Strategies to combat addictions

Preventing Addiction

The greater vulnerability of adolescents to experimentation with drugs of abuse and to subsequent addiction underscores why prevention of early exposure is such an important strategy to combat drug addiction. Epidemiologic studies show that the prevalence of drug use in adolescents has changed significantly over the past 30 years, and some of the decreases seem to be related to education about the risks of drugs. For example, for marijuana, the prevalence rates of use in the United States in 1979 were as high as 50%, whereas in 1992, they were as low as 20% (¹⁰⁰) (Fig. 1-4). This changing pattern of marijuana use seems to be related in part to the perception of the risks associated with the drug; when adolescents perceived the drug to be risky, the rate of use was low, whereas when they did not, the rate of use was high. Similarly, the significant decreases in ecstasy use as well as cigarette smoking in adolescents (¹⁰⁰) seem to partly reflect effective educational campaigns. These results show that, despite the fact that adolescents are at a stage in their lives when they are more likely to take risks, interventions that educate them about the harmful effects of drugs with age-appropriate messages can decrease the rate of drug use (¹⁰¹,¹⁰²,¹⁰³). However, not all media campaigns and school-based educational programs have been successful (¹⁰⁴,¹⁰⁵). Tailored interventions that take into account socioeconomic, cultural, and age and gender characteristics of children and adolescents are more likely to improve the effectiveness of the interventions.

At present, prevention strategies include not only educational interventions based on comprehensive school-based programs and effective media campaigns and strategies that decrease access to drugs and alcohol but also strategies that provide supportive community activities that engage adolescents in productive and creative ways. However, as we begin to understand the neurobiologic consequences that underlie the adverse environmental factors that increase the risks for drug use and for addiction, we will be able to develop interventions to counteract these changes. In addition, as we deepen our knowledge of how different genes (and their encoded proteins) make a person more or less vulnerable to taking drugs and to addiction, more targets will be available to tailor interventions for those at higher risk.

Finally, we can also expect a renewed focus in the near future in the research and development of interventions that increase general resilience leading to universally better outcomes. Particularly promising in this context are the recent results of a major longitudinal study showing a dramatic positive influence of childhood self-control upon a wide range of life outcomes, including substance abuse risk, overall health, and financial status (¹⁰⁶).

Treating Addiction

The adaptations in the brain that result from chronic drug exposure are long-lasting; therefore, addiction must be viewed as a chronic disease. This is why long-term treatment will be required for most addiction cases, just as it is for other chronic diseases, like hypertension, diabetes, or asthma (¹⁰⁷). By recognizing the likelihood of relapse, this perspective radically modifies our expectations of addiction treatment outcomes, establishing the need for a more rational, chronic management model for addiction treatment (¹⁰⁸). First, discontinuation of treatment, as for other chronic diseases, is likely to result in relapse. Also, as for other chronic medical conditions, relapse should not be interpreted as a failure of treatment (as is the prevailing view in most cases of addiction), but instead as a temporary setback due to a lack of compliance or tolerance to an effective treatment (¹⁰⁷). It is rather telling that the rates of relapse and recovery in the treatment of drug addiction are equivalent to those of other medical diseases (¹⁰⁷).

The involvement of multiple brain circuits (reward, motivation, memory, learning, interoception, inhibitory control, and executive function) and the associated behavioral disruptions point to the need for a multimodal approach in the treatment of the addicted individual. Therefore, interventions should not be limited to inhibiting the rewarding effects of a drug but also explore and include strategies to enhance the saliency value of natural reinforcers (including social support), strengthen inhibitory control, decrease conditioned responses, improve mood if disrupted, and strengthen executive function and decision making. For example, a recent report details an apparently successful targeting of executive function by exposing the left dorsolateral prefrontal cortex of smokers with repetitive transcranial magnetic stimulation, a single session of which significantly reduced subjective craving induced by smoking cues in these nicotine-dependent participants (¹⁰⁹). However, more work is required to determine if these effects are sustained outside the laboratory setting and to determine if they result in decreased smoking.

Among the recommended multimodal approaches, the most obvious rely on the combination of pharmacologic and behavioral interventions, which might target different underlying factors and therefore yield synergistic effects. Such combined treatment is strongly recommended because behavioral and pharmacologic treatments are thought to operate by different yet complementary mechanisms that can have additive or even synergistic effects. Thus, it could be expected that addiction treatments that use behavioral interventions would be more effective if complemented with medications to help the patient remain drug free. For example, behavioral approaches complement most tobacco addiction treatment programs. They can amplify the effects of medications by teaching people how to manage stress, recognize and avoid high-risk situations for smoking relapse, and develop alternative coping strategies (e.g., cigarette refusal skills, assertiveness, and time management skills) that they can practice in treatment, social, and work settings (¹¹⁰,¹¹¹). Thus, it is rather unfortunate that most alcohol and drug abuse treatment programs in the United States are, because of their 12-Step orientation, more often than not adamantly opposed to taking advantage of effective pharmacotherapies (¹¹²).

