Abstract
Background and Aims:
Previous findings have been equivocal as to whether a single nucleotide polymorphism (rs2832407) in GRIK1, which encodes a glutamate receptor subunit, moderates the effects of topiramate treatment for drinking reduction. We leveraged intensive longitudinal data to provide greater precision and allow an examination of intermediate outcomes addressing this question. We used data from a randomized controlled trial (RCT) to test the hypotheses that topiramate treatment reduces daily heavy drinking, desire to drink, and positive alcohol expectancies and that these effects are stronger in rs2832407*C-allele homozygotes.
Design:
Secondary data analysis of a randomized controlled trial
Setting:
University of Pennsylvania Treatment Research Center in the United States of America
Participants/Cases:
Participants were 164 individuals (70.1% male, mean age=51.42, 36% rs2832407*C-allele homozygotes) who sought to reduce or stop drinking.
Intervention and Comparator:
Participants were assigned to medication (topiramate or placebo), with stratification by genotype group (CC vs. AA/AC) and treatment goal (reduce versus abstain).
Measurements:
Over the 12-week treatment period, participants completed daily interactive voice response (IVR) surveys.
Findings:
On any given day during treatment, participants who received topiramate had lower odds of IVR-reported heavy drinking (odds ratio [OR]=0.259, b(standard error [SE])=−1.351 (0.334), p<0.001) and lower levels of desire to drink (b(SE)=−0.323 (0.122), p=0.009) and positive alcohol expectancies (b(SE)=−0.347 (0.138), p=0.013) than those who received placebo. Participants who received topiramate also reported greater reductions in positive alcohol expectancies over the first 2 weeks of treatment than those who received placebo (b(SE)=−0.028(0.008), p=0.001), but topiramate did not impact the daily rate of change in heavy drinking or desire to drink. Genotype did not moderate the effects of topiramate on any outcomes examined (ps>0.05).
Conclusions:
Topiramate is an effective medication for individuals seeking to reduce heavy drinking. The effects are not moderated by the single nucleotide polymorphism rs2832407.
Keywords: topiramate, pharmacogenetics, intensive longitudinal methods, alcohol expectancies, craving
Few medications are approved by the U.S. Food and Drug Administration (FDA) or European Medicines Agency (EMA) to treat alcohol use disorder (AUD) (1). Because medications for AUD are only moderately efficacious (1), more effective medications and/or precision medicine approaches to improve treatment efficacy are needed (2).
Topiramate, approved for treating epilepsy, migraine, and weight loss (1,3), but not AUD, has nonetheless shown efficacy for treating AUD. A meta-analysis of randomized placebo-controlled trials (RCTs) of topiramate yielded small-to-moderate effects on abstinence, heavy drinking, and the biomarker γ-glutamyltranspeptidase (GGT) (4). In a network meta-analysis of pharmacotherapies for AUD, topiramate was associated with lower total alcohol consumption than placebo, naltrexone, and acamprosate (5). Topiramate’s effect could be due to its increasing GABAA neuronal activity and antagonism of glutamate receptors, specifically kainate receptors containing the GluK1 subunit (encoded by GRIK1) (3,6).
Previously, a single-nucleotide polymorphism (SNP) in GRIK1 was examined as a potential genetic moderator of topiramate response (7). In an RCT, individuals with the rs2832407*CC genotype who received topiramate experienced greater reductions in heavy drinking days and GGT than the placebo group, with no significant medication effects observed for A-allele carriers (8). In intensive longitudinal analyses rs2832407*C-allele homozygotes treated with topiramate experienced greater daily reductions in alcohol consumption, desire to drink, and positive alcohol expectancies than the placebo group or A-allele carriers (9). Thus, topiramate may exert effects by reducing craving and perceptions of the positive effects of alcohol.
However, a prospective pharmacogenetic RCT showed no significant interactive effect of topiramate and rs2832407 on heavy drinking days, although effects were in the hypothesized direction (6). Analyzing daily interactive voice response (IVR) surveys of daily drinking, desire to drink, and positive alcohol expectancies during treatment in this study could clarify inconsistent findings on the moderating effect of rs2832407 and elucidate mechanisms by which topiramate exerts effects, particularly among rs2832407*C-allele homozygotes. Intensive longitudinal data from pharmacotherapy and precision medicine trials (10,11) could increase the precision of outcomes by reducing recency and availability biases (11,12), yielding greater statistical power (10). Examining IVR-reported intermediate outcomes could show greater effects of topiramate among rs2832407*C-allele homozygotes, even without effects on alcohol consumption. Lastly, studying non-consumption outcomes can provide information on mechanisms of change and precision medicine targets.
Current Study
In this secondary data analysis project, we used IVR data from the prospective pharmacogenetic RCT (NCT02371889) to examine main effects of topiramate and interactive effects of rs2832407 and medication on trajectories of heavy drinking, desire to drink, and positive alcohol expectancies. We examined change in heavy drinking at the daily level of analysis, whereas the primary RCT (6) examined change in heavy drinking at the weekly level. We also examined intermediate, non-consumption outcomes, including desire to drink and positive alcohol expectancies, whereas the primary RCT did not. Although the analysis was not pre-registered and results should be considered exploratory, hypotheses were based on results from the RCT (6) and analyses of IVR data from a previous pharmacogenetic study (9). We hypothesized that topiramate would be associated with greater reductions in heavy drinking, desire to drink, and positive alcohol expectancies than placebo, with reductions most pronounced among rs2832407*C-allele homozygotes.
