Lara A. Ray

Study Objectives: Sleep disturbance is common in alcohol use disorder (AUD). Inflammation may play a role in the relationship between alcohol use and sleep disturbance. Interleukin-8 (IL-8), a pro-inflammatory chemokine, may be implicated in this relationship. Therefore, this study investigated the role of IL-8 in the relationship between AUD and sleep disturbance. Methods: Sixty-two individuals with AUD (35 M/27F) and sixty-four controls (33 M/31F) completed the Pittsburgh Sleep Quality Index (PSQI), a self-report questionnaire assessing past-month sleep quality and disturbances and provided blood samples to assess IL-8 levels. Univariate ANCOVAs compared groups on PSQI global scores and IL-8 levels. An indirect cross-sectional association analysis tested if diagnostic group and PSQI global scores were indirectly associated via IL-8 levels. Results: Individuals with AUD had higher PSQI global scores (F = 11.08, p = 0.001), indicating worse sleep, and higher IL-8 levels (F = 7.35, p = 0.008) compared to controls. AUD diagnosis was associated with higher IL-8 levels (a = 0.129, p = 0.008), and higher IL-8 levels were associated with worse PSQI scores (b = 3.157, p = 0.012). A partial indirect association effect was found where AUD diagnosis influenced PSQI scores through IL-8 levels (ab = 0.407, 95% CI = (0.062,0.905)); the direct effect of group on PSQI scores remained significant (c’ = 1.864, p = 0.005). Conclusions: Results suggest that AUD diagnosis is associated with worse sleep, partially through an association with greater IL-8 levels. Identifying a role for IL-8 as a link between AUD and sleep disturbance will need to be tested longitudinal studies. If replicated, IL-8 inhibition may offer a novel treatment target for those with AUD and comorbid sleep disorders. This paper is part of the Sleep and Circadian Mechanisms in Mental Health Collection.

Background: The neuropeptide oxytocin offers a potentially effective treatment for alcohol use disorder (AUD). Acting centrally in the brain, oxytocin mediates a range of behavioral effects, including reward, stress response, social affiliation, learning, memory, and addictive behaviors. Animal studies demonstrate oxytocin's ability to reduce alcohol consumption, but results in human trials have been mixed. Some studies report reductions in withdrawal symptoms, heavy drinking, and craving, whereas others show no effects. The purpose of this 12‐week clinical trial was to evaluate the efficacy and safety of intranasal oxytocin in individuals with AUD. Methods: Oxytocin (up to 70 International Units [IU]/day) or placebo was administered to 100 individuals diagnosed with AUD in a double‐blind, randomized, 12‐week multisite trial. The primary outcome was the weekly percentage of heavy drinking days (PHDD) over 10 weeks of maintenance treatment. Secondary outcomes included additional drinking measures, urge to drink, psychological assessments, alcohol‐related consequences, nicotine use, and safety and tolerability of intranasal oxytocin. Results: No significant differences were observed in PHDD between groups during the 10‐week maintenance phase. However, a small, numerically greater reduction in drinking was seen in the oxytocin group compared with placebo from weeks 9 to 12. Similar patterns were found across secondary drinking outcomes. No significant differences were observed in AUD symptoms, alcohol‐related consequences, craving, mood, sleep, pain, or substance use. At the end of treatment, participants receiving oxytocin scored significantly lower on measures of anger and physical aggression. Oxytocin was well tolerated; adverse events were mild and comparable across groups. The most common event in both groups was hyposmia. Conclusion: Intranasal oxytocin was well tolerated but did not significantly reduce drinking or AUD‐related outcomes. Higher doses, longer treatment duration, or larger trials may be required to identify responsive subgroups and determine oxytocin's efficacy in AUD. Trial Registration: ClinicalTrials.gov , Identifier: NCT03878316. Registered March 14, 2019 ( https://clinicaltrials.gov/ct2/show/NCT03878316 )

