Kinetics of brain nicotine accumulation in dependent and nondependent smokers assessed with PET and cigarettes containing 11C-nicotine

Jed E Rose; Alexey G Mukhin; Stephen J Lokitz; Timothy G Turkington; Joseph Herskovic; Frederique M Behm; Sudha Garg; Pradeep K Garg

doi:10.1073/pnas.0909184107

. 2010 Mar 8;107(11):5190–5195. doi: 10.1073/pnas.0909184107

Kinetics of brain nicotine accumulation in dependent and nondependent smokers assessed with PET and cigarettes containing ¹¹C-nicotine

Jed E Rose ^a,¹, Alexey G Mukhin ^a, Stephen J Lokitz ^a,^b, Timothy G Turkington ^b, Joseph Herskovic ^a, Frederique M Behm ^b, Sudha Garg ^c, Pradeep K Garg ^c

PMCID: PMC2841893 PMID: 20212132

Abstract

Tobacco smoking is a chronic, relapsing disorder that constitutes one of the primary preventable causes of death in developed countries. Two of the popular hypotheses to explain the development and maintenance of strong nicotine dependence in cigarette smokers posit (i) a rapid brain nicotine accumulation during cigarette smoking and/or (ii) puff-associated spikes in brain nicotine concentration. To address these hypotheses, we investigated the dynamics of nicotine accumulation in the smoker's brain during actual cigarette smoking using PET with 3-s temporal resolution and ¹¹C-nicotine loaded into cigarettes. The results of the study, performed in 13 dependent smokers (DS) and 10 nondependent smokers (NDS), suggest that puff-associated spikes in the brain nicotine concentration do not occur during habitual cigarette smoking. Despite the presence of a puff-associated oscillation in the rate of nicotine accumulation, brain nicotine concentration gradually increases during cigarette smoking. The results further suggest that DS have a slower process of brain nicotine accumulation than NDS because they have slower nicotine washout from the lungs and that DS have a tendency to compensate for their slower rate of brain nicotine accumulation compared with NDS by inhaling a larger volume of smoke. For these reasons, smokers’ dependence on cigarette smoking, or the resistance of NDS to becoming dependent, cannot be explained solely by a faster brain nicotine accumulation.

Keywords: cigarette smoking, nicotine dependence, tobacco, addiction, lung

Tobacco smoking is a chronic, relapsing disorder that constitutes one of the leading preventable causes of death in developed countries. Smoking leads to the development of a strong dependency, and the efficacy of smoking cessation treatments is very low (1, 2). One vital issue in developing improved strategies to assist with smoking cessation is to understand the mechanisms that underlie nicotine dependence in cigarette smokers.

Nicotine is the one of the ingredients of cigarette smoke that is most closely linked to tobacco dependence (3). This alkaloid interacts with both central and peripheral neuronal nicotinic acetylcholine receptors (nAChRs). The nAChRs belong to the superfamily of ligand-gated ion channels and are composed of five protein subunits. To date, nine α-subunits (α2–α10) and three β-subunits (β2–β4) have been identified in the nervous system (reviewed in ref. 4). Most of these subunits may form a heteromeric complex, but others (α7–α9) appear to function predominantly as a homomeric group. High diversity in neuronal nAChR subunits can potentially lead to an enormous variety of these receptors in the nervous system.

After acute administration of nicotinic agonists, the nAChR channel complex is activated and becomes permeable for sodium, potassium, and calcium ions. Nonetheless, prolonged exposure of nAChRs to nicotinic agonists leads to desensitization of the receptors. The desensitization diminishes channel permeability and the capability of the receptors to be activated in response to subsequent administration of agonist. For nAChRs to recover from desensitization, it is necessary to wash out the nicotinic agonists. Both the desensitization and the recovery from desensitization of nAChRs are dynamic processes that require from seconds to minutes, depending on the receptor subtypes. The sensitivities of nAChRs to nicotine and to other nicotinic agonists, both in processes to be activated and those to be desensitized, are also dependent on the receptor subtypes. It should be noted that prolonged exposure of nAChRs to subthreshold concentrations of nicotinic agonists can cause the receptor to desensitize without its significant activation (4). As a result, the measured in vitro EC₅₀ values for activation (for nicotine, 0.5–100 μM) are in the range of at least one order of magnitude greater than the EC₅₀ values for desensitization (5, 6). Finally, extended exposure of nAChRs to nicotine (from several hours to days) results in up-regulation of the receptors. The sensitivity to nicotine and the extent of this up-regulation are also dependent on receptor subtype (7).

Taken together, the different nAChR subtypes may have different sensitivities to nicotine. The extent of the receptors’ activation, desensitization, re-sensitization, and up-regulation is dependent on the following factors: the receptor subtype, the amplitude and duration of exposure to nicotine, and the dynamics of nicotine concentration in the vicinity of receptors.

