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. Author manuscript; available in PMC: 2023 Sep 1.
Published in final edited form as: Addict Biol. 2022 Sep;27(5):e13197. doi: 10.1111/adb.13197

The Effects of Acute Alcohol Administration on Circulating Endocannabinoid Levels in Humans

Matthew E Sloan 1,2,3,4,5, Caroline W Grant 6, Bethany L Stangl 7, Timothy D Klepp 6, Honoree W Brewton 7, Resat Cinar 8, George Kunos 9, Vijay A Ramchandani 7
PMCID: PMC9413364  NIHMSID: NIHMS1815058  PMID: 36001429

Abstract

Several lines of evidence suggest that endocannabinoid signaling may influence alcohol consumption. Preclinical studies have found that pharmacological blockade of cannabinoid receptor 1 leads to reductions in alcohol intake. Furthermore, variations in endocannabinoid metabolism between individuals may be associated with the presence and severity of alcohol use disorder. However, little is known about the acute effects of alcohol on the endocannabinoid system in humans. In this study, we evaluated the effect of acute alcohol administration on circulating endocannabinoid levels by analyzing data from two highly-controlled alcohol administration experiments. In the first within-subjects experiment, 47 healthy participants were randomized to receive alcohol and placebo in a counterbalanced order. Alcohol was administered using an intravenous clamping procedure such that each participant attained a nearly identical breath alcohol concentration of 0.05%, maintained over 3 hours. In the second experiment, 23 healthy participants self-administered alcohol intravenously; participants had control over their exposure throughout the paradigm. In both experiments, circulating concentrations of two endocannabinoids, N-arachidonoylethanolamine (AEA) and 2-arachidonoylglycerol (2-AG), were measured at baseline and following alcohol exposure. During the intravenous clamping procedure, acute alcohol administration reduced circulating AEA but not 2-AG levels when compared to placebo. This finding was confirmed in the self-administration paradigm, where alcohol reduced AEA levels in an exposure-dependent manner. Future studies should seek to determine whether alcohol administration has similar effects on brain endocannabinoid signaling. An improved understanding of the bidirectional relationship between endocannabinoid signaling and alcohol intake may deepen our understanding of the etiology and repercussions of alcohol use disorder.

Keywords: Alcohol, Alcohol Self-Administration, Binge Drinking, Endocannabinoids

INTRODUCTION:

Despite increasing rates of alcohol use and misuse over the past decades1, no new pharmacological treatments for alcohol use disorder have been approved by the FDA in over 15 years. One potential novel target of interest is the endocannabinoid system2. Preclinical evidence suggests that blocking cannabinoid receptor 1 (CB1) decreases alcohol intake3–5. Altered endocannabinoid signaling may also affect human alcohol consumption. For example, individuals with a less functional variant of the gene for Fatty Acid Amide Hydrolase (FAAH), an enzyme that degrades the endocannabinoid transmitter anandamide, were more likely to be diagnosed with alcohol dependence6. Individuals with alcohol dependence who carried this polymorphism and were of European ancestry were also found to binge drink more often, have higher scores on the Alcohol Use Disorder Identification Test (AUDIT), and have more severe alcohol dependence based on symptom counts6. Despite these findings, blocking endocannabinoid signaling in humans has not been an effective treatment for alcohol use disorder (AUD) thus far. Treatment with the inverse CB1 agonist rimonabant failed to reduce relapse to alcohol use compared with placebo in a clinical trial7 or decrease alcohol self-administration in a human laboratory study8. Nevertheless, novel agents targeting the endocannabinoid system are being developed which may hold promise for the treatment of AUD2.

Endocannabinoid signaling seems to influence alcohol consumption and, conversely, alcohol consumption may also impact endocannabinoid signaling. An acute infusion of intravenous alcohol has been shown to increase CB1 receptor availability in healthy human participants9. By contrast, there is evidence from several studies that chronic alcohol intake may downregulate central CB1 receptors10. CB1 receptors are also present in the periphery and there are circulating endocannabinoids present within serum and plasma. The two major endocannabinoids that function as endogenous ligands of cannabinoid receptors are N-arachidonoylethanolamine (AEA, also known as anandamide) and 2-arachidonoylglycerol (2-AG). Both AEA and 2-AG are agonists of CB1, although 2-AG is a more efficacious agonist than AEA11,12. In the brain, AEA and 2-AG are synthesized on demand by the postsynaptic cell and function as retrograde neurotransmitters, binding to CB1 receptors in presynaptic terminals and suppressing neurotransmitter release13. AEA may additionally act in a paracrine fashion in the periphery, with preclinical evidence suggesting that macrophage-derived anandamide may lead to neighboring pancreatic beta cell death in a mouse model of type 2 diabetes mellitus14. However, the overall physiological roles of AEA and 2-AG in the periphery are still not well defined15. Understanding the impact of acute and chronic alcohol intake on both central and circulating endocannabinoids is of importance in order to fully elucidate the relationship between alcohol use and endocannabinoid signaling.

