Pharmacogenetics, Emotional Reactivity and Smoking
Phase: PHASE2
Conditions: Tobacco Use Disorder, Smoking Cessation
Sponsor: M.D. Anderson Cancer Center

 
 
 
 

 
 
 
 
..................................................................................................................................................4
Overview ...........................................................................................................................................................4
.......................................................................................................................6
Neurotransmitters Genes and Smoking............................................................................................................6
Dopamine (DA) and the Dopamine Transporter (DAT) .................................................................................6
Serotonin (5-HT) and the Serotonin Transporter Gene (SERT)........................................................................7
Norepinephrine (NA) and Norepinephrine Transporter (NET) ..........................................................................8
Focusing on Endophenotypes...........................................................................................................................9
Rationale for Studying Smoking and Mood.....................................................................................................10
Relationship of the Startle Response to Affect................................................................................................11
Antidepressants used for Smoking Cessation ................................................................................................11
......................................................................................................................................12
.....................................................................................................................17
Design Summary.............................................................................................................................................17
Table 2 Study Time Line and Procedures ...................................................................................................20
The Demographic, Health and Smoking Health Questionnaires .................................................................21
The Fagerstrom Test for Nicotine Dependence (FTND) .............................................................................21
The Positive and Negative Affect Scale (PANAS).......................................................................................21
The Center for Epidemiologic Studies Depression Scale (CES-D) .............................................................21
Smoking Status Questionnaire (SSQ) & Expired CO ..................................................................................22
Nicotine/Cotinine .........................................................................................................................................22
Adverse Event Monitoring & Concomitant Medication ................................................................................22
DRD2...........................................................................................................................................................22
DRD4...........................................................................................................................................................22
DAT .............................................................................................................................................................22
SERT...........................................................................................................................................................22
NET .............................................................................................................................................................22
Treatment Intervention....................................................................................................................................23
Counseling Component...............................................................................................................................23
Bupropion ....................................................................................................................................................23
Placebo........................................................................................................................................................23
Medication Blinding .....................................................................................................................................23
Abstinence Compliance and Startle Assessments......................................................................................24
Abstinence compliance following startle assessments (28 days post quit). ................................................25
Laboratory Startle Assessment Sessions .......................................................................................................25
Startle Probe Trial Composition: Slides (stimulus materials) & Instrumentation .............................................26
Physiological Recording and Data Reduction .............................................................................................27
Participant Compensation ...........................................................................................................................27
Data Analysis ..................................................................................................................................................27
Statistical Approach ........................................................................................................................................28
Power..............................................................................................................................................................28
Primary Hypotheses........................................................................................................................................30
Secondary Analyses Involving Other Markers ................................................................................................31
..........................................................................................................................32
Protection of Human Subjects.........................................................................................................................32
Inclusion of Women.........................................................................................................................................34
Inclusion of Minorities......................................................................................................................................34
Table 6 Inclusion Enrollment Report ...........................................................................................................35

 
 
 
Table 7 Targeted/Planned Enrollment Table...............................................................................................37
Inclusion of Children........................................................................................................................................37
Data Quality and Integrity................................................................................................................................37
.............................................................................................................................................38
....................................................................................................47
.................................................................................................................................................48

 
 
 
The specific aims of this proposal are to evaluate the differences in emotional reactivity (peak startle response 
to affective stimuli) during a cessation attempt among smokers treated with bupropion, nortriptyline or placebo 
and to determine if these differences are moderated by genotype. We will also assess the relationship between 
emotional reactivity and days to relapse, following the quit date. 
 
This proposal will evaluate the following hypotheses: 
1. The emotional reactivity of smokers during quitting will be significantly higher among those that receive 
placebo vs. either bupropion or nortriptyline therapy for smoking cessation. Emotional reactivity will be 
assessed by measuring the peak eye blink (EMG) response to an acoustic startle probe delivered during 
the presentation of emotionally valent stimuli (positive, negative, neutral, smoking related pictures). 
2. The emotional reactivity of smokers during cessation will be moderated by genotype. Our initial hypothesis 
will focus on the DRD2: 
2.1. We hypothesize that emotional reactivity will be lower for those carrying the DRD2 A1 allele and using 
bupropion vs. A1 smokers using either nortriptyline or placebo. A1 nortriptyline users are expected to 
have lower reactivity than A1 placebo users[PCP1]. Homozygous A2s are expected to respond similarly 
to both drugs with higher levels of emotional reactivity being observed for placebo vs. either bupropion 
or nortriptyline. 
3. Higher levels of emotional reactivity of smokers at baseline and during cessation will be inversely related to 
abstinence at the 3 and 6-month follow-up periods.  
 
Although our initial genetic hypotheses are focused on the DRD2, we will also use emotional reactivity 
assessments to characterize the phenotypes of several other biomarkers that have potential importance for 
neuroregulatory function and response to pharmacotherapy for smoking cessation. These include the DRD4, 
SERT (serotonin transporter), DAT (dopamine transporter) and NET (norepinephrine transporter).  Several 
exploratory hypotheses are proposed, for example: 
 
1. We hypothesize that those carrying the long form of the DRD4 (6 repeat or longer) will experience less 
reactivity during either drug therapy than those homozygous for the short form.  
2. We hypothesize that smokers who are heterozygous (S/L) or homozygous (L/L) for the long form of the 
SERT gene are likely to experience less emotional reactivity in response to nortriptyline therapy vs. 
either bupropion or placebo. 
3. Polymorphisms of the NET gene have not been extensively characterized in humans, and its 
relationship to antidepressant therapy has not yet been explored. We will evaluate the relationship of 
one of the currently known NET polymorphisms (1287G/A) and emotional reactivity during 
pharmacotherapy. As a working hypothesis we expect that that smokers carrying the GG allele of the 
1287G/A variant will show reduced emotional reactivity during nortriptyline therapy vs. bupropion or 
placebo, in comparison to their GA or AA counterparts, who are not expected to differ in response to 
the antidepressants. 
It is estimated that cigarette smoking is responsible for over 40% of premature deaths and disability in 
the US. The adverse health risks of smoking increase significantly with duration and amount smoked per day, 
and it is precisely these heavier and more nicotine dependent smokers that are most refractory to treatment 1. 
Although significant advances have occurred in smoking cessation therapy, approximately 26% of men and 
22% of women continue to smoke. Smoking has been characterized as a chronic relapsing disorder. Over 40% 
of smokers make a serious cessation attempt each year but less than 3% of all smokers successfully quit2. 
One of the most fundamental aspects of nicotine dependence involves its neuroregulatory function on mood. 
The experience of negative affect, in particular, is a significant contributor to the risk of relapse and constitutes 
a major factor of the nicotine withdrawal syndrome. Recent advances in smoking cessation have focused on 

 
 
 
the use of antidepressants for the treatment of nicotine dependence (i.e., bupropion and nortriptyline). While 
the efficacy of these treatments has been established in previous studies, we know little about how they work. 
The impact of these and other pharmacological treatments on the public health may be significantly improved 
by gaining a better understanding of the underlying psychobiological and genetic mechanisms associated with 
the modulation of mood during cessation (nicotine withdrawal), and the interaction between these mechanisms 
and treatment. This research is focused on understanding genetic and psychobiological differences in 
response to two pharmacotherapies for smoking cessation that target the neurotransmitters, dopamine, 
norepinephrine, and serotonin with differing degrees of specificity.  
The specific aims of this project are to assess the effects of bupropion and nortriptyline vs. a placebo 
control, on changes in emotional reactivity during smoking cessation, and to determine if these effects are 
moderated by genotype.  We will also determine whether emotional reactivity predicts abstinence and time to 
relapse. We will use a standardized laboratory assessment procedure, known as the acoustic startle probe, to 
evaluate the differences in emotional reactivity. The startle reflex (eye blink) is an orienting response that 
follows an unexpected auditory stimulus (startle probe). It is thought to reflect immediate changes in cortical 
and subcortical activity related to motivation and emotion, such as approach or defensive behavior. Negative 
emotional cues, such as slides of upsetting events delivered prior to the probe, activate defensive 
neuroregulatory pathways and increase blink response magnitude (eye muscle EMG), while positive cues 
inhibit the response, activating appetitive or approach pathways. Unlike retrospective self-report measures of 
affect, startle occurs in real time proximity to the emotional cue, is not subject to recall bias, and provides 
information about momentary and subtle changes in motivational predisposition and affect. This startle-affect 
relationship provides an ideal paradigm for studying genetic differences between smokers and the disruptive 
effects of smoking cessation on emotional reactivity and mood.  
Our initial genetic analysis will focus on the A1/A2 polymorphism of the DRD2 receptor gene. Data from 
our laboratory suggest that smokers carrying the A1 allele vs. those with only the A2 are both less likely to quit 
smoking and experience less consistent reduction in negative affect when given venlafaxine, (a modest 
serotonin/low norepinephrine/very low dopamine/ reuptake inhibitor 3). Our preliminary studies also suggests 
that reactivity is substantially elevated for A1 vs. A2 smokers prior to quitting and between A1 smokers 
attempting to quit vs. A1 controls, or A2 trying to quit and their controls. Moreover, among A1 smokers 
destined to relapse, emotional reactivity to negative cues is substantially higher at baseline, and sharply 
increases in the first few days of withdrawal. A1 smokers who never quit appear to have significantly lower 
levels of reactivity at baseline to positive and smoking related pictures. These results indicate that this 
genotype may be associated with differences in emotional processing before smokers attempt to quit and 
during the cessation attempt.  
In this study, 354 smokers will be randomly assigned to receive bupropion, nortriptyline, or placebo. All 
three conditions will include a behavioral counseling component, consistent with previous research examining 
the efficacy of these pharmacotherapies. After a baseline startle assessment, all participants will complete 
startle assessments at 2,5 and 28 days post-quit. Each assessment will involve a series of startle probe trials 
consisting of the presentation of an acoustic stimulus (startle probe), preceded by positive, negative or neutral 
emotional cues.  
With the research proposed in this application, we hope to understand more fully how 
pharmacotherapies for smoking cessation affect emotional reactivity during cessation and what role genetics 
may play in conferring an advantage to one treatment vs. another.  For example, functional differences in 
dopaminergic, serotonergic or noradrenergic responsivity, which are at least partly genetically controlled, could 
influence the balance between reduction in positive mood or exaggeration of negative affect during a quit 
attempt. Relapse in smokers attempting to quit is often attributed to the level of negative affect, and an 
examination of the startle reflex during quitting may provide important information on emotional reactivity and 
predisposition to relapse. We propose using startle based assessments of emotional reactivity to characterize 
the endophenotype of smokers carrying candidate genes, and subsequently assess their response to drugs 
that have different degrees of specificity for neuromodulators thought to be associated with the candidate 
gene. Ultimately this knowledge may contribute to the development of more effective interventions, especially 
in the area of pharmacogenetics. [PCP2][PMC3]Targeting specific groups of individuals with specific treatments 
may improve effectiveness of pharmacologically based treatments. 

 
 
 
 
Dopaminergic neurotransmission in the mesolimbic system, and particularly in the nucleus accumbens, 
is a recognized and critical target of many drugs of abuse, including alcohol, cocaine, and stimulants 4-6.  
Dopamine neurotransmission is involved in the experience of pleasure/reward 4 and is the principal 
neurotransmitter involved in the initial assignment of incentive salience to environmental stimuli, which later 
governs motivated action (i.e., movement towards or away from the stimuli)7.  Recent animal studies have 
implicated dopaminergic transmission in the reinforcing effects of nicotine on behavior 8, 9.  Nicotine can 
stimulate dopamine 10, 11 and inhibit its re-uptake 12, 13 , and the activation and desensitization of midbrain 
neurons by nicotine may play an important role in the development of tolerance 14. Inherited variants of genes 
coding for proteins involved in dopaminergic transmission could contribute to genetic differences in drug use, 
including smoking, by regulating dopamine synthesis, metabolism and expression of the receptors. The most 
widely studied of these variants has been the DRD2 receptor gene. 
 
The human D2 dopamine receptor (DRD2) gene is located on chromosome 11q and several 
polymorphisms have been described. These include the uncommon TaqIA restriction fragment length 
polymorphism (RFLP) located on the 3¶ flanking region of the DRD2 gene, and the 5¶ TaqIB. Studies suggest 
that these alleles are located on a part of the chromosome believed to have regulatory influence on the 
dopamine receptor 15. For this review, references to the A1 genotype correspond to individuals having either 
the A1/A1 or the A1/A2 genotype; and the A2 refers to the A2/A2 homozygote. The A1 allele has been 
associated with a decrease in D2 receptor density 16, 17 and the D2 receptor has been implicated as a prime 
target of psychotropic drugs 18. Studies with chronic cocaine users, for example, show that significant 
reductions in D2 receptor availability persist after cocaine withdrawal and are associated with dysphoric mood 
19, 20. D2 receptor occupancy has also been associated with the intensity of the ³high´ produced by 
psychostimulants 21. Moreover, stimulation of the D2 receptors with bromocriptine (a dopamine agonist) 
decreases smoking, whereas blocking the D2 receptors with haloperidol (a dopamine antagonist) increases 
smoking behavior 22, 23.   
Significant differences have been noted in a general population sample for the frequency of A1 allele 
between current (OR =2.15) and former smokers (OR =1.17) in comparison to non-smokers24.  Among 
smokers trying to quit, the frequency of A1 allele is significantly higher than non-smoker controls (48.7% vs. 
25.9%, p<. 00001), inversely related to duration of previous quitting and age of initiation; and positively related 
to cigarettes smoked per day 25. We have noted similar findings for the B1 allele in a study of lung cancer 
patients and non-patient controls, with the B1 being more common among the non-patient smokers. Both 
[pmc4]A1s & B1s also initiated smoking at an earlier age and made fewer attempts to quit 26.  However, in a 
small sample family linkage study 27 and in a separate study of German heavy smokers 28 no significant 
association between smoking and the DRD2 was noted. More recently, in an unpublished report Lerman29 
found weak main effects for the DRD2 (p =.1) on1 year abstinence rates but no interaction between genotype 
and treatment (bupropion or placebo). This study is yet incomplete and further analysis is required before 
conclusions can be reached. However, the general approach to studying gene drug interactions in smoking 
cessation is relevant to the current proposal and is discussed in more detail below (see discussion of 
endophenotypes). 
 
