Effects of Opioid Receptor Gene Variation on TargetedNalmefene Treatment in Heavy Drinkers

Albert J. Arias, Stephen Armeli, Joel Gelernter, Jonathan Covault, Antero Kallio, SakariKarhuvaara, Tiina Koivisto, Rauno Makela, and Henry R. Kranzler

Background: Recent studies examining the moderating effects of polymorphic variation in opi-oid receptor genes have yielded conicting results. We examined opioid receptor gene polymor-phisms as moderators of the therapeutic effects of the opioid antagonist nalmefene.

Methods: Participants (n = 272) were subjects who consented to the pharmacogenetic analysisof a multi-site, randomized, placebo-controlled trial of targeted nalmefene for the reduction ofheavy drinking. We genotyped two single nucleotide polymorphisms (SNPs) in OPRM1 (includingA118G, a commonly studied SNP that encodes an Asn40Asp amino acid substitution), two SNPsin OPRD1, and one SNP in OPRK1, which encode the l-, d-, and j-opioid receptors, respec-tively. Regression analysis served to examine the moderating effects of these SNPs on medicationresponse.

Results: As previously described by Karhuvaara et al. (2007), nalmefene signicantly reducedthe number of heavy drinking and very heavy drinking days per week, compared with placebo.There were no main or moderating effects of the genotypes examined on these outcomes.

Conclusions: Our nding that the therapeutic effects of targeted nalmefene were not moderatedby polymorphic variation in opioid receptor genes is consistent with two recent reports showingthat variation in opioid receptor genes does not moderate the response to naltrexone. However,these ndings contrast with those from two other studies, in which the Asn40Asp polymorphismin OPRM1 moderated the naltrexone treatment response. Additional research is needed to clarifythe role of variation in opioid receptor genes on the response to opioid antagonist treatment ofalcoholism.

Key Words: Alcohol treatment, Pharmacogenetics, OPRM1, OPRK1, OPRD1, Nalmefene.

I N 1994, THE U.S. Food and Drug Administrationapproved the opioid receptor antagonist naltrexone as anoral formulation to treat alcohol dependence. In 2006, a long-acting, injectable formulation of naltrexone was alsoapproved for this indication. Although naltrexone has beenshown to be superior to placebo in the treatment of alcoholdependence, a substantial number of patients still do notrespond to treatment with the medication (Garbutt et al.,2005; Srisurapanont and Jarusuraisin, 2005).Efforts to identify moderators of naltrexone response have

shown a family history of alcohol dependence to be the mostconsistent clinical predictor (Monterosso et al., 2001; Rubio

et al., 2005; Volpicelli et al., 1995). Recently, pharmacogeneticstudies have been used in an effort to identify alcohol-dependent individuals who are most likely to benet fromnaltrexone treatment. In this regard, the l-opioid receptor(genetic locus OPRM1), which is the primary pharmacologictarget for opioid antagonists, has been of greatest interest.The most widely studied polymorphism in OPRM1 is

A118G, a single nucleotide polymorphism (SNP) that encodesan amino acid substitution (Asn40Asp), which has an impacton receptor binding or expression (Befort et al., 2001; Beyeret al., 2004; Bond et al., 1998; Zhang et al., 2005). Bond et al.(1998) found that the receptor encoded by the Asp40 allelehad a threefold greater binding of the endogenous opioidb-endorphin (but no other endogenous or exogenous opioidligands, including naloxone) than the receptor encoded by theAsn40 allele. In contrast, Befort et al. (2001) found no differ-ence in the receptors afnity for various exogenous or endo-genous opioids (including b-endorphin), but reduced receptorexpression of the variant allele in a mammalian cell line. Beyeret al. (2004) also found reduced expression of the receptor,but no functional change associated with the variant allele.Zhang et al. (2005) found the Asp40 allele to be associatedwith reduced mRNA and protein levels in both human post-mortem tissue and transfected Chinese hamster ovary cells. Inpostmortem brain tissue from humans heterozygous for theAsn40Asp SNP, Zhang and colleagues found the mRNA

From the Alcohol Research Center, University of ConnecticutSchool of Medicine (AJA, JC, HRK), Farmington, Connecticut;Department of Psychology, Fairleigh-Dickinson University (SA),Madison, New Jersey; Yale University School of Medicine (JG),New Haven, Connecticut and VA-Connecticut, West Haven, Connecti-cut; Biotie Therapies Corp. (AK, SK, TK), Turku, Finland; andA-Clinic Foundation (RM), Helsinki, Finland.

Received for publication October 21, 2007; accepted February 27, 2008.Reprint requests: Henry R. Kranzler, MD, Department of Psychia-

try, University of Connecticut Health Center, 263 Farmington Ave.,Farmington, CT 06030-2103; Fax: 860-679-1316; E-mail: kranzler@psychiatry.uchc.edu

Copyright 2008 by the Research Society on Alcoholism.

DOI: 10.1111/j.1530-0277.2008.00735.x

Alcoholism: Clinical and Experimental Research Vol. 32, No. 7July 2008

Alcohol Clin Exp Res, Vol 32, No 7, 2008: pp 11591166 1159

from the A118 allele to be 1.5 to 2.5 times more abundantthan from the G118 allele. The observed allelic expressionimbalance was conrmed in Chinese hamster ovary cells usinga paradigm that compared expression of mRNA based ontransfection of the OPRM1 coding sequence with A118,C118, T118, or G118, with a difference from the wild-typeA118 found only with the G118 allele.Although two meta-analyses of casecontrol studies

showed no evidence of an etiologic association of theAsp40Asn polymorphism to substance dependence (Ariaset al., 2006), several studies have shown the polymorphism tomoderate naloxone-induced activation of the hypothalamicpituitary axis axis in humans (Chong et al., 2006; Hernandez-Avila et al., 2003; Wand et al., 2002). Hernandez-Avila et al.(2007), in a naloxone challenge study conducted in a sampleselected to have a high proportion of Asp40 allele carriers,found that an altered cortisol response was associated withthe Asp40 allele in subjects of European ancestry, but notthose of Asian ancestry.In a study of intravenous ethanol administration in heavy

