Abstract
Objective
Patients with craniopharyngioma (CP) frequently suffer from morbid obesity. Endocannabinoids (ECs) are involved in weight gain and rewarding behavior but have not been investigated in this context.
Design
Cross-sectional single-center study.
Methods
Eighteen patients with CP and 16 age- and sex-matched controls were included. Differences in endocannabinoids (2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (AEA)) and endocannabinoid-like molecules (oleoyl ethanolamide (OEA), palmitoylethanolamide (PEA), and arachidonic acid (AA) were measured at baseline and following endurance exercise. We further explored ECs-dynamics in relation to markers of HPA-axis activity (ACTH, cortisol, copeptin) and hypothalamic damage.
Results
Under resting conditions, independent of differences in BMI, 2-AG levels were more than twice as high in CP patients compared to controls. In contrast, 2-AG and OEA level increased in response to exercise in controls but not in CP patients, while AEA levels decreased in controls. As expected, exercise increased ACTH and copeptin levels in controls only. In a mixed model analysis across time and group, HPA measures did not provide additional information for explaining differences in 2-AG levels. However, AEA levels were negatively influenced by ACTH and copeptin levels, while OEA levels were negatively predicted by copeptin levels only. There were no significant differences in endocannabinoids depending on hypothalamic involvement.
Conclusion
Patients with CP show signs of a dysregulated endocannabinoid system under resting conditions as well as following exercise in comparison to healthy controls. Increased 2-AG levels under resting conditions and the missing response to physical activity could contribute to the metabolic phenotype of CP patients.
Introduction
Craniopharyngiomas (CP) are epithelial tumors arising along the path of the craniopharyngeal duct. With an overall incidence of 1.3 cases per 1 000 000 person-years they are extremely rare (1). Despite their histologically benign character, they are associated with a high degree of morbidity due to their location and growth pattern, which commonly results in panhypopituitarism and hypothalamic dysfunction (2). Depending on the extension and the hypothalamic nuclei affected, sequela may include homeostatic imbalances such as disturbed thermoregulation, impaired circadian rhythm, and most commonly morbid obesity (2, 3). Despite growing understanding of hypothalamic functioning, the exact mechanisms for weight gain in these patients are incompletely understood (4), but there is a clear association with the extent of hypothalamic involvement (5). While hyperphagia does not seem to be the main culprit in these patients, autonomic dysfunction (6) resulting in reduced sympathetic activity (7) has been reported, potentially explaining a reduction in energy expenditure (8, 9). In addition, patients often complain about persistent fatigue (10) and show reduced physical activity (9, 11).
A potential mediator of hypothalamic obesity not yet investigated in this context is the endocannabinoid (EC) system, as it might explain reduced energy expenditure as well as reduced physical activity. ECs are abundantly expressed in the CNS, including the hypothalamus (12) as well as in various peripheral tissues (13), and it might play a crucial role in central and peripheral regulation of energy metabolism. They modulate, for example, food intake, energy expenditure, lipogenesis and glucose homeostasis (14),both via central and peripheral mechanisms (15, 16). Furthermore, ECs likely affect reward behavior (17, 18) and have been shown to increase during physical exercise (19, 20). The main ECs are 2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (anandamide; AEA). ECs are synthesized on demand and can either act in an autocrine or paracrine manner or be secreted into the bloodstream. There are two major endocannabinoid receptors. CB1 receptors are found predominantly in the central and peripheral nervous system, while CB2 receptors are expressed predominantly in the immune system (21). AEA is the main ligand for CB1 receptors, while 2-AG acts as a full agonist on both CB receptors (13). CB1 blockage in the forebrain as well as in sympathetic neurons increases energy expenditure by activating the peripheral sympathetic nervous system (22) and subsequently increasing noradrenaline excretion (23). While AEA and 2-AG have been associated with the development of metabolic syndrome and thus have been targets for pharmacological weight loss drugs such as the CB1 blocker rimonabant (24), other EC-related compounds such as oleoylethanolamide (OEA) (25) and N‐palmitoylethanolamide (PEA) have been associated with more favorable metabolic health outcomes (26). Due to their widely distributed expression, the exact source of circulating ECs is not completely understood; however, evidence demonstrates that systemic 2-AG and/or AEA levels are increased in people with obesity (27), and these elevated levels correlate specifically with visceral fat mass (28). Finally, ECs also show a close interaction with the activation of the hypothalamus–pituitary–adrenal (HPA) axis (29), with peripheral levels rising in response to a psychological stressor (30). Matching this, an exercise-induced rise of peripheral ECs has been shown to correlate with cortisol levels (20). Importantly, the interaction between ECs and the HPA axis seems to be bidirectional (31). While glucocorticoids can, for example, stimulate hypothalamic EC release (32), ECs, in turn, are involved in adrenal steroid synthesis (33). The integration of EC signaling is complex, and receptive brain regions include among others, the hypothalamus, prefrontal cortex, brain stem and amygdala (14).
In the present study, we hypothesized endocannabinoid function in CP patients to be dysregulated, since the hypothalamus is both a crucial source as well as signaling target for ECs. In detail, we hypothesized that independent of BMI, baseline ECs might be higher in CP patients than controls, and furthermore that CP patients show a blunted EC-response to a stimulus, specifically to physical activity, which is known to substantially increase EC release and might contribute to beneficial effects of exercise (18). Lastly, due to the known interaction of EC signaling with the HPA axis on the one hand and the high prevalence of pituitary insufficiency in CP patients, including the corticotropic axis on the other, we were interested if blunted EC-release during exercise would be explained by a reduced endogenous HPA-axis activity, as measured via ACTH and copeptin levels.
Methods
Study design and participants
Patients were recruited from the Neuroendocrine Outpatient Unit of the Max-Planck Institute of Psychiatry (MPIP) and the Endocrine Department of the Medical Clinic IV, Ludwig Maximilian Universität, Munich, Germany. In this study, 18 adult patients participated, and 16 adult controls were recruited by public advertising and were included only if they had not been using hormonal contraceptive medication in the 6 months before the study. For further clinical characteristics of CP patients, see Table 1. The study was approved by the local ethics committee and conducted in accordance with the 2013 Declaration of Helsinki. All participants gave their written informed consent.
