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Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References
  7. Appendix

One postulated mechanism for obstructive sleep apnoea (OSA) is insufficient drive to the upper-airway musculature during sleep, with increased (compensatory) drive during wakefulness. This generates more electromyographic activity in upper airway muscles including genioglossus. To understand drives to upper airway muscles, we recorded single motor unit activity from genioglossus in male groups of control (n= 7, 7 ± 2 events h−1) and severe OSA (n= 9, 54 ± 4 events h−1) subjects. One hundred and seventy-eight genioglossus units were recorded using monopolar electrodes. Subjects were awake, supine and breathing through a nasal mask. The distribution of the six types of motor unit activity in genioglossus (Inspiratory Phasic, Inspiratory Tonic, Expiratory Phasic, Expiratory Tonic, Tonic and Tonic Other) was identical in both groups. Single unit action potentials in OSA were larger in area (by 34%, P < 0.05) and longer in duration (by 23%, P < 0.05). Inspiratory units were recruited earlier in OSA than control subjects. In control subjects, Inspiratory Tonic units peaked earlier than Inspiratory Phasic units, while in OSA subjects, Inspiratory Tonic and Phasic units peaked simultaneously. Onset frequencies did not differ between groups, but the peak discharge frequency for Inspiratory Phasic units was higher in OSA (22 ± 1 Hz) than control subjects (19 ± 1 Hz, P= 0.003), but conversely, the peak discharge frequency of Inspiratory Tonic units was higher in control subjects (28 ± 1 Hz versus 25 ± 1 Hz, P < 0.05). Increased motor unit action potential area indicates that neurogenic changes have occurred in OSA. In addition, the differences in the timing and firing frequency of the inspiratory classes of genioglossus motor units indicate that the output of the hypoglossal nucleus may have changed.

The patency of the human upper airway is influenced by neural activity to airway dilator muscles. Reduced neural drive to these muscles could contribute to the development of obstructive sleep apnoea (OSA), a disorder in which the upper airway collapses repetitively during sleep. Obstructive sleep apnoea affects ∼4% of adult males and is more common in the elderly (e.g. Young et al. 1993; Kim et al. 2004) and the obese (Resta et al. 2001).

The human genioglossus muscle is one of the largest extrinsic muscles of the tongue (Abd-El-Malek, 1938; Takemoto, 2001) and directly dilates the upper airway. It contracts during inspiration and maintains some activity during expiration (e.g. Sauerland & Harper, 1976; Remmers et al. 1978; Hudgel & Harasick, 1990; Mezzanotte et al. 1992; Otsuka et al. 2000; Akahoshi et al. 2001; Fogel et al. 2001). Its contraction pulls the base of the tongue forward (Abd-El-Malek, 1938; Brouillette & Thach, 1979) and, together with other muscles, enlarges the upper airway (e.g. Lowe, 1980; Schwartz et al. 1996, 2001; Fuller et al. 1999; Sokoloff, 2000; Oliven et al. 2001; Mann et al. 2002; Bailey & Fregosi, 2004).

Multiunit electromyographic activity (EMG) of genioglossus is greater in OSA subjects than in healthy subjects during wakefulness (Mezzanotte et al. 1992; Fogel et al. 2001). It is believed this reflects increased drive to airway dilator muscles and that this increased drive is needed to overcome the increased upper airway resistance and compliance (e.g. Malhotra & White, 2002; Randerath, 2006). During sleep, the compensatory increased drive appears to be lost leading to repetitive airway collapse (Gastaut et al. 1966; Suratt et al. 1988; Wheatley et al. 1993).

We recently demonstrated in awake healthy subjects that motor units innervating genioglossus show a variety of discharge patterns during the respiratory cycle (Saboisky et al. 2006a). While the majority of units discharge phasically or increase their discharge frequency with inspiration (Inspiratory Phasic and Inspiratory Tonic units), a minority discharge more during expiration (Expiratory Phasic and Expiratory Tonic units). Moreover, ∼15% of the units discharge tonically without respiratory modulation (Tonic and Tonic Other units). Thus, the neural control of the genioglossus is complex (e.g. Hwang et al. 1983; Haxhiu et al. 1992), as its motor nucleus receives multiple premotoneuronal drives during normal awake breathing (e.g. Ugolini, 1995; Peever et al. 2002; Chamberlin et al. 2007; for review see Gestreau et al. 2005).

