A Mechanism for Upper Airway Stability during Slow Wave Sleep

A MECHANISM FOR UPPER AIRWAY STABILITY DURING SLOW WAVE SLEEP http://dx.doi.org/10.5665/sleep.2544

A Mechanism for Upper Airway Stability during Slow Wave Sleep

David G. McSharry, MB1; Julian P. Saboisky, PhD2; Pam DeYoung, BA1; Paul Matteis, BS1; Amy S. Jordan, PhD3; John Trinder, PhD3; Erik Smales, BS1; Lauren Hess, BS1; Mengshuang Guo, BS1; Atul Malhotra, MD1 Sleep Disorders Research Laboratory, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA; 2Neuroscience Research Australia, Randwick, Sydney, New South Wales, Australia; 3Sleep Laboratory, Psychological Sciences, The University of Melbourne, Grattan Street, Parkville, Victoria, Australia 1

Study Objectives: The severity of obstructive sleep apnea is diminished (sometimes markedly) during slow wave sleep (SWS). We sought to understand why SWS stabilizes the upper airway. Increased single motor unit (SMU) activity of the major upper airway dilating muscle (genioglossus) should improve upper airway stability. Therefore, we hypothesized that genioglossus SMUs would increase their activity during SWS in comparison with Stage N2 sleep. Design: The activity of genioglossus SMUs was studied on both sides of the transition between Stage N2 sleep and SWS. Setting: Sleep laboratory. Participants: Twenty-nine subjects (age 38 ± 13 yr, 17 males) were studied. Intervention: SWS. Measurement and Results: Subjects slept overnight with fine-wire electrodes in their genioglossus muscles and with full polysomnographic and end tidal carbon dioxide monitors. Fifteen inspiratory phasic (IP) and 11 inspiratory tonic (IT) units were identified from seven subjects and these units exhibited significantly increased inspiratory discharge frequencies during SWS compared with Stage N2 sleep. The peak discharge frequency of the inspiratory units (IP and IT) was 22.7 ± 4.1 Hz in SWS versus 20.3 ± 4.5 Hz in Stage N2 (P < 0.001). The IP units also fired for a longer duration (expressed as a percentage of inspiratory time) during SWS (104.6 ± 39.5 %TI) versus Stage N2 sleep (82.6 ± 39.5 %TI, P < 0.001). The IT units fired faster during expiration in SWS (14.2 ± 1.8 Hz) versus Stage N2 sleep (12.6 ± 3.1 Hz, P = 0.035). There was minimal recruitment or derecruitment of units between SWS and Stage N2 sleep. Conclusion: Increased genioglossus SMU activity likely makes the airway more stable and resistant to collapse throughout the respiratory cycle during SWS. Keywords: Apnea, genioglossus, lung, single motor unit, sleep Citation: McSharry DG; Saboisky JP; DeYoung P; Matteis P; Jordan AS; Trinder J; Smales E; Hess L; Guo M; Malhotra A. A mechanism for upper airway stability during slow wave sleep. SLEEP 2013;36(4):555-563.

INTRODUCTION Obstructive sleep apnea syndrome (OSA) is common1 and is associated with serious sequelae such as road traffic accidents and cardiovascular disease.2-5 The pathophysiology of OSA remains incompletely understood. Because treatment of OSA is unsatisfactory due to poor adherence or variable efficacy with the standard treatments, further mechanistic work is required to determine new potential therapeutic strategies.6,7 The severity of OSA is significantly diminished during slow wave sleep (SWS).8 Understanding the physiologic mechanisms underlying the improvement of OSA during SWS could lead to new therapeutic targets. In non-rapid eye movement sleep, the major upper airway dilator muscle (genioglossus) is more active during periods of stable breathing compared with periods of cyclical breathing when obstructive apneas are occurring,9 suggesting that upper airway dilator muscles are necessary and sufficient to stabilize the upper airway. Given the undoubted stabilizing properties of the genioglossus it is reasonable to predict that there would be increased genioglossus activity during SWS compared with Stage N2 sleep. However, the existing multiunit electromyogram (EMG) genioglossus studies comparing

genioglossus activity between SWS and Stage N2 sleep have not shown consistent results.9-12 The activity of the genioglossus can be increased primarily through one of three mechanisms that multiunit recording cannot decipher between: (1) increased rate coding of active single motor units (SMUs); (2) increased discharge duration of active SMUs; and (3) recruitment of new SMUs.13 No studies have compared SMU activity in SWS compared with Stage N2 sleep. Thus, the existing multiunit literature has not adequately explained the role, if any, of the genioglossus in the improvement in OSA seen in SWS. Therefore, through the analysis of human genioglossus SMUs we sought to understand the exact physiologic processes by which SWS stabilizes the upper airway. Specifically, we hypothesized that SMU activity would be increased during periods of stable breathing in SWS compared with similar periods in Stage N2 sleep, thus providing a novel mechanism for upper airway stability during SWS. We defined increased SMU activity as one or more of the following occurrences: increased rate coding, increased discharge duration, or recruitment.