Pharmacologic Intervention

Pharmacologic interventions can be grouped into two classes. First, there are those that interfere with the reinforcing effects of drugs of abuse (i.e., medications that interfere with the binding to a target, drug-induced dopamine increase, postsynaptic responses, or with the drug’s delivery to the brain like antidrug antibodies, or medications that trigger aversive responses). Second, there are those that compensate for the adaptations that either preceded or developed after long-term use (i.e., medications that decrease the prioritized motivational value of the drug, enhance the saliency value of natural reinforcers, or interfere with conditioned responses, stress-induced relapse, or physical withdrawal). The usefulness of some addiction medications has been clearly validated; for others, the data are still preliminary, and for these, most results are limited to promising preclinical findings. Table 1-1 summarizes proven medications and medications for which there are preliminary clinical/preclinical data. Many of these promising new medications target different neurotransmitters (such as GABA, serotonin, or glutamate) relative to older drugs, offering a wider range of therapeutic options. Also combining medications may increase their efficacy as recently shown for the treatment of smoking cessation (¹⁵⁴). Thus, future studies are needed to determine if medications that by themselves have not been shown to be effective for treatment of addiction (i.e., amphetamine for cocaine addiction) might provide benefits when combined with drugs with different mechanisms of action (i.e., amphetamines + topiramate).

Behavioral Interventions

In a similar fashion, behavioral interventions can be classified by their intended remedial function, such as to strengthen inhibitory control circuits, provide alternative reinforcers, or strengthen executive function. Traditionally, behavioral therapy has focused on symptom-based targets rather than underlying causes of addiction. However, for other brain disorders, new views of brain plasticity, which recognize the capacity of neurons in the adult brain to increase synaptic connections and in certain instances to regenerate (¹⁵⁵), have resulted in more focused cognitive–behavioral interventions designed to increase the efficiency of dysfunctional brain circuits. This has been applied in attempts to improve reading in children with learning disabilities (¹⁵⁶), memory-related brain activity in Alzheimer patients (¹⁵⁷), to strengthen voluntary cortical control in children with ADHD (¹⁵⁸), and to facilitate motor and memory rehabilitation after brain injury (⁵⁸). We are beginning to see the first glimpses of this general approach as potentially applicable for the treatment of drug addiction. For example, a small positive relationship has been found between cognitive-specific strategies, such as using positive self-talk and an increased ability to cope with the urge to smoke (¹⁵⁹). Similarly, a recent imaging study of cocaine abusers showed that specific instructions to purposefully inhibit cue-induced craving was associated with inhibition in the (limbic) NAc, insula, and orbitofrontal and cingulate cortices and did indeed reduce cocaine craving (¹⁶⁰). Dual approaches that pair cognitive–behavioral strategies with medications to compensate or counteract the neurobiologic changes induced by chronic drug exposure are also a promising area of translational research that might, in the near future, provide more robust and longer-lasting treatments for addiction than either given in isolation (¹⁶¹). A new and exciting area of research in this context has emerged to address the question of whether putative cognitive enhancers (e.g., galanthamine, modafinil, atomoxetine, methylphenidate, and guanfacine) could improve treatment outcomes when used as adjuvants for substance users with discernible cognitive impairments (¹⁶²). An additional emerging area of translational research focuses on understanding how and why behavioral interventions work in terms of neurobiologic function and structure (¹⁶³,¹⁶⁴).

Treating Comorbidities

Abuse of multiple substances, such as alcohol and nicotine or alcohol and cocaine, should be considered in the proper management of the addicted individual. Similarly, comorbidities with other mental illnesses will require treatment for the mental illness concurrent with the treatment for drug abuse. Because drugs of abuse adversely affect many organs in the body (Fig. 1-5), they can contribute to the burden of many medical diseases, including cancer, cardiovascular and pulmonary diseases, HIV/AIDS, and hepatitis C, as well as to accidents and violence. Therefore, substance-abuse treatment will help to prevent or improve the outcome for many medical diseases. The HIV/AIDS epidemic provides one of the best examples: Drug abuse and addiction has been fueling the global spread of HIV from the very beginning of the AIDS epidemic. This inextricable connection is predicated on at least three major threads: (a) the direct effects of contaminated injection drug use on infection rates, (b) the indirect impact of abused drugs on high-risk sex behaviors and treatment adherence, and (c) drugs’ ability to worsen the neurologic complications stemming from an HIV infection. Fortunately, recent research has now shown conclusively (a) that HIV prevention among drug users (which includes HIV treatment) is effective in reducing HIV prevalence and (b) that treating substance use disorders (particularly with the aid of new and more effective medications) improves HIV treatment outcomes can and should be parlayed into global instruments for severing those threads once and for all. A particularly promising approach in this context has emerged in the form of the Seek, Test, Treat, and Retain paradigm that seeks out hard-to-reach/high-risk populations, including substance abusers and those in the criminal justice system; tests them for HIV; links those who test positive to HIV treatment and other services; and provides the necessary support to ensure these individuals remain in the care system (¹⁶⁵,¹⁶⁶).

Références

1. Parvaz MA, Alia-Klein N, Woicik PA, et al. Neuroimaging for drug addiction and related behaviors. Rev Neurosci 2011;22:609–624.

2. Seo D, Lacadie CM, Tuit K, et al. Disrupted ventromedial prefrontal function, alcohol craving, and subsequent relapse risk. JAMA Psychiatry 2013;70:1–13.

3. Leshner AI. Addiction is a brain disease, and it matters. Science 1997;278:45–47.

4. Baler RD, Volkow ND. Addiction as a systems failure: focus on adolescence and smoking. J Am Acad Child Adolesc Psychiatry 2011;50:329–339.