By using data from two well-controlled human laboratory studies, we sought to examine how acute alcohol administration influences circulating levels of two of the main endocannabinoid transmitters: AEA and 2-AG. In the first within-subjects study (the fixed-dose study), healthy participants were administered either placebo or intravenous alcohol clamped at a fixed breath alcohol concentration (BrAC) of 50mg%, equivalent to 5/8th of the current legal limit for driving (80 mg% or 0.08%). The target BrAC of 50mg% was chosen to represent a moderate exposure comparable to 2–3 drinks in most people. On each experimental day, circulating endocannabinoids were measured prior to and following an intravenous infusion of alcohol. In the second study (the alcohol self-administration study), a separate group of healthy participants completed an intravenous alcohol self-administration paradigm. Circulating endocannabinoid concentrations were measured both before and during the self-administration procedure. Based on the results of a prior study, which found reductions in AEA and 2-AG levels following oral alcohol consumption16, we hypothesized that both alcohol self-administration and fixed alcohol exposure using the alcohol clamp would decrease AEA and 2-AG concentrations in an exposure-related manner.

MATERIALS AND METHODS:

Experimental Paradigms

Two human laboratory studies were conducted at the National Institute on Alcohol Abuse and Alcoholism (NIAAA) in Bethesda, Maryland. All study procedures were approved by the NIH Intramural Institutional Review Board at the National Institutes of Health. Participants provided written informed consent prior to enrolling in each study.

The fixed-dose study utilized an intravenous alcohol clamp paradigm17 in which participants were infused with alcohol with the goal of attaining and maintaining a target BrAC of 50mg% over a period of 3 hours. The main goal of this study was to evaluate the influence of age and sex on alcohol elimination rates and responses in healthy men and women. Forty-eight participants were recruited for this study. Of these participants, forty-seven had both pre- and post-infusion blood samples (i.e. blood draws occurred just prior to the paradigm and after 180 minutes) (Figure 1). The alcohol self-administration study utilized an intravenous computer-assisted alcohol self-administration paradigm in which participants controlled their own exposure to alcohol, which was allowed to range from 0 to 100mg%18,19. The main goal of this study was to compare the effects of stress, alcohol-related, and neutral cues on alcohol self-administration. For the present analysis, we evaluated data from the neutral cues session to maintain consistency with the clamped infusion study (data from the other sessions will be published elsewhere). Thirty-three participants enrolled in the alcohol self-administration study. Of these, data from twenty-three were analyzed; data from eight participants were not analyzed due to study withdrawal prior to sample collection, and data from two participants could not be analyzed due to significant hemolysis of samples or damaged sample vials. Endocannabinoid concentrations were detectable in all participants with non-hemolyzed blood samples and were measured at baseline (approximately 20 minutes prior to the start of alcohol self-administration) and after 30 minutes of alcohol self-administration (see Table S1 for a comparison of the two studies).

Figure 1: Fixed-Dose and Self-Administration Study Timelines:

Figure 1:

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Top: Fixed-dose study. Bottom: Self-administration study. In both studies, participants received a light meal. The duration of IV ethanol infusion was 180 minutes for the fixed-dose study. Baseline blood samples were collected earlier in the day for the fixed-dose study (approximately 9:30 AM; infusion started at approximately 10:00 AM) compared with the self-administration study (approximately 11:45 AM; self-administration session started at approximately 12:05 PM). Post-exposure blood samples were collected at approximately 1:00 PM (fixed-dose) and 12:35 PM (self-administration). Estimated breath alcohol concentrations (BrAC) of participants for each study are shown.

Study Population

Both the fixed-dose and the self-administration studies recruited healthy participants, as determined by medical history, physical exam, electrocardiogram, and routine blood tests. The studies shared the following inclusion and exclusion criteria: participants were current non-smokers (although past smokers who had quit for over one year were eligible); participants with a current or prior history of serious medical illness including cardiovascular, respiratory, gastrointestinal, hepatic, renal, endocrine, or reproductive disorders were excluded; individuals with a positive hepatitis or HIV test at screening were also excluded; participants were evaluated using the Structured Clinical Interview for DSM-IV (SCID-IV)20 and were excluded if they had any current Axis-I psychiatric disorder or a past history of drug or alcohol dependence; participants were excluded if they were using prescription or over the counter medications that are known to interact with alcohol within two weeks of the study or if they had a positive result on a urine drug screen or alcohol breathalyzer at the start of any study visit; females were excluded if they were currently pregnant (positive urine beta-hCG test) or intended to become pregnant; and participants who were alcohol naïve or alcohol abstainers were excluded.

