0109 Slow Wave Sleep and REM Sleep Differentially Affect Nocturnal Glucose Levels. (12th April 2019)

• Record Type: Journal Article
• Authors: Brandt, Rachel; Chapotot, Florian; Rashid, Mudassir; Broussard, Josiane; Cinar, Ali; Tasali, Esra
• Is Part Of: Sleep. Volume 42(2019)Supplement 1
• Page Start: A45
• Page End: A45
• Publication Date: 2019-04-12
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsz067.108
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Disruptions in sleep quality impair daytime glucose metabolism. Normal sleep consists of non-REM sleep (stages N1, N2, and slow wave sleep [SWS]) and rapid-eye-movement (REM) sleep, which have distinct physiological characteristics. Here, we investigate how different sleep stages affect nocturnal glucose levels. Methods: Sixteen healthy, young lean adults were studied under 2 controlled laboratory conditions (normal sleep and SWS suppression) with 8.5-hour bedtimes for four nights in a randomized order separated by at least one month. SWS suppression was achieved via acoustic stimuli. Sleep recordings were visually scored in 30-second epochs according to standard criteria. Glucose levels were assessed by a continuous glucose monitoring (CGM) device that measures interstitial glucose concentrations every 5 minutes. Additionally, on the 3 rd night of each condition, frequent blood samples were collected to measure venous glucose concentrations. Concomitant venous and CGM glucose profiles from the 3 rd night of each condition were treated using Kalman filtering techniques in order to correct artifacts and impute missing values in the CGM profiles. These CGM profiles were then interpolated to 30-second intervals to align with the scored sleep stages. One subject had missing sleep data for the of SWS suppression condition leaving a total of 31 nights used for this analysis. Multinomial logistic regression was performed over 10-min intervals to determine the relationships between sleep stages and nocturnal glucose levels. Results: The time spent in SWS was associated (p=0.050) with a concomitant increase in glucose levels, whereas the time spent in REM sleep was associated (p=0.004) with a concomitant decrease in glucose levels. Additionally, the time spent in SWS predicted (p=0.007) an increase in glucose levels in the following 10-min period. Stages N1 and N2 did not show significant associations with glucose levels. Conclusion: SWS and REM sleep differentially affect nocturnal glucose levels. These findings may have important clinical implications for the integration of novel sleep modules into artificial pancreas systems that are commonly used in the management of Type 1 diabetes. Support (If Any)