Submitted for publication June, 2012 Submitted in final revised form September, 2012 Accepted for publication September, 2012 Address correspondence to: David McSharry, MB, 221 Longwood Avenue, Boston, MA 02115; Tel: +353876127421; E-mail: [email protected]

Study Subjects Ethics approval was granted by the local Institutional Review Board. Exclusion criteria were active cardiorespiratory disease, diabetes mellitus or other endocrine disorders, myopathy, pregnancy, neurologic illness, or medications that could alter neuro-

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METHODS

555

A Mechanism for Upper Airway Stability during SWS—McSharry et al

Table 1—Demographics and polysomnography detailsa Number of subjects with SMU data in both stage N2 sleep and SWS Age (yr)

AHI 9 23 30 8 24

36 ± 16

Sex

Five males, two females

Body mass index (kg/m2) Neck circumference (cm)

Table 2—Apnea-hypopnea indices in the various sleep stages in the five subjects with obstructive sleep apnea

7

26.4 ± 4.2 b

38.9 ± 4.9

Depth to geniohyoid (mm)

11.8 ± 1.3

Depth to genioglossus (mm)

20.2 ± 1.9

Depth of wire insertion (mm)

26.4 ± 2.6

Total sleep time (min) Stage N2 sleep (%TST)

8.2 ± 9.5 3.8 ± 2.8

toprazole. Two of the subjects consumed alcohol occasionally, one smoked five cigarettes per week, and one had mild visual impairment. The apnea-hypopnea index (AHI) of each subject was 0, 1, 9, 23, 30, 8, and 24/h, respectively. The AHIs in the various sleep stages of the subjects with OSA (AHI > 5) are provided in Table 2.

a Data presented as mean ± standard deviation. bNot available for one of the subjects. TST, total sleep time.

Materials and Procedures Subjects arrived at our Center for Clinical Investigation 3 hours before their usual bedtime. Medical assessment and physical examination were carried out by the admitting physician. All subjects gave written informed consent. Pregnancy was excluded with a urinary human chorionic gonadotropin test in all women of childbearing ability. Topical local anesthetic cream (lidocaine 2.5% / prilocaine 2.5%, E. Fougera & Co., Melville, NY) was applied to the skin posterior to the genial tubercle of the mandible for 30 min prior to fine-wire insertion. Ultrasonography with electronic calipers was performed in the sagittal and coronal planes to define the exact anatomy to ensure fine-wire electrode placement in the genioglossus (12L high-frequency linear array transducer, Vivid i GE Healthcare, Chalfont St. Giles, Bucks, UK)14 (Figure 1). Next, the subjects were instrumented with three electroencephalograms (F3-A2, C3-A2, O2-A1), submental EMG, left and right electrooculograms, and an electrocardiogram with surface electrodes for the duration of their overnight sleep. Subjects were fitted with a nasal mask and pneumotachograph (Hans Rudolph, Shawnee, KS) with differential pressure transducer for measurement of airflow and calculation of ventilation. End-tidal carbon dioxide (ETCO2) (Vacumed, Ventura, CA) was monitored from one nostril and arterial oxygen saturation (SaO2) measured with finger pulse oximetry. Respiratory effort bands (Protech ZRIP Effort Sensor, Respironics, Mukilteo, WA) were placed on the chest (midsternum) and abdomen (umbilicus). The final part of the instrumentation was conducted as follows. The local anesthetic cream was removed with sterile alcohol wipes. The subject was asked to lie flat supine on the bed with one pillow. Fine-wire electrode insertion was conducted similar to the technique of Eastwood et al.14 A cross was drawn in the midline 10 mm posterior to the genial tubercle of the mandible. Three 27G needles (Becton Dickinson, Franklin Lakes, NJ) were used to guide the three fine-wire electrodes into the genioglossus. Each of these guide needles was immediately re-

Figure 1—Sagittal ultrasound image from a patient showing a schematic representation of a Teflon-coated fine-wire electrode in situ in the genioglossus. The most distal 0.5 mm of the fine wire is bare. The fanshaped nature of the genioglossus from anterior to posterior can be appreciated in this figure.

muscular function (e.g., selective serotonin reuptake inhibitors or benzodiazepines). Twenty-nine human volunteers were recruited from advertisements in a local newspaper, website, and our clinical sleep clinic. Baseline demographic information for the seven subjects who yielded comprehensive data (i.e., sortable motor units across SWS and Stage N2 sleep) is provided in Table 1. Of the seven subjects: the two female subjects were taking an oral contraceptive. One of the men was taking panSLEEP, Vol. 36, No. 4, 2013

SWS as %TST 8.3 4.7 0.5a 0.2 1.8

The paradoxical increase in AHI in SWS is explained by two hypopneas and one obstructive apnea occurring during the four epochs of SWS that this patient slept. AHI, apnea-hypopnea index; SWS, slow wave sleep; TST, total sleep time.