No information exists about the discharge of single motor units which generate the increased multiunit EMG in genioglossus in OSA. It is not known if the increased EMG is due to a uniform increase in firing frequencies of all motor units or whether some of the six patterns change selectively. However, an alternative possibility is that changes in the morphology of the action potentials of active motor units generate the increased multiunit EMG. Such peripheral changes may reflect muscle fibre hypertrophy (Carrera et al. 1999) or neurogenic changes affecting motor axons (Svanborg, 2005; Hagander, 2006).

To address these questions, we measured the activity of populations of single motor units from the genioglossus in control and OSA subjects breathing quietly while awake. We investigated both peripheral and central causes for the alterations in genioglossus EMG activity seen in OSA. We hypothesized that firing rates would be higher in OSA and that unit types with an inspiratory firing pattern would occur more frequently. Some data from this study have been previously presented in abstracts (Saboisky et al. 2006b, 2007a; Butler et al. 2007).

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References
  7. Appendix

Studies were performed on seven male healthy age-matched volunteers and nine male subjects with untreated obstructive sleep apnoea (OSA). Anthropometric details of the group are given in Table 1. The data from one control subject who had full polysomnography (see below) came from a previous study (Saboisky et al. 2006a). All other control and OSA subjects were new. All subjects gave informed written consent to the procedures, which had been approved by the Human Research Ethics Committee of the University of New South Wales. The study conformed with the Declaration of Helsinki. All subjects underwent a formal sleep study and a separate neurophysiological examination.

Table 1.  Group data for OSA and control subjects
 ControlOSA
  1. OSA: Obstructive sleep apnoea, BMI: Body mass index; AHI apnoea/hypopnea index; ESS: Epworth sleepiness scale. mean ±s.e.m. for the inspiratory time, expiratory time, ventilation, tidal volume, mean inspiratory flow and respiratory frequency. For each group a mean value is derived from the mean for each subject. There were no significant differences for the ventilatory data between the two groups (P > 0.05). † Values for BMI, neck circumference and AHI were significantly larger in the OSA than control group (P > 0.05).

Subjects79
Age (years)45 ± 4  51 ± 5  
BMI (kg m−2) 24 ± 0.533 ± 3†
Neck circumference (cm)40 ± 1 43 ± 1†
AHI (events h−1)7 ± 254 ± 4†
ESS5.8 ± 1.58.3 ± 2.0
Inspiratory time (s)1.9 ± 0.21.6 ± 0.1
Expiratory time (s)2.5 ± 0.22.4 ± 0.2
Ventilation (l min−1)8.2 ± 0.69.2 ± 0.4
Tidal volume (l)0.59 ± 0.040.60 ± 0.03
Mean inspiratory flow (l s−1)0.32 ± 0.020.37 ± 0.02
Respiratory frequency (breaths min−1)13.8 ± 0.7115.8 ± 0.88
Number of units7999

Sleep studies

All subjects underwent full overnight polysomnography with recordings of the electroencephalogram, electrooculogram, chin and surface electromyographic activity (EMG) from tibialis anterior, electrocardiogram, nasal (pressure) and oral flow (thermister), respiratory (chest and abdominal) movements, oxyhaemoglobin saturation (pulse oximeter) and body position. All signals were recorded for offline analysis (EMBLA, Reykjavik, Iceland). The apnoea-hypopnoea index (number of apnoeas plus hypopnoea per hour of sleep) was determined using AASM guidelines (American Academy of Sleep Medical Task Force, 1999). The Epworth sleepiness scale (ESS) assessed subjective sleepiness.

Neurophysiological studies

Subjects breathed quietly through a sealed nose mask connected to a pneumotachometer (3700 series, Hans-Rudolph Inc, Kansas City, MO, USA) with their mouth closed (Fig. 1A). The flow signal was integrated to give volume. Subjects lay comfortably supine and relaxed, breathed quietly and remained awake throughout the procedure. All EMG recordings were obtained during periods when subjects experienced minimal or no discomfort as measured with a 10-point Borg scale. There was no difference between the control or OSA subjects in the discomfort they felt during recordings (control 1.5 ± 0.4 and OSA 0.7 ± 0.3, mean ±s.e.m.). However, for one control subject the experimental procedures were stopped prematurely after significant discomfort was reported.

