Background: Identifying the biological basis of smoking cessation success is of growing interest. The rate of nicotine metabolism, measured by the nicotine metabolite ratio, affects multiple aspects of nicotine dependence. Fast nicotine metabolizers tend to smoke more, experience more withdrawal and craving, and have lower cessation rates compared with slow metabolizers. The nicotine metabolite ratio predicts treatment response, and differences in brain activation between fast metabolizers and slow metabolizers have been reported in fMRI studies. As reinforcing/rewarding effects of tobacco are associated with dopamine transmission, the purpose of the present study was to study the dopaminergic system in human smokers based on their nicotine metabolite ratio. Methods: The first aim of the study was to explore if there were differences in D and D receptor binding between fast 2 3 metabolizers and slow metabolizers during abstinence. The second aim was to explore smoking-induced dopamine release in both groups. Participants underwent 2 [ C]-(+)-PHNO PET scans: one scan during abstinence and the other after smoking a tobacco cigarette. Subjective measures were recorded and blood was drawn for measurement of nicotine and cotinine levels. Results: During abstinence, slow metabolizers (n = 13) had lower C]-(+)-PHNO [ binding potential than fast metabolizers (n = 15) restricted to the D regions of the associative striatum and sensorimotor striatum. After smoking a cigarette C]-(+)- , [ PHNO binding potential was decreased in the limbic striatum and ventral pallidum, suggestive of increases in dopamine, but there were no nicotine metabolite ratio differences. Conclusions: Further studies are required to delineate if differences in [ C]-(+)-PHNO binding between slow metabolizers and fast metabolizers at abstinence baseline are preexisting traits or induced by prolonged tobacco use. Keywords: Cigarettes, dopamine, D2, D3, NMR Received: October 24, 2017; Revised: December 19, 2017; Accepted: January 9, 2018 © The Author(s) 2018. Published by Oxford University Press on behalf of CINP. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, 503 provided the original work is properly cited. For commercial re-use, please contact email@example.com Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 504 | International Journal of Neuropsychopharmacology, 2018 Significance Statement Smoking is a serious public health problem, and it is known that the rate of metabolism of nicotine can influence key smoking characteristics such as the amount smoked and the ability to quit. The aim of the present study was to determine the impact of the rate of metabolism of nicotine on the brain reward system in tobacco smokers. We found that slow metabolizers had fewer dopamine receptors (of the D2-type) than fast metabolizers, but the two groups had a similar dopamine response to smoking a cigarette. Thus, the rate of nicotine metabolism may contribute to dopaminergic signaling in the brain. 2004). In our previous study (Le Foll et al., 2014b), we demon- Introduction strated a good magnitude of change in [C]-(+)-PHNO BP ND There is increasing interest in understanding the biological due to smoking (approximately 12%) in the LST and VP using basis of individual differences in smoking characteristics. One 11 [ C]-(+)-PHNO. Further, it is also known from PET studies that biomarker of individual differences is the rate at which nicotine DA D receptor availability is lower in the striatum of people who is metabolized, or the nicotine metabolite ratio (NMR) (Dempsey are nicotine dependent (Fehr et al., 2008), similar to other drugs et al., 2004). When stratified by NMR, it has been shown that of abuse (Volkow et al., 1993; Martinez et al., 2004). By compari- fast metabolizers (FM) smoke more than slow metabolizers (SM) son, D receptor levels (in the SN) are reportedly higher in drug (Benowitz et al., 2003; Johnstone et al., 2006; Malaiyandi et al., dependence (Boileau et al., 2012). It would be of interest to deter - 2006; Mwenifumbo et al., 2007; Schnoll et al., 20092014 , ) and take mine whether fast metabolizers and slow metabolizers have larger puff volumes (Strasser et al., 2011), suggesting an attempt different levels of basal D and D receptors and whether the 2 3 to titrate smoking. Perhaps due to more cigarette smoking and response to smoking a cigarette is different. higher levels of dependence, FM have higher craving (Kaufmann The purpose of the present study was: (1) to measure differ - et al., 2015) and reward (Sofuoglu et al., 2012) and greater with- 11 ences in [ C]-(+)-PHNO binding at abstinence baseline in FM vs drawal (Rubinstein et al., 2008). Consistent with these findings, SM; and (2) to measure smoking-induced differences in [ C]-(+)- FM and SM also differ in response to both placebo and active PHNO binding in these groups. Prior to conducting this study, smoking cessation treatments, with SM showing greater suc- preliminary analyses were conducted on our previous study (Le cess in quitting (Lerman et al., 2006 2015 , ; Patterson et al., 2008; Foll et al., 2014b). Based on these results, it was hypothesized Schnoll et al., 2009Cheno ; weth et al., 2013, 2016; Vaz et al., 2015; that SM metabolizers will show greater decreases in [ C]-(+)- Ebbert et al., 2016). PHNO binding after smoking. It was further hypothesized, based Studies have begun to delineate differences in brain responses on these preliminary results, that SM would have lower levels of in SM vs FM. In 2 fMRI studies, FM had greater neural response to basal D receptors in the striatum, and higher D receptor levels 2 3 smoking cues than did the SM (Tang et al., 2012) (Falcone et al., (in the SN), than FM. 2016). It was also found that, in smokers, those with the faster nicotine metabolizer genotype had higher brain activation in Methods the anterior cingulate and ventral striatum; no genotype group differences were observed among nonsmokers (Li et al., 2017). Participants Although these studies are informative, dopamine (DA) is a final common path in addiction (Di Chiara et al., 1992), and the effects All procedures were approved by the Centre for Addiction and Mental Health Research Ethics Board and the University of of NMR on baseline DA receptor levels and on DA transmission after a smoking challenge are currently unknown. Toronto and complied with the 1975 Helsinki Declaration (5th revision, 2000). Participants