Teresa R. Franklin

Voxel-based morphometry (VBM) studies have interpreted longitudinal medication- or behaviorally induced changes observed on T1-weighted magnetic resonance images (MRIs) as changes in neuronal structure. Although neurogenesis or atrophy certainly occurs, the use of T1-weighted scans to identify change in brain structure in vivo in humans has vulnerability: the T1 relaxation time for arterial blood and gray matter are not clearly distinguishable and therefore, apparent reported structural findings might be at least partially related to changes in blood flow or other physiological signals. To examine the hypothesis that apparent structural modifications may reflect changes introduced by additional mechanisms irrespective of potential neuronal growth/atrophy, we acquired a high-resolution T1-weighted structural scan and a 5-min perfusion fMRI scan (a measurement of blood flow), before and after administration of an acute pharmacological manipulation. In a within-subject design, 15 subjects were either un-medicated or were administered a 20 mg dose of baclofen (an FDA-approved anti-spastic) approximately 110 min before acquiring a T1-weighted scan and a pseudo continuous arterial spin labeled perfusion fMRI scan. Using diffeomorphic anatomical registration through exponentiated lie algebra within SPM7, we observed macroscopic, and therefore implausible, baclofen-induced decreases in VBM ‘gray matter’ signal in the dorsal rostral anterior cingulate (family wise error corrected at p < 0.04, T = 6.54, extent: 1,460 voxels) that overlapped with changes in blood flow. Given that gray matter reductions are unlikely following a single dose of medication these findings suggest that changes in blood flow are masquerading as reductions in gray matter on the T1-weighted scan irrespective of the temporal interval between baseline measures and longitudinal manipulations. These results underscore the crucial and immediate need to develop in vivo neuroimaging biomarkers for humans that can uniquely capture changes in neuronal structure dissociable from those related to blood flow or other physiological signals.

Numerous factors are involved in the motivation to smoke and are associated with relapse, including stress, peer pressure, availability, menstrual cycle phase, and even weight management.^1-5 However, smoking cue–induced and withdrawal-induced cravings are 2 of the major contributors to relapse.^6-9 Inability to combat withdrawal-induced craving, which declines within a month,¹⁰ plays a role in early relapse. Nevertheless, smokers report that smoking cues (eg, seeing a pack of cigarettes, socializing with others who smoke, and even internal mood states repeatedly associated with smoking) can trigger relapse months or even years after quitting. Some smokers who are thought to possess high “cue reactivity” are especially vulnerable and have an increased probability of relapse initiated by exposure to smoking cues.^11,12 Therefore, treatments that target cue reactivity are important, particularly for cue-vulnerable individuals, but the effect of existing smoking cessation medications on smoking cue reactivity has not been thoroughly investigated. Thus far, research has focused on reduction of withdrawal and nicotine reward, which are known mechanisms underlying the effectiveness of first-line smoking cessation agents, such as varenicline, nicotine replacement therapy, and bupropion hydrochloride.^13-15

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.

We previously demonstrated differential activation of the mesocorticolimbic reward circuitry in response to cigarette cues independent of withdrawal. Despite robust effects, we noted considerable individual variability in brain and subjective responses. As dopamine (DA) is critical for reward and its predictive signals, genetically driven variation in DA transmission may account for the observed differences. Evidence suggests that a variable number of tandem repeats (VNTRs) polymorphism in the DA transporter (DAT) SLC6A3 gene may influence DA transport. Brain and behavioral responses may be enhanced in probands carrying the 9-repeat allele. To test this hypothesis, perfusion fMR images were acquired during cue exposure in 19 smokers genotyped for the 40 bp VNTR polymorphism in the SLC6A3 gene. Contrasts between groups revealed that 9-repeat (9-repeats) had a greater response to smoking (vs nonsmoking) cues than smokers homozygous for the 10-repeat allele (10/10-repeats) bilaterally in the interconnected ventral striatal/pallidal/orbitofrontal cortex regions (VS/VP/OFC). Activity was increased in 9-repeats and decreased in 10/10-repeats in the VS/VP/OFC (pr²=0.79–0.86, p<0.001 in all regions). Alternatively, there were no significant correlations between brain and behavior in 9-repeats. There were no differences in cigarette dependence, demographics, or resting baseline neural activity between groups. These results provide evidence that genetic variation in the DAT gene contributes to the neural and behavioral responses elicited by smoking cues.

