bluuebunny/crossref_metadata_2025 huggingface dataset:
0008 University-wide chronotyping shows late-type students have lower grades, shorter sleep, and more absenteeism
Authors: Yeo Sing Chen , Tan Jacinda , Lai Clin , Lim Samantha , Chandramoghan Yuvan , Gooley Joshua
Published: May 2022

Introduction

A person’s preferred timing of nocturnal sleep (chronotype) has important implications for cognitive performance. Students who prefer to sleep late may have a selective learning disadvantage for morning classes due to inadequate sleep and circadian desynchrony. We tested whether late-type students perform worse only for morning classes, and we investigated factors that may contribute to their poorer academic achievement.

Methods

Chronotype was determined objectively in 33,645 university students (early, n = 3,965; intermediate, n = 23,787; late, n = 5,893) by analysing the diurnal distribution of their logins on the university’s Learning Management System (LMS). Linear mixed models were used to test for differences between chronotype groups in grade point average (n = 33,645), actigraphy-estimated sleep behaviour (n = 261), and class attendance estimated using Wi-Fi connection data (n = 17,356).

Results

Late-type students had lower grades than their peers for courses held at all different times of day, and during semesters when they had no morning classes. Actigraphy studies confirmed LMS-derived chronotype was associated with students’ sleep patterns. Nocturnal sleep on school days was shortest in late-type students because they went to bed later than the other chronotype groups and woke up earlier compared with non-school days. Wi-Fi connection logs for classrooms revealed that late-type students had lower lecture attendance than their peers for both morning and afternoon classes.

Conclusion

Large university-archived datasets can be used to assess relationships between chronotype and academic performance. Late-type students had lower grades, shorter sleep, and were more likely to miss classes. Shifting classes later may improve sleep and circadian synchrony in late-type students. However, this probably will not eliminate the performance gap because they still had lower grades when they only had afternoon classes. Interventions that focus on improving students’ well-being and learning strategies may be important for addressing the late-type academic disadvantage.

Support (If Any)

Data storage and management were supported by the NUS Office of the Senior Deputy President & Provost and ALSET. The work was funded by the Ministry of Education, Singapore (MOE2019-T2-2-074) and the National Research Foundation, Singapore (NRF2016-SOL002-001).
0010 Bed Sharing Versus Sleeping Alone Associated with Sleep Health and Mental Health
Authors: Fuentes Brandon , Kennedy Kathryn , Killgore William , Wills Chloe , Grandner Michael
Published: May 2022

Introduction

Although many adults do not sleep alone, associations between bed-sharing and sleep parameters in community samples are not well-known. The present study explored whether sharing a bed was associated with sleep duration and quality and mental health factors.

Methods

Data was obtained as part of the Sleep and Health Activity, Diet, Environment, and Socialization (SHADES) study of N=1,007 working-age adults from southeastern Pennsylvania. Bed Sharing was assessed with survey items assessing frequency in the past month of sharing a bed with a partner/spouse, child/children, pet(s), other family member(s), or nobody (sleeping alone). Other sleep health factors assessed included Insomnia Severity Index, Brief Index of Sleep Control, Epworth Sleepiness Scale, Fatigue Severity Scale, STOP-BANG apnea score, sleep duration, sleep latency, and wake after sleep onset. Mental health factors included PHQ9 depression score, GAD7 anxiety score, Multidimensional Scale of Perceived Social Support, Perceived Stress Scale, and global ratings for overall life satisfaction and relationship satisfaction. Covariates included age, sex, race/ethnicity, income, and education.

Results

Compared to those who reported “Never,” those who shared a bed with a partner “Most nights” reported less insomnia severity (B=-1.60; 95%CI[-2.55,-0.66]; p=0.001), more sleep (B=0.25; 95%CI[0.02,0.48]; p=0.035), less fatigue (B=-2.24; 95%CI[-4.10,-0.39]; p=0.018), less sleep apnea risk (B=-0.25; 95%CI[-0.42,-0.09]; p=0.003), shorter sleep latency (B=-6.32; 95%CI[-11.15,-1.50]; p=0.010) and less WASO (B=-8.69; 95%CI[-15.85,-1.52]; p=0.018). Those who slept with their child “Most nights” reported greater insomnia severity (B=2.14; 95%CI[0.65,3.62; p=0.005), less control over sleep (B=-0.37; 95%CI[-0.59,-0.15]; p=0.001), and greater sleep apnea risk (B=0.33; 95%CI[0.07,0.59]; p=0.012). Those who slept with other family members reported more apnea risk (B=0.44; 95%CI[0.07,0.82]; p=0.021). Those who slept alone reported greater insomnia severity (B=2.28; 95%CI[1.28,3.28]; p<0.0001), more sleepiness (B=0.98; 95%CI[0.22,1.74]; p=0.011), more fatigue (B=2.87; 95%CI[0.89,4.84]; p=0.005), and greater apnea risk (B=0.24; 95%CI[0.06,0.41]; p=0.007). In addition, sleeping with a partner was associated with lower depression, anxiety, and stress scores, and greater social support and satisfaction with life and relationships. Sleeping with children was associated with more stress. Sleeping alone was associated with higher depression scores, and lower social support and life and relationship satisfaction.

Conclusion

Sleeping with a partner/spouse is associated with better sleep quality and mental health overall. Sleeping with a child, on the other hand, was associated with worse sleep in general.