The results from tobacco smoking studies also suggest the importance of nicotine concentration dynamics in the manifestation of its pharmacological effects. For example, cigarette smoking has the fastest kinetics of nicotine accumulation in arterial blood as well as higher dependence compared with the use of other products that contain nicotine, such as nicotine gum and patches. The importance of the rate of drug administration for its subjective effects was demonstrated in human studies with cocaine (8) and methylphenidate (9). If it is true that faster brain nicotine accumulation is responsible for dependence on smoking, one can hypothesize that dependent smokers (DS) might have faster brain nicotine accumulation than nondependent smokers (NDS), which might lead to dependence.

The other special aspect of nicotine pharmacokinetics during smoking might be the existence of brief spikes in brain nicotine concentration associated with each puff from a cigarette (10, 11). Such fluctuations in nicotine concentration (fast onset and fast offset before the next puff) could explain how nAChRs can be activated during cigarette smoking without remarkable desensitization.

To investigate the dynamics of nicotine accumulation in the smoker's brain during actual cigarette smoking, we used PET with 3-s temporal resolution and ¹¹C-nicotine loaded into cigarettes. To test the hypothesis that DS have faster kinetics of brain nicotine accumulation, we performed our study on both dependent and nondependent groups of smokers.

Results

Under Typical Smoking Conditions (Interpuff Intervals <90 s), Puff-Associated Spikes in Brain Nicotine Concentration Do Not Occur.

Brain ¹¹C-nicotine accumulation was found to begin approximately 7 s after the radioactivity was detected in the mouth cavity (7.0 ± 1.5 s and 6.9 ± 1.2 s for DS and NDS, respectively). However, an inhaled dose (ID) of nicotine required 3 to 5 min to reach the maximal values of 4.7 ± 0.5 % ID/kg brain and 6.3 ± 0.7 % ID/kg brain for DS and NDS, respectively (Fig. 1A). The respective times to reach maximal accumulation (T_max) were 290 ± 30 s and 210 ± 40 s (Fig. 1B). Such T_max values suggest that with typical interpuff intervals of 15 to 90 s, the nicotine after each successive puff is “superimposed” on a brain nicotine concentration that is still increasing as a result of the previous puff, thereby excluding the possibility of puff-associated spikes (i.e., peaks and troughs) of nicotine concentration in the brain during cigarette smoking.

DS Have a Lower Brain Nicotine Accumulation Rate than NDS.

As shown in Fig. 1, we observed: (i) significantly lower nicotine concentrations in the brain of DS than those of NDS over the first 3 min (Fig. 1A); (ii) half-maximal accumulation (T_1/2) values of brain nicotine accumulation in DS that were 1.8 times longer than those in NDS (33 ± 4 s and 19 ± 3 s, respectively; P < 0.01; Fig. 1B); (iii) initial slopes of brain nicotine accumulation in DS that were 2.2 times smaller than those in NDS (0.17 ± 0.02% ID/kg brain/min and 0.37 ± 0.05% ID/kg brain/min, respectively; P < 0.001; Fig. 1B); and (iv) concentrations of ¹¹C-nicotine at 2 min after inhalation that were significantly lower in DS than in NDS for both gray and white brain matter (P < 0.02; Fig. 1C).

Slow Brain Nicotine Accumulation in DS Is a Consequence of Diminished Nicotine Washout from Their Lungs.

The key results that support this conclusion are summarized in Fig. 2 and include the following observations: First, nicotine washout from the lungs was significantly slower in DS compared with NDS. As evidence for this conclusion, (i) over the first 240 s, the residual fraction of the inhaled nicotine dose in the lung tissue was higher in DS versus NDS (P < 0.05; Fig. 2A); (ii) the T_1/2 of the nicotine washout in DS was almost three times that in NDS (89 ± 18 s and 27 ± 5 s, respectively; P < 0.01); (iii) the initial slope of the nicotine washout in DS was approximately one half that in NDS (2.1 ± 0.4 % ID/sec and 4.1 ± 0.4 % ID/sec, respectively; P < 0.002; Fig. 2B); and (iv) the calculated blood nicotine concentration in DS (Fig. 2C) was significantly lower over the first 17 s than that in NDS (P < 0.05). Second, there was a strong correlation (Fig. 2D) between the T_1/2 of the nicotine washout from the lung and the T_1/2 for nicotine accumulation in the brain (r = 0.9 and r_S = 0.8; P < 0.002 for both correlations). The observed T_1/2 values of the nicotine washout in DS are close to that (120 s) determined previously in a single subject after smoking of an entire cigarette containing ¹¹C-nicotine (12), but were much longer than that in rats (4 s) observed after ³H-nicotine was administered into the right heart (13).

The nature of prolonged retention of nicotine in the lungs of DS is not clear. It is interesting that similar prolonged retention in the lungs of smokers has been shown for ¹¹C-labeled clorgyline and deprenyl (14), which are irreversible inhibitors for monoamine oxidase A and monoamine oxidase B, respectively. Because both of these compounds as well as nicotine are organic cations, it is possible that the lungs of smokers have some common features for retaining organic cations (e.g., lower pH compared with the lung tissue of nonsmokers). If that is true, the distribution of other compounds (e.g., some anesthetics) to brain and other organs after inhalation or i.v. administration might be altered in smokers as a result of increased lung retention. This possibility merits further investigation.

