Tobacco addiction

Chapter 9

Tobacco addiction: cognition, reinforcement, and mood Merideth A. Addicott Department of Psychiatry, University of Arkansas for Medical Science, Little Rock, AR, United States

Introduction This chapter introduces current research topics in tobacco addiction, beginning with a brief overview of the scope of the tobacco use problem and pharmacology of nicotine and tobacco. This chapter then focuses on three specific areas of research: nicotine and tobacco’s effects on cognition, reinforcement enhancement, and mood regulation. In each section, I review recent work in these areas. While relevant behavioral experiments in animals and human are discussed, there is an emphasis on neuroimaging research.

Scope of the problem Smoking prevalence Tobacco is the second most used drug after caffeine, used by about 30% of men and 6% of women worldwide (Ng et al., 2014). Currently in the United States, about 20% of adults use some form of tobacco, with cigarettes being the most common followed by electronic cigarettes (e-cigs), cigars/cigarillos, smokeless tobacco (e.g., chewing tobacco or snuff), and pipe (e.g., pipe, waterpipe/hookah) (Phillips et al., 2017). Given its prevalence, this review is focused on cigarette smoking. Among American adults, smoking rates have declined from a peak of about 40% in the 1960s to about 15% in 2017. However, between 35 and 40 million American adults currently smoke an average of 14 cigarettes per day (cigs/day) (Jamal et al., 2016; Drope et al., 2018). Despite the overall decline, some groups of people continue to have high smoking rates. Tobacco use, cigarette smoking in particular, tends to be higher among individuals with low education level (no more than a high school education), low socioeconomic status (earning <$35,000/year), physical disabilities, and individuals who are American Indian/ Alaska Natives, living in the Midwest, members of the

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lesbian/gay/bisexual community, uninsured or covered by Medicaid, and low ranking members of the military (Phillips et al., 2017; Drope et al., 2018). These disparities may have arisen from intentional tobacco industry targeting (e.g., retail density is higher in low income neighborhoods), reduced access to smoking cessation support, less support and/or pressure to quit smoking, and perhaps an increased vulnerability for tobacco addiction. In particular, these populations may experience high levels of social and/or economic stress that feeds into the emotionesmoking relationship (see The emotionesmoking relationship section). Compared with the general population, smoking is also much higher among individuals with serious psychological distress and mental illness, including schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, major depression, anxiety/panic disorders, posttraumatic stress disorder, alcohol or other drug use disorders, and gambling addiction (Grant and Potenza, 2005; Weinberger et al., 2016; Phillips et al., 2017; Drope et al., 2018).

Smoking-related morbidity and mortality Cigarette smoking continues to be the leading cause of preventable morbidity and mortality. It is responsible for 12.7% of all deaths in high-income countries (Lopez et al., 2006). It is well known that smoking causes cancer, and there are at least 70 carcinogens in cigarette smoke (FDA, 2012). Smoking also causes chronic obstructive pulmonary disease, type II diabetes, heart attacks, and strokes (Rostron et al., 2014). There is no safe level of smoking, as individuals who smoke only 1 cig/day have half the risk of developing coronary heart disease as individuals who smoke 20 cig/day (not 1/20th the risk as might be expected) (Hackshaw et al., 2018). Smoking is also associated with reproductive risks, such as infertility, spontaneous abortion,

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low birth weight, and sudden infant death syndrome (DHHS, 2016). Among HIV smokers receiving antiretroviral therapy, more years of life are lost due to smoking than to the HIV infection (Pacek and Cioe, 2015). Individuals with chronic mental illness die prematurely primarily due to cardiovascular disease and cancer (Colton and Manderscheid, 2006), which can be caused or exacerbated by smoking.

Smoking cessation Tobacco addiction is a chronic, relapsing disorder, and many smokers will make repeated quit attempts throughout their lives. Quitting smoking at any age significantly reduces the associated health risks. By 2015, 59% of adults in the United States who had ever smoked had quit, 68% of current smokers reported that they wanted to quit, and 55% reported making a past year quit attempt, of which about 7% were successful (Babb et al., 2017). Smoking cessation support consists of pharmacotherapies and psychosocial therapies/support groups that can increase cessation success by 82%, although few smokers use proven cessation treatments. Unfortunately, in 2017, only about two-thirds of smokers reported receiving advice from health professionals to quit in spite of the high morbidity and mortality burden (Babb et al., 2017).