Materials and Methods
Overview of Procedures
Participants (N=164) were recruited at the University of Pennsylvania Treatment Research Center (Penn). The Penn Institutional Review Board approved the study. Participants completed telephone screening and an in-person visit that included written informed consent, a medical history, a blood sample for genotyping, questionnaires, interviews, physical examination, and urine drug screen. Participants were assigned to medication (topiramate versus placebo), using block randomization and stratification by genotype group (CC vs. AA/AC) and treatment goal (reduce versus abstain).
Participants were seen weekly for six weeks and the medication dosage was increased gradually from 25 mg/day to a maximum of 200 mg/day. The dosage was not increased or was reduced due to adverse effects. Participants were seen biweekly during the last six weeks and completed questionnaires, interviews, and medical management counseling (13).
Participants completed an IVR phone survey daily over the 12-week medication period, a method demonstrating acceptability, reliability, and potentially less underreporting of alcohol use than traditional calendar-based recall methods (12). Participants called between 1700 and 2100 hr to complete the IVR survey to allow schedule flexibility and before they were most likely to drink heavily. IVR procedures are described in Supplementary Materials.
Participants
Inclusion criteria were age 18–70; European ancestry (given population differences in allele frequencies); average weekly consumption of ≥24/≥18 standard drinks (men/women); a current DSM-5 AUD diagnosis (14); desire to reduce/stop drinking; 8th-grade reading level; no gross cognitive impairment; and not pregnant/planning to become pregnant. Exclusion criteria were a clinically-significant physical disease or psychiatric disorder; topiramate contraindications; current psychiatric medications; current diagnosis of drug dependence (other than nicotine); or urine drug screen positive for opioids, cocaine, benzodiazepines, barbiturates, or amphetamines. See the CONSORT diagram in the primary outcomes manuscript (6).
Measures and Materials
Baseline Measures
Alcohol consumption in the 90 days before the baseline appointment was measured using the Timeline Follow-Back (15), a retrospective calendar-based method, and GGT was used to confirm alcohol consumption biochemically. We used percent heavy drinking days (PHDD) as a covariate in study analyses.
IVR Measures
Participants reported the number of standard drinks of beer, wine, liquor, and “other beverages” consumed the previous day. The number of standard drinks (containing 14 g of ethanol (17)) reported for the previous day was recoded to a binary outcome of heavy drinking (4+/5+ drinks for women/men) to test the hypothesis that topiramate would impact heavy drinking (6) and because the daily drinking outcome was highly skewed (1.329; SE=0.024)1 (16).
Participants used a five-point response scale (0=definitely false, 4=definitely true) to rate three desire-to-drink questions adapted from the Alcohol Urge Questionnaire (18): “I didn’t feel like drinking today (reverse-scored),” “I could really use a drink today,” and “The idea of drinking today is appealing.” The three items were averaged.
A five-point scale (0 = not at all likely, 4 = extremely likely) was also used to answer two questions regarding participants’ expectations for drinking later in the night (adapted from (19)): “Likely to make me less tense and more relaxed” and “Likely to have a good time.” These items were averaged.
Data Analyses
We used data from two sources to determine the functional form for change in heavy drinking a priori to avoid overfitting the model to the treatment effects and overestimating the effect of topiramate on outcomes. First, daily drinking data from the control group was examined. Second, average changes in drinking reported in the primary pharmacogenetic RCT results (6) were used. Both sources showed large reductions in heavy drinking in the first two weeks of treatment and relative stability thereafter across treatment conditions and genotypic groups (6). Thus, we modeled change for the treatment period with two slopes: 1) the entire 84- day treatment period; and 2) the first two weeks of treatment, which we refer to as the early treatment period. We were most interested in examining the impact of topiramate and genotype on the rate of change over the entire treatment period; however, we included the slope for the early treatment period to characterize the shape of change in outcomes across the placebo and topiramate treatment conditions and genotype groups. Because topiramate dosage was titrated over six weeks, we conducted separate sensitivity analyses that estimated the initial slope separately for the first six weeks of treatment and the entire treatment period. Both the primary analyses examining the first two weeks and sensitivity analyses examining the first six weeks allowed us to assess the total effect of topiramate (i.e., main effects) and ascertain when they occur (i.e., overall, as an initial response to treatment and/or an increasing response across the entire treatment course). Penalized information criteria (i.e., Akaike and Bayesian information criteria) were used to compare the primary analyses with the sensitivity analyses modeling the slope for the first six weeks of treatment.
Using multilevel models, we examined the main effects of medication day (Level 1), treatment condition (coded 0=placebo, 1=topiramate; Level 2), and their interaction to determine whether topiramate-treated participants demonstrated greater reductions in heavy drinking, desire to drink, and positive alcohol expectancies than placebo-treated patients. These models controlled for Level 2 genotype (coded 0=A-allele carrier, 1=C-allele homozygote), sex (coded 0=female, 1=male), and baseline proportion of heavy drinking days (grand-mean centered). Next, we added the two-way interactions between treatment day and genotype and treatment condition and genotype, and the three-way interactions involving treatment day, treatment condition, and genotype to determine whether rs2832407*C-allele homozygotes who received topiramate reported the greatest reductions in outcomes. For each model, we included random intercepts and slopes and a lag 2 autocorrelation (see Supplementary Table 1).