Lerman and her colleagues 30 investigated the interaction of the dopamine transporter gene (DAT), 
SCL6A3-9 and the DRD2 A1 on smoking behavior. The SLC6A3 gene regulates synaptic dopamine by coding 
for a re-uptake protein called DAT 31. It has a 3' variable number tandem repeat (VNTR; 40 bp) polymorphism 
32. Smokers with the SLCA63-9 allele started smoking later and quit for a longer time than those without it. 
These effects were not modified by DRD2 status and the SLCA63-9 was not associated with Fagerstrom 
dependence scores. However, the SLC6A3-9 repeat was more frequent among Caucasian nonsmokers (62%) 
who also had the A2 allele but not among those who had the A1 allele (46%). Similar but non-significant trends 
were noted for African American smokers. It appears that the ³protective´ effect of the SLC63A-9 for smoking 
(greater frequency among nonsmokers vs. smokers) is eliminated by the presence of the A1 allele. Similar 
findings have been reported by Sabol et al. 33, who found the odds of smoking cessation (i.e., being a former 

 
 
 
vs. current smoker) was higher for those having the SLC63A-9 allele (51.9% vs. 42%). Smoking rates were 
also higher for participants carrying the A1 allele, and more people quit who had SLC6A3-9 and did not have 
the DRD2 A1 allele, although these effects were not statistically significant. However, the relationship between 
smoking and the DAT was not replicated in a large Australian study using a non-clinical sample 34 or in a US 
community based sample35. 
 
Studies have also associated the DRD4 receptor (a member of the D2 family of receptors) with 
smoking. The data suggest that the long form of the gene is associated with a blunted response to dopamine 36 
and higher scores on the Tridimensional Personality Questionnaire 37 ³Novelty-Seeking´ subscale 38, 39, among 
smokers 33. The long form of the gene (S/L or L/L) is comprised of 6-8 repeats, of which 7 is most common 
while the short form (S/S) consists of 2-5 repeats with 4 being the most frequent. A study by Shields, et al., 40 
found that the long allele was more frequent among African American vs. Caucasian smokers. African 
Americans with this allele were more likely to be smokers, are less likely to quit, started smoking at an earlier 
age, and smoked more often within 30 min of waking than those with the short form.  
 
Like the DRD2 A1, the DR4 L allele may confer some impairment in dopaminergic responsivity. Data 
from at least one study suggests this could increase craving when such smokers are confronted with smoking 
related cues 41. Smokers in this study with the DRD4 long allele also decreased positive affect during exposure 
to smoking cues, in comparison to those with the short allele. The presence of smoking cues in the 
environment has been positively related to relapse 42.  This study is note worthy because like those described 
in our preliminary studies, it is among the first that attempts to define the phenotype of the candidate gene in 
terms that have relevance to the treatment of nicotine dependence (i.e., affect, response to smoking cues).  
 
Serotonin is involved in the regulation of many brain functions, including sleep, cognition, sensory 
perception, motor activity, temperature regulation, nociception, mood, appetite, sexual behavior, and hormone 
secretion. There appears to be an important interplay that is not completely understood, between the effects of 
nicotine and nicotine withdrawal on serotonergic mechanisms, on the one hand, and serotonin¶s role in 
modulating affect and dopaminergic reward systems on the other. Nicotine may stimulate serotonin (5-HT) 
release at high doses 43, 44 and its withdrawal may decrease 5-HT in limbic and forebrain structures, possibly by 
increasing the inhibitory influence of 5 HT1A autoreceptors within the raphe nuclei 45. These structures are 
important in the regulation of emotion and are themselves activated by nicotine administration in humans 46. 
Increased serotonin has also been associated with increased striatal dopamine concentrations 47. Loss of 
serotonergic stimulation could lead to an increase in emotional reactivity during nicotine withdrawal. In fact, 
drugs that increase serotonin by inhibiting the action of 5-HT1A receptors, block the increased startle response 
in animals undergoing nicotine withdrawal 48. Inhibiting the reuptake of serotonin also rapidly reverses the 
elevation in brain-stimulation reward thresholds observed in rats undergoing nicotine withdrawal 49. Balfour 50 
has suggested, however, that nicotine may ultimately decrease 5-HT in the hippocampus (possibly by 
increasing 5-HT1A receptors), an action that could be interpreted as depressogenic. Thus, continued smoking 
may be necessary to offset the negative affect associated with reduced serotonergic activity. Interestingly, 
Cheeta 51 has asserted that reducing serotonergic activity during nicotine withdrawal may also reverse the 
increase in ³anxiety´ observed in animals during a social interaction test. The implication for human studies is 
unclear. However, perhaps context (i.e., anxiety or fear inducing) can modulate the relationship between 
nicotine and serotonin. Acute administration studies suggest that serotonergic activity may have an inhibitory 
influence on the reinforcing properties of nicotine, either by reducing dopaminergic activity 52-55 or blocking its 
rewarding effects 56. Reductions in VTA firing rate 57, 58 and reduced self-administration of a variety of drugs of 
abuse 59-61 have been shown following administration of selective serotonin reuptake inhibitors. This would 
suggest that drugs that inhibit the reuptake of serotonin could modulate a smokers affect during cessation 
(their antidepressant effect) and perhaps reduce the reinforcing properties of smoking should they relapse. 
However, the selective serotonin reuptake inhibitors have not generally been effective for smoking cessation 
(see preliminary studies and 62-64) although there is some evidence to suggest that they may reduce craving 
and improve cessation rates among those who have some depressive symptoms 65. 
Serotonin transporters (SERTs) are principally responsible for the deactivation of serotonin and are 
high affinity targets for antidepressant medications 66. Altered SERT expression has long been suspected to 

 
 
 
contribute to anxiety and affective disorders 67 and serotonin reuptake inhibitors have been effectively used in 
their treatment. The connection between smoking, depression and negative affect is extensive and discussed 
in a later section of this review. Suffice it to say however, that the modulatory role of serotonin on mood, 
particularly negative affect, makes the serotonin transporter gene a plausible candidate for influencing 
emotional reactivity due to nicotine and nicotine withdrawal. A single gene, 5-HTT (SERT), encodes SERTs in 
the CNS. Its gene product modulates the magnitude and duration of serotonergic signaling by controlling the 
uptake of serotonin from the synaptic junction 68, 69. The 5-HTT is located on chromosome 17q12 and contains 
two polymorphic sites: a 5¶-flanking promoter region (5-HTT gene-linked polymorphic region or 5-HTTLPR) and 
a variable nucleotide tandem repeat (VNTR) of 17bp repeats in intron two. The 5-HTTLPR contains two allelic 
variants: either a long variant (L allele) due to a 44-bp insertion or a short variant (S allele) due to a deletion in 
the promoter region. These variants are believed to regulate HTT gene transcription. The S allele is believed to 
be a less efficient promoter than the L allele. The S allele reduces the transcriptional efficiency of the HTT 
promoter, therefore decreasing serotonin transporter expression and serotonin uptake 70. 
Current studies have assessed the relationship between smoking behavior and S allele or S/S 
genotype and the data has yielded conflicting results.  In a Japanese population, males with the S/S genotype 
were less likely to be smokers and more likely to stop than those carrying the long form of the allele (S/L & L/L 
combined)71. However, no association between the 3 different variants (S/S, S/L, L/L) and smoking behavior 
(e.g., quitting history, smoking rate, age on initiation) was found among either Caucasian or African American 
smokers 72. However, in a mixed racial sample, the personality trait neuroticism was positively correlated with 
current smoking status and measures of nicotine dependence (FTND) among smokers carrying the S allele 
(S/S and S/L combined) but not among L/L homozygotes 73, 74. We found the S/S genotype in bladder cancer 
patients was less prevalent in current smokers (12.3%) than in never smokers (37.5%) and former smokers 
(39.6%), and was associated with lower FTQ scores, fewer years of smoking and more quitting activity, 
compared to the S/L and L/L genotypes 75.  
 
The locus coeruleus (LC) is the major noradrenergic nucleus in the brain and its neurons are thought to 
regulate attention, vigilance, sympathetic nervous system activity, and to be implicated in the actions of stress, 
opiates and antidepressants76. Nicotine increases the firing rate and stimulates release of NA from the LC 77. A 
recent study suggested that the effects of long term smoking on the LC and on enzymes involved in the 
production of NA (tyrosine hydroxylase) are similar to the morphological changes seen in the brains of 
individuals who suffered from major depression 78 (i.e. down regulation of 
2-adrenoceptors). Noradrenergic 
projections to the hypothalamus and limbic system (e.g., amygdala and hippocampus) have received 
considerable attention in the study of depressive disorders79. The original hypothesis concerning the role of NA 
in the regulation of mood implicated hypofunction of the noradrenergic system in development of depression. 
Indeed the principal action of the tricyclic antidepressants (including nortriptyline) is inhibition of NA reuptake 
by high affinity targeting of the norepinephrine transporters66 thereby substantially increasing extracellular 
levels of norepinephrine. However, the therapeutic effect of these drugs is thought to result not from enhanced 
NA transmission but from some gradually developing neuroadaptations to enhanced NA 79. While conflicting 
studies exist, a recent review80 concludes that these drugs may achieve their therapeutic effect at least in some 
individuals by attenuating NA transmission, possibly by decreasing sensitivity and down regulating beta-
adrenoreceptor in the presence of the higher levels of NA. 
Just as there may be subtypes of depression that may differentially respond to different drugs, there 
may be important differences in how pharmacological treatments for nicotine dependence affect emotional 
reactivity during nicotine withdrawal. It is plausible that these differences could be related to genes that 
regulate NA activity, chiefly through controlling norepinephrine reuptake.  The human NET (SLC6A2) gene is 
located on the long arm of chromosome 16 (16q12.2 ) and its coding regions consist of 14 exons spanning 45 
kilobases (kb).  The NET shares a similar general structure with the DAT and the SERT, with an overall identity 
in amino acid sequences of 66% and 48% with the DAT and SERT, respectively 81. Thirteen DNA sequence 
polymorphisms have been described in the coding region of the NET gene 82, including five intron variants, 
three silent mutations and five variants predicting amino acid substitutions in the transporter protein (missense 
substitutions) 83.  

 
 
 
The most compelling evidence for the involvement of the NET in drug dependence comes from a series 
of elegant animal studies by Xu and colleagues 84. Using mice that completely lacked the NET gene (NET-/-) 
they showed that these animals had enhanced extracellular levels of NA levels and performed better (vigor in 
forced swim test) than untreated wild types mice in behavioral tests of ³despair,´ and the same as wild types 
treated with antidepressants. Importantly, the increased NA appeared associated with enhanced sensitization 
and reward salience to cocaine and increased sensitivity of D2/D3 receptors. However, it also down regulated 
dopamine receptors, suggesting it plays a role in dopamine homeostasis. While there have been no studies 
with nicotine and the NET, many animal studies have shown similarities between nicotine and 
psychostimulants suggesting that increased NA could play a role in nicotine reinforcement, perhaps by 
increasing its reward value and exacerbating the effects of nicotine withdrawal.  
There have been no association studies relating variations in the NET to smoking behavior. Little 
population data exists regarding the frequency of these polymorphisms although in one study at least 7 of the 
13 appear to have rare alleles 81 which would make them unlikely candidates for any relationship with smoking 
behavior. Recently, the G1287A/G NET polymorphism has received some attention in the study of major 
depression although findings to date have been negative 82, 85. However, the GG allele vs. the AA or AG alleles 
of this gene has been associated with enhanced norepinephrine turnover suggesting reduced transport and 
higher levels of NA for these individuals. The G1287A/G polymorphism is located in a non-coding region of the 
gene and while it may not directly influence NET activity, like other similar genes it may be in linkage 
disequilibrium (close to) with a functional polymorphism that does 86. It is, however, noteworthy that this is the 
first study to demonstrate a link between a NET polymorphism and NA. We have selected the G1287A/G 
polymorphism for exploratory analysis of the relationship of the NET to emotional reactivity, hypothesizing that 
the GG smokers may be more likely to show reduced emotional reactivity during nortriptyline therapy vs. 
bupropion or placebo, than their GA or AA counterparts. Although we have chosen the G1287A/G 
polymorphism for our initial hypothesis we will assay the remaining polymorphisms of the NET for additional 
exploratory analysis based on having sufficient frequency and power to detect differences if they exist. The 
cost for the NET assay will add only a fraction (less than $10/person) to our genotyping budget and may 
provide clues regarding the relationship of the NET to emotional reactivity. 
 
