Clinical features, plasma neurotransmitter levels and plasma neurohormone levels in sleep disorders among patients with early-stage Parkinson’s disease

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Neurotransmitters and neurosteroids are known to be involved in various neurophysiological processes, including sleep development. Objective: We aimed to assess the association between peripheral neurotransmitter and neurosteroid levels and various sleep disorders in early-stage PD. Methods: 59 patients with early-stage PD and 30 healthy controls were enrolled. Demographic and clinical data were collected and sleep conditions were comprehensively assessed with clinical questionnaires and polysomnography. Blood samples were obtained at 1:00 AM and 9:00 AM in all participants. The concentrations of plasma neurotransmitters and neurohormones were detected using high-performance liquid chromatography tandem mass spectrometry. Results: Sleep disorders were common non-motor symptoms (81.4%) and coexisted in approximately half of the patients. Dysautonomia was significantly associated with the presence of multiple sleep disorders. RBD was associated with dysautonomia and was negatively correlated with plasma melatonin concentration at 1:00 AM (r = −0.40, p = 0.002) in early-stage PD patients. The RLS group had higher PSQI score, and RLS was negatively associated with the levels of 5-hydroxytryptamine (r = −0.40, p = 0.002) at 1:00 AM and glutamine (r = −0.39, p = 0.002) at 9:00 AM. SDB was associated with cognitive impairment, higher body mass index, and lower plasma acetylcholine concentrations at 1:00 AM. Conclusion: Combined sleep disturbances were frequent in early-stage PD. Dysautonomia was closely related to various sleep disorders, including RBD, EDS, and insomnia. Changes in peripheral neurotransmitter and neurohormone levels may be involved in the development of sleep disorders. Parkinson’s disease Sleep disorders plasma neurotransmitter and neurohormone levels Figures Figure 1 Figure 2 Figure 3 Introduction Sleep disorders are one of the most common non-motor symptoms in Parkinson’s disease (PD) [1] , including rapid eye movement sleep behavior disorder (RBD), restless legs syndrome (RLS), excessive daytime sleepiness (EDS), insomnia, and sleep-disordered breathing (SDB) [2] . Sleep disorders are commonly present in the prodromal and early phases of PD [3-4] , and can exist alone or in various combinations. Sleep dysfunction in PD is multifactorial and encompasses medication side effects, nocturnal PD motor symptoms, an impaired sleep-wake cycle, and the presence of co-existing sleep and neuropsychiatric disorders, and is related to a broad range of neurological structures and diverse neurotransmitters [5] . The previous researches confirmed that the principal neuroendocrine system and the crucial neurotransmitter systems that mediate sleep, including melatonin, acetylcholine, norepinephrine, serotonin, dopamine, and gamma-aminobutyric acid, are disrupted in PD [6-9] . One previous study reported that the levels of dopamine and serotonin in the cerebrospinal fluid were significantly decreased in PD patients with RLS [10] . In addition, several studies support the involvement of peripheral neurotransmitters in PD-related sleep dysfunction with changes in blood neurotransmitters and neurohormones in patients [11-13] . The circulating levels of the aforementioned mediating substances may alternate with the circadian rhythm and play a role in the peripheral mechanisms of sleep disorders. However, few studies have systematically explored the associations between the diurnal and nocturnal levels of blood neurotransmitters and neurohormones, and the different types of sleep disorders (EDS, RBD, RLS, SDB and insomnia) in early-stage PD. In the current study, we aimed to investigate the association between plasma neurotransmitter and neurohormone levels and sleep disorders, and to determine the prevalence of sleep disturbances in patients with early-stage PD. Subjects and Methods Subjects We consecutively recruited 59 patients with early-stage PD from the Parkinson’s Disease and Movement Disorder Clinic, Tianjin Huanhu Hospital, between January 2021 and October 2022. The inclusion criteria were as follows: diagnosis of clinically established PD according to MDS Clinical Diagnostic Criteria for Parkinson’s Disease; Hoehn and Yahr (H-Y) stage ≤ 2.5; no or minimal cognitive disturbances (defined as a Mini-Mental State Examination (MMSE) score greater than 26/30). The exclusion criteria were as follows: diagnosis of secondary, hereditary or atypical parkinsonism according to the aforementioned diagnostic criteria. Age-matched and sex-matched healthy controls (n = 30) with no history of any neurological or sleep disorders (as assessed after interview and clinical examination by a neurologist) were enrolled from the patients’ spouses. Assessments of clinical symptoms All participants underwent examination by movement disorder specialists through face-to-face interviews and detailed questionnaires. Demographic information, including gender, onset age, disease duration, use of anti-Parkinson’s drugs, antidepressants and sedatives were recorded. Additionally, the levodopa equivalent daily dose (LEDD) was calculated using conversion factors and parameters reported elsewhere, by submitting daily doses of commonly used anti-Parkinson drugs (single or in combination) [14] . All PD patients completed the Chinese version of the MDS-UPDRS part I, MDS-UPDRS part II (activities of daily living, ADL), MDS-UPDRS part III (motor symptoms). Disease severity was rated by Hoehn and Yahr (H-Y) stage. Motor subtypes [15] were defined using the MDS-UPDRS parts II and III, including tremor dominant subtype (ratio ≥ 1.15), postural instability and gait disorders (PIGD) subtype (ratio ≤ 0.90) and indeterminate subtype (0.9 < ratio < 1.15). Total disease progression was calculated using the scores of MDS-UPDRS Parts I, II and III divided by disease duration, motor progression was calculated using the scores of MDS-UPDRS part III divided by disease duration, and ADL progression was calculated using the scores of MDS-UPDRS part II divided by disease duration. Non-motor symptoms were screened using the Non-Motor Symptoms Scale (NMSS) followed by a battery of scales, including the Montreal Cognitive Scale (MoCA, corrected education level) for cognitive impairment, Hamilton Depression Scale-24 items (HAMD-24) for depression, Hamilton Anxiety Scale (HAMA) for anxiety, the Scale of Autonomic Function in PD (SCOPA-AUT) for autonomic dysfunction, the Fatigue Severity Scale (FSS) for fatigue, the Pittsburgh Sleep Quality Index (PSQI) for general sleep, and the REM Sleep Behavior Disorder Questionnaire-Hong Kong (RBDQ-HK) for parasomnias. Quality of life was assessed using the 39-item PD quality questionnaire (PDQ-39). All motor and non-motor symptoms were examined in the OFF-drug condition. Sleep assessment All patients underwent night-time video-polysomnography at the Parkinson’s Disease and Movement Disorder Impatient Clinic. The recordings included eight (F1/A2, C3/A2, O1/A2, T3/A2, F2/A2, C4/A2, T4/A2, O2/A2) bipolar electroencephalogram (EEG) channels, two electrooculograms (EOG), surface electromyogram (EMG) of the chin and left and right tibialis anterior muscles, electro-cardiogram (ECG), airflow via nasal pressure and naso-oral thermistor, respiratory effort (via thoracic and abdominal plethysmography), transcutaneous oxyhemoglobin, body position, and tracheal sound (snoring detector), as well as synchronized infrared video and ambient sounds. Sleep neurologists scored sleep stages, arousal, RBD, periodic leg movements and respiratory events according to international criteria. Sleep-disordered breathing (SDB) was defined as an apnea-hypopnea index greater than 15/h. RBD, restless legs syndrome (RLS) and insomnia were diagnosed according to the criteria of the International Classification of Sleep Disorders, 3rd Edition [16] . Excessive daytime sleepiness (EDS) was defined as an ESS score of 10 or greater [17] . Detections of circadian levels of neurotransmitters and neurohormones in plasma On the same day, 3 ml venous blood specimens from all subjects (patients and controls) were collected at 1:00 AM and 9:00 AM, respectively, under fasting conditions, followed by centrifugation within 4 hours, and preserved at −80 °C until tested. The concentrations of neurotransmitters and neurohormones, including dopamine (DA), epinephrine (E), aspartate (Asp), 5-hydroxytryptamine (5-HT), glutamic acid (Glu), acetylcholine (Ach), glutamine (Gln), melatonin (MT), and gamma-aminobutyric acid (GABA) were detected using high-performance liquid chromatography tandem mass spectrometry (HPLC-MS). The multi reaction monitoring scanning mode was used for LC-MS/MS detection. The Waters Iclass-AB Sciex 6500 liquid-mass tandem mass spectrometry system was used as an analytical instrument, with the Waters BEH C18 (model: 1.7 um * 2.1 * 100 mm) chromatographic column. Mobile phase A was water + 0.1% formic acid, and mobile phase B was methanol + 0.1% formic acid. The flow rate was 0.35 mL/min, and the gradient settings were 0–2 min, 2% B, 2.5–15 min, 20%–80% B. Statistical analysis We used SPSS Statistics (version 25.0, SPSS Inc, Chicago, IL, USA) and R software (version 4.3.0) for statistical analysis. We evaluated differences in demography, clinical information, neurotransmitter and neurohormones levels between PD patients and controls using the Chi-square test for categorical variables, and Welch’s t test and the Mann-Whitney U test for continuous variables. Within PD participants, the Chi-square test or Fisher’s exact test were used for categorical variables, and one-way analysis of variance and the Mann-Whitney U test were used for numerical variables, to compare three groups defined by the number of sleep symptoms (0, 1, and ≥ 2). To determine which groups differed from each other, post hoc comparisons were made using the pairwise least significant difference test and Mann-Whitney-Wilcoxon test for numerical variables and the pairwise Fisher’s exact test for categorical variables, both followed by the Bonferroni correction. The same methods were used to compare levels of plasma neurotransmitters and neurohormones between PD patients (with and without specific sleep disorder, different numbers of sleep disorders) and controls. To select factors related to an increase in the number of sleep disturbances, we performed an ordinal logistic regression analysis that included disease course and scores of MDS UPDRS part II, NMSS, SCOPA-AUT, PDQ-39, and PSQI as covariates. To