Wu and schulz 2012 advancing addiction treatment

Advancing Addiction Treatment: What Can We Learn from Animal Studies?

Peter H. Wu and Kalynn M. Schulz

Abstract

Key Words: addiction; dependence; drug abuse; memory; reinforcement; reward; rodent model

Introduction

I

s drug addiction a single disease or a collection of different diseases that share common features of compulsive drug use behavior? The current state of addiction research gives the impression that addiction is a collection of diseases (e.g., cocaine addiction, heroin addiction, and so forth) that share common behavioral features, although most researchers do not hold this view. The downside of this multidisease concept is that it creates challenges for the development of effective treatment strategies. For example, both cocaine and amphetamine are central nervous system stimulants, but they have completely different treatment strategies. Although it is true that these drugs exert their action through different receptors and modulate different neurotransmitter systems, the addictive nature of the drugs converges on the neurocircuitry that underlies their rewarding properties. The convergence argues for the idea that drug addiction is a single disease—a disease of the reward circuit that drives maladaptive behavPeter H. Wu, PhD, is an assistant professor and Kalynn M. Schulz, PhD, is an instructor in the Department of Psychiatry at the University of Colorado Anschutz Medical Campus in Aurora.

Address correspondence and reprint requests to Dr. Peter H. Wu, Department of Psychiatry, University of Colorado Anschutz Medical Campus, Research Complex-1 North, Mail Stop 8344, 12800 East 19th Avenue, Aurora, Colorado 80045, or email peter.wu@ucdenver.edu.

4

Criteria for the Development of a Valid Animal Model Drug addiction is a disease characterized by compulsive, uncontrolled drug-seeking and drug-taking behavior that is very difficult to quit despite the user’s recognition of its harmful consequences (Hasin et al. 2006). Drug dependence is characterized by withdrawal symptoms in the absence of the drug that drive individuals to resume drug taking. For example, cocaine withdrawal produces profound fatigue, alcohol withdrawal produces anxiety and sometimes seizures, and opiate withdrawal results in marked dysphoria. Addicts resume drug taking to alleviate the negative symptoms of withdrawal, a phenomenon termed negative reinforcement.

Evidence indicates that, even in the absence of withdrawal symptoms, animals, like humans, self-administer psychoactive substances to experience the pleasurable (rewarding) effects of a drug. This phenomenon is termed positive reinforcement.

Thus, a valid animal model of drug addiction should exhibit both negatively reinforced drug-seeking behavior to alleviate withdrawal symptoms and positively reinforced voluntary drugusing (drug self-administration) behavior to induce pleasurable sensations.

Because it is often impractical and unethical to perform research on addictive behavior in humans, the use of animal models makes it possible to gain insights essential for developing effective treatment strategies for such behavior. Animal models have become indispensable for the development ILAR Journal

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

Substance addiction is a maladaptive behavior characterized by compulsive and uncontrolled self-administration of a substance (drug). Years of research indicate that addictive behavior is the result of complex interactions between the drug, the user, and the environment in which the drug is used; therefore, addiction cannot simply be attributed to the neurobiological actions of a drug. However, despite the obvious complexity of addictive behavior, animal models have both advanced understanding of addiction and contributed importantly to the development of medications to treat this disease. We briefly review recent animal models used to study drug addiction and the contribution of data generated by these animal models for the clinical treatment of addictive disorders.

ioral responses to positive and/or negative reinforcement.

Thus, conceptual models of drug addiction that incorporate all drug classes could significantly advance understanding of the addicted brain.

This review is organized according to addiction to specific classes of drugs because research programs tend to focus on specific drugs (e.g., cocaine, amphetamines, opioids, nicotine, or alcohol). We discuss various animal models that are used to study drug addiction and dependence, with particular emphasis on investigations of the reward system, which acts as a convergent point for drug actions. We also discuss how gene-targeting technologies have advanced understanding of addictive behaviors and how animal research has informed clinical treatments of drug addiction. We conclude with thoughts about particularly promising directions for addiction research.

of drug addiction treatments because they enable mapping of the specific regions of the brain where individual drugs exert their actions and determination of the mechanisms by which drugs produce their effects. Animal models also permit testing of the pharmacological efficacy and verification of the biosafety of medications before they are used in clinical practice (Lynch et al. 2010).

Negative Versus Positive Reinforcement Theories of Drug Addiction

Modeling Relapse of Drug-Taking Behaviors in Animals Many natural experiences important to survival are highly rewarding and cause increased dopamine release in the NAc.

that appear ≥3x throughout this article: CPP, conditioned place preference; GABA, ␥-aminobutyric acid; KO, knockout; MDMA, 3,4-methylenedioxy-N-methamphetamine; NAc, nucleus accumbens; VTA, ventral tegmental area 1Abbrevations

Volume 53, Number 1

2012

Modeling Drug Self-Administration in Animals Drug self-administration animal models developed over the past 40 years in an effort to mimic human drug addiction have helped pinpoint dopamine as a primary mediator of brain reward pathways where cocaine, amphetamines, and nicotine clearly act. In addition, the development of receptor gene research has been integral in determining that dopamine acts on D1 to D4 dopamine receptors coupled to G protein signaling systems (for review see Missale et al. 1998).

Activation of these signaling pathways leads to changes in neuronal function that in turn result in the expression of addictive behavior(s) (Schultz 2010; Wise 2008). Furthermore, glutamate, ␥-aminobutyric acid (GABA1), serotonin, and norepinephrine play modulatory roles in regulating dopaminergic neuronal activity, making these neurotransmitters potential targets for drug addiction treatments (Kalivas and Volkow 2011).

Several classes of psychoactive drugs—psychostimultants (e.g., cocaine, amphetamines), opioids, nicotine, and alcohol—are widely used in the population, and their chronic use causes significant health problems and is of great concern to society. In the sections below, we discuss the animal models used to study self-administration of these drugs.

5

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

Given the severity of withdrawal symptoms for many drugs, it is not surprising that negative reinforcement was the prevailing viewpoint during the early years of addiction research (discussed in Ahmed and Koob 1998; Ahmed et al.

2000). A major scientific advance occurred when Olds and Milner (1954) reported a “positive reinforcement brain center” and demonstrated that rats self-administer electric stimulation at selective brain regions such as the nucleus accumbens (NAc1) and ventral tegmental area (VTA1). After many more years of research, it was determined that animals also self-administer psychoactive drugs into these brain areas even in the absence of withdrawal symptoms, thereby establishing the “reward” theory of drug self-administration (reviewed in Wise 1996).

These studies determined that the positive reinforcement brain center first described by Olds and Milner consists of VTA dopaminergic cell bodies and NAc terminals (Corbett and Wise 1980; Wise 1981). In addition, investigators found that different drugs have different sites of action in the reward system. For example, the rewarding properties of morphine (opioids or opiates) are mediated by synapses at VTA dopamine cell bodies, alcohol reward is mediated by VTA neurons (Brodie et al. 1999), and NAc dopamine terminals are the site of action for amphetamine and cocaine (Broekkamp et al. 1975; Colle and Wise 1988).

Taken together, these observations indicate that the site of action that regulates the rewarding properties of drugs depends on the drug in question. Opiates and alcohol disinhibit VTA dopaminergic neuronal cell bodies, causing the release of dopamine at nerve terminals in the NAc. In contrast, cocaine and amphetamine exert their effects on dopaminergic neuronal terminals to increase dopamine concentrations at NAc synapses.

The reward system is closely tied to the memory system, and associative memory processes linking positive emotions with certain experiences and behaviors help individuals find the “right” kind of food, choose the “right” mate, and survive to pass on their genes (Kelley 2004). Similarly, individuals remember the positive emotions caused by a psychoactive drug and its associated environmental cues.