In conclusion, the majority of evidence linking smoking behavior to specific genetic polymorphisms has 
relied on gene association studies comparing smokers to former smokers or non-smokers. Not surprisingly, 
these studies have yielded mixed results because they rely on making gross distinctions in a behavior 
(smoking or not), as opposed to studying more specific aspects of the target behavior (i.e., craving negative 
mood). This is not a problem unique to smoking. Other areas of investigation relating polymorphisms to 
complex behaviors, such as major depression, bipolar and other affective disorders have also provided 
conflicting results when the phenotype is cast in all or nothing terms (see Blakely for review 66). Yet it would be 
hard to fathom that genes that influence neurotransmitter function, particularly dopamine, have no bearing on 
motivation, reward, the experience of pleasure or the modulation of mood associated with nicotine 
dependence, given the complex interactions between nicotine and these biogenic amines. Part of the problem 
may be that we are looking in the wrong place. Rather than focus on the presence or absence of a globally 
defined characteristic (e.g., smoking or not) we might do better by focusing on specific behavioral phenotypes, 
or endophenotypes, that can be tested for their relationship to genetic factors. Modulation of the startle 
response by affective cues is one such endophenotype.  It provides a continuous measure of emotional 
reactivity, associated with drive and motivation (e.g. appetitive-approach, escape-reward) and is much more 
likely to detect genetic differences among smokers. 
The negative findings for association between the DRD2 and DAT following bupropion treatment in the 
recent unpublished report by Lerman 29 deserve further comment in this regard because of their potential 
relevance to the current proposal. This study, like all of the others in this area focused, on relapse.  Although 
relapse is considered the ultimate outcome measure for evaluating smoking cessation treatments, like the 
smoker/nonsmoker distinction discussed above, it is a relatively gross measure (e.g. dichotomous outcome) 
that is insensitive to the subtle processes and mechanisms that ultimately lead to treatment failure (i.e., 
negative affect). Relapse is typically measured at time points quite distal to these events. Thus, it will fail to 

 
 
 
discriminate smokers on important characteristics revealed early in the cessation process, or even before 
quitting is attempted. For example, while treatment outcome studies have suggested a limited role for the 
DRD4 40 in smoking cessation, the study by Hutchinson 87 clearly shows its relevance to craving in response to 
smoking cues, a factor that could ultimately affect a smoker¶s ability to sustain abstinence. A similar argument 
may be made for the DRD2. For example, while no differences in long term relapse to bupropion treatment 
were found for the DRD2 in the Lerman report 29, important differences have been observed in the early phase 
of treatment in terms of both cessation and negative affect reduction 88. Moreover, in another report, Lerman 
and colleagues 89 have shown that a reduction in negative affect between the pre and 1 week post quit periods 
mediates the beneficial effects of bupropion on 8-week post-treatment abstinence rates, in the same sample 
used in the unpublished report mentioned above. However, an analysis of the negative affect data for a 
genotype by drug interactions has not yet been reported. Our studies (see preliminary studies) suggest that the 
impact of the DRD2 (and likely other candidate genes in the DA pathway) on smoking cessation is most 
pronounced early in the cessation process (i.e., the first few weeks). This is a time when negative affect may 
have its maximal effect of treatment success 90. We have also shown that pharmacological treatments 
(venlafaxine) differentially attenuate negative affect by genotype (DRD2), and this too happens early in the 
cessation process. Moreover, we have also shown in our preliminary studies that the startle response provides 
a highly sensitive measure of emotional reactivity before and during the first week of smoking cessation that is 
directly associated with genetic factors (DRD2). These associations have direct relevance for understanding 
the genetic contribution to negative affect during cessation, a factor that has major implications for quitting 
success. Therefore, we would argue that a focus on relapse alone is unlikely to shed much light on the 
relationship between genetics and mood during cessation, nor might it tell us much about whether certain 
pharmacological treatments (i.e. bupropion or nortriptyline) differentially modify mood during the early stage of 
quitting. Refining our measure of the endophenotype associated with candidate genes by using startle 
assessments of emotional reactivity is likely to be a more fruitful approach. 
 
Negative affect is related to smoking and poor treatment outcome among smokers trying to quit. 
Research on the relationship between negative affect and smoking cessation has included evaluation of the 
effects of a past history of diagnosable major depression, which may serve as a marker for vulnerability to 
future depressed mood, and evaluation of the effects of pre and post-cessation negative affect (self reported 
ratings of dysphoria, depression, tension, etc). A positive history of major depression 91 has been associated 
with an increased prevalence of smoking 92-95, nicotine dependence 92, greater nicotine withdrawal severity, and 
both increased depressive symptoms during nicotine withdrawal 96-98 and risk of a subsequent major depressive 
episode 99. History of major depression has also been associated with a reduced likelihood of quitting, 93, 100-103 
particularly among those whose symptoms rise after quitting 104, although the connection between relapse and 
depression history has not been uniform105-108. Several studies have also suggested that precessation negative 
affect may predict relapse 108-111 although these effects may diminish when accounting for past depression 90. 
[PC5]Negative affect following a quit attempt has been related to treatment failure and relapse across studies 
using a variety of treatment modalities (e.g., behavioral, nicotine replacement therapy (NRT), bupropion) 90, 112. 
Indeed, the presence of negative affect following cessation has been found to characterize over 50% of all 
smoking lapses, with 19% of all lapses occurring under conditions of extreme negative mood 42. Postcessation 
negative affect profoundly influences both the trajectory and duration of nicotine withdrawal 113 and the 
expectation that nicotine will produce desirable emotional consequences, particularly negative affect reduction, 
is an important predictor of cessation relapse and withdrawal severity 114. The subsequent loss of such means 
to manipulate mood when one abstains from smoking, increases negative affect and raises the likelihood of 
relapse.  
An improved understanding of the effects of smoking cessation on mood appears to be a critical step 
toward the development of new behavioral and pharmacological treatments for nicotine dependence. Previous 
investigations of smoking and mood have relied heavily on patient self-report, such as ratings of stress during 
regular smoking 115, or studies of the mood correlates of smokers trying to quit (e.g. 42, 116). These studies have 
yielded important findings regarding the relationship between normal smoking behavior, relapse and negative 
mood. However, traditional means of self-report require extensive cognitive processing and may not be 

 
 
 
sensitive to some of the subtle yet important changes in affect during cessation. Moreover the assessment of 
mood by retrospective self-report in clinical studies is far less sensitive to the changes in affect associated with 
smoking behavior than information collected while smoking is taking place or during extended periods of 
abstinence (ecological momentary assessment, 42, 117). The startle response, on the other hand, is immediate 
and sensitive to ambient emotional cues, and could prove to be a reliable indicator of the effects of nicotine 
withdrawal on a smoker¶s affect.  
 
The startle (eye blink) response is an orienting reflex, which occurs during the presentation of 
unexpected auditory stimulus (probe). Its strength is measured by the electromyographic (EMG) changes in 
the orbicularis oculi region of the eye. It is well established that the magnitude of the blink (EMG) response to 
the startling acoustic probe varies according to valence of emotional cues presented during the startle 
assessment. For example, blinks are enhanced when subjects view unpleasant rather than pleasant pictures 
(e.g., 118, 119) and are reduced during viewing of positive as opposed to negative or neutral emotional cues 120. 
Moreover, the startle response to both positive and negative affect cues is maintained after accounting for any 
habituation-related decrement in blink magnitude 121. The robustness of this affect-startle effect has been 
demonstrated across a variety of populations including college students, incarcerated prisoners 122, anxious 
and phobic patients 123, 124, and 8-month-old infants 125.  An exaggerated startle response to negative emotional 
cues has been associated with induction of negative moods using verbal scripts among normals 126, early 
phases of post-traumatic stress disorder 127, exposure to fear relevant stimuli among phobic patients 124 and 
those with social anxiety 128. 
This interplay between the strength of the startle response and foreground emotional cues is thought to 
reflect the influence of affective perception on the activation of underlying mechanisms governing motivation 129, 
130. Negative affect normally activates the defensive system and motivates avoidance or escape. Positive affect 
stimulates the appetitive system and motivates approach and exploratory behavior. Thus, an independently 
evoked defensive reflex, such as the startle response, provides a measure of emotional reactivity of the 
organism to its environment. Reactivity is augmented when the organism perceives an unpleasant stimulus 
since the aversive/defensive motivational system is engaged. However, this same reflex will be reduced in 
amplitude when the organism is processing positive emotional cues, which activates the appetitive or approach 
motivational system 129, 130.  
These dynamic characteristics of the startle response have important implications for the study of drug 
motivation and nicotine dependence, since the engagement of the aversive emotional system would appear to 
be an obvious consequence of negative affect experienced during nicotine withdrawal. Improving our 
understanding of factors that modulate this response, including pharmacological and genetic ones, can have 
important implications for the treatment of nicotine dependence. For example, we may show that bupropion or 
nortriptyline has differential effects on startle magnitude in the presence of negative emotional cues, and these 
effects are modulated by genotype. If successful, future studies could use this approach to determine which 
candidate drugs or behavioral procedures provide an optimum level of affect modulation during nicotine 
withdrawal, and for which participants. Intervention procedures could be easily compared in the laboratory 
before launching larger field investigations to test their efficacy and a detailed profile of the differential 
effectiveness of certain treatments could be ascertained However, before any of these potential treatment-
matching scenarios can be realized, basic laboratory work as proposed in the current study must be carried 
out. 
 
Bupropion (Amfebutamone) is an antidepressant that is chemically dissimilar to tricyclic, 
tetracyclic, selective serotonin re-uptake inhibitors (SSRIs), or other antidepressants. The sustained-release 
(SR) form of bupropion was approved as non-nicotine based pharmacotherapy for smoking cessation in 1997. 
Bupropion¶s mechanism of action is thought to be mediated through both dopaminergic (DA) and 
noradrenergic (NA) systems. Findings from in vitro experiments suggest that bupropion is a modest inhibitor of 
DA uptake and weak inhibitor of NA uptake 131. In vitro, bupropion¶s potency score for NA and DA reuptake 
inhibition (lower scores=more potency) is 1400 IC50 and 570 IC50, in comparison to 3.4 IC50 and 3500 IC50 for 

 
 
 
nortriptyline, respectively 132. Nortriptyline is one of the most potent NA reuptake inhibitors. Bupropion produces 
a dose-dependent increase in dopamine concentrations in the nucleus accumbens in the mesolimbic system of 
rats 133. Terry and Katz 134 also found that rats trained to bar press in response to bupropion injection would 
exhibit the same behavior when they were injected with other dopamine reuptake blockers. In all, 9 of 10 
tested dopamine uptake inhibitors fully substituted for bupropion. None of the serotonin or norepinephrine 
uptake inhibitors tested achieved either full or partial substitution. Thus, it has been suggested that bupropion¶s 
mechanism of action in smoking cessation is mediated at least in part, by the stimulatory effects it has on the 
mesolimbic dopamine system 135. Other researchers suggested that bupropion may also act as a nicotine 
antagonist , which might reduce the reinforcing properties of nicotine. For instance, Slemmer and her 
colleagues136 reported that bupropion selectively blocks nicotine¶s antinociceptive, motor, hypothermic, and 
convulsive effects in rats. It also blocks the activation of a number of nicotinic acetylcholine receptors 
(nAChRs) that include [BS6]
3
2, 
4
2, and 
7.  
Interestingly, studies examining bupropion¶s antidepressant effects suggest it is more effective in 
suppressing the firing rate of norepinephrine than dopamine neurons at locus coeruleus in rats 137, 138. A 
decrease in neuronal firing rate is an indication of high level of synaptic norepinephrine concentrations possibly 
caused by a blockade of neurotransmitter reuptake. Thus, it is suggested that bupropion¶s antidepressant 
effects may be mediated through noradrenergic rather than dopaminergic pathways.   
A number of studies have demonstrated that bupropion SR is an effective treatment for smoking 
cessation 139-142. Abstinence rates in one of the first clinical trials 140 averaged 19.0% vs. 44.2% at the end of 
treatment and 12.4%, vs. 23.1% at the end of one year, for the placebo and 300mg bupropion, respectively. A 
similar cessation advantage for either bupropion alone or bupropion combined with a nicotine patch was noted 
in a subsequent trial 141. Extended use of bupropion has also been shown to prevent relapse 139. With respect to 
mood and withdrawal symptoms measured during drug treatment, withdrawal symptoms were generally higher 
in the placebo vs. active drug group in these studies, but no differences in depressive symptoms, as measured 
by the Beck Depression Inventory (BDI), have been observed. In contrast, negative affect reduction as 
measured by the PANAS (Positive and Negative Affect Scale 143), was found to be a significant mediator of 
bupropion¶s efficacy 89. The PANAS is robust measure of negative affect in smoking cessation trials 90, while 
few studies support such a role for the BDI. The BDI is a better measure of treatment outcome for depression 
and these clinical trials exclude individuals who meet criteria for major depression so, it is unlikely this measure 
would provide much information.  
Nortriptyline is a tricyclic antidepressant that has highly specific effects on NA reuptake 
inhibition 132. It is10 times more potent than venlafaxine (a drug used in our previous studies) in this regard and 
about 7 times less effective at serotonin reuptake inhibition. In contrast to bupropion, it is almost 50 times more 
effective at NA reuptake inhibition but 6 times less effective at dopamine reuptake inhibition (in vitro) 132. In the 
most recent Clinical Practice Guidelines, nortriptyline has been recommended as an effective treatment for 
smoking cessation 144. Prochazka 145 showed that nortriptyline produced significantly higher sustained 
abstinence rates over a 6 month period compared to placebo (14% versus 3%, respectively). Participants who 
received nortriptyline also experienced less severe withdrawal symptoms including craving, anger/irritability, 
anxiety, concentration difficulty, restlessness, impatience, and insomnia. Hall and colleagues 146 have also 
shown that independent of depression history, participants who received nortriptyline achieved a significantly 
higher sustained (12 months) abstinence rate than those received placebo (24% versus 12%, respectively). 
 
