Multi-level prediction of substance use: Interaction of white matter integrity, resting-state connectivity and inhibitory control measured repeatedly in every-day life.

Substance use disorders are characterized by inhibition deficits related to disrupted connectivity in white matter pathways, leading via interaction to difficulties in resisting substance use. By combining neuroimaging with smartphone-based ecological momentary assessment (EMA), we questioned how biomarkers moderate inhibition deficits to predict use. Thus, we aimed to assess white matter integrity interaction with everyday inhibition deficits and related resting-state network connectivity to identify multi-dimensional predictors of substance use. Thirty-eight patients treated for alcohol, cannabis or tobacco use disorder completed 1 week of EMA to report substance use five times and complete Stroop inhibition testing twice daily. Before EMA tracking, participants underwent resting state functional MRI and diffusion tensor imaging (DTI) scanning. Regression analyses were conducted between mean Stroop performances and whole-brain fractional anisotropy (FA) in white matter. Moderation testing was conducted between mean FA within significant clusters as moderator and the link between momentary Stroop performance and use as outcome. Predictions between FA and resting-state connectivity strength in known inhibition-related networks were assessed using mixed modelling. Higher FA values in the anterior corpus callosum and bilateral anterior corona radiata predicted higher mean Stroop performance during the EMA week and stronger functional connectivity in occipital-frontal-cerebellar regions. Integrity in these regions moderated the link between inhibitory control and substance use, whereby stronger inhibition was predictive of the lowest probability of use for the highest FA values. In conclusion, compromised white matter structural integrity in anterior brain systems appears to underlie impairment in inhibitory control functional networks and compromised ability to refrain from substance use.

Is impulsivity related to attentional bias in cigarette smokers? An exploration across levels of nicotine dependency and deprivation.

Research has largely focused on how attentional bias to smoking-related cues and impulsivity independently influence the development and maintenance of cigarette smoking, with limited exploration of the relationship between these mechanisms. The current experiments systematically assessed relationships between multiple dimensions of impulsivity and attentional bias, at different stages of attention, in smokers varying in nicotine dependency and deprivation. Nonsmokers (NS; n  = 26), light-satiated smokers (LS; n  = 25), heavy-satiated smokers (HS; n  = 23) and heavy 12-hour nicotine-deprived smokers (HD; n  = 30) completed the Barratt Impulsivity Scale, delayed discounting task, stop-signal task, information sampling task and a visual dot-probe assessing initial orientation (200 ms) and sustained attention (2000 ms) toward smoking-related cues. Sustained attention to smoking-related cues was present in both HS and LS, while initial orientation bias was only evident in HS. HS and LS also had greater levels of trait motor and nonplanning impulsivity and heightened impulsive choice on the delay discounting task compared with NS, while heightened trait attentional impulsivity was only found in HS. In contrast, in HD, nicotine withdrawal was associated with no attentional bias but heightened reflection impulsivity, poorer inhibitory control and significantly lower levels of impulsive choice relative to satiated smokers. Trait and behavioral impulsivity were not related to the extent of attentional bias to smoking-related cues at any stage of attention, level of nicotine dependency or state of deprivation. Findings have both clinical and theoretical implications, highlighting the unique and independent roles impulsivity and attentional bias may play at different stages of the nicotine addiction cycle.

Combining neuroimaging and brain stimulation to test alternative causal pathways for nicotine addiction in schizophrenia.

