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Volume 14 No. 05
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Scientific Investigations

The Effects of Experimental Sleep Fragmentation and Sleep Deprivation on the Response of the Genioglossus Muscle to Inspiratory Resistive Loads

Jennifer M. Cori, PhD1; Christian L. Nicholas, PhD1,2; Joanne Avraam, PhD1,2; V. Vien Lee, BSc (Hons)1,3; Rachel Schembri, PhD1,3; Melinda L. Jackson, PhD1,2,3; Amy S. Jordan, PhD1,2
1Institute for Breathing and Sleep and Austin Health, Heidelberg, Victoria, Australia; 2Melbourne School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia; 3School of Health & Biomedical Sciences, RMIT University, Bundoora, Victoria, Australia

ABSTRACT

Study Objectives:

Poor upper airway dilator muscle function may contribute to obstructive sleep apnea (OSA). Sleep deprivation reduces dilator muscle responsiveness, but sleep fragmentation, which is most characteristic of OSA, has not been assessed. This study compared the effects of sleep deprivation and fragmentation on dilator muscle responsiveness during wakefulness.

Methods:

Twenty-four healthy individuals (10 female) participated in two consecutive overnight polysomnography (PSG) sessions. The first was an adaptation PSG of normal sleep. The second was an experimental PSG, where participants were allocated to groups of either normal sleep, no sleep, or fragmented sleep. Inspiratory resistive loading assessment occurred the morning following each PSG. Four 10 cmH2O and four 20 cmH2O loads were presented in random order for 60 seconds while participants were awake and supine. Sleep (electroencephalogram, electrooculogram, electromyogram [EMG]), intramuscular genioglossus activity (EMGGG), and ventilation were measured throughout the loading sessions.

Results:

Five controls, seven sleep deprivation participants, and seven sleep fragmentation participants provided data. Contrary to expectations, neither EMGGG nor ventilation showed significant interaction effects (group × session × load) during resistive loading. There was a main effect of load, with peak EMGGG (mean % max ± standard error) significantly higher for the 20 cmH2O load (4.1 ± 0.6) than the 10 cmH2O load (3.3 ± 0.6) across both sessions and all groups. Similar results were observed for peak inspiratory flow, duty cycle, and mask pressure.

Conclusions:

Upper airway function was not affected by 1 night of no sleep or poor-quality sleep. This raises doubt as to whether fragmented sleep in OSA increases disorder severity via reduced upper airway dilator responses.

Citation:

Cori JM, Nicholas CL, Avraam J, Lee VV, Schembri R, Jackson ML, Jordan AS. The effects of experimental sleep fragmentation and sleep deprivation on the response of the genioglossus muscle to inspiratory resistive loads. J Clin Sleep Med. 2018;14(5):715–724.


BRIEF SUMMARY

Current Knowledge/Study Rationale: Poor sleep is theorized to worsen upper airway dilator muscle responsiveness and subsequently increase upper airway collapsibility in obstructive sleep apnea (OSA). Despite sleep fragmentation being the primary sleep disturbance in OSA, support for this theory comes from studies that have demonstrated reduced dilator muscle responsiveness and increased upper airway collapsibility following sleep deprivation.

Study Impact: This study demonstrated that neither a single night of lack of sleep nor fragmented sleep reduced dilator muscle or ventilatory responsiveness to inspiratory resistive loads in healthy individuals during wakefulness. Should these results persist during sleep following multiple nights of disturbed sleep, they would suggest that fragmented sleep in OSA is unlikely to increase disorder severity via reduced dilator muscle activity.

INTRODUCTION

The primary function of the upper airway dilator muscles is to maintain upper airway patency. To do this effectively, the dilator muscles must overcome negative intraluminal pressures generated during inspiration and positive extraluminal pressures exerted by the surrounding soft-tissue structures. Failure to do so during sleep may contribute to obstructive sleep apnea (OSA), a disorder characterized by repetitive episodes of upper airway collapse during sleep. As upper airway collapse typically leads to arousal, sleep in OSA is often heavily fragmented. Poor-quality sleep in OSA is thought to increase upper airway collapsibility, thus creating a self-perpetuating cycle. Reduced dilator muscle responsiveness may be a mechanism by which poor sleep increases collapsibility.1

Support for the self-perpetuating hypothesis comes primarily from sleep deprivation studies. In individuals with OSA, the metric that describes the frequency of upper airway collapse, the apnea-hypopnea index, is twice as high during daytime polysomnography (PSG) preceded by a night of sleep deprivation compared to nocturnal PSG preceded by a night of normal sleep.2 In addition, sleep deprivation in individuals with OSA has been reported to increase respiratory event duration,3 increase oxygen desaturations,4,5 and lower the minimum oxygen desaturation.4 In healthy individuals, sleep deprivation does not affect these respiratory parameters but does double the portion of sleep spent snoring.4

