The impact of chronic primary insomnia on the heart rate--EEG variability link

High-Frequency Heart Rate Variability Is Prospectively Associated With Sleep Complaints in a Healthy Working Cohort

OBJECTIVE

Vagus nerve functioning, as indexed by high-frequency heart rate variability (HF-HRV), has been implicated in a wide range of mental and physical health conditions, including sleep complaints. This study aimed to test associations between HF-HRV measured during sleep (sleep HF-HRV) and subjective sleep complaints 4 years later.

METHODS

One hundred forty-three healthy employees (91% male; MAge = 47.8 years [time 2], SD = 8.3 years) of an industrial company in Southern Germany completed the Jenkins Sleep Problems Scale, participated in a voluntary health assessment, and were given a 24-hour ambulatory heart rate recording device in 2007. Employees returned for a health assessment and completed the Jenkins Sleep Problems Scale 4 years later.

RESULTS

Hierarchical regression analyses showed that lower sleep HF-HRV measured in 2007 was associated with higher self-reported sleep complaints 4 years later after controlling for covariates (rab,c = -0.096, b = -0.108, 95% CI, -0.298 to 0.081, ΔR2 = 0.009, p = .050).

CONCLUSIONS

These data are the first to show that lower sleep HF-HRV predicted worse sleep 4 years later, highlighting the importance of vagus nerve functioning in adaptability and health.

The potential of biomarkers for diagnosing insomnia: Consensus statement of the WFSBP Task Force on Sleep Disorders

OBJECTIVES

Thus far, the diagnosis of insomnia is based on purely clinical criteria. Although a broad range of altered physiological parameters has been identified in insomniacs, the evidence to establish their diagnostic usefulness is very limited. Purpose of this WFSBP Task Force consensus paper is to systematically evaluate a series of biomarkers as potential diagnostic tools for insomnia.

METHODS

A newly created grading system was used for assessing the validity of various measurements in establishing the diagnosis of insomnia; these measurements originated from relevant studies selected and reviewed by experts.

RESULTS

The measurements with the highest diagnostic performance were those derived from psychometric instruments. Biological measurements which emerged as potentially useful diagnostic instruments were polysomnography-derived cyclic alternating pattern, actigraphy, and BDNF levels, followed by heart rate around sleep onset, deficient melatonin rhythm, and certain neuroimaging patterns (mainly for the activity of frontal and pre-frontal cortex, hippocampus and basal ganglia); yet, these findings need replication, as well as establishment of commonly accepted methodology and diagnostic cut-off points. Routine polysomnography, EEG spectral analysis, heart rate variability, skin conductance, thermoregulation, oxygen consumption, HPA axis, and inflammation indices were not shown to be of satisfactory diagnostic value.

CONCLUSIONS

Apart from psychometric instruments which are confirmed to be the gold standard in diagnosing insomnia, six biomarkers emerge as being potentially useful for this purpose.

Heart rate variability in patients with insomnia disorder: a systematic review and meta-analysis

BACKGROUND

Though logical inference based on small studies suggests that patients with insomnia have a blunted heart rate variability (HRV), this condition not been clearly shown. This meta-analysis aimed to determine whether or not HRV was impaired in patients with insomnia.

MATERIALS AND METHODS

We conducted a comprehensive literature search for studies that examined the association of HRV with insomnia disorder. HRV measures were extracted using the SDNN (time-domain measure, i.e., standard deviation of all NN intervals,) or the HF-norm (frequency-domain measure, i.e., high-frequency power normalized using total power). The effect size estimates of R_equivalent obtained from p values and sample size were synthesized.

RESULTS

We identified 17 studies with 921 participants. The pooled R_equivalent was 0.19 with 95% CI of 0.12 and 0.25 (p < 0.001), and there was no significant heterogeneity (I2 = 0.0%, p = 0.809). A p value of 0.075 corresponding to the R_equivalent of 0.19 was obtained, suggesting that blunted HRV was not significant in patients with insomnia disorder.

CONCLUSION

The current evidence did not confirm that HRV was reliably impaired in patients with insomnia disorder. Prospective studies using standard HRV measures are needed to clarify the HRV dynamics in different insomnia subtypes.

The First-Night Effect on the Instability of Stage N2: Evidence from the Activity of the Central and Autonomic Nervous Systems

A series of studies have suggested that stage N2 is vulnerable and strongly affected by the first-night effect (FNE). However, the neurophysiological mechanism underlying the vulnerability of stage N2 of the FNE has not been well examined. A total of 17 healthy adults (11 women and 6 men, mean age: 21.59 ± 2.12) underwent two nights of polysomnogram recordings in the sleep laboratory. We analyzed sleep structure and central and autonomic nervous system activity during stage N2 and applied the electroencephalographic (EEG) activation index (beta/delta power ratio) and heart rate variability to reflect changes in central and autonomic nervous system activity caused by the FNE. Correlation analyses were performed between EEG activation and heart rate variability. The results showed that EEG activation and high-frequency heart rate variability increased on the adaptation night (Night 1). Importantly, EEG activation was significantly associated with the percentage of stage N1, and the correlation between EEG activation and high-frequency heart rate variability decreased due to the FNE. These findings indicate that the FNE affects the instability of stage N2 by increasing central nervous system activity and uncoupling the activity between the central and autonomic nervous systems.

Acupuncture for hypertension with insomnia: Study protocol for a randomized, sham-controlled, subject-and-assessor-blinded trial

BACKGROUND

Previous studies show that insomnia and hypertension are closely related. Currently, intervention for hypertension with insomnia has become a research hotspot. Acupuncture, as a representative non-pharmaceutical therapy of traditional Chinese medicine (TCM), has been widely used in improving insomnia and hypertension. However, there are few clinical studies on acupuncture for hypertension with insomnia.

