrence of fatigue,38 39 and depression and autonomic dysfunctions have been found to exacerbate the subjective perception of fatigue.40 When Lewy bodies are deposited in the lower raphe nuclei, magnocellular portions of the reticular formation, and the locus coeruleus of PD patients, they may manifest as autonomic dysfunction and fatigue, both of which may share the same pathological mechanism.41 Our previous study showed that the FSS score is positively correlated with the SCOPA-AUTO score (r=058, p=0.035, unpublished data) (Table 5). These data are indicative of the strong correlation of fatigue with depression, anxiety, and autonomic dysfunction. A few studies have explored the relationship between fatigue and cognitive impairment, as well as restless legs symptom. The present study found no significant difference in cognitive function and restless legs symptom between the fatigue and non-fatigue groups.

We investigated the potential mechanisms of fatigue in PD by measuring the levels of pathological proteins in the CSF. The pathological hallmark of PD is the formation of α-synuclein-containing Lewy bodies. The oligomer is the most neurotoxic form of α-synuclein in Lewy bodies.42 α-synuclein oligomer has been observed in the extracellular space,43 and it may be released from degenerative or dead neurons. An excessive level of the α-synuclein oligomer in the CSF may reflect an elevated level of α-synuclein oligomer in the brain.44

In the current study, the CSF level of α-synuclein oligomer in the fatigue group was remarkably enhanced relative to those in the non-fatigue and control groups. In multiple linear regression the FSS score was associated with the elevated α-synuclein oligomer level in the CSF of PD patients. Moreover, even after adjusting for demographic factors and additional clinical variables, the increased CSF level of α-synuclein oligomer was still associated with the fatigue severity as assessed by the FSS. The levels of Aβ_1-42, T-tau, P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s, and the UPDRS III, rigidity, bradykinesia, HAMA, HAMD, and SCOPA-AUTO scores did not enter in the regression equation. These results imply that the increased α-synuclein oligomer in the brain may be the pathogenesis of fatigue in PD patients. A previous study demonstrates that motor symptoms and some nonmotor symptoms, such as cognitive impairment and RBD, are both correlated with the CSF level of α-synuclein oligomer.10 13 45 The present study is the first to explore the relationship between PD with fatigue and the level of pathological proteins in the CSF, and it finds that fatigue is correlated with an enhanced level of α-synuclein oligomer in the CSF. A previous study found that missense and multiplication mutations in the α-synuclein gene were linked to clinical and pathological phenotypes in PD,46 highlighting a direct role of α-synuclein overexpression in the pathogenesis of PD. The CSF level of α-synuclein oligomer has previously been reported to be higher in PD patients than in normal brains.44,47,48,49 However, some studies found the opposite result, which may be explained by cerebral accumulation of the α-synuclein oligomer.50 The patients included in previous studies had a higher H-Y stage (higher than stage 2.5),51 and an increased CSF α-synuclein level might be a marker of more intense synaptic degeneration in PD.52 However, most of the PD patients in the present study were from geriatric clinics, and their H-Y stage was 2.05±0.80. Thus, the CSF α-synuclein oligomer level might vary during the course of PD progression: it might be elevated in the early stage of PD and then decreased in the later stage. Therefore, we postulate that degenerative or dead brain cells can release more α-synuclein oligomer into the extracellular spaces of fatigue-related areas, and thereby cause sustained brain cell death, and eventually induce the occurrence of fatigue in PD patients. The results obtained in this study suggest that the α-synuclein oligomer could serve as a useful biomarker indicating the severity of PD with fatigue.