were recruited from the community, PET imaging provides a noninvasive means to measure neurotransmitter levels and receptors. [ C]-(+)-PHNO (Wilson provided written informed consent, and participated in a com- prehensive screening interview. All met the following criteria: et al., 2005) allows for the measurement of DA D and D recep- 2 3 tors, but also provides a more sensitive measure of DA fluc- (1) Males and females of any ethnic origin 18 years of age or older; (2) No use of medication for smoking cessation in the pre- tuations compared with the traditionally used [ C]-raclopride (Shotbolt et al., 2012). An advantage of PET imaging with vious month; (3) Smokers who are nontreatment seekers (smok- ing status verified by expired CO and the presence of nicotine [ C]-(+)-PHNO is the ability to measure not only D receptors 2/3 (as with traditional [C]-raclopride), but to explore the expres- and cotinine in plasma); (4) No DSM diagnoses or other drug dependence; (5) No medical conditions requiring immediate sion of D vs D receptors, based on a regional signal analysis 2 3 approach (Kiss et al., 2011; Le Foll et al., 2014a). In an elegant investigation or treatment; (6) Not pregnant; (7) No regular use of any therapeutic or recreational psychoactive drug use that study by Tziortizi et al., gradients of binding to or D D receptors 3 2 were demonstrated, with 100% of the signal obtained from the may interfere with PET scanning; (8) No exposure to radiation in the last 12 months exceeding permissible limits for participants substantia nigra (SN) being attributed to D (Tziortzi et al., 2011). By contrast, the entire signal from striatal regions was due to the participating in research; (9) No current use of medication that may interfere with [ C]-(+)-PHNO; (10) No PET or MRI scanning D receptor. The ventral pallidum (VP; 75%), globus pallidus (GP; 65%), and ventral/limbic striatum (LST; 50%) provide intermedi- contraindications; (11) (Not having any clinical condition, drug sensitivity, or prior therapy that, in the investigator’s opinion, ate D fractions. PET imaging has also been used to study smoking-induced makes the participant unsuitable for the study; (12) No cur - rent use of antidepressants that may inhibit CYP2A6 or impact change in DA. Studies with [ C]-raclopride showed smoking- induced changes in binding potential (BP ) (Brody et al., 2004, responses to nicotine. After initial determination of eligibility, ND those that qualified as FM (NMR > 0.47) or SM (NMR < 0.23) were 2009, 2010). In some studies, changes in DA were limited to sub- jects that had a hedonic response, as measured with a 10-point enrolled in the study. Data from 10 (7 FM and 3 SM) participants were included from a previous study (Le Foll et al., 2014b). scale of subjective ratings while in the scanner (Barrett et al., Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 Di Ciano et al. | 505 Tanner et al., 2015). This study used the same range of NMR as Procedure previously seen (Tang et al., 2012), resulting in the lowest tertile, Participants were recruited by word-of-mouth, advertisements slow metabolizers, with NMRs < 0.23, and the faster tertile, fast in local newspapers, social media, through posters, and from metabolizers, with NMRs > 0.47. referral from other studies. After an initial phone screen, eli- gibility was assessed after obtaining signed informed consent. PET Image Acquisition In the current study, after confirmation of eligibility, partici- pants underwent 2 PET scans after being asked to refrain from 11 The radiosynthesis of [ C]-(+)-PHNO has been described in de- smoking for a period of 12 (Le Foll et al., 2014b) or 48 hours of tail elsewhere (Wilson et al., 2005). PET scans were performed abstinence from smoking. All efforts were made to conform using a Siemens-Biograph HiRez XVI (Siemens Molecular to the 48-abstinence time line. However, there were unfore- Imaging) PET/CT camera system, which measures radioactivity seen circumstances. For some participants, there were delays in 81 brain sections with a reconstructed pixel size of 1.07x 1.07 in scanning, so the actual abstinence was longer; for others, x 2.00 mm each with an in-plane resolution of 5 mm full-width the participants requested to refrain from smoking for longer at half maximum. A transmission scan was acquired and the than 48 hours. For some, the scans had to be rescheduled at the emission scan, acquired in 32-bit list mode, began after bolus last minute so the abstinence was shorter than 48 hours (i.e., 11 injection of [ C]-(+)-PHNO (duration of the bolus injection ap- about 24 hours; range of abstinence period: 12–144 hours). In proximately 2 minutes). Emission data were reconstructed by all cases, abstinence was verified with expired CO levels below 2D filtered back projection to yield dynamic images with fifteen 10 ppm. Participants were then escorted to a room where they 1-minute frames and fifteen 5-minute frames. The emission either smoked their preferred cigarette (smoking condition) or scan lasted for 90 minutes. The raw data were reconstructed by relaxed (abstinence condition). The order of these sessions was filtered-back projection. A custom-fitted thermoplastic mask counterbalanced. During each PET session, participants were (Tru-Scan Imaging) was made for each subject to reduce move- screened for use of recreational drugs and given a pregnancy ment during the acquisition. A total of ~370 ± 40 MBq (approxi- test if applicable. The cigarette was smoked with the use of a 11 mately 10 ± 1 mCi) of [ C]-(+)-PHNO was injected as a bolus into smoking topography device (CReSS, Borgwaldt KC). Measures an antecubital vein. taken were: average flow (milliliters-per-second), number of puffs, puff volume (milliliters), puff duration (seconds), and MRI Image Acquisition inter-puff interval (seconds). Questionnaires (Visual Analog Scale [VAS], Tobacco Craving Questionnaire [TCQ], Minnesota Subjects underwent standard proton density weighted brain Nicotine Withdrawal Scale [MNWS], Questionnaire on Smoking MRI on a Discovery MR750 3T MRI scanner (General Electric, Urges [QSU]) were administered at baseline and at the com- 3T MR750) (slice thickness 2 mm; interleaved; slice number, 84; pletion of the 90-minute PET scan. The participants visited the repetition time, 6000 ms; echo time, 8 ms; number of excitations, negative pressure room between 26 and 74 minutes prior to the 2; acquisition matrix, 