Fatigue Correlates with Sleep Disturbances in Parkinson’s Disease

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Fatigue Correlates with Sleep Disturbances in Parkinson’s Disease: A Comprehensive Analysis of Polysomnographic and Clinical Findings

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor symptoms such as bradykinesia, rigidity, and tremors. However, non-motor symptoms, including fatigue and sleep disturbances, significantly impact patients’ quality of life. Fatigue, reported by 33–58% of PD patients, is often described as debilitating and independent of physical exertion. Sleep disorders, such as rapid eye movement (REM) sleep behavior disorder (RBD), insomnia, and excessive daytime sleepiness, affect 60–98% of PD patients. Despite their prevalence, the relationship between fatigue and objective sleep abnormalities remains poorly understood. This study investigates the association between fatigue severity and polysomnography (PSG)-measured sleep disturbances in PD, providing critical insights into the interplay of these non-motor symptoms.

Study Design and Participant Characteristics

A cohort of 232 PD patients was recruited, divided into two groups based on fatigue severity: 152 with mild fatigue (Fatigue Severity Scale [FSS] <4) and 80 with severe fatigue (FSS ≥4). Participants were assessed using standardized clinical tools, including the Unified Parkinson’s Disease Rating Scale (UPDRS), Hoehn and Yahr (H-Y) staging, and levodopa equivalent daily dose (LEDD). Depression, anxiety, cognition, and sleep quality were evaluated via the Hamilton Rating Scale for Depression (HRSD), Hamilton Anxiety Rating Scale (HAMA), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Epworth Sleepiness Scale (ESS), and Pittsburgh Sleep Quality Index (PSQI). Overnight PSG was conducted to quantify sleep architecture, REM sleep parameters, and RBD prevalence.

Key exclusion criteria included secondary parkinsonism, severe psychiatric comorbidities, and medications affecting REM sleep muscle atonia (e.g., clonazepam, SSRIs). Patients with apnea-hypopnea index (AHI) >15 or REM sleep duration <5 minutes were excluded to ensure accurate RBD assessment.

Clinical and Demographic Findings

Patients with severe fatigue exhibited distinct clinical profiles compared to the mild fatigue group:

  • Disease Severity: Longer disease duration (5.40 vs. 3.15 years, P<0.001), higher UPDRS-III scores (32.64 vs. 19.87, P<0.001), and advanced H-Y stages (2.63 vs. 1.91, P<0.001).
  • Medication Burden: Higher LEDD (400 mg vs. 262.5 mg, P<0.001).
  • Non-Motor Symptoms: Worse depression (HRSD: 12.74 vs. 7.89, P<0.001), anxiety (HAMA: 9.26 vs. 5.85, P<0.001), and daytime sleepiness (ESS: 7.34 vs. 6.18, P=0.046).
  • Autonomic Dysfunction: Higher rates of hypersalivation (50% vs. 21.05%, P<0.001) and urinary urgency (47.5% vs. 25.66%, P=0.001).

No differences were observed in age, sex, body mass index (BMI), or cognitive scores (MMSE, MoCA), suggesting fatigue severity is independent of baseline demographics or global cognitive decline.

Polysomnography Findings

PSG revealed significant differences in sleep architecture between fatigue groups:

  1. REM Sleep Reduction: Severe fatigue patients had lower REM sleep percentage (13.04% vs. 16.23%, P=0.009).
  2. REM Sleep Without Atonia (RWA): Elevated tonic RWA (20.77% vs. 13.25%, P=0.012) and phasic RWA (22.76% vs. 11.11%, P=0.002) in severe fatigue.
  3. RBD Prevalence: 67.5% of severe fatigue patients met PSG criteria for RBD vs. 51.31% in mild fatigue (P=0.018). Clinical RBD symptoms (e.g., dream-enacting behaviors) were also more frequent in severe fatigue (73.75% vs. 59.21%, P=0.028).

Other PSG parameters, including total sleep time, sleep latency, AHI, and oxygen desaturation index (ODI), showed no group differences, indicating fatigue specifically correlates with REM-related disturbances rather than general sleep fragmentation or respiratory issues.

Multivariate Regression Analyses

Two models identified independent predictors of fatigue severity:

  1. Logistic Regression: After adjusting for age, sex, disease duration, BMI, UPDRS-III, LEDD, HRSD, and HAMA, the presence of RBD (OR=2.256, P=0.015) and reduced REM sleep percentage (OR=0.952, P=0.013) remained significant. Higher LEDD (OR=1.004, P<0.001) and depression (OR=1.099, P<0.001) also contributed.
  2. Linear Regression: REM sleep percentage inversely correlated with FSS scores (β=−0.037, P<0.001), while tonic RWA (β=0.012, P=0.015) and phasic RWA (β=0.013, P=0.003) positively predicted fatigue severity, even after adjusting for confounders.

These results highlight RBD and REM sleep disruption as robust, independent contributors to fatigue, beyond the effects of motor disability or mood disorders.

Pathophysiological and Clinical Implications

1. RBD and Synucleinopathy

RBD is a hallmark of alpha-synuclein pathology, preceding motor symptoms in PD by years. Elevated RWA and RBD prevalence in fatigued patients suggest shared neurodegenerative mechanisms. Cerebrospinal fluid (CSF) studies link higher alpha-synuclein oligomer levels to both fatigue and RBD, implicating synaptic dysfunction and Lewy body propagation in brainstem regions regulating sleep and energy.

2. REM Sleep Deprivation and Central Fatigue

REM sleep is critical for emotional processing and neuronal recovery. Its reduction in PD may exacerbate central fatigue, characterized by persistent exhaustion unrelated to physical activity. Compensatory increases in non-REM sleep (NREM) did not mitigate fatigue, implying REM-specific restorative functions are irreplaceable.

3. Clinical Overlap with Other Non-Motor Symptoms

Fatigue correlated strongly with depression, anxiety, and autonomic dysfunction, reflecting a “non-motor cluster” driven by overlapping neurochemical deficits (e.g., dopamine, norepinephrine). However, multivariate models confirmed RBD and REM abnormalities as unique predictors, advocating for targeted sleep interventions.

4. Limitations and Future Directions

  • Sample Constraints: Single-center design and moderate sample size limit generalizability.
  • Cross-Sectional Data: Longitudinal studies are needed to establish causality between RBD progression and fatigue.
  • Subjective Measures: FSS, though validated, may conflate physical and mental fatigue. Objective biomarkers (e.g., CSF synuclein, neuroimaging) could refine fatigue subtyping.

Clinical Recommendations

  1. Routine Sleep Assessments: PSG should be considered for fatigued PD patients to identify RBD and REM sleep deficits.
  2. Pharmacological Caution: Dopaminergic agents, while alleviating motor symptoms, may exacerbate fatigue at higher doses (e.g., LEDD >400 mg).
  3. Non-Pharmacologic Interventions: Cognitive-behavioral therapy for sleep hygiene and REM-specific strategies (e.g., melatonin for RBD) may improve fatigue.

Conclusion

This study establishes a significant association between fatigue severity, RBD, and REM sleep abnormalities in PD, independent of motor disability or mood disorders. The findings position fatigue as a distinct non-motor subtype linked to brainstem synucleinopathy and disrupted sleep architecture. Clinicians should prioritize sleep evaluations in fatigued PD patients, as addressing RBD and REM deficits may offer novel therapeutic avenues. Future research must explore longitudinal relationships and neuropathological underpinnings to optimize management strategies.

doi.org/10.1097/CM9.0000000000001303

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