image

Figure 1. Recording of single motor unit activity in the genioglossus A, experimental set-up showing subject lying supine. The monopolar electrode was positioned 10 mm posterior to the genial tubercle of the mandible and 3 mm from the midline with the reference electrode over the left mandible and a ground electrode above the right clavicle. Subjects breathed through a nasal mask that was connected to a pneumotachograph. The dotted rectangle under the chin indicates where the ultrasound transducer was positioned. B, an image recorded in the sagittal plane using ultrasonography to show the location and depth of geniohyoid and genioglossus muscles and the site of insertion of the monopolar electrode. C, from bottom to top traces, the raw EMG, rectified and integrated EMG (time constant, 50 ms, calibration 0–40 μV), flow, volume, instantaneous frequency plots for 2 units, and the superimposed motor unit potentials for each unit (inset). Two simultaneously recorded units increase their discharge in phase with inspiration. Unit 1 was classed as Inspiratory Tonic and Unit 2 as Inspiratory Phasic. Inset calibrations 400 μV and 2 ms. D, a typical example of an averaged motor unit potential (∼50 sweeps). The shaded modulus indicates the area measured; duration and peak to peak amplitude were also measured.

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To determine the depth and location for the recording electrode in genioglossus, the local anatomy of the upper airway musculature was examined with ultrasonography (Fig. 1B, model 128XP/4; Acuson, Mountain View, USA) (Eastwood et al. 2003; Saboisky et al. 2006a). Motor unit activity was recorded using a Teflon-coated monopolar needle electrode (TECA, Oxford Instruments, 0.46 mm diameter, recording area 0.34 mm2, impedance 100 kΩ at 1 kHz). A reference electrode was positioned over the mandible. The needle electrode was inserted ∼10 mm posterior to the inner border of the mental protuberance and ∼3 mm lateral to the midline perpendicular to the skin to a depth determined from the ultrasound measurements. EMG was filtered (53 Hz to 3 kHz), amplified (×1000–10 000), sampled at 10 kHz, stored on computer for analysis (Spike2 with 1401 interface, Cambridge Electronic Design, Cambridge, UK), as well as monitored continually on an oscilloscope. Genioglossus EMG activity was recorded during stable quiet breathing for a minimum of 10 breaths at each recording site (Fig. 1C). Once a stable recording was made the monopolar needle was moved to a new site. We aimed to record from 10 different intramuscular sites via one to three skin insertions in each subject.

Single motor units sorting and classification

Motor unit potentials were extracted from the raw electromyographic signal using a spike-triggered threshold. Individual single motor units were sorted into ‘templates’ based on their amplitude and detailed morphology (Spike2 analysis system). Manual re-inspection of all motor unit potentials confirmed the sorting. Instantaneous frequency plots were derived from the time of discharge of the unit. The activity of each motor unit was then classified into one of six types based on its pattern of discharge during the respiratory cycle determined from the airflow signal (Fig. 1C) (Saboisky et al. 2006a).

All units were classified into tonic or phasic categories depending on whether they discharged throughout both inspiration and expiration (Tonic), or only during either inspiration or expiration (Phasic). Units were further classified according to the timing of their peak activity: ‘Inspiratory Phasic’ motor units discharged phasically with their peak frequency during inspiration; ‘Expiratory Phasic’ units discharged phasically with their peak frequency during expiration; ‘Inspiratory Tonic’ units discharged through inspiration and expiration, but increased their discharge frequency during inspiration; and ‘Expiratory Tonic’ units discharged through inspiration and expiration but increased their discharge during expiration. ‘Tonic’ units discharged throughout inspiration and expiration with no obvious respiratory modulation of discharge frequency. A small number of units discharged continuously with some modulation but not in time with the respiratory cycle and they were classified as ‘Tonic Other’ units. In addition to this categorization of the different types of motor unit activity, cross-correlations between volume (from the integrated flow signal) and instantaneous firing frequency (smoothed over 200 ms) were computed for all possible phase differences between the two signals. The strength of each correlation was evaluated by calculating the linear coefficient of determination (r2) and the timing of the maximal value of this coefficient. The respiratory phase of the maximal r2 (lag time) indicated whether the unit had a predominant inspiratory or expiratory modulation (see Fig. 3, Table 2).

image

Figure 3. Classification of single motor unit units in genioglossus based on their firing frequency–volume coefficient of determination A (obstructive sleep apnoea subjects) and B (control subjects) plot the strength (coefficient, r2) and the time of the peak cross-correlations for each unit. The correlations were calculated between volume (inspiratory or expiratory) and the discharge frequency (smoothed over 200 ms) of the motor unit by computing all possible x-axis phase differences between the two signals (see Methods). Time zero represents the end of inspiration. Units were classified into Inspiratory Phasic (filled circles), Inspiratory Tonic (half-filled circles), Expiratory Phasic (filled squares), Expiratory Tonic (half-filled squares), and Tonic and Tonic Other units (crosses). In general, Tonic units showed low r2 values (< 0.4), while units with a clear respiratory modulation had high r2 values (> 0.4). Inspiratory units had a peak r2 before the end of inspiration (negative times) and expiratory units had a peak r2 after the end of inspiration during expiration (positive times).

