{"paper_id":"2affe551-c8dc-405f-8252-b314bba40cb4","body_text":"Acute Alcohol-Induced Glutamate Changes Measured with Metabotropic Glutamate Receptor 5 Positron Emission Tomography | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Acute Alcohol-Induced Glutamate Changes Measured with Metabotropic Glutamate Receptor 5 Positron Emission Tomography Nakul Ravi Raval, Kelly Smart, Rachel Miller, Yiyun Huang, John H. Krystal, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5183167/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Alcohol consumption at clinically relevant doses alters brain glutamate release. However, few techniques exist to measure these changes in humans. The metabotropic glutamate receptor 5 (mGluR5) PET radioligand [ 11 C]ABP688 is sensitive to acute alcohol in rodents, possibly mediated by alcohol effects on glutamate release. This study aimed to determine the sensitivity of [ 11 C]ABP688 PET to an acute alcohol challenge in humans. Methods: Eight social drinkers (25–42 years; 5 females) with a recent drinking occasion achieving blood alcohol level (BAL)>80 mg/dL were recruited. All participants underwent a 90-minute dynamic baseline [ 11 C]ABP688 PET scan. Two weeks later (range: 7-29 days), participants completed an oral laboratory alcohol challenge over 30 minutes, targeting a BAL of 60 mg/dL. Immediately after the challenge, a second [ 11 C]ABP688 PET scan was performed. Non-displaceable binding potential ( BP ND ; indicative of mGluR5 availability) and R 1 (indicative of relative blood flow) were estimated using the Simplified Reference Tissue Model with the cerebellum as the reference region. Blood samples were taken throughout the scanning procedure to measure the BAL. Results: Seven participants (4 females) completed the study. The mean peak BAL achieved was 61 ± 18 mg/dL. Acute alcohol significantly decreased [ 11 C]ABP688 BP ND (F(1,42) = 17.05, p < 0.001; Cohen’s d = 0.32–0.60) and increased [ 11 C]ABP688 R 1 (F(1,42) = 6.67, p = 0.013; Cohen’s d = 0.32–0.48) across brain regions. Exploratory analysis showed a positive relationship between alcohol-induced % change in [ 11 C]ABP688 R 1 in cortical regions and peak BAL (Spearman rho = 0.78 & 0.85; p = 0.024 & 0.011). Conclusions: This proof-of-concept study demonstrates that [ 11 C]ABP688 PET imaging is sensitive to the effects of acute alcohol consumption. The observed decrease in mGluR5 availability aligns with preclinical data indicating acute increased extracellular glutamate concentrations following ethanol dosing. This imaging tool could be useful for future investigations into the acute effects of alcohol on the brain during abstinence and withdrawal. Cellular & Molecular Neuroscience metabotropic glutamate type 5 receptors positron emission tomography alcohol challenge glutamate release social drinkers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Glutamate is the primary excitatory neurotransmitter in the mammalian brain, playing a central role in physiological processes such as learning, memory, and neuroplasticity. Dysregulated glutamate signaling is reported with both acute and chronic alcohol exposure 1 . Ethanol has dose-related effects on extracellular limbic glutamate levels in rats with doses associated with social drinking (0.5 g/kg) elevating extracellular glutamate levels, while much higher levels (2.0 g/kg) reducing these levels 2 . In models of binge-like consumption 3 – 5 , alcohol initially raises extracellular glutamate levels in, but then glutamate release levels drop below baseline as blood alcohol levels (BAL) decline 2 , 6 , 7 . Chronic alcohol exposure has been associated with excessive extracellular glutamate levels and excitatory signaling 7 – 10 . Importantly, disrupted glutamate signaling has been associated with craving and relapse propensity during abstinence 11 . While ethanol effects on brain glutamate release in rodents seems important, limited tools exist to measure changes in glutamate release in people 12 . Studies have shown that positron emission tomography (PET) imaging with the radiotracer [ 11 C]ABP688 [3-((6-methylpyridin-2-yl)ethynyl) cyclohex-2-en-1-one-O-[ 11 C]methyloxime] is sensitive to changes in extracellular glutamate levels. [ 11 C]ABP688 binds selectively to the allosteric site of metabotropic type 5 glutamate receptors (mGluR5) 13 , 14 , which are excitatory Gq-coupled G protein receptors predominantly expressed on the postsynaptic sites of neurons 15 . Acute administration of ketamine, which transiently elevates glutamate levels, reduces [ 11 C]ABP688 volumes of distribution ( V T ) 16 , 17 , supporting use of [ 11 C]ABP688 PET to measure changes in extracellular glutamate concentrations. A recent rodent study used simultaneous microdialysis and [ 11 C]ABP688 microPET imaging to show concurrent increases in glutamate release and decreases in striatal [ 11 C]ABP688 binding following administration of ethanol 18 . This is consistent with prior reports of calcium-dependent glutamate release in the rodent brain following ethanol administration 2 , 6 , 7 , 19 . In animals, at doses higher than typically seen with social drinking (EC 50 ~ 200 mM), ethanol inhibits mGluR5 function by promoting PKC-related phosphorylation 20 . Motivated by these findings, the goal of this study was to translate these findings to people by evaluating the mGluR5 response to an acute laboratory alcohol challenge with [ 11 C]ABP688 and PET. The hypothesis for this study was that acute alcohol consumption would decrease mGluR5 availability in the brain. A secondary goal was to evaluate the acute alcohol effects on relative [ 11 C]ABP688 delivery (R 1 ), a surrogate of relative blood flow with other radiotracers 21 , 22 , as acute alcohol is known to increase blood flow 23 – 25 . The findings establish a novel imaging tool to measure alcohol-induced glutamate fluctuations in the human brain. Material and methods Recruitment and Study Participants The Yale School of Medicine Human Investigation Committee and the Radiation Safety Committee approved all procedures. Study participants were recruited from the local New Haven population. Participants self-reported at least a single drinking occasion sufficient to reach an estimated BAL of 80 mg/dL in the past three months, operationally defined as more than three drinks for females and more than four drinks for males at intake. This ensured that study participants had prior drinking experience consistent with levels achieved in this study. Participants were asked to recall the two heaviest days of drinking in the previous three months, useful for calculating the BAL achieved for those episodes. Prior to their participation, all subjects provided written informed consent. Recruited participants had no current or past significant medical or neurological disorders, did not meet DSM-5 criteria for current or past psychiatric or substance use disorder. Subjects who had a history of perceptual distortions, seizures, delirium, or hallucinations upon alcohol withdrawal or scored > 12 on the Clinical Institute Withdrawal Assessment scale at intake appointments was excluded. Additionally, participants did not use psychotropic medication over the month prior to participation. Participants medically contraindicated to consuming alcohol were also excluded. Negative pregnancy tests were required for all females during screening and on the day of radiotracer administration. During intake and on scan day, alcohol drinking over the prior 30 days was recorded with the Alcohol Timeline Followback Interview 26 . A total of eight social drinkers (five women and three men) were recruited to participate (see Results and Table 1 for demographics). One subject met criteria for mild AUD. Experimental Design All subjects participated in two [ 11 C]ABP688 PET scans and a laboratory alcohol drinking session (see Fig. 1 ). Participants were asked to abstain from alcohol for at least 48 hours prior to the study day, confirmed by self-report. Abstinence on the morning of scanning was confirmed with a negative breath alcohol test. Baseline [ 11 C]ABP688 PET scans were acquired on the ‘Baseline Day’. Two to three weeks after the Baseline Day, participants came in for the ‘Alcohol Challenge Day’. The Alcohol Challenge Day started with a standardized lunch. Next, at approximately 12:00 pm, participants consumed an alcohol dose calculated to achieve a BAL of at least 60 mg/dL. The dose was prepared taking into account the participant’s total body water (based on sex, age, height, and weight), duration of drinking, and ratio of alcohol to mixer, based on Watson et al. 's update of the Widmark Eq. 2 7 . Alcohol was administered as 80-proof vodka mixed with a decarbonated, non-caffeinated, and non-caloric drink of the participant’s choice at a 1:3 alcohol-to-mixer ratio. The total volume was divided into three equal drinks, with each consumed over a 10-minute period to pace the rate of consumption, requiring 30 minutes for completion. Immediately after the completion of the laboratory alcohol session, the post-alcohol [ 11 C]ABP688 PET scan was acquired. To avoid the diurnal effects of [ 11 C]ABP688 28 , PET scans were scheduled at the same time on different days (approximately 12:30 pm). The Biphasic Alcohol Effects Scale (BAES) 29 and Drug Effects Questionnaire (DEQ) 30 were used to assess the subjective effects of alcohol. BAES is a 14-item questionnaire on an 11-point scale measuring alcohol's stimulating and sedating effects. DEQ, a 5-item visual analog scale, evaluates the subjective effects of alcohol, and includes items assessing FEEL and HIGH drug effect. BAES was measured at baseline (roughly five minutes prior to the start of the alcohol session), and every 30 minutes after the start of the alcohol session for at least 180 minutes after the start of the alcohol session. DEQ was measured at baseline, and every 15 minutes until at least 45 minutes after the start of the alcohol session. To measure BAL, venous blood samples were acquired at 30-min intervals from the start of the alcohol drinking session until the end of the scanning routine, including a baseline sample approximately 5 min before the start of the session. BAL was measured with headspace gas chromatography at the Yale-New Haven Hospital Clinical Laboratories using their standard protocol. Imaging data acquisition [ 11 C]ABP688 of high E/Z ratio (70:1) 16 