Models that use the conditioned place preference (CPP1) paradigm take advantage of these powerful and long-lasting memories for drug-associated environmental cues (conditioned stimuli) to evoke drug-seeking behavior (Hernandez and Kelley 2005; Robinson and Berridge 1993; Stewart et al.

1984). For example, when morphine or cocaine treatment is paired with a specific environment, rats later spend significantly more time in the environment in which they received the drug.

Intracranial infusion of morphine into the VTA produces CPP (Bozarth et al. 1980; Olmstead and Franklin 1997; Phillips and LePiane 1980), as does intracranial administration of amphetamine into the NAc (Josselyn and Beninger 1993; Schildein et al. 1998). And conversely, when a given environment is paired with an aversive stimulus such as naloxone (an opioid antagonist), rats later avoid that environment (Mucha et al. 1982), suggesting that the environment is perceived as a place of punishment. CPP is thus an extremely useful experimental tool for exploring associations between reward and memory systems and determining the reward value of different drugs.

Psychostimulant Addiction

Cocaine Cocaine has been shown to interact with the dopamine transporter (DAT), so it was anticipated that knockout (KO1) of the DAT gene would alter behaviors related to cocaine addiction such as cocaine self-administration and reward in the CPP paradigm. Overall, studies have demonstrated that cocaine-activated locomotor activity is decreased or eliminated in DAT knockouts; for example, Giros and colleagues (1996) reported that cocaine-induced locomotion and CPP are attenuated in DAT KO mice.

In contrast, cocaine self-administration patterns in DAT KO animals are less clear. Some studies suggest that such animals display substantially decreased self-administration (Thomsen et al. 2009a), whereas others report that selfadministration is unaffected (Rocha et al. 1998; Tilley et al.

2007). Thus, unknown factors likely influence cocaine addictive behaviors to cause different study outcomes.

Another problem with DAT knockout is that significant compensatory changes can occur in KO animals. To overcome potential compensation caused by gene deletion, Chen and colleagues (2006) used a knock-in (KI) mouse line carrying a functional but cocaine-insensitive DAT. In these mice, cocaine administration suppressed locomotor activity, did not increase extracellular dopamine levels in the NAc, and failed to produce cocaine reward. Furthermore, the mice did not selfadminister cocaine (Thomsen et al. 2009b). Thus a functional DAT is necessary and sufficient to maintain cocaine addiction.

In addition to the DAT KO and KI animals, other transgenic mice have been developed to study the effects of cocaine: DAT-overexpressing transgenic mice (Donovan et al.

1999), vesicular monoamine transporter KO mice (VMAT2),

2The

US Drug Enforcement Agency classifies controlled substances according to five schedules; information is available on the DEA website (www.deadiversion.usdoj.gov/schedules/index.html).

6

Amphetamines Amphetamines (including methamphetamine and MDMA) work by different mechanisms to increase synaptic dopamine concentrations. Unlike cocaine, amphetamine blocks the vesicular transporter to reverse dopamine reuptake (release) (Seiden et al. 1993; Sulzer et al. 2005).

In a DAT KO mouse model, the rewarding effects of amphetamine remained intact in the CPP paradigm. However, amphetamine-induced CPP is abolished by pretreatment of mice with a serotonin 5-HT1A antagonist (Budygin et al.

2004). These results are consistent with the hypothesis that amphetamines interact not only with dopamine but also with serotonin and norepinephrine systems to exert their rewarding effects (Bhatia et al. 2011).

Efficacious pharmacological treatments for psychostimulant amphetamine addiction are not available in clinical practice despite the social problems associated with this drug (Huddleston et al. 2008). But rodent models demonstrate that the memory system may be a candidate for treatment (Lee et al. 2006). For example, long-term methamphetamine exposure in the rat leads to motor sensitization, which can be prevented by combining the nonselective dopamine agonist pergolide with the 5-HT3 ILAR Journal

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

The most commonly abused schedule I or schedule IV2 psychostimulants include cocaine, amphetamine, and 3,4-methylenedioxy-N-methamphetamine (MDMA1 or “ecstasy”).

All three psychostimulants increase synaptic dopamine concentrations, but their mechanisms of action differ. Cocaine inhibits the dopamine transporter and thus prevents reuptake of dopamine into presynaptic elements. Amphetamines produce their effects by reversing the reuptake of dopamine, serotonin, and/or norepinephrine in the brain (Gudelsky and Yamamoto 2008; Sager and Torres 2011). MDMA also selectively targets the serotonin reuptake transporter (Seger 2010).

Repeated exposure to MDMA may lead to sensitization of dopaminergic responses to the substance, thereby increasing an individual’s addiction risk (Schenk 2011; Schenk et al.

2011). MDMA has recently gained tremendous popularity due to its availability.

cocaine-insensitive mice, DAT-serotonin (SER) reuptake transporter (DAT/SER) double-KO mice, and dopaminedeficient mice (Hnasko et al. 2007). Data from these transgenic lines suggest that the dopaminergic system interacts with serotoninergic signaling to influence the acquisition of cocaine CPP (Hnasko et al. 2007). The involvement of serotonin and serotonin receptor subtypes in cocaine sensitization, discrimination, self-administration, reinstatement of cocaineseeking behavior, and CPP in laboratory animals has been reviewed elsewhere (Filip et al. 2010).

Studies in rodents suggest that dopamine D3 receptor antagonists (Song et al. 2012) and monoamine transporter inhibitors (Peng et al. 2010) reduce cocaine self-administration.

A primary concern about using DAT inhibitors to treat cocaine addiction is that they may behave like cocaine and support self-administration. Data from DAT KI mice suggest that selective blockade of cocaine interactions with DAT may be an alternative approach to examine the role of DAT in cocaine addiction.

Treatment of cocaine addiction is a formidable clinical challenge (Somaini et al. 2011). Therapeutic agents are not readily available, but animal and clinical research offers some promise for the development of potential treatments. For example, the dopamine agonist bromocriptine lowers the threshold for the rewarding effects of cocaine in rodents (Knapp and Kornetsky 1994; Ushijima et al. 1995; Weissenborn et al.

1996), and controlled human trials have indicated that, in addition to bromocriptine, other such agonists (amantadine, carbamazepine, and desipramine) are effective in relieving some of the symptoms of cocaine abstinence (Withers et al.

1995). However, the efficacy of these treatments in a clinical setting has been mixed (Montoya et al. 2002).

antagonist ondansetron (Bhatia et al. 2011). Thus, drug-seeking behavior can be reversed in addicted animals by administering first a selective dopamine agonist to “reactivate” the addiction “circuit” and then a 5-HT3 antagonist to block memory reconsolidation of methamphetamine sensitization and addiction (Bhatia et al. 2011). This approach holds promise for new pharmacological treatment of stimulant addiction including cocaine and amphetamines.

Opioids

Nicotine Mechanisms Opioids activate µ and ␦ opioid receptors in the VTA and NAc, leading to the release of dopamine (Hirose et al. 2005; Yoshida et al. 1999). In the VTA, opioid-activated µ opioid receptors result in decreased GABA inhibition (disinhibition of GABAergic neurons) (Johnson and North 1992).

Studies using animal models have shown that opioid agonists with selective affinity to µ opioid receptors possess the highest abuse potential (Devine and Wise 1994), but ␦ opioid receptor agonists can also induce rewarding effects in animals (Hutcheson et al. 2001). Pharmacological studies have shown that ␦ opioid receptors are about 100 times less effective than µ opioid receptors in maintaining intracranial self-administration and striatal dopamine release (Devine et al. 1993).