It has been reported that the decreased Aβ_1-42 level in the CSF is related to memory impairment in PD patients.8,11,53,54 A reduced Aβ_1-42 level in the CSF even tends to precede the onset of PD with mild cognitive impairment.55 Studies have revealed common mechanisms in AD and PD. However, no previous study has investigated the relationship between fatigue and Aβ_1-42 level in the CSF. The present study is therefore the first to show that the CSF level of Aβ_1-42 in PD patients with fatigue is significantly decreased relative to control patients. The level of Aβ_1-42 in the CSF did not differ between the fatigue and non-fatigue groups. However, our analysis of multiple linear regression models revealed no association between fatigue severity and decreased Aβ_1-42 level. These data imply that Aβ_1-42 alone might not be associated with fatigue, but it could still combine with other mechanisms to contribute to PD with fatigue. Furthermore, most of patients in our study were in the early stage, and Aβ_1-42 aggregation might not play a key role in the pathological progression of PD with fatigue at that time.

It has been reported that tau is involved in the mechanisms underlying PD.56 In the present study the CSF levels of P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s were significantly higher in both the fatigue and non-fatigue groups than in the control group, but there were no differences between the fatigue and non-fatigue groups. The T-tau level in the CSF did not differ among the control, fatigue, and non-fatigue groups. These data indicate that T-tau, P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s are more relevant to PD itself than the fatigue symptom that appears with PD.

In summary, the frequency of fatigue in the current PD patients was 62.7%. PD with fatigue was associated with advanced H-Y stage, worse motor symptoms (especially rigidity and bradykinesia), and several worse nonmotor symptoms (e.g., anxiety, depression, and autonomic dysfunctions). The increased level of α-synuclein oligomer in the CSF appears to be associated with fatigue severity in PD patients. This study has highlighted the clinical characteristics and potential mechanisms relevant to α-synuclein oligomer in PD patients with fatigue.

This study was subject to some limitations. Firstly, relatively few CSF samples were analyzed due to the difficulties of obtaining CSF from PD patients, which may have weakened the statistical power of the analyses, such as of the correlation between PD with fatigue and the Aβ_1-42 level in the CSF. Secondly, this study was designed to identify the clinical characteristics and potential mechanisms relevant to pathological proteins in PD patients who experience fatigue, it is a cross-sectional study, therefore, causal relationships between the levels of pathological proteins in the CSF of PD patients and fatigue could not be determined.

Figures and Tables

Table 1

Demographic variables in the control, fatigue, and non-fatigue groups

Variable	Control group (n=25)	Non-fatigue group (n=38)	Fatigue group (n=64)	p
Male/total [cases/total (%)]	12/25 (48.0)	17/38 (44.7)	33/64 (51.5)	0.45
Age (years, mean±SD)	56.7±11.2	55.9±12.2	60.8±9.9	0.23
Education level [cases/total (%)]				0.12
Primary school and below	8/25 (32.0)	11/38 (28.9)	20/64 (31.2)
Middle and high school	10/25 (40.0)	20/38 (52.6)	34/64 (53.1)
Bachelor's degree and above	7/25 (28.0)	7/38 (18.4)	10/64 (15.6)

Table 2

Clinical variables associated with fatigue in Parkinson's disease (PD)

Variable	Non-fatigue group (n=38)	Fatigue group (n=64)	p
Disease duration [years, median (IQR)]	2.1 (3.1)	3.2 (4.3)	0.05
Fatigue severity [score, median (IQR)]	2.2 (1.9)	5.7 (1.8)	<0.001^*
Levodopa equivalent daily dose (mg, mean±SD)	302.8±109.4	313.2±113.5	0.347
Motor symptoms
H-Y stage (mean±SD)	1.8±0.7	2.2±0.8	<0.001^*
UPDRS III scores [median (IQR)]	21.0 (17.1)	26.5 (17.0)	<0.001^*
Tremor	4.0 (4.0)	4.0 (4.0)	0.49
Rigidity	1.0 (3.0)	2.0 (3.0)	<0.001^*
Bradykinesia	9.0 (8.0)	10.0 (8.0)	<0.001^*
Postural and gait abnormalities	4.0 (3.0)	4.0 (3.0)	0.06
Nonmotor symptoms
HAMD score (mean±SD)	38.0±9.2	56.0±14.6	<0.001^*
HAMA score (mean±SD)	29.0±8.7	36.0±13.2	<0.001^*
SCOPA-AUTO score (mean±SD)	32.6±8.9	38.7±8.1	<0.001^*
MMSE score (mean±SD)	26.8±4.0	26.4±3.9	0.186
RLSRS score [median (IQR)]	3.0 (15.8)	5.0 (18.0)	0.289

_*p<0.01.