Logistic regression was conducted in the R package lmer (20), and linear multilevel models in nlme (21). All models used restricted maximum likelihood (REML) estimation, which accounts for missing data in outcomes conditioning on all model predictors and weights for participants with more daily reports than others. A false discovery rate procedure (22) adjusted the p-value for multiple testing for each outcome.
Results
Descriptive Statistics, IVR Compliance, and Psychometric Properties
Participant baseline characteristics, medication adherence, and IVR outcomes are reported in Table 1. Individuals who received topiramate were less likely to be employed and to reach the full medication dosage than those who received placebo.
Table 1.
Descriptive statistics by treatment condition
| Total (N=164) | Topiramate Condition (n=82) | Placebo Condition (n=82) | |||||
|---|---|---|---|---|---|---|---|
| Person-Level Baseline Measures | Mean (SD) or n (%) |
Median (IQR) | Mean (SD) or n (%) |
Median (IQR) | Mean (SD) or n (%) |
Median (IQR) | χ2/t (df) |
| Male sex | 115 (70.1%) | 58 (70.7%) | 57 (69.5%) | 0.03 (1) | |||
| Married | 92 (56.1%) | 44 (53.7%) | 48 (58.5%) | 0.40 (1) | |||
| Employed full- or part-time | 127 (77.4%) | 58 (70.7%) | 69 (84.1%) | 4.22 (1)* | |||
| Hispanic | 6 (3.7%) | 4 (4.9%) | 2 (2.4%) | 0.69 (1) | |||
| Goal to abstain | 40 (24.4%) | 18 (22.0%) | 22 (26.8%) | 0.53 (1) | |||
| C-allele homozygotes | 59 (36.0%) | 30 (36.6%) | 29 (35.4%) | 0.03 (1) | |||
| Age | 51.42 (11.71) | 54 (43.25, 60) | 52.45 (10.55) | 54 (48, 60.25) | 50.39 (12.75) | 54 (40.75, 60) | −1.13 (156.5) |
| Years of education | 16.26 (2.41) | 16 (14, 18) | 16.16 (2.39) | 16 (14, 18) | 16.37 (2.45) | 16 (16, 18) | 0.55 (162) |
| Baseline PDD (%) | 87.11 (17.22) | 95.56 (79.44, 100) | 87. 56 (17.40) | 95.56 (83.33, 100) | 86.65 (17.13) | 94.44 (77.78, 100) | −0.34 (162) |
| Baseline PHDD (%) | 72.39 (25.39) | 76.67 (50.00, 98.89) | 75.38 (24.18) | 83.33 (56.11, 98.89) | 69.40 (26.35) | 70.56 (46.11, 98.89) | −1.51 (162) |
| IVR compliance (%) | 79.10 (22.42) | 85.71 (73.81, 94.94) | 79.70 (22.11) | 86.31 (72.32, 96.43) | 78.50 (22.84) | 84.52 (73.81, 94.05) | −0.34 (162) |
| Reached maximum dosage (200 mg) | 131 (79.90%) | 56 (68.3%) | 75 (91.5%) | 13.70 (1)** | |||
| Number of days adherent to medication | 74.46 (20.15) | 84 (81, 84) | 72.98 (20.85) | 84 (77, 84) | 75.94 (19.45) | 84 (82, 84) | 0.94 (160) |
| Person-Level Averages of IVR Measures | Mean (SD) or n (%) | Median (IQR) | Mean (SD) or n (%) | Median (IQR) | Mean (SD) or n (%) | Median (IQR) | t (df) |
| Average daily standard drinks1 | 4.29 (2.67) | 4.08 (2.48, 5.50) | 3.91 (2.66) | 3.53 (1.94, 4.78) | 4.67 (2.65) | 4.44 (2.74, 6.03) | 1.82 (162) |
| Percent heavy drinking days (%) | 44.55 (31.27) | 41.35 (16.67, 72.98) | 37.37 (29.56) | 31.04 (11.89, 55.58) | 51.73 (31.46) | 49.15 (23.67, 81.33) | 3.01 (162)** |
| Percent days drinking beer heavily (%) | 15.14 (26.31) | 1.62 (0.00, 16.19) | 12.05 (23.75) | 1.27 (0.00, 11.31) | 18.23 (28.44) | 3.68 (0.00, 23.45) | 1.51 (157.0) |
| Percent days drinking wine heavily (%) | 10.74 (19.53) | 1.43 (0.00, 12.45) | 9.69 (17.56) | 1.32 (0.00, 12.85) | 11.77 (20.98) | 1.77 (0.00, 12.66) | 0.68 (162) |
| Percent days drinking liquor heavily (%) | 10.28 (21.18) | 1.21 (0.00, 7.30) | 8.30 (17.59) | 1.22 (0.00, 6.91) | 12.27 (24.20) | 1.20 (0.00, 9.12) | 1.20 (147.9) |
| Desire to drink | 1.74 (0.77) | 1.77 (1.33, 2.21) | 1.60 (0.74) | 1.71 (1.09, 1.99) | 1.89 (0.77) | 1.92 (1.52, 2.28) | 2.50 (162)** |
| Positive alcohol expectancies | 1.48 (0.87) | 1.26 (0.90, 2.05) | 1.33 (0.81) | 1.20 (0.70, 1.93) | 1.64 (0.90) | 1.56 (0.94, 2.32) | 2.35 (162)* |
| Tension reduction expectancies | 1.60 (0.87) | 1.46 (1.01, 2.16) | 1.39 (0.85) | 1.21 (0.80, 1.97) | 1.81 (0.85) | 1.77 (1.10, 2.43) | 3.14 (162)** |
| Good time expectancies | 1.36 (0.94) | 1.11 (0.76, 2.04) | 1.26 (0.82) | 1.07 (0.56, 1.85) | 1.47 (1.03) | 1.20 (0.79, 2.22) | 1.42 (154.5) |
Note: IVR = interactive voice response; SD = standard deviation; IQR = interquartile range representing the difference between the 25th and 75th percentiles of the data; χ2 = chi-squared test statistic assessing differences between the topiramate and placebo conditions; t = t-value test statistic assessing differences between the topiramate and placebo conditions; df = degrees of freedom; PDD = percent drinking days; PHDD = percent heavy drinking days; IVR interactive voice response.