The ␬ opioid receptors appear to play a negative regulatory role such that ␬ agonists increase brain reward thresholds for intracranial self-administration (Beguin et al. 2008; Carlezon et al. 2006) and cause aversive effects (Land et al. 2008). In addition, ␬ receptor gene knockout results in elevated dopamine levels in the NAc (Chefer et al. 2005), indicating that this knockout may directly alter the rewarding property of opioids.

Future treatment strategies will benefit from the outcome of studies using various opioid receptor transgenic animals to map the involvement of these receptor subtypes on opioid tolerance, dependence, and self-administration.

Treatment Treatment of opioid addiction is a two-step process that involves detoxification and relapse prevention. Detoxification is designed to remove the drug from the patient, but withdrawal symptoms occur when addicts stop using opioids and often are severe enough to cause relapse into drug-taking behavior.

Because treatment of opioid addiction by detoxification alone leads to high rates of relapse (Lobmaier et al. 2010), the most effective means of relapse prevention is agonist replaceVolume 53, Number 1

2012

Mechanisms Nicotine is the major active component in tobacco smoke that supports smoking behavior and nicotine addiction (Polosa and Benowitz 2011). It works by activating brain nicotinic receptors (nAChRs), which are ligand-gated cation channels that conduct Na+, K+, and/or Ca2+ currents (Taly et al. 2009). nAChRs are formed from different subunits, ␣2–9 and ␤2–4, that are encoded by 17 different genes. The two main types of nAChRs that have been identified are the homo-oligomer receptors (e.g., the ␣7 nAChRs) and the hetero-oligomer receptors (e.g., the ␣4␤2 nAChRs and other oligomers). The ␣7 receptors, present in many brain areas, are characterized by fast activation, low ligand affinity, and high Ca2+ permeability.

In contrast, the ␣4␤2 nAChRs are high-affinity and slowdesensitizing receptors. Nicotine activates nAChRs in the VTA (␣4␤2, ␣5␤2, ␣6␤2, ␣6␤3, ␣3␤4, and ␣7 isoforms) and NAc (␣4␤2, ␣4␣5␤2, ␣6␤2␤3, and ␣6␣4␤␤3 isoforms), leading to dopamine release in these brain areas that mediates reward.

Gene deletion studies have been useful in determining the involvement of specific nAChR isoforms in nicotine selfadministration. For example, mice lacking ␤2, ␣4, or ␣6 subunits do not self-administer nicotine, but do so when these receptor subunits are reexpressed in the VTA. In contrast, ␣7 gene knockout did not affect nicotine self-administration (Pons et al. 2008). Moreover, deletion of ␣5 or overexpression of ␤4 increased nicotine self-administration. ␣5 subunit, which is highly expressed in dopaminergic neurons (Klink et al. 2001), regulates nicotine self-administration in an animal model of nicotine addiction (Changeux 2010).

Treatment There have been significant efforts in recent years to promote smoking cessation, but cessation is different from the treatment of nicotine addiction.

The current practice for smoking cessation is to use nicotine patches to sustain nicotine addiction without smoking.

7

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

The opioid analgesics—morphine, diacetylmorphine (heroin), and other compounds that share morphine-like properties— produce rewarding effects through their actions on endogenous opioid receptors, and frequent use leads to tolerance and dependence.

ment therapy (Lobmaier et al. 2010; Veilleux et al. 2010). This treatment involves use of a less efficacious and longer-acting opioid agonist to decrease the frequency of drug taking. For example, buprenorphine is a µ opioid receptor partial agonist that dissociates slowly from the receptor and thus produces smaller effects and prolonged duration of actions.

Methadone is the most common replacement medication, typically presented in a tapered procedure during 10 to 28 days of detoxification (Gossop et al. 1989; Strang and Gossop 1990). Buprenorphine, buprenorphine-naloxone, and other opioid agonists such as heroin, slow-release oral morphine, codeine, and levomethadyl acetate hydrochloride (LAAM) are also used (Veilleux et al. 2010). In addition, buprenorphine, clonidine, or lofexidine are sometimes used to decrease craving (Gossop 1988; Gowing et al. 2009).

Alcohol Alcohol abuse does not fully conform to the same compulsive behavioral characteristics—uncontrolled drug seeking and drug taking—associated with addictions to drugs such as cocaine, nicotine, amphetamine, and opiates. Indeed, significant disagreements in both the clinical and research communities have surrounded the adoption of the term addiction for alcohol abuse; instead, alcohol dependence or alcoholism is usually used (O’Brien 2011; Ripley and Stephens 2011).

Given the disagreements about the definition of human alcoholism, it is perhaps not surprising that modeling alcohol addiction in animals is complicated. There is no single paradigm that models all characteristics of alcohol dependence (Ripley and Stephens 2011). Instead, investigators separately model specific subcomponents of alcohol dependence, such as voluntary intake (Goldstein 1977), increased consumption (Falk et al. 1972), preference (Myers and Veale 1968), sensitivity (short sleep [SS] and long sleep [LS]; McClearn 1972), tolerance (Erwin and Deitrich 1996), and withdrawal behavior (Crabbe et al. 1990).

The first challenge in modeling alcohol use and abuse has been that most laboratory animals do not find alcohol palatable; they therefore do not consume it unless they are water deprived or sweetening agents have been added. Although it is possible that many human alcoholics also start with sweetened alcoholic beverages (e.g., during adolescence), laboratory animals rarely compulsively self-administer large quantities of alcohol for long durations as seen in human alcoholism.

Thus, significant attention has been given to developing animal models of alcohol consumption behavior.

Given that the first step in becoming addicted to alcohol is to consume alcohol, animal models of alcohol consumption enhance understanding of the neurobiology and genetics of this behavior. Such models may reveal factors that regulate alcohol intake in both normal and diseased states of alcohol consumption behavior.

8

Models of Alcohol Consumption One feature of alcoholism is the consumption of large quantities of alcohol. It is known that animals may drink alcohol for caloric purposes. However, a rat that drinks alcohol for the pharmacological effects must consume enough alcohol to have a blood ethanol concentration (BEC) of 80 to 100 mg/dL. Among the five rat lines genetically selected for high alcohol consumption, Sinclair and colleagues (1989) developed the ALKO AA (alcohol-preferring) rats, which prefer 10% alcohol solution over water. They differ from the nonpreferring (ANA) line of rats in alcohol-related reinforcement behaviors, alcohol metabolism, alcohol tolerance, and alcohol-induced neurochemical changes (Kiianmaa et al. 1991).

The second line is the Sardinian alcohol-preferring line of rats (sP; Colombo 1997), which consume more than 4 g/kg of 10% alcohol solution during the first alcohol drinking session and can drink up to 6 g/kg of alcohol in subsequent weeks. They are reported to achieve pharmacologically relevant BEC at each drinking session and to exhibit “binge”like drinking behavior (i.e., three drinking bouts per day; Loi et al. 2010).

The third line, Marchigian Sardinian (msP) rats, was genetically selected for the animals’ high alcohol preference from the original sP rats (Ciccocioppo et al. 1998). Although the msP rats share many of the sP rats’ phenotypic traits (e.g., alcohol preference and binge-like drinking behavior), they are also highly vulnerable to stress-induced relapse of alcohol consumption (Ciccocioppo et al. 2006). Indeed, they exhibit many of the behavioral traits of human alcoholics.