 We recently completed a study evaluating the relationship between cessation treatment outcome and 
the DRD2 A1 allele. Participants were 134 smokers that took part in a larger clinical trial evaluating the effects 
of an antidepressant medication (venlafaxine or placebo) plus standard care (brief counseling and nicotine 
replacement). Venlafaxine is an antidepressant that inhibits the reuptake of serotonin and to some extent 
norepinephrine. We hypothesized an overall poor response rate for smokers carrying the A1 allele, which 
might be improved with the addition of the drug to the treatment regimen, particularly for those with high levels 
of negative affect. The results from this trial showed significant overall treatment effects at the end of the 18-
week drug intervention (37% vs. 25%) but no interaction with depression history or genotype was observed. 

 
 
 
Abstinence at the one-year follow-up, while higher in the active drug group, did not significantly differ from the 
control 147. However, we did find a main effect for genotype on 
abstinence. Smokers carrying the DRD2 A1 allele (A1/A1/A2) quit 
significantly less often than the homozygous A2s (F (1,131)=4.14, p=.04; 
OR=1.82, 95% CI=1.02, 3.32)148. This effect was most pronounced 
during the early weeks of quitting. Moreover, as shown in 
we 
noted a significant pharmacogenetic effect of the drug on negative mood 
while quitting. Smokers absent the A1 allele (A2/A2) responded to the 
drug with a substantial reduction in negative affect during the entire post-
quitting period for which it was available (F (1,130)=6.71, p=.01). These 
effects were reversed when the drug was withdrawn. In contrast, 
smokers carrying the A1 allele, showed no significant reduction in 
negative mood during drug therapy 88. These results are contrary to what 
we expected ,but if the A1 allele is implicated in reduced DA 
transmission, the results may be due to the relatively weak DA and NA 
reuptake properties of venlafaxine. While efficacious in the treatment of 
depression, in comparison to other antidepressants, venlafaxine is 
almost 5 times less effective than bupropion at DA reuptake, 10 times 
less effective at NA reuptake inhibition than nortriptyline and is among 
the least potent inhibitors of serotonin reuptake of all the SSRIs 132. We 
[PCP7]conclude that genotype is important for predicting abstinence but 
venlafaxine, and likely other drugs in this class (SSRI) are unlikely to be effective for the control of negative 
affect during cessation, for the A1 smokers. The current study will ascertain whether bupropion (or 
nortriptyline) can differentially modify emotional reactivity of A1 or A2 smokers tying to quit, and whether or not 
this ultimately leads to a better treatment outcome[PCP8].  
During the last two years we were part of a Lung Cancer SPORE (P50CA70907) that provided the 
support for preliminary data described below. The goal of this project was to characterize the endophenotype 
associated with potential genetic markers of nicotine dependence (e.g., DRD2 A1 and others), using 
psychophysiological measures of emotional reactivity (startle) and measures of negative affect during a 
cessation attempt. The methodology is similar to that proposed for the current proposal. Smokers, with an 
expressed interest in quitting were recruited from the general community and randomly assigned to Quit and 
Control conditions. All participants were exposed to four laboratory startle assessment sessions:  (1) baseline, 
(2) 1-1.5, (3) 3-5, and (4) 10-14 days post-quit in the Quit group and at the corresponding points in time for the 
Control group. Each session involved the presentation of slides from the International Affective Picture 
System149, of positive, negative and neutral valence, plus slides of smoking cues. Three of four slides within 
each category were paired with an acoustic probe resulting in the startle response (see methods section). 
Smokers in the Quit group were asked to quit smoking following their baseline assessment while those in the 
Control Group were asked to smoke normally this time. Smokers in the Quit group received a program of 
behavioral counseling to facilitate abstinence.  Controls were treated following their last laboratory 
session[PCP9]. 
 
 

 
 
 
[PCP10]. The startle and physiological data for 96 [PCP11](57-Treatment and 39-Controls: Note 
randomization is done on approximately a 2:1 ratio) of 150 
planned participants have been processed and were available 
for analysis at the time of this writing. In the Quit group, 28 
(50%) were abstinent on the quit date and at every session 
thereafter, while 16 (30%) relapsed some time after the quit 
date and 13 (20%) failed to abstain on their quit date and 
smoked more than one cigarette at each of the post quit 
assessments.  Genotyping [PCP12]information (DRD2) is 
currently available on 62 participants (34-Treatment and 28-
Controls). The proportion of participants carrying the A1 allele 
(A1/A1 or A1/A2) did not differ by group (
2.<1, p=>.05), 
gender (
2 <1 p>.05), race (
2=3.1, p=0.08), or abstinence 
status (
2=3.89, p=0.28). 
Our results showed that daily 
cigarette consumption did not differ between the Quit 
(22.5/day) and Control (21.4/day) participants or 
between A2 (21/day) and A1 (18/day) participants at 
baseline. However, as shown in 
 after the quit 
date all smokers in the Quit group, regardless of 
Abstinence status (Relapsers, Abstainers and Never 
Quitters) or Genotype significantly reduced their 
cigarette consumption (F(9,92)=28.14, p=.0001- for the 
Time by Abstinence status interaction). Over the two- 
week post-quit period, Abstainers dropped to zero 
cigarettes/day; both Relapsers and Never Quitters 
averaged well below their baseline; and Controls 
showed no significant reduction in smoking. At the same 
time, all smokers in the Quit group, independent of 
abstinence status, experienced a significant increase in 
PANAS negative affect scores (F(9,91)=3.99, p=.0003- for 
the Time by Abstinence status interaction), reflecting the 
adverse effects of nicotine withdrawal. Given these 
facts, some analyses described below include all 
smokers in the Quit group as well as breakdown by 
Abstinence status. This practice is often followed in 
clinical trials that examine the effects of a particular 
treatment on the post quitting nicotine withdrawal or 
negative affect for all smokers exposed to the 
intervention.  
A 
significant group (Quit vs. Controls) by Genotype 
interaction was observed for PANAS negative affect 
scores (F(1,58)=10.57, p=.0001), with A1 Quit participants 
being the highest. Baseline differences using an a priori 
contrast (F-test for simple effects) showed no 
differences by Group or Genotype. However, 
comparisons at subsequent time points showed negative affect of A1s in the Quit group exceeded that of 
controls while the same was not true of the A2s. Analysis by Abstinence status (Abstainers, Relapsers, Never 
Quitters and Controls) also showed a significant Abstinence X Genotype interaction (F(3,54)=6.63, p=0007) for 
 
 

 
 
 
PANAS negative affect. Contrasts at each of the sessions revealed that among the A2s, negative affect did not 
differ by abstinence status, at any time point. However, as shown in Figure 3, among the A1s, Never Quitters 
and Relapsers experienced the highest level of negative affect followed by Abstainers and then Controls. We 
repeated this series of analyses controlling for the following variables: hours continuously abstinent at the time 
each post quit assessment; number of cigarettes smoked in between sessions; race; and gender. No 
differences in the results were noted. 
To evaluate the hypothesis that startle 
responses to negative stimuli would be enhanced compared to neutral and positive stimuli, we first examined 
the baseline startle responses of all participants. This analysis may be regarded as a validity check for our 
procedures ensuring that we can replicate the basic valence modulation effect on startle. We used mixed 
model linear regression with startle amplitude from the baseline session as the dependent variable and 
valence as the independent variable. The model included the value of the startle response to neutral stimuli as 
a covariate. In this way, we could compare the relative magnitude of startle responses to negative and positive 
stimuli, adjusted for the response to neutral cues. A significant effect due to valence was found in the expected 
direction (F (1,93=44.40, p<.0001), with responses to negative stimuli (Lsmean=92.66 uV, SE=2.44) being 
significantly higher than responses to positive stimuli (Lsmean=77.23 uV, SE=2.21). No significant differences 
were noted for main effects due to Group (Quit vs. Controls), gender or race. Thus, all smokers (regardless of 
group) responded similarly to negative cues at baseline. 
When we examined baseline startle responding to 
positive and negative stimuli (adjusted for neutral responses), significant differences (F (1,58) = 8.52, p=0.0005) 
were noted by Genotype (A1s vs. A2s). As shown in Figure 4, smokers carrying the A1 allele showed a 
significantly higher response to both negative and positive stimuli than those with the A2 allele. We also 
evaluated responding to smoking cues (pictures of cigarettes, people smoking, ash tray, etc.) at baseline and 
found that overall reactivity to smoking cues was similar in magnitude to that of positive pictures for both 
groups, although higher responses were observed for the A1s. Interactions with Group (Quit/Control) were not 
observed. Genotype main effects remained significant when controlling for gender or race. The [pmc13]results 
suggest that the startle response is a useful tool for detecting baseline (smoking and non deprived) differences 
in emotional reactivity that at least in part, are genetically mediated. Moreover, taken together with the PANAS 
data shown in Figure 3, our results suggest that the A1¶s enhanced emotional reactivity to both negative and 
positive stimuli seen at baseline, may be assessing a dimension of pre-quitting emotional reactivity not 
apparent on the baseline PANAS. It may also presage the increased negative affect observed during the first 
week of quitting for all the A1s but not the A2s in the Quit group.  
 
 In this series of 
analyses, startle responding served as the dependent 
variable, with Valence (negative, positive, cigarette) 
and Time (baseline, post-cessation days 1-1.5, 3-5 
and 10-14 and corresponding time points for the 
controls) as within subjects factors. Abstinence status 
(Abstainer, Relapser, Never Quitter and Controls) and 
Genotype (A1/A1/A2 vs. A2/A2) were the between 
subjects factors. Responses to neutral stimuli served 
as the covariate. A significant interaction was 
observed for the Valence X Time X Abstinence X 
Genotype component (F(27,54)=3.39, p=.003). This 
interaction, while seemingly complex, produced some 
very interesting and robust findings. To parse the 
interaction, we first used a series of contrasts to 
evaluate the differences within the Genotype by 
Abstinence status combination, at each session. 
Separate analyses were carried out for each Valence. 
Given our space limitations we present graphical 
images for the results involving only negative and 

 
 
 
positive stimuli, as they are of primary interest to our study. It should be noted that the main effects of 
Genotype and Valence were maintained within this analysis, with overall responding of the A1s being greater 
than the A2s, and startle to negative pictures exceeding those to positive and cigarette pictures.  
As shown in Figure 5, the results for negative valence show that A2 Abstainers, Relapsers and Never 
Quitters, and Controls, differed neither at baseline nor at any subsequent point in time. However, A1 Relapsers 
were higher than all other A1 or A2 groups, including controls, at baseline and remained that way until the final 
assessment, at which time their reactivity rebounded below their initial baseline level. Moreover, A1 Relapsers 
reacted sharply to negative stimuli during the first 24-36 hours of withdrawal, increasing startle even further 
above the A1 Controls, Abstainers or Never Quitters. No such increase was observed for the A2s. The 
response of the A1 Relapsers to positive stimuli at baseline, while well below their response to negative cues, 
was also significantly above all other A1 or A2 groups. The response of the A1 Relapsers to positive cues did 
not rise during the 1-1.5 day period following quitting, as it did for negative cues. However, their response to 
positive cues dropped below their baseline by the end of the two-week post-cessation period. A1 Never 
Quitters showed the lowest baseline response to positive stimuli of all the groups, and fluctuated little during 
the post quit assessments, with the exception of a slight rise in reactivity at the 10-14 day post-quit mark. A1 
and A2s also differed in their reaction to cigarette pictures. For the A2s, reactivity to cigarette pictures was 
similar in magnitude to positive stimuli across all post-quit sessions. However, the reactivity of all A1s to 
cigarette pictures was significantly below their responding to positive cues, at the post-quit assessments. 
 Given the clear baseline differences between A1 and A2 smokers, we also evaluated startle 
responding during cessation, using the baseline level of responding as a covariate in the models described 
above. The results were similar to our earlier analyses: an interaction was observed between Abstinence 
status, Genotype, Time and Valence (F(18,54)=2.75, p=.002). A significant increase in startle responding to 
negative stimuli for the A1 Relapsers was noted at the 1-1.5 day mark, followed by a dramatic decline at two 
weeks post-quit, consistent with our earlier findings.  
 

