Alcohol cue-elicited reward activation is predictive of treatment response; thus demonstrating that functional neuroimaging can provide mechanistic data for AUD pharmacotherapy development. This may be particularly relevant in the case of IBUD, where the mechanism of action as an AUD treatment is currently unknown, but can be hypothesized to involve the striatum, which is activated in the alcohol cue-reactivity paradigm. Therefore, the present study sought to investigate the efficacy of IBUD to attenuate alcohol cue-elicited VS activation in individuals with AUD. The current study was an experimental medication trial of IBUD compared to placebo in non-treatment-seeking individuals with an AUD. To advance the development of IBUD as an AUD treatment, the present study examined the efficacy of IBUD, relative to placebo, to reduce negative mood and reduce heavy drinking as ≥5 drinks/day for men and ≥4 drinks/day for women over the course of 2-weeks. We hypothesized that ibudilast would reduce negative mood and decrease heavy drinking over the course of the study. To investigate the neural substrates underlying IBUD’s action, the present study also examined the effect of IBUD on neural alcohol cue-reactivity. We hypothesized that ibudilast would attenuate alcohol cue-elicited activation in the VS relative to placebo. Finally, this study explored the relationship between neural alcohol cuereactivity in the VS and drinking outcomes.Participants completed a series of assessments for eligibility and individual differences.
These measures included the Structured Clinical Interview for DSM-5, the Clinical Institute Withdrawal Assessment for Alcohol Scale – Revised, and the 30-day Timeline Follow back Interview for alcohol, cigarette, and cannabis. Participants also completed assessments regarding their alcohol use,vertical cannabis including: Alcohol Use Disorder Identification Test and Alcohol Dependence Scale, which measure severity of alcohol use problems, Penn Alcohol Craving Scale and Obsessive Compulsive Drinking Scale, which measure alcohol craving, and the Reasons for Heavy Drinking Questionnaire to assess withdrawal-related dysphoria, indicated by question #6: “I drink because when I stop, I feel bad ”. Participants also completed measures of smoking severity and depressive symptomology. At each in-person visit, participants were required to have a breath alcohol concentration of 0.00 g/dl and test negative on a urine toxicology screen for all drugs of abuse . Blood pressure and heart rate were assessed at screening and at each visit. Participants completed three in-person study visits occurring on Day 1 , Day 8 , and Day 15 . Randomization visits occurred on Mondays and Tuesdays to ensure that participants were at the target medication dose by the weekend. Side effects were elicited in open ended fashion and were reviewed by the study physicians . Adverse events were coded using the MedDRA v22.0 coding dictionary. Treatmentemergent adverse events were defined as adverse events that started after the first dose of the study drug or worsened in intensity after the first dose of study drug. Participants completed daily diary assessments, reporting on their past-day alcohol use, mood, assessed with a shortened form of the Profile of Mood States , and craving, assessed through a shortened form of the Alcohol Urge Questionnaire . Participants received daily text message reminders with links to these assessments.A set of generalized estimating equations with compound symmetric covariance structure were run in SAS 9.4 to account for repeated measures.
GEEs were selected as the analytical method because parameter estimates are consistent even when the covariance structure is mis-specified. As such, a compound symmetric covariance structure was chosen. Of note, due to missing data on all outcome and predictor variables, two participants were naturally excluded via list wise deletion for the GEE analysis. A GEE model was first run to assess the effect of medication on negative mood. The dependent variable, negative mood , was treated as continuous so a normal distribution with identity link function was chosen. A compound symmetric covariance structure was chosen to account for the repeated assessments. Independent variables for these analyses were medication , drinking day , and the interaction of medication by drinking day. Sex, age, depressive symptomology , and smoking status were examined as covariates; only significant covariates were retained in the final model to improve model clarity and ease of replication. A similar model was conducted to assess the effect of medication on craving, with the dependent variable being craving as measured by the AUQ. For both analyses, predicted means, standard errors, and 95% confidence intervals for negative mood and craving were calculated based on final models. The dependent variables for the drinking analyses were binary, such that 1 indicated a heavy drinking day or drinking day and a 0 indicated no heavy drinking or drinking, respectively. A binomial distribution with logit link function was chosen to model the binary dependent variable . Since participants were not on medication at baseline , this time point was excluded from the analysis. Independent variables included in the models were medication , time , and the interaction of medication by time. Baseline drinking information were also included in the model as a control.
As above, sex, age, depressive symptomology , and smoking status were examined as covariates; only significant covariates were retained in the final model to improve model clarity and ease of replication. For both analyses, predicted probabilities, standard errors, and 95% confidence intervals for heavy drinking and any drinking were calculated based on final models. A general linear model was used to evaluate the effect of medication on VS activation. The dependent variable was VS percent signal change between ALC and BEV blocks. Medication was the independent variable. Age, sex, depressive symptomology , and smoking status were examined as covariates; only significant covariates were retained in the final model. Finally, to evaluate if VS activation interacted with medication in predicting drinking in the week following the scan, a between-subject factor for VS activation was added to the model, along with a medication by VS activation split interaction. The dependent variable was drinks per drinking day in the last week of the study. Baseline drinks per drinking day were included as an additional covariate for this analysis.This was the first study to evaluate the effects of ibudilast, a neuroimmune modulator, on mood and drinking outcomes in a clinical sample with AUD. Contrary to our hypothesis, ibudilast did not have a significant effect on negative mood on drinking or non-drinking days. However, in support of our hypotheses, ibudilast significantly reduced the probability of heavy drinking compared to placebo. Ibudilast also significantly attenuatedalcohol cue-elicited activation in the bilateral VS. Furthermore, exploratory analyses indicated that ventral striatal activation to alcohol cues was predictive of drinking in the week following the neuroimaging scan. These results suggest a bio-behavioral mechanism through which ibudilast acts, namely,plant benches by reducing the rewarding response to alcohol cues in the brain leading to a reduction in heavy drinking per se. Unexpectedly, this study did not find support for an effect of ibudilast on negative mood or a moderating effect of baseline depressive symptomology on medication response. This contrasts with previous findings from our lab in which ibudilast improved mood response to stress and alcohol cues. The current study differs from the previous study in several important methodological variables including using a between-subjects instead of a crossover design and the use of a daily-diary mood reporting approach compared to tightly controlled human laboratory experimental paradigms. Furthermore, the current study did not directly evaluate the effect of drinking on mood, which would be more comparable to the findings reported previously. Additionally, this study recruited individuals with mild-to-severe AUD.