General characteristics. Data are presented as mean ± s.d. or n (%).
| CP | Controls | P | |
|---|---|---|---|
| n | 18 | 16 | |
| Age (years) | 39.1 ± 10.6 | 34.9 ± 15.7 | 0.377* |
| BMI (kg/m²) | 28.8 ± 7.6 | 24.0 ± 6.5 | 0.036* |
| Years since diagnosis | 13.7 ± 9.4 | NA | NA |
| Age at diagnosis | 25.2 ± 11.9 | NA | NA |
| Sex | 0.716 | ||
| Women | 9 (50.0%) | 9 (56.3%) | |
| Men | 9 (50.0%) | 7 (43.8%) | |
| Smoking | 0.451 | ||
| Never | 14 (77.8%) | 13 (81.3 %) | |
| Current | 0 (0.0%) | 1 (6.3%) | |
| Former | 4 (22.2%) | 2 (12.5%) | |
| Alcohol consumption | 0.917 | ||
| Never | 3 (16.7%) | 2 (12.5%) | |
| Less than once a week | 9 (50.0%) | 9 (56.3%) | |
| 1–3 times a week | 6 (33.3%) | 5 (31.3%) | |
| Sports activity | 0.691 | ||
| Never | 4 (22.2%) | 3 (18.8%) | |
| Less than once a week | 4 (22.2%) | 1 (6.3%) | |
| 1–3 times a week | 3 (16.7%) | 3 (18.8%) | |
| 3–4 times a week | 6 (33.3%) | 7 (43.8%) | |
| More than 4 times a week | 1 (5.6%) | 2 (12.5%) | |
| Surgery | |||
| Transsphenoidal | 15 (83.3%) | NA | NA |
| Transcranial | 3 (16.7%) | NA | |
| Radiation | 3 (16.7%) | NA | NA |
| MRI grading | NA | NA | |
| Missing | 2 (11.1%) | ||
| 0 | 6 (33.3%) | ||
| 1 | 5 (27.7%) | ||
| 2 | 5 (27.7%) | ||
| Diabetes insipidus | 10 (55.6%) | NA | NA |
| Any pituitary insufficiency | 17 (94.4%) | NA | NA |
| Pituitary axes affected | NA | NA | |
| 0 | 1 (5.6%) | ||
| 1 | 1 (5.6%) | ||
| 2 | 1 (5.6%) | ||
| 3 | 2 (11.1%) | ||
| 4 | 13 (72.2%) | ||
| Complete anterior hypopituitarism | 13 (72.2%) | NA | NA |
| Corticotropic insufficiency | 14 (77.8%) | NA | NA |
| Thyrotropic insufficiency | 16 (88.9%) | NA | NA |
| Gonadotropic insufficiency | 15 (83.3%) | NA | NA |
| Substituted | 13 (72.2%) | NA | NA |
| Somatotropic insufficiency | 16 (88.9%) | NA | NA |
| Substituted | 11 (61.1%) | NA | NA |
T-test and X2-test: *log-transformed.
NA, not applicable.
Hormone and endocannabinoid measurements
Participants arrived at the outpatient unit of the MPIP at 8:30 h in fasting state (food > 12 h, water > 1 h). Patients suffering from hypopituitarism were asked to take their morning hydrocortisone and l-thyroxin dose approximately 1 h before arrival. Blood was drawn before and directly after exercise (see below). Blood samples were placed on ice, plasma was separated immediately, and aliquots were stored at −80°C until analysis. Endocannabinoids, endocannabinoid-like molecules oleoyl ethanolamide (OEA), palmitoylethanolamide (PEA) and arachidonic acid (AA) levels from 100-mL plasma samples were extracted and measured by liquid chromatography/multiple reaction monitoring (LC/MRM) according to the protocol previously described (34, 35). Cortisol was measured by RIA (DRG International, Inc., USA) with an intra-assay CV of 8.6% and an interassay CV of 10.8 and 8.7%, respectively. The lower detection limit for cortisol was 0.9 μg/L. ACTH was measured by RIA (MP Biomedicals, Solon, USA) with an intra-assay CV of 6.8% and an interassay CV of 10.7%, and the lower detection limit was 5.7 pg/mL. Copeptin was determined using a commercially available luminescence assay device (BRAHMS Kryptor, Berlin, Germany). Intra- and interassay CVs were below 8%, respectively (36).
Grading of hypothalamic lesions
MRI classification was based on patients’ most recent post-surgical MRI-data and classified by a board-certified radiologist blinded to the clinical data who assessed the degree of individual hypothalamic damage according to a previously applied grading system (37). Patients were assigned to one of the following three groups: grade 0 = no hypothalamic lesion, grade 1 = anterior hypothalamic lesions sparing mammillary bodies, or grade 2 = anterior and posterior hypothalamic lesion, including mammillary bodies.
Exercise paradigm
A detailed description of the exercise paradigm has been published elsewhere (32). Summarized in brief, participants exercised on a bicycle ergometer (Kettler Ergometer TXl, Germany). Lactate in capillary blood was measured repeatedly (Lactate Pro2, Arkray, Japan) to standardize for individual exertion. Briefly, participants exercised for > 7 min, and then stopped either (a) whenever lactate levels reached > 4 mmol/L (considered to be the anaerobic threshold) or (b) if lactate continuously remained < 4 mmol/L when participants either reached physical exhaustion or after overall 25 min of exercise.
Statistical analysis
Data were checked for normality using Q–Q plots. Non-normally distributed variables were log-transformed before further analysis. For clarity, untransformed values are reported. Comparisons of groups at baseline were conducted by t test (for continuous variables) and X2 tests (categorical variables). Group scores are presented as mean ± s.d. or as percent. For correlation analyses, Pearson correlation was used. To evaluate the effects of exercise on different outcome variables, group, time, and interaction effects were examined using linear mixed-effects model analysis with time and group effects as fixed, and subject effects as random and an unstructured covariance structure. To ascertain whether changes in ECs-outcome variables occurred independently of differences in BMI, BMI was added as a covariate. In addition, separate models were built. including ACTH, cortisol and copeptin, to explore potential effects of HPA-activity on EC levels across time and groups. Statistical analysis was performed with SPSS 24 ® for Windows (IBM Corporation), with P < 0.05 considered statistically significant.