Brain Nicotine Accumulation During Multiple Cigarette Puffs.

Assuming linearity and time invariance, the net brain concentration from multiple puffs may be expressed as a superimposition of the brain responses to each individual puff. With these assumptions, the brain nicotine concentration at time t [C(t)], expressed as the fraction of a total dose of inhaled nicotine, may be given as:

where Inline graphic characterizes a magnitude of the puff n, F(t) is a function describing the tissue response to a single puff, and t_i is the time of the puff n. These calculations are illustrated in Fig. S1A, where the averaged brain nicotine concentration curve, obtained after a single puff in DS (Fig. 1A), has been used for superimposition. Consistent with the results shown in Fig. S1, the kinetics of brain nicotine accumulation over an entire period of cigarette smoking, performed with the same puff magnitude and interpuff interval, can be closely approximated by a linear function. It should be noted that the absolute rate of brain nicotine accumulation can be increased both by an increase of the magnitude of inhaled nicotine dose (e.g., puff volume) and by shortening the interpuff interval (Fig. S1B).

Using the same approach as the one described earlier, we have calculated the individual brain nicotine accumulation curves for smoking an entire cigarette, carried out as 10 of the same puff volumes taken with 48-s interpuff intervals (assuming the same nicotine content in each puff). In line with our prediction, the brain nicotine concentrations in DS versus NDS (Fig. 3A) were significantly lower over the entire period of smoking (448 s; P < 0.05), and the overall rate of nicotine accumulation in DS was 1.4 times smaller than that in NDS (0.52 ± 0.06% total ID/kg/min and 0.71 ± 0.07% total ID/kg/min, respectively; P < 0.05).

Fig. 3. — Consistent with results from the study of brain nicotine accumulation after a single puff, the brain nicotine accumulation calculated for multiple puffs is slower in DS than in NDS. (A) Averaged brain nicotine accumulation curves calculated for the conditions of 10 puffs and 48-s interpuff intervals. Gray areas represent mean ± SEM. Gray lines show the time intervals when the difference between DS and NDS is statistically significant (P < 0.05); Inset shows the averaged slopes of nicotine accumulation over 7 min. (B) Examples of the brain nicotine accumulation curves calculated for conditions when the individual number of puffs per cigarette and interpuff intervals were measured during unrestricted smoking of Quest 1 cigarettes. Black dots show the time points when subsequent puffs were taken.

Puff-Associated Oscillation in the Rate of Brain Nicotine Accumulation.

It should be noted that, although the overall brain nicotine accumulation can be closely approximated by a linear function, there are still some puff-associated waves of deviation from a straight line in the calculated curve. To quantify these oscillations, we generated the nicotine accumulation curves for each participant using individual puff volume and interpuff intervals measured when smoking a cigarette during the screening session. For example, two pairs (one from a DS and one from an NDS) that have the smallest and the largest oscillation in each group are presented in Fig. 3B.

Fig. S3 A and B illustrates our further analysis of the curve shown in Fig. 3B (DS-1). As is evident, even small oscillations in nicotine accumulation are translated into pronounced oscillations in the rate of brain nicotine accumulation (the first derivative of accumulation). Between groups, comparisons of the average pre- and postpuff rates of brain nicotine accumulation, calculated using individual smoking topography data, suggest that DS have only half as large a postpuff rate of nicotine accumulation (P < 0.002), with no significant differences in the prepuff rates between groups. The post- to prepuff ratio values in DS and NDS reach 4.3 ± 0.5 and 18 ± 6, respectively, with statistically significant differences between groups (P < 0.02).

Discussion

This study has revealed the following three most important findings: (i) smokers do not experience puff-associated spikes in brain nicotine concentration; (ii) nicotine accumulation in the brain of DS is slower than in NDS; and (iii) this slow brain nicotine accumulation in DS is dependent on their diminished nicotine washout from the lungs compared with NDS.

Potential Limitation of the Use of PET for ¹¹C-Nicotine Studies.

To our knowledge, this is the first published study in which ¹¹C-nicotine loaded into cigarettes has been used with PET to assess the dynamics of nicotine accumulation in the human brain and lung during actual cigarette smoking. Previously ¹¹C-nicotine cigarettes were used to compare nicotine lung deposition from a nicotine inhaler and a cigarette (12). Preliminary results from a study of brain nicotine accumulation and lung radioactivity after smoking of ¹¹C-nicotine cigarettes were presented by Berridge and coworkers at the Annual Conference of Academy of Molecular Imaging in 2006, but these results have not yet been published. Although this approach has several limitations that require special consideration in the interpretation of study results, this technique appears to be the only way to measure nicotine dynamics in the human brain.

