Abstract
Study Objectives:
Autonomic nervous system (ANS) dysfunction is common in chronic fatigue syndrome (CFS). One of the main complaints in CFS is unrefreshing sleep. We aimed to study the nocturnal cardiac ANS in different sleep stages in patients filling the 2015 Institute of Medicine CFS diagnostic criteria.
Methods:
In this case series study, the nocturnal heart rate variability and blood pressure (BP) variables in polysomnography were studied in groups of patients with CFS (n = 8) and tired controls (n = 8) aged 16–49 years. Five of the patients with CFS and controls were female. The heart rate variability and BP parameters and heart rate were studied in all sleep stages and wake.
Results:
The amount of low-frequency oscillations of the electrocardiography R-R-intervals spectra (LF; predominantly reflects sympathetic activity) was higher for patients with CFS in all sleep stages compared to controls (P < .001). During wake, the amount of LF was lower for the patients with CFS (P < .05). The amount of high-frequency oscillations (HF; reflects parasympathetic activity) was lower in stage N3 sleep in the patients with CFS than for the controls (P < .0001), but, in total, HF was higher in patients with CFS (P < .001). Patients with CFS had higher overall nocturnal systolic and mean BP (P < .0001) and lower heart rate (P < .0001) than controls. No significant differences were found in sleep stage distributions.
Conclusions:
The results suggest a nocturnal dysfunction of the cardiac ANS in CFS, presenting as lower parasympathetic tone in deep sleep and higher sympathetic tone asleep.
Citation:
Orjatsalo M, Alakuijala A, Partinen M. Autonomic nervous system functioning related to nocturnal sleep in patients with chronic fatigue syndrome compared to tired controls. J Clin Sleep Med. 2018;14(2):163–171.
Keywords: autonomic nervous system, blood pressure, chronic fatigue syndrome, dysautonomia, heart rate variability, polysomnography, sleep, systemic exertion intolerance disease
BRIEF SUMMARY
Current Knowledge/Study Rationale: Patients with chronic fatigue syndrome (CFS) often suffer from unrefreshing sleep, even if their sleep recordings show normal sleep stage distribution and sleep microstructure. Heart rate variability is a noninvasive method to assess nocturnal cardiac autonomic nervous system functioning.
Study Impact: Our results suggest that patients with CFS have lower parasympathetic tone in deep sleep and higher sympathetic tone in all sleep stages compared to tired controls. Detachment of parasympathetic tone and deep sleep might be contributing to nonrestorative sleep and even symptoms of cognitive impairment in patients with CFS.
INTRODUCTION
Chronic fatigue syndrome (CFS) is a controversial but serious and debilitating condition with a prevalence of 0.06% to 6.40% when diagnosed with the 1994 Fukuda Case Definition Criteria, and 0.11% when using the Canadian Consensus Criteria of 2003 for diagnosis.1–3 In 2015, Institute of Medicine (IOM) introduced new diagnostic criteria for CFS and recommended a new name for the entity, systemic exertion intolerance disease, and a new status as a disease opposed to its previous appellation as a syndrome.4 The key manifestations of CFS are fatigue, postexertional physical or cognitive malaise, orthostatic intolerance and autonomic dysfunction, and subjective sleep disturbances: insomnia and unrefreshing sleep, and neurocognitive manifestations.4–7 According to the new IOM criteria, objectively measured orthostatic intolerance and/or cognitive impairment is required.
Heart rate variability (HRV) is a noninvasive method to assess cardiac autonomic nervous system (ANS) functioning.8 Heart rate (HR) has a constant beat-to-beat temporal variation affected by the autonomic sympathetic beta 1 adrenergic receptor and parasympathetic muscarinic 2 acetylcholine receptor mediated regulation influencing the sinus node.9 The sympathetic system prepares the body for energy expenditure, exercise, emergency, or stressful situations, whereas the para-sympathetic system is most active under restful conditions and restores the body.9 Beat-to-beat R-R-interval analysis of the HRV is a good measurement of the parasympathetic nervous system (high-frequency oscillations, HF), but the method is not so well validated in assessing the sympathetic nervous system (low-frequency oscillations, LF, or sympathovagal balance [SVB, LF/HF]).8,10 LF and LF/HF are assumed to, at least predominantly, represent sympathetic activity. HF, LF, and LF/ HF have good intraindividual reproducibility.11
There is growing evidence of ANS dysfunction (ie, dysautonomia) in CFS,4,12 and symptoms of ANS dysfunction are prominent in those with CFS.7 Furthermore, patients with CFS present with cardiac alterations including smaller cardiac size,4 vascular endothelial cell dysfunction,13 and decreased cardiac index compared to healthy controls.4 A subgroup of patients with CFS have elevated antibodies against one or more muscarinic acetylcholine and beta (β) adrenergic receptors,14,15 in addition to cerebral cytokine dysregulation16,17 and evidence of neuroinflammation and natural killer cell dysfunction.4 Reduced cerebral blood flow,18,19 impaired postural cerebral oxygenation,20 and altered brain stem sympathetic and para-sympathetic signaling areas21 are found in patients with CFS compared to healthy controls. The alleged prefrontal cortex gray matter volume reduction in CFS might be associated with dysfunction in ANS and sleep.12,22 In addition, evidence of CFS as a hypometabolic state has been presented.23 Further, patients with CFS urinary free cortisol excretion might be lower than in healthy controls,4,24 suggesting an additional hypothalamic-pituitary-adrenal axis dysfunction.
