Impact of circadian rhythmicity and sleep restriction on circulating endocannabinoid (eCB) N-arachidonoylethanolamine (anandamide)
Introduction
Humans have long been using Cannabis sativa with the noted effects of euphoria, decreased stress, increased hunger, and potential alterations in anxiety. The active component of cannabis, Δ9-tetra-hydrocannabinol (THC) was isolated in 1964 (Gaoni and Mechoulam, 1964) but the major components of the endogenous cannabinoid (eCB) system were not identified until the early 1990′s. It is now well established that the endocannabinoid system is comprised of the cannabinoid receptors (CBR), the endogenous ligands of these receptors, including 2 – arachidonoylglycerol (2-AG) and N – arachidonylethanolamine (AEA or anandamide), and the enzymes responsible for the biosynthesis and degradation of the eCBs (Devane et al., 1992; Gerard et al., 1991; Mechoulam et al., 1995; Munro et al., 1993; Sugiura et al., 1995). Components of the eCB system are located both centrally and peripherally and the ubiquity of the system lends itself to involvement in multiple aspects of human physiology (Mazier et al., 2015). A large body of literature has documented that the eCB system is not only involved in mediating feeding behavior, reward, stress and anxiety but also in glucose metabolism, pain, immune response, neurological disorders, and depression (Hillard, 2018; Iannotti et al., 2016; Turcotte et al., 2015). Endocannabinoids can be measured in blood from lipid extracts of plasma or serum, although the specific origin of peripheral concentrations of serum eCBs remains unclear (Hillard, 2018). Some data suggests that circulating eCBs are derived from the multiple tissues in which the enzymatic machinery to synthesize eCBs are located (Hillard, 2018). These tissues include, but are not limited to brain, gut, muscle, pancreas, and adipose tissue (Mazier et al., 2015). The eCB like compounds N-acyl ethanolamines (NAEs), oleoylethanolamide (OEA) and palmitoylethanolamide (PEA), are structurally similar to AEA but do not bind cannabinoid receptors. These lipids are produced by similar enzymatic machinery as for AEA and can also be measured in circulation (Hillard, 2018). They are frequently measured in conjunction with AEA as they may produce similar physiological effects as AEA, without binding eCB receptors (Lam et al., 2010). Whether these eCBs and NAEs are purposefully released into the circulation as a physiological signal with explicit function or are simply a marker of tissue endocannabinoid tone remains to be seen.
Much attention has been paid in recent years to the ability of the eCB system to control feeding, body weight, and peripheral metabolism in diet-induced or genetically obese animals (Chen and Pang, 2013; Fong et al., 2007; Jbilo et al., 2005; Poirier et al., 2005; Ravinet Trillou et al., 2003); thus this system has been the target of efforts to develop new anti-obesity drugs (Chen and Pang, 2013; Despres et al., 2005; Kipnes et al., 2010; Proietto et al., 2010; Scheen et al., 2006; Van Gaal et al., 2008). Most notably, rimonabant, a selective CB1 receptor blocker was approved in Europe as an appetite-suppressant in 2006 and was shown to have beneficial metabolic effects beyond those mediated by weight loss (Despres et al., 2005; Scheen et al., 2006; Van Gaal et al., 2005, 2008). The drug had to be withdrawn in 2008 due to serious psychiatric adverse effects (Sam et al., 2011). These notable side-effects have sidelined drug development, but the role of the eCB system in the regulation of energy balance, glucose and lipid metabolism, and food intake remains nonetheless a putative target of the pharmacological treatment of obesity. The eCB system is indeed involved in modulating not only homeostatic (energy balance) pathways but also hedonic and reward mechanisms that govern food intake (Coccurello and Maccarrone, 2018). The endocannabinoid system is also known to affect other reward-related behaviors as well as reinforcement, mood, anxiety, and cognition (Wenzel and Cheer, 2018). There is also evidence that the eCB system is involved in the inflammatory response; eCBs can alter macrophage migration, and macrophages along with T and B cells have the capacity to release eCBs (Cabral and Griffin-Thomas, 2009; Di Marzo et al., 1999; Sido et al., 2016). Moreover, reports suggest that the eCB system can mediate stress responses and, alternatively, can be altered by stress (Hillard, 2014), suggesting their role as regulators of endocrine response to stress (Hillard et al., 2016). Surprisingly, the vast literature on the functions of the eCB system and the efforts to target the eCB system in drug development have largely ignored the role of the circadian system and of sleep, both major modulators of mammalian metabolism, mood and behavior.