Support (If Any)
0021 The effect of video gaming on the sleep patterns and well-being of U.S. Marines
Authors: Matsangas Panagiotis , Shattuck Nita , Shattuck Lawrence , Xu Jason , Orpilla Edrie , Lawrence-Sidebottom Darian , Dotson Elizabeth , Bowen Zena
Published: May 2022

Introduction

Video gaming (VGs) is a popular activity among active-duty service members (ADSMs) and can have both positive and negative impacts on ADSM well-being and behavior. The overall aim of the project was to assess attributes and aspects of video gaming in the United States Navy and Marine Corps (USMC). Our current results specifically address the effects of video gaming on the sleep patterns of Marines.

Methods

Data were collected from 927 Marines from three USMC commands. Volunteers completed a survey and participated in semi-structured focus groups. The survey items focused on demographic and occupational characteristics, behavioral habits, video gaming habits, why ADSMs play video games, and functional effects. Validated tools were used to assess depression (Patient Health Questionnaire-8), generalized anxiety (GAD-7), excessive daytime sleepiness (Epworth Sleepiness Scale), and drinking habits (Alcohol Use Disorders Identification Test for Consumption-AUDIT-C).

Results

The study sample included predominantly males (854, 92.3%) and enlisted personnel (771, 83.3%). Also, 850 (91.7%) Marines reported playing video games (799 [94.0%] males). Gamers reported playing VGs predominantly later in the day (i.e., after work and before bedtime). Approximately 16% of gamers reported sleeping later because of playing VGs when at home/off duty, ~14% when on duty/in port, and ~5% when deployed/underway. When deployed/underway, most gamers reported playing video games in their racks (93.2%). Gamers reported symptoms of depression (~23% of ADSMs), generalized anxiety (~19%), excessive daytime sleepiness (~33%), and AUDIT-C scores suggestive of heavy drinking (39%). Excessive gamers tended to be younger, used dysfunctional coping styles more frequently, and played VGs more frequently and for more hours. Excessive gamers were more likely to report sleeping later because of playing VGs and to be identified with symptoms of depression, anxiety, and excessive daytime sleepiness.

Conclusion

This study provided valuable insight into how video gaming habits affect ADSM sleep patterns. Further research is needed to objectively assess the relationship between video gaming and sleep in operational conditions.

Support (If Any)

Supported by the Manpower and Reserve Affairs (M&RA), Headquarters Marine Corps (HQMC), and the Office of the Chief of Naval Operations/21st Century Sailor Office (OPNAV/N17).
0024 ARC Genotype Modulates EEG Spectral Power Following Total Sleep Deprivation
Authors: Satterfield Brieann , Finlay Myles , Skeiky Lillian , Lawrence-Sidebottom Darian , Schmidt Michelle , Wisor Jonathan , Van Dongen Hans
Published: May 2022

Introduction

Sleep homeostasis is manifested by a robust increase in slow wave sleep (SWS) following acute total sleep deprivation (TSD), with concomitant changes in spectral power of the non-REM (NREM) sleep EEG marked by substantial interindividual differences. We previously found that a single nucleotide polymorphism of the activity-regulated cytoskeleton associated protein (ARC) gene modulates SWS rebound following TSD. Here we sought to determine whether ARC genotype is also associated with interindividual differences in spectral power of the NREM sleep EEG.

Methods

50 healthy adults (27.3±4.9 years; 28 females) participated in one of two in-laboratory studies. Each participant had a 10h baseline sleep opportunity (22:00–08:00), 38h TSD, and a 10h recovery sleep opportunity (22:00–08:00). Sleep periods were recorded polysomnographically and visually scored according to AASM criteria. Genomic DNA was assayed for the ARC c.*742 + 58C>T non-coding SNP, rs35900184. Log-transformed NREM sleep EEG spectral power (C3-M3 derivation) over 0.2 Hz frequency bins in each of four frequency bands – delta (0.8–4.0 Hz), theta (4.2–8.0 Hz), alpha (8.2–12.0 Hz), and beta (12.2–16.0 Hz) – was analyzed by band using mixed-effects ANOVA with fixed effects for ARC genotype, night (baseline, recovery), frequency bin, and their interactions. Analyses included study and age as covariates and a random effect over subjects on the intercept.

Results

The genotype distribution in this sample was 33 C/C homozygotes, 11 C/T heterozygotes, and 6 T/T homozygotes. There was a significant ARC by night interaction in the theta (F2,1833=5.94, p=0.003) and alpha (F2,1833=8.58, p<0.001) bands. Compared to baseline sleep, during recovery sleep C/C homozygotes had 18.9% more theta power and 8.7% more alpha power, C/T heterozygotes had 17.9% more theta power and 7.6% more alpha power, and T/T homozygotes had 20.0% more theta power and 15.1% more alpha power.

Conclusion

Our results show that ARC genotype mediates the NREM sleep EEG response to TSD; compared to C allele carriers, homozygosity for the T allele is associated with a much more pronounced increase in alpha power, as well as a larger increase in theta power. The functional implications of this ARC effect remain to be determined.

Support (If Any)

ONR N00014-13-1-0302, NIH R21CA167691, and USAMRDC W81XWH-18-1-0100.
0034 Genetic Determinants of Cardiometabolic and Pulmonary Traits and Obstructive Sleep Apnea in the Hispanic Community Health Study/Study of Latinos
Authors: Zhang Yuan , Elgart Michael , Kurniansya Nuzulul , Spitzer Brian , Wang Heming , Shah Neomi , Daviglus Martha , Phylis Zee , Cai Jianwen , Gottlieb Daniel , Cade Brian , Redline Susan , Sofer Tamar
Published: May 2022

Introduction

Obstructive sleep apnea (OSA) often co-occurs with other health outcomes. The respiratory event index (REI), often used to define OSA, is similarly correlated with several health phenotypes. Genetic data provide an opportunity to explain the nature of these associations.