compare every specific type of sleep disorder in PD patients, we identified important covariates with borderline significance in the univariate analysis, which were then verified in the multivariate logistic model using automatic forward selection methods. Two-tailed p- values of < 0.05 were considered statistically significant. We used the UpSetR v1.4.0 package based on the full dataset to build the figure of presence of five sleep disturbances. R patchwork package, ggpubr package, ggsci package and tidyverse package were conducted to display changes of MT level in RBD and 5-HT in RLS. Using the R software ggpmisc package for Pearson’s correlation coefficient analysis, we evaluated the correlations between plasma neurotransmitter and neurohormones levels and the occurrence of each specific kind of sleep disorder. Results Demographic and clinical characteristics of participants Demographic information and clinical characteristics of 59 PD patients and 30 controls are presented in Table S1 . There were no significant differences in age and gender between the two groups. Of the 59 early-stage PD patients, the mean onset age and disease duration were 61.25±9.07 and 3.90±3.06 years, respectively. The mean H-Y stage was 2.5 (2.0, 2.5). Thirty-six patients (61.0%) received anti-Parkinson’s drugs. Six (10.2%) and 11 (18.6%) patients were taking antidepressants and benzodiazepines, respectively. The total LEDD was 418.54 ± 218.41 mg/24h. The mean scores of MDS-UPDRS part I, II and III were 12.97 ± 6.89, 14.37 ± 8.54, and 25.61 ± 12.80, respectively. Scores of non-motor symptoms were as follows: HAMA 15.05 ± 7.99, HAMD-24 11.73 ± 8.35, MoCA 22.81 ± 4.22, SCOPA-AUT 13.40 ± 7.60, NMSS 42.07 ± 26.21, and FSS 2.70 ± 2.52. Coexistence of sleep disorders in PD PD patients were categorized into three groups: no sleep disorder, one sleep disorder, and combined sleep disorders (more than two sleep disturbances), which accounted for 18.6%, 39.0%, and 42.4% of patients, respectively. Isolated or co-occurrence sleep disturbances in PD subjects are shown in Fig. 1 . Isolated RBD was the most common, followed by isolated RLS and isolated SDB. The combinations of sleep disorders were relatively scattered—each sleep disorder could be associated with any other, and there was no preference in the combinations. The demographic and clinical characteristics of the three groups are shown in Table 1 . PD patients with multiple sleep disorders had higher scores for the MDS-UPDRS part II, NMSS, PSQI, and PDQ-39 compared with those with no sleep disorder. SCOPA-AUT scores were higher in the group with multiple sleep disorders compared with those in the other two groups. Compared with those in patients with no sleep disorder, NMSS scores were higher in patients with one sleep disorder. However, gender, onset age, disease duration, MDS-UPDRS part I and III scores, MoCA scores, HAMA scores, HAMD-24 scores, FSS scores, and disease progression were similar in the three groups. The ordinal logistic regression analysis using a forward selection showed that the SCOPA-AUT score (OR = 1.16, 95%CI = 1.02–1.31, p =0.025) was a contributing factor for multiple sleep disturbances (Table 2) . Factors associated with PD-RBD Patients with PSG-confirmed RBD (24, 40.7%) had higher SCOPA-AUT scores than those without RBD. Binary logistic regression analysis revealed that RBD in PD was significantly associated with higher SCOPA-AUT scores (OR = 1.08, 95% CI = 1.00–1.17, p = 0.040), while it was not associated with motor symptoms, disease progression, depression, anxiety, cognition, fatigue, or other sleep disorders (Table S2) . Factors associated with PD-RLS Table S3 shows the results of univariate and multivariate regression analyses for PD patients with and without RLS.RLS was significantly associated with disease duration, LEDD, scores of mNMSS, PSQI, FSS, and motor progression in the univariate model. These covariates were further included in the multivariate analysis, then higher PSQI scores (OR = 1.92, 95% CI = 1.01–1.64, p = 0.039) were significantly correlated with RLS, indicating that higher PSQI scores may be independent risk factor for RLS. No differences were found in red blood cell count and the levels of hemoglobin, serum ferritin, folic acid and vitamin B12 between patients with and without RLS ( Table S7 ). Factors associated with PD-SDB Higher body mass index (OR = 1.21, 95% CI = 1.01–1.45, p = 0.044) and lower MoCA scores (OR = 0.84, 95% CI = 0.72–0.98, p = 0.029) were significantly correlated with SDB both in univariate and multivariate regression analyses (Table S4) . No other differences in clinical factors were observed between PD patients with and without SDB. Factors associated with PD-insomnia Table S5 shows clinical characteristics of PD patients with and without insomnia. In univariate regression model, non-motor scores including MDS-UPDRS part I, mNMSS, HAMA, HAMD-24, MoCA, SCOPA-AUT and PSQI, taking antidepressants, scores of PQD-39 and MDS-UPDRS part II were significantly correlated with insomnia. In multivariate logistic regression analyses, higher scores of MDS-UPDRS part I (OR = 2.05, 95% CI = 1.04–4.05, p = 0.038), HAMD-24 (OR = 1.88, 95% CI = 1.10–3.20, p = 0.021) and SCOPA-AUT (OR = 1.43, 95% CI = 1.07–1.92, p = 0.016) were significantly correlated with insomnia. Factors associated with PD-EDS PD patients with EDS (10/59, 16.9%) had higher scores for MDS-UPDRS part I, part II, SCOPA-AUT and PDQ-39 in the univariate regression analysis. When these covariates were included in the multivariate analyses, the results revealed that only autonomic dysfunction increased the risk of EDS, by 1.17 times (95% CI = 1.05–1.31, p = 0.006) ( Table S6 ). Comparison of plasma neurotransmitter and neurohormone concentrations in PD patients and controls In healthy controls, the plasma dopamine level at 1:00 am was significantly lower than that at 9:00 am, and the melatonin level at 1:00 am was significantly higher than that at 9:00 am, consistent with the findings of previous studies [18-19] . Patients with PD had decreased plasma concentrations of Asp, Glu, GABA, MT and epinephrine at 1:00 am and a decreased plasma concentration of Asp, Glu, DA and epinephrine at 9:00 am. The peripheral level of Gln was increased at 9:00 am in the PD group ( Table S8 ). Peripheral melatonin and DA levels in PD-RBD The plasma concentration of melatonin at 1:00 am was significantly decreased in PD patients with RBD compared with the findings in controls and PD patients without RBD ( Figure 2 ), while the levels of DA were elevated in PD patients with RBD compared with those in patients without RBD at this time point, although no difference was identified between the PD-RBD and control groups ( Table S9) . The plasma melatonin level at 1:00 am was negatively correlated with RBD (r = −0.40, p = 0.0018) and the DA level was positively correlated with RBD (r = 0.29, p = 0.025) ( Figure 3 ). Peripheral 5-HT and glutamine levels in PD-RLS At 1:00 am, PD patients with RLS had a significantly lower level of 5-HT compared with patients without RLS ( Figure S ). Glutamine level decreased significantly in the PD-RLS group at 9:00 am ( Table S10 ). PD-RLS was negatively correlated with levels of 5-hydroxytryptamine at 1:00 am (r = −0.40, p = 0.0016) and glutamine at 9:00 am (r = −0.39, p = 0.0022) ( Figure 3 ). Peripheral acetylcholine levels in PD-SDB PD patients with SDB had a lower plasma acetylcholine concentration than patients without SDB at 1:00 am ( Table S11 ). There was also a negative correlation between SDB and acetylcholine level at 1:00 am in PD patients (r = −0.39, p = 0.0025). PD patients with EDS or insomnia did not exhibit a significant change in peripheral neurotransmitter or neurohormone levels ( Table S9, S11 ). Discussion In the current study, we confirmed that the incidence of sleep disturbances was high, and that multiple sleep disorders often coexisted in early-stage PD. RBD was the most common sleep disorder, followed by RLS, OSA, insomnia, and EDS. The incidence of insomnia (18.6%) was lower than that reported in a previous study [4] . Approximately 80% of PD patients had at least one type of sleep disturbance, and approximately 50% of patients had two or more sleep disturbances, similar to previously reported findings in the ICEBERG cohort [4] . The percentage of patients with combined sleep disorders in the PPMI cohort [20] was 11.5%, on the basis of assessments using questionnaires and a limited range of sleep disorders (RBD, EDS and PD-related sleep symptoms). The number of combined sleep disorders increased with the severity of dysautonomia, possibly related to the presence of RBD, EDS, and insomnia, and PD patients with RBD, EDS, and insomnia had higher scores for dysautonomia compared with those without sleep disorders. The current findings revealed that RBD diagnosed by PSG accounted for the highest proportion (40.7%) of early-stage PD patients with sleep disorders, and was associated with dysautonomia. Evidence indicates that autonomic dysfunction and RBD share common neuropathology [21] . Patients presenting with pure autonomic failure (PAF) and isolated RBD (iRBD) are reported to be at high risk of converting to α-synucleinopathy [22-23] . Compared with healthy controls, iRBD subjects exhibit more prominent autonomic dysfunction [24] , suggesting a correlation between PAF and iRBD. Substantial evidence suggests that PD patients with RBD may constitute a distinct phenotype compared with PD patients without RBD, including autonomic dysfunction [4,25-26] . RBD is considered to constitute a key marker of diffuse–malignant PD subtypes with cognitive loss, severe autonomic dysfunction, fast motor progression and loss of independent living and mortality. Our study revealed a lower level of plasma melatonin in PD patients with RBD compared with the findings in patients without RBD and healthy controls at 1:00 AM. In addition, plasma melatonin level at this time was negatively correlated with RBD, suggesting that the decrease of peripheral melatonin level in early morning might be involved in RBD development. Previous studies using animal experiments reported that α‑synuclein reduces acetylserotonin O-methyltransferase-mediated melatonin biosynthesis [27-28] . Two previous studies reported that patients with PD exhibited reduced circulating melatonin levels [6,11] . Furthermore, some studies reported that melatonin treatment can alleviate the symptoms of RBD in PD patients [29] . The current results were consistent with previous findings, and supported the role of melatonin in RBD occurrence. We also found that plasma dopamine levels were higher in PD patients