The reported values for standard drinks yesterday represent a winsorized variable, wherein extreme values greater than 30 drinks were recoded to 30 drinks.
p<0.05
p<0.01.
There were 10,897 observations across 164 participants, indicating overall completion of 79.10% of the total IVR days, nearing the recommended compliance rate of 80% (23). Sex, medication condition, treatment goal, baseline drinking, IVR-reported drinking, and IVR-reported desire to drink were not associated with average compliance rates (ps>0.05). Older age (r=0.35, p<0.001), lower IVR-reported positive alcohol expectancies (r=−0.25, p=0.001), days of full medication adherence (r=0.78, p<0.001), and reaching the maximum medication dosage (t(34.22)=−5.18, p<0.001) were associated with greater IVR compliance.
The intraclass correlations from unconditional models indicated that most of the variance in desire to drink (52.5%) and positive expectancies (68.2%) was between individuals. The remaining 47.5% in desire to drink and 31.8% in positive expectancies were within persons across time. We assessed scale reliability (ω) at the within- and between-person levels (24,25) using multilevelTools (26). For both desire to drink and expectancies, reliability was acceptable at the daily level of analysis (desire to drink: ω=0.668; positive expectancies: ω=0.632) and excellent at the between-person level (desire to drink: ω=0.898; positive expectancies: ω=0.911).
Heavy Drinking
The sample for the heavy drinking models comprised 10,852 Level-1 observations nested within 164 Level-2 individuals (99.6% of the 10,897 IVR surveys completed). Topiramate reduced the odds of heavy drinking on a given day by 74% over the entire treatment period (OR (95% CI)=0.259 (0.135, 0.498), p<0.001). The interactions between treatment condition and treatment day (OR (95% CI)=0.991 (0.981, 1.001), p=0.088) and treatment condition and early treatment day (OR (95% CI)=0.968 (0.915, 1.025), p=0.264) were not statistically significant (Table 2), indicating that the slope across time for the probability of heavy drinking did not significantly differ by treatment condition (Figure 1). The model jointly testing all genotype effects on changes in heavy drinking did not fit significantly better than that examining only treatment effects (χ2(5)=0.539, p=0.991). The three-way interactions of treatment day, treatment condition, and genotype were not significant.
Table 2.
Results from the multilevel logistic regression models examining the heavy drinking outcome
| Model 1 (Treatment Effects) |
Model 2 (Genotype Effects) |
|||||||
|---|---|---|---|---|---|---|---|---|
| Fixed Effects | Odds ratio | b (SE) | t-value1 | p-value | Odds ratio | b (SE) | t-value2 | p-value |
| Intercept | 1.161 | 0.150 (0.331) | 0.452 | 0.651 | 1.131 | 0.123 (0.357) | 0.344 | 0.731 |
| Treatment day | 0.991 | −0.009 (0.004) | −2.382 | 0.017 | 0.991 | −0.009 (0.005) | −2.037 | 0.042 |
| Early treatment day3 | 0.962 | −0.039 (0.021) | −1.853 | 0.064 | 0.962 | −0.038 (0.025) | −1.506 | 0.132 |
| Topiramate treatment | 0.259 | −1.351 (0.334) | −4.040 | <0.001 | 0.275 | −1.292 (0.416) | −3.103 | 0.002 |
| Genotype (C-allele homozygote) | 1.010 | 0.010 (0.298) | 0.033 | 0.974 | 1.092 | 0.088 (0.497) | 0.177 | 0.859 |
| Male sex | 0.998 | 0.002 (0.312) | 0.007 | 0.994 | 0.997 | −0.003 (0.312) | −0.009 | 0.993 |
| Baseline PHDD | 37.085 | 3.613 (0.579) | 6.244 | <0.001 | 37.033 | 3.612 (0.578) | 6.244 | <0.001 |
| Treatment day x topiramate | 0.991 | −0.009 (0.005) | −1.706 | 0.088 | 0.991 | −0.009 (0.007) | −1.403 | 0.161 |
| Early treatment day x topiramate | 0.968 | −0.032 (0.029) | −1.117 | 0.264 | 0.978 | −0.022 (0.036) | −0.608 | 0.543 |
| Treatment day x genotype | 1.001 | 0.001 (0.008) | 0.184 | 0.854 | ||||
| Early treatment day x genotype | 1.000 | −0.0004 (0.043) | −0.010 | 0.992 | ||||
| Topiramate x genotype | 0.848 | −0.165 (0.694) | −0.238 | 0.812 | ||||
| Treatment day x topiramate x genotype | 1.001 | 0.001 (0.011) | 0.057 | 0.955 | ||||
| Early treatment day x topiramate x genotype | 0.971 | −0.030 (0.061) | −0.488 | 0.626 | ||||
| Random Effects | Variance | SD | Correlation with intercept |
Variance | SD | Correlation with intercept |
||
| Intercept | 4.185 | 2.046 | 4.183 | 2.045 | ||||
| Treatment day | 0.001 | 0.026 | 0.50 | 0.001 | 0.026 | 0.50 | ||
| Early treatment day | 0.015 | 0.122 | 0.25 | 0.015 | 0.122 | 0.26 | ||
Note: Bold font indicates associations that are significant using false discovery rate correction (p≤.002) for all hypothesis tests. b = unstandardized regression coefficient; SE = standard error; SD = standard deviation; PHDD = percent heavy drinking days.