One of the major problems of using PET for ¹¹C-nicotine studies is that, because PET measures total tissue radioactivity, it therefore cannot distinguish the parent ¹¹C-nicotine from its radioactive products, which can be present as a result of metabolism or as a consequence of the breakdown of nicotine during cigarette combustion. Nonetheless, consistent with the early results obtained when ¹⁴C-nicotine was loaded into a cigarette (15), the major portion (76%) of the total radioactivity in mainstream smoke corresponds to parent ¹⁴C-nicotine and only a small fraction (24%) to the products of nicotine degradation. The majority (90%) of these degradation products was observed in mainstream vapor (not trapped on a Cambridge filter) and was presumably represented by ¹¹C-CO₂ and ¹¹C-CO (15).

We also should not expect to observe a significant level of ¹¹C-nicotine metabolism in the body over the first several minutes after inhalation because in such a case, the half-time of nicotine elimination in humans would be much less than the range of 100 to 150 min, as determined previously (16). In support of this, an earlier assessment of the ¹⁴C-cotinine (the primary metabolite of nicotine) after smoking a cigarette that contained ¹⁴C-nicotine (17) demonstrated that the concentrations of ¹⁴C-cotinine in arterial blood did not exceed one twentieth of the ¹⁴C-nicotine concentrations over the entire 10-min period of smoking (10 puffs). At 5 min after the end of smoking, the concentration of ¹⁴C-cotinine was four times smaller than that of ¹⁴C-nicotine. Similarly, at 2 and 4 min after i.v. administration of ¹¹C-nicotine, the fraction of unchanged compound in arterial plasma was represented by 95% and 75% of total plasma radioactivity, respectively (18). Despite the caveats just noted regarding the possible metabolism and breakdown of ¹¹C-nicotine during the smoking of radiolabeled cigarettes, our conclusions are warranted in view of the absence of a remarkable amount of ¹¹C-nicotine radioactive degradation products over the first minutes after smoke inhalation.

Cigarette Smokers Do Not Experience Puff-Associated Spikes in Brain Nicotine Concentration.

Our results from the study of brain radioactivity after smokers inhaled puffs containing ¹¹C-nicotine (Fig. 1) indicate that smokers have much slower brain nicotine kinetics than postulated earlier (10, 19). As a result, they do not experience puff-associated spikes because there is no decline in brain nicotine concentrations during typical (e.g., 45-s) interpuff intervals (Figs. 1A and 3).

The major reason for the absence of puff-associated spikes in brain nicotine concentration is insufficient cerebral perfusion. Although the brain is one of the most perfused organs in the body, the normal cerebral blood flow (CBF) is only 0.45 to 0.50 mL/g/min (0.0075–0.0083 mL/g/sec) (20–22), which is not sufficient to accomplish the fast washout nicotine from the brain and to sustain short-duration (tens of seconds) spikes in brain nicotine concentration. This conclusion can be illustrated by the following calculations. Let us assume that nicotine is delivered into the brain instantaneously and that there is no nicotine recirculation (i.e., the brain is always perfused by arterial blood without nicotine). Obviously, with these two conditions, the nicotine kinetics are the fastest possible, and Eq. S5 (SI Methods) can be reduced to the following:

After integration we have the following:

Using the literature data for the brain gray matter CBF of 0.6 mL/g/min and V_T of 3 (23), we can then calculate the following from Eq. 3: T_1/2, the time required to wash out 50% of nicotine from the brain is 208 s; the maximal rate of nicotine washout is 0.33% s⁻¹; and the fraction of washout nicotine over 45 s is 13.9% (which is consistent with the results of simulation modeling; SI Text 1 and Fig. S2A). In the case of CBF of 0.9 mL/g/min (1.5 times the normal CBF in gray matter), the respective values will be 139 s, 0.5% s⁻¹, and 20.2%. It should be noted that these calculations were done without the involvement of any data from the present study and that the conclusions from these calculations are in agreement with those from direct measurement of brain ¹¹C-nicotine kinetics.

Puff-Associated Oscillation in the Rate of Brain Nicotine Accumulation.

Based on the rationale presented here, puff-associated spikes in brain nicotine concentration do not and could not exist during regular cigarette smoking, even when there is a puff-associated fluctuation of nicotine in arterial blood. Instead of spikes in brain nicotine concentration, there is a remarkable puff-associated oscillation in the rate of brain nicotine accumulation, which we observed with interest (Fig. S3). If the rate theory of drug action, originally introduced by Paton in 1961 (24), is applicable to brain nAChR (25), we might expect puff-associated changes in the function of these receptors. Otherwise, cigarette smoking should be considered as a single, continuous source of nicotine treatment (over a period of smoking one cigarette), which can be mimicked by i.v. and possibly other routes of nicotine administration. In that case, during the smoking of one cigarette, the receptors are gradually occupied by nicotine and, consistent with conventional occupation theory, will be gradually activated and/or desensitized. Before the smoking of a new cigarette, nicotine is washed out from the receptors to some extent, allowing their partial recovery.