METHODS

A single-center, subject-and-assessor-blind, randomized, sham-controlled trial has been designed for a study to be conducted in Jiangsu Province Hospital of Chinese Medicine. Sixty eligible patients will be randomly assigned to the treatment group and the control group in a 1:1 ratio. The treatment group will receive acupuncture treatment, while the control group will receive sham acupuncture treatment. Both groups will be treated three times per week for 4 weeks. Data will be collected at baseline and after 4 weeks of treatment and analyzed by using SPSS 25.0. The primary outcome measures are sleep parameters of portable polysomnography before and after treatment. Secondary outcomes are Pittsburgh Sleep Quality Index, Insomnia Severity Index, home blood pressure, and heart rate variability.

DISCUSSION

This study aims to evaluate the efficacy of acupuncture using the portable polysomnography combined with sleep scales, and analyze heart rate variability to preliminarily explore the underlying mechanism of acupuncture on hypertension with insomnia. The trail, if proven to be effective, will provide strong scientific evidence to support acupuncture is effective to manage patients for hypertension with insomnia.

CLINICAL TRIAL REGISTRATION

ChiCTR2200059161.

Changes in physiological network connectivity of body system in narcolepsy during REM sleep

BACKGROUND

Narcolepsy is marked by pathologic symptoms including excessive daytime drowsiness and lethargy, even with sufficient nocturnal sleep. There are two types of narcolepsy: type 1 (with cataplexy) and type 2 (without cataplexy). Unlike type 1, for which hypocretin is a biomarker, type 2 narcolepsy has no adequate biomarker to identify the causality of narcoleptic phenomenon. Therefore, we aimed to establish new biomarkers for narcolepsy using the body's systemic networks.

METHOD

Thirty participants (15 with type 2 narcolepsy, 15 healthy controls) were included. We used the time delay stability (TDS) method to examine temporal information and determine relationships among multiple signals. We quantified and analyzed the network connectivity of nine biosignals (brainwaves, cardiac and respiratory information, muscle and eye movements) during nocturnal sleep. In particular, we focused on the differences in network connectivity between groups according to sleep stages and investigated whether the differences could be potential biomarkers to classify both groups by using a support vector machine.

RESULT

In rapid eye movement sleep, the narcolepsy group displayed more connections than the control group (narcolepsy connections: 24.47 ± 2.87, control connections: 21.34 ± 3.49; p = 0.022). The differences were observed in movement and cardiac activity. The performance of the classifier based on connectivity differences was a 0.93 for sensitivity, specificity and accuracy, respectively.

CONCLUSION

Network connectivity with the TDS method may be used as a biomarker to identify differences in the systemic networks of patients with narcolepsy type 2 and healthy controls.

Autonomic dysregulation and sleep homeostasis in insomnia

STUDY OBJECTIVES

Insomnia is common in older adults, and is associated with poor health, including cognitive impairment and cardio-metabolic disease. Although the mechanisms linking insomnia with these comorbidities remain unclear, age-related changes in sleep and autonomic nervous system (ANS) regulation might represent a shared mechanistic pathway. In this study, we assessed the relationship between ANS activity with indices of objective and subjective sleep quality in older adults with insomnia.

METHODS

Forty-three adults with chronic insomnia and 16 age-matched healthy sleeper controls were studied. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), objective sleep quality by electroencephalogram spectral components derived from polysomnography, and ANS activity by measuring 24-h plasma cortisol and norepinephrine (NE).

RESULTS

Sleep cycle analysis displayed lower slow oscillatory (SO: 0.5-1.25 Hz) activity in the first cycle in insomnia compared to controls. In insomnia, 24-h cortisol levels were higher and 24-h NE levels were lower than controls. In controls, but not in insomnia, there was a significant interaction between NE level during wake and SO activity levels across the sleep cycles, such that in controls but not in insomnia, NE level during wake was positively associated with the amount of SO activity in the first cycle. In insomnia, lower 24-h NE level and SO activity in the first sleep cycle were associated with poorer subjective sleep quality.

CONCLUSION

Dysregulation of autonomic activity may be an underlying mechanism that links objective and subjective measures of sleep quality in older adults with insomnia, and potentially contribute to adverse health outcomes.

Discrepancies in the Time Course of Sleep Stage Dynamics, Electroencephalographic Activity and Heart Rate Variability Over Sleep Cycles in the Adaptation Night in Healthy Young Adults

OBJECTIVE

The aim of the present study was to characterize the cyclic sleep processes of sleep-stage dynamics, cortical activity, and heart rate variability during sleep in the adaptation night in healthy young adults.

METHODS

Seventy-four healthy adults participated in polysomnographic recordings on two consecutive nights. Conventional sleep variables were assessed according to standard criteria. Sleep-stage continuity and dynamics were evaluated by sleep runs and transitions, respectively. These variables were compared between the two nights. Electroencephalographic and cardiac activities were subjected to frequency domain analyses. Cycle-by-cycle analysis was performed for the above variables in 34 subjects with four sleep cycles and compared between the two nights.

RESULTS

Conventional sleep variables reflected lower sleep quality in the adaptation night than in the experimental night. Bouts of stage N1 and stage N2 were shorter, and bouts of stage Wake were longer in the adaptation night than in the experimental night, but there was no difference in stage N3 or stage REM. The normalized transition probability from stage N2 to stage N1 was higher and that from stage N2 to N3 was lower in the adaptation night, whereas that from stage N3 to other stages did not differ between the nights. Cycle-by-cycle analysis revealed that sleep-stage distribution and cortical beta EEG power differed between the two nights in the first sleep cycle. However, the HF amplitude of the heart rate variability was lower over the four sleep cycles in the adaptation night than in the experimental night.

CONCLUSION

The results suggest the distinct vulnerability of the autonomic adaptation processes within the central nervous system in young healthy subjects while sleeping in a sleep laboratory for the first time.