Level-1 degrees of freedom=10684, Level-2 degrees of freedom=159
Level-1 degrees of freedom=10680, Level-2 degrees of freedom=158.
Early treatment period refers to the daily rate of change over the first two weeks of treatment above and beyond the daily rate of change over the entire treatment period.
Figure 1. Predicted heavy drinking trajectories over the treatment period by treatment condition.
Note: This figure represents the main effect of topiramate on lower odds of heavy drinking over the entire treatment period (i.e., days 1-84; OR=0.259, b(SE)=−1.351(0.334), p<0.001), as well as the null interactions between treatment condition and treatment day (i.e., days 1-84; OR=0.991, b(SE)= −0.009(0.005), p=0.088) and early treatment day (i.e., days 1-14; OR=0.968, b(SE)= −0.032(0.029), p=0.264). Overall, this indicates that those in the topiramate condition had a lower probability of heavy drinking over the entire treatment period but that the daily rate of change in the probability of heavy drinking did not significantly differ between the two groups during the entire treatment period or the first two weeks of treatment.
Desire to Drink
The analyzed sample for the desire to drink models comprised 10,884 Level-1 observations nested within 164 Level-2 individuals (99.9% of the 10,897 IVR surveys completed). Topiramate treatment was associated with lower desire to drink (b(SE)=−0.323(0.122), p=0.009) across the entire treatment period (Table 3). However, there were no significant interactions between treatment day and treatment condition. Averaged across all treatment days, topiramate-treated individuals had lower desire to drink than placebo-treated individuals. However, the daily rate of change in desire to drink did not differ significantly by treatment condition (Figure 2). The model examining genotype effects on changes in desire to drink did not fit significantly better than that examining only treatment effects (χ2(5)=3.300, p=0.654) and three-way interactions of treatment day, treatment condition, and genotype on desire to drink were not significant.
Table 3.
Results from the multilevel linear regression models examining the desire to drink outcome
| Model 1 (Treatment Effects) |
Model 2 (Genotype Effects) |
|||||
|---|---|---|---|---|---|---|
| Fixed Effects | b (SE) | t-value1 | p-value | b (SE) | t-value2 | p-value |
| Intercept | 1.735 (0.122) | 14.228 | <0.001 | 1.711 (0.132) | 13.006 | <0.001 |
| Treatment day | −0.002 (0.001) | −2.098 | 0.036 | −0.002 (0.001) | −1.508 | 0.132 |
| Early treatment day3 | −0.022 (0.007) | −3.267 | 0.001 | −0.024 (0.008) | −2.833 | 0.005 |
| Topiramate treatment | −0.323 (0.122) | −2.643 | 0.009 | −0.309 (0.153) | −2.023 | 0.045 |
| Genotype (C-allele homozygote) | −0.093 (0.111) | −0.843 | 0.401 | −0.020 (0.182) | −0.111 | 0.912 |
| Male sex | 0.219 (0.116) | 1.888 | 0.061 | 0.216 (0.116) | 1.861 | 0.065 |
| Baseline PHDD | 0.516 (0.213) | 2.427 | 0.016 | 0.519 (0.213) | 2.432 | 0.016 |
| Treatment day x topiramate | 0.001 (0.001) | 0.669 | 0.503 | −0.001 (0.002) | −0.275 | 0.783 |
| Early treatment day x topiramate | −0.015 (0.010) | −1.551 | 0.121 | −0.014 (0.012) | −1.194 | 0.233 |
| Treatment day x genotype | −0.001 (0.002) | −0.315 | 0.753 | |||
| Early treatment day x genotype | 0.005 (0.014) | 0.361 | 0.718 | |||
| Topiramate x genotype | 0.043 (0.255) | −0.170 | 0.866 | |||
| Treatment day x topiramate x genotype | 0.004 (0.003) | 1.319 | 0.187 | |||
| Early treatment day x topiramate x genotype | −0.001 (0.020) | −0.072 | 0.943 | |||
| Random Effects | Variance | SD | Correlation with intercept |
Variance | SD | Correlation with intercept |
| Intercept | 0.582 | 0.763 | 0.586 | 0.765 | ||
| Treatment day | 0.0001 | 0.007 | 0.114 | 0.0001 | 0.007 | 0.115 |
| Early treatment day | 0.002 | 0.046 | 0.561 | 0.002 | 0.047 | 0.560 |
| Residual | 0.463 | 0.681 | 0.463 | 0.681 | ||
| Autoregressive Errors | Φ | Φ | ||||
| Correlation with one day before | 0.153 | 0.153 | ||||
| Correlation with two days before | 0.071 | 0.072 | ||||
Note: Bold font indicates associations that are significant using false discovery rate correction (p≤.009) for all hypothesis tests. b = unstandardized regression coefficient; SE = standard error; SD = standard deviation; Φ = autoregressive correlation; PHDD = percent heavy drinking days.