 
 
 
Our analysis of this data will continue but these interim results suggest several interesting findings. 
First, it appears that smokers carrying the A1 allele are predisposed to higher levels of emotional reactivity at 
baseline (normal smoking), suggesting a greater activation of defensive motivational systems than the A2s. 
Moreover, these differences appeared to be enhanced by a cessation attempt, as evidenced by higher levels 
of reactivity of all A1s in the Quit group, regardless of abstinence status. A1 smokers who are destined to 
become relapsers are more reactive than all other groups, even at baseline, and significantly increase 
reactivity to negative cues during first 1-1.5 days of abstinence. This is often regarded as a vulnerable time for 
relapse and startle reactivity to negative stimuli may provide a way to differentiate those who are most 
vulnerable to relapse in the early phase of quitting. The rise in reactivity is likely a response to acute nicotine 
deprivation, and it would appear to reverse by day 3-5, and 10-14, as the Relapsers return to smoking. The 
reason for the rebound below baseline at 10-14 is unclear but it could signal significant suppression of 
emotional reactivity as they return to smoking, consistent with the acute effects of nicotine observed in our 
other studies150. In addition, relapse (smoking) not only suppresses defensive activation to negative cues, but 
increases approach motivation to positive cues, as evidenced by the reduction in reactivity of the Relapsers to 
positive stimuli. Cessation may also differentially affect approach motivation associated with smoking cues. 
Among the A1s, startles are lower to smoking cues vs. other positive stimuli, possibly signaling an increase in 
approach motivation for smoking cues, during cessation. The same is not true of the A2s. While further work is 
needed to clarify these results, such differences may be related to an increased saliency of the reinforcer (e.g., 
cigarettes), which for the A1s may be evidence of a narrow reinforcement gradient (i.e., drug related stimuli 
have greater motivational significance than other positive events).  
 
We have also completed some preliminary analyses involving some of the other genotypes, noting 
Group (Quit vs. Control) by genotype interactions for the SERT and DRD2 B1, similar to what we found for the 
A1. These analyses were not complete at the time of this writing but the results for the B1 are very similar to 
what we observed for the A1. In addition, an interesting finding was observe for the SERT. Smokers carrying 
the S/S form of the SERT show a significant decline in startle following abstinence, whereas those with the S/L 
or L/L polymorphism show a significant elevation. This meaning of this finding is unclear but suggests that like 
the A1s, S/L or S/L smokers are more likely to react to nicotine withdrawal with enhanced activation of 
avoidance pathways, but emotional reactivity of S/S smokers is reduced.  In one of our recent studies 75 we 
have found evidence of reduced nicotine dependence among S/S smokers. Individuals with this genotype are 
thought to have higher levels serotonin than those with S/L or S/S genotypes and this might reduce their 
dependence on nicotine (e.g., they may have less need to use nicotine for affect regulation). We did not find 
evidence in this preliminary analysis of higher levels of negative affect (PANAS) for Treatment S/S-S/L 
smokers, but this remains a question to be addressed as we accrue more participants.  
 
The main objectives of this study are to assess the effects of bupropion and nortriptyline on smokers¶ 
emotional reactivity during a quit attempt, as assessed by startle responding to positive and negative emotional 
cues, and smoking related stimuli; whether this emotional reactivity predicts time to relapse; and, if genetic 
differences in influence the magnitude of these effects. The present study will use a 3x4x4 repeated measures 
design, with Group (Bupropion/Nortriptyline/ Placebo) serving as the between groups factor, and Days (days 
post-quit/laboratory assessments) and stimulus valence (positive, negative, neutral, cigarette) serving as within 
subject factors. The sample will be stratified for race, gender, previous history of major depression, and the 
DRD2A1/A2 genotype, since the DRDD2 marker is of primary interest. As shown Figure 6, 354 smokers will be 
exposed to four laboratory assessment sessions over a period of 38 days.  Medication will be administered in a 
blinded fashion.  Participants will complete a baseline laboratory session before any treatment begins (while 
still smoking).  Immediately after their baseline laboratory session participants will be randomized into one of 
the three treatments and begin taking the appropriate medication.  After ten days of medication, all groups will 
quit smoking for the duration of the study.  Participants in all groups will also receive a series of in-person 
smoking cessation counseling sessions, two prior to quitting and five after the quit date, plus a series of 
telephone counseling calls at selected intervals in between the in-person counseling sessions.  After 
completion of all laboratory and counseling sessions, all participants will return for follow up assessments at 3 

 
 
 
 
Volunteers from the 
Houston Community 
Telephone 
assessment for 
Incl./Excl. criteria 
Informed consent 
Medical Screening 
Demographics, 
questionnaires 
SCID assessment 
for past Major 
Depression 
Genotyping 
Startle probe assessments @
Baseline (pre-treatment)
2 day post quit (1-2)
5 days post quit (3-5)
28 days post quit (27-30)
Group comparisons at each time  
Post Cessation Follow-up @
3 months
6 months
N=354 stratified by gender, 
race depression history, & 
DRD2 genotype 
Bupropion  
Nortriptyline  
Placebo  
Medication initiated 10 days 
prior to quitting for 12 weeks 
All receive individual 
counseling and telephone 
support 
months (10 days after medication ends) and 6 months post quit.  In addition, telephone assessments of 
abstinence status will be carried out 2 and 4 months post-quit. A study time line is provided on page 20. 
Participants who want to quit smoking will be recruited from Houston 
metropolitan area using newspaper, 
radio and TV public service 
announcements, feature articles in the 
MD Anderson newsletter, and posted 
flyers. They will be offered monetary 
compensation for their time and for 
maintaining their abstinence. We 
expect to have no difficulty recruiting 
the needed number of smokers. The 
psychophysiology laboratory is a 
resource of the MDACC Tobacco 
Research and Treatment Program 
(TRTP). The TRTP is directed by the 
PI and has a high degree of 
community visibility. We have had 
considerable success recruiting 
participants for our clinical trials 
research. 
The 
population of the greater Houston 
community from which the sample will 
be drawn (Harris and its 6 adjacent 
counties) is estimated at 4,636,908 
people. The ethnic distribution has 
been reported as 73.5% Caucasian; 
18.4% Hispanic or Latino (of any 
race); 12.6% African-American; 3.2% 
Asian; and .5% Native American, 151.  Although the literature on the 
relationship of the DRD2 A1 allele to alcoholism 152, cocaine 153, other 
substance abuse 15, and smoking 24, 154 has been largely limited to 
Non-Hispanic Caucasians and some studies with African Americans 
40 155, we will recruit without regard to race or ethnicity, as we did in 
our preliminary studies.  As described in the Inclusion Enrollment 
Report (see Table 6) we have had reasonable success recruiting from 
ethnic minority populations. 
All smokers will be 
prescreened by telephone for basic eligibility requirements (see Table 
1). An initial description of the study design will be provided and data 
will be obtained on age, smoking history, other tobacco use, medical 
history, medication use, and pregnancy/lactation status. Participants 
will also be administered a version of the PRIME-MD, modified for 
use over the telephone (see 
). The PRIME-MD screens 
for the five major mental disorders (DSM-IV) commonly encountered 
in the general population (mood, anxiety, somatoform, alcohol, and 
eating disorders). The PRIME-MD consists of a 25-item patient self-
report questionnaire, which is administered first, and is followed by a 
more detailed interview, if the participant endorses a sufficient 
number of positive responses on the questionnaire. Follow-up items 
 
Inclusion Criteria: 
Age: 18-60 years old 
Ethnicity: All 
Smoking: >10 cigarettes per day & expired 
CO > 10ppm. 
English speaking & have a telephone 
Other: provide informed consent & agree to 
all assessments & study procedures 
Exclusion Criteria: 
Current psychotropic medication or current 
(w/i 6mo.) psychiatric disorder (PRIME-MD). 
Involvement in any smoking cessation 
activities 
Contraindications for bupropion (e.g., history 
of seizure disorder) or nortriptyline (e.g., 
alcohol dependence) 
Uncontrolled Medical Illness 

 
 
 
are used to determine if DSM-IV criteria are met for these current psychiatric disorders and adequate reliability 
and validity have been demonstrated 156. Our experience administering this instrument and a subsequent SCID 
(Structured Clinical Interview for DSM-III-R, 157 in another study 158, suggests that the phone based PRIME-MD 
successfully eliminates virtually all smokers with current psychiatric disorders[PMC15]. Administering the 
telephone screening takes 10-15 minutes and places a minimal assessment burden on potential participants.  
All subjects who remain eligible after pre-screening will be scheduled for 
subsequent in-clinic screening visit. Following an initial orientation and explanation of the study, interested 
participants will be asked to provide informed consent and complete additional assessments as shown in 
 

 
 
 
STUDY TIME 
FRAME 
0 
3 
10 
17 
20 
21 
22 
23 
24 
 
25 
32 
39 
46 
48 
78 
94 
104 
134 
202 
-20 
-17 
-10 
-3 
0 
1 
2a 
3 
4 
 
5b 
12 
19 
26 
28c 
58 
74 
84 
114 
182 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1 
2  
 
3 
4  
6 
 
 
1 
 
 
 
 
 
 
 
 
 
 
 
 
 
12 
 
 
 
TYPE OF 
CONTACT 
Inclusion Exclusion 
Criteria & Prime 
MD 
X 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
 
 
 
X 
 
 
 
X 
 
 
 
X 
 
 
 
 
 
 
 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
 
 
 
 
 
 
 
 
 
X 
X 
 
X 
X 
 
 
 
 
X 
 
 
 
 
 
 
ASSESSMENTS 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
 
 
X 
 
 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
 
 
 
 
X 
 
 
 
 
 
 
 
 
M 
 
X 
M 
X 
 
X 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
  
 
X 
 
X 
 
X 
X 
X 
X 
X 
X 
X 
X 
 
X 
X 
X 
X 
X 
X 
 
X 
X 
X 
 
X 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
 
 
X 
 
X 
 
X 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
 
 
X 
 
X 
 
X 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
 
 
X 
 
X 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
 
 
 
 
 
 
 
X 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
 
 
X 
 
 
 
 
 
X 
 
 
X 
 
 
 
X 
X 
X 
 
X 
X 
 
X 
X 
 
 
 
 
X 
 
 
 
 
 
 
X 
 
 
 
 
 
 
 
 
 

 
 
 
- Range of 24-36 hrs; 
Range of 3-5 days
- Range of 26-30 days - Phone Interview only; 
- mail cotinine 
requested for abstainers only; 
 
 
Medical screening for potential contraindications for either bupropion or nortriptyline use will then be 
conducted by our study physician, Dr. Walter Baile. These conditions include the presence of a seizure 
disorder, a history or current diagnosis of eating disorders (bulimia or anorexia), recent myocardial infarction, 
hypersensitivity to tricyclic antidepressants or bupropion, concomitant use of monoamine oxidase, tricyclic 
antidepressants, or other bupropion products. Standard blood chemistries may be ordered as medically 
appropriate to evaluate a participant¶s health status. Furthermore, to identify cardiovascular or other 
exclusionary conditions for nortriptyline use, all participants will receive a 12-lead electrocardiogram before the 
initiation of medications.  
History of Depression 
 All eligible smokers will also be evaluated for current and history of Major Depression using the 
Affective disorders portion of the SCID 156, 157 administered at their orientation visit. Eligible participants who 
meet criteria for past major depression (>6 months previous) will be categorized as history positive. The 
current depression section of SCID will also provide a cross check on our initial screen for current depression 
serving to exclude those initially classified as not currently depressed but who meet diagnostic criteria for 
current depression, at the interview. It should be noted that this happens relatively rarely, occurring in only 2 of 
165 participants in a recent clinical trial. Reliability and validity of the SCID has been adequately demonstrated 
in both non-patient 157 and substance abusing populations 159.  
 
As shown in Table 2 participants will be asked to complete additional assessments throughout the 
course of the study. Brief descriptions of these assessments are provided below and copies of individual 
instruments have been provided in 
. 
The Demographic, Health and Smoking Health Questionnaires  
These instruments expand on the data obtained during the pre-screening, providing more detailed 
information on demographics, health/medication history, alcohol, caffeine, and other drug use, for use in the 
medical screening. Information on smoking history (e.g., years smoked, previous quit attempts, relapse, 
current smoking rate, and other nicotine/tobacco use) is also obtained. These questionnaires have been used 
in our previous and current cessation studies to provide descriptive data for the study population (e.g., 160, 161). 
The Fagerstrom Test for Nicotine Dependence (FTND)  
The FTND is a 6 item questionnaire that measures nicotine dependence by assessing various 
components of smoking behavior such as daily intake, difficulty in refraining from smoking, time to first 
cigarette, etc.162, 163. In some studies, the scale has been found to correlate with cotinine level 164, 165 and to 
predict smoking treatment outcome 166. It was modified from the most commonly used nicotine dependence 
measure, the Fagerstrom Tolerance Questionnaire 167. 
The Positive and Negative Affect Scale (PANAS)  
The PANAS 143 is comprised of two 10-item mood scales: Positive Affect (PA) and Negative Affect 
(NA). Participants rate different feelings and emotions on a scale of 1-5.  Various time instructions (e.g., today, 
past few days, past week, general, etc.) have been used with acceptably high alpha reliability ranging from .86 
to .90 for PA and .84 to .87 for NA. Post-cessation PANAS negative affect is a robust predictor of relapse 90. 
The Center for Epidemiologic Studies Depression Scale (CES-D)  
The CES-D is a 20-item self-report measure developed to [PMC16]assess depressive symptoms in community 
(nonclinical) populations 170 and in recent studies of smoking cessation 110. This scale consists of four factors: 
depressed affect, enervation, lack of positive affect and interpersonal problems. 

