Skip to main content

Advertisement

Log in

Using Genetics to Improve Addiction Treatment Outcomes

  • Addictions (J Grant, Section Editor)
  • Published:
Current Behavioral Neuroscience Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

This review will discuss recent studies that have employed pharmacogenetic findings to advance development of therapeutics and improve treatment outcomes for substance use disorder.

Recent Findings

Pharmacogenetic studies have inspired new treatment targets for smoking cessation, with mixed results. Promising initial evidence that mu-opioid receptor genotype (OPRM1 A118G) was associated with response to naltrexone treatment for alcohol dependence has not been supported in prospective trials. The nicotine metabolite ratio (NMR) may be useful for predicting response to smoking cessation treatment. Candidate gene studies suggest several genes that may identify responders for cocaine or opiate pharmacotherapy, but these studies require replication.

Summary

Significant progress has been made in pharmacogenetics studies of addiction treatment; however, efforts must be made to bridge the translational gap. Robust prospective studies are needed in order to gather sufficient information on the clinical utility of pharmacogenetic testing prior to implementation in a clinical setting.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance, •• Of major importance

  1. Center for Behavioral Health Statistics and Quality 2014 Behavioral health trends in the United States: results from the National Survey on Drug Use and Health. HHS Publication No. SMA 15–2927, NSDUH Series H-50). 2015. Retrieved from http://www.samhsa.gov/data/

  2. Substance Abuse and Mental Health Services Administration 2014. Prevention of substance abuse and mental illness. Available from: http://www.samhsa.gov/prevention.

  3. American Psychological Association 2013. Diagnostic and Statistical Manual of Mental Disorders. Washington, DC.

  4. Giacomini KM, Brett CM, Altman RB, Benowitz NL, Dolan ME, Flockhart DA, et al. The pharmacogenetics research network: from SNP discovery to clinical drug response. Clin Pharmacol Ther. 2007;81(3):328–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. de Leon J. Pharmacogenomics: the promise of personalized medicine for CNS disorders. Neuropsychopharmacology. 2009;34(1):159–72.

    Article  PubMed  Google Scholar 

  6. Murphy Jr GM, Kremer C, Rodrigues HE, Schatzberg AF. Pharmacogenetics of antidepressant medication intolerance. Am J Psychiatry. 2003;160(10):1830–5.

    Article  PubMed  Google Scholar 

  7. de Leon J, Armstrong SC, Cozza KL. Clinical guidelines for psychiatrists for the use of pharmacogenetic testing for CYP450 2D6 and CYP450 2C19. Psychosomatics. 2006;47(1):75–85.

    Article  PubMed  Google Scholar 

  8. Scordo MG, Spina E. Cytochrome P450 polymorphisms and response to antipsychotic therapy. Pharmacogenomics. 2002;3(2):201–18.

    Article  CAS  PubMed  Google Scholar 

  9. Rogers JF, Nafziger AN, Bertino Jr JS. Pharmacogenetics affects dosing, efficacy, and toxicity of cytochrome P450-metabolized drugs. Am J Med. 2002;113(9):746–50.

    Article  CAS  PubMed  Google Scholar 

  10. Malhotra AK, Murphy Jr GM, Kennedy JL. Pharmacogenetics of psychotropic drug response. Am J Psychiatry. 2004;161(5):780–96.

    Article  PubMed  Google Scholar 

  11. Roses AD. Pharmacogenetics and drug development: the path to safer and more effective drugs. Nat Rev Genet. 2004;5(9):645–56.

    Article  CAS  PubMed  Google Scholar 

  12. Nutt DJ, Lingford-Hughes A, Erritzoe D, Stokes PR. The dopamine theory of addiction: 40 years of highs and lows. Nat Rev Neurosci. 2015;16(5):305–12.

    Article  CAS  PubMed  Google Scholar 

  13. Volkow ND, Morales M. The brain on drugs: from reward to addiction. Cell. 2015;162(4):712–25.

    Article  CAS  PubMed  Google Scholar 

  14. Brody AL, Mandelkern MA, Olmstead RE, Allen-Martinez Z, Scheibal D, Abrams AL, et al. Ventral striatal dopamine release in response to smoking a regular vs a denicotinized cigarette. Neuropsychopharmacology. 2009;34(2):282–9.