5. Koob GF, Volkow ND. Neurocircuitry of addiction. Neuropsychopharmacology 2010;35:217–238.

6. Nielsen DA, Utrankar A, Reyes JA, et al. Epigenetics of drug abuse: predisposition or response. Pharmacogenomics 2012;13:1149–1160.

7. Chen CY, Storr CL, Anthony JC. Early-onset drug use and risk for drug dependence problems. Addict Behav 2009;34:319–322.

8. Mental Health Services Administration (SAMHSA). Results from the 2008 National Survey on Drug Use and Health: National findings. (Office of Applied Studies, NSDUH Series H–36, DHHS Publication No. SMA 09–4434). Rockville, MD: SAMHSA. Retrieved June 6, 2011.

9. Doremus-Fitzwater TL, Varlinskaya EI, Spear LP. Motivational systems in adolescence: possible implications for age differences in substance abuse and other risk-taking behaviors. Brain Cogn2009;72:114–123.

10. Spear LP. The adolescent brain and age-related behavioral manifestations. Neurosci Biobehav Rev2000;24:417–463.

11. Sowell ER, Peterson BS, Thompson PM, et al. Mapping cortical change across the human life span. Nat Neurosci 2003;6:309–315.

12. Adriani W, Spijker S, Deroche-Gamonet V, et al. Evidence for enhanced neurobehavioral vulnerability to nicotine during periadolescence in rats. J Neurosci 2003;23:4712–4716.

13. Adriani W, Deroche-Gamonet V, Le Moal M, et al. Preexposure during or following adolescence differently affects nicotine-rewarding properties in adult rats. Psychopharmacology (Berl)2006;184:382–390.

14. Goriounova NA, Mansvelder HD. Nicotine exposure during adolescence leads to short- and long-term changes in spike timing-dependent plasticity in rat prefrontal cortex. J Neurosci2012;32:10484–10493.

15. Levine A, Huang Y, Drisaldi B, et al. Molecular mechanism for a gateway drug: epigenetic changes initiated by nicotine prime gene expression by cocaine. Sci Transl Med 2011;3:107ra109.

16. Fleming RL, Acheson SK, Moore SD, et al. In the rat, chronic intermittent ethanol exposure during adolescence alters the ethanol sensitivity of tonic inhibition in adulthood. Alcohol Clin Exp Res2012;36:279–285.

17. Fleming RL, Li Q, Risher ML, et al. Binge-pattern ethanol exposure during adolescence, but not adulthood, causes persistent changes in GABA(A) receptor-mediated tonic inhibition in dentate granule cells. Alcohol Clin Exp Res 2013;37:1154–1160.

18. Grant BF, Stinson FS, Harford TC. Age at onset of alcohol use and DSM-IV alcohol abuse and dependence: a 12-year follow-up. J Subst Abuse 2001;13:493–504.

19. Di Chiara G, Bassareo V, Fenu S, et al. Dopamine and drug addiction: the nucleus accumbens shell connection. Neuropharmacology 2004;47(Suppl 1):227–241.

20. Gupta S, Kulhara P. Cellular and molecular mechanisms of drug dependence: an overview and update. Indian J Psychiatry 2007;49:85–90.

21. Wise RA. Brain reward circuitry: insights from unsensed incentives. Neuron 2002;36:229–240.

22. Madras BK, Fahey MA, Bergman J, et al. Effects of cocaine and related drugs in nonhuman primates. I. [3H]cocaine binding sites in caudate-putamen. J Pharmacol Exp Ther 1989;251:131–141.

23. McFadden LM, Stout KA, Vieira-Brock PL, et al. Methamphetamine self-administration acutely decreases monoaminergic transporter function. Synapse 2012;66:240–245.

24. Partilla JS, Dempsey AG, Nagpal AS, et al. Interaction of amphetamines and related compounds at the vesicular monoamine transporter. J Pharmacol Exp Ther 2006;319:237–246.

25. Kreek MJ, LaForge KS, Butelman E. Pharmacotherapy of addictions. Nat Rev Drug Discov2002;1:710–726.

26. Salamone JD, Correa M. The mysterious motivational functions of mesolimbic dopamine. Neuron2012;76:470–485.

27. Schultz W, Tremblay L, Hollerman JR. Reward processing in primate orbitofrontal cortex and basal ganglia. Cereb Cortex 2000;10:272–284.

28. Schultz W. Behavioral dopamine signals. Trends Neurosci 2007;30:203–210.

29. Cohen JY, Haesler S, Vong L, et al. Neuron-type-specific signals for reward and punishment in the ventral tegmental area. Nature 2012;482:85–88.

30. Volkow ND, Wang GJ, Fowler JS, et al. Addiction: beyond dopamine reward circuitry. Proc Natl Acad Sci U S A 2011;108:15037–15042.

31. Schultz W. Updating dopamine reward signals. Curr Opin Neurobiol 2013;23:229–238.

32. Horvitz JC. Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events. Neuroscience 2000;96:651–656.

33. McClure SM, Daw ND, Montague PR. A computational substrate for incentive salience. Trends Neurosci 2003;26:423–428.

34. Schultz W. Reward signaling by dopamine neurons. Neuroscientist 2001;7:293–302.

35. Ito R, Dalley JW, Howes SR, et al. Dissociation in conditioned dopamine release in the nucleus accumbens core and shell in response to cocaine cues and during cocaine-seeking behavior in rats. J Neurosci 2000;20:7489–7495.

