Cardiac sympathetic index identifies patients with Parkinson's disease and REM behavior disorder

Periodic Leg Movements during Sleep Associated with REM Sleep Behavior Disorder: A Machine Learning Study

Most patients with idiopathic REM sleep behavior disorder (iRBD) present peculiar repetitive leg jerks during sleep in their clinical spectrum, called periodic leg movements (PLMS). The clinical differentiation of iRBD patients with and without PLMS is challenging, without polysomnographic confirmation. The aim of this study is to develop a new Machine Learning (ML) approach to distinguish between iRBD phenotypes. Heart rate variability (HRV) data were acquired from forty-two consecutive iRBD patients (23 with PLMS and 19 without PLMS). All participants underwent video-polysomnography to confirm the clinical diagnosis. ML models based on Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) were trained on HRV data, and classification performances were assessed using Leave-One-Out cross-validation. No significant clinical differences emerged between the two groups. The RF model showed the best performance in differentiating between iRBD phenotypes with excellent accuracy (86%), sensitivity (96%), and specificity (74%); SVM and XGBoost had good accuracy (81% and 78%, respectively), sensitivity (83% for both), and specificity (79% and 72%, respectively). In contrast, LR had low performances (accuracy 71%). Our results demonstrate that ML algorithms accurately differentiate iRBD patients from those without PLMS, encouraging the use of Artificial Intelligence to support the diagnosis of clinically indistinguishable iRBD phenotypes.

Heart rate variability during sleep in synucleinopathies: a review

Synucleinopathies are a group of neurodegenerative diseases characterized by abnormal accumulations of insoluble alpha-synuclein in neurons or glial cells. These consist of Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Moreover, idiopathic REM sleep behavior disorder (iRBD) is often the first manifestation of synucleinopathies, demonstrating a pathophysiological continuum. While these disorders vary in prevalence, symptom patterns, and severity, they can all include autonomic nervous system (ANS) dysfunction, which significantly reduces quality of life and worsens prognosis. Consequently, identifying abnormalities of the ANS can provide opportunities for improving quality of life through symptomatic treatments that are tailored to the individual's symptoms. An exciting development is using heart rate variability (HRV) as a non-invasive research tool for analyzing how the ANS regulates physiological processes. HRV during sleep, however, may provide a more accurate and reliable measure of ANS activity than during wakefulness, as during awake time, ANS activity is influenced by a variety of factors, including physical activity, stress, and emotions, which may mask or confound the underlying patterns of ANS activity. This review aims to provide an overview of the current knowledge regarding sleep-related HRV in synucleinopathies and to discuss contributing mechanisms. Evidence suggests that iRBD, PD, and MSA are associated with nocturnal ANS dysfunction. Further, comparative studies indicate that the presence of RBD could exacerbate this abnormality. In contrast, no studies have been conducted in patients with DLB. Overall, this review provides new insight into the complex interplay between the ANS and synucleinopathies and underscores the need for further research in this area to develop effective therapies to improve sleep and overall quality of life in patients with synucleinopathies.

Circadian disruption and sleep disorders in neurodegeneration

Disruptions of circadian rhythms and sleep cycles are common among neurodegenerative diseases and can occur at multiple levels. Accumulating evidence reveals a bidirectional relationship between disruptions of circadian rhythms and sleep cycles and neurodegenerative diseases. Circadian disruption and sleep disorders aggravate neurodegeneration and neurodegenerative diseases can in turn disrupt circadian rhythms and sleep. Importantly, circadian disruption and various sleep disorders can increase the risk of neurodegenerative diseases. Thus, harnessing the circadian biology findings from preclinical and translational research in neurodegenerative diseases is of importance for reducing risk of neurodegeneration and improving symptoms and quality of life of individuals with neurodegenerative disorders via approaches that normalize circadian in the context of precision medicine. In this review, we discuss the implications of circadian disruption and sleep disorders in neurodegenerative diseases by summarizing evidence from both human and animal studies, focusing on the bidirectional links of sleep and circadian rhythms with prevalent forms of neurodegeneration. These findings provide valuable insights into the pathogenesis of neurodegenerative diseases and suggest a promising role of circadian-based interventions.