The alcohol clamp study enrolled social drinkers stratified by age and sex. By design, half of the participants were young females and males between 21 and 25 years of age and the other half were older females and males between 55 and 65 years of age (Table 1). Participants with alcohol use exceeding 14 drinks per week for males and 7 drinks per week for females or use of more than four drinks on any one occasion in the 6 months prior to the study were excluded. Participants needed to be family history negative for alcoholism (i.e. no family history of alcoholism in first or second degree relatives). All participants needed to report the absence of flushing either currently or in the past based on the Alcohol Flushing Questionnaire, assessed during screening. Young women needed to have normal menstrual cycles and were tested in the follicular phase of their menstrual cycle (within 7 days of offset of menses) and needed to have a negative urine pregnancy test at the start of each study session. Older women were post-menopausal with cessation of menses for at least 12 months prior to enrollment into the study and a serum follicle stimulating hormone (FSH) level > 40 IU/L. Younger female participants were not permitted to use oral contraceptive pills and older female participants were not permitted to use hormone replacement therapy. Participants were also not permitted to use herbal preparations containing soy isoflavones, which may have estrogenic properties. Participants were not permitted to have ferromagnetic objects in their bodies which might adversely be affected by MRI and could not be unable to undergo an MRI scan for liver volume due to claustrophobia or anxiety when confined to small spaces.

Table 1: Demographics for the Fixed-Dose Study and the Alcohol Self-Administration Study.

The fixed-dose study was stratified by age (younger group aged 21–25, older group aged 55–65) and sex. The self-administration study was stratified by binge drinking status. Binge drinking participants reported at least 2 binge drinking sessions in the month prior to the session, with a binge being defined as at least 4 drinks for females and at least 5 drinks for males in a given day. Average drinks per drinking day, total drinking days, and binge drinking days were derived from a 90-day Timeline Followback interview. Drinking data for the fixed-dose study were not available for 8 participants.

Fixed-Dose Study Alcohol Self-Administration Study
Participants (N) 47 23
Age (Mean [SD]) Young Group: 23.1 (1.0)
Older Group: 59.4 (3.0)		 26.9 (4.8)
Sex (Male, N [%]) 23 (48.9%) 13 (56.5%)
Body Mass Index (Mean [SD]) 25.2 (3.9) 24.7 (4.4)
Caucasian (N [%]) 39 (83.0%) 15 (65.2%)
African American (N [%]) 3 (6.4%) 5 (21.7%)
Hispanic (N [%]) 3 (6.4%) 3 (13.0%)
Average Drinks Per Drinking Day (Median [Q1, Q3]) 1.6 (1.1, 2.2) Bingers (N=14): 3.4 (2.8, 3.9)
Non-bingers (N=9): 1.7 (1.5, 2.1)
Total Drinking Days (Median [Q1, Q3]) 17.0 (7.0, 37.0) Bingers (N=14): 29.5 (20.0, 38.0)
Non-bingers (N=9): 29.0 (14.0, 39.0)
Binge Drinking Days (Median [Q1, Q3]) 0.0 (0.0, 1.0) Bingers (N=14): 7.5 (4.0, 12.0)
Non-bingers (N=9): 0.0 (0.0, 0.0)
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By contrast, the alcohol self-administration study enrolled male and female participants between 21–45 years of age stratified by binge-drinking status, where bingers were defined as consuming at least 4 drinks (females) or 5 drinks (males) in at least two drinking sessions during the month prior to the study and non-bingers were defined as having no binge drinking episodes in the month prior to the study (Table 1). Individuals seeking treatment for alcohol use disorders were excluded. All participants had at least one experience drinking 5 or more drinks on one occasion in their lifetime. Females had normal menstrual cycles and were tested outside of the menses phase of their cycle. Females also needed to have a negative urine pregnancy test at the start of each study session. Participants were excluded if they had a history of significant withdrawal symptoms or presented at screening with clinically significant withdrawal symptoms (Clinical Institute Withdrawal Assessment for Alcohol scale revised21 score > 8). Participants were also excluded if they had current or prior history of alcohol-induced flushing reactions.

