bluuebunny/crossref_metadata_2025_split huggingface dataset:
0010 Using Chronotype and Polygenic Risk Scores to Predict Age of Mood Symptom Onset in People with Bipolar Disorder
Authors: Miranda Alannah , Holloway Breanna , Perry William , Minassian Arpi , McCarthy Michael 
Published: April 2024

Abstract

Introduction
Sleep and circadian rhythm disturbances are hallmark features of people with bipolar disorder (BD). Genetic and preclinical models of BD suggest that disruption of the circadian clock may predispose individuals with BD towards disruption of sleep/wake cycles. Phase delays in sleep/wake cycles are common in BD, causing difficulty initiating morning behaviors. Many people with BD report regularly using cannabis to ameliorate sleep disturbances. Although cannabis has been shown to have sedative properties, cannabis use may also destabilize mood and worsen sleep, and circadian disruption may also increase the risk of problematic substance use. Therefore, it remains unclear how cannabis use impacts sleep and circadian rhythms in people with BD. Here, we determined whether chronotype (self-reported and polygenic scores) and cannabis use disorder (CUD) predicted BD mood symptom onset.

Methods
Participants with BD I (n=309) from the Pharmacogenomics of Bipolar Disorder study were studies. The Diagnostic Interview for Genetic Studies was used to confirm BD and CUD diagnoses. Polygenic scores (PGS) were calculated for chronotype and BD. Basic Language Morningness scale (BALM) was used to assess chronotype. Bivariate correlation analyses were performed between morningness, PGS, and BD symptoms. Multiple regression analyses were performed using gender, morningness, or PGS, and CUD as predictors, and BD symptoms as the dependent variables.

Results
Morningness was not significantly correlated with PGS for chronotype. Higher morningness was positively correlated with onset of manic symptoms (p&lt; 0.001) and mean number of mood episodes per year. Both CUD and BALM scores significantly predicted BD age of onset (p&lt; 0.05); greater morningness delayed age of onset and patients with CUD had an earlier age of onset.

Conclusion
Consistent with a role in destabilizing mood, CUD use is associated with earlier age of onset, while morningness appears protective, and associated with later age of onset. The study is limited by its cross-sectional and retrospective design. Future studies should continue to explore the interaction of CUD and chronotype in BD patients using cannabis for sleep.

Support (if any)
NIDA R01DA043535 and R01DA051295
0012 Morning Misery: Circadian Timing and Negative Affect in a Sample of Adolescents
Authors: Mirchandaney Riya , Buysse Daniel , Clark Duncan , Guo Kathryn , Siegle Greg , Hasler Brant 
Published: April 2024

Abstract

Introduction
Adolescents with later circadian timing evidence an increased risk for depression. Depressed individuals report higher negative affect (NA), especially in the morning, which may reflect altered circadian timing in NA. Untangling the circadian influences on mood is challenging due to inconsistent operationalizations of circadian timing. This study aims to analyze the associations between three metrics of circadian timing (circadian preference, chronotype, and circadian phase) and daily levels of NA among adolescents.

Methods
This study analyzed 8 days of ecological momentary assessment (EMA) data among 119 adolescents (54.6% female; mean age 17.3 years). Participants completed sleep diaries with a visual analog scale (VAS) measuring NA (0-100; calm-tense) each morning, and the Positive and Negative Affect Scale–Short Form (PANAS-SF) approximately every 3 waking hours. NA scores were averaged across mornings, evenings, and overall. Circadian preference was assessed by the Composite Scale of Morningness (CSM), chronotype by the Munich Chronotype Questionnaire (MCTQ), and circadian phase by salivary dim light melatonin onset (DLMO; 4pg/ml threshold). We conducted multiple regression analyses to examine circadian preference, chronotype, and circadian phase predicting morning (PANAS, VAS), evening, and overall NA (PANAS), controlling for age, sex, and socioeconomic status.

Results
Correlations between circadian metrics were low (rDLMO-MCTQ=.20; rDLMO-CSM=.39; rCSM-MCTQ=.27). Greater evening preference predicted higher morning NA (PANAS: p=.026, β=-.21; VAS: p&lt; 0.001, β=-.33) and evening NA (p=.032, β=-.20), but not overall NA (p=.106, β=-.15). These associations were not significant after isolating the Sleep Timing and Activity factor of the CSM. Later chronotype predicted higher NA on the morning VAS (VAS: p=.048, β=.18), but not on the PANAS (p=.756, β=-.03); chronotype did not predict evening NA (p=.259, β=-.11) or overall NA (p=.412, β=-.08). Circadian phase did not predict morning NA (PANAS: p=.841, β=-.02; VAS: p=.552, β=.05), evening NA (p=.625, β=.05), or overall NA (p=.391, β=.03).

