Skip to main content

Abstract

Heavy drinkers trying to cut back but not completely eliminate their alcohol intake were treated with topiramate as an adjunct to counseling and reduced their drinking more rapidly than patients given placebo. The effect of topiramate was significant only in patients with a specific gene variation, the CC genotype of the GRIK1 polymorphism, offering a way to identify heavy drinkers who are likely to respond well to this treatment.

Abstract

Objective

Topiramate has been shown to reduce drinking and heavy drinking in individuals with alcohol dependence whose goal was to stop drinking. The authors evaluated the efficacy and tolerability of topiramate in heavy drinkers whose treatment goal was to reduce drinking to safe levels.

Method

A total of 138 individuals (62.3% men) were randomly assigned to receive 12 weeks of treatment with topiramate (N=67), at a maximal daily dose of 200 mg, or matching placebo (N=71). Both groups received brief counseling to reduce drinking and increase abstinent days. It was hypothesized that topiramate-treated patients would be better able to achieve these goals, and it was predicted that based on prior research, the effects would be moderated by a single nucleotide polymorphism (rs2832407) in GRIK1, encoding the kainate GluK1 receptor subunit.

Results

The rate of treatment completion was 84.9% and equal by treatment group. Topiramate treatment significantly reduced heavy drinking days and increased abstinent days relative to placebo. Patients receiving topiramate also had lower concentrations of the liver enzyme γ-glutamyl transpeptidase and lower scores on a measure of alcohol-related problems than the placebo group. In a European American subsample (N=122), topiramate’s effect on heavy drinking days was significantly greater than that for placebo only in rs2832407 C-allele homozygotes.

Conclusions

These findings support the use of topiramate at a daily dose of 200 mg to reduce heavy drinking in problem drinkers. The moderator effect of rs2832407, if validated, would facilitate the identification of heavy drinkers who are likely to respond well to topiramate treatment and provide an important personalized treatment option. The pharmacogenetic findings also implicate the kainate receptor in the mechanism of topiramate’s effects on heavy drinking.
Heavy drinking is common in the United States. In 2010, 23.1% of U.S. individuals age 12 or older reported that, during the prior month, they drank five or more drinks on an occasion, and 6.7% reported doing so on at least 5 days (1). As the frequency of heavy drinking increases, so does the incidence of a variety of alcohol-related problems, including alcohol use disorder (2). Despite these risks, only a small fraction of heavy drinkers in the population receives any kind of alcohol treatment, with medications particularly underutilized (3).
Furthermore, the development of alcohol treatment medications has focused on patients who meet criteria for alcohol dependence, particularly patients whose treatment goal is abstinence, rather than reduced drinking. Some studies of opioid antagonists are exceptions to this (48).
Although topiramate has shown substantial promise in reducing drinking in patients whose ultimate goal is abstinence (9, 10), there are no studies, to our knowledge, of its efficacy in treating heavy drinkers whose goal is to reduce their drinking. In an initial single-site 12-week study of topiramate (9), patients with alcohol dependence who received 300 mg/day of the drug (N=75) had a lower percentage of heavy drinking days than placebo-treated patients (N=75). This effect was replicated in a 14-week multicenter trial of 371 patients (10). In a study of 61 nontreatment-seeking subjects (11), individuals were randomly assigned to receive 39 days of treatment with topiramate at a dosage of 200 mg/day, topiramate at a dosage of 300 mg/day, or placebo. Results of the study showed that the frequency of heavy drinking was significantly lower in both topiramate groups than in the placebo group.
Topiramate has multiple pharmacologic effects, including the facilitation of GABAergic function by interacting with a nonbenzodiazepine site on the GABAA receptor (12) and antagonism of glutamate activity at AMPA and kainate receptors (13, 14). Topiramate’s effects on glutamate receptors are most potent and selective for those containing the GluK1 and GluK2 (formerly referred to as GluR5 and GluR6) subunits (encoded by GRIK1 and GRIK2, respectively) (15, 16). Topiramate also blocks voltage-dependent Na+ and l-type voltage-gated Ca++ channels, inhibits carbonic anhydrase, and enhances K+ conductance (17).
To identify potential moderators of topiramate response, in a previous study we examined the association of seven single-nucleotide polymorphisms (SNPs) in GRIK1 to alcohol dependence (18). One SNP, rs2832407, a C-to-A noncoding substitution, was significantly associated with alcohol dependence, with the C allele being more common in subjects with the disorder. Ray et al. (19) found that when treated with topiramate, GRIK1*rs2832407 C-allele homozygotes experienced significantly fewer adverse medication effects than A-allele carriers.
In the present study, we tested two hypotheses: 1) that patients receiving topiramate would show a greater reduction in the number of heavy drinking days and a greater increase in the number of abstinent days than patients receiving placebo and 2) that GRIK1*rs2832407 would moderate the therapeutic response to topiramate. Support for these hypotheses would provide an important option for the personalized treatment of heavy drinking.