Background: The U.S. Food and Drug Administration (FDA) recommends a minimum duration of 6 months for randomized controlled trials (RCTs) evaluating pharmacotherapies for alcohol use disorder (AUD). The relationship between trial length and treatment effects is not well understood. The current study conducted meta‐regression analyses of RCTs for AUD to examine the association between trial length and observed medication effect sizes in clinical trials. Methods: This secondary data analysis utilized data from a systematic literature review that identified 139 pharmacotherapy RCTs for AUD conducted between 1985 and 2023. Meta‐regressions were conducted using the metafor package in R to examine whether shorter (< 12 weeks) or longer (> 12 weeks) trials differed in observed medication effect sizes for abstinence‐ and drinking‐based endpoints, relative to 12‐week trials, which represented the median trial duration. Publication bias was addressed using a weight‐function model. Results: For abstinence‐based endpoints, neither shorter (< 12 weeks; β = 0.13, SE = 0.21, p = 0.54) nor longer (> 12 weeks; β = 0.11, SE = 0.11, p = 0.30) trials differed significantly from the 12‐week reference group in observed medication effect sizes. Similarly, for drinking‐based endpoints, neither shorter (< 12 weeks; β = −0.07, SE = 0.09, p = 0.39) nor longer (> 12 weeks; β = 0.06, SE = 0.05, p = 0.26) trials differed significantly from 12‐week trials in observed medication effect sizes. All results remained nonsignificant after adjusting for publication bias. In sensitivity analyses restricted to trials with statistically significant effect sizes, trials > 12 weeks showed smaller estimated treatment effects compared to trials ≤ 12 weeks. Conclusions: Observed medication effect sizes did not differ significantly across trial lengths for abstinence and drinking‐based endpoints, except for analyses restricted to trials with significant effect sizes, where there was an advantage for trials that were 12 weeks or shorter. These findings inform efforts to optimize AUD RCT design.

Background: Cognitive behaviorally based interventions have broad appeal and potential for impact when treating adult alcohol and other drug use. Digitally delivered cognitive behaviorally based interventions (dCBIs) may offer this impact with the benefit of increased accessibility. Although prior reviews have indicated the benefits of dCBIs on substance use outcomes, the extension to psychosocial functioning outcomes is unknown. Objective: This meta-analysis provides an overview of dCBI effects across a range of functional end points. Methods: A literature search was conducted through October 2024. All primary and secondary reports of clinical trials of dCBI were obtained, and all available study end points were eligible for meta-analysis. Descriptive data were extracted and categorized into 1 of 13 different outcome types (eg, abstinence, quantity, cognitive, and quality of life) and into 2 broader outcome classes (ie, consumption and psychosocial). Robust variance estimation was used to conduct hypothesis tests on random effects pooled estimates with outcome class and comparison type as the primary subgroup variables of interest. Results: The study sample included 65 randomized trials (K=110 publications; 753 effect sizes) of dCBI for adult alcohol and other drug use. With respect to efficacy, dCBI as a stand-alone treatment in contrast to a minimal treatment control showed positive and statistically significant effects for consumption (g=0.27; P<.001; I2=85.1%; k=31; kes=134) and psychosocial (g=0.16; P=.008; I2=75.2%; k=16; kes=60) outcomes. As an addition to usual care, efficacy was demonstrated for consumption (g=0.23; P<.001; I2=9.8%; k=20; kes=65), but not psychosocial functioning. Efficacy compared to another digital or in-person intervention or cognitive behaviorally based intervention delivered by a therapist was not observed. Within the dCBI condition, large effect sizes were observed for both outcome classes (ie, 60%-80% of participants showed improvement relative to baseline), and effect size magnitude and statistical heterogeneity varied by the type of outcome examined. Conclusions: These results show a benefit for dCBI as a stand-alone therapy and an addition to usual care. Importantly, stand-alone effects were observed for both consumption and some psychosocial outcomes. This study is the first to offer a comprehensive look at dCBI intervention effects across a range of functional end points.