 
 
 
Smoking Status Questionnaire (SSQ) & Expired CO  
The SSQ is a 16-item interview administered questionnaire that will be used to assesses smoking behavior 
and abstinence throughout the course of the study. Abstinence will be verified by an expired CO reading of < 
8ppm at each in-person measurement occasion. Using a time-line follow back procedure all smoking in 
between assessments will also be recorded.  
Nicotine/Cotinine   
Cotinine is the first metabolite of nicotine and has a half-life of about 20 hrs; nicotine has a half-life of 
approximately 2 hours 171. Saliva nicotine levels will be assessed immediately following smoking in the baseline 
laboratory assessment. This will allow us to quantify available nicotine, immediately before the startle probe 
assessment. Cotinine data also obtained at this time will provide information regarding the participant¶s 
tobacco exposure within the previous 24 hours. Baseline cotinine values will be used in the descriptive analysis 
of smoker characteristics, along with other variables from the smoking history questionnaire. Cotinine values 
(<25ng/ml) from subsequent assessments will be used as a crosscheck on abstinence requirements as 
described below (see Abstinence compliance following startle assessments page 25). Dr. Helen Van Vunakis 
of Brandeis University has agreed to analyze the samples for nicotine and cotinine using the HPLC method of 
Hariharan & VanNoord 172. This assay provides sensitivity to <1ng/ml of nicotine and cotinine. Dr. Van Vunakis¶ 
laboratory does the cotinine and nicotine assays for our current clinical studies. We anticipate no problems in 
transporting samples or obtaining valid results. 
Adverse Event Monitoring & Concomitant Medication  
At each of post-baseline laboratory and in-person counseling session, participants will be assessed for 
side effects and concomitant medications using standard FDA guidelines recommended for these two 
procedures. Adverse events will be reviewed by our study physician who will recommend changes in dosage 
or other clinical intervention as appropriate for the event. Adverse event monitoring will continue up to 30 days 
after medication is completed, or longer if on going events are observed. 
Eligible volunteers will be asked to provide a blood sample during the orientation visit for 
conducting genetic analyses. Genotyping assays are described in the 
 and summarized below. 
Genomic DNA will be extracted from each coded blood sample for polymerase chain reaction (PCR) analyses 
using standard phenol extraction methods. 
DRD2  
Genotyping for the DRD2 TaqI A and TaqI B polymorphisms will follow the procedures of 26.  Smokers 
will be categorized into three DRD2 TaqIA genotypes: the predominant homozygote (A2/A2), the heterozygote 
(A1/A2), and the rare homozygote (A1/A1).  Smokers will also be categorized into three DRD2 TaqIB 
genotypes:  the predominant homozygote (B2B2), the heterozygote (B1B2), and the rare homozygote (B1/B1).  
DRD4   
For the DRD4 dopamine receptor gene, genotyping will be performed as described by 173. Smokers will 
be classified as having long genotypes (L/L or S/L (i.e., homozygous or heterozygous for an allele  6 repeats) 
or short genotypes (S/S (both alleles < 6 repeats))40. 
DAT  
Genotyping procedures for the dopamine transporter gene (SLC6A3) will be similar to that of 32.The 
SLC6A3 genotype will be classified as described by 30, according to the presence or absence of the 9 allele 
(9/9 or 9/* vs. */*, where * refers to alleles other than 9). We will also analyze DAT data by categorizing 
smokers with and with out the 10 allele as described by Vandenbergh and colleagues.35  
SERT  
Genotyping for the serotonin transporter (5-HTTLPR) will be carried out according to the methods of 174.  
Two variants of the 5-HTTLPR have been described:  the long (L) variant (528 bp) and the short (S) variant 
(484 bp).    
NET  
Several variants of the norepinephrine transporter (NET) gene have been identified.  One of these 
polymorphisms, an exonic silent RFLP (1287G/A) in the NET gene, will be analyzed as previously described86. 
For all assays, 20% of the samples will be repeated for quality control. Additionally, all gels will be read 
independently by two investigators. 
 

 
 
 
Counseling Component   
 An individual behavioral counseling intervention will be provided to all participants to facilitate their 
cessation and continued abstinence over the course of the laboratory assessments. Behavioral counseling is a 
recommended standard of care to be used in conjunction with pharmacotherapy 175. The counseling 
intervention is adapted from our Life-Cheq Smoking Cessation Treatment Manual 176 (see 
), developed for use in our other studies and used in our preliminary studies. Our individual counseling 
sessions are shorter in duration but comparable in scope to the group counseling provided in one of the 
original trials of nortriptyline (12 weekly group counseling sessions, 90 minutes each) 146, albeit longer than that 
used in the original trial of bupropion (7 weekly individual counseling sessions, 1 call, 10-15 minutes each) 140. 
We feel this is appropriate balance given the fact that this is the only intervention received by the placebo 
group. Studies have shown that difficulty maintaining abstinence in the first two weeks of cessation is 
frequently associated with relapse 177, 178. However, behavioral counseling reduces this risk substantially. 
Counseling will not eliminate withdrawal symptoms (as documented in our preliminary studies) but will provide 
basic coping skills and support for maintaining abstinence. As shown Table 2, seven individual counseling 
sessions and 5 telephone support calls will be provided over the 38 days of the program. Each contact will last 
approximately 30 minutes. To facilitate compliance with the initial stages of abstinence, two treatment sessions 
will be provided before the quit-date to prepare the smoker for cessation.  Further treatment sessions will be 
scheduled immediately after each laboratory session and at 2-7 day intervals between laboratory visits.  A 
telephone counseling session will also be provided on the quit date and at selected intervals in between the in-
person counseling sessions.  
Bupropion  
Smokers in the Bupropion Group will receive a 12-week regimen of bupropion (150 mg q AM for three 
days; 150 mg b.i.d. thereafter). Bupropion has been used effectively for smoking cessation in regimes ranging 
from 7-12 weeks 140-142. Our procedures will closely resemble those used in earlier trials. Participants will begin 
bupropion on the day they attend their baseline laboratory session (10 days before the target quit day), but 
after the session is completed. Bupropion will be tapered to 150 mg/day one week before the conclusion of the 
regimen.  
Nortriptyline  
Smokers assigned to the Nortriptyline Group will receive a 12-week regimen of nortriptyline.  
Medication administration procedures will be similar to those used by Hall et al. 146 in one of the first 
randomized clinical trials using nortriptyline for smoking cessation.  Ten days before their target quit day and 
following the baseline startle assessment, smokers in this group will receive 25 mg/day of nortriptyline for three 
days.  Medication dose will then be increased to 50mg (25 mg bid) for four days. Serum levels will be assessed 
at the end of the first week of medication (3 days before quitting) and the dosage will be increased to a 
maximum of 50 mg bid if plasma concentrations do not reach the recommended therapeutic range (between 
50 and 150 ng/mL). Blood samples will be drawn again at week 4 (5 days after quitting) of the medication and 
dosage will be adjusted again and checked the following week if necessary. The modal dose in the Hall study 
146 was 100mg/day. Participants will remain on the adjusted dose until the eleventh week of medication when 
the dosage will be tapered to 50 mg/day.     
Placebo  
Participants in the placebo group will receive a total of 12 weeks of placebo plus the behavioral 
counseling described above. All other assessment procedures will be identical to the other groups.  
Medication Blinding  
Medications will be supplied by the Drug Product Services Laboratory in the Department of Clinical Pharmacy, 
University of California, San Francisco (see letter of support section I). This pharmacy made the nortriptyline 
and bupropion placebo preparations used in Dr. Sharon Hall¶s nortriptyline and bupropion research studies 146, 
179 and has agreed to provide our study with similar preparations. To keep all medications similar in 
appearance, active and placebo formulations will be enclosed in unmarked sealed and brushed capsules and 
shipped to MD Anderson Department of Experimental Therapeutics Research Pharmacy for patient 
distribution. The MD Anderson pharmacy will implement the randomization schedule as developed by the 
study statistician. Because nortriptyline levels can only be detected in the nortriptyline group, only the study 

 
 
 
physician (and his staff) will be un-blinded as to treatment condition, as they will be responsible for the dose 
titration and medication checks. Our study physician will not be involved in the counseling or startle 
assessments and he or a member of his staff will conduct the adverse reports assessments. All other members 
of the research team will remain blind to treatment condition. 
 
To maintain the integrity of the blind among the participants themselves and the other research staff, 
about 10% of all participants in the placebo and bupropion groups will also undergo the same schedule of 
blood analysis as the nortriptyline group. We feel this is an appropriate compromise to maintain a blinded 
research protocol and at the same time, minimize the risk of unnecessary blood draws among the bupropion 
and placebo groups. The code for who will be selected for the blood draw will be imbedded in the 
randomization schedule. Medication will be un-blinded in the event of drug related a serious adverse event, 
Abstinence Compliance and Startle Assessments 
As shown in 
, compliance with abstinence requirements will be checked at the beginning of each 
laboratory session, all telephone counseling sessions, and each in-person counseling session that does not 
coincide with a laboratory startle assessment. Abstinence at each startle assessment will be defined in two 
ways. The first will involve stringent criteria of no smoking (not even a puff) from the target quit date to the day 
of each post-quit startle assessment plus a corresponding expired CO of <8ppm. Less stringent criteria of 
abstinence will also be applied to evaluate the effects of the quit attempt among all smokers, even those who 
do not meet the stringent criteria of abstinence as defined above. The less stringent criteria will be as follows: 
(1) Abstinence prior to the first post-quit startle probe assessment (2 days pos-quit) be defined as a self-report 
on the SSQ of being abstinent on their quit date, and smoking no cigarettes at least 24 hours prior to the 
assessment plus a current CO <8ppm. (2) For the time period encompassing the 5 and 28 days post-quit 
startle assessments, abstinence will defined by the following conditions (a) abstinence on the quit date; b) 
abstinence at the first post-quit assessment; c) self-report of abstinence at the 5 and 28 day post-quit 
laboratory assessments with corresponding CO levels <8ppm, and (c) having smoked no more than 1 
cigarette, between the 2 and 5 day assessments, and no more than 2 cigarettes in the 4 weeks between the 5 
and 28 day post quit laboratory assessments.  Our data will be analyzed using both criteria to evaluate 
abstinence. We took a similar approach in our preliminary studies and saw no differences in the startle 
comparisons between abstainers defined by either the more or less stringent criteria, although both were 
different from controls. Participants who are not abstinent on the quit day or prior to the 2nd laboratory session 
(by the less stringent standard) will not undergo the 2nd laboratory assessment procedure at their originally 
scheduled time. Within the context of their scheduled counseling, these smokers will be provided with support 
and given an additional opportunity to abstain from smoking for a 2 day period as called for in the first startle 
assessment. Participants who fail a second time or who relapse after their 2nd laboratory session (using the 
less stringent criteria described above) will continued to be counseled to quit and will be evaluated on the 
same schedule of laboratory assessments as the abstainers. Our preliminary data clearly show that these, 
³never quitters´, or ³relapsers´, both significantly reduce their smoking and experience a substantial increase in 
negative affect and startle reactivity as a function of nicotine withdrawal. Thus even though some smokers may 
not quit entirely, they experience considerable distress and do not return to baseline levels of smoking, at least 
for the period in which the behavioral counseling is provided. In our preliminary studies and in the current study 
the counseling is coincident with the startle assessments and is designed to encourage continuous quitting 
activity even if they initially fail. Hence, as described in our preliminary studies we will analyze our startle data 
using models that both separate and combine relapsers and never quitters. This analytic strategy will maximize 
the information gained form this experiment.  
Based on our preliminary data about 25%-50% of the participants may fail to achieve 
abstinence/maintain abstinence after their quit date, using only the behavioral counseling provided. Our 
preliminary studies are not yet complete and our abstinence rates have ranged been as high as 75% at other 
times when we have undertaken interim analysis. To enhance abstinence rates in the present study, we have 
both increased the counseling frequency, in comparison to our previous study, and provided a monetary bonus 
for abstinence. With these adjustments, we feel it is reasonable to expect 60%-75% of those in the placebo 
group (counseling alone) will be abstinent at the 28-day post-quit assessment.  Based on the initial clinical 
trials with both drugs, we expect 75%-80% of those in both drug groups to have achieved abstinence by day 
28 post-quit.  Our power calculations for interactions involving abstinence status, treatment and genotype have 

 
 
 
3 min. Deprivation Assessment: expired CO 
20 min. Questionnaires 
 
WSWS, PANAS,CES-D 
 
Smoke 1 cigarette:  
Baseline Only 
30 min Startle Probe Trial Block 
48 slides-5 Valences: Positive, Negative, 
Neutral, Cigarette
12 per valence-order counter balanced
6 s presentation, 10-20 s variable ITI 
acoustic probe w/I 2-5 s of slide onset 
probe of 3 of 4 slides per combination 
Response: blink strength (EMG) & latency 
15 min. Baseline 
Hook-up for EMG, HR & SCR, followed by rest 
Rate slides for affect & arousal in free view 
following completion of session 
taken this range of abstinence into account (see page 29). We have also outlined a strategy for comparing all 
participants in the drug treatment groups to placebo, similar to those we conducted between the Quit and 
Control groups in our preliminary studies. This approach 
is outlined in our data analysis section, along with our 
plan to evaluate differences in abstinence status between 
and within groups.  
Abstinence compliance following startle assessments (28 
days post quit).   
 