HAMA: Hamilton Anxiety Scale, HAMD: Hamilton Depression Scale, H-Y: Hoehn and Yahr, IQR: interquartile range, MMSE: Mini Mental State Examination, RLSRS: Restless Legs Syndrome Rating Scale, SCOPA-AUTO: Scale for Outcomes in Parkinson's Disease for Autonomic Symptoms, UPDRS III: Unified Parkinson's Disease Rating Scale, Part III.

Table 3

Cerebrospinal fluid (CSF) levels of pathological proteins in the control, fatigue, and non-fatigue groups

Protein	Control group (n=25)	Non-fatigue group (n=38)	Fatigue group (n=64)	P	P1	P2	P3
α-synuclein oligomer [ng/mL, median (IQR)]	0.08 (0.02)	0.29 (0.19)	0.70 (0.32)	<0.001^‡	<0.001^‡	<0.001^‡	0.004^‡
Aβ_1-42 [ng/mL, median (IQR)]	83.3 (49.2)	41.9 (29.4)	21.6 (24.0)	<0.001^‡	0.021	<0.001^‡	0.030
T-tau [pg/mL, median (IQR)]	34.2 (117.5)	96.9 (112.8)	105.7 (119.9)	<0.001^‡	0.052	<0.001^‡	0.036
P-tau_231t (pg/mL, mean±SD)	78.1±37.8	116.6±59.8	138.2±60.4	0.018^*	0.016^*	0.011^*	0.442
P-tau_181t (pg/mL, mean±SD)	31.4±15.8	66.3±6.3	78.9±28.8	0.022^*	0.026^*	<0.001^†	0.224
P-tau_199s (pg/mL, mean±SD)	3.3±1.3	6.4±1.5	6.5±1.8	0.012^*	0.019^*	<0.001^†	0.812
P-tau_396s (pg/mL, mean±SD)	31.4±15.3	72.0±27.3	78.0±32.4	0.013^*	0.018^*	<0.001^†	0.654

^*p<0.05, ^†p<0.01, ^‡p<0.017.

P: Kruskal-Wallis test was used to compare CSF levels of α-synuclein oligomer, Aβ_1-42, and T-tau among control, fatigue, and non-fatigue groups; p<0.05, statistically significant. ANOVA was used to compare P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s CSF levels among control, fatigue, and non-fatigue groups; p<0.05, statistically significant. P1: Control group vs. non-fatigue group; Kruskal-Wallis test was used to compare CSF levels of α-synuclein oligomer, Aβ_1-42, and T-tau between control and non-fatigue groups; p<0.017, statistically significant. Two-tailed t-test was used to compare P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s CSF levels between the control and non-fatigue groups, p<0.05 was defined as statistically significant. P2: Control group vs. fatigue group; Kruskal-Wallis test was used to compare CSF levels of α-synuclein oligomer, Aβ_1-42, and T-tau between control and fatigue groups; p<0.017, statistically significant. Two-tailed t-test was used to compare CSF levels of P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s between control and fatigue groups; p<0.05, statistically significant. P3: Fatigue group vs. non-fatigue group; Kruskal-Wallis test was used to compare CSF levels of α-synuclein oligomer, Aβ_1-42, and T-tau between fatigue and non-fatigue groups; p<0.017, statistically significant. Two-tailed t-test was used to compare CSF levels of P-tau_231t, P-tau_181t, P-tau_199s, and P-tau_396s between fatigue and non-fatigue groups; p<0.05, statistically significant.

Aβ_1-42: β-amyloid_1-42.