Electronic cigarettes E-cigs and vaporizers are devices that use a batterypowered heating element to aerosolize a cartridge of liquid nicotinedalong with flavorants and other additivesdfor the user to inhale. The e-liquid usually contains propylene glycol and/or glycerin as a solvent and flavorants, such as fruit or candy flavors. Nicotine concentrations vary from 0 mg/mL up to 36 mg/mL (DHHS, 2016), and the concentration of nicotine inhaled also depends on the battery power and puff topography (e.g., duration and volume of inhalation). Given their recent rise in popularity, the long-term effects of e-cig use is poorly understood, but e-cigs can expose users to carbonyl compounds and volatile organic compounds, nitrosamines, formaldehyde, acetaldehyde, and glycidol, which are thought to have adverse health effects (DHHS, 2016). Another health threat is the accidental ingestion of liquid nicotine. The number of calls to poison control centers regarding e-cig fluid exposure have risen dramatically since 2010 (Kim and Baum, 2015). Although they are not marketed as smoking cessation aids, some smokers report using e-cigs to cut back or quit smoking (Etter and Bullen, 2011; Siegel et al., 2011). But other evidence indicates the development of co-use among conventional cigarette smokers (Pokhrel et al., 2015). For current smokers, e-cigs may be a means of harm reduction,

but the primary concern regarding e-cigs is their use among adolescents and young adults. E-cig use increased 900% between 2011 and 2015 among high school students, and ecigs are now the most commonly used tobacco product among youth (DHHS, 2016). Adolescents may become addicted to nicotine in e-cigs, face long-term health consequences from inhaling e-cig vapor, and switch to conventional cigarettes. Preventing adolescents from experimenting with tobacco products is critical to decreasing smoking rates across the life span.

Tobacco policy in the United States and the world The tobacco industry has played a major role in the prevalence of cigarette smoking in the United States via mass production and widespread advertising. Although the medical community had been aware of the link between smoking and disease before the 1960s, fierce opposition from tobacco companies stymied policy and social change and even promoted the beneficial health effects of smoking in cigarette advertisements (DHHS, 2014). In 1998, internal documents from the tobacco industry became widely available as the result of the Master Settlement Agreement. These documents reveal the internal operations of the industry regarding how they profited off the sale of tobacco while preventing litigation, resisting regulation, and protecting industry credibility. To accomplish these goals, they actively deceived the public and policy makers about the health risks of smoking, created controversy about these health risks, used lawyers extensively in the decisionmaking process, and used third parties to hide political lobbying, among other activities (Bero, 2003). Since the 1960s, there have been gradual changes in tobacco control policies in the United States, including warning labels on tobacco products, disclosure of tar and nicotine content of cigarettes, antismoking public service announcements, prohibition of tobacco advertisements in some media, banning smoking in public places, taxes on cigarettes to deter sales, and prohibition of the sale of tobacco to minors (DHHS, 2014). In 2009, the Family Smoking Prevention and Tobacco Control Act was signed into law, giving the Food and Drug Administration (FDA) the power to regulate tobacco, including the ability to set national standards for the nicotine content, manufacture, labeling, advertising, and sale of all tobacco products (Gostin, 2009). As of 2017, the FDA is considering tobacco product standards that would reduce nicotine in cigarettes to a minimal or nonaddictive level, considering regulating tobacco flavors, such as menthol, and considering actions to increase access to nicotine replacement therapies (FDA, 2017). In 2005, the World Health Organization entered into force the Framework Convention on Tobacco Control

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(FCTC), a global health treaty designed to stem the epidemic of tobacco-related health problems. The FCTC recommends a series of actions to achieve this goal, including measures to reduce both supply and demand of tobacco products. For example, recommendations include preventing tobacco industry interference with tobacco control policies, banning tobacco advertisements and industry sponsorships, and increasing price and taxes to reduce demand. By 2018, implementation of these recommendations across countries varied from 13% to 88% (WHO, 2018). The most successfully implemented actions have been restricting smoking in public places, placing health warnings on tobacco packages, educating tobacco users, and restricting sales to minors (WHO, 2018). There remains a significant unmet need for cessation support, and Parties to the FCTC have been slow to implement tobacco cessation measures, possibly due to the costs or uncertain effectiveness of tobacco cessation treatment (Raw et al., 2017).

Pharmacology Chemicals in tobacco smoke Nicotine is an alkaloid found in the tobacco plant and acts as a naturally occurring insecticide. Nicotine is considered the primary psychoactive substance responsible for tobacco addiction. However, cigarette smoke contains >7000 chemicals (Rodgman and Perfetti, 2009). Other chemicals in cigarette smoke may be psychoactive and either have their own abuse potential or contribute to the abuse potential of nicotine (Hoffman and Evans, 2013). These chemicals include acetaldehyde (a major metabolite of alcohol), minor alkaloids (e.g., nornicotine, myosmine, cotinine, anabasine, anatabine), and b-carbolines (e.g., harman and norharman) (Rupprecht et al., 2015). Furthermore, commercial tobacco products contain other additives as preservatives, moisteners, and flavors that affect the burn rate, aroma, and rate of nicotine absorption (Goodman, 2005).