Daytime LF (representing sympathetic activity) was significantly increased in Fukuda-diagnosed patients with CFS compared to controls, whereas parasympathetic markers were significantly reduced in one study,25 but a review concluded that there was no significant difference in daytime resting autonomic functioning in patients with CFS compared to controls.26
The role of the nocturnal ANS in CFS has been disputed for years,12,26,27 yet studies with polysomnography (PSG) recording combined with HRV analysis are extremely scarce.28 Nocturnal parasympathetic activity in CFS measured with HF might be reduced and nocturnal sympathetic activity might be increased.5,28,29 Furthermore, low nocturnal HRV was correlated with unrefreshing sleep and disrupted sleep in patients with CFS compared to controls.24,28
Parasympathetic nervous system is predominant during sleep,9 and sleep quality might be associated with non-rapid eye movement (NREM) sleep parasympathetic tone. HF increases with sleep onset, reaching maximal values during deep slow wave sleep (SWS) (ie, stage N3 sleep).10,30,31 Parasympathetic tone and brain cell membrane hyperpolarization increase with SWS,32 helping to restore optimal function. For healthy individuals, increased daytime resting parasympathetic tone was associated with better subjective and objective sleep quality.33
Nocturnal sympathetic activity can also be evaluated with HR and blood pressure (BP) variables. In CFS, nocturnal BP might be reduced, and HR might be elevated compared to controls.5,29,34
We aimed to measure the nocturnal cardiac autonomic function and simultaneous PSG recording in patients with CFS compared to controls to unfold reasons for unrefreshing sleep and daytime fatigue in the microstructure of sleep in relation to ANS. We used the IOM 2015 criteria for CFS diagnosis. Furthermore, by choosing controls who also suffered from tiredness, we could accurately measure the effects of CFS pathology on the HRV, HR, and BP variables, not the effects of tiredness in general. We assumed that nocturnal parasympathetic tone would be decreased, and sympathetic tone would be increased in our patients with CFS compared to the control group.
METHODS
This is a case series analysis of patient files, questionnaires, and PSG recordings. The institutional review board of Vital-med Helsinki Sleep Clinic approved the study. Written informed consent was obtained. Data from all the controls and patients were anonymized before the analysis of the data.
Subjects
The subjects were 9 individuals with clinically diagnosed CFS according to the 2015 IOM criteria and 9 controls aged between 16 and 49 years from Vitalmed Helsinki Sleep Clinic. All patients in whom CFS was diagnosed in the sleep clinic using IOM 2015 criteria and had all the necessary recordings done, were included in the study. The control group comprised 9 individuals who were matched by age, sex, and body mass index to those in whom CSF was diagnosed. The individuals in the control group had significant daytime tiredness, and they were randomly selected for the control group. The controls had a diagnosis of insomnia or delayed sleep phase syndrome that explained their tiredness. We excluded one patient and therefore his control from the analysis, because the patient had an apnea-hypopnea index (AHI) over 30 events/h in PSG, leaving us with 8 patients and 8 controls. Five subjects were female and 3 were male in both groups. The diagnosis of CFS was set by a specialist in neurology with a special competence in sleep medicine. Both patients with CFS and controls were all negative for untreated hypothyroidism, significant sleep apnea (more than 15 apneas or hypopneas per hour of sleep or AHI > 15 events/h), narcolepsy, any past or current diagnosis of major depression with psychotic or melancholic features, bipolar affective disorders, schizophrenia, delusional disorder of any subtype, dementia, anorexia nervosa, or bulimia nervosa. We decided to use controls with severe tiredness to have the results more convincing in comparison to having healthy controls. Two of the patients with CFS were taking medication that influenced cardiac autonomic functioning and inhibited melatonin secretion35: one took propranolol 10 mg once a day and another twice a day for orthostatic intolerance.
Polysomnography
All the subjects had undergone a single in-laboratory PSG study with SOMNOscreen plus PSG system (Somnomedics, Randersacker, Germany). The recordings were set to start at 9:00 pm and were ended in the morning depending on the subjects' individual waking up time (6:00–10:00 am). The PSG recordings were scored in 30-second epochs by a certified PSG technologist and reviewed by a medical specialist with experience in sleep scoring according to the American Academy of Sleep Medicine guidelines.36,37
Continuous Electrocardiography and Blood Pressure Measurements
The SOMNOscreen system included beat-to-beat continuous, noninvasive BP measurement based on pulse transit time from electrocardiography leads to pulse oximeter at fingertip. Pulse transit time method is a validated and patented noninvasive technique to study nocturnal ambulatory BP,38 with no need for a sleep-disturbing sphygmomanometer in the patient's arm applying pressure and breaking up the sleep architecture. We collected the HRV, HR, and BP data epoch by epoch, and each epoch was classified into 1 of the 4 different sleep stages (N1, N2, N3, and R) or wake. The ANS activity was analyzed using different quantitative measurements of HRV equivalent to the guidelines given by the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.8 Specifically these measurements were high-frequency components of HRV spectra in absolute units (0.15–0.4 Hz) (HF), low-frequency components of HRV spectra in absolute units (0.04–0.15 Hz) (LF), and sympathovagal balance (SVB or LF/HF). The collected parameters were sleep stage, position, HR, HF, LF, LF/HF, systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure. The values of the parameters for every epoch were exported using the build-in export data tool from the SOMNOscreen program. Only epochs when the patient was lying in bed were included in the analysis.