49.6 ± 10.3

Number of single motor units per subject

Stage N2 Stage N2 AHI as %TST SWS AHI 2.6 58.6 2.3 24.1 55.1 2.5 19 59 60 11 37.2 0 21.6 58.5 18.5

a

336.1 ± 65.3

SWS (%TST)

TST/min 249 391 316 425 284

556


moved once the fine-wire electrodes were placed in situ. The fine-wire electrodes were custom-made, stainless-steel, Tefloncoated wires (0.076 mm bare, 0.140 mm coated, A-M Systems, Inc., Carlsborg, WA) hooked over the bevel of each needle with 0.5 mm of insulation removed. The hooked portion was approximately 3 to 4 mm long. The needles were inserted 90° to the skin surface to a depth determined by the ultrasound. The first needle was inserted 3 to 5 mm from the center of the marked cross anterolaterally. The second and third needles were inserted 3 to 5 mm from the center of the cross posterolaterally to the left and right of the midline, respectively. The fine-wire electrodes were referenced to a surface electrode placed over the mandible (MEDI-TRACE 100 series, Kendall Healthcare, Mansfield, MA) and grounded to a large electrode placed over the right scapula (1180, 3M Health Care, St. Paul, MN). Finally, the subject’s mouth was taped shut to ensure exclusive nasal breathing, enabling accurate measurement of flow measured with the pneumotachograph and ETCO2 measured via nasal probe. The subject was then given the opportunity to sleep for up to 8 hours with the fine-wire electrodes in place. All subjects were instructed to sleep supine. When a patient turned on his or her side during sleep, he or she was awakened after 5 min in this position to facilitate return to supine sleeping. Genioglossus EMG signals were filtered (10 Hz to 3 KHz) and amplified (×1,000– 20,000) (Model 15, Grass Technologies, West Warwick, RI). All signals were recorded on a Spike 2 data acquisition system (Spike 2 version 7.03 with 1401 interface, Cambridge Electronic Design, Cambridge, England). Genioglossus EMGs were recorded at 25 kHz; electroencephalogram, electrooculogram, electrocardiogram,and submental EMG at 500 Hz; ETCO2, airflow, and tidal volume at 125 Hz and SaO2 at 25 Hz. All data were stored on a computer for offline analysis.

mate stage prior to the sleep stage transition or the first three breaths of the second epoch after the sleep stage transition (i.e. 35 sec separated the two three-breath data segments). (3). For transitions from Stage N2 sleep to SWS where the first epoch of SWS was followed by one additional epoch of Stage N2 sleep and then by two or more epochs of SWS, the six breaths were chosen as the last three breaths of the penultimate consecutive Stage N2 sleep epoch and the first three breaths of the second consecutive SWS epoch (i.e., 120 sec separated the two threebreath data segments). In addition to these six breaths, we analyzed an additional three-breath segment (chosen similar to the three criteria) in the following Stage N2 sleep (or SWS) epochs specifically looking for recruitment and derecruitment in the transition back to Stage N2 sleep (or SWS). There were no detectable changes in body position over the transition periods. Data were not analyzed if they occurred during or less than 10 sec after an apnea, hypopnea, or arousal. Snoring or flow limitation that did not meet criteria for an hypopnea16 did not preclude inclusion. Data Analysis: Sorting and Classification of SMUs The SMUs were extracted from the raw EMG signal offline using a Spike-triggered threshold (Spike 2 version 7.03 software). Figure 2 shows an example of a trigger threshold (represented as the dashed gray line) that would extract all the motor units. Spike templates were drawn on the basis of the size and detailed morphology of the SMUs. Every single discharge of each SMU was manually inspected to confirm that it was classified correctly. Manual inspection was facilitated by a computer script (Gandevia Laboratory, Randwick, Sydney, Australia). Instantaneous discharge frequency plots were derived from the time of discharge of the unit. The activity of each SMU was then classified based on its pattern of discharge during the respiratory cycle, which was determined from the volume signal.17,18 Briefly, units that fired throughout the respiratory cycle were classified as tonic. Units that fired for part of the respiratory cycle were classified as phasic. In addition, the units were further visually sub-classified as inspiratory, expiratory, or other depending on when they fired at their peak discharge frequency. As well as this visual classification of the different types of motor units, cross-correlation between volume and instantaneous firing frequency (smoothed over 200 ms) was calculated between the signals on a breathby-breath basis. The volume signal was derived from the flow signal using a script. Figure 2 shows the instantaneous discharge frequency and the volume signal. The strength of the correlation between these measures (linear coefficient of determination, r2) and the timing of the maximal value of this coefficient, the lag time, were calculated. Time zero is the reference point and represents the end of inspiration. Inspiratory units have a peak r2 before the end of inspiration (negative lag times) and expiratory units have a peak r2 after the end of inspiration during expiration (positive lag times).