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Table 2.  Correlation between firing frequency and volume for single units with different patterns of firing in OSA and control subjects
 ControlOSA
Lag time (s)r2Lag time (s)r2
  1. The mean correlation and lag time for units in the genioglossus muscle for both the control and OSA subjects are shown (mean ±s.e.m.). Negative lag times indicate that the peak correlation between firing frequency and volume occurred prior to the end of inspiration (see Methods and Saboisky et al. 2006a).

Inspiratory Phasic−1.0 ± 0.10.75 ± 0.02−1.0 ± 0.10.77 ± 0.02
Inspiratory Tonic−1.1 ± 0.10.63 ± 0.03−1.1 ± 0.10.61 ± 0.03
Expiratory Phasic+0.6 ± 0.50.31 ± 0.09+0.80.42
Expiratory Tonic+1.1 ± 0.30.54 ± 0.06+0.6 ± 0.40.55 ± 0.07
Tonic 0.3 ± 0.20.29 ± 0.04 0.4 ± 0.20.37 ± 0.05
Tonic Other 0.4 ± 0.40.42 ± 0.08 0.4 ± 0.30.41 ± 0.07

Measurement of discharge properties of single motor units

Measurements of each motor unit's action potential were derived from an average of the electromyographic signal that was triggered by the discharge of the unit (n∼50 potentials). Figure 1D shows a typical example. As indicated on the figure, the following parameters were measured: peak-to-peak amplitude of the motor unit action potential, its duration, and its area.

Measurements of single motor unit discharge behaviour were derived from instantaneous frequency plots for each motor unit. Discharge timing was expressed relative to the integrated flow signal. For Phasic units, the time of onset of discharge was measured at the first discharge for each breath and the end time was measured at the last discharge in each breath. For Inspiratory and Expiratory Tonic units, onset time was taken visually from when the discharge frequency first increased above the tonic levels and the end time when the discharge frequency first returned to the tonic level. Onset discharge frequency for Phasic units was calculated from the first interspike interval for each breath. For Inspiratory Tonic and Expiratory Tonic units, onset firing frequency was measured at the first increase in the discharge frequency above the tonic level. Peak discharge frequencies were derived from the peak of the instantaneous frequency with a running average for each breath (smoothed over 200 ms). A time-and-frequency plot (TAF Plot) which depicts the timing and frequency of firing for each unit was used to depict the data from the whole sample of units throughout the respiratory cycle (see also Saboisky et al. 2007b). All measurements of the firing behaviour were made with a suite of custom programs using Spike2.

All variables were averaged across three typical consecutive breaths. Statistical differences for the discharge parameters were assessed using either a one-way or two-way analysis of variance (ANOVA) with Student–Newman–Keuls post hoc analysis. If data were not normally distributed then the Kruskal–Wallis test was applied or two-way ANOVA was performed on ranks. Differences in behaviour and distribution of unit types were analysed with Fisher's exact tests and Chi-square tests. Statistical significance was set at P < 0.05. Values are given as the means ±s.e.m.

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References
  7. Appendix

Neural drive to the genioglossus was compared in healthy age-matched control subjects and obstructive sleep apnoea subjects (OSA) during wakefulness. Based on full polysomnography, the apnoea hypopnoea index in control subjects was significantly lower than the OSA subjects who were severely affected (mean ±s.e.m., 7.3 ± 1.6 events h−1, versus 54.7 ± 4.3 events h−1, P < 0.001). Measurements were made from 178 single motor units recorded from the genioglossus during quiet breathing (see Methods). The mean number of motor units recorded from control and OSA subjects was 10 ± 1 (range 1–17). There was no significant difference for inspiratory time, expiratory time, ventilation, tidal volume, mean inspiratory flow, or respiratory frequency when recordings from the two groups were compared. Baseline data for the two groups are given in Table 1.