36. Nieh EH, Kim SY, Namburi P, et al. Optogenetic dissection of neural circuits underlying emotional valence and motivated behaviors. Brain Res 2013;1511:73–92.

37. Volkow ND, Wang GJ, Tomasi D, et al. The addictive dimensionality of obesity. Biol Psychiatry2013;73:811–818.

38. Koob GF. Theoretical frameworks and mechanistic aspects of alcohol addiction: alcohol addiction as a reward deficit disorder. Curr Top Behav Neurosci 2013;13:3–30.

39. Bock R, Shin JH, Kaplan AR, et al. Strengthening the accumbal indirect pathway promotes resilience to compulsive cocaine use. Nat Neurosci 2013;16:632–638.

40. Cuzon Carlson VC, Seabold GK, Helms CM, et al. Synaptic and morphological neuroadaptations in the putamen associated with long-term, relapsing alcohol drinking in primates. Neuropsychopharmacology 2011;36:2513–2528.

41. Naqvi NH, Bechara A. The insula and drug addiction: an interoceptive view of pleasure, urges, and decision-making. Brain Struct Funct 2010;214:430–450.

42. Baldwin PR, Alanis R, Salas R. The role of the habenula in nicotine addiction. J Addict Res Ther2011;S1:2.

43. Schmidt HD, McGinty JF, West AE, et al. Epigenetics and psychostimulant addiction. Cold Spring Harb Perspect Med 2013;3(3):a012047.

44. Nestler EJ. Transcriptional mechanisms of drug addiction. Clin Psychopharmacol Neurosci2012;10:136–143.

45. Zhou FC, Anthony B, Dunn KW, et al. Chronic alcohol drinking alters neuronal dendritic spines in the brain reward center nucleus accumbens. Brain Res 2007;1134:148–161.

46. Kroener S, Mulholland PJ, New NN, et al. Chronic alcohol exposure alters behavioral and synaptic plasticity of the rodent prefrontal cortex. PLoS One 2012;7:e37541.

47. Robinson TE, Gorny G, Mitton E, et al. Cocaine self-administration alters the morphology of dendrites and dendritic spines in the nucleus accumbens and neocortex. Synapse 2001;39:257–266.

48. Cui C, Noronha A, Morikawa H, et al. New insights on neurobiological mechanisms underlying alcohol addiction. Neuropharmacology 2012;67:223–232.

49. Volkow ND, Fowler JS. Addiction, a disease of compulsion and drive: involvement of the orbitofrontal cortex. Cereb Cortex 2000;10:318–325.

50. Volkow ND, Fowler JS, Wang GJ, et al. Dopamine in drug abuse and addiction: results of imaging studies and treatment implications. Arch Neurol 2007;64:1575–1579.

51. Goldstein RZ, Volkow ND. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci 2011;12:652–669.

52. Volkow ND, Wang GJ, Tomasi D, et al. Unbalanced neuronal circuits in addiction. Curr Opin Neurobiol 2013;23(4):639–648.

53. McFarland K, Davidge SB, Lapish CC, et al. Limbic and motor circuitry underlying footshock-induced reinstatement of cocaine-seeking behavior. J Neurosci 2004;24:1551–1560.

54. Coller JK, Hutchinson MR. Implications of central immune signaling caused by drugs of abuse: mechanisms, mediators and new therapeutic approaches for prediction and treatment of drug dependence. Pharmacol Ther 2012;134:219–245.

55. Blednov YA, Ponomarev I, Geil C, et al. Neuroimmune regulation of alcohol consumption: behavioral validation of genes obtained from genomic studies. Addict Biol 2012;17:108–120.

56. Crews FT, Zou J, Qin L. Induction of innate immune genes in brain create the neurobiology of addiction. Brain Behav Immun 2011;25(Suppl 1):S4–S12.

57. Uhl GR, Grow RW. The burden of complex genetics in brain disorders. Arch Gen Psychiatry2004;61:223–229.

58. Laakso A, Mohn AR, Gainetdinov RR, et al. Experimental genetic approaches to addiction. Neuron2002;36(2):213–228.

59. Ehlers CL, Walter NA, Dick DM, et al. A comparison of selected quantitative trait loci associated with alcohol use phenotypes in humans and mouse models. Addict Biol 2010;15:185–199.

60. Treutlein J, Rietschel M. Genome-wide association studies of alcohol dependence and substance use disorders. Curr Psychiatry Rep 2011;13:147–155.

61. Schumann G, Coin LJ, Lourdusamy A, et al. Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption. Proc Natl Acad Sci U S A 2011;108:7119–7124.

62. Kang SJ, Rangaswamy M, Manz N, et al. Family-based genome-wide association study of frontal theta oscillations identifies potassium channel gene KCNJ6. Genes Brain Behav 2012;11:712–719.

63. Kalsi G, Prescott CA, Kendler KS, et al. Unraveling the molecular mechanisms of alcohol dependence. Trends Genet 2009;25:49–55.

