bluuebunny/crossref_metadata_2025 huggingface dataset:
0173 Baseline Actigraphic Sleep Measures Predict Cardiovascular Responses to Sleep Deprivation and Psychological Stress
Authors: Pasetes Lauren , Rosendahl-Garcia Kathleen , Goel Namni
Published: April 2024

Introduction

We determined whether baseline sleep measures the night before total sleep deprivation (TSD) predicted cardiovascular (CV) responses to TSD and to TSD and psychological stress.

Methods

We conducted a five-day experiment under controlled conditions in thirty-two healthy adults (ages 27-53; 14 females). During this experiment, CV measures were collected via echocardiography or blood pressure monitor at four assessment time points: 1) after two baseline 8h time in bed (TIB) nights (B1, B2); 2) in the morning of TSD (TSD AM; after 25h of TSD); 3) in the evening of TSD following a modified Trier Social Stress Test, which induced psychological stress (TSD PM; after 34h of TSD); and 4) after two recovery nights of 8-10h TIB. Seated stroke volume (SV), heart rate (HR), cardiac index (CI), left ventricular ejection time (LVET), systemic vascular resistance index (SVRI), mean arterial pressure (MAP), and systolic and diastolic blood pressure (SBP and DBP) were collected. Wrist actigraphy (Actiwatch Spectrum) assessed sleep indices during the second baseline night (B2) including sleep duration, sleep onset latency (SOL), wake after sleep onset (WASO), sleep efficiency (SE), percent sleep, and the timing of sleep onset, offset, and midpoint. Pearson’s correlations assessed relationships between B2 sleep metrics and TSD AM and TSD PM CV responses (p≤0.05 was significant).

Results

Higher WASO during baseline was significantly associated with lower SV (r=−0.374; r2=0.140) and higher SVRI (r=0.358; r2=0.128) during the TSD evening. By contrast, there were inverse relationships for percent sleep and SE during baseline, whereby these metrics were significantly associated with higher SV and lower SVRI during the TSD evening (r:−0.398-0.387; r2:0.126-0.159). In addition, a later sleep offset during baseline was significantly associated with higher MAP, SBP, and DBP during the morning and the evening of TSD (r:0.391-0.453; r2:0.153-0.205).

Conclusion

Our novel results found that actigraphic sleep metrics the night before TSD predicted CV responses in healthy adults, particularly during TSD and psychological stress in the evening. Thus, WASO, percent sleep, SE, and sleep offset timing during fully rested conditions are possible predictors and biomarkers for assessing the adverse cardiovascular responses to TSD and psychological stress.

Support (if any)

NASA grants NNX14AN49G and 80NSSC20K0243 (NG)
0178 Cumulative Effects of Mild Sleep Restriction on Lapses of Attention
Authors: Barley Blake , Scullin Michael
Published: April 2024

Introduction

Sleep deprivation leads to detriments in performance, including alertness and vigilance. Less is known, however, about the cognitive impact of mild sleep restriction, including whether negative outcomes are time-dependent and cumulative. We tested the impact of sleep restriction on sustained attention in a multi-week, crossover experiment in a controlled laboratory setting.

Methods

Sixty-six young adults (Mage = 20.03; 53.0% female; 51.5% non-white) completed seven nights of in-laboratory testing, spread across 3-weeks. On the first week, participants completed a polysomnography adaptation night and baseline assessments including the psychomotor vigilance task (PVT) in the evening (9:00PM) and in the morning (7:30AM) with buffer time to prevent sleep inertia following initial awakening. During the following week, participants completed either three nights of sleep restriction (5 hours of sleep/night) or three nights of normal sleep (8 hours of sleep/night), with PVT testing each morning and evening. After a four-night washout period, participants returned to complete the other sleep condition (order counterbalanced). Research assistants who administered the PVT were kept blinded to the participant’s sleep condition.

Results

Relative to normal sleep, three nights of sleep restriction significantly worsened PVT mean reaction times (RTs; M = 361 ms versus M = 390 ms; t(65) = 4.38, p < .001, d = .54) and number of lapses (M= 3.78 versus M = 5.80; t(65) = 5.00, p < .001, d = .62]. There were no main effects of time of day or interactions with sleep condition (ps>.05). However, study day significantly interacted with sleep condition (F(2, 128) = 3.42, p = .036, η2 = .051) such that the negative impact of sleep restriction on lapses worsened across the week (night 1: Mdiff = 1.59, night 2: Mdiff = 0.88; night 3: Mdiff = 3.26).

Conclusion

Mild sleep restriction quickly produces detriments in sustained attention, with effects being cumulative across repeated days of sleep loss.

Support (if any)

This study was supported by the National Science Foundation (1920730).
0179 Cardiovascular Responses to Sleep Deprivation and Psychological Stress Predict Actigraphic Sleep During Recovery
Authors: Pasetes Lauren , Rosendahl-Garcia Kathleen , Goel Namni
Published: April 2024

Introduction

We assessed whether cardiovascular (CV) responses to total sleep deprivation (TSD) and to TSD and psychological stress predicted sleep measures during that night’s recovery.