    Article  CAS  PubMed  Google Scholar 

  15. Stokes PR, Mehta MA, Curran HV, Breen G, Grasby PM. Can recreational doses of THC produce significant dopamine release in the human striatum? NeuroImage. 2009;48(1):186–90.

    Article  PubMed  Google Scholar 

  16. Cruz MT, Bajo M, Schweitzer P, Roberto M. Shared mechanisms of alcohol and other drugs. Alcohol Res Health. 2008;31(2):137–47.

    PubMed  PubMed Central  Google Scholar 

  17. Patriquin MA, Bauer IE, Soares JC, Graham DP, Nielsen DA. Addiction pharmacogenetics: a systematic review of the genetic variation of the dopaminergic system. Psychiatr Genet. 2015;25(5):181–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bauer IE, Soares JC, Nielsen DA. The role of opioidergic genes in the treatment outcome of drug addiction pharmacotherapy: a systematic review. Am J Addict. 2015;24(1):15–23.

    Article  PubMed  Google Scholar 

  19. Allain F, Minogianis EA, Roberts DC, Samaha AN. How fast and how often: the pharmacokinetics of drug use are decisive in addiction. Neurosci Biobehav Rev. 2015;56:166–79.

    Article  PubMed  Google Scholar 

  20. Chen J, Lipska BK, Halim N, Ma QD, Matsumoto M, Melhem S, et al. Functional analysis of genetic variation in catechol-O-methyltransferase (COMT): effects on mRNA, protein, and enzyme activity in postmortem human brain. Am J Hum Genet. 2004;75(5):807–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Floresco SB, Magyar O. Mesocortical dopamine modulation of executive functions: beyond working memory. Psychopharmacology. 2006;188(4):567–85.

    Article  CAS  PubMed  Google Scholar 

  22. Caldú X, Vendrell P, Bartrés-Faz D, Clemente I, Bargalló N, Jurado MA, et al. Impact of the COMT Val108/158 Met and DAT genotypes on prefrontal function in healthy subjects. NeuroImage. 2007;37(4):1437–44.

    Article  PubMed  Google Scholar 

  23. Goldberg TE, Egan MF, Gscheidle T, Coppola R, Weickert T, Kolachana BS, et al. Executive subprocesses in working memory: relationship to catechol-O-methyltransferase Val158Met genotype and schizophrenia. Arch Gen Psychiatry. 2003;60(9):889–96.

    Article  CAS  PubMed  Google Scholar 

  24. Blasi G, Mattay VS, Bertolino A, Elvevåg B, Callicott JH, Das S, et al. Effect of catechol-O-methyltransferase Val158met genotype on attentional control. J Neurosci. 2005;25(20):5038–45.

    Article  CAS  PubMed  Google Scholar 

  25. Degen C, Zschocke J, Toro P, Sattler C, Wahl HW, Schönknecht P, et al. The COMT Val158Met polymorphism and cognitive performance in adult development, healthy aging and mild cognitive impairment. Dement Geriatr Cogn Disord. 2016;41(1–2):27–34.

    CAS  PubMed  Google Scholar 

  26. Bellander M, Bäckman L, Liu T, Schjeide BM, Bertram L, Schmiedek F, et al. Lower baseline performance but greater plasticity of working memory for carriers of the Val allele of the COMT Val158Met polymorphism. Neuropsychology. 2015;29(2):247–54.

    Article  PubMed  Google Scholar 

  27. Heim AF, Coyne MJ, Kamboh MI, Ryan C, Jennings JR. The catechol-O-methyltransferase Val158 Met polymorphism modulates organization of regional cerebral blood flow response to working memory in adults. Int J Psychophysiol. 2013;90(2):149–56.

    Article  PubMed  Google Scholar 

  28. Ihne JL, Gallagher NM, Sullivan M, Callicott JH, Green AE. Is less really more: does a prefrontal efficiency genotype actually confer better performance when working memory becomes difficult? Cortex. 2016;74:79–95.

    Article  PubMed  Google Scholar 

  29. Barnett JH, Scoriels L, Munafò MR. Meta-analysis of the cognitive effects of the catechol-O-methyltransferase gene Val158/108Met polymorphism. Biol Psychiatry. 2008;64(2):137–44.