Table 4

Linear regression analyses between CSF pathological proteins and fatigue severity (n=102)

	Model l	Model 2	Model 3
α-synuclein oligomer (ng/mL)	0.8 (0.4~1.2)^*	0.7 (0.2~1.2)^*	0.6 (0.1~1.3)^*
Aβ_1-42 (ng/mL)	8.0 (-7.8~23.8)	7.7 (-10.3~25.0)	7.6 (-9.5~26.2)
T-tau (pg/mL)	-0.3 (-1.2~2.2)	-0.3 (-2.5~5.7)	-2.4 (-2.0~5.1)
P-tau_231t (ng/mL)	0.0 (-0.1~0.1)	0.0 (-0.1~0.1)	0.0 (-0.2~0.2)
P-tau_181t (ng/mL)	0.0 (-0.2~0.2)	0.0 (-0.2~0.2)	0.0 (-0.5~0.2)
P-tau_199s (ng/mL)	0.1 (-2.5~2.6)	-0.5 (-3.8~2.8)	-1.6 (-4.0~2.6)
P-tau_396s (ng/mL)	0.0 (-0.2~0.1)	0.0 (-0.2~0.2)	0.0 (-0.3~0.2)

Data β (95% confidence interval) values. Model 1: unadjusted. Model 2: adjusted for age, sex, disease duration, and levodopa equivalent daily doses. Model 3: additionally adjusted for UPDRS III, rigidity, bradykinesia, HAMA, HAMD, and SCOPA-AUTO scores.

^*p<0.01.

CSF: cerebrospinal fluid, HAMA: Hamilton Anxiety Scale, HAMD: Hamilton Depression Scale, SCOPA-AUTO: Scale for Outcomes in Parkinson's Disease for Autonomic Symptoms, UPDRS III: Unified Parkinson's Disease Rating Scale, Part III.

Table 5

Correlations of fatigue severity with CSF 5-HT level and autonomic dysfunction score in the PD group

Fatigue severity	r	p
5-HT (ng/µL)	-0.45	0.003^‡
SCOPA-AUTO score	0.58	0.035^*

^*p<0.05, ^†p<0.01.

CSF: cerebrospinal fluid, PD: Parkinson's disease, SCOPA-AUTO: Scale for Outcomes in Parkinson's Disease for Autonomic Symptoms.

Acknowledgements

This work was performed at Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

This work is supported by the National Key Basic Research Program of China (2011CB504100), the National Natural Science Foundation of China (81571229, 81071015, 30770745), the Natural Science Foundation of Beijing, China (7082032), the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2013BAI09B03), the project of Beijing Institute for Brain Disorders (BIBD PXM2013_014226_07_000084), the High Level Technical Personnel Training Project of Beijing Health System, China (2009-3-26), the Project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges Under Beijing Municipality (IDHT20140514), the Capital Clinical Characteristic Application Research (Z121107001012161), the Beijing Healthcare Research Project (JING-15-2, JING-15-3), the Excellent Personnel Training Project of Beijing, China (20071D0300400076), the Important National Science & Technology Specific Projects (2011ZX09102-003-01), the Key Project of National Natural Science Foundation of China (81030062), the Key Project of Beijing Natural Science Foundation (kz200910025001) and the Basic-Clinical Research Cooperation Funding of Capital Medical University (10JL49, 14JL15, 2015-JL-PT-X04), and Youth Research Fund, Beijing Tiantan Hospital, Capital Medical University, China (2014-YQN-YS-18).

Notes

^{Conflicts of Interest} The authors have no financial conflicts of interest.

References

1. World Health Organization. International statistical classification of diseases and related health problems. 10th revision [Internet]. Geneva: World Health Organization;2010. cited 2015 Oct 8. Available from: URL: www.who.int/classifications/icd/ICD10Volume2_en_2010.pdf?ua=1.

2. Barone P, Antonini A, Colosimo C, Marconi R, Morgante L, Avarello TP, et al. The PRIAMO study: a multicenter assessment of nonmotor symptoms and their impact on quality of life in Parkinson's disease. Mov Disord. 2009; 24:1641–1649.

3. Abe K, Takanashi M, Yanagihara T. Fatigue in patients with Parkinson's disease. Behav Neurol. 2000; 12:103–106.

4. Alves G, Wentzel-Larsen T, Larsen JP. Is fatigue an independent and persistent symptom in patients with Parkinson disease? Neurology. 2004; 63:1908–1911.