Methods

Thirty-two healthy adults (ages 27-53; 14 females) participated in a five-day experiment under controlled conditions. During this experiment, CV measures were collected via blood pressure monitor or echocardiography at four assessment time points: 1) after two baseline 8h time in bed (TIB) nights; 2) in the morning of TSD (TSD AM; after 25h of TSD); 3) in the evening of TSD following a modified Trier Social Stress Test, which induced psychological stress (TSD PM; after 34h of TSD); and 4) after two recovery nights (R1=10h TIB; R2=8h TIB). Seated heart rate (HR), cardiac index (CI), stroke volume (SV), systemic vascular resistance index (SVRI), left ventricular ejection time (LVET), systolic and diastolic blood pressure (SBP and DBP), and mean arterial pressure (MAP) were collected. Wrist actigraphy (Actiwatch Spectrum) assessed sleep measures during the first recovery night (R1) including the timing of sleep onset, offset, and midpoint, sleep duration, wake after sleep onset (WASO), sleep efficiency (SE), percent sleep, and sleep onset latency (SOL). Pearson’s correlations assessed relationships between TSD AM and TSD PM CV responses and R1 sleep indices (p< 0.05 was significant).

Results

Longer LVET in the morning and in the evening of TSD were significantly associated with longer sleep duration and later sleep offset during recovery (r: 0.386-0.471; r2: 0.149-0.222). In addition, longer LVET in the evening of TSD was significantly associated with higher WASO during recovery (r=0.385; r2=0.148). By contrast, lower HR in the morning (r=−0.449; r2=0.202) and in the evening (r=−0.499; r2=0.249) of TSD were significantly related to a later sleep offset during recovery.

Conclusion

To the best of our knowledge, this is the first demonstration that CV responses to TSD and to TSD and psychological stress, are reflected in the duration, quality, and timing of actigraphic sleep during the immediate recovery night in healthy adults. Overall, LVET and HR during sleep deprivation may be unique biomarkers for determining sleep responses during recovery that night.

Support (if any)

NASA grants NNX14AN49G and 80NSSC20K0243 (NG)
0193 The Effect of Sleep Deprivation on Pain Perception in Awake Rats
Authors: Lim Sung Chul
Published: April 2024

Introduction

This study was conducted to determine how sleep deprivation affects headache perception and brain structure in an animal model of headache.

Methods

The effect of sleep deprivation on mechanical pain threshold was assessed in two groups of animals: (i) NSD-C group and (ii) SD group. The VFMF thresholds were assessed every day during 96 hours of sleep deprivation. After 96 hours sleep deprivation, the brain of each groups were analyzed with immunohistochemistry staining. The effect of sleep deprivation in supradural capsicin infusion were assessed in two groups. The VFMF threshold was performed during sleep deprivation and 4 weeks of recovery phase.

Results

1) The effect of sleep deprivation on mechanical pain threshold. In comparison between SD and NSD-C group, the significant difference appeared after 1 day of sleep deprivation and lasted 4 days. 2) The effect of sleep deprivation on FOS reactivity. In hyptothalamus, the number of Fos-positive cells in PoHT increased significantly in SD group compared NSD-C group. In PAG, the number of Fos-positive cells in VLPAG increased significantly in SD group compared NSD-C group. The number of Fos-positive cells of supf C in TCC increased significantly in SD group compared NSD-C group. 3) The effect of sleep deprivation on mechanical pain threshold in supradural capsicin infusion. SD-Capsicin showed the tendency of lower VFMF threshold compared to NSD-Capsicin, which reach to statistical significant 3rd days of capsicin infusion period. During the recovery phase, the reduced VFMF threshold of NSD-Capsicin group was persisted 1 week after sleep deprivation and returned to baseline thereafter. In SD-Capsicin group, the reduced VFMF threshold was persisted 3 week after sleep deprivation.

Conclusion

In this study, pain lasted for 1 week after 4 days of continuous infusion of capsicin without sleep deprivation, but lasted for more than 3 weeks when combined with sleep deprivation, confirming the possibility that sleep deprivation contributes to the chronicity of headache. The chronicity and persistence of headache is associated with the centralization of pain. The findings of this study that sleep deprivation results in changes in TNC activity, which plays an important role in centralization, support this possibility.

Support (if any)
0194 Impact of Sleep Deprivation Combined with Alcohol or Oxycodone on Sleep Architecture in Healthy Young Adults
Authors: Chowdhury Madihah , Finlay Myles , Layton Matthew , Van Dongen Hans , Stroer Claire , Mollicone Daniel , Hansen Devon
Published: April 2024

Introduction

Alcohol and opioids disturb sleep, but the impact of substance use on recovery sleep after sleep deprivation is largely unknown. Here we piloted a study protocol to assess the combined impact of total sleep deprivation (TSD) and substance administration on recovery sleep.

Methods

N=6 healthy normal sleepers (ages 28.2±5.6y; 4 males) completed two 24h laboratory study sessions. During each session, which began at 15:00, participants were kept awake for 15h until 06:00 the next day. They were then given an 8h recovery sleep opportunity (06:00–14:00) and went home. During the second study session, participants were randomly assigned to receive alcohol (n=3; peak BAC of 0.043±0.008% at 00:55, decayed to zero by 06:00) or an opioid (n=3; 10mg oxycodone administered at 22:30). Recovery sleep was recorded polysomnographically and scored using AASM criteria; analyses focused on total sleep time (TST), sleep efficiency, sleep latency, sleep stages N1–N3 and REM, and latency to each of the sleep stages.

Results

Session 1 (pre-substance) TST was considerably shorter in the opioid group (282±28min) than the alcohol group (403±24min). Therefore, we analyzed sleep variables for the two groups separately, using mixed-effects ANOVA with a fixed effect for study session (TSD vs. TSD+drug) and a random effect over subjects on the intercept. For the opioid group, latency to N3 sleep was significantly longer by 10±2min after opioid administration compared to TSD alone (F=33.8, p=0.028). There were no significant effects of TSD+alcohol compared to TSD alone.