Study Design

The intravenous alcohol clamp study used a physiologically-based pharmacokinetic (PBPK) model paradigm to maintain participants at a fixed BrAC throughout the study22,23. The PBPK model calculated infusion-rate profiles for each participant to achieve and maintain BrAC at the target values of 50mg% and 0mg% in the alcohol and placebo sessions, respectively. The alcohol and placebo sessions were conducted in cross-over, counter-balanced order across participants and scheduled approximately 7 days apart. Participants were asked to abstain from alcohol for 48 hours prior to the infusion session. They arrived at the NIAAA outpatient clinic at around 7:00AM following an overnight fast and received a light breakfast (~300 calories) approximately 3 hours prior to the infusion. The infusion was started at approximately 10:00 AM. A breathalyzer test was performed to ensure a zero breath alcohol concentration prior to the infusion. An indwelling intravenous catheter for ethanol or normal saline infusion and blood sampling was inserted into the antecubital vein of the arm using a sterile technique. Approximately 30 minutes prior to the start of the infusion, baseline blood samples were collected. Next, participants received either 6% v/v ethanol or 0.9% sodium chloride, administered in randomized, counter-balanced order between two single-blinded sessions. For the alcohol session, the infusion rate increased exponentially until a target blood alcohol concentration (BAC) of 50mg% was reached at 15 minutes followed by an exponentially decreasing infusion rate which tapers to a constant steady-state value, to maintain the BAC at the target value for the predetermined 165 minute interval. Serial breathalyzer measurements ensured that participants were within 5mg% of the target BAC and enabled minor adjustments to the infusion rate to overcome errors in parameter estimation and experimental variability. The infusion was terminated at the end of the 3 hour period.

The IV alcohol self-administration study used the computer-assisted self-administration of alcohol paradigm, which allows participants to infuse ethanol to their preferred level of intoxication24,25. This procedure has been shown to differentiate drinkers at high-risk and low-risk for alcohol use disorder18,19 and has been used to examine potential genetic risk factors for AUD26. Participants were recruited to the National Institute on Alcohol Abuse and Alcoholism’s outpatient clinic for five sessions. The first session was a baseline alcohol self-administration session, which allowed individuals to acclimatize to the IV alcohol self-administration procedure. The second session consisted of a manual-based semi-structured interview session27 to obtain personal vignettes from participants for the creation of personalized guided imagery scripts (approximately 5 minutes in length) to induce alcohol, stress, or neutral states. In each of the final three alcohol self-administration sessions, participants were exposed to one of their three scripts in randomized order prior to alcohol self-administration. Data utilized in our analysis come from the neutral self-administration session as our main objective in these analyses was to determine the effects of alcohol on circulating endocannabinoid concentrations. The effects of stress-cues and alcohol-cues will be examined in future publications. For each self-administration session, participants arrived at the clinic at around 11:00AM after abstaining from alcohol for 48 hours and received a light lunch (~350 calories). Unlike the fixed-dose study, participants were not asked to fast overnight. A breathalyzer test was performed to ensure a zero breath alcohol concentration prior to alcohol self-administration. Indwelling intravenous catheters were inserted into the antecubital vein of both arms, one for the alcohol infusion and the other for blood sampling. Following a one-hour relaxation period, participants heard their personalized neutral script via headphones and were asked to imagine the situation being described as if they were actively participating in it. The guided imagery was presented over five minutes. Then participants participated in a free-access alcohol self-administration paradigm, during which time they could press a button for standardized IV infusions of alcohol. The free-access period lasted 120 minutes overall. Participants could infuse up to a maximum breath alcohol concentration of 100mg%, imposed for safety reasons. Blood samples taken at baseline (approximately 20 minutes prior to the infusion) and at 30 minutes after the start of the infusion were analyzed. The 30-minute timepoint was selected to evaluate the short-term effect of alcohol on circulating AEA and 2-AG concentrations, which were previously found to be reduced following red wine consumption at 20 and 45 minutes, respectively16.