Acetylcholine system Nicotine agonizes nicotinic acetylcholine receptors (nAChRs). In the brain, acetylcholine (ACh) is a neuromodulator (i.e., a neurotransmitter that is not directly excitatory or inhibitory) that regulates cerebral blood flow, cortical activity, sleep/wake cycle, cognitive function (learning and memory in particular), and neural plasticity (Schliebs and Arendt, 2006). ACh neurons are found in the pedunculopontine and laterodorsal tegmental areas, the medial habenula, and the basal forebrain, and these neurons project throughout the brain. There are two classes of ACh receptors (AChRs): metabotropic muscarinic receptors and

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ionotropic nicotinic receptors (nAChRs), both of which are located pre- and postsynaptically (Picciotto et al., 2012). nAChRs are ligand-gated ion channels composed of five a and b subunits. The a4b2* (*indicates possible presence of other subunits) is one of the most abundant nAChR subtypes in the human brain and is believed to mediate nicotine addiction (Benowitz, 2009).

Neural effects of nicotine Low doses of nicotine (equivalent to the absorption from 1 cigarette, 0.2e2.4 mg) improve mood, enhance arousal, and can produce a brief, mild euphoric sensation (Kalman, 2002). Moderate doses of nicotine are anxiogenic and cause vomiting, dizziness, abdominal pain, hypertension, and tachycardia (Kim and Baum, 2015). High doses (>50 mg) cause hypotension, bradycardia, dyspnea, loss of consciousness, seizure, coma, and death (Mayer, 2014; Kim and Baum, 2015). Nicotine acutely agonizes nAChRs on dopamine (DA) neurons in the ventral tegmental area and nucleus accumbens, which stimulates DA release in the mesolimbic pathway. Nicotine also indirectly facilitates DA release by enhancing glutamate release (Benowitz, 2009). Nicotine administration releases other neurotransmitters, including ACh, norepinephrine, and gamma-aminobutyric acid (GABA) (Wonnacott, 1997). At nicotine concentrations typical for daily smokers, a4b2* receptors are nearly saturated (Brody et al., 2006) and are likely in a desensitized state (i.e., have a reduced effect). nAChRs return to a sensitized state following overnight abstinence. Chronic daily smoking upregulates nAChRs (Mukhin et al., 2008), thought to be due to the prolonged desensitization, and also downregulates DA receptors in the striatum (Dagher et al., 2001). Nicotine has a half-life of about 2 h (Benowitz et al., 1982), and withdrawal symptoms may begin as little as an hour after the last cigarette. Symptoms include cigarette craving, irritability, anxiety, difficulty concentrating, increased appetite, restlessness, depressed mood, and insomnia (APA, 2013). Withdrawal symptoms peak within the first week of abstinence and last 2e4 weeks (Hughes, 2007), although cigarette cue-induced cravings can continue and even escalate over time (Bedi et al., 2011). Smoking cessation results in readaptations in nAChR; the density of b2 subunit normalizes to nonsmoker levels after 6e12 weeks of abstinence (Cosgrove et al., 2009).

Addiction liability Tobacco has a higher rate of dependence among users than other drugs of abuse (Lopez-Quintero et al., 2011), which appears incongruent with the modest, acute effects of low nicotine doses. An important mediator between initial

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smoking and addiction may be the age of acquisition. Approximately 90% of adult daily smokers initiated use before the age of 18, and nearly all began before the age of 25 (DHHS, 2014). Adolescence is a critical period for brain development and is marked by increased plasticity and rapid growth of neural circuits that underlie social, emotional, and motivational processes. Many of these processes are regulated by the prefrontal cortex, which continues developing into young adulthood, up to 25 years of age. The combination of immature prefrontal cognitive control and increased reactivity of subcortical rewarde related processes may lead to a greater susceptibility to addiction (DHHS, 2016). In fact, symptoms of nicotine dependence can precede daily smoking among adolescents (Gervais et al., 2006). This, in combination with tobacco availability and popularity, may partly account for high rates of tobacco addiction.

Cognitive effects of nicotine and tobacco Short-term effects Nicotine influences a range of cognitive processes, such as reaction time, attention, learning, and memory. nAChRs have a role in encoding new memories; agonists enhance encoding of new information and antagonists produce memory deficits (Felix and Levin, 1997; Prickaerts et al., 2012). However, the effects on memory performance have been demonstrated in rodents more than in humans (Levin et al., 2006). In nonabstinent smokers and nonsmokers, nicotine has primarily been shown to reduce reaction times on tests of attention and memory (Levin et al., 2006; Swan and Lessov-Schlaggar, 2007; Heishman et al., 2010). It is possible that the broad array of nicotine effects on cognition are indirectly due to its effects on attentional performance: nicotine could simply improve the ability to focus attention and maintain task engagement and reduce the influence of distracting irrelevant stimuli (Evans and Drobes, 2009). In addition, nicotine’s effects on cognitive performance may depend on the level of effort required by the task, the individual’s baseline level of performance, or their underlying cholinergic function. Nicotine improves attention in people with poor baseline performance, such as schizophrenia and attention deficit/hyperactivity disorder, which may explain why certain populations with poor attentional performance are at higher risk of tobacco dependence (Evans and Drobes, 2009). Furthermore, genetic variations in ACh and DA receptors could contribute to individual differences in the attentional effects of nicotine (Ahrens et al., 2015). Functional neuroimaging measures how nicotine and tobacco withdrawal affect brain activity. Recent neuroimaging work focuses on the functional organization of the