    Article  CAS  PubMed  Google Scholar 

  30. Colilla S, Lerman C, Shields PG, Jepson C, Rukstalis M, Berlin J, et al. Association of catechol-O-methyltransferase with smoking cessation in two independent studies of women. Pharmacogenet Genomics. 2005;15(6):393–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Johnstone EC, Elliot KM, David SP, Murphy MF, Walton RT, Munafò MR. Association of COMT Val108/158Met genotype with smoking cessation in a nicotine replacement therapy randomized trial. Cancer Epidemiol Biomark Prev. 2007;16(6):1065–9.

    Article  CAS  Google Scholar 

  32. Munafò MR, Johnstone EC, Guo B, Murphy MF, Aveyard P. Association of COMT Val108/158Met genotype with smoking cessation. Pharmacogenet Genomics. 2008;18(2):121–8.

    Article  PubMed  Google Scholar 

  33. Nedic G, Nikolac M, Borovecki F, Hajnsek S, Muck-Seler D, Pivac N. Association study of a functional catechol-O-methyltransferase polymorphism and smoking in healthy Caucasian subjects. Neurosci Lett. 2010;473(3):216–9.

    Article  CAS  PubMed  Google Scholar 

  34. Munafò MR, Freathy RM, Ring SM, St Pourcain B, Smith GD. Association of COMT Val(108/158)Met genotype and cigarette smoking in pregnant women. Nicotine Tob Res. 2011;13(2):55–63.

    Article  PubMed  Google Scholar 

  35. Omidvar M, Stolk L, Uitterlinden AG, Hofman A, Van Duijn CM, Tiemeier H. The effect of catechol-O-methyltransferase Met/Val functional polymorphism on smoking cessation: retrospective and prospective analyses in a cohort study. Pharmacogenet Genomics. 2009;19(1):45–51.

    Article  CAS  PubMed  Google Scholar 

  36. Loughead J, Wileyto EP, Ruparel K, Falcone M, Hopson R, Gur R, et al. Working memory-related neural activity predicts future smoking relapse. Neuropsychopharmacology. 2015;40(6):1311–20.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Patterson F, Jepson C, Loughead J, Perkins K, Strasser AA, Siegel S, et al. Working memory deficits predict short-term smoking resumption following brief abstinence. Drug Alcohol Depend. 2010;106(1):61–4.

    Article  PubMed  Google Scholar 

  38. Loughead J, Wileyto EP, Valdez JN, Sanborn P, Tang K, Strasser AA, et al. Effect of abstinence challenge on brain function and cognition in smokers differs by COMT genotype. Mol Psychiatry. 2009;14(8):820–6.

    Article  CAS  PubMed  Google Scholar 

  39. Ashare RL, Valdez JN, Ruparel K, Albelda B, Hopson RD, Keefe JR, et al. Association of abstinence-induced alterations in working memory function and COMT genotype in smokers. Psychopharmacology. 2013;230(4):653–62.

    Article  CAS  PubMed  Google Scholar 

  40. Apud JA, Mattay V, Chen J, Kolachana BS, Callicott JH, Rasetti R, et al. Tolcapone improves cognition and cortical information processing in normal human subjects. Neuropsychopharmacology. 2007;32(5):1011–20.

    Article  CAS  PubMed  Google Scholar 

  41. Ashare RL, Wileyto EP, Ruparel K, Goelz PM, Hopson RD, Valdez JN, et al. Effects of tolcapone on working memory and brain activity in abstinent smokers: a proof-of-concept study. Drug Alcohol Depend. 2013;133(3):852–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Benowitz NL, Hukkanen J, Jacob 3rd P. Nicotine chemistry, metabolism, kinetics and biomarkers. Handb Exp Pharmacol. 2009;192:29–60.

    Article  CAS  Google Scholar 

  43. Messina ES, Tyndale RF, Sellers EM. A major role for CYP2A6 in nicotine C-oxidation by human liver microsomes. J Pharmacol Exp Ther. 1997;282(3):1608–14.

    CAS  PubMed  Google Scholar 

  44. Ray R, Tyndale RF, Lerman C. Nicotine dependence pharmacogenetics: role of variation in nicotine metabolizing enzymes. J Neurogenet. 2009;23(3):252–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Zhang W, Kilicarslan T, Tyndale RF, Sellers EM. Evaluation of methoxsalen, tranylcypromine, and tryptamine as specific and selective CYP2A6 inhibitors in vitro. Drug Metab Dispos. 2001;29(6):897–902.