Subjective Questionnaires
The subjects had completed questionnaires including Epworth Sleepiness Scale (ESS) and Rimon's Brief Depression Scale,39 with range of zero to 21, with 21 being most depressed. The Rimon's Brief Depression Scale was chosen because it is the most unconfounding depression scale when analyzing tired patients. Subjects also completed the Basic Nordic Sleep Questionnaire (BNSQ), which comprised questions of nonrestorative sleep, sleepiness, tiredness, and fatigue.40 The question about tiredness in BNSQ was “Have you felt daytime tiredness?” and the scale was from 1 to 5 according to the subjective prevalence of tiredness. The original terms were in the Finnish language.
Statistical Analyses
Statistical analyses were performed using Stata 14.2 (Stata-Corp, College Station, Texas, United States). The different variables were tested for normality using the skewness/kurtosis test for normality. As none of the variables were normally distributed, nonparametric measures were used. Group comparisons between patients with CFS and controls in defined sleep stages were conducted using the two-sample Wilcoxon rank-sum (Mann-Whitney U) test, and P values were computed with z scores. The comparisons between different sleep stages and wake were conducted using the Kruskal-Wallis equality-of-populations rank test and post hoc testing with Dunn post hoc test. A value of P < .05 was considered statistically significant. The results were confirmed with median tests when applicable. For reader-friendly descriptive purposes, we report means and 95% confidence intervals in selected cases.
RESULTS
Table 1 and Table 2 depict the demographic and clinical characteristics of the patients with CFS and controls. There were no significant differences in age, body mass index, AHI, or oxygen desaturation index of 3% between the groups. There were no significant differences in the ESS scores, Rimon's Brief Depression Scale scores, subjective feeling of unrefreshing sleep, subjective daytime tiredness, or subjective feeling of sleepiness between the groups, but the patients with CFS experienced fatigue significantly more often than the controls (P = .0253).
Table 1.
Characteristics of patients with CFS and controls.
Table 2.
Occurrence of symptoms in patients with CFS and controls.
All the patients with CFS and the controls had all sleep stages during the PSG night. The distribution of different sleep stages did not significantly differ between the groups, nor did the total sleep time (Table S1 in the supplemental material).
Table S2 in the supplemental material presents the total number of epochs of different sleep stages and wake in CFS patient and controls included in the HRV and BP analysis. Epochs that gave artefactual values for the parameters were excluded from that particular HRV or BP analysis. The variables were counted for the whole night for each epoch of sleep and wake with total count of 17,909 epochs. The group of patients with CFS counted for 8,951 epochs and the control group counted for 8,958 epochs.
High-Frequency Oscillations
Table 3 depicts selected HRV and HR values of the CFS patient and control groups. Figure 1 presents the values of HF for the CFS patient and control groups in different sleep stages. In the group of patients with CFS, HF varied significantly between all the other sleep stages (P < .05), but not significantly between stage N1 and stage N3 sleep. The amount of HF did not increase toward deeper NREM sleep in the patients with CFS group; instead HF decreased from stage N2 to stage N3 sleep. In the control group, HF was significantly different between all the different sleeps stages and wake (P < .05) and the amount of HF increased with deeper NREM sleep.
Table 3.
Heart rate variables.
Figure 1. HF values in different sleep stages for chronic fatigue syndrome patients and controls.
The whiskers are adjacent lines, boxes are 25th to 75th percentile with median and the dots are outliers. * = P < .0001. CFS = chronic fatigue syndrome, HF = high-frequency components of the heart rate variability spectra.
The amount of HF was significantly lower in the group of patients with CFS than in the control group in stage N3 sleep (Figure 1 and Table 3). By contrast and to highlight the difference in stage N3 sleep, HF in stage N1 and stage N2 sleep and wake was significantly higher in the group of patients with CFS compared to the control group. Nocturnal HF in total was significantly higher for the group of patients with CFS. In stage R sleep, HF did not significantly differ between the group of patients with CFS and controls.
LF and LF/HF
Figure 2 shows the values of LF for the group of patients with CFS and controls in different sleep stages. Total nocturnal LF and LF in different sleep stages was significantly higher in the group of patients with CFS compared to the controls, but no such difference existed between the two groups in wake (Figure 2 and Table 3).
Figure 2. LF values in different sleep stages for chronic fatigue syndrome patients and controls.
The whiskers are adjacent lines, boxes are 25th to 75th percentile with median and the dots are outliers. * = P < .0001. CFS = chronic fatigue syndrome, LF = low-frequency components of the heart rate variability spectra.
Figure 3 presents the values of LF/HF for the group of patients with CFS and controls in different sleep stages. Nocturnal LF/HF (SVB) was significantly elevated in the group of patients with CFS in total and in stage N2, stage N3, and stage R sleep. LF/HF was significantly decreased in the group of patients with CFS compared to the controls in wake (Figure 3 and Table 3).
Figure 3. LF/HF values in different sleep stages for chronic fatigue syndrome patients and controls.