Measurement of Circulating Endocannabinoid Concentrations

Blood processing steps included centrifugation at 1880G for 10 minutes at 4°C, pipetting off the supernatant plasma, and freezing the sample at −80°C until analysis. AEA and 2-AG were quantified in plasma samples from human subjects by liquid chromatography/tandem mass spectrometry. 100 μL plasma was incubated at −20°C for 10 minutes with 900 ml ice-cold acetone and 400 μL Tris buffer (50 mM, pH 8.0) to precipitate proteins. After spinning at 3000g at 4°C for 10 minutes, the supernatant was transferred to a glass tube to evaporate the acetone phase under nitrogen flow. Then, the supernatant was extracted two times with 2 ml of CHCl3:MeOH (2:1, vol/vol). Lower chloroform phase was collected and transferred to another glass tube. Then combined chloroform phases were dried under nitrogen flow. The dried samples were reconstituted in 50 μL of ice-cold methanol prior to loading the autosampler for mass spectrometry measurements. The LC–MS/MS measurements were conducted on an Agilent 6410 triple quadrupole mass spectrometer (Agilent Technologies, USA) coupled to an Agilent 1200 LC system (Agilent Technologies, Waldbron, Germany) with conditions set as previously described28. Liquid chromatographic separation was obtained using 2 μl injections of samples onto a Zorbax SB-C18 rapid resolution HT column (2.1mm×50 mm, 1.8 Micron) from Agilent Technologies. The autosampler temperature was set at 4°C and the column was maintained at 34°C during the analysis. Gradient elution mobile phases consisted of A (0.1% formic acid in Water) and B (0.1% formic acid in methanol). Gradient elution (250 μL/ min) began and was held at 10% B for the first 0.5 minutes, followed by a linear increase towards 85% B at 1 minute; this was maintained until 12.5 minutes and then increased linearly again to 100% B at 13 minutes; this was maintained until 22 minutes. At minute 28.5, the gradient changed linear to the initial setting which was maintained for 6 minutes. The Agilent 6410 triple quadrupole mass spectrometer was set for electrospray ionization (ESI). The electrospray interface was operated in positive ion mode. The source parameters were as follows; capillary voltage, 4000V; gas temperature, 350°C; drying gas, 10 liters/min; and nitrogen was used as the nebulizing gas with a pressure of 40 psig. Collision-induced dissociation (CID) energy was performed by using nitrogen. Levels of endocannabinoids were analyzed by multiple reactions monitoring (MRM). The molecular ion and fragment for each compound were measured as follows: m/z 348.3→62.1 for AEA, m/z 352.3→66.1 for [2H4]AEA, and m/z 379.3→91.1 for 2-AG. The analytes were quantified using MassHunter Workstation LC/QQQ Acquisition and MassHunter Workstation Quantitative Analysis software (Agilent Technologies). The amounts of AEA and 2-AG in the samples were determined against standard curves using [2H4]AEA as internal standard. Values are expressed as pmol/ml.

Data Analysis

Fixed-Dose Study:

Circulating endocannabinoid concentrations were log-transformed to a normal distribution. A repeated measures ANOVA was then used to analyze the effect of alcohol exposure on circulating AEA and 2-AG concentrations. Drug (alcohol or placebo) and time (pre- or post- infusion) were included as within-subjects factors. The main outcome of interest in this analysis was whether the change in circulating endocannabinoid concentrations over time differed by drug condition, i.e. whether there was a significant drug by time interaction. Given that sample recruitment was stratified by age and sex, we also performed exploratory ANOVAs with sex or age group (21–25 years and 55–65 years) as between-subjects factors. The main objectives of these exploratory analyses were to determine whether there were drug by time by age or drug by time by sex interactions. The relationships between age group, sex, drug condition, and time were explored visually with boxplots (Figure 3). Wilcoxon signed-rank tests were used for boxplot visualization to compare changes in endocannabinoids across time in each drug, sex, or age subgroup. For all AEA and 2-AG analyses, we excluded individuals with extreme outlying circulating endocannabinoid concentrations. The standard definition of extreme outliers was used: values three times the interquartile range above the third quartile or below the first quartile29. Two individuals were removed from the AEA analyses and one individual was removed from the 2-AG analyses.

Alcohol Self-Administration Study:

In the alcohol self-administration study, we examined circulating AEA and 2-AG concentrations at baseline (20 minutes prior to the infusion) and 30 minutes after the start of the alcohol self-administration. First, paired samples t-tests were used to determine whether there were reductions in AEA and 2-AG during the first 30 minutes of the alcohol self-administration period. Then, we assessed whether total alcohol exposure (defined as the area under the estimated BAC versus time curve) was associated with change in circulating endocannabinoid concentrations using Pearson’s correlations and linear regression. As sample recruitment for this study was stratified by a binary measure of binge drinking, we covaried for binge drinking status in addition to age and sex. As above, we assessed extreme outlying endocannabinoid concentrations using values three times the interquartile range above the third quartile or below the first quartile. There were no extreme outlying endocannabinoid concentrations at baseline, so all data points were retained in the AEA and 2-AG analyses. Finally, as an exploratory analysis, we used paired samples t-tests to analyze changes in AEA and 2-AG in the 3 individuals in our sample with the highest alcohol exposure (AUC > 500 mg%*min) and in the 4 individuals in our sample with no alcohol exposure (AUC = 0 mg%*min), with the hypothesis that only individuals with high exposure would experience significant reductions in AEA and 2-AG.