Methods

We used data from the Hispanic Community Healthy Study/Study of Latinos (HCHS/SOL) to estimate genetic correlations (i.e., the correlation between phenotypes that is due to genetic effects) between OSA severity as measured by the REI and 56 anthropometric, glycemic, cardiometabolic, and pulmonary traits. Genetically-correlated traits (>0.2 and p-value<0.05) were carried forward for additional analysis. Using summary statistics from published genome-wide association studies (GWAS), we constructed Polygenic Risk Scores (PRSs) representing the genetic basis of each correlated trait and OSA, and studied their associations with the genetically-correlated traits, REI and OSA. OSA was defined as REI5. When a PRS for a correlated-trait was associated (p-value<0.05) with REI/OSA or vice versa, we used GWAS summary statistics to test causal relationships using Mendelian Randomization (MR) analysis. We further estimated correlated-trait PRS associations with REI and OSA in subgroups of individuals with and without obesity (BMI>30).

Results

The dataset included 11,155 participants (mean age: 46.2 (SD =13.8) years; 41.1% males) from the baseline HCHS/SOL exam who underwent home sleep apnea testing. 30.65% had OSA. 22 traits were genetically correlated with REI. Without BMI adjustment, the PRSs of BMI, waist-to-hip ratio (WHR), diastolic blood pressure (DBP), pulse pressure (PP), HbA1c, triglycerides (TG), FEV1/FVC and insomnia were significantly associated with REI/OSA. The associations of WHR, DBP, PP, HbA1c and insomnia PRSs and REI/OSA remained in BMI adjusted analysis. In obesity-stratified analysis, PRS of BMI, WHR and DBP were associated with REI/OSA in individuals with obesity, while PRSs of FEV1/FVC, HbA1c, insomnia, PP, TG, and WHR were associated with REI/OSA in individuals without obesity. MR analysis identified robust causal effect of increased BMI on OSA, and suggestive causal effects of WHR, DBP, and PP on OSA.

Conclusion

Our results support shared genetic basis of anthropometric traits, blood pressure traits, and insomnia with OSA, with potential differences in disease mechanisms in individuals with and without obesity.

Support (If Any)

Funding: R35HL135818, R21HL145425.
0053 The Role of Social Isolation on Sleep Problems Interfering with Daily Functioning
Authors: Wellman Camryn , Jankowski Samantha , Grandner Michael , Reign Deva , Dailey Natalie , Killgore William
Published: May 2022

Introduction

Amidst the COVID-19 pandemic, widespread feelings of social isolation have become more prevalent than ever before as lockdowns and social distancing measures led people to remain in their homes. The constructs of social isolation and loneliness are similar but reflect slightly different aspects of social experience. Social isolation reflects the amount of social contact a person experiences, whereas loneliness reflects the subjective experience of an emotional yearning for such contact. While is known that sleep problems have increased during the pandemic, there has been little research into the potential effects of social isolation on sleep problems. Here, we examined the influence of social isolation on the extent to which insomnia has interfered with daily life activities. We hypothesized that social isolation would contribute to greater disruption in daily functioning from insomnia, exclusive of the effects of loneliness.

Methods

13,298 English-speaking adults from across the U.S. (18-92 years old; 57.5% female) completed an online battery of assessments that included demographic questions, the Insomnia Severity Index (ISI), and the UCLA Loneliness Scale – Version 3 between April 2020 and April 2021. Participants were grouped based on whether they felt “socially isolated” or not at the time of assessment. Social isolation groups were compared for the extent that insomnia interfered with daily functioning, while statistically controlling for loneliness.

Results

After controlling for loneliness, socially isolated individuals reported much greater daily interference from sleep problems, M=1.58, SD=1.19, compared to those who denied feeling socially isolated, M=0.96, SD=1.04, F(1,13295)=287.67, p=7.5x10-64.

Conclusion

Social isolation during the pandemic was associated with significantly greater disruption of daily functioning due to sleep-related issues, even after adjusting for self-reported loneliness. Thus, feeling isolated and lacking social contact was related to functional degradation due to sleep problems. Prior evidence suggests that social isolation can have a dramatic negative impact on mental health and can lead to increased all-cause mortality, but these results suggest social isolation may also impact sleep health and functional outcomes (whether that be physical, cognitive, or psychological). Thus, being isolated during the pandemic was associated with greater degradation of functional outcomes of sleep, regardless of subjective loneliness.

Support (If Any)
0077 Exploring Psychological and Behavioral Factors with Sleep Health in Latinx Children
Authors: Nguyen-Rodriguez Selena , Lee Soomi , Jiao June , Master Lindsay , Buxton Orfeu
Published: May 2022

Introduction

While sleep health is comprised of multiple dimensions, extant research tends to investigate single elements of sleep, such as sleep duration or sleep quality. The current study aimed to explore whether psychological and behavioral factors were associated with a multidimensional sleep health score as well as if sleep health was related to adiposity among Latinx children.

Methods

A community sample of 100 Latinx 10-to-12-year-olds were recruited from Los Angeles and Orange Counties (California, US). Psychological (perceived stress, anxiety and depressive symptoms), sleep hygiene and chronotype (lower scores indicate more adaptive sleep hygiene and eveningness, respectively) measures were collected with surveys. Diet data (sugar, fiber) was collected by two 24-hour recalls. Adiposity (BMI percentile, percent body fat) was assessed via bioimpedance scale. Sleep actigraphy (1 week) provided objective sleep dimension data. A composite score of sleep health across 6 dimensions (regularity, satisfaction, alertness, timing, efficiency, and duration) was constructed (0=better to 6=poorer). Hierarchical linear regressions, controlling for demographics (age, gender, monthly household income), assessed associations for each set of factors.

