Context Greater prefrontal cortex and anterior cingulate cortex monoamine oxidase A (MAO-A) binding is associated with depressed mood. Substances in cigarette smoke, such as harman, inhibit MAO-A, and cigarette withdrawal is associated with depressed mood. Dysphoria during cigarette withdrawal predicts relapse. It is unknown whether MAO-A binding increases during early cigarette withdrawal.
Objectives To measure prefrontal and anterior cingulate cortex MAO-A binding during acute cigarette withdrawal and to assess the relationship with smoking severity, plasma levels of harman, and severity of depression.
Design Study via positron emission tomography of healthy control and cigarette-smoking individuals.
Patients Twenty-four healthy nonsmoking and 24 otherwise healthy cigarette-smoking individuals underwent positron emission tomography with harmine labeled with carbon 11. Healthy nonsmoking individuals underwent scanning once. Cigarette-smoking individuals underwent scanning after acute withdrawal and after active cigarette smoking. Cigarette smoking was heavy (≥25 cigarettes per day) or moderate (15-24 cigarettes per day).
Setting Tertiary care psychiatric hospital.
Main Outcome Measure An index of MAO-A density, MAO-A VT, was measured in the prefrontal and anterior cingulate cortices.
Results In heavy-smoking individuals, prefrontal and anterior cingulate cortex MAO-A VT was greater during withdrawal (23.7% and 33.3%, respectively; repeated-measures multivariate analysis of variance, F1,22 = 25.58, P < .001). During withdrawal from heavy smoking, prefrontal and anterior cingulate cortex MAO-A VT was greater than in healthy controls (25.0% and 25.6%, respectively; multivariate analysis of variance, F2,33 = 6.72, P = .004). The difference in MAO-A VT in the prefrontal cortex and anterior cingulate cortex between withdrawal and active, heavy smoking covaried with change in plasma harman levels in the prefrontal cortex and anterior cingulate cortex (multivariate analysis of covariance, F1,10 = 9.97, P = .01). The change in MAO-A VT between withdrawal and active, heavy smoking also covaried with severity of depression (multivariate analysis of covariance, F1,10 = 11.91, P = .006).
Conclusions The increase in prefrontal and anterior cingulate cortex MAO-A binding and associated reduction in plasma harman level represent a novel, additional explanation for depressed mood during withdrawal from heavy cigarette smoking. This finding resolves a longstanding paradox regarding the association of cigarette smoking with depression and suicide and argues for additional clinical trials on the effects of MAO-A inhibitors on quitting heavy cigarette smoking.
Cigarette smoking is a major public health problem: it is the second leading cause of preventable death and an important risk factor for coronary artery disease, lung disease, suicide, and cancer.1-3 Prevalence rates are high, typically ranging from 10% to 50%, depending on the country.2 Although many people who smoke cigarettes would like to quit, the effects of withdrawal frequently lead to relapse. Relapse is particularly problematic in early withdrawal because 50% of people relapse within the first 3 days of quitting.4,5
Most biological conceptualizations of early cigarette withdrawal focus on abnormal modulation by nicotine on dopamine-releasing neurons projecting from the ventral tegmental area to the ventral striatum.6-8 This model is important because it has been applied in therapeutic interventions, which, when combined with therapy, achieve 6-month abstinence rates of as high as 40%.5,9 However, other neural targets that may be important in cigarette withdrawal are affected by cigarette smoke. For example, several substances in cigarette smoke bind to monoamine oxidase A (MAO-A).10,11 Moreover, a study using carbon 11–labeled clorgyline positron emission tomography (PET)12 found that cigarette smoking was associated with globally reduced MAO-A binding in active-smoking participants compared with nonsmoking control individuals in a between-group design.
Monoamine oxidase A binding, particularly in the prefrontal and anterior cingulate cortices, is strongly implicated in affect regulation.13-19 Negative affect is an important component of cigarette withdrawal because its severity is strongly predictive of relapse.20-22 Monoamine oxidase A has a functional role tightly related to mood because it is an enzyme that metabolizes serotonin, norepinephrine, and dopamine.23,24 Depletion of these monoamines is associated with depressed mood.25-29 In addition, elevations in MAO-A binding in affect modulating regions, particularly the prefrontal cortex and anterior cingulate cortex, occur during major depressive episodes, before recurrence of major depressive episodes, and shortly after pregnancy during postpartum blues (ie, when symptoms are within healthy range).13-15 Conversely, MAO-A inhibition is a well-established property for a longstanding class of antidepressants.
Although it is often described that MAO-A binding is reduced in those who smoke cigarettes irrespective of their active smoking or withdrawal state, there is reason to suspect that regional MAO-A binding may change between active smoking and withdrawal because the plasma half-life of the MAO-A–binding substances found in cigarette smoke is short. For example, harman and norharman are 2 substances present in cigarette smoke, and their plasma half-lives are 70 and 50 minutes, respectively, in humans.30 Therefore, during acute cigarette withdrawal, it is possible that these substances quickly leave the plasma and then the brain, resulting in a rapid elevation in MAO-A binding. Whether this sequence of events occurs is uncertain because some brain-penetrant substances clear from plasma much faster than from the brain.31 Currently, it is unknown whether MAO-A binding increases during acute cigarette withdrawal because MAO-A binding has not been investigated during withdrawal, to our knowledge.
Positron emission tomography with carbon 11–labeled harmine ([11C]harmine) is an excellent method to measure changes in brain MAO-A binding. This radiotracer has high brain uptake, selective binding, reversible binding, and metabolites that are not brain penetrant.32-34 The main hypothesis of this study is that MAO-A binding increases during acute cigarette withdrawal in regions implicated in affect regulation, such as the prefrontal cortex and the anterior cingulate cortex. The second hypothesis is that the anticipated increase in MAO-A binding during acute withdrawal will be greater in those who smoke heavily compared with those who smoke moderately. The third hypothesis is that the anticipated increase in prefrontal and anterior cingulate cortex MAO-A binding during acute withdrawal will be greater in those who have greater reductions in plasma levels of harman and norharman, 2 MAO-A brain-penetrant substances present in cigarette smoke with reasonably high affinity for MAO-A.10,35 The fourth hypothesis is that given the inverse relationship between MAO-A binding and mood,13-15 the increase in MAO-A binding in the prefrontal and anterior cingulate cortices will be greater in those who experience more severe depression during acute cigarette withdrawal.
