bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract

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

Abstract

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 &lt; 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 &lt; 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 &lt; 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

Abstract

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

Abstract

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

Abstract

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&lt;.001), social jetlag (F[2,206]=6.77, p=.001), PSQI total score (F[2,206]=9.73, p&lt;.001), and ISI total score (F[2,206]=11.19, p&lt;.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&lt;.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&lt;.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

Abstract

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

Abstract

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&lt; 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

Abstract

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&gt;0.17). Among ε4-carriers, male participants showed no significant associations (all ps&gt;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