Conclusion

Opioid administration during TSD delayed N3 onset, but no other effects of opioid or alcohol administration were seen during recovery sleep. Our sample was small, but the within-subjects study design provided considerable statistical power – substance effects on neurobehavioral performance during TSD (reported elsewhere) were readily detectable. However, BAC at the onset of recovery sleep had decayed to zero, and elevated homeostatic sleep pressure from TSD may have negated any residual substance effects other than the opioid-induced delay in N3. Investigating the impact of substances on recovery sleep after TSD, as well as post-recovery neurobehavioral functioning, is important for safety and health in today’s sleep-deprived society.

Support (if any)

National Safety Council
0199 Circadian Misalignment, Cardiac-Autonomic and Inflammatory Pathways, and Metabolic Syndrome in Adolescents
Authors: Morales-Ghinaglia Natasha , Calhoun Susan , Liao Jason , Vgontzas Alexandros , Liao Duanping , Bixler Edward , Fernandez-Mendoza Julio
Published: April 2024

Introduction

Although insufficient sleep is a known risk factor for metabolic syndrome (MetS), circadian misalignment, which is highly prevalent during adolescence, may also impact cardiac, autonomic and immune regulation. Prior studies have shown that circadian misalignment impacts the association between visceral adiposity (VAT) and MetS in youth, which is not explained by lifestyle factors such as diet or physical activity. We hypothesize that cardiac-autonomic and inflammatory pathways will significantly diminish the impact of circadian misalignment on the relationship between VAT and MetS in adolescents.

Methods

We analyzed 262 adolescents from the Penn State Child Cohort (median 16y; 48% female; 22% racial/ethnic minority) who had at least 5 nights of actigraphy (ACT) and were evaluated while in-school (n=171) or on-break (n=91). They also had 9-h polysomnography (PSG), a dual-energy X-ray absorptiometry (DXA) scan, 24-h Holter-monitoring heart rate variability (HRV), and a composite score of inflammatory biomarkers, including fasting C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNFα), adiponectin, and leptin data. DXA-measured VAT was the predictor. A continuous MetS score was the outcome. ACT-measured sleep midpoint (SM), sleep irregularity (SI), and social jetlag (SJL) were tested as effect modifiers. Linear regression models were first adjusted for essential covariates (i.e., sex, race/ethnicity, age, ACT-sleep duration, ACT-sleep variability, and PSG-apnea/hypopnea index), and, thereafter, for HRV and inflammatory biomarkers.

Results

Significant interactions were found between VAT and SM, SI or SJL while in-school on MetS adjusting for essential covariates (interaction effects: 0.58 (0.25) p=0.023, 0.38 (0.15) p=0.013, and 0.69 (0.22) p=0.002, respectively). Further adjusting for 24-HRV indices (e.g., Log-HF and RMSSD) or for inflammatory biomarkers did not significantly impact the effect modifications observed (e.g., interaction effects after adjusting for 24-h Log-HF: 0.55 (0.25) p=0.028, 0.36 (0.15) p=0.018, and 0.67 (0.21) p=0.002, respectively).

Conclusion

Cardiac-autonomic or inflammatory pathways do not significantly account for the role that circadian misalignment has in increasing the impact of VAT on MetS burden in adolescents. Other pathways, specific to circadian rhythms either biological or behavioral, may be involved in how circadian misalignment contributes to the development of cardiometabolic sequelae associated with central obesity.

Support (if any)

AHA (23PRE1011962), NIH (R01HL136587,R01MH118308,UL1TR000127)
0200 Greater Social Jetlag Is Associated with Higher BMI-z in Early Childhood
Authors: Choubai Sophia , Harsh John , Hartstein Lauren , Wong Sachi , Abbas Leen , LeBourgeois Monique
Published: April 2024

Introduction

Misalignment between biological and social timing, as evidenced by the weekend-weekday difference in sleep midpoint, is termed social jetlag (SJL). SJL is associated with higher BMI and obesity in adults, adolescents, and older children; however, to our knowledge, no research to date has addressed SJL and BMI in early childhood. The present study examined the relationship between SJL and BMI-z in young children aged 2.0–8.9 years. We hypothesized that children with greater SJL would have higher BMI-z, before and after adjusting for potential covariates.

Methods

Data were collected from 158 children aged 2.0–8.9 years (M = 5.6 ± 1.98y, 46.2% females) from the RESONANCE cohort of the NIH Environmental Influences on Child Health Outcomes (ECHO) study between 2018–2021. Caregivers completed the ECHO Child Sleep Health Questionnaire and trained staff measured children’s height and weight. Age- and sex-adjusted BMI-z was computed (CDC). SJL was calculated as the weekend-weekday difference in nocturnal sleep midpoint. Primary linear regression models adjusted for child age, sex, race, ethnicity, and maternal education; secondary models further adjusted for average sleep duration, weekday-weekend sleep duration difference, and napping frequency.

Results

On average, weekend midpoints were 41 minutes later relative to weekdays (t(157) = 12.5, p < 0.001). A positive association between SJL and BMI-z was observed in unadjusted and adjusted linear regression models. After controlling for all covariates, SJL remained significantly associated with BMI-z (R2 = 0.54, F(14, 143) = 12.18, p < 0.001). For every 1hr of SJL, BMI-z increases 0.389 units (b = 0.00647, p = 0.016). In children already overweight or obese, 1hr increase in SJL is associated with a 0.893 unit increase in BMI-z (b = 0.0149, p < 0.001).