Results

The mean sleep health score was 2.08±1.41; 31.6% of Latinx children in our sample had poor sleep health (using median cut-point of 2). Poorer sleep hygiene (std. β=-.235, p=.037) and higher income (std. β=.244, p=.022) were significantly associated with poorer sleep health, while eveningness was marginally related (std. β=-.210, p=.068). Lower fiber intake (std. β=-.235, p=.037) and higher income (std. β=-.245, p=.038) were significantly associated with poorer sleep health. Psychological and adiposity variables were not associated with sleep health after controlling for demographics.

Conclusion

This study shows the prevalence and correlates of poor sleep health in Latinx children, an understudied group at risk for several health disparities. Better sleep hygiene was related to better sleep health. Several findings diverge from the literature based on single dimensions of sleep in general samples. Higher SES was related to poorer sleep health. Psychological factors and adiposity were not related to sleep health. A novel finding was that higher fiber intake was related to better sleep health. Additional research is needed to better understand factors related to multidimensional sleep health in Latinx children.

Support (If Any)

This work was supported by the National Institute of General Medical Sciences under Award Numbers UL1GM118979, TL4GM118980, and RL5GM118978 as well as the National Heart, Lung and Blood Institute Award Number 1K01HL140283.
0081 Physiologic anatomy, use of Infra-Red Thermography in Hypersomnia
Authors: Govindan Srini
Published: May 2022

Introduction

In the words of Michel Salmon, " Between anatomy and physiology there is room for a functional anatomy and for a physiologic anatomy “. This concept was applied to analyze our (1) Sleep Research 21, 1992,341 (2) Sleep Research 22, 1993, 363, and (3) SLEEP 31, 2008, A219 publications on patients with Hypersomnia who had intracranial and extracranial blood flow evaluations.

Methods

For “Functional Anatomy”, Intracranial cerebral blood flow was done with Xenon 133 inhalation. For “Physiologic Anatomy”, Extracranial facial blood flow Imaging, Infra-Red thermography was done. 1992,3 and 2008 data was classified: Groups I, II and III. Group I had Intracranial and Extracranial blood flow study, 5% CO2 inhalation. Groups II had Extracranial flow study with 5 % CO2 and 100 % Oxygen inhalation. Groups III had Extracranial flow study 100 % Oxygen inhalation. Response interpretation: Normal response to 5% CO2, vasodilation. For 100% Oxygen / hyperoxia, vasoconstriction. Response is considered as normal or abnormal, if response is absent or paradoxical.

Results

Group I: All three patients 5% CO2 inhalation, intracranial Functional anatomy vasomotor response normal. Physiological Anatomy response abnormal. Group II, Physiological Anatomy study. 8 patients. CO2 response, 7/8 vasoconstriction, abnormal response. 100% Oxygen challenge, 4/8 had no vasoconstriction, abnormal response. Group III: Physiological anatomy. 7 patients tested with 100% Oxygen challenge. 6/7 abnormal response, (1 vasoconstriction, 4 no response, 2 vasodilation). Total of 18 patients in all groups, physiological anatomy/ Extracranial flow vasomotor response was abnormal in 16/18, (Group I = 3, Group II = 7, and Group III = 6)

Conclusion

In hypersomnia patients vasomotor testing, Functional Anatomy, intracranial flow vasomotion normal in 3/3 for hypercarbia inhalation. For Physiologic Anatomy, using Infra-Red Thermography to image extracranial facial blood flow (not coupled with metabolism) vasomotion was abnormal in 16/18 patients. 5% CO2 and 100% Oxygen inhalation used as contrast agents is well tolerated and facilitates imaging vasomotor dysfunction in the facial blood flow, trigeminal angiosomes, which can be correlated with hypersomnia. Association between trigeminal system and the hypocretin receptor 1 gene HCRTR1 gene has been reported.

Support (If Any)

None.
0092 The Effects of Slow-Oscillatory Galvanic Vestibular Stimulation on Sleep Physiology in Healthy Humans
Authors: Kishi Akifumi , Togo Fumiharu , Yamamoto Yoshiharu
Published: May 2022

Introduction

Recent studies have demonstrated that rocking promotes sleep in animals and humans. The application of an alternating current galvanic vestibular stimulation (GVS) can elicit body sway like rocking sensation. Here, we examined the effects of slow-oscillatory GVS, which can evoke the virtual rocking sensation in the brain, on objective and subjective sleep quality in healthy young adults.

Methods

We studied 14 healthy subjects (age: 22.7 p/m 1.4 years) who underwent 3 nap conditions (adaptation, sham [SHAM], and stimulation [STIM]), where SHAM and STIM were randomly allocated with a 1-week interval in general. The polysomnographic recordings were started at 2 pm and time in bed was restricted to 90 min for all subjects. In both conditions, electrodes were placed on both mastoids for GVS; in STIM condition, the slow-oscillatory (0.25 Hz sinusoidal) GVS was applied throughout the nap period with a current intensity of approximately 80% of sensory thresholds of each subject. The pattern of center of pressure during quiet standing was also measured using a force plate, with or without the same slow-oscillatory GVS. We analyzed sleep variables and electroencephalographic (EEG) spectral power and compared them between STIM and SHAM. Subjective sleep quality was also measured and compared between STIM and SHAM.

Results

We confirmed that subsensory slow-oscillatory GVS induced body sway corresponding to the stimulation frequency for all subjects. We found that sleep latency was significantly shorter and total sleep time as well as N2 duration were significantly longer in STIM than in SHAM. N3 duration did not differ significantly between the conditions. EEG power spectrum densities in delta, theta, and sigma bands were significantly greater in STIM than in SHAM. Subjective sleep quality was significantly better in STIM than in SHAM.