Results
CP patients had a significantly higher BMI than controls (28.8 ± 7.6 kg/m² vs 24.0 kg/m² ± 6.5; P = 0.036), while there were, as intended, no significant differences in sex (P = 0.716) or age (P = 0.377). Patients and controls did also not differ regarding alcohol consumption (P = 0.917), smoking habits (P = 0.451) or regular physical activity (=0.691) (Table 1). Regarding the exercise paradigm, there was also no difference in maximal lactate value reached (P = 0.115), total exercise duration in minutes (P = 0.263) or the proportion of those having reached predefined (200 W minus age) submaximal wattage goals (P = 0.311) (Table 2).
Exercise measures. Data are presented as mean ± s.d. or as n (%).
| CP | Controls | P | |
|---|---|---|---|
| Submaximum exhaustion level reached | 0.331 | ||
| No | 5 (27.8%) | 7 (43.8%) | |
| Yes | 13 (72.2%) | 9 (56.3%) | |
| Max Lactate (mmol/L) | 4.3 ± 1.1 | 4.8 ± 0.7 | 0.115 |
| Duration of exercise (min) | 14.9 ± 3.7 | 13.4 ± 4.0 | 0.263 |
| Wattage reached (W) | 157.2 ± 34.1 | 156.1 ± 24.0 | 0.919 |
*Log transformed.
HPA-axis measures
ACTH levels were higher in controls than in patients (group: F(1, 34.5) = 9.246; P = 0.004) and rose significantly more (6.0% vs 27.8%) in response to exercise (group × time: F(1, 34.5) = 12.622; P = 0.001). A similar pattern was seen for copeptin levels which increased only 12.3% in patients but 75.9% in controls (group: F(1, 28) = 10.214; P = 0.003), time: F(1, 28) = 17.030; P < 0.001), group ×time interaction: F(1, 28) = 8.154; P = 0.008). Cortisol levels did not differ between patients and controls and were only affected by BMI, independent of group (F(1, 33.4; = 6.918; P = 0.013).
Endocannabinoids
At baseline, there was a significant positive correlation of BMI with all endocannabinoid measures (AA: R = 0.649, P = 0.004; AEA: R = 0.656, P = 0.003; PEA: R = 0.626, P = 0.005; OEA: R = 0.708, P = 0.001), except for 2-AG (R = 0.339, P = 0.169) in CP patients but not in controls (Fig. 1). When one patient with noticeably high 2-AG levels despite a relatively low BMI was excluded from analysis 2-AG correlated also significantly with BMI (R = 0.579; P = 0.015).
Correlation of EC measures with BMI in CP patients. At baseline, there was a significant positive correlation of BMI with all endocannabinoid measures (AA: R = 0.649; P = 0.004; AEA: R = 0.656; P = 0.003; PEA: R = 0.626; P = 0.005; OEA: R = 0.708; P = 0.001), except for 2-AG (R = 0.339; P = 0.169) in CP patients but not in controls (Fig. 1). When one patient with noticeably high 2-AG levels despite a relatively low BMI was excluded from analysis 2-AG correlated also significantly with BMI (R = 0.579; P = 0.015).
Citation: European Journal of Endocrinology 185, 2; 10.1530/EJE-21-0178
Correlation of EC measures with BMI in CP patients. At baseline, there was a significant positive correlation of BMI with all endocannabinoid measures (AA: R = 0.649; P = 0.004; AEA: R = 0.656; P = 0.003; PEA: R = 0.626; P = 0.005; OEA: R = 0.708; P = 0.001), except for 2-AG (R = 0.339; P = 0.169) in CP patients but not in controls (Fig. 1). When one patient with noticeably high 2-AG levels despite a relatively low BMI was excluded from analysis 2-AG correlated also significantly with BMI (R = 0.579; P = 0.015).
Citation: European Journal of Endocrinology 185, 2; 10.1530/EJE-21-0178
Correlation of EC measures with BMI in CP patients. At baseline, there was a significant positive correlation of BMI with all endocannabinoid measures (AA: R = 0.649; P = 0.004; AEA: R = 0.656; P = 0.003; PEA: R = 0.626; P = 0.005; OEA: R = 0.708; P = 0.001), except for 2-AG (R = 0.339; P = 0.169) in CP patients but not in controls (Fig. 1). When one patient with noticeably high 2-AG levels despite a relatively low BMI was excluded from analysis 2-AG correlated also significantly with BMI (R = 0.579; P = 0.015).
Citation: European Journal of Endocrinology 185, 2; 10.1530/EJE-21-0178
For AEA we found a trend for a time effect (F(1, 34) = 3.20; P = 0.082) and a significant time ×group interaction (F(1,34) = 13.46; P = 0.001), as AEA decreased in controls (−13.7%) but remained relatively stable in patients. Moreover, a significant effect of BMI (F(1, 34) = 11.55; P = 0.002) was found. 2-AG levels were higher in patients at baseline (1.7 ± 1.2 pmol/L vs 0.8 ± 0.2 pmol/L) but did only significantly rise in patients in response to exercise (+60.2%) (group: F(1, 34.6) = 10.55; P = 0.003; time: F(1, 34.6) = 10.55; P = 0.003; time ×group: F(1, 34) = 5.08; P = 0.031). There were significant effects of time (F(1, 34) = 14.66; P = 0.001) and BMI (F(1, 34) = 9.14; P = 0.005) for AA, without significant interactions, indicating a slight rise in both groups. There was a significant group × time interaction for PEA levels (F(1, 34) = 5.189; P = 0.029) which decreased in controls but not in patients. In addition, there was an effect for BMI (F(1, 34) = 5.41; P = 0.026). There was a trend for a group effect for OEA which tended to be lower at both timepoints in patients (F(1, 34.4) = 3.92; P = 0.056) and a significant group × time interaction (F(1, 34) = 6.74; P = 0.014) demonstrating increasing levels in patients (+13%) but decreasing levels in controls (−6.8%) (Table 3). There was no significant difference in baseline or stimulated ECs measures depending on the hypothalamic involvement as graded on MRI (data not shown). However, these groups were small reducing statistical power.