Nonetheless, because of the existence of puff-associated oscillations in the rate of brain nicotine accumulation, two possible mechanisms could be involved in the effect of nicotine on brain nAChRs during cigarette smoking. One mechanism is based on the receptor occupancy theory, and the other is based on the rate theory. Verification of the specific role of these two possible mechanisms in the effects of cigarette smoking is an important area for future investigations. Still, in view of the results of the present study, it appears that increased puff-associated oscillations in the rate of brain nicotine accumulation (which, consistent with rate theory, leads to increased receptor activation) is not a major component in dependence on smoking [as assessed by using the Fagerström test for nicotine dependence (FTND) questionnaire]. First, in both DS and NDS, individual subjects having both low and high oscillation can be found (Fig. 3B). Second, despite the intuitive expectation, the average amplitude of oscillation in DS is significantly smaller than that in NDS (Fig. S3 C–F).

The difference in the puff-associated oscillation in the rate of brain nicotine accumulation between DS and NDS is a result of the dynamics of brain nicotine accumulation being almost two times slower in DS versus NDS (Fig. 1). Consistent with the results presented in Fig. 2, this unexpected difference is a consequence of the release of nicotine from the lungs to the blood being almost twice as slow in DS versus NDS. The nature of the slower nicotine release from the lung in DS versus NDS is not clear. It is unlikely that this pronounced difference can be explained by differences in the nicotine metabolism or the presence of a small fraction of the radioactive nicotine degradation products in main stream smoke (as detailed earlier). Rather, the cumulative effects of exposure to cigarette smoke, or innate interindividual differences, may be responsible for the observed contrast in lung elimination rates between DS and NDS.

Relationship Between Nicotine Kinetics and Smoking History.

Calculating within each group, we found no statistically significant correlations (Pearson or Spearman) between any brain and lung nicotine kinetic parameters from age or smoking history parameters [FTND score, years of smoking, Federal Trade Commission (FTC) nicotine yield of the usual brand, number of cigarettes per day, and puff volume]. We did, however, identify a trend for a correlation between the initial rate of nicotine washout from the lungs and years of smoking in the DS (r = −0.44; r_S = −0.56; P = 0.132 and P = 0.051, respectively). Thus, it is possible that slow lung nicotine kinetics in DS can be explained at least partially by chronic cigarette smoking. If that is correct, the progressive decrease in the rate of nicotine washout from the lungs of smokers, followed by a decrease in the brain nicotine rate accumulation, could be at least one of the mechanisms in the development of tolerance to smoking.

It should be noted that, if novice smokers show similar nicotine dynamics to that of NDS, during smoking initiation a faster brain nicotine accumulation may be achieved, which could facilitate the acquisition of dependence in susceptible individuals. We are hopeful that future studies will address this hypothesis.

Maximal Values of Brain Nicotine Concentration During Cigarette Smoking.

In the present study, we deliberately expressed all nicotine concentrations as percentages of inhaled doses of nicotine for consistency with our measurements. Nonetheless, we can easily calculate the absolute concentration values for the wide range of inhaled nicotine doses if the assumption of linearity in the dose–concentration dependency is valid (SI Text 2). As an example, let us consider the following calculation for a regular cigarette with an FTC nicotine yield of 1.1 mg (10 puffs, 35 mL each). Assuming 10 puffs per cigarette and the puff volume as 43 mL (measured for DS in this study), the inhaled doses of nicotine will be 0.135 mg per puff and 1.35 mg per cigarette, or 0.83 μmol per puff and 8.3 μmol per cigarette. Provided that the maximal brain concentrations of ¹¹C-nicotine in a DS after a single puff and after an entire cigarette are 4.8% ID/kg tissue (Fig. 1A) and 4.3% ID/kg tissue (Fig. 3A), respectively, the maximal total brain nicotine concentrations can be calculated as 40 nM after a single puff and 357 nM after smoking a single cigarette.

For comparison with this example, we also calculated the boost in brain nicotine concentration using the arterial blood nicotine data obtained in DS after smokers had taken 10 puffs of 1.1 mg FTC nicotine cigarettes (26). In this study, the maximal boost in arterial concentration of nicotine was determined to be 27 ng/mL (167 nM). Assuming the V_T value for the entire brain as 2.6 [3.0 and 2.2 for gray and white matter, respectively (23)], the boost in total brain nicotine concentration was calculated to be 434 nM. Overall, the good agreement between this value and that obtained in the present study (357 nM) verifies the validity of our approach and our assumptions. The small difference (approximately 20%) between these values can be explained by overestimation of the nicotine-inhaled dose in the present study because of the presence in inhaled smoke of a small amount [approximately 24% (15)] of radioactive products of ¹¹C-nicotine degradation.

For heavy smokers, smoking cigarettes with higher nicotine yield and/or taking puffs greater than 48 mL volume and more than 10 puffs per cigarette, the maximal boost nicotine concentration in the brain during unrestricted smoking could be larger than that calculated here. In several studies that included measurement of arterial blood nicotine (19, 27, 28), investigators found that, on average, the maximal boost in blood nicotine concentration after one cigarette was in the range of 33 to 48 ng/mL. This concentration would result in a boost in brain nicotine concentration in the range of 520 to 770 nM. It should be noted that, assuming the absence of active transport of nicotine through the blood brain barrier and a V_T value for brain nicotine distribution of 2.6, the boost in concentration of free nicotine, available for interaction with nAChRs, corresponds to 0.38 of the total brain nicotine concentration. Based on this analysis, the post-cigarette boost concentration of free brain nicotine is approximately 240 nM on average. Therefore, as a result of smoking one cigarette, typically the concentration in free brain nicotine increases from 25 to 265 nM after overnight abstinence and from 200 to 465 nM during afternoon smoking.

