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Methods Ten healthy adults (six females, aged 52±2 years (mean±SEM)) participated in a forced desynchrony protocol in dim light where all behaviours were evenly spread across the circadian cycle (figure 1A).3 After a normal night of sleep and baseline testing, participants underwent 10 recurring 5-hours 20-min of ‘behavioural cycles’ of 2-hours 40-min of sleep opportunities and 2-hours 40-min of standardised waking episodes.3 Approximately 1 hour after each sleep episode, participants performed mild intensity cycle ergometer exercise for 15 min at 50% predicted maximal heart rate (Karvonen’s formula4). If similar results prevail in athletes performing high-intensity exercise, this would lead to the intriguing possibility of optimising circadian phase of athletes (eg, with bright light) to the expected time of performance.6 Contributors SST had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. R01-HL125893 (SAS), F32-HL131308, National Space Biomedical Research Institute through NCC 9-58 and Medical Research Foundation of Oregon (SST), F32DK107146 (AWM), American Sleep Medicine Foundation (MPB), Ford Foundation (NPB) and Oregon Institute of Occupational Health Sciences and CTSA grant (UL1TR000128).

Introduction The use of cannabis as a sleep aid has increased despite inadequate evidence of its efficacy or associated risks. Delta-9-tetrahydrocannabinol (THC) is the primary psychoactive constituent of cannabis. Acute THC administration can induce CB1R mediated reductions in total peripheral resistance resulting in dose-dependent increases in heart rate and reductions in heart rate variability (HRV) in awake subjects. However, the influence of THC on vagal-cardiac modulation during sleep is unclear. Methods 7 individuals who use cannabis (>3x/week for 3 months; CUDIT-R = 8±1) and 8 cannabis-naïve participants (combined: age range 21-32 years; 9 female) were recruited to participate in this repeated measure, single blinded, placebo-controlled study. One hour before habitual sleep, participants received either a placebo pill or 10mg of THC. Polysomnography (PSG) and ECG were recorded over these 2 nights. HRV was assessed in both time and frequency domains in 2-min epochs of stable N2, N3 and REM sleep. Repeated measures ANOVA comparisons were made for PSG and HRV variables. [(*)=p< 0.05] Results There were no significant changes in total sleep duration or sleep architecture (N2%, N3%, & REM%) between the placebo and dosing night in either group. Compared to the placebo night, both individuals who use cannabis and cannabis naïve participants exhibited significant decreases in HRV variables throughout the night when dosed with THC. R-R interval decreased by 25±10* ms [mean±SE] (2%) in the naïve group and 62±11* ms (6%) in the cannabis group. RMSSD decreased by 15±3* ms (22%) in the naïve group and 11±3* ms (23%) in the cannabis group. PNN50 decreased by 9±3* % in the naïve group and 11±3* % in the cannabis group. In naïve participants high frequency spectral power decreased by 398±76* ms^2 (32%). Conclusion Our results suggest that THC ingestion before bedtime did not systematically affect sleep depth or duration, but did significantly reduce vagal-cardiac modulation in individuals who use cannabis as well as in cannabis naïve participants. Acute reductions in parasympathetic control of the heart may indicate increased cardiovascular stress during sleep when THC is ingested. Support (if any) AASM; K01HL151745; T32HL083808; OHSU OFDIR; R35 HL155681; Oregon Institute of Occupational Health Sciences

Introduction In the US cannabis is recreationally legal in 15 states and medically legal in 34 states. Preclinical studies suggest beneficial effects of cannabis on the cardiovascular system (e.g., vasorelaxation). Yet, acute cases of hospitalization after cannabis consumption indicate potential adverse cardiac effects. Vascular endothelial function is a marker of cardiovascular disease and is measured as a change in resting brachial artery diameter (flow-mediated dilation, FMD) during reactive hyperemia. Both resting diameter (positively) and FMD response (negatively) are associated with cardiovascular risk. Resting diameter likely depends on long-term structural changes, and FMD response mostly depends on nitric oxide. Reactive hyperemia is more complex and depends on numerous variables, including adenosine and prostaglandins. FMD is attenuated in the morning when the frequency of adverse cardiovascular events peaks. To begin to understand the effects of chronic cannabis use on the cardiovascular system, in this pilot study, we compared morning measurements of vascular endothelial function, blood pressure, and heart rate between chronic cannabis users and controls while controlling for prior nighttime sleep opportunities. Methods Participants, cannabis non-users (n=5) and users (n=4), 44% female, age 25.4 ± 3.6 years - no demographic differences between groups, kept a consistent 2-week sleep schedule at home followed by an 8h sleep opportunity at their habitual time in the laboratory. Upon-wakening, we measured resting blood pressure, heart rate, baseline diameter, hyperemic response, and FMD. Statistical differences between groups were calculated using a two-tailed t-test. Results Systolic and diastolic blood pressures (p=0.13 and 0.26 respectively), heart rate (p=0.97), and FMD response (p=0.99) did not differ between groups. However, chronic cannabis users had a significantly higher baseline brachial artery diameter (mean difference: 1.04 mm ± 0.26, p=0.005), and lower hyperemic response (mean difference: -7944 iu/s ± 2538, p=0.02) compared to non-users. Conclusion These preliminary findings suggest that chronic cannabis consumption may be associated with adverse structural and functional changes in the vasculature of otherwise healthy young adults. Based on these initial observations, cannabis may act on the cardiovascular system via non-nitric oxide mechanisms. However, it is necessary to increase our sample size to test the robustness of these findings. Support (if any) KL2TR002370, AASM