Background: In alcohol research studies, nonresponse is plausibly related to unobserved drinking scores. These so‐called missing not at random (MNAR) processes can reflect situations in which missingness is associated with the underlying level of drinking or changes in drinking over time. Examples include participants experiencing heavy drinking, increasing use or symptoms who may be less likely to report their behavior, and participants whose drinking improves substantially who disengage after achieving their goals or no longer perceiving a need for continued participation. Methods and Results: Calls for missing data sensitivity analyses have become increasingly common. To implement this approach, researchers compare models that make different assumptions about the missing data process and examine the stability of substantive conclusions across these alternatives. Sensitivity analyses are particularly valuable because assumptions about missing data are inherently untestable. However, clear guidance on how to implement them in practice remains limited. To address these recommendations and advance the application of sophisticated missing data methods in alcohol research, this paper provides a practical, step‐by‐step account of how to conduct such analyses. We focus on selection and shared parameter models because they align with the intuitive idea that a person's unobserved drinking behavior may influence the likelihood of nonresponse, either through individual change trajectories or recent episodic shifts in drinking behavior. Annotated scripts and output are provided in supplemental materials to support implementation. Although missing data assumptions did not appear to have a substantial impact, they easily could under slightly different conditions. Conclusions: Our sensitivity analysis strategy is applicable to a broad range of alcohol research settings. However, data‐specific features can meaningfully alter certain steps. We describe how aspects of our clinical trial illustration may or may not generalize to other alcohol research contexts, and we propose several recommendations for reporting the results of a sensitivity analysis.

Despite increasing attention to the neurobiology of alcohol use disorder (AUD), development of effective pharmacotherapies remains limited. Many medications with promising preclinical profiles fail to translate into clinical efficacy. This scoping review characterizes preclinical studies evaluating medications for AUD that have also been tested in human laboratory paradigms or clinical trials. We focus on two widely used paradigms: the two‐bottle choice (2 BC ) task, which measures alcohol consumption and preference, and operant reinstatement models, which capture relapse‐like behavior. A systematic search and data extraction identified preclinical studies using 2 BC and reinstatement paradigms to evaluate medications that progressed to human testing. Study characteristics (species, strain, sex, outcomes, and sample sizes) were recorded and effect sizes (corrected Cohen's d ) were summarized across outcome domains. Ninety‐two unique studies met criteria: 74 employing the 2 BC paradigm and 18 using operant reinstatement models, including 1731 animals. Rats were the most common species and sex bias was pronounced: 77 2 BC studies using only males, five only females, and all 18 reinstatement studies used male rats exclusively. For 2 BC consumption, the largest effects were observed for medications with limited studies, such as levetiracetam ( d = −4.58), while more extensively tested medications showed moderate effects, including prazosin ( d = −0.74) and naltrexone ( d = −0.63). For 2 BC preference, levetiracetam again showed a large effect in a single study ( d = −4.29). In reinstatement models, rimonabant showed the largest effect ( d = −3.11), while naltrexone ( d = −0.70), baclofen ( d = −1.05), and varenicline ( d = −0.72) had moderate effects. This review highlights substantial heterogeneity in study design and underutilization of reinstatement and female animals. Medications with moderate, replicable preclinical effects, especially those tested across both 2 BC and reinstatement models, may hold greater translational promise. These findings offer key opportunities for enhancing the translational alignment of preclinical AUD pharmacotherapy research.