was synthesized at the Yale PET Center as previously described 31 , resulting in high molar activities of 420 ± 129 GBq/µmol (minimum = 299 GBq/µmol). PET data were acquired with a High Resolution Research Tomograph (Siemens Medical Solutions USA, Inc., Malvern, PA, USA). Head motion data were acquired with an optical motion-tracking tool (Vicra; NDI Systems, Waterloo, ON, Canada). A six-minute transmission scan was acquired for attenuation correction prior to the radiotracer injection. PET data acquisition began simultaneously with the administration of [ 11 C]ABP688 as a slow bolus over one minute. Dynamic PET data were acquired for 90 minutes alongside arterial blood sampling to measure the metabolite-corrected input function 16 . On a separate day, all participants underwent T1-weighted structural magnetic resonance (MR) scans, acquired with a Siemens 3.0T scanner (Siemens Medical Solutions USA, Inc., Malvern, PA, USA) equipped with a 64-channel head coil, providing high-resolution anatomical maps for PET data coregistration. A sagittal gradient-echo MPRAGE sequence was employed (FOV: 256 × 256 mm², 176 slices at 1 mm thickness, TE: 2.77 ms, TR: 2530 ms, TI: 1100 ms, FA: 7°). Preprocessing and Kinetic modeling Dynamic list-mode brain PET data were binned into discrete time frames of increasing length up to five minutes and reconstructed with the MOLAR algorithm 32 . The first ten minutes of PET brain data were registered to the subject-specific T1-weighted MRI using a mutual information algorithm with six degrees of freedom (FLIRT, FSL 3.2; Analysis Group; FMRIB, Oxford, UK). To define the regions of interest, the native MRI was co-registered to the Montreal Neurological Institute template space with a nonlinear transformation algorithm (BioImage Suite; http://www.bioimagesuite.com ). Time-activity curves were generated from the frontal cortex, temporal cortex, striatum, hippocampus, and cerebellum. These regions were chosen due to their known involvement in glutamate neurotransmission and their relevance to the neurobiological effects of alcohol. Regions of interest were gray matter masked as assessed by CAT (A Computational Anatomy Toolbox for Statistical Parametric Mapping [SPM12; Institute of Neurology, University College of London, London, England]; Jena University Hospital, Jena, Germany). For a subset of the participants (n = 4, 2 males, 2 females), arterial blood samples were collected throughout both the scanning procedures. [ 11 C]ABP688 volumes of distribution ( V T ) were calculated in the selected regions, including the cerebellum. V T is the ratio of [ 11 C]ABP688 concentration in tissue to [ 11 C]ABP688 concentration in arterial plasma at equilibrium and was estimated with the two tissue compartment model (2TCM). However, arterial blood sampling was not available for both scans in three participants, leading us to primarily use [ 11 C]ABP688 non-displaceable binding potential ( BP ND ) as the outcome measure for this study. BP ND provides a measure of receptor availability in the brain regions, indicating the density of available receptors in relation to non-displaceable binding. BP ND and R 1 were estimated using the Simplified Reference Tissue Model 34 with the cerebellum as the reference region. While the cerebellum is commonly used as a reference region due to its minimal specific binding 35 , 36 , there is evidence for small amounts of mGluR5-specific binding, which could bias BP ND estimates (see Discussion). R 1 values, defined as the ratio of rate constants ( K 1 ) describing tracer influx from plasma to the target region and to the reference region, were also estimated. The R 1 value quantifies relative radiotracer delivery to different brain regions. Since [ 11 C]ABP688 has high first-pass extraction 37 , R 1 provides a proxy measure of relative blood flow as complements to BP ND analyses, providing a more comprehensive understanding of the acute effects of alcohol on brain function. Statistical analysis Separate linear mixed-effect models were employed for the statistical analysis of [ 11 C]ABP688 BP ND and R 1 , following confirmation of the data's normal distribution. The constructed model incorporated PET state (baseline vs. post-alcohol) and Region as fixed effects, along with their interaction, while a random intercept accounted for individual variability (PatientID). Post hoc pairwise comparisons (Fisher’s Least Significant Difference) were utilized to determine the impact of alcohol on the frontal cortex, temporal cortex, hippocampus, and striatum. Alcohol-induced Δ BP ND and Δ R 1 were quantified as percentage differences ([Post-alcohol – Baseline]/Baseline * 100). Exploratory analyses examined potential relationships between Δ BP ND and Δ R 1 with the following factors: (1) subjective alcohol effects, (2) peak BAL, and (3) self-reported alcohol consumption over the past month. These analyses were designed to test hypotheses concerning the mGluR5 response to alcohol: (1) its association with subjective alcohol responses, (2) its dependence on alcohol dosage, and (3) its correlation with recent drinking history. Subjective effects analyses focused on stimulation during the ascending limb (30-minute intervals of BAES stimulation, DEQ FEEL, and DEQ HIGH) and sedation during the descending limb (150-minute and 210-minute intervals of BAES sedation). Further partial correlation analyses, controlling for baseline subjective effects, were conducted to explore the associations between Δ BP ND and Δ R 1 and BAL measures, as well as recent drinking history. Given the exploratory nature of these analyses, Spearman rank correlation coefficients (Spearman’s rho) were calculated without correction for multiple comparisons. Scan characteristic and V T value comparisons were made using paired t-tests. Statistical analyses were performed using R 4.2.2 (“Innocent and Trusting”) and RStudio (RStudio Team, Boston, MA, USA), with data visualization carried out using GraphPad Prism (v. 9.4.1; GraphPad Software, San Diego, CA, United States). Results Participant demographics and characteristics Table 1 Participant demographics and scanning parameters Age 27.7 ± 6 years (range: 22–42) Sex 3M; 4F Number of drinks in the last 30 days on Scan Day 22 ± 20 drinks (range: 2–53) AUD status (DSM-5) 1 Mild AUD (1F) Peak BAL 61 ± 18 mg/dL (n = 7) Days between scan 17 ± 8 days (range: 7–29) Injected dose Baseline: 614.5 ± 62 MBq (range: 530–684) Post-alcohol: 638 ± 53 MBq (range: 529–688) Injected mass Baseline: 0.36 ± 0.1 µg (range: 0.19–0.43) Post-alcohol: 0.39 ± 0.1 µg (range: 0.27–0.54) Scan Start Time of Dat Baseline: 12:17 (range: 11:55 − 12:35) Post-alcohol: 12:24 (range: 11:59 − 12:36) Abbreviations: AUD, Alcohol Use Disorder; F, female; M, male; No significant differences were noted in the [ 11 C]ABP688 injected dose or mass. Eight participants (3 males, 5 females) enrolled in the study. One female met DSM-5 criteria for mild alcohol use disorder. One participant did not complete the study, vomiting during the laboratory alcohol session, with a peak BAL of 33 mg/dL at 120 minutes. This participant was excluded from the final analysis. The final analysis included seven participants (3 males, 4 females) with an average age of 27.7 ± 6 years. These participants reported consuming an average of 22 ± 20 drinks in the last 30 days. During the laboratory drinking session, males consumed 150.7 ± 11 mL of 80-proof alcohol, while females consumed 111.6 ± 20 mL. The average peak BAL among the included participants was 61.4 ± 18 mg/dL, exhibiting a typical biphasic BAL curve (see Fig. 2 ). Behavioral data indicated that alcohol consumption led to a decrease in stimulation and increase in sedation, as measured by the BAES, and in subjective feelings of intoxication, as FEEL and HIGH measured by the DEQ (Supp. Figure 1 ). For PET scans, no significant differences were observed in injected activity, injected mass, or the time of scan between the baseline and post-alcohol scans (Table 1 ). Using the Cerebellum as a reference region Analysis of [ 11 C]ABP688 V T was restricted to the four people for which arterial input function was acquired for both scans (see Supp. Table. 1). The cerebellum exhibited little change from baseline (1.95 ± 0.4; range = 1.66–2.44) compared with post-alcohol (2.03 ± 0.3; range = 1.71–2.46), with an overall change of 4.5 ± 4% (range = 0.07–8.58%), within the reported cerebellum [ 11 C]ABP688 V T test-retest variability of 13% 28 . This result was taken to support use of the cerebellum as a reference region for this study design. Acute alcohol decreases brain mGluR5 availability Brain mGluR5 availability, quantified by [ 11 C]ABP688 BP ND , significantly decreased post-alcohol compared to baseline. The main effect of alcohol (F(1,42) = 17.05, p < 0.001) was statistically significant. The interaction between alcohol and region was not statistically significant (F(4,42) = 0.57, p = 0.632), suggesting that the decrease in mGluR5 availability was potentially a whole-brain effect. On average, [ 11 C]ABP688 BP ND values decreased by 9% post-alcohol compared to baseline, as illustrated in Fig. 3 . Post hoc analysis revealed moderate effect sizes of alcohol in the following brain regions: frontal cortex (9.08% decrease, Cohen’s d = 0.49, p = 0.015), temporal cortex (11.2% decrease, Cohen’s d = -0.60, p = 0.010), striatum (8.9% decrease, Cohen’s d = -0.49, p = 0.021), and hippocampus (6.6% decrease, Cohen’s d = -0.32, p = 0.317). Relative blood flow, quantified by [ 11 C]ABP688 R 1 , significantly increased post-alcohol compared to baseline. The main effect of alcohol (F(1,42) = 6.69, p = 0.013) was statistically significant, while the interaction between alcohol and region was not statistically significant (F(4,42) = 0.08, p = 0.970). Exploratory post hoc analysis revealed a significant increase in the striatum (2.59% increase, Cohen’s d = 0.46, p = 0.046) but no significant changes in the frontal cortex, hippocampus, or temporal cortex (see Fig. 2 ). Relationship of [ 11 C]ABP688 mGluR5 availability and relative blood flow with peak BAL, recent drinking behavior, and subjective effects Exploratory analyses revealed no significant relationships between Δ BP ND and peak BAL, past month number of drinks, or subjective effects such as BAES or DEQ. In contrast, there was initial evidence for significant (uncorrected for multiple comparisons) poasitive