Conclusion

Greater SJL was related to higher BMI-z in young children, consistent with findings in older children, adolescents, and adults. Thus, SJL may represent an obesity risk factor in early childhood. Targeted interventions to promote sleep regularity, especially in already overweight/obese children, may be beneficial. Future research should examine cumulative impacts of SJL across development and employ objective measures of body weight, including adiposity and waist circumference.

Support (if any)

UH3-0D023313
0202 Later Sleep Onset Timing Predicts Greater Postpartum Weight Retention at One Year Postpartum
Authors: Petrov Megan , Jiao Nana , Shu Jingmin , Liedike Bethany , Reifsnider Elizabeth , Coonrod Dean , St-Onge Marie-Pierre , Aggarwal Brooke , Whisner Corrie
Published: April 2024

Introduction

Postpartum weight retention (PPWR), defined as ≥5kg difference between pre-pregnancy and 12-month postpartum weights, is associated with sustained weight retention across the life course. Maternal insufficient sleep duration is associated with PPWR. However, few studies have measured sleep objectively and other potentially relevant sleep dimensions. Moreover, little is known about these associations in the first month postpartum, the period with the greatest maternal sleep disruption. We investigated whether nocturnal total sleep time (TST), wake after sleep onset (WASO), and sleep onset time, predicted PPWR among mothers with full-term infants.

Methods

This study is a preliminary, secondary analysis of a subsample of mothers from the Snuggle Bug study (n=51, age M±SD= 32.2±5.2y, 35.3% Hispanic/Latina), a longitudinal cohort of mother-infant dyads with infants of normal birth weight. Sleep in mothers was measured using wrist-actigraphy and sleep logs over five days at three weeks postpartum. Pre-pregnancy weight and post-delivery weight were self-reported at three weeks postpartum and gestational weight gain (GWG) was computed. At 12 months postpartum, maternal weight was measured twice using an electronic digital scale (nearest 0.1kg), and breastfeeding duration was reported. Linear and binary logistic, multiple regression models examined the associations of each sleep metric with change in maternal weight (pre-pregnancy to 12-month postpartum) and PPWR status (≥5kg difference), respectively, adjusting for age, pre-pregnancy weight, GWG, and breastfeeding duration, and in the models with WASO and sleep onset, TST was added.

Results

At 3 weeks postpartum, mothers’ mean TST, WASO, and sleep onset were 354.0±65.0min, 146.3±50.3min, and 23:19±1:23, respectively. The mean weight change from pre-pregnancy to 12 months postpartum was 3.0±6.8kg (5.0±8.7% increase from pre-pregnancy weight), and 34.0% had PPWR. Age and breastfeeding duration were not associated with the outcomes and were dropped from the models. Each one-hour delay in sleep onset predicted greater weight change (ΔR2=0.08, B=1.71kg, β=0.35, p=0.03), and greater odds of PPWR (OR: 1.90, 95%CI: 1.01-3.55, p=0.045). TST and WASO were not associated with the outcomes.

Conclusion

Among mothers, later bedtimes during early postpartum, independent of sleep duration, may heighten the risk for PPWR at one-year postpartum, which may have significant implications for cardiometabolic outcomes later in life.

Support (if any)

NIH/NHLBI R01HL147931
0209 A Sleepery Slope: Inhibitory Control in Child-adolescent Transition Linked to Power-law Scaling in NREM Sleep EEG
Authors: Dave Abhishek , Lui Kitty K , Chen Ivy Y , Chappel-Farley Miranda G , Radom-Aizik Shlomit , Benca Ruth , Neikrug Ariel , Mander Bryce
Published: April 2024

Introduction

Structural changes emblematic of brain development, e.g., synaptic pruning/myelination, are theorized to impact sleep architecture, local sleep physiology, and sleep-dependent cognition. Conventional analyses of sleep in development, relying on absolute or relative power from electroencephalography (EEG) to study the function of sleep rhythms, have disregarded the 1/f EEG power law as “neural noise". However, evidence tying steepness (1/f exponent) and intercept (1/f offset) of the power law curve to excitatory-inhibitory (E/I) balance and asynchronous neuronal population spiking warrants a reexamination of developmental sleep EEG.

Methods

19 healthy children and adolescents (ages 11-17, 11 girls) underwent overnight polysomnography with 128 channel EEG. Inhibitory control was assessed following sleep using inhibition scaled score (ISS) on a Color Word Interference Test. Spectral parameterization (fooof) was applied to median NREM multitaper absolute spectra (0.5-40Hz) to extricate oscillatory from aperiodic features (1/f exponent, 1/f offset, and residual oscillatory power). Topographical correlations between parameterized spectra, age and ISS were obtained with 5000-permutation threshold free cluster enhancement. Bootstrapped multiple regressions adjusting for age and sex modeled the association between ISS and parameterized neural spectra.

Results

Age showed widespread negative topographical correlations with broadband absolute spectral power, but these effects vanished in correlations with all oscillatory residuals except slow sigma (11-13Hz), which showed a modest negative trend over a central cluster. Remarkably, age showed widespread negative associations with 1/f offset, while age and 1/f exponent showed a negative trend over central channels. ISS was not significantly correlated with absolute power or with oscillatory residuals in canonical bands but was strongly negatively associated with 1/f exponent in a bilateral parietal arc. The cluster average of exponents from this parietal association significantly predicted next day ISS performance, adjusting for age and sex (B = 0.803, p = 0.013).

Conclusion

Aperiodic rather than oscillatory activity may drive broadband changes in developmental NREM spectra , and parietal E/I balance during sleep may partially explain (independent of age) developmental inhibitory control during wakefulness. More broadly, aperiodic features may complement neural oscillations in balancing localized and systemwide information processing demands to support developmental cognition.