Level-1 degrees of freedom=10,716; Level-2 degrees of freedom=159
Level-1 degrees of freedom=10,712; Level-2 degrees of freedom=158.
Early treatment period refers to the daily rate of change over the first two weeks of treatment above and beyond the daily rate of change over the entire treatment period.
Figure 2. Predicted desire to drink trajectories over the treatment period by treatment condition.
Note: This figure represents the main effect of topiramate on lower levels of desire to drink over the entire treatment period (i.e., days 1-84; b(SE)=−0.323(0.122), p=0.001), as well as the null interactions between treatment condition and treatment day (i.e., days 1-84; b(SE)=0.001(0.001), p=0.503) and early treatment day (i.e., days 1-14; b(SE)=−0.015(0.010), p=0.121). Overall, this indicates that those in the topiramate condition had lower levels of desire to drink over the entire treatment period but that the daily rate of change in desire to drink did not significantly differ between the two groups during the entire treatment period or the first two weeks of treatment.
Positive Alcohol Expectancies
The sample for the positive alcohol expectancies models comprised 10,874 Level-1 observations nested within 164 Level-2 individuals (99.8% of the 10,897 IVR surveys completed). Topiramate was associated with lower positive alcohol expectancies across the treatment period (b(SE)=−0.347(0.138), p=0.013; Table 4). There was a significant interaction between treatment day and treatment condition during the early treatment period (b(SE)=−0.028(0.008), p=0.001), but not the overall treatment period (b(SE)=0.001(0.002), p=0.632; Figure 3). The model examining genotype effects on changes in positive alcohol expectancies did not fit significantly better than the model examining treatment effects (χ2(5)= 4.289, p=0.509). There were no three-way interactions of treatment day, treatment condition, and genotype.
Table 4.
Results from the multilevel linear regression models examining the positive alcohol expectancies outcome
| Model 1 (Treatment Effects) |
Model 2 (Genotype Effects) |
|||||
|---|---|---|---|---|---|---|
| Fixed Effects | b (SE) | t-value1 | p-value | b (SE) | t-value2 | p-value |
| Intercept | 1.421 (0.133) | 10.677 | <0.001 | 1.354 (0.145) | 9.317 | <0.001 |
| Treatment day | −0.004 (0.001) | −3.150 | 0.002 | −0.003 (0.001) | −2.291 | 0.022 |
| Early treatment day3 | −0.032 (0.006) | −5.328 | <0.001 | −0.037 (0.007) | −5.015 | <0.001 |
| Topiramate treatment | −0.347 (0.138) | −2.508 | 0.013 | −0.297 (0.173) | −1.719 | 0.088 |
| Genotype (C-allele homozygote) | −0.016 (0.116) | −0.138 | 0.891 | 0.179 (0.206) | 0.871 | 0.385 |
| Male sex | 0.232 (0.121) | 1.913 | 0.058 | 0.230 (0.122) | 1.889 | 0.061 |
| Baseline PHDD | −0.073 (0.223) | −0.327 | 0.744 | −0.073 (0.222) | −0.327 | 0.744 |
| Treatment day x topiramate | 0.001 (0.002) | 0.480 | 0.632 | −0.001 (0.002) | −0.381 | 0.703 |
| Early treatment day x topiramate | −0.028 (0.008) | −3.304 | 0.001 | −0.024 (0.011) | −2.300 | 0.021 |
| Treatment day x genotype | −0.001 (0.002) | −0.429 | 0.668 | |||
| Early treatment day x genotype | 0.016 (0.013) | 1.232 | 0.218 | |||
| Topiramate x genotype | −0.145 (0.288) | −0.504 | 0.615 | |||
| Treatment day x topiramate x genotype | 0.004 (0.003) | 1.257 | 0.209 | |||
| Early treatment day x topiramate x genotype | −0.010 (0.018) | −0.591 | 0.555 | |||
| Random Effects | Variance | SD | Correlation with intercept | Variance | SD | Correlation with intercept |
| Intercept | 0.759 | 0.871 | 0.762 | 0.873 | ||
| Treatment day | 0.0001 | 0.009 | 0.064 | 0.0001 | 0.009 | 0.069 |
| Early treatment day | 0.002 | 0.045 | 0.655 | 0.002 | 0.045 | 0.651 |
| Residual | 0.256 | 0.506 | 0.256 | 0.506 | ||
| Autoregressive errors | Φ | Φ | ||||
| Correlation with one day before | 0.163 | 0.163 | ||||
| Correlation with two days before | 0.067 | 0.067 | ||||
Note: Bold font indicates associations that are significant using false discovery rate correction (p≤.013) for all hypothesis tests. b = unstandardized regression coefficient; SE = standard error; SD = standard deviation; Φ = autoregressive correlation; PHDD = percent heavy drinking days.