Method

Overview

The study was a parallel-group placebo-controlled trial of topiramate in heavy drinkers, all of whom received medical management (20), a brief psychosocial intervention, at each of nine treatment visits. Patients were randomly assigned to treatment group, and double-blind conditions were maintained throughout the study. Raters were trained in the reliable use of all assessments. The study was conducted in three phases: a 1-week pretreatment assessment period, a 12-week treatment period, and a 9-day medication taper period.

Patients

Inclusion criteria were as follows: age 18–65; an average weekly consumption of ≥24 standard drinks for men and ≥18 standard drinks for women; an explicit goal of reducing drinking to safe levels; ability to read English at a level ≥8th grade; no gross evidence of cognitive impairment; willingness to name a potential locator to ensure follow-up; and written, informed consent to participate. Women of childbearing potential were required to be nonlactating and practicing a reliable method of birth control and to have a negative serum pregnancy test at screening.
Exclusion criteria were the presence of a current, clinically significant physical disease or abnormality on the basis of medical history, physical examination, or routine laboratory evaluation; history of nephrolithiasis; serious psychiatric illness on the basis of history or examination; a current DSM-IV diagnosis of drug (other than nicotine) dependence; and evidence of the likely need for abstinence from alcohol (i.e., current severe alcohol dependence, disorders exacerbated by heavy drinking [e.g., gastritis], self-reported inability to reduce drinking, or current alcohol withdrawal symptoms or a history of severe withdrawal symptoms).
We screened 200 prospective participants in person, of whom 138 (86 men, 62.3%) were randomly assigned to treatment with topiramate (N=67, 48.6%) or placebo (N=71, 51.4%). The CONSORT diagram of the study is presented in the data supplement that accompanies the online edition of this article. The study was initiated at the University of Connecticut Health Center (N=76) and completed at the University of Pennsylvania Treatment Research Center (N=62), and the institutional review boards at both universities approved the study protocol. Patients were paid to complete research assessments.

Procedures

Individuals were recruited through advertisements. An initial telephone screening interview was followed by an in-person visit, at which time patients provided written, informed consent to participate, and they underwent a history, physical examination, routine laboratory testing, and a urine drug screen, as well as pregnancy testing (for female patients).
Prior to randomization, patients completed questionnaires and were administered research interviews by a trained research evaluator. A nurse then administered the first medical management session and dispensed the study medication. We balanced the medication groups on age, sex, and frequency of drinking days and heavy drinking days during pretreatment using urn randomization, and we stratified the randomization for patients receiving antidepressants.
During the first 6 weeks of treatment, patients were seen weekly for medication titration, followed by three biweekly visits. At each visit, the patients’ breath alcohol concentration, weight, and vital signs were measured; patients completed questionnaires; and the research nurse elicited information on concurrent medications, the occurrence of adverse events, and protocol adherence and delivered the medical management intervention (20). At each visit, patients were interviewed to measure drinking and medication use since the last visit. The nurse compared self-reported adherence with the number of capsules returned and discussed discrepancies with the patients to resolve them. At the end of treatment, patients again completed questionnaires and were interviewed by the research nurse and the research evaluator.

Study Treatments

Counseling.

The medical management manual we used focuses on medication adherence and treatment participation through education and support; it was modified to be consistent with a goal of sensible drinking. The initial session included a review of the results of the initial evaluation and a discussion of sensible drinking limits using a World Health Organization guide on sensible drinking (21), as well as a rationale for and information about pharmacotherapy and the importance of medication adherence. At subsequent sessions (20–30 minutes), the nurse briefly assessed the patients’ drinking, monitored medication adherence, and made recommendations related to both. Based on guidelines for nonhazardous drinking (22), men were advised to consume no more than three standard drinks per day and 12 standard drinks per week, and women were advised to consume no more than two drinks per day and eight drinks per week. Thus, patients were counseled both to avoid heavy drinking days and to increase the number of abstinent days. Sessions were audiotaped and reviewed, and feedback was provided to nurses to ensure consistency in their delivery.

Medication.

We selected a maximal daily dosage of 200 mg of topiramate based on evidence of its efficacy (911) and to limit the adverse effects associated with a higher medication dosage (10). Topiramate treatment was initiated at a dosage of 25 mg at bedtime and at weekly intervals was increased as follows: 50 mg at bedtime, then 25 mg in the morning and 50 mg at bedtime, then 50 mg twice daily, then 50 mg in the morning and 100 mg at bedtime, and, finally, 100 mg twice daily. Placebo and topiramate were encapsulated and indistinguishable from one another. Dosage reductions or a delay in the increase in dosage was used to manage adverse effects.

Assessments

Laboratory assessments.

