fragmented sleep – American ME and CFS Society

Behavioral perturbation and sleep in healthy and virus-infected inbred mice

Abstract:

Murine gammaherpesvirus (MuGHV) is a natural pathogen of wild rodents that has been studied extensively in terms of host immune responses to herpesviruses during acute infection, latency, and reactivation from latency. Although herpesvirus infections in people can be associated with fatigue and excessive sleepiness during both acute and latent infection, MuGHV has not been assessed extensively as a model for studying the behavioral consequences of chronic latent herpesvirus infections.

To assess MuGHV infection as a model for evaluating fatigue and assessing potential mechanisms that underlie the exacerbation of fatigue during chronic viral disease, we evaluated sleep, temperature, and activity after exposure of healthy and latently MuGHV-infected mice to sleep fragmentation and social interaction. Neither treatment nor infection significantly affected temperature. However, at some time points, latently infected mice that underwent sleep fragmentation had less locomotor activity and more slow-wave sleep than did mice exposed to social interaction. In addition, delta-wave amplitude during slow-wave sleep was lower in infected mice exposed to sleep fragmentation compared with uninfected mice exposed to the same treatment.

Both reduced locomotor activity and increased time asleep could indicate fatigue in infected mice after sleep fragmentation; reduced delta-wave amplitude during slow-wave sleep indicates a light plane of sleep from which subjects would be aroused easily. Identifying the mechanisms that underlie sleep responses of mice with chronic latent MuGHV infection may increase our understanding of fatigue during infections and eventually contribute to improving the quality of life for people with chronic viral infections.

Source: Trammell RA, Toth LA. Behavioral perturbation and sleep in healthy and virus-infected inbred mice. Comp Med. 2014 Aug;64(4):283-92. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4170093/ (Full article)

Are there sleep-specific phenotypes in patients with chronic fatigue syndrome? A cross-sectional polysomnography analysis

Abstract:

OBJECTIVES: Despite sleep disturbances being a central complaint in patients with chronic fatigue syndrome (CFS), evidence of objective sleep abnormalities from over 30 studies is inconsistent. The present study aimed to identify whether sleep-specific phenotypes exist in CFS and explore objective characteristics that could differentiate phenotypes, while also being relevant to routine clinical practice.

DESIGN: A cross-sectional, single-site study.

SETTING: A fatigue clinic in the Netherlands.

PARTICIPANTS: A consecutive series of 343 patients meeting the criteria for CFS, according to the Fukuda definition.

MEASURES: Patients underwent a single night of polysomnography (all-night recording of EEG, electromyography, electrooculography, ECG and respiration) that was hand-scored by a researcher blind to diagnosis and patient history.

RESULTS: Of the 343 patients, 104 (30.3%) were identified with a Primary Sleep Disorder explaining their diagnosis. A hierarchical cluster analysis on the remaining 239 patients resulted in four sleep phenotypes being identified at saturation. Of the 239 patients, 89.1% met quantitative criteria for at least one objective sleep problem. A one-way analysis of variance confirmed distinct sleep profiles for each sleep phenotype. Relatively longer sleep onset latencies, longer Rapid Eye Movement (REM) latencies and smaller percentages of both stage 2 and REM characterised the first phenotype. The second phenotype was characterised by more frequent arousals per hour. The third phenotype was characterised by a longer Total Sleep Time, shorter REM Latencies, and a higher percentage of REM and lower percentage of wake time. The final phenotype had the shortest Total Sleep Time and the highest percentage of wake time and wake after sleep onset.

CONCLUSIONS: The results highlight the need to routinely screen for Primary Sleep Disorders in clinical practice and tailor sleep interventions, based on phenotype, to patients presenting with CFS. The results are discussed in terms of matching patients’ self-reported sleep to these phenotypes in clinical practice.

Source: Gotts ZM, Deary V, Newton J, Van der Dussen D, De Roy P, Ellis JG. Are there sleep-specific phenotypes in patients with chronic fatigue syndrome? A cross-sectional polysomnography analysis. BMJ Open. 2013 Jun 20;3(6). pii: e002999. doi: 10.1136/bmjopen-2013-002999. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3669720/ (Full article)

Heart rate variability during sleep and subsequent sleepiness in patients with chronic fatigue syndrome

Abstract:

We determined whether alterations in heart rate dynamics during sleep in patients with chronic fatigue syndrome (CFS) differed from controls and/or correlated with changes of sleepiness before and after a night in the sleep laboratory. We compared beat-to-beat RR intervals (RRI) during nocturnal sleep, sleep structure, and subjective scores on visual analog scale for sleepiness in 18 CFS patients with 19 healthy controls aged 25-55 after excluding subjects with sleep disorders. A short-term fractal scaling exponent (α1) of RRI dynamics, analyzed by the detrended fluctuation analysis (DFA) method, was assessed after stratifying patients into those who reported more or less sleepiness after the night’s sleep (a.m. sleepier or a.m. less sleepy, respectively).

Patients in the a.m. sleepier group showed significantly (p<0.05) higher fractal scaling index α1 during non-rapid eye movement (non-REM) sleep (Stages 1, 2, and 3 sleep) than healthy controls, although standard polysomnographic measures did not differ between the groups. The fractal scaling index α1 during non-REM sleep was significantly (p<0.05) higher than that during awake periods after sleep onset for healthy controls and patients in the a.m. less sleepy group, but did not differ between sleep stages for patients in the a.m. sleepier group. For patients, changes in self-reported sleepiness before and after the night correlated positively with the fractal scaling index α1 during non-REM sleep (p<0.05). These results suggest that RRI dynamics or autonomic nervous system activity during non-REM sleep might be associated with disrupted sleep in patients with CFS.

Source: Togo F, Natelson BH. Heart rate variability during sleep and subsequent sleepiness in patients with chronic fatigue syndrome. Auton Neurosci. 2013 Jun;176(1-2):85-90. doi: 10.1016/j.autneu.2013.02.015. Epub 2013 Mar 15. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4100066/ (Full article)

Reduced heart rate variability predicts poor sleep quality in a case-control study of chronic fatigue syndrome

Abstract:

Parasympathetic function is important in the induction and maintenance of sleep. We examined whether nocturnal vagal modulation of heart rate is related to the poor sleep quality commonly reported in chronic fatigue syndrome (CFS).

Heart rate (HR, as R-R intervals) was continuously monitored during sleep in 20 patients with CFS and 20 matched control subjects. Questionnaires assessed demographic information, symptoms, functional impairment, and subjective sleep quality.

CFS was associated with more sleep problems in general and poorer subjective sleep quality on the study night (all p < 0.003), and reports of repeated awakening during the night were 7 times more likely compared to healthy subjects (p = 0.017). Time and frequency-domain parameters of HR variability during sleep were significantly lower in patients with CFS (all p < 0.006). Multiple regression analyses revealed that heart rate variability (HRV) parameters were the best predictors of subjective sleep measures.

This study identified significant reductions in vagal modulation of heart rate during sleep in CFS. Low HRV strongly predicted sleep quality-suggesting a pervasive state of nocturnal sympathetic hypervigilance in CFS.

Source: 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 Jul;204(1):71-8. doi: 10.1007/s00221-010-2296-1. Epub 2010 May 26. https://www.ncbi.nlm.nih.gov/pubmed/20502886