The whiskers are adjacent lines, boxes are 25th to 75th percentile with median and the dots are outliers. * = P < .0001. CFS = chronic fatigue syndrome, LF/HF = sympathovagal balance.
Heart Rate
Figure 4 displays HR values in different sleep stages for the patients with CFS and controls. In the group of patients with CFS, HR was significantly different between different sleep stages and wake (P < .05). HR was the lowest in stage N1 sleep and increased toward deeper NREM sleep. The HR values of controls were also significantly different between all the other sleep stages (P < .05), but not between stage N1 and stage N3 sleep. HR in total and separately in all the sleep stages and in wake was significantly lower in the group of patients with CFS compared to the controls (Figure 4 and Table 3).
Figure 4. HR values in different sleep stages for chronic fatigue syndrome patients and controls.
The whiskers are adjacent lines, boxes are 25th to 75th percentile with median and the dots are outliers. * = P < .0001. CFS = chronic fatigue syndrome, HR = heart rate.
Blood Pressure
Table 4 depicts selected BP values of the group of patients with CFS and controls. Nocturnal SBP in total and separately in all NREM sleep stages and in wake was slightly but significantly higher in the group of patients with CFS. There was no difference between the group of patients with CFS and controls in the total nocturnal DBP, nor in stage N1 and stage R sleep, but DBP was significantly lower in the group of patients with CFS compared to the controls in stage N3 sleep and in wake. Nocturnal mean arterial pressure was significantly higher in total for patients with CFS than for the control group.
Table 4.
Blood pressure variables.
Sensitivity Analysis
The significant results did not change when we ran the same analysis in a sample with manually reassessed transitional epochs and elusive epochs removed.
In addition, we analyzed the data without the 2 patients with CFS who used propranolol and their controls, with 6 patients with CFS and 6 controls. In this analysis, the results did not change for HF or HR parameters or for the LF parameters during sleep.
For sensitivity analysis, we computed median and mean values in all sleep stages for all the patients with CFS and controls and did the same statistical analysis with that sample (n = 16) for both median and mean values separately. With so few subjects, we found no statistical significance between patients with CFS and controls for the HRV, HR, or the BP variables.
DISCUSSION
The reason for self-reported low quality of sleep in CFS has been unclear for decades. Nevertheless, to our knowledge, only one study has been published presenting cardiac ANS activity in relation to sleep microstructure in CFS.28 Furthermore, in that study the condition was diagnosed with the unspecific Fukuda criteria, so it remains somewhat unclear which disease the subjects actually had. In our study, the amount of sleep and the relative distribution of sleep stages in the group of patients with CFS was not inferior compared to the controls, in accordance with previous studies.4,24 Still, previously the sleep stage distribution of patients with CFS has only been compared with that of healthy controls. Thus, superficially the sleep of our patients with CFS seemed to be as good and as restorative as of any healthy individual.
Our current study, however, reveals differences in the nocturnal autonomic function between the groups: parasym-pathetic tone in SWS was reduced and the nocturnal sympathetic tone was increased in the patients with CFS. The results concerning attenuated parasympathetic power in deep sleep are in line with a previous study.28 The cardiac parasympathetic system was not functioning as physiologically in our CFS group as in the control group, which may be caused by the hypothesized underlying dysregulation of the ANS (ie, dysautonomia).10,30,31
In healthy subjects, a gradual increase in parasympathetic activity—presenting as an increase in HF—from stage N1 sleep to SWS has been shown.31 This increase was not present in our CFS patient group. Even though the control group was subjectively as tired as the group of patients with CFS, their parasympathetic tone increased more physiologically when they shifted into deeper sleep stages.10,31 Therefore, parasym-pathetic functioning during deep restorative sleep seems to be impaired in our group of patients with CFS. Reduced vagal tone in SWS may offer an alternative explanation for unrefreshing sleep in CFS, as indices of HRV were the best predictors of sleep quality.5 Detachment of parasympathetic tone and SWS might be contributing to the feeling of unrefreshing sleep as there should be a strong physiological interaction between parasympathetic vagal activity and SWS.32
Our patients with CFS had increased total nocturnal sympathovagal balance, which is in line with previous findings.5,28 Increased sympathetic tone, as shown in HRV, might be a sign of incipient cardiac autonomic neuropathy,41 and sympathetic predominance in HRV was associated with acute subjective fatigue.42
In one previous study,5 a decrease in total nocturnal HF values and no differences in LF values was found, in contrast to our findings. The results cannot be directly compared, however, because the previous study was done without PSG and HRV parameters were obtained with an ambulatory monitor during the self-reported sleep period.
Our patients with CFS had higher average nocturnal BP values compared to the control group, as opposed to previous findings with healthy controls,34 though the results are not directly comparable because in the previous study, BP was only measured every 60 minutes in comparison to our continuous measurement. Regarding impaired parasympathetic activity during SWS, our CFS group might be expected to have higher BP than the controls; their DBP was lower than in the control group in SWS. However, BP is also influenced by factors other than autonomic regulation (eg, hormones and renin-angiotensin-aldosterone system) that may explain this finding.
Our patients presented with lower nocturnal HR compared to the tired controls, whereas previously patients with CFS had mostly manifested with higher nocturnal HR compared to healthy controls.5,29 Normally, HR is known to be the lowest in SWS, slightly higher in stage N2 sleep, increasing further in stage R and stage N1 sleep, and finally the highest in wake.31 Our group of patients with CFS had the lowest HR values in stage N1 sleep, increasing in stage N2 and stage N3 sleep, in contrast to the controls, who had lowest HR values in stage N2 and stage N3 sleep.