The smoking rate is high in patients with schizophrenia. Brain stimulation targeting conventional brain circuits associated with nicotine addiction has also yielded mixed results. We aimed to identify alternative circuitries associated with nicotine addiction in both the general population and schizophrenia, and then test whether modulation of such circuitries may alter nicotine addiction behaviors in schizophrenia. In Study I of 40 schizophrenia smokers and 51 non-psychiatric smokers, cross-sectional neuroimaging analysis identified resting state functional connectivity (rsFC) between the dorsomedial prefrontal cortex (dmPFC) and multiple extended amygdala regions to be most robustly associated with nicotine addiction severity in healthy controls and schizophrenia patients (p = 0.006 to 0.07). In Study II with another 30 patient smokers, a proof-of-concept, patient- and rater-blind, randomized, sham-controlled rTMS design was used to test whether targeting the newly identified dmPFC location may causally enhance the rsFC and reduce nicotine addiction in schizophrenia. Although significant interactions were not observed, exploratory analyses showed that this dmPFC-extended amygdala rsFC was enhanced by 4-week active 10Hz rTMS (p = 0.05) compared to baseline; the severity of nicotine addiction showed trends of reduction after 3 and 4 weeks (p ≤ 0.05) of active rTMS compared to sham; Increased rsFC by active rTMS predicted reduction of cigarettes/day (R = -0.56, p = 0.025 uncorrected) and morning smoking severity (R = -0.59, p = 0.016 uncorrected). These results suggest that the dmPFC-extended amygdala circuit may be linked to nicotine addiction in schizophrenia and healthy individuals, and future efforts targeting its underlying pathophysiological mechanisms may yield more effective treatment for nicotine addiction.

Data-driven connectivity profiles relate to smoking cessation outcomes.

At a group level, nicotine dependence is linked to differences in resting-state functional connectivity (rs-FC) within and between three large-scale brain networks: the salience network (SN), default mode network (DMN), and frontoparietal network (FPN). Yet, individuals may display distinct patterns of rs-FC that impact treatment outcomes. This study used a data-driven approach, Group Iterative Multiple Model Estimation (GIMME), to characterize shared and person-specific rs-FC features linked with clinically-relevant treatment outcomes. 49 nicotine-dependent adults completed a resting-state fMRI scan prior to a two-week smoking cessation attempt. We used GIMME to identify group, subgroup, and individual-level networks of SN, DMN, and FPN connectivity. Regression models assessed whether within- and between-network connectivity of individual rs-FC models was associated with baseline cue-induced craving, and craving and use of regular cigarettes (i.e., "slips") during cessation. As a group, participants displayed shared patterns of connectivity within all three networks, and connectivity between the SN-FPN and DMN-SN. However, there was substantial heterogeneity across individuals. Individuals with greater within-network SN connectivity experienced more slips during treatment, while individuals with greater DMN-FPN connectivity experienced fewer slips. Individuals with more anticorrelated DMN-SN connectivity reported lower craving during treatment, while SN-FPN connectivity was linked to higher craving. In conclusion, in nicotine-dependent adults, GIMME identified substantial heterogeneity within and between the large-scale brain networks. Individuals with greater SN connectivity may be at increased risk for relapse during treatment, while a greater positive DMN-FPN and negative DMN-SN connectivity may be protective for individuals during smoking cessation treatment.

Functional connectivity during feedback learning in smokers.

BACKGROUND: Although it has been traditionally assumed that dysregulation of psychological processes in smokers results from activity within specific brain regions, an emerging view regards such dysregulation as attributable to aberrant communication between distinct brain regions. These processes can be measured during appropriate task paradigms such as the learning from errors task. This study aims to elucidate interactions between brain regions underlying the process of learning from errors, punishment and sensitivity to reward in dependent smokers. METHODS: Functional MRI data from 23 age-matched dependent smokers (8 females, mean age = 25.48, SD = 4.46) and 23 controls (13 females, mean age = 24.83, SD = 5.99) were analysed during a feedback-based associative learning task. Functional connectivity between the dorsal anterior cingulate cortex, nucleus accumbens and reward/sensorimotor areas was investigated during a feedback learning task. RESULTS: Behaviourally, smokers exhibited lower error correction rates and were less sensitive to punishment magnitude. Smokers showed increased functional connectivity between dorsal anterior cingulate cortex/nucleus accumbens seed regions and numerous reward-related target regions including the putamen, anterior cingulate and orbitofrontal cortex. CONCLUSIONS: Reduced learning from errors and widespread aberrant functional connectivity contribute to the emerging functional characterisation of dependent smokers and may bear significant implications when considering the efficacy of smoking interventions.

Disentangling craving- and valence-related brain responses to smoking cues in individuals with nicotine use disorder.