Conclusion
These results highlight the importance of specificity when operationalizing circadian timing and NA, and add to the mixed literature concerning the role of circadian phase in negative mood modulation. Adolescents with later chronotype may be particularly vulnerable to negative mood in the morning. Important next steps involve modeling diurnal patterns of NA and positive affect.

Support (if any)
R01-AA025626 (Hasler)
0014 Time to Step Up: The Role of Circadian Misalignment on Adolescent Physical Activity Metrics
Authors: Crandall Gracie , Wright Isabella , Kay Daniel , Duraccio Kara 
Published: April 2024

Abstract

Introduction
Circadian misalignment, the discrepancy between internal circadian timing and sleep timing, impacts overall health and well-being. While past research emphasizes the connection between physical activity and sleep duration, we aim to examine differences in physical activity levels and abilities in adolescents experiencing experimentally manipulated circadian-aligned versus misaligned sleep conditions.

Methods
29 night-owl adolescents underwent both aligned (12:30am-9:30am) and misaligned sleep (9:30pm-6:30am) for five nights each, with order randomized. To determine adherence to study protocols, wrist accelerometers tracked sleep duration and timing and waist accelerometers measured physical activity. After each experimental period, participants completed the 6-minute walk test and a sit-to-stand test. Repeated measures t-tests were used to assess the impact of the circadian timing condition on minutes in sedentary behavior, minutes in moderate-to-vigorous physical activity (MVPA), 6-minute walk distance, and sit-to-stand repetitions.

Results
Participants in the aligned condition significantly outperformed the misaligned group in sit-to-stand repetitions (M=24.10, SD=8.978; M=19.72, SD=6.524, respectively; p=0.003, d=0.616). Additionally, 6-min walk results revealed a significant difference, with participants in the aligned condition walking significantly farther than the control group (M=0.2952, SD=0.13095; M=0.2331, SD=0.10674, respectively; p=0.011, d=0.503). There was no significant difference between aligned and misaligned conditions in MVPA or sedentary behavior.

Conclusion
Participants undergoing circadian alignment had significantly better performance in walking and sitting tasks compared to when they were misaligned; there was no impact of circadian timing on physical activity levels across the week. These results could have significant implications for how teen athletes train and compete. Specifically, aligning teen athlete’s school and sport training and competition schedules with their circadian rhythm might lead to better performance.

Support (if any)
0015 Feasibility of an At-Home Experimental Circadian Misalignment Induction for Adolescents
Authors: Beebe Dean , Fidler Andrea , Crowley Stephanie 
Published: April 2024

Abstract

Introduction
For many adolescents, the only practical way to lengthen sleep on school nights is an earlier bedtime. However, this can be misaligned with their circadian phase. The effects of circadian misalignment remain understudied. Here, we present preliminary findings from an ongoing experimental trial comparing sleep extension that is aligned vs. misaligned with adolescents’ circadian phase.

Methods
Healthy 14-18-year-olds in the bottom and top quartile of reported midsleep on non-school nights (“lark” vs “owl” chronotype) underwent a 3-week protocol with three multi-night periods at home: 8-hours/night of sleep opportunity aligned with their chronotype (Week1), 6.5-hours/night centered between chronotypes (Week2), and 9.5 hours/night randomly assigned to early bedtime or late risetime conditions (Week3). Linear mixed models compared Dim Light Melatonin Onset (DLMO, collected at the end of each week) and sleep midpoint and duration (via wrist actigraphy) across week, chronotype, and random assignment during Week3 (early vs late sleep extension). Alpha was set at .01.