drinkers, individuals with the Asp40 allele experienced a moreintense high, and greater subjective intoxication, stimula-tion, sedation, and happiness from alcohol, and were morelikely to report a family history of alcohol use disorders thandid Asn40 homozygotes (Ray and Hutchison, 2004). Further,male heavy drinkers with the Asp40 allele reported higher lev-els of craving when exposed to an alcohol stimulus than didAsn40 homozygotes (van den Wildenberg et al., 2007). How-ever, cue-elicited craving was paradoxically increased inAsp40 allele carriers in a sample of heavy drinkers who werepretreated with naltrexone, while no change in craving wasnoted for Asn40 homozygotes (McGeary et al., 2006).Other opioid receptor gene variants have also been exam-

ined in relation to the risk for substance dependence. Zhanget al. (2006), in a haplotypic analysis of the risk for alcohol ordrug dependence, genotyped 12 intronic SNPs and 1 exonicSNP (Asn40Asp) in OPRM1 and identied two haplotypeblocks, one of which was signicantly more common in cases(with alcohol or drug dependence), and another that was sig-nicantly more common in controls. Although the Asn40AspSNP was in complete linkage disequilibrium with most of theintronic SNPs in one haplotype block, allelic analysis revealedthat it was not associated with substance dependence in thissample. Two other studies of OPRM1 showed an associationof substance dependence with haplotypes found mainly in theputative regulatory region of the gene (Hoehe et al., 2000;Luo et al., 2003). An association to substance dependencewas also reported for an intronic polymorphism in OPRM1(Kranzler et al., 1998).To date, there have been three studies examining the mod-

erating effect of the Asn40Asp polymorphism on naltrexonetreatment response in alcohol dependence and one study in asample of nontreatment-seeking heavy drinkers. Oslin et al.(2003) studied 130 European American (EA) subjects fromthree placebo-controlled trials. They found that, amongpatients treated with naltrexone, those with one or more

Asp40 alleles were signicantly less likely than Asn40 homo-zygotes to relapse to heavy drinking. Placebo-treated subjectsshowed no moderating effect of genotype. Gelernter et al.(2007) examined the moderating effect of polymorphic varia-tion in opioid receptor genes on treatment response in asubset of patients [n = 220, 73.6% EAs and 26.4% AfricanAmericans (AAs)] from the VA Cooperative Study ofNaltrexone Treatment (Krystal et al., 2001). In addition tothe Asn40Asp polymorphism, these investigators studied twoother OPRM1 SNPs, three markers in OPRD1 (whichencodes the d-opioid receptor), and one marker in OPRK1(which encodes the j-opioid receptor). They found no signi-cant interaction between any of the SNPs studied and theresponse to naltrexone treatment. Anton et al. (2008) exam-ined the moderating effect of the Asn40Asp polymorphismon the response to naltrexone treatment in a subsample ofsubjects from the COMBINE study (Anton et al., 2006).Subjects included in the primary pharmacogenetic analysis(n = 297) were EAs who were treated with naltrexone orplacebo and medication management. A positive moderatingeffect on the response to naltrexone was observed for carriersof the Asp40 allele on the percentage of heavy drinking days(HDD) and on a global measure of treatment outcome. Sec-ondary analyses, which included subjects from all racialgroups, as well as those receiving treatment with naltrexoneor placebo and an intensive behavioral intervention, showedno moderating effect of the Asn40Asp polymorphism. In abrief cross-over trial of naltrexone versus placebo in a groupof nontreatment-seeking heavy drinkers (n = 30, 77.8% EA),no difference in treatment response was observed for thosewith the Asp40 allele (Mitchell et al., 2007).Nalmefene, a specic and potent opioid antagonist, has

afnity for the three opioid receptor subtypes, all of whichhave been implicated in the pathophysiology of alcoholdependence (Oswald and Wand, 2004). Nalmefene has apotential therapeutic advantage over naltrexone owing to itslack of hepatic toxicity, longer half-life, and greater bioavail-ability (Ingman et al., 2005; Mason et al., 1999). Nalmefenesafnity for the l-, and j-opioid receptors is similar to that ofnaltrexone, though its afnity for the d-opioid receptor isgreater than naltrexones (Emmerson et al., 1994; Michelet al., 1985). A single 50-mg oral dose of nalmefene com-pletely blocked respiratory depression, analgesia, and subjec-tive effects of fentanyl for 48 hours (Gal et al., 1986). Inalcohol-dependent individuals, nalmefene treatment reduceddrinking during a 5-day natural observation period, as well asafter a priming dose of alcohol in a bar-laboratory paradigm(Drobes et al., 2004). Of the three studies of daily nalmefenetreatment of alcohol dependence, two showed lower rates ofrelapse to heavy drinking, more abstinent days week, andfewer drinks per drinking day in the nalmefene-treatedpatients compared with those receiving placebo (Anton et al.,2004; Karhuvaara et al., 2007; Mason et al., 1994, 1999).In the present study, we examined the moderating effect

of opioid receptor gene variants in subjects from the28-week, multi-center trial by Karhuvaara et al. (2007),

1160 ARIAS ET AL.

the primary aim of which was to test the efcacy andsafety of nalmefene when used on an as needed basis toreduce heavy drinking. That study enrolled a total of 403subjects, who were included based on their self-identica-tion of drinking problems rather than a formal diagnosisof alcohol dependence and no treatment goals wereimposed on them. The study showed that targeted nalmef-ene was signicantly better than placebo in reducingHDD, very heavy drinking days (VHDD), and drinks perdrinking day, and in increasing abstinent days. We hypoth-esized that one or more SNPs in the genes encoding opi-oid receptors that had previously been identied asputatively functional would moderate the effects of nalmef-ene on drinking outcomes. To that end, we examined theinteractive effects of ve SNPs in the genes encoding thel-, d-, and j-opioid receptors on drinking outcomes fol-lowing treatment with nalmefene or placebo.

METHODS

The study protocol and consent materials (both of which includeda description of the pharmacogenetic substudy) were approved byethics committees at all of the 15 participating clinical sites inFinland. Institutional review boards at the University of ConnecticutHealth Center, Yale University, and VA-Connecticut also approvedthe pharmacogenetic substudy. The methodology for the treatmenttrial is described in detail in Karhuvaara et al. (2007); a brief sum-mary is provided here.