EC and HPA measures during exercise. Linear mixedeffects model, all models included BMI as a covariate.
| CP | Controls | Group | Time | Time × group | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Baseline | Post-exercise | % | Baseline | Post-exercise | % | F | P | F | P | F | P | |
| AEA (pmol/mL) | 0.46 ± 0.09 | 0.49 ± 0.10 | 5.16 | 0.51 ± 0.12 | 0.44 ± 0.12 | −13.70 | 1.23 | 0.276 | 3.20 | 0.082 | 13.46 | 0.001 |
| 2-AG (pmol/mL)* | 1.70 ± 1.23 | 1.78 ± 0.68 | 4.78 | 0.76 ± 0.23 | 1.22 ± 0.37 | 60.15 | 10.55 | 0.003 | 22.03 | <0.001 | 5.08 | 0.031 |
| AA (nmol/mL) | 1.51 ± 0.60 | 1.86 ± 0.57 | 23.05 | 1.62 ± 0.52 | 1.82 ± 0.44 | 12.76 | 1.70 | 0.201 | 14.66 | 0.001 | 0.96 | 0.334 |
| PEA (pmol/mL) | 3.89 ± 0.88 | 4.10 ± 0.80 | 5.52 | 4.14 ± 1.37 | 3.69 ± 0.90 | −10.89 | 0.25 | 0.619 | 0.65 | 0.424 | 5.19 | 0.029 |
| OEA (pmol/mL) | 1.50 ± 0.25 | 1.70 ± 0.28 | 13.01 | 1.94 ± 0.66 | 1.80 ± 0.50 | −6.97 | 3.912 | 0.056 | 0.20 | 0.655 | 6.74 | 0.014 |
| ACTH (pg/mL) | 43.83 ± 16.77 | 46.47 ± 19.14 | 6.03 | 51.03 ± 15.50 | 77.19 ± 27.79 | 51.27 | 9.25 | 0.004 | 18.94 | <0.001 | 12.62 | 0.001 |
| Cortisol (µg/L)* | 138.60 ± 83.31 | 157.73 ± 96.17 | 13.80 | 158.87 ± 39.73 | 138.15 ± 62.80 | −13.04 | 0.0 | 0.974 | 0.01 | 0.930 | 2.36 | 0.134 |
| Copeptin (pmol/L)* | 2.52 ± 0.96 | 2.82 ± 1.28 | 12.26 | 3.68 ± 2.12 | 6.47 ± 3.99 | 75.88 | 10.21 | 0.003 | 17.03 | <0.001 | 8.15 | 0.008 |
*Log-transformed.
Effect of HPA-axis measures on ECs
Independent of the effect of BMI, across time and group, AEA levels were influenced by ACTH levels (F(1,46.1) = 4.26; P = 0.045, t = −2.064) and copeptin levels (F(1,49,179) = 4.99; P = 0.030; t = −2.234), indicating that HPA-axis activation has negative effects on AEA release. In contrast, HPA measures did not provide additional information for explaining 2-AG and AA levels. There was a positive effect of cortisol levels on PEA levels (F(1,46.5) = 8.48; P = 0.005; t = 2.912). Independent of a group effect, OEA levels were negatively predicted by copeptin levels (F(1, 52.1) = 8.10; P = 0.006; t = −2.846) but not by ACTH or cortisol (Supplements).
Discussion
Patients with CP show differences in ECs compared to healthy controls both under resting conditions and after exercise. Although BMI has a well-established effect on ECs that was also evident in our study, it did not solely explain most of the observed differences. The most striking result of our study was that while 2-AG levels were significantly elevated at resting conditions in CP patients, they did not respond to exercise compared to controls. Other ECs and EC-like molecules were also showing signs of dysregulation in CP patients, however, to a smaller degree than 2-AG.
It has been shown before that there is an increase in AEA (19, 20, 38), 2-AG (19, 39), PEA (19) and also OEA levels (39) following different exercise regimes. These findings were however not consistent across all studies, potentially due to differences in duration and intensity that seem to affect ECs response (38). The relatively short bout of exercise in the present study may not have been sufficient to increase AEA levels as most previous studies used exercise regimes that lasted considerably longer (24, 25).
We initially hypothesized that the EC system in CP patients might be impaired as the hypothalamus is crucial as a source as well as a target for ECs (14). However, our study failed to show differences in EC depending on the estimated extend of hypothalamic damage.
Due to the complex interaction of ECs with metabolism, the correlation of BMI and fat mass with EC measures (28) is not necessarily causal. On the one hand, ECs are synthesized in adipose tissue (40), and correlation with fat mass is therefore obvious, but on the other hand, they also promote fat mass accumulation by decreasing energy expenditure and promoting lipogenesis (14). That the correlation of all ECs with BMI was restricted to CP patients and not observed in controls, may be due to differences in fat mass distribution that was not separately assessed in our study. It has been shown that, in particular, visceral fat mass correlates with EC measures (28). Nonetheless, differences in resting 2-AG levels as well as the following exercise were independent of BMI.
2-AG in general favors energy preservation. It has been shown to increase fat accumulation (41) and reduce energy expenditure in mice (34) and correlates negatively with energy expenditure in humans (35). Likewise blocking the 2-AG receptor CB1 in the forebrain and sympathetic neurons increases energy expenditure via elevating the peripheral sympathetic activity (22) and subsequently increasing noradrenaline excretion (23). The observed baseline increase of 2-AG in our patient group matches the previously reported decrease in energy expenditure and sympathetic activity (7) in CP patients (9, 11). Of course, other causes for this generally decreased energy expenditure in CP patients are possible. Previous research, for example, suggested damage of the PVN and its autonomous efferences as a potential mechanism (5). However, until now, studies have failed to find a clear association between autonomous imbalances and hypothalamic lesion in CP (36).