Tobacco smoking is one of the leading causes of preventable death and disease worldwide. Most smokers want to quit, but relapse rates are high. To improve current smoking cessation treatments, a better understanding of the underlying mechanisms of nicotine dependence and related craving behaviour is needed. Studies on cue-driven cigarette craving have been a particularly useful tool for investigating the neural mechanisms of drug craving. Here, functional neuroimaging studies in humans have identified a core network of craving-related brain responses to smoking cues that comprises of amygdala, anterior cingulate cortex, orbitofrontal cortex, posterior cingulate cortex and ventral striatum. However, most functional Magnetic Resonance Imaging (fMRI) cue-reactivity studies do not adjust their stimuli for emotional valence, a factor assumed to confound craving-related brain responses to smoking cues. Here, we investigated the influence of emotional valence on key addiction brain areas by disentangling craving- and valence-related brain responses with parametric modulators in 32 smokers. For one of the suggested key regions for addiction, the amygdala, we observed significantly stronger brain responses to the valence aspect of the presented images than to the craving aspect. Our results emphasize the need for carefully selecting stimulus material for cue-reactivity paradigms, in particular with respect to emotional valence. Further, they can help designing future research on teasing apart the diverse psychological dimensions that comprise nicotine dependence and, therefore, can lead to a more precise mapping of craving-associated brain areas, an important step towards more tailored smoking cessation treatments.

The impact of adolescent nicotine exposure on alcohol use during adulthood: The role of neuropeptides.

Nicotine and alcohol abuse and co-dependence represent major public health crises. Indeed, previous research has shown that the prevalence of alcoholism is higher in smokers than in non-smokers. Adolescence is a susceptible period of life for the initiation of nicotine and alcohol use and the development of nicotine-alcohol codependence. However, there is a limited number of pharmacotherapeutic agents to treat addiction to nicotine or alcohol alone. Notably, there is no effective medication to treat this comorbid disorder. This chapter aims to review the early nicotine use and its impact on subsequent alcohol abuse during adolescence and adulthood as well as the role of neuropeptides in this comorbid disorder. The preclinical and clinical findings discussed in this chapter will advance our understanding of this comorbid disorder's neurobiology and lay a foundation for developing novel pharmacotherapies to treat nicotine and alcohol codependence.

Conceptual model for the evaluation of attractiveness, addictiveness and toxicity of tobacco and related products: The example of JUUL e-cigarettes.

Many new tobacco and related products (nTRP) have emerged on the market, with unknown health risks. Here, we present a conceptual model containing the factors and relations between them that contribute to the nTRP's health effects. Factors that determine attractiveness, addictiveness and toxicity of nTRP were defined based on previous assessments, literature, and expert discussions. Our model will aid in identifying key risk factors contributing to increased risk of adverse health effects for a product in a qualitative manner. Additionally, it can gauge attractiveness for specific user groups, as a determinant for population prevalence of use. Our model can be used to identify aspects of nTRP that require attention for public information or product regulation. As an example, we applied this to JUUL, a popular e-cigarette in the US. Aspects of concern for JUUL are its attractive and discrete shape, user-friendly prefilled pods, flavors, high aerosol nicotine levels, and liquids containing nicotine salts instead of free-based nicotine. The addictiveness and especially attractiveness are sufficiently high to have a large potential impact on population health due to its contribution to use and hence exposure. Products and their use can change over time; therefore market research and monitoring are crucial.

Mixed-effects multilevel analysis followed by canonical correlation analysis is an effective fMRI tool for the investigation of idiosyncrasies.