Automatic identification of insomnia using optimal antisymmetric biorthogonal wavelet filter bank with ECG signals

Sleep is a fundamental human physiological activity required for adequate working of the human body. Sleep disorders such as sleep movement disorders, nocturnal front lobe epilepsy, insomnia, and narcolepsy are caused due to low sleep quality. Insomnia is one such sleep disorder where a person has difficulty in getting quality sleep. There is no definitive test to identify insomnia; hence it is essential to develop an automated system to identify it accurately. A few automated methods have been proposed to identify insomnia using either polysomnogram (PSG) or electroencephalogram (EEG) signals. To the best of our knowledge, we are the first to automatically detect insomnia using only electrocardiogram (ECG) signals without combining them with any other physiological signals. In the proposed study, an optimal antisymmetric biorthogonal wavelet filter bank (ABWFB) has been used, which is designed to minimize the joint duration-bandwidth localization (JDBL) of the underlying filters. The L₁-norm feature is computed from the various wavelet sub-bands coefficients of ECG signals. The L₁ norm features are fed to various supervised machine learning classifiers for the automated detection of insomnia. In this work, ECG recordings of seven insomnia patients and six normal subjects are used from the publicly available cyclic alternating pattern (CAP) sleep database. We created ten different subsets of ECG signals based on annotations of sleep-stages, namely wake (W), S1, S2, S3, S4, rapid eye moment (REM), light sleep stage (LSS), slow-wave sleep (SWS), non-rapid eye movement (NREM) and W + S1+S2+S3+S4+REM for the automated identification of insomnia. Our proposed ECG-based system obtained the highest classification accuracy of 97.87%, F1-score of 97.39%, and Cohen's kappa value of 0.9559 for K-nearest neighbour (KNN) with the ten-fold cross-validation strategy using ECG signals corresponding to the REM sleep stage. The support vector machine (SVM) yielded the highest value of 0.99 for area under the curve with the ten fold cross-validation corresponding to REM sleep stage.

High-resolution, relational, resonance-based, electroencephalic mirroring (HIRREM) improves symptoms and autonomic function for insomnia: A randomized, placebo-controlled clinical trial

INTRODUCTION

Effective insomnia interventions that also address autonomic dysregulation are lacking. We evaluate high-resolution, relational, resonance-based, electroencephalic mirroring (HIRREM® ), in a randomized, controlled clinical trial. HIRREM is a noninvasive, closed-loop, allostatic, acoustic stimulation neurotechnology, to support self-optimization of brain rhythms.

METHODS

One hundred and seven adults (mean age 45.7, SD ± 5.6, 73 women), with Insomnia Severity Index (ISI) scores of ≥15, received ten, 90-min sessions of HIRREM, with tones linked to brainwaves (LB, 56), or random tones not linked to brainwaves (NL, 51), as an active, sham placebo. Outcomes were obtained at enrollment (V1), 1-7 days (V2), 8-10 weeks (V3), and 16-18 weeks (V4) after intervention. Primary outcome was differential change in ISI from V1 to V3. Secondary measures assessed depression (BDI), anxiety (BAI), quality of life (EQ-5D), and a sleep diary. Ten minute recordings of HR and BP allowed analysis of heart rate variability (HRV) and baroreflex sensitivity (BRS).

RESULTS

Of 107 randomized, 101 completed the intervention. Intention-to-treat analysis (107) of change from V1 to V3 revealed a mean reduction of ISI in NL of -4.93 (SE ± 0.76) points, with additional, significant reduction of -2.05 points (0.74) in LB (total reduction of -6.98, p = .045). Additional reduction of -2.30 points (0.76) was still present in the LB at V4 (p = .058). Total ISI reduction from V1 to V4 was -5.90 points for NL and -7.93 points in LB. There were group differences (p < .05) for multiple HRV and BRS measures (rMSSD, SDNN, HF alpha, and Seq ALL), as well as total sleep time, sleep onset latency, and sleep efficiency. There were no serious adverse events.

CONCLUSIONS

Results of this controlled clinical trial showed clinically relevant reduction of insomnia symptoms with HIRREM, over, and above an active, sham control, with associated, durable improvement in autonomic cardiovascular regulation.

Stress, sleep, and autonomic function in healthy adolescent girls and boys: Findings from the NCANDA study

OBJECTIVES

Starting in adolescence, female sex is a strong risk factor for the development of insomnia. Reasons for this are unclear but could involve altered stress reactivity and/or autonomic nervous system (ANS) dysregulation, which are strongly associated with the pathophysiology of insomnia. We investigated sex differences in the effect of stress on sleep and ANS activity in adolescents, using the first night in the laboratory as an experimental sleep-related stressor.

DESIGN

Repeated measures (first night vs. a subsequent night) with age (older/younger) and sex (males/females) as between factors.

SETTING

Recordings were performed at the human sleep laboratory at SRI International.

PARTICIPANTS

One hundred six healthy adolescents (Age, mean ± SD: 15.2 ± 2.0 years; 57 boys).

MEASURES

Polysomnographic sleep, nocturnal heart rate (HR), and frequency-domain spectral ANS HR variability (HRV) indices.

RESULTS

Boys and girls showed a first-night effect, characterized by lower sleep efficiency, lower %N1 and %N2 sleep, more wake after sleep onset and %N3 sleep, altered sleep microstructure (increased high-frequency sigma and Beta1 electroencephalographic activity), and reduced vagal activity (P < .05) on the first laboratory night compared to a subsequent night. The first night ANS stress effect (increases in HR and suppression in vagal HRV during rapid eye movement sleep) was greater in girls than boys (P < .05).

CONCLUSIONS

Sleep and ANS activity were altered during the first laboratory night in adolescents, with girls exhibiting greater ANS alterations than boys. Findings suggest that girls may be more vulnerable than boys to sleep-specific stressors, which could contribute to their increased risk for developing stress-related sleep disturbances.