Recruitment

Subjects were recruited mainly through newspaper advertisements.Following a preliminary telephone interview, eligible subjects wereinvited to the nearest recruiting site for a screening visit. Inclusion cri-teria were age 18, 14 consecutive days of abstinence (ABS), and18 HDD during the preceding 12 weeks, the absence of intoxicationand severe withdrawal symptoms at the enrollment visit, a stableaddress and telephone number, and an identied locator person.Exclusion criteria included the presence of any severe medical, psy-chiatric, or social problem that required resolution or that wouldinterfere with the conduct of the study or impair treatment compli-ance; drug dependence or illicit drug use; previous participation instudies of nalmefene or recent participation in other drug studies;recent treatment with disulram or naltrexone; and current preg-nancy or nursing.

Assessments

Following medical and psychiatric screening, including clinical lab-oratory testing, subjects drinking during the 90 days prior to enroll-ment was quantied using the Timeline Follow-Back method(TLFB; Sobell and Sobell, 1992). Subjects also completed the Alco-hol Dependence Scale (ADS; Skinner and Allen, 1982), DrinkerInventory of Consequences (Miller et al., 1995); Beck DepressionInventory (BDI; Beck et al., 1996), and the Beck Anxiety Inventory(BAI; Beck and Steer, 1993). The Structured Clinical Interview forthe Diagnostic and Statistical Manual of Mental Disorders, 4th edi-tion (DSM-IV) (First et al., 2001) was used to characterize the sub-jects alcohol problems at the outset of the study.

Medication Treatment

Eligible subjects were randomly assigned (in a 3:2 ratio) to nalmef-ene 20 mg or matching placebo groups using random permutedblocks. Subjects were instructed to take one tablet of the study medi-cation 1 to 2 hours before any intake of alcohol, when drinkingseemed imminent. Only one dose of study drug was allowed per day.After 2 weeks of treatment, the dose could be doubled (i.e., to 40 mgonce daily) if the treatment response was considered by the investiga-tor to be inadequate, or it could be halved because of adverse effects.During the 28-week treatment period, subjects returned to the studysite nine times (initially weekly, then biweekly, and later monthly) forresearch assessments and medication dispensing. At each visit, alco-hol use and study medication intake since the previous visit wererecorded using the TLFB and a report of adverse events was elicited.At each visit, a brief psychosocial intervention based on the

BRENDAmodel (Volpicelli et al., 2001) was provided to all subjects,the main emphasis of which was on the correct use of the medication.The intervention included biopsychosocial assessment, feedback tothe subject on the assessment, simple advice to reduce alcohol drink-ing, and the monitoring of progress in treatment. No specic treat-ment goals were set.

SUBJECTS

Complete data were available for 272 subjects (i.e., 67.3% of thesubjects from the clinical trial, including 106 subjects from the pla-cebo group and 166 subjects from the nalmefene group). Enrollmentand blood samples for DNA began after the medication trial wasunderway, and subjects who had already dropped out by that timecould generally not be reached or persuaded to give a blood sample,which is reected in the signicantly greater completion rate forsubjects who participated in the pharmacogenetic substudy (85%),compared with the 131 subjects who did not provide a sample forgenetic analysis (21%) [v2(1) = 152.8, p < 0.001]. Table 1 shows the

Table 1. Demographic and Clinical Characteristics by Treatment Conditiona

Nalmefene (n = 166) Placebo (n = 106) Statistic p-value

Age (mean year [SD]) 49.8 (9.1) 49.3 (8.8) F(1,270) = 0.22 0.64Women (%) 32 (19.3%) 20 (18.9%) v2 = 0.01, df = 1 0.93Family history of alcoholism (%) 92 (55.4%) 63 (59.4%) v2 = 0.43, df = 1 0.52Previous alcohol treatments (n) 1.3 (2.9) 1.5 (3.7) F(1,270) = 0.28 0.60Number of DSM-IV alcohol dependence symptoms 6.6 (1.6) 6.8 (1.4) F(1,270) = 0.53 0.47Alcohol Dependence Scale score 17.5 (6.9) 18.3 (7.2) F(1,270) = 0.83 0.36Heavy drinking daysa per week 3.8 (1.7) 4.2 (1.7) F(1,270) = 3.81 0.052Very heavy drinking daysb per week 2.0 (1.8) 2.1 (1.7) F(1,270) = 0.08 0.77Abstinent days per week 2.5 (1.7) 2.1 (1.7) F(1,270) = 3.94 0.048Beck Depression Inventory score 13.8 (7.5) 14.2 (8.6) F(1,270) = 0.14 0.71Beck Anxiety Inventory score 9.2 (7.5) 11.0 (10.0) F(1,270) = 2.78 0.097

Values are mean (SD) or number (%).aDays on which men consumed 5 and women consumed 4 standard drinks.bDays on which men consumed 10 and women consumed 8 standard drinks.

OPIOID GENES AND NALMEFENE TREATMENT RESPONSE 1161

demographic and clinical characteristics of the participants in thepharmacogenetic substudy, by medication group. All subjects wereCaucasian and of Finnish ancestry and 80% were male.

Genes and Genotyping

DNA was extracted from whole blood using standard methods.Some of the SNPs (Table 2) examined were possible functionalvariants (OPRM1: rs1799971, rs648893, OPRK1: rs963549); theother SNPs (OPRD1: rs678849, rs2234918) were selected becausethey were genotyped in previous studies examining their associationto substance dependence [(Gelernter and Kranzler, 2000; Luo et al.,2003; Zhang et al., 2006); described in more detail in (Gelernter et al.,2007)].Four of the SNPs (rs1799971, rs648893, rs678849, and rs2234918)

were genotyped using the TaqMan uorogenic 5 nuclease assay(Livak et al., 1995) and the ABI PRISM 7900 Sequence DetectionSystem (ABI, Foster City, CA). All Taqman reactions were run induplicate using 2 ng of DNA and with 100% concordance. OPRK1rs963549 was genotyped as an restriction fragment length poly-morphism using 10 ng of DNA, 0.5 M Betaine, PC and KlenTaq;cycling parameters were 95C for 5 min followed by 35 cycles of 95 53 72 30s 30s 30s. PCR product was digested overnight with10 U of BstNI and run out on a 3% Metaphor agarose gel. At least8% of genotypes were repeated for quality control, with completeconcordance.

Statistical Analysis

The number of HDD per week (during the 28-week treatmentperiod), dened as a day on which men consumed 5 standarddrinks and women consumed 4 drinks, was the primary efcacy

variable in the treatment trial. A standard drink contained approxi-mately 12 g of ethanol. Secondary efcacy variables included theweekly number of days of ABS and of VHDD (men: 10 drinks;women: 8 drinks).Hierarchal multiple regression was used to test the interactive

effects of genotype and treatment. To ensure an adequate number ofsubjects in all subgroups, for each of the SNPs the minor allelehomozygote group was combined with the heterozygote group toyield a binary genotype variable. However, for SNPs rs2234918 andrs678849, where the genotype subgroups had adequate numbers, wealso used two dummy codes to contrast the more common homozy-gote to both the less common homozygote and the heterozygotegroup. Covariates (i.e., gender, family history of alcoholism, numberof previous alcohol treatments, the number of DSM-IV criteria met,ADS score, BDI total score, and BAI total score) were included inthe regression models if they demonstrated a signicant bivariateassociation with the dependent measures. We also covaried therespective pretreatment drinking measure (i.e., number of HDD,VHDD, and abstinent days per week in the 90 days prior to random-ization) in all analyses. Thus, signicant effects can be interpreted asaccounting for variance in residual change in the outcomes frombaseline to the end of treatment.We entered the predictors in three blocks: rst we entered the con-

trol variables and the treatment condition dummy code (0 = con-trol, 1 = treatment). Second, we entered all ve genotype dummycodes. We chose this strategy (i) because the genotype dummy codeswere virtually uncorrelated (of 10 pair-wise associations, only threegenotypes were signicantly related; the strongest association wasbetween rs648893 and rs1799971, phi = 0.318) and (ii) to control thetype I error rate (i.e., we only interpreted unique effects if the omni-bus test for the change in r2 was signicant). In the third block, weentered the ve treatment genotype product terms to test for theinteractive effects. Again, to protect against inating the type I errorrate, unique effects were only examined in the context of a signicantchange in r2. Regarding effect size, we report squared semi-partialcorrelations (i.e., Dr2 because of entry of the individual predictor)and 95% condence intervals for the unstandardized partial regres-sion coefcients.

RESULTS

A breakdown of pretreatment variables is shown in Table 1.There were signicant baseline differences in abstinent daysand a trend toward a signicant difference in the number ofHDD between the treatment groups. This possible bias washandled by the baseline correlation analysis.Results from the multiple regression analysis for HDD are

shown in Table 3. The analyses did not differ substantially forthe other outcome measures, particularly when the potentialfor type 1 error was accounted for. Consequently, the datawere not shown for the analysis of VHDD or ABS. Block oneaccounted for a signicant amount of variance for all threeoutcomes. The pretreatment drinking covariate was a signi-cant predictor in all models. Treatment condition was a signif-icant predictor in the HDD and VHDD models, but not inthe ABS model. Given the coding of treatment condition, thecoefcients shown in Table 3 represent the covariate-adjustedmean differences in HDD per week during treatment.Entry of blocks two (the genotype dummy codes) and three

(the treatment genotype product terms) into the modelsdid not result in signicant changes in r2. As a check, were-estimated the models examining each genotype separately

Table 2. Genotype and Allele Frequencies as a Function of MedicationGroup

Placebo(n = 106)

Nalmefene(n = 166) Statistic p-value

OPRM1 rs648893AA (%) 66 (62.3%) 103 (62.1%) v2 = 0.008, df = 2 0.996AG (%) 37 (34.9%) 58 (34.9%)GG (%) 3 (2.8%) 5 (3.0%)f(A) 0.80 0.80 v2 = 0.003, df = 1 0.995f(G) 0.20 0.20OPRD1 rs2234918 (T921C)AA (%) 42 (39.6%) 59 (35.5%) v2 = 1.29, df = 2 0.526AG (%) 45 (42.5%) 82 (49.4%)GG (%) 19 (17.9%) 25 (15.1%)f(A) 0.61 0.60 v2 = 0.02, df = 1 0.888f(G) 0.39 0.40OPRM1 rs1799971 (Asn40Asp)AA (%) 59 (55.7%) 108 (58.1%) v2 = 2.412, df = 1 0.120AG (%) 43 (40.6%) 53 (28.5%)GG (%) 4 (3.7%) 25 (13.4%)f(A) 0.76 0.72 v2 = 0.917, df = 1 0.338f(G) 0.24 0.28OPRD1 rs678849TT (%) 28 (26.4%) 32 (19.3%) v2 = 2.012, df = 2 0.366TC (%) 54 (50.9%) 90 (54.2%)CC (%) 24 (22.6%) 44 (26.5%)f(T) 0.52 0.46 v2 = 1.57, df = 1 0.211f(C) 0.48 0.54OPRK1 rs963549TT (%) 74 (69.8%) 131 (78.9%) v2 = 3.815, df = 2 0.149TC (%) 31 (29.2%) 32 (19.3%)CC (%) 1 (1.0%) 3 (1.8%)f(T) 0.84 0.89 v2 = 1.94, df = 1 0.164f(C) 0.16 0.11

1162 ARIAS ET AL.

along with its interaction with medication condition.Specically, these models included only the genotype of inter-est, medication condition, the treatment genotype productterm, and the corresponding pretreatment levels of drinking(the only signicant covariate). The substantive ndings weregenerally the same for this and the other outcome measures.Thus, the null ndings for the treatment genotype inter-actions were not because of redundancy among the predictorsor multicollinearity (Table 4).We also modeled rs2234918 and rs678849 as 3-level nomi-

nal variables (using two dummy codes and two geno-type treatment interaction predictors); the ndings did notchange substantively. Finally, the examination of the residualsfrom all three models showed no departure from normality.Some evidence of heteroscedastic residuals was found in theVHDD model; however, results using a log-transformed vari-able were identical to those reported above.

DISCUSSION

We found no evidence that allelic variation in any of thethree genes studied moderated the response to nalmefenetreatment. Specically, there was no evidence to support atreatment interaction with the Asn40Asp polymorphism

(rs1799971), or the other polymorphisms that were examined(including rs2234918 and rs678849 in OPRD1, and rs963549in OPRK1). The lack of a moderating effect of the Asn40Asppolymorphism differs from two of the four studies that haveexamined the moderating effect of this SNP on naltrexonetreatment effects (Anton et al., 2008; Mitchell et al., 2007;Oslin et al., 2003).There are a number of possible explanations for the lack of

a moderating effect of the Asn40Asp polymorphism on theresponse to nalmefene treatment. The underlying hypothesisis based on an unclear mechanism of interaction betweenmedication and genotype. Although there is consistent evi-dence to support an altered physiologic response to naloxonebased on the presence of the Asn40Asp polymorphism(Chong et al., 2006; Hernandez-Avila et al., 2003, 2007; Wandet al., 2002), a similar effect for naltrexone or nalmefene hasyet to be demonstrated. Further, although the structure ofnalmefene is similar to that of naltrexone, and the generalmechanism of action in alcohol dependence is thought to bethe same (Mason et al., 1999), the genetic moderators of theeffects of these medications may differ as a result of theirsubtle but potentially signicant pharmacokinetic and phar-macodynamic differences. It is also possible that the scheduleof administration (i.e., targeted in the nalmefene study, daily

Table 3. Multiple Regression Results for Heavy Drinking Days per Week

Block F Dr2 p-value Predictor B SE t p-value

95% CI for B

Dr2Lower Upper

1 19.752a 0.271

in the studies of naltrexone) could have inuenced themoderating effect of opioid receptor genotype on treatmentoutcome. The medication may need to be present andpharmacologically active on a daily basis in order to providea pharmacogenetic effect on drinking outcomes. It has alsobeen proposed that the duration of treatment (i.e., the initialacute phase of several weeks vs. longer-term treatment),and the expectation that pharmacogenetic effects will be mostprominent early in treatment, with the effect not being evidentover the course of a treatment trial, may explain the lack ofndings of genetic moderators of treatment with opioidantagonists (Gelernter et al., 2007). Specically, neuro-adaptive changes in opioid receptor regulation because ofchronic exposure may result in tolerance to some aspects ofthe response to opioid antagonists, which could includepharmacogenetic effects (Lesscher et al., 2003).The use of tag SNPs representing haplotype blocks in

OPRM1 that have been associated with risk of alcohol anddrug dependence and the inclusion of SNPs in both OPRD1and OPRK1 provide good representation of the opioid genevariation that could moderate the response to nalmefenetreatment. However, in this analysis only opioid receptorgenes were examined, so that other genetic effects were notdetectable. The Finnish population examined in this study isan isolated one that is ancestrally homogeneous, even com-pared with other European populations (Finnish GenomeCenter, https://bioportal.giu.). As much of the pharmacoge-netic research with Asn40Asp and other opioid gene variantshas been in more heterogeneous EA populations, it is possiblethat there are trans-acting genetic effects specic to the Finn-ish population that could obscure a pharmacogenetic effect.A factor that could potentially explain the discrepancy in

the ndings reported here and studies of the moderatingeffects of the Asn40Asp polymorphism on the response tonaltrexone treatment of alcohol dependence is that the tar-geted nalmefene study did not require a goal of ABS. This issimilar to the study by Mitchell et al. (2007), but in contrastto the studies by Oslin et al. (2003) and Anton et al. (2008),which had total ABS as their treatment goal. This interpreta-tion is not supported by the ndings of Gelernter et al. (2007),whose subjects were drawn from the VA Cooperative Studyof Naltrexone, the goal of which was ABS. In view of recentevidence that variation in c-aminobutyric acid A receptorsubunit genes (GABA-A) subunit genes may inuence theresponse to the psychotherapeutic treatment of alcoholism(Bauer et al., 2008), it is possible that the different psychoso-cial treatments in the studies examining the moderating effectsof opioid gene variation on medication response could haveconfounded the pharmacogenetic effects.The strengths of the present study are the homogeneous

sample, the positive nding of a medication treatment effect(which provides a clearer basis for a pharmacogenetic effect),and the examination of polymorphisms in all three opioidreceptor genes. Despite these strengths, detection of pharma-cogenetic effects may require greater statistical power thanwas afforded by a comparatively small sample size. Using the

data from Oslin et al. (2003), which compared the risk ofrelapse to heavy drinking within the group treated with nal-trexone, we estimated the effect size to be 0.695 (Chinn,2000), which is a medium effect size (Cohen, 1988). Using asimilar approach, data from Anton et al. (2008) on the likeli-hood of a good clinical outcome showed an effect size of0.966 for naltrexone in the Asp40 group. The analysis we con-ducted for HDD week had power of >0.8 to detect an effectsize of >0.6, with alpha = 0.05 and as many as 12 regres-sors, thus arguing against type II error. Reducing the numberof covariates (e.g., using only medication, genotype, and pre-treatment HDD) yields higher power to detect an effect sizeof this magnitude. However, given the possibility that the truepharmacogenetic effect for nalmefene could be smaller thanthat for naltrexone, we acknowledge that type II error couldexplain the lack of a pharmacogenetic effect in this analysis.In addition to reducing the size of the sample, the potential

exists for bias to have resulted from the fact that only two-thirds of the participants in the clinical trial by Karhuvaaraet al. (2007) provided blood for genetic analysis. The differ-ence in study completion rates between subjects in the phar-macogenetic analysis and those who did not offer bloodsamples was considerable (85% vs. 21%), and suggests thatthe subset of subjects included in the pharmacogenetic analy-sis were more adherent to treatment. As greater adherence toand or motivation to participate in treatment may lead tobetter outcomes in treatment trials, even when patients receivea placebo, it is possible that this may have obscured a phar-macogenetic effect (Oslin et al., 2002). However, the fact thatthe pharmacogenetic analysis subset showed a robust medica-tion treatment effect versus placebo argues against such con-founding. The greater exposure to medication in the subset ofsubjects participating in the pharmacogenetic analysis alsosupports the validity of our ndings, as these subjects wouldhave likely received enough exposure to the medication todemonstrate a gene by medication treatment interaction. Thefrequency of the Asp40 allele in the pharmacogenetic samplewas higher than the range of frequencies seen in other Euro-pean populations (Arias et al., 2006) and could reect differ-ential attrition in the sample participating in thepharmacogenetic substudy. The presence of a clear pharma-cological effect in the subsample for which we have geneticinformation argues against a relevant bias. Although the tar-geted medication approach used in the nalmefene study couldmake detection of a pharmacogenetic effect more difcult, itis unclear why this would not apply equally to the detectionof a pharmacological effect.Pharmacogenetic analysis of treatment trials in alcohol

dependence has focused on the moderating effects of opioidreceptor gene variation. It appears from the variable ndingsobtained in these studies that additional studies of multipleopioid receptor gene variants are required to clarify thegenetic basis for treatment response to naltrexone and nalmef-ene. In addition, the study of other genes that may inuencethe response to pharmacological treatment of alcoholism is afertile area of investigation. There is growing evidence that

1164 ARIAS ET AL.

variation in GABRA2, which encodes the alpha-2 subunit ofthe GABA-A receptor, is associated with alcohol dependence(Covault et al., 2004; Edenberg et al., 2004; Enoch et al.,2006; Fehr et al., 2006; Lappalainen et al., 2005; Soyka et al.,2008). Variation in that gene has also been shown to moder-ate the subjective response to acute alcohol administration(Pierucci-Lagha et al., 2005) and to predict drinking behavioras both a main effect and in combination with specic psy-chotherapies in Project MATCH (Bauer et al., 2008). To date,however, there are no published studies of the role of this genein predicting the response to pharmacotherapy. Other genesthat could moderate the response to alcoholism treatmentinclude dopaminergic, serotonergic, glutamatergic, choliner-gic, endocannabinoidergic, and neuroendocrine-related genes(Edenberg and Kranzler, 2005; Gelernter and Kranzler, inpress). Studies of the molecular signicance of variation inthese genes, as well as their functional evaluation in humanlaboratory studies, will help to determine their potential asmoderators of the response to alcohol pharmacotherapy.

ACKNOWLEDGMENTS

Clinical trial supported by Biotie Therapies Corp., Turku,Finland; genotyping and analysis supported by NIH grantsP50 AA03510, M01 RR06192 (University of ConnecticutGeneral Clinical Research Center), K24 AA13736 (to HRK),R01 AA11330, and K24 DA15105 (to JG).

REFERENCES

Anton RF, OMalley SS, Ciraulo DA, Cisler RA, Couper D, Donovan DM,

Gastfriend DR, Hosking JD, Johnson BA, LoCastro JS, Longabaugh R,

Mason BJ, Mattson ME, Miller WR, Pettinati HM, Randall CL, Swift R,

Weiss RD, Williams LD, Zweben A (2006) Combined pharmacotherapies

and behavioral interventions for alcohol dependence: the COMBINE study:

a randomized controlled trial. JAMA 295:20032017.

Anton RF, Oroszi G, OMalley S, Couper D, Swift R, Pettinati H, Goldman

D (2008) An evaluation of mu-opioid receptor (OPRM1) as a predictor of

naltrexone response in the treatment of alcohol dependence: results from the

Combined Pharmacotherapies and Behavioral Interventions for Alcohol

Dependence (COMBINE) study. Arch Gen Psychiatry 65:135144.

Anton RF, Pettinati H, Zweben A, Kranzler HR, Johnson B, Bohn MJ,

McCaul ME, Anthenelli R, Salloum I, Galloway G, Garbutt J, Swift R,

Gastfriend D, Kallio A, Karhuvaara S (2004) A multi-site dose ranging

study of nalmefene in the treatment of alcohol dependence. J Clin Psycho-

pharmacol 24:421428.

Arias A, Feinn R, Kranzler HR (2006) Association of an Asn40Asp (A118G)

polymorphism in the mu-opioid receptor gene with substance dependence: a

meta-analysis. Drug Alcohol Depend 83:262268.

Bauer LO, Covault J, Harel O, Das S, Gelernter J, Anton R, Kranzler HR

(2008) Variation in GABRA2 predicts drinking behavior in project

MATCH subjects. Alcohol Clin Exp Res 31:17801787.

Beck A, Steer R (1993) Beck Anxiety Inventory Manual. The Psychological

Corporation, San Antonio, TX.

Beck A, Steer R, Brown G (1996) Beck Depression Inventory, 2nd ed. Man-

ual. The Psychological Corporation, San Antonio, TX.

Befort K, Filliol D, Decaillot FM, Gaveriaux-Ruff C, Hoehe MR, Kieffer BL

(2001) A single nucleotide polymorphic mutation in the human mu-opioid

receptor severely impairs receptor signaling. J Biol Chem 276:31303137.

Beyer A, Koch T, Schroder H, Schulz S, Hollt V (2004) Effect of the A118G

polymorphism on binding afnity, potency and agonist-mediated endocyto-

sis, desensitization, and resensitization of the human mu-opioid receptor.

J Neurochem 89:553560.

Bond C, LaForge KS, Tian M, Melia D, Zhang S, Borg L, Gong J, Schluger

J, Strong JA, Leal SM, Tischeld JA, Kreek MJ, Yu L (1998) Single-

nucleotide polymorphism in the human mu opioid receptor gene alters beta-

endorphin binding and activity: possible implications for opiate addiction.

Proc Natl Acad Sci USA 95:96089613.

Chinn S (2000) A simple method for converting an odds ratio to effect size for

use in meta-analysis. Stat Med 19:31273131.

Chong RY, Oswald L, Yang X, Uhart M, Lin PI, Wand GS (2006) The l-opi-oid receptor polymorphism A118G predicts cortisol responses to naloxone

and stress. Neuropsychopharmacology 31:204211.

Cohen J (1988) Statistical Power Analysis for the Behavioral Sciences, 2nd ed.

Lawrence Erlbaum Associates, Hillsdale, NJ.

Covault J, Gelernter J, Hesselbrock V, Nellissery M, Kranzler HR (2004) Alle-

lic and haplotypic association of GABRA2 with alcohol dependence. Am J

Med Genet B Neuropsychiatr Genet 129:104109.

Drobes DJ, Anton RF, Thomas SE, Voronin K (2004) Effects of naltrexone

and nalmefene on subjective response to alcohol among non-treatment-seek-

ing alcoholics and social drinkers. Alcohol Clin Exp Res 28:13621370.

Edenberg HJ, Dick DM, Xuei X, Tian H, Almasy L, Bauer LO, Crowe RR,

Goate A, Hesselbrock V, Jones K, Kwon J, Li TK, Nurnberger JI Jr,

OConnor SJ, Reich T, Rice J, Schuckit MA, Porjesz B, Foroud T, Begleiter

H (2004) Variations in GABRA2, encoding the alpha 2 subunit of the

GABA(A) receptor, are associated with alcohol dependence and with brain

oscillations. Am J HumGenet 74:705714.

Edenberg HJ, Kranzler HR (2005) The contribution of genetics to addiction

therapy approaches. Pharmacol Ther 108:8693.

Emmerson PJ, Liu MR, Woods JH, Medzihradsky F (1994) Binding afnity

and selectivity of opioids at mu, delta and kappa receptors in monkey brain

membranes. J Pharmacol Exp Ther 271:16301637.

Enoch MA, Schwartz L, Albaugh B, Virkkunen M, Goldman D (2006)

Dimensional anxiety mediates linkage of GABRA2 haplotypes with alco-

holism. Am JMed Genet B Neuropsychiatr Genet 141:599607.

Fehr C, Sander T, Tadic A, Lenzen KP, Anghelescu I, Klawe C, Dahmen N,

Schmidt LG, Szegedi A (2006) Conrmation of association of the GABRA2

gene with alcohol dependence by subtype-specic analysis. Psychiatr Genet

16:917.

First M, Spitzer R, Gibbon M, Williams J (2001) 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 StatePsychiatric Institute, New York: Biometrics Research.

Gal TJ, DiFazio CA, Dixon R (1986) Prolonged blockade of opioid effect

with oral nalmefene. Clin Pharmacol Ther 40:537542.

Garbutt JC, Kranzler HR, OMalley SS, Gastfriend DR, Pettinati HM,

Silverman BL, Loewy JW, Ehrich EW (2005) Efcacy and tolerability of

long-acting injectable naltrexone for alcohol dependence: a randomized

controlled trial. JAMA 293:16171625.

Gelernter J, Gueorguieva R, Kranzler HR, Zhang H, Cramer J, Rosenheck

R, Krystal JH (2007) Opioid receptor gene (OPRM1, OPRK1, and

OPRD1) variants and response to naltrexone treatment for alcohol depen-

dence: results from the VA Cooperative Study. Alcohol Clin Exp Res

31:555563.

Gelernter J, Kranzler HR (2000) Variant detection at the delta opioid receptor

(OPRD1) locus and population genetics of a novel variant affecting protein

sequence. HumGenet 107:8688.

Gelernter J, Kranzler HR (2008) Genetics of addiction, in Textbook of

Substance Abuse Treatment, 4th ed. (Galanter M, Kleber H eds), pp.

1727. American Psychiatric Press, Inc, Washington, DC.

Hernandez-Avila C, Covault J, Wand G, Zhang H, Gelernter J, Kranzler HR

(2007) Population-specic effects of the Asn40Asp polymorphism at the m-

opioid receptor gene (OPRM1) on HPA axis activation. Pharmacogenet

Genomics 17:10311038.

Hernandez-Avila CA, Wand G, Luo X, Gelernter J, Kranzler HR (2003)

Association between the cortisol response to opioid blockade and the

Asn40Asp polymorphism at the mu-opioid receptor locus (OPRM1). Am J

Med Genet 118B:6065.

OPIOID GENES AND NALMEFENE TREATMENT RESPONSE 1165

Hoehe MR, Kopke K, Wendel B, Rohde K, Flachmeier C, Kidd KK,

Berrettini WH, Church GM (2000) Sequence variability and candidate gene

analysis in complex disease: association of mu opioid receptor gene varia-

tion with substance dependence. HumMol Genet 9:28952908.

Ingman K, Hagelberg N, Aalto S, Nagren K, Juhakoski A, Karhuvaara S,

Kallio A, Oikonen V, Hietala J, Scheinin H (2005) Prolonged central

mu-opioid receptor occupancy after single and repeated nalmefene dosing.

Neuropsychopharmacology 30:22452253.

Karhuvaara S, Simojoki K, Virta A, Rosberg M, Loyttyniemi E, Nurminen

T, Kallio A, Makela R (2007) Targeted nalmefene with simple medical man-

agement in the treatment of heavy drinkers: a randomized double-blind pla-

cebo-controlled multicenter study. Alcohol Clin Exp Res 31:11791187.

Kranzler HR, Gelernter J, OMalley S, Hernandez-Avila CA, Kaufman D

(1998) Association of alcohol or other drug dependence with alleles of the

mu opioid receptor gene (OPRM1). Alcohol Clin Exp Res 22:13591362.

Krystal JH, Cramer JA, Krol WF, Kirk GF, Rosenheck RA (2001)

Naltrexone in the treatment of alcohol dependence. N Engl J Med

345:17341739.

Lappalainen J, Krupitsky E, Remizov M, Pchelina S, Taraskina A, Zvartau E,

Somberg LK, Covault J, Kranzler HR, Krystal JH, Gelernter J (2005) Asso-

ciation between alcoholism and gamma-amino butyric acid alpha2 receptor

subtype in a Russian population. Alcohol Clin Exp Res 29:493498.

Lesscher HM, Bailey A, Burbach JP, Van Ree JM, Kitchen I, Gerrits MA

(2003) Receptor-selective changes in mu-, delta- and kappa-opioid receptors

after chronic naltrexone treatment in mice. Eur J Neurosci 17:10061012.

Livak KJ, Flood SJ, Marmaro J, Giusti W, Deetz K (1995) Oligonucleotides

with uorescent dyes at opposite ends provide a quenched probe system use-

ful for detecting PCR product and nucleic acid hybridization. PCRMethods

Appl 4:357362.

Luo X, Kranzler HR, Zhao H, Gelernter J (2003) Haplotypes at the

OPRM1 locus are associated with susceptibility to substance dependence

in European-Americans. Am J Med Genet B Neuropsychiatr Genet

120:97108.

Mason BJ, Ritvo EC, Morgan RO, Salvato FR, Goldberg G, Welch B, Man-

tero-Atienza E (1994) A double-blind, placebo-controlled pilot study to

evaluate the efcacy and safety of oral nalmefene HCl for alcohol depen-

dence. Alcohol Clin Exp Res 18:11621167.

Mason BJ, Salvato FR, Williams LD, Ritvo EC, Cutler RB (1999) A double-

blind, placebo-controlled study of oral nalmefene for alcohol dependence.

Arch Gen Psychiatry 56:719724.

McGeary JE, Monti PM, Rohsenow DJ, Tidey J, Swift R, Miranda R Jr

(2006) Genetic moderators of naltrexones effects on alcohol cue reactivity.

Alcohol Clin Exp Res 30:12881296.

Michel ME, Bolger G, Weissman BA (1985) Binding of a new opiate antago-

nist, nalmefene, to rat brain membranes. Methods Find Exp Clin Pharma-

col 7:175177.

Miller WR, Tonigan JS, Longabaugh R (1995) The Drinker Inventory of

Consequences (DrInC): An instrument for assessing adverse conse-

quences of alcohol abuse. Test Manual (Volume 4, Project MATCH

monograph Series). Rockville, MD: National Institute on Alcohol Abuse

and Alcoholism.

Mitchell JM, Fields HL, White RL, Meadoff TM, Joslyn G, RowbothamMC

(2007) The Asp40 mu-opioid receptor allele does not predict naltrexone

treatment efcacy in heavy drinkers. J Clin Psychopharmacol 27:112115.

Monterosso JR, Flannery BA, Pettinati HM, Oslin DW, Rukstalis M, OBrien

CP, Volpicelli JR (2001) Predicting treatment response to naltrexone: the

inuence of craving and family history. Am J Addict 10:258268.

Oslin DW, Berrettini W, Kranzler HR, Pettinati H, Gelernter J, Volpicelli JR,

OBrien CP (2003) A functional polymorphism of the mu-opioid receptor

gene is associated with naltrexone response in alcohol-dependent patients.

Neuropsychopharmacology 28:15461552.

Oslin DW, Pettinati H, Volpicelli JR (2002) Alcoholism treatment adherence:

older age predicts better adherence and drinking outcomes. Am J Geriatr

Psychiatry 10:740747.

Oswald LM, Wand GS (2004) Opioids and alcoholism. Physiol Behav 81:339

358.

Pierucci-Lagha A, Covault J, Feinn R, Nellissery M, Hernandez-Avila C,

Oncken C, Morrow AL, Kranzler HR (2005) GABRA2 alleles moderate

the subjective effects of alcohol, which are attenuated by nasteride. Neuro-

psychopharmacology 30:11931203.

Ray LA, Hutchison KE (2004) A polymorphism of the mu-opioid receptor

gene (OPRM1) and sensitivity to the effects of alcohol in humans. Alcohol

Clin Exp Res 28:17891795.

Rubio G, Ponce G, Rodriguez-Jimenez R, Jimenez-Arriero MA, Hoenicka J,

Palomo T (2005) Clinical predictors of response to naltrexone in alcoholic

patients: who benets most from treatment with naltrexone? Alcohol

Alcohol 40:227233.

Skinner HA, Allen BA (1982) Alcohol dependence syndrome: measurement

and validation. J Abnorm Psychol 91:199209.

Sobell L, Sobell M (1992) Timeline follow-back: a technique for assessing self-

reported alcohol consumption, in Measuring Alcohol Consumption (Litten

R, Allen J eds), pp 4165. Humana Press, Clifton, NJ.

Soyka M, Preuss UW, Hesselbrock V, Zill P, Koller G, Bondy B (2008)

GABA-A2 receptor subunit gene (GABRA2) polymorphisms and risk for

alcohol dependence. J Psychiatr Res 42:184191.

Srisurapanont M, Jarusuraisin N (2005) Opioid antagonists for alcohol depen-

dence. Cochrane Database Syst Rev, January 25, CD001867.

Volpicelli J, Pettinati HM, McLellan AT, OBrien CP (2001) Combining Med-

ication and Psychosocial Treatments for Addictions: the BRENDA

Approach. Guilford Press, New York.

Volpicelli JR, Volpicelli LA, OBrien CP (1995) Medical management of alco-

hol dependence: clinical use and limitations of naltrexone treatment. Alco-

hol Alcohol 30:789798.

Wand GS, McCaul M, Yang X, Reynolds J, Gotjen D, Lee S, Ali A (2002)

The mu-opioid receptor gene polymorphism (A118G) alters HPA axis acti-

vation induced by opioid receptor blockade. Neuropsychopharmacology

26:106114.

van den Wildenberg E, Wiers RW, Dessers J, Janssen RG, Lambrichs EH,

Smeets HJ, van Breukelen GJ (2007) A functional polymorphism of the

mu-opioid receptor gene (OPRM1) inuences cue-induced craving for alco-

hol in male heavy drinkers. Alcohol Clin Exp Res 31:110.

Zhang H, Luo X, Kranzler HR, Lappalainen J, Yang BZ, Krupitsky E,

Zvartau E, Gelernter J (2006) Association between two l-opioid receptorgene (OPRM1) haplotype blocks and drug or alcohol dependence. Hum

Mol Genet 15:807819.

Zhang Y, Wang D, Johnson AD, Papp AC, Sadee W (2005) Allelic expression

imbalance of human mu opioid receptor (OPRM1) caused by variant

A118G. J Biol Chem 280:3261832624.

1166 ARIAS ET AL.