Twenty-four healthy nonsmoking individuals (mean [SD] age, 33.2 [8.3]) and 24 individuals who smoke cigarettes but are otherwise healthy (mean [SD] age, 36 [6.7]) were recruited. Some of the nonsmoking participants (n = 24) were described in an earlier study.14 Participants were aged 18 to 50 years. Demographics are listed in Table 1. For each study participant, written consent was obtained after the procedures had been fully explained. The study and recruitment procedures were approved by the Research Ethics Board for Human Subjects at the Centre for Addiction and Mental Health, University of Toronto.
The severity of smoking was classified as moderate for those individuals smoking 15 to 24 cigarettes per day and as heavy for those smoking 25 cigarettes per day or more. To verify smoking status, scores on the Fagerström Test for Nicotine Dependence36,37 and the Nicotine Dependence Syndrome Scale38 were recorded. In addition, the exhaled carbon monoxide level (MicroSmokerlyzer; Bedfont Scientific Ltd, Kent, England) at the initial visit was taken, and a cutoff of 10 ppm was applied.7 All participants were physically healthy and had no history of neurotoxin use. Women in perimenopause or menopause were excluded. Healthy participants were screened to rule out any Axis I disorders, and participants who smoke cigarettes were screened to rule out lifetime history of Axis I disorders other than cigarette abuse or dependence using the Structured Clinical Interview for DSM-IV.39 All were screened to rule out borderline and antisocial personality disorder using the Structured Clinical Interview for DSM-IV for Axis II disorders.40 All participants underwent a urine drug test at screening, and on each day they underwent a scan via [11C]harmine PET. Those with positive results for other substances were excluded.
All study participants had no history of psychotropic medication use and had not taken over-the-counter medications for at least 1 month before scanning. Participants were required not to drink tea or coffee on the day of scanning. Because this latter criterion is difficult for those who drink a lot of coffee, only those who drink fewer than 3 cups of tea or coffee per day were enrolled. Given that some MAO-A inhibitor substances are found in some kinds of alcohol, participants were required not to drink any alcohol the day before and the day of scanning.
Healthy study participants underwent a single scan via [11C]harmine PET. Cigarette-smoking study participants underwent 2 scans via [11C]harmine PET, separated by a minimum of 1 month to allow healing from the arterial catheter insertion.
Scanning for cigarette-smoking individuals occurred during cigarette withdrawal or active smoking, and the order was randomized. During the day of active smoking, participants smoked on a regular schedule at a rate to match the number of cigarettes smoked daily. During the withdrawal day, participants stopped smoking cigarettes 8 hours before scanning via PET. Otherwise, the daily protocol was the same for both conditions. To verify compliance, participants were accompanied by a research coordinator for 8 hours before scanning via PET. During the time before scanning at 0, 2, 4, 6, and 8 hours before scanning, 10-cm visual analog scales (VASs) for mood (ie, happy-depressed), energy (ie, most-least), and anxiety (ie, relaxed-tense) and the Urge to Smoke Scale, an analog scale (range, 1-7) with 10 craving-related questions, were completed.41 For the VAS, participants were instructed to draw a vertical line crossing the 10-cm linear scale at the point corresponding to the strength of their experience of the given dimension of the mood/energy state. As part of the instruction process, participants were asked to focus on their current internal state and to avoid thinking about recent life stressors or daily stressors. They also were asked to focus on their internal state at the moment of doing the VAS and not their state earlier in the day.
Before scanning via PET, plasma measurements of several MAO-A–binding substances (ie, harman, norharman, harmol, harmine, and 2-napthylamine) were measured using high-performance liquid chromatography with mass spectroscopy. To validate the assay for each substance, purchased standards were measured in duplicate to verify reliability and sensitivity. Harman and norharman are the most commonly reported MAO-A inhibitors found in cigarette smoke.42 Harmol is often detected in plants that contain harman and norharman.43 It was reported that harman sometimes may be metabolized in rodents to become harmine,44 which has a high affinity for MAO-A (2 nM).32 2-Napthylamine is found in high concentrations in cigarette smoke and has a moderate affinity for MAO-A (52μM).11
A dose of 370 MBq of intravenous [11C]harmine was administered as a bolus for each scan via PET. An automatic blood sampling system was used to measure arterial blood radioactivity continuously for the first 10 minutes. Manual samples were obtained at 2.5, 7.5, 15.0, 20.0, 30.0, 45.0, 60.0, and approximately 90.0 minutes after injection. The radioactivity in whole blood and plasma was measured, as described previously.33 Frames were acquired as follows: 15 frames of 1 minute each, then 15 frames of 5 minutes each. The [11C]harmine was of high radiochemical purity (98.91% [1%]; n = 55) and high specific activity (1545.64 [820.55] mCi/μmol at the time of injection).
The images via PET were obtained using a High Resolution Research Tomograph PET camera (in-plane resolution; full width at half maximum, 3.1 mm; 207 axial sections of 1.2 mm; Siemens Molecular Imaging, Knoxville, Tennessee), in the manner described previously.14
For the region of interest (ROI) method, each participant underwent magnetic resonance imaging (GE Signa 1.5-T scanner; fast spoiled gradient echo, T1-weighted image; x, y, z voxel dimensions, 0.78, 0.78, and 1.5 mm; GE Medical Systems, Milwaukee, Wisconsin). The ROIs were determined on magnetic resonance images that were coregistered to each summed image obtained via [11C]harmine PET using a mutual information algorithm.45 The ROIs were determined using a semiautomated method in which regions on a template magnetic resonance image are transposed onto the individual image via a series of transformation and deformation parameters that match the template image to the coregistered image,46,47 followed by selection of gray matter voxels within the ROI.48,49 The location of the ROI was verified by visual assessment of the ROI on the coregistered and summated image obtained via [11C]harmine PET.
The ROIs selected included those for which abnormal function, neurochemistry, or MAO-A binding has been implicated in mood regulation and/or mood disorders.13-19 The ROIs sampled included the whole prefrontal cortex, the anterior cingulate cortex (ie, Brodmann areas 24, part of 32), the dorsal putamen, the ventral striatum,50 the thalamus, the anterior temporal cortex (ie, Brodmann areas 38, part of 20, 21, and 22), the midbrain, and the hippocampus.