A Machine Learning Approach for Detecting Idiopathic REM Sleep Behavior Disorder

Background and purpose: Growing evidence suggests that Machine Learning (ML) models can assist the diagnosis of neurological disorders. However, little is known about the potential application of ML in diagnosing idiopathic REM sleep behavior disorder (iRBD), a parasomnia characterized by a high risk of phenoconversion to synucleinopathies. This study aimed to develop a model using ML algorithms to identify iRBD patients and test its accuracy. Methods: Data were acquired from 32 participants (20 iRBD patients and 12 controls). All subjects underwent a video-polysomnography. In all subjects, we measured the components of heart rate variability (HRV) during 24 h recordings and calculated night-to-day ratios (cardiac autonomic indices). Discriminating performances of single HRV features were assessed. ML models based on Logistic Regression (LR), Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) were trained on HRV data. The utility of HRV features and ML models for detecting iRBD was evaluated by area under the ROC curve (AUC), sensitivity, specificity and accuracy corresponding to optimal models. Results: Cardiac autonomic indices had low performances (accuracy 63-69%) in distinguishing iRBD from control subjects. By contrast, the RF model performed the best, with excellent accuracy (94%), sensitivity (95%) and specificity (92%), while XGBoost showed accuracy (91%), specificity (83%) and sensitivity (95%). The mean triangular index during wake (TIw) was the best discriminating feature between iRBD and HC, with 81% accuracy, reaching 84% accuracy when combined with VLF power during sleep using an LR model. Conclusions: Our findings demonstrated that ML algorithms can accurately identify iRBD patients. Our model could be used in clinical practice to facilitate the early detection of this form of RBD.

Quantification Analysis of Sleep Based on Smartwatch Sensors for Parkinson's Disease

Rapid eye movement (REM) sleep behavior disorder (RBD) is associated with Parkinson's disease (PD). In this study, a smartwatch-based sensor is utilized as a convenient tool to detect the abnormal RBD phenomenon in PD patients. Instead, a questionnaire with sleep quality assessment and sleep physiological indices, such as sleep stage, activity level, and heart rate, were measured in the smartwatch sensors. Therefore, this device can record comprehensive sleep physiological data, offering several advantages such as ubiquity, long-term monitoring, and wearable convenience. In addition, it can provide the clinical doctor with sufficient information on the patient's sleeping patterns with individualized treatment. In this study, a three-stage sleep staging method (i.e., comprising sleep/awake detection, sleep-stage detection, and REM-stage detection) based on an accelerometer and heart-rate data is implemented using machine learning (ML) techniques. The ML-based algorithms used here for sleep/awake detection, sleep-stage detection, and REM-stage detection were a Cole-Kripke algorithm, a stepwise clustering algorithm, and a k-means clustering algorithm with predefined criteria, respectively. The sleep staging method was validated in a clinical trial. The results showed a statistically significant difference in the percentage of abnormal REM between the control group (1.6 ± 1.3; n = 18) and the PD group (3.8 ± 5.0; n = 20) (p = 0.04). The percentage of deep sleep stage in our results presented a significant difference between the control group (38.1 ± 24.3; n = 18) and PD group (22.0 ± 15.0, n = 20) (p = 0.011) as well. Further, our results suggested that the smartwatch-based sensor was able to detect the difference of an abnormal REM percentage in the control group (1.6 ± 1.3; n = 18), PD patient with clonazepam (2.0 ± 1.7; n = 10), and without clonazepam (5.7 ± 7.1; n = 10) (p = 0.007). Our results confirmed the effectiveness of our sensor in investigating the sleep stage in PD patients. The sensor also successfully determined the effect of clonazepam on reducing abnormal REM in PD patients. In conclusion, our smartwatch sensor is a convenient and effective tool for sleep quantification analysis in PD patients.