Data Analysis: Sleep Staging and Identification of SMUs All sleep periods were staged and scored in accordance with the American Academy of Sleep Medicine criteria15,16 by a registered polysomnographic technician, with airflow used in place of nasal pressure/thermistor. All sleep staging and scoring were performed while the technician was blinded to the three genioglossus EMG channels. After the formal scoring of the sleep study, one author (DM) chose the areas of data for analysis based on a priori defined criteria: for each transition between Stage N2 sleep to SWS (or SWS to N2), six breaths were analyzed if an SMU was present either before and/or after the sleep stage transition. The following three criteria ensured that SMUs were extracted from unambiguous sleep stage and not the actual transition itself. Also, these criteria confirmed that the extracted SMUs were as near as possible to the transition so as to see the effects of the sleep stage per se and minimize other influences. (1) For transitions where more than two epochs of a given stage occurred after the transition, the six breaths were chosen as the last three breaths of the penultimate stage prior to the sleep stage transition and the first three breaths of the second epoch after the sleep stage transition (i.e. 60 sec separated the two three-breath data segments). (2) For transitions where only one epoch of a given sleep stage occurred before or after the transition, the six breaths were chosen as the middle three breaths of the lone epoch and either the last three breaths of the penultiSLEEP, Vol. 36, No. 4, 2013

Measurement of Respiratory Variables and Discharge Properties of SMUs The respiratory variables analyzed (inspiratory time [TI, s], tidal volume [L], and ETCO2 [mm Hg]) were measured over the three breaths of Stage N2 sleep and the three breaths of SWS. 557


25 Instantaneous discharge frequency plot (Hz)

Onset frequency

Peak time & frequency

Overdrawn wavemark End time & frequency -0.5mV

Onset time

2ms

0 0.75 Raw genioglossus EMG signal (mV)

0

-0.75

Trigger threshold

0.5 Volume (L)

0

Inspiratory Time

1 second

Figure 2—Single motor unit (SMU) measurements. Example of raw data focused around the inspiratory phase (shaded in gray) of one breath. The raw electromyogram (EMG) represents the firing of one SMU, which fires predominantly during inspiration. The unit is classified as an inspiratory phasic unit. A trigger threshold is set using Spike software to extract the SMUs. The ideal trigger threshold extracts the discharges of the SMU(s) without extracting the baseline noise and unsortable smaller units. The overdrawn wavemark is in the top right of the figure. Each discharge of the SMU is carefully sorted and an instantaneous discharge frequency plot is generated and used to obtain key measurements of the SMU behavior. Key measurements are circled. Each of these measurements are made for each breath and averaged over three breaths in both Stage N2 sleep and slow wave sleep. The timing of the SMU firing is normalized as a percentage of inspiratory time (%TI). A negative onset time means that the unit started firing before inspiratory flow. The volume channel is derived directly from the flow channel.

Mean values were calculated for each of the two sleep stages yielding two data points. The instantaneous discharge frequency plots of the sorted SMUs were used to identify SMU discharge behavior, such as the discharge frequency and the discharge duration. All SMU characteristics reported here were calculated from the instantaneous discharge frequency plots using Spike 2 (Spike 2 version 7.03) and a custom developed script (Gandevia Laboratory). Examples of instantaneous discharge frequency plots are given in Figure 2 and Figure 3. Discharge timing was expressed relative to the integrated flow signal and referenced to the start of inspiration. The discharge timing was calculated as a percentage of the inspiratory time (%TI). Mean motor unit discharge characteristics were measured over the three continuous breaths and averaged in both Stage N2 sleep and SWS, yielding two data points that allowed comparisons between the sleep stages. Recruitment of a new SMU was defined as the appearance of a new unit in SWS that was not present in Stage N2 sleep. Derecruitment of an SMU was defined as the disappearance of a unit in SWS that had been present in Stage N2 sleep. For inspiratory phasic units, the onset discharge time was measured at the first SMU discharge for each breath and the end time was measured at the last discharge in each breath (Figure 2). For inspiratory tonic units, onset time was taken visually from when SLEEP, Vol. 36, No. 4, 2013