In our study, sympathetic tone was reduced in patients with CFS compared to the controls in quiet wake during the night, whereas contradictory resting results have been published when compared with healthy controls,25 but it is worth noting that those results were obtained during the day. In one study, nocturnal wake LF was higher in healthy controls than in patients with CFS, but the result did not reach statistical significance.28
Restorative sleep plays an essential role in maintaining cognitive functions. Patients with CFS frequently report symptoms of cognitive impairment and feeling of “brain fog” in addition to unrefreshing sleep. Dysregulation of cholinergic and adrenergic signaling could also explain these other various clinical symptoms in CFS (eg, cognitive postexertional malaise, memory impairment, and slowed information processing) in addition to nonrestorative sleep, as ANS dysfunction and decreased cerebral blood flow have been proposed as possible factors in cognitive dysfunction in CFS.6,18,19 Poor subjective sleep quality was associated with altered pattern of glucose metabolism in brain regions involved with cognition.43 Newly found glymphatic system removes potential neurotoxic waste from the brain during SWS and the attenuation of adrenergic signaling is possibly activating the glymphatic system.44,45
With age, the prevalence of neurodegenerative—neurotoxic waste-accumulating diseases—increases,46 and at the same time parasympathetic activity and cardiorespiratory coupling during sleep decreases.47,48 Impairment of SWS was associated with accumulation of harmful substances in the brain,49 and accumulation of neurotoxic waste in the brain with poor sleep quality has been linked to cognitive disturbances.50 SWS and simultaneous parasympathetic activity might have a key role in conserving brain function instead of neurodegeneration, whereas sympathetic predominance in sleep may decrease clearance of pathogenic proteins in the brain.51
We hypothesize that toxic waste might be removed from the brain during SWS combined with high vagal tone. Perhaps some toxic substances cumulate in the brain in CFS, because SWS and high vagal tone are not concurrent.
Previously, CFS has been suspected to be a functional psychosomatic disease without any biological basis, but recently there is accumulating evidence that CFS might be related to ANS dysfunction of autoimmune origin,14 thus, being a functional multisystem dysautonomia. In accordance with the new IOM criteria,4 objectively measured orthostatic intolerance and/or cognitive impairment is required. Thus, all the patients fulfilling the new IOM 2015 criteria must have objective autonomic or neurocognitive symptoms; hence, patients with only functional psychosomatic symptoms do not fulfill the criteria. Furthermore, patients with CFS are actually likely to understate their symptoms and had low indication of psychosomatic symptoms.7 Even though the new IOM criteria offer more diagnostic precision compared to the previous situation,4 it might be wise to separate patients with objective dysautonomia from patients with CFS without dysautonomia as two different phenotypes.
Strengths
The studies of nocturnal cardiac ANS in respect to the sleep microstructure are extremely rare in CFS. Though we had only 8 patients with CFS in our study, their diagnosis was accurately set by a specialist according to the strict 2015 IOM criteria. This is the first study to measure the HR, HRV, and BP parameters in patients with CFS using the new IOM 2015 diagnostic criteria. Furthermore, unlike all the previous nocturnal HRV studies, we had a tired control group to avoid Berkson's bias. The differences could have been even larger if we had had healthy (nontired) controls. We can thus believe that the results reflect the true nocturnal ANS pathology in CFS.
Limitations
Unfortunately, the study sample was small because we had strict criteria for CFS. We excluded patients in whom a previous diagnosis was made with Fukuda criteria. Thus, the power of the statistics came from the natural repetition of the 30-second epochs in the long hours of nocturnal sleep compared by groups in defined sleep stages. Due to the skewness of our distributions, we also had a limited number of statistical tests to use. When we computed one median and mean for each subject in each sleep stage, the statistical significance disappeared. Still, by doing so we would have also blotted out the effects of the natural nocturnal temporal variability of the HR, HRV, and BP parameters, the nocturnal HR drop, and BP “dipping.” Therefore, we used epoch-to-epoch analysis as we wanted to look at the variation of the ANS temporal functioning.
Thus, the reader is advised to focus on the actual numeric values of the parameters instead of the small P values because of the large amount of sleep stage epochs used in the analysis. Of note, in studies made with large material, even results with minor clinical significance show small P values. Nonetheless, the original numeric values in our study show logical differences between the groups.
The small amount of beta blocker medication used by two patients was not ideal in relation to credibility of the results, but the sensitivity analysis showed that it had no significant influence on the main outcomes of the study. The high number of outliers in our HRV parameters HF and LF are due to the large individual variability of the variables.41 Another option would have been to use normalized units of HF and LF, which are not as validated as the parameters chosen.10
In our study, the tiredness of the patients with CFS and controls was only measured subjectively, by completing questionnaires such as ESS and BNSQ. No objective measurement of tiredness was used. Furthermore, we did not compare the tired controls or the patients with CFS to healthy nontired controls. Subjectively, both controls and patients with CFS suffered from unrefreshing sleep. The question of whether unrefreshing sleep in CFS is due to ANS dysfunction in SWS would have been better examined if we would have, in addition, compared patients with CFS with healthy controls, whose sleep was subjectively refreshing. But the fact that, in our study, the controls had unrefreshing sleep, too, does not rule out that in CFS unrefreshing sleep is due to ANS dysfunction in SWS. After all, it is well known that patients with CFS suffer from unrefreshing sleep and autonomic disturbances.4 Further research is needed to clarify this topic.