256 x 192; FOV, 22 x 16.5 cm) to aid region start of the PET scan. Blood was taken for determination of nico- of interest delineation of the PET images. tine and cotinine levels at the start of each scan. Questionnaires consisted of a the 32-item QSU (Tiffany and PET Image Analysis Drobes, 1991), which can be separated into two factors (QSU1: desire to smoke for the pleasurable effects of the cigarette; Region of Interest (ROI)-Based Analysis QSU2: relief of negative affect), and the TCQ, a 12-item scale ROI delineation and time activity curve analyses were per - (Singleton et al., 2003) with 4 factors (TCQ1: relief from with- formed using ROMI (details in Rusjan et al., 2006). Functional drawal symptoms or negative mood; TCQ2: anticipation of posi- subcompartments of the striatum (Martinez et al., 2003) includ- tive outcomes from smoking; TCQ3: lack of control over tobacco ing the associative striatum (AST), limbic striatum (LST), and use; TCQ4: intent and planning to smoke for positive outcomes). sensorimotor striatum (SMST) were chosen as ROIs. Delineation Also included were the MNWS, an 8-item scale assessing the for the GP (whole), VP, and SN is described elsewhere (Boileau degree of withdrawal and a 21-item Visual Analog Scale to de- et al., 2012). termine changes in emotional reactivity (VAS1: I feel anxious; VAS2: I feel irritable; VAS3: I feel alert; VAS4: I feel restless; VAS5: Binding Potential I feel an increase of energy; VAS6: I feel an increase in my speed [ C]-(+)-PHNO specific binding potential (BP ) was estimated ND of thinking; VAS7: I have a craving for cigarettes; VAS8: I feel in each ROI using the simplified reference tissue method hungry; VAS9: I feel unhappy and unwell; VAS10: I feel impa- (Lammertsma and Hume, 1996) (SRTM), with cerebellar cortex tient; VAS11: I feel sleepy; VAS12: I feel tense; VAS13: I feel dizzy; (excluding vermis) as reference region. Parameter estimation VAS14: I have difficulty in concentrating; VAS15: I feel frustrated; was performed using PMOD (version 2.8.5; PMOD Technologies VAS16: I feel angry; VAS17: I feel depressed; VAS18: I have a Ltd). The change in [ C]-(+)-PHNO BP from abstinence baseline ND headache; VAS19: I have gastrointestinal disturbances; VAS20: to smoking condition was calculated as: My last cigarette was completely different; VAS21: My last cig- % Change in [ C]-(+)-PHNO = ((BP Smoking-BP Abstinence)/ ND ND arette tasted the best). BP Abstinence)*100. ND Determination of NMR Data Analyses Nicotine, cotinine, and 3’hydroxycotinine were assessed by [ C]-(+)-PHNO BP at abstinence baseline was analyzed using ND LC-MS/MS as previously described; limits of quantification a repeated-measures ANOVA (SPSS 24) (2 groups x 6 ROIs). were 0.1 ng/mL whole blood for each compound. NMR, which is ROIs with significant group differences in [ C]-(+)-PHNO BP ND highly reproducible across time and laboratory, was calculated at abstinence baseline were further investigated for rela- as the ratio of 3’hydroxycotinine/cotinine (St Helen et al., 2012; tionship with plasma cotinine and nicotine with Pearson’s Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 506 | International Journal of Neuropsychopharmacology, 2018 Product-Moment Correlation. Changes in [C]-(+)-PHNO BP (Benowitz et al., 2002). There were no group differences in the time ND after smoking were analyzed with a mixed condition (2 lev- from smoking to the start of the scan or between mass injected, els; abstinence and smoking) x ROI (6 levels; SN, VP, GP, LST, corrected activity or specific activity between the smoking and AST, SMST) x group (2 levels; FM, SM [between-subjects factor]) abstinence PET scans. The area under the curve for cerebellar ANOVA. ROIs with significant effects of condition were corre- Time Activity Curves was not different between groups or condi- lated with objective measures and smoking topography values tion. All participants tested negative for drugs of abuse on the days using Pearson’s Product-Moment Correlation. Percent (%) change of the PET scans (with the exception of one who tested positive for in BP (((BP Smoking-BP Abstinence)/BP Abstinence)*100) MDMA on the abstinence day) and had a CO reading of <10 ppm ND ND ND ND was entered into an ANOVA (ROI (6) x group) investigating group upon arrival. There were no group differences in plasma nicotine, differences in smoking-induced DA release between FM and cotinine, or CO at either PET scan or in average flow, number of SM. Group differences in smoking topography were analyzed puffs, puff volume, puff duration, or inter-puff interval (Table 1). with t tests. Subjective measures were analyzed with ANOVAs. Throughout, sphericity in repeated-measures ANOVAs was eval- Baseline Abstinence uated with the Mauchley’s test, and the Geisser-Greenhouse cor - rection was applied. A group x ROI ANOVA revealed no significant interaction and no effect of group; only an effect of ROI was revealed (F(5, 130) = 89.343, P < .001; partial eta squared: 0.775). Since we had GG Results a priori hypotheses about group differences in the striatum and D3-rich areas (SN), data were further analyzed with planned Participant Characteristics comparisons investigating group differences for each ROI. This In total, 15 FM and 13 SM completed the study (7 FM and 3 SM analysis revealed significant differences in the AST (P = .028) and from the previous study; Le Foll et al., 2014bT ). able 1 presents SMST (P = .024) with SM having lower binding in both regions. demographic information. There were no group differences in See Figure 1. Correlations of BP at abstinence baseline with ND age, gender, cigarettes per day (CPD), Fagerstrom Test of Nicotine either cotinine or nicotine levels revealed no significant correla- Dependence (FTND), pack-years, CO levels at baseline, cotinine tions for the AST (cotinine SM: r = -.497, P = .084; nicotine SM: 2 2 at baseline, or cotinine + 3’hydrozycotinine at baseline (the last 2 r = -.253, P = .405; cotinine FM: r = -.014, P = .960; nicotine FM: 2 2 measures were based on 8 FM and 10 SM). The relatively greater r = .394, P = .146) or SMST (cotinine SM: r = .008, P = .978; nico- 2 2 number of Asian smokers with slow NMRs is consistent with the tine SM: r = .144, P = .638; cotinine FM: r = .212, P = .447; nicotine higher frequency of reduced/null activity variant alleles in Asians FM: r = .375, P = .168). Table 1. Subject Characteristics. SM FM P value NMR .17 ± .02 .65 ± .05 <.001 Males 8 5 - Asian 6 1 - Caucasian 4 11 - Black 2 1 - Hispanic 1 2 - Age 37.5 ± 3.8 34.5 ± 2.7 .528 Years of education 14.2 ± .7 15.5 ± .6 .184 Cigarettes per day 11.6 ± 1.2 14.9 ± 2.0 .164 Cotinine levels (ng/mL) 10.9 ± 2.3 10.7 ± 2.3 .788 Cotinine + 3 hydroxycotinine (ng/mL) 200.1 ± 49.8 299.8 ± 90.1 .322 Fagerstrom test of nicotine dependence 4.4 ± .6 6.0 ± 1.0 .201 Pack-years 16.5 ± 4.3 12.1 ± 2.4 .363 CO level (ppm) 15.3 ± 2.4 12.9 ± 1.7 .422 Time between smoking and scan (min) 40.1 ± 3.5 46.5 ± 4.3 .272 Average Flow (mL/s) 36.8 ± 2.7 36.0 ± 3.3 .863 Number of puffs 15.5 ± 1.1 16.3 ± 1.5 .656 Puff volume (ml) 55.1 ± 4.3 59.3 ± 8.9 .696 Puff duration (s) 1.6 ± .1 2.2 ± .5 .289 Inter-puff interval (s) 19.4 ± 1.9 17.6 ± 2.0 .525 Abstinence Smoking P value Mass injected (µg) 2.3 ± .1 2.1 ± .1 .054 Corrected activity (mCi) 9.1 ± .3 9.2 ± .2 .75 Specific activity (mCi/µmol) 1078.2 ± 66.9 1193.6 ± 70.4 .254 Abstinence Smoking SM FM P value SM FM P value Plasma nicotine (ng/mL) 1.4 ± 0.6 1.0 ± .3 .62 9.9 ± 1.1 8.04 ± 1.2 .273 Plasma cotinine (ng/mL) 76.9 ± 22.1 66.7 ± 15.9 .704 86.1 ± 21.3 56.5 ± 10.4 .29 CO level (ppm) 3.5 ± .6 3.5 ± .6 .931 4.3 ± .7 3.1 ± .5 .194 P values represent the results of t tests. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 Di Ciano et al. | 507 Figure 1. Binding potential (BP ) measured at abstinence baseline in participants with fast nicotine metabolism ratios (NMRs) (open symbols) or slow NMRs (dark ND symbols) in regions of interest (ROIs) (presented in order of D fraction: SN: substantia nigra; VP: ventral pallidum; GP: globus pallidus; LST: ventral/limbic striatum; AST: associative striatum; SMST: sensorimotor striatum). *P < .05, fast NMR different from slow NMR. levels were not correlated with the time between smoking and Difference Between Abstinence and Smoking the scan (r = -.285, P = .142) Conditions A condition (2 levels, abstinence and smoking) x group (2 levels) Questionnaires x ROI (SN, GP, VP, LST, AST, SMST) ANOVA revealed a significant ROI x condition interaction (F(5, 130) = 8.301, P = .001; partial Questionnaire data from after the PET scans were analyzed with GG eta squared: 0.242) with no effects of group (3-way interaction: condition (abstinence, smoking) x group (FM, SM) ANOVAs and F(5, 130) = .361, P = .702; partial eta squared = .014), suggesting revealed a significant interaction for TCQ1 (F(1, 26) = 5.155, P = .032; GG that the effects of smoking were different in the various ROIs but follow-up analyses revealed no differences in the direction of that the FMs were not different from the SMs (Figure 2). Indeed, effect of condition). Effects of condition were revealed for TCQ3 analysis of the percent change in BP from abstinence to smok- (F(1, 26) = 6.182, P = .02), MNWS (F(1, 26) = 0.021), QSU2 (F(1, 26) = ND ing condition with comparisons on the effect of group for each 13.894, P = .001), VAS1 F(1, 26) = 11.252, P = .002), VAS2 (F(1, ROI revealed no significant effects (group x ROI interaction: F(5, 26) = 15.396, P = .001), VAS4 (F(1, 26) = 15.064, P = .001), VAS 7 (F(1, 130) = .710, P = .617; partial eta squared = .124; Figure 2; SN: 26) = 13.834, P = .001), VAS10 (F(1, 26) = 10.894, P = .003), VAS12 GG P = .726; VP: P = .145; GP: P = .899; LST:P = .544; AST: P = .335;SMST: (F(1, 26) = 6.282, P = .019), VAS14 (F(1, 26) = 5.418, P = .028), VAS15 P = .354). Follow-up analyses of the significant condition x group (F(1, 26) = 7.651, P = .010), and VAS16 (F(1, 26) = 5.677, P = .025). interaction with comparisons on the effect of condition for each ROI revealed that the changes in [C]-(+)-PHNO BP from ab- ND Discussion stinence to smoking were significant in the LST (P < .001) and VP (P = .001), suggesting that smoking increased DA levels in those The purpose of the present study was to investigate differences in DA receptor levels at abstinence baseline between FM and SM areas. Two participants had VP values that were more than 2 SDs above the mean. Removal of the 2 participants with high [ C]-(+)- and also to determine whether differences exist between FM and SM in changes in DA levels after smoking a cigarette. It was PHNO BP levels in the VP did not change the results (condition ND x ROI: F(5, 120) = 8.149, P = .001; partial eta squared = 0.253; found that, at abstinence baseline, SMs had lower DA D receptor GG levels in the AST and SMST than FMs, with no group differences condition x ROI x group: F(5, 120) = 1.185, P = .314, partial eta GG squared = .047; effect of condition: P = .003). in the D3 region of the SN. After smoking a cigarette, decreases 11 11 in [ C]-(+)-PHNO BP , corresponding to increases in DA levels, The change in [ C]-(+)-PHNO BP in the LST was corre- ND ND lated with the time between smoking and the start of the scan were seen in the LST and VP in both the FMs and SMs, with no 2 2 group differences based on NMR status. The amount of change (r = .415, P = .028) and the number of puffs (r = -.446, P = .017) (Figure 3) but not with nicotine or cotinine assessed just before in [ C]-(+)-PHNO BP in the LST was correlated with the time ND between smoking and the scan and the number of puffs taken smoking scan. The change in [ C]-(+)-PHNO BP in the VP was ND significantly correlated with the inter-puff interval (r = .376, on a cigarette (but not cotinine or nicotine levels), while change in [ C]-(+)-PHNO BP in the VP was correlated with inter-puff P = .049, Figure 3); this correlation was no longer significant ND when the data from the participants with the 2 extreme val- interval. In the present study, SMs had lower [C]-(+)-PHNO BP in ues in the VP were removed. No correlations with changes in ND [ C]-(+)-PHNO BP in either the LST or VP were found with nico- the D regions of the AST and SMST at abstinence baseline. ND These differences were not attributable to plasma nicotine or tine levels taken before smoking scan (LST: r = -.237, P = .225; VP: r = -.190, P = .334) or cotinine levels taken before smoking scan cotinine levels, which did not differ between groups and did 2 2 not correlate with BP in these ROIs, and were observed in the (LST: r = -.283, P = .144; VP: r = -.334, P = .082). Further, nicotine ND Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 508 | International Journal of Neuropsychopharmacology, 2018 Figure 2. Top: Binding potential (BP ) measured at abstinence baseline (open symbols) or after smoking a preferred cigarette (dark symbols) in regions