brain into networks, identified by their synchronous coupling of spontaneous activity fluctuations at rest and when engaged in a cognitive task. This is referred to as “functional connectivity” and represents the efficiency of neural communication within and between brain networks. Three major networks include the executive control network, which is active during cognitive task performance, the default mode network, which is active during rest, and the salience network, which switches between them (Seeley et al., 2007; Buckner et al., 2008; Goulden et al., 2014). Nicotine and nAChR agonists may diminish default mode network activity and/or enhance executive control network activity, thus improving cognition by shifting brain network activity from internally directed to externally directed processes (Sutherland et al. 2012, 2015). For example, in nonsmokers, nicotine suppressed activity in the default mode network and increased activity in the visual attention network (Tanabe et al., 2011).

Long-term effects Long-term tobacco smoke exposure has been associated with cognitive deficits across the life span. Secondhand smoke exposure in children and fetuses produces cognitive deficits later in life (Swan and Lessov-Schlaggar, 2007). For example, tobacco smoke extract (compared with nicotine alone) administered to pregnant rats in doses equivalent to secondhand smoke produced hyperactivity, working memory deficits, and impaired emotional processing in their adolescent and adult offspring (Hall et al., 2016). Smoking during adolescence produces both acute and long-term impairments in cognition and attention, and nicotine exposure in adolescent rats produces long-lasting synaptic changes in prefrontal cortical regions that may underlie cognition and attention (DHHS, 2016). These cognitive deficits may be partly due to smoking-related smaller gray matter volume and lower gray matter density, especially in the prefrontal cortex (Brody et al., 2004; Gallinat et al., 2006; Vnukova et al., 2017). Smoking is also associated with cognitive deficits and decline in late life, and it may increase the risk of neurodegeneration in Alzheimer’s disease or other dementias possibly via oxidative stress, inflammation, or atherosclerosis (Swan and LessovSchlaggar, 2007).

Withdrawal effects Nicotine withdrawal impairs response inhibition, attention, reaction time, and working memory (McClernon et al., 2015). Although, the most consistent effects of overnight smoking abstinence are on subjective withdrawal symptoms such as craving, negative mood, self-reported difficulty concentrating, and increased hunger. Abstinence

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effects on cognitive performance are generally of a smaller magnitude but reliably show deficits such as slower reaction times (Leventhal et al., 2010). Neuroimaging studies suggest that these cognitive deficits relate to dysfunction in frontal cortical areas (McClernon et al., 2015). One of the most consistent effects of withdrawal is on diminished sustained attention, which may indirectly contribute to other cognitive deficits (Evans and Drobes, 2009). Smoking, or nicotine administration, can improve these deficits in withdrawn smokers. For example, nicotine improved cued spatial attentional orienting among withdrawn smokers who had slower reaction time (RT)s at baseline; which supports the idea of baseline performance dependency of nicotine’s attentional effects (Hammersley et al., 2016). In another study, individual differences in cognitive withdrawal symptom improvement during nicotine replacement were associated with inverse coupling between the executive control network and the default mode network (Cole et al., 2010). This suggests that the therapeutic effects of nicotine replacement are related to modulation of brain processes involved in cognitive control. Cognitive improvement may be a form of smoking reinforcement, especially when it reverses the effects of withdrawal. Although there is some quantitative evidence for improvements in cognition, nicotine could indirectly influence cognitive performance by improving mood and the motivation to maintain attention and exert cognitive effort. This may be a small improvement above smokers’ baseline function or a return to baseline during withdrawal (Evans and Drobes, 2009).

Nicotine reinforcement Reinforcement enhancement Nicotine is a weak primary reinforcer compared with other drugs of abuse. Rats that have been trained to selfadminister cocaine will work harder for the drug as the schedule of reinforcement becomes more challenging (Richardson and Roberts, 1996), but rats tend to not work harder for nicotine (Rupprecht et al., 2015). Nicotine alone does support modest levels of rat self-administration, but nicotine self-administration is facilitated by having a paired sensory stimulus cue, such as a sound or light, even if the stimulus itself has little to no reinforcing value on its own (Sorge et al., 2009). Interestingly, pairing nicotine with another weak, unconditioned reinforcer produces a synergistic effect on motivation to obtain both (Donny et al., 2003). This synergy is referred to as “reinforcement enhancement” (Caggiula et al., 2009), and this may be a critical mechanism for understanding the discrepancy between the modest abuse liability of nicotine and the tenacity