CONCLUSIONS
Chronic fatigue syndrome may be associated with nocturnal SWS parasympathetic tone attenuation and increased nocturnal sympathetic tone. We need more studies with strict IOM 2015 inclusion criteria to further conclude the possible nocturnal autonomic dysfunction in patients with CFS.
DISCLOSURE STATEMENT
Work for this study was performed at Vitalmed Helsinki Sleep Clinic. All authors have seen and approved the manuscript. The authors report no conflicts of interest.
ACKNOWLEDGMENTS
The authors are grateful to all our patients for the participation in the study. We thank Outi Hämäläinen, Anne Huutoniemi, and all the study personnel for their valuable help in organizing and collecting data.
ABBREVIATIONS
- AHI
apnea-hypopnea Index
- ANS
autonomic nervous system
- BMI
body mass index
- BP
blood pressure
- CFS
chronic fatigue syndrome
- DBP
diastolic blood pressure
- ESS
Epworth Sleepiness Scale
- HF
high-frequency components of heart rate variability spectra
- HR
heart rate
- HRV
heart rate variability
- IOM
Institute of Medicine
- LF
low-frequency components of the heart rate variability spectra
- LF/HF
sympathovagal balance, SVB
- NREM
non-rapid eye movement
- PSG
polysomnography
- SBP
systolic blood pressure
- SVB
sympathovagal balance, LF/HF
- SWS
slow wave sleep
REFERENCES
- 1.Fukuda K, Straus SE, Hickie I, et al. The chronic fatigue syndrome: a comprehensive approach to its definition and study. Ann Intern Med. 1994;121(12):953–959. doi: 10.7326/0003-4819-121-12-199412150-00009. [DOI] [PubMed] [Google Scholar]
- 2.Johnston S, Brenu EW, Staines DR, Marshall-Gradisnik S. The adoption of chronic fatigue syndrome/myalgic encephalomyelitis case definitions to assess prevalence: a systematic review. Ann Epidemiol. 2013;23(6):371–376. doi: 10.1016/j.annepidem.2013.04.003. [DOI] [PubMed] [Google Scholar]
- 3.Carruthers BM, Jain AK, De Meirleir KL, et al. Myalgic encephalomyelitis/ chronic fatigue syndrome. J Chronic Fatigue Syndrome. 2003;11(1):7–115. [Google Scholar]
- 4.Institute of Medicine. Committee on the Diagnostic Criteria for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome; Board on the Health of Select Populations. Beyond Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Redefining an Illness. Washington, DC: National Academies Press (US); 2015. [PubMed] [Google Scholar]
- 5.Burton AR, Rahman K, Kadota Y, Lloyd A, Vollmer-Conna U. Reduced heart rate variability predicts poor sleep quality in a case-control study of chronic fatigue syndrome. Exp Brain Res. 2010;204(1):71–78. doi: 10.1007/s00221-010-2296-1. [DOI] [PubMed] [Google Scholar]
- 6.Cvejic E, Birch RC, Vollmer-Conna U. Cognitive dysfunction in chronic fatigue syndrome: a review of recent evidence. Curr Rheumatol Rep. 2016;18(5):24. doi: 10.1007/s11926-016-0577-9. [DOI] [PubMed] [Google Scholar]
- 7.Newton JL, Okonkwo O, Sutcliffe K, Seth A, Shin J, Jones DE. Symptoms of autonomic dysfunction in chronic fatigue syndrome. QJM. 2007;100(8):519–526. doi: 10.1093/qjmed/hcm057. [DOI] [PubMed] [Google Scholar]
- 8.Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation. 1996;93(5):1043–1065. [PubMed] [Google Scholar]
- 9.Gordan R, Gwathmey JK, Xie LH. Autonomic and endocrine control of cardiovascular function. World J Cardiol. 2015;7(4):204–214. doi: 10.4330/wjc.v7.i4.204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Stein PK, Pu Y. Heart rate variability, sleep and sleep disorders. Sleep Med Rev. 2012;16(1):47–66. doi: 10.1016/j.smrv.2011.02.005. [DOI] [PubMed] [Google Scholar]
- 11.Dantas EM, Goncalves CP, Silva AB, et al. Reproducibility of heart rate variability parameters measured in healthy subjects at rest and after a postural change maneuver. Braz J Med Biol Res. 2010;43(10):982–988. doi: 10.1590/s0100-879x2010007500101. [DOI] [PubMed] [Google Scholar]
- 12.Tanaka M, Tajima S, Mizuno K, et al. Frontier studies on fatigue, autonomic nerve dysfunction, and sleep-rhythm disorder. J Physiol Sci. 2015;65(6):483–498. doi: 10.1007/s12576-015-0399-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Newton DJ, Kennedy G, Chan KK, Lang CC, Belch JJ, Khan F. Large and small artery endothelial dysfunction in chronic fatigue syndrome. Int J Cardiol. 2012;154(3):335–336. doi: 10.1016/j.ijcard.2011.10.030. [DOI] [PubMed] [Google Scholar]
- 14.Loebel M, Grabowski P, Heidecke H, et al. Antibodies to beta adrenergic and muscarinic cholinergic receptors in patients with Chronic Fatigue Syndrome. Brain Behav Immun. 2016;52:32–39. doi: 10.1016/j.bbi.2015.09.013. [DOI] [PubMed] [Google Scholar]