We report that regions-of-interest (ROIs) associated with idiosyncratic individual behavior can be identified from functional magnetic resonance imaging (fMRI) data using statistical approaches that explicitly model individual variability in neuronal activations, such as mixed-effects multilevel analysis (MEMA). We also show that the relationship between neuronal activation in fMRI and behavioral data can be modeled using canonical correlation analysis (CCA). A real-world dataset for the neuronal response to nicotine use was acquired using a custom-made MRI-compatible apparatus for the smoking of electronic cigarettes (e-cigarettes). Nineteen participants smoked e-cigarettes in an MRI scanner using the apparatus with two experimental conditions: e-cigarettes with nicotine (ECIG) and sham e-cigarettes without nicotine (SCIG) and subjective ratings were collected. The right insula was identified in the ECIG condition from the χ2 -test of the MEMA but not from the t-test, and the corresponding activations were significantly associated with the similarity scores (r = -.52, p = .041, confidence interval [CI] = [-0.78, -0.17]) and the urge-to-smoke scores (r = .73, p <.001, CI = [0.52, 0.88]). From the contrast between the two conditions (i.e., ECIG > SCIG), the right orbitofrontal cortex was identified from the χ2 -tests, and the corresponding neuronal activations showed a statistically meaningful association with similarity (r = -.58, p = .01, CI = [-0.84, -0.17]) and the urge to smoke (r = .34, p = .15, CI = [0.09, 0.56]). The validity of our analysis pipeline (i.e., MEMA followed by CCA) was further evaluated using the fMRI and behavioral data acquired from the working memory and gambling tasks available from the Human Connectome Project.

Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population.

Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to evaluate the DNA methylation level of cg05575921 (AHRR) and cg23771366 (PRSS23) and their correlation with lung function variables, cigarette consumption, and nicotine addiction in the Mexican smoking population. We included 114 non-smokers (NS) and 102 current tobacco smokers (TS); we then further subclassified them as heavy smokers (HS) (n = 53) and light smokers (LS) (n = 49). We used restriction enzymes (MspI/HpaII) and qPCR to determine the DNA methylation level. We observed significant hypomethylation of cg05575921 in smokers compared to NS (p = 0.003); further analysis found a difference between HS and NS (p = 0.02). We did not observe differences between other groups or a positive correlation between methylation levels and age, BMI, cigarette consumption, nicotine addiction, or lung function. In conclusion, the cg05575921 site of AHRR is significantly hypomethylated in Mexican smokers, especially in HS (≥20 cigarettes per day).

Clinical Pharmacology of Electronic Nicotine Delivery Systems (ENDS): Implications for Benefits and Risks in the Promotion of the Combusted Tobacco Endgame.

Electronic nicotine delivery systems (ENDS) such as e-cigarettes and heated tobacco products are novel battery-operated devices that deliver nicotine without combustion of tobacco. Because cigarette smoking is sustained by nicotine addiction and the toxic combustion products are mainly responsible for the harmful effects of smoking, ENDS could be used to promote smoking cessation while exposing users to lower levels of toxicants compared with conventional cigarettes. The currently available evidence from clinical and observational studies indicates a potential role of e-cigarettes as smoking cessation aids, although many continue to use e-cigarettes long after quitting smoking. Nicotine and toxicant delivery vary considerably by device and depend on the characteristics of the e-liquid formulation. Because smokers tend to titrate their nicotine intake to maintain their desired pharmacologic effects, device and liquid characteristics need to be considered when using ENDS as an aid to quit smoking. Factors potentially limiting their use are the currently still unknown long-term safety of these products and concerns regarding widespread use among youth. Implications of clinical pharmacology data on ENDS for the cigarette endgame and regulation by the U.S. Food and Drug administration are discussed.

A reexamination of motor and prefrontal TMS in tobacco use disorder: Time for personalized dosing based on electric field modeling?

OBJECTIVE: In this study, we reexamined the use of 120% resting motor threshold (rMT) dosing for transcranial magnetic stimulation (TMS) over the left dorsolateral prefrontal cortex (DLPFC) using electric field modeling. METHODS: We computed electric field models in 38 tobacco use disorder (TUD) participants to compare figure-8 coil induced electric fields at 100% rMT over the primary motor cortex (M1), and 100% and 120% rMT over the DLPFC. We then calculated the percentage of rMT needed for motor-equivalent induced electric fields at the DLPFC and modeled this intensity for each person. RESULTS: Electric fields from 100% rMT stimulation over M1 were significantly larger than what was modeled in the DLPFC using 100% rMT (p < 0.001) and 120% rMT stimulation (p = 0.013). On average, TMS would need to be delivered at 133.5% rMT (range = 79.9 to 247.5%) to produce motor-equivalent induced electric fields at the DLPFC of 158.2 V/m. CONCLUSIONS: TMS would have to be applied at an average of 133.5% rMT over the left DLPFC to produce equivalent electric fields to 100% rMT stimulation over M1 in these 38 TUD patients. The high interindividual variability between motor and prefrontal electric fields for each participant supports using personalized electric field modeling for TMS dosing to ensure that each participant is not under- or over-stimulated. SIGNIFICANCE: These electric field modeling in TUD data suggest that 120% rMT stimulation over the DLPFC delivers sub-motor equivalent electric fields in many individuals (73.7%). With further validation, electric field modeling may be an impactful method of individually dosing TMS.