with RBD at 1:00 AM compared with the levels in those without RBD, possibly resulting from a higher L-dopa requirement because of worsening motor symptoms. In the current study, RLS was the second most common sleep disorder in early-stage PD, with a frequency of 35.6%, which was higher than that reported in previous studies (4.6%–16.3%) [30-31] . In the current study population, PD patients with RLS exhibited poorer sleep quality than those without RLS, which was similar to findings reported in previous investigations [10,32-33] . RLS can have a negative impact on sleep quality by decreasing sleep time and efficiency [4,34] . Our study indicated that PD patients with RLS exhibited abnormal neurotransmitter levels, including reduced plasma levels of 5-hydroxytryptamine (5-HT) at 1:00 AM and reduced plasma levels of glutamine at 9:00 AM, which were negatively correlated with RLS. Piao et al. [10] reported a similar 5-HT change in cerebrospinal fluid. Another study reported that sleep dysfunction in PD is associated with reduced serotonergic function in the midbrain raphe, basal ganglia and hypothalamus using [11 C ] DASB positron emission tomography [35] . A possible mechanism underlying this phenomenon is that 5-HT may interact with dopamine-pathway activity or disturb iron metabolism [36-37] . One previous study confirmed that glutaminergic neurotransmitters in the thalamus are involved in the development of RLS by increasing the arousal [38] , although it is unclear how glutaminergic neurotransmitters are involved in the development of PD-RLS. SDB was previously reported to be more prevalent in early-stage PD patients than in the general population [39] . In the current study, SDB was associated with higher body mass index and cognitive dysfunction in PD, these outcomes are in accord with several previous reports [40-42] . Sleep-related hypoxemia disorder can affect cognitive function and result in a worse prognosis for PD, and longitudinal studies have reported that continuous positive airway pressure (CPAP) can improve global cognitive function over a 12-month period in PD patients with OSA [43-44] . In PD patients with SDB, the plasma levels of acetylcholine at 1:00 AM were found to be significantly decreased compared with the findings in patients without SDB and controls. Hilker et al. [45] observed that PD patients with dementia exhibited significantly reduced neocortical acetylcholinesterase (AChE) activity compared with PD subjects without dementia. Therefore, the current findings indicate that cholinergic denervation may account for cognitive impairment in PD-SDB. In the current study cohort, approximately one-fifth of PD subjects had EDS. Patients with EDS experienced severe autonomic dysfunction, which was consistent with the findings of previous studies [4 6 -4 8 ] . Aleksandar et al. observed that PD participants with EDS had a significantly lower amplitude of melatonin rhythm and 24-hour melatonin area under the curve (AUC) compared with PD participants without EDS [ 11 ] . In the current study, the absence of a change in the levels of melatonin among PD patients with or without EDS may have occurred because the patients were enrolled in the early stage when circadian rhythm disruption is less severe compared with that in the advanced stage. The frequency of insomnia in this study was lower than that reported in a previous study (21%–41%) [4] , possibly because the patients enrolled in the current study were in the early stage of PD, whereas insomnia is more prevalent in advanced PD [ 39 ] . Although the current findings suggest that insomnia may be related to depression, dysautonomia, and poorer ADL in patients with early-stage PD [ 20,49 ] , we observed no significant changes in peripheral neurotransmitters and neurohormones levels in the PD-insomnia subgroup, indicating the heterogenous nature of insomnia in PD [ 50 ] . Several limitations of our study should be noted. First, the sample size of 89 was modest. However, this sample still allowed a comprehensive analysis of sleep disturbances in early-stage PD, and all participants underwent comprehensive motor, non-motor, and sleep assessments. Second, patients were medicated rather than drug-naïve which could potentially have an impact on sleep disturbances. However, there were no significant differences in daily doses of levodopa or dopamine receptor agonists among the sleep disorder subgroups. Finally, blood samples were only collected at two time points, although the sampling was conducted at two representative times, morning and midnight. Circadian peripheral changes of these bioactive substances should be taken into consideration in future studies. Conclusion Combined sleep disturbances were found to be common in early-stage PD patients. Dysautonomia was closely related to the presence of combined and specific sleep disorders, including RBD, EDS and insomnia. Changes in peripheral neurotransmitters and neurohormones may be involved in the development of sleep disturbances. Therefore, a better understanding of the role of these endogenous compounds could be helpful for optimizing the treatments for PD-related sleep disorders in the future. Declarations Funding:This study was funded by Tianjin Key Medical Discipline (Specialty) Construction Project (No. TJYXZDXK-052B). Ethics statement: This study was conducted in accordance with the Declaration of Helsinki. 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Tables Table 1 Demographical and clinical characteristics by co-occurrence of sleep-related disorders in early-stage PD patients Group No sleep disorder a N=11 (19%) One sleep disorder b N=23 (39%) at least two sleep diorders c N=25 (42%) F/H/X 2 P Demography Onset age (years) 61.59±10.74 58.83±8.81 63.32±8.34 1.51 0.23 Disease course (years) 2.06±1.52 3.96±3.20 4.67±3.17 2.95 0.06 Male sex, N (%) 4 (36.4) 13 (56.5) 14 (56.0) 1.42 0.49 Global assessment of disease H-Y stage(on-OFF condition) 2.00 (1.00, 2.50) 2.50 (2.00, 2.50) 2.50 (2.00, 2.50) 3.99 0.14 MDS-UPDRS I (score) 10.82±5.33 11.65±6.95 15.12±7.07 2.27 0.11 MDS-UPDRS II (score) 9.45±2.70 c 13.65±8.44 17.20±9.39 a 3.56 0.04 MDS-UPDRS III (score) 19.36±10.04 28.17±12.43 26.00±13.70 1.84 0.17 Non motor symptoms NMSS (score) 20.45±8.56 b, c 40.04±20.83 a 53.44±29.65 a 7.56 0.001 PSQI (score) 5.09±2.95 c 7.17±4.14 c 10.20±5.12 a,b 5.31 0.008 MoCA (score) 24.91±3.59 23.14±4.66 21.48±3.78 2.81 0.07 HAMA (score) 11.18±6.01 14.26±8.34 17.48±7.86 2.71 0.08 HAMD-24 (score) 8.27±7.04 11.13±8.73 13.80±8.23 1.82 0.17 SCOPA-AUT (score) 7.27±4.52 c 11.34±6.39 c 17.58±6.92 a, b 11.56 ＜ 0.001 FSS (score) 1.61±1.19 2.70±3.40 3.17±1.85 1.49 0.23 Disease progression and life quality Total disease progression 33.77±28.06 21.43±16.57 20.15±19.53 1.86 0.17 Motor progression 15.52±15.26 10.95±7.90 9.26±9.50 1.43 0.25 ADL progression 8.22±6.24 4.93±3.75 5.09±3.35 2.68 0.08 PDQ-39 (score) 19.45±13.41 c 30.17±24.57 43.44±27.79 a 4.07 0.02 Treatment LEDD (mg/day) 170.45±153.22 214.04±244.26 314.04±314.04 1.44 0.25 Dopamine agonist, N (%) 3 (27.3) 5 (21.7) 9 (36.0) 1.21 0.55 Data are shown as mean±SD, median (quartile range) or N (%). Statistical significance was set at p < 0.05. Significant differences are shown in bold. a For a pairwise difference with no sleep disturbance; b For a pairwise difference with one sleep disorder; c For a pairwise difference with at least two sleep disorders. Abbreviations: MDS UPDRS:Movement Disorder Society-Unified Parkinson’s Disease Rating Scale; NMSS:non-motor symptom evaluation scale; PSQI:Pittsburgh Sleep Quality Index; MoCA: Montreal Cognitive Assessment; HAMA: Hamilton Anxiety Scale; HAMD-24:Hamilton Depression Scale -24; SCOPA-AUT: scale of outcomes in PD for autonomic symptoms; FSS: Fatigue Severity Scale; LEDD: L-dopa equivalent daiyl dose; ADL:activities of daily living; PDQ-39:39-item Parkinsons Disease Questionnaire. Table 2 Logistic regression analyses for PD patients with only one, multiple types and without sleep disorders Varibles OR a (95%CI) P -value OR b (95%CI) P- value Disease course 1.21 (1.01-1.44) 0.039 MDS UPDRS II 1.08 (1.02-1.16) 0.017 NMSS 1.04 (1.02-1.07) 0.001 SCOPA-AUT 1.20 (1.09-1.38) ＜0.001 1.16 (1.02-1.31) 0.025 PDQ-39 1.03 (1.01-1.05) 0.009 PSQI 1.18 (1.05-1.32) 0.005 a Univariate ordinal logistic regression; b Multivariate ordinal logistic regression. Abbreviations: MDS UPDRS II:Movement Disorder Society-Unified Parkinson’s Disease Rating Scale part II; NMSS:non-motor symptom evaluation scale; SCOPA-AUT: scale of outcomes in PD for autonomic symptoms; PDQ-39:39-item Parkinsons Disease Questionnaire; PSQI:Pittsburgh Sleep Quality Index. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.docx Supplementary information This study included some sipplementary information. Cite Share Download PDF Status: Published Journal Publication published 18 Mar, 2025 Read the published version in Cell Communication and Signaling → Version 1 posted Editorial decision: Revision requested 07 Feb, 2025 Reviews received at journal 26 Aug, 2024 Reviewers agreed at journal 09 Aug, 2024 Reviewers agreed at journal 02 Aug, 2024 Reviewers invited by journal 02 Aug, 2024 Editor assigned by journal 29 Jul, 2024 Submission checks completed at journal 29 Jul, 2024 First submitted to journal 27 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4813635","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":343038310,"identity":"e2c58442-b8f9-4bb8-9e52-aa33f58ccf3b","order_by":0,"name":"Cui-Hong Ma","email":"","orcid":"","institution":"Tianjin Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cui-Hong","middleName":"","lastName":"Ma","suffix":""},{"id":343038311,"identity":"3b8c4e4c-820e-477c-adff-90c5ce897580","order_by":1,"name":"Ning Ren","email":"","orcid":"","institution":"Clinical College of Neurology, Neurosurgery and Neurorehabilitation","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Ren","suffix":""},{"id":343038312,"identity":"fdec8888-9a9a-4706-96f8-ec86f0ab0dc7","order_by":2,"name":"Jing Xu","email":"","orcid":"","institution":"Chengde Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Xu","suffix":""},{"id":343038313,"identity":"8092c8bc-2630-405f-99fa-358c4e674ec1","order_by":3,"name":"Lei Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYDACCQaGAwwFQJK9sfHhB+K1GABJnsPNxhLEamFgMAAx0tsEeIjRwT+79+HBHwYWeeaSD9uA+u3kdBsIWXLnuMFhHgOJYsvZiW0PChiSjc0OENBiIJHGcBhIJm64ndgO9NKBxG3EaAE6DKjl5sE2CR5itRzgAWm5wUikFokbQIeBtZxJBAayARF+4Z+RxvzxR0Vd4objxx8+/FBhJ0dQC7o7SVM+CkbBKBgFowAHAAB8zEFPW28T2wAAAABJRU5ErkJggg==","orcid":"","institution":"Clinical College of Neurology, Neurosurgery and Neurorehabilitation","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-07-27 14:56:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4813635/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4813635/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12964-025-02153-8","type":"published","date":"2025-03-18T15:57:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63809043,"identity":"840aea57-a5c8-4ce5-8af6-615c0209e1cb","added_by":"auto","created_at":"2024-09-02 13:50:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":141518,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of sleep disorders in PD patients.