Objective

Heavy drinking smokers experience significant difficulties with smoking cessation. Craving is closely tied to relapses during cessation attempts, and alcohol consumption increases cigarette craving among heavy drinking smokers. To date, however, few moderators of the relationship between craving and relapse have been identified. Individuals' capacity for distress tolerance predicts smoking cessation outcomes and may be connected to craving. Relatedly, pharmacotherapies like varenicline and naltrexone reduce cigarette and alcohol cravings, respectively. No studies have examined the interrelationships among distress tolerance, craving, and pharmacotherapy effects. This study therefore examines distress tolerance as a moderator of the relationship between overnight abstinence-induced cigarette craving and subsequent alcohol- and cigarette-induced changes in craving among heavy drinking smokers. This study also examines the impact of varenicline and naltrexone on these relationships.

Method

A total of 120 non-treatment-seeking heavy drinking smokers were randomized and titrated to one of the following conditions: (a) placebo, (b) varenicline, (c) naltrexone, or (d) varenicline + naltrexone. Participants then completed a laboratory paradigm after overnight abstinence that included consumption of alcohol (target .06 g/dl breath alcohol concentration) and one cigarette. Craving was assessed as abstinence-induced (Time 1), alcohol-induced (Time 2), and cigarette-induced (Time 3).

Results

Within varenicline + naltrexone, low distress tolerance individuals exhibited higher increases from abstinence- to alcohol-induced cigarette craving relative to high distress tolerance individuals. Across medications, low distress tolerance individuals reported flatter decreases from abstinence- to cigarette-induced cigarette craving relative to high distress tolerance individuals.

Conclusions

Distress tolerance may differentially predict alcohol-induced cigarette craving when titrated to pharmacotherapy, as well as moderate decreases in craving after cigarette consumption. Future exploration of the identified interactive effects could elucidate specific conditions in which cravings are more proximally related to abstinence-induced smoking.

Studies have implicated neuroinflammatory processes in the pathophysiology of various psychiatric conditions, including addictive disorders. Neuroimmune signaling represents an important and relatively poorly understood biological process in drug addiction. The objective of this review is to update the field on recent developments in neuroimmune therapies for addiction. First, we review studies of neuroinflammation in relation to alcohol and methamphetamine dependence followed by a section on neuroinflammation and accompanying neurocognitive dysfunction in HIV infection and concomitant substance abuse. Second, we provide a review of pharmacotherapies with neuroimmune properties and their potential development for the treatment of addictions. Pharmacotherapies covered in this review include ibudilast, minocycline, doxycycline, topiramate, indomethacin, rolipram, anakinra (IL-1Ra), peroxisome proliferator-activated receptor agonists, naltrexone, and naloxone. Lastly, summary and future directions are provided with recommendations for how to efficiently translate preclinical findings into clinical studies that can ultimately lead to novel and more effective pharmacotherapies for addiction.

Background

Subjective responses (SRs) to alcohol have been implicated in alcoholism etiology, yet less is known about the latent factor structure of alcohol responses. The aim of this study was to examine the factor structure of SR using a battery of self-report measures during a controlled alcohol challenge.

Methods

Nontreatment seeking drinkers (N = 242) completed an intravenous alcohol challenge including the following SR measures: Biphasic Alcohol Effects Scale, Subjective High Assessment Scale, Profile of Mood States, Alcohol Urge Questionnaire, and single items assessing alcohol "Liking" and "Wanting." Ascending limb target breath alcohol concentrations were 0.02, 0.04, and 0.06, and descending limb target was 0.04 g/dl. Exploratory factor analyses were conducted separately on estimates of mean and dose responses on the ascending limb and on descending limb data. To examine the generalizability of this factor structure, these analyses were repeated in heavy drinkers (≥14 drinks/wk for men, ≥7 for women; n = 132) and light drinkers (i.e., nonheavy drinkers; n = 110).

Results

In the full sample, a 4-factor solution was supported for ascending limb mean and dose responses and descending limb data representing the following SR domains: Stimulation/Hedonia, Craving/Motivation, Sedation/Motor Intoxication, and Negative Affect. This 4-factor solution was replicated in heavy drinkers. In light drinkers, however, SR was better summarized by a 3-factor solution where ascending mean and descending limb responses consisted of Stimulation/Hedonia, Craving/Motivation, and a general negative valence factor, and dose responses consisted of a general positive valence factor, Sedation/Motor Intoxication, and Negative Affect.