Properties of single motor units

The mean peak-to-peak amplitude of motor unit action potentials for units recorded during quiet breathing in the control subjects (550 ± 43 μV) was slightly lower (∼10%) than OSA subjects (603 ± 35 μV) although this difference was not statistically significant (P= 0.08, Fig. 2A). However, across all units, the duration of motor unit action potentials in control subjects (9.2 ± 2.5 ms) was 23% shorter than in OSA subjects (11.3 ± 3.5 ms, P < 0.05, Fig. 2B). This difference was evident for both phasically and tonically discharging units. Furthermore, when the units were grouped into Phasic and Tonic types, the mean durations of both the control Phasic and Tonic units (9.2 ± 3.2 ms and 9.1 ± 3.9 ms, respectively) were significantly shorter than the, OSA Phasic and Tonic units (11.1 ± 4.3 ms and 11.5 ± 5.6 ms, respectively, P < 0.05). As a consequence, across all units, the mean area of motor unit action potentials of the control subjects (0.64 ± 0.054 μV s) was significantly smaller (by 34%) than the OSA subjects (0.86 ± 0.048 μV s, P < 0.05 (Fig. 2C). Again, this difference was observed in both tonic and phasic units. When the units were grouped into Phasic and Tonic types, the mean modulated areas of the control Phasic units (0.648 ± 0.0654 μV s) were significantly smaller than the OSA Phasic units (0.966 ± 0.069 μV s), control Tonic units (0.629 ± 0.07 μV s) and OSA Tonic units (0.747 ± 0.0789 μV s, P < 0.05). This result suggests that even if the recruitment and firing rate of motor units in control and OSA subjects were the same, the overall multiunit EMG must be greater in OSA subjects simply due to the increased area of their motor unit potentials.

image

Figure 2. Motor unit action potential (MUAP) parameters for genioglossus in control and obstructive sleep apnoea subjects A, mean peak-to-peak amplitude of motor unit action potentials in the control (triangles) and OSA subjects (circles). B, mean motor unit potential duration. In OSA subjects potential duration was significantly longer compared to control subjects (P < 0.05). C, in OSA subjects, the mean area of motor unit potentials was larger than in the control subjects (P < 0.05). Individual values as well as the mean ±s.e.m. are shown in all panels.

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Classification and discharge times of single motor units

The initial classification of the six types of unit activity was confirmed with a correlation of each single unit's firing with the signal of lung volume. Figure 3 shows the timing of the peak correlation for each motor unit plotted against strength of the coefficient of determination (r2) with pooled data in Table 2. In general, Tonic units showed low r2 values (< 0.4), while units with a clear respiratory modulation had high r2 values (> 0.4). Inspiratory units had a peak r2 before the end of inspiration (negative times) and expiratory units had a peak r2 after the end of inspiration during expiration (positive times). Table 3 shows the key firing parameters for the two types of inspiratory units in the control and OSA subjects.

Table 3.  Firing parameter for inspiratory phasic and inspiratory tonic units recorded from the genioglossus in control and OSA subjects recorded during quiet breathing when awake
 Onset time (%TI)Onset frequency (Hz)Peak time (%TI)Peak frequency (Hz)End time (%TI)End frequency (Hz)
  1. Timing and frequency details of the Inspiratory Phasic and Inspiratory Tonic motor unit types for the control and OSA subjects. OSA: Obstructive sleep apnoea,%TI: timing values are normalized as a percentage of inspiratory time (TI), Hz: frequency. For each group a mean value (±sem) is derived from the number of motor units in the classification. *OSA onset time earlier than control subjects. #Peak frequency in OSA subjects is higher than control subjects. **Peak frequency in OSA subjects is lower than the control subjects (P < 0.05).

Inspiratory Phasic units
 Control (n= 41) 5.7 ± 1.512.7 ± 0.447.8 ± 2.519.0 ± 0.8102.0 ± 4.98.9 ± 0.4
 OSA (n= 50) −2.5 ± 1.9*14.2 ± 0.843.0 ± 2.5 22.2 ± 0.8#105.3 ± 5.49.7 ± 0.4
Inspiratory Tonic units
 Control (n= 23)−7.1 ± 1.419.6 ± 1.038.1 ± 3.528.3 ± 1.098.3 ± 4.818.8 ± 1.2
 OSA (n= 28)−14.2 ± 2.2*18.3 ± 0.842.1 ± 5.1  25.4 ± 0.8**109.9 ± 8.118.7 ± 0.8

Figure 4 shows the time-and-frequency plot (TAF Plot) for the discharge for the various types of motor units recorded from the genioglossus throughout the respiratory cycle in the control (left panel) and OSA subjects (right panel). Thick horizontal lines depict the onset and end firing time for each motor unit while the thin horizontal lines denote tonic firing. Data are colour coded for frequency (Saboisky et al. 2007b). The different types of motor unit activity were present in the same proportions in the control and OSA subjects (Chi-square and Fisher exact tests, P > 0.05, Fig. 4). For the control and OSA subjects, about half of the units discharged phasically only during inspiration (51% and 50%, respectively). An additional third of units in control (30%) and OSA (28%) subjects increased their discharge from tonic levels during inspiration and were classified as Inspiratory Tonic units. Small numbers of units were classified as Expiratory Tonic units (∼5%) or Expiratory Phasic units (∼2%). The remaining units were Tonic (∼15%) and discharged throughout inspiration and expiration with no respiratory-related increases in activity. Thus, for both control and OSA subjects, ∼80% of motor units increased their activity during inspiration and ∼50% fired tonically throughout respiration.