The fourth line of “alcoholic” rat was selectively bred to exhibit high alcohol consumption, resulting in the highly useful alcohol-preferring P rat line at Indiana University (Li et al. 1987). P rats exhibit voluntary alcohol consumption of 10 to 30% alcohol solution to the point of intoxication, and bar-press to self-administer alcohol resulting in pharmacologically relevant BECs (in the range of 50–200 mg%; McBride and Li 1998). P rats also show binge-like drinking patterns during the dark cycle, consuming about 6 g/kg of ethanol during a 1-hour access period (Bell et al. 2006). In addition to consuming high quantities of alcohol, P rats are less sensitive to the sedative and aversive effects of alcohol (Stewart et al. 1996), exhibit greater responses to its euphoric (stimulatory) properties (Bell et al. 2006), and show enhanced anxiety-related behaviors (Stewart et al. 1993). The P rats self-administer alcohol in a variety of experimental paradigms (e.g., intragastric, intracranial, and operant administration; Bell et al. 2006) and work very hard to obtain alcohol (Penn et al. 1978). Thus, the P rat appears to be a valid animal model for human alcoholism (Li et al. 1987).

The fifth rat line is the UCh-B line. In the 1940s, researchers at the University of Chile used genetic selection to develop a rat model for high alcohol consumption, resulting in the selection and breeding of high- and low-alcohol-consuming rats (UCh-abstainer, or UCh-A, and UCh-bibulous, or UCh-B, ILAR Journal

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

To cure the addiction, however, one must stop taking nicotine, and currently there is no effective therapy for this condition.

Clinical practice suggests that nicotine replacement therapy (bupropion, varenicline, and other nicotinic receptor partial agonists) and second-line medications such as nortriptyline and clonidine can ease craving (Fiore and Jaen 2008; Polosa and Benowitz 2011). In addition to dopamineand serotonin-based drugs, glutamatergic medications may be useful for the treatment of nicotine addiction (Olive et al.

2012) as preclinical studies suggest that glutamatergic transmission plays a critical role in drug addiction including drug reward, reinforcement, and relapse (Bird and Lawrence 2009; Moussawi and Kalivas 2010). Various other drugs tested for their treatment potential in nicotine addiction are discussed in a review by Polosa and Benowitz (2011).

respectively) (Tampier et al. 1984). Although these animals were the earliest known strains of rats that differ in alcohol preference, they were not widely used in alcohol research outside South America. Thus, the validity of this rat strain as a model for alcohol addiction research remains to be determined.

Models of Binge Drinking

Volume 53, Number 1

2012

Treatment Treatments for alcohol abuse have not advanced much since the early 1900s. Disulfiram (Antabuse), used to deter individuals from drinking alcohol, has been prescribed in clinical practice since the 1940s. This drug prevents aldehyde dehydrogenase from breaking down acetaldehyde to form acetic acid, resulting in a buildup of acetaldehyde in the body that causes aversive reactions such as flushing, increased heart rate, and nausea. Given these adverse effects, the primary barrier for employing disulfiram as a clinical treatment is patient compliance; thus a disulfiram implant is a treatment choice for some medical practitioners.

Neurobiological research using animal models indicates that opioid receptors and ␤-endorphin systems modulate alcohol consumption behavior, presumably via the corticomesolimbic dopamine system (Anton 2008; Haile et al. 2008; Rosner et al. 2010). For example, opioid receptor antagonists such as naltrexone and nalmefene reduce alcohol consumption (Garbutt 2010; Lobmaier et al. 2010; Rosner et al.

2010).

9

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

Binge drinking is defined as a pattern of alcohol consumption that results in a BEC of more than 80 mg% in about 2 hours (Crabbe et al. 2011). This clearly harmful drinking behavior (NIAAA Newsletter 2004) is practiced by a growing number of young drinkers: the 2010 NIDA-sponsored Monitoring the Future Survey reports that rates of binge drinking (defined as five or more drinks in a row in the previous 2-week period) were a worrisome 8%, 16%, and 25% among 8th, 10th, and 12th graders, respectively. The age of drinking onset is of particular concern given the link between adolescent binge drinking and the likelihood of later addiction (Enoch 2011): individuals who start drinking at ages 14 to 16 are four times more likely to become alcohol dependent than those who begin drinking at age 21 (Hingson et al. 2006).

Both human and animal studies suggest that binge-like alcohol exposure during adolescence is particularly harmful to brain and behavioral development. It is not known, however, how normal adolescent changes in psychosocial, endocrine, and brain function increase risky behaviors such as alcohol use, and how early alcohol use in turn alters the trajectory of adolescent development toward addiction risk. Animal models and controlled environmental conditions are necessary for disentangling these issues, especially given that alcohol use in humans is often accompanied by other potential mediating factors such as stress and drug use. Thus, it is important to include developmental aspects in animal models of alcohol abuse to improve scientific understanding of the etiology of alcoholism.

Animal studies should also model key aspects of human adolescent alcohol use such as increased alcohol intake relative to adults and binge drinking to intoxication. Rodent models are emerging that meet these criteria for adolescent drinking. For example, investigators have studied adolescent rats and mice that voluntarily drink more than adults under both continuous-access (Doremus et al. 2005; Tolliver and Samson 1991; Truxell et al. 2007; Vetter et al. 2007) and limited-access conditions (Maldonado-Devincci et al. 2010; Metten et al. 2011). In addition, some adolescent rodents actually do drink to intoxication, especially when tested in limited-access paradigms (Rhodes et al. 2005; Strong et al.

2010).

Limited-access paradigms have been particularly valuable in inducing adolescent binge-drinking behavior. “Drinking in the dark” (DID) models allow temporary access (2–4 hours) to alcohol during the dark phase of the light:dark cycle, when animals are most active. Although overall alcohol intake is

lower relative to continuous-access drinking paradigms, animals drink to intoxication in a short period of time and consume more alcohol per drinking bout (Rhodes et al. 2005).

Recent data also demonstrate that limited access to alcohol during adolescence causes increased baseline (Metten et al.

2011; Strong et al. 2010) and dependence-related alcohol consumption in adulthood (Gilpin et al. 2012). Thus, limitedaccess adolescent drinking paradigms appear to be successful in modeling both the binge-like pattern of adolescent drinking behavior and the consequences of adolescent alcohol consumption on adult alcohol use and risk of dependence.

The addictive properties of alcohol may be mediated by GABA neural transmission. Alcohol has been shown to disinhibit VTA GABA neurons (Brodie et al. 1999), resulting in the release of dopamine in the NAc. Connexin-36 (Cx36) gap junctions regulate the functional activity of GABA neurons in the VTA. Cx36 KO mice exhibit less motor impairment by acute alcohol administration and drink significantly less alcohol than wild types in a binge DID paradigm. Decreased drinking in Cx36 KO mice may be due to a diminished hedonic valence for alcohol (Steffensen et al. 2011).

GABAA receptors are known to mediate various effects of alcohol including behavioral sensitivity and consumption (for review see Boehm et al. 2006). GABAA receptors are composed of ␣1–6, ␤2–3, ␥2, and/or ␦ subunits, and these receptor activities are determined by the composition of subunits. For example, ␦ subunit KO resulted in significantly lower alcohol consumption (Mihalek et al. 2001), but ␣5 subunit gene deletion had no effect on alcohol reward (Stephens et al. 2005). Moreover, mice lacking PKCepsilon (PKC␧) drink less alcohol and show greater alcohol sensitivity (Newton and Messing 2007; Wallace et al. 2007). However, systematic studies are needed to validate these models for altering alcohol consumption.

Recent studies also suggest that gamma-hydroxybutyric acid (Addolorato et al. 2009), acamprosate (Mann et al. 2008), baclofen (Soyka and Rosner 2010), and desipramine (O’Brien et al. 2011) may have potential for the treatment of alcohol dependence, most likely through varied and unidentified mechanisms. This variability is not surprising given that alcohol addiction is a polygenic disease that involves many neurobiological pathways and numerous genes (for review see Goldman et al. 2005). As such, finding an effective treatment for alcohol addiction is a significant scientific challenge.