Laboratory assessments included urinalysis and urine toxicology testing, a complete blood count, γ-glutamyl transpeptidase concentration measurement, and a chemistry panel (including electrolytes, liver enzymes, and bilirubin). Measurement of electrolyte levels was repeated at the study midpoint to screen for metabolic acidosis. Measurement of γ-glutamyl transpeptidase concentration was repeated at the midpoint and at the end of treatment to validate self-reported drinking.

Psychological and behavioral assessments.

Psychological and behavioral assessments are listed below.
1) Sociodemographic/clinical information: Marital status, educational and occupational information, medical history, and substance abuse treatment history were included.
2) Psychiatric diagnosis: The Structured Clinical Interview for DSM-IV-TR Axis I Disorders (23) was used to classify patients according to the presence or absence of standard psychiatric disorders according to DSM-IV criteria (24).
3) Alcohol use patterns: The timeline follow-back method (25) was used to estimate the number of abstinent days and heavy drinking days during the 90-day pretreatment period and at each treatment visit.
4) Alcohol-related problems: The Short Index of Problems (26), a 15-item single-factor measure of alcohol-related problems (27), was administered at baseline and study endpoint.
5) Depressive symptoms: The Beck Depression Inventory (28), a 21-item self-report measure of depressive symptoms (score=0–63), was administered at baseline. It was repeated at every study visit for patients who were receiving an antidepressant or whose depression score was elevated at baseline.

Genotyping Procedure

DNA was extracted from whole blood using the PureGene kit (GentraSystems, Minneapolis). We genotyped rs2832407 using the TaqMan SNP genotyping assay (Life Technologies, Grand Island, N.Y.). All genotypes were obtained in duplicate with consistent results.

Statistical Analysis

Descriptive statistics included means and standard deviations for continuous variables (group differences analyzed using t tests) and percentages for categorical variables (group differences analyzed using chi-square). Factorial models crossing treatment assignment with a three-level genotype for group were analyzed using the general linear model for continuous variables and logistic regression for dichotomous categorical variables.

Timeline follow-back data.

Drinking data were aggregated to the weekly level. The number of days per week of heavy drinking (i.e., four or more drinks in a day for women and five or more drinks in a day for men) and of abstinence were the primary outcomes. Generalized linear mixed models with a binomial distribution and logit link function were used to examine medication group differences in changes in these outcomes during treatment. The models included 1) fixed effects for medication group, week, and interaction between medication and week and 2) a random effect for intercept. “Week” was recoded by subtracting the number of weeks of the study (12) so that the test of treatment compared the groups at the conclusion of the study (week 12), rather than at baseline. The interaction term tested for different rates of change in the outcome during the study.
Two sets of analyses of the number of heavy drinking and abstinent days were conducted. First, an intent-to-treat analysis included all 138 patients. In addition to examining changes in drinking over time, we conducted a responder analysis that examined the number of patients in each group with no heavy drinking days during the last 4 weeks of treatment, consistent with the approach recommended by the Food and Drug Administration (29). Second, we conducted a pharmacogenetic analysis that was limited to self-identified European American patients (N=122) because of substantial population differences in rs2832407 allele frequency. Initially, we used the three-level genotype for rs2832407 by adding it to the linear mixed analysis. We then combined the AA and AC groups, comparing them with the CC group as a dichotomous genotype.
Timeline follow-back data were available for 92.4% (SD=22.7) of the 84 days of treatment (92.9% [SD=20.9] for topiramate patients and 91.9% [SD=24.5] for placebo patients). To examine the effect of missing data, multiple imputation using a Markov Chain Monte Carlo single chain method based on patient baseline characteristics and weekly drinking was employed to create 10 imputed data sets. Models were rerun on the imputed data sets using SAS Proc Mianalyze (SAS Institute, Cary, N.C.).

Measures to validate drinking outcomes.

The γ-glutamyl transpeptidase concentrations were analyzed at the study midpoint and endpoint. Because of severe positive skewness and kurtosis, the values were log transformed. The Short Index of Problems score was analyzed using analysis of covariance, controlling for the pretreatment score.