of interest ND (ROIs). *P < .05, abstinence different from smoking.Bottom : Change in [ C]-(+)-PHNO BP between abstinence baseline and smoking condition in ROIs. Open symbols ND are the fast metabolizers (FM) and closed symbols are the slow metabolizers (SM). No differences were found between the FMs and SMs. ROIs are presented in order of D fraction: SN: substantia nigra; VP: ventral pallidum; GP: globus pallidus; LST: ventral/limbic striatum; AST: associative striatum; SMST: sensorimotor striatum. Figure 3. Left: Correlation between change in binding potential (BP ) in the ventral/limbic striatum (LST) after smoking and time between smoking and the start of ND the scan (open symbols) and the number of puffs of the preferred cigarette (dark bars). Right: Correlation between change in BP in the ventral pallidum (VP) after ND smoking and inter-puff interval. absence of other group differences in demographic, subjective, consistent with faster breakdown of nicotine (Li et al., 2017). One or objective variables. These findings are consistent with a pre- possible difference between the NMR groups could be that, due vious report of group differences in brain activity at baseline; to differences in nicotine elimination kinetics, the intensity of in this previous report, it was found that those with the faster withdrawal may be greater in FM compared with SM (Rubinstein CYP2A6 genotype had higher brain activation at resting state, et al., 2008). However, here we did not observe any differences in Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 Di Ciano et al. | 509 withdrawal ratings and we controlled for prolonged abstinence, [ C]-(+)-PHNO BP in the LST. The present study extends those of ND which allowed for essentially complete elimination of nicotine. our previous report by revealing that the length of time between Indeed, very low levels, and no difference, in the plasma levels smoking a cigarette and the start of the PET scan is important of nicotine between the two groups was observed. In addition, in determining the magnitude of effect, and also that inter-puff as there were no nonsmokers included in the present study, it interval is related to changes in [ C]-(+)-PHNO BP in the VP. ND remains to be determined whether these changes would also Thus, important effects of smoking characteristics on changes be observed in control subjects (i.e., are these differences pre- in DA levels were found, suggesting that smoking affects DA existing or induced by tobacco exposure. No group differences levels. It should be noted, however, that the changes in [ C]-(+)- by CYP2A6 genotype in functional connectivity as measured by PHNO BP were only marginally associated with nicotine levels ND resting state fMRI were observed among nonsmokers (Li et al., (P = 0.08), and the time between smoking and scan was not asso- 2017), only among smokers, which argues for a gene x environ- ciated with nicotine levels. Thus, although the length of time ment interaction. Future studies will be needed in healthy con- between smoking and scanning is important, nicotine may not trols and in subjects after prolonged cessation to determine if be the only critical variable in determining the elevation of DA these changes are persistent or not. Indeed, it is possible that levels. Other contributors, such as environmental cues or alter - the SM had lower BP at abstinence baseline because their native tobacco constituents could also participate (Tang et al., ND receptor levels recover more slowly from abstinence; this is an 2012; Chiuccariello et al., 2013; Falcone et al., 2016). empirical question for future research. One finding that is worthy of note is the decrease in [ ]-(+)- Another interesting finding is that the relative difference in PHNO BP in the VP, corresponding to an increase in DA in this ND [ C]-(+)-PHNO BP at abstinence baseline between the groups area, after smoking. The VP is an efferent region of the LST and ND was seen in ROIs in which binding of [ C]-(+)-PHNO is to D was originally studied for its role as a limbic-interface, within receptors, but not in those where binding is to D receptors. a LST-VP circuit (Mogenson et al., 1993). Since then, it has been There are clear differences in the role and regulation of vs D posited to have roles in feeding, cue-induced feeding, taste re- D receptors (Boileau et al., 2012Le F ; oll et al., 2014a). One con- activity, maternal behavior, cognition, intracranial self-stimula- sistent finding in the literature is that of lower D receptor levels tion, aversion, and, most relevant to the present discussion, drug in those with drug dependence (Volkow et al., 1993Martinez ; self-administration (Root et al., 2015). In particular, Berridge et al., 2004). In addition, it has been shown that lower D re- and colleagues posit that it is a hedonic “hotspot” (Castro and ceptor levels predict relapse to drug use (Wang et al., 2012). In Berridge, 2014). Although the VP has not been as extensively this context, the present finding is somewhat surprising given studied in drug dependence as other brain regions such as the that SMs have largely been found to have higher response rates nucleus accumbens of cingulate cortex, the present study adds during behavioral counselling and during active treatment in to the growing literature on the VP by implicating it in smoking. clinical trials (Lerman et al., 2006 Patterson et ; al., 2008 Ho et ; al., In the present study, no group differences were found on 2009; Schnoll et al., 2009Cheno ; weth et al., 2013, 2016; Vaz et al., any demographic variables or on measures of smoking topog- 2015; Ebbert et al., 2016). However, a recent prospective study raphy. This is in contrast to previous reports of differences in demonstrated the opposite, that people with faster NMRs are cigarettes per day (Benowitz et al., 2003 Johnstone ; et al., 2006; more likely to quit (Fix et al., 2017). The authors suggest that Mwenifumbo et al., 2007; Schnoll et al., 20092014 , ) or puff vol- one reason for this discrepancy is the difference between the umes (Strasser et al., 2011). Differences in puff volume may be clinical trial situation in previous studies and the prospective attributable to the fact that, in the present study, participants ratings in their study. Thus, the lower [C]-(+)-PHNO BP at were in withdrawal when they smoked their cigarette, while ND baseline in the SMs in the current study may be related to poor