Results
Of 68 adolescents randomized, 57 (84%) completed the protocol (Mean age=15.9, 53% female). At Week1, larks and owls markedly differed in midsleep (03:16 vs 05:38) and DLMO (21:18 vs 23:30), ps&lt;.001, with midsleep and DLMO correlating well (r=.76, p&lt;.001). By design, sleep duration markedly differed across weeks (7.7 vs 6.4 vs 8.5 hours; p&lt;.001) without any significant interactions involving chronotype or randomization. Sleep midpoint and DLMO each showed week-by-randomization interactions (ps&lt;.001) but no 3-way interactions. By design, late risetime significantly delayed midsleep in Week3 only (p&lt;.001). Week-by-week follow-up tests of the randomization effect on DLMO were non-significant. Sleep midpoint showed a week-by-chronotype interaction (p&lt;.001), with later midsleep for owls pre-randomization (ps&lt;.003), but not during Week3. Midsleep at Week3 and subsequent DLMO correlated well for adolescents who were randomized to a condition that aligned with their chronotype (r=.70, p&lt;.001), but not those randomized to a misaligned condition (r=.26, p&gt;.2).

Conclusion
It is feasible to experimentally induce sleep patterns that meet recommendations for healthy sleep duration but are aligned or misaligned with individual adolescents’ circadian phase. We will use this protocol to study the effect of circadian misalignment on health outcomes.

Support (if any)
US National Institutes of Health (R01HL147915)
0017 Circadian Phase Alignment and Sleep Duration in Overweight Adults: Associations with Cardiometabolic Risk Factors
Authors: Baron Kelly , Appelhans Bradley , Burgess Helen , Quinn Laurie , Carlson Steven , Allen Chelsea , Greene Tom 
Published: April 2024

Abstract

Introduction
Both short sleep duration and circadian rhythm misalignment are associated with increased cardiometabolic risk factors. Although experimental research has demonstrated the independent and interactive effects of these two exposures, few studies have examined the interaction between these two factors on outcomes among free-living participants. The goal of this study is to examine how sleep duration and circadian alignment predict cardiometabolic risk factors and extend prior research by examining the mechanisms of insulin resistance.

Methods
Participants included adults aged 18-60 y with BMI 25-35 kg/m2 who completed body measurements, at least 7 days of actigraphy and an in lab dim light melatonin onset assessment (DLMO). The main measure of circadian misalignment was the phase angle, or duration between DLMO and habitual sleep onset time in the past 7 days. Participants attended an outpatient visit to the clinical research unit to complete a frequently sampled intravenous glucose tolerance test (FSIVGTT) and data were analyzed using Bergman’s minimal model analysis. Multivariable linear regression models evaluated the effects of sleep duration both individually and their interaction in predicting cardiometabolic outcomes in models controlling for age, sex, race and ethnicity.

Results
Body measurement data were available for n= 92 participants and FSIVGTT were available for 87 participants (age: M= 36 SD=10 years, 47 female). Average sleep duration was 6.9 hours (SD=0.6) and average phase angle was 3.3 hours (SD=1.0). We found there was higher insulin sensitivity among those with shorter phase angle (Si, estimate= -2.58 CI= -4.63, -0.53 (mU/L)-1min-1, p=.02) and a trend among shorter sleep duration (estimate = -3.71, CI= -7.35, -0.07 (mU/L)-1min-1, p=.05). Phase angle and sleep duration were not associated with metabolic measures, BMI, body fat or hip/waist ratio.

Conclusion
Results demonstrate contrary to our hypotheses, shorter phase angle and sleep were associated with higher insulin sensitivity and unrelated to other cardiometabolic risk markers in our sample of overweight adults without diabetes.

Support (if any)
The research reported in this publication was supported in part by the National Heart Lung and Blood Institute under Award Number 1R01HL141706-01A1 and the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR002538
0018 Extroversion Predicts Higher Evening Caloric Intake
Authors: Kennedy Kathryn , Huskey Alisa , Grandner Michael , Killgore William 
Published: April 2024

Abstract

Introduction
Personality has been shown to predict health-related outcomes, including eating behavior. However, the findings on extroversion and caloric intake have been inconsistent. This study sought to examine whether trait extroversion predicted total caloric intake, as well as calories from specific macronutrients, at different times of day during a sleep deprivation protocol.