Results

DSM-IV Diagnoses and Antidepressant Treatment

Although a DSM-IV diagnosis of current alcohol dependence was not an inclusion criterion, the vast majority of patients (92.5% of topiramate patients and 91.5% of placebo patients) met criteria for the diagnosis. Despite a high lifetime prevalence of major depression (Table 1), only three patients receiving topiramate and five patients in the placebo group met current criteria for an anxiety or depressive disorder. A total of 23 patients were receiving antidepressants at the time of randomization (16.4% of topiramate patients and 16.9% of placebo patients).
TABLE 1. Demographic and Pretreatment Clinical Measures
CharacteristicTopiramate (N=67)Placebo (N=71)Analysisa
 N%N%p
Sex (male)4567.24157.70.25
Race (European American)5683.66693.00.09
Married3958.24563.40.54
Employment status    0.68
 Full-time4161.24567.6 
 Part-time1116.41115.5 
 Not working1522.41216.9 
Income (annual)b    0.92
 Less than $40,00069.1912.7 
 $40,000–$79,9991421.21521.1 
 $80,000 –$119,0001827.31926.8 
 $120,000 or more2842.42839.4 
Lifetime major depression1826.92231.00.59
 MeanSDMeanSDp
Age (years)49.39.052.87.40.01
Education (years)15.82.515.32.50.25
Beck Depression Inventory score6.14.86.85.30.40
Abstinent daysc0.130.160.120.150.52
Heavy drinking daysc0.670.270.660.270.87
Short Index of Problems score14.98.615.56.70.68
a
For continuous measures, t tests were used; chi-square tests were used for categorical measures.
b
Income data were missing for one topiramate patient.
c
Data represent the proportion of the 90 days preceding the screening visit.

Treatment Completion

Treatment completers were those who completed 12 weeks of treatment. Overall, 117 patients (84.9%) completed treatment (topiramate patients: N=55, 82.1%; placebo patients: N=62, 87.3%; χ2=0.73, df=1, p=0.39). The two medication groups were comparable on the number of weeks of treatment received (topiramate patients: mean=10.9 weeks [SD=2.6], placebo patients: mean=11.1 weeks [SD=2.7]). Among European Americans, there was no main effect of genotype group or interaction of genotype group with medication group on treatment weeks.

Medication Adherence and Maximal Dosage Achieved

Using self-reports, with verification by capsule counts, there was a high rate of adherence in both medication groups (placebo patients: mean=91.1% of daily doses [SD=24.7]; topiramate patients: 89.4% of daily doses [SD=23.1]). The finding of placebo patients taking a higher dosage of the study medication (equivalent dosage=187.7 mg [SD=43.1]) than topiramate patients (173.5 mg [SD=45.6]) fell short of statistical significance (F=3.53, df=1,136, p=0.06). Among European Americans, there was no difference in maximal dosage by genotype group or the interaction of genotype group with medication group.

Main Effects of Topiramate

Demographic and pretreatment clinical measures.

The study sample consisted predominantly of middle-aged, European American, married, employed men, with an average of 3 years of college (Table 1). During pretreatment, patients drank alcohol approximately 6 days per week and drank heavily 5 days per week. The only pretreatment demographic or clinical measure on which the groups differed significantly was age. Placebo patients were approximately 3.5 years older than topiramate patients. We included age as a factor in the analyses, as described below. There were site differences with regard to demographic characteristics. Patients from Connecticut were predominantly European American (97%), whereas in Philadelphia there were fewer European Americans (77%) and more African Americans (18%) (χ2=14.60, df=3, p=0.002). In addition, the Connecticut patients were significantly (χ2=7.36, df=1, p=0.007) more likely to be married (71%) than the Philadelphia patients (48%) and to work full-time (78% compared with 48%, χ2=13.38, df=2, p=0.001). We examined site as a factor in the analyses, as described below.

Heavy drinking days.

There was a significant main effect of medication group, with topiramate patients reducing heavy drinking more than placebo patients (F=23.37, df=1, 1399, p<0.001), and an interaction of medication group and treatment week (F=19.91, df=1, 1399, p<0.0001), with topiramate patients decreasing heavy drinking more rapidly than placebo patients. By the last week of treatment, the odds of experiencing a heavy drinking day in the placebo group was 5.33 times (95% confidence interval [CI]=1.68–7.28) that of the topiramate treatment group (Figure 1).
FIGURE 1. Mean Heavy Drinking Days Per Week by Medication Groupa
a There was a significant main effect of medication group (F=23.37, df=1, 1399, p<0.001) and interaction of medication group-by-treatment week (F=19.91, df=1, 1399, p<0.0001). The standard error of the mean is represented.
The number of patients with no heavy drinking days during the last 4 weeks of treatment in the topiramate group (N=24, 35.8%) was more than double that found in the placebo group (N=12, 16.9%) (odds ratio=2.75, 95% CI=1.24–6.10).

Abstinent days.

There was a main effect of medication group (F=4.63, df=1, 1398, p=0.03), with topiramate patients reporting more abstinent days than placebo patients. There was also a significant interaction of medication group and treatment week (F=6.26, df=1, 1398, p=0.01). Topiramate patients increased the number of abstinent days per week more rapidly than placebo patients. By the last week of treatment, the odds of abstaining from drinking among topiramate patients was 2.57 times (95% CI=1.13–5.84) that of placebo patients (Figure 2).
FIGURE 2. Mean Abstinent Days Per Week by Medication Groupa
a There was a significant main effect of medication group (F=4.63, df=1, 1398, p=0.03) and interaction of medication group-by-treatment week (F=6.26, df=1, 1398, p=0.01). The standard error of the mean is represented.