Rodent models for nicotine withdrawal.

BACKGROUND: Animal models are critical to improve our understanding of the neuronal mechanisms underlying nicotine withdrawal. Nicotine dependence in rodents can be established by repeated nicotine injections, chronic nicotine infusion via osmotic minipumps, oral nicotine intake, tobacco smoke exposure, nicotine vapor exposure, and e-cigarette aerosol exposure. The time course of nicotine withdrawal symptoms associated with these methods has not been reviewed in the literature. AIM: The goal of this review is to discuss nicotine withdrawal symptoms associated with the cessation of nicotine, tobacco smoke, nicotine vapor, and e-cigarette aerosol exposure in rats and mice. Furthermore, age and sex differences in nicotine withdrawal symptoms are reviewed. RESULTS: Cessation of nicotine, tobacco smoke, nicotine vapor, and e-cigarette aerosol exposure leads to nicotine withdrawal symptoms such as somatic withdrawal signs, changes in locomotor activity, anxiety- and depressive-like behavior, learning and memory deficits, attention deficits, hyperalgesia, and dysphoria. These withdrawal symptoms are most pronounced within the first week after cessation of nicotine exposure. Anxiety- and depressive-like behavior, and deficits in learning and memory may persist for several months. Adolescent (4-6 weeks old) rats and mice display fewer nicotine withdrawal symptoms than adults (>8 weeks old). In adult rats and mice, females show fewer nicotine withdrawal symptoms than males. The smoking cessation drugs bupropion and varenicline reduce nicotine withdrawal symptoms in rodents. CONCLUSION: The nicotine withdrawal symptoms that are observed in rodents are similar to those observed in humans. Tobacco smoke and e-cigarette aerosol contain chemicals and added flavors that enhance the reinforcing properties of nicotine. Therefore, more valid animal models of tobacco and e-cigarette use need to be developed by using tobacco smoke and e-cigarette aerosol exposure methods to induce dependence.

Sex Differences in the Association of Cigarette Craving With Insula Structure.

BACKGROUND: Cigarette craving, which can negatively impact smoking cessation, is reportedly stronger in women than in men when they initiate abstinence from smoking. Identifying approaches to counteract craving in people of different sexes may facilitate the development of personalized treatments for Tobacco Use Disorder, which disproportionately affects women. Because cigarette craving is associated with nicotine dependence and structure of the insula, this study addressed whether a person's sex influences these associations. METHODS: The research participants (n = 99, 48 women) reported daily cigarette smoking and provided self-reports of nicotine dependence. After overnight abstinence from smoking, they underwent structural magnetic resonance imaging scanning to determine cortical thickness of the left and right anterior circular insular sulcus, and self-rated their cigarette craving before and after their first cigarette of the day. RESULTS: Women reported stronger craving than men irrespective of smoking condition (i.e., pre- and post-smoking) (P = .048), and smoking reduced craving irrespective of sex (P < .001). A 3-way interaction of sex, smoking condition, and right anterior circular insular sulcus thickness on craving (P = .033) reflected a negative association of cortical thickness with pre-smoking craving in women only (P = .012). No effects of cortical thickness in the left anterior circular insular sulcus were detected. Nicotine dependence was positively associated with craving (P < .001) across groups and sessions, with no sex differences in this association. CONCLUSIONS: A negative association of right anterior insula thickness with craving in women only suggests that this region may be a relevant therapeutic target for brain-based smoking cessation interventions in women.