Information Transfer in Linear Multivariate Processes Assessed through Penalized Regression Techniques: Validation and Application to Physiological Networks

The framework of information dynamics allows the dissection of the information processed in a network of multiple interacting dynamical systems into meaningful elements of computation that quantify the information generated in a target system, stored in it, transferred to it from one or more source systems, and modified in a synergistic or redundant way. The concepts of information transfer and modification have been recently formulated in the context of linear parametric modeling of vector stochastic processes, linking them to the notion of Granger causality and providing efficient tools for their computation based on the state-space (SS) representation of vector autoregressive (VAR) models. Despite their high computational reliability these tools still suffer from estimation problems which emerge, in the case of low ratio between data points available and the number of time series, when VAR identification is performed via the standard ordinary least squares (OLS). In this work we propose to replace the OLS with penalized regression performed through the Least Absolute Shrinkage and Selection Operator (LASSO), prior to computation of the measures of information transfer and information modification. First, simulating networks of several coupled Gaussian systems with complex interactions, we show that the LASSO regression allows, also in conditions of data paucity, to accurately reconstruct both the underlying network topology and the expected patterns of information transfer. Then we apply the proposed VAR-SS-LASSO approach to a challenging application context, i.e., the study of the physiological network of brain and peripheral interactions probed in humans under different conditions of rest and mental stress. Our results, which document the possibility to extract physiologically plausible patterns of interaction between the cardiovascular, respiratory and brain wave amplitudes, open the way to the use of our new analysis tools to explore the emerging field of Network Physiology in several practical applications.

Major depressive disorder and insomnia: Exploring a hypothesis of a common neurological basis using waking and sleep-derived heart rate variability

It remains unclear whether neurobiological dysfunction observed in major depressive disorder (MDD) and insomnia is an expression of common or independent bases. The present investigation sought to explore differences in heart rate variability (HRV)-a widely utilized biomarker of neurobiological functioning-among individuals with MDD, insomnia, and healthy controls, while awake and during distinct sleep stages (REM, N2), with the goal of improving our understanding of shared neurobiological factors in depression and insomnia. Participants were 73 adults who underwent home polysomnography. All N2 and REM sleep epochs with a duration greater than or equal to 5 min were identified for HRV analysis. Additionally, a single waking epoch was defined for each participant. From waking to N2 sleep, and waking to REM sleep, changes in HRV indices indicated participants experienced reductions in sympathetic arousal and increases in parasympathetic arousal. Contrary to hypotheses, however, no between group differences were observed in HRV. Though the present findings do not support the hypotheses of a shard neurobiological pathway between MDD and insomnia, more work is warranted to advance our understanding of the neurobiological bases of these common, debilitating, and frequently co-occurring psychiatric conditions, to improve early detection and identify novel intervention targets for these disorders.

Increased glymphatic influx is correlated with high EEG delta power and low heart rate in mice under anesthesia

The glymphatic system is responsible for brain-wide delivery of nutrients and clearance of waste via influx of cerebrospinal fluid (CSF) alongside perivascular spaces and through the brain. Glymphatic system activity increases during sleep or ketamine/xylazine (K/X) anesthesia, yet the mechanism(s) facilitating CSF influx are poorly understood. Here, we correlated influx of a CSF tracer into the brain with electroencephalogram (EEG) power, heart rate, blood pressure, and respiratory rate in wild-type mice under six different anesthesia regimens. We found that glymphatic CSF tracer influx was highest under K/X followed by isoflurane (ISO) supplemented with dexmedetomidine and pentobarbital. Mice anesthetized with α-chloralose, Avertin, or ISO exhibited low CSF tracer influx. This is the first study to show that glymphatic influx correlates positively with cortical delta power in EEG recordings and negatively with beta power and heart rate.

Clinical neurophysiology of postural tachycardia syndrome

Postural tachycardia syndrome (POTS) is one of several disorders of orthostatic intolerance (OI). It is defined by the development of symptoms of cerebral hypoperfusion or sympathetic activation and a sustained heart rate increment of 30 beats/min or more (40 beats/min for teenagers) within 10min of standing or head-up tilt in the absence of orthostatic hypotension; the standing heart rate is often 120 beats/min or higher. POTS is approximately five times more common in women than men. This heterogeneous syndrome is caused by several pathophysiologic mechanisms (limited autonomic neuropathy, hyperadrenergic state, hypovolemia, venous pooling, deconditioning), which are not mutually exclusive. Anxiety and somatic hypervigilance play significant roles in POTS. Common comorbidities include visceral pain and dysmotility, chronic fatigue and fibromyalgia, migraine, joint hypermobility, mitral valve prolapse, and inappropriate sinus tachycardia. Patients with suspected POTS should undergo comprehensive cardiac and neurologic examinations and autonomic and laboratory tests to determine the most likely pathophysiologic basis of OI. The objectives of POTS management are to (1) increase the time that patients can stand, perform daily activities, and exercise and (2) avoid syncope. Management involves nonpharmacologic (fluid and salt loading, physical countermaneuvers, compression garments, exercise training) and pharmacologic (β-blockers, pyridostigmine, fludrocortisone, midodrine) approaches.

Associations of Insomnia Symptoms With Blood Pressure and Resting Heart Rate: The HUNT Study in Norway

OBJECTIVE

Although elevated heart rate and blood pressure might represent biologically plausible links for the association of insomnia symptoms with increased risk of cardiovascular disease (CVD), few large studies have investigated the associations of insomnia symptoms with these factors. Our aim was to investigate the associations of self-reported insomnia symptoms with systolic and diastolic blood pressure and resting heart rate in a large population-based study.

PARTICIPANTS

Self-reported information on insomnia symptoms, including sleep initiation problems, frequent awakening and early awakenings during night, and measurements of resting heart rate and blood pressure were collected from a total of 50,806 men and women who participated in the third wave of the Nord-Trøndelag Health Study (HUNT-3) in 2006-2008.

METHODS

In multivariable analyses, we adjusted for sociodemographic factors, lifestyle factors, established CVD risk factors, and snoring or breathing pauses.