relationships between Δ R 1 and peak BAL in frontal cortex (Spearman rho = 0.85; p = 0.011) and temporal cortex (Spearman rho = 0.78; p = 0.024), as illustrated in Fig. 5 . No other significant relationships were found between Δ R 1 and peak BAL, recent drinking amounts, or subjective effects like BAES or DEQ (Supp. Tables 2 and 3). Discussion This study reveals evidence that a laboratory alcohol challenge achieving an average peak BAL of ~ 60 mg/dL significantly reduced brain mGluR5 availability, as measured by [ 11 C]ABP688 BP ND . Further analyses yielded modest evidence that alcohol increased relative blood flow in cortical regions, as measured by [ 11 C]ABP688 R 1 , with positive correlations between R 1 increases and peak BAL, largely confirming prior findings. No significant associations were found between post-alcohol Δ BP ND or Δ R 1 and recent drinking behavior or subjective effects. The findings establish a novel imaging paradigm for investigating the dynamic effects of acute alcohol on brain glutamate function. This in vivo human evidence for imaging [ 11 C]ABP688 response to alcohol aligns with preclinical rodent literature 18 , suggesting that alcohol-induced glutamate release contributes to the observed decrease in mGluR5 availability. Despite the preliminary nature of the data reported here, it is noteworthy that all subjects exhibited a consistent decrease in [ 11 C]ABP688 binding. This uniformity in response supports the reliability of our findings and underscores the potential of [ 11 C]ABP688 PET imaging to measure alcohol-induced changes in mGluR5 availability, although the results should be validated in larger cohorts. A plausible mechanism for this finding is that increases in glutamate cause mGluR5s to internalize within the cell membrane, and these receptors are no longer available for [ 11 C]ABP688 binding since this radiotracer targets an allosteric site on mGluR5 on cell surface receptors only 38 . This decrease in [ 11 C]ABP688 BP ND following acute alcohol highlights potential disruptions in glutamate signaling pathways, which are essential for synaptic plasticity and cognitive functions 39 . Such disruptions can lead to long-term changes in glutamate function and behavior associated with AUD and subsequent recovery 11 , 40 , and are important areas of research for future studies leveraging this imaging paradigm as is evaluation of targeted therapies aimed at modulating glutamate signaling to treat or prevent AUD. The primary outcome measure for this study was [ 11 C]ABP688 BP ND using the cerebellum as a reference region. This allowed for use of the full dataset, as arterial blood sampling was available for both baseline and challenge studies in only 4 participants. The cerebellum contains small but significant [ 11 C]ABP688 specific binding, which could introduce systematic biases and potentially reduce the accuracy of detected associations 41 , 42 . Cerebellum [ 11 C]ABP688 V T values were carefully examined in the data and no significant changes were found after the acute alcohol, supporting validity of this reference region in the context of this challenge. Should alcohol indeed cause small reductions in cerebellum [ 11 C]ABP688 specific binding, this would cause underestimation of decreases in [ 11 C]ABP688 BP ND , increasing confidence for using this analytic approach in the context of alcohol challenge. Indeed, [ 11 C]ABP688 BP ND values derived using the cerebellum correlate well with those obtained from arterial input 43 , and the inherent variability of [ 11 C]ABP688 V T values 28 , 44 are poorer than that of [ 11 C]ABP688 BP ND 35 . Future investigations into alcohol's effects on these areas may require larger sample sizes to strengthen statistical confidence in the findings. Taken together, this supports use of [ 11 C]ABP688 BP ND as the primary outcome for this study, although caution must be used when interpreting study results. Previous human imaging studies with PET 45 – 48 and arterial spin labeling 23 – 25 , 49 , 50 have shown that alcohol stimulates cortical gray matter hemodynamics across varying BALs. In line with these findings, our study observes a modest increase in [ 11 C]ABP688 R 1 values, which represent relative blood flow. This increase in R 1 highlights the vasodilatory effect of acute alcohol consumption. Importantly, a strong positive correlation was found between peak BAL and Δ R 1 , particularly in cortical gray matter regions, similar to previous studies 45 , 46 , 51 . These findings highlight the necessity of accounting for regional blood flow alterations when studying alcohol's impact on the brain, especially in fMRI studies of both resting state and task-based activities, as well as in multimodal (including PET and fMRI) approaches 52 . In conclusion, this study provides in vivo human evidence that an oral alcohol challenge decreased [ 11 C]ABP688 BP ND values in cortical and subcortical regions, which may reflect glutamate fluctuations in the brain as previously reported in preclinical studies. These results establish a novel imaging paradigm that allows for the examination of the dynamic effects of acute alcohol on human brain glutamate function and investigate glutamatergic underpinnings of AUD. This study advances the field’s knowledge of the acute effects of alcohol on the brain and the associated glutamate response, providing a foundation for future research in this area. Declarations Acknowledgements We express our gratitude to the exceptional staff at the Yale PET Center for their expertise and support in radiochemistry, metabolite analysis, and image acquisition. We also extend our thanks to the personnel at the Clinical Neuroscience Research Unit at the Connecticut Mental Health Center and the Hospital Research Unit at the Yale Clinical Center for Investigation for their assistance with participant monitoring and evaluation. Funding We gratefully acknowledge the funding support from the National Institute on Alcohol Abuse and Alcoholism (K01AA024788; P50AA012870; K24031345) and State of Connecticut Support for the Clinical Neuroscience Research Unit. Competing interests The authors declare they have no competing financial and/or non-financial interests in relation to the work described herein. References Olive MF, Cleva RM, Kalivas PW, Malcolm RJ. Glutamatergic medications for the treatment of drug and behavioral addictions. 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Alcohol Alcohol . 2013;48(2):160-165. doi:10.1093/alcalc/ags121 Sobell LC, Sobell MB. Timeline Follow-Back. In: Measuring Alcohol Consumption . Humana Press; 1992:41-72. doi:10.1007/978-1-4612-0357-5_3 Watson PE, Watson ID, Batt RD. Prediction of blood alcohol concentrations in human subjects. Updating the Widmark Equation. J Stud Alcohol . 1981;42(7):547-556. doi:10.15288/jsa.1981.42.547 DeLorenzo C, Gallezot JD, Gardus J, et al. In vivo variation in same-day estimates of metabotropic glutamate receptor subtype 5 binding using [11C]ABP688 and [18F]FPEB. J Cereb Blood Flow Metab . 2017;37(8):2716-2727. doi:10.1177/0271678X16673646 Martin CS, Earleywine M, Musty RE, Perrine MW, Swift RM. Development and validation of the Biphasic Alcohol Effects Scale. Alcohol Clin Exp Res . 1993;17(1):140-146. doi:10.1111/j.1530-0277.1993.tb00739.x Morean ME, de Wit H, King AC, Sofuoglu M, Rueger SY, O’Malley SS. The drug effects questionnaire: psychometric support across three drug types. Psychopharmacology . 2013;227(1):177-192. doi:10.1007/s00213-012-2954-z Sandiego CM, Nabulsi N, Lin SF, et al. Studies of the metabotropic glutamate receptor 5 radioligand [ 11 C]ABP688 with N-acetylcysteine challenge in rhesus monkeys. Synapse . 2013;67(8):489-501. doi:10.1002/syn.21656 Jin X, Mulnix T, Gallezot JD, Carson RE. Evaluation of motion correction methods in human brain PET imaging--a simulation study based on human motion data. Med Phys . 2013;40(10):102503. doi:10.1118/1.4819820 Lammertsma AA, Hume SP. Simplified reference tissue model for PET receptor studies. Neuroimage . 1996;4(3 Pt 1):153-158. doi:10.1006/nimg.1996.0066 Smart K, Cox SML, Nagano-Saito A, Rosa-Neto P, Leyton M, Benkelfat C. Test-retest variability of [11 C]ABP688 estimates of metabotropic glutamate receptor subtype 5 availability in humans. Synapse . 2018;72(9):e22041. doi:10.1002/syn.22041 Elmenhorst D, Minuzzi L, Aliaga A, et al. In vivo and in vitro Validation of Reference Tissue Models for the mGluR5 Ligand [11C]ABP688. J Cereb Blood Flow Metab . 2010;30(8):1538-1549. doi:10.1038/jcbfm.2010.65 Ametamey SM, Treyer V, Streffer J, et al. Human PET studies of metabotropic glutamate receptor subtype 5 with 11C-ABP688. J Nucl Med . 2007;48(2):247-252. https://www.ncbi.nlm.nih.gov/pubmed/17268022 Lin X, Donthamsetti P, Skinberg M, Slifstein M, Abi-Dargham A, Javitch J. FPEB and ABP688 cannot accesss internalized mGluR5 receptors. In: MGluR5 Workshop . Columbia University; 2015. Jeffrey Conn P, Patel J. The Metabotropic Glutamate Receptors . Springer Science & Business Media; 2013. https://play.google.com/store/books/details?id=HPbTBwAAQBAJ Alasmari F, Goodwani S, McCullumsmith RE, Sari Y. Role of glutamatergic system and mesocorticolimbic circuits in alcohol dependence. Prog Neurobiol . 2018;171:32-49. doi:10.1016/j.pneurobio.2018.10.001 DeLorenzo C, Milak MS, Brennan KG, Kumar JSD, Mann JJ, Parsey RV. In vivo positron emission tomography imaging with [ 11 C]ABP688: binding variability and specificity for the metabotropic glutamate receptor subtype 5 in baboons. Eur J Nucl Med Mol Imaging . 2011;38(6):1083-1094. doi:10.1007/s00259-010-1723-7 Kågedal M, Cselényi Z, Nyberg S, et al. A positron emission tomography study in healthy volunteers to estimate mGluR5 receptor occupancy of AZD2066 - estimating occupancy in the absence of a reference region. Neuroimage . 2013;82:160-169. doi:10.1016/j.neuroimage.2013.05.006 Milella MS, Minuzzi L, Benkelfat C, et al. Quantification of [ 11 C]ABP688 binding in human brain using cerebellum as reference region: biological interpretation and limitations. bioRxiv . Published online February 13, 2024. doi:10.1101/2024.02.12.24302279 Esterlis I, Holmes SE, Sharma P, Krystal JH, DeLorenzo C. Metabotropic Glutamatergic Receptor 5 and Stress Disorders: Knowledge Gained From Receptor Imaging Studies. Biol Psychiatry . 2018;84(2):95-105. doi:10.1016/j.biopsych.2017.08.025 Sano M, Wendt PE, Wirsén A, Stenberg G, Risberg J, Ingvar DH. Acute effects of alcohol on regional cerebral blood flow in man. J Stud Alcohol . 