bluuebunny/crossref_metadata_2025_split huggingface dataset:
0208 Sleep Irregularity Predicts Emotional Change After Sleep Restriction Among School-aged Children
Authors: Myers Annika , Kim Jinu , Rech Megan , Vieira Alyssa , Cifre Anthony , Rizvi Sarah , Alfano Candice 
Published: April 2024

Abstract

Introduction
Sleep irregularity has been associated with more negative emotional outcomes in adolescents and young adults. Although commonly used, standard deviation of sleep duration may be a less sensitive metric of sleep regularity in school-aged children given increased need for sleep and parental influence on sleep timing during childhood. We therefore examined another metric of sleep regularity, mean sum of successive differences (MSSD), in association with children’s responses to emotional stimuli when rested and after partial sleep restriction.

Methods
Healthy children (N = 50, 7-11 years, M age = 9.65; 56% female) wore actigraphs for one week from which MSSD of sleep time (TST) and midsleep point (MSP) was calculated. Both after a night of full sleep and after two night of sleep restriction (SR; 7 and 6 hours sleep), participants were asked to suppress their facial expressions in response to negatively valanced movies while respiratory sinus arrythmia (RSA), a measure of physiological emotional regulation, was monitored. Participants also rated difficulty of emotional suppression (ES). Hierarchical linear regressions were run with change in RSA during negative movies and difficulty of ES while rested and after SR as dependent variables, and regularity metrics as independent variables. Average TST and pubertal status were entered as covariates, as well as resting RSA and change in resting RSA after SR in relevant models.

Results
Sleep regularity did not predict emotional variables when children were rested. However, greater TST MSSD (β=0.26, p=0.02) predicted increased RSA during movies after SR, suggesting greater difficulty regulating emotional responses (overall model: F(4,28)=3.12, p=0.03, addition of TST MSSD: ΔR2 = 0.15, F(1,28)=6.21, p=0.02). Additionally, greater MSP MSSD (β=-0.9, p=0.0003) predicted less ES difficulty post SR, indicative of blunted affective expression (overall model: F(3,46)=6.22, p=0.001, addition of MSP MSSD: ΔR2=0.24, F(1,46)=15.27, p=0.0003).

Conclusion
Irregularity in TST may exert the greatest impacts on school-aged children’s physiological emotional responses when sleep duration is inadequate. Analyses also suggest a blunting effect of irregular sleep timing on emotional expression after inadequate sleep duration. Our findings warrant further exploration.

Support (if any)
Data collection was supported by grant #R21MH099351
0211 The Intersection of Sleep, Pain, and Executive Function in Girls Following the Menarcheal Transition
Authors: Khatoon Sofia , Adornetti Julianna , Hagy Hannah , Crowley Stephanie , Hellman Kevin , Tu Frank , Kmiecik Matthew 
Published: April 2024

Abstract

Introduction
Adolescence is marked by shifts in sleep, both in terms of timing and quality. Little is known about how these disruptions in sleep relate to pain and executive functioning (EF) following the onset of menstruation (e.g., menarche) in females. This study examines the relations between 1) sleep disturbances and pain, 2) sleep disturbances and EF, and 3) pain and EF in a sample of adolescents who experienced menarche in the past year.

Methods
A community sample of biological females (n = 159; M age = 12.8; SD age = 1.1; 74% white) and their caregivers were recruited from a Midwestern metropolitan area. Caregivers reported on demographics, sleep disturbance (PROMIS Sleep Disturbance Short Form), and EF problems (BRIEF scales: Inhibitory Control (IC), Emotion Control (EC), Shift (S), Working Memory (WM), and Task Switching (TS) subscales). Adolescents reported on somatic symptoms (Children’s Somatic Symptom Inventory: CSSI) and period pain (“Over the last three months, what was the average cramping pain you experienced with your period?”; rating scale 0 [no pain] to 10 [worst pain imaginable]).