Background and Objective: The deleterious health consequences of smoking are even more severe for women, yet ironically, they have more difficulty quitting than men. Identifying relapse predictors for women and implementing strategies to increase their chances of successfully quitting and remaining abstinent are important goals. Clinicians and researchers suggest that women could achieve greater success in smoking cessation interventions if the initial quit attempt coincided with the follicular phase (i.e., preovulatory phase) of their menstrual cycle (MC) rather than the luteal phase (i.e., premenstrual). However, no experimental data have been published to support this claim. Our objective was to determine whether MC phase affected smoking status in premenopausal female smokers participating in a smoking cessation treatment trial. Methods: Data from 102 treatment-seeking smokers who participated in an 8-week nicotine replacement therapy (NRT) plus behavioral intervention smoking cessation study were examined retrospectively. NRT began the day subjects attempted to quit smoking (quit date). For analyses, smokers were grouped according to sex, and women were subdivided by MC phase at quit date into follicular (FF, days 1–14, n = 16) and luteal (LF, days 15–30, n = 21) groups. Results: Smoking status was examined on the third day after the quit date (day 3) and at 1 week posttreatment (week 9). On day 3, 52% of LFs reported smoking compared with 19% of FFs (p < 0.04), and at week 9, 71% of LFs reported smoking compared with 31% of FFs (p < 0.02). In a comparison group of men (n = 65), 25% were smoking at day 3 and 68% at week 9. Self-report at week 9 was verified by urine cotinine levels. Conclusions: These data support the supposition that better treatment outcomes can be achieved by scheduling quit dates to coincide with the follicular phase of the MC in female smokers.

Exposure to cigarette smoking cues can trigger physiological arousal and desire to smoke. The brain substrates of smoking cue-induced craving (CIC) are beginning to be elucidated; however, it has been difficult to study this state independent of the potential contributions of pharmacological withdrawal from nicotine. Pharmacological withdrawal itself may have substantial effects on brain activation to cues, either by obscuring or enhancing it, and as CIC is not reduced by nicotine replacement strategies, its neuro-anatomical substrates may differ. Thus, characterizing CIC is critical for developing effective interventions. This study used arterial spin-labeled (ASL) perfusion fMRI, and newly developed and highly appetitive, explicit smoking stimuli, to examine neural activity to cigarette CIC in an original experimental design that strongly minimizes contributions from pharmacological withdrawal. Twenty-one smokers (12 females) completed smoking and nonsmoking cue fMRI sessions. Craving self-reports were collected before and after each session. SPM2 software was employed to analyze data. Blood flow (perfusion) in a priori-selected regions was greater during exposure to smoking stimuli compared to nonsmoking stimuli (pr²=0.54) and posterior cingulate (r²=0.53). This pattern of activation that includes the ventral striatum, a critical reward substrate, and the interconnected amygdala, cingulate and OFC, is consistent with decades of animal research on the neural correlates of conditioned drug reward.

Cigarettes acquire reinforcing properties from nicotine and from cues associated with their intake. However, smoking in males and females may be reinforced differentially. Smoking in females is posited to be influenced more by cues whereas male smoking is influenced predominantly by the direct pharmacological actions of nicotine in the brain. Menstrual cycle phase may contribute to some of the sex differences observed in smokers. We hypothesized that females may report more intense craving to smoking cue exposure than males and, further, that female craving scores may be influenced by menstrual cycle phase. Thus, we reexamined previously collected cue exposure data with respect to sex and cycle phase. Self-report measures were collected from subjects prior to and immediately following exposure to visual smoking stimuli. The study included 69 male and 41 female treatment-seeking subjects who smoked more than 15 cigarettes per day for more than 10 years. Females were grouped according to cycle phase. Of the female subjects, 17 were classified as follicular phase females (FFemales) and 24 were classified as luteal phase females (LFemales). Change scores were calculated from the subjective data collected before and after stimulus presentation. Contrary to our hypothesis, overall, males and all females did not differ in their level of cue-induced craving; however, when females were separated into groups by cycle phase, FFemales reported significantly less craving than either males or LFemales (p<.05). The suppressed craving response in FFemales suggests an influence of cycle phase on cue-induced craving.