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of tobacco addiction. There are a couple different hypotheses about how this mechanism works: (1) Nicotine may be enhancing the reinforcement strength of other primary reinforcers or amplifying their incentive salience (Chaudhri et al., 2006; Rupprecht et al., 2015). Specifically, rats’ response rates to obtain both a nondrug reinforcer and nicotine are twice the response rate produced for either reinforcer alone (Donny et al., 2003). This couse of nicotine and other reinforcers appears to parallel some human behavior, such as nondaily smokers using tobacco while socializing, attending parties, and/or drinking alcohol (Nguyen and Zhu, 2009; Shiffman et al., 2009). Another example is that taking a break from school/work to relax and socialize with friends/coworkers can elicit tobacco cravings if frequently paired with smoking (i.e., a “smoke break”). The repeated pairing of smoking with other reinforcers may be an important phase in the transition from initial use to tobacco addiction. (2) Neutral stimuli consistently paired with nicotine may become conditioned stimuli that develop their own secondary reinforcing properties (Palmatier et al., 2007). For example, when initially experienced, the sensorimotor aspects of smoking (e.g., sight, smell, flavor, throat sensation, and hand to mouth motion) may be subjectively aversive, but over time, these aspects can become reinforcing on their own. In fact, replacing smokers’ cigarettes with denicotinized cigarettes will maintain smoking behavior (Donny and Jones, 2009). Outside the laboratory, the subjective effects of nicotine may play a role in the initial use and acquisition of smoking, but over time, tobacco use becomes associated with contextual cues, such as one’s mood and surrounding environment, in addition to the nonnicotine sensorimotor aspects of smoking. Habitual cigarette smoking is maintained by this conditioning, as many smokers reach for a cigarette while driving their car, with a cup of coffee or glass of beer. Likewise, withdrawal symptoms such as irritability and anxiety can be alleviated by smoking a cigarette, thus smokers can become conditioned to regard stress and frustration derived from any source as a cue for smoking (Benowitz, 2009).

Neural mechanisms Although classical conditioning paradigms based on animal models may not be fully reproducible in humans because of the amount of time involved, neuroimaging studies can provide insights into neural mechanisms of how nicotine interacts with nondrug reinforcers (usually money) in the absence of behavioral effects.

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An important concept in reinforcement learning is prediction errordthe difference between the cue-predicted outcome and the actual outcome (i.e., what was expected vs. what was received). Prediction errors may serve to alert and orient the individual’s attention to the discrepancy. The orienting of attention can then drive additional learning and memory about the cueeoutcome relationship, ultimately helping the individual adapt its behavior to changes in the environment. DA signaling in the mesolimbic pathway appears to code prediction errors. There is a phasic DA signal following unexpected natural rewards, and this signal shifts to a predictive cue after classical conditioning (Schultz and Dickinson, 2000). Nicotine helps boost DA transmission and could potentially enhance DA signaling of prediction errors, thereby amplifying the saliency of reward cues or outcomes, or improve attention, learning, and memory for these events. Perhaps by strengthening the cueeoutcome relationship, nicotine enhances learning and memory for its own use. Conversely, if withdrawal dampens prediction errors, perhaps this is related to anhedonic effects of withdrawal (i.e., loss of interest in alternative reinforcers). Alternatively, nicotine and tobacco withdrawal may affect tonic DA tone or both tonic and phasic signaling (Zhang et al., 2012). There have been a few neuroimaging studies on how nicotine/smoking affects prediction error signaling during classical conditioning, although results have been mixed. Compared with nonsmokers, smokers had reduced prediction error signaling in the striatum and medial prefrontal cortex, which was related to the duration of smoking in years (Rose et al., 2012). Although these smokers were not withdrawn, this may inform the anhedonic consequences of smoking cessation. In nonsmokers, both unexpected outcomes and acute nicotine increased activation in the anterior insula, which is part of the salience network, and may subserve how nicotine amplifies the salience of nondrug reinforcers (Addicott et al., 2017). Another study reported that smoking withdrawal decreased the signal associated with phasic DA signals across both expected and unexpected outcomes, suggesting that changes in phasic DA are unlikely contributing to reward processing deficits (Oliver et al., 2016). An interesting twist in this line of research is the influence of drug expectations. Smokers who believed they were smoking nicotine-free cigarettes had less neural responses in the striatum to reward prediction errors, compared with when they were told they were smoking nicotine cigarettes. These effects were not observed in other brain regions activated by the task. This suggests that beliefs about the presence of a neuroactive substance such as nicotine can override its physical presence. Evidently, drug expectation is an important cognitive mechanism in addiction (Gu et al., 2015). A related type of neuroimaging paradigm used to understand the function of the mesolimbic DA pathway uses

an anticipatory money-reward cue phase, followed by a feedback phase indicating whether any money was won on that trial based on the individual’s performance. This type of paradigm typically elicits activation in the striatum and prefrontal cortex as well as other regions (e.g., Knutson et al., 2001) and has been used in a number of studies to investigate the acute and chronic effects of nicotine and tobacco. This research tends to show that nicotine increases activation to anticipatory cues (Fedota et al., 2015; Moran et al., 2018) and reward feedback (Addicott et al., 2019) (although one study reported acute nicotine reduced anticipatory activation in satiated smokers) (Rose et al., 2013), and smoking withdrawal reduces activation to reward feedback (Sweitzer et al., 2014; Addicott et al., 2019). However, smokers’ anticipation-related activation for cigarette reward is greater than for money reward during withdrawal (Sweitzer et al., 2014). This could account for the withdrawal-induced bias toward anticipation of smoking rewards at the expense of other, nondrug rewards, which motivates smoking behavior and interferes with cessation success.