In addition, 2-AG mediates the consumption of palatable food (42), increases during fasting (43) and is associated with feelings of hunger (39). While most, but not all studies (44), could not confirm an increase in food intake in CP patients (9, 11), there is at least evidence for an increase in hunger perception (10).
Lastly, as a rise during exercise has been associated with the rewarding effect of exercise (18, 19), a blunted release of ECs during exercise might reduce motivation for physical activity in the long-term as it is often observed in CP (9, 11). In the present study, however, patients and controls did not differ in average weekly sports activity, keeping in mind that duration, intensity and time spent per session was not in detail documented.
Lower baseline OEA levels in CP patients may also reflect a negative impact on metabolic health, as OEA has been associated with beneficial health effects (26), for example, by enhancing lipolysis (25) and reducing appetite (45). OEA as well as PEA are expressed in subcutaneous adipose tissue (40) but are also derived from the intestines (46). While OEA levels increased in CP patients following exercise and may therefore potentially indicate health benefits of physical activity in these patients, they did not reach the baseline levels seen in controls.
As there is a well-established, though complex interaction between the HPA axis and ECs functioning (29) and due to the fact that an increase in ECs during exercise has been attributed to HPA-axis activation (20), we were interested if the expected high prevalence of secondary (tertiary) adrenal insufficiency in CP patients would affect ECs dynamics. As it was not justifiable to perform the strenuous exercise in CP patients without them taking their morning hydrocortisone (HC) dosage, measured cortisol levels in patients primarily reflect pharmacokinetics following HC-intake. We were, therefore, more interested in the effects of markers of endogenous HPA-axis activation, namely ACTH and copeptin as a marker of antidiuretic hormone (ADH) release that acts synergistically with CRH on promoting ACTH release from the pituitary. While ADH is also an important regulator of water balance, copeptin levels may serve as a surrogate marker for the activity of the hypothalamic level of the HPA axis (47, 48).
As expected, healthy controls responded to exercise with an increase in ACTH and copeptin that was absent in CP patients. The fact that cortisol levels as opposed to copeptin and ACTH levels in controls did not change following exercise might most likely be explained by a delayed cortisol response that was not detectable in our samples. As only four patients in the CP group were not suffering from adrenal insufficiency, subgroup analysis regarding ECs response during exercise was not useful. We, therefore, explored if surrogate measures of HPA-axis activity, in particular ACTH and copeptin, could explain differences in ECs.
With regard to AEA, there was a negative association with ACTH and copeptin, indicating that HPA-axis activation has actually negative effects on AEA release across groups. This is in contrast to the study by Heyman et al. that speculated on a positive effect of cortisol on AEA release during exercise (20). ECs are an important part of the negative feedback loop of the HPA axis (32). In particular, AEA serves as a kind of gatekeeper. A rise in CRH results in a decrease in central AEA levels (49, 50) by inducing its degradation in the amygdala (50) in order to disinhibit the HPA axis (14). Although we did not measure CRH directly due to its instability, the inverse relationship of AEA with copeptin and ACTH is in line with these findings. While stress also induces central 2-AG synthesis, these changes occur later than for AEA (51). We, however, have to keep in mind that, in particular, the source of peripheral ECs during exercise is not completely understood (18, 31) and peripheral and central EC levels do not necessarily correlate (52) and even inverse correlation of hypothalamic and peripheral EC levels has been described in rodents (16). Thus, the source of circulating ECs in response to exercise is still a puzzle as previous studies have also not been able to identify where they are mainly produced and released (22).
Lastly, we cannot exclude that differences in baseline EC levels between patients and controls may be due to differences in circadian rhythm that can be compromised in CP patients (53). It has in particular been shown that 2-AG levels follow a circadian rhythm with 2-AG concentrations peaking between 00:00 h and 15:00 h. that do not follow HPA-axis activation patterns (54). The difference between nadir and peak can be up to 300%. In line, sleep restriction increases 2-AG levels by 80% in the morning (39).
Limitations
Although our study is unique and was performed in a well-characterized patient cohort, there are several limitations that have to be kept in mind. First, our cohort was not large enough to control for potential confounding effects of further pituitary insufficiency. However, the majority of patients was on a stable substitution therapy (two women were not receiving sex hormone substitution due to postmenopausal age and five patients showed unsubstituted GH-deficiency). A further subgroup of patients with isolated pituitary insufficiency without hypothalamic involvement would also have helped to disentangle the effects of tertiary and secondary hormonal deficiencies as well as hypothalamic involvement. It would also be further interesting to investigate potential differences in EC dynamics between different subtypes of CP, namely papillary and adamantinomatous tumors. Pathological sub-classification was not available in all our patients and given the rather small sample size of our study it would be interesting to investigate this issue in more detail in a follow-up study, including more patients. Papillary and adamantinomatous CP are regarded as distinct histological entities and although we assume that potential differences in hypothalamic function and ECs would be due to differences in mass effects, it is also thinkable that differences in the tumoral microenvironment (55) may have an independent effect on EC released. Lastly, we did not collect data on body composition, in particular visceral and subcutaneous fat mass, that may have different effects on ECs independent of BMI.
Conclusion
Patients with CP present with differences in ECs under resting conditions as well as following exercise in comparison to healthy controls. In particular, the increase in 2-AG under resting conditions and the missing response to physical activity could contribute to the metabolic phenotype of CP patients. While these disturbances were independent of BMI and measures of HPA-axis activity, we could further demonstrate that there is an inverse association between the stress response and peripheral AEA levels as postulated on the basis of rodent models.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding
This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.
Acknowledgements
The authors thank Madlen Lahne for her help in the recruitment of CP patients and all participants of this study.
References
- 1↑
Bunin GR, Surawicz TS, Witman PA, Preston-Martin S, Davis F, Bruner JM. The descriptive epidemiology of craniopharyngioma. Journal of Neurosurgery 1998 89 547–551. (https://doi.org/10.3171/jns.1998.89.4.0547).