Conclusions

These findings suggest that SR represents a multifaceted construct with consistent factor structure across both ascending and descending limbs. Further, as drinking levels escalate, more defined Craving/Motivation and negative valence dimensions may emerge. Longitudinal studies examining these constructs are needed to further our understanding of SR as potentially sensitive to alcohol-induced neuroadaptation.

Naltrexone (NTX) has been widely studied for the treatment of alcohol use disorder with overall support for its efficacy. The mechanisms of action of naltrexone are thought to involve attenuation of the hedonic effects of alcohol and potentiation of its aversive effects. In order to provide a quantitative estimate of the effects of naltrexone on subjective response to alcohol, the aims of this meta-analytic review are to examine the effects of naltrexone across four domains of subjective response. Meta-analyses of naltrexone effects on alcohol craving (k = 16, N = 686), stimulation (k = 15, N = 675), sedation (k = 18, N = 777), and negative mood (k = 9, N = 281) suggested that under laboratory conditions and compared with placebo, naltrexone reduces craving (Hedges g = -0.252; SE = 0.054; 95% CI, -0.375 to -0.130; P < 0.01), reduces stimulation (g = -0.223; SE = 0.067; 95% CI, -0.372 to -0.074; P < 0.01), increases sedation (g = 0.251; SE = 0.064; 95% CI, 0.112-0.389; P < 0.01), and increases negative mood (g = 0.227; SE = 0.047; 95% CI, 0.100-0.354; P < 0.01). Results were robust when drinks per month and alcohol dose were added to the models as covariates. The effects of naltrexone varied by severity of alcohol use with medication effects on craving and stimulation being observed in sample of both heavy drinkers and AUD individuals. These results are consistent with the hypothesized mechanisms of action of NTX, although the effects are of small magnitude. This meta-analysis aggregates across multiple human laboratory studies of NTX's effects on subjective response to alcohol, providing a comprehensive summary of a key mechanism of NTX efficacy, namely, alteration of the subjective experience of alcohol.

Behavioral pharmacology paradigms have been used for early efficacy testing of novel compounds for alcohol use disorder (AUD). However, the degree to which early efficacy in the human laboratory predicts clinical efficacy remains unclear. To address this gap in the literature we employed a novel meta-analytic approach. We searched the literature for medications tested for AUD using both behavioral pharmacology (i.e., alcohol administration) and randomized clinical trials (RCTs). For behavioral pharmacology, we computed medication effects on alcohol-induced stimulation, sedation, and craving during the alcohol administration (k = 51 studies, 24 medications). For RCTs, we computed medication effects on any drinking and heavy drinking (k = 118 studies, 17 medications). We used medication as the unit of analysis and applied the Williamson-York bivariate weighted least squares estimation to preserve the errors in both the independent and dependent variables. Results, with correction for publication bias, revealed a significant and positive relationship between medication effects on alcohol-induced stimulation (β = 1.18 p < 0.05), sedation (β = 2.38, p < 0.05), and craving (β = 3.28, p < 0.001) in the laboratory, and drinking outcomes in RCTs, such that medications that reduced stimulation, sedation, and craving during the alcohol administration were associated with better clinical outcomes. A leave-one-out Monte Carlo analysis examined the predictive utility of these laboratory endpoints for each medication. The observed clinical effect size was within one standard deviation of the mean predicted effect size for all but three pharmacotherapies. This proof-of-concept study demonstrates that behavioral pharmacology endpoints of alcohol-induced stimulation, sedation, and craving track medication effects from the human laboratory to clinical trial outcomes. These results apply to alcohol administration phenotypes and may be especially useful to medications for which the mechanisms of action involve alterations in subjective responses to alcohol (e.g., antagonist medication). These methods and results can be applied to a host of clinical questions and can streamline the process of screening novel compounds for AUD. For instance, this approach can be used to quantify the predictive utility of cue-reactivity screening models and even preclinical models of medication development.