Negative mood states and negative reinforcement driven drinking may only occur at more severe presentations of AUD; therefore, the present study may have been under powered to identify medication effects on negative mood symptoms. Regarding the drinking outcomes in this study, IBUD significantly reduced the probability of heavy drinking compared to placebo. Specifically, individuals treated with IBUD were 45.3% less likely to drink heavily compared to individuals treated with placebo. This resulted in a 24% predicted probability of heavy drinking over the course of the study in the ibudilast group, compared with a 37% predicted probability in the placebo group. Of note, there were no significant differences in AE’s between groups, indicating that this reduction was not due to increased side effects, including nausea, in the IBUD group. There was not a significant effect of IBUD on the probability of overall drinking compared to placebo. While non-significant, the effect of IBUD for any drinking days was in the expected direction, such that individuals on IBUD were 16.9% less likely to engage in any drinking relative to placebo, but high variability in the prediction prevented conclusive statistical findings. This non-significant effect may not be surprising, as the study sample was comprised of non-treatment-seekers and therefore not motivated to abstain from drinking altogether. Rather, participants treated with IBUD reduced their heavy drinking, which produces a harm reduction benefit, particularly for those with a mild-tomoderate AUD. This finding is also consistent with preclinical studies, where treatment with ibudilast reduced ethanol intake by 50% under maintenance conditions. Importantly, the drinking results combined with the AE reports indicate that ibudilast is a safe medication for individuals who are still drinking and may want to reduce their drinking. IBUD also reduced craving on non-drinking days, at trend level, as compared to placebo. This effect supports our previous finding of a reduction in tonic craving under ibudilast during a week-long human laboratory study during which participants were instructed not to drink. This study also examined a potential bio-behavioral mechanism underlying IBUD’s action using an fMRI alcohol cue-reactivity paradigm. IBUD attenuated alcohol cue-elicited reward activation in the VS compared to placebo. PDE4 and PDE10 are highly expressed in the striatum and negatively regulate dopaminergic signaling. Thus, inhibition of these PDEs through IBUD may reduce striatal excitability to alcohol cues. In rats IBUD reduced morphine-induced nucleus accumbens dopamine release . Moreover, IBUD has been shown to enhance the production of neurotrophic factors, including glia-derived neurotrophic factor, which is a critical survival factor for dopamine neurons. Preclinical findings indicate that infusion of GDNF normalizes dopamine levels in the ventral tegmental area and the VS and reduces alcohol seeking and alcohol consumption. In humans with AUD, GDNF levels are reduced in blood serum samples. Furthermore, in individuals with AUD, presentation of alcohol cues reduced interleukin-10, an anti-inflammatory cytokine, and the level of reduction was correlated with increased alcohol craving. Thus, though the underlying molecular mechanism is still unknown, this finding indicates that ibudilast may normalize the dopaminergic response to alcohol cues in individuals with AUD. This study has several strengths and limitations which should be considered when interpreting the results. Study strengths include the use of daily diary reporting, which captures real world drinking and minimizes recall bias, and the combination of neurobiological with behavioral and self-report methodologies. However, this study recruited a non-treatment seeking sample; therefore, these findings may not generalize to a treatment-seeking sample with AUD . An ongoing randomized controlled trial of IBUD in treatment-seeking individuals with AUD will address this open question. Relatedly, this study recruited individuals with mild-to severe AUD, which may not be representative of clinical samples. This limitation may have impacted our ability to detect medication effects that require a pathology associated with more severe AUD, which is particularly relevant for negative mood and withdrawal states. Furthermore, participants were required to have a 0.00 g/dl breath alcohol reading for each in person visit. This requirement was to ensure participant safety; however, it may have artificially reduced drinking on in-person study visit days. Of note, in the daily diary assessment,participants reported on their past day drinking for the full day and were able to begin drinking when they returned home after the study visit. Additionally, the sample size for this experimental study was modest, particularly for the fMRI outcomes. This limited our ability to conduct additional, whole-brain analyses which are necessary to fully elucidate the neural mechanism of ibudilast. Finally, this study did not include a fixed-dose alcohol challenge to evaluate the safety and efficacy of ibudilast in combination with alcohol and to replicate our previous work. However, given that our sample did report drinking while taking ibudilast, we believe that ibudilast can be safely taken with alcohol with limited side effects. In conclusion, this is the first combined clinical and neuroimaging study of ibudilast , a neuroimmune modulator, to treat AUD.