γ-Glutamyl transpeptidase concentrations.

There was a significant medication group-by-time interaction (F=3.44, df=2, 241, p=0.03). Topiramate-treated patients had a significantly greater decline in γ-glutamyl transpeptidase concentrations than placebo patients. Although concentrations were equivalent at baseline (topiramate patients: N=67, mean=65.9 IU/L [SD=91.5]; placebo patients: N=71, mean=56.1 IU/L [SD=71.6]), there was a near-significant difference at midpoint (topiramate patients: N=59, mean=37.6 IU/L [SD=36.7]; placebo patients: N=64, mean=50.1 IU/L [SD=64.8]; p=0.06), and a significant difference at endpoint (topiramate patients: N=58, mean=36.3 IU/L [SD=40.2]; placebo patients: N=63, mean=47.9 IU/L [SD=52.1]; p=0.01).

Short Index of Problems score.

Controlling for baseline scores, there was a significant difference in Short Index of Problems scores at the study endpoint (Δ=7.9 for topiramate patients, from 14.9 [SD=8.6] at randomization to 7.0 [SD=7.2] at endpoint, and Δ=4.4 for placebo patients, declining from 15.5 [SD=6.7] at randomization to 11.1 [SD=7.5] at endpoint [F=11.42, df=1, 128, p=0.001]).

Moderation of the Effects of Topiramate by rs2832407

The demographic and pretreatment clinical features as a function of both genotype and treatment groups for the European American subsample that was the focus of the pharmacogenetic analyses are summarized in Table 2. Consistent with the finding in the intent-to-treat sample, placebo-treated patients were significantly older than topiramate-treated patients. No other demographic or clinical features differed significantly among the groups.
TABLE 2. Baseline Demographic and Clinical Characteristics by Genotype (rs2832407) and Treatment Assignment of European American Patients (N=122)
CharacteristicCC Genotype (42%)aAC Genotype (43%)aAA Genotype (15%)a
TopiramatePlaceboTopiramatePlaceboTopiramatePlacebo
 N%N%N%N%N%N%
Sex (male)2171.43046.72466.72962.11154.5785.7
Married2166.73066.72466.72962.11163.6785.7
Lifetime major depression2123.83036.72420.82924.11127.3728.6
 MeanSDMeanSDMeanSDMeanSDMeanSDMeanSD
Age (years)b51.78.352.56.449.86.853.08.250.66.756.37.2
Education (years)15.72.415.02.215.91.915.12.815.02.415.91.5
Beck Depression Inventory score7.45.16.85.15.13.97.15.44.93.35.44.6
Short Index of Problems score14.58.015.46.514.59.915.67.216.67.212.65.1
90-Day pretreatment drinkingc            
 Percent days abstinent0.120.140.070.110.130.170.130.150.070.080.190.17
 Percent heavy drinking days0.700.250.720.270.660.280.580.250.700.320.740.25
a
The genotype frequencies in European Americans were consistent with Hardy-Weinberg equilibrium expectations (χ2=0.61, df=2, p=0.74).
b
There was statistical significance for a main effect between groups (p=0.04) (topiramate patients: mean age=50.7 years [SD=7.3]; placebo patients: mean age=53.1 years [SD=7.3]).
c
The data represent information preceding the screening visit.

Heavy drinking days.

There was a significant medication group-by-genotype interaction (F=5.50, df=2, 1227, p=0.004) on heavy drinking days. As shown in Figure 3, topiramate was efficacious only in patients with the CC genotype. In follow-up comparisons in patients with the CC genotype, topiramate reduced heavy drinking days significantly more than placebo (F=23.81, df=1,1228, p<0.001), whereas in A-allele carriers the difference between topiramate and placebo was not significant.
FIGURE 3. Mean Heavy Drinking Days Per Week by Medication Group and rs2832407 Genotypea
a There was a significant medication group-by-genotype interaction (F=5.50, df=2, 1227, p=0.004). The standard error of the mean is represented.

Abstinent days.

For abstinent days, the interaction of medication group-by-genotype group was not statistically significant. Nonetheless, as with heavy drinking days, the effect of topiramate appeared to be limited to the C-allele homozygotes (Figure 4), and a contrast between topiramate and placebo within C-allele homozygotes (compared with A-allele carriers) was significant (F=4.08, df=1, 1228, p=0.04).
FIGURE 4. Mean Abstinent Days Per Week by Medication Group and rs2832407 Genotypea
a The interaction of medication group-by-genotype group was not statistically significant. The standard error of the mean is represented.

Effect of age, site differences, antidepressant treatment, and missing data.

Age, treatment site, and antidepressant treatment were not associated with the drinking outcomes, and including them in the models did not substantially alter the findings. Furthermore, analyses based on multiple imputation of missing data yielded findings that were wholly consistent with the primary analyses.