Level-1 degrees of freedom=10706, Level-2 degrees of freedom=159
Level-1 degrees of freedom=10702, Level-2 degrees of freedom=158.
Early treatment period refers to the daily rate of change over the first two weeks of treatment above and beyond the daily rate of change over the entire treatment period.
Figure 3. Predicted positive alcohol expectancies trajectories over the treatment period by treatment condition.
Note: This figure represents the main effect of topiramate on lower positive alcohol expectancies over the entire treatment period (i.e., days 1-84; b(SE)=−0.347(0.138), p=0.013), a significant interaction effect between treatment condition and early treatment day (i.e., days 1-14; b(SE)=−0.028(0.008), p=0.001), and a null interaction between treatment condition and treatment day (i.e., days 1-84; b(SE)=0.001(0.002), p=0.632). Overall, this indicates that those in the topiramate condition had lower levels of positive alcohol expectancies over the entire treatment period and that the daily rate of change in positive alcohol expectancies was greater in the topiramate condition than in the placebo condition over the first two weeks of treatment, but not the entire treatment period.
Post Hoc Power Analysis and Sensitivity Analyses
Post hoc power considerations for the primary analyses and sensitivity analyses are presented in Supplementary Materials. We had 80% power to detect small-to-moderate effects for most interactions of interest that were not statistically significant in the present analysis for desire to drink and alcohol expectancies. Specifically, the effect sizes for the three-way interactions of topiramate treatment, genotype, and treatment day that we were powered to detect for these outcomes were approximately the same as the statistically-significant effect sizes reported in a prior pharmacogenetic trial of topiramate that analyzed intensive longitudinal data (9). Thus, it is unlikely that the null findings for these three-way interactions were due to inadequate power. The effect sizes we were powered to detect for the heavy drinking outcome are more difficult to contextualize. Because the prior pharmacogenetic trial of topiramate that analyzed intensive longitudinal data (9) examined drinking as a continuous outcome, effect sizes are not comparable.
Sensitivity analyses indicated additional covariates (i.e., cigarettes smoked, treatment goal, days of medication adherence, cannabis-positive urine drug screen) (Supplementary Tables 2-4) did not impact the findings. We also examined the positive alcohol expectancies outcomes (“Likely to make me less tense/more relaxed” and “Likely to have a good time”) separately, given research indicating differential medication response and drinking outcomes by tension reduction (negative reinforcement) and reward (positive reinforcement) expectancies (27-29). Topiramate impacted tension reduction more than reward expectancies (Supplementary Tables 5-6 and Figures 1-2). Lastly, we examined change in the titration period (first six weeks of treatment) in addition to the entire treatment period. The sensitivity analyses examining an alternative shape of change indicated no substantial improvement in model fit (Supplementary Table 7). Topiramate had a main effect on all outcomes examined (Supplementary Tables 8-10) and on the rate of change in positive alcohol expectancies over the first six weeks of treatment.
Discussion
We used daily IVR data from a prospective pharmacogenetic RCT to examine interactions between topiramate treatment and rs2832407 genotype on reductions in heavy drinking, desire to drink, and positive alcohol expectancies. Consistent with the primary study (6), the observed topiramate treatment effects on all outcomes did not depend on the rs2832407*CC genotype. Perhaps most notably, topiramate-treated participants had a 74% lower likelihood of heavy drinking over the treatment period than placebo —a large effect size. These findings add to the growing body of literature indicating that topiramate is an effective medication for individuals aiming to reduce heavy drinking (3,4).
The lack of a moderating effect of rs2832407 genotype in predicting daily alcohol-related outcomes is consistent with the primary study (6) and subsequent analyses that combined an initial pharmacogenetic trial and the recent prospective trial to increase statistical power (30). The findings are inconsistent with prior analyses of IVR data from retrospective analyses of an RCT of topiramate (9). The lack of a topiramate effect among rs2832407*C allele homozygotes reported here is notable, given that IVR could provide more data and greater power than methods typically used to quantify drinking in RCTs (10,11). Thus, prior findings indicating that topiramate is most effective among rs2832407*C allele homozygotes were likely spurious.
Topiramate-treated participants had lower positive alcohol expectancies than those who received placebo, which appeared to occur primarily in the initial weeks of treatment. Thus, topiramate could reduce drinking and/or desire to drink by modifying expectations of alcohol effects. Clinically, the initial response to topiramate could include reducing expectations that alcohol might produce positive effects. Future studies should explore the possibility that topiramate acutely impacts the reinforcing properties of alcohol and, thereby, positive alcohol expectancies, particularly given evidence that acute medication response could serve as a phenotype for matching patients to treatment (11).