DS Have a Tendency to Compensate for Their Slow Nicotine Kinetics.

If NDS inhale the same dose of nicotine as DS, their boost in brain nicotine concentration will be higher than that for DS by a factor of 1.4. Nonetheless, at least in our groups of smokers, NDS took smaller puff volumes than DS by a factor of 1.4 (30.0 ± 2.4 mL and 42.8 ± 2.8 mL, respectively; P < 0.003). Therefore, the between-groups difference in nicotine concentration boost, as well as the difference in the overall rate of brain nicotine accumulation after smoking an entire cigarette (Fig. 3A), become almost negligible. In our study, smoking topography was measured during the smoking of Quest 1 cigarettes (Vector Tobacco). If this difference in between-group smoking topography reflects the situation in real-life cigarette smoking, one might hypothesize that DS inhale a larger puff volume of smoke to compensate for their slow washout of nicotine from the lung, and in so doing, they gain their desired rate of brain nicotine accumulation. We recommend that future studies address this intriguing hypothesis.

Conclusion

The results of the present study suggest the following:

Puff-associated spikes in brain nicotine concentration do not and could not exist during usual habitual cigarette smoking. Despite the presence of a puff-associated oscillation in the rate of nicotine accumulation, brain nicotine concentration steadily increases during cigarette smoking, producing only a single spike in brain nicotine associated with smoking of an entire cigarette.
DS have a slower process of brain nicotine accumulation than NDS because they have slower nicotine washout from the lungs. For this reason, more rapid brain nicotine accumulation alone is not sufficient to maintain a dependency on cigarette smoking.

It should be noted that, even without discrete puff-associated spikes, the rapid brain accumulation of nicotine, which starts at approximately 7 s after inhalation, may be a factor leading to the relatively high addictiveness of cigarettes relative to other forms of nicotine administration (e.g., nicotine patch). Also, the absence of measurements of the onset of subjective rewarding effects of inhaled nicotine precluded reaching any conclusions about whether the rate of brain nicotine uptake is correlated with the rapidity with which nicotine's reinforcing effects are perceived. The elucidation of the specific role of the rate of brain nicotine accumulation in governing cigarette smoking behavior will continue to be an important subject for future investigation.

Methods

The design of this study was approved by the institutional review boards of Duke University Medical Center and Wake Forest University School of Medicine. All participants gave written informed consent after receiving an explanation of the study and its procedures.

Twenty-three otherwise healthy cigarette smokers participated in this study, including 13 DS and 10 NDS, with respective scores of ≥5 and 0 on the FTND (29,30). The average values (±SD) characterizing both groups of participants are shown in Table S1.

Each subject was asked to attend one screening and two research PET sessions on different days. In one PET session, the head of the subject was scanned after inhalation of a single puff of smoke from a cigarette containing ¹¹C-labeled (S)-nicotine and in the second session the chest of the subject was scanned after a similar inhalation. The ¹¹C-labeled (S)-nicotine was prepared from the precursor (S)-nor-nicotine according to previously published methods (18). After inhalation, a 12-minute PET scan (twenty 3-s frames, six 10-s frames, three 20-s frames, two 60-s frames, one 120-s frame, and one 240-s frame) was acquired using a GE Advance NXi scanner (GE Medical Systems). All image processes as well as kinetic modeling were performed using PMOD software (version 2.85; PMOD Technologies).

Two-sample two-tailed Student t tests were used for between-group comparisons. Correlational analyses were performed using both Pearson product–moment correlation and Spearman rank-order correlation analyses, yielding r and r_S values, respectively. If it is not specified, all group average values are presented as mean ± SEM.

Additional method details are provided in SI Methods.

Supplementary Material

Supporting Information

supp_107_11_5190__index.html^{(992B, html)}

Acknowledgments

We thank Holly C. Smith for PET imaging assistance; Richard C. Minton for assistance in radiosynthesis; Shannon Smith, Sarah Wildrick, and Wendy Roberts for assistance in conducting the study protocol; and Susan S. Vaupel for excellent editing. Research described in this article was supported by Philip Morris USA and Philip Morris International. The companies had no role in the design or conduct of the study, data analysis or publication of results.

Footnotes

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

This article contains supporting information online at www.pnas.org/cgi/content/full/0909184107/DCSupplemental.