Adverse Effects

Topiramate patients reported significantly more adverse events (mean=5.5 [SD=3.1]) than placebo patients (mean=3.0 [SD=2.5]; F=29.0, df=1, 135, p<0.001). Although approximately two-thirds of the adverse events were rated as mild, topiramate patients reported more moderate or severe events (mean=1.8 [SD=1.3]) than placebo patients (mean=0.4 [SD=0.7]) (F=62.2, df=1, 135, p<0.001). The adverse events that occurred in at least 10% of the patients and the number of patients from each group that experienced the event are summarized in Table S1 of the online data supplement. A significantly greater number of topiramate patients reported numbness/tingling, change in taste, loss of appetite, weight loss, difficulty concentrating, and difficulty with memory; these are all adverse effects that have been associated commonly with topiramate treatment (9, 10).

Discussion

In this study, we examined the efficacy of topiramate at a maximal daily dose of 200 mg in patients whose goal was to reduce their drinking, rather than to become abstinent from alcohol. We found significantly greater effects of topiramate than placebo in reducing heavy drinking days and increasing abstinent days. Both γ-glutamyl transpeptidase concentration, an objective measure of heavy drinking, and Short Index of Problems scores, a measure of alcohol-related problems, were consistent with the self-reported drinking data. This evidence of efficacy compares favorably with the findings from two previous studies that compared topiramate 300 mg with placebo to promote abstinence (9, 10). Furthermore, the findings reported in the present study are consistent with those of a study of nontreatment-seeking heavy drinkers, in which both 200 mg and 300 mg of topiramate reduced the frequency of heavy drinking more than placebo (11).
Of particular note, we observed that rs2832407, a noncoding intronic SNP in GRIK1, moderated topiramate’s effects on heavy drinking days. Although a similar pharmacogenetic effect was seen for the number of abstinent days, it did not reach statistical significance. A larger sample could yield a significant moderator effect on this outcome as well. In a previous analysis of moderation by this SNP (19), patients with the CC genotype had lower plasma concentrations of topiramate and fewer adverse effects of the medication than A-allele carriers. We did not measure topiramate plasma concentrations but found no effect of rs2832407 on adverse effects produced by topiramate (see the online data supplement).
Although the functional effects of rs2832407 are unknown, the SNP is located 802 base pairs upstream of a GRIK1 antisense transcript that overlaps with exon 9. Analysis of data from the 1,000 Genomes Project (30) shows that it is in near-complete linkage disequilibrium (r2=0.99) with rs363431, which maps to the antisense transcript in GRIK1. Furthermore, ENCODE data show that rs2832407, which is a C-to-A substitution, lies within a CpG island (31). Thus, one possible mechanism for the observed moderating effect of rs2832407 is that the polymorphism, or another GRIK1 polymorphism that is linked to it, affects the level of expression of GRIK1 mRNA, reducing the number of GluK1-containing kainate receptors and the effect of topiramate.
The high rate of treatment completion was a strength of this study. In contrast to the multicenter study by Johnson et al. (10), in which a significantly larger proportion of topiramate-treated patients than placebo patients discontinued treatment prematurely, we found no evidence of differential attrition. The observed reduction in heavy drinking days, particularly in patients with the CC genotype at rs2832407, to less, on average, than one heavy drinking day per week is clinically important, since the frequency of heavy drinking is correlated with a variety of alcohol-related negative consequences (3234). In addition to requiring replication in a larger sample, the effects of topiramate and the moderating effects of rs2832407 require evaluation in populations other than European Americans. Together, these efforts will help to personalize the pharmacological treatment of heavy drinking.

Footnote

ClinicalTrials.gov registry number, NCT00626925 (www.clinicaltrials.gov).

Supplementary Material

Supplementary Material (445_ds001.pdf)