Indeed, only a limited number of reports have examined circadian fluctuations in the eCB system or regulation of circadian rhythms by the eCB system (reviewed in (Prospero-Garcia et al., 2016)). An early study by Perron and colleagues (Perron et al., 2001), revealed that discontinuation of treatment with an exogenous cannabinoid (THC), inverted the circadian rhythm of brain temperature suggesting a role for the eCB system in modulating brain temperature rhythm. More recent studies have shown diurnal variation in CB1 receptor and protein levels, as well as in the CBR ligands AEA and 2-AG, in rat brain (Martinez-Vargas et al., 2013, 2003; Rueda-Orozco et al., 2008; Valenti et al., 2004), and in rat liver (Bazwinsky-Wutschke et al., 2017). However, to date, only a few studies have examined the rhythm of circulating endocannabinoid levels in humans (Hanlon et al., 2015; Vaughn et al., 2010). Whether the impact of the circadian system and sleep may differ for the two major eCB ligands, AEA and 2-AG, has not been examined. Delineating the 24-h variation in the activity of the eCB system may help unravel the links between eCBs and disturbances of circadian and sleep regulation, and their behavioral and physiological implications.
We therefore examined the 24-h profile of serum AEA under normal sleep conditions and during sleep restriction. We contrast the findings with our previously published characterization of the 24-h profile of 2-AG (Hanlon et al., 2016).
Section snippets
Participants
Healthy men and women between the ages of 18–30 years, with a body mass index (BMI; in kg/m2) less than 27 for women, 28 for men were recruited for participation in this study. Individuals had self-reported habitual sleep duration of 7.5–8.5 h between the hours of 2300 and 0900. All participants had an overnight polysomnography in the laboratory to exclude sleep disorders, as well as a standard 75-g oral glucose tolerance test and fasting blood sample collection for routine laboratory analyses.
Demographics
Fourteen individuals, 3 women and 11 men, with a mean BMI of 23.9 ± 0.7 kg/m2 and mean age of 23.4 ± 0.8 years participated in this study. Eight of the 14 participants were tested under the Restricted Sleep (RS) condition first, and the remaining 6 participants began with Normal Sleep (NS). All demographic information and sleep characteristics have been reported in our previous publication (Hanlon et al., 2016).
24-h Profiles of AEA under normal sleep conditions
As expected, mean 24-h serum concentrations of AEA were approximately 100-fold lower
Discussion
The current study examined 24-h rhythms of serum concentrations of one of the most studied endogenous ligands of the cannabinoid receptors, AEA, also known as anandamide. As expected (Hillard et al., 2012), mean 24-h concentrations of AEA were significantly lower than those previously reported for 2-AG (Hanlon et al., 2016). Despite the vast difference in synthesis pathways and serum concentrations, 24-h mean values of AEA were highly correlated with values for 2-AG. Most interestingly, the
Contributors
ECH executed the clinical research protocol, analyzed all the data and wrote the manuscript.
Funding sources
This study was supported by Grant Number KL2RR025000from theNational Center for Research Resources, contractW81XWH-07-2-0071 from theDepartment of Defense Peer Reviewed Medical Research Program, and theUniversity of Chicago Institute for Translational Medicine supported byUL1 RR024999. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Center for Research Resources, the Department of Defense or the National Institutes of
Declaration of Competing Interest
The author reports no conflicts of interest.
Acknowledgements
The author would like to thank Kara L Stuhr, Elizabeth Doncheck, and Harry Whitmore for their assistance in data collection. Thanks are also due to her collaborators on the initial project and publications, including Rachel Leproult, PhD and Esra Tasali, MD, and Harriet de Wit, PhD. Special thanks to Cecilia J. Hillard, PhD and Eve Van Cauter, PhD for their critical review of the final draft of the manuscript.
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