RESULTS

Compared to participants reporting none of the insomnia symptoms, those having all three insomnia symptoms several times a week had lower diastolic blood pressure (-0.80 [95% CI: -1.47 to -0.14] mmHg, p = 0.02), lower systolic blood (-1.69 [95% CI: -2.76 to -0.63) mmHg, p < 0.001), and higher resting heart rate (0.83 [95% CI: 0.11 to 1.55] beats/minute, p = 0.02).

CONCLUSIONS

We found a modest positive association of insomnia symptoms with resting heart rate, and a modest inverse association of insomnia with blood pressure. However, the actual differences were small, and likely of less clinical importance. Prospective studies are needed to establish whether the potential link between insomnia and CVD is mediated through changes in heart rate and/or blood pressure.

Dynamic coupling between the central and autonomic nervous systems during sleep: A review

Sleep is characterized by coordinated cortical and cardiac oscillations reflecting communication between the central (CNS) and autonomic (ANS) nervous systems. Here, we review fluctuations in ANS activity in association with CNS-defined sleep stages and cycles, and with phasic cortical events during sleep (e.g., arousals, K-complexes). Recent novel analytic methods reveal a dynamic organization of integrated physiological networks during sleep and indicate how multiple factors (e.g., sleep structure, age, sleep disorders) affect "CNS-ANS coupling". However, these data are mostly correlational and there is a lack of clarity of the underlying physiology, making it challenging to interpret causality and direction of coupling. Experimental manipulations (e.g., evoking K-complexes or arousals) provide information on the precise temporal sequence of cortical-cardiac activity, and are useful for investigating physiological pathways underlying CNS-ANS coupling. With the emergence of new analytical approaches and a renewed interest in ANS and CNS communication during sleep, future work may reveal novel insights into sleep and cardiovascular interactions during health and disease, in which coupling could be adversely impacted.

Sleep: important considerations for the prevention of cardiovascular disease

PURPOSE OF REVIEW

Sleep plays many roles in maintenance of cardiovascular health. This review summarizes the literature across several areas of sleep and sleep disorders in relation to cardiometabolic disease risk factors.

RECENT FINDINGS

Insufficient sleep duration is prevalent in the population and is associated with weight gain and obesity, inflammation, cardiovascular disease, diabetes, and mortality. Insomnia is also highly present and represents an important risk factor for cardiovascular disease, especially when accompanied by short sleep duration. Sleep apnea is a well-characterized risk factor for cardiometabolic disease and cardiovascular mortality. Other issues are relevant as well. For example, sleep disorders in pediatric populations may convey cardiovascular risks. Also, sleep may play an important role in cardiovascular health disparities.

SUMMARY

Sleep and sleep disorders are implicated in cardiometabolic disease risk. This review addresses these and other issues, concluding with recommendations for research and clinical practice.

Altered nocturnal blood pressure profiles in women with insomnia disorder in the menopausal transition

OBJECTIVE

Insomnia disorder is a risk factor for cardiovascular (CV) pathology. It is unknown whether insomnia that develops in the context of the menopausal transition (MT) impacts the CV system. We assessed nocturnal blood pressure (BP) and heart rate (HR) profiles in women with insomnia disorder in the MT.

METHODS

Twelve women meeting DSM-IV criteria for insomnia in the MT (age, mean ± SD: 50.5 ± 3.6 y) and 11 controls (age, mean ± SD: 49.0 ± 3.0 y) had polysomnographic recordings on one or two nights during which beat-to-beat BP and HR were assessed and analyzed hourly from lights-out across the first 6 hours of the night and according to sleep stage. Physiological hot flashes were identified from fluctuations in sternal skin conductance.

RESULTS

Women with insomnia and controls had similar distributions of sleep stages and awakenings/arousals across hours of the night, although insomnia participants tended to have more wakefulness overall. More women in the insomnia group (7 of 12) than in the control group (2 of 11) had at least one physiological hot flash at night (P < 0.05). Both groups showed a drop in BP in the first part of the night; however, systolic and diastolic BP patterns diverged later, remaining low in controls but increasing in insomnia participants 4 to 6 hours after lights-out (P < 0.05). Both groups showed a similar pattern of decline in HR across the night.

CONCLUSIONS

Our findings suggest altered regulatory control of BP during sleep in the MT insomnia. The causes and long-term consequences of this altered nocturnal BP profile remain to be determined.

Measures of cardiovascular autonomic activity in insomnia disorder: A systematic review

BACKGROUND

Insomnia disorder is a widespread sleep disorder with a prevalence of approximately 10%. Even though the link between insomnia and cardiovascular activity is not exactly clear, it is generally assumed that cardiovascular autonomic modifications could occur as a result of sleeplessness, or, alternatively, that autonomic alterations could be an expression of a hyper-arousal state. This review investigates whether cardiovascular measures are different between insomniacs and controls.

METHODS

Electronic databases were systematically searched, and 34 studies were identified. Heart rate variability features, the association of cardiac and EEG activity, physiologic complexity measures, and cardiovascular activity, assessed by measures such as pre-ejection time, blood pressure, and heart rate dynamics were studied. Given the heterogeneity of the studies, a narrative synthesis of the findings was performed.

RESULTS

This review study found overall differences in cardiovascular activity between insomniacs and controls in most of the observational studies (21/26), while the expression of cardiovascular regulation varied between the examined insomniac groups. All the studies that investigated the association of cardiac activity and EEG power reported an altered relation between autonomic activity and EEG parameters in insomniacs.

CONCLUSION

Autonomic regulation tends to be consistent between insomniacs, as long as they are grouped according to their respective phenotype, as shown in the insomnia subgroup with objectively short sleep duration. Our hypothesis is that these differences in the expression of cardiovascular activity could be explained by the heterogeneity of the disorder. Therefore, the determination of insomnia phenotypes, and the study of cardiovascular measures, rather than heart rate variability alone, will give more insight into the link between insomnia and cardiovascular regulation. This study suggests that cardiovascular activity differs between insomniacs and controls. These new findings are of interest to clinicians and researchers for a more accurate insomnia assessment, and the development of personalized technological solutions in insomnia.