The emotionesmoking relationship Smoking as a maladaptive response to negative mood Tobacco addiction disproportionately affects individuals with mood disorders. Compared with never smokers, smokers are 1.85 times more likely to have depression, 1.71 times more likely to have anxiety, and 1.69 times more likely to experience psychological distress (Taylor et al., 2014a). Nicotine and other nAChR agonists have antidepressant effects (Gandelman et al., 2018), and smoking could potentially mitigate symptoms of depression while nicotine withdrawal exacerbates them. A smoker’s propensity to relieve stress and negative mood by smoking parsimoniously explains emotion-smoking comorbidity (Leventhal and Zvolensky, 2015). Several important concepts related to the emotione smoking relationship are anhedonia, anxiety sensitivity, and distress tolerance. Anhedonia is the loss of an ability to feel pleasure and may be a symptom of tobacco withdrawal (Cook et al., 2017). High levels of anhedonia have been negatively associated with smokers’ time to relapse (Cook et al., 2010). Anxiety sensitivity is the belief that symptoms of anxiety are intolerable or have harmful consequences, and it is related to more severe nicotine withdrawal symptoms (Zvolensky et al., 2004). During a quit attempt, smokers with high anxiety sensitivity had a greater risk of smoking on days when they experienced increased negative affect (Langdon et al., 2016). Distress tolerance is the ability to pursue a goal (e.g., smoking cessation) in spite of physical or psychological distress (e.g., withdrawal

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symptoms or cigarette craving). Laboratory-based behavioral measures of distress tolerance have been positively associated with smokers’ time to lapse/relapse (Brown et al., 2009; Kahler et al., 2013), and low distress tolerance may be related to diminished top-down cognitive control of behavior during stress (Daughters et al., 2016). Leventhal and Zvolensky wrote a comprehensive review and analysis of research linking anhedonia, anxiety sensitivity, and distress tolerance to smoking behaviors, including the initiation of smoking, progression to regular smoking, tobacco addiction/dependence, cessation, and lapse/relapse. To summarize, smoking is particularly reinforcing for individuals with poor emotional regulation because smoking can enhance positive affect, relieve anxiety, and terminate distress. Individuals with anhedonia, anxiety sensitivity, and low distress tolerance may be hypermotivated to react to emotional disturbance with smoking behavior. They may also be more sensitive to the effects of smoking on affective state. Likewise, these three emotional vulnerabilities amplify the effects of tobacco withdrawal on loss of reward, anxiogenesis, and distress exacerbation (Leventhal and Zvolensky, 2015).

Neural mechanisms Common to many mental illnesses, including addictions, is an increased sensitivity to stress or elevated stress levels (Esch et al., 2002). Across different drug addictions, stress often provokes craving and relapse (Mantsch et al., 2016), and chronic stress is an important trigger for relapse during a smoking cessation attempt (McKee et al., 2003). In fact, acute stress, which can reinstate extinguished drug-seeking behavior, is an animal model for relapse (Shaham et al., 2003). Several different neural mechanisms may underlie the stressesmoking relationship. To begin with, cholinergic signaling in the hippocampus, amygdala, prefrontal cortex, and striatum modulates behavioral responses to stressors (Higley and Picciotto, 2014). In addition, stress-related drug-taking behaviors are associated with amygdala function (Sharp, 2017), and noradrenergic and cholinergic signaling in the amygdala regulate anxiety- and depressionrelated behaviors (Mineur et al., 2018). Another neural mechanism is the extrahypothalamic corticotropine releasing factor receptor system, which elicits anxietyrelated behaviors and is thought to be related to negative mood states associated with withdrawal from nicotine or other drugs (George et al., 2007). This system is also implicated in stress-induced reinstatement of nicotineseeking behavior (Zislis et al., 2007). Lastly, the medial habenulaeinterpeduncular axis has a high density of nAChRs, and accumulating evidence suggests that this axis relates to fear/anxiety-related responses. Animal studies have shown nicotine withdrawal increases glutamatergic

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signaling in the interpeduncular nucleus, and overactivation of neurons in the interpeduncular nucleus intermediate subregion may be responsible for anxiogenic effects of withdrawal (Molas et al., 2017).

