Dopamine transporter genotype modulation of neural responses to smoking cues: confirmation in a new cohort.

Previously we demonstrated profound effects of dopamine transporter (DAT) SLC6A3 genotype on limbic responses to smoking cues (SCs). Probands carrying at least one copy of the 9-repeat allele (9-repeat carriers) had greater neural responses to SCs in the anatomically interconnected rostral ventral striatum/medial orbitofrontal cortex (VS/mOFC), compared with homozygotes for the 10-repeat allele (10/10-repeats). To test the reliability of the initial findings, we examined perfusion functional magnetic resonance images acquired during SC exposure in a new cohort of smokers (N=26) who were genotyped for the SLC6A3 polymorphism. In smokers overall, activity was enhanced in the VS/mOFC (t=3.77). Contrasts between allelic groups revealed that 9-repeat carriers had a greater response to SCs in the VS (t=3.12) and mOFC (t=3.19). In separate groups, 9-repeat carriers showed increased activity in the VS (t=5.47) and mOFC (T=4.96), while no increases were observed in 10-repeats. Subjective reports of craving correlated with increased activity in reward-related structures including the extended amygdala, insula and post-central gyrus, and decreased activity in the dorsolateral prefrontal cortex, and were DAT-genotype dependent (r=0.63-0.96). In secondary analyses, we found that The Fagerström Test for Nicotine Dependence scores correlated with enhanced SC-induced perfusion in 10/10-repeats in the insula, mOFC, medial temporal and superior frontal gyri (r=0.50-0.82), while correlations were absent in 9-repeat carriers. Despite heterogeneity introduced by a host of factors, including variance in other genes involved in smoking behavior, we confirm that DAT genotype predicts the direction and location of neural responses to SCs.

Effects of varenicline on smoking cue­triggered neural and craving responses.

CONTEXT: Varenicline, an effective smoking cessation medication, functions as an α4ß2 nicotinic acetylcholine receptor partial agonist. It indirectly affects the dopaminergic reward system by reducing withdrawal symptoms during abstinence and by decreasing the reinforcement received from nicotine while smoking. We hypothesize that varenicline would have a third mechanism to blunt responses to smoking cues in the reward-related ventral striatum and medial orbitofrontal cortex and would be associated with a reduction in smoking cue­elicited craving. DESIGN: A laboratory model of conditioned responding and arterial spin-labeled perfusion functional magnetic resonance imaging, a biomarker of regional brain activity, was used to test our hypothesis. Perfusion functional magnetic resonance imaging is quantitative and stable across time, facilitating the measurement of medication-induced neural modifications in the brain in response to a challenge (smoking cue exposure) and in the brain in the resting condition (without provocation). Smokers were imaged during rest and during smoking cue exposure before and after a 3-week randomized placebo-controlled medication regimen. Subjects were nonabstinent to explicitly examine the effects of varenicline on cue reactivity independent of withdrawal. SETTING: Center for the Study of Addictions, University of Pennsylvania, Philadelphia. Subjects Subjects were nicotine-dependent smokers who responded to advertisements placed on local radio and Listservs to participate in a medication-related research study that specifically stated "this is not a Quit Smoking Study" and "smokers may be contemplating but not currently considering quitting." RESULTS: Prerandomization smoking cues vs nonsmoking cues activated the ventral striatum and medial orbitofrontal cortex (t = 3.77) and elicited subjective reports of craving (P = .006). Craving reports correlated with increased activity in the posterior cingulate (t = 4.11). Administration of varenicline diminished smoking cue­elicited ventral striatum and medial orbitofrontal cortex responses (t values from ­3.75 to ­5.63) and reduced self-reported smoking cue­elicited craving, whereas placebo-treated subjects exhibited responses similar to those observed prior to randomization. Varenicline-induced activation of lateral orbitofrontal cortex in the brain at rest (t = 5.63) predicted blunting of smoking cue responses in the medial orbitofrontal cortex (r = ­0.74). CONCLUSIONS: Varenicline's reciprocal actions in the reward-activated medial orbitofrontal cortex and in the reward-evaluating lateral orbitofrontal cortex underlie a diminished smoking cue response, revealing a distinctive new action that likely contributes to its clinical efficacy.

Identifying risk factors for marijuana use among veterans affairs patients.

OBJECTIVES: Cannabis is the most widely used drug in the United States, and its use carries negative health consequences; however, universal screening for cannabis use is cumbersome. If data commonly collected in the primary care setting (eg, use of alcohol, smoking status, and depression symptoms) could predict cannabis use, then providers can implement targeted marijuana screening in high-risk groups. METHODS: We reviewed Behavioral Health Laboratory data collected between 2003 and 2006 from 5512 patients referred by Veterans Affairs primary care clinics for potential mental health needs. Logistic regression was used to determine the predictors of past year marijuana use. RESULTS: A total of 11.5% of the sample reported using marijuana in the past year. Age, gender, other drug use, presence of alcohol use disorders, smoking status, depressive disorders, posttraumatic stress disorder, anxiety disorders, and psychotic symptoms, individually, were associated with the patients' use of marijuana during the past year. When controlling for age, race, and gender in a logistic regression analyses, only other drug use, alcohol use disorder, and smoking status were linked to past year marijuana use. Patients were 5.4 (95% confidence interval [CI] 4.3-6.7) times more likely to have used marijuana during the past year if they used another illicit drug during the past year. Those with alcohol use disorder diagnosis or current smokers were 2.3 (95% CI 1.9-2.8) and 1.5 times (95% CI 1.3-1.7), respectively, more likely to have used marijuana during the past year. Receiver operating characteristic curve (area under curve = 0.79) represents good sensitivity and specificity of the model, correctly classifying 88.4% of the past year marijuana users. CONCLUSION: Identifying patients at high risk for cannabis use may facilitate targeted screening and provision of interventions in primary care. Patients who screen positive for cigarette use, alcohol abuse or dependence, or have evidence of other illicit drug use could be considered for cannabis screening.