The effect of neuroimmune modulation on subjective response to alcohol in the natural environment.

BACKGROUND: Despite the promising implications for novel immune therapeutics, few clinical trials have tested these therapies to date. An understanding of how immune pharmacotherapies influence complex alcohol use disorder (AUD) profiles, including subjective response to alcohol, is very limited. Initial findings show that ibudilast, a neuroimmune modulator, reduces rates of heavy drinking and measures of alcohol craving. METHODS: This study is a secondary analysis of a 2-week clinical trial of ibudilast that enrolled a nontreatment-seeking sample with AUD. Eligible participants (N = 52) were randomized to receive ibudilast or matched placebo and completed daily diary assessments (DDAs) during the 2-week period. Each morning, participants reported on their mood and craving levels both before and during the previous day's drinking episode, as well as stimulation and sedation levels during the previous day's drinking episode. Multilevel models were used to compare the effects of ibudilast and placebo on subjective alcohol response. Exploratory analyses tested whether ibudilast moderated the relationship between daily stimulation/sedation and alcohol intake and whether withdrawal-related dysphoria moderated ibudilast's effects on subjective response. RESULTS: Ibudilast did not significantly alter mean levels of stimulation or sedation (p's > 0.05). It did, however, moderate the effect of daily stimulation on drinking (p = 0.045). Ibudilast attenuated alcohol-induced increases in craving compared with placebo (p = 0.047), but not other subjective response measures. Ibudilast significantly tempered daily alcohol-induced changes in urge to drink and positive mood only among individuals without withdrawal-related dysphoria. CONCLUSIONS: Ibudilast's effects on subjective alcohol responses appear to be nuanced and perhaps most salient for individuals drinking for positive reinforcement as distinguished from those who drink to feel normal. Consistent with previous findings, reductions in alcohol craving may represent a primary mechanism of ibudilast's effects on drinking. The ecologically valid nature of DDAs provide a clinically useful window into how individuals experience alcohol's effects while taking ibudilast.

Effect of alcohol, tobacco, and cannabis co-use on gray matter volume in heavy drinkers.

OBJECTIVE: Alcohol, tobacco, and cannabis are the three most frequently used drugs in the United States and co-use is common. Alcohol, tobacco, and cannabis use has been separately associated with altered brain structure, and alcohol and tobacco co-use results in decreases in gray matter volume. Less is known about the effect of alcohol and cannabis co-use, and alcohol, tobacco, and cannabis tri-use. Therefore, this study examined the effect of co- and tri-use on gray matter volume, a measure of brain cell density, in heavy drinkers. METHOD: Heavy drinkers (n = 237; 152m/85f; age = 32.52; white = 111; black = 28; Latino = 9; American Indian = 2; Pacific Islander = 4; Asian = 59; mixed = 15; other = 9) were classified into four groups based on their alcohol, tobacco, and cannabis use: alcohol only users (n = 70), alcohol and tobacco co-users (n = 90), alcohol and cannabis co-users (n = 35), and alcohol, tobacco, and cannabis tri-users (n = 42). All participants completed a structural MRI scan. Voxel-based morphometry was conducted to evaluate the effect of co-use on gray matter volume, with alcohol only users as the reference group. Age, sex, and scanner were included as covariates. RESULTS: Alcohol and tobacco co-users had significantly decreased left orbitofrontal gray matter volume relative to alcohol only users (Cohen's d = .79). There were no differences in gray matter volume between the alcohol only and alcohol and cannabis co-users, or between the alcohol only and tri-user groups. CONCLUSION: The additive effect of tobacco co-use on gray matter volumes in heavy drinkers was limited and localized. The effect of tri-use of alcohol, tobacco, and cannabis may have interacted, such that overlapping cannabis and tobacco use masked volume differences present in separate co-using groups. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Ibudilast, a neuroimmune modulator, reduces heavy drinking and alcohol cue-elicited neural activation: a randomized trial.

Ibudilast, a neuroimmune modulator which selectively inhibits phosphodiesterases (PDE)-3, -4, -10, and -11, and macrophage migration inhibitory factor (MIF), shows promise as a novel pharmacotherapy for alcohol use disorder (AUD). However, the mechanisms of action underlying ibudilast's effects on the human brain remain largely unknown. Thus, the current study examined the efficacy of ibudilast to improve negative mood, reduce heavy drinking, and attenuate neural reward signals in individuals with AUD. Fifty-two nontreatment-seeking individuals with AUD were randomized to receive ibudilast (n = 24) or placebo (n = 28). Participants completed a 2-week daily diary study during which they filled out daily reports of their past day drinking, mood, and craving. Participants completed an functional magnetic resonance imaging (fMRI) alcohol cue-reactivity paradigm half-way through the study. Ibudilast did not have a significant effect on negative mood (ß = -0.34, p = 0.62). However, ibudilast, relative to placebo, reduced the odds of heavy drinking across time by 45% (OR = 0.55, (95% CI: 0.30, 0.98)). Ibudilast also attenuated alcohol cue-elicited activation in the ventral striatum (VS) compared to placebo (F(1,44) = 7.36, p = 0.01). Alcohol cue-elicited activation in the VS predicted subsequent drinking in the ibudilast group (F(1,44) = 6.39, p = 0.02), such that individuals who had attenuated ventral striatal activation and took ibudilast had the fewest number of drinks per drinking day in the week following the scan. These findings extend preclinical and human laboratory studies of the utility of ibudilast to treat AUD and suggest a biobehavioral mechanism through which ibudilast acts, namely, by reducing the rewarding response to alcohol cues in the brain leading to a reduction in heavy drinking.