As shown in Table 2, we will assess abstinence 
and days to relapse using a telephone SSQ interview 
administered at 2 and 4 months post-and at the 3 and 6 
month post-quit follow-up points. Participants will have 
completed the medication regime 10 days prior to the 3-
month follow-up. Abstinence from the phone interviews 
will be verified using return mail cotinine, At the 3 and 6 
months follow-up, abstinence will be verified by expired 
CO (<8ppm) obtained in the clinic. Cotinine will also be 
assessed at follow-up to provide a measure of tobacco 
exposure among those who fail to quit. For of these 
assessments, relapse will be defined in two ways: 1) 
using the traditional 7-day point prevalence criteria at 
each assessment (no smoking not even a puff in the 7 
days prior to the assessment) and 2) using the recently 
developed guidelines from the SRNT committee on 
measurement of abstinence 180, which defines relapse as 
having smoked for 7 consecutive days, or, a puff a week 
for 2 consecutive weeks, beginning 2 weeks after the 
target quit date. 
 
We recognize that the telephone interviews 
described for the 2 and 4 months pos-quit time points 
may seem redundant with the 3 and 6 months follow-ups, 
that are more typical of a clinical trial. However, this study 
is not exclusively a treatment outcome comparison in 
which abstinence rates at 6 months are the only focus. A 
primary dependent variable in this study is the number of 
days to relapse in relation to startle responding and we 
feel it is appropriate to assess abstinence status more 
often in order to better capture this data. Participants who report abstinence in these telephone assessments 
will be asked to provide a saliva cotinine sample using a mail kit developed for a current clinical trial. 
Participants will also be paid $5 for each saliva sample provided.  The procedure of having participants provide 
saliva samples by mail has worked successfully in previous studies conducted by our group 181. We have had 
few problems using the mail-in cotinine procedure in our current trial.  Experience in our current trial, suggests 
that participants become very familiar with the salivette collection procedure since it is used in prior clinic visits. 
The kits contain a Teflon strip to stimulate saliva production, a cotton dental roll which is placed in the mouth 
for 30-45 seconds (until well saturated), a salivette collection tube to retain the dental roll after use, and a self-
addressed bio-container envelope with pre-paid postage for over-night mail.  
 
The protocol for the individual laboratory startle assessments will be similar for all four sessions, and is 
described in 
Each laboratory session will begin at approximately the same time of day for each 
participant (10-11am)  Participants will be asked to limit their intake of coffee (or equivalent) to no more than 1 
cup prior to 8:00 am on the day of each laboratory session. Smoking for all groups will be unrestricted prior to 

 
 
 
the first (baseline) laboratory assessment session. The first session will be used to assess normal startle 
responses to affective stimuli prior to any nicotine deprivation or pharmacological treatment.  Subsequent 
sessions will be used to assess the effects of treatment modality (nortriptyline, bupropion, placebo) and 
genotype on startle responses to affective stimuli during the 28 days following the quit attempt. The target days 
for these assessments are 2 days post quit (range 1-3 days); 5 days post (range 3-5) and 28 days post-quit 
(range 26-30). Ranges are provided as in our preliminary studies to accommodate scheduling changes 
resulting from missed visits or a repeat visit 2 (see abstinence criteria). Moreover, we have extended our final 
session from 10-14 days in our preliminary study to 28 days in the current proposal to more readily capture 
medication effects on startle responding about midway through drug treatment and towards the end of the 30-
day withdrawal period. 
At the beginning of each laboratory session, participants will be asked to complete the WSWS, CES-D, 
and PANAS, as described above. At the baseline session all participants will be instructed to smoke one 
cigarette after completing these instruments, to ensure similar conditions of non-deprivation preceding the 
startle probe trials. This is similar to the procedure used by Tiffany and colleagues 182 and is identical to the 
baseline session described in our preliminary study. 
Within each of the four sessions, smokers will be exposed to 48 startle probe trials. Each trial will involve the 
presentation of a picture with either positive, negative, neutral emotional content, or a smoking cue, while an 
acoustic stimulus is administered. Each startle probe trial will involve the assessment of eye-blink magnitude.  
After completing the questionnaires (20 minutes), EMG electrodes will be attached around the participant¶s left 
orbicularis oculi region. A Biopac photoelectric sensor (plethysmograph) will also be placed over the 
participant¶s left index finger to monitor concurrent changes in heart rate and two mini-electrodes will be placed 
adjacently on the left hypothenar eminence to measure skin conductance. As shown in 
, participants 
will be asked to rest quietly, while seated in a comfortable recliner, for a 15-minute baseline period. The subject 
will be told that a series of slides will be presented and that each slide should be viewed the entire time it is on 
the screen. In addition, the subject will be told that occasional noises may be heard over the headphones and 
can be ignored. Then one trial block consisting of 48 slides will be presented using procedures similar to those 
listed in the preliminary studies. Each slide will be presented for 6s, followed by a randomly determined 
interslide interval, 10 to 20 seconds in duration.  The valence slides were selected from the International 
Affective Picture System (IAPS) (Center for the Study of Emotion and Attention, 1995) and are the same as 
used in our preliminary studies.  These slides have been used in many previous startle probe experiments and 
have been standardized for valence and arousal (e.g., 120, 124, 183).  The smoking cue slides (lit cigarette, ash tray, 
people smoking, etc.) were developed in our laboratory for our preliminary study 184 and will also be used here. 
The slides will be equally divided among the three valence categories and the smoking cues. Although the 
same slides will used in each session, they will be counterbalanced across sessions so that subjects will see 
pictures from each category equally often in each position. Counterbalancing for slide order will be arranged so 
that, across subjects, each slide will be associated with a startle probe equally often. Using a computer 
controlled visual analog scale (electronic slider), participants will be asked to rate their current mood (e.g., 
interested, distressed, nervous, alert, tired, upset, etc.) and craving (none-very strong) following one out every 
fourth slide within each valence.  
Startle probes and picture stimuli will be controlled and digitally presented with E-Prime software 
(Psychology Tools, Inc.).  Picture stimuli will be projected onto a 3 x 5 foot white screen with an image size of 
20 x 30 inches.  Participants will sit approximately six feet from the viewing screen. The acoustic startle 
stimulus will consist of a 50-ms presentation of white noise with instantaneous rise time. The noise burst will be 
presented over matched (left and right) Telephonics TDH-49 headphones at an intensity of 100 dB. A startle 
probe will be presented during 32 of the 48 slides at a random time of 2-5 seconds after slide onset, such that 
a probe will be presented during 8 of the 12 slides within each valence condition. To enhance unpredictability 
of the startle presentation, startle probes will also be presented during 12 randomly selected inter-slide 
intervals (ITIs). Responses to startle probes given during the ITIs will be used as a control measure to assess 
startle responding in absence of emotional stimuli.  

 
 
 
Physiological Recording and Data Reduction  
For eye blink recordings, the electromyogram (EMG) from the orbicularis oculi region under the left eye 
will be amplified with a bioamplifier (Biopac, Inc.) using a bandpass filter of 90-1K Hz and contour-following 
integrator with a time constant of 125 ms. To enhance recording sensitivity during the blink response, the EMG 
signal will be digitized at 1000 Hz from 50 ms before until 250 ms after acoustic startle probes. The Biopac 
MP100 data acquisition software permits real time scoring of each blink for peak and latency. Trials with clear 
movement artifact or excessive baseline activity will be rejected and trials with no blink will be scored as 0 
magnitude.  
As a concurrent measure of autonomic arousal, we will monitor heart rate and skin conductance using 
Biopac MP100 physiological monitoring system and data acquisition software.  Previous studies suggest that 
heart rate deceleration is marked during negative picture viewing 120, 185. In contrast, skin conductance 
responses increase with arousal level of the stimuli but are enhanced for both positive and negative events, in 
comparison to neutral slides 120. Heart rate data will be recorded continuously throughout the session and 
edited to correct for any missed or double triggered intervals. It will then be transformed to averages for every 
half second, and the values during slides will be expressed as change scores deviated from a 1-s pre-slide 
baseline. The average of seconds 2-4 (6.5-s values) will be computed for a summary score to use in 
subsequent descriptive analysis. Skin conductance responses (SCRs) will be scored as the largest response 
between 0.9 and 4 s after slide onset 186. A log transformation (log[SCR + 1]) will be performed to normalize the 
distribution. The skin conductance amplifier will be calibrated prior to each session to record a range of 0-40 
S. All raw data, analog signals and scoring transformations will be stored directly on a 900Hz computer 
interfaced with the physiological recording instruments. Real time display of EMG (startle probe) activity, HR, 
and SC will be implemented during the session using the corresponding software. 
At the end of the fourth and final session, all 48 slides will be repeated in a free-viewing procedure. The 
subject will be asked to view each slide for as long as desired (to a maximum of 30 s), terminating with a 
button press. Viewing time will be recorded to the nearest millisecond. The subject will then rate the slide on 
affective dimensions (positive, negative) and arousal (low, high) using an interactive computer display. These 
ratings, along with HR and SCR measures will be used as a cross-validation of the slide¶s intended effect on 
emotional valence (negative/positive) and arousal (high). 
 
Participant Compensation  
Participants will be paid $300 for attending all laboratory sessions.  Payments will be structured as follows:  
$60 per completed laboratory session ($240 total), $20 bonus for remaining abstinent at each of the 3 post-
baseline sessions[PCP17]. In addition, following all laboratory sessions, participants will be paid $5 per 
assessment for providing saliva samples to verify their abstinence. 
 
Prior to inferential procedures, extensive descriptive analyses will be conducted of the startle magnitude 
scores.  Standard descriptive statistics, including means, standard deviations, ranges, etc., will be computed 
together with ninety-five percent confidence intervals.  Graphical methods, including boxplots and histograms, 
will also be employed to closely examine the distributions of the scores.  If required, potential normalizing 
transformations will be explored.  Bivariate associations between the scores and selected demographic 
variables including age, ethnicity, gender, initial cotinine, FTND score, depression history, baseline smoking 
level and other initial assessments will be evaluated Pearson¶s product moment correlation coefficients and 
ANOVA.  Descriptive analyses of the distributions of the WSWS, CES-D, PANAS scores and other 
psychological assessments between groups and over the laboratory sessions will also be conducted. In 
addition, we will conduct descriptive and graphical analyses of the affective ratings for each slide obtained at 
the end all sessions. The end of study ratings from the free viewing situation will be plotted against startle 
magnitude as a check of the intended manipulation of valence. As described by Cuthbert, et al. 120, startle 
magnitude will also be plotted against skin conductance levels to verify the arousal level (high) of the selected 
slides. Skin conductance has been shown to reliably track subjective arousal independent of valence 120. 
Similar descriptives will also be provided for the in-session mood and cravings ratings within each valence.  
 

 
 
 
Our primary analytic strategy involves the use a mixed 
model approach to examine the effects of the dependent 
variables (e.g., startle magnitude, time to rela9pse) 
across assessments. The mixed model approach 
provides a generalization to the classic linear regression 
model, using likelihood functions instead of least squares 
to estimate effects.187 The mixed model approach is 
ideally suited for analysis of repeated measures data in 
that it allows for more specific estimation of the 
correlation structure of the residuals, and more efficiently 
handles unbalanced designs and missing data, without 
excluding participants or imputing values.188, 189. Fit 
statistics (e.g., Akaike's Information Criterion) will be 
evaluated for all models to ascertain the best fit of the 
correlation structure of the dataset. We use a computer 
program, PROC MIXED, (SAS Institute Inc, Cary, NC) to 
estimate and test the models. This procedure was used 
in our preliminary studies. 
 