Sensitivity analyses indicated that topiramate’s effects on tension reduction expectancies (“Likely to make me less tense and more relaxed”) were stronger than on reward expectancies (“Likely to have a good time”). These findings are somewhat contrary to prior literature suggesting that topiramate reduces the stimulating, but not the sedating effects of alcohol (31). Given topiramate has mood-stabilizing effects among patients with major depressive disorder (32), it may have modified negative affect among participants in the present study and, consequently, their expectations that alcohol would further reduce stress and tension. Some medications for treating AUD, such as naltrexone and acamprosate, have shown differential efficacy based on patients’ reward or relief motives for drinking (27,28,33,34), and future studies should determine whether different alcohol expectancies moderate topiramate treatment response. In addition, topiramate produces taste aversion to carbonated beverages by inhibiting carbonic anhydrase isoenzymes, rendering carbonated alcoholic beverages unpleasant (3). Topiramate may have decreased the palatability of beer, the most common beverage for heavy drinking during the treatment period (Table 1), and thereby decreased overall positive alcohol expectancies.
Topiramate treatment did not significantly influence the daily rate of change in heavy drinking or desire to drink. Nonetheless, topiramate-treated participants had a lower probability of heavy drinking and lower desire to drink on any given day over the entire treatment period than placebo-treated participants. Our analyses allowed us to assess the total effect of topiramate and ascertain when those effects occur. Interestingly, topiramate’s effect on heavy drinking and desire to drink occurred across the entire course of treatment, rather than primarily in the initial stages of treatment or increasing over time.
Limitations
Individuals who reached the maximum medication dosage and had more days with medication adherence also had greater IVR compliance rates, though including these variables in sensitivity analyses did not impact our findings. Although over 30% of patients in the topiramate treatment condition did not reach the maximum medication dosage, medication adherence was generally high, and in sensitivity analyses of medication adherence this variable was not statistically significantly associated with treatment outcomes and did not modify results. Our post hoc power analyses indicated we were powered to detect small-to-moderate effects of genotype on intermediate outcomes. Yet, these power analyses were more challenging to interpret for the heavy drinking outcome given the lack of published comparable data. Our primary outcomes, including alcohol use, were self-reported. This limitation is mitigated by the IVR methods, which asked participants to recall outcomes over short windows, and findings that self-reported alcohol use in an intensive longitudinal study demonstrated high correspondence with a biochemical measure of alcohol use (36). Although daily cannabis and somatic medication use during the trial may have impacted results by interacting with topiramate, these data were not collected.
Lastly, our decision to examine the first two weeks of treatment separately from the entire treatment period was based on a review of data from the primary outcomes manuscript (6) rather than theory regarding periods over which topiramate is expected to exert effects. Thus, changes in positive alcohol expectancies over the first two weeks of treatment may represent motivation to change rather than medication effects (35). Because sensitivity analyses examining the first six weeks of treatment separately from the entire treatment period produced similar results, our having modeled the first two weeks separately from the entire treatment period likely did not substantially impact results. The issue of timing of medications in the course of AUD treatment is a particularly important issue for clinical practice. A recent pragmatic trial in primary care that used a two-week window to assess initial change before treatment with nalmefene showed significant reductions in heavy drinking after the two-week window, thus establishing a precedent as a window for change (35).
Conclusions
We found significant effects of topiramate on the likelihood of heavy drinking, desire to drink, and positive alcohol expectancies among individuals seeking to reduce or stop drinking, which did not vary based on rs2832407 genotype. These findings add to a growing body of literature and treatment guidelines (37,38) advocating the use of topiramate for individuals interested in reducing their alcohol use, regardless of rs2832407 genotype. Intensive longitudinal methods increase confidence in these results by decreasing the risk of retrospective bias, likely increasing precision (10,11). Future studies should examine additional mechanisms of change in topiramate treatment and genotypic and phenotypic moderators of topiramate response to determine whether specific individuals benefit more from topiramate. Given that sensitivity analysis showed an effect of topiramate on tension reduction alcohol expectancies, relief drinking might be a candidate phenotypic moderator of topiramate response.
Supplementary Material
Funding and disclosure:
Supported by grants R01AA023192 and F31AA029266 from the National Institute on Alcohol Abuse and Alcoholism and the Mental Illness Research, Education, and Clinical Center of the Veterans Integrated Service Network 4, U.S. Department of Veterans Affairs. Dr. Kranzler is a member of advisory boards for Dicerna Pharmaceuticals, Sophrosyne Pharmaceuticals, and Enthion Pharmaceuticals; a consultant to Sobrera Pharmaceuticals; recipient of funding and medication supplies from Alkermes for an investigator-initiated clinical trial; and a holder of US patent 10,900,082 titled: “Genotype-guided dosing of opioid agonists,” issued January 26, 2021. Drs. Kranzler and Witkiewitz are members of the American Society of Clinical Psychopharmacology’s Alcohol Clinical Trials Initiative, which was supported in the last three years by Alkermes, Amygdala Neurosciences, Arbor, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka.
Footnotes
The skewness value reported is for a winsorized variable for number of drinks yesterday, wherein extreme values greater than 30 drinks were recoded to 30 drinks. The skewness estimate for the non-winsorized variable was 2.542 (SE=0.024).
Contributor Information
Victoria R. Votaw, University of New Mexico, Center on Alcohol, Substance use, And Addictions (CASAA), Albuquerque NM
Katie Witkiewitz, University of New Mexico, Center on Alcohol, Substance use, And Addictions (CASAA), Albuquerque NM
M. Lee Van Horn, Department of Individual, Family, & Community Education, Educational Psychology Program, University of New Mexico, Albuquerque, NM
Richard C. Crist, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
Timothy Pond, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
Henry R. Kranzler, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
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