\u003c/strong\u003e Each horizontal bar represents the total number of patients with a specific sleep disorder;\u003c/p\u003e\n\u003cp\u003eEach vertical bar represents the number of patients related to the combined disorders indicated by the connected dots below.\u003c/p\u003e\n\u003cp\u003eAbbreviations:RBD:REM behavior disorder; RLS: Restless legs syndrome; SDB: Sleep-disordered breathing; EDS:Excessive daytime sleepiness.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4813635/v1/7141862c7aaa452f24d803a4.png"},{"id":63809048,"identity":"cba80a3a-8240-4635-8ac8-365ab6e80ae0","added_by":"auto","created_at":"2024-09-02 13:50:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":189425,"visible":true,"origin":"","legend":"\u003cp\u003eComparisons of plasma melatonin concentration between groups.\u003c/p\u003e\n\u003cp\u003eDifferent colors representes different group; A two-point line indicates a comparison of \u003cem\u003ep\u003c/em\u003e-values between groups.\u003c/p\u003e\n\u003cp\u003eAbbreviations: MT:melatonine; CG:control group; PD-RBD: PD patients with RBD; PD-NRBD: PD patients without RBD; 1:1:00 \u0026nbsp;AM; 9:9:00 AM.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4813635/v1/9481eec7b0c7fd3f1178f468.png"},{"id":63809044,"identity":"d69e2cd3-8b34-487d-942c-371dca33758c","added_by":"auto","created_at":"2024-09-02 13:50:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":230320,"visible":true,"origin":"","legend":"\u003cp\u003ePoint-biserial correlation between the levels of plasma neurotransmitters and neurohormones and specific sleep disorders in PD patients.\u003c/p\u003e\n\u003cp\u003eEach scatter point is the corresponding value, the line representes the regression line, and the shaded part is the confidence interval.\u003c/p\u003e\n\u003cp\u003eAbbreviations: 5-HT:5-hydroxytryptamine; Ach:acetylcholine; MT:melatonine; DA:dopammine; Gln:glutamine.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4813635/v1/38f1967640289beb28425463.png"},{"id":79120760,"identity":"233f9f42-c77c-4cf6-97c4-954925172e82","added_by":"auto","created_at":"2025-03-24 16:11:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1521388,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4813635/v1/b1c2c297-3e56-4e26-b7a3-013378f7ee54.pdf"},{"id":63809046,"identity":"9405f135-0fd4-43c0-b646-bc2f8e47f94c","added_by":"auto","created_at":"2024-09-02 13:50:19","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":263965,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included some sipplementary information.\u003c/p\u003e","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-4813635/v1/b42cb43bc2543ba0b3c589be.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical features, plasma neurotransmitter levels and plasma neurohormone levels in sleep disorders among patients with early-stage Parkinson’s disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSleep disorders are one of the most common non-motor symptoms in Parkinson\u0026rsquo;s disease (PD)\u003cstrong\u003e\u003csup\u003e[1]\u003c/sup\u003e\u003c/strong\u003e,\u003cstrong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003eincluding rapid eye movement sleep behavior disorder (RBD), restless legs syndrome (RLS), excessive daytime sleepiness (EDS), insomnia, and sleep-disordered breathing (SDB)\u003cstrong\u003e\u003csup\u003e[2]\u003c/sup\u003e\u003c/strong\u003e. Sleep disorders are commonly present in the prodromal and early phases of PD\u003cstrong\u003e\u003csup\u003e[3-4]\u003c/sup\u003e\u003c/strong\u003e, and can exist alone or in\u0026nbsp;various\u0026nbsp;combinations. Sleep dysfunction in PD is multifactorial and encompasses medication side effects, nocturnal PD motor symptoms, an impaired sleep-wake cycle, and the presence of co-existing sleep and neuropsychiatric disorders, and is related to a broad range of neurological structures and diverse neurotransmitters\u003cstrong\u003e\u003csup\u003e[5]\u003c/sup\u003e\u003c/strong\u003e. The previous researches confirmed that the principal neuroendocrine system and the crucial neurotransmitter systems that mediate sleep, including melatonin, acetylcholine, norepinephrine, serotonin, dopamine, and gamma-aminobutyric acid, are disrupted in PD\u003cstrong\u003e\u003csup\u003e[6-9]\u003c/sup\u003e\u003c/strong\u003e. One previous study reported that the levels of dopamine and serotonin in the cerebrospinal fluid were significantly decreased in PD patients with RLS\u003cstrong\u003e\u003csup\u003e[10]\u003c/sup\u003e\u003c/strong\u003e. In addition, several studies support the involvement of peripheral neurotransmitters in PD-related sleep dysfunction with changes in blood neurotransmitters and neurohormones in patients\u003cstrong\u003e\u003csup\u003e[11-13]\u003c/sup\u003e\u003c/strong\u003e. The circulating levels of the aforementioned mediating substances may alternate with the circadian rhythm and play a role in the peripheral mechanisms of sleep disorders. However, few studies have systematically explored the associations between the diurnal and nocturnal levels of blood neurotransmitters and neurohormones, and the different types of sleep disorders (EDS, RBD, RLS, SDB and insomnia) in early-stage PD.\u003c/p\u003e\n\u003cp\u003eIn the current study, we aimed to investigate the association between plasma neurotransmitter and neurohormone levels and sleep disorders, and to determine the prevalence of sleep disturbances in patients with early-stage PD.\u003c/p\u003e"},{"header":"Subjects and Methods","content":"\u003cp\u003e\u003cstrong\u003eSubjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe consecutively recruited 59 patients with early-stage PD from the Parkinson’s Disease and Movement Disorder Clinic, Tianjin Huanhu Hospital, between January 2021 and October 2022. The inclusion criteria were as follows: diagnosis of clinically established PD according to MDS Clinical Diagnostic Criteria for Parkinson’s Disease; Hoehn and Yahr (H-Y) stage ≤ 2.5; no or minimal cognitive disturbances (defined as a Mini-Mental State Examination (MMSE) score greater than 26/30). The exclusion criteria were as follows: diagnosis of secondary, hereditary or atypical parkinsonism according to the aforementioned diagnostic criteria. Age-matched and sex-matched healthy controls (n = 30) with no history of any neurological or sleep disorders (as assessed after interview and clinical examination by a neurologist) were enrolled from the patients’ spouses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessments of clinical symptoms\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants underwent examination by movement disorder specialists through face-to-face interviews and detailed questionnaires. Demographic information, including gender, onset age, disease duration, use of anti-Parkinson’s drugs, antidepressants and sedatives were recorded. Additionally, the levodopa equivalent daily dose (LEDD) was calculated using conversion factors and parameters reported elsewhere, by submitting daily doses of commonly used anti-Parkinson drugs (single or in combination)\u003cstrong\u003e\u003csup\u003e[14]\u003c/sup\u003e\u003c/strong\u003e. All PD patients completed the Chinese version of the MDS-UPDRS part I, MDS-UPDRS part II (activities of daily living, ADL), MDS-UPDRS part III (motor symptoms). Disease severity was rated by Hoehn and Yahr (H-Y) stage. Motor subtypes\u003cstrong\u003e\u003csup\u003e[15]\u003c/sup\u003e\u003c/strong\u003e were defined using the MDS-UPDRS parts II and III, including tremor dominant subtype (ratio\u0026nbsp;≥\u0026nbsp;1.15), postural instability and gait disorders (PIGD) subtype (ratio\u0026nbsp;≤\u0026nbsp;0.90) and indeterminate subtype (0.9 \u0026lt; ratio \u0026lt; 1.15). Total disease progression was calculated using the scores of MDS-UPDRS Parts I, II and III divided by disease duration, motor progression was calculated using the scores of MDS-UPDRS part III divided by disease duration, and ADL progression was calculated using the scores of MDS-UPDRS part II divided by disease duration. Non-motor symptoms were screened using the Non-Motor Symptoms Scale (NMSS) followed by a battery of scales, including the Montreal Cognitive Scale (MoCA, corrected education level) for cognitive impairment, Hamilton Depression Scale-24 items (HAMD-24) for depression, Hamilton Anxiety Scale (HAMA) for anxiety, the Scale of Autonomic Function in PD (SCOPA-AUT) for autonomic dysfunction, the Fatigue Severity Scale (FSS) for fatigue, the Pittsburgh Sleep Quality Index (PSQI) for general sleep, and the REM Sleep Behavior Disorder Questionnaire-Hong Kong (RBDQ-HK) for parasomnias. Quality of life was assessed using the 39-item PD quality questionnaire (PDQ-39). All motor and non-motor symptoms were examined in the OFF-drug condition.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSleep assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients underwent night-time video-polysomnography at the Parkinson’s Disease and Movement Disorder Impatient Clinic. The recordings included eight (F1/A2, C3/A2, O1/A2, T3/A2, F2/A2, C4/A2, T4/A2, O2/A2) bipolar electroencephalogram (EEG) channels, two electrooculograms (EOG), surface electromyogram (EMG) of the chin and left and right tibialis anterior muscles, electro-cardiogram (ECG), airflow via nasal pressure and naso-oral thermistor, respiratory effort (via thoracic and abdominal plethysmography), transcutaneous oxyhemoglobin, body position, and tracheal sound (snoring detector), as well as synchronized infrared video and ambient sounds. Sleep neurologists scored sleep stages, arousal, RBD, periodic leg movements and respiratory events according to international criteria.