Acknowledgments

Perspectives and Other Considerations

Disclosure

One promising area of addiction research is the study of the interactions between memory and reward neural circuitry. It is clear from the literature that relapse into drug seeking is a key feature of addiction, and that drug-seeking behavior for all classes of drugs is driven in part by associations formed between drug-related stimuli and the rewarding effects of a drug (Miller and Marshall 2005).

Associations between drug-paired cues and the rewarding effects of a drug can be conceptualized as an “addiction memory” (Kelley 2004). In this view, addiction is composed of two primary processes—the acquisition and the extinction of the cue-paired reinforcing effects of a drug. Thus, failure to extinguish an acquired “memory of addiction” may lead to relapse.

In line with this reasoning, recent studies have emphasized the importance of drug-cue extinction in addiction treatment (Dhonnchadha and Kantak 2011; Weiss 2010). Extinction is not memory erasure per se but rather involves the formation of new memories that inhibit the existing memory. Interestingly, the process of extinction is sensitive to different memoryforming techniques as well as to medications that improve memory and enhance the efficacy of exposure therapy (Taylor et al. 2009).

In addition to extinction processes, other means of disrupting addiction memories are available; for example, interfering with drug memory reconsolidation shows some promise (Milton and Everitt 2010; Milton et al. 2012). Memory reconsolidation, considered to be a process distinct from extinction, occurs immediately after a memory is reactivated or retrieved, when the newly retrieved memory is vulnerable to modification. Thus, manipulating memory reconsolidation processes may disrupt cue-drug memories in animal models of drug relapse. For example, despite evidence that cocaine addiction is resistant to extinction (Weiss et al. 2001), recent work using a CPP model demonstrated that the N-methyl-d-aspartate (NMDA) antagonist MK-801 disrupts reconsolidation of cocaine-associated memories in rats (Brown et al. 2008) and that the addiction memory can thus be “erased” by manipulating reconsolidation processes.

A greater combined understanding of the neurobiological processes involved in memory extinction and reconsolidation will support the development of efficacious medications for the therapeutic treatment of drug addiction.

The authors declare no conflict of interest. The opinion expressed in this article is exclusively the authors’ own and is not a reflection of the policies of the University of Colorado Denver Anschutz Medical Campus. The university is not liable for any legal problems as a direct result of this publication.

References Addolorato G, Leggio L, Ferrulli A, Caputo F, Gasbarrini A. 2009. The therapeutic potential of gamma-hydroxybutyric acid for alcohol dependence: Balancing the risks and benefits—A focus on clinical data.

Expert Opin Investig Drugs 18:675-686.

Ahmed SH, Koob GF. 1998. Transition from moderate to excessive drug intake: Change in hedonic set point. Science 282:298-300.

Ahmed SH, Walker JR, Koob GF. 2000. Persistent increase in the motivation to take heroin in rats with a history of drug escalation. Neuropsychopharmacology 22:413-421.

Anton RF. 2008. Naltrexone for the management of alcohol dependence. N Engl J Med 359:715-721.

Beguin C, Potter DN, Dinieri JA, Munro TA, Richards MR, Paine TA, Berry L, Zhao Z, Roth BL, Xu W, Liu-Chen LY, Carlezon WA Jr, Cohen BM. 2008. N-methylacetamide analog of salvinorin A: A highly potent and selective kappa-opioid receptor agonist with oral efficacy. J Pharmacol Exp Ther 324:188-195.

Bell RL, Rodd ZA, Lumeng L, Murphy JM, McBride WJ. 2006. The alcohol-preferring P rat and animal models of excessive alcohol drinking.

Addict Biol 11:270-288.

Bhatia KS, Szabo ST, Fowler JC, Wetsel WC, Lee TH. 2011. Reversal of long-term methamphetamine sensitization by combination of pergolide with ondansetron or ketanserin, but not mirtazapine. Behav Brain Res 223:227-232.

Bird MK, Lawrence AJ. 2009. Group I metabotropic glutamate receptors: Involvement in drug-seeking and drug-induced plasticity. Curr Mol Pharmacol 2:83-94.

Boehm SL 2nd, Ponomarev I, Blednov YA, Harris RA. 2006. From gene to behavior and back again: New perspectives on GABAA receptor subunit selectivity of alcohol actions. Adv Pharmacol 54:171-203.

Bozarth MA, Gerber GJ, Wise RA. 1980. Intracranial self-stimulation as a technique to study the reward properties of drugs of abuse. Pharmacol Biochem Behav 13 Suppl 1:245-247.

Brodie MS, Pesold C, Appel SB. 1999. Ethanol directly excites dopaminergic ventral tegmental area reward neurons. Alcohol Clin Exp Res 23:1848-1852.

Broekkamp CL, Pijnenburg AJ, Cools AR, Van Rossum JM. 1975. The effect of microinjections of amphetamine into the neostriatum and the nucleus accumbens on self-stimulation behaviour. Psychopharmacologia 42:179-183.

Brown TE, Lee BR, Sorg BA. 2008. The NMDA antagonist MK-801 disrupts reconsolidation of a cocaine-associated memory for conditioned

ILAR Journal

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

10

This work is supported in part by National Institutes of Health National Institute on Alcohol Abuse and Alcoholism (NIH-NIAAA) grant AA018328 (Wu), a Veterans Administration Career Development Award (Schulz), and the Developmental Psychobiology Research Group (Schulz) at the University of Colorado Anschutz Medical Campus. We thank Dr. Karen Stevens, Dr. Kristin Andrud, and April Mattson for their helpful comments on this manuscript.

Volume 53, Number 1

2012

Fiore MC, Jaen CR. 2008. A clinical blueprint to accelerate the elimination of tobacco use. JAMA 299:2083-2085.

Garbutt JC. 2010. Efficacy and tolerability of naltrexone in the management of alcohol dependence. Curr Pharm Des 16:2091-2097.

Gilpin NW, Karanikas CA, Richarson HN. 2012. Adolescent binge drinking leads to changes in alcohol drinking, anxiety, and amygdalar corticotropin releasing factor cells in adulthood in male rats. PLoS One 7:e31466.

Giros B, Jaber M, Jones SR, Wightman RM, Caron MG. 1996. Hyperlocomotion and indifference to cocaine and amphetamine in mice lacking the dopamine transporter. Nature 379:606-612.

Goldman D, Oroszi G, Ducci F. 2005. The genetics of addictions: Uncovering the genes. Nat Rev Genet 6:521-532.

Goldstein DB. 1977. Temporal patterns of voluntary alcohol intake. Adv Exp Med Biol 85B:539-546.

Gossop M. 1988. Clonidine and the treatment of the opiate withdrawal syndrome. Drug Alcohol Depend 21:253-259.

Gossop M, Griffiths P, Bradley B, Strang J. 1989. Opiate withdrawal symptoms in response to 10-day and 21-day methadone withdrawal programmes. Br J Psychiatry 154:360-363.

Gowing L, Ali R, White JM. 2009. Buprenorphine for the management of opioid withdrawal. Cochrane Database Syst Rev:CD002025.

Gudelsky GA, Yamamoto BK. 2008. Actions of 3,4-methylenedioxymethamphetamine (MDMA) on cerebral dopaminergic, serotonergic and cholinergic neurons. Pharmacol Biochem Behav 90:198-207.

Haile CN, Kosten TA, Kosten TR. 2008. Pharmacogenetic treatments for drug addiction: Alcohol and opiates. Am J Drug Alcohol Abuse 34:355381.

Hasin D, Hatzenbuehler ML, Keyes K, Ogburn E. 2006. Substance Use Disorders: Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) and International Classification of Diseases, 10th ed.

(ICD-10). Addiction 101(Suppl 1):59-75.

Hernandez PJ, Kelley AE. 2005. Cracking addiction the second time around: Reconsolidation of drug-related memories. Neuron 47:772775.