Rationale

During a smoking quit attempt, a single smoking lapse is highly predictive of future relapse. While several risk factors for a smoking lapse have been identified during clinical trials, a laboratory model of lapse was until recently unavailable and, therefore, it is unclear whether these characteristics also convey risk for lapse in a laboratory environment.

Objectives

The primary study goal was to examine whether real-world risk factors of lapse are also predictive of smoking behavior in a laboratory model of smoking lapse.

Methods

After overnight abstinence, 77 smokers completed the McKee smoking lapse task, in which they were presented with the choice of smoking or delaying in exchange for monetary reinforcement. Primary outcome measures were the latency to initiate smoking behavior and the number of cigarettes smoked during the lapse. Several baseline measures of smoking behavior, mood, and individual traits were examined as predictive factors.

Results

Craving to relieve the discomfort of withdrawal, withdrawal severity, and tension level were negatively predictive of latency to smoke. In contrast, average number of cigarettes smoked per day, withdrawal severity, level of nicotine dependence, craving for the positive effects of smoking, and craving to relieve the discomfort of withdrawal were positively predictive of number of cigarettes smoked.

Conclusions

The results suggest that real-world risk factors for smoking lapse are also predictive of smoking behavior in a laboratory model of lapse. Future studies using the McKee lapse task should account for between subject differences in the unique factors that independently predict each outcome measure.

Background

Alcohol administration paradigms have been used for early efficacy testing of novel compounds for alcohol use disorder (AUD). There has been an ongoing debate about sample characteristics and methodological features that affect the likelihood of detecting an early efficacy signal for AUD medications. We conducted a meta-regression to test whether the drinking level of the study sample and the peak breath alcohol concentration (BrAC) in the alcohol administration study predict the efficacy of AUD pharmacotherapies on the subjective responses to alcohol.

Methods

We computed the effects of 21 medications on alcohol-induced stimulation, sedation, negative mood, and craving during alcohol administration in 49 studies.

Results

Meta-regression analyses indicated a significant and positive effect of pre-study drinks per month on alcohol-induced stimulation (β = 0.142, p < 0.0001), such that as drinking increases, the benefit of medication over placebo decreases. There was an effect of drinks per month on negative mood (β = -0.164, p = 0.0248), such that at higher levels of drinks per month, the effects of medications on negative mood are stronger. For sedation, there was an effect of peak BrAC (β = 0.119, p = 0.0002), such that at low levels of peak BrAC, the effects of medication on sedation were null. For craving, there was a peak BrAC × drinks per month interaction such that at low levels of BrAC, a heavier drinking sample is required to detect the effects of medication on craving. Sensitivity analyses comparing naltrexone studies and non-naltrexone studies suggested that naltrexone was less sensitive to drinks per month across subjective response domains.

Conclusions

These analyses show that design features are critical in studies that test the effects of medications on the subjective responses to alcohol. By specifying the significance and directionality of these effects, as well as the specific points in BrAC or drinks per month at which medication effects are detectable, the study offers recommendations for design features of alcohol administration studies that aim to inform AUD medication development.

Background

While methamphetamine (MA) and alcohol are often used in combination, little is known about the pattern of co-use between these substances. The goal of the present study is to examine the relationship between MA use and alcohol use in a community sample of non-treatment seeking regular MA users.

Methods

Participants completed a face-to-face assessment battery, which included a diagnostic interview for MA dependence and the timeline follow-back interview for both alcohol and MA use over the past 30 days. Sixty regular MA and alcohol users supplied data for 1800 person-days.

Results

Compared with non-drinking days, drinking days and binge drinking days increased the odds of same day MA use by 4.22 and 4.50 times, respectively (p's<0.0001). Further, binge drinking incrementally increased risk for MA use above and beyond the effects of drinking itself (p<0.0001). Lagged models revealed previous day MA use to predict following day MA use (p<0.0001), yet, after controlling for this relationship, neither previous day alcohol use nor previous day binge drinking predicted following-day MA use. Finally, the effect of binge drinking on MA use was stronger among individuals with lower MA dependence severity or higher alcohol problem severity (p's<0.05).

Conclusions

These results suggest that alcohol and MA are co-used in predictable patterns, and in particular, that binge drinking may be incrementally associated with the likelihood of MA use. Future studies are needed to explore the temporal relationship between alcohol and MA use within a given episode.