Baseline Drinking Patterns in Non-Treatment Seeking Problem Drinkers.

AIMS: Natural processes of change have been documented in treatment-seekers who begin to reduce their drinking in anticipation of treatment. The study examined whether non-treatment-seeking problem drinkers would engage in drinking reduction in anticipation of participating in a research study. METHODS: Non-treatment-seeking problem drinkers (n = 935) were culled from five behavioral pharmacology studies. Participants reported on their alcohol use during the past 30 days using the Timeline Followback. Cluster analysis identified distinct groups/clusters based on drinking patterns over the 30-day pre-visit period. The identified clusters were compared on demographic and clinical measures. RESULTS: Three distinct clusters were identified (a) heavy-decreasing drinking group (n = 255, 27.27%); (b) a moderate-stable drinking group (n = 353, 37.75%) and (c) low-stable drinking group (n = 327, 34.97%). The three clusters differed significantly on a host of measures including pre-visit drinking (age at first drink, drinking days, drinks per week, drinks per drinking day), alcohol use severity, alcohol craving, readiness for change, depression and anxiety levels. These differences were alcohol dose-dependent such that the heavier drinking group reported the highest levels on all constructs, followed by the moderate group, and the low drinking group last. CONCLUSIONS: Baseline drinking patterns of non-treatment-seekers were generally stable and pre-visit reductions were only observed among the heavy drinking group. This generally stable pattern stands in contrast to previous reports for treatment-seeking samples. Nevertheless, the heavier drinking group, which is most similar to treatment-seekers, displayed pre-study drinking reduction. Overall, naturalistic processes of change may pose less of a threat to randomization and testing in this population.

A novel human laboratory model for screening medications for alcohol use disorder.

BACKGROUND: Alcohol use disorder (AUD) is a highly prevalent, chronic relapsing disorder with a high disease burden in the USA. Pharmacotherapy is a promising treatment method for AUD; however, the few FDA-approved medications are only modestly effective. Medications development for AUD is a high priority research area, but the cumbersome drug development process hinders many potential compounds from reaching approval. One area with major opportunities for improvement is the process of screening novel compounds for initial efficacy, also known as early phase 2 trials. Early phase 2 trials incorporate human laboratory paradigms to assess relevant clinical constructs, such as craving and subjective responses to alcohol. However, these controlled paradigms often lack the ecological validity of clinical trials. Therefore, early phase 2 trials can be more efficient and clinically meaningful if they combine the internal validity of experimental laboratory testing with the external validity of clinical trials. To that end, the current study aims to develop and validate a novel early efficacy paradigm, informed by smoking cessation literature, to screen novel medications for AUD. As an established AUD medication, naltrexone will serve as an active control to test both the practice quit attempt model and the efficacy of a promising AUD pharmacotherapy, varenicline. METHODS: Individuals with current AUD reporting intrinsic motivation to change their drinking will complete a week-long "practice quit attempt" while on study medication. Participants are randomized and blinded to either naltrexone, varenicline, or placebo. During the practice quit attempt, participants will complete daily visits over the phone and fill out online questionnaires regarding their drinking, alcohol craving, and mood. Additionally, participants will undergo two alcohol cue-reactivity sessions. DISCUSSION: The successful completion of this study will advance medications development by proposing and validating a novel early efficacy model for screening AUD pharmacotherapies, which in turn can serve as an efficient strategy for making go/no-go decisions as to whether to proceed with clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT04249882 . Registered on 31 January 2020.

Inclusion of Cannabis Users in Alcohol Research Samples: Screening In, Screening Out, and Implications.

BACKGROUND: Alcohol and cannabis are frequently co-used, as 20-50% of those who drink alcohol report co-using cannabis. This study is based on the argument that alcohol researchers should enroll cannabis users in human laboratory studies of alcohol use disorder (AUD) to strengthen generalizability. This study examines how heavy drinking cannabis users differ from non-cannabis using heavy drinkers. METHODS: In a community sample of non-treatment-seeking heavy drinkers (n = 551, 35% female), cannabis users were identified through: (a) self-reported cannabis use in the past 6 months and (b) positive urine toxicology test for tetrahydrocannabinol (THC). Cannabis users, identified as described previously, were compared with non-cannabis users on demographic and clinical characteristics. RESULTS: Those who endorsed cannabis use in the past 6 months reported more binge drinking days. Participants who tested positive for THC had higher Alcohol Use Disorder Identification Test scores and more binge drinking days. Younger age and being a tobacco smoker were associated with an increased likelihood of cannabis use in the past 6 months, whereas male gender and being a tobacco use were associated with a greater likelihood of testing positive for THC. Individuals with cannabis use disorder (CUD) endorsed more depression and anxiety and had higher AUD symptom counts than cannabis users without CUD. CONCLUSIONS: The inclusion of cannabis users in AUD samples allows for increased clinical severity. Excluding cannabis users from AUD studies may limit representativeness and expend unnecessary study resources. Lastly, tobacco use may explain a large portion of the effects of cannabis use on sample characteristics. SHORT SUMMARY: Alcohol and cannabis are frequently co-used substances. In a sample of non-treatment-seeking heavy drinkers (n = 551, 35% female), cannabis users reported higher alcohol use and higher likelihood of tobacco use than non-cannabis users. Including cannabis users in alcohol research studies will improve representativeness and likely increase clinical severity.