RESULTS

Fixed-Dose Study

To examine the effects of intravenous alcohol on circulating AEA and 2-AG levels, we used repeated measures ANOVAs with drug (alcohol or placebo) and time (pre- or post-infusion) as within-subjects factors. For AEA, there was a significant drug by time interaction (F(1, 44) = 6.401, p = 0.015), with circulating AEA concentrations showing a greater decline during the alcohol infusion than the placebo infusion (Figure 2 and Figure S1). Average AEA concentrations decreased by 0.97 pmol/ml (SD = 1.14) during the alcohol infusion and 0.36 pmol/ml (SD = 0.97) during the placebo infusion. For 2-AG, there was a significant main effect of drug condition (F(1, 45) = 4.898, p = 0.032), but no significant main effect of time (F(1, 45) = 0.064, p = 0.802) or drug by time interaction (F(1, 45) = 0.476, p = 0.494, Figure 2 and Figure S1). Therefore, although overall 2-AG levels were slightly lower on average on the alcohol infusion day than on the placebo infusion day at both time points, there was no significant decline in 2-AG levels during either infusion.

Figure 2: Change in AEA and 2-AG Over Time in the Fixed-Dose Study:

Figure 2:

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Circulating endocannabinoid levels were measured once approximately 30 minutes prior to the start of the alcohol or placebo infusion and again following the 180-minute infusion. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, according to Wilcoxon signed-rank tests.

Because the sample was recruited by age and sex, further exploratory ANOVAs were conducted. These models were conducted with age group (21–25 years of age or 55–65 years of age) or sex as a between-subjects variable and drug (alcohol or placebo) and time (pre- or post-infusion) as within-subjects variables. There was a significant three-way interaction between sex, drug, and time on AEA levels (F(1, 43) = 10.788, p = 0.002, Figure 3, Table S2, and Figure S2) and a significant three-way interaction between age group, drug, and time on 2-AG levels ((F(1, 44) = 7.650, p = 0.008, Figure 3, Table S2, and Figure S2). There were no additional three-way interactions between either sex, drug, and time on 2-AG levels, or age group, drug, and time on AEA levels. Given the three-way interaction for AEA levels, we performed an ANOVA with drug and time as within-subjects factors for each sex. For females, there was a significant drug by time interaction (F(1, 21) = 20.872, p < 0.001), but for males there was no significant drug by time interaction (F(1, 22) = 0.080, p = 0.781). Given the three-way interaction for 2-AG levels, we performed an ANOVA with drug and time as within-subjects factors for each age group. For the younger age group there was no significant drug by time interaction (F(1, 23) = 1.555, p = 0.225), but for the older age group there was a significant drug by time interaction (F(1, 21) = 8.331, p = 0.009).

Figure 3: Change in AEA and 2-AG Over Time by Sex and Age in the Fixed-Dose Study:

Figure 3:

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Circulating endocannabinoid levels were measured once approximately 30 minutes prior to the start of the alcohol or placebo infusion and again following the 180-minute infusion. *p < 0.05, **p < 0.01, ***p < 0.001, according to Wilcoxon signed-rank tests.

Self-Administration Study

In the alcohol self-administration study, circulating endocannabinoid concentrations were measured at baseline (20 minutes prior to the start of self-administration) and at minute 30 of self-administration. A paired-samples t-test demonstrated that during alcohol self-administration, there was a reduction in circulating AEA levels from baseline (t(22) = −7.61, p < 0.001, Figure 4A). There was a correlation between alcohol exposure and change in AEA levels such that individuals with greater alcohol exposure had greater decreases in AEA levels (r = −0.42, p = 0.046, Figure 4B). A linear regression demonstrated that change in AEA was associated with alcohol exposure at a trend level after accounting for binge-drinking status, age, and sex (b = −0.00083, 95% CI −0.0017 to 0.000052, p = 0.063, Table 2). In contrast, there was no decline in 2-AG levels during self-administration (t(22) = −1.44, p = 0.16). However, there was a trend level relationship between 2-AG levels and alcohol exposure (r = −0.41, p = 0.052), an effect that remained present at a trend level in a linear regression model accounting for age, sex, and binge drinking status (b = −0.0079, 95% CI −0.016 to 0.00063, p = 0.068, Table 2). There was no significant correlation between change in AEA concentration and change in 2-AG concentration over this time period (r = 0.128, p = 0.562).

Figure 4: Change in AEA and 2-AG During Alcohol Self-Administration.