Neurometabolic alterations in the nucleus accumbens of smokers assessed with 1 H magnetic resonance spectroscopy: The role of glutamate and neuroinflammation.

Tobacco use is one of the leading causes of premature death and morbidity worldwide. For smokers trying to quit, relapse rates are high, even after prolonged periods of abstinence. Recent findings in animal models highlight the role of alterations in glutamatergic projections from the prefrontal cortex onto the nucleus accumbens (NAc) in relapse vulnerability. Moreover, inflammatory responses in the NAc have been reported during withdrawal. A novel proton magnetic resonance spectroscopy (1 H-MRS) protocol was applied in humans to measure molar concentrations for glutamate, its sum with glutamine (Glx), and myoinositol plus glycine (mI + Gly) in the NAc (19 smokers, 20 matched controls). Smokers were measured at baseline and during withdrawal and satiation. No difference between groups or smoking states was found for glutamate or Glx, but, in smokers, stronger craving and more severe nicotine dependence were associated with lower baseline glutamate and Glx levels, respectively. Interestingly, mI + Gly concentrations were higher during withdrawal than baseline and correlated negatively with nicotine dependence severity and pack years of smoking. The lack of glutamatergic changes between groups and smoking states may imply that glutamate homeostasis is not significantly altered in smokers or that changes are too small for detection by 1 H-MRS. Moreover, the observed increase in mI + Gly may imply that neuroinflammatory processes occur in the NAc during nicotine withdrawal. These findings shed light on neurobiological relapse mechanisms in smokers and may provide the opportunity to develop more effective treatment options targeting the glutamate and neuroinflammation system.

Association between functional brain alterations and neuropsychological scales in male chronic smokers using resting-state fMRI.

RATIONALE: Recent studies have demonstrated that cigarette smoking is related to changes in brain structure and function. However, few studies focus on functional brain differences between male chronic smokers and nonsmokers in both local spontaneous activity and whole-brain functional networks. OBJECTIVES: Our study recruited 67 chronic smokers and 43 nonsmokers who underwent functional magnetic resonance imaging (fMRI) scans to investigate functional activity and connectivity alterations in chronic smokers. METHODS: We used the mean fractional amplitude of the low-frequency fluctuation (mfALFF) and mean regional homogeneity (mReHo) methods to investigate resting-state spontaneous activity in chronic smokers and nonsmokers. The graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also used to investigate functional connectivity alterations. RESULTS: Compared with nonsmokers, chronic smokers exhibited higher activation in the reward system and portions of the prefrontal cortex but lower activation in the default mode networks (DMN) and visual-related regions. In addition, correlation analysis was conducted to assess the associations between neuroimaging findings and the severity of nicotine dependence or expectations of smoking effects. Our results showed that certain brain regions correlated with the Fagerström Test for Nicotine Dependence (FTND), the positive aspect of the Drug Use Disorders Identification Test Extended (DUDIT-E), and the negative aspect of the DUDIT-E, especially in the attentional control networks and hippocampus. The graph theoretical analysis (GTA) results indicated chronic smokers exhibited a trend toward increased assortativity. Our network-based statistical (NBS) analysis revealed reduced functional connections between the subnetwork in the prefrontal cortex, olfactory cortex, angular gyrus, and cingulate gyrus of chronic smokers. CONCLUSIONS: We concluded that chronic smokers have neural adaptations in local spontaneous activity but remain healthy brain functional networks.

Addiction-related neuroadaptations following chronic nicotine exposure.