The mechanisms that underlie the deterioration in ventilatory parameters following sleep deprivation are not well understood. Sleep deprivation has been demonstrated to decrease both the hypercapnic68 and hypoxic ventilatory response,7 although not in all studies.1 A study that measured the genioglossus, a large dilator muscle responsible for protrusion of the tongue and pulling it away from the posterior pharyngeal wall, demonstrated that a night of sleep deprivation decreased the muscle's responsiveness to carbon dioxide (CO2) rebreathing in healthy adults aged 30 years or older.1 Preliminary analysis of a study yet to be published also found reduced genioglossus responsiveness to a CO2 stimulus following sleep deprivation.9

Although prior research suggests an adverse effect of sleep deprivation on upper airway function, the primary sleep disturbance in OSA is sleep fragmentation and not sleep deprivation. Despite this, very few studies have assessed sleep fragmentation. A study of healthy individuals reported no difference in the slope of the ventilatory response to hypercapnia following a night of sleep fragmentation versus a night of normal sleep.10 Another study that assessed upper airway collapsibility in healthy individuals demonstrated that the critical closing pressure of the airway was less negative following sleep fragmentation (−12.3 cmH2O) than following sleep deprivation (−17.1 cmH2O).11 The authors speculated that a possible mechanism responsible for the increased upper airway collapsibility following sleep fragmentation was reduced upper airway dilator muscle activation.

Despite sleep fragmentation being the sleep disturbance most characteristic of OSA, there is no information on how sleep fragmentation affects the upper airway dilator muscles. The aim of this study was to determine whether sleep deprivation and experimentally induced sleep fragmentation have differential effects on the upper airway dilator muscle response and the ventilatory response to resistive loading in healthy individuals.

METHODS

Participants were 24 (female = 10) healthy individuals aged between 20 and 32 years. The participants were part of a larger study (n = 33) that assessed the effect of sleep disturbance on cognition, mood, metabolism, and cardiorespiratory physiology. The larger study comprised assessment across 5 days. The participants spent the first 48 hours in the sleep laboratory, where they ate meals and performed neurocognitive tasks and physiological tests at set times. The first night in the laboratory, during which the participants slept undisturbed, was designated the adaptation PSG. The second night in the laboratory, during which the participants were randomly allocated to one of three groups: normal sleep, sleep deprivation or sleep fragmentation, was designated the experimental PSG. Due to technical difficulties with the sleep fragmentation equipment in the early phase of the study, many of the participants for this group (10 of 12) were not randomly allocated, rather they were collected last. Participants in the control and sleep fragmentation groups were blinded to their group allocation, whereas this was not possible for the sleep deprivation group. Nights 3 and 4 the participants slept at home, with sleep monitored via actigraphy. On day 5 the participants returned to laboratory for final assessment. The genioglossus resistive loading tests were optional and were conducted on the mornings following both the adaption PSG and experimental PSG. Ethics approval was obtained from the University of Melbourne Human Research Ethics Committee (no. 1339512.1) and the study conformed to the Declaration of Helsinki.

Recruitment occurred via advertisements placed around the University of Melbourne campus and on the University of Melbourne student portal. All participants signed written informed consent before undergoing rigorous screening. The included participants were physically and psychologically healthy (< 15 on the Centre for Epidemiological Studies-Depression scale),12 were not taking medication (oral contraceptive excepted), had no history of drug or alcohol abuse, were not current smokers, had regular sleep durations between 6 to 10 hours, awoke regularly between 6:00 AM  9:00 AM, and had not traveled across time zones or participated in shift work within the previous month. The participants were unlikely to have a sleep or circadian disorder with scores of < .05 on the multivariate apnea prediction index,13 < 15 on the Epworth Sleepiness Scale,14 ≤ 5 on the Pittsburgh Sleep Quality Index15 and a midrange score (30–60) on a revised version of the morningness-eveningness questionnaire.16

Measurement

Polysomnography

The participants underwent electroencephalography (EEG: F3-A2, F4-A1, C3-A2, C4-A1, O1-A2 and O2-A1), left and right electrooculography (EOG), and mentalis electromyography (EMG) for sleep and arousal scoring. Anterior tibialis EMG measured leg movements, nasal cannula measured nasal airflow, thermistor measured oronasal airflow, chest and abdomen piezoelectric bands measured respiratory effort, finger pulse oximeter measured oxygen saturation, a microphone measured snoring, electrocardiography (ECG) measured heart rate, and a position sensor and video camera monitored body position.