Results
A series of linear regressions investigated the relation between sleep, pain, and EF. Participants with higher somatic symptoms, but not greater period pain, experienced more sleep disturbance (β =.098, p=.032). More sleep disturbance was associated with more EF problems including EC (β = .016, p&lt;.001), S (β =.169, p&lt;.001), WM (β = .136, p=.01), and TS (β = .169, p&lt;.001). There were no significant associations between either somatic symptoms or period pain and EF problems. Thus, adolescents who experienced more sleep disturbance exhibited higher levels of somatic symptoms and more difficulty with emotional regulation, cognitive flexibility, and memory.

Conclusion
Preliminary results indicate that sleep disturbance in the year following menarche is related to more somatic symptoms, but not more period pain. Further, sleep disturbance appears to be closely linked to EF problems. Data collection is ongoing, and actigraphy data on sleep (duration, quality) will be used to further investigate how sleep relates to pain and EF during this important developmental transition.

Support (if any)
0213 Latent Typologies of College Students’ Sleep-related Habits and Behaviors
Authors: Peltz Jack , Rogge Ronald 
Published: April 2024

Abstract

Introduction
With 43% of college students obtaining less than the recommended 7-9 hours of sleep per night and with over 75% reporting feeling tired/sleepy most days of the week (American College Health Association, 2023), this population is at significant risk for mental health, physical, and academic problems (Gaultney, 2010; Peltz & Rogge, 2016). Research has tended to focus on links between deficient sleep and negative outcomes via variable-center approaches (e.g., linear modeling), which may fail to capture individuals who exhibit multivariate sleep patterns (Yue et al., 2022). The present study used a latent profile analysis to identify subpopulations based on an extensive group of sleep-related habits and behaviors endorsed by a large sample of college students.

Methods
The current sample’s mean age (N=638, 82.4% female) was 21.3 years (SD=2.4; range 18-34), and 64.3% of participants were white, with 19.6% Asian/Pacific Islander, 6.9% Black, 6.7% Hispanic/Latinx, and 2.5% multi-racial or “other.” Approximately 60.5% of the sample lived on campus, and 56.8% maintained part- or full-time employment while attending school. The sleep-related habits and behaviors included in the latent profile analysis included the following scales: sleep disturbance, daytime impairment, environmental noise, sleep environment, sleep competency, sleep hygiene, work hours, problematic smartphone use, chronotype, and melatonin usage.

Results
Five sleep classes were identified including two more adaptive groups (great sleepers-23% & typical sleepers-35%), and three groups reporting greater sleep challenges (poor but conscientious sleepers-19%, poor sleepers-20%, & self-sabotaging sleepers-3%). The two adaptive groups reported fewer depressive/anxiety symptoms and higher GPAs, whereas the groups reporting disrupted sleep reported greater depressive/anxiety symptoms, life stress, and lower GPAs. The poor but conscientious sleepers were distinguished by better sleep environments and sleep hygiene (with slightly lower impairment), whereas the sabotaged sleepers were distinguished by poorer sleep hygiene, sleep environments, and greater problematic phone and alcohol use (with slightly greater impairment). Regressions predicting individual, interpersonal, and adaptive functioning highlighted that the typologies contributed unique predictive validity toward understanding college student functioning.

Conclusion
Our results highlight the diversity of sleep typologies present in college students. Students falling into poor/problematic sleep groups remain at risk for negative psychosocial and other health-related outcomes.

Support (if any)
0215 Optogenetic Rescue of Sleep Slows Alzheimer's Progression in a Mouse Model
Authors: Kastanenka Ksenia 
Published: April 2024

Abstract

Introduction
Alzheimer’s disease (AD) patients exhibit memory disruptions and sleep disturbances, such as disruption of deep non-rapid eye movement (NREM) sleep. Slow-wave activity (SWA) is a restorative feature of NREM sleep and is important for memory consolidation.