Methods
Participants (n=46; 23 women) conducted a baseline personality assessment before completing a 30-hour sleep deprivation protocol a week later. The laboratory visit began at 6pm, and participants departed the following day at 2pm. While in the lab, participants completed serial neurocognitive assessments and engaged in ad libitum feeding. Caloric intake was assessed in 6-hour bins from 6pm (start of laboratory protocol) until 12am, 12am-6am, and 6am-12pm. Multivariate regression models were used with extroversion as the primary predictor (assessed via NEO Personality Inventory scores) and primary outcomes including total caloric intake, calories from total carbohydrates, sugars, protein, total fat, saturated fat, and transfats. Models were adjusted for age, sex, BMI, and chronotype (assessed using the Morningness-Eveningness Questionnaire (MEQ)).

Results
The fitted regression model with extroversion as the primary predictor and food variables as outcomes was statistically significant for total carbohydrates (F(4,40) = 3.153; R2 = 0.164; p = 0.024) and total calories (F(4,40) = 3.179; R2 = 0.165; p = 0.023) consumed between 6pm and midnight, adjusted for age, sex, and BMI. Extroversion was positively associated with greater total carbohydrates (β (3.148) = p &lt; 0.0174) and greater total calories (β (22.088) = p &lt; 0.0057) consumed between 6pm and midnight. Chronotype did not predict food intake in models further adjusted for MEQ score.

Conclusion
Trait extroversion may be associated a greater propensity for hedonic eating behavior, thus leading to higher caloric intake. However, it may also be that in a laboratory setting where social interactions are limited, extroversion predicts the consumption of foods as a self-soothing strategy in the event of loneliness. Further investigation is needed to understand this association in real world settings.

Support (if any)
DARPA AWARD #: D12AP00241
0020 Heart Rate Variability Changes During Sleep in Postmenopausal Women
Authors: Pérez-Medina-Carballo Rafael , Kosmadopoulos Anastasi , Boudreau Philippe , Boivin Diane B 
Published: April 2024

Abstract

Introduction
Young women present a lower risk of cardiovascular disease (CVD) than age-matched men, but this risk steeply increases at menopause. Heart rate variability (HRV) has been proposed as a marker of cardiovascular health, which changes with circadian phase and menopause. We aim to understand the changes in the circadian variation of HRV that occurs in postmenopausal women.

Methods
Eight healthy PMW (54.8±3.4 years, one taking hormones) and 12 healthy young women (YW; 25.8±3.4 years) in their mid-follicular phase were enrolled. Participants were healthy sleepers. After a regular 8-h sleep schedule at home for ≥2 weeks, participants entered the laboratory. After a baseline nocturnal sleep period, they underwent a 48-h (PMW) or 72-h (YW) ultradian sleep-wake cycle procedure (USW) consisting of alternating 60-min wake and nap opportunities. Sleep was polysomnographically recorded. EKG recordings were used to calculate HRV parameters: heart rate (HR), SDNN, RMSSD, HF. Circadian parameters (mesor, amplitude, phase) were calculated by fitting a cosinor to HRV parameters during the first 24 naps of the USW. Linear mixed-effects models were used for between-group comparisons.

Results
During the hourly analysis of the baseline sleep period, PMW presented lower SDNN, RMSSD and HF compared to YW (p≤0.025), with no differences in HR. PMW also had lower SDNN, RMSSD, and HF throughout N2, N3, REM sleep, and wake epochs (p≤0.013). During the USW procedure, YW showed a significant circadian variation of HR during NREM sleep and wake, and HF during NREM sleep (p≤0.010), whereas these variations were not significant in PMW. Both groups presented a significant circadian variation of SDNN in NREM sleep and wake (p≤0.037), with no differences in amplitude or phase. PMW also presented a lower mesor of SDNN, RMSSD and HF (p≤0.024).

Conclusion
The lower HRV (SDNN) and parasympathetic activity (RMSSD and HF) during the sleep of PMW is consistent with the increased risk of developing CVD after menopause. Furthermore, the dampened circadian variation of HR and HF in PMW suggest a weakened circadian regulation of the cardiovascular system. This could be a mechanism involved in the increased CV risk after menopause, although this would require further investigation.

Support (if any)
Canadian Institutes of Health Research.
0023 Light- and Meal-induced Phase Resetting of Circadian Lipid Rhythms in Humans
Authors: Grant Leilah , Chung Joon , Garbazza Corrado , McKenzie Lauren , Nogueiras Montserrat Perez , Gotto Alexander , Hilaire Melissa St , Lockley Steven , Rahman Shadab 
Published: April 2024

Abstract

Introduction
We have characterized endogenous circadian rhythms in total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) and shown that they can be reset according to a Type I phase response curve (PRC) by a combined stimulus of light exposure and meals. The resulting PRCs are different in phase and amplitude than that describing melatonin rhythm resetting and therefore we hypothesized that lipid rhythms may be reset by meal timing rather than light. In the current study, we are constructing three PRCs that systematically examine the contribution of light and/or meal timing on the circadian resetting response of lipids.