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20.Binks AP, Cunningham VJ, Adams L, Banzett RB. Gray matter blood flow change is unevenly distributed during moderate isocapnic hypoxia in humans. J Appl Physiol. 2008;104:212–217. doi: 10.1152/japplphysiol.00069.2007. [DOI] [PubMed] [Google Scholar]
21.Okazawa H, Vafaee M. Effect of vascular radioactivity on regional values of cerebral blood flow: evaluation of methods for H(2)(15)O PET to distinguish cerebral perfusion from blood volume. J Nucl Med. 2001;42:1032–1039. [PubMed] [Google Scholar]
22.Muzic RF, Jr, Berridge MS, Friedland RP, Zhu N, Nelson AD. PET quantification of specific binding of carbon-11-nicotine in human brain. J Nucl Med. 1998;39:2048–2054. [PubMed] [Google Scholar]
23.Nybäck H, Halldin C, Ahlin A, Curvall M, Eriksson L. PET studies of the uptake of (S)- and (R)-[11C]nicotine in the human brain: difficulties in visualizing specific receptor binding in vivo. Psychopharmacology (Berl) 1994;115:31–36. doi: 10.1007/BF02244748. [DOI] [PubMed] [Google Scholar]
24.Paton WDM. A Theory of Drug Action Based on the Rate of Drug-Receptor Combination. Proc R Soc Lond B Biol Sci. 1961;154:21–69. [Google Scholar]
25.Domino EF. Tobacco smoking and nicotine neuropsychopharmacology: some future research directions. Neuropsychopharmacology. 1998;18:456–468. doi: 10.1016/S0893-133X(97)00193-0. [DOI] [PubMed] [Google Scholar]
26.Gourlay SG, Benowitz NL. Arteriovenous differences in plasma concentration of nicotine and catecholamines and related cardiovascular effects after smoking, nicotine nasal spray, and intravenous nicotine. Clin Pharmacol Ther. 1997;62:453–463. doi: 10.1016/S0009-9236(97)90124-7. [DOI] [PubMed] [Google Scholar]
27.Guthrie SK, Ni L, Zubieta JK, Teter CJ, Domino EF. Changes in craving for a cigarette and arterial nicotine plasma concentrations in abstinent smokers. Prog Neuropsychopharmacol Biol Psychiatry. 2004;28:617–623. doi: 10.1016/j.pnpbp.2004.01.005. [DOI] [PubMed] [Google Scholar]
28.Shinohara T, et al. Acute effects of cigarette smoking on global cerebral blood flow in overnight abstinent tobacco smokers. Nicotine Tob Res. 2006;8:113–112. doi: 10.1080/14622200500431759. [DOI] [PubMed] [Google Scholar]
29.Fagerström KO. Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addict Behav. 1978;3:235–341. doi: 10.1016/0306-4603(78)90024-2. [DOI] [PubMed] [Google Scholar]
30.Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. The Fagerström test for nicotine dependence: a revision of the Fagerström tolerance questionnaire. Br J Addict. 1991;86:1119–1127. doi: 10.1111/j.1360-0443.1991.tb01879.x. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information

supp_107_11_5190__index.html^{(992B, html)}

0909184107_pnas.200909184SI.pdf^{(276.6KB, pdf)}

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[r12] 12.Lunell E, Bergström M, Antoni G, Långström B, Nordberg A. Nicotine deposition and body distribution from a nicotine inhaler and a cigarette studied with positron emission tomography. Clin Pharmacol Ther. 1996;59:593–594. doi: 10.1016/S0009-9236(96)90188-5. [DOI] [PubMed] [Google Scholar]

[r13] 13.Brewer BG, Roberts AM, Rowell PP. Short-term distribution of nicotine in the rat lung. Drug Alcohol Depend. 2004;75:193–198. doi: 10.1016/j.drugalcdep.2004.02.011. [DOI] [PubMed] [Google Scholar]

[r14] 14.Logan J, Fowler JS. Evidence for reduced arterial plasma input, prolonged lung retention and reduced lung monoamine oxidase in smokers. Nucl Med Biol. 2005;32:521–529. doi: 10.1016/j.nucmedbio.2005.03.004. [DOI] [PubMed] [Google Scholar]

[r15] 15.Houseman TH. Studies of cigarette smoke transfer using radioisotopically labeled tobacco constituents. Part II: the transference of radioisotopically labeled nicotine to cigarette smoke. Beitr Tabakforsch. 1973;7:142–147. [Google Scholar]

[r16] 16.Hukkanen J, Jacob P, 3rd, Benowitz NL. Metabolism and disposition kinetics of nicotine. Pharmacol Rev. 2005;57:79–115. doi: 10.1124/pr.57.1.3. [DOI] [PubMed] [Google Scholar]

[r17] 17.Armitage AK, et al. Absorption and metabolism of nicotine from cigarettes. BMJ. 1975;4:313–316. doi: 10.1136/bmj.4.5992.313. [DOI] [PMC free article] [PubMed] [Google Scholar]

[r18] 18.Halldin C, Någren K, Swahn CG, Långström B, Nybäck H. (S)- and (R) [11C]nicotine and the metabolite (R/S)-[11C]cotinine. Preparation, metabolite studies and in vivo distribution in the human brain using PET. Int J Rad Appl Instrum B. 1992;19:871–880. doi: 10.1016/0883-2897(92)90173-v. [DOI] [PubMed] [Google Scholar]