the discharge frequency first increased above the tonic levels and the end time when the discharge frequency first returned to the tonic level (Figure 3). Onset discharge frequency for inspiratory phasic units was calculated from the first interspike interval for each breath (Figure 2). The tonic level was the baseline discharge frequency of the inspiratory tonic unit. This tonic level is the tonic expiratory discharge frequency that is measured and averaged over 500 ms (Figure 3). Peak discharge frequencies were derived from the peak of the instantaneous frequency with a running average for each breath (smoothed over 200 ms; Figure 2). The mean frequency was calculated over 200 ms. Statistical Analysis All results of the SMUs were compared between Stage N2 sleep and SWS by paired t-tests. If the Shapiro-Wilk normality test failed, then a Wilcoxon signed rank test was conducted instead of a paired t-test. All statistics were performed using SigmaPlot (version 11) statistical software (SigmaPlot, San Jose, CA). RESULTS Twenty segments of data from ten subjects that yielded sortable motor units on one or both sides of the SWS-Stage N2 sleep transition were fully analyzed. The baseline demo558


Instantaneous discharge frequencies (Hz) Instantaneous discharge frequencies (Hz) Instantaneous discharge frequencies (Hz) Raw genioglossus EMG (mV) End tidal CO2 (mmHg)

Volume (L)

40

Onset time & frequency

Tonic expiratory discharge frequency

End time & frequency

0 40 0 40 0 +1

-0.5 mV

-1 50

2ms

0 0.4 0 1 second

Figure 3—Example of raw data from slow wave sleep. This figure shows the instantaneous discharge frequency plots of the three single motor units (SMUs) that were sorted and extracted from the raw genioglossus electromyogram signals. The overlaid detailed morphologies for each SMU are seen in the inset. The baseline tonic frequency is measured as the tonic expiratory discharge frequency averaged over 500 ms. The onset time of inspiratory tonic units refers to the time that the units start firing faster than the baseline/tonic expiratory discharge frequency. The end time of inspiratory tonic units refers to the time that the units resume firing at the baseline/tonic expiratory discharge frequency. EMG, electromyogram, CO2, carbon dioxide.

graphics and polysomnography details for the seven subjects whose SMU data we reported (including discharge frequencies) are listed in Table 1. Data from the other 19 subjects were not included in this analysis because they did not fulfill the predefined criteria outlined in the paragraph on data analysis. There was minimal recruitment/derecruitment observed between the two stages. Stage N2 sleep occurred first in 19 of the 20 data segments analyzed. Every unit that was firing in SWS had already been firing in Stage N2 sleep. On analysis of the transitions back to Stage N2 sleep from SWS in the 19 data segments and back to SWS from Stage N2 sleep in the other instance we observed the following: (1) Sixteen of the data segments involved prompt (< 200 sec) transitions back to Stage N2 sleep (or SWS in one instance). There was no recruitment seen in these data segments. Two data segments that each had one expiratory tonic unit showed derecruitment in Stage N2 sleep from SWS. (2) In the other four data segments, wake epoch(s) occurred between SWS and Stage N2 sleep. In two of these data segments derecruitment without recruitment occurred. In the other two data segments no derecruitment or definite recruitment occurred, although the signals became more multiunit. The SMU overnight results are presented in Table 3. All the inspiratory units analyzed together showed that the SMUs had significantly higher onset, peak, end, and mean discharge frequencies during SWS compared with during Stage N2 sleep. Moreover, they discharged above the baseline frequency for a significantly longer duration in SWS than during Stage N2 sleep. Inspiratory phasic units had significantly higher peak, end, and mean discharge frequencies during SWS compared with Stage N2 sleep. Inspiratory phasic units discharged 7%TI earliSLEEP, Vol. 36, No. 4, 2013

er and finished discharging 15%TI later in SWS compared with during Stage N2 sleep. Figure 4 shows the longer durations of inspiratory phasic SMU firing that occur in SWS compared with Stage N2 sleep. There was greater preactivation of phasic activity (of both inspiratory phasic and inspiratory tonic units) in SWS compared with Stage N2 sleep. Pooling the 26 inspiratory units together, during Stage N2 sleep eight units had preactivated phasic activity. During SWS these eight units were also preactivated. On three of these eight occasions the SMUs fired earlier during SWS compared with Stage N2 sleep. However, overall an additional six units that were not preactivated during Stage N2 sleep were preactivated during SWS. With regard to inspiratory tonic units, the onset, peak, end, and mean firing frequencies were significantly higher in SWS compared with Stage N2 sleep. Inspiratory tonic units also had significantly higher tonic expiratory discharge frequencies during SWS compared with Stage N2 sleep. Figures 5 and 6 illustrate the increased peak and tonic expiratory discharge frequencies, respectively, seen in SWS compared with Stage N2 sleep. Three expiratory tonic units were characterized and their peak frequencies are plotted in Figure 5. Given their scarcity they were not reported further. The r2 (presented in Table 3) averaged 0.9 in SWS and Stage N2 sleep for both inspiratory tonic and phasic units, confirming that their activity increased during inspiration. In three instances (in three different subjects) SMUs were sorted and extracted from the same wire at different times during the study periods. However, on careful examination the SMUs had different morphologies and discharge frequencies, making it unlikely that we have reported the activity of any unit more than once. Most units were sorted from the predefined 559