1993;54(3):369-376. doi:10.15288/jsa.1993.54.369 Mathew RJ, Wilson WH. Regional cerebral blood flow changes associated with ethanol intoxication. Stroke . 1986;17(6):1156-1159. doi:10.1161/01.str.17.6.1156 Newlin DB, Golden CJ, Quaife M, Graber B. Effect of alcohol ingestion on regional cerebral blood flow. Int J Neurosci . 1982;17(3):145-150. doi:10.3109/00207458208985916 Volkow ND, Mullani N, Gould L, et al. Effects of acute alcohol intoxication on cerebral blood flow measured with PET. Psychiatry Res . 1988;24(2):201-209. doi:10.1016/0165-1781(88)90063-7 Tolentino NJ, Wierenga CE, Hall S, et al. Alcohol effects on cerebral blood flow in subjects with low and high responses to alcohol. Alcohol Clin Exp Res . 2011;35(6):1034-1040. doi:10.1111/j.1530-0277.2011.01435.x Tiihonen J, Kuikka J, Hakola P, et al. Acute ethanol-induced changes in cerebral blood flow. Am J Psychiatry . 1994;151(10):1505-1508. doi:10.1176/ajp.151.10.1505 Bjork JM, Gilman JM. The effects of acute alcohol administration on the human brain: insights from neuroimaging. Neuropharmacology . 2014;84:101-110. doi:10.1016/j.neuropharm.2013.07.039 Smart K, Worhunsky PD, Scheinost D, et al. Multimodal neuroimaging of metabotropic glutamate 5 receptors and functional connectivity in alcohol use disorder. Alcohol Clin Exp Res . 2022;46(5):770-782. doi:10.1111/acer.14816 Additional Declarations The authors declare no competing interests. Supplementary Files 20240821abpdrinksupplementary.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-5183167\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":360817879,\"identity\":\"58958221-5ca5-411f-ae7c-b25c52461806\",\"order_by\":0,\"name\":\"Nakul Ravi Raval\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYFACNgaGB2AGcyOQtgCxDAhrSQAzGJuBSiVI09ImQZQWc/ZjaRIJDPfkDY4fbKvmqZGQY2Bv3iaBT4tlT9oxoJZiww1nEttu8xyTMGbgOVaGV4vBgfQ2oJYExpkNIC1sEokNEjlm+LWcfw7WYj+z/2FbMc8/ifoG+TcEtNwAOywhsV8isY2ZF6RdgoeQlmfJFgkGCcn9Eg+bJef2SRi28aQVW+B3WJrhjQ8VCbZt/MkHP7z5ZiPPz3544w18WqAaIRQTDwM4nkgAjD9IUj4KRsEoGAUjBQAAsjFDzzCCEqMAAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0001-5637-7219\",\"institution\":\"1.Yale PET Center, Yale University, New Haven, CT, USA. 2.Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Nakul\",\"middleName\":\"Ravi\",\"lastName\":\"Raval\",\"suffix\":\"\"},{\"id\":360817880,\"identity\":\"f9176425-a9a4-4fa8-8b44-044a5fcce387\",\"order_by\":1,\"name\":\"Kelly Smart\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0002-4775-6943\",\"institution\":\"1.Yale PET Center, Yale University, New Haven, CT, USA. 2.Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kelly\",\"middleName\":\"\",\"lastName\":\"Smart\",\"suffix\":\"\"},{\"id\":360817881,\"identity\":\"a06a1c9d-050b-4193-a6a0-a57eab2eed31\",\"order_by\":2,\"name\":\"Rachel Miller\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"1.Yale PET Center, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rachel\",\"middleName\":\"\",\"lastName\":\"Miller\",\"suffix\":\"\"},{\"id\":360817882,\"identity\":\"a2ded0d5-b06a-4d36-9489-497ce64d96d8\",\"order_by\":3,\"name\":\"Yiyun Huang\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0002-6757-3220\",\"institution\":\"1.Yale PET Center, Yale University, New Haven, CT, USA. 2.Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yiyun\",\"middleName\":\"\",\"lastName\":\"Huang\",\"suffix\":\"\"},{\"id\":360817883,\"identity\":\"b7d0fe37-a936-4dde-a7d1-c5ce8d85e1bf\",\"order_by\":4,\"name\":\"John H. Krystal\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"3.Department of Psychiatry, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"John\",\"middleName\":\"H.\",\"lastName\":\"Krystal\",\"suffix\":\"\"},{\"id\":360817884,\"identity\":\"d1e50d3f-f506-4f2c-aae9-67d4640a2692\",\"order_by\":5,\"name\":\"Richard E. Carson\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"1.Yale PET Center, Yale University, New Haven, CT, USA. 2.Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Richard\",\"middleName\":\"E.\",\"lastName\":\"Carson\",\"suffix\":\"\"},{\"id\":360817885,\"identity\":\"7c3d2e7a-af7c-4953-a018-e81606fab242\",\"order_by\":6,\"name\":\"Kelly P. Cosgrove\",\"email\":\"\",\"orcid\":\"https://orcid.org/0000-0003-1351-9576\",\"institution\":\"2.Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA. 3.Department of Psychiatry, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Kelly\",\"middleName\":\"P.\",\"lastName\":\"Cosgrove\",\"suffix\":\"\"},{\"id\":360817886,\"identity\":\"95152a75-95cb-468f-965c-86c47f0acc7f\",\"order_by\":7,\"name\":\"Stephanie S. O’Malley\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"3.Department of Psychiatry, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Stephanie\",\"middleName\":\"S.\",\"lastName\":\"O’Malley\",\"suffix\":\"\"},{\"id\":360817887,\"identity\":\"a45d8681-d705-484e-bee0-ca34db2fe660\",\"order_by\":8,\"name\":\"Ansel T. Hillmer\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYLCCBwwHePjYQawKBgY+EM1DSEsCUAsbM4h1hoGBjVgtDGAtjG1EaOGf3f7wQQLDHRk2Zu7Ex5XzDsuzsTcwPnjbhluLxJ0zxgYJDM+ADuPdbHh222HDNp4DzIZz8WhhuJHDJpHAcBikZZtk47bDjG0SCWzSvHi0yN9If/4DqmX7z8Y5h+3b5B+w/8anxeBGghkDzBbGxobDiW0SwKDAp8XwRo6xRIIBWMtmyYZj6cltPInNknPO4dYidyP94YcPFYft+dl7N35sqLG27Wc/fPDDmzI83oc4D85qBmLGBkLqUUAdSapHwSgYBaNgZAAAqDxMNFvCCCoAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"1.Yale PET Center, Yale University, New Haven, CT, USA. 2.Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA. 3.Department of Psychiatry, Yale University, New Haven, CT, USA.\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Ansel\",\"middleName\":\"T.\",\"lastName\":\"Hillmer\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-09-30 19:51:28\",\"currentVersionCode\":1,\"declarations\":{\"humanSubjects\":true,\"vertebrateSubjects\":false,\"conflictsOfInterestStatement\":false,\"humanSubjectEthicalGuidelines\":true,\"humanSubjectConsent\":true,\"humanSubjectClinicalTrial\":false,\"humanSubjectCaseReport\":false,\"vertebrateSubjectEthicalGuidelines\":false},\"doi\":\"10.21203/rs.3.rs-5183167/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5183167/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":66068343,\"identity\":\"d481c11d-eb2f-4060-86c3-951958902093\",\"added_by\":\"auto\",\"created_at\":\"2024-10-07 11:38:43\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":78126,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eStudy design. Eight social drinkers had a baseline 90-min [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 PET scan. Two to three weeks later, they completed a 30-min alcohol session targeting BAL ~60 mg/dL, followed by a second 90-min PET scan. Scans were done at the same time of day to control for diurnal variations.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5183167/v1/e412e0929cb60dfac3670f51.png\"},{\"id\":66067159,\"identity\":\"eb0e41fb-8b35-4d34-b0e1-704e672928ff\",\"added_by\":\"auto\",\"created_at\":\"2024-10-07 11:30:43\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":38320,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eMean blood alcohol level (BAL, \\u003cem\\u003en\\u003c/em\\u003e=7) during and after the alcohol drinking session lasting 30 mins. Error bars denote the standard deviation. Horizontal dashed line denotes the lower limit of detection (LLOD).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5183167/v1/55524e13dcdcf1fba4242a43.png\"},{\"id\":66068344,\"identity\":\"d49dd885-20a7-4739-bbf1-bbd0ddd73664\",\"added_by\":\"auto\",\"created_at\":\"2024-10-07 11:38:43\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":94363,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e[\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e, indicative of mGluR5 availability, decreases in all regions after the laboratory alcohol challenge (n=7). Cohen’s d values are presented.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5183167/v1/446b345183f1b4b0c5fa4614.png\"},{\"id\":66067155,\"identity\":\"c7541453-f2f9-4cee-909b-e44932224cc7\",\"added_by\":\"auto\",\"created_at\":\"2024-10-07 11:30:43\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":93065,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e[\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e\\u003cem\\u003e,\\u003c/em\\u003e indicative of relative blood flow, increased in most regions after the laboratory alcohol challenge \\u003cem\\u003e(n\\u003c/em\\u003e=7). Cohen’s d values are presented.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5183167/v1/041ff684c0ac633145be0564.png\"},{\"id\":66067161,\"identity\":\"265e4d6c-ed72-4228-a8dd-9426394d0963\",\"added_by\":\"auto\",\"created_at\":\"2024-10-07 11:30:43\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":38396,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRelationships between [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e\\u003cem\\u003e,\\u003c/em\\u003e indicative of percent change in relative blood flow after alcohol, and peak BAL. Spearman’s\\u0026nbsp; rho are color-coded for the frontal and temporal cortices and inserted in the figure\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5183167/v1/1dd8defef9eaa9231c41c6ca.png\"},{\"id\":66069382,\"identity\":\"3988ec35-9249-4d66-b278-88c4089bed3d\",\"added_by\":\"auto\",\"created_at\":\"2024-10-07 11:46:43\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":855297,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5183167/v1/aa71c157-b176-4318-99fb-e37747ed01a8.pdf\"},{\"id\":66067160,\"identity\":\"a5c9a0be-e4c2-4291-9612-390eab503f91\",\"added_by\":\"auto\",\"created_at\":\"2024-10-07 11:30:43\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":260364,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"20240821abpdrinksupplementary.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5183167/v1/ebd7284ab08d14bce6df61de.docx\"}],\"financialInterests\":\"The authors declare no competing interests.