- 15.Tanaka S, Kuratsune H, Hidaka Y, et al. Autoantibodies against muscarinic cholinergic receptor in chronic fatigue syndrome. Int J Mol Med. 2003;12(2):225–230. [PubMed] [Google Scholar]
- 16.Hornig M, Gottschalk G, Peterson DL, et al. Cytokine network analysis of cerebrospinal fluid in myalgic encephalomyelitis/chronic fatigue syndrome. Mol Psychiatry. 2016;21(2):261–269. doi: 10.1038/mp.2015.29. [DOI] [PubMed] [Google Scholar]
- 17.Tomoda A, Joudoi T, Rabab el M, Matsumoto T, Park TH, Miike T. Cytokine production and modulation: comparison of patients with chronic fatigue syndrome and normal controls. Psychiatry Res. 2005;134(1):101–104. doi: 10.1016/j.psychres.2005.01.002. [DOI] [PubMed] [Google Scholar]
- 18.Yoshiuchi K, Farkas J, Natelson BH. Patients with chronic fatigue syndrome have reduced absolute cortical blood flow. Clin Physiol Funct Imaging. 2006;26(2):83–86. doi: 10.1111/j.1475-097X.2006.00649.x. [DOI] [PubMed] [Google Scholar]
- 19.Biswal B, Kunwar P, Natelson BH. Cerebral blood flow is reduced in chronic fatigue syndrome as assessed by arterial spin labeling. J Neurol Sci. 2011;301(1-2):9–11. doi: 10.1016/j.jns.2010.11.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Tanaka H, Matsushima R, Tamai H, Kajimoto Y. Impaired postural cerebral hemodynamics in young patients with chronic fatigue with and without orthostatic intolerance. J Pediatr. 2002;140(4):412–417. doi: 10.1067/mpd.2002.122725. [DOI] [PubMed] [Google Scholar]
- 21.Barnden LR, Kwiatek R, Crouch B, Burnet R, Del Fante P. Autonomic correlations with MRI are abnormal in the brainstem vasomotor centre in chronic fatigue syndrome. Neuroimage Clin. 2016;11:530–537. doi: 10.1016/j.nicl.2016.03.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Okada T, Tanaka M, Kuratsune H, Watanabe Y, Sadato N. Mechanisms underlying fatigue: a voxel-based morphometric study of chronic fatigue syndrome. BMC Neurol. 2004;4(1):14. doi: 10.1186/1471-2377-4-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Naviaux RK, Naviaux JC, Li K, et al. Metabolic features of chronic fatigue syndrome. Proc Natl Acad Sci U S A. 2016;113(37):E5472–E5480. doi: 10.1073/pnas.1607571113. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Rahman K, Burton A, Galbraith S, Lloyd A, Vollmer-Conna U. Sleep-wake behavior in chronic fatigue syndrome. Sleep. 2011;34(5):671–678. doi: 10.1093/sleep/34.5.671. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Frith J, Zalewski P, Klawe JJ, et al. Impaired blood pressure variability in chronic fatigue syndrome—a potential biomarker. QJM. 2012;105(9):831–838. doi: 10.1093/qjmed/hcs085. [DOI] [PubMed] [Google Scholar]
- 26.Meeus M, Goubert D, De Backer F, et al. Heart rate variability in patients with fibromyalgia and patients with chronic fatigue syndrome: a systematic review. Semin Arthritis Rheum. 2013;43(2):279–287. doi: 10.1016/j.semarthrit.2013.03.004. [DOI] [PubMed] [Google Scholar]
- 27.Tak LM, Riese H, de Bock GH, Manoharan A, Kok IC, Rosmalen JGM. As good as it gets? A meta-analysis and systematic review of methodological quality of heart rate variability studies in functional somatic disorders. Biol Psychol. 2009;82(2):101–110. doi: 10.1016/j.biopsycho.2009.05.002. [DOI] [PubMed] [Google Scholar]
- 28.Togo F, Natelson BH. Heart rate variability during sleep and subsequent sleepiness in patients with chronic fatigue syndrome. Auton Neurosci. 2013;176(1):85–90. doi: 10.1016/j.autneu.2013.02.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Boneva RS, Decker MJ, Maloney EM, et al. Higher heart rate and reduced heart rate variability persist during sleep in chronic fatigue syndrome: a population-based study. Auton Neurosci. 2007;137(1-2):94–101. doi: 10.1016/j.autneu.2007.08.002. [DOI] [PubMed] [Google Scholar]
- 30.Baharav A, Kotagal S, Gibbons V, et al. Fluctuations in autonomic nervous activity during sleep displayed by power spectrum analysis of heart rate variability. Neurology. 1995;45(6):1183–1187. doi: 10.1212/wnl.45.6.1183. [DOI] [PubMed] [Google Scholar]
- 31.Bonnet MH, Arand DL. Heart rate variability: sleep stage, time of night, and arousal influences. Electroencephalogr Clin Neurophysiol. 1997;102(5):390–396. doi: 10.1016/s0921-884x(96)96070-1. [DOI] [PubMed] [Google Scholar]
- 32.Jerath R, Harden K, Crawford M, Barnes VA, Jensen M. Role of cardiorespiratory synchronization and sleep physiology: effects on membrane potential in the restorative functions of sleep. Sleep Med. 2014;15(3):279–288. doi: 10.1016/j.sleep.2013.10.017. [DOI] [PubMed] [Google Scholar]