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Figure 4. Time-and-frequency Plots of firing of single motor units in the human genioglossus muscle in control subjects and obstructive sleep apnoea subjects during quiet breathing The motor units were sampled during the respiratory cycle and their discharge times are normalized to inspiratory time (0–100% horizontal axis label). A, firing time for control subjects (n= 79 single motor units). B, firing time for each single motor unit for the genioglossus muscle in OSA subjects (n= 99 units). The vertical darkest lines in each panel represent the onset (0%) and end (100%) of inspiration measured from the flow signal. For units which discharged throughout both phases of the respiratory cycle, a continuous horizontal line indicates tonic firing. The time of the peak firing frequency is indicated by a black circle and the mean peak frequency is indicated by the colour of the thick horizontal line. The firing frequencies corresponding to each colour are shown in the inset. The initial and final frequencies are also added as coloured circles. The units are ordered within each category (phasic or tonic) according to their onset discharge time. The percentages for each type of unit were similar for the control and OSA subjects and the onset time of Inspiratory Phasic and Inspiratory Tonic units was earlier in the OSA subjects (see text).

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While proportions of the different unit types were similar for control and OSA subjects, the timing of their inspiratory activation was not. The recruitment of Inspiratory Tonic units in control subjects (at −7.1 ± 2.3% inspiratory time (TI) −121 ± 39 ms, i.e. before inspiratory flow) was significantly later than for the OSA subjects (at a mean time of −14.2 ± 2.2% (TI), −227 ± 36 ms, P < 0.05). The Inspiratory Phasic units of the control subjects were also recruited later relative to inspiratory flow (+6.1 ± 1.7%TI, +123 ± 30 ms, i.e. after inspiratory flow) than in the OSA subjects in whom the mean recruitment time was before inspiratory flow commenced (at −2.5 ± 1.5%TI, −32 ± 27 ms, P < 0.05). For both groups, the Inspiratory Phasic units were recruited later than the Inspiratory Tonic units (P < 0.001).

In control subjects, the mean time to peak firing of the Inspiratory Tonic units (38.1 ± 4.1%TI) was significantly earlier than the Inspiratory Phasic units (48.0 ± 3.0%TI, P= 0.017). There was no such difference for the OSA subjects; the time to peak firing for Inspiratory Tonic and Phasic units occurred at the same time (42.2 ± 3.7%TI, and 43.0 ± 2.7%TI, respectively, n.s. P= 0.2). The de-recruitment times of the Inspiratory Phasic units were not significantly different for the control and OSA subjects (101.5 ± 5.5%TI and 105.3 ± 5.0%TI, respectively, n.s.). Similarly, the time of firing rate decline for the Inspiratory Tonic units for the control and OSA subjects was not significantly different (98.3 ± 7.4%TI and 109.8 ± 6.7%TI, respectively, n.s). For the control subjects, fewer Inspiratory Phasic units (4%) and Inspiratory Tonic units (79%) became active before the onset of inspiratory flow compared to OSA subjects (58% and 88%, respectively; P= 0.01). The Inspiratory Phasic units of control subjects tended towards a shorter firing time. At 75% of inspiratory time, 17% of Inspiratory Phasic units had stopped discharging in the control subjects compared to only 8% of units in OSA subjects (P= 0.087). However, at 75%TI for both control and OSA subjects ∼80% of Inspiratory Tonic units were still discharging at an elevated rate.

Single motor unit discharge frequencies

The mean onset and peak discharge frequencies are also plotted in Fig. 5 for each type of genioglossus motor unit activity (see also Fig. 4 and Table 3). The mean onset discharge frequency for the Inspiratory Tonic units (19.6 ± 1.0 Hz and 18.3 ± 0.9 Hz, for both control and OSA subjects, respectively) was significantly higher than for the Inspiratory Phasic units (12.7 ± 0.7 Hz and 14.2 ± 0.6 Hz, P < 0.01), and Expiratory Phasic units (9.3 Hz and 16.6 ± 3.2 Hz, P < 0.05).