64. Kreek MJ, Levran O, Reed B, et al. Opiate addiction and cocaine addiction: underlying molecular neurobiology and genetics. J Clin Invest 2012;122:3387–3393.

65. Chen CC, Lu R-B, Chen Y-C, et al. Interaction between the functional polymorphisms of the alcohol-metabolism genes in protection against alcoholism. Am J Hum Genet 1999;65:795–807.

66. Rao Y, Hoffmann E, Zia M, et al. Duplications and defects in the CYP2A6 gene: identification, genotyping, and in vivo effects on smoking. Mol Pharmacol 2000;58(4):747–755.

67. Kathiramalainathan K, Kaplan HL, Romach MK, et al. Inhibition of cytochrome P450 2D6 modifies codeine abuse liability. J Clin Psychopharmacol 2000;20(4):435–444.

68. Berrettini W, Yuan X, Tozzi F, et al. α-5/α-3 Nicotinic receptor subunit alleles increase risk for heavy smoking. Mol Psychiatry 2008;13:368–373.

69. Saccone SF, Hinrichs AL, Saccone NL, et al. Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs. Hum Mol Genet 2007;16:136–149.

70. Schlaepfer IR, Hoft NR, Collins AC, et al. The CHRNA5/A3/B4 gene cluster variability as an important determinant of early alcohol and tobacco initiation in young adults. Biol Psychiatry2008;63:1039–1046.

71. Bierut LJ, Madden P, Breslau N, et al. Novel genes identified in a high-density genome wide association study for nicotine dependence. Hum Mol Genet 2007;16:24–25.

72. Thorgeirsson TE, Geller F, Sulem P, et al. Variant associated with nicotine dependence, lung cancer and peripheral arterial disease. Nature 2008;452:638–642.

73. Dick DM, Edenberg HJ, Xiaoling X, et al. Association of GABRG3 with alcohol dependence. Alcohol Clin Exp Res 2004;28(1):4–9.

74. Edenberg HJ, Dick DM, Xuei X, et al. Variations in GABRA2, encoding the alpha 2 subunit of the GABA(A) receptor, are associated with alcohol dependence and with brain oscillations. Am J Hum Genet 2004;74:705–714.

75. McGeary J. The DRD4 exon 3 VNTR polymorphism and addiction-related phenotypes: a review. Pharmacol Biochem Behav 2009;93:222–229.

76. Grady DL, Thanos PK, Corrada MM, et al. DRD4 genotype predicts longevity in mouse and human. J Neurosci 2013;33:286–291.

77. Edenberg HJ. Genes contributing to the development of alcoholism: an overview. Alcohol Res2012;34:336–338.

78. Haass-Koffler CL, Bartlett SE. Stress and addiction: contribution of the corticotropin releasing factor (CRF) system in neuroplasticity. Front Mol Neurosci 2012;5:91.

79. Koob GF. The role of CRF and CRF-related peptides in the dark side of addiction. Brain Res2010;1314:3–14.

80. Whitaker LR, Degoulet M, Morikawa H. Social deprivation enhances VTA synaptic plasticity and drug-induced contextual learning. Neuron 2013;77:335–345.

81. Chappell AM, Carter E, McCool BA, et al. Adolescent rearing conditions influence the relationship between initial anxiety-like behavior and ethanol drinking in male Long Evans rats. Alcohol Clin Exp Res 2012;37(Suppl 1):E394–E403.

82. Morgan D, Grant KA, Gage HD, et al. Social dominance in monkeys: dopamine D2 receptors and cocaine self-administration. Nat Neurosci 2002;5:169–174.

83. Thanos PK, Volkow ND, Freimuth P, et al. Overexpression of dopamine D2 receptors reduces alcohol self-administration. J Neurochem 2001;78:1094–1103.

84. Pandey SC, Ugale R, Zhang H, et al. Brain chromatin remodeling: a novel mechanism of alcoholism. J Neurosci 2008;28:3729–3737.

85. Varga MD. Adderall abuse on college campuses: a comprehensive literature review. J Evid Based Soc Work 2012;9:293–313.

86. Bogle KE, Smith BH. Illicit methylphenidate use: a review of prevalence, availability, pharmacology, and consequences. Curr Drug Abuse Rev 2009;2:157–176.

87. Bohnert AS, Valenstein M, Bair MJ, et al. Association between opioid prescribing patterns and opioid overdose-related deaths. JAMA 2011;305:1315–1321.

88. Compton WM, Volkow ND. Major increases in opioid analgesic abuse in the United States: concerns and strategies. Drug Alcohol Depend 2006;81:103–107.

89. Thurstone C, Lieberman SA, Schmiege SJ. Medical marijuana diversion and associated problems in adolescent substance treatment. Drug Alcohol Depend 2011;118:489–492.

90. Compton WM, Thomas YF, Stinson FS, et al. Prevalence, correlates, disability, and comorbidity of DSM-IV drug abuse and dependence in the United States: results from the national epidemiologic survey on alcohol and related conditions. Arch Gen Psychiatry 2007;64:566–576.

91. Hassel S, Almeida JR, Frank E, et al. Prefrontal cortical and striatal activity to happy and fear faces in bipolar disorder is associated with comorbid substance abuse and eating disorder. J Affect Disord2009;118:19–27.