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Three vigilance states dominate mammalian life: wakefulness, non-rapid eye movement (non-REM) sleep, and REM sleep. As more neural correlates of behavior are identified in freely moving animals, this three-fold subdivision becomes too simplistic. During wakefulness, ensembles of global and local cortical activities, together with peripheral parameters such as pupillary diameter and sympathovagal balance, define various degrees of arousal. It remains unclear the extent to which sleep also forms a continuum of brain states-within which the degree of resilience to sensory stimuli and arousability, and perhaps other sleep functions, vary gradually-and how peripheral physiological states co-vary. Research advancing the methods to monitor multiple parameters during sleep, as well as attributing to constellations of these functional attributes, is central to refining our understanding of sleep as a multifunctional process during which many beneficial effects must be executed. Identifying novel parameters characterizing sleep states will open opportunities for novel diagnostic avenues in sleep disorders. We present a procedure to describe dynamic variations of mouse non-REM sleep states via the combined monitoring and analysis of electroencephalogram (EEG)/electrocorticogram (ECoG), electromyogram (EMG), and electrocardiogram (ECG) signals using standard polysomnographic recording techniques. Using this approach, we found that mouse non-REM sleep is organized into cycles of coordinated neural and cardiac oscillations that generate successive 25-s intervals of high and low fragility to external stimuli. Therefore, central and autonomic nervous systems are coordinated to form behaviorally distinct sleep states during consolidated non-REM sleep. We present surgical manipulations for polysomnographic (i.e., EEG/EMG combined with ECG) monitoring to track these cycles in the freely sleeping mouse, the analysis to quantify their dynamics, and the acoustic stimulation protocols to assess their role in the likelihood of waking up. Our approach has already been extended to human sleep and promises to unravel common organizing principles of non-REM sleep states in mammals.

Hyperarousal during sleep in untreated primary insomnia sufferers: A polysomnographic study

Because some evidence favors the hyperarousal model of insomnia, we sought to learn more about the dynamics of this phenomenon during sleep. Polysomnographic data from 30 normative subjects and 86 untreated primary insomnia sufferers recruited from the database of the sleep laboratory were studied for whole nights and in terms of thirds of the night. Untreated primary insomnia sufferers had an increased sleep latency and excess of WASO, together with a deficit in REM and NREM sleep during the entire night. In terms of thirds of the night, they presented a major excess of WASO during the first and last thirds of the night but an excess of lesser importance during the middle third. A deficit in SWS was found during the first third of the night, but for REM, the deficit was present during both the first and last thirds. Primary insomnia sufferers had no SWS or REM deficit during the second third of the night. We found that the hyperarousal phenomenon occurs mainly during the sleep-onset period of the first and last thirds of the night and is less important during the middle third. These results open new avenues for understanding the pathophysiology of primary insomnia.

Post-infarct sleep disruption and its relation to cardiac remodeling in a rat model of myocardial infarction

Sleep disruption after myocardial infarction (MI) by affecting ubiquitin-proteasome system (UPS) is thought to contribute to myocardial remodeling and progressive worsening of cardiac function. The aim of current study was to test the hypothesis about the increased risk of developing heart failure due to experience of sleep restriction (SR) after MI. Male Wistar rats (n = 40) were randomly assigned to four experimental groups: (1) Sham, (2) MI, (3) MI and SR (MI + SR) (4) Sham and SR (Sham + SR). MI was induced by permanent ligation of left anterior descending coronary artery. Twenty-four hours after surgery, animals were subjected to chronic SR paradigm. Blood sampling was performed at days 1, 8 and 21 after MI for determination of serum levels of creatine kinase-MB (CK-MB), corticosterone, malondialdehyde (MDA) and nitric oxide (NO). Finally, at 21 days after MI, echocardiographic parameters and expression of MuRF1, MaFBx, A20, eNOS, iNOS and NF-kB in the heart were evaluated. We used H&E staining to detect myocardial hypertrophy. We found out that post infarct SR increased corticosterone levels. Our results highlighted deteriorating effects of post-MI SR on NO production, oxidative stress, and echocardiographic indexes (p < 0.05). Moreover, its detrimental effects on myocardial damage were confirmed by overexpression of MuRF1, MaFBx, iNOS and NF-kB (p < 0.001) in left ventricle and downregulation of A20 and eNOS (p < 0.05). Furthermore, histological examination revealed that experience of SR after MI increased myocardial diameter as compared to Sham subjects (p < 0.05). Our data suggest that SR after MI leads to an enlargement of the heart within 21 days, marked by an increase in oxidative stress and NO production as well as an imbalance in UPS that ultimately results in cardiac dysfunction and heart failure.

Searching arousals: A fuzzy logic approach

This paper presents a computational approach to detect spontaneous, chin tension and limb movement-related arousals by estimating neuronal and muscular activity. Features extraction is carried out by Time Varying Autoregressive Moving Average (TVARMA) models and recursive particle filtering. Classification is performed by a fuzzy inference system with rule-based decision scheme based upon the AASM scoring rules. Our approach yielded two metrics: arousal density and arousal index to comply with standardised clinical benchmarking. The obtained statistics achieved error deviation around ±1.5 to ±30. These results showed that our system can differentiate amongst 3 different types of arousals, subject to inter-subject variability and up-to-date scoring references.

Sleep electroencephalography and heart rate variability interdependence amongst healthy subjects and insomnia/schizophrenia patients

The quantification of interdependencies within autonomic nervous system has gained increasing importance to characterise healthy and psychiatric disordered subjects. The present work introduces a biosignal processing approach, suggesting a computational resource to estimate coherent or synchronised interactions as an eventual supportive aid in the diagnosis of primary insomnia and schizophrenia pathologies. By deploying linear, nonlinear and statistical methods upon 25 electroencephalographic and electrocardiographic overnight sleep recordings, the assessment of cross-correlation, wavelet coherence and [Formula: see text]:[Formula: see text] phase synchronisation is focused on tracking discerning features amongst the clinical cohorts. Our results indicate that certain neuronal oscillations interact with cardiac power bands in distinctive ways responding to standardised sleep stages and patient groups, which promotes the hypothesis of subtle functional dynamics between neuronal assembles and (para)sympathetic activity subject to pathophysiological conditions.