\u0026nbsp;Sleep-disordered breathing (SDB) was defined as an apnea-hypopnea index greater than 15/h. RBD, restless legs syndrome (RLS) and insomnia were diagnosed according to the criteria of the International Classification of Sleep Disorders, 3rd Edition\u003cstrong\u003e\u003csup\u003e\u0026nbsp;[16]\u003c/sup\u003e\u003c/strong\u003e. Excessive daytime sleepiness (EDS) was defined as an ESS score of 10 or greater\u003cstrong\u003e\u003csup\u003e\u0026nbsp;[17]\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetections of circadian levels of neurotransmitters and neurohormones in plasma\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn the same day, 3 ml venous blood specimens from all subjects (patients and controls) were collected at 1:00 AM and 9:00 AM, respectively, under fasting conditions, followed by centrifugation within 4 hours, and preserved at −80 °C until tested.\u0026nbsp;The concentrations of neurotransmitters and\u0026nbsp;neurohormones, including\u0026nbsp;dopamine (DA), epinephrine (E), aspartate (Asp), 5-hydroxytryptamine (5-HT), glutamic acid (Glu), acetylcholine (Ach), glutamine (Gln), melatonin (MT), and gamma-aminobutyric acid (GABA)\u0026nbsp;were detected using\u0026nbsp;high-performance liquid chromatography tandem mass spectrometry (HPLC-MS). The multi reaction monitoring scanning mode was used for LC-MS/MS detection. The Waters Iclass-AB Sciex 6500 liquid-mass tandem mass spectrometry system was used as an analytical instrument, with the Waters BEH C18 (model: 1.7 um * 2.1 * 100 mm) chromatographic column. Mobile phase A was water + 0.1% formic acid, and mobile phase B was methanol + 0.1% formic acid. The flow rate was 0.35 mL/min, and the gradient settings were 0–2 min, 2% B, 2.5–15 min, 20%–80% B.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used SPSS Statistics (version 25.0, SPSS Inc, Chicago, IL, USA) and R software (version 4.3.0) for statistical analysis. We evaluated differences in demography, clinical information,\u0026nbsp;neurotransmitter\u0026nbsp;and neurohormones levels between PD patients and controls using the Chi-square test for categorical variables, and Welch’s t test and the Mann-Whitney U test for continuous variables. Within PD participants, the Chi-square test or Fisher’s exact test were used for categorical variables, and one-way analysis of variance and the Mann-Whitney U test were used for numerical variables, to compare three groups defined by the number of sleep symptoms (0, 1, and\u0026nbsp;≥\u0026nbsp;2). To determine which groups differed from each other, post hoc comparisons were made using the pairwise least significant difference test and Mann-Whitney-Wilcoxon test for numerical variables and the pairwise Fisher’s exact test for categorical variables, both followed by the Bonferroni correction. The same methods were used to compare levels of plasma neurotransmitters and neurohormones between PD patients (with and without specific sleep disorder, different numbers of sleep disorders) and controls. To select factors related to an increase in the number of sleep disturbances, we performed an ordinal logistic regression analysis that included disease course and scores of MDS UPDRS part II, NMSS, SCOPA-AUT, PDQ-39, and PSQI as covariates. To compare every specific type of sleep disorder in PD patients, we identified important covariates with borderline significance in the univariate analysis, which were then verified in the multivariate logistic model using automatic forward selection methods. Two-tailed \u003cem\u003ep-\u003c/em\u003evalues of \u0026lt; 0.05 were considered statistically significant. We used the UpSetR v1.4.0 package based on the full dataset to build the figure of presence of five sleep disturbances. R patchwork package, ggpubr package, ggsci package and tidyverse package were conducted to display changes of MT level in RBD and 5-HT in RLS. Using the R software ggpmisc package for Pearson’s correlation coefficient analysis, we evaluated the correlations between plasma neurotransmitter and neurohormones levels and the occurrence of each specific kind of sleep disorder.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographic and clinical characteristics of participants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic information and clinical characteristics of 59 PD patients and 30 controls are presented in \u003cstrong\u003eTable S1\u003c/strong\u003e. There were no significant differences in age and gender between the two groups. Of the 59 early-stage PD patients, the mean onset age and disease duration were 61.25±9.07 and 3.90±3.06 years, respectively. The mean H-Y stage was 2.5 (2.0, 2.5). Thirty-six patients (61.0%) received\u0026nbsp;anti-Parkinson’s drugs. Six (10.2%) and 11 (18.6%) patients were taking antidepressants and benzodiazepines, respectively. The total LEDD was 418.54 ± 218.41 mg/24h. The mean scores of MDS-UPDRS part I, II and III were 12.97 ± 6.89, 14.37 ± 8.54, and 25.61 ± 12.80, respectively. Scores of non-motor symptoms were as follows: HAMA 15.05 ± 7.99, HAMD-24 11.73 ± 8.35, MoCA 22.81 ± 4.22, SCOPA-AUT 13.40 ± 7.60, NMSS 42.07 ± 26.21, and FSS 2.70 ± 2.52.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCoexistence of sleep disorders in PD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePD patients were categorized into three groups: no sleep disorder, one sleep disorder, and combined sleep disorders (more than two sleep disturbances), which accounted for 18.6%, 39.0%, and 42.4% of patients, respectively. Isolated or co-occurrence sleep disturbances in PD subjects are shown in \u003cstrong\u003eFig. 1\u003c/strong\u003e. Isolated RBD was the most common, followed by isolated RLS and isolated SDB. The combinations of sleep disorders were relatively scattered—each sleep disorder could be associated with any other, and there was no preference in the combinations. The demographic and clinical characteristics of the three groups are shown in \u003cstrong\u003eTable 1\u003c/strong\u003e. PD patients with multiple sleep disorders had higher scores for the MDS-UPDRS part II, NMSS, PSQI, and PDQ-39 compared with those with no sleep disorder. SCOPA-AUT scores were higher in the group with multiple sleep disorders compared with those in the other two groups. Compared with those in patients with no sleep disorder, NMSS scores were higher in patients with one sleep disorder. However, gender, onset age, disease duration, MDS-UPDRS part I and III scores, MoCA scores, HAMA scores, HAMD-24 scores, FSS scores, and disease progression were similar in the three groups. The ordinal logistic regression analysis using a forward selection showed that the SCOPA-AUT score (OR = 1.16, 95%CI = 1.02–1.31, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e=0.025) was a contributing factor for multiple sleep disturbances \u003cstrong\u003e(Table 2)\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with PD-RBD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients with PSG-confirmed RBD (24, 40.7%) had higher SCOPA-AUT scores than those without RBD. Binary logistic regression analysis revealed that RBD in PD was significantly associated with higher SCOPA-AUT scores (OR = 1.08, 95% CI = 1.00–1.17, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.040), while it was not associated with motor symptoms, disease progression, depression, anxiety, cognition, fatigue, or other sleep disorders \u003cstrong\u003e(Table S2)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with PD-RLS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S3\u0026nbsp;\u003c/strong\u003eshows the results of univariate and multivariate regression analyses for PD patients with and without RLS.RLS was significantly associated with disease duration, LEDD, scores of mNMSS, PSQI, FSS, and motor progression in the univariate model. These covariates were further included in the multivariate analysis, then higher PSQI scores (OR = 1.92, 95% CI = 1.01–1.64, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.039) were significantly correlated with RLS, indicating that higher PSQI scores may be independent risk factor for RLS. No differences were found in red blood cell count and the levels of hemoglobin, serum ferritin, folic acid and vitamin B12 between patients with and without RLS (\u003cstrong\u003eTable S7\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with PD-SDB\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigher body mass index (OR = 1.21, 95% CI = 1.01–1.45, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.044) and lower MoCA scores (OR = 0.84, 95% CI = 0.72–0.98, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.029) were significantly correlated with SDB both in univariate and multivariate regression analyses \u003cstrong\u003e(Table S4)\u003c/strong\u003e. No other differences in clinical factors were observed between PD patients with and without SDB.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with PD-insomnia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S5\u003c/strong\u003e shows clinical characteristics of PD patients with and without insomnia. In univariate regression model, non-motor scores including MDS-UPDRS part I, mNMSS, HAMA, HAMD-24, MoCA, SCOPA-AUT and PSQI, taking antidepressants, scores of PQD-39 and MDS-UPDRS part II were significantly correlated with insomnia. In multivariate logistic regression analyses, higher scores of MDS-UPDRS part I (OR = 2.05, 95% CI = 1.04–4.05, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.038), HAMD-24 (OR = 1.88, 95% CI = 1.10–3.20, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.021) and SCOPA-AUT (OR = 1.43, 95% CI = 1.07–1.92, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.016) were significantly correlated with insomnia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with PD-EDS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePD patients with EDS (10/59, 16.9%) had higher scores for MDS-UPDRS part I, part II, SCOPA-AUT and PDQ-39 in the univariate regression analysis. When these covariates were included in the multivariate analyses, the results revealed that only autonomic dysfunction increased the risk of EDS, by 1.17 times (95% CI = 1.05–1.31, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.006) (\u003cstrong\u003eTable S6\u003c/strong\u003e). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of plasma neurotransmitter and neurohormone\u003c/strong\u003e \u003cstrong\u003econcentrations in PD patients and controls\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn healthy controls, the plasma dopamine level at 1:00 am was significantly lower than that at 9:00 am, and the melatonin level at 1:00 am was significantly higher than that at 9:00 am, consistent with the findings of previous studies\u003cstrong\u003e\u003csup\u003e[18-19]\u003c/sup\u003e\u003c/strong\u003e. Patients with PD had decreased plasma concentrations of Asp, Glu, GABA, MT and epinephrine at 1:00 am and a decreased plasma concentration of Asp, Glu, DA and epinephrine at 9:00 am. The peripheral level of Gln was increased at 9:00 am in the PD group (\u003cstrong\u003eTable S8\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePeripheral melatonin and DA levels in PD-RBD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe plasma concentration of melatonin at 1:00 am was significantly decreased in PD patients with RBD compared with the findings in controls and PD patients without RBD (\u003cstrong\u003eFigure 2\u003c/strong\u003e), while the levels of DA were elevated in PD patients with RBD compared with those in patients without RBD at this time point, although no difference was identified between the PD-RBD and control groups (\u003cstrong\u003eTable S9)\u003c/strong\u003e. The plasma melatonin level at 1:00 am was negatively correlated with RBD (r = −0.40, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.0018) and the DA level was positively correlated with RBD (r = 0.29, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.025) (\u003cstrong\u003eFigure 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePeripheral 5-HT and glutamine levels in PD-RLS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt 1:00 am, PD patients with RLS had a significantly lower level of 5-HT compared with patients without RLS (\u003cstrong\u003eFigure S\u003c/strong\u003e). Glutamine level decreased significantly in the PD-RLS group at 9:00 am (\u003cstrong\u003eTable S10\u003c/strong\u003e). PD-RLS was negatively correlated with levels of 5-hydroxytryptamine at 1:00 am (r = −0.40, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.0016) and glutamine at 9:00 am (r = −0.39, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.0022) (\u003cstrong\u003eFigure 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePeripheral acetylcholine levels in PD-SDB\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePD patients with SDB had a lower plasma acetylcholine concentration than patients without SDB at 1:00 am (\u003cstrong\u003eTable S11\u003c/strong\u003e). There was also a negative correlation between SDB and acetylcholine level at 1:00 am in PD patients (r = −0.39, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.0025).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePD patients with EDS or insomnia did not exhibit a significant change in peripheral neurotransmitter or neurohormone levels (\u003cstrong\u003eTable S9, S11\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the current study, we confirmed that the incidence of sleep disturbances was high, and that multiple sleep disorders often coexisted in early-stage PD. RBD was the most common sleep disorder, followed by RLS, OSA, insomnia, and EDS. The incidence of insomnia (18.6%) was lower than that reported in a previous study\u003cstrong\u003e\u003csup\u003e[4]\u003c/sup\u003e\u003c/strong\u003e. Approximately 80% of PD patients had at least one type of sleep disturbance, and approximately 50% of patients had two or more sleep disturbances, similar to previously reported findings in the ICEBERG cohort\u003cstrong\u003e\u003csup\u003e[4]\u003c/sup\u003e\u003c/strong\u003e. The percentage of patients with combined sleep disorders in the PPMI cohort\u003cstrong\u003e\u003csup\u003e[20]\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ewas 11.5%, on the basis of assessments using questionnaires and a limited range of sleep disorders (RBD, EDS and PD-related sleep symptoms). The number of combined sleep disorders increased with the severity of dysautonomia, possibly related to the presence of RBD, EDS, and insomnia, and PD patients with RBD, EDS, and insomnia had higher scores for dysautonomia compared with those without sleep disorders.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe current findings revealed that RBD diagnosed by PSG accounted for the highest proportion (40.7%) of early-stage PD patients with sleep disorders, and was associated with dysautonomia. Evidence indicates that autonomic dysfunction and RBD share common neuropathology\u003cstrong\u003e\u003csup\u003e[21]\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;Patients presenting with pure autonomic failure (PAF) and isolated RBD (iRBD) are reported to be at high risk of converting to α-synucleinopathy\u003cstrong\u003e\u003csup\u003e[22-23]\u003c/sup\u003e\u003c/strong\u003e. Compared with healthy controls, iRBD subjects exhibit more prominent autonomic dysfunction\u003cstrong\u003e\u003csup\u003e[24]\u003c/sup\u003e\u003c/strong\u003e, suggesting a correlation between PAF and iRBD. Substantial evidence suggests that PD patients with RBD may constitute a distinct phenotype compared with PD patients without RBD, including autonomic dysfunction\u003cstrong\u003e\u003csup\u003e\u0026nbsp;[4,25-26]\u003c/sup\u003e\u003c/strong\u003e. RBD is considered to constitute a key marker of diffuse–malignant PD subtypes with cognitive loss, severe autonomic dysfunction, fast motor progression and loss of independent living and mortality. Our study revealed a lower level of plasma melatonin in PD patients with RBD compared with the findings in patients without RBD and healthy controls at 1:00 AM. In addition, plasma melatonin level at this time was negatively correlated with RBD, suggesting that the decrease of peripheral melatonin level in early morning might be involved in RBD development. Previous studies using animal experiments reported that α‑synuclein reduces acetylserotonin O-methyltransferase-mediated melatonin biosynthesis\u003cstrong\u003e\u003csup\u003e[27-28]\u003c/sup\u003e\u003c/strong\u003e. Two previous studies reported that patients with PD exhibited reduced circulating melatonin levels\u003cstrong\u003e\u003csup\u003e[6,11]\u003c/sup\u003e\u003c/strong\u003e. Furthermore, some studies reported that melatonin treatment can alleviate the symptoms of RBD in PD patients\u003cstrong\u003e\u003csup\u003e[29]\u003c/sup\u003e\u003c/strong\u003e\u003cem\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/em\u003eThe current results were consistent with previous findings, and supported the role of melatonin in RBD occurrence. We also found that plasma dopamine levels were higher in PD patients with RBD at 1:00 AM compared with the levels in those without RBD, possibly resulting from a higher L-dopa requirement because of worsening motor symptoms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the current study, RLS was the second most common sleep disorder in early-stage PD, with a frequency of 35.6%, which was higher than that reported in previous studies (4.6%–16.3%)\u003cstrong\u003e\u003csup\u003e[30-31]\u003c/sup\u003e\u003c/strong\u003e. In the current study population, PD patients with RLS exhibited poorer sleep quality than those without RLS, which was similar to findings reported in previous investigations\u003cstrong\u003e\u003csup\u003e[10,32-33]\u003c/sup\u003e\u003c/strong\u003e. RLS can have a negative impact on sleep quality by decreasing sleep time and efficiency\u003cstrong\u003e\u003csup\u003e[4,34]\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;Our study indicated that PD patients with RLS exhibited abnormal neurotransmitter levels, including reduced plasma levels of 5-hydroxytryptamine (5-HT) at 1:00 AM and reduced plasma levels of glutamine at 9:00 AM, which were negatively correlated with RLS. Piao et al.\u003cstrong\u003e\u003csup\u003e[10]\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003ereported a similar 5-HT change in cerebrospinal fluid. Another study\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ereported\u0026nbsp;that sleep dysfunction in PD is associated with reduced serotonergic function in the midbrain raphe, basal ganglia and hypothalamus using \u003csup\u003e[11\u003c/sup\u003eC\u003csup\u003e]\u003c/sup\u003eDASB positron emission tomography\u003cstrong\u003e\u003csup\u003e[35]\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;A possible mechanism underlying this phenomenon is that 5-HT may interact with dopamine-pathway activity or disturb iron metabolism\u003cstrong\u003e\u003csup\u003e[36-37]\u003c/sup\u003e\u003c/strong\u003e. One previous study confirmed that glutaminergic neurotransmitters in the thalamus are involved in the development of RLS by increasing the arousal\u003cstrong\u003e\u003csup\u003e[38]\u003c/sup\u003e\u003c/strong\u003e, although it is unclear how glutaminergic neurotransmitters are involved in the development of PD-RLS.\u003c/p\u003e\n\u003cp\u003eSDB was previously reported to be more prevalent in early-stage PD patients than in the general population\u003cstrong\u003e\u003csup\u003e[39]\u003c/sup\u003e\u003c/strong\u003e. In the current study, SDB was associated with higher body mass index and cognitive dysfunction in PD, these outcomes are in accord with several previous reports\u003cstrong\u003e\u003csup\u003e[40-42]\u003c/sup\u003e\u003c/strong\u003e. Sleep-related hypoxemia disorder can affect cognitive function and result in a worse prognosis for PD, and longitudinal studies have reported that continuous positive airway pressure (CPAP) can improve global cognitive function over a 12-month period in PD patients with OSA\u003cstrong\u003e\u003csup\u003e[43-44]\u003c/sup\u003e\u003c/strong\u003e. In PD patients with SDB, the plasma levels of acetylcholine at 1:00 AM were found to be significantly decreased compared with the findings in patients without SDB and controls. Hilker et al.\u003cstrong\u003e\u003csup\u003e[45]\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003eobserved that PD patients with dementia exhibited significantly reduced neocortical acetylcholinesterase (AChE) activity compared with PD subjects without dementia. Therefore, the current findings indicate that cholinergic denervation may account for cognitive impairment in PD-SDB.\u003c/p\u003e\n\u003cp\u003eIn the current study cohort,\u0026nbsp;approximately one-fifth\u0026nbsp;of PD subjects\u0026nbsp;had EDS. Patients with EDS experienced\u0026nbsp;severe\u0026nbsp;autonomic dysfunction, which\u0026nbsp;was consistent with\u0026nbsp;the findings of previous\u0026nbsp;studies\u003cstrong\u003e\u003csup\u003e[4\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e-4\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e. Aleksandar et al.\u003cstrong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003eobserved\u0026nbsp;that PD participants with EDS had a significantly lower amplitude of melatonin rhythm and 24-hour melatonin\u0026nbsp;area\u0026nbsp;under the\u0026nbsp;curve (AUC)\u0026nbsp;compared with PD participants without EDS\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;In the current study,\u0026nbsp;the absence of a change in the levels of melatonin among PD patients\u0026nbsp;with or without EDS may have occurred because the patients were enrolled in the early stage when circadian rhythm disruption is less severe compared with that in the advanced stage.