- 2↑
Müller HL Craniopharyngioma. Endocrine Reviews 2014 35 513–543. (https://doi.org/10.1210/er.2013-1115)
- 3↑
Karavitaki N, Wass JA. Craniopharyngiomas. Endocrinology and Metabolism Clinics of North America 2008 37 173–1 93. (https://doi.org/10.1016/j.ecl.2007.10.012)
- 4↑
Lustig RH Hypothalamic obesity after craniopharyngioma: mechanisms, diagnosis, and treatment. Frontiers in Endocrinology 2011 2 60. (https://doi.org/10.3389/fendo.2011.00060)
- 5↑
Müller HL, Gebhardt U, Teske C, Faldum A, Zwiener I, Warmuth-Metz M, Pietsch T, Pohl F, Sörensen N & Calaminus G et al. Post-operative hypothalamic lesions and obesity in childhood craniopharyngioma: results of the multinational prospective trial KRANIOPHARYNGEOM 2000 after 3-year follow-up. European Journal of Endocrinology 2011 165 17–24. (https://doi.org/10.1530/EJE-11-0158)
- 6↑
Jung HW, Kim HY, Kim JY, Cheon JE, Kim IO, Kim SK, Shin CH, Yang SW, Lee YA. Autonomic dysfunction is associated with increased cardiometabolic risk in patients with childhood-onset craniopharyngioma. Hormone and Metabolic Research 2020 52 500–508. (https://doi.org/10.1055/a-1169-0307)
- 7↑
Roth CL, Hunneman DH, Gebhardt U, Stoffel-Wagner B, Reinehr T, Müller HL. Reduced sympathetic metabolites in urine of obese patients with craniopharyngioma. Pediatric Research 2007 61 496–501. (https://doi.org/10.1203/pdr.0b013e3180332cd6)
- 8↑
Holmer H, Pozarek G, Wirfält E, Popovic V, Ekman B, Björk J, Erfurth EM. Reduced energy expenditure and impaired feeding-related signals but not high energy intake reinforces hypothalamic obesity in adults with childhood onset craniopharyngioma. Journal of Clinical Endocrinology and Metabolism 2010 95 5395–5402. (https://doi.org/10.1210/jc.2010-0993)
- 9↑
Shaikh MG, Grundy RG, Kirk JMW. Reductions in basal metabolic rate and physical activity contribute to hypothalamic obesity. Journal of Clinical Endocrinology and Metabolism 2008 93 2588–2593. (https://doi.org/10.1210/jc.2007-2672)
- 10↑
Roemmler-Zehrer J, Geigenberger V, Störmann S, Ising M, Pfister H, Sievers C, Stalla GK, Schopohl J. Specific behaviour, mood and personality traits may contribute to obesity in patients with craniopharyngioma. Clinical Endocrinology 2015 82 106–114. (https://doi.org/10.1111/cen.12523)
- 11↑
Harz KJ, Müller HL, Waldeck E, Pudel V, Roth C. Obesity in patients with craniopharyngioma: assessment of food intake and movement counts indicating physical activity. Journal of Clinical Endocrinology and Metabolism 2003 88 5227–5231. (https://doi.org/10.1210/jc.2002-021797)
- 12↑
Kirkham TC, Williams CM, Fezza F, Marzo VD. Endocannabinoid levels in rat limbic forebrain and hypothalamus in relation to fasting, feeding and satiation: stimulation of eating by 2-arachidonoyl glycerol. British Journal of Pharmacology 2002 136 550–557. (https://doi.org/10.1038/sj.bjp.0704767)
- 13↑
Matias I, Di Marzo V. Endocannabinoids and the control of energy balance. Trends in Endocrinology and Metabolism 2007 18 27–37. (https://doi.org/10.1016/j.tem.2006.11.006)
- 14↑
Silvestri C, Di Marzo V. The endocannabinoid system in energy homeostasis and the etiopathology of metabolic disorders. Cell Metabolism 2013 17 475–490. (https://doi.org/10.1016/j.cmet.2013.03.001)
- 15↑
Bellocchio L, Soria-Gómez E, Quarta C, Metna-Laurent M, Cardinal P, Binder E, Cannich A, Delamarre A, Häring M & Martín-Fontecha M et al. Activation of the sympathetic nervous system mediates hypophagic and anxiety-like effects of CB1 receptor blockade. PNAS 2013 110 4786–4791. (https://doi.org/10.1073/pnas.1218573110)
- 16↑
Miralpeix C, Fosch A, Casas J, Baena M, Herrero L, Serra D, Rodríguez-Rodríguez R, Casals N. Hypothalamic endocannabinoids inversely correlate with the development of diet-induced obesity in male and female mice. Journal of Lipid Research 2019 60 1260–1269. (https://doi.org/10.1194/jlr.M092742)
- 17↑
Fuss J, Bindila L, Wiedemann K, Auer MK, Briken P, Biedermann SV. Masturbation to orgasm stimulates the release of the endocannabinoid 2-arachidonoylglycerol in humans. Journal of Sexual Medicine 2017 14 1372–1379. (https://doi.org/10.1016/j.jsxm.2017.09.016)
- 18↑
Fuss J, Steinle J, Bindila L, Auer MK, Kirchherr H, Lutz B, Gass P. A runner's high depends on cannabinoid receptors in mice. PNAS 2015 112 13105–13108. (https://doi.org/10.1073/pnas.1514996112)
- 19↑
Siebers M, Biedermann SV, Bindila L, Lutz B, Fuss J. Exercise-induced euphoria and anxiolysis do not depend on endogenous opioids in humans. Psychoneuroendocrinology 2021 126 105173. (https://doi.org/10.1016/j.psyneuen.2021.105173)
- 20↑
Heyman E, Gamelin FX, Goekint M, Piscitelli F, Roelands B, Leclair E, Di Marzo V, Meeusen R. Intense exercise increases circulating endocannabinoid and BDNF levels in humans—possible implications for reward and depression. Psychoneuroendocrinology 2012 37 844–851. (https://doi.org/10.1016/j.psyneuen.2011.09.017)