92. Brady KT, Sinha R. Co-occurring mental and substance use disorders: the neurobiological effects of chronic stress. Am J Psychiatry 2005;162:1483–1493.

93. Moran LV, Sampath H, Stein EA, et al. Insular and anterior cingulate circuits in smokers with schizophrenia. Schizophr Res 2012;142:223–229.

94. Grant BF, Stinson FS, Dawson DA, et al. Prevalence and co-occurrence of substance use disorders and independent mood and anxiety disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry 2004;61:807–816.

95. Markou A, Kosten TR, Koob GF. Neurobiological similarities in depression and drug dependence: a self-medication hypothesis. Neuropsychopharmacology 1998;18:135–174.

96. Fowler JS, Logan J, Wang GJ, et al. Monoamine oxidase and cigarette smoking. Neurotoxicology2003;24:75–82.

97. Brook DW, Brook JS, Zhang C, et al. Drug use and the risk of major depressive disorder, alcohol dependence, and substance use disorders. Arch Gen Psychiatry 2002;59:1039–1044.

98. Castle DJ. Cannabis and psychosis: what causes what? F1000 Med Rep 2013;5:1.

99. Johnston LD, O’Malley PM, Bachman JG, et al. Monitoring the future national survey results on drug use. 2012 Overview. Publication No. 07-6205. Bethesda, MD: National Institutes of Health. 2012.

100. Block LG, Morwitz VG, Putsis WP Jr, et al. Assessing the impact of antidrug advertising on adolescent drug consumption: results from a behavioral economic model. Am J Public Health2002;92:1346–1351.

101. Carpenter CS, Pechmann C. Exposure to the above the influence antidrug advertisements and adolescent marijuana use in the United States, 2006–2008. Am J Public Health 2011;101:948–954.

102. Terry-McElrath YM, Emery S, Szczypka G, et al. Potential exposure to anti-drug advertising and drug-related attitudes, beliefs, and behaviors among United States youth, 1995–2006. Addict Behav2011;36:116–124.

103. Clayton RR, Cattarello AM, Johnstone BM. The effectiveness of Drug Abuse Resistance Education (project DARE): 5-year follow-up results. Prev Med 1996;25:307–318.

104. Gruber AJ, Pope HG Jr. Marijuana use among adolescents. Pediatr Clin North Am 2002;49:389–413.

105. Moffitt TE, Arseneault L, Belsky D, et al. A gradient of childhood self-control predicts health, wealth, and public safety. Proc Natl Acad Sci USA 2011;108:2693–2698.

106. McLellan AT, Lewis DC, O’Brien CP, et al. Drug dependence, a chronic medical illness: implications for treatment, insurance, and outcomes evaluation. JAMA 2000;284:1689–1695.

107. Saitz R, Larson MJ, Labelle C, et al. The case for chronic disease management for addiction. J Addict Med 2008;2:55–65.

108. Li X, Hartwell KJ, Owens M, et al. Repetitive transcranial magnetic stimulation of the dorsolateral prefrontal cortex reduces nicotine cue craving. Biol Psychiatry 2013;73:714–720.

109. Alterman AI, Gariti P, Mulvaney F. Short- and long-term smoking cessation for three levels of intensity of behavioral treatment. Psychol Addict Behav 2001;15:261–264.

110. Hall SM, Humfleet GL, Muñoz RF, et al. Using extended cognitive behavioral treatment and medication to treat dependent smokers. Am J Public Health 2011;101:2349–2356.

111. Frank D. The trouble with morality: the effects of 12-step discourse on addicts’ decision-making. J Psychoactive Drugs 2011;43:245–256.

112. Anton RF. Pharmacologic approaches to the management of alcoholism. J Clin Psychiatry2001;62(Suppl 20):11–17.

113. Johnson BA. Update on neuropharmacological treatments for alcoholism: scientific basis and clinical findings. Biochem Pharmacol 2008;75:34–56.

114. Yahn SL, Watterson LR, Olive MF. Safety and efficacy of acamprosate for the treatment of alcohol dependence. Subst Abuse 2013;6:1–12.

115. Mason BJ, Lehert P. Acamprosate for alcohol dependence: a sex-specific meta-analysis based on individual patient data. Alcohol Clin Exp Res 2012;36:497–508.

116. Kenna GA, Lomastro TL, Schiesl A, et al. Review of topiramate: an antiepileptic for the treatment of alcohol dependence. Curr Drug Abuse Rev 2009;2:135–142.

117. Addolorato G, Mirijello A, Leggio L, et al. Management of alcohol dependence in patients with liver disease. CNS Drugs 2013 27:287–299.

118. Mann K, Bladstrom A, Torup L, et al. Extending the treatment options in alcohol dependence: a randomized controlled study of as-needed nalmefene. Biol Psychiatry 2013;73:706–713.

119. Addolorato G, Leggio L, Ferrulli A, et al. Effectiveness and safety of baclofen for maintenance of alcohol abstinence in alcohol-dependent patients with liver cirrhosis: randomised, double-blind controlled study. Lancet 2007;370:1915–1922.

120. Morikawa H, Morrisett RA. Ethanol action on dopaminergic neurons in the ventral tegmental area: interaction with intrinsic ion channels and neurotransmitter inputs. Int Rev Neurobiol 2010;91:235–288.