Hingson RW, Heeren T, Winter MR. 2006. Age at drinking onset and alcohol dependence: Age at onset, duration, and severity. Arch Pediatr Adolesc Med 160:739-746.

Hirose N, Murakawa K, Takada K, Oi Y, Suzuki T, Nagase H, Cools AR, Koshikawa N. 2005. Interactions among mu- and delta-opioid receptors, especially putative delta1- and delta2-opioid receptors, promote dopamine release in the nucleus accumbens. Neuroscience 135:213-225.

Hnasko TS, Sotak BN, Palmiter RD. 2007. Cocaine-conditioned place preference by dopamine-deficient mice is mediated by serotonin. J Neurosci 27:12484-12488.

Huddleston HG, Racowsky C, Jackson KV, Fox JH, Ginsburg ES. 2008.

Coasting vs. Cryopreservation of all embryos for prevention of ovarian hyperstimulation syndrome in in vitro fertilization. Fertil Steril 90:12591262.

Hutcheson DM, Matthes HW, Valjent E, Sanchez-Blazquez P, Rodriguez-Diaz M, Garzon J, Kieffer BL, Maldonado R. 2001. Lack of dependence and rewarding effects of deltorphin ii in mu-opioid receptor-deficient mice.

Eur J Neurosci 13:153-161.

Johnson SW, North RA. 1992. Opioids excite dopamine neurons by hyperpolarization of local interneurons. J Neurosci 12:483-488.

Josselyn SA, Beninger RJ. 1993. Neuropeptide Y: Intraaccumbens injections produce a place preference that is blocked by cis-flupenthixol.

Pharmacol Biochem Behav 46:543-552.

Kalivas PW, Volkow ND. 2011. New medications for drug addiction hiding in glutamatergic neuroplasticity. Mol Psychiatry 16:974-986.

Kelley AE. 2004. Memory and addiction: Shared neural circuitry and molecular mechanisms. Neuron 44:161-179.

Kiianmaa K, Stenius K, Sinclair JD. 1991. Determinants of alcohol preference in the AA and ANA rat lines selected for differential ethanol intake. Alcohol Alcohol 1:115-120.

Klink R, de Kerchove d’Exaerde A, Zoli M, Changeux JP. 2001. Molecular and physiological diversity of nicotinic acetylcholine receptors in the midbrain dopaminergic nuclei. J Neurosci 21:1452-1463.

11

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

place preference but not for self-administration in rats. Learn Mem 15:857-865.

Budygin EA, Brodie MS, Sotnikova TD, Mateo Y, John CE, Cyr M, Gainetdinov RR, Jones SR. 2004. Dissociation of rewarding and dopamine transporter-mediated properties of amphetamine. Proc Natl Acad Sci U S A 101:7781-7786.

Carlezon WA Jr, Beguin C, DiNieri JA, Baumann MH, Richards MR, Todtenkopf MS, Rothman RB, Ma Z, Lee DY, Cohen BM. 2006. Depressive-like effects of the kappa-opioid receptor agonist salvinorin A on behavior and neurochemistry in rats. J Pharmacol Exp Ther 316:440447.

Changeux JP. 2010. Nicotine addiction and nicotinic receptors: Lessons from genetically modified mice. Nat Rev Neurosci 11:389-401.

Chefer VI, Czyzyk T, Bolan EA, Moron J, Pintar JE, Shippenberg TS. 2005.

Endogenous kappa-opioid receptor systems regulate mesoaccumbal dopamine dynamics and vulnerability to cocaine. J Neurosci 25:5029-5037.

Chen R, Tilley MR, Wei H, Zhou F, Zhou FM, Ching S, Quan N, Stephens RL, Hill ER, Nottoli T, Han DD, Gu HH. 2006. Abolished cocaine reward in mice with a cocaine-insensitive dopamine transporter. Proc Natl Acad Sci U S A 103:9333-9338.

Ciccocioppo R, Economidou D, Cippitelli A, Cucculelli M, Ubaldi M, Soverchia L, Lourdusamy A, Massi M. 2006. Genetically selected marchigian sardinian alcohol-preferring (msP) rats: An animal model to study the neurobiology of alcoholism. Addict Biol 11:339-355.

Ciccocioppo R, Panocka I, Polidori C, Froldi R, Angeletti S, Massi M. 1998. Mechanism of action for reduction of ethanol intake in rats by the tachykinin nk-3 receptor agonist aminosenktide. Pharmacol Biochem Behav 61:459-464.

Colle LM, Wise RA. 1988. Effects of nucleus accumbens amphetamine on lateral hypothalamic brain stimulation reward. Brain Res 459:361-368.

Colombo G. 1997. Esbra-Nordmann 1996 Award Lecture: Ethanol drinking behaviour in Sardinian alcohol-preferring rats. Alcohol Alcohol 32:443453.

Corbett D, Wise RA. 1980. Intracranial self-stimulation in relation to the ascending dopaminergic systems of the midbrain: A moveable electrode mapping study. Brain Res 185:1-15.

Crabbe JC, Harris RA, Koob GF. 2011. Preclinical studies of alcohol binge drinking. Ann N Y Acad Sci 1216:24-40.

Crabbe JC, Merrill CM, Kim D, Belknap JK. 1990. Alcohol dependence and withdrawal: A genetic animal model. Ann Med 22:259-263.

Devine DP, Leone P, Pocock D, Wise RA. 1993. Differential involvement of ventral tegmental mu, delta and kappa opioid receptors in modulation of basal mesolimbic dopamine release: In vivo microdialysis studies. J Pharmacol Exp Ther 266:1236-1246.

Devine DP, Wise RA. 1994. Self-administration of morphine, damgo, and dpdpe into the ventral tegmental area of rats. J Neurosci 14:1978-1984.

Dhonnchadha BA, Kantak KM. 2011. Cognitive enhancers for facilitating drug cue extinction: Insights from animal models. Pharmacol Biochem Behav 99:229-244.

Donovan DM, Miner LL, Perry MP, Revay RS, Sharpe LG, Przedborski S, Kostic V, Philpot RM, Kirstein CL, Rothman RB, Schindler CW, Uhl GR. 1999. Cocaine reward and MPTP toxicity: Alteration by regional variant dopamine transporter overexpression. Brain Res Mol Brain Res 73:37-49.

Doremus TL, Brunell SC, Rajendran P, Spear LP. 2005. Factors influencing elevated ethanol consumption in adolescent relative to adult rats. Alcoholism 29:1796-1808.

Enoch MA. 2011. The role of early life stress as a predictor for alcohol and drug dependence. Psychopharmacology (Berl) 214:17-31.

Erwin VG, Deitrich RA. 1996. Genetic selection and characterization of mouse lines for acute functional tolerance to ethanol. J Pharmacol Exp Ther 279:1310-1317.

Falk JL, Samson HH, Winger G. 1972. Behavioral maintenance of high concentrations of blood ethanol and physical dependence in the rat. Science 177:811-813.

Filip M, Alenina N, Bader M, Przegalinski E. 2010. Behavioral evidence for the significance of serotoninergic (5-ht) receptors in cocaine addiction.

Addict Biol 15:227-249.

12

NIAAA Newsletter. 2004. NIAAA Council approves definition of binge drinking. Department of Health and Human Services, National Institutes of Health, number 3.

O’Brien C. 2011. Addiction and dependence in DSM-V. Addiction 106:866867.

O’Brien CP, Gastfriend DR, Forman RF, Schweizer E, Pettinati HM. 2011.

Long-term opioid blockade and hedonic response: Preliminary data from two open-label extension studies with extended-release naltrexone. Am J Addict 20:106-112.