Support (if any)

NIH NCATS Grant #UL1TR001414; Pediatric Exercise and Genomics Research Center Systems Biology Fund
0210 Chronotype, Sleep Difficulties and Lifestyle Habits in Adolescent Athletes During the COVID-19 Pandemic
Authors: Bourgon Vincent , Caron Jean-François , Forest Geneviève
Published: April 2024

Introduction

It is increasingly known that elite athletes have a high prevalence of sleep difficulties and that chronotype may influence this relationship. Although adolescents are also at risk for sleep disturbances, including a phase delay, few studies have characterized the sleep of adolescent athletes. The aim of this study was to investigate sleep difficulties and lifestyle habits in young athletes of different chronotypes.

Methods

208 young elite athletes (M=14.9y) completed the following online questionnaires during the first wave of the pandemic: Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and homemade questions on electronic and caffeine usage. Training quantity during, and before the pandemic (retrospectively) was also assessed. One-way ANOVAs were computed with chronotypes on 1) sleep duration and 2) social jetlag calculated from the PSQI, 3) PSQI total score, 4) ISI total score, 5) average number of time they use electronic during the hour before bedtime/week, and 6) average number of caffeinate product consume/day. A repeated measures ANOVA was also computed with the chronotypes on the training quantity before and during the pandemic.

Results

Results reveal significant differences between chronotypes in sleep duration (F[2,206]=20.12, p<.001), social jetlag (F[2,206]=6.77, p=.001), PSQI total score (F[2,206]=9.73, p<.001), and ISI total score (F[2,206]=11.19, p<.001). Post-hoc analyses show that in all cases, evening types had significantly more sleep disturbances than neutral types and morning types, while they were no differences between neutral and morning types. The same pattern was also found in usage of electronic devices less than an hour before bed (F[2,206]=10.04, p<.001), where evening types used electronic devices before bed significantly more than neutral types and morning types. No differences were found between neutral and morning types. No differences were found in caffeine usage (p=.06). Finally, results show that athletes of all chronotypes significantly reduced their amount of training hours during the pandemic (F[2,206]=123.47, p<.001).

Conclusion

This study raises important questions about challenges associated with sleep difficulties and evening chronotypes in young athletes. Given the very early onset of these difficulties, the implementation of prevention strategies and sleep hygiene awareness programs in young adolescents should be included and prioritized in national athlete development programs.

Support (if any)
0212 Associations Between Sleep EEG and Report Card Grades in Mathematics in Adolescents
Authors: Gruber Reut , Hubert Reto , Saha Sujata , scorah Julie , Chai Xiaoqian , Barbeau Rosalie , Wise Merrill
Published: April 2024

Introduction

Academic success plays an important role in improving future lifetime opportunities. Numerous factors have been identified as being relevant to academic achievement, but the role played by sleep in this process has been largely under studied. Accumulating evidence indicates that healthy sleep has beneficial effects on academic success, but the brain mechanisms underlying the interplay between sleep and academic outcomes in adolescents are poorly understood. Sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system. EEG signals during NREM and REM sleep have been validated to be excellent noninvasive correlates of adolescents’ brain maturation. However, previous studies examining the associations between sleep and academic achievement were based on primarily subjective measures of sleep or actigraphy. Thus, it is not known if or how these associations are related to adolescents’ brain activity during the night. The objective of this study was to examine the association between sleep EEG and report card marks in Mathematics in healthy adolescents.

Methods

Sample of 40 adolescents (26 girls, 18 boys) between the ages of 12 to 15 years (M= 13.9; SD = 0.95) participated in the study. Sleep EEG was recorded using a single night of ambulatory sleep EEG monitoring with frontal derivations during the school week in the child’s home. The Sleep Profiler was used to evaluate sleep EEG through the measurement of ambulatory EEG recorded from three frontal sensors placed at approximately F7, F8 and Fpz; Automated sleep/wake scoring was performed using the Sleep Profiler system followed by visual analysis by an experienced pediatric sleep specialist. Report card grades were used to assess adolescents’ academic achievement in Mathematics for the current semester.

Results

Multiple linear regression analyses revealed that longer duration of N3 sleep was significantly associated with higher marks in Mathematics, above and beyond the contributions of age, gender, socioeconomic status and PSG-measured sleep duration.

Conclusion

Our findings suggest that longer duration of N3 sleep recorded in the home environment in healthy adolescents is positively associated with better grades in Mathematics.

Support (if any)

The Azrieli Centre for Autism Research NSERC Discovery Grant RGPIN-2021-03363 Reut Gruber
0216 Behavioral State Recording & Sleep Deprivation in Mice to Explore the Underlying Mechanisms of Alzheimer’s Disease
Authors: Locklear Clarence , Wahlestedt Claes , Volmar Claude-Henry , Rogers April , Scott Sadeaqua , Gallop Erin-Leigh , Coppello Matthew , Carasco Mary , Chandler Alaina , Bernard Mark A , Moise Rhoda , Blanc Judite , Seixas Azizi , Jean-Louis Girardin
Published: April 2024

Introduction

Alzheimer's disease (AD), the most common form of dementia in the US, affecting 6.5 million individuals with a total healthcare cost of $321 billion, is characterized by cognitive dysfunction, memory problems, and disrupted sleep. Mice are crucial for studying AD and sleep patterns in humans, but current methods for inducing sleep disruption have limitations such as wired telemetry, real-time monitoring challenges, and disrupting the mouse's home environment. Better tools are needed to maximize the potential of mouse models in AD and sleep research. Objectives: This study aims to fill this gap by developing a novel system of sleep deprivation in mice to explore the underlying mechanisms connecting sleep and AD.