    CAS  PubMed  Google Scholar 

  46. Bagdas D, Muldoon PP, Zhu AZ, Tyndale RF, Damaj MI. Effects of methoxsalen, a CYP2A5/6 inhibitor, on nicotine dependence behaviors in mice. Neuropharmacology. 2014;85:67–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Sellers EM, Kaplan HL, Tyndale RF. Inhibition of cytochrome P450 2A6 increases nicotine’s oral bioavailability and decreases smoking. Clin Pharmacol Ther. 2000;68(1):35–43.

    Article  CAS  PubMed  Google Scholar 

  48. Schnoll RA, Lerman C. Current and emerging pharmacotherapies for treating tobacco dependence. Expert Opin Emerg Drugs. 2006;11(3):429–44.

    Article  CAS  PubMed  Google Scholar 

  49. Bart G. Maintenace medication for opiate addiction: the foundation of recovery. J Addict Dis. 2012;31(3):207–25.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Sturgess JE, George TP, Kennedy JL, Heinz A, Müller DJ. Pharmacogenetics of alcohol, nicotine and drug addiction treatments. Addict Biol. 2011;16(3):357–76.

    Article  CAS  PubMed  Google Scholar 

  51. Verebey K, Mule SJ. Naltrexone pharmacology, pharmacokinetics, and metabolism: current status. Am J Drug Alcohol Abuse. 1975;2(3–4):357–63.

    Article  CAS  PubMed  Google Scholar 

  52. Zhang Y, Wang D, Johnson AD, Papp AC, Sadée W. Allelic expression imbalance of human mu-opioid receptor (OPRM1) caused by variant A118G. J Biol Chem. 2005;280:32618–24.

    Article  CAS  PubMed  Google Scholar 

  53. Robinson JE, Vardy E, DiBerto JF, Chefer VI, White KL, Fish EW, et al. Receptor reserve moderates mesolimbic responses to opioids in a humanized mouse model of the OPRM1 A118G polymorphism. Neuropsychopharmacology. 2015;40(11):2614–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Mura E, Govoni S, Racchi M, Carossa V, Ranzani GN, Allegri M, et al. Consequences of the 118A>G polymorphism in the OPRM1 gene: translation from bench to bedside? J Pain Res. 2013;6:331–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Mague SD, Blendy JA. OPRM1 SNP (A118G): involvement in disease development, treatment response, and animal models. Drug Alcohol Depend. 2010;108(3):172–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ray LA, Hutchison KE. A polymorphism of the mu-opioid receptor gene (OPRM1) and sensitivity to the effects of alcohol in humans. Alcohol Clin Exp Res. 2004;28(12):1789–95.

    Article  CAS  PubMed  Google Scholar 

  57. Ray LA, Hutchison KE. Effects of naltrexone on alcohol sensitivity and genetic moderators of medication response: a double-blind placebo-controlled study. Arch Gen Psychiatry. 2007;64(9):1069–77.

    Article  CAS  PubMed  Google Scholar 

  58. van den Wildenberg E, Wiers RW, Dessers J, Janssen RG, Lambrichs EH, Smeets HJ, et al. A functional polymorphism of the mu-opioid receptor gene (OPRM1) influences cue-induced craving for alcohol in male heavy drinkers. Alcohol Clin Exp Res. 2007;31(1):1–10.

    Article  PubMed  Google Scholar 

  59. Oslin DW, Berrettini W, Kranzler HR, Pettinati H, Gelernter J, Volpicelli JR, et al. A functional polymorphism of the mu-opioid receptor gene is associated with naltrexone response in alcohol-dependent patients. Neuropsychopharmacology. 2003;28(8):1546–52.

    Article  CAS  PubMed  Google Scholar 

  60. Anton RF, Oroszi G, O’Malley S, Couper D, Swift R, Pettinati H, et al. 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. 2008;65(2):135–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Chen AC, Morgenstern J, Davis CM, Kuerbis AN, Covault J, Kranzler HR. Variation in mu-opioid receptor gene (OPRM1) as a moderator of naltrexone treatment to reduce heavy drinking in a high functioning cohort. J Alcohol Drug Depend. 2013;1(1):101.