Olds J, Milner P. 1954. Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain. J Comp Physiol Psychol 47:419-427.

Olive MF, Cleva RM, Kalivas PW, Malcolm RJ. 2012. Glutamatergic medications for the treatment of drug and behavioral addictions. Pharmacol Biochem Behav 100:801-810.

Olmstead MC, Franklin KB. 1997. The development of a conditioned place preference to morphine: Effects of microinjections into various CNS sites. Behav Neurosci 111:1324-1334.

Peng XQ, Xi ZX, Li X, Spiller K, Li J, Chun L, Wu KM, Froimowitz M, Gardner EL. 2010. Is slow-onset long-acting monoamine transport blockade to cocaine as methadone is to heroin? Implication for antiaddiction medications. Neuropsychopharmacology 35:2564-2578.

Penn PE, McBride WJ, Lumeng L, Gaff TM, Li TK. 1978. Neurochemical and operant behavioral studies of a strain of alcohol-preferring rats.

Pharmacol Biochem Behav 8:475-481.

Phillips AG, LePiane FG. 1980. Reinforcing effects of morphine microinjection into the ventral tegmental area. Pharmacol Biochem Behav 12:965-968.

Polosa R, Benowitz NL. 2011. Treatment of nicotine addiction: Present therapeutic options and pipeline developments. Trends Pharmacol Sci 32:281-289.

Pons S, Fattore L, Cossu G, Tolu S, Porcu E, McIntosh JM, Changeux JP, Maskos U, Fratta W. 2008. Crucial role of alpha4 and alpha6 nicotinic acetylcholine receptor subunits from ventral tegmental area in systemic nicotine self-administration. J Neurosci 28:12318-12327.

Rhodes JS, Best K, Belknap JK, Finn DA, Crabbe JC. 2005. Evaluation of a simple model of ethanol drinking to intoxication in c57bl/6j mice.

Physiol Behav 84:53-63.

Ripley TL, Stephens DN. 2011. Critical thoughts on current rodent models for evaluating potential treatments of alcohol addiction and withdrawal.

Br J Pharmacol 164:1335-1356.

Robinson TE, Berridge KC. 1993. The neural basis of drug craving: An incentive-sensitization theory of addiction. Brain Res Brain Res Rev 18:247-291.

Rocha BA, Fumagalli F, Gainetdinov RR, Jones SR, Ator R, Giros B, Miller GW, Caron MG. 1998. Cocaine self-administration in dopaminetransporter knockout mice. Nat Neurosci 1:132-137.

Rosner S, Hackl-Herrwerth A, Leucht S, Vecchi S, Srisurapanont M, Soyka M. 2010. Opioid antagonists for alcohol dependence. Cochrane Database Syst Rev:CD001867.

Sager JJ, Torres GE. 2011. Proteins interacting with monoamine transporters: Current state and future challenges. Biochemistry 50:7295-7310.

Schenk S. 2011. MDMA (“Ecstasy”) abuse as an example of dopamine neuroplasticity. Neurosci Biobehav Rev 35:1203-1218.

Schenk S, Gittings D, Colussi-Mas J. 2011. Dopaminergic mechanisms of reinstatement of MDMA-seeking behaviour in rats. Br J Pharmacol 162:1770-1780.

Schildein S, Agmo A, Huston JP, Schwarting RK. 1998. Intraaccumbens injections of substance P, morphine and amphetamine: Effects on conditioned place preference and behavioral activity. Brain Res 790:185-194.

Schultz W. 2010. Dopamine signals for reward value and risk: Basic and recent data. Behav Brain Funct 6:24.

Seger D. 2010. Cocaine, metamfetamine, and MDMA abuse: The role and clinical importance of neuroadaptation. Clin Toxicol (Phila) 48:695708.

Seiden LS, Sabol KE, Ricaurte GA. 1993. Amphetamine: Effects on catecholamine systems and behavior. Annu Rev Pharmacol Toxicol 33:639677.

ILAR Journal

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

Knapp CM, Kornetsky C. 1994. Bromocriptine, a D2 receptor agonist, lowers the threshold for rewarding brain stimulation. Pharmacol Biochem Behav 49:901-904.

Land BB, Bruchas MR, Lemos JC, Xu M, Melief EJ, Chavkin C. 2008. The dysphoric component of stress is encoded by activation of the dynorphin kappa-opioid system. J Neurosci 28:407-414.

Lee JL, Milton AL, Everitt BJ. 2006. Cue-induced cocaine seeking and relapse are reduced by disruption of drug memory reconsolidation. J Neurosci 26:5881-5887.

Li TK, Lumeng L, McBride WJ, Murphy JM. 1987. Rodent lines selected for factors affecting alcohol consumption. Alcohol Alcohol 1:91-96.

Lobmaier P, Gossop M, Waal H, Bramness J. 2010. The pharmacological treatment of opioid addiction: A clinical perspective. Eur J Clin Pharmacol 66:537-545.

Loi B, Lobina C, Maccioni P, Fantini N, Carai MA, Gessa GL, Colombo G. 2010. Increase in alcohol intake, reduced flexibility of alcohol drinking, and evidence of signs of alcohol intoxication in Sardinian alcoholpreferring rats exposed to intermittent access to 20% alcohol. Alcohol Clin Exp Res 34:2147-2154.

Lynch WJ, Nicholson KL, Dance ME, Morgan RW, Foley PL. 2010. Animal models of substance abuse and addiction: Implications for science, animal welfare, and society. Comp Med 60:177-188.

Maldonado-Devincci AM, Alipour KK, Michael LA, Kirstein CL. 2010.

Repeated binge ethanol administration during adolescence enhances voluntary sweetened ethanol intake in young adulthood in male and female rats. Pharmacol Biochem Behav 96:476-487.

Mann K, Kiefer F, Spanagel R, Littleton J. 2008. Acamprosate: Recent findings and future research directions. Alcohol Clin Exp Res 32:11051110.

McBride WJ, Li TK. 1998. Animal models of alcoholism: Neurobiology of high alcohol-drinking behavior in rodents. Crit Rev Neurobiol 12:339-369.

McClearn GE. 1972. Genetics as a tool in alcohol research. Ann N Y Acad Sci 197:26-31.

Metten P, Brown LL, Crabbe JC. 2011. Limited access ethanol drinking in the dark in adolescent and adult mice. Pharmacol Biochem Behav 98:279-285.

Mihalek RM, Bowers BJ, Wehner JM, Kralic JE, VanDoren MJ, Morrow AL, Homanics GE. 2001. GABA(A)-receptor delta subunit knockout mice have multiple defects in behavioral responses to ethanol. Alcohol Clin Exp Res 25:1708-1718.

Miller CA, Marshall JF. 2005. Molecular substrates for retrieval and reconsolidation of cocaine-associated contextual memory. Neuron 47: 873-884.

Milton AL, Everitt BJ. 2010. The psychological and neurochemical mechanisms of drug memory reconsolidation: Implications for the treatment of addiction. Eur J Neurosci 31:2308-2319.

Milton AL, Schramm MJ, Wawrzynski JR, Gore F, Oikonomou-Mpegeti F, Wang NQ, Samuel D, Economidou D, Everitt BJ. 2012. Antagonism at NMDA receptors, but not beta-adrenergic receptors, disrupts the reconsolidation of Pavlovian conditioned approach and instrumental transfer for ethanol-associated conditioned stimuli. Psychopharmacology (Berl) 219:751-761.

Missale C, Nash SR, Robinson SW, Jaber M, Caron MG. 1998. Dopamine receptors: From structure to function. Physiol Rev 78:189-225.

Montoya ID, Preston KL, Rothman R, Gorelick DA. 2002. Open-label pilot study of bupropion plus bromocriptine for treatment of cocaine dependence. Am J Drug Alcohol Abuse 28:189-196.