Circadian rhythms in neurodegenerative disorders

Endogenous biological clocks, orchestrated by the suprachiasmatic nucleus, time the circadian rhythms that synchronize physiological and behavioural functions in humans. The circadian system influences most physiological processes, including sleep, alertness and cognitive performance. Disruption of circadian homeostasis has deleterious effects on human health. Neurodegenerative disorders involve a wide range of symptoms, many of which exhibit diurnal variations in frequency and intensity. These disorders also disrupt circadian homeostasis, which in turn has negative effects on symptoms and quality of life. Emerging evidence points to a bidirectional relationship between circadian homeostasis and neurodegeneration, suggesting that circadian function might have an important role in the progression of neurodegenerative disorders. Therefore, the circadian system has become an attractive target for research and clinical care innovations. Studying circadian disruption in neurodegenerative disorders could expand our understanding of the pathophysiology of neurodegeneration and facilitate the development of novel, circadian-based interventions for these disabling disorders. In this Review, we discuss the alterations to the circadian system that occur in movement (Parkinson disease and Huntington disease) and cognitive (Alzheimer disease and frontotemporal dementia) neurodegenerative disorders and provide directions for future investigations in this field.

Association of heart rate variability with REM sleep without atonia in idiopathic REM sleep behavior disorder

STUDY OBJECTIVES

Idiopathic rapid eye movement sleep behavior disorder (iRBD), characterized by rapid eye movement sleep without atonia (RSWA) and dream-enactment behavior, has been suggested to be a predictor of α-synucleinopathies. Autonomic instability, represented by heart rate variability, is a common characteristic of both iRBD and α-synucleinopathies. Previous studies reported that RSWA was associated with autonomic dysfunction and was a possible predictor of phenoconversion. Therefore, we sought to compare heart rate variability between iRBD and control groups and explore the relationship between heart rate variability and RSWA in patients with iRBD.

METHODS

Nocturnal polysomnographic data on 47 patients (28 men, 19 women) diagnosed with iRBD based on video-polysomnography and 26 age-matched and sex-matched controls were reviewed. The first 5-minute epoch with a stable electrocardiogram lead II on video-polysomnography was selected from stage N2, wake, and rapid eye movement. For quantification of RSWA, tonic activity was analyzed from the submentalis electromyogram and phasic activity from the submentalis and bilateral anterior tibialis electromyogram channels.

RESULTS

Compared to the control group, the iRBD group showed significant reductions in the standard deviation of the R-R intervals, the root mean square of successive R-R interval differences, and high-frequency values. Quantified tonic activity was inversely correlated with normalized low-frequency values and low-frequency/high-frequency ratios and positively correlated with normalized high-frequency values.

CONCLUSIONS

This study implied decreased cardiac autonomic function in patients with iRBD, which showed parasympathetic predominance. Heart rate variability of the patients with iRBD in this study was associated with quantified tonic RSWA, which was previously reported to be a possible predictor of phenoconversion.

Usefulness of cardiac parasympathetic index in CPAP-treated patients with obstructive sleep apnea: A preliminary study