Methods

This study utilized a combination of DSI Co. wireless telemetry, Spike-2 software from CED Co., and third-party olfactory controllers to achieve automatic sleep deprivation via air-puffs. C57BL/6J (B6) mice were utilized for validation of the behavioral state recording/sleep deprivation system and preliminary biological analyses. The system was employed to achieve sleep deprivation in mice for 9 hours, then blood and brain tissue were collected for subsequent genetic analysis. qPCR was then applied to determine the expression of genes of interest related to AD, which was utilized in combination with analysis of variance to elucidate significance.

Results

Behavioral state recordings indicate the system can accurately collect and analyze telemetry signals in real time then initiate an air-puff, which successfully wakes the animal. qPCR results indicate a significant decrease in DNA damage repair enzyme and an increase in inflammatory cytokine gene expression, relative to controls, following ~9 hours of sleep deprivation (p< 0.05). These results collectively indicate the progression of an AD-phenotype.

Conclusion

These preliminary results indicate this novel system of behavioral state recording and sleep deprivation in mice can be applied to successfully explore the underlying mechanisms connecting sleep and AD. Future studies will extend to further proteomic and epigenetic analyses and explore specific sleep stages in relation to AD-progression.

Support (if any)

Center for Therapeutic Innovation (CTI)
0217 Among Older Adults, Sex Modulates the APOE Genotype Effects on Sleep and Sleep-Dependent Memory Consolidation
Authors: Barabadi Negin Sattari , Mander Bryce , Dave Abhishek , Lui Kitty K , Sprecher Kate E , Chappel-Farley Miranda G , Chen Ivy Y , Riedner Brady , Bendlin Barbara , Benca Ruth
Published: April 2024

Introduction

Alzheimer’s disease (AD) is a world-wide healthcare crisis among older adults. Sex, aging, and apolipoprotein E (APOE) genotype are among the most impactful risk factors for AD. Sleep is beneficial for memory and changes with age. We aimed to test whether sex and APOE (ε4-carriers/non-carriers) interact to impact sleep-dependent memory consolidation (SDMC).

Methods

We tested 67 older adults (41 women, 25 ε4-carriers, mean±SD; 61.8±6.1 years). Participants encoded word-pairs in the evening, were tested immediately, then underwent overnight in-lab polysomnography, and performed a delayed test in the morning. SDMC was computed as a difference score (morning-evening). Time spent in non-rapid eye movement (NREM) sleep stages, and electroencephalography (EEG) spectral power in frontal canonical frequency bands during NREM sleep, were quantified. ANOVA, independent t-tests, and bivariate correlation analyses were employed in the study.

Results

A sex×APOE interaction predicted SDMC (p=0.02). Post hoc analysis revealed no difference between male ε4-carriers and non-carriers (p=0.36), but among women, ε4-non-carriers exhibited increased deterioration (more forgetting) compared to ε4-carriers (p=0.02). Additionally, male ε4-carriers had worse memory retention than female ε4-carriers (p=0.01). Further analysis showed that female ε4-carriers spent more time in N3 sleep (p=0.01), correlating with better SDMC (r=0.72, p=0.02), while male ε4-carriers spent more time in N2 sleep (p=0.04), also linked to better SDMC (r=0.68, p=0.03). Regardless of sex, among ε4 non-carriers, no significant associations were found between theta, alpha, slow-sigma, fast-sigma during NREM sleep and memory (all ps>0.17). Among ε4-carriers, male participants showed no significant associations (all ps>0.54), whereas females exhibited positive associations between memory and theta (r=0.80, p=0.005), alpha (r=0.82, p=0.004), slow-sigma (r=0.85, p=0.002), and fast-sigma (r=0.77, p=0.009).

Conclusion

Our study reveals that the interplay of sex and APOE affects sleep patterns and memory consolidation in older adults. Notably, distinct NREM sleep stages impact SDMC differently in male and female APOE ε4-carriers. While enhanced sleep quality may mitigate APOE and sex-related cognitive decline in later life, considering sex-related differences in memory benefits from sleep is crucial for older adults at high risk for AD.

Support (if any)

R56AG052698, P50AG033514, F31AG048732, K01AG068353
0220 Circadian Rhythms and Resting State Functional Connectivity of the Hippocampus in Later Life Adults
Authors: Moon Chooza , Burgess Helen , Harmata Gail , Hopkins Lauren , Axelson Eric , Magnotta Vincent
Published: April 2024

Introduction

Functional decline in the hippocampus is a prominent neurodegenerative feature of Alzheimer’s Disease and related dementias. Alterations in circadian rhythms can exacerbate cognitive aging and neurodegeneration. This study examined how dim light melatonin onset (DLMO) is associated with resting state functional connectivity of the hippocampus and three cortical regions (i.e., prefrontal, temporal, and posterior cingulate).

Methods

We studied data from 52 later-life adults (mean age =70.0 SD= 6.3). T1-weighted anatomical images and resting-state Blood Oxygenation Level Dependent (BOLD) images from 3.0T MRI data were collected. DLMO information was also collected from participants and was used to determine circadian timing. We then assessed the relationship between circadian timing and resting state functional connectivity of the hippocampus to the three cortical regions. Multiple linear regression modeling with hippocampal connectivity as the dependent variable was used to analyze the data while controlling for age and sex.