- 33.Werner GG, Ford BQ, Mauss IB, Schabus M, Blechert J, Wilhelm FH. High cardiac vagal control is related to better subjective and objective sleep quality. Biol Psychol. 2015;106:79–85. doi: 10.1016/j.biopsycho.2015.02.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Newton JL, Sheth A, Shin J, et al. Lower ambulatory blood pressure in chronic fatigue syndrome. Psychosom Med. 2009;71(3):361–365. doi: 10.1097/PSY.0b013e31819ccd2a. [DOI] [PubMed] [Google Scholar]
- 35.Claustrat B, Brun J, Chazot G. The basic physiology and pathophysiology of melatonin. Sleep Med Rev. 2005;9(1):11–24. doi: 10.1016/j.smrv.2004.08.001. [DOI] [PubMed] [Google Scholar]
- 36.Iber C, Ancoli-Israel S, Chesson A, Quan SF for the American Academy of Sleep Medicine. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications. 1st ed. Westchester, IL: American Academy of Sleep Medicine; 2007. [Google Scholar]
- 37.Berry RB, Budhiraja R, Gottlieb DJ, et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med. 2012;8(5):597–619. doi: 10.5664/jcsm.2172. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Bilo G, Zorzi C, Ochoa Munera JE, Torlasco C, Giuli V, Parati G. Validation of the Somnotouch-NIBP noninvasive continuous blood pressure monitor according to the European Society of Hypertension International Protocol revision 2010. Blood Press Monit. 2015;20(5):291–294. doi: 10.1097/MBP.0000000000000124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Keltikangas-Järvinen L, Rimon R. Rimon's Brief Depression Scale, a rapid method for screening depression. Psychol Rep. 1987;60(1):111–119. doi: 10.2466/pr0.1987.60.1.111. [DOI] [PubMed] [Google Scholar]
- 40.Partinen M, Gislason T. Basic Nordic Sleep Questionnaire (BNSQ): a quantitated measure of subjective sleep complaints. J Sleep Res. 1995;4(S1):150–155. doi: 10.1111/j.1365-2869.1995.tb00205.x. [DOI] [PubMed] [Google Scholar]
- 41.Metelka R. Heart rate variability--current diagnosis of the cardiac autonomic neuropathy. A review. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2014;158(3):327–338. doi: 10.5507/bp.2014.025. [DOI] [PubMed] [Google Scholar]
- 42.Tanaka M, Mizuno K, Yamaguti K, et al. Autonomic nervous alterations associated with daily level of fatigue. Behav Brain Funct. 2011;7:46. doi: 10.1186/1744-9081-7-46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Kay DB, Karim HT, Soehner AM, et al. Sleep-wake differences in relative regional cerebral metabolic rate for glucose among patients with insomnia compared with good sleepers. Sleep. 2016;39(10):1779–1794. doi: 10.5665/sleep.6154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Mendelsohn AR, Larrick JW. Sleep facilitates clearance of metabolites from the brain: glymphatic function in aging and neurodegenerative diseases. Rejuvenation Res. 2013;16(6):518–523. doi: 10.1089/rej.2013.1530. [DOI] [PubMed] [Google Scholar]
- 45.Xie L, Kang H, Xu Q, et al. Sleep drives metabolite clearance from the adult brain. Science. 2013;342(6156):373. doi: 10.1126/science.1241224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Tarasoff-Conway JM, Carare RO, Osorio RS, et al. Clearance systems in the brain-implications for Alzheimer disease. Nat Rev Neurol. 2015;11(8):457–470. doi: 10.1038/nrneurol.2015.119. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Bartsch RP, Schumann AY, Kantelhardt JW, Penzel T, Ivanov P. Phase transitions in physiologic coupling. Proc Natl Acad Sci U S A. 2012;109(26):10181–10186. doi: 10.1073/pnas.1204568109. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Crasset V, Mezzetti S, Antoine M, Linkowski P, Degaute JP, van de Borne P. Effects of aging and cardiac denervation on heart rate variability during sleep. Circulation. 2001;103(1):84–88. doi: 10.1161/01.cir.103.1.84. [DOI] [PubMed] [Google Scholar]
- 49.Mander BA, Marks SM, Vogel JW, et al. Beta-amyloid disrupts human NREM slow waves and related hippocampus-dependent memory consolidation. Nat Neurosci. 2015;18(7):1051–1057. doi: 10.1038/nn.4035. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Molano JR, Roe CM, Ju YS. The interaction of sleep and amyloid deposition on cognitive performance. J Sleep Res. 2017;26(3):288–292. doi: 10.1111/jsr.12474. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Musiek ES, Holtzman DM. Mechanisms linking circadian clocks, sleep, and neurodegeneration. Science. 2016;354(6315):1004–1008. doi: 10.1126/science.aah4968. [DOI] [PMC free article] [PubMed] [Google Scholar]
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