    PubMed  Google Scholar 

  62. •• Oslin DW, Leong SH, Lynch KG, Berrettini W, O’Brien CP, Gordon AJ, et al. Naltrexone vs placebo for the treatment of alcohol dependence: a randomized clinical trial. JAMA Psychiatry. 2015;72(5):430–7. The first prospective study of OPRM1 A112G polymorphism in predicting response to naltrexone treatment for alcohol dependence.

    Article  PubMed  Google Scholar 

  63. Coller JK, Cahill S, Edmonds C, Farquharson AL, Longo M, Minniti R, et al. OPRM1 A118G genotype fails to predict the effectiveness of naltrexone treatment for alcohol dependence. Pharmacogenet Genomics. 2011;21(12):902–5.

    Article  CAS  PubMed  Google Scholar 

  64. Arias AJ, Gelernter J, Gueorguieva R, Ralevski E, Petrakis IL. Pharmacogenetics of naltrexone and disulfiram in alcohol dependent, dually diagnosed veterans. Am J Addict. 2014;23(3):288–93.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Cahill K, Stevens S, Perera R, Lancaster T. Pharmacological interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. 2013;5:CD009329.

    Google Scholar 

  66. Bauld L, Bell K, McCullough L, Richardson L, Greaves L. The effectiveness of NHS smoking cessation services: a systematic review. J Public Health (Oxf). 2010;32(1):71–82.

    Article  Google Scholar 

  67. Hughes JR, Stead LF, Hartmann-Boyce J, Cahill K, Lancaster T. Antidepressants for smoking cessation. Cochrane Database Syst Rev. 2014;1:CD000031.

    Google Scholar 

  68. Silagy C, Lancaster T, Stead L, Mant D, Fowler G. Nicotine replacement therapy for smoking cessation. Cochrane Database Syst Rev. 2004;3:CD000146.

    Google Scholar 

  69. National Institute for Clinical Excellence 2002, Guidance on the use of nicotine replacement therapy (NTR) and bupropion for smoking cessation. Washington, DC: National Institute for Clinical Excellence. Technical appraisal report 39

  70. • Jones JD, Comer SD. A review of pharmacogenetic studies of substance-related disorders. Drug Alcohol Depend. 2015;152:1–14. A thorough review of studies evaluating candidate polymorphisms predicting treatment outcome for for nicotine, heroin, opiate, and stimulant dependence pharmacotherapy.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Allenby CE, Boylan KA, Lerman C, Falcone M. Precision medicine for tobacco dependence: development and validation of the nicotine metabolite ratio. J NeuroImmune Pharmacol. 2016;11(3):471–83.

    Article  PubMed  Google Scholar 

  72. Chenoweth MJ, Novalen M, Hawk Jr LW, Schnoll RA, George TP, Cinciripini PM, et al. Known and novel sources of variability in the nicotine metabolite ratio in a large sample of treatment-seeking smokers. Cancer Epidemiol Biomark Prev. 2014;23(9):1773–82.

    Article  CAS  Google Scholar 

  73. Lerman C, Tyndale R, Patterson F, Wileyto EP, Shields PG, Pinto A, et al. Nicotine metabolite ratio predicts efficacy of transdermal nicotine for smoking cessation. Clin Pharmacol Ther. 2006;79(6):600–8.

    Article  CAS  PubMed  Google Scholar 

  74. Schnoll RA, Patterson F, Wileyto EP, Tyndale RF, Benowitz N, Lerman C. Nicotine metabolic rate predicts successful smoking cessation with transdermal nicotine: a validation study. Pharmacol Biochem Behav. 2009;92(1):6–11.

    Article  CAS  PubMed  Google Scholar 

  75. Kaufmann A, Hitsman B, Goelz PM, Veluz-Wilkins A, Blazekovic S, Powers L, et al. Rate of nicotine metabolism and smoking cessation outcomes in a community-based sample of treatment-seeking smokers. Addict Behav. 2015;51:93–9.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Patterson F, Schnoll RA, Wileyto EP, Pinto A, Epstein LH, Shields PG, et al. Toward personalized therapy for smoking cessation: a randomized placebo-controlled trial of bupropion. Clin Pharmacol Ther. 2008;84(3):320–5.