Introduction Adverse cardiovascular (CV) events occur most commonly at ~9 AM in the general population, but ~3 AM in people with obstructive sleep apnea (OSA). Standing up after a night of sleep generates changes in blood pressure (BP) and heart rate (HR) and autonomic activation. We tested whether the CV reactivity to standing is different in OSA versus healthy controls (HC) across all phases of the circadian cycle. Methods 21 HC (age: 52±7 [mean±SD] years) and 8 OSA (age: 48±7 years; AHI range 15-74.1) participants with similar body mass indices completed a 5-day forced desynchrony (FD) protocol with 10 identical recurring 5 h 20 min sleep/wake cycles in dim light. Twenty-five minutes after awakening and continued supine rest, participants stood up. Systolic BP, diastolic BP and HR were measured during supine rest and after one min of standing at all circadian phases. Salivary melatonin was used as a circadian phase marker. Data were analyzed using mixed-model cosinor analyses. Results While supine, mean HR was higher in OSA but there were no mean differences in BP between groups, and no group by circadian phase interactions for BP or HR. Similarly, there were no significant mean group differences upon standing in the changes in BP or HR (first minute CV reactivity; p>0.05). However, upon standing, the circadian time of the peak increase in diastolic BP was significantly different in OSA versus HC (peaks at circadian phases corresponding to ~11PM and ~1PM respectively, p=0.008). And there was a trend for systolic BP reactivity to be different in OSA versus HC (peaks at ~6AM and ~4PM respectively, p=0.059). There was no evidence of a group by phase interaction for HR reactivity to standing. Conclusion In this preliminary analysis, the peak circadian phase of diastolic BP reactivity to change in posture differs between OSA and HC. These results may have implications for differences in time of adverse CV events in OSA and the general population. Support (If Any) NIH R01-HL125893; CTSA UL1TR000128

Introduction Hunger in young, lean individuals is modulated by a circadian rhythm which is lowest near 8AM and peaks around 8PM. Further, later circadian timing of food intake is independently associated with increased body fat. It is unknown, however, whether the circadian rhythm in hunger in non-lean (BMI>25 kg/m2) individuals is delayed or disproportionately higher at a particular circadian phase as compared to lean (BMI≤25 kg/m2) individuals, potentially providing a mechanism for increased food intake at later circadian times. We therefore investigated subjective hunger in lean and non-lean individuals under tightly controlled laboratory conditions. Methods After 1-3 weeks of an 8h regular and habitual sleep schedule at home, 22 healthy participants (aged 52±7 years [mean±SD]; 11 female) underwent a 5-day in-laboratory circadian protocol free of time cues and in dim-lighting. The protocol consisted of ten recurring 5 h 20 min cycles in which all scheduled behaviors—including meals—were identical and evenly distributed across the circadian cycle. Meals were designed via Harris-Benedict equation to meet each participant’s caloric needs. Lean (n=7; BMI: 23.1±2 kg/m2; age: 52±9 years) and non-lean (n=15; BMI: 30.6±5.4 kg/m2; age: 52±7 years) participants were identified. Hunger was measured regularly via visual analog scale and circadian phase was calculated relative to salivary dim-light melatonin onset (>3 pg/mL threshold). Data were analyzed using mixed-effect models and significance was set at p<0.05. Results On average, subjective hunger scores followed a significant circadian pattern (p=0.003) independent of all scheduled behaviors; hunger trough/peak for this cohort was ~4AM/~9PM. The respective rhythms between lean and non-lean groups were not significantly different (p=0.19); furthermore, the interaction of group by circadian phase was not significant (p=0.45). Conclusion The present findings suggest that increased evening intake in non-lean individuals is not due to a different rhythm in hunger. Future work should assess the contribution of other behavioral factors leading to the later circadian timing of intake in non-lean individuals. Support (If Any) Work reported in this poster was supported by the National Institutes of Health Common Fund and Office of Scientific Workforce Diversity (UL1GM118964, RL5GM118963, TL4GM118965).

Introduction The endocannabinoid anandamide (AEA) signals ubiquitously throughout the body and has been shown to modulate endocrine systems and sleep/wake cycles. Previous analyses suggest a diurnal variation in plasma levels of AEA. We sought to determine the endogenous circadian profile of AEA and how this distribution may vary by body mass index (BMI) and sleep. Methods Thirteen healthy participants (mean age, 51 years; 9 females; 8 lean mean BMI, 24.5 kg/m2; 5 non-lean mean BMI, 36.7 kg/m2) underwent a laboratory protocol that balanced eucaloric meals and sleep opportunities evenly across the circadian cycle (achieved by scheduling 10 identical, recurrent 5 h 20 min ‘days’ in dim light thereby desynchronizing the circadian and behavioral cycles). Blood was sampled before sleep and upon awakening through a midline catheter. AEA was quantified by liquid chromatography-mass spectrometry. Salivary melatonin was used to assess circadian phase (phase marker = dim-light melatonin onset [DLMO]). Results Average plasma AEA was lower in lean compared to non-lean participants (means: 0.4 pmol/mL versus 0.8 pmol/mL, respectively; p=0.024). The endogenous rhythm of plasma AEA was driven by non-lean participants: peak to trough range 0.65-0.96 pmol/mL; peaking in the biological afternoon (~2:45pm, ~18 hours after DLMO; p=0.01) with no significant rhythm in lean participants. Finally, the circadian rhythm of AEA did not significantly differ when measured immediately before or after sleep. Conclusion The variation in AEA across 24 hours is modulated by the circadian system in non-lean individuals, whereas levels remain relatively constant in lean healthy adults. Future studies are needed to determine if the 1.5-fold increase of peak to trough in AEA in non-lean adults is related to an increase in hunger cues and caloric intake that may account for increased BMI. This initial analysis does not account for sleep efficiency, which may alter AEA levels across sleep. Support (If Any) Ford Foundation, R01 HL125893, NCC 9-58, F32HL131308, and UL1TR000128.