Time-varying correlations between delta EEG power and heart rate variability in midlife women: the SWAN Sleep Study

No studies have evaluated the dynamic, time-varying relationship between delta electroencephalographic (EEG) sleep and high frequency heart rate variability (HF-HRV) in women. Delta EEG and HF-HRV were measured during sleep in 197 midlife women (M(age)  = 52.1, SD = 2.2). Delta EEG-HF-HRV correlations in nonrapid eye movement (NREM) sleep were modeled as whole-night averages and as continuous functions of time. The whole-night delta EEG-HF-HRV correlation was positive. The strongest correlations were observed during the first NREM sleep period preceding and following peak delta power. Time-varying correlations between delta EEG-HF-HRV were stronger in participants with sleep-disordered breathing and self-reported insomnia compared to healthy controls. The dynamic interplay between sleep and autonomic activity can be modeled across the night to examine within- and between-participant differences including individuals with and without sleep disorders.

REM sleep as a potential indicator of hyperarousal in psychophysiological and paradoxical insomnia sufferers

STUDY OBJECTIVES

The objective was to study REM sleep macrostructure and microstructure as potential indicators of hyperarousal in insomnia by comparing good sleepers (GS) and insomnia sufferers (INS) (subdivided into psychophysiological "PSY-I" and paradoxical "PARA-I").

DESIGN

Cross-sectional comparisons of GS, PSY-I and PARA-I.

SETTING

Participants slept for 4 consecutive nights in the laboratory where PSG was recorded. Nights 2 and 3 were combined to compare REM sleep between groups.

PARTICIPANTS

Thirty-nine PSY-I, 27 PARA-I and 47 GS completed the study, comprising home questionnaires, clinical interviews and night PSG recordings. All participants were aged between 25 and 55 and met inclusion criteria for either PSY-I, PARA-I or GS.

INTERVENTIONS N/A MEASUREMENTS AND RESULTS

Results showed no between group differences on REM sleep macrostructure. As for REM sleep microstructure, PSY-I had an increased number of wake intrusions compared to PARA-I (p=.03). Subjective SE, TST and TWT were significantly correlated with the duration of REM sleep (REMD; p≤.002) and with the proportion of REM sleep for PARA-I (p≤.06).

CONCLUSIONS

REM sleep macrostructure does not seem to be an adequate indicator of hyperarousal in insomnia. However, the number of wake intrusions in REM could be used to differentiate PSY-I from PARA-I and could reflect the heightened arousal of the former group. Relationships between REM sleep duration and proportion could be linked to dream imagery activity, especially in PARA-I. Further investigations are needed to identify variables that could reflect hyperarousal and differentiate insomnia types.

Heart rate and heart rate variability modification in chronic insomnia patients

Chronic insomnia is highly prevalent in the general population, provoking personal distress and increased risk for psychiatric and medical disorders. Autonomic hyper-arousal could be a pathogenic mechanism of chronic primary insomnia. The aim of this study was to investigate autonomic activity in patients with chronic primary insomnia by means of heart rate variability (HRV) analysis. Eighty-five consecutive patients affected by chronic primary insomnia were enrolled (38 men and 47 women; mean age: 53.2 ± 13.6). Patients were compared with a control group composed of 55 healthy participants matched for age and gender (23 men and 32 women; mean age: 54.2 ± 13.9). Patients underwent an insomnia study protocol that included subjective sleep evaluation, psychometric measures, and home-based polysomnography with evaluation of HRV in wake before sleep, in all sleep stages, and in wake after final awakening. Patients showed modifications of heart rate and HRV parameters, consistent with increased sympathetic activity, while awake before sleep and during Stage-2 non-REM sleep. No significant differences between insomniacs and controls could be detected during slow-wave sleep, REM sleep, and post-sleep wake. These results are consistent with the hypothesis that autonomic hyper-arousal is a major pathogenic mechanism in primary insomnia, and confirm that this condition is associated with an increased cardiovascular risk.

Nocturnal cardiac autonomic profile in young primary insomniacs and good sleepers

We investigated cardiac vagal and sympathetic activity in 13 young primary insomniacs (PI; 24.4±1.6years) and 14 good sleepers (GS; 23.3±2.5years) during nocturnal sleep. Pre-ejection period (PEP; inversely related to beta-adrenergic sympathetic activity), interval between consecutive R-waves (RR), and vagal-related indices of time- and frequency-domain heart rate variability were computed during pre-sleep wakefulness and undisturbed arousal-free sleep stages (N2, SWS, REM) as well as across the whole night irrespective of the presence of disruptive sleep events (e.g. sleep arousals/awakenings) and/or sleep stage transitions. Groups exhibited a similar vagal activity throughout each undisturbed sleep stage as well as considering the whole night, with a higher modulation during sleep compared to prior wakefulness. However, PEP was constantly shorter (higher sympathetic activity) during pre-sleep wakefulness and each sleep stage in PI compared to GS. Moreover, pre-sleep RR intervals were positively associated with sleep efficiency and negatively associated with wake after sleep onset in PI. Altogether our findings indicated a dysfunctional sympathetic activity but a normal parasympathetic modulation before and during sleep in young adults with insomnia.