Recordings were made using Compumedics E-Series and Siesta equipment (Abbottsford, Victoria, Australia). EEG, EMG, and ECG were sampled at 512 Hz, body position at 16 Hz, piezo electrode bands at 64Hz, airflow at 128 Hz, and oximeter at 16 Hz.

Genioglossus Resistive Loading

Four fine-wire electrodes (000-318-130, Chalgren Enterprises, Inc, Gilroy, California, United States) with 5 mm bare were inserted into the genioglossus percutaneously via two 27-gauge needles (which inserted two electrodes each). The insertion location was 10 mm from the inferior border of the mandible and 3 to 4 mm from the midline on either side (one needle to each side). The electrodes were inserted to a depth of approximately 25 mm. Electrodes from across the midline were referenced to each other to provide two bipolar genioglossus muscle recordings (EMGGG). Participants were fitted with a leak-proof nasal mask (Modified Profile-Lite, Phillips, Respironics, Murrysville, Pennsylvania, United States), with a heated pneumotachograph attached (model 3700; Hans Rudolph, Shawnee, Kansas, United States). The heated pneumotachograph was connected to a two-way valve (model 2600; Hans Rudolph) that separated inspiratory and expiratory flow. Tubing was attached to the inspiratory side of the valve, which ran through the bedroom wall and into the experimental control room. On the end of the tubing in the experimental control room was a three-way tap that enabled linear resistive loads (10 cmH2O and 20 cmH2O, model 7100 R5 (two) and R20; Hans Rudolph) to be switched into the inspiratory line. Mask pressure was also monitored continuously (Pmask; DP45; Validyne, Northridge, California, United States). Data were recorded on a computer using an analog to digital converter (1401plus and Spike2 software, Cambridge Electronic Design, Cambridge, United Kingdom). EMGGG was sampled at 1000 Hz. EEG, EMG, and EOG were sampled at 250 Hz and remaining respiratory signals at 125 Hz.

Procedure

On the adaptation PSG night, the participants arrived at the laboratory at approximately 6:00 PM after keeping regular sleep-wake cycles for the prior 7 days (confirmed by actigraphy). They ate a standardized meal at 7:00 PM before being set up for overnight PSG. Participants were allowed to sleep from 11:00 PM as per normal without interference. Participants were awakened by the researcher at 8:00 AM if they did not awake earlier.

At approximately 9:00 AM the morning following the adaptation PSG, the participants were fitted with the equipment for the resistive load testing. Resistive load testing commenced between 10:00 and 11:30 AM. The participants were asked to lie supine. To calibrate EMGGG the participants were asked to swallow and protrude their tongue against the back of their teeth three times each to determine the maximal EMGGG. The participants were exposed to a practice load to reduce any anxiety associated with the stimuli. They were then instructed to lay quietly with minimal movement for 5 minutes so that baseline measures could be obtained. Following this, the loading trials commenced. Each loading trial was preceded by a 60-second pre-load phase, before a resistive load was attached to the circuit for 60 seconds. This was followed by a 60-second recovery time with no load. There were eight resistive load trials in total, four with 10 cmH2O loads and four with 20 cmH2O loads. The order of the loads was randomized. Loads were switched into the circuit during expiration. Following resistive load testing the respiratory equipment was removed but the genioglossus wires were left in. The wires were held in place with Tegaderm film dressing (3M, New South Wales, Australia) and tape.

The experimental PSG session was conducted the evening following the adaptation resistive load session. Participants were instrumented with the same equipment as for the adaptation PSG with the exception of the nasal cannula, thermistor, and respiratory bands, as participants who were shown to have significant sleep apnea on the adaptation PSG night did not continue the protocol. Participants in the control group slept normally as on the adaptation PSG night. Those in the sleep deprivation group remained awake all night. This was ensured by continuous monitoring by the researchers. For the sleep fragmentation group, arousals were induced via a combination of auditory tone stimuli, which were administered via insert earphones (E-A-RTONE 3A, 3M Indianapolis, Indiana, United States) and vibration stimuli administered via a bed shaker system placed under the mattress (Vibes Bedshaker, TabTimer, New South Wales, Australia). The general procedure was to induce arousal when the participant entered any sleep stage other than stage N1 sleep. Auditory tones were used before the vibration stimuli, commencing at 45 db and 1 second in duration. If arousal was induced, 1 minute elapsed before another tone of the same volume was played. If no arousal was observed the tones were increased in 5-db increments until arousal. The maximum tone volume used was 100 db, which unlike the other tone volumes was also available in 2- and 3-second durations. If the 3-second 100 db tone failed to induce an arousal then the bed shaker was used. The bed shaker stimuli length was variable and left on as long as necessary to induce arousal, with simultaneous tones if required. If the bed shaker failed to arouse the participant the researcher would enter the room and awaken the participant on the premise that they had to fix equipment. If the participant completely awoke on any stimulus, a lower intensity stimulus was used on the next occasion.