they had only refrained from smoking for one hour in the pre- quit rates in non-treatment seekers. However, greater quitting in vious study (Strasser et al., 2011). Indeed, in a study where par - CYP2A6 genotypic SMs vs FMs, using frequencies among current ticipants were tested at 12 hours of withdrawal, no differences vs former smokers, supports greater success in quitting among in smoking topography were observed (Faulkner et al., 2017). SMs (Gu et al., 2000; Schoedel et al., 2004; Chenoweth et al., 2013). Alternatively, the differences may be related to demographic Thus the relationship between the lower [ C]-(+)-PHNO BP at variables in that participants were not required to smoke a min- ND baseline among SMs smokers and success in quitting smoking imal number of cigarettes per day, or to have a minimal FTND, requires investigation. for inclusion in this study. The inclusion criteria were intention- In the present study, contrary to our planned hypothesis, ally selected to allow for a broader range of participants, but this no group differences were found between FMs and SMs in may have inadvertently diminished some of the baseline dif- the change in [ C]-(+)-PHNO BP after smoking. These find- ferences between groups. However, it should be noted that not ND ings are somewhat surprising given the extensive literature all studies found relationships between NMR and CPD or FTND on differences in smoking characteristics between FM and SM (Ross et al., 2016; Faulkner et al., 2017). Future studies will need (Benowitz et al., 2003; Johnstone et al., 2006; Lerman et al., 2006, to determine the relative contribution of experience, and lev- 2015; Malaiyandi et al., 2006; Audrain-McGovern et al., 2007; els of dependence, on smoking-induced changes in DA, and the Mwenifumbo et al., 2007; Patterson et al., 2008Rubinstein et ; al., interaction of NMR with these changes. 2008; Schnoll et al., 20092014 , ; Strasser et al., 2011; Sofuoglu et al., 2012; Chenoweth et al., 2013; Kaufmann et al., 2015; Vaz Limitations et al., 2015; Chenoweth et al., 2016). It is possible that due to our limited sample, we may have been underpowered to detect dif- This study is not without limitations. First, the present findings ferences on this response based on NMR. The present findings rely on relatively small samples. Our sample size determination nevertheless support the results of our previous study (Le Foll was based on our preliminary data (Le Foll et al., 2014b). Over et al., 2014b) in which we reported significant elevations of DA the course of the study, it was decided to combine data sets to in the ventral/limbic striatum (LST) after smoking a cigarette. increase power, and thus the study was terminated near com- We also support our previous finding of a relationship between pletion to obtain the present sample size. In addition, we could the number of puffs taken on a cigarette and the change in not explore important variables such as gender, which has been Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 510 | International Journal of Neuropsychopharmacology, 2018 shown to influence many aspects of tobacco smoking (Cosgrove Benowitz NL, Pomerleau OF, Pomerleau CS, Jacob P 3rd (2003) et al., 2014). Our inclusion/exclusion criteria allowed for subjects Nicotine metabolite ratio as a predictor of cigarette con- with different degrees of dependence to be included (which also sumption. Nicotine Tob Res 5:621–624. can be seen as a strength). Due to the complexity of running Boileau I, Payer D, Houle S, Behzadi A, Rusjan PM, Tong J, Wilkins the experimental procedures, we had also significant variability D, Selby P, George TP, Zack M, Furukawa Y, McCluskey T, Wilson in the duration of abstinence before the scans or with the time AA, Kish SJ (2012) Higher binding of the dopamine D3 recep- between the smoking cessation and the PET sessions. Those tor-preferring ligand [11C]-(+)-propyl-hexahydro-naphtho- factors could have decreased our statistical power by increasing oxazin in methamphetamine polydrug users: a positron variability in our outcome measure. Further, although the mass emission tomography study. J Neurosci 32:1353–1359. injected was not different between conditions, it approached Brody AL, Olmstead RE, London ED, Farahi J, Meyer JH, Grossman significance, raising the question as to whether this influenced P, Lee GS, Huang J, Hahn EL, Mandelkern MA (2004) Smoking- the results. However, the cerebellar time activity curves were induced ventral striatum dopamine release. Am J Psychiatry not different between conditions, suggesting that this was not 161:1211–1218. a confounding variable. Brody AL, Mandelkern MA, Olmstead RE, Allen-Martinez Z, Scheibal D, Abrams AL, Costello MR, Farahi J, Saxena S, Monterosso J, London ED (2009) Ventral striatal dopamine Conclusions release in response to smoking a regular vs a denicotinized cigarette. Neuropsychopharmacology 34:282–289. The present study demonstrated baseline differences in [C]-(+)- PHNO BP in D , but not D, regions, between FMs and SMs at Brody AL, London ED, Olmstead RE, Allen-Martinez Z, ND 2 3 Shulenberger S, Costello MR, Abrams AL, Scheibal D, Farahi J, abstinence. We also validate in a larger sample our previous findings of a decrease in [ C]-(+)-PHNO BP (increase in DA) in Shoptaw S, Mandelkern MA (2010) Smoking-induced change ND in intrasynaptic dopamine concentration: effect of treatment the LST and VP after smoking. However, no group differences based on NMR were revealed in changes in [ C]-(+)-PHNO BP for tobacco dependence. Psychiatry Res 183:218–224. ND Castro DC, Berridge KC (2014) Advances in the neurobiological after smoking a cigarette. Whether differences at abstinence baseline exist between FMs and SMs before exposure to smok- bases for food ‘liking’ versus ‘wanting’. Physiol Behav 136:22–30. ing, whether it affects cessation, and the time it may take for those changes to normalize after smoking cessation can be the Chenoweth MJ, O’Loughlin J, Sylvestre MP, Tyndale RF (2013) CYP2A6 slow nicotine metabolism is associated with topic of further studies. increased quitting by adolescent smokers. Pharmacogenet Genomics 23:232–235. Acknowledgments Chenoweth MJ, Schnoll RA, Novalen M, Hawk LW Jr, George TP, Cinciripini PM, Lerman C, Tyndale RF (2016) The nicotine This work was supported by the National Institute on metabolite ratio is associated with early smoking abstinence Drug Abuse of the National Institutes