Cardiac autonomic indexes, including cardiac parasympathetic index and cardiac sympathetic index, have been reported to accurately identify patients with sleep disorders such as obstructive sleep apnea. Our study aimed to assess cardiac autonomic indexes in patients with obstructive sleep apnea before and during a single full-night continuous positive airway pressure therapy using a combined approach. Our simultaneous heart rate variability-polysomnographic study included 16 never-treated obstructive sleep apnea patients. Two patients dropped out. Patients underwent combined recordings in two consecutive days, at baseline and during a single full-night of acute continuous positive airway pressure treatment. We calculated cardiac parasympathetic index and cardiac sympathetic index as night/day ratio for high-frequency and low-frequency heart rate variability spectral components, respectively. Continuous positive airway pressure treatment significantly reduced cardiac autonomic indexes values in comparison with baseline values (cardiac parasympathetic index: p < .0001; cardiac sympathetic index: p = .001). After acute continuous positive airway pressure treatment, the percentage of decrease of cardiac parasympathetic index was greater than that of cardiac sympathetic index (51.02 ± 15.72 versus 34.64 ± 26.93). A positive statistical correlation was also found between decrease of cardiac parasympathetic index and decrease of apnea-hypopnea index after continuous positive airway pressure (p < .001). This study improves the knowledge on cardiac autonomic modulation during acute continuous positive airway pressure therapy in obstructive sleep apnea. Our results demonstrate that both autonomic indexes decreased significantly after a single-night of acute continuous positive airway pressure therapy. Cardiac parasympathetic index more than cardiac sympathetic index was related to decrease of apnea-hypopnea index after continuous positive airway pressure therapy, thus representing a potential help in everyday clinical practice.

Daytime sleepiness and its relationships to fatigue and autonomic dysfunction in adults with spinal cord injury

OBJECTIVE

To determine the extent of daytime sleepiness in adults with spinal cord injury (SCI) and investigate the contribution of fatigue and autonomic function to sleepiness status.

METHODS

Participants included 45 adults with SCI attending outpatient services or living in the community and 44 able-bodied controls. The Oxford Sleep Resistance Test (OSLER) was used to assess daytime sleepiness, while eye blink rate duration (electrooculography) and the Iowa Fatigue Scale assessed fatigue. Heart rate variability (HRV) was used to assess autonomic function. Survival analysis (Kaplan Meier) was used to estimate the rate of loss in participation in the OSLER task, as a measure of daytime sleepiness. Repeated measures ANOVA was used to determine HRV differences between groups. Regression analysis was used to establish factors that contributed to daytime sleepiness.

RESULTS

Participants with high lesions ("T3 and above") had significantly increased daytime sleepiness. OSLER results revealed only 33% of those with high lesions remained awake during the task. Those with high lesions also had significantly reduced sympathetic activity while no differences in parasympathetic activity were found between groups. Lesion completeness had no effect. Standardized variation in heart rate, slow eye blinks, low frequency HRV and self-reported fatigue contributed to daytime sleepiness.

CONCLUSION

Neurological lesions at "T3 or above" have an increased risk of daytime sleepiness, impacting on independence in daily functional tasks and work performance. Autonomic imbalance alters cardiovascular control, affecting health and wellbeing. The interaction of these factors requires further investigation.

Cardiac parasympathetic index identifies subjects with adult obstructive sleep apnea: A simultaneous polysomnographic-heart rate variability study

OBJECTIVE

To evaluate circadian fluctuations and night/day ratio of Heart Rate Variability (HRV) spectral components in patients with obstructive sleep apnea (OSA) in comparison with controls.

PARTICIPANTS AND METHODS

This is a simultaneous HRV-polysomnographic (PSG) study including 29 patients with OSA and 18 age-sex-matched controls. Four patients with OSA dropped out. All participants underwent PSG and HRV analysis. We measured the 24-hour fluctuations and the night/day ratio of low frequency (LF) and high frequency (HF) spectral components of HRV in all subjects and controls. The LF night/day ratio was termed the cardiac sympathetic index while the HF night/day ratio was termed the cardiac parasympathetic index.

RESULTS

All twenty-five OSA patients were PSG positive (presence of OSA) while 18 controls were PSG negative (absence of OSA). There was no significant difference in LF and HF 24-hour fluctuation values between OSA patients and controls. In OSA patients, LF and HF values were significantly higher during night-time than day time recordings (p<0.001). HF night/day ratio (cardiac parasympathetic index) accurately (100%) differentiated OSA patients from controls without an overlap of individual values. The LF night/day ratio (cardiac sympathetic index) had sensitivity of 84%, specificity of 72.2% and accuracy of 79.1% in distinguishing between groups.