Figure 4:

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(A) Circulating endocannabinoid levels were measured once approximately 20 minutes prior to the start of the alcohol self-administration period and again at minute 30 of the alcohol self-administration period. (B) Correlations between alcohol exposure (measured by the area under the estimated breath alcohol concentration versus time curve) and change in circulating endocannabinoid levels.

Table 2: Linear Regression Models for Change in Endocannabinoids by Ethanol Exposure:

Alcohol exposure indicates the area under the curve of the estimated blood alcohol versus time curve during the first 30 minutes of the intravenous alcohol self-administration session. Sex is coded as a binary value (0 = female, 1 = male). Binge drinker is also coded as a binary value (0 = non-binge drinker, 1 = binge drinker). For Model 1, R2 = 0.177 for the AEA model and R2 = 0.168 for the 2-AG model. For Model 2, R2 = 0.475 for the AEA model and R2 = 0.242 for the 2-AG model.

AEA 2-AG
Linear Model 1: No covariates b Standard Error t p b Standard Error t p
Intercept −0.64 0.14 4.40 <0.01 0.38 1.17 0.32 0.75
Alcohol Exposure −0.00095 0.00045 −2.12 0.046 −0.0075 0.0036 −2.06 0.052
Linear Model 2: With covariates b Standard Error t p b Standard Error t p
Intercept 0.17 0.62 0.27 0.79 −3.16 5.97 −0.53 0.60
Alcohol Exposure −0.00083 0.00042 −1.98 0.063 −0.0079 0.0041 −1.95 0.068
Age −0.03 0.02 −1.51 0.15 0.15 0.20 0.75 0.47
Sex −0.31 0.18 −1.67 0.11 −1.74 1.78 −0.98 0.34
Binge Drinker 0.33 0.20 1.66 0.11 0.89 1.93 0.46 0.65
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In the alcohol self-administration paradigm, we compared changes in circulating endocannabinoid concentrations in the three individuals who achieved the highest alcohol exposure in our study (AUC > 500 mg%*min) to four individuals who did not self-administer any alcohol (AUC = 0 mg%*min). For AEA, there was a significant reduction from baseline to post-infusion in the high AUC group (t(2) = −4.51, p = 0.046) but no significant change in AEA in the individuals who did not self-administer any alcohol (t(3) = −2.07, p = 0.13, Figure S3). In contrast, there was no significant change in 2-AG in either the high AUC group (t(2) = −0.74, p = 0.53) or the group that did not self-administer any alcohol (t(3) = 1.09, p = 0.36, Figure S3).

DISCUSSION

This is the first study to examine the effects of pharmacokinetically-controlled intravenous infusions of alcohol on circulating endocannabinoid levels. We found that exposure to alcohol significantly reduced AEA levels but not 2-AG levels when compared to placebo. To determine whether there was an exposure-related suppression in AEA levels, we then looked at data from an intravenous alcohol self-administration study. We found a correlation between alcohol exposure and AEA reductions, such that individuals who self-administered greater amounts of alcohol had larger reductions in AEA. There was some evidence to suggest a similar relationship between alcohol exposure and reductions in circulating 2-AG levels, although overall circulating 2-AG levels did not decline significantly during the first 30 minutes of the self-administration paradigm.

To our knowledge, only one other study has examined the effects of acute alcohol administration on circulating endocannabinoid levels. This study found that red wine consumption reduced both AEA and 2-AG levels in humans 20 minutes and 45 minutes after consumption16. AEA had its maximal decline after 20 minutes whereas 2-AG reached its lowest point after approximately 45 minutes16. Interestingly, we did not find similar levels of decline in 2-AG, which may be due to the differences in the time frame of sampling between our studies. It is also possible that methodological differences such as in the route of alcohol administration account for these disparate findings; for example, 2-AG levels could be affected by alcohol cues (e.g. smell, taste) or other compounds present in red wine. There is some evidence of such cue-related effects; for example, in social drinkers, alcohol cues have been found to increase circulating AEA levels30. Future studies should seek to more fully characterize the time course of circulating endocannabinoid changes following alcohol exposure and whether the presence of alcohol cues impacts AEA and 2-AG levels. Furthermore, determining the sources of these alcohol-induced changes in circulating endocannabinoids is another important goal for future studies, as circulating levels may be derived from various organs and tissues including the brain, adipose tissue, and skeletal muscle15.