The morning following the experimental PSG resistive load testing occurred. The procedures were identical to the adaptation resistive load testing and commenced at the same time (10:00 AM to 11:30 AM) that each participant completed the adaptation resistive load testing.

Data Analysis

A trained sleep technician who was blinded to experimental hypotheses and conditions scored sleep and arousals during the adaptation and experimental PSG.17 Respiratory events were scored only on the adaptation PSG.18

EMGGG signals were rectified and smoothed with a moving-time average time constant of 100 ms (Spike 2, CED Cambridge United Kingdom). The EMGGG was converted to a percentage of the participant's maximal activity by using the highest activity attained (100%) during the calibration maneuvers (tongue protrusions and swallows) and electrical zero (0%).

Muscle and respiratory data during the resistive load tests were analyzed breath by breath. The time points of interest during the restive load tests were the baseline measures (attained in the first 5 minutes) and the 8 load trials (the first 60 seconds pre-load and the 60 seconds during the load).

For each breath, during the time points of interest, custom written software extracted minute ventilation (VI), inspiratory duty cycle (TI/TTOT), peak inspiratory flow (PIF), nadir mask pressure (nadir Pmask), maximal genioglossus activity during inspiration (peak EMGGG), and lowest genioglossus activity during expiration (tonic EMGGG). If swallowing or artifact was present on any signal traces (eg, due to movement), or if the EEG was indicative of sleep, the affected breath was removed from analyses.

Statistical Analysis

Data are presented as mean ± standard deviation (SD) unless otherwise indicated. Normality was assessed using Shapiro-Wilk tests. Demographics between groups (control versus sleep deprivation versus sleep fragmentation) were assessed with one-way analysis of variance (ANOVA). Sleep parameters between groups on the adaptation and experimental PSG were assessed with one-way ANOVAs. Two-way mixed ANOVAs (group by session – adaptation versus experimental) assessed baseline differences in respiratory and muscle variables between groups and session during the resistive load tests. Three-way mixed ANOVAs (group × session × load condition – pre-load, 10 cmH2O load and 20 cmH2O load) compared differences in respiratory and muscle variables, between groups, sessions and loading conditions. Where sphericity assumptions were violated, Greenhouse-Geisser corrections were applied. Significance was set at P < .05.

RESULTS

Adequate data were obtained from 19 participants (control = 5, sleep deprivation = 7 and sleep fragmentation = 7). Data from five participants was discarded because one control and two sleep deprivation participants had their intramuscular wires fall out prior to the second day of testing; due to discomfort one sleep fragmentation participant requested the wires to be removed and one control participant was withdrawn from the protocol because study requirements had been violated.

There were some violations of normality when assessed using Shapiro-Wilk test (see Table S1 in the supplemental material for details). As violations were infrequent and sample size was small, no transformations were applied.

The demographics of the participants included in the control, deprivation, and fragmentation groups and are listed in Table 1. As shown, there were no significant differences between the groups with respect to age, height, weight, or body mass index (BMI).

Demographics for the control, deprivation and sleep fragmentation groups.

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Table 1

Demographics for the control, deprivation and sleep fragmentation groups.

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There were no significant differences in sleep indices between groups on the adaptation PSG (Table 2). There were, however, significant differences between the control and fragmentation groups on the experimental PSG (Table 2). The arousal index was significantly higher for the fragmentation group compared to the control group, as per the intervention aim. The fragmentation group also had significantly more minutes of stage N1 sleep and significantly fewer minutes of stage N3 sleep and stage R sleep than the control group. There were no significant differences between the control and fragmentation groups in respect to total sleep time, stage N2 sleep, or sleep efficiency.

Sleep parameters for the control, deprivation, and fragmentation groups during PSG.

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Table 2

Sleep parameters for the control, deprivation, and fragmentation groups during PSG.

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The respiratory and muscle parameters during the baseline recordings are shown in Table 3. For the respiratory parameters there were no group effects or group by session interaction effects. There was a significant main effect of session as VI was significantly less (P = .008) during the adaptation session (8.0 ± 0.4) compared to the experimental session (8.6 ± 0.4). Similarly, TI/TTOT was significantly less (P = .003) during the adaptation session (0.40 ± 0.04) compared to the experimental session (0.42 ± 0.05). For the muscle parameters there was no session or session by group effects. There was a significant group effect for peak and tonic EMGGG. Pairwise comparisons demonstrated that the sleep fragmentation group had significantly greater (P < .01) baseline peak EMGGG activity (mean % max 4.7 ± 0.6) than the control (1.2 ± 0.7) and sleep deprivation groups (1.9 ± 0.6). As Levene test of equality of variance was violated for tonic EMGGG (P = .026 for the adaptation session), Dunnett T3 was used for pairwise comparisons, which demonstrated that the sleep fragmentation group (mean % max 2.2 ± 0.2) had significantly (P < .001) greater baseline tonic EMGGG activity compared to the control (mean % max 0.5 ± 0.2) and sleep deprivation (mean % max 0.7 ± 0.2) groups.