of Health (grant no. even after controlling for factors that influence the nicotine R21DA039453 to B.L.F., I.B., R.T., S.H., and C.H.) and the Canada metabolite ratio. Nicotine Tob Res 18:491–495. Research Chairs program (to R.T. and C.H.). Research reported Chiuccariello L, Boileau I, Guranda M, Rusjan PM, Wilson AA, in this publication was supported by the National Institute on Zawertailo L, Houle S, Busto U, Le Foll B (2013) Presentation Drug Abuse of the National Institutes of Health under Award of smoking-associated cues does not elicit dopamine release Number R21DA039453. The content is solely the responsibility after one-hour smoking abstinence: A [(11)C]-(+)-PHNO PET of the authors and does not necessarily represent the official Study. PLoS One 8:e60382. views of the National Institutes of Health. Cosgrove KP, Wang S, Kim SJ, McGovern E, Nabulsi N, Gao H, Labaree D, Tagare HD, Sullivan JM, Morris ED (2014) Sex differ - Statement of Interest ences in the brain’s dopamine signature of cigarette smoking. J Neurosci 34:16851–16855. R. F. Tyndale has consulted for Apotex and Quinn Emmanuel Dempsey D, Tutka P, Jacob P 3rd, Allen F, Schoedel K, Tyndale RF, on unrelated topics and received funding from GRAND (unre- Benowitz NL (2004) Nicotine metabolite ratio as an index of stricted funding support from Pfizer) as well as university and cytochrome P450 2A6 metabolic activity. Clin Pharmacol Ther hospital speaker honorariums. Bernard Le Foll has received fi- 76:64–72. nancial compensation from Bioprojet, GRAND Awards and Di Chiara G, Acquas E, Carboni E (1992) Drug motivation and Allergan. abuse: a neurobiological perspective. Ann N Y Acad Sci 654:207–219. References Ebbert JO, Severson HH, Danaher BG, Benowitz NL, Schroeder DR Audrain-McGovern J, Al Koudsi N, Rodriguez D, Wileyto EP, (2016) Nicotine metabolite ratio is associated with lozenge Shields PG, Tyndale RF (2007) The role of CYP2A6 in the emer - use but not quitting in smokeless tobacco users. Nicotine Tob gence of nicotine dependence in adolescents. Pediatrics Res 18:366–370. 119:e264–274. Falcone M, Cao W, Bernardo L, Tyndale RF, Loughead J, Lerman C Barrett SP, Boileau I, Okker J, Pihl RO, Dagher A (2004) The hedonic (2016) Brain Responses to smoking cues differ based on nico- response to cigarette smoking is proportional to dopamine tine metabolism rate. Biol Psychiatry 80:190–197. release in the human striatum as measured by positron Faulkner P, Ghahremani DG, Tyndale RF, Cox CM, Kazanjian emission tomography and [11C]raclopride. Synapse 54:65–71. AS, Paterson N, Lotfipour S, Hellemann GS, Petersen N, Vigil Benowitz NL, Perez-Stable EJ, Herrera B, Jacob P 3rd (2002) Slower C, London ED (2017) Reduced-nicotine cigarettes in young metabolism and reduced intake of nicotine from cigarette smokers: impact of nicotine metabolism on nicotine dose smoking in Chinese-Americans. J Natl Cancer Inst 94:108–115. effects. Neuropsychopharmacology 42:1610–1618. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 Di Ciano et al. | 511 Fehr C, Yakushev I, Hohmann N, Buchholz HG, Landvogt C, Martinez D, Slifstein M, Broft A, Mawlawi O, Hwang DR, Huang Deckers H, Eberhardt A, Klager M, Smolka MN, Scheurich A, Y, Cooper T, Kegeles L, Zarahn E, Abi-Dargham A, Haber SN, Dielentheis T, Schmidt LG, Rosch F, Bartenstein P, Grunder G, Laruelle M (2003) Imaging human mesolimbic dopamine Schreckenberger M (2008) Association of low striatal dopa- transmission with positron emission tomography. Part II: mine d2 receptor availability with nicotine dependence simi- amphetamine-induced dopamine release in the functional lar to that seen with other drugs of abuse. Am J Psychiatry subdivisions of the striatum. J Cereb Blood Flow Metab 165:507–514. 23:285–300. Fix BV, O’Connor RJ, Benowitz N, Heckman BW, Cummings KM, Martinez D, Broft A, Foltin RW, Slifstein M, Hwang DR, Huang Fong GT, Thrasher JF (2017) Nicotine metabolite ratio (NMR) Y, Perez A, Frankle WG, Cooper T, Kleber HD, Fischman prospectively predicts smoking relapse: longitudinal find- MW, Laruelle M (2004) Cocaine dependence and d2 recep- ings from ITC Surveys in five countries. Nicotine Tob Res tor availability in the functional subdivisions of the stri- 19:1040–1047. atum: relationship with cocaine-seeking behavior. Gu DF, Hinks LJ, Morton NE, Day IN (2000) The use of long PCR to Neuropsychopharmacology 29:1190–1202. confirm three common alleles at the CYP2A6 locus and the Mogenson GJ, Brudzynski SM, Wu M, Yang CR, Yim CCY (1993) relationship between genotype and smoking habit. Ann Hum From motivation to action: a review of dopaminergic regula- Genet 64:383–390. tion of limbic -nucleus accumbens- ventral pallidum - pedun- Ho MK, Mwenifumbo JC, Al Koudsi N, Okuyemi KS, Ahluwalia culopontine nucleus circuitries involved in limbic-motor JS, Benowitz NL, Tyndale RF (2009) Association of nicotine integration. In: Limbic Motor Circuits and Neuropsychiatry metabolite ratio and CYP2A6 genotype with smoking ces- (Kalivas PW, Barnes CD, eds), pp 193–236. Boca Raton: CRC sation treatment in African-American light smokers. Clin Press. Pharmacol Ther 85:635–643. Mwenifumbo JC, Sellers EM, Tyndale RF (2007) Nicotine metab- Johnstone E, Benowitz N, Cargill A, Jacob R, Hinks L, Day I, olism and CYP2A6 activity in a population of black African Murphy M, Walton R (2006) Determinants of the rate of descent: impact of gender and light smoking. Drug Alcohol nicotine metabolism and effects on smoking behavior. Clin Depend 89:24–33. Pharmacol Ther 80:319–330. Patterson F, Schnoll RA, Wileyto EP, Pinto A, Epstein LH, Shields Kaufmann A, Hitsman B, Goelz PM, Veluz-Wilkins A, Blazekovic PG, Hawk LW, Tyndale RF, Benowitz N, Lerman C (2008) Toward S, Powers L, Leone FT, Gariti P, Tyndale RF, Schnoll RA (2015) personalized therapy for smoking cessation: a randomized Rate of nicotine metabolism and smoking cessation out- placebo-controlled trial of bupropion. Clin Pharmacol Ther comes in a community-based sample of treatment-seeking 84:320–325. smokers. Addict Behav 51:93–99. Root DH, Melendez RI, Zaborszky L, Napier TC (2015) The ventral Kiss B, Horti F, Bobok A (2011) In vitro and in vivo comparison pallidum: subregion-specific functional anatomy and roles in of [(3)H](+)-PHNO and [(3)H]raclopride binding to rat stri- motivated behaviors. Prog Neurobiol 130:29–70. atum and lobes 9 and 10 of the cerebellum: a method to Ross KC, Gubner NR, Tyndale RF, Hawk LW Jr, Lerman C, George distinguish dopamine D(3) from D(2) receptor sites. Synapse TP, Cinciripini P, Schnoll RA, Benowitz NL (2016) Racial differ - 65:467–478. ences in the relationship between rate of nicotine metabol- Lammertsma AA, Hume SP (1996) Simplified reference tissue ism and nicotine intake from cigarette smoking. Pharmacol model for PET receptor studies. Neuroimage 4:153–158. Biochem Behav 148:1–7. Le Foll B, Wilson AA, Graff A, Boileau I, Di Ciano P (2014a) Recent Rubinstein ML, Benowitz NL, Auerback GM, Moscicki AB (2008) methods for measuring dopamine D3 receptor occupancy Rate of nicotine metabolism and withdrawal symptoms in in vivo: importance for drug development. Front Pharmacol adolescent light smokers. Pediatrics 122:e643–e647. 