Methods
To date, 15 young healthy adults (mean age±SD= 25.9±3.6 yrs, 7F) have been randomized to one of three stimulus conditions: Light + Meals (n=5): 6.5-h ~10,000 lux white light exposure with a 12-h meal window; Meals only (n=4): dim light (&lt; 3 lux) with a 12-h meal window; or Time-restricted Meals (n=6): dim light with a 6.5-h meal window. Individuals are randomized to one of 16 stimulus times distributed every 90-minutes (~22.5◦) across the 24-hour day. Cosinor analysis was used to assess 24-h rhythms in lipids measured during constant routines conducted before and after stimulus administration. Phase shifts were calculated as the difference between pre- and post-stimulus acrophase.

Results
Endogenous circadian rhythms were observed in 73%, 86% and 100% of participants for TC, HDL-C and TG, respectively, during the first CR. These percentages were similar for the second CR: 80% for TC and HDL-C and 93% for TG. Consistent with our previous work, TC and HDL-C peaked in the afternoon (~15:30), whereas TG peaked in the early morning (~03:30). TC, HDL-C and TG demonstrated both advance (up to 7.1 hours) and delay (up to 8.9 hours) phase shifts depending on the circadian time of stimulus administration that were broadly consistent with our published PRCs.

Conclusion
Once completed, these PRCs will differentiate the role of light versus meals in resetting lipid rhythms, and the impact of meal window duration. This work is essential for providing evidence-based advice to shift workers and others with circadian misalignment to reduce their risk of lipid rhythm desynchrony.

Support (if any)
R01HL159207
0028 Chronotype and Circadian Timing in Day and Chronic Night-shift Workers
Authors: McAuliffe Kathryn , Shafer Brooke , McHill Andrew 
Published: April 2024

Abstract

Introduction
In populations who live and work typical day-shift work hours, chronotype (i.e., morning lark or night owl) is tightly associated with dim-light melatonin onset (DLMO) timing, the gold standard marker of circadian phase. The association between these markers is less clear in populations chronically working fixed, overnight shift work schedules which may be vital for making population-based recommendations. We therefore examined the relationship between chronotype and DLMO in chronic, fixed overnight shift working nurses compared to fixed day-shift working nurses.

Methods
Sixteen volunteers (15 female; aged [average ± SD] 31.8±7.7yr) working either a fixed day (n=8) or nightshift schedule (n=8; 19:00-07:00 shift; duration of night-shift work 8.6 ± 7.2yr) participated in an ~8h evening in-laboratory stay in dim-lighting (&lt; 5 lux). Beginning at 17:00, saliva was collected every 30 minutes to calculate circadian phase via salivary DLMO (3pg/ml threshold). Chronotype was determined via daily sleep/wake diaries collected over 7-days and defined as mid-sleep time on free days corrected for sleep loss on participant-identified work days (MSFsc). Pearson Correlations were used to determine associations between DLMO and MSFsc within each work-schedule group and circadian timing between groups was compared using Independent T-Test. DLMO was not captured in two night-shift working participants, thus they were not included in DLMO analysis.

Results
The timing of MSFsc and DLMO were significantly correlated such that later mid-sleep timing was correlated with later DLMO timing in day-shift (r=0.77, p&lt; 0.025), but not night-shift (r=0.005, p=0.99) workers. Moreover, the average MSFsc (01:25± 0:45 vs 11:16±01:35; p&lt; 0.001) and DLMO timing (19:13±01:04 vs 21:12±01:01; p=0.005) of the day-shift nurses were significantly earlier than the night-shift nurses.

Conclusion
Working and living on a day-shift schedule results in an association between chronotype and circadian timing, while a stable night-shift schedule results in no discernable relationship between the measures, despite a later DLMO timing. Understanding the connection between these sleep and circadian measurements could have implications for interventions to improve sleep, health, and performance in shift-working populations.

Support (if any)
OHSU School of Nursing PhD Student Scholarship Award, T32HL083808, K01HL146992