Methods
We made a mouse model where GABAergic interneurons could be targeted in the presence of APPswe/PS1dE9 (APP) amyloidosis, APP-GAD-Cre mice. An electroencephalography (EEG) / electromyography (EMG) telemetry system was used to monitor sleep disruptions in these animals. Optogenetic stimulation of GABAergic interneurons in the anterior cortex targeted with channelrhodopsin-2 (ChR2) allowed us to examine examining the role GABAergic interneurons play in sleep deficits. We also examined the effect of optogenetic stimulation on amyloid plaques, neuronal calcium as well as sleep-dependent memory consolidation. In addition, microglial morphological features and functions were assessed using confocal microscopy and flow cytometry. Finally, we performed sleep deprivation during optogenetic stimulation to investigate whether sleep restoration was necessary to slow AD progression.

Results
APP-GAD-Cre mice exhibited impairments in sleep architecture including decreased time spent in NREM sleep, decreased delta power, and increased sleep fragmentation compared to nontransgenic (NTG) NTG-GAD-Cre mice. Optogenetic stimulation of cortical GABAergic interneurons increased SWA and rescued sleep impairments in APP-GAD-Cre animals. Furthermore, it slowed AD progression by reducing amyloid deposition, normalizing neuronal calcium homeostasis, and improving memory function. These changes were accompanied by increased numbers and a morphological transformation of microglia, elevated phagocytic marker expression, and enhanced amyloid β (Aβ) phagocytic activity of microglia. Sleep was necessary for amelioration of pathophysiological phenotypes in APP-GAD-Cre mice.

Conclusion
In summary, our study shows that optogenetic targeting of GABAergic interneurons rescues sleep, which then ameliorates neuropathological as well as behavioral deficits by increasing clearance of Aβ by microglia in an AD mouse model.

Support (if any)
NIH, BrightFocus Foundation, Alzheimer's Association
0218 Sleep and Circadian Polygenic Risk Scores Predict Actigraphy-derived Traits and Cognition in Older Adults
Authors: Maués Cássia , Zayats Tetyana , Blankenship Anneka , Bock Karen , Watts Amber , Hunt Suzanne , Siengsukon Catherine , Veatch Olivia , Honea Robyn , Morris Jill , Santoro Marcos , Mazzotti Diego 
Published: April 2024

Abstract

Introduction
Sleep disturbances are prevalent in older adults and have been associated with major pathophysiological characteristics of Alzheimer’s disease. Genome-wide association studies (GWAS) of sleep and circadian traits identified hundreds of genetic loci influencing variability in these phenotypes. GWAS summary statistics can be used to derive polygenic risks scores (PRS), a quantitative measure of genetic risk for a particular phenotype. In this study, we assessed whether sleep and circadian PRS can predict actigraphy-derived measures and cognition scores among older adults followed at the University of Kansas Alzheimer’s Disease Research Center.

Methods
We collected 7-days of actigraphy and cognitive assessments of verbal memory, attention, and executive function among participants of European ancestry with genome-wide genotyping data. Linkage disequilibrium reference panels and GWAS summary statistics for insomnia, chronotype, and sleep duration were used to calculate PRS using a Bayesian regression approach with continuous shrinkage priors (PRS-CS). We used Spearman correlations and general linear models adjusted for age, sex, and education to test for associations of PRS with actigraphy-derived traits (sleep duration, sleep efficiency, wake after sleep onset [WASO], number of awakenings, and sleep midpoint) and cognitive factors.

Results
The final dataset consisted of 61 participants (mean [standard deviation (SD)] age 74.1 [6.5] years; 39.3% female; mean 16 [3] years of education). No associations were observed between early chronotype PRS and early sleep midpoint, nor sleep duration PRS and objective sleep duration. However, early chronotype PRS was negatively correlated with WASO (ρ=-0.32; p=0.012) and positively correlated sleep efficiency (ρ=0.30; p=0.018). Adjusted analyses suggest that a one SD increase in early chronotype PRS was associated with lower WASO (β[95%CI]=-15.0[-29.3;-0.76] minutes; p=0.043) and higher sleep efficiency (2.9[0.6;5.1] %; p=0.014). Furthermore, one SD increase in sleep duration PRS was associated with better performance on attention (2.9 [0.6;5.1] SD; p=0.009). No significant associations with insomnia PRS were observed.