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[r22] 22.Muzic RF, Jr, Berridge MS, Friedland RP, Zhu N, Nelson AD. PET quantification of specific binding of carbon-11-nicotine in human brain. J Nucl Med. 1998;39:2048–2054. [PubMed] [Google Scholar]

[r23] 23.Nybäck H, Halldin C, Ahlin A, Curvall M, Eriksson L. PET studies of the uptake of (S)- and (R)-[11C]nicotine in the human brain: difficulties in visualizing specific receptor binding in vivo. Psychopharmacology (Berl) 1994;115:31–36. doi: 10.1007/BF02244748. [DOI] [PubMed] [Google Scholar]

[r24] 24.Paton WDM. A Theory of Drug Action Based on the Rate of Drug-Receptor Combination. Proc R Soc Lond B Biol Sci. 1961;154:21–69. [Google Scholar]

[r25] 25.Domino EF. Tobacco smoking and nicotine neuropsychopharmacology: some future research directions. Neuropsychopharmacology. 1998;18:456–468. doi: 10.1016/S0893-133X(97)00193-0. [DOI] [PubMed] [Google Scholar]

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[r28] 28.Shinohara T, et al. Acute effects of cigarette smoking on global cerebral blood flow in overnight abstinent tobacco smokers. Nicotine Tob Res. 2006;8:113–112. doi: 10.1080/14622200500431759. [DOI] [PubMed] [Google Scholar]

[r29] 29.Fagerström KO. Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addict Behav. 1978;3:235–341. doi: 10.1016/0306-4603(78)90024-2. [DOI] [PubMed] [Google Scholar]

[r30] 30.Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. The Fagerström test for nicotine dependence: a revision of the Fagerström tolerance questionnaire. Br J Addict. 1991;86:1119–1127. doi: 10.1111/j.1360-0443.1991.tb01879.x. [DOI] [PubMed] [Google Scholar]

PERMALINK

Kinetics of brain nicotine accumulation in dependent and nondependent smokers assessed with PET and cigarettes containing ¹¹C-nicotine

Jed E Rose

Alexey G Mukhin

Stephen J Lokitz

Timothy G Turkington

Joseph Herskovic

Frederique M Behm

Sudha Garg

Pradeep K Garg

Abstract

Results

Under Typical Smoking Conditions (Interpuff Intervals <90 s), Puff-Associated Spikes in Brain Nicotine Concentration Do Not Occur.

Fig. 1.

DS Have a Lower Brain Nicotine Accumulation Rate than NDS.

Slow Brain Nicotine Accumulation in DS Is a Consequence of Diminished Nicotine Washout from Their Lungs.

Fig. 2.

Brain Nicotine Accumulation During Multiple Cigarette Puffs.

Fig. 3.

Puff-Associated Oscillation in the Rate of Brain Nicotine Accumulation.

Discussion

Potential Limitation of the Use of PET for ¹¹C-Nicotine Studies.

Cigarette Smokers Do Not Experience Puff-Associated Spikes in Brain Nicotine Concentration.

Puff-Associated Oscillation in the Rate of Brain Nicotine Accumulation.

Relationship Between Nicotine Kinetics and Smoking History.

Maximal Values of Brain Nicotine Concentration During Cigarette Smoking.

DS Have a Tendency to Compensate for Their Slow Nicotine Kinetics.

Conclusion

Methods

Supplementary Material

Acknowledgments

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Cite

Add to Collections

PERMALINK

Kinetics of brain nicotine accumulation in dependent and nondependent smokers assessed with PET and cigarettes containing 11C-nicotine

Jed E Rose

Alexey G Mukhin

Stephen J Lokitz

Timothy G Turkington

Joseph Herskovic

Frederique M Behm

Sudha Garg

Pradeep K Garg

Abstract

Results

Under Typical Smoking Conditions (Interpuff Intervals <90 s), Puff-Associated Spikes in Brain Nicotine Concentration Do Not Occur.

Fig. 1.

DS Have a Lower Brain Nicotine Accumulation Rate than NDS.

Slow Brain Nicotine Accumulation in DS Is a Consequence of Diminished Nicotine Washout from Their Lungs.

Fig. 2.

Brain Nicotine Accumulation During Multiple Cigarette Puffs.

Fig. 3.

Puff-Associated Oscillation in the Rate of Brain Nicotine Accumulation.

Discussion

Potential Limitation of the Use of PET for 11C-Nicotine Studies.

Cigarette Smokers Do Not Experience Puff-Associated Spikes in Brain Nicotine Concentration.

Puff-Associated Oscillation in the Rate of Brain Nicotine Accumulation.

Relationship Between Nicotine Kinetics and Smoking History.

Maximal Values of Brain Nicotine Concentration During Cigarette Smoking.

DS Have a Tendency to Compensate for Their Slow Nicotine Kinetics.

Conclusion

Methods

Supplementary Material

Acknowledgments

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Kinetics of brain nicotine accumulation in dependent and nondependent smokers assessed with PET and cigarettes containing ¹¹C-nicotine

Potential Limitation of the Use of PET for ¹¹C-Nicotine Studies.