References

1.
SAMHSA: National Survey on Drug Use and Health. Washington, DC, US Department of Health and Human Services, 2013. http://www.oas.samhsa.gov/nsduhLatest.htm
2.
Kranzler HR, Babor TF, Lauerman RJ: Problems associated with average alcohol consumption and frequency of intoxication in a medical population. Alcohol Clin Exp Res 1990; 14:119–126
3.
Cohen E, Feinn R, Arias A, Kranzler HR: Alcohol treatment utilization: findings from the National Epidemiologic Survey on Alcohol and Related Conditions. Drug Alcohol Depend 2007; 86:214–221
4.
Kranzler HR, Armeli S, Tennen H, Blomqvist O, Oncken C, Petry N, Feinn R: Targeted naltrexone for early problem drinkers. J Clin Psychopharmacol 2003; 23:294–304
5.
Kranzler HR, Tennen H, Armeli S, Chan G, Covault J, Arias AJ, Oncken C: Targeted naltrexone for problem drinkers. J Clin Psychopharmacol 2009; 29:350–357
6.
Mann K, Bladström A, Torup L, Gual A, van den Brink W: Extending the treatment options in alcohol dependence: a randomized controlled study of as-needed nalmefene. Biol Psychiatry 2013; 73:706–713
7.
van den Brink W, Sorensen P, Torup L, Mann K, Gaul A: Long-term efficacy, tolerability, and safety of nalmefene as-needed in alcohol dependence: a randomized, double-blind, placebo-controlled study. Alcohol Clin Exp Res 2012; 36:247A
8.
Gual A, He Y, Torup L, van den Brink W, Mann K; ESENSE 2 Study Group: A randomised, double-blind, placebo-controlled, efficacy study of nalmefene, as-needed use, in patients with alcohol dependence. Eur Neuropsychopharmacol 2013; 23:1432–1442
9.
Johnson BA, Ait-Daoud N, Bowden CL, DiClemente CC, Roache JD, Lawson K, Javors MA, Ma JZ: Oral topiramate for treatment of alcohol dependence: a randomised controlled trial. Lancet 2003; 361:1677–1685
10.
Johnson BA, Rosenthal N, Capece JA, Wiegand F, Mao L, Beyers K, McKay A, Ait-Daoud N, Anton RF, Ciraulo DA, Kranzler HR, Mann K, O’Malley SS, Swift RM; Topiramate for Alcoholism Advisory Board; Topiramate for Alcoholism Study Group: Topiramate for treating alcohol dependence: a randomized controlled trial. JAMA 2007; 298:1641–1651
11.
Miranda R, MacKillop J, Monti PM, Rohsenow DJ, Tidey J, Gwaltney C, Swift R, Ray L, McGeary J: Effects of topiramate on urge to drink and the subjective effects of alcohol: a preliminary laboratory study. Alcohol Clin Exp Res 2008; 32:489–497
12.
White HS, Brown SD, Woodhead JH, Skeen GA, Wolf HH: Topiramate modulates GABA-evoked currents in murine cortical neurons by a nonbenzodiazepine mechanism. Epilepsia 2000; 41(suppl 1):S17–S20
13.
Skradski S, White HS: Topiramate blocks kainate-evoked cobalt influx into cultured neurons. Epilepsia 2000; 41(suppl 1):S45–S47
14.
Gibbs JW, Sombati S, DeLorenzo RJ, Coulter DA: Cellular actions of topiramate: blockade of kainate-evoked inward currents in cultured hippocampal neurons. Epilepsia 2000; 41(suppl 1):S10–S16
15.
Gryder DS, Rogawski MA: Selective antagonism of GluR5 kainate-receptor-mediated synaptic currents by topiramate in rat basolateral amygdala neurons. J Neurosci 2003; 23:7069–7074
16.
Kaminski RM, Banerjee M, Rogawski MA: Topiramate selectively protects against seizures induced by ATPA, a GluR5 kainate receptor agonist. Neuropharmacology 2004; 46:1097–1104
17.
McDonald R, Rogawski M: Cellular effects of antiepileptic drugs, in Epilepsy: A Comprehensive Textbook, 2nd ed. Edited by, Engel J, Pedley TA. Philadelphia, Lippincott, Williams, and Wilkins, 2006, pp 1433–1446
18.
Kranzler HR, Gelernter J, Anton RF, Arias AJ, Herman A, Zhao H, Burian L, Covault J: Association of markers in the 3′ region of the GluR5 kainate receptor subunit gene to alcohol dependence. Alcohol Clin Exp Res 2009; 33:925–930
19.
Ray LA, Miranda R, MacKillop J, McGeary J, Tidey JW, Rohsenow DJ, Gwaltney C, Swift RW, Monti PM: A preliminary pharmacogenetic investigation of adverse events from topiramate in heavy drinkers. Exp Clin Psychopharmacol 2009; 17:122–129
20.
Pettinati H, Weiss R, Miller W, Donovan D, Ernst D, Rounsaville B: COMBINE Monograph Series, vol 2: Medical Management Treatment Manual: A Clinical Research Guide for Medically Trained Clinicians Providing Pharmacotherapy as Part of the Treatment for Alcohol Dependence (Publication number, NIH 04-5289). Bethesda, Md, National Institute on Alcohol Abuse and Alcoholism, 2004
21.
WHO Brief Intervention Study Group: A cross-national trial of brief interventions with heavy drinkers. Am J Public Health 1996; 86:948–955
22.
Sanchez-Craig M, Wilkinson DA, Davila R: Empirically based guidelines for moderate drinking: 1-year results from three studies with problem drinkers. Am J Public Health 1995; 85:823–828
23.
First M, Spitzer R, Gibbon M, Williams J: Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition with Psychotic Screen (SCID-I/P W/PSY Screen). New York, New York State Psychiatric Institute, Biometrics Research, 2001
24.
American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC, American Psychiatric Publishing, 1994
25.
Sobell L, Sobell M: Timeline follow-back: a technique for assessing self-reported alcohol consumption, in Measuring Alcohol Consumption. Edited by, Allen J. New York, Humana Press, 1992, pp 41–65
26.
Miller W, Tonigan J: The Drinker Inventory of Consequences (DrInC), NIAAA Project MATCH Monograph Series, vol 4. Bethesda, Md, National Institutes of Health, 1995, pp 95–3911
27.
Feinn R, Tennen H, Kranzler HR: Psychometric properties of the Short Index of Problems as a measure of recent alcohol-related problems. Alcohol Clin Exp Res 2003; 27:1436–1441
28.
Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J: An inventory for measuring depression. Arch Gen Psychiatry 1961; 4:561–571
29.
Falk D, Wang XQ, Liu L, Fertig J, Mattson M, Ryan M, Johnson B, Stout R, Litten RZ: Percentage of subjects with no heavy drinking days: evaluation as an efficacy endpoint for alcohol clinical trials. Alcohol Clin Exp Res 2010; 34:2022–2034
30.
1,000 Genomes Project ConsortiumAbecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA: An integrated map of genetic variation from 1,092 human genomes. Nature 2012; 491:56–65
31.
Raney BJ, Cline MS, Rosenbloom KR, Dreszer TR, Learned K, Barber GP, Meyer LR, Sloan CA, Malladi VS, Roskin KM, Suh BB, Hinrichs AS, Clawson H, Zweig AS, Kirkup V, Fujita PA, Rhead B, Smith KE, Pohl A, Kuhn RM, Karolchik D, Haussler D, Kent WJ: ENCODE whole-genome data in the UCSC genome browser (2011 update). Nucleic Acids Res 2011; 39:D871–D875
32.
Breslow RA, Graubard BI: Prospective study of alcohol consumption in the United States: quantity, frequency, and cause-specific mortality. Alcohol Clin Exp Res 2008; 32:513–521
33.
Dawson DA, Li TK, Grant BF: A prospective study of risk drinking: at risk for what? Drug Alcohol Depend 2008; 95:62–72
34.
Jackson KM: Heavy episodic drinking: determining the predictive utility of five or more drinks. Psychol Addict Behav 2008; 22:68–77