\",\"formattedTitle\":\"\\u003cp\\u003eAcute Alcohol-Induced Glutamate Changes Measured with Metabotropic Glutamate Receptor 5 Positron Emission Tomography\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eGlutamate is the primary excitatory neurotransmitter in the mammalian brain, playing a central role in physiological processes such as learning, memory, and neuroplasticity. Dysregulated glutamate signaling is reported with both acute and chronic alcohol exposure\\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u003c/sup\\u003e. Ethanol has dose-related effects on extracellular limbic glutamate levels in rats with doses associated with social drinking (0.5 g/kg) elevating extracellular glutamate levels, while much higher levels (2.0 g/kg) reducing these levels\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e. In models of binge-like consumption\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR4\\\" citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u003c/sup\\u003e, alcohol initially raises extracellular glutamate levels in, but then glutamate release levels drop below baseline as blood alcohol levels (BAL) decline\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u003c/sup\\u003e. Chronic alcohol exposure has been associated with excessive extracellular glutamate levels and excitatory signaling\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR8 CR9\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u003c/sup\\u003e. Importantly, disrupted glutamate signaling has been associated with craving and relapse propensity during abstinence\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003e. While ethanol effects on brain glutamate release in rodents seems important, limited tools exist to measure changes in glutamate release in people\\u003csup\\u003e\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eStudies have shown that positron emission tomography (PET) imaging with the radiotracer [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 [3-((6-methylpyridin-2-yl)ethynyl) cyclohex-2-en-1-one-O-[\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]methyloxime] is sensitive to changes in extracellular glutamate levels. [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 binds selectively to the allosteric site of metabotropic type 5 glutamate receptors (mGluR5)\\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u003c/sup\\u003e, which are excitatory Gq-coupled G protein receptors predominantly expressed on the postsynaptic sites of neurons\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003e. Acute administration of ketamine, which transiently elevates glutamate levels, reduces [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 volumes of distribution (\\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e)\\u003csup\\u003e\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e\\u003c/sup\\u003e, supporting use of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 PET to measure changes in extracellular glutamate concentrations. A recent rodent study used simultaneous microdialysis and [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 microPET imaging to show concurrent increases in glutamate release and decreases in striatal [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 binding following administration of ethanol\\u003csup\\u003e\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e\\u003c/sup\\u003e. This is consistent with prior reports of calcium-dependent glutamate release in the rodent brain following ethanol administration\\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u003c/sup\\u003e. In animals, at doses higher than typically seen with social drinking (EC\\u003csub\\u003e50\\u003c/sub\\u003e\\u0026thinsp;~\\u0026thinsp;200 mM), ethanol inhibits mGluR5 function by promoting PKC-related phosphorylation\\u003csup\\u003e\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u003c/sup\\u003e. Motivated by these findings, the goal of this study was to translate these findings to people by evaluating the mGluR5 response to an acute laboratory alcohol challenge with [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 and PET. The hypothesis for this study was that acute alcohol consumption would decrease mGluR5 availability in the brain. A secondary goal was to evaluate the acute alcohol effects on relative [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 delivery (R\\u003csub\\u003e1\\u003c/sub\\u003e), a surrogate of relative blood flow with other radiotracers\\u003csup\\u003e\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u003c/sup\\u003e, as acute alcohol is known to increase blood flow\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR24\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e\\u003c/sup\\u003e. The findings establish a novel imaging tool to measure alcohol-induced glutamate fluctuations in the human brain.\\u003c/p\\u003e\"},{\"header\":\"Material and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eRecruitment and Study Participants\\u003c/h2\\u003e \\u003cp\\u003eThe Yale School of Medicine Human Investigation Committee and the Radiation Safety Committee approved all procedures. Study participants were recruited from the local New Haven population. Participants self-reported at least a single drinking occasion sufficient to reach an estimated BAL of 80 mg/dL in the past three months, operationally defined as more than three drinks for females and more than four drinks for males at intake. This ensured that study participants had prior drinking experience consistent with levels achieved in this study. Participants were asked to recall the two heaviest days of drinking in the previous three months, useful for calculating the BAL achieved for those episodes.\\u003c/p\\u003e \\u003cp\\u003e Prior to their participation, all subjects provided written informed consent. Recruited participants had no current or past significant medical or neurological disorders, did not meet DSM-5 criteria for current or past psychiatric or substance use disorder. Subjects who had a history of perceptual distortions, seizures, delirium, or hallucinations upon alcohol withdrawal or scored\\u0026thinsp;\\u0026gt;\\u0026thinsp;12 on the Clinical Institute Withdrawal Assessment scale at intake appointments was excluded. Additionally, participants did not use psychotropic medication over the month prior to participation. Participants medically contraindicated to consuming alcohol were also excluded. Negative pregnancy tests were required for all females during screening and on the day of radiotracer administration. During intake and on scan day, alcohol drinking over the prior 30 days was recorded with the Alcohol Timeline Followback Interview\\u003csup\\u003e\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e\\u003c/sup\\u003e. A total of eight social drinkers (five women and three men) were recruited to participate (see Results and Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e for demographics). One subject met criteria for mild AUD.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eExperimental Design\\u003c/h3\\u003e\\n\\u003cp\\u003eAll subjects participated in two [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 PET scans and a laboratory alcohol drinking session (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Participants were asked to abstain from alcohol for at least 48 hours prior to the study day, confirmed by self-report. Abstinence on the morning of scanning was confirmed with a negative breath alcohol test. Baseline [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 PET scans were acquired on the \\u0026lsquo;Baseline Day\\u0026rsquo;. Two to three weeks after the Baseline Day, participants came in for the \\u0026lsquo;Alcohol Challenge Day\\u0026rsquo;. The Alcohol Challenge Day started with a standardized lunch. Next, at approximately 12:00 pm, participants consumed an alcohol dose calculated to achieve a BAL of at least 60 mg/dL. The dose was prepared taking into account the participant\\u0026rsquo;s total body water (based on sex, age, height, and weight), duration of drinking, and ratio of alcohol to mixer, based on Watson et al. 's update of the Widmark Eq.\\u0026nbsp;2\\u003csup\\u003e7\\u003c/sup\\u003e. Alcohol was administered as 80-proof vodka mixed with a decarbonated, non-caffeinated, and non-caloric drink of the participant\\u0026rsquo;s choice at a 1:3 alcohol-to-mixer ratio. The total volume was divided into three equal drinks, with each consumed over a 10-minute period to pace the rate of consumption, requiring 30 minutes for completion. Immediately after the completion of the laboratory alcohol session, the post-alcohol [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 PET scan was acquired. To avoid the diurnal effects of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688\\u003csup\\u003e28\\u003c/sup\\u003e, PET scans were scheduled at the same time on different days (approximately 12:30 pm).\\u003c/p\\u003e \\u003cp\\u003eThe Biphasic Alcohol Effects Scale (BAES)\\u003csup\\u003e\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u003c/sup\\u003e and Drug Effects Questionnaire (DEQ)\\u003csup\\u003e\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e\\u003c/sup\\u003e were used to assess the subjective effects of alcohol. BAES is a 14-item questionnaire on an 11-point scale measuring alcohol's stimulating and sedating effects. DEQ, a 5-item visual analog scale, evaluates the subjective effects of alcohol, and includes items assessing FEEL and HIGH drug effect. BAES was measured at baseline (roughly five minutes prior to the start of the alcohol session), and every 30 minutes after the start of the alcohol session for at least 180 minutes after the start of the alcohol session. DEQ was measured at baseline, and every 15 minutes until at least 45 minutes after the start of the alcohol session.\\u003c/p\\u003e \\u003cp\\u003eTo measure BAL, venous blood samples were acquired at 30-min intervals from the start of the alcohol drinking session until the end of the scanning routine, including a baseline sample approximately 5 min before the start of the session. BAL was measured with headspace gas chromatography at the Yale-New Haven Hospital Clinical Laboratories using their standard protocol.