    Article  CAS  PubMed  Google Scholar 

  77. •• Lerman C, Schnoll RA, Hawk Jr LW, Cinciripini P, George TP, Wileyto EP, et al. Use of the nicotine metabolite ratio as a genetically informed biomarker of response to nicotine patch or varenicline for smoking cessation: a randomised, double-blind placebo-controlled trial. Lancet Respir Med. 2015;3(2):131–8. A prospective clinical trial evaluating the nicotine metabolite ratio as a biomarker of response to smoking cessation treatment.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Carroll KM, Fenton LR, Ball SA, Nich C, Frankforter TL, Shi J, et al. Efficacy of disulfiram and cognitive behavior therapy in cocaine-dependent outpatients: a randomized placebo-controlled trial. Arch Gen Psychiatry. 2004;61(3):264–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Schroeder JP, Cooper DA, Schank JR, Lyle MA, Gaval-Cruz M, Ogbonmwan YE, et al. Disulfiram attenuates drug-primed reinstatment of cocaine seeking via inhibition of dopamine β-hydroxylase. Neuropsychopharmacology. 2010;35(12):2440–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. • Kosten TR, Wu G, Huang W, Harding MJ, Hamon SC, Lappalainen J, et al. Pharmacogenetic randomized trial for cocaine abuse: disulfiram and dopamine beta-hydroxylase. Biol Psychiatry. 2013;73(3):219–24. A randomized clinical trial providing evidence that DBH genotype significantly influences response to disulfiram for treatment of cocaine dependence.

    Article  CAS  PubMed  Google Scholar 

  81. Spellicy CJ, Kosten TR, Hamon SC, Harding MJ, Nielsen DA. ANKK1 and DRD2 pharmacogenetics of disulfiram treatment for cocaine abuse. Pharmacogenet Genomics. 2013;23(7):333–40.

    Article  CAS  PubMed  Google Scholar 

  82. Spellicy CJ, Kosten TR, Hamon SC, Harding MJ, Nielsen DA. The MTHFR C677T variant is associated with responsiveness to disulfiram treatment for cocaine dependency. Front Psychiatry. 2012;3:109.

    PubMed  Google Scholar 

  83. Nielsen DA, Ji F, Yuferov V, Ho A, Chen A, Levran O, Ott J, Kreek MJ. Genotype patterns that contribute to increased risk for or protection from developing heroin addiction. Mol Psychiatry. 2008;13(4):417–28.

    Article  CAS  PubMed  Google Scholar 

  84. Fonseca F, Gratacòs M, Escaramís G, De Cid R, Martín-Santos R, Fernández-Espejo E, et al. Response to methadone maintenance treatment is associated with the MYOCD and GRM6 genes. Mol Diagn Ther. 2010;14(3):171–8.

    Article  CAS  PubMed  Google Scholar 

  85. de Cid R, Fonseca F, Gratacòs M, Gutierrez F, Martín-Santos R, Estivill X, et al. BDNF variability in opioid addicts and response to methadone treatment: preliminary findings. Genes Brain Behav. 2008;7(5):515–22.

    Article  PubMed  Google Scholar 

  86. Gerra G, Somaini L, Leonardi C, Cortese E, Maremmani I, Manfredini M, et al. Association between gene variants and response to buprenorphine maintenance treatment. Psychiatry Res. 2014;215(1):202–7.

    Article  CAS  PubMed  Google Scholar 

  87. Clarke TK, Crist RC, Ang A, Ambrose-Lanci LM, Lohoff FW, Saxon AJ, et al. Genetic variation in OPRD1 and the response to treatment for opioid dependence with buprenorphine in European-American females. Pharmacogenomics J. 2014;14(3):303–8.

    Article  CAS  PubMed  Google Scholar 

  88. Shields AE, Lerman C. Anticipating clinical integration of pharmacogenetic treatment strategies for addiction: are primary care physicians ready? Clin Pharmacol Ther. 2008;83(4):635–9.

    Article  CAS  PubMed  Google Scholar 

  89. Bosker FJ, Hartman CA, Nolte IM, Prins BP, Terpstra P, Posthuma D, et al. Poor replication of candidate genes for major depressive disorder using genome-wide association data. Mol Psychiatry. 2011;16(5):516–32.

    Article  CAS  PubMed  Google Scholar 

  90. Shields AE, Lerman C, Sullivan P. Translating emerging research on the genetics of smoking into clinical practice: ethical and social considerations. Nicotine Tob Res. 2004;6(4):675–88.