Conclusion
This study identified novel associations between early chronotype and sleep duration PRS and relevant actigraphy-derived traits and attention in a clinical cohort of older adults. Results may inform the potential role of genetically informed sleep traits towards understanding their impact on cognition.

Support (if any)
NIA P30AG035982; General Faculty Research Fund (University of Kansas)
0219 Sleep Disturbances, Cortisol, and Neuroimaging Correlates Among Memory Clinic Patients
Authors: Sørensen Charlotte , Kåreholt Ingemar , Kalpouzos Grégoria , Udeh-Momoh Chinedu T , Holleman Jasper , Aspö Malin , Hagman Göran , Spulber Gabriela , Kivipelto Miia , Solomon Alina , Sindi Shireen 
Published: April 2024

Abstract

Introduction
Several sleep disturbance parameters as well as abnormal cortisol secretion levels are increasingly acknowledged as risk factors for Alzheimer’s disease (AD). Currently, the mechanisms between sleep disturbances and AD, and the interplay with abnormal cortisol levels, are still not understood. This study examines how self-reported sleep disturbances are associated with structural brain measures and diurnal cortisol dysregulation in a cohort of memory clinic patients.

Methods
The study was based on a cohort of 146 memory clinic patients diagnosed with either mild cognitive impairment or subjective cognitive impairment. The Karolinska Sleep Questionnaire (KSQ) was used to measure self-reported sleep. Neuroimaging (MRI or CT) was used to quantify structural brain measures using four visual rating scales (Scheltens, Pasquier, Koedam, and Fazekas scales). Salivary cortisol was sampled to measure diurnal cortisol patterns through five computed measures of awakening, bedtime, total, AM/PM cortisol ratio, and cortisol awakening response.

Results
Some associations were found between sleep, structural brain measures and cortisol. Increased apnea index (based on the KSQ) was associated with greater odds of posterior brain atrophy (OR=1.20, p=0.015) measured by the Koedam visual rating scale. Further, increased apnea index was associated with reduced awakening cortisol (β=-0.03; p=0.045, and an increased daytime sleepiness index (based on the KSQ) was associated with both reduced awakening cortisol (β=-0.03; p=0.025) and a reduced AM/PM cortisol ratio (β=-0.04; p=0.021).

Conclusion
In a memory clinic cohort, self-reported apnea disturbances are associated with a neuroimaging correlate of increased posterior atrophy and lower awakening cortisol, while daytime sleepiness index is associated with lower awakening cortisol and a reduced AM/PM cortisol ratio. These findings add insights into the early identification of modifiable AD risk factors an¬d their mechanisms.

Support (if any)
0221 Effect of Acutely Induced OSA During SWS on AD Plasma Biomarkers
Authors: Kam Korey , Mullins Anna , Parekh Ankit , Bubu Omonigho , Valencia Daphne , Berkalieva Asem , Ayappa Indu , Rapoport David , Osorio Ricardo , Varga Andrew 
Published: April 2024

Abstract

Introduction
OSA induces both sleep fragmentation and intermittent hypoxemia and has been associated with AD progression. We hypothesized that SWS-specific OSA can influence plasma AD biomarkers.

Methods
We developed a model of SWS-specific CPAP-withdrawal in subjects with AHI4% ≥ 20/hour to create 3 polysomnologically (PSG)-verified conditions per subject: 1) stable-SWS on CPAP, 2) SWS-fragmentation with intermittent hypoxemia (OSAsws), and 3) SWS-fragmentation with reduced hypoxemia (OSAsws+O2). We examined post-PSG morning plasma Aβ42 and Aβ40 by mass-spectrometry and plasma T-tau, P-tau181, NfL and GFAP by SIMOA in a study of 34 patients. Wilcoxon signed rank and Kruskal Wallace tests were used to compare SWS-specific OSA metrics and plasma measures across PSG conditions.