The role of the insular cortex The insular cortex, folded deeply within the lateral sulcus, plays a special role in the emotionesmoking relationship. The insula is integral to interoception (i.e., the conscious awareness of the internal state of one’s body) and its subjective emotional interpretation (Craig, 2009). The insula is also connected to cognitive control brain regions that subserve goal-directed behavior (Nelson et al., 2010; Chang et al., 2013). This is highly relevant to addiction because the insula may link the physical and emotional awareness of drug withdrawal and cravings to volitional drug-taking behavior (e.g., smoking a cigarette in response to craving) (Garavan, 2010; Naqvi et al., 2014). A landmark study reported that smokers with strokeinduced insula lesions were more likely to quit smoking easily, notably with a sudden loss of the urge to smoke or “disruption of smoking addiction” (Naqvi et al., 2007). Although this retrospective study was limited by potentially inaccurate recollection of smokers’ behavior, several prospective studies have reported similar results. One study found that smokers with insula lesions were more likely to have quit smoking 1-year poststroke and had less difficulty quitting (Suner-Soler et al., 2012), although a follow-up investigation showed insula lesions no longer predicted abstinence at 6-years poststroke (Suner-Soler et al., 2018). Other prospective studies have shown that strokes affecting the basal ganglia, and the basal ganglia and the insula, were more likely to result in smoking cessation at 12-months poststroke (Gaznick et al., 2014), and smokers with insula lesions had less withdrawal symptom severity during hospitalization (Abdolahi et al., 2015). With one exception (Bienkowski et al., 2010) these studies support the role of the insula in tobacco addiction. Neuroimaging studies of neurologically intact smokers also support a role for the insula. At rest, smokers have weaker functional connectivity between the insula and other brain regions than nonsmokers (Bi et al., 2017; Zhou et al., 2017). Weaker insula connectivity among smokers has also been associated with an increased likelihood of lapse and relapse (Janes et al., 2010; Addicott et al., 2015; Zelle et al., 2017). Alternatively, while viewing cigaretterelated images, stronger insula connectivity was associated with the magnitude of smokers’ craving (Maria et al., 2015) and with increased pleasantness ratings for smoking images during withdrawal (Avery et al., 2017). Although an insula lesion may lessen the interoceptive awareness of withdrawal or cravings, in an intact brain, the insula coordinates with other brain regions to respond, or inhibit a

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response, to cravings according to one’s goal to smoke or remain abstinent. Thus, both stronger and weaker connectivity between the insula and other brain regions can support tobacco addiction or smoking cessation.

Cause, consequence, or shared underlying mechanism Is smoking a cause or consequence of mood disorders? The “self-medication” hypothesis postulates that symptoms of mood disorders precede smoking and smoking helps alleviate these symptoms, suggesting that tobacco addiction is a consequence of these disorders. Smoking may provide temporary relief of negative mood symptoms and improve arousal and motivation, while nicotine withdrawal could exacerbate negative mood symptoms and interfere with tobacco cessation efforts. As smokers learn to modulate their mood with tobacco, they may lose the ability to engage alternative coping mechanisms, thus becoming more and more dependent on smoking to provide stress relief. Alternatively, smoking may increase the risk of depression or anxiety. Chronic nicotine dysregulates the hypothalamicepituitaryeadrenal axis, which leads to hypersecretion of cortisol and changes in associated monoamine neurotransmitters (Markou et al., 1998). Ultimately, this can change the response to stress and exacerbate symptoms of depression and anxiety over time, suggesting that tobacco addiction can cause mood disorders. However, recent genetic research does not suggest a causal role for smoking heaviness in the development of depression and anxiety (Taylor et al., 2014a; Skov-Ettrup et al., 2017). A review of longitudinal studies reported that about 50% of studies provided evidence that smoking was a consequence of depression or anxiety, and about 33% of studies provided evidence that smoking caused depression and anxiety. However, there was substantial heterogeneity across studies in populations, design, and diagnostic measures (Fluharty et al., 2017). It is also possible that smoking and mood disorders have a shared etiology or develop in conjunction with one another. There may be shared genetic vulnerability, or early life stress may precipitate the onset and progression of both.

Smoking cessation and mood Despite the interaction between smoking and mood, smokers with mental illness desire to quit smoking similar to smokers in the general population (Prochaska et al., 2017). However, their actual rates of smoking cessation are lower (RCP, 2013). This could be due to an exacerbation of mood symptoms during withdrawal. Among smokers with mood disorders, anxiety and depression may initially worsen during a quit attempt, especially if the quit attempt

failed (Berlin et al., 2010). However, another study reported that successful quitters did not show significant changes in depression or anxiety over a 1-month period, nor did quitting contribute to adverse mental health outcomes (Capron et al., 2014). Ultimately, long-term cessation is associated with improvements in depression, anxiety, stress, and mood, both in the general population and clinical populations. This is perhaps due to breaking the cycle of recurring withdrawal symptoms. Effect sizes on the improvements in mood due to smoking cessation are equal or larger than those of antidepressant treatment for mood and anxiety disorders (Taylor et al., 2014b). Long-term cessation may even lead to a reduced incidence of depression (Shahab et al., 2014; Bakhshaie et al., 2015). Potentially, quitting smoking improves mental health, or improving mental health assists cessation, or there is a common underlying factor. However, existing studies cannot determine causality (Taylor et al., 2014b). Smokers with mood disorders and other mental illnesses face additional barriers to smoking cessation. The most commonly cited barriers are the management of mental illness symptoms (i.e., smoking to improve attention/ cognition/motivation, reduce negative affect, cope with stress) and social barriers (i.e., smoking is a way to fit in, smoking with peers) (Trainor and Leavey, 2017). The efficacy of pharmacotherapy is similar between smokers with and without mental illness (West et al., 2018), but the high rates of smoking suggest that tobacco cessation programs designed for the general population are poorly integrated, less effective, or not addressing the additional barriers faced by individuals with mental illness (Cook et al., 2014). Research is needed on the development and implementation of effective cessation interventions for this group (Metse et al., 2017).