5. Schifitto G, Friedman JH, Oakes D, Shulman L, Comella CL, Marek K, et al. Fatigue in levodopa-naive subjects with Parkinson disease. Neurology. 2008; 71:481–485.

6. Marder K. Cognitive impairment and dementia in Parkinson's disease. Mov Disord. 2010; 25:Suppl 1. S110–S116.

7. Buongiorno M, Compta Y, Martí MJ. Amyloid-β and τ biomarkers in Parkinson's disease-dementia. J Neurol Sci. 2011; 310:25–30.

8. Compta Y, Martí MJ, Ibarretxe-Bilbao N, Junqué C, Valldeoriola F, Muñoz E, et al. Cerebrospinal tau, phospho-tau, and beta-amyloid and neuropsychological functions in Parkinson's disease. Mov Disord. 2009; 24:2203–2210.

9. Kang JH, Irwin DJ, Chen-Plotkin AS, Siderowf A, Caspell C, Coffey CS, et al. Association of cerebrospinal fluid β-amyloid 1-42, T-tau, P-tau181, and α-synuclein levels with clinical features of drug-naive patients with early Parkinson disease. JAMA Neurol. 2013; 70:1277–1287.

10. Montine TJ, Shi M, Quinn JF, Peskind ER, Craft S, Ginghina C, et al. CSF Aβ(42) and tau in Parkinson's disease with cognitive impairment. Mov Disord. 2010; 25:2682–2685.

11. Shi M, Bradner J, Hancock AM, Chung KA, Quinn JF, Peskind ER, et al. Cerebrospinal fluid biomarkers for Parkinson disease diagnosis and progression. Ann Neurol. 2011; 69:570–580.

12. Jellinger KA. Synuclein deposition and non-motor symptoms in Parkinson disease. J Neurol Sci. 2011; 310:107–111.

13. Hu Y, Yu SY, Zuo LJ, Cao CJ, Wang F, Chen ZJ, et al. Parkinson disease with REM sleep behavior disorder: features, α-synuclein, and inflammation. Neurology. 2015; 84:888–894.

14. Irwin DJ, Lee VM, Trojanowski JQ. Parkinson's disease dementia: convergence of α-synuclein, tau and amyloid-β pathologies. Nat Rev Neurosci. 2013; 14:626–636.

15. Hughes AJ, Daniel SE, Kilford L, Lees AJ. Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatry. 1992; 55:181–184.

16. Chung KF. Use of the Epworth Sleepiness Scale in Chinese patients with obstructive sleep apnea and normal hospital employees. J Psychosom Res. 2000; 49:367–372.

17. Starkstein SE. Apathy in Parkinson's disease: diagnostic and etiological dilemmas. Mov Disord. 2012; 27:174–178.

18. Friedman JH, Alves G, Hagell P, Marinus J, Marsh L, Martinez-Martin P, et al. Fatigue rating scales critique and recommendations by the Movement Disorders Society task force on rating scales for Parkinson's disease. Mov Disord. 2010; 25:805–822.

19. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989; 46:1121–1123.

20. Antonini A, Barone P, Marconi R, Morgante L, Zappulla S, Pontieri FE, et al. The progression of non-motor symptoms in Parkinson's disease and their contribution to motor disability and quality of life. J Neurol. 2012; 259:2621–2631.

21. Stocchi F, Abbruzzese G, Ceravolo R, Cortelli P, D'Amelio M, De Pandis MF, et al. Prevalence of fatigue in Parkinson disease and its clinical correlates. Neurology. 2014; 83:215–220.

22. Beiske AG, Loge JH, Hjermstad MJ, Svensson E. Fatigue in Parkinson's disease: prevalence and associated factors. Mov Disord. 2010; 25:2456–2460.

23. Berardelli A, Rothwell JC, Thompson PD, Hallett M. Pathophysiology of bradykinesia in Parkinson's disease. Brain. 2001; 124(Pt 11):2131–2146.