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe frequency of insomnia in this study was lower than that reported in a previous study\u0026nbsp;(21%–41%)\u003cstrong\u003e\u003csup\u003e[4]\u003c/sup\u003e\u003c/strong\u003e, possibly because\u0026nbsp;the\u0026nbsp;patients enrolled in the current study\u0026nbsp;were in the early stage of PD, whereas insomnia is more prevalent in advanced PD\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e39\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;Although the current findings suggest that insomnia may be related to depression, dysautonomia, and poorer ADL in patients with early-stage PD\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e20,49\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e, we observed no significant changes in peripheral neurotransmitters and neurohormones levels in the PD-insomnia subgroup, indicating the heterogenous nature of insomnia in PD\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e50\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSeveral limitations of our study should be noted. First, the sample size of 89 was modest. However, this sample still allowed a comprehensive analysis of sleep disturbances in early-stage PD, and all participants underwent comprehensive motor, non-motor, and sleep assessments. Second, patients were medicated rather than drug-naïve which could potentially have an impact on sleep disturbances. However, there were no significant differences in daily doses of levodopa or dopamine receptor agonists among the sleep disorder subgroups. Finally, blood samples were only collected at two time points, although the sampling was conducted at two representative times, morning and midnight. Circadian peripheral changes of these bioactive substances should be taken into consideration in future studies.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"Combined sleep disturbances were found to be common in early-stage PD patients. Dysautonomia was closely related to the presence of combined and specific sleep disorders, including RBD, EDS and insomnia. Changes in peripheral neurotransmitters and neurohormones may be involved in the development of sleep disturbances. Therefore, a better understanding of the role of these endogenous compounds could be helpful for optimizing the treatments for PD-related sleep disorders in the future."},{"header":"Declarations","content":"\u003cp\u003eFunding:This study was funded by Tianjin Key Medical Discipline (Specialty) Construction Project (No. TJYXZDXK-052B).\u003c/p\u003e\n\u003cp\u003eEthics statement: This study was conducted in accordance with the Declaration of Helsinki. This study was approved by the ethics committee of Huanhu Hospital, and written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003eRelevant conflicts of interests/financial disclosures: Nothing to report.\u003c/p\u003e\n\u003cp\u003eData Availability Statement:The data that support the findings of this study are available on request from the Parkinson’s Disease and Movement Disorder Clinic, Tianjin Huanhu Hospital.\u003c/p\u003e\n\u003cp\u003eContributions: (I) Conception, design and collection and assembly of data: Cui-Hong Ma; (II) Administrative support: Lei Chen; (III) Provision of study materials or patients: Ning Ren; (IV)Data analysis and interpretation: Cui-hong Ma, Jing Xu; (V) Manuscript writing: Cui-hong Ma; (VI) Final approval of manuscript: All authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSchapira A, Chaudhuri KR, Jenner P. Non-motor features of Parkinson disease[J]. 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Neurology, 2017,88(4):352-358. doi:10.1212/WNL.0000000000003540.\u003c/li\u003e\n\u003cli\u003eSobreira-Neto MA, Pena-Pereira MA, Sobreira E, et al. Chronic Insomnia in Patients With Parkinson Disease: Which Associated Factors Are Relevant?[J]. J Geriatr Psychiatry Neurol, 2020,33(1):22-27. doi:10.1177/0891988719856687.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eDemographical and clinical characteristics by co-occurrence of sleep-related disorders in early-stage PD patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"852\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003eNo sleep disorder\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eN=11 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003eOne sleep disorder\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eN=23 (39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003eat least two sleep diorders\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003eN=25 (42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003eF/H/X\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemography\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\" valign=\"top\"\u003e\n \u003cp\u003eOnset age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e61.59\u0026plusmn;10.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e58.83\u0026plusmn;8.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e63.32\u0026plusmn;8.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\" valign=\"top\"\u003e\n \u003cp\u003eDisease course (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e2.06\u0026plusmn;1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e3.96\u0026plusmn;3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e4.67\u0026plusmn;3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\" valign=\"top\"\u003e\n \u003cp\u003eMale sex, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e4 (36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e13 (56.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e14 (56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal assessment of disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\" valign=\"top\"\u003e\n \u003cp\u003eH-Y stage(on-OFF condition)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e2.00 (1.00, 2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e2.50 (2.00, 2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e2.50 (2.00, 2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eMDS-UPDRS I (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e10.82\u0026plusmn;5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e11.65\u0026plusmn;6.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e15.12\u0026plusmn;7.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eMDS-UPDRS II (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e9.45\u0026plusmn;2.70\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e13.65\u0026plusmn;8.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e17.20\u0026plusmn;9.39\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eMDS-UPDRS III (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e19.36\u0026plusmn;10.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e28.17\u0026plusmn;12.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e26.00\u0026plusmn;13.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon motor symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eNMSS (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e20.45\u0026plusmn;8.56\u003csup\u003eb, c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e40.04\u0026plusmn;20.83\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e53.44\u0026plusmn;29.65\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e7.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003ePSQI (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e5.09\u0026plusmn;2.95\u003csup\u003e\u0026nbsp;c\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e7.17\u0026plusmn;4.14\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e10.20\u0026plusmn;5.12\u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e5.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eMoCA (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e24.91\u0026plusmn;3.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e23.14\u0026plusmn;4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e21.48\u0026plusmn;3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eHAMA (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e11.18\u0026plusmn;6.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e14.26\u0026plusmn;8.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e17.48\u0026plusmn;7.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eHAMD-24 (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e8.27\u0026plusmn;7.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e11.13\u0026plusmn;8.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e13.80\u0026plusmn;8.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eSCOPA-AUT (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e7.27\u0026plusmn;4.52\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e11.34\u0026plusmn;6.39\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e17.58\u0026plusmn;6.92\u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e11.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eFSS (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e1.61\u0026plusmn;1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e2.70\u0026plusmn;3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e3.17\u0026plusmn;1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease progression and life quality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eTotal disease progression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e33.77\u0026plusmn;28.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e21.43\u0026plusmn;16.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e20.15\u0026plusmn;19.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eMotor progression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e15.52\u0026plusmn;15.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e10.95\u0026plusmn;7.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e9.26\u0026plusmn;9.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eADL progression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e8.22\u0026plusmn;6.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e4.93\u0026plusmn;3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e5.09\u0026plusmn;3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003ePDQ-39 (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e19.45\u0026plusmn;13.41\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e30.17\u0026plusmn;24.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e43.44\u0026plusmn;27.79\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eLEDD (mg/day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e170.45\u0026plusmn;153.