    Article  PubMed  Google Scholar 

  91. Lesko LJ, Zineh I, Huang SM. What is clinical utility and why should we care? Clin Pharmacol Ther. 2010;88(6):729–33.

    Article  CAS  PubMed  Google Scholar 

  92. David SP, Commentary on Chen, et al. Another step on the road to clinical utility of pharmacogenetics for smoking cessation? Addiction, 2014. 2014;109(1):138–9.

    Google Scholar 

  93. FitzGerald GA. Measure for measure: biomarker standards and transparency. Sci Transl Med. 2016;8(343):343fs10.

    Article  PubMed  Google Scholar 

  94. • Lyman GH, Moses HL. Biomarker tests for molecularly targeted therapies: laying the foundation and fulfilling the dream. J Clin Oncol. 2016;34(17):2061-+. An overview of the recommendations set by the Institute of Medicine’s Committee on Policy Issues in the Clinical Development and Use of Biomarkers for Molecularly Targeted Therapies to lay the groundwork for using biomarker tests in a clinical setting.

  95. Bough KJ, Lerman C, Rose JE, McClernon FJ, Kenny PJ, Tyndale RF, et al. Biomarkers for smoking cessation. Clin Pharmacol Ther. 2013;93(6):526–38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Manolio TA. Bringing genome-wide association findings into clinical use. Nat Rev Genet. 2013;14(8):549–58.

    Article  CAS  PubMed  Google Scholar 

  97. Teutsch SM, Bradley LA, Palomaki GE, Haddow JE, Piper M, Calonge N, et al. The evaluation of genomic applications in practice and prevention (EGAPP) initiative: methods of the EGAPP Working Group. Genet Med. 2009;11(1):3–14.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Roses A. “Personalized medicine: elusive dream or imminent reality?”: a commentary. Clin Pharmacol Ther. 2007;81(6):801–5.

    Article  CAS  PubMed  Google Scholar 

  99. Khoury MJ, Coates RJ, Evans JP. Evidence-based classification of recommendations on use of genomic tests in clinical practice: dealing with insufficient evidence. Genet Med. 2010;12(11):680–3.

    Article  PubMed  Google Scholar 

  100. Hendershot CS. Pharmacogenetic approaches in the treatment of alcohol use disorders: addressing clinical utility and implementation thresholds. Addict Sci Clin Pract. 2014;9(1):20.

    Article  PubMed  PubMed Central  Google Scholar 

  101. Karriker-Jaffe KJ, Liu H, Kaplan LM. Understanding associations between neighborhood socioeconomic status and negative consequences of drinking: a moderated mediation analysis. Prev Sci. 2016;17(4):513–24.

    Article  PubMed  Google Scholar 

  102. Grosse SD, Teutsch SM, Haddix AC. Lessons from cost-effectiveness research for United States public health policy. Annu Rev Public Health. 2007;28:365–91.

    Article  PubMed  Google Scholar 

  103. Van den Bruel A, Cleemput I, Aertgeerts B, Ramaekers D, Buntinx F. The evaluation of diagnostic tests: evidence on technical and diagnostic accuracy, impact on patient outcome and cost-effectiveness is needed. J Clin Epidemiol. 2007;60(11):1116–22.

    Article  CAS  PubMed  Google Scholar 

  104. Levy DE, Youatt EJ, Shields AE. Primary care physicians’ concerns about offering a genetic test to tailor smoking cessation treatment. Genet Med. 2007;9(12):842–9.

    Article  PubMed  Google Scholar 

  105. Thompson C, Hamilton SP, Hippman C. Psychiatrist attitudes towards pharmacogenetic testing, direct-to-consumer genetic testing, and integrating genetic counseling into psychiatric patient care. Psychiatry Res. 2015;226(1):68–72.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Cheyenne Allenby is supported by a grant from the National Institutes of Health (T32 GM008076-32 to Dr. Julie Blendy).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mary Falcone.

Ethics declarations

Conflict of Interest

Cheyenne Allenby and Dr. Mary Falcone declare that they have no conflicts of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

This article is part of the Topical Collection on Addictions

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Allenby, C., Falcone, M. Using Genetics to Improve Addiction Treatment Outcomes. Curr Behav Neurosci Rep 4, 1–9 (2017). https://doi.org/10.1007/s40473-017-0106-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40473-017-0106-9

Keywords

Navigation