Conclusion

We demonstrated that subsensory slow-oscillatory GVS facilitated wake-sleep transition and improved objective and subjective sleep quality. The results suggest that weak periodic inputs into vestibular systems promote sleep by modulating the thalamocortical mechanisms in humans. This finding may open a new avenue toward a development of novel techniques for human sleep augmentation.

Support (If Any)

JST PRESTO (JPMJPR19J3) and JSPS KAKENHI (18K17891) to AK.
0144 Identification of sleep factors related to blood pressure in emergency medicine healthcare workers
Authors: Belloir Joseph , Firew Tsion , Miranda Maody , Shaw Kaitlin , Schwartz Joseph , Makarem Nour , Marcon Kathryn , Schultebraucks Katharina , Sullivan Alexandra , Chang Bernard , Shechter Ari
Published: May 2022

Introduction

Emergency Department (ED) healthcare workers (HCWs) may be at elevated risk for the development of cardiovascular disease (CVD), due in part to sleep and/or circadian disturbances. This study aimed to evaluate the relationship of sleep factors with blood pressure, a primary marker of CVD risk, in ED HCWs.

Methods

Participants were HCWs (physicians, nurses, advanced practice providers, technicians, etc.) from 4 EDs in New York City who completed study procedures between November 2020-October 2021. Participants completed a 2-week data burst, which included sleep/activity (Fitbit Inspire) and home blood pressure monitoring (Omron 5 Series BP7250; preceding and following their main daily sleep episode). Linear regression models, adjusted for age, gender, and race/ethnicity, were conducted predicting blood pressure from sleep factors.

Results

The sample included n=74 ED HCWs (mean [SD] age=38.4 [8.7] years). Most were female (62.2%) and non-Hispanic/Latino White (55.6%). Mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) were 116.1 (12.5) mmHg and 75.1 (7.6) mmHg, respectively. Actigraphy-derived sleep factor means for the data burst period were: a) Total sleep time (TST): 6.8 (1.0) hours; b) Sleep efficiency (SE): 94.5 (2.2)%; c) Percentage of main sleep episodes throughout the burst with TST <6 hours: 25.9 (20.8)%; d) Sleep start time: 24:06 (01:24); and e) Within-subject inter-daily bedtime variability (i.e., SD of sleep start times): 2.4 (1.8) hours. Higher TST was associated with lower SBP (B [SE] =-0.50 [0.30] mmHg/10 min, p=.04) and DBP (B [SE] =-0.50 [0.20] mmHg/10 min, p=.01). Greater SE was associated with lower SBP (B [SE] =-1.23 [0.55], mmHg/%, p=.03) and DBP (B [SE] =-1.05 [0.39], mmHg/%, p=.01). A higher proportion of nights with TST <6 hours was associated with higher DBP (B [SE] =1.4 [0.40], mmHg/10%, p<0.01) but not SBP. Sleep start time and bedtime variability were not associated with BP.

Conclusion

These findings provide support for the relationship between sleep and blood pressure. Of note, data were collected during the COVID-19 pandemic, which may impact observed relationships. Because this is a cross-sectional analysis, the causal direction of the association may be (at least partially) reversed. Further research should examine psychological and work-related factors in ED HCWs that may modify these relationships, e.g., stress/anxiety, burnout, and job strain, and include assessments of the circadian system.

Support (If Any)

R01HL146911
0167 Obesity-Induced Breathing Variability During Sleep Is Not Entirely Attributed to Apneas and Sleep Fragmentation
Authors: Kim Lenise , Alexandre Chloe , Pho Huy , Latremoliere Alban , Polotsky Vsevolod , Pham Luu
Published: May 2022

Introduction

Obesity is a major cause of sleep-disordered breathing (SDB). Conventional metrics of SDB can be confounded by the effects of obesity on oxygenation and lack of standard definitions. Sleep fragmentation is frequently observed in obese individuals, but whether it occurs independently of SDB remains unknown. Quantitative analysis of ventilation may delineate the effects of obesity on breathing patterns and sleep fragmentation. We aimed to examine the effects of obesity on respiratory patterns during sleep and the relationship between obesity-related respiratory variability and sleep fragmentation.

Methods

Sleep recordings were performed in 15 lean C57BL/6J and 17 diet-induced obese (DIO) mice on the same genetic background. We applied Poincaré analysis of minute ventilation (VE) during sleep to estimate the breathing variability. Arousals were classified as respiratory when associated with ≥30% drops in VE from baseline.

Results

Breathing variability was significantly higher in DIO mice during NREM sleep, but not during REM sleep. Obesity-induced breathing variability could not be entirely attributed to apneas or arousals. Sleep fragmentation was 45% greater in DIO mice. Respiratory arousals comprised 15% of the arousals in both strains. Breathing variability was inversely associated with sleep fragmentation regardless of obesity.

Conclusion

Obesity increased respiratory variability during NREM sleep, which was not fully attributed to apneas and macro-sleep architecture. Obesity caused sleep fragmentation that was not entirely explained by SDB severity. Our quantitative analysis of VE identified differences in breathing variability in obesity that were not captured by traditional SDB metrics, which may be applicable for human SDB.