121. McLaughlin PJ. Reports of the death of CB1 antagonists have been greatly exaggerated: recent preclinical findings predict improved safety in the treatment of obesity. Behav Pharmacol2012;23:537–550.

122. Tam J, Cinar R, Liu J, et al. Peripheral cannabinoid-1 receptor inverse agonism reduces obesity by reversing leptin resistance. Cell Metab 2012;16:167–179.

123. McKee SA, Harrison EL, O’Malley SS, et al. Varenicline reduces alcohol self-administration in heavy-drinking smokers. Biol Psychiatry 2009;66:185–190.

124. Mitchell JM, Teague CH, Kayser AS, et al. Varenicline decreases alcohol consumption in heavy-drinking smokers. Psychopharmacology (Berl) 2012;223:299–306.

125. Edwards S, Guerrero M, Ghoneim OM, et al. Evidence that vasopressin V1b receptors mediate the transition to excessive drinking in ethanol-dependent rats. Addict Biol 2011;17:76–85.

126. Simpson TL, Saxon AJ, Meredith CW, et al. A pilot trial of the alpha-1 adrenergic antagonist, prazosin, for alcohol dependence. Alcohol Clin Exp Res 2009;33:255–263.

127. George DT, Gilman J, Hersh J, et al. Neurokinin 1 receptor antagonism as a possible therapy for alcoholism. Science 2008;319:1536–1539.

128. George TP, O’Malley SS. Current pharmacological treatments for nicotine dependence. Trends Pharmacol Sci 2004;25:42–48.

129. Carpenter MJ, Jardin BF, Burris JL, et al. Clinical strategies to enhance the efficacy of nicotine replacement therapy for smoking cessation: a review of the literature. Drugs 2013;73:407–426.

130. Tonstad S, Tonnesen P, Hajek P, et al. Effect of maintenance therapy with varenicline on smoking cessation: a randomized controlled trial. JAMA 2006;296:64–71.

131. Berlin I, Hunneyball IM, Greiling D, et al. A selective reversible monoamine oxidase B inhibitor in smoking cessation: effects on its own and in association with transdermal nicotine patch. Psychopharmacology (Berl) 2012;223:89–98.

132. Hoogsteder PH, Kotz D, van Spiegel PI, et al. The efficacy and safety of a nicotine conjugate vaccine (NicVAX(R)) or placebo co-administered with varenicline (Champix(R)) for smoking cessation: study protocol of a phase IIb, double blind, randomized, placebo controlled trial. BMC Public Health2013;12:1052.

133. King AC, Cao D, O’Malley SS, et al. Effects of naltrexone on smoking cessation outcomes and weight gain in nicotine-dependent men and women. J Clin Psychopharmacol 2012;32:630–636.

134. Krupitsky EM, Zvartau EE, Masalov DV, et al. Naltrexone for heroin dependence treatment in St. Petersburg, Russia. J Subst Abuse Treat 2004;26:285–294.

135. Comer SD, Sullivan MA, Yu E, et al. Injectable, sustained-release naltrexone for the treatment of opioid dependence: a randomized, placebo-controlled trial. Arch Gen Psychiatry 2006;63:210–218.

136. Krantz MJ, Mehler PS. Treating opioid dependence. Growing implications for primary care. Arch Intern Med 2004;164:277–288.

137. Mattick RP, Kimber J, Breen C, et al. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev 2008;(2):CD002207.

138. Johnson BA, Roache JD, Ait-Daoud N, et al. Topiramate’s effects on cocaine-induced subjective mood, craving and preference for money over drug taking. Addict Biol 2013;18:405–416.

139. Mariani JJ, Pavlicova M, Bisaga A, et al. Extended-release mixed amphetamine salts and topiramate for cocaine dependence: a randomized controlled trial. Biol Psychiatry 2013;72:950–956.

140. Shoptaw S, Yang X, Rotheram-Fuller EJ, et al. Randomized placebo-controlled trial of baclofen for cocaine dependence: preliminary effects for individuals with chronic patterns of cocaine use. J Clin Psychiatry 2003;64:1440–1448.

141. Porrino LJ, Hampson RE, Opris I, et al. Acute cocaine induced deficits in cognitive performance in rhesus macaque monkeys treated with baclofen. Psychopharmacology (Berl) 2013;225:105–114.

142. Dackis C, O’Brien C. Glutamatergic agents for cocaine dependence. Ann N Y Acad Sci2003;1003:328–345.

143. Mahler SV, Hensley-Simon M, Tahsili-Fahadan P, et al. Modafinil attenuates reinstatement of cocaine seeking: role for cystine-glutamate exchange and metabotropic glutamate receptors. Addict Biol 2014;19(1):49–60.

144. Carroll KM, Fenton LR, Ball SA, et al. Efficacy of disulfiram and cognitive behavior therapy in cocaine-dependent outpatients: a randomized placebo-controlled trial. Arch Gen Psychiatry2004;61:264–272.

145. Spellicy CJ, Kosten TR, Hamon SC, et al. The MTHFR C677T variant is associated with responsiveness to disulfiram treatment for cocaine dependency. Front Psychiatry 2012;3:109.

146. Kosten T, Domingo C, Orson F, et al Vaccines against stimulants: cocaine and methamphetamine. Br J Clin Pharmacol 2013 (accepted for publication).