One can measure MAO-A VT via [11C]harmine PET. The MAO-A VT represents the total tissue binding of [11C]harmine at equilibrium, of which 85% is specifically binding to MAO-A. Hence, changes in MAO-A VT may be interpreted as representing changes in harmine binding to MAO-A. The VT can be expressed in terms of kinetic rate parameters as follows: VT = (K1/k2) (k3/k4) + (K1/k2), where K1 and k2 are influx and efflux rate parameters for radiotracer passage across the blood-brain barrier and k3 and k4 describe the radioligand transfer between the free and nonspecific compartment and the specific binding compartment. Among different groups, K1/k2 is similar (for further details, see Ginovart et al33). One may validly and reliably measure VT with an unconstrained 2-tissue compartment model or the Logan model with arterial sampling (for which the underestimate of VT is negligible); we applied the latter technique in our study.33 This method has been described in greater detail elsewhere.14,33
We performed 4 main analyses. The first was a repeated-measures multivariate analysis of variance (MANOVA) applied to determine the effect of condition (ie, active smoking vs withdrawal) and smoking severity (ie, heavy vs moderate) on prefrontal and anterior cingulate cortex MAO-A VT in the entire cigarette-smoking group. The second was a MANOVA to assess the group effect (ie, withdrawal from smoking vs health) on prefrontal and anterior cingulate cortex MAO-A VT in the heavy-smoking and healthy nonsmoking groups. The third was a repeated-measures multivariate analysis of covariance (MANCOVA) in the heavy–cigarette-smoking group with harman plasma level as the covariate and conditions of active smoking and withdrawal on prefrontal and anterior cingulate cortex MAO-A VT. The fourth was a repeated-measures MANCOVA in the heavy–cigarette-smoking group with change in the depression VAS as the covariate and conditions of active smoking and withdrawal on prefrontal and anterior cingulate cortex MAO-A VT. For the fourth analysis, the covariate reflecting change in the depression VAS was determined as follows: the change score on the depression VAS for each protocol day was defined as the VAS score before scanning minus the VAS score at t = 0. The difference in the change score between active smoking and withdrawal days was the covariate applied in the fourth main analysis.
Cigarette-smoking habits of the cigarette-smoking group
Twelve individuals comprised the moderate-smoking subgroup and 12 comprised the heavy-smoking subgroup. The mean (SD) number of cigarettes smoked per day was 20.89 (−2.42) and 40.00 (−7.69), respectively, in these groups. Exhaled carbon monoxide levels were 25.70 (−10.74) and 6.58 (3.78) ppm during active-smoking days and 38.00 (−13.64) and 12.00 (−7.62) ppm during withdrawal days in the moderate- and heavy-smoking groups, respectively. In our sample, the ratio of cigarette smoking in men to women was 7:1, which was consistent with the sex frequencies of cigarette smoking for moderate and heavy levels among the ethnicities represented in Toronto.2,51
Difference in mao-a vt between the active smoking state and withdrawal
The predominant change was an elevation in MAO-A VT during withdrawal in the heavy-smoking subgroup not present in the moderate-smoking subgroup (Figure 1 and Table 2). The magnitude of this change was 23.7% and 33.3% in the prefrontal and anterior cingulate cortices, respectively. Repeated-measures MANOVA found a highly significant interaction between smoking severity (ie, moderate or heavy smoking) and condition (ie, measurement of MAO-A VT during active smoking and withdrawal) in the prefrontal cortex and anterior cingulate cortex regions (F1,22 = 25.58, P < .001). Repeated-measures ANOVA confirmed similar results in the individual regions of an interaction between smoking severity and condition (ie, active smoking and withdrawal) on MAO-A VT, the prefrontal cortex (F1,22 = 20.9, P < .001), and the anterior cingulate cortex (F1,22 = 28.09, P < .001). Repeated-measures MANOVA also found a significant interaction between smoking severity and condition (ie, active smoking or withdrawal) on MAO-A VT for all the regions assayed (F1,22 = 28.24, P < .001), and in these additional regions, the findings were confirmed with a repeated-measures ANOVA in each region (interaction between smoking severity and condition, repeated-measures ANOVA, F1,22 = 11.16-28.87, P = .003 to P < .001).
Repeated-measures MANOVA found no significant effect of condition on the prefrontal and anterior cingulate cortex MAO-A VT (F1,11 = 3.195, P = .10) within the moderate-smoking group. Similarly, no effect of condition was present on MAO-A VT within all the brain regions (repeated-measures MANOVA, F1,11 = 3.292, P = .10).
Difference in mao-a vt between the withdrawal-from-heavy-smoking and healthy nonsmoking states
Prefrontal and anterior cingulate cortex MAO-A VT levels were significantly greater in the withdrawal state of those in the heavy-smoking subgroup compared with healthy nonsmoking controls (MANOVA, F2,33 = 6.72, P = .004). This finding was confirmed in each region (independent t test, t34 = 3.61 and 3.72, P = .001 and P = .001, respectively). The magnitudes were 25.0% and 25.6% greater in the withdrawal state from heavy cigarette smoking compared with healthy nonsmoking individuals. Greater MAO-A VT during withdrawal from heavy cigarette smoking compared with healthy nonsmoking controls also was found in all the brain regions assayed (MANOVA, F7,28 = 3.25, P = .01). Most other individual regions also were significantly different (independent t test, t34 = 3.39-1.66, P = .002 -.10, respectively) (Figure 2).
RELATIONSHIP BETWEENβ-CARBOLINE LEVELS AND CHANGE IN MAO-A VT IN THE HEAVY-SMOKING GROUP
Harman and norharman levels were detectable (ie, >5 pg/mL) in all 12 study participants in the heavy–cigarette-smoking group during the active-smoking state, but levels of harmine, harmol, and 2-napthylamine were not detectable (ie,≥5 pg/mL) during the active-smoking state. The reduction in harman levels between active-smoking and withdrawal states significantly covaried with the change in prefrontal and anterior cingulate cortex MAO-A VT (repeated-measures MANCOVA, F1,10 = 9.97, P = .01), which was confirmed by correlations within the individual regions (r = 0.71, P = .009, and r = 0.68, P = .02, respectively) (Figure 3). The reduction in norharman between active smoking and withdrawal states did not significantly covary with the change in prefrontal and anterior cingulate cortex MAO-A VT (MANCOVA, F1,10 = 1.67, P = .23).
Relationship between mood changes, rating scales of state, and change in mao-a v t in heavy-smoking group
The change toward depression on the VAS was found in the withdrawal day and the active-smoking day. The difference in this change score significantly covaried with the increase in MAO-A VT within the prefrontal cortex and anterior cingulate cortex in participants in the heavy-smoking subgroup (repeated-measures MANCOVA, F1,10 = 11.91, P = .006; prefrontal cortex: r = 0.74, P = .006; anterior cingulate cortex: r = 0.70, P = .01) (Figure 4). A similar analysis for the other VAS scores was not significant (energy: MANCOVA, F1,10 = 2.57, P = .14; anxiety: MANCOVA, F1,10 = 0.01, P = .92).