Table 3—Results SMU Type All Inspiratory Units (n = 26)

Inspiratory Phasic Units (n = 15)

Inspiratory Tonic Units (n = 11)

Tidal volume (L)

Stage N2 0.39 ± 0.06

SWS 0.42 ± 0.05*

Stage N2 0.41 ± 0.06

SWS 0.44 ± 0.05

Stage N2 0.36 ± 0.06

SWS 0.39 ± 0.04

ETCO2 (mm Hg)

38.7 ± 4.2

39.2 ± 4.2*

38.7 ± 3.8

39.2 ± 3.8*

38.7 ± 4.9

39.2 ± 4.9

1.8 ± 0.2

1.7 ± 0.2*

1.8 ± 0.2

1.7 ± 0.2*

1.8 ± 0.3

1.8 ± 0.2

Onset discharge frequency (Hz)

15.0 ± 4.5

16.9 ± 5.9*

14.0 ± 5.4

16.3 ± 7.4

16.4 ± 2.5

17.8 ± 3.0*

Peak discharge frequency (Hz)

20.2 ± 4.5

22.7 ± 4.1*

19.8 ± 5.4

22.2 ± 4.9*

21.0 ± 3.0

23.3 ± 2.8*

End discharge frequency (Hz)

10.8 ± 4.0

12.9 ± 4.5*

8.7 ± 3.0

10.4 ± 3.5*

13.7 ± 3.4

16.3 ± 3.3*

Mean discharge frequency (Hz)

16.9 ± 3.8

18.8 ± 3.3*

16.5 ± 4.4

18.2 ± 3.7*

17.6 ± 2.8

19.6 ± 2.5*

N/A

N/A

N/A

N/A

12.6 ± 3.1

14.2 ± 1.8*

-3.3 ± 6.6

-5.2 ± 4.3

Inspiratory time (s)

Tonic expiratory discharge frequency (Hz) Onset firing time (%TI )

8.4 ± 18.5

Peak firing time (%TI )

50.8 ± 16.4

48.6 ± 15.1

59.0 ± 10.2

55.0 ± 9.3

39.5 ± 16.9

39.9 ± 17.5

End firing time (%TI )

106.2 ± 23.3

117.3 ± 23.7*

99.5 ± 23.6

114.2 ± 27.2*

115.4 ± 20.3

121.6 ± 18.1

97.9 ± 36.7

114.0 ± 33.7*

82.6 ± 39.5

104.6 ± 39.5*

118.7 ± 18.7

126.8 ± 18.2

Volume correlation (r 2)

0.8 ± 0.1

0.8 ± 0.1

0.8 ± 0.2

0.8 ± 0.1

0.9 ± 0.1

0.8 ± 0.1

Volume lag (s)

-0.8 ± 0.2

-0.8 ± 0.2

-0.7 ± 0.2

-0.7 ± 0.2

-0.8 ± 0.2

-0.9 ± 0.2

Duration of SMU firing (%TI )

3.4 ± 13.7*

17.0 ± 19.8

9.6 ± 14.9*

All results expressed as mean ± standard deviation. *P < 0.05. The onset firing time of an inspiratory tonic unit is the time when the unit starts firing faster than its baseline/tonic expiratory discharge frequency. The end firing time of an inspiratory tonic unit is the time that the unit resumes firing at its baseline/tonic expiratory discharge frequency. ETCO2, end-tidal carbon dioxide; N/A, not applicable; SMU, single motor unit.

areas as described in the first part of the data analysis section, except in rare instances where swallowing or technical artefacts led to sorting adjacent areas instead.