Baseline respiratory and muscle parameters for each of the groups during the adaptation and experimental sessions.

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Table 3

Baseline respiratory and muscle parameters for each of the groups during the adaptation and experimental sessions.

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Respiratory parameters during the adaptation and experimental sessions for the pre-load, 10 cmH2O load, and 20 cmH2O load conditions are shown in Figure 1. There were no interaction effects for VI, TI/TTOT, PIF, or nadir Pmask, nor were there main effects for group or session. There was a significant main effect of load for TI/TTOT, PIF and nadir Pmask. For TI/ TTOT, pairwise comparisons demonstrated significant differences (P < .001) between each of the three load conditions (pre-load = 0.41 ± 0.01, 10 cmH2O load = 0.45 ± 0.01, 20 cmH2O load = 0.49 ± 0.01). Similarly, pairwise comparisons for PIF also demonstrated significant differences (P < .001) between each of the load conditions (mean L/min for pre-load = 29.4 ± 1.2, 10 cmH2O load = 27.5 ± 1.4 and 20 cmH2O load = 24.8 ± 1.5), as did nadir Pmask (mean cmH2O for pre-load = −1.3 ± 0.1, 10 cmH2O load = −5.1 ± 0.3 and 20 cmH2O load = −8.2 ± 0.5). There was no significant main effect of load for VI.

Ventilatory parameters during the adaptation and experimental resistive load sessions during the pre-load, 10 cmH2O load, and 20 cmH2O load.

Minute ventilation (VI), inspiratory duration/total breath duration (TI/TTOT), peak inspiratory flow (PIF), and nadir Pmask (cmH2O) during pre-load, 10 cmH2O loads and 20 cmH2O loads for the control, deprivation, and fragmentation groups on the adaptation session (blue line) and the experimental (red line) session. Asterisk (*) indicates a significant (P < .05) load effect. Error bars are standard error.

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Figure 1

Ventilatory parameters during the adaptation and experimental resistive load sessions during the pre-load, 10 cmH2O load, and 20 cmH2O load.

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Genioglossus parameters during the adaptation and experimental sessions for the pre-load, 10 cmH2O load, and the 20 cmH2O load conditions are shown in Figure 2. There were no interaction effects for peak or tonic EMGGG, nor were there main effects of session. There was a significant main effect of load for both peak EMGGG and tonic EMGGG. Pairwise comparisons demonstrated significant differences (P < .01) between each load condition for Peak EMGGG (mean % max for pre-load = 2.8 ± 0.4, 10 cmH2O load = 3.3 ± 0.55 and 20 cmH2O load = 4.1 ± 0.6). Pairwise comparisons also demonstrated that tonic EMGGG during the 20 cmH2O load (mean % max = 1.3 ± 0.2) was significantly (P = .049) greater than during the pre-load (1.2 ± 0.1), but not significantly different (P = .057) than during the 10 cmH2O load (1.2 ± 0.2). There was also a significant group effect (P = .024) for peak EMGGG and tonic EMGGG. Pairwise comparisons demonstrated that the sleep fragmentation group had significantly greater (P < .05) peak EMGGG (mean % max = 5.4 ± 0.8) than the control group (2.2 ± 0.9) and the sleep deprivation group (2.6 ± 0.8). Similarly, the fragmentation group also had significantly greater (P < .01) tonic EMGGG (mean % max = 2.1 ± 0.2) than the control group (0.8 ± 0.3) and the sleep deprivation group (0.8 ± 0.2).

Genioglossus muscle activity during the adaptation and experimental resistive load sessions during the pre-load, 10 cmH2O load, and 20 cmH2O load.

Peak genioglossus muscle activity (peak EMGGG) and tonic genioglossus muscle activity (tonic EMGGG) during pre-load, 10 cmH2O loads, and 20 cmH2O loads for the control, deprivation, and fragmentation groups. The blue line indicates the adaptation session and the red line indicates the experimental session. Asterisk (*) indicates a significant (P < .05) load effect. Hash (#) indicates a significant group effect. Error bars are standard error.

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Figure 2

Genioglossus muscle activity during the adaptation and experimental resistive load sessions during the pre-load, 10 cmH2O load, and 20 cmH2O load.