CONCLUSIONS

The cardiac parasympathetic index accurately differentiated patients with OSA from controls, on an individual basis.

An overview of sleep and circadian dysfunction in Parkinson's disease

Sleep and circadian alterations are amongst the very first symptoms experienced in Parkinson's disease, and sleep alterations are present in the majority of patients with overt clinical manifestation of Parkinson's disease. However, the magnitude of sleep and circadian dysfunction in Parkinson's disease, and its influence on the pathophysiology of Parkinson's disease remains often unclear and a matter of debate. In particular, the confounding influences of dopaminergic therapy on sleep and circadian dysfunction are a major challenge, and need to be more carefully addressed in clinical studies. The scope of this narrative review is to summarise the current knowledge around both sleep and circadian alterations in Parkinson's disease. We provide an overview on the frequency of excessive daytime sleepiness, insomnia, restless legs, obstructive apnea and nocturia in Parkinson's disease, as well as addressing sleep structure, rapid eye movement sleep behaviour disorder and circadian features in Parkinson's disease. Sleep and circadian disorders have been linked to pathological conditions that are often co-morbid in Parkinson's disease, including cognitive decline, memory impairment and neurodegeneration. Therefore, targeting sleep and circadian alterations could be one of the earliest and most promising opportunities to slow disease progression. We hope that this review will contribute to advance the discussion and inform new research efforts to progress our knowledge in this field.

Heart rate variability in leucine-rich repeat kinase 2-associated Parkinson's disease

BACKGROUND

Heart rate variability is reduced in idiopathic PD, indicating cardiac autonomic dysfunction likely resulting from peripheral autonomic synucleinopathy. Little is known about heart rate variability in leucine-rich repeat kinase 2-associated PD.

OBJECTIVES

This study investigated heart rate variability in LRRK2-associated PD.

METHODS

Resting electrocardiograms were obtained from 20 individuals with LRRK2-associated PD, 37 nonmanifesting carriers, 48 related noncarriers, 26 idiopathic PD patients, and 32 controls. Linear regression modelling compared time and frequency domain values, adjusting for age, sex, heart rate, and disease duration.

RESULTS

Low-frequency power and the ratio of low-high frequency power were reduced in idiopathic PD versus controls (P < .008, P < .029 respectively). In contrast, individuals with LRRK2-associated PD were not statistically different from controls in any parameter measured. Furthermore, all parameters trended toward being higher in LRRK2-associated PD when compared with idiopathic PD.

CONCLUSIONS

Heart rate variability may remain intact in LRRK2-associated PD, adding to a growing literature supporting clinical-pathologic differences between LRRK2-associated and idiopathic PD. © 2017 International Parkinson and Movement Disorder Society.

A New Perspective for Parkinson's Disease: Circadian Rhythm

Circadian rhythm is manifested by the behavioral and physiological changes from day to night, which is controlled by the pacemaker and its regulator. The former is located at the suprachiasmatic nuclei (SCN) in the anterior hypothalamus, while the latter is composed of clock genes present in all tissues. Circadian desynchronization influences normal patterns of day-night rhythms such as sleep and alertness cycles, rest and activity cycles. Parkinson's disease (PD) exhibits diurnal fluctuations. Circadian dysfunction has been observed in PD patients and animal models, which may result in negative consequences to the homeostasis and even exacerbate the disease progression. Therefore, circadian therapies, including light stimulation, physical activity, dietary and social schedules, may be helpful for PD patients. However, the cellular and molecular mechanisms that underlie the circadian dysfunction in PD remain elusive. Further research on circadian patterns is needed. This article summarizes the existing research on the circadian rhythms in PD, focusing on the clinical symptom variations, molecular changes, as well as the available treatment options.