genioglossus activity during SWS.9,11,12 In the study by Pillar et al.,11 subjects slept in the lateral decubitus position and hence may not have been as dependent on genioglossus tone to maintain airway patency as subjects in other studies10,20; these subjects slept supine. Although Jordan et al.9 did see a significant increase in peak genioglossus activity between stable SWS and all of Stage N2 sleep, they did not observe a difference between stable Stage N2 sleep and stable SWS. Tangel et al.12 showed that although phasic genioglossus activity was increased in SWS compared with wake, it was similar to Stage N2 sleep and there were no differences noted in tonic genioglossus activity in expiration. Increased carbon dioxide is an unlikely explanation for the increase in activity in genioglossus motor units. ETCO2 was not sufficiently raised during SWS to have a meaningful effect on drive from the hypoglossal motor nucleus because hypercapnia does not have marked effects on genioglossus activity during sleep.11 In a multiunit EMG study, Pillar et al.11 showed that increasing the ETCO2 by 6 mm Hg during sleep did not result in increased genioglossus activity despite increased ventilation, although a subsequent study showed more variable effects.21 Saboisky et al.22 showed increased discharge frequencies of SMUs in response to elevating the ETCO2 to 6 mm Hg above baseline.22 There was only a 0.5 mm Hg increase in carbon dioxide during SWS compared to Stage N2 sleep in our study,

DISCUSSION Our novel findings can be summarized as follows. As hypothesised, SMU activity was greater during periods of stable breathing in SWS compared with similar periods in Stage N2 sleep. Inspiratory SMUs had higher discharge frequencies during inspiration in SWS compared with during Stage N2 sleep. Inspiratory phasic SMUs fired for longer durations in SWS compared with Stage N2 sleep. Inspiratory tonic SMUs discharged at higher frequencies during expiration in SWS compared with Stage N2 sleep. No recruitment of new units occurred in SWS. We speculate that the augmented inspiratory SMU activity we have demonstrated would make the airway more resistant to negative pressure-induced collapse during inspiration in SWS.19 The increased tonic expiratory discharge frequency of the inspiratory tonic units could lead to a more favorable posture of the tongue during SWS and reduced propensity to expiratory collapse of the upper airway.19 The current findings are somewhat similar to the multiunit genioglossus study by Basner et al.,10 which showed increased phasic electromyographic activity of the genioglossus during SWS compared with Stage N2 sleep in five normal subjects. Three multiunit studies did not show significantly increased SLEEP, Vol. 36, No. 4, 2013

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Figure 5—Peak frequencies during Stage N2 sleep (x-axis) versus slow wave sleep (SWS, y-axis). Peak frequencies are presented from all 26 inspiratory and three expiratory tonic units. Most data points are above the diagonal identity line, indicating that the peak frequencies are significantly higher during SWS (P < 0.001). There were no significant differences between the peak frequencies of inspiratory phasic and inspiratory tonic units. ET, expiratory tonic; IP, inspiratory phasic; IT, inspiratory tonic.

Figure 4—Durations of discharge from the 15 inspiratory phasic single motor units (SMUs) in Stage N2 sleep (x-axis) versus slow wave sleep (SWS, y-axis). The duration of discharge is expressed as a percentage of inspiratory time (%TI). Each circle shows the duration of firing of an individual SMU during both stage N2 sleep and SWS. Most data points are above the diagonal identity line, indicating that the inspiratory phasic SMUs discharge for a significantly longer duration in SWS versus Stage N2 sleep (P < 0.001). IP, inspiratory phasic.

which is not enough to explain the increased rate coding during SWS seen in our study. There remain at least two other possibilities for the increase in genioglossus SMU firing: local mechanoreceptor activation from increased upper airway resistance and/or a primarily central mechanism augmenting drive to the genioglossus coincident with SWS. Prior studies have reported pharyngeal resistance in the different sleep stages. Basner et al.,10 who reported genioglossus findings similar to ours but with multiunit recording techniques, found no difference in pharyngeal resistance between SWS and Stage N2 sleep in three of their subjects studied on a different night of their genioglossus recordings.10 Pillar et al.11 showed that there was a trend for a higher airway resistance in SWS than Stage N2 sleep. In contrast, Trinder et al.23 showed an increase in upper airway resistance in men but less so in women during SWS compared with stage N2 sleep. Wiegand et al.24 showed increased upper airway resistance in SWS compared with Stage N2 sleep but no correlation between normalized upper airway resistance and geniohyoid EMG activity. Therefore, it is possible that the increased genioglossus activity we have observed is driven by increased upper airway resistance triggering local mechanoreceptor activation. However, given that there was increased tonic expiratory genioglossus SMU activity during expiration, when the upper airway pressure is positive, mechanisms beyond negative pressure-induced local mechanoreceptor activation may be involved. Another possibility is a primary central mechanism. The neural circuitry that induces SWS might activate the hypoglosSLEEP, Vol. 36, No. 4, 2013