Ours is the first study, to our knowledge, to measure brain MAO-A binding in acute cigarette withdrawal. Prefrontal and anterior cingulate cortex MAO-A VT levels increased during withdrawal in the heavy-smoking group but not in the moderate-smoking group. In those who smoked heavily, prefrontal and anterior cingulate cortex MAO-A VT levels increased during withdrawal such that the levels of MAO-A VT were greater than those in healthy controls. The magnitude of increase in MAO-A VT in the prefrontal and anterior cingulate cortices during withdrawal was significantly correlated with the shift in VAS scores toward depressed mood in those who smoke heavily. The increase in MAO-A VT level also correlated with the decline in the MAO-A–binding substance harman in those who smoke heavily. Plasma levels of 3 other MAO-A–binding substances were extremely low. These results have significant implications for quitting heavy smoking and for understanding what has previously appeared to be a paradoxical association of cigarette smoking with major depressive disorder and suicide. Understanding the neurobiology of heavy cigarette smoking is important because those who smoke heavily are much more likely to have major depressive disorder and to experience medical complications resulting from cigarette smoking.52,53
The increase in prefrontal and anterior cingulate cortex MAO-A VT during withdrawal from heavy smoking was robust and highly significant. The process of a rapid change in available binding is important because substances with greater addictiveness are more rapidly removed from target sites.7,54 A plausible explanation for the MAO-A VT changes during cigarette withdrawal from heavy smoking is that rapid loss of harman during acute cigarette withdrawal lead to an increase in available regional MAO-A binding. The relationship between the increase in MAO-A VT and greater depression may be explained by the inverse relationship between MAO-A levels and metabolism rate of monoamines because abrupt decreases in serotonin, norepinephrine, and dopamine are consistently associated with depressed mood,26-29 and elevated MAO-A VT levels, particularly in the prefrontal and anterior cingulate cortices, are consistently associated with states that generate low mood, such as major depressive episodes, postpartum blues, and predisposition to recurrence of major depressive episodes.13-15 Subregions of the prefrontal cortex and anterior cingulate cortex participate in interpreting experiences optimistically or pessimistically, including recalled and anticipated experiences.55-57 Alterations in extracellular serotonin modulate this optimism and pessimism, and markers associated with ongoing decreased serotonin release in these regions are associated with greater pessimism.58-60 Subregions of the prefrontal cortex and/or anterior cingulate cortex also participate in the recall of emotional material and the interpretation of the valence of perceptual stimuli.16 Manipulations of extracellular norepinephrine levels influence these latter functions such that relatively lower norepinephrine is associated with a bias of these functions toward negative valence.61,62 Thus, excessive metabolism of serotonin and norepinephrine in these regions may affect many cognitive processes implicated in generating depressed mood.
It is intriguing that the MAO-A VT level was greater in the withdrawal condition of the heavy-smoking group compared with healthy nonsmoking controls. Possible explanations are that people who smoke heavily have a preexisting trait or condition associated with greater MAO-A levels or that long-term, heavy cigarette smoking is associated with greater production and reduced degradation of MAO-A protein (although the MAO-A site can be transiently occupied by MAO-A–binding substances). A preexisting difference between groups in personality is unlikely to explain greater MAO-A VT during withdrawal in the cigarette-smoking participants because this potential bias should be related to a reduction in MAO-A binding in the cigarette-smoking group. Personality traits of greater neuroticism and lower deliberation are associated with cigarette smoking,63 but greater neuroticism (particularly aggression) and lower deliberation also are associated with reduced MAO-A binding.64,65 In the present study, levels of neuroticism and personality facets of angry-hostility or deliberation were similar between those who smoked cigarettes and those who did not. Relative levels of these traits were not reported in the cross-sectional studies comparing MAO-A binding in cigarette smoking to health12,66,67 because the relationship between personality traits and MAO-A binding was discovered recently.64,65 The question of whether MAO-binding substances may increase production of MAO-A binding has been investigated minimally; however, ethanol administration (which may be associated with greater plasma levels of harman in humans68) was associated with greater levels of monoamine oxidase B (MAO-B) protein.69 Future studies will need to address whether substances such as harman or norharman influence synthesis or removal of MAO-A.
We prefer an occupancy explanation to account for the rapid change in MAO-A VT within individuals because 2 brain-penetrant substances that bind to MAO-A, harman and norharman, were detected in plasma in the active-smoking state and were rapidly removed from plasma during withdrawal. In addition, the changes in plasma levels of harman correlated significantly with the change in MAO-A VT in the prefrontal and anterior cingulate cortices (as well as most other brain regions). To our knowledge, ours is the first study to measure plasma levels of a series of MAO-A–binding substances in people who smoke cigarettes, unconfounded by coffee or alcohol consumption.68 Because plasma levels of harmine, harmol, and napthylamine were below the threshold of 5 pg/mL, they were viewed as unlikely candidates for an MAO-A occupancy model. Given the low levels of other suspected MAO-A–binding substances, the fairly high affinity of harman for MAO-A (for harman, Ki [equilibrium dissociation for a competitor] = 220 nM, and for norharman, Ki = 2200 nM35), and the significant correlation of plasma harman levels with change in MAO-A binding, reductions in harman best explain the greater MAO-A VT levels during withdrawal from heavy cigarette smoking.
Greater rates of completed suicide and major depressive disorder are associated with cigarette smoking, the former occurring even when controlling for comorbidity of psychiatric illnesses.52,53,70,71 This relationship is perplexing because, in the past, it was believed that cigarettes had an antidepressant effect23 by steadily occupying MAO-A. Our study resolves this paradox by demonstrating that binding to MAO-A is transient. Greater MAO-A VT in the prefrontal and anterior cingulate cortices during acute cigarette withdrawal and associated depressed mood is relevant to suicide research. Depressed mood is associated with greater risk of death by suicide, and in a retrospective study of 100 individuals who completed suicide, Barraclough et al72 reported that 5 deaths were associated with a recent change in cigarette smoking. A retrospective study investigates a related issue, namely, comparing suicide rates during active treatment for quitting vs placebo, and then assessing the link to suicide; however, it did not focus on the early quit period.73 Future investigations of the relationship between suicide and cigarette smoking should consider the early quit period in those who smoke heavily and focus on individuals with major depressive disorder.
The rapid increase in MAO-A VT levels during acute cigarette withdrawal has significant implications for the clinical use of MAO-A inhibitors to assist quitting. This rapid increase in MAO-A VT is targetable with an MAO-A inhibitor such as moclobemide. The results of the present study predict that people who smoke cigarettes heavily should benefit from treatment with an MAO-A inhibitor early in withdrawal. We are aware of 1 such study. In 88 nondepressed individuals, Berlin et al74 reported that treatment with the MAO-A inhibitor moclobemide was associated with significantly greater abstinence rates at 1 week through 6 months compared with placebo. Interestingly, 60% of the participants in this trial smoked fairly heavily, at a rate of more than 30 cigarettes per day. It is also possible that better quit rates may be obtained in the future with substitution therapy for multiple targets with consideration for the timing of withdrawal effects. For example, during cigarette withdrawal, the occupancy ofα4β2 receptors persists for more than a day, and the occupancy of MAO-B persists for at least 11 hours.8,75
Our study has limitations typical of studies involving PET. The measure of MAO-A, an index of MAO-A density called MAO-A VT, reflects total binding and is computationally efficient, highly stable, and the least variable measure of [11C]harmine binding. However, approximately 15% of this measure reflects free and nonspecific binding, so it is assumed that free and nonspecific binding does not differ tremendously between conditions.33 An elevation in MAO-A VT also may reflect greater affinity of MAO-A, although this would not change our interpretation because greater affinity of MAO-A for monoamines would be expected to contribute to monoamine loss. We performed 4 main analyses in this study, so it could be argued that the significances for the main analyses should be multiplied by 4; however, each of these uncorrected significances were sufficiently low, so the results still hold even when considering the 4 main analyses.
In summary, ours is the first study, to our knowledge, of brain MAO-A binding during early cigarette withdrawal. To better explain the complexity of acute cigarette withdrawal after heavy smoking, we argue for adding a new model to previously established mechanisms, focusing on the rapid change in available MAO-A binding. During the withdrawal state in individuals who smoke heavily, MAO-A binding increases rapidly in affect modulating brain regions, such as the prefrontal cortex and anterior cingulate cortex, with MAO-A binding exceeding levels observed in healthy nonsmoking individuals. A greater increase in MAO-A VT in the prefrontal and anterior cingulate cortices may contribute to a shift toward depressed mood given the correlation between the 2 measures, namely, the role of MAO-A in metabolizing monoamines23,24 and the inverse relationship between MAO-A VT and mood.13-15 The increase in MAO-A VT during acute withdrawal is explained best by a reduction in harman because plasma levels of this MAO-A–binding substance were associated with the change in MAO-A VT between active smoking and withdrawal. This study also resolves the paradox of how cigarette smoking can be associated with major depressive disorder and suicide if persistent, antidepressant-like MAO-A inhibition is present. Our answer is that the MAO-A inhibition observed is not like the effect of antidepressants because the inhibition is highly transient and MAO-A VT increases during early withdrawal. This finding suggests that the early withdrawal period should be an area of focus in future investigations of suicide in heavy cigarette smoking.70,71 The increase in MAO-A VT during acute withdrawal also argues in support of additional clinical trials of MAO-A inhibitors for the earliest stages of quitting heavy cigarette smoking, during which relapse rates are highest.74
Correspondence: Jeffrey H. Meyer, MD, PhD, Vivian M. Rakoff PET Imaging Centre, College Street Site, Centre for Addiction and Mental Health, 250 College St, Toronto, ON M5T 1R8, Canada (jeff.meyer@camhpet.ca).
Submitted for Publication: October 1, 2010; final revision received January 27, 2011; accepted February 22, 2011.
Author Contributions: Drs Bacher, Houle, Xu, Zawertailo, George, and Meyer had full access to all of the data in the study and take responsibility for the integrity of the data and accuracy of the data analysis.
Financial Disclosure: Drs Meyer, Wilson, and Houle have received operating grant funding for other studies from Eli Lilly and Company, H. Lundbeck A/S, GlaxoSmithKline plc, Bristol-Myers Squibb, and SK Biopharmaceuticals Co Ltd, and Dr Meyer has consulted for several of these companies. None of these companies participated in the design or execution of this study or writing of the manuscript. Dr Meyer holds a Canada Research Chair from the Canadian Institutes of Health Research. He is developing natural health products to treat high MAO-A states and is applying for a patent to apply measures of MAO to diagnose or treat mood disorders. Dr George receives grant support for smoking-cessation studies from Pfizer Inc. Dr Kish receives research funding from the National Institutes of Health, grant DA025096 from the National Institute on Drug Abuse, and receives expert witness fees to provide an opinion regarding amphetamine toxicity.
Funding Support: This research received project support from the Canadian Institutes of Health Research.
Additional Contributions: We thank the Canadian Foundation for Innovation and the Ontario Ministry for Research and Innovation for infrastructure support. We thank technicians Maggie Lee, BS, Alvina Ng, BSc, Laura Nguyen, BSc, Jeannie Fong, MBA, Jun Parkes, BM, Armando Garcia, BSc, Winston Stableford, BSc, and Min Wong, BSc; engineers Terry Bell, BTech, and Ted Brandts-Harris, BA; and Jinoos Sotodeh, PhD, for their assistance with this project.
1.Makomaski Illing EM, Kaiserman MJ. Mortality attributable to tobacco use in Canada and its regions, 1998.
Can J Public Health. 2004;95(1):38-4414768740
PubMedGoogle Scholar 2.World Health Organization. World Health Organization Report on the Global Tobacco Epidemic: Implementing Smoke-Free Environments. Geneva, Switzerland: World Health Organization; 2009
3.Danaei G, Ding EL, Mozaffarian D, Taylor B, Rehm J, Murray CJL, Ezzati M. The preventable causes of death in the United States: comparative risk assessment of dietary, lifestyle, and metabolic risk factors.
PLoS Med. 2009;6(4):e100005819399161
PubMedGoogle ScholarCrossref 4.Garvey AJ, Bliss RE, Hitchcock JL, Heinold JW, Rosner B. Predictors of smoking relapse among self-quitters: a report from the Normative Aging Study [published correction appears in
Addict Behav. 1992;17(5):513].
Addict Behav. 1992;17(4):367-3771502970
PubMedGoogle ScholarCrossref 5.Law M, Tang JL. An analysis of the effectiveness of interventions intended to help people stop smoking.
Arch Intern Med. 1995;155(18):1933-19417575046
PubMedGoogle ScholarCrossref 6.Laviolette SR, van der Kooy D. The neurobiology of nicotine addiction: bridging the gap from molecules to behaviour.
Nat Rev Neurosci. 2004;5(1):55-6514708004
PubMedGoogle ScholarCrossref 7.Brody AL, Mandelkern MA, London ED, Olmstead RE, Farahi J, Scheibal D, Jou J, Allen V, Tiongson E, Chefer SI, Koren AO, Mukhin AG. Cigarette smoking saturates brainα
4β
2 nicotinic acetylcholine receptors.
Arch Gen Psychiatry. 2006;63(8):907-91516894067
PubMedGoogle ScholarCrossref 8.Cosgrove KP, Batis J, Bois F, Maciejewski PK, Esterlis I, Kloczynski T, Stiklus S, Krishnan-Sarin S, O’Malley S, Perry E, Tamagnan G, Seibyl JP, Staley JK. β
2-Nicotinic acetylcholine receptor availability during acute and prolonged abstinence from tobacco smoking.
Arch Gen Psychiatry. 2009;66(6):666-67619487632
PubMedGoogle ScholarCrossref 9.Piper ME, Smith SS, Schlam TR, Fiore MC, Jorenby DE, Fraser D, Baker TB. A randomized placebo-controlled clinical trial of 5 smoking cessation pharmacotherapies [published correction appears in
Arch Gen Psychiatry. 2010;67(1):77].
Arch Gen Psychiatry. 2009;66(11):1253-126219884613
PubMedGoogle ScholarCrossref 10.Herraiz T, Chaparro C. Human monoamine oxidase is inhibited by tobacco smoke:β-carboline alkaloids act as potent and reversible inhibitors.
Biochem Biophys Res Commun. 2005;326(2):378-38615582589
PubMedGoogle ScholarCrossref 11.Hauptmann N, Shih JC. 2-Naphthylamine, a compound found in cigarette smoke, decreases both monoamine oxidase A and B catalytic activity.
Life Sci. 2001;68(11):1231-124111233991
PubMedGoogle ScholarCrossref 12.Fowler JS, Volkow ND, Wang G-J, Pappas N, Logan J, Shea C, Alexoff D, MacGregor RR, Schlyer DJ, Zezulkova I, Wolf AP. Brain monoamine oxidase A inhibition in cigarette smokers.
Proc Natl Acad Sci U S A. 1996;93(24):14065-140698943061
PubMedGoogle ScholarCrossref 13.Meyer JH, Ginovart N, Boovariwala A, Sagrati S, Hussey D, Garcia A, Young T, Praschak-Rieder N, Wilson AA, Houle S. Elevated monoamine oxidase A levels in the brain: an explanation for the monoamine imbalance of major depression.
Arch Gen Psychiatry. 2006;63(11):1209-121617088501
PubMedGoogle ScholarCrossref 14.Meyer JH, Wilson AA, Sagrati S, Miler L, Rusjan P, Bloomfield PM, Clark M, Sacher J, Voineskos AN, Houle S. Brain monoamine oxidase A binding in major depressive disorder: relationship to selective serotonin reuptake inhibitor treatment, recovery, and recurrence.
Arch Gen Psychiatry. 2009;66(12):1304-131219996035
PubMedGoogle ScholarCrossref 15.Sacher J, Wilson A, Houle S, Rusjan P, Hassan S, Bloomfield P, Stewart D, Meyer J. Elevated brain monoamine oxidase A binding in the early postpartum period.
Arch Gen Psychiatry. 2010;67(5):468-474
Google ScholarCrossref 16.Ressler KJ, Mayberg HS. Targeting abnormal neural circuits in mood and anxiety disorders: from the laboratory to the clinic.
Nat Neurosci. 2007;10(9):1116-112417726478
PubMedGoogle ScholarCrossref 17.Liotti M, Mayberg HS, McGinnis S, Brannan SL, Jerabek P. Unmasking disease-specific cerebral blood flow abnormalities: mood challenge in patients with remitted unipolar depression.
Am J Psychiatry. 2002;159(11):1830-184012411216
PubMedGoogle ScholarCrossref 18.Krüger S, Alda M, Young LT, Goldapple K, Parikh S, Mayberg HS. Risk and resilience markers in bipolar disorder: brain responses to emotional challenge in bipolar patients and their healthy siblings.
Am J Psychiatry. 2006;163(2):257-26416449479
PubMedGoogle ScholarCrossref 20.al’Absi M, Hatsukami D, Davis GL, Wittmers LE. Prospective examination of effects of smoking abstinence on cortisol and withdrawal symptoms as predictors of early smoking relapse.
Drug Alcohol Depend. 2004;73(3):267-27815036549
PubMedGoogle ScholarCrossref 21.Carey MP, Kalra DL, Carey KB, Halperin S, Richards CS. Stress and unaided smoking cessation: a prospective investigation.
J Consult Clin Psychol. 1993;61(5):831-8388245280
PubMedGoogle ScholarCrossref 22.Kenford SL, Smith SS, Wetter DW, Jorenby DE, Fiore MC, Baker TB. Predicting relapse back to smoking: contrasting affective and physical models of dependence.
J Consult Clin Psychol. 2002;70(1):216-22711860048
PubMedGoogle ScholarCrossref 23.Haefely W, Burkard WP, Cesura AM, Kettler R, Lorez HP, Martin JR, Richards JG, Scherschlicht R, Da Prada M. Biochemistry and pharmacology of moclobemide, a prototype RIMA.
Psychopharmacology (Berl). 1992;106:(suppl)
S6-S141546143
PubMedGoogle ScholarCrossref 24.Youdim MBH, Edmondson D, Tipton KF. The therapeutic potential of monoamine oxidase inhibitors.
Nat Rev Neurosci. 2006;7(4):295-30916552415
PubMedGoogle ScholarCrossref 25.Freis ED. Mental depression in hypertensive patients treated for long periods with large doses of reserpine.
N Engl J Med. 1954;251(25):1006-100813214379
PubMedGoogle ScholarCrossref 26.Hasler G, Fromm S, Carlson PJ, Luckenbaugh DA, Waldeck T, Geraci M, Roiser JP, Neumeister A, Meyers N, Charney DS, Drevets WC. Neural response to catecholamine depletion in unmedicated subjects with major depressive disorder in remission and healthy subjects.
Arch Gen Psychiatry. 2008;65(5):521-53118458204
PubMedGoogle ScholarCrossref 27.Neumeister A, Nugent AC, Waldeck T, Geraci M, Schwarz M, Bonne O, Bain EE, Luckenbaugh DA, Herscovitch P, Charney DS, Drevets WC. Neural and behavioral responses to tryptophan depletion in unmedicated patients with remitted major depressive disorder and controls.
Arch Gen Psychiatry. 2004;61(8):765-77315289275
PubMedGoogle ScholarCrossref 28.Verhoeff NPLG, Kapur S, Hussey D, Lee M, Christensen B, C Psych , Papatheodorou G, Zipursky RB. A simple method to measure baseline occupancy of neostriatal dopamine D
2 receptors by dopamine
in vivo in healthy subjects.
Neuropsychopharmacology. 2001;25(2):213-22311425505
PubMedGoogle ScholarCrossref 29.Young SN, Smith SE, Pihl RO, Ervin FR. Tryptophan depletion causes a rapid lowering of mood in normal males.
Psychopharmacology (Berl). 1985;87(2):173-1773931142
PubMedGoogle ScholarCrossref 30.Rommelspacher H, Meier-Henco M, Smolka M, Kloft C. The levels of norharman are high enough after smoking to affect monoamineoxidase B in platelets.
Eur J Pharmacol. 2002;441(1-2):115-12512007928
PubMedGoogle ScholarCrossref 31.Tauscher J, Jones C, Remington G, Zipursky RB, Kapur S. Significant dissociation of brain and plasma kinetics with antipsychotics.
Mol Psychiatry. 2002;7(3):317-32111920159
PubMedGoogle ScholarCrossref 32.Bergström M, Westerberg G, Långström B.
11C-harmine as a tracer for monoamine oxidase A (MAO-A): in vitro and in vivo studies.
Nucl Med Biol. 1997;24(4):287-2939257326
PubMedGoogle ScholarCrossref 33.Ginovart N, Meyer JH, Boovariwala A, Hussey D, Rabiner EA, Houle S, Wilson AA. Positron emission tomography quantification of [
11C]-harmine binding to monoamine oxidase–A in the human brain.
J Cereb Blood Flow Metab. 2006;26(3):330-34416079787
PubMedGoogle ScholarCrossref 34.Wilson A, Meyer J, Garcia A, Singh K, Hussey D, Houle S, Ginovart N. Determination of the arterial input function of the MAO-A inhibitor [11C] harmine in human subjects [abstract].
J Labelled Compounds Radiopharm. 2003;46(S1):S367
Google Scholar 35.May T, Rommelspacher H, Pawlik M. [3H]Harman binding experiments, I: a reversible and selective radioligand for monoamine oxidase subtype A in the CNS of the rat.
J Neurochem. 1991;56(2):490-4991988552
PubMedGoogle ScholarCrossref 36.Fagerström KO. Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment.
Addict Behav. 1978;3(3-4):235-241735910
PubMedGoogle ScholarCrossref 37.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(9):1119-11271932883
PubMedGoogle ScholarCrossref 38.Shiffman S, Waters A, Hickcox M. The nicotine dependence syndrome scale: a multidimensional measure of nicotine dependence.
Nicotine Tob Res. 2004;6(2):327-34815203807
PubMedGoogle ScholarCrossref 39.First M, Spitzer R, Gibbon M, Williams J. Structured Clinical Interview for DSM-IV Axis I Disorders, Patient Edition (SCID-P), Version 2. New York, NY: Biometrics Research; 1995
40.Blais MA, Norman DK. A psychometric evaluation of the
DSM-IV personality disorder criteria.
J Pers Disord. 1997;11(2):168-1769203111
PubMedGoogle ScholarCrossref 41.Jarvik ME, Madsen DC, Olmstead RE, Iwamoto-Schaap PN, Elins JL, Benowitz NL. Nicotine blood levels and subjective craving for cigarettes.
Pharmacol Biochem Behav. 2000;66(3):553-55810899369
PubMedGoogle ScholarCrossref 42.Poindexter EH Jr, Carpenter RD. The isolation of harman and norharman from tobacco and cigarette smoke.
Phytochemistry. 1962;1(3):215-221
Google ScholarCrossref 43.Kartal M, Altun ML, Kurucu S. HPLC method for the analysis of harmol, harmalol, harmine and harmaline in the seeds of
Peganum harmala L.
J Pharm Biomed Anal. 2003;31(2):263-26912609665
PubMedGoogle ScholarCrossref 44.Guan Y, Louis ED, Zheng W. Toxicokinetics of tremorogenic natural products, harmane and harmine, in male Sprague-Dawley rats.
J Toxicol Environ Health A. 2001;64(8):645-66011766171
PubMedGoogle ScholarCrossref 45.Studholme C, Hill DLG, Hawkes DJ. An overlap invariant entropy measure of 3D medical image alignment.
Pattern Recognition. 1999;32(1):71-86
Google ScholarCrossref 47.Ashburner J, Neelin P, Collins DL, Evans A, Friston K. Incorporating prior knowledge into image registration.
Neuroimage. 1997;6(4):344-3529417976
PubMedGoogle ScholarCrossref 48.Rusjan P, Mamo D, Ginovart N, Hussey D, Vitcu I, Yasuno F, Tetsuya S, Houle S, Kapur S. An automated method for the extraction of regional data from PET images.
Psychiatry Res. 2006;147(1):79-8916797168
PubMedGoogle ScholarCrossref 49.Ashburner J, Friston K. Multimodal image coregistration and partitioning: a unified framework.
Neuroimage. 1997;6(3):209-2179344825
PubMedGoogle ScholarCrossref 50.Mawlawi O, Martinez D, Slifstein M, Broft A, Chatterjee R, Hwang D-R, Huang Y, Simpson N, Ngo K, Van Heertum R, Laruelle M. Imaging human mesolimbic dopamine transmission with positron emission tomography, I: accuracy and precision of D2 receptor parameter measurements in ventral striatum.
J Cereb Blood Flow Metab. 2001;21(9):1034-1057
Google ScholarCrossref 51.Baumert J, Ladwig K-H, Ruf E, Meisinger C, Döring A, Wichmann H-E.KORA Investigators. Determinants of heavy cigarette smoking: are there differences in men and women? results from the population-based MONICA/KORA Augsburg surveys.
Nicotine Tob Res. 2010;12(12):1220-122720952600
PubMedGoogle ScholarCrossref 52.Pratt LA, Brody DJ. Depression and smoking in the U.S. household population aged 20 and over, 2005-2008.
NCHS Data Brief. 2010;34(34):1-820604991
PubMedGoogle Scholar 53.Glassman AH, Covey LS, Stetner F, Rivelli S. Smoking cessation and the course of major depression: a follow-up study.
Lancet. 2001;357(9272):1929-193211425414
PubMedGoogle ScholarCrossref 54.Fowler JS, Volkow ND, Ding YS, Wang GJ, Dewey S, Fischman MW, Foltin R, Hitzemann R. Positron emission tomography studies of dopamine-enhancing drugs.
J Clin Pharmacol. 1999;(suppl)
13S-16S10434242
PubMedGoogle Scholar 55.Knutson B, Taylor J, Kaufman M, Peterson R, Glover G. Distributed neural representation of expected value.
J Neurosci. 2005;25(19):4806-481215888656
PubMedGoogle ScholarCrossref 56.Sharot T, Riccardi AM, Raio CM, Phelps EA. Neural mechanisms mediating optimism bias.
Nature. 2007;450(7166):102-10517960136
PubMedGoogle ScholarCrossref 57.Tom SM, Fox CR, Trepel C, Poldrack RA. The neural basis of loss aversion in decision-making under risk.
Science. 2007;315(5811):515-51817255512
PubMedGoogle ScholarCrossref 58.Bhagwagar Z, Hinz R, Taylor M, Fancy S, Cowen P, Grasby P. Increased 5-HT
2A receptor binding in euthymic, medication-free patients recovered from depression: a positron emission study with [
11C]MDL 100,907.
Am J Psychiatry. 2006;163(9):1580-158716946184
PubMedGoogle ScholarCrossref 59.Meyer JH, Houle S, Sagrati S, Carella A, Hussey DF, Ginovart N, Goulding V, Kennedy J, Wilson AA. Brain serotonin transporter binding potential measured with carbon11–labeled DASB positron emission tomography: effects of major depressive episodes and severity of dysfunctional attitudes.
Arch Gen Psychiatry. 2004;61(12):1271-1279
Google ScholarCrossref 60.Meyer JH, McMain S, Kennedy SH, Korman L, Brown GM, DaSilva JN, Wilson AA, Blak T, Eynan-Harvey R, Goulding VS, Houle S, Links P. Dysfunctional attitudes and 5-HT
2 receptors during depression and self-harm.
Am J Psychiatry. 2003;160(1):90-9912505806
PubMedGoogle ScholarCrossref 61.Harmer CJ, Hill SA, Taylor MJ, Cowen PJ, Goodwin GM. Toward a neuropsychological theory of antidepressant drug action: increase in positive emotional bias after potentiation of norepinephrine activity.
Am J Psychiatry. 2003;160(5):990-99212727705
PubMedGoogle ScholarCrossref 62.Harmer CJ, O’Sullivan U, Favaron E, Massey-Chase R, Ayres R, Reinecke A, Goodwin GM, Cowen PJ. Effect of acute antidepressant administration on negative affective bias in depressed patients.
Am J Psychiatry. 2009;166(10):1178-118419755572
PubMedGoogle ScholarCrossref 64.Alia-Klein N, Goldstein RZ, Kriplani A, Logan J, Tomasi D, Williams B, Telang F, Shumay E, Biegon A, Craig IW, Henn F, Wang G-J, Volkow ND, Fowler JS. Brain monoamine oxidase A activity predicts trait aggression.
J Neurosci. 2008;28(19):5099-510418463263
PubMedGoogle ScholarCrossref 65.Soliman A, Bagby RM, Wilson AA, Miler L, Clark M, Rusjan P, Sacher J, Houle S, Meyer JH. Relationship of monoamine oxidase A binding to adaptive and maladaptive personality traits.
Psychol Med. 2011;41(5):1051-106020810002
PubMedGoogle ScholarCrossref 66.Leroy C, Bragulat V, Berlin I, Grégoire M-C, Bottlaender M, Roumenov D, Dollé F, Bourgeois S, Penttilä J, Artiges E, Martinot J-L, Trichard C. Cerebral monoamine oxidase A inhibition in tobacco smokers confirmed with PET and [11C]befloxatone.
J Clin Psychopharmacol. 2009;29(1):86-8819142115
PubMedGoogle ScholarCrossref 67.Klimek V, Zhu M-Y, Dilley G, Konick L, Overholser JC, Meltzer HY, May WL, Stockmeier CA, Ordway GA. Effects of long-term cigarette smoking on the human locus coeruleus.
Arch Gen Psychiatry. 2001;58(9):821-82711545664
PubMedGoogle ScholarCrossref 68.Pfau W, Skog K. Exposure toβ-carbolines norharman and harman.
J Chromatogr B Analyt Technol Biomed Life Sci. 2004;802(1):115-12615036003
PubMedGoogle ScholarCrossref 69.Ou X-M, Stockmeier CA, Meltzer HY, Overholser JC, Jurjus GJ, Dieter L, Chen K, Lu D, Johnson C, Youdim MBH, Austin MC, Luo J, Sawa A, May W, Shih JC. A novel role for glyceraldehyde-3-phosphate dehydrogenase and monoamine oxidase B cascade in ethanol-induced cellular damage.
Biol Psychiatry. 2010;67(9):855-86320022592
PubMedGoogle ScholarCrossref 70.Oquendo MA, Galfalvy H, Russo S, Ellis SP, Grunebaum MF, Burke A, Mann JJ. Prospective study of clinical predictors of suicidal acts after a major depressive episode in patients with major depressive disorder or bipolar disorder.
Am J Psychiatry. 2004;161(8):1433-144115285970
PubMedGoogle ScholarCrossref 71.Miller M, Hemenway D, Bell NS, Yore MM, Amoroso PJ. Cigarette smoking and suicide: a prospective study of 300,000 male active-duty Army soldiers.
Am J Epidemiol. 2000;151(11):1060-106310873129
PubMedGoogle ScholarCrossref 72.Barraclough B, Bunch J, Nelson B, Sainsbury P. A hundred cases of suicide: clinical aspects.
Br J Psychiatry. 1974;125(0):355-3734425774
PubMedGoogle ScholarCrossref 74.Berlin I, Saïd S, Spreux-Varoquaux O, Launay J-M, Olivares R, Millet V, Lecrubier Y, Puech AJ. A reversible monoamine oxidase A inhibitor (moclobemide) facilitates smoking cessation and abstinence in heavy, dependent smokers.
Clin Pharmacol Ther. 1995;58(4):444-4527586937
PubMedGoogle ScholarCrossref 75.Fowler JS, Wang G-J, Volkow ND, Franceschi D, Logan J, Pappas N, Shea C, MacGregor RR, Garza V. Maintenance of brain monoamine oxidase B inhibition in smokers after overnight cigarette abstinence.
Am J Psychiatry. 2000;157(11):1864-186611058487
PubMedGoogle ScholarCrossref