An important future area of work will be to distinguish the effects of acute versus chronic alcohol exposure on endocannabinoid system functioning. With respect to chronic ethanol intake, it has recently been shown that individuals with AUD in early abstinence have higher levels of circulating AEA and lower brain levels of fatty acid amide hydrolase than healthy controls31. Individuals diagnosed with AUD also have decreased CB1 availability compared with healthy controls9,32, which may be due to receptor downregulation or increased CB1 occupancy by endocannabinoids. It is therefore possible that whereas acute exposure to alcohol leads to reductions in endocannabinoid signaling and subsequent CB1 upregulation9, longer term exposure eventually leads to compensatory effects in which endocannabinoid signaling is ultimately enhanced through increased synthesis, decreased degradation, or both mechanisms. Before this can be elucidated, studies evaluating circulating and central endocannabinoid system functioning in larger samples of individuals with AUD need to be conducted. Future studies should also determine whether acute alcohol exposure leads to a similar depression of circulating endocannabinoid signaling in chronic heavy drinkers. It should also be noted that not all studies have reported similar findings. For example, the aforementioned PET study found that individuals with AUD had higher circulating AEA concentrations than healthy controls31, but in another study, abstinent individuals with alcohol dependence had lower circulating AEA concentrations than healthy controls30. This further highlights the need for larger replication studies.

It is also necessary to elucidate whether altered endocannabinoid signaling perpetuates drinking behavior in those with AUD. Individuals with the FAAH C385A polymorphism, which reduces FAAH function, are more likely to be diagnosed with alcohol dependence6. Carriers of this polymorphism who are of European ancestry and have already been diagnosed with alcohol dependence display evidence of a greater addiction severity and increased levels of alcohol consumption6. In line with this finding, PET imaging using the FAAH radiotracer [11C]CURB found that lower brain levels of FAAH and higher circulating levels of AEA were correlated with greater consumption of alcohol31. The mechanism for this remains unclear, but there is some evidence that it could be due to cross-talk between the endocannabinoid and dopaminergic systems. For example, administration of AEA increases dopamine release in rodents33. In both humans and rodents, there is evidence that the FAAH C385A polymorphism leads to changes in D3 receptor levels34, which may also impact pharmacological responses to alcohol. More studies need to be conducted to determine the mechanism by which endocannabinoid signaling affects alcohol consumption and responses; this should include investigating how altered endocannabinoid signaling influences other neurotransmitter systems.

Our study had several limitations. For the alcohol clamp study, we only measured circulating endocannabinoid levels at two time points; therefore, we are unable to characterize the time course of alcohol exposure’s effect on AEA levels. However, data from the alcohol self-administration study suggests that AEA levels start to decline within the first hour of exposure, which is in keeping with other findings16. We only looked at the effects of relatively low levels of alcohol exposure on circulating endocannabinoid concentrations; it is unclear whether the higher blood alcohol concentrations typically achieved by heavy drinkers would have similar effects. We were investigating the effect of alcohol on circulating levels of endocannabinoids rather than central endocannabinoid signaling. Although there are strong correlations between brain FAAH levels and endocannabinoid levels in the peripheral circulation31, cerebrospinal AEA levels have not always been found to correspond to serum levels35. Future studies should therefore examine the effects of acute alcohol exposure on both cerebrospinal endocannabinoid levels and brain FAAH levels using [11C]CURB and other PET tracers. Finally, our self-administration study was limited by a small sample size, therefore we were not able to assess for sex-specific and age-specific effects in this sample. However, given the three-way interactions observed in the fixed-dose study, studies examining temporal and exposure-response effects in a larger sample of male and female participants of varying ages are clearly necessary.

In conclusion, we found evidence that acute alcohol administration suppresses circulating AEA levels in an exposure-dependent manner in healthy participants. We did not find clear evidence of alcohol effects on 2-AG levels. These results, when taken together with our previous findings that altered endocannabinoid signaling is associated with AUD severity, highlight the complex interrelationship between endocannabinoid signaling and alcohol use. As new studies further unravel this complex relationship, the resulting knowledge will hopefully facilitate the development of successful interventions for AUD that target the endocannabinoid system.

Supplementary Material

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ACKNOWLEDGEMENTS

This study was supported by the NIAAA Division of Intramural Clinical and Biological Research (Z1AAA000466 and Z1A AA000310). Development of the CAIS software used for the intravenous alcohol self-administration paradigm was supported by Sean O’Connor, MD, and Martin Plawecki, MD, PhD, at the Indiana Alcohol Research Center (NIH P60 AA007611). Interest in using the CAIS software for IV alcohol laboratory studies may be directed to Vijay Ramchandani (vijayr@mail.nih.gov) or Martin Plawecki (mplaweck@iupui.edu). We would like to thank the clinical staff at NIAAA’s intramural program for their invaluable assistance with conducting this study. We also thank Marcos Sanches for providing helpful advice regarding data analysis.

Footnotes

TRIAL REGISTRATION: clinicaltrials.gov Identifiers: NCT00713492

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