Complexity analysis of sleep and alterations with insomnia based on non-invasive techniques

For the first time, fractal analysis techniques are implemented to study the correlations present in sleep actigraphy for individuals suffering from acute insomnia with comparisons made against healthy subjects. Analysis was carried out for 21 healthy individuals with no diagnosed sleep disorders and 26 subjects diagnosed with acute insomnia during night-time hours. Detrended fluctuation analysis was applied in order to look for 1/f-fluctuations indicative of high complexity. The aim is to investigate whether complexity analysis can differentiate between people who sleep normally and people who suffer from acute insomnia. We hypothesize that the complexity will be higher in subjects who suffer from acute insomnia owing to increased night-time arousals. This hypothesis, although contrary to much of the literature surrounding complexity in physiology, was found to be correct-for our study. The complexity results for nearly all of the subjects fell within a 1/f-range, indicating the presence of underlying control mechanisms. The subjects with acute insomnia displayed significantly higher correlations, confirmed by significance testing-possibly a result of too much activity in the underlying regulatory systems. Moreover, we found a linear relationship between complexity and variability, both of which increased with the onset of insomnia. Complexity analysis is very promising and could prove to be a useful non-invasive identifier for people who suffer from sleep disorders such as insomnia.

Linear and non-linear interdependence of EEG and HRV frequency bands in human sleep

The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests upon 10 overnight polysomnographic (PSG) recordings, allowed the computation of wavelet coherence and phase locking values, in order to identify discerning features amongst the clinical healthy subjects. Our findings showed that neuronal oscillations θ, α and σ interact with cardiac power bands at mid-to-high rank of coherence and phase locking, particularly during NREM sleep stages.

Relation between heart beat fluctuations and cyclic alternating pattern during sleep in insomnia patients

Insomnia is a condition that affects the nervous and muscular system. Thirty percent of the population between 18 and 60 years suffers from insomnia. The effects of this disorder involve problems such as poor school or job performance and traffic accidents. In addition, patients with insomnia present changes in the cardiac function during sleep. Furthermore, the structure of electroencephalographic A-phases, which builds up the Cyclic Alternating Pattern during sleep, is related to the insomnia events. Therefore, the relationship between these brain activations (A-phases) and the autonomic nervous system would be of interest, revealing the interplay of central and autonomic activity during insomnia. With this goal, a study of the relationship between A-phases and heart rate fluctuations is presented. Polysomnography recording of five healthy subjects, five sleep misperception patients and five patients with psychophysiological insomnia were used in the study. Detrended Fluctuation Analysis (DFA) was used in order to evaluate the heart rate dynamics and this was correlated with the number of A-phases. The results suggest that pathological patients present changes in the dynamics of the heart rate. This is reflected in the modification of A-phases dynamics, which seems to modify of heart rate dynamics.

Heart rate variability in normal and pathological sleep

Sleep is a physiological process involving different biological systems, from molecular to organ level; its integrity is essential for maintaining health and homeostasis in human beings. Although in the past sleep has been considered a state of quiet, experimental and clinical evidences suggest a noteworthy activation of different biological systems during sleep. A key role is played by the autonomic nervous system (ANS), whose modulation regulates cardiovascular functions during sleep onset and different sleep stages. Therefore, an interest on the evaluation of autonomic cardiovascular control in health and disease is growing by means of linear and non-linear heart rate variability (HRV) analyses. The application of classical tools for ANS analysis, such as HRV during physiological sleep, showed that the rapid eye movement (REM) stage is characterized by a likely sympathetic predominance associated with a vagal withdrawal, while the opposite trend is observed during non-REM sleep. More recently, the use of non-linear tools, such as entropy-derived indices, have provided new insight on the cardiac autonomic regulation, revealing for instance changes in the cardiovascular complexity during REM sleep, supporting the hypothesis of a reduced capability of the cardiovascular system to deal with stress challenges. Interestingly, different HRV tools have been applied to characterize autonomic cardiac control in different pathological conditions, from neurological sleep disorders to sleep disordered breathing (SDB). In summary, linear and non-linear analysis of HRV are reliable approaches to assess changes of autonomic cardiac modulation during sleep both in health and diseases. The use of these tools could provide important information of clinical and prognostic relevance.

Inattentive and hyperactive preschool-age boys have lower sympathetic and higher parasympathetic activity

The presented study aimed to clarify the relationship between the autonomic nervous system and disruptive behaviors among preschoolers. Possible gender differences in autonomic activity were also examined. A total of 88 preschool-age children were enrolled in this study. Autonomic activities were measured by power spectrum analysis of heart rate variability (HRV). The Swanson, Nolan and Pelham parents and teachers rating scale (SNAP-IV) was applied to evaluate each subject's severity of disruptive behavior. The relationship between the HRV results and the SNAP-IV was evaluated by correlation analysis, which disclosed that the scores for inattention, hyperactivity/impulsivity and oppositional defiant disorder showed a negative association with LF % and LF/HF. The above scales, except for the hyperactivity subscale, also showed a positive association with HF. On separating the two genders, only boys showed the above correlations. Preschool-age boys who show more inattentive and hyperactive features have lower sympathetic and higher parasympathetic activity.

Cardiac autonomic impairment during sleep is linked with disease severity in Parkinson's disease

OBJECTIVE

Cardiac physiology during sleep in Parkinson's disease (PD) remains poorly explored. We studied heart rate variability (HRV) across sleep stages in PD patients and correlated the results with clinical features.

METHODS

Cross-sectional study comprising 33 patients with PD and 29 controls matched for age, gender, and number of apneas/hypopneas per hour. HRV measures, (mean R-R interval, SDNN, ULF, VLF, LF, HF and LF/HF) were calculated separately for all sleep stages as well as wakefulness just before and after sleep during one-night polysomnography. Correlation analysis was performed between HRV values and PD patients' characteristics.

RESULTS

The mean R-R interval was lower in all sleep stages in PD patients when compared with controls. VLF and LF were lower during REM sleep in PD patients. HF during N1-N2 stage was higher in PD. We found inverse correlations between VLF and LF during REM sleep and UPDRS-ON and UPDRS-OFF.

CONCLUSION

VLF and LF during REM sleep might constitute surrogate markers of disease severity.

SIGNIFICANCE

These findings provide additional clinical evidence of the autonomic impairment commonly observed in PD, and prove that cardiac autonomic dysfunction during REM sleep is correlated with disease severity.