147. Mardikian PN, LaRowe SD, Hedden S, et al. An open-label trial of N-acetylcysteine for the treatment of cocaine dependence: a pilot study. Prog Neuropsychopharmacol Biol Psychiatry 2007;31:389–394.

148. Schmaal L, Veltman DJ, Nederveen A, et al. N-acetylcysteine normalizes glutamate levels in cocaine-dependent patients: a randomized crossover magnetic resonance spectroscopy study. Neuropsychopharmacology 2012;37:2143–2152.

149. Mello NK, Fivel PA, Kohut SJ, et al. Effects of chronic buspirone treatment on cocaine self-administration. Neuropsychopharmacology 2012;38:455–467.

150. Newman AH, Blaylock BL, Nader MA, et al. Medication discovery for addiction: translating the dopamine D3 receptor hypothesis. Biochem Pharmacol 2012;84:882–890.

151. Cordery SF, Taverner A, Ridzwan IE, et al. A non-rewarding, non-aversive buprenorphine/naltrexone combination attenuates drug-primed reinstatement to cocaine and morphine in rats in a conditioned place preference paradigm. Addict Biol 2013 doi: 10.1111/adb.12020.

152. Wee S, Vendruscolo LF, Misra KK, et al A combination of buprenorphine and naltrexone blocks compulsive cocaine intake in rodents without producing dependence. Sci Transl Med2012;4:146ra110.

153. Ebbert JO, Croghan IT, Sood A, et al. Varenicline and bupropion sustained-release combination therapy for smoking cessation. Nicotine Tob Res 2009;11:234–239.

154. Schaffer DV, Gage FH. Neurogenesis and neuroadaptation. Neuromolecular Med 2004;5:1–9.

155. Kujala T, Karma K, Ceponiene R, et al. Plastic neural changes and reading improvement caused by audiovisual training in reading-impaired children. Proc Natl Acad Sci USA 2001;98:10509–10514.

156. van Paasschen J, Clare L, Yuen KS, et al. Cognitive rehabilitation changes memory-related brain activity in people with Alzheimer disease. Neurorehabil Neural Repair 2013;27:448–459.

157. Liechti MD, Maurizio S, Heinrich H, et al. First clinical trial of tomographic neurofeedback in attention-deficit/hyperactivity disorder: evaluation of voluntary cortical control. Clin Neurophysiol2012;123:1989–2005.

158. Merchant G, Pulvers K, Brooks RD, et al. Coping with the urge to smoke: a real-time analysis. Res Nurs Health 2013;36:3–15.

159. Volkow ND, Fowler JS, Wang GJ, et al. Cognitive control of drug craving inhibits brain reward regions in cocaine abusers. Neuroimage 2010;49:2536–2543.

160. Stead LF, Lancaster T. Behavioural interventions as adjuncts to pharmacotherapy for smoking cessation. Cochrane Database Syst Rev 2013;12:CD009670.

161. Sofuoglu M, DeVito EE, Waters AJ, et al. Cognitive enhancement as a treatment for drug addictions. Neuropharmacology 2013;64:452–463.

162. Feldsten-Ewing S, Chung T. Neuroimaging mechanisms of change in psychotherapy for addictive behaviors: emerging translational approaches that bridge biology and behavior. Psychol Addict Behav 2013;27:329–335.

163. Morgenstern J, Bechara A, Breiter HC. The contributions of cognitive neuroscience and neuroimaging to understanding mechanisms of behavior change in addiction. Psychol Addict Behav2013;27:336–350.

164. Volkow ND, Baler RD, Normand JL. The unrealized potential of addiction science in curbing the HIV epidemic. Curr HIV Res 2011;9:393–395.

165. Volkow ND, Montaner J. The urgency of providing comprehensive and integrated treatment for substance abusers with HIV. Health Aff (Millwood) 2011;30:1411–1419.

166. Butzin CA, Martin SS, Inciardi JA. Evaluating component effects of a prison-based treatment continuum. J Subst Abuse Treat 2002;22:63–69.

167. Hiller ML, Knight K, Simpson DD. Prison-based substance abuse treatment, residential aftercare and recidivism. Addiction 1999;94:833–842.

168. Cropsey KL, Binswanger IA, Clark CB, et al. The unmet medical needs of correctional populations in the United States. J Natl Med Assoc 2012;104:487–492.

169. Pilowsky DJ, Wu LT. Screening instruments for substance use and brief interventions targeting adolescents in primary care: a literature review. Addict Behav 2013;38:2146–2153.

170. Madras BK, Compton WM, Avula D, et al. Screening, brief interventions, referral to treatment (SBIRT) for illicit drug and alcohol use at multiple healthcare sites: comparison at intake and 6 months later. Drug Alcohol Depend 2009;99:280–295.

171. Volkow ND, Skolnick P. New medications for substance use disorders: challenges and opportunities. Neuropsychopharmacology 2012;37:290–292.

172. Fulco CE, Liverman CT, Earley LE., eds. Development of medications for the treatment of opiate and cocaine addictions: issues for the government and private sector (Institute of Medicine). Washington DC: National Academy Press, 1995.

173. Fulco CE, Liverman CT, Earley LE., eds. Development of medications for the treatment of opiate and cocaine addictions: issues for the government and private sector (Institute of Medicine). Washington DC: National Academy Press, 1995.