Moussawi K, Kalivas PW. 2010. Group II metabotropic glutamate receptors (MGLU2/3) in drug addiction. Eur J Pharmacol 639:115-122.

Mucha RF, van der Kooy D, O’Shaughnessy M, Bucenieks P. 1982. Drug reinforcement studied by the use of place conditioning in rat. Brain Res 243:91-105.

Myers RD, Veale WL. 1968. Alcohol preference in the rat: Reduction following depletion of brain serotonin. Science 160:1469-1471.

Newton PM, Messing RO. 2007. Increased sensitivity to the aversive effects of ethanol in PKCepsilon null mice revealed by place conditioning. Behav Neurosci 121:439-442.

Volume 53, Number 1

2012

Thomsen M, Han DD, Gu HH, Caine SB. 2009b. Lack of cocaine selfadministration in mice expressing a cocaine-insensitive dopamine transporter. J Pharmacol Exp Ther 331:204-211.

Tilley MR, Cagniard B, Zhuang X, Han DD, Tiao N, Gu HH. 2007. Cocaine reward and locomotion stimulation in mice with reduced dopamine transporter expression. BMC Neurosci 8:42.

Tolliver GA, Samson HH. 1991. The influence of early postweaning ethanol exposure on oral self-administration behavior in the rat. Pharmacol Biochem Behav 38:575-580.

Truxell EM, Molina JC, Spear NE. 2007. Ethanol intake in the juvenile, adolescent, and adult rat: Effects of age and prior exposure to ethanol.

Alcoholism 31:755-765.

Ushijima I, Carino MA, Horita A. 1995. Involvement of D1 and D2 dopamine systems in the behavioral effects of cocaine in rats. Pharmacol Biochem Behav 52:737-741.

Veilleux JC, Colvin PJ, Anderson J, York C, Heinz AJ. 2010. A review of opioid dependence treatment: Pharmacological and psychosocial interventions to treat opioid addiction. Clin Psychol Rev 30:155-166.

Vetter CS, Doremus-Fitzwater TL, Spear LP. 2007. Time course of elevated ethanol intake in adolescent relative to adult rats under continuous, voluntary-access conditions. Alcoholism 31:1159-1168.

Wallace MJ, Newton PM, Oyasu M, Chou WH, Connolly J, Messing RO. 2007. Acute functional tolerance to ethanol mediated by protein kinase Cepsilon. Neuropsychopharmacology 32:127-136.

Weiss F. 2010. Advances in animal models of relapse for addiction research.

In: Kuhn CM, Koob GF, eds. Advances in the Neuroscience of Addiction. Boca Raton: CRC Press.

Weiss F, Martin-Fardon R, Ciccocioppo R, Kerr TM, Smith DL, BenShahar O. 2001. Enduring resistance to extinction of cocaine-seeking behavior induced by drug-related cues. Neuropsychopharmacology 25:361-372.

Weissenborn R, Deroche V, Koob GF, Weiss F. 1996. Effects of dopamine agonists and antagonists on cocaine-induced operant responding for a cocaine-associated stimulus. Psychopharmacology (Berl) 126:311322.

Wise RA. 1981. Intracranial self-stimulation: Mapping against the lateral boundaries of the dopaminergic cells of the substantia nigra. Brain Res 213:190-194.

Wise RA. 1996. Addictive drugs and brain stimulation reward. Annu Rev Neurosci 19:319-340.

Wise RA. 2008. Dopamine and reward: The anhedonia hypothesis 30 years on. Neurotox Res 14:169-183.

Withers NW, Pulvirenti L, Koob GF, Gillin JC. 1995. Cocaine abuse and dependence. J Clin Psychopharmacol 15:63-78.

Yoshida Y, Koide S, Hirose N, Takada K, Tomiyama K, Koshikawa N, Cools AR. 1999. Fentanyl increases dopamine release in rat nucleus accumbens: Involvement of mesolimbic mu- and delta-2-opioid receptors.

Neuroscience 92:1357-1365.

13

Downloaded from http://ilarjournal.oxfordjournals.org/ at University of Colorado systems on June 30, 2013

Sinclair JD, Le AD, Kiianmaa K. 1989. The AA and ANA rat lines, selected for differences in voluntary alcohol consumption. Experientia 45:798-805.

Somaini L, Donnini C, Raggi MA, Amore M, Ciccocioppo R, Saracino MA, Kalluppi M, Malagoli M, Gerra ML, Gerra G. 2011. Promising medications for cocaine dependence treatment. Recent Pat CNS Drug Discov 6:146-160.

Song R, Yang RF, Wu N, Su RB, Li J, Peng XQ, Li X, Gaal J, Xi ZX, Gardner EL. 2012. Yqa14: A novel dopamine D(3) receptor antagonist that inhibits cocaine self-administration in rats and mice, but not in D(3) receptor-knockout mice. Addict Biol 17:259-273.

Soyka M, Rosner S. 2010. Nalmefene for treatment of alcohol dependence.

Expert Opin Investig Drugs 19:1451-1459.

Steffensen SC, Bradley KD, Hansen DM, Wilcox JD, Wilcox RS, Allison DW, Merrill CB, Edwards JG. 2011. The role of connexin-36 gap junctions in alcohol intoxication and consumption. Synapse 65:695-707.

Stephens DN, Pistovcakova J, Worthing L, Atack JR, Dawson GR. 2005.

Role of GABAa alpha5-containing receptors in ethanol reward: The effects of targeted gene deletion, and a selective inverse agonist. Eur J Pharmacol 526:240-250.

Stewart J, de Wit H, Eikelboom R. 1984. Role of unconditioned and conditioned drug effects in the self-administration of opiates and stimulants.

Psychol Rev 91:251-268.

Stewart RB, Gatto GJ, Lumeng L, Li TK, Murphy JM. 1993. Comparison of alcohol-preferring (P) and nonpreferring (NP) rats on tests of anxiety and for the anxiolytic effects of ethanol. Alcohol 10:1-10.

Stewart RB, Murphy JM, McBride WJ, Lumeng L, Li TK. 1996. Place conditioning with alcohol in alcohol-preferring and -nonpreferring rats.

Pharmacol Biochem Behav 53:487-491.

Strang J, Gossop M. 1990. Comparison of linear versus inverse exponential methadone reduction curves in the detoxification of opiate addicts. Addict Behav 15:541-547.

Strong MN, Yoneyama N, Fretwell AM, Snelling C, Tanchuck MA, Finn DA. 2010. “Binge� drinking experience in adolescent mice shows sex differences and elevated ethanol intake in adulthood. Horm Behav 58:82-90.

Sulzer D, Sonders MS, Poulsen NW, Galli A. 2005. Mechanisms of neurotransmitter release by amphetamines: A review. Prog Neurobiol 75:406-433.

Taly A, Corringer PJ, Guedin D, Lestage P, Changeux JP. 2009. Nicotinic receptors: Allosteric transitions and therapeutic targets in the nervous system. Nat Rev Drug Discov 8:733-750.

Tampier L, Quintanilla ME, Contreras S, Segovia-Requelme N, Mardones J. 1984. Biological similarities and differences between rats genetically different in alcohol preference. Alcohol Alcohol 19:203-209.

Taylor JR, Olausson P, Quinn JJ, Torregrossa MM. 2009. Targeting extinction and reconsolidation mechanisms to combat the impact of drug cues on addiction. Neuropharmacology 56(Suppl)1:186-195.

Thomsen M, Hall FS, Uhl GR, Caine SB. 2009a. Dramatically decreased cocaine self-administration in dopamine but not serotonin transporter knock-out mice. J Neurosci 29:1087-1092.