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003eImaging data acquisition\\u003c/h3\\u003e\\n\\u003cp\\u003e[\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 of high E/Z ratio (70:1)\\u003csup\\u003e\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u003c/sup\\u003e was synthesized at the Yale PET Center as previously described\\u003csup\\u003e\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u003c/sup\\u003e, resulting in high molar activities of 420\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;129 GBq/\\u0026micro;mol (minimum\\u0026thinsp;=\\u0026thinsp;299 GBq/\\u0026micro;mol). PET data were acquired with a High Resolution Research Tomograph (Siemens Medical Solutions USA, Inc., Malvern, PA, USA). Head motion data were acquired with an optical motion-tracking tool (Vicra; NDI Systems, Waterloo, ON, Canada). A six-minute transmission scan was acquired for attenuation correction prior to the radiotracer injection. PET data acquisition began simultaneously with the administration of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 as a slow bolus over one minute. Dynamic PET data were acquired for 90 minutes alongside arterial blood sampling to measure the metabolite-corrected input function\\u003csup\\u003e\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eOn a separate day, all participants underwent T1-weighted structural magnetic resonance (MR) scans, acquired with a Siemens 3.0T scanner (Siemens Medical Solutions USA, Inc., Malvern, PA, USA) equipped with a 64-channel head coil, providing high-resolution anatomical maps for PET data coregistration. A sagittal gradient-echo MPRAGE sequence was employed (FOV: 256 \\u0026times; 256 mm\\u0026sup2;, 176 slices at 1 mm thickness, TE: 2.77 ms, TR: 2530 ms, TI: 1100 ms, FA: 7\\u0026deg;).\\u003c/p\\u003e\\n\\u003ch3\\u003ePreprocessing and Kinetic modeling\\u003c/h3\\u003e\\n\\u003cp\\u003eDynamic list-mode brain PET data were binned into discrete time frames of increasing length up to five minutes and reconstructed with the MOLAR algorithm\\u003csup\\u003e\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e\\u003c/sup\\u003e. The first ten minutes of PET brain data were registered to the subject-specific T1-weighted MRI using a mutual information algorithm with six degrees of freedom (FLIRT, FSL 3.2; Analysis Group; FMRIB, Oxford, UK). To define the regions of interest, the native MRI was co-registered to the Montreal Neurological Institute template space with a nonlinear transformation algorithm (BioImage Suite; \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.bioimagesuite.com\\u003c/span\\u003e\\u003cspan address=\\\"http://www.bioimagesuite.com\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Time-activity curves were generated from the frontal cortex, temporal cortex, striatum, hippocampus, and cerebellum. These regions were chosen due to their known involvement in glutamate neurotransmission and their relevance to the neurobiological effects of alcohol. Regions of interest were gray matter masked as assessed by CAT (A Computational Anatomy Toolbox for Statistical Parametric Mapping [SPM12; Institute of Neurology, University College of London, London, England]; Jena University Hospital, Jena, Germany).\\u003c/p\\u003e \\u003cp\\u003eFor a subset of the participants (n\\u0026thinsp;=\\u0026thinsp;4, 2 males, 2 females), arterial blood samples were collected throughout both the scanning procedures. [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 volumes of distribution (\\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e) were calculated in the selected regions, including the cerebellum. \\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e is the ratio of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 concentration in tissue to [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 concentration in arterial plasma at equilibrium and was estimated with the two tissue compartment model (2TCM). However, arterial blood sampling was not available for both scans in three participants, leading us to primarily use [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 non-displaceable binding potential (\\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e) as the outcome measure for this study. \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e provides a measure of receptor availability in the brain regions, indicating the density of available receptors in relation to non-displaceable binding.\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eBP\\u003c/em\\u003e \\u003csub\\u003eND\\u003c/sub\\u003e and \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e were estimated using the Simplified Reference Tissue Model\\u003csup\\u003e\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e\\u003c/sup\\u003e with the cerebellum as the reference region. While the cerebellum is commonly used as a reference region due to its minimal specific binding\\u003csup\\u003e\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e\\u003c/sup\\u003e, there is evidence for small amounts of mGluR5-specific binding, which could bias \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e estimates (see Discussion). \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e values, defined as the ratio of rate constants (\\u003cem\\u003eK\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e) describing tracer influx from plasma to the target region and to the reference region, were also estimated. The \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e value quantifies relative radiotracer delivery to different brain regions. Since [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 has high first-pass extraction\\u003csup\\u003e\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e\\u003c/sup\\u003e, \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e provides a proxy measure of relative blood flow as complements to \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e analyses, providing a more comprehensive understanding of the acute effects of alcohol on brain function.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e \\u003cp\\u003eSeparate linear mixed-effect models were employed for the statistical analysis of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e and \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e, following confirmation of the data's normal distribution. The constructed model incorporated \\u003cem\\u003ePET state\\u003c/em\\u003e (baseline vs. post-alcohol) and \\u003cem\\u003eRegion\\u003c/em\\u003e as fixed effects, along with their interaction, while a random intercept accounted for individual variability (PatientID). Post hoc pairwise comparisons (Fisher\\u0026rsquo;s Least Significant Difference) were utilized to determine the impact of alcohol on the frontal cortex, temporal cortex, hippocampus, and striatum.\\u003c/p\\u003e \\u003cp\\u003eAlcohol-induced Δ\\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e and Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e were quantified as percentage differences ([Post-alcohol \\u0026ndash; Baseline]/Baseline * 100). Exploratory analyses examined potential relationships between Δ\\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e and Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e with the following factors: (1) subjective alcohol effects, (2) peak BAL, and (3) self-reported alcohol consumption over the past month. These analyses were designed to test hypotheses concerning the mGluR5 response to alcohol: (1) its association with subjective alcohol responses, (2) its dependence on alcohol dosage, and (3) its correlation with recent drinking history. Subjective effects analyses focused on stimulation during the ascending limb (30-minute intervals of BAES stimulation, DEQ FEEL, and DEQ HIGH) and sedation during the descending limb (150-minute and 210-minute intervals of BAES sedation). Further partial correlation analyses, controlling for baseline subjective effects, were conducted to explore the associations between Δ\\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e and Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e and BAL measures, as well as recent drinking history. Given the exploratory nature of these analyses, Spearman rank correlation coefficients (Spearman\\u0026rsquo;s rho) were calculated without correction for multiple comparisons.\\u003c/p\\u003e \\u003cp\\u003eScan characteristic and \\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e value comparisons were made using paired t-tests. Statistical analyses were performed using R 4.2.2 (\\u0026ldquo;Innocent and Trusting\\u0026rdquo;) and RStudio (RStudio Team, Boston, MA, USA), with data visualization carried out using GraphPad Prism (v. 9.4.1; GraphPad Software, San Diego, CA, United States).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eParticipant demographics and characteristics\\u003c/h2\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eParticipant demographics and scanning parameters\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"2\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e27.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6 years (range: 22\\u0026ndash;42)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSex\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3M; 4F\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNumber of drinks in the last 30 days on Scan Day\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;20 drinks (range: 2\\u0026ndash;53)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAUD status (DSM-5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 Mild AUD (1F)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePeak BAL\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e61\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;18 mg/dL (n\\u0026thinsp;=\\u0026thinsp;7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDays between scan\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e17\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;8 days (range: 7\\u0026ndash;29)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eInjected dose\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBaseline: 614.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;62 MBq (range: 530\\u0026ndash;684)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePost-alcohol: 638\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;53 MBq (range: 529\\u0026ndash;688)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eInjected mass\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBaseline: 0.36\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.1 \\u0026micro;g (range: 0.19\\u0026ndash;0.43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePost-alcohol: 0.39\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.1 \\u0026micro;g (range: 0.27\\u0026ndash;0.54)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eScan Start Time of Dat\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBaseline: 12:17 (range: 11:55\\u0026thinsp;\\u0026minus;\\u0026thinsp;12:35)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePost-alcohol: 12:24 (range: 11:59\\u0026thinsp;\\u0026minus;\\u0026thinsp;12:36)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eAbbreviations: AUD, Alcohol Use Disorder; F, female; M, male; No significant differences were noted in the [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 injected dose or mass.