Information & Authors

Information

Published In

Go to American Journal of Psychiatry
Go to American Journal of Psychiatry
American Journal of Psychiatry
Pages: 445 - 452
PubMed: 24525690

History

Received: 2 August 2013
Revision received: 8 October 2013
Accepted: 25 November 2013
Published online: 1 April 2014
Published in print: April 2014

Authors

Details

Henry R. Kranzler, M.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Jonathan Covault, M.D., Ph.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Richard Feinn, Ph.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Stephen Armeli, Ph.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Howard Tennen, Ph.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Albert J. Arias, M.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Joel Gelernter, M.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Timothy Pond, M.P.H.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Cheryl Oncken, M.D., M.P.H.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.
Kyle M. Kampman, M.D.
From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia; VISN 4 Mental Illness, Research, Education, and Clinical Center, Philadelphia Veterans Administration Medical Center, Philadelphia; the Alcohol Research Center, Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Conn.; the Frank Netter School of Medicine, Quinnipiac University, Hamden, Conn.; the Department of Psychology, Fairleigh Dickinson University, Teaneck, N.J.; the Department of Community Medicine and Healthcare, University of Connecticut School of Medicine, Farmington, Conn.; the Department of Psychiatry, Yale University School of Medicine, New Haven, Conn.; VA Connecticut Healthcare System, West Haven, Conn.; and the Department of Medicine, University of Connecticut School of Medicine, Farmington, Conn.

Notes

Address correspondence to Dr. Kranzler ([email protected]).

Funding Information

Dr. Kranzler has served as a consultant to or advisory board member for Alkermes, Lilly, Lundbeck, Pfizer, and Roche; he is also a member of the American Society of Clinical Psychopharmacology’s Alcohol Clinical Trials Initiative, which is supported by Abbott, Lilly, Lundbeck, and Pfizer. Dr. Oncken has received study supplies from Pfizer for a smoking cessation study. All other authors report no financial relationships with commercial interests.
Supplementary Material
Supported by National Institutes of Health grants P60 AA03510 and K24 AA13736, from the National Institute on Alcohol Abuse and Alcoholism, and the VISN 4 Mental Illness Research, Education, and Clinical Center of the U.S. Department of Veterans Affairs.

Metrics & Citations

Metrics

Citations

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format
Citation style
Style
Copy to clipboard

View Options

View options

PDF/EPUB

View PDF/EPUB

Get Access

Login options

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Personal login Institutional Login Open Athens login
Purchase Options

Purchase this article to access the full text.

PPV Articles - American Journal of Psychiatry

PPV Articles - American Journal of Psychiatry

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Media

Figures

Other

Tables

Share

Share

Share article link

Share