The addiction-relevant molecular, cellular, and behavioral actions of nicotine are derived from its stimulatory effects on neuronal nicotinic acetylcholine receptors (nAChRs) in the central nervous system. nAChRs expressed by dopamine-containing neurons in the ventral midbrain, most notably in the ventral tegmental area (VTA), contribute to the reward-enhancing properties of nicotine that motivate the use of tobacco products. nAChRs are also expressed by neurons in brain circuits that regulate aversion. In particular, nAChRs expressed by neurons in the medial habenula (mHb) and the interpeduncular nucleus (IPn) to which the mHb almost exclusively projects regulate the "set-point" for nicotine aversion and control nicotine intake. Different nAChR subtypes are expressed in brain reward and aversion circuits and nicotine intake is titrated to maximally engage reward-enhancing nAChRs while minimizing the recruitment of aversion-promoting nAChRs. With repeated exposure to nicotine, reward- and aversion-related nAChRs and the brain circuits in which they are expressed undergo adaptations that influence whether tobacco use will transition from occasional to habitual. Genetic variation that influences the sensitivity of addiction-relevant brain circuits to the actions of nicotine also influence the propensity to develop habitual tobacco use. Here, we review some of the key advances in our understanding of the mechanisms by which nicotine acts on brain reward and aversion circuits and the adaptations that occur in these circuits that may drive addiction to nicotine-containing tobacco products.

Smoking-induced craving relief relates to increased DLPFC-striatal coupling in nicotine-dependent women.

BACKGROUND: Craving is a major contributor to drug-seeking and relapse. Although the ventral striatum (VS) is a primary neural correlate of craving, strategies aimed at manipulating VS function have not resulted in efficacious treatments. This incongruity may be because the VS does not influence craving in isolation. Instead, craving is likely mediated by communication between the VS and other neural substrates. Thus, we examined how striatal functional connectivity (FC) with key nodes of networks involved in addiction affects relief of craving, which is an important step in identifying viable treatment targets. METHODS: Twenty-four nicotine-dependent non-abstinent women completed two resting-state (rs) fMRI scans, one before and one following smoking a cigarette in the scanner, and provided craving ratings before and after smoking the cigarette. A seed-based approach was used to examine rsFC between the VS, putamen and germane craving-related brain regions; the dorsolateral prefrontal cortex (dlPFC), the posterior cingulate cortex, and the anterior ventral insula. RESULTS: Smoking a cigarette was associated with a decrease in craving. Relief of craving correlated with increases in right dlPFC- bilateral VS (r = 0.57, p = 0.003, corrected) as did increased right dlPFC-left putamen coupling (r = 0.62, p = 0.001, corrected). CONCLUSIONS: Smoking-induced relief of craving is associated with enhanced rsFC between the dlPFC, a region that plays a pivotal role in decision making, and the striatum, the neural structure underlying motivated behavior. These findings are highly consistent with a burgeoning literature implicating dlPFC-striatal interactions as a neurobiological substrate of craving.

La disfunción de las pequeñas vías aéreas inducida por el tabaco ¿podría ser un marcador precoz de una futura EPOC? / Smoking-Induced Small Airway Dysfunction. An Early Marker of Future Copd?

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Mechanisms of Nicotine Addiction.

Tobacco smoking results in more than five million deaths each year and accounts for ∼90% of all deaths from lung cancer.3 Nicotine, the major reinforcing component of tobacco smoke, acts in the brain through the neuronal nicotinic acetylcholine receptors (nAChRs). The nAChRs are allosterically regulated, ligand-gated ion channels consisting of five membrane-spanning subunits. Twelve mammalian α subunits (α2-α10) and three ß subunits (ß2-ß4) have been cloned. The predominant nAChR subtypes in mammalian brain are those containing α4 and ß2 subunits (denoted as α4ß2* nAChRs). The α4ß2* nAChRs mediate many behaviors related to nicotine addiction and are the primary targets for currently approved smoking cessation agents. Considering the large number of nAChR subunits in the brain, it is likely that nAChRs containing subunits in addition to α4 and ß2 also play a role in tobacco smoking. Indeed, genetic variation in the CHRNA5-CHRNA3-CHRNB4 gene cluster, encoding the α5, α3, and ß4 nAChR subunits, respectively, has been shown to increase vulnerability to tobacco dependence and smoking-associated diseases including lung cancer. Moreover, mice, in which expression of α5 or ß4 subunits has been genetically modified, have profoundly altered patterns of nicotine consumption. In addition to the reinforcing properties of nicotine, the effects of nicotine on appetite, attention, and mood are also thought to contribute to establishment and maintenance of the tobacco smoking habit. Here, we review recent insights into the behavioral actions of nicotine, and the nAChR subtypes involved, which likely contribute to the development of tobacco dependence in smokers.