Results
In 34 patients (57 years, 32% female) CPAP withdrawal caused sleep disruption and recurrence of underlying OSA such that the OSAsws and OSAsws+O2 conditions caused significant increases in AHI4 and arousals during SWS [CPAP: 0 ±0, OSAsws: 16.1 ±15.7, OSAsws+O2: 16.2 ±12.0 in evts/hr, p&lt; 0.0001], and arousal index during SWS [CPAP: 0.9 ±2.0, OSAsws: 11.7 ±14.3, OSAsws+O2: 11.7 ±15.5 in evts/hr, p&lt; 0.0001] compared to CPAP treatment. Furthermore, the minimum SpO2 desaturation level of OSAsws was lower than OSAsws+O2 (OSAsws: 89.9 ±4.0, OSAsws+O2: 90.1 ±5.9 in % SpO2, p= 0.007). No change was observed between PSG conditions in Aβ42 (CPAP: 22.9 ±6.2, OSAsws: 21.3 ±6.2, OSAsws+O2: 21.2 ±6.8 in pg/mL), Aβ40 (CPAP: 232.3 ±39.9, OSAsws: 233.2 ±89.6, OSAsws+O2: 197.7 ±114.6), the ratio of Aβ42 to Aβ40 (CPAP: 0.10 ±0.01, OSAsws: 0.10 ±0.02, OSAsws+O2: 0.10 ±0.01), T-tau (CPAP: 3.1 ±0.3, OSAsws: 3.3 ±1.1, OSAsws+O2: 2.9 ±0.8 in pg/mL), P-tau181 (CPAP: 1.4 ±1.0, OSAsws: 1.5 ±0.5, OSAsws+O2: 1.6 ±0.9 in pg/mL), NfL (CPAP: 8.7 ±4.4, OSAsws: 6.0 ±3.0, OSAsws+O2: 7.8 ±6.0 in pg/mL), and GFAP (CPAP: 42.9 ±33.2, OSAsws: 30.9 ±25.6, OSAsws+O2: 39.5 ±36.9 in pg/mL).

Conclusion
Although we were able to recapitulate OSA in SWS, the degree of OSA severity was less than that on subjects’ diagnostic studies, and breathing was normal in N1, N2, and REM sleep, factors which possibly account for the lack of significant differences in biomarkers between conditions.

Support (if any)
R01AG056682, R01AG066870, RF1AG083975, R01AG080609, R01AG082278, K24HL109156, T32HL160511, K23AG068534, K25HL151912
0223 Temporal Correlations in Motor Activity Fluctuations and Risk of Parkinson’s Disease in Middle-to-older Aged Adults
Authors: Zheng Xi , Li Peng , Gao Lei , Hu Kun , Haghayegh Shahab 
Published: April 2024

Abstract

Introduction
Physiological outputs such as motor activity display complex fluctuations with a delicate pattern balanced between randomness and excessive regularity. Altered fractal patterns were observed in patients with Parkinson’s disease (PD). We examined whether perturbed motor activity fluctuation patterns are associated with the risk of developing PD in middle-to-older aged adults.

Methods
Actigraphy recordings (up to 7 days) were collected from more than 100,000 participants in the UK Biobank between 2013-2015. Participants were followed after actigraphy assessments for up to 7.5 years (median: 5 years). The detrended fluctuation analysis was performed to obtain a scaling exponent, α, that quantifies temporal correlations in activity fluctuations at timescales ~6-90 min: α close to 1 indicates the highest complexity or the balance between randomness and excessive regularity as observed in health young adults; deviations from 1 indicate reduced complexity — more randomness (close to 0.5) or excessive regularity or rigidity (close to 1.5) as occurred with aging or in diseases. We performed Cox proportional hazards models to examine the association of |α-1| with incident PD (ascertained by ICD-10 codes) during the follow-up while adjusting for age, sex, education, ethnicity, obesity, sleep apnea, alcohol intake, smoking status, morbidity burden, circulatory system disorder, and Townsend Deprivation Index (TDI).