Recommendations for clinicians and researchers Given its broad range of negative health effects, clinicians in all fields of medicine should discuss tobacco use with their patients, especially e-cig use with adolescent patients. Unfortunately, many clinicians and health-care systems do not treat tobacco use consistently and effectively (Fiore et al., 2008b), possibly because clinicians lack training in tobacco intervention strategies, or health-care systems lack policies for routine tobacco screening and intervention. However, many resources are available to help guide discussions about patients’ smoking (e.g., Fiore et al., 2008a). Additionally, the National Institutes of Health provides a free toolbox (nihtoolbox.org) of standardized measures of smoking and tobacco use, such as emotional and health expectations for smoking, motivations for smoking, and

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nicotine dependence severity. These measures can help improve communication between clinicians and patients. The research reviewed in this chapter brings together the cognitive, affective, and reinforcing effects of nicotine and tobacco. There is an ongoing need for smoking cessation therapies that target where and how these three areas overlap. In particular, we need cessation interventions tailored to specific populations, such as people with schizophrenia, depression, type II diabetes, or substance use disorders. Each group has its own set of challenges and standard of care. Smoking cessation interventions should be custom fit for each population. As described in this chapter, smoking has a high rate of comorbidity with other psychiatric disorders, especially substance use disorders. If a patient is undergoing treatment for a serious substance use disorder, his/her smoking may not be considered a priority. However, evidence suggests that smoking can act synergistically with other drugs of abuse, and treatment for tobacco dependence does not interfere with treatment for other substance use disorders (e.g., alcoholism) (Kalman et al., 2010). Clinicians should consider providing concurrent treatment for tobacco and other substance use disorders. Importantly, research should investigate if quitting smoking improves overall well-being and therapeutic outcomes for other physical and mental health problems.

Summary and conclusions In summary, tobacco remains a widely used drug. Although cigarettes are the most commonly used form of tobacco, ecig use is on the rise. The popularity of e-cigs among adolescents and young adults is especially troubling because the risk of developing nicotine addiction and then transitioning to cigarette usage could undermine the decline in smoking rates. Now that the FDA has the power to regulate tobacco, additional policies could be implemented to reduce nicotine content and flavorants in tobacco and e-cigs to help prevent such a reversal. While smoking rates have generally been in decline, certain populations, such as those with mental illness, have persistently high rates of smoking. One explanation for this is the relationship between smoking and mood regulation. Many smokers, especially those experiencing anhedonia and anxiety, smoke to relieve negative mood and stress. Withdrawal symptoms can exacerbate negative moods and create an additional barrier to cessation. Evidence suggests that quitting smoking can improve mood in the long term, but additional research is needed to improve the efficacy of smoking cessation treatments for individuals with mental illness and affective distress. There may be some overlap in the effects of nicotine and tobacco on mood and on cognitive performance. As mood is improved by smoking, there may be increased motivation to concentrate and perform well. Nicotine

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improves attention, especially in populations with poor baseline performance characteristic of some mental illnesses. Neuroimaging studies suggest that these cognitive effects may relate to enhancement of the executive control network (engaged by externally driven processes, e.g., a cognitive task), suppression of the default mode network (engaged by internally driven processes, e.g., while daydreaming), or a combination of both. Likewise, tobacco withdrawal may change the relationship between these two networks. If true, future research in this area ought to investigate how these networks can be manipulated to support tobacco cessation, via pharmacological or nonpharmacological (e.g., neurofeedback, transcranial magnetic stimulation) methods. It is difficult to understand why tobacco is so highly addictive, given its modest acute effects. The extent of classical conditioning (i.e., the number of times cigarette smoking is paired with another stimulus or experience) and the age of initiation play critical roles in the transition from occasional to daily smoking. Nicotine appears to enhance the motivation for other reinforcers as well, which is evident in the amount of effort expended to obtain other reinforcers when nicotine is physiologically present and in DA-rich mesolimbic brain activation when anticipating or receiving other reinforcers. Research in this area is important to understanding withdrawal-related anhedonia and the loss of motivation for nondrug rewards. As the smoking rates in the general population decline, there may be less concern or funding for tobacco addiction research. This may leave many vulnerable populations understudied and underserved. As tobacco addiction is a pervasive disease that interacts with and exacerbates other physical and mental illnesses, treatment for tobacco addiction should be an integral part of primary care medicine.

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