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DISCUSSION

This study found that neither sleep deprivation nor sleep fragmentation had an adverse effect on genioglossus or ventilatory responsiveness to resistive loading during subsequent wakefulness. For all groups, the magnitude of the genioglossus and ventilatory response was proportional to the load magnitude and did not differ between the adaptation and experimental sessions.

Sleep Deprivation Effects on Genioglossus Muscle Responsiveness to Resistive Loading

In this study sleep deprivation did not reduce peak or tonic genioglossus muscle responsiveness to resistive loading during wakefulness. This finding is inconsistent with the study by Leiter et al.,1 which demonstrated that a single night of sleep deprivation reduced genioglossus responsiveness to hypercapnia in healthy individuals during wakefulness. In the study by Leiter et al. hypercapnia was assessed at five different CO2 levels between 50 mmHg and 64 mmHg. Following sleep deprivation, genioglossus activity was reduced for one CO2 level (approximately 53–55 mmHg). However, when only participants aged 30 years or older were considered, genioglossus activity was significantly reduced at three CO2 levels (approximately 53–55 mmHg, approximately 56–58 mmHg, approximately 59–61 mmHg). From this the authors concluded that sleep deprivation adversely affected dilator muscle responsiveness in older adults. We are aware of only one other study that has assessed sleep deprivation effects on genioglossus activity.9 This study is yet to be published but preliminary analysis of nine participants in an abstract reported that in healthy individuals a single night of sleep deprivation reduced the genioglossus response to moderate hypercapnia (+10 mmHg above normocapnia) and resistive loading (15 cmH2O).

It is unclear why there is a discrepancy between the current and prior studies. One potential explanation is participant age. For the study by Leiter et al.1 sleep deprivation effects were most apparent in those aged 30 years or older. Similarly, the same group of authors demonstrated that diazepam reduced genioglossus muscle responsiveness to CO2 rebreathing in healthy individuals, but only in the participants aged 30 years or older.19 For the study reported in an abstract, the age range of participants was 19 to 50 years. In contrast, the participants in the current study were relatively young, ranging from 20 to 32 years of age. Together these findings suggest that older age may be associated with a vulnerability to reduced dilator muscle responsiveness. Genioglossus muscle responsiveness to negative pressure pulses progressively decreases with age.20 Perhaps with this decline, the genioglossus also becomes more susceptible to inhibitory influences such as sleep deprivation.

In the current study, genioglossus activity increased only minimally in response to loading and this may have limited the ability to detect an adverse effect of sleep deprivation. For instance, in the sleep deprivation group, peak genioglossus activity during the pre-load was approximately 3% of max and increased by only approximately 1% of max during the 20 cmH2O load. This was presumably because the participants were young and healthy, and therefore did not require a large increase in genioglossus activity to maintain ventilation during the load. This may have, however, resulted in a floor effect whereby participants were already close to their “minimal activity,” such that sleep deprivation did not adversely affect genioglossus activity to an extent that was either statistically or physiologically significant. In individuals with OSA, who are heavily reliant on their dilator muscles to keep the upper airway patent, genioglossus activity is increased during wakefulness relative to healthy controls.2124 Therefore, in individuals with OSA sleep deprivation effects may be more apparent.

The discrepancy between studies may also be accounted for by methodological differences. For instance, the study by Leiter et al.1 used surface electrodes attached to an intraoral appliance to measure genioglossus activity. Surface EMG can be problematic because it is sensitive to crosstalk from other neighboring muscles.25 In contrast, fine-wire electromyography, as used in the current study, is a more conventional measure of genioglossus muscle activity that minimizes crosstalk. Therefore, discordant findings may be due to measurement technique. However, this does not explain the discrepancy between our study and the study reported in an abstract that also used intramuscular wires.9 The duration of sleep deprivation may have also been a factor. For the study reported in an abstract, genioglossus responsiveness was assessed in the evening before bed following approximately 34 hours of sleep deprivation, whereas for the current study genioglossus responsiveness was assessed in the morning following approximately 26 hours of sleep deprivation. For the study by Leiter et al. the exact duration of sleep deprivation was not reported but assessments were conducted in the morning.1 Another methodological difference was that in the study by Leiter et al.1 EEG was not monitored during genioglossus assessment. Therefore, as acknowledged by the authors, it is possible that the participants fell asleep during the wakefulness assessment that followed sleep deprivation and this may have reduced dilator muscle activity. The authors state that this was unlikely because the participants' eyes were open throughout testing. In the current study, any breaths associated with EEG indicative of sleep or dozing (theta activity) were discarded. Therefore, more rigorous methodology in the current study may have accounted for the null finding. In addition, it has been demonstrated that during wakefulness females have a greater magnitude genioglossus response to inspiratory resistive loads.26 For the current study 8 of 19 participants were female, whereas for the study by Leiter et al.1 all participants were male and in the abstract reported by Eckert et al., 2 of 9 participants were female.9 Thus, the higher proportion of females in the current study may have accounted for the disparate findings between studies. However, when comparing peak genioglossus responsiveness to the 20 cmH2O load on the adaptation night in the current study, there were no significant differences between males (5.53 ± 2.99 % max) and females (3.44 ± 2.05 % max), suggesting that sex was unlikely to account for the observed differences. Finally, the eliciting stimulus may be a factor. For the Leiter et al.1 study and the abstract report9 the eliciting stimulus was hypercapnia via rebreathing, whereas for the current study it was negative pressure via resistive loading. It is recognized that the genioglossus is highly responsive to negative pressure stimuli, and therefore the negative pressure response may be more resilient to sleep deprivation effects than the hypercapnic response. Further studies would be required to determine whether this is the case.