Background and aims: The alcohol cue‐reactivity paradigm is widely used to test the initial efficacy of potential medications for alcohol use disorder (AUD); however, there is limited quantitative evidence demonstrating that medication effects on cue‐induced craving are associated with efficacy in clinical trials. This meta‐analysis examined whether medication effects on cue‐induced alcohol craving are associated with medication effects in randomized clinical trials (RCTs). Methods: Follow‐up meta‐analysis of RCTs. Participants included people who engaged in heavy drinking or have AUD. Medications were compared with a placebo control. We computed medication effect sizes (Cohen's d ) for cue‐induced craving (k _{# of studies} = 36 studies; 15 medications) and for the following individual RCT endpoints (k _{# of studies} = 139 studies; 19 medications): percent days abstinent, percent heavy drinking days, the percentage of participants who returned to any drinking, the percentage of participants who returned to heavy drinking, drinks per day and drinks per drinking day. We applied Williamson‐York regression models to test the relationship between medication effects on cue‐induced craving and the six individual RCT endpoints. One‐sided P values were used to test directional hypotheses and two‐sided P values were also reported to allow for exploratory interpretation. Results: Medication effect sizes on cue‐induced craving were positively associated with medication effect sizes on percent participants who returned to heavy drinking [ = 1.06, standard error (SE) = 0.63, one‐sided P = 0.04, two‐sided P = 0.09; k _{# of effect size} = 74; 7 medications] in RCTs but no other RCT endpoints tested. Specifically, medications that reduced cue‐induced craving in the human laboratory also decreased the percentage of participants who returned to heavy drinking in RCTs. Conclusions: Medications that produce greater reductions in cue‐induced alcohol craving appear to be associated with lower rates of return to heavy drinking, but not consistently with other drinking outcomes. This pattern indicates that the cue‐reactivity paradigm has limited and outcome‐specific translational validity rather than functioning as a universal indicator of clinical efficacy.

Background: Alcohol use disorder (AUD) represents a highly prevalent, costly, and often untreated condition in the United States. Post-traumatic stress disorder (PTSD) represents a common comorbidity with AUD which worsens outcomes and decreases functional outcomes. Suvorexant (SUV) shows clear promise as a novel therapeutic candidate to treat AUD and PTSD. Methods: This study features a promising compound (i.e., suvorexant), the application of a well-established human laboratory paradigm (i.e., alcohol cue reactivity), and a novel early efficacy laboratory model (i.e., practice quit attempt) to provide a cost/time-efficient evaluation of safety and initial efficacy of suvorexant for AUD with comorbid PTSD. Additionally, by collecting both objective and subjective sleep measures, the study provides an assessment of a putative mechanism through which suvorexant jointly addresses an intervening variable common to both AUD and PTSD. Discussion: The combination of human laboratory modeling and real-world clinical outcomes provides a unique and synergistic set of data that can advance the development of suvorexant and identify its behavioral mechanisms of action. The recruitment of individuals with AUD and PTSD with sleep disturbances and who are intrinsically motivated to quit is a novel approach to screening pharmacotherapies by bridging the gap between experimental studies with non-treatment seekers and clinical trials with treatment-seeking individuals. Trial registration: ClinicalTrials.gov NCT06679062 “Suvorexant for Treatment of AUD and PTSD (SUV).” Registered on November 12, 2024.

27.1 million adults in the United States have alcohol use disorder (AUD). However, current medications for AUD have mixed efficacy. As such, a shift in treatment approach and the development of novel pharmacotherapies for AUD is imperative. This review addresses novel insights on treating AUD through precision medicine that identifies subgroups of individuals most responsive to existing single or combination pharmacotherapies for AUD. In parallel, this review synthesizes the emergence of pharmacological agents for AUD that are on the treatment horizon. These include glucagon-like peptide 1 receptor agonists, classic psychedelics, ketamine, immune modulators, and cannabinoids. Data reviewed were culled from searches of the PubMed database and clinicaltrials.gov registry. Adopting a precision medicine approach and investigating novel compounds for AUD treatment requires a shift in systems of care. Precision medicine navigates away from the traditional 'one size fits all' health care model to emphasize the individual, leading to long-term cost-effectiveness and improved patient outcomes. Moreover, novel pharmacotherapies face challenges in the scale of their distribution throughout healthcare settings. The developments reviewed in this paper elucidate a paradigm shift necessary to facilitate the integration of precision medicine and the adoption of novel pharmacotherapies within the AUD field.