Support (If Any)

NHLBI NIH R01 HL135483, 2R01 HL133100-05, R01 HL128970, and R01 HL13892; NINDS NIH R01 NS112266; American Academy of Sleep Medicine Foundation 238-BS-20; American Thoracic Society Unrestricted Award; Johns Hopkins Blaustein Pain Research Grant; American Heart Association Postdoctoral Fellowship Award 828142.
0213 Circadian Entrainment and Cognition in College Students using Antidepressants
Authors: Gilmore Gabriel , Bianchetta Megan , Reinert Oda , Davic Steven , Trimp Gabrielle , Dyche Jeff
Published: May 2022

Introduction

Depression, sleep disturbances, and cognitive deficits often co-occur. Compared to non-medicated controls, people using antidepressant medications (particularly serotonin agonists) often have improved sleep including increased slow wave sleep, quality and continuity. Improvements to cognition after antidepressant treatments are also common including benefits to reaction time, inhibition, and memory. Importantly, circadian deficits, including sleep onset latency, fragmentation, and phase shifts are common in patients with depression, yet the effect of antidepressant medication on circadian indicators is unclear. The current project examined sleep, circadian entrainment, and cognition in college students who were diagnosed with depression and using serotonin agonists and in those without depressive symptoms.

Methods

Participants completed cognitive tasks that assessed reaction time, memory, attention, inhibition, and logical reasoning via the Automated Neuropsychological Assessment Metric between 1100-1700 two times, first at study enrollment and second after a two-week study interval. After initial cognitive assessments, participants wore actigraphs for two weeks from which we extracted their sleep-wake patterns, total sleep time(TST), time in bed(TIB), sleep-onset latency(SOL), sleep efficiency, and wake after sleep onset(WASO). Study 1 included 15 undergraduate students (11F, 7 antidepressant users, Mage=19.53) and Study 2 included 25 graduate students (21F, 13 antidepressant users, Mage=25.37), all recruited from James Madison University.

Results

Study 1 found that undergraduate antidepressant users had longer TIB, TST, and SOL. No cognitive or entrainment differences were found between drug use conditions. Within the antidepressant group, higher dosage predicted shorter TIB(r2=.64, p<.05), poorer spatial processing speed(r2=.73, p<.05) and logical relation performance(r2=.81, p<.05). In study 2, no circadian or cognitive differences were present across drug conditions. Deficits in WASO and sleep efficiency for antidepressant users were present. Within the antidepressant group, years of antidepressant use and dosage predicted poorer reaction time(r2=.84, p<.05), inhibition(r2=.70, p<.05), and spatial processing(r2=.98, p<.05). Self-reported wake episodes also predicted poorer reaction time and inhibition. Years of antidepressant use, dosage, and time of antidepressant use predicted TIB(r2=.73, p<.05), and time of antidepressant use predicted TST(sr2=.79, p<.05).

Conclusion

Future studies should use longitudinal research designs and prospective methods to examine the impact of antidepressant medications on circadian rhythms, sleep and cognition.

Support (If Any)
0221 Pre-Sleep Breath alcohol concentrations (psBrAC) and sleep polysomnography (PSG)
Authors: McCullar Katie , Barker David , McGeary John , Saletin Jared , Gredvig-Ardito Caroline , Carskadon Mary
Published: May 2022

Introduction

Alcohol use before bedtime has been shown to alter sleep including decreasing sleep latency, decreasing sleep efficiency, and fragmenting sleep stage distribution. Few studies manipulate pre-sleep alcohol concentration, instead focusing on a target dose or peak alcohol concentration during the night. Thus, we investigated how presleep breath alcohol concentrations (psBrAC) level (targeting a BrAC of 0.08), are associated with same-night sleep.

Methods

Thirty (15F; ages=22-57, mean=33yr) healthy adults who self-reported moderate drinking were instructed to maintain a consistent sleep schedule (8-9h time in bed) for a least 7-days before entering a cross-over design involving two sets (separated by>3 days) of 3 consecutive nights of in-lab polysomnography. For all nights in each condition, participants drank either mixer alone or mixer+alcohol in 3 portions across 45 minutes ending 1h before lights out. psBrAC was measured within 5 minutes of lights out. PSGs were staged according to Rechtschaffen and Kales (1968). We computed: slow wave sleep (SWS) and REM as percentages of total sleep for the full night (%SWS) & (%REM), %SWS in the first third of the night (%SWST1), %REM in the last third of the night (%REMT3), minutes until sleep onset from lights out (Sleep Latency), and minutes after sleep onset until REM onset. Linear regressions tested if psBrAC on the first mixer+alcohol night predicted changes in sleep using the average of the three nights of sleep in the mixer-only condition as a covariate.

Results

psBrAC values ranged from 0.038 to 0.087 (mean = 0.066) mg/L. We identified minimal influence of BrAC on sleep: % SWS (β = -0.78; p = 0.07), % REM (β = 0.032; p = 0.96), % SWS T1 (β = -0.52; p = 0.522), % REM T3 (β = -1.01; p = 0.125), REM latency (β = 3.95; p = 0.302), and sleep latency (β = -1.23; p = 0.13).

Conclusion

These findings indicate that psBrAC was not associated with any of our sleep variables, when adjusting for sleep on nights without alcohol. Future work will examine peak BrAC as well whether the effects observed change over multiple nights of pre-sleep alcohol consumption.

Support (If Any)

R01AA025593
0264 Sleepiness in cognitively unimpaired older adults is associated with CSF biomarkers of inflammation and axonal integrity
Authors: Carvalho Diego , Louis Erik St , Przybelski Scott , Morgenthaler Timothy , Boeve Bradley , Petersen Ronald , Jack Clifford , Graff-Radford Jonathan , Vemuri Prashanthi , Mielke Michele
Published: May 2022

Introduction

We have previously shown that older adults with excessive daytime sleepiness (EDS) appear to be more vulnerable to longitudinal amyloid PET accumulation before the onset of the dementia. It remains unclear whether this vulnerability is specific to amyloid or extends to other biomarkers of Alzheimer’s disease pathology, or axonal integrity and inflammation, which can also contribute to neurodegeneration and cognitive changes.