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Figure 5. Onset and peak discharge frequencies of genioglossus motor units A (OSA subjects) and B (control subjects) depict mean onset (open circles) and peak discharge frequencies (open triangles) for each motor unit recorded during normal breathing. The overall mean onset (±s.e.m.; filled circles) and peak discharge frequencies (filled triangle) are shown for each of the 5 types of genioglossus units modulated by respiration. The mean onset and peak frequencies are joined by a line. Only the peak frequency is shown for Tonic units.

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There were no differences between control and OSA subjects for onset discharge frequencies. The mean peak discharge frequency for the Inspiratory Phasic units for the control subjects (19.0 ± 0.8 Hz) was significantly lower than for OSA subjects (22.2 ± 0.7 Hz P= 0.003). The mean peak discharge frequency for the Inspiratory Tonic units of the control subjects (28.2 ± 1.1 Hz) was significantly higher than that of the OSA subjects (25.4 ± 1.0 Hz, P < 0.05). The background ‘tonic’ frequency of the Inspiratory Tonic units was similar between the control and OSA subjects (16.5 ± 1.2 Hz, versus 14.1 ± 0.8 Hz, respectively, P= 0.08). The Inspiratory Tonic units' peak frequencies were significantly higher than for the Inspiratory Phasic units (for both control and OSA subjects, P < 0.05). There was no difference in the background or peak firing frequencies of the Expiratory Tonic units in the two groups. Overall, the change in frequency during the respiratory cycle was similar for each type of unit in the control and OSA subjects.

For all units, the duration of discharge correlated positively with the peak firing frequency, while the onset time correlated negatively with the duration of discharge and with the peak firing frequency (all P < 0.05). Thus, units that discharged for the longest time were the earliest activated and reached the highest peak firing frequency. This correlation occurred for both the control and OSA groups.

Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References
  7. Appendix

To identify the possible mechanisms for the reported increase in multiunit EMG in OSA subjects during wakefulness, we assessed single motor unit activity in the genioglossus and quantified the motor unit action potential size, motor unit firing frequencies, and the timing of their discharge. These measures all have an impact on the total EMG signal and ultimately represent the drive generating the force from this major airway dilator muscle. It is well accepted that the genioglossus muscle has significantly more activity in both inspiration and expiration in OSA compared to control subjects (e.g. Mezzanotte et al. 1992; Fogel et al. 2001; Fogel et al. 2005; Saboisky et al. unpublished observations). In the past, this has been considered a compensatory mechanism to maintain airway patency. However, an increased EMG signal may be caused by a number of factors. These include increased ‘premotoneuronal’ or ‘motoneuronal’ drive (leading to higher discharge rates of motor units and/or recruitment of additional motor units) and peripheral changes due to increased size of motor unit action potentials in the active muscle fibres.

Contrary to our initial hypothesis, the current results indicate that during quiet breathing the distribution of the different classes of motor unit activity was identical for the control and OSA subjects (see Fig. 4). However, while there were similarities between the discharge patterns of single motor units in the genioglossus in control and OSA subjects, there is some evidence that the central drive may show subtle changes. Relative to inspiratory airflow, Inspiratory Tonic and Inspiratory Phasic units began to discharge significantly earlier in the OSA subjects, but their peak firing frequencies were altered differentially. However, a major finding was an increased duration and area of the motor unit action potentials in OSA compared to control subjects. This suggests significant ‘remodelling’ of the motor unit which has resulted in peripheral changes in motor unit action potentials in OSA subjects.

A range of morphological and histochemical changes have been reported in upper airway muscles in OSA, presumably secondary to repetitive mechanical loading due to airway obstruction. These include shifts in proportions of muscle fibre types (from type I to type IIA) (Smirne et al. 1991; Series et al. 1995, 1996; Carrera et al. 1999;) and some muscle fibre atrophy (Woodson et al. 1991; see also Boyd et al. 2004). However, despite these peripheral changes, OSA patients are still more prone to upper airway collapse (e.g. Guilleminault et al. 1973; Gleadhill et al. 1991; see also Younes, 2003). There is some electromyographic evidence that chronic partial denervation may occur in the palatopharyngeus muscle in OSA (Svanborg, 2005; Hagander, 2006). Svanborg (2005) suggests that the trauma of chronic snoring in OSA (due to airway vibration at ∼30 Hz, Liistro et al. 1991) damages nerves in the upper airway, as occurs in occupational neuropathies secondary to the use of vibrating equipment (Takeuchi et al. 1986). However, none of this evidence has been obtained in genioglossus, a crucial muscle required for airway patency. The present study shows that these kinds of peripheral changes could contribute to the increased genioglossus EMG in awake OSA subjects. The duration of the motor unit action potentials was increased in OSA subjects by 23% and the area was increased by 34%. This increased area is a combination of the increased duration of the potentials and by a small increase in the amplitude of the motor unit potentials. Many factors could contribute to the larger ‘size’ of these potentials during quiet breathing (altered intracellular action potentials; increased fibre diameter; increased fibre number), but increased duration of the motor unit potentials strongly favours active reinnervation as part of a chronic neuropathic process remodelling the motor unit (e.g. Buchthal & Clemmesen, 1941). Irrespective of the precise cause for this change, it would significantly increase the amplitude of the multiunit EMG signal (e.g. Fuglevand et al. 1993; Keenan et al. 2006), and may be sufficiently large to account fully for the previously reported difference in multiunit EMG between the control and OSA subjects (Mezzanotte et al. 1992; Fogel et al. 2001).