24. Berardelli A, Conte A, Fabbrini G, Bologna M, Latorre A, Rocchi L, et al. Pathophysiology of pain and fatigue in Parkinson's disease. Parkinsonism Relat Disord. 2012; 18:Suppl 1. S226–S228.

25. Chung M, Park YS, Kim JS, Kim YJ, Ma HI, Jang SJ, et al. Correlating Parkinson's disease motor symptoms with three-dimensional [18F]FP-CIT PET. Jpn J Radiol. 2015; 33:609–618.

26. Eggers C, Kahraman D, Fink GR, Schmidt M, Timmermann L. Akinetic-rigid and tremor-dominant Parkinson's disease patients show different patterns of FP-CIT single photon emission computed tomography. Mov Disord. 2011; 26:416–423.

27. Hubbuch M, Farmakis G, Schaefer A, Behnke S, Schneider S, Hellwig D, et al. FP-CIT SPECT does not predict the progression of motor symptoms in Parkinson's disease. Eur Neurol. 2011; 65:187–192.

28. Louis ED, Tang MX, Cote L, Alfaro B, Mejia H, Marder K. Progression of parkinsonian signs in Parkinson disease. Arch Neurol. 1999; 56:334–337.

29. Beudel M, Little S, Pogosyan A, Ashkan K, Foltynie T, Limousin P, et al. Tremor reduction by deep brain stimulation is associated with gamma power suppression in Parkinson's disease. Neuromodulation. 2015; 18:349–354.

30. Stochl J, Boomsma A, Ruzicka E, Brozova H, Blahus P. On the structure of motor symptoms of Parkinson's disease. Mov Disord. 2008; 23:1307–1312.

31. Grajić M, Stanković I, Radovanović S, Kostić V. Gait in drug naïve patients with de novo Parkinson's disease--altered but symmetric. Neurol Res. 2015; 37:712–716.

32. Havlikova E, Rosenberger J, Nagyova I, Middel B, Dubayova T, Gdovinova Z, et al. Clinical and psychosocial factors associated with fatigue in patients with Parkinson's disease. Parkinsonism Relat Disord. 2008; 14:187–192.

33. Herlofson K, Ongre SO, Enger LK, Tysnes OB, Larsen JP. Fatigue in early Parkinson's disease. Minor inconvenience or major distress. Eur J Neurol. 2012; 19:963–968.

34. Valko PO, Waldvogel D, Weller M, Bassetti CL, Held U, Baumann CR. Fatigue and excessive daytime sleepiness in idiopathic Parkinson's disease differently correlate with motor symptoms, depression and dopaminergic treatment. Eur J Neurol. 2010; 17:1428–1436.

35. Pavese N, Metta V, Bose SK, Chaudhuri KR, Brooks DJ. Fatigue in Parkinson's disease is linked to striatal and limbic serotonergic dysfunction. Brain. 2010; 133:3434–3443.

36. Chaudhuri A, Behan PO. Fatigue and basal ganglia. J Neurol Sci. 2000; 179(S 1-2):34–42.

37. Politis M, Niccolini F. Serotonin in Parkinson's disease. Behav Brain Res. 2015; 277:136–145.

38. Friedman JH, Abrantes A, Sweet LH. Fatigue in Parkinson's disease. Expert Opin Pharmacother. 2011; 12:1999–2007.

39. Hagell P, Brundin L. Towards an understanding of fatigue in Parkinson disease. J Neurol Neurosurg Psychiatry. 2009; 80:489–492.

40. Friedman JH, Brown RG, Comella C, Garber CE, Krupp LB, Lou JS, et al. Fatigue in Parkinson's disease: a review. Mov Disord. 2007; 22:297–308.

41. Braak H, Rüb U, Gai WP, Del Tredici K. Idiopathic Parkinson's disease: possible routes by which vulnerable neuronal types may be subject to neuroinvasion by an unknown pathogen. J Neural Transm. 2003; 110:517–536.