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e214.04\u0026plusmn;244.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e314.04\u0026plusmn;314.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.87323943661972%\"\u003e\n \u003cp\u003eDopamine agonist, N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.1924882629108%\"\u003e\n \u003cp\u003e3 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.431924882629108%\"\u003e\n \u003cp\u003e5 (21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.366197183098592%\"\u003e\n \u003cp\u003e9 (36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.389671361502348%\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.746478873239437%\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are shown as mean\u0026plusmn;SD, median (quartile range) or N (%). Statistical significance was set at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. Significant differences are shown in bold.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eFor a pairwise difference with no sleep disturbance; \u003csup\u003eb\u003c/sup\u003eFor a pairwise difference with one sleep disorder; \u003csup\u003ec\u003c/sup\u003eFor a pairwise difference with at least two\u0026nbsp;\u003c/p\u003e\n\u003cp\u003esleep disorders.\u003c/p\u003e\n\u003cp\u003eAbbreviations: MDS UPDRS:Movement Disorder Society-Unified Parkinson\u0026rsquo;s Disease Rating Scale; NMSS:non-motor symptom evaluation scale; PSQI:Pittsburgh Sleep Quality Index; MoCA: Montreal Cognitive Assessment; HAMA: Hamilton Anxiety Scale; HAMD-24:Hamilton Depression Scale -24; SCOPA-AUT: scale of outcomes in PD for autonomic symptoms; FSS: Fatigue Severity Scale; LEDD: L-dopa equivalent daiyl dose; ADL:activities of daily living; PDQ-39:39-item Parkinsons Disease Questionnaire.\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eLogistic regression analyses for PD patients with only one, multiple types and without sleep disorders\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.595744680851062%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaribles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.113475177304963%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.539007092198581%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.099290780141843%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003csup\u003eb\u0026nbsp;\u003c/sup\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.652482269503546%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.595744680851062%\" valign=\"top\"\u003e\n \u003cp\u003eDisease course\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.113475177304963%\" valign=\"top\"\u003e\n \u003cp\u003e1.21 (1.01-1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.539007092198581%\" valign=\"top\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.099290780141843%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.652482269503546%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.595744680851062%\" valign=\"top\"\u003e\n \u003cp\u003eMDS UPDRS II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.113475177304963%\" valign=\"top\"\u003e\n \u003cp\u003e1.08 (1.02-1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.539007092198581%\" valign=\"top\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.099290780141843%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.652482269503546%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.595744680851062%\" valign=\"top\"\u003e\n \u003cp\u003eNMSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.113475177304963%\" valign=\"top\"\u003e\n \u003cp\u003e1.04 (1.02-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.539007092198581%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.099290780141843%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.652482269503546%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.595744680851062%\" valign=\"top\"\u003e\n \u003cp\u003eSCOPA-AUT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.113475177304963%\" valign=\"top\"\u003e\n \u003cp\u003e1.20 (1.09-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.539007092198581%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.099290780141843%\" valign=\"top\"\u003e\n \u003cp\u003e1.16 (1.02-1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.652482269503546%\" valign=\"top\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.595744680851062%\" valign=\"top\"\u003e\n \u003cp\u003ePDQ-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.113475177304963%\" valign=\"top\"\u003e\n \u003cp\u003e1.03 (1.01-1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.539007092198581%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.099290780141843%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.652482269503546%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.595744680851062%\" valign=\"top\"\u003e\n \u003cp\u003ePSQI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.113475177304963%\" valign=\"top\"\u003e\n \u003cp\u003e1.18 (1.05-1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.539007092198581%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.099290780141843%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.652482269503546%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eUnivariate ordinal logistic regression;\u003csup\u003eb\u003c/sup\u003eMultivariate ordinal logistic regression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbbreviations: MDS UPDRS II:Movement Disorder Society-Unified Parkinson\u0026rsquo;s Disease Rating Scale part II; NMSS:non-motor symptom evaluation scale; SCOPA-AUT: scale of outcomes in PD for autonomic symptoms; PDQ-39:39-item Parkinsons Disease Questionnaire; PSQI:Pittsburgh Sleep Quality Index.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-communication-and-signaling","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ccas","sideBox":"Learn more about [Cell Communication and Signaling](http://biosignaling.biomedcentral.com/)","snPcode":"12964","submissionUrl":"https://submission.nature.com/new-submission/12964/3","title":"Cell Communication and Signaling","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Parkinson’s disease, Sleep disorders, plasma neurotransmitter and neurohormone levels","lastPublishedDoi":"10.21203/rs.3.rs-4813635/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4813635/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eSleep disorders occur frequently in patients with Parkinson’s disease (PD). Neurotransmitters and neurosteroids are known to be involved in various neurophysiological processes, including sleep development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003eWe aimed to assess the association between peripheral neurotransmitter and neurosteroid levels and various sleep disorders in early-stage PD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e59 patients with early-stage PD and 30 healthy controls were enrolled. Demographic and clinical data were collected and sleep conditions were comprehensively assessed with clinical questionnaires and polysomnography. Blood samples were obtained at 1:00 AM and 9:00 AM in all participants. The concentrations of plasma neurotransmitters and neurohormones were detected using high-performance liquid chromatography tandem mass spectrometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eSleep disorders were common non-motor symptoms (81.4%) and coexisted in approximately half of the patients. Dysautonomia was significantly associated with the presence of multiple sleep disorders. RBD was associated with dysautonomia and was negatively correlated with plasma melatonin concentration at 1:00 AM (r = −0.40, \u003cem\u003ep \u003c/em\u003e= 0.002) in early-stage PD patients. The RLS group had higher PSQI score, and RLS was negatively associated with the levels of 5-hydroxytryptamine (r = −0.40, \u003cem\u003ep \u003c/em\u003e= 0.002) at 1:00 AM and glutamine (r = −0.39,\u003cem\u003e p \u003c/em\u003e= 0.002) at 9:00 AM. SDB was associated with cognitive impairment, higher body mass index, and lower plasma acetylcholine concentrations at 1:00 AM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eCombined\u003cstrong\u003e \u003c/strong\u003esleep disturbances were frequent in early-stage PD. Dysautonomia was closely related to various sleep disorders, including RBD, EDS, and insomnia. Changes in peripheral neurotransmitter and neurohormone levels may be involved in the development of sleep disorders.\u003c/p\u003e","manuscriptTitle":"Clinical features, plasma neurotransmitter levels and plasma neurohormone levels in sleep disorders among patients with early-stage Parkinson’s disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-02 13:50:14","doi":"10.21203/rs.3.rs-4813635/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-07T16:49:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-26T17:44:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147964831662509625009632817974323464017","date":"2024-08-09T07:26:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81492759621526096728397033520429756283","date":"2024-08-02T19:13:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-02T14:53:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-29T23:52:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-29T23:51:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Communication and Signaling","date":"2024-07-27T14:55:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-communication-and-signaling","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ccas","sideBox":"Learn more about [Cell Communication and Signaling](http://biosignaling.biomedcentral.com/)","snPcode":"12964","submissionUrl":"https://submission.nature.com/new-submission/12964/3","title":"Cell Communication and Signaling","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0c8f85f4-2956-4f6e-82ed-b0d030264d72","owner":[],"postedDate":"September 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-24T16:07:45+00:00","versionOfRecord":{"articleIdentity":"rs-4813635","link":"https://doi.org/10.1186/s12964-025-02153-8","journal":{"identity":"cell-communication-and-signaling","isVorOnly":false,"title":"Cell Communication and Signaling"},"publishedOn":"2025-03-18 15:57:18","publishedOnDateReadable":"March 18th, 2025"},"versionCreatedAt":"2024-09-02 13:50:14","video":"","vorDoi":"10.1186/s12964-025-02153-8","vorDoiUrl":"https://doi.org/10.1186/s12964-025-02153-8","workflowStages":[]},"version":"v1","identity":"rs-4813635","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4813635","identity":"rs-4813635","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}