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eEight participants (3 males, 5 females) enrolled in the study. One female met DSM-5 criteria for mild alcohol use disorder. One participant did not complete the study, vomiting during the laboratory alcohol session, with a peak BAL of 33 mg/dL at 120 minutes. This participant was excluded from the final analysis. The final analysis included seven participants (3 males, 4 females) with an average age of 27.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6 years. These participants reported consuming an average of 22\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;20 drinks in the last 30 days. During the laboratory drinking session, males consumed 150.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11 mL of 80-proof alcohol, while females consumed 111.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;20 mL. The average peak BAL among the included participants was 61.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;18 mg/dL, exhibiting a typical biphasic BAL curve (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Behavioral data indicated that alcohol consumption led to a decrease in stimulation and increase in sedation, as measured by the BAES, and in subjective feelings of intoxication, as FEEL and HIGH measured by the DEQ (Supp. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). For PET scans, no significant differences were observed in injected activity, injected mass, or the time of scan between the baseline and post-alcohol scans (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eUsing the Cerebellum as a reference region\\u003c/h3\\u003e\\n\\u003cp\\u003eAnalysis of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e was restricted to the four people for which arterial input function was acquired for both scans (see Supp. Table. 1). The cerebellum exhibited little change from baseline (1.95\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.4; range\\u0026thinsp;=\\u0026thinsp;1.66\\u0026ndash;2.44) compared with post-alcohol (2.03\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.3; range\\u0026thinsp;=\\u0026thinsp;1.71\\u0026ndash;2.46), with an overall change of 4.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4% (range\\u0026thinsp;=\\u0026thinsp;0.07\\u0026ndash;8.58%), within the reported cerebellum [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e test-retest variability of 13%\\u003csup\\u003e28\\u003c/sup\\u003e. This result was taken to support use of the cerebellum as a reference region for this study design.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAcute alcohol decreases brain mGluR5 availability\\u003c/h2\\u003e \\u003cp\\u003eBrain mGluR5 availability, quantified by [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e, significantly decreased post-alcohol compared to baseline. The main effect of alcohol (F(1,42)\\u0026thinsp;=\\u0026thinsp;17.05, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) was statistically significant. The interaction between alcohol and region was not statistically significant (F(4,42)\\u0026thinsp;=\\u0026thinsp;0.57, p\\u0026thinsp;=\\u0026thinsp;0.632), suggesting that the decrease in mGluR5 availability was potentially a whole-brain effect. On average, [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e values decreased by 9% post-alcohol compared to baseline, as illustrated in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e. Post hoc analysis revealed moderate effect sizes of alcohol in the following brain regions: frontal cortex (9.08% decrease, Cohen\\u0026rsquo;s d\\u0026thinsp;=\\u0026thinsp;0.49, p\\u0026thinsp;=\\u0026thinsp;0.015), temporal cortex (11.2% decrease, Cohen\\u0026rsquo;s d = -0.60, p\\u0026thinsp;=\\u0026thinsp;0.010), striatum (8.9% decrease, Cohen\\u0026rsquo;s d = -0.49, p\\u0026thinsp;=\\u0026thinsp;0.021), and hippocampus (6.6% decrease, Cohen\\u0026rsquo;s d = -0.32, p\\u0026thinsp;=\\u0026thinsp;0.317).\\u003c/p\\u003e \\u003cp\\u003eRelative blood flow, quantified by [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e, significantly increased post-alcohol compared to baseline. The main effect of alcohol (F(1,42)\\u0026thinsp;=\\u0026thinsp;6.69, p\\u0026thinsp;=\\u0026thinsp;0.013) was statistically significant, while the interaction between alcohol and region was not statistically significant (F(4,42)\\u0026thinsp;=\\u0026thinsp;0.08, p\\u0026thinsp;=\\u0026thinsp;0.970). Exploratory post hoc analysis revealed a significant increase in the striatum (2.59% increase, Cohen\\u0026rsquo;s d\\u0026thinsp;=\\u0026thinsp;0.46, p\\u0026thinsp;=\\u0026thinsp;0.046) but no significant changes in the frontal cortex, hippocampus, or temporal cortex (see Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eRelationship of [\\u003c/em\\u003e \\u003csup\\u003e \\u003cem\\u003e \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e \\u003c/em\\u003e \\u003c/sup\\u003e \\u003cem\\u003eC]ABP688 mGluR5 availability and relative blood flow with peak BAL, recent drinking behavior, and subjective effects\\u003c/em\\u003e \\u003c/p\\u003e \\u003cp\\u003eExploratory analyses revealed no significant relationships between Δ\\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e and peak BAL, past month number of drinks, or subjective effects such as BAES or DEQ. In contrast, there was initial evidence for significant (uncorrected for multiple comparisons) poasitive relationships between Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e and peak BAL in frontal cortex (Spearman rho\\u0026thinsp;=\\u0026thinsp;0.85; p\\u0026thinsp;=\\u0026thinsp;0.011) and temporal cortex (Spearman rho\\u0026thinsp;=\\u0026thinsp;0.78; p\\u0026thinsp;=\\u0026thinsp;0.024), as illustrated in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e. No other significant relationships were found between Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e and peak BAL, recent drinking amounts, or subjective effects like BAES or DEQ (Supp. Tables\\u0026nbsp;2 and 3).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study reveals evidence that a laboratory alcohol challenge achieving an average peak BAL of ~\\u0026thinsp;60 mg/dL significantly reduced brain mGluR5 availability, as measured by [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e. Further analyses yielded modest evidence that alcohol increased relative blood flow in cortical regions, as measured by [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e, with positive correlations between \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e increases and peak BAL, largely confirming prior findings. No significant associations were found between post-alcohol Δ\\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e or Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e and recent drinking behavior or subjective effects. The findings establish a novel imaging paradigm for investigating the dynamic effects of acute alcohol on brain glutamate function.\\u003c/p\\u003e \\u003cp\\u003eThis in vivo human evidence for imaging [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 response to alcohol aligns with preclinical rodent literature\\u003csup\\u003e\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e\\u003c/sup\\u003e, suggesting that alcohol-induced glutamate release contributes to the observed decrease in mGluR5 availability. Despite the preliminary nature of the data reported here, it is noteworthy that all subjects exhibited a consistent decrease in [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 binding. This uniformity in response supports the reliability of our findings and underscores the potential of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 PET imaging to measure alcohol-induced changes in mGluR5 availability, although the results should be validated in larger cohorts. A plausible mechanism for this finding is that increases in glutamate cause mGluR5s to internalize within the cell membrane, and these receptors are no longer available for [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 binding since this radiotracer targets an allosteric site on mGluR5 on cell surface receptors only\\u003csup\\u003e\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e\\u003c/sup\\u003e. This decrease in [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e following acute alcohol highlights potential disruptions in glutamate signaling pathways, which are essential for synaptic plasticity and cognitive functions\\u003csup\\u003e\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u003c/sup\\u003e. Such disruptions can lead to long-term changes in glutamate function and behavior associated with AUD and subsequent recovery\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e\\u003c/sup\\u003e, and are important areas of research for future studies leveraging this imaging paradigm as is evaluation of targeted therapies aimed at modulating glutamate signaling to treat or prevent AUD.