Results
In total, 94,041 participants (56.4% females; age: 62.4±7.83 [SD], range 43.5-79.0 years) who had valid actigraphy or had no PD diagnosis at baseline were included. Among them, 290 participants (~0.3%) developed PD after 3.7±1.8 [SD] years from baseline. Older age (hazard ratio [HR] per 1 year increase=1.15, 95% CI: 1.12-1.17, p&lt; 0.0001) and being male (HR= 2.42, 95% CI: 1.88-3.13, p&lt; 0.0001) were associated with a higher risk of developing PD. The mean and SD of the squared root transformed |α-1| were 0.2±0.1. With a square root transform on |α-1| (to account for the right skewed distribution) and after controlling for co-variables, larger |α-1| was associated with increased risk of developing PD (for 1-SD increase, HR=1.15, 95% CI: 1.02-1.28, p=0.017; Q4 vs. Q1: HR=1.46, 95% CI: 1.05-2.04, p=0.025).

Conclusion
Perturbed balance between randomness and regularity in motor activity fluctuations was associated with higher PD risk.

Support (if any)
5T32HL007901-25, NIH RF1AG064312, BrightFocus A2020886S.
0225 Actigraphy-Assessed Daytime Napping Links to Mild Cognitive Impairment and Dementia in Middle-to-Older Aged Adults
Authors: Gao Chenlu , Haghayegh Shahab , Zheng Xi , Cai Ruixue , Rutter Martin K , Bennett David , Gao Lei , Hu Kun , Li Peng 
Published: April 2024

Abstract

Introduction
Prior studies of older adults have demonstrated that the development and progression of Alzheimer’s disease are tightly linked with longer daytime naps in a potentially bidirectional manner. It remains unclear whether daytime sleep behaviors in middle-to-older aged adults are linked to the risk for dementia.

Methods
We studied 85,037 cognitively intact non-shift-workers (baseline age=63 years, SD=8, range: 43-69; 57% female) in the UK Biobank cohort who completed 7-day actigraphy and had been followed for up to 8 years. We implemented the Cole-Kripke algorithm to identify daytime sleep episodes and considered three types of napping metrics: (1) mean nap duration between 9am-7pm; (2) intra-individual variability (individual SD) in the nap duration between 9am-7pm; (3) timing of napping quantified as the percentage of nap duration in each 2-h bin between 9am-7pm (9-11am, 11am-1pm, 1-3pm, 3-5pm, 5-7pm). Incidences of all-cause dementia and mild cognitive impairment (MCI) were identified via ICD-10 codes. Nap variables were square-root transformed to correct for skewness. We conducted Cox proportional hazards models, adjusting for demographic characteristics, lifestyle, comorbidities, polygenic genetic risk score for Alzheimer's disease, nighttime sleep, and chronotype.

Results
Almost all participants (99.97%) napped at least once. Median nap duration was 0.40 hours per day (IQR=0.20-0.78), and intra-individual variability of nap duration was 0.39 (IQR=0.19-0.69) hours. Twenty-eight percent (IQR=12%-52%) of the naps were taken between 9-11am, 5% (IQR=0%-17%) between 11am-1pm, 9% (IQR=0%-22%) between 1-3pm, 16% (IQR=1%-29%) between 3-5pm, and 17% (IQR=4%-32%) between 5-7pm. During follow-up, 557 (0.66%) participants developed MCI or dementia on average 4.62 (range: 0.01-7.98) years after baseline. Longer nap duration (for 1-SD, HR=1.21, 95%CI: 1.12-1.31, p&lt; 0.0001), larger intra-individual variability (for 1-SD, HR=1.14, 95%CI: 1.04-1.24, p=0.004), and higher percentage of naps between 1-3pm (for 1-SD, HR=1.11, 95%CI: 1.02-1.22, p=0.017) were associated with increased risk for MCI/dementia.

Conclusion
Longer and increased intra-individual variability in daytime nap as well as higher percentage of naps in the early afternoon are associated with a greater risk of MCI/dementia in middle-to-older aged adults. These findings highlight the potential importance of monitoring napping in screening for the risk for developing dementia.

Support (if any)
AASM (290-FP-22), Alzheimer’s Association (AARFD-22-928372), NIH 5T32HL007901-25, BRI Fund to Sustain Research Excellence.