Results

The findings of this study indicated that later DLMO time was associated with greater functional connectivity between the hippocampus and prefrontal cortex (b = 0.04, p = .016), and hippocampus and temporal (b = 0.05, p = .006) cortices. However, DLMO was not associated with the functional connectivity of the hippocampus and posterior cingulate cortex.

Conclusion

The findings suggest that later circadian timing (DLMO) is related to increased hippocampal connectivity to the prefrontal and temporal cortices in later-life adults. This indicates that earlier DLMO may be associated with a greater risk for hippocampal-related cognitive aging. Future studies using larger sample sizes, multimodal neuroimaging techniques, and longitudinal designs are needed to understand the relationships better.

Support (if any)

Part of this work was supported by the University of Iowa Institute for Clinical and Translational Science (NIH/ ACTS KL2TR002536, PI: Bassuk, Scholar: Moon), University of Iowa Center for Advancing Multimorbidity Science (NIH/NINR P20 NR018081, MPI: Gardner & Rakel, Pilot PI: Moon), Alzheimer’s Association (AARG-19-618403, PI: Moon). This work was conducted on an MRI instrument funded by 1S10OD025025-01. Contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH/ACTS, NIH/NINR, or Alzheimer’s Association.
0222 Greater Sleep Regularity Is Associated with Slower Pace of Epigenetic Aging
Authors: Wallace Danielle , Rotter Jerome , Rich Steven , Redline Susan , Sofer Tamar
Published: April 2024

Introduction

Sleep timing regularity is an important component of overall sleep health. People with more irregular sleep-wake schedules may more rapidly incur marks of biological aging, such as altered DNA methylation (DNAm). Here, we test whether sleep regularity index (SRI), a metric of the consistency of sleep-wake epochs, is associated with accelerated epigenetic aging in the Multi-Ethnic Study of Atherosclerosis (MESA).

Methods

SRI was calculated from scored sleep-wake epochs derived from actigraphy (wrist-worn ActiWatch Spectrum) collected over a week during the MESA Sleep Ancillary Study. Three epigenetic “clocks” representing markers of biological (Horvath DNAmAge 2018; developed by selecting DNAm sites associated with chronological age), phenotypic (Levine PhenoAge; developed by selecting DNAm sites associated with age-related biomarkers), and pace of aging (Belsky DunedinPACE; developed by selecting DNAm sites associated with individual trajectories of age-related biomarkers) were constructed from whole-blood DNAm data (EPIC Illumina Array) collected at MESA Exam 5, prior to actigraphy measurement. Associations between epigenetic age acceleration (outcome; the difference between chronological age and epigenetic age) and SRI (exposure, 10-unit increase) were evaluated with linear regression models adjusted for age, gender, study days between blood collection and actigraphy, self-reported race/ethnicity, study site, BMI, smoking status, depression score, and sleep duration.

Results

431 MESA participants with valid actigraphy and DNAm data were included (mean chronological age=68 years, DNAm age=66 years, PhenoAge=56 years, pace of aging=1.01). Spearman correlations between chronological age and epigenetic aging measures were highest for biological aging (DNAmAge rho=0.89, PhenoAge rho=0.76, DunedinPACE rho=0.18). Results did not support an association between SRI and accelerated biological aging (DNAmAge; β=0.09, 95%CI:-0.23, 0.41) or phenotypic aging after additional adjustment for smoking (PhenoAge; β=-0.48, 95%CI:-1.0, 0.04). However, greater SRI was associated with slower pace of aging in fully adjusted models (10-unit SRI increase on DunedinPACE; β=-0.09, 95%CI:-0.02, -0.0004) and directionality was similar between PhenoAge and DunedinPACE.

Conclusion

Greater sleep regularity is associated with slower pace of aging in a cross-sectional analysis of older U.S. adults. Further work will assess epigenetic aging with other measures of sleep health.

Support (if any)

NIH-NHLBI K99HL166700, R35HL135818, R01HL098433, R01HL161012, Career Development Award from the Sleep Research Society Foundation.
0229 Poor Habitual Sleep Quality Predicts Heightened Interoceptive Awareness Particularly with Older Age
Authors: Nishiyama Risako , Ravandi Dona , Lee Kyoungeun , Duarte Audrey
Published: April 2024

Introduction

Interoception is the sensation of the body’s internal states. Previous literature suggests that disordered sleep, including insomnia, in younger participants is associated with altered interoceptive awareness. However, the relationship between habitual sleep and interoception in healthy individuals observed across the adult lifespan, including old adults who tend to have poorer sleep quality, remains unclear.

Methods

Here, we aimed to disentangle the impact of poor habitual sleep and older age on interoceptive awareness. Seventy-two participants ranging across the adult lifespan (ages 18 to 78) were asked to perform subjective and objective measures of interoception. Specifically, they completed a self-report questionnaire regarding subjective interoceptive beliefs and performed an objective tapping task in which they tapped in resonance with their perceived heartbeats. Finally, we varied demands on autonomic arousal by asking participants to rate the intensity of sensation in their heart in response to viewing emotionally arousing images. Their habitual sleep patterns were measured using actigraphy for 7 days.

Results

Higher levels of sleep discontinuity (i.e., WASO, fragmentation) predicted greater performance in the objective interoception heartbeat counting task (β=0.254, p=0.049) across age. Greater night-to-night variability in sleep time was associated with greater interoceptive awareness when autonomic arousal was manipulated in the emotional viewing task, particularly with increasing age (Age x Sleep Variability, β=0.279, p=0.023). Similarly, reduced sleep time predicted better interoceptive awareness in the same task, particularly with increasing age (Age x Sleep Time, β=-0.322, p=0.012). Higher levels of variability in sleep discontinuity, another indicator of poor sleep quality, predicted greater subjective interoceptive beliefs across ages (β=0.242, p=0.046).