Figure 6—Tonic expiratory discharge frequencies from the same 11 inspiratory tonic single motor units (SMUs) in Stage N2 sleep (x-axis) versus slow wave sleep (SWS, y-axis). Most data points are above the diagonal identity line, meaning that the inspiratory tonic SMUs discharge at a significantly faster frequency during expiration in SWS versus Stage N2 sleep (P < 0.035). IT, inspiratory tonic. 561


sal motor nucleus or premotor neurons coincident with SWS generation. To date there is nothing in the literature, to our knowledge, that has addressed this claim. Tangel et al.12 showed increased surface diaphragmatic EMG in SWS compared with Stage N2 sleep, which might suggest an increased central respiratory drive during SWS. Genioglossus SMU techniques are being increasingly used in upper airway physiology studies, providing insight into the neural output of the hypoglossal motor nucleus. No study had compared genioglossus SMU activity in SWS to Stage N2 sleep prior to our current study. Wilkinson et al.25 showed that there was a marked derecruitment of inspiratory SMUs at sleep onset but expiratory and tonic units kept discharging, unaffected by the transition. These authors speculated that upper airway patency during sleep was dependent on the stiffening properties of expiratory and tonic units. Other studies using SMU techniques have shown that upper airway dilating muscles have a preference for recruitment/derecruitment rather than rate coding, particularly in response to rising ETCO2.26,27 Our study shows increased genioglossus rate coding and discharge duration and no recruitment of new units in SWS. We have shown that inspiratory units may be important in maintaining upper airway patency because these units show increased rate coding and discharge duration during SWS (when less obstructive apneas occur) compared with Stage N2 sleep. Additionally, we have shown that during SWS, increased rate coding and firing durations are more important mechanisms than recruitment in maintaining airway patency. The peak frequencies of inspiratory phasic and inspiratory tonic units did not differ significantly from one another, indicating that these units act in unison during inspiration in sleep. Despite our study’s strengths, we acknowledge limitations. We did not place epiglottic catheters or esophageal balloons in our subjects because we wanted them to achieve deep sleep. As a result, we cannot draw any direct conclusions about mechanoreceptive stimulation, e.g., via the negative pressure reflex. We had limited sample size in terms of the number of motor units. Sorting of motor units is extremely time consuming; thus, performing a much larger study is not logistically feasible. In addition, 11 subjects did not yield sortable motor units during stable periods of breathing in SWS. When the EMG signals are too multiunit, despite there being numerous SMUs, it is not possible to sort them fully. In such cases it is possible that we may have missed episodes of recruitment or derecruitment. Some of the subjects could not tolerate their mouth being taped shut and thus may have breathed by mouth. When mouth breathing occurred, measures of ETCO2 and exact timing of SMU activity with respect to inspiration could not be guaranteed. Subjects who were breathing by mouth were excluded, further limiting the yield of motor units. Also, eight of 27 subjects did not have any SWS. In addition, we only assessed the genioglossus muscle. We recognize that the genioglossus is one of many upper airway muscles and that other muscles such as the tensor palatini are important in maintaining airway patency. However, the genioglossus is the largest and most commonly studied upper airway dilating muscle and its activity is thought to be representative of other respiratory phasic muscles. Thus, the data we obtained are likely as definitive as can be obtained using existing techniques in humans. Despite these acknowledged limitaSLEEP, Vol. 36, No. 4, 2013

tions, we believe that our findings are robust and that ultimately new therapeutic targets may emerge from work which defines mechanisms of stable breathing.28,29 In summary, all of our genioglossal EMG findings represent mechanisms that should make the airway more stable and resistant to collapse throughout the respiratory cycle during SWS compared with Stage N2 sleep. Future studies could determine the neurobiological mechanisms underlying the observed electrophysiological findings, which may ultimately yield new therapeutic approaches to stabilize breathing during sleep. ACKNOWLEDGMENTS The authors thank the research subjects and the nursing staff of the Brigham and Women’s Hospital Center for Clinical Investigation for their help during the study nights. We acknowledge Andrea Carusona and Alison Foster for recruiting study participants, Lisa Campana for writing scripts, and Ellen Young for administrative support. We also thank Nancy Chamberlin, PhD for her helpful insight into the relevant literature from animal studies. Work for this study was performed at Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts. The authors were supported by the following grants: Dr. Malhotra is PI on AHA 0840159N, NIH R01 HL090897, NIH K24 HL 093218, NIH 1 P01 HL 095491 (Overall PI: Saper, Brigham PI: Malhotra), NIH R01HL110350, NIH UM1HL108724 (Overall PIs: Talmor/Loring, Brigham PI: Malhotra), NIH R01- AG035117, NIH R01 HL085188. The Harvard Catalyst is funded by UL1 RR 025758-01. David McSharry is PI on AHA 11POST5660004. DISCLOSURE STATEMENT This was not an industry supported study. Dr. Malhotra has received consulting and/or research income from Philips Respironics, Pfizer, SHC, SGS, Apnex, and Apnicure. The other authors have indicated no financial conflicts of interest. REFERENCES

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