Sleep Fragmentation Effects on the Genioglossus Muscle Response to Loading

This is the first study to assess sleep fragmentation effects on dilator muscle activity. Sleep fragmentation doubled the arousal index (from 19 to 43), increased stage N1 sleep, and decreased stage N3 and stage R sleep. Despite this, neither the peak nor the tonic genioglossus response to resistive loading differed between the adaptation and experimental loading sessions for the sleep fragmentation group. Therefore, reduced deep sleep and increased arousal frequency do not appear to affect the dilator muscle response to negative pressure. This finding contrasts with the study by Sériès et al., which suggested that dilator muscle function is more affected by sleep fragmentation than sleep deprivation.11 The study by Sériès et al. demonstrated that upper airway collapsibility, as measured by critical closing pressure during sleep, was worse following sleep fragmentation than sleep deprivation. From this it was inferred that reduced dilator muscle function, secondary to the depressive effects of sleep fragmentation, was likely responsible for the increased collapsibility. For the current study, the age of the participants was similar to those in the study by Sériès et al. (20–27 years).11 In addition, for the current study sleep fragmentation was more severe (mean arousal index = 43 ± 4) than in the study by Sériès et al. (32 ± 2).11 Despite this, no adverse effect of sleep fragmentation on dilator muscle activity was observed for the current study. It is possible that sleep fragmentation only affects genioglossus muscle responsiveness during sleep and not during wakefulness. Indeed, in OSA the dilator muscles are able to increase their activity to effectively overcome collapse during wakefulness but cannot always do so in sleep. Sleep deprivation may have a similar effect, whereby impairment is only present during sleep and not during wakefulness.

Sleep Deprivation and Sleep Fragmentation Effects on the Ventilatory Response to Loading

The ventilatory response to loading did not differ between the adaptation and experimental sessions for either the sleep deprivation or sleep fragmentation group. There were expected effects of load on the ventilatory parameters, as loading decreased both PIF and mask pressure and increased duty cycle. The magnitude of change observed in these variables was proportional to load magnitude. The only other studies to have assessed the effects of sleep deprivation and fragmentation on ventilatory responsiveness used chemical stimuli to elicit the responses. The studies that assessed sleep deprivation generally reported reduced hypercapnic and hypoxic ventilatory responses during wakefulness,68 although the study by Leiter et al.1 found no change in the hypercapnic ventilatory response following sleep deprivation. A study of sleep fragmentation also demonstrated no difference in the hypercapnic and hypoxic ventilatory response during wakefulness following sleep fragmentation compared to normal sleep.10 Therefore, given the mixed findings, further work is required to determine whether sleep deprivation and sleep fragmentation adversely affect the ventilatory response.