- 21↑
De Petrocellis L, Cascio MG, Di Marzo V. The endocannabinoid system: a general view and latest additions. British Journal of Pharmacology 2004 141 765–774. (https://doi.org/10.1038/sj.bjp.0705666)
- 22↑
Quarta C, Bellocchio L, Mancini G, Mazza R, Cervino C, Braulke LJ, Fekete C, Latorre R, Nanni C & Bucci M et al. Bucci M. CB1 signaling in forebrain and sympathetic neurons is a key determinant of endocannabinoid actions on energy balance. Cell Metabolism 2010 11 273–285. (https://doi.org/10.1016/j.cmet.2010.02.015)
- 23↑
Mølhøj S, Hansen HS, Schweiger M, Zimmermann R, Johansen T, Malmlöf K. Effect of the cannabinoid receptor-1 antagonist rimonabant on lipolysis in rats. European Journal of Pharmacology 2010 646 38–45. (https://doi.org/10.1016/j.ejphar.2010.08.006)
- 24↑
van Gaal LF, Rissanen AM, Scheen AJ, Ziegler O, Rössner S. Effects of the cannabinoid-1 receptor blocker rimonabant on weight reduction and cardiovascular risk factors in overweight patients: 1-year experience from the RIO-Europe study. Lancet 2005 365 1389–1397. (https://doi.org/10.1016/S0140-6736(0566374-X)
- 25↑
Guzmán M, Lo Verme J, Fu J, Oveisi F, Blázquez C, Piomelli D. Oleoylethanolamide stimulates lipolysis by activating the nuclear receptor peroxisome proliferator-activated receptor alpha (PPAR-alpha). Journal of Biological Chemistry 2004 279 27849–27854. (https://doi.org/10.1074/jbc.M404087200)
- 26↑
Fanelli F, Mezzullo M, Repaci A, Belluomo I, Ibarra Gasparini D, Di Dalmazi G, Mastroroberto M, Vicennati V, Gambineri A & Morselli-Labate AM et al. Profiling plasma N-Acylethanolamine levels and their ratios as a biomarker of obesity and dysmetabolism. Molecular Metabolism 2018 14 82–94. (https://doi.org/10.1016/j.molmet.2018.06.002)
- 27↑
Engeli S, Böhnke J, Feldpausch M, Gorzelniak K, Janke J, Bátkai S, Pacher P, Harvey-White J, Luft FC & Sharma AM et al. Activation of the peripheral endocannabinoid system in human obesity. Diabetes 2005 54 2838–2843. (https://doi.org/10.2337/diabetes.54.10.2838)
- 28↑
Cote M, Matias I, Lemieux I, Petrosino S, Almeras N, Despres JP, Di Marzo V. Circulating endocannabinoid levels, abdominal adiposity and related cardiometabolic risk factors in obese men. International Journal of Obesity 2007 31 692–699. (https://doi.org/10.1038/sj.ijo.0803539)
- 29↑
Patel S, Roelke CT, Rademacher DJ, Cullinan WE, Hillard CJ. Endocannabinoid signaling negatively modulates stress-induced activation of the hypothalamic-pituitary-adrenal axis. Endocrinology 2004 145 5431–5438. (https://doi.org/10.1210/en.2004-0638)
- 30↑
Hill MN, Miller GE, Carrier EJ, Gorzalka BB, Hillard CJ. Circulating endocannabinoids and N-acyl ethanolamines are differentially regulated in major depression and following exposure to social stress. Psychoneuroendocrinology 2009 34 1257–1262. (https://doi.org/10.1016/j.psyneuen.2009.03.013)
- 31↑
Hillard CJ Circulating endocannabinoids: From whence do they come and where are they going? Neuropsychopharmacology 2018 43 155–172. (https://doi.org/10.1038/npp.2017.130)
- 32↑
Gebert D, Auer MK, Stieg MR, Freitag MT, Lahne M, Fuss J, Schilbach K, Schopohl J, Stalla GK, Kopczak A. De-masking oxytocin-deficiency in craniopharyngioma and assessing its link with affective function. Psychoneuroendocrinology 2018 88 61–69. (https://doi.org/10.1016/j.psyneuen.2017.11.006)
- 33↑
Ziegler CG, Mohn C, Lamounier-Zepter V, Rettori V, Bornstein SR, Krug AW, Ehrhart-Bornstein M. Expression and function of endocannabinoid receptors in the human adrenal cortex. Hormone and Metabolic Research 2010 42 88–92. (https://doi.org/10.1055/s-0029-1241860)
- 34↑
Jung KM, Clapper JR, Fu J, D’Agostino G, Guijarro A, Thongkham D, Avanesian A, Astarita G, DiPatrizio NV & Frontini A et al. 2-arachidonoylglycerol signaling in forebrain regulates systemic energy metabolism. Cell Metabolism 2012 15 299–310. (https://doi.org/10.1016/j.cmet.2012.01.021)
- 35↑
Argueta DA, DiPatrizio NV. Peripheral endocannabinoid signaling controls hyperphagia in western diet-induced obesity. Physiology and Behavior 2017 171 32–39. (https://doi.org/10.1016/j.physbeh.2016.12.044)
- 36↑
Coutant R, Maurey H, Rouleau S, Mathieu E, Mercier P, Limal JM & Le Bouil A Defect in epinephrine production in children with craniopharyngioma: functional or organic origin? Journal of Clinical Endocrinology and Metabolism 2003 88 5969–5975. (https://doi.org/10.1210/jc.2003-030552)
- 37↑
Müller HL, Gebhardt U, Faldum A, Warmuth-Metz M, Pietsch T, Pohl F, Calaminus G, Sörensen N & Kraniopharyngeom 2000 Study Committee. Xanthogranuloma, Rathke’s cyst, and childhood craniopharyngioma: results of prospective multinational studies of children and adolescents with rare sellar malformations. Journal of Clinical Endocrinology and Metabolism 2012 97 3935–3943. (https://doi.org/10.1210/jc.2012-2069).