5:161. Rusjan P, Mamo D, Ginovart N, Hussey D, Vitcu I, Yasuno F, Le Foll B, Guranda M, Wilson AA, Houle S, Rusjan PM, Wing VC, Tetsuya S, Houle S, Kapur S (2006) An automated method for Zawertailo L, Busto U, Selby P, Brody AL, George TP, Boileau I the extraction of regional data from PET images. Psychiatry (2014b) Elevation of dopamine induced by cigarette smoking: Res 147:79–89. novel insights from a [11C]-+-PHNO PET study in humans. Schnoll RA, Patterson F, Wileyto EP, Tyndale RF, Benowitz N, Neuropsychopharmacology 39:415–424. Lerman C (2009) Nicotine metabolic rate predicts successful Lerman C, Tyndale R, Patterson F, Wileyto EP, Shields PG, Pinto smoking cessation with transdermal nicotine: a validation A, Benowitz N (2006) Nicotine metabolite ratio predicts effi- study. Pharmacol Biochem Behav 92:6–11. cacy of transdermal nicotine for smoking cessation. Clin Schnoll RA, George TP, Hawk L, Cinciripini P, Wileyto P, Tyndale RF Pharmacol Ther 79:600–608. (2014) The relationship between the nicotine metabolite ratio Lerman C, Schnoll RA, Hawk LW Jr, Cinciripini P, George TP, and three self-report measures of nicotine dependence across Wileyto EP, Swan GE, Benowitz NL, Heitjan DF, Tyndale RF, sex and race. Psychopharmacology (Berl) 231:2515–2523. Group P-PR (2015) Use of the nicotine metabolite ratio as a Schoedel KA, Hoffmann EB, Rao Y, Sellers EM, Tyndale RF (2004) genetically informed biomarker of response to nicotine patch Ethnic variation in CYP2A6 and association of genetically or varenicline for smoking cessation: a randomised, double- slow nicotine metabolism and smoking in adult Caucasians. blind placebo-controlled trial. Lancet Respir Med 3:131–138. Pharmacogenetics 14:615–626. Li S, Yang Y, Hoffmann E, Tyndale RF, Stein EA (2017) CYP2A6 Shotbolt P, Tziortzi AC, Searle GE, Colasanti A, van der Aart J, genetic variation alters striatal-cingulate circuits, network Abanades S, Plisson C, Miller SR, Huiban M, Beaver JD, Gunn hubs, and executive processing in smokers. Biol Psychiatry RN, Laruelle M, Rabiner EA (2012) Within-subject comparison 81:554–563. of [(11)C]-(+)-PHNO and [(11)C]raclopride sensitivity to acute Malaiyandi V, Lerman C, Benowitz NL, Jepson C, Patterson F, amphetamine challenge in healthy humans. J Cereb Blood Tyndale RF (2006) Impact of CYP2A6 genotype on pretreat- Flow Metab 32:127–136. ment smoking behaviour and nicotine levels from and usage Singleton EG, Anderson LM, Heishman SJ (2003) Reliability and of nicotine replacement therapy. Mol Psychiatry 11:400–409. validity of the Tobacco Craving Questionnaire and validation Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018 512 | International Journal of Neuropsychopharmacology, 2018 of a craving-induction procedure using multiple measures of Tiffany ST, Drobes DJ (1991) The development and initial val- craving and mood. Addiction 98:1537–1546. idation of a questionnaire on smoking urges. Br J Addict Sofuoglu M, Herman AI, Nadim H, Jatlow P (2012) Rapid 86:1467–1476. nicotine clearance is associated with greater reward Tziortzi AC, Searle GE, Tzimopoulou S, Salinas C, Beaver JD, and heart rate increases from intravenous nicotine. Jenkinson M, Laruelle M, Rabiner EA, Gunn RN (2011) Imaging Neuropsychopharmacology 37:1509–1516. dopamine receptors in humans with [11C]-(+)-PHNO: dissec- St Helen G, Novalen M, Heitjan DF, Dempsey D, Jacob P 3rd, tion of D3 signal and anatomy. Neuroimage 54:264–277. Aziziyeh A, Wing VC, George TP, Tyndale RF, Benowitz NL Vaz LR, Coleman T, Cooper S, Aveyard P, Leonardi-Bee J; the SNAP (2012) Reproducibility of the nicotine metabolite ratio in trial team (2015) The nicotine metabolite ratio in pregnancy cigarette smokers. Cancer Epidemiol Biomarkers Prev measured by trans-3’-Hydroxycotinine to cotinine ratio: 21:1105–1114. characteristics and relationship with smoking cessation. Strasser AA, Benowitz NL, Pinto AG, Tang KZ, Hecht SS, Carmella Nicotine Tob Res 17:1318–1323. SG, Tyndale RF, Lerman CE (2011) Nicotine metabolite ratio Volkow ND, Fowler J, Wang G- J, Hitzemann R, Logan J, Schlyer predicts smoking topography and carcinogen biomarker J, Wolf AP (1993) Decreased dopamine D2 receptor availabil- level. Cancer Epidemiol Biomarkers Prev 20:234–238. ity is associated with reduced frontal metabolism in cocaine Tang DW, Hello B, Mroziewicz M, Fellows LK, Tyndale RF, Dagher abusers. Synapse 14:169–177. A (2012) Genetic variation in CYP2A6 predicts neural reactiv- Wang GJ, Smith L, Volkow ND, Telang F, Logan J, Tomasi D, Wong ity to smoking cues as measured using fMRI. Neuroimage CT, Hoffman W, Jayne M, Alia-Klein N, Thanos P, Fowler JS 60:2136–2143. (2012) Decreased dopamine activity predicts relapse in meth- Tanner JA, Novalen M, Jatlow P, Huestis MA, Murphy SE, Kaprio amphetamine abusers. Mol Psychiatry 17:918–925. J, Kankaanpaa A, Galanti L, Stefan C, George TP, Benowitz Wilson AA, McCormick P, Kapur S, Willeit M, Garcia A, Hussey NL, Lerman C, Tyndale RF (2015) Nicotine metabolite ratio D, Houle S, Seeman P, Ginovart N (2005) Radiosynthesis and (3-hydroxycotinine/cotinine) in plasma and urine by differ - evaluation of [11C]-(+)-4-propyl-3,4,4a,5,6,10b-hexahydro-2H- ent analytical methods and laboratories: implications for naphtho[1,2-b][1,4]oxazin-9-ol as a potential radiotracer for clinical implementation. Cancer Epidemiol Biomarkers Prev in vivo imaging of the dopamine D2 high-affinity state with 24:1239–1246. positron emission tomography. J Med Chem 48:4153–4160. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/6/503/4807487 by Ed 'DeepDyve' Gillespie user on 21 June 2018
International Journal of Neuropsychopharmacology – Oxford University Press
Published: Jan 13, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera