An Evaluation of μ-Opioid Receptor (OPRM1) as a Predictor of Naltrexone Response in the Treatment of Alcohol Dependence

Anton, Raymond F.; Oroszi, Gábor; O’Malley, Stephanie S.; Couper, David J.; Swift, Robert M.; Pettinati, Helen M.; Goldman, David

doi:10.1001/archpsyc.65.2.135

Cited by 413 publications

(141 citation statements)

References 52 publications

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“…While the amount of therapy provided was not extensive and is not as specific as cognitive behavioural therapy (CBT), it is possible that the nine sessions of BRENDA therapy could have interfered with finding a significant pharmacogenetic effect via a ‘ceiling effect’. A similar explanation was proposed by Anton et al, [58] who found no effect when subjects who received the CBI were included in the analysis.…”

Section: Clinical Pharmacogenetic Treatment Trialssupporting

confidence: 69%

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Pharmacogenetically Driven Treatments for Alcoholism

Arias

Sewell

2012

CNS Drugs

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Pharmacogenetic analyses of treatments for alcohol dependence attempt to predict treatment response and side-effect risk for specific medications. We review the literature on pharmacogenetics relevant to alcohol dependence treatment, and describe state-of-the-art methods of pharmacogenetic research in this area. Two main pharmacogenetic study designs predominate: challenge studies and treatment-trial analyses. Medications studied include US FDA-approved naltrexone and acamprosate, both indicated for treating alcohol dependence, as well as several investigational (and off-label) treatments such as sertraline, olanzapine and ondansetron. The best-studied functional genetic variant relevant to alcoholism treatment is rs1799971, a single-nucleotide polymorphism in exon 1 of the OPRM1 gene that encodes the μ-opioid receptor. Evidence from clinical trials suggests that the presence of the variant G allele of rs1799971 may predict better treatment response to opioid receptor antagonists such as naltrexone. Evidence from clinical trials also suggests that several medications interact pharmacogenetically with variation in genes that encode proteins involved in dopaminergic and serotonergic neurotransmission. Variation in the DRD4 gene, which encodes the dopamine D4 receptor, may predict better response to naltrexone and olanzapine. A polymorphism in the serotonin transporter gene SLC6A4 promoter region appears related to differential treatment response to sertraline depending on the subject’s age of onset of alcoholism. Genetic variation in SLC6A4 may also be associated with better treatment response to ondansetron. Initial pharmacogenetic efforts in alcohol research have identified functional variants with potential clinical utility, but more research is needed to further elucidate the mechanism of these pharmacogenetic interactions and their moderators in order to translate them into clinical practice.

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Section: Clinical Pharmacogenetic Treatment Trialssupporting

confidence: 69%

“…A higher percentage of subjects with abstinence or a controlled, non-risky drinking pattern, and low ratings of alcohol-related consequences also had the Gallele (p= 0.005, OR= 5.75, 95% CI 1.88, 17.54). [58,59] …”

Section: Clinical Pharmacogenetic Treatment Trialsmentioning

confidence: 99%

Pharmacogenetically Driven Treatments for Alcoholism

Arias

Sewell

2012

CNS Drugs

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“…For example, a secondary analysis of the COMBINE study (Anton et al 2006) was designed to examine whether patients heterozygous (Asp40/Asn40) or homozygous (Asp40/Asp40) for the mu-opioid receptor gene (ORPM1) Asp40 allele responded better to naltrexone (Anton et al 2008). Results of the genotyping in 911 of the 1383 patients demonstrated that patients receiving naltrexone as well as medication management to have a significantly greater response if that individual had at least one copy of the OPRM1 Asp40 allele (Anton et al 2008).…”

Section: The Potential Contribution Of Subtype Classifications In Thementioning

confidence: 99%

“…Results of the genotyping in 911 of the 1383 patients demonstrated that patients receiving naltrexone as well as medication management to have a significantly greater response if that individual had at least one copy of the OPRM1 Asp40 allele (Anton et al 2008).…”

Section: The Potential Contribution Of Subtype Classifications In Thementioning

confidence: 99%

Typologies of Alcohol Dependence. From Jellinek to Genetics and Beyond

et al. 2009

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The goal of typology research is to identify subtypes of alcohol dependent (AD) patients sharing fundamental characteristics and try to match each subtype, with the most precise treatment strategy. This review provides a comprehensive history of the literature on alcohol dependent subtypes starting from the earliest attempt made by Jellinek. The binary models identified most closely with Cloninger and Babor as well as the successively more complex classifications are discussed. Typology classification potentially useful in guiding the treatment of AD patients, especially in the case of the serotonergic medications. Contrasting data suggests that other factors could influence the response to a medication and/or that more complex typologies should be identified. In summary, typology models may assist in the ascertainment criteria for clinical trials performed in behavioral and pharmacotherapeutic interventions. Greater emphasis, however, must be made to more clearly delineate this field of research, while moving toward more standardized typologies.

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“…While the value of the single-nucleotide polymorphism (SNP) of the μ-opioid receptor (OPRM1 Asn40Asp) to guide pharmacotherapy in opioid dependence remains uncertain, the search for other SNPs and more complex models integrating multiple genes with environment continues. [36][37][38][39] Another category of predictors of addiction severity and treatment response not usually employed in clinical trials and practice includes symptom provocation, such as drug craving in response to drug-related cues. [40][41][42][43] To some extent, this is analogous to a cardiac stress test or a glucose tolerance test in medicine.…”

mentioning

confidence: 99%