42. Kouti L, Noroozian M, Akhondzadeh S, Abdollahi M, Javadi MR, Faramarzi MA, et al. Nitric oxide and peroxynitrite serum levels in Parkinson's disease: correlation of oxidative stress and the severity of the disease. Eur Rev Med Pharmacol Sci. 2013; 17:964–970.

43. Lee HJ, Patel S, Lee SJ. Intravesicular localization and exocytosis of alpha-synuclein and its aggregates. J Neurosci. 2005; 25:6016–6024.

44. Tokuda T, Qureshi MM, Ardah MT, Varghese S, Shehab SA, Kasai T, et al. Detection of elevated levels of α-synuclein oligomers in CSF from patients with Parkinson disease. Neurology. 2010; 75:1766–1772.

45. Hernández-Romero MC, Delgado-Cortés MJ, Sarmiento M, de Pablos RM, Espinosa-Oliva AM, Argüelles S, et al. Peripheral inflammation increases the deleterious effect of CNS inflammation on the nigrostriatal dopaminergic system. Neurotoxicology. 2012; 33:347–360.

46. Brueggemann N, Odin P, Gruenewald A, Tadic V, Hagenah J, Seidel G, et al. Re: Alpha-synuclein gene duplication is present in sporadic Parkinson disease. Neurology. 2008; 71:1294.

47. Paleologou KE, Kragh CL, Mann DM, Salem SA, Al-Shami R, Allsop D, et al. Detection of elevated levels of soluble alpha-synuclein oligomers in post-mortem brain extracts from patients with dementia with Lewy bodies. Brain. 2009; 132(Pt 4):1093–1101.

48. Sharon R, Bar-Joseph I, Frosch MP, Walsh DM, Hamilton JA, Selkoe DJ. The formation of highly soluble oligomers of alpha-synuclein is regulated by fatty acids and enhanced in Parkinson's disease. Neuron. 2003; 37:583–595.

49. Park MJ, Cheon SM, Bae HR, Kim SH, Kim JW. Elevated levels of α-synuclein oligomer in the cerebrospinal fluid of drug-naïve patients with Parkinson's disease. J Clin Neurol. 2011; 7:215–222.

50. Hall S, Öhrfelt A, Constantinescu R, Andreasson U, Surova Y, Bostrom F, et al. Accuracy of a panel of 5 cerebrospinal fluid biomarkers in the differential diagnosis of patients with dementia and/or parkinsonian disorders. Arch Neurol. 2012; 69:1445–1452.

51. Hansson O, Hall S, Ohrfelt A, Zetterberg H, Blennow K, Minthon L, et al. Levels of cerebrospinal fluid α-synuclein oligomers are increased in Parkinson's disease with dementia and dementia with Lewy bodies compared to Alzheimer's disease. Alzheimers Res Ther. 2014; 6:25.

52. Hall S, Surova Y, Öhrfelt A, Zetterberg H, Lindqvist D, Hansson O. CSF biomarkers and clinical progression of Parkinson disease. Neurology. 2015; 84:57–63.

53. Alves G, Brønnick K, Aarsland D, Blennow K, Zetterberg H, Ballard C, et al. CSF amyloid-beta and tau proteins, and cognitive performance, in early and untreated Parkinson's disease: the Norwegian ParkWest study. J Neurol Neurosurg Psychiatry. 2010; 81:1080–1086.

54. Mollenhauer B, Trenkwalder C, von Ahsen N, Bibl M, Steinacker P, Brechlin P, et al. Beta-amlyoid 1-42 and tau-protein in cerebrospinal fluid of patients with Parkinson's disease dementia. Dement Geriatr Cogn Disord. 2006; 22:200–208.

55. Alves G, Lange J, Blennow K, Zetterberg H, Andreasson U, Førland MG, et al. CSF Aβ42 predicts early-onset dementia in Parkinson disease. Neurology. 2014; 82:1784–1790.

56. Xie A, Gao J, Xu L, Meng D. Shared mechanisms of neurodegeneration in Alzheimer's disease and Parkinson's disease. Biomed Res Int. 2014; 2014:648740.

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