During normal breathing, the drive to hypoglossal motoneurons will depend on both descending respiratory and reflex inputs and the level of drive will affect the timing and rates of discharge of single motor units. Although breathing variables were similar for control and OSA subjects, there were differences in the timing of firing of the genioglossus motor units relative to inspiratory air flow and some differences in their peak firing rates. The onset discharge frequencies of the motor units for the various populations were similar for the control and OSA subjects, and, hence, there does not appear to be a major compensatory increase in drive to the genioglossus in OSA subjects during wakefulness. Generally, increased drive to a respiratory muscle is reflected by higher onset and peak firing frequencies of its motor units (Butler et al. 1999; Gandevia et al. 1999) as also occurs for limb muscles (for review see Freund, 1983; Enoka, 1995; Binder et al. 1996). While the peak discharge rate of Inspiratory Phasic motor units showed an increase in the OSA subjects, there was a concurrent decrease in the peak discharge rate of Inspiratory Tonic motor units. In terms of the total EMG produced by the muscle, these changes would tend to offset each other. Increases in drive could also lead to recruitment of additional motor units without a concurrent increase in the discharge frequencies of the already active motor units, but only if the motoneurons are effectively ‘saturated’ (Bailey et al. 2007). While this is unlikely given the relatively low level of genioglossus muscle contraction during quiet breathing (< 10% maximum, Fogel et al. 2001), the peak firing rates during inspiration, commonly > 25 Hz, are much higher than for motor units innervating inspiratory muscles that act on the chest wall (e.g. diaphragm 11 Hz) (Gandevia et al. 1999; Saboisky et al. 2006c).

The genioglossus motor units of the control and OSA subjects differed in the timing of their initial inspiratory discharge. In OSA the activity occurred earlier with respect to the onset of inspiratory flow. This may reflect either an advance of descending neural drive to motoneurons or a delay in the generation of inspiratory flow in the face of increased mechanical loading, or a combination of both effects. Relative to inspiratory flow, this ‘advance’ in OSA subjects was ∼125 ms. For the Inspiratory Phasic units, but not for the Inspiratory Tonic units, the time of the peak discharge frequency was significantly earlier in OSA subjects. This difference in the timing of the peak discharge frequency is possibly due to a difference in the central or reflex drive to the genioglossus motoneurones (e.g. Wheatley et al. 1991; Horner, 1996; Fogel et al. 2000; Malhotra et al. 2000, 2002; Akahoshi et al. 2001). While the control subjects and patients with OSA were matched for age, they were not matched for body mass index. As central respiratory drive may be increased due to the effects of increased load, we cannot confirm that any central changes were due solely to airway obstruction.

In conclusion, our findings provide a new explanation for the increased multiunit EMG in genioglossus in OSA, previously thought to represent a compensatory neural mechanism to keep the upper airway open. Our results provide direct evidence that the increased multiunit EMG signal in OSA is due in large part to peripheral neurogenic changes in the motor units. However, there are also changes in the timing and level of firing of particular groups of inspiratory motor units within the genioglossus. The combined changes based on all types of motor unit activity are not consistent with a generalized increase in drive to the genioglossus in OSA.

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  6. References
  7. Appendix
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Appendix

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. References
  7. Appendix

Acknowledgements

We thank Dr Kirsti Withell, Associate Professor Frank Maccioni and Ms Erlinda Balong-e and staff at the Department of Respiratory and Sleep Medicine, Prince of Wales Hospital, for their assistance. We also thank Dr Janette Smith for advice on statistical analysis. This work was supported by the National Health Medical Research Council of Australia and the United Sates National Institutes of Health, HL 048531.