Methods

For this cross-sectional analysis, we identified 260 cognitively unimpaired adults (>60 years old) without neurologic disorder who underwent CSF quantification of AD biomarkers (CSF Aβ-42, p-tau181, p-tau217) along with at least one other biomarker of interest (neurofilament light chain [NfL], IL-6, IL-10, and TNF-α) from the Mayo Clinic Study of Aging – a longitudinal population-based cohort in Olmsted County, Minnesota. CSF biomarkers were available in 251-260 individuals, depending on the biomarker. We fit linear regression models to assess whether the CSF biomarkers were associated with sleepiness as measured by the Epworth Sleepiness Scale (ESS), after controlling for age, sex, APOE4 genotype, BMI, hypertension, dyslipidemia, and OSA diagnosis (by chart review).

Results

Higher ESS scores were independently associated with higher CSF IL-6 and NfL, but not with the other biomarkers in the whole sample. For every single-point increase in the ESS score, there was a .008 ([95% CI .001-.016], p=0.033) increase in the log of IL-6 and .01 ([95% CI .002-.018], p=0.016) increase in the log of NfL. A sensitivity analysis showed a correlation between ESS scores and log of p-tau/Aβ-42 ratio only in participants with abnormal ratio (>0.023), after controlling for APOE4 (partial r=.27, p=039).

Conclusion

Our results corroborate previous literature suggesting that higher inflammatory milieu reflected by increased CSF IL-6 is associated with sleepiness. The association between NfL and sleepiness suggests that sleepiness may be related to disturbed connectivity due to axonal damage. Alternatively, NfL may be a surrogate of active axonal injury associated with more disrupted sleep. A correlation between sleepiness and CSF p-tau/ab-42 ratio was only seen in patients with abnormal ratio, suggesting a stronger association between sleepiness and AD pathology as the disease progresses, possibly because AD pathology worsens sleep quality and/or vice-versa.

Support (If Any)

NIH/NIA
0272 Decreased Risk of 2-Year Incidence of Alzheimer’s Disease Among Older Adults Who Report Sleep Symptoms
Authors: Mason Brooke , Wills Chloe , Tubbs Andrew , Seixas Azizi , Turner Arlener , Jean-Louis Girardin , Killgore William , Grandner Michael
Published: May 2022

Introduction

Those with dementia or Alzheimer’s Disease report an elevated amount of sleep difficulties compared to age-matched controls. Sleep-based interventions may be especially useful for this group, such as cognitive behavioral therapy for insomnia or pharmacological interventions. Therefore, it is important to expand the current understanding of the nature of sleep difficulties in those with Alzheimer’s Disease.

Methods

Data from the 2018 Health and Retirement Survey was collected from 17,146 older adults. Poisson regression analyses were used to explore the relationship between Alzheimer’s Disease as diagnosed by a doctor and sleep difficulties. Individuals who reported no Alzheimer’s Disease in the previous wave (N=16,751) were asked if they had since become diagnosed. N=101 individuals reported incident Alzheimer’s Disease in the 2-year gap between assessments. Sleep difficulties were assessed by asking participants if they had difficulties initiating or maintaining sleep, waking up too early, and how rested they felt upon awakening. All 4 of these symptoms were coded as “never,” “sometimes,” or “often.”

Results

Unexpectedly, there was a significant decreased risk of developing Alzheimer’s Disease among those who reported difficulties maintaining sleep (IRR=0.9962; 95%CI[0.9936,0.9988]; p=0.004), and early morning awakenings (IRR=0.9961; 95%CI[0.9938,0.9984]; p=0.001) “sometimes”. When the model was adjusted for sex, race, ethnicity, age, and depression, a similar finding of decreased risk for Alzheimer’s Disease for those who reported difficulties maintaining sleep (IRR=0.9953; 95%CI[0.9927,0.9980]; p<0.001), and early morning awakenings (IRR=0.9954; 95%CI[0.9930,0.9978]; p=0.001), “sometimes” were maintained.

Conclusion

Although previous studies have shown that poor sleep may lead to increased risk of Alzheimer’s and related dementias, the present study, which examined longitudinal data from a large, national sample of older adults, found that there was no association between frequent sleep disturbances and 2-year incidence of Alzheimer’s Disease, and a small association between more mild symptoms and decreased risk. It is possible that the 2-year observation window was insufficient to detect effects. Also, there is a risk of measurement error in collecting self-reported data on sleep and Alzheimer’s diagnoses.

Support (If Any)

The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan.
0273 Sleep Disorders as a Potential Risk Factor for Dementia in Elderly Adults
Authors: Kuhler Cassandra , Wills Chloe , Mason Brooke , Tubbs Andrew , Seixas Azizi , Turner Arlener , Jean-Louis Girardin , Killgore William , Grandner Michael
Published: May 2022

Introduction

Sleep disorders such as insomnia are seen in the early onset of Alzheimer’s disease, the most common form of dementia. Simultaneously, sleep disorders may indicate increased risk for the development of dementia. Due to the rate of comorbidity of these two conditions seen in the elderly population, the relationship between dementia and sleep disorders is a topic of interest for researchers. A bidirectional correlation between the two could have important implications in the clinical field exploring factors that lead to dementia

Methods

Data was assessed from 17,146 older adults from the 2018 Health and Retirement Survey. Participants were surveyed using questionnaires regarding both incident dementia or serious memory impairment in the past 2 years and the presence of a sleep disorder, as diagnosed by a doctor or health professional. Those who reported no dementia in the previous wave (N=16,547) were asked if they had been diagnosed since they were last asked. N=185 individuals reported incident dementia in the 2-years between assessments. Responses were coded to either “Yes” or “No”. A Poisson regression analysis was conducted to explore the relationship between incident dementia and sleep disorders.