- 38↑
Raichlen DA, Foster AD, Seillier A, Giuffrida A, Gerdeman GL. Exercise-induced endocannabinoid signaling is modulated by intensity. European Journal of Applied Physiology 2013 113 869–875. (https://doi.org/10.1007/s00421-012-2495-5)
- 39↑
Cedernaes J, Fanelli F, Fazzini A, Pagotto U, Broman JE, Vogel H, Dickson SL, Schiöth HB, Benedict C. Sleep restriction alters plasma endocannabinoids concentrations before but not after exercise in humans. Psychoneuroendocrinology 2016 74 258–268.. (https://doi.org/10.1016/j.psyneuen.2016.09.014)
- 40↑
Gonthier MP, Hoareau L, Festy F, Matias I, Valenti M, Bès-Houtmann S, Rouch C, Robert-Da Silva C, Chesne S & Lefebvre d’Hellencourt C et al. Identification of endocannabinoids and related compounds in human fat cells. Obesity 2007 15 837–845. (https://doi.org/10.1038/oby.2007.581)
- 41↑
Simon V, Cota D. Mechanisms in endocrinology: endocannabinoids and metabolism: past, present and future. European Journal of Endocrinology 2017 176 R309–R324. (https://doi.org/10.1530/EJE-16-1044).
- 42↑
Yoshida R, Ohkuri T, Jyotaki M, Yasuo T, Horio N, Yasumatsu K, Sanematsu K, Shigemura N, Yamamoto T & Margolskee RF et al. Endocannabinoids selectively enhance sweet taste. PNAS 2010 107 935–939. (https://doi.org/10.1073/pnas.0912048107)
- 43↑
DiPatrizio NV, Igarashi M, Narayanaswami V, Murray C, Gancayco J, Russell A, Jung KM, Piomelli D. Fasting stimulates 2-AG biosynthesis in the small intestine: role of cholinergic pathways. American Journal of Physiology: Regulatory, Integrative and Comparative Physiology 2015 309 R805–R813. (https://doi.org/10.1152/ajpregu.00239.2015).
- 44↑
Roth C, Wilken B, Hanefeld F, Schröter W, Leonhardt U. Hyperphagia in children with craniopharyngioma is associated with hyperleptinaemia and a failure in the downregulation of appetite. European Journal of Endocrinology 1998 138 89–91. (https://doi.org/10.1530/eje.0.1380089)
- 45↑
Laleh P, Yaser K, Alireza O. Oleoylethanolamide: A novel pharmaceutical agent in the management of obesity-an updated review. Journal of Cellular Physiology 2019 234 7893–7902. (https://doi.org/10.1002/jcp.27913)
- 46↑
Fu J, Astarita G, Gaetani S, Kim J, Cravatt BF, Mackie K, Piomelli D. Food intake regulates oleoylethanolamide formation and degradation in the proximal small intestine. Journal of Biological Chemistry 2007 282 1518–1528. (https://doi.org/10.1074/jbc.M607809200)
- 47↑
Fuss J, Claro L, Ising M, Biedermann SV, Wiedemann K, Stalla GK, Briken P, Auer MK. Does sex hormone treatment reverse the sex-dependent stress regulation? A longitudinal study on hypothalamus-pituitary-adrenal (HPA) axis activity in transgender individuals. Psychoneuroendocrinology 2019 104 228–237. (https://doi.org/10.1016/j.psyneuen.2019.02.023)
- 48↑
Drummond JB, Soares BS, Pedrosa W, Vieira ELM, Teixeira AL, Christ-Crain M, Ribeiro-Oliveira A Jr. Copeptin response to hypoglycemic stress is linked to prolactin activation in children. Pituitary 2020 23 681–690. (https://doi.org/10.1007/s11102-020-01076-6)
- 49↑
Gray JM, Wilson CD, Lee TT, Pittman QJ, Deussing JM, Hillard CJ, McEwen BS, Schulkin J, Karatsoreos IN & Patel S et al. Sustained glucocorticoid exposure recruits cortico-limbic CRH signaling to modulate endocannabinoid function. Psychoneuroendocrinology 2016 66 151–158. (https://doi.org/10.1016/j.psyneuen.2016.01.004)
- 50↑
Hill MN, McLaughlin RJ, Morrish AC, Viau V, Floresco SB, Hillard CJ, Gorzalka BB. Suppression of amygdalar endocannabinoid signaling by stress contributes to activation of the hypothalamic–pituitary–adrenal axis. Neuropsychopharmacology 2009 34 2733–2745. (https://doi.org/10.1038/npp.2009.114)
- 51↑
Bassir Nia A, Bender R, Harpaz-Rotem I. Endocannabinoid system alterations in posttraumatic stress disorder: a review of developmental and accumulative effects of trauma. Chronic Stress 2019 3 2470547019864096. (https://doi.org/10.1177/2470547019864096)
- 52↑
Jumpertz R, Guijarro A, Pratley RE, Piomelli D, Krakoff J. Central and peripheral endocannabinoids and cognate acylethanolamides in humans: association with race, adiposity, and energy expenditure. Journal of Clinical Endocrinology and Metabolism 2011 96 787–791. (https://doi.org/10.1210/jc.2010-2028)
- 53↑
Pickering L, Jennum P, Gammeltoft S, Poulsgaard L, Feldt-Rasmussen U, Klose M. Sleep-wake and melatonin pattern in craniopharyngioma patients. European Journal of Endocrinology 2014 170 873–884. (https://doi.org/10.1530/EJE-13-1025)
- 54↑
Hanlon EC, Tasali E, Leproult R, Stuhr KL, Doncheck E, De Wit H, Hillard CJ, Van Cauter E. Circadian rhythm of circulating levels of the endocannabinoid 2-arachidonoylglycerol. Journal of Clinical Endocrinology and Metabolism 2015 100 220–226. (https://doi.org/10.1210/jc.2014-3455)
- 55↑
Martinez-Barbera JP, Andoniadou CL. Biological behaviour of craniopharyngiomas. Neuroendocrinology 2020 110 797–804. (https://doi.org/10.1159/000506904)