Conclusion

The results support the idea that habitually poor sleep quality and increased sleep variability may contribute to better interoception, and that this relationship is strengthened with increasing age.

Support (if any)

This research was supported by NSF award # 2152492.
0230 Comparing Subjective and Objective Measures of Chronotypes and Their Associations with Age in Older Adults
Authors: Pan Yulu , Cho Gawon , Burzynski Chase , Polisetty Lakshmi , Doyle Margaret , Iannone Lynne , Knauert Melissa , Yaggi Henry , Gill Thomas , Miner Brienne
Published: April 2024

Introduction

While much is known about the development and variability of chronotype (CT) in young adults, little is known in older adults, whose circadian rhythms tend to advance with aging. We assessed the associations between subjective and objective non-invasive chronotype markers, and their associations with demographics in older adults.

Methods

In an observational study of 60 community-living adults aged ≥60 years with self-reported sleep complaints, participants completed a Morningness-Eveningness Questionnaire (reduced version; rMEQ) and seven days of actigraphy. We dichotomized rMEQ into morning (>17) and other-CT(≤17). Seven-day average sleep midpoint, the midpoint between sleep onset and sleep offset, was measured by actigraphy. Seven-day average peak time in activity during the day was calculated using cosinor analysis of activity counts from actigraphy. Two-sample T-tests and Chi-square tests compared demographic factors (age, gender, race, education) and objective chronotype markers (sleep midpoint, peak time) between dichotomized CT groups (Morning-CT vs Other-CT). Pearson correlation coefficients examined the associations between the continuous rMEQ score and objective chronotype markers, and their associations with age.

Results

The mean age was 74±6.4 years [range: 60-90], 65% were women and 33.3% were minority race. Morning-CT (54%) and Other-CT (46%) had significantly different sleep midpoints (2:43 AM vs 3:20 AM, p=0.01) and different peak times (2:00 PM vs 3:00 PM, p=0.006). No significant differences were found in demographics between Morning-CT and Other-CT. Higher rMEQ score was significantly associated with earlier sleep midpoint (r=-0.52, p< 0.001) and earlier peak time (r=-0.51, p< 0.001). Advanced age was associated with earlier sleep midpoint (r=-0.46, p=0.0003), earlier peak time(p=-0.46, p=0.0003), and higher rMEQ score (r=0.22, p=0.09).

Conclusion

Among community-living older adults with sleep disturbances, we observed moderate correlations between subjective and objective chronotype markers. The rMEQ score significantly differentiated people with distinct objective chronotype markers, demonstrating the potential validity of rMEQ as a feasible marker for chronotype. Future studies with larger sample sizes should validate our findings, and could investigate whether subjective or objective chronotype markers have stronger associations with adverse outcomes.

Support (if any)

NIA (K76AG0749505, R03AG073991, P30AG021342)
0234 Wearable-derived Temperature Measured During Sleep Allows Menstrual Cycle Study at Different Reproductive Stages
Authors: Gombert Marie , Alzueta Elisabet , Perez-Amparan Evelyn , Camacho Leticia , Fan Ruby , Kerr Erin , Tager Lucas , Arra Nicole , Kiss Orsolya , Yuksel Dilara , de Zambotti Massimiliano , Pena Andres Alejandro , Zhang Jing , Shuster Alessandra , Morehouse Allison , Simon Katharine C , Mednick Sara C , Baker Fiona
Published: April 2024

Introduction

Numerous physiological processes display menstrual cycle variations, including body temperature. The advances in quality and accessibility of wearables facilitate collecting time series of physiological data, including skin temperature during sleep. The cosinor method, frequently used in circadian rhythms biology, may be a useful tool to assess if a menstrual cycle is ovulatory, based on a biphasic temperature rhythm. It could also be used to derive metrics about the cycle, in turn allowing the investigation of rhythm characteristics of females at different reproductive stages.

Methods

Here, 67 females in the early reproductive (age: 25.5 ± 5.4 years (mean ± SD)) and 53 females in the late reproductive/menopausal transition (age: 47 ± 2.9 years) stages tracked sleep and temperature with an Oura ring 2 across a menstrual cycle. They also reported menses and used an ovulation kit that detects a rise in luteinizing hormone. A cosinor method was fitted to daily skin temperature points extracted during the sleep period, and the fit quality was compared with the ovulation kits results. The cycle metrics were extracted and compared between the two groups with Wilcoxon tests.

Results

With the cosinor method, a cycle was considered ovulatory when the fit had a r2 > .25, a method that agreed with the ovulation kit in 82% of cases. When the fit quality was r2 > .4, the model was considered sufficiently good to calculate derived metrics. There was no difference in the fit quality, acrophase relative to menses, or amplitude of the rhythm between the early and late reproductive/menopausal transition groups. However, the latter had a higher mesor compared with the early reproductive stage group (p = 0.03).

Conclusion

The cosinor method can be used to model not only circadian but also menstrual rhythms, allowing identification of ovulatory cycles, and derivation of metrics about menstrual cycle rhythms that can be used to track characteristics within and between individuals over time. The overall higher skin temperature rhythms found in the late reproductive/early menopausal transition group could reflect shifted temperature regulation and more heat dissipation during this stage.

Support (if any)

National Institutes of Health (NIH) grant RF1AG061355 (Baker/Mednick)