Limitations

Although in the larger study there were 33 participants, some opted out of the genioglossus assessment. As a result, the groups had a small sample size (control = 5, sleep deprivation = 7 and sleep fragmentation = 7) and thus it is possible that the study was underpowered to detect significant differences between conditions. Leiter et al. demonstrated adverse effects of sleep deprivation in a sample of only 7 healthy individuals, but those individuals were aged 30 years or older.1 In a younger cohort who are potentially less susceptible to sleep disruption, larger sample sizes may be required to demonstrate an adverse effect. Indeed, for the sleep deprivation group there was a non-significant trend toward reduced genioglossus activity, as during the 20 cmH2O load peak genioglossus activity on the adaptation session was 4.0 ± 1.1% of max compared to 2.0 ± 1.0% of max during the experimental session. Perhaps with increased participant numbers a significant difference may have been detected. However, there was no similar trend for sleep fragmentation, which is more characteristic of the nightly sleep disturbance in OSA than sleep deprivation. In addition, we did not screen for a familial history of OSA. It has been demonstrated that the offspring of parents with OSA have smaller magnitude ventilatory responses to inspiratory resistive loading, even if they do not themselves have OSA.27 Therefore, we were not able to control for these potential confounding effects. Another limitation was that because of equipment availability, the sleep fragmentation group were mostly assessed last and not randomized between the control and sleep deprivation groups. Interestingly, genioglossus activity was systematically higher during both sessions for the sleep fragmentation group, although why this was the case is unclear as respiratory parameters did not differ significantly between groups, nor did the anthropometric variables that are known to affect genioglossus activity (age, weight, and BMI). It is possible that the sleep fragmentation group, simply by chance, had higher genioglossus activity, but importantly, this group showed no difference or trend toward difference between the adaptation and experimental sessions, and therefore the baseline differences were not considered important. It is possible that individuals with inherently higher baseline levels of dilator muscle activity are less susceptible to inhibitory effects, but this remains to be assessed. A further limitation was that there was a nonsignificant trend toward a group effect for BMI (P = .115) which may have become significant with increased sample size. However, because prior research has demonstrated no effect of obesity on dilator muscle responsiveness in healthy individuals,28 we believe the slight BMI differences are unlikely to have had a major influence on outcomes. An additional weakness was that pharyngeal pressures were not measured; therefore, we do not know if the genioglossus-pressure relationship was altered under the sleep deprivation and fragmentation interventions and thus caution should be applied when interpreting the results. Further, sampling only from the genioglossus muscle to infer overall dilator muscle function is limited. The genioglossus muscle was selected because it is the dilator muscle most commonly assessed and is believed to have a clear role in the maintenance of upper airway patency.29 It also was feasible to leave in the recording electrodes for 24 hours due to percutaneous insertion. However, the genioglossus is primarily a phasic muscle and is highly responsive to negative pressure stimuli. It is possible that other muscles such as the tensor palatini, which is primarily a tonic muscle, may respond differently.

Implications

This study demonstrated that genioglossus and ventilatory responsiveness to resistive loading was not affected by either sleep deprivation or fragmentation. Therefore, at least in healthy, young individuals, poor sleep or lack of sleep does not appear to influence upper airway function during wakefulness. For individuals with OSA, who experience sleep fragmentation secondary to upper airway collapse, it is thought that poor sleep quality worsens dilator muscle activity and therefore increases OSA severity. This pattern of upper airway collapse and sleep disruption is considered to be a perpetuating cycle. The current study suggests this is not the case. However, whether these findings apply to patients with OSA who have a greater reliance on dilator muscles to prevent upper airway collapse is unknown. It has been demonstrated that for patients with OSA, during wakefulness, the genioglossus-pressure slope response to resistive loading is comparable to healthy individuals.22 Similarly, the responsiveness of the genioglossus to negative pressures during induced obstruction in sleep does not differ between healthy controls and patients with OSA.30 However, even if the dilator muscle responses to resistive loading are similar during sleep in patients with OSA, their airways are more critically reliant on the amount of muscle activity present and therefore the adverse effects of sleep deprivation or fragmentation may be more apparent. Thus, studies should assess the effects of disrupted sleep on upper airway dilator muscle responsiveness in patients with OSA during sleep, as well as consider age-related effects.

CONCLUSIONS

This study demonstrated that genioglossus muscle and ventilatory responsiveness to inspiratory resistive loads during wakefulness is not affected by either sleep fragmentation or sleep deprivation. Although this may be related to insufficient power, it is possible that neither a lack of sleep nor poor sleep quality contributes to a worsening of upper airway function in response to high resistances. Further work needs to assess whether these results extend beyond healthy, young individuals to individuals with OSA, whom are typically older in age and have anatomically compromised upper airways, and thus unlike healthy individuals are highly dependent on the upper airway dilator muscles to maintain airway patency, particularly during sleep.

DISCLOSURE STATEMENT

All authors have seen and approved the final manuscript. Work for this study was performed at the Melbourne School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia. Dr. Jordan and the study were supported by the Australian Research Council (FT100100203). Dr. Jackson was supported by a National Health and Medical Research Council of Australia Early Career Fellowship (APP1036292). The study was also supported by an Institute for Breathing and Sleep research grant. The authors report no conflicts of interest.

ABBREVIATIONS

BMI

body mass index

CO2

carbon dioxide

ECG

electrocardiogram

EEG

electroencephalogram

EMG

electromyogram

EMGGG

genioglossus electromyogram

EOG

electrooculogram

OSA

obstructive sleep apnea

peak EMGGG

maximal genioglossus activation during inspiration

PIF

peak inspiratory flow

PSG

polysomnography

TI/TTOT

duty cycle

tonic EMGGG

lowest genioglossus activation during expiration

VI

minute ventilation

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