Results

In a sample of older adults, unadjusted results indicate that having a sleep disorder was associated with a 0.6% increased risk of new onset dementia (PRR=1.006; 95%CI[1.001,1.012]; p=0.026). These results were sustained when adjusted for sex, age, race, ethnicity, and depression (PRR=1.006; 95%CI[1.001,1.012]; p=0.013).

Conclusion

Chronic sleep disturbances may be a factor used to indicate increased risk for dementia and help with early detection of the disease. These results demonstrate the value of sleep disorders screening among those at risk for dementia. Further research is needed to clarify these findings (e.g., explore specific sleep disorders) and expand the follow-up window (i.e., beyond 2 years).

Support (If Any)

The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan.
0274 Effect of aging on sleep architecture including a novel REM Behavior Disorder phenotype in the PS19 mouse model of tauopathy and effect of a dual orexin receptor antagonist
Authors: Kam Korey , Vetter Kenny , Varga Andrew
Published: May 2022

Introduction

This project examines changes to sleep micro-architecture with aging in the PS19 (MAPT P301S) model of tauopathy and response to a dual orexin receptor antagonist (DORA-12) in aged PS19 mice.

Methods

24-hour video PSG recordings occurred in 28 PS19 mice and 22 littermate controls at 2-3 months (young) and 10-14 months (old).

Results

Spindle density significantly deceased as a function of both advanced age and PS19 genotype without interaction. We observed a significant interaction between age and genotype on slow oscillation (SO) density such that SO density was higher in young PS19 lower in old PS19 mice vs controls without main effects of age or genotype. Phase amplitude coupling of spindles to detected SO events was significantly decreased as a function of age with a trend toward an age/genotype interaction such that the reduction in coupling was greater with aging in PS19 mice vs controls. We observed unexpected dream enactment during REM in 3 of 11 old PS19 but not in young PS19 mice or control mice at any age. Normalized cumulative EMG area during REM sleep, cumulative duration of elevated EMG in REM, and %REM w/o atonia were all significantly increased in mice displaying dream enactment.Old PS19 mice were also video-PSG recorded for 24 hours while receiving 100 mg/kg DORA-12 vs vehicle control orally twice daily. DORA-12 resulted in significant reduction in latency to persistent NREM and REM sleep, and significant increases in spindle density and SO density, without significant difference in spindle-SO coupling. While we did not observe significant differences in dream enactment measures with DORA-12 due to low sample size, all 3 mice with dream enactment displayed decreases in normalized EMG amplitude in REM and %REM with EMG bursts with DORA-12 ranging from 10 to 60%.

Conclusion

Given the importance of spindles, SO’s, and their coupling on cognitive processes, these observations can motivate further evaluation of DORA’s toward such cognitive processes in neurodegenerative models as well as effect of DORA’s on RBD phenotypes.

Support (If Any)
0278 Isolated REM sleep behavior disorder is associated with 24-hour rhythm disruption
Authors: Winer Joseph , Lok Renske , Cahuas Ana , Bueno Flavia , Poston Kathleen , Mormino Elizabeth , Zeitzer Jamie , During Emmanuel
Published: May 2022

Introduction

Isolated REM sleep behavior disorder (iRBD), the loss of motor inhibition during REM sleep, is a symptom of prodromal Lewy body disease, with over 80% of iRBD patients eventually phenoconverting to Parkinson’s disease or Dementia with Lewy bodies. Rest-activity rhythm disruption, also an established predictor of Parkinson’s disease, has not been well characterized in patients with iRBD. Here, we tested the hypothesis that accelerometer-based measures of 24-hour rhythms would indicate greater fragmentation and variability in patients with iRBD relative to matched healthy controls.

Methods

N=36 patients with iRBD recruited from the Stanford Sleep Clinic had 24-hour activity continuously monitored for (mean ± SD) 25.3 ± 8.4 days using an Axivity wristworn device. A control dataset of age, sex, and body mass index matched healthy older adults (N=126) was selected from the UK Biobank accelerometer dataset. Raw accelerometer data were processed using the GGIR, nparACT, and ActCR software packages in R, with a focus on nonparametric and 5-parameter cosinor measures of 24-hour rhythms. Functional PCA analyses (fPCA) were applied to detect overall differences in 24-hour rhythms and during sleep.

Results

Patients with iRBD had lower interdaily stability and higher intradaily variability than controls (IS, Cohen’s d=-1.15, Mann-Whitney test p<0.001; IV, d=0.46, p=0.04). Cosine amplitude was lower in iRBD patients (d=-0.22, p=0.001), but mean activity (mesor) did not differ (d=0.03, p=0.31), suggesting differences in rest-activity patterns rather than overall activity levels. A shape naïve approach utilizing fPCA indicated that increased activity during the night may explain overall rhythm differences observed in iRBD.

Conclusion

Multiple metrics of rest-activity rhythms support the hypothesis that 24-hour rhythms are disrupted in iRBD. It remains to be determined whether rhythm fragmentation in iRBD reflects higher activity levels during REM sleep, or if dysfunctional rhythms represent the direct effects of degenerating sleep-wake regulating circuits, indicating the early stages of Lewy body disease.

Support (If Any)

NIA F32AG074625 to JW; NIA P30AG066515 to JW, KP, and EM