\\u003c/p\\u003e \\u003cp\\u003eThe primary outcome measure for this study was [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e using the cerebellum as a reference region. This allowed for use of the full dataset, as arterial blood sampling was available for both baseline and challenge studies in only 4 participants. The cerebellum contains small but significant [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 specific binding, which could introduce systematic biases and potentially reduce the accuracy of detected associations\\u003csup\\u003e\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e\\u003c/sup\\u003e. Cerebellum [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e values were carefully examined in the data and no significant changes were found after the acute alcohol, supporting validity of this reference region in the context of this challenge. Should alcohol indeed cause small reductions in cerebellum [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 specific binding, this would cause underestimation of decreases in [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e, increasing confidence for using this analytic approach in the context of alcohol challenge. Indeed, [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e values derived using the cerebellum correlate well with those obtained from arterial input\\u003csup\\u003e\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e\\u003c/sup\\u003e, and the inherent variability of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eV\\u003c/em\\u003e\\u003csub\\u003eT\\u003c/sub\\u003e values\\u003csup\\u003e\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e\\u003c/sup\\u003e are poorer than that of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e\\u003csup\\u003e\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e\\u003c/sup\\u003e. Future investigations into alcohol's effects on these areas may require larger sample sizes to strengthen statistical confidence in the findings. Taken together, this supports use of [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e as the primary outcome for this study, although caution must be used when interpreting study results.\\u003c/p\\u003e \\u003cp\\u003ePrevious human imaging studies with PET\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR46 CR47\\\" citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e\\u003c/sup\\u003e and arterial spin labeling\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR24\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e\\u003c/sup\\u003e have shown that alcohol stimulates cortical gray matter hemodynamics across varying BALs. In line with these findings, our study observes a modest increase in [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e values, which represent relative blood flow. This increase in \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e highlights the vasodilatory effect of acute alcohol consumption. Importantly, a strong positive correlation was found between peak BAL and Δ\\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e1\\u003c/sub\\u003e, particularly in cortical gray matter regions, similar to previous studies\\u003csup\\u003e\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e\\u003c/sup\\u003e. These findings highlight the necessity of accounting for regional blood flow alterations when studying alcohol's impact on the brain, especially in fMRI studies of both resting state and task-based activities, as well as in multimodal (including PET and fMRI) approaches\\u003csup\\u003e52\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eIn conclusion, this study provides in vivo human evidence that an oral alcohol challenge decreased [\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e values in cortical and subcortical regions, which may reflect glutamate fluctuations in the brain as previously reported in preclinical studies. These results establish a novel imaging paradigm that allows for the examination of the dynamic effects of acute alcohol on human brain glutamate function and investigate glutamatergic underpinnings of AUD. This study advances the field\\u0026rsquo;s knowledge of the acute effects of alcohol on the brain and the associated glutamate response, providing a foundation for future research in this area.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003eAcknowledgements\\u003c/p\\u003e\\n\\u003cp\\u003eWe express our gratitude to the exceptional staff at the Yale PET Center for their expertise and support in radiochemistry, metabolite analysis, and image acquisition. We also extend our thanks to the personnel at the Clinical Neuroscience Research Unit at the Connecticut Mental Health Center and the Hospital Research Unit at the Yale Clinical Center for Investigation for their assistance with participant monitoring and evaluation.\\u003c/p\\u003e\\n\\u003cp\\u003eFunding\\u003c/p\\u003e\\n\\u003cp\\u003eWe gratefully acknowledge the funding support from the National Institute on Alcohol Abuse and Alcoholism (K01AA024788; P50AA012870; K24031345) and State of Connecticut Support for the Clinical Neuroscience Research Unit.\\u003c/p\\u003e\\n\\u003cp\\u003eCompeting interests\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare they have no competing financial and/or non-financial interests in relation to the work described herein.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eOlive MF, Cleva RM, Kalivas PW, Malcolm RJ. 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Effect of alcohol ingestion on regional cerebral blood flow. \\u003cem\\u003eInt J Neurosci\\u003c/em\\u003e. 1982;17(3):145-150. doi:10.3109/00207458208985916\\u003c/li\\u003e\\n\\u003cli\\u003eVolkow ND, Mullani N, Gould L, et al. Effects of acute alcohol intoxication on cerebral blood flow measured with PET. \\u003cem\\u003ePsychiatry Res\\u003c/em\\u003e. 1988;24(2):201-209. doi:10.1016/0165-1781(88)90063-7\\u003c/li\\u003e\\n\\u003cli\\u003eTolentino NJ, Wierenga CE, Hall S, et al. Alcohol effects on cerebral blood flow in subjects with low and high responses to alcohol. \\u003cem\\u003eAlcohol Clin Exp Res\\u003c/em\\u003e. 2011;35(6):1034-1040. doi:10.1111/j.1530-0277.2011.01435.x\\u003c/li\\u003e\\n\\u003cli\\u003eTiihonen J, Kuikka J, Hakola P, et al. Acute ethanol-induced changes in cerebral blood flow. \\u003cem\\u003eAm J Psychiatry\\u003c/em\\u003e. 1994;151(10):1505-1508. doi:10.1176/ajp.151.10.1505\\u003c/li\\u003e\\n\\u003cli\\u003eBjork JM, Gilman JM. The effects of acute alcohol administration on the human brain: insights from neuroimaging. \\u003cem\\u003eNeuropharmacology\\u003c/em\\u003e. 2014;84:101-110. doi:10.1016/j.neuropharm.2013.07.039\\u003c/li\\u003e\\n\\u003cli\\u003eSmart K, Worhunsky PD, Scheinost D, et al. Multimodal neuroimaging of metabotropic glutamate 5 receptors and functional connectivity in alcohol use disorder. \\u003cem\\u003eAlcohol Clin Exp Res\\u003c/em\\u003e. 2022;46(5):770-782. doi:10.1111/acer.14816\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"Yale School of Medicine\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"metabotropic glutamate type 5 receptors, positron emission tomography, alcohol challenge, glutamate release, social drinkers \",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5183167/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5183167/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground: \\u003c/strong\\u003eAlcohol consumption at clinically relevant doses alters brain glutamate release. However, few techniques exist to measure these changes in humans. The metabotropic glutamate receptor 5 (mGluR5) PET radioligand [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 is sensitive to acute alcohol in rodents, possibly mediated by alcohol effects on glutamate release. This study aimed to determine the sensitivity of [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 PET to an acute alcohol challenge in humans.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e Eight social drinkers (25–42 years; 5 females) with a recent drinking occasion achieving blood alcohol level (BAL)\\u0026gt;80 mg/dL were recruited. All participants underwent a 90-minute dynamic baseline [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 PET scan. Two weeks later (range: 7-29 days), participants completed an oral laboratory alcohol challenge over 30 minutes, targeting a BAL of 60 mg/dL. Immediately after the challenge, a second [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 PET scan was performed. Non-displaceable binding potential (\\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e; indicative of mGluR5 availability) and \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e\\u003cem\\u003e \\u003c/em\\u003e(indicative of relative blood flow) were estimated using the Simplified Reference Tissue Model with the cerebellum as the reference region. Blood samples were taken throughout the scanning procedure to measure the BAL.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e Seven participants (4 females) completed the study. The mean peak BAL achieved was 61 ± 18 mg/dL. Acute alcohol significantly decreased [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eBP\\u003c/em\\u003e\\u003csub\\u003eND\\u003c/sub\\u003e (F(1,42) = 17.05, p \\u0026lt; 0.001; Cohen’s d = 0.32–0.60) and increased [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e\\u003cem\\u003e \\u003c/em\\u003e(F(1,42) = 6.67, p = 0.013; Cohen’s d = 0.32–0.48) across brain regions. Exploratory analysis showed a positive relationship between alcohol-induced % change in [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 \\u003cem\\u003eR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e\\u003cem\\u003e \\u003c/em\\u003ein cortical regions and peak BAL (Spearman rho = 0.78 \\u0026amp; 0.85; p = 0.024 \\u0026amp; 0.011).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusions: \\u003c/strong\\u003eThis proof-of-concept study demonstrates that [\\u003csup\\u003e11\\u003c/sup\\u003eC]ABP688 PET imaging is sensitive to the effects of acute alcohol consumption. The observed decrease in mGluR5 availability aligns with preclinical data indicating acute increased extracellular glutamate concentrations following ethanol dosing. This imaging tool could be useful for future investigations into the acute effects of alcohol on the brain during abstinence and withdrawal.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Acute Alcohol-Induced Glutamate Changes Measured with Metabotropic Glutamate Receptor 5 Positron Emission Tomography\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-10-07 11:30:38\",\"doi\":\"10.21203/rs.3.rs-5183167/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"2e31d714-3173-440e-9a90-a9825a26ce16\",\"owner\":[],\"postedDate\":\"October 7th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":38387443,\"name\":\"Cellular \\u0026 Molecular Neuroscience\"}],\"tags\":[],\"updatedAt\":\"2024-10-07T11:30:39+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-10-07 11:30:38\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5183167\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5183167\",\"identity\":\"rs-5183167\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}