 
Analysis of the startle responses will be conducted using mixed model regression. The study design involves 
both between subject and within subject fixed effects 
and correlations due to repeated measures on the 
participants. Within subject fixed effects include Days 
(baseline, post quit days 2,5, 28) and slide valence 
(positive, negative, neutral, cigarette). Between 
subjects effects include Treatment (Placebo, 
Bupropion, Nortriptyline) and Genotype (e.g., A1/A1 
or A1/A2 and A2/A2 for our main hypothesis, and 
others as described for secondary hypotheses).  
Because of the nonstandard design, power 
calculations were conducted using simulations in 
SAS (PROC MIXED). To simplify calculations, we 
assume that the response to the slides at each level of valence within session will be averaged. The repeated 
measures on each subject are associated with correlations between observations from the same subject 
across sessions, and between observations from the same subject within session.  We estimated these 
correlations using data from our previous work.  For the primary hypothesis described below, we will fit three 
models.  The first (Model 1) will restrict analyses to positive, negative and cigarette, stimuli and use the score 
to the neutral stimuli as a covariate, the second (Model 2) will use data from all valences together, and the third 
(Model 3) will use all data but examine post-quit scores controlling for baseline scores. The within subject-
between-session and within subject-within session correlations varied for each model in our preliminary work.  
For Model 1, we estimated the within subject-between session and within subject-within session correlations to 
be .03 and .45, respectively; for the Model 2 we estimated them to be .7 and .9, respectively, and for Model3, 
we estimated them to be .6 and .9, respectively.  
We estimated power based on 354 subjects and a Type I error rate of 0.05.  Power calculations were 
repeated for each of the three models. For Hypothesis 1, we estimated power for the group contrast between 
placebo and either bupropion or nortriptyline. A sample size of 354 subjects provides 80% power to detect 
effect sizes of .17, .32 and .30 standard deviations between these groups for Models 1, 2 and 3, respectively.  
Given the variability estimates in the raw startle magnitude scores we found by applying the three models to 
our previous work, these effect sizes translate into group differences in startle magnitude of 4, 22 and 16 
 
A1A1 or 
A1A2 
25.9a 
 
42.6g 
A2A2 
74.1 
 
57.4 
B1B1or 
B1B2 
13.2b 
 
41.6g 
B2B2 
86.8 
 
58.4 
SS 
79c 
 
76i 
SL or LL 
21 
 
24 
9/9 or 9/10 
55.8d 
 
46.7d 
10/10 
44.2 
 
53.3 
SS or SL 
70.3e 
 
59.6g 
LL 
29.7 
 
40.4 
 
 
 
 
GG 
44f 
 
unknown 
GA 
44 
 
 
 
AA 
12 
 
 
a=154 b=190 c= 191d= 30 e=192 f=85 g=147 i=72 
.15 (3) 
.29 (20) 
.29 (16) 
.16 (3) 
.30 (20) 
.30 (16) 
.17 (4) 
.32 (22) 
.31 (17) 
.20 (4) 
.36 (25) 
.35 (19) 
 

 
 
 
volts, for Models 1,2 and 3, respectively.  These values are well within the range observed in our preliminary 
studies where the overall difference between treatment and controls averaged 27 volts. This range also 
provides adequate power for detecting interactions with valence for any of the Models, as the range of 
differences between positive and negative valence between groups, is above 16 volts. For Hypothesis 2, we 
estimated power for the genotype comparisons across a range of possible prevalence for the ³at risk´ allele, 
among smokers. The expected allele frequency among smokers is shown in 
Data from controls are 
provided for comparison but except in the case of the NET, are not considered in the power calculations.  
Power analyses for genotype effects are summarized in 
. Effect sizes are shown in standard deviation 
units. The corresponding difference in raw scores ( volts) is shown in parentheses. Our major hypothesis 
involving genotype center on the DRD2, for which the A1 is the ³at risk allele. As shown in 
the 
expected frequency in our sample of smokers is above 40%. Effect sizes at this frequency and above vary 
from .15-.30, which corresponds to differences of 3-16 volts (see 
for the three respective models In 
our preliminary studies, the average difference in startle magnitude across all valences between A1 and A2 
smokers who quit during the study was 26 volts, so we will have adequate power for these comparisons. 
 As described in the proposal, we will also examine other genotypes in exploratory analysis. For 
purposes of these comparisons, the ³at risk´ allele can be considered the GG allele of the NET, the L form of 
the DRD4 and the SERT, and the DAT 10/10. Data on the GG genotype of the NET are unknown for smokers 
so we used the control data from Zill 85. For all but the DRD4 the effect sizes and corresponding startle 
magnitudes are similar to the A1. For the DRD4 L allele the frequency is estimated at .24, corresponding to an 
effect size of .2-.35, and startle differences between 4-25 volts, across the three models. If the differences in 
startle magnitude are similar to those of the A1, we will still have adequate power to detect them, although this 
might be at the upper range for Model 2. 
For the moderation of emotional reactivity during cessation by genotype, we again provide estimated 
power for the three models in 
. The effect estimates represent the difference in emotional reactivity 
between placebo and bupropion or nortriptyline 
between each of the two genotypes (e.g. A1 vs. A2). 
Our preliminary studies indicate that the difference 
between A1 participants in Quit group and A1 
Controls (adjusting for baseline) ranged from 25-
60 volts over the two week of cessation period. 
Corresponding differences for A2s ranged from 25-
2 volts, and a significant interaction between 
genotype and Group (Quit vs. Control) was observed 
(i.e., A1 Quitters showed an elevated startle during 
cessation. Based on this estimate we will have 
adequate power for detecting 2 way interactions with genotype, for all Models for our primary hypothesis 
(DRD2), and for our exploratory analysis of other genotypes, if similar results are observed. Our analytic 
strategy also calls for exploratory analysis of possible interactions between genotype abstinence status 
(Abstainers Relapsers Never Quitters), and treatment conditions. We expect all smokers in treatment to 
experience significant startle elevation as a consequence of abstinence or the reduced smoking observed 
among the Relapsers or Never Quitters, at least through the first week following cessation. If we estimate an 
overall abstinence rate at the end of treatment of 60%, and an at risk allele frequency of .43 (for the A1), that is 
the equivalent of a .26 ³at risk´ allele rate in 
. Therefore we should be able to detect differences in startle 
magnitude of 8-43 volts, depending on the Model, for interactions between genotype, abstinence status and 
treatment. This range of startle activity also provides us with adequate power to detect interactions with 
valence, should they occur, as seen in our previous studies. Differences between A1 Relapsers, Never 
Quitters and Abstainers and A1 Controls across valences ranged from 7 to 40 volts, across assessments. For 
A2s the range was more narrow (4-22 volts). Thus, we should have we should have adequate power to detect 
interactions with valence, genotype, abstinence and treatment, should they occur. 
  
Power for hypothesis 3 was estimated by dichotomizing emotional reactivity into two groups (high 
versus low), in order to make use of available standard power formulas. Our actual dependent measure will be 
a continuous measure of startle, which will offer a much finer gradation of the incremental differences in 
.32 (7) 
.57 (39) 
.57 (31) 
.34 (7) 
.60 (41) 
.59 (32) 
.37 (8) 
.63 (43) 
.62 (34) 
.42 (9) 
.72 (49) 
.70 (39) 

 
 
 
abstinence attributable to startle activity. Nevertheless, these calculations should provide a conservative 
estimate of power. We used data from Hall 146 to estimate abstinence rates for nortriptyline vs. placebo. Her 
data provides comparability to our study as she used an extensive behavioral counseling in both her placebo 
and nortriptyline treatment groups. The abstinence rates at the end of treatment, 3 months and 6 months 
follow-up for the nortriptyline group were 64%, 54% and 42%, and for the placebo group were 42%, 26% and 
26%, yielding an average abstinence rate of 53%, 41% and 34% at the 3 respective time points. The 
bupropion/placebo abstinence rates of Hurt 140 are somewhat lower than observed for nortriptyline, but were 
not used in these calculations because the behavioral treatment provided in that study was not as extensive as 
provided here. We believe our counseling intervention would increase rates similar to the nortriptyline group. 
However, the current study is not specifically powered to detect absolute differences in the abstinence rates 
between the two drug groups. The literature suggests that the rates for the two drug treated groups should be 
very similar to each other, assuming a similar level of behavioral counseling in both. However, we do expect to 
find differences in how smokers respond to each treatment in terms of emotional reactivity and genotype 
(Hypothesis 1 and 2) and that emotional reactivity predicts abstinence, independent of treatment (Hypothesis 
3). If we assume an overall abstinence rate across all three groups at 6 months of approximately 40%, then 
150 subjects per group (dichotomizing into high versus low) provides 80% power to detect differences in 6 
month abstinence rates of 48% versus 32%, between high and low startle groups. If the overall abstinence rate 
is 30%, then we have 80% power to detect differences in the 6 months relapse rates of 37% versus 21%, and 
for overall abstinence of 20%, we have 80% power to detect differences of 26% versus 12%. These estimates 
are well within expected scenarios in the smoking cessation treatment literature. Thus, we have adequate 
power to differentiate startle responses across a range of abstinence rates. 
 
1. The emotional reactivity of smokers during nicotine withdrawal will be significantly higher among those that 
receive placebo vs. either bupropion or nortriptyline therapy for smoking cessation. Emotional reactivity will 
be assessed using the eye blink response to an acoustic startle probe and by evaluating responses to 
emotionally valent stimuli (positive, negative, cigarette) relative to neutral visual slides.   
1.1. Mixed model repeated measure regression analyses will be used to evaluate this hypothesis, 
regressing peak startle magnitude, on Group (Bupropion, Nortriptyline, Placebo with Days (e.g., 
baseline, post-quit days 2, 5, 28) as the repeated measures factor. Three types of models will be 
evaluated. Model 1 will be restricted to startle responses to positive negative and cigarette stimuli and 
will include valence (positive/negative/cigarette) as a factor. This model will also include the 
corresponding value of the startle response to neutral stimuli as a covariate. In this way, we can 
compare the relative magnitude of startle responses to each valence adjusted for the response to 
neutral cues. The main effect of treatment Group is of primary interest in this model and will be 
evaluated first, followed by Days, and the Group X Day interaction. Other interactions including Group 
X Valence and Group X Valence X Days will also be explored. To assess Group differences (if any) at 
the beginning of the study, an a priori contrast on the baseline values only will also be carried out for 
this model, evaluating the main effect of Group and the Group by Valence interaction. In Model 2, 
startle will not be restricted to positive, negative or cigarette valences but will include all valences.  The 
main effect of Group will be evaluated first, followed by Days, each of the two way interaction terms, 
and the Group X Day X Valence interaction. An a priori contrast will also be carried out as in Model 1 
on the baseline values, to assess Group differences (if any) at the beginning of the study. The third 
model will involve only the post-quit assessments. This model is similar to Model 2, but will include the 
corresponding baseline value for each stimulus valence as a covariate. In this way, post cessation 
startle values may be expressed as a function of the corresponding pre cessation baseline values. As 
described in our preliminary studies, we believe this analysis can be quite informative, as it focuses on 
post cessation startle in relation to responses under nondeprived (baseline) conditions. 
2. The emotional reactivity of smokers during cessation will be moderated by genotype. Our initial hypotheses 
focuses on the DRD2: 
2.1. We hypothesize that emotional reactivity will be lower for those carrying the DRD2 A1 and using 
bupropion vs. A1 smokers using either nortriptyline or placebo. A1 nortriptyline users are expected to 

 
 
 
have lower reactivity than A1 placebo users[PCP18]. Homozygous A2s are expected to respond similarly 
to both drugs with higher levels of emotional reactivity being observed for placebo vs. either bupropion 
or nortriptyline. 
This hypothesis will be evaluated using models similar to those described for hypothesis 1, but with the 
addition of Genotype (A1/A2 or A1/A1 vs. A2/A2) as a term in each model. We will specifically evaluate 
the main effect of Genotype first, followed by the Genotype X Group interaction (the term of interest). 
Other interactions involving Genotype with Days and Valence will be explored as described for Models 
2 and 3 above. Planned contrasts involving the difference in startle magnitude between each Group 
condition, within Genotype, will also be carried out.  
3. Higher levels of emotional reactivity of smokers at baseline and or during cessation will be inversely related 
to abstinence at the 3 and 6 month follow-ups. 
3.1. Two types of analysis will be carried out. Our primary focus will be on predicting days to relapse. For 
this analysis, startle responses will serve as the independent variable with days to relapse as the 
dependent measure. The primary analysis will focus on the average startle response from the baseline 
assessment.  In secondary models, average response to each valence will be included as predictors to 
determine the relative predictive strength of the different valences.   Startle response from each of the 
post-quit assessments will also be examined as time dependent variables to determine if startle 
responses from the other assessments predicts relapse. Each model will also be evaluated controlling 
for or not controlling for treatment Group.  For this analysis we will use Cox proportional hazards 
regression. We are also interested in predicting abstinence (yes/no) at the 3 and 6 month follow-up. 
Therefore we will also use the GLIMMIX Macro from SAS, which is an adaptation of the PROC Mixed 
procedure for hypothesis 1 and 2 for dichotomous out come variables (abstinence) to test whether 
startle responses are related to abstinence, modeling baseline, valence and time dependent 
characteristics of the model in the manner proposed above. Interactions between genotype (DRD2 A1 
vs. A2) and startle in the prediction of abstinence, will also be explored using in the separate and 
combined valence models. 
Covariates will be included in all models described above to correct for any baseline differences and help 
improve power.  The covariates to be used include ethnicity, age, gender, smoking history, and depression 
history.  Interactions between ethnicity or gender and genotype will be explored.  If we find statistically 
significant interactions, separate models for each ethnicity or gender will also be tested. 
The contribution of the WSWS, CES-D, PANAS scores and in-session ratings of craving and mood, to 
the observed startle effects in the primary hypotheses will be explored by fitting these variables as covariates 
in the above models.  In addition we will examine the relationship between these measures, startle values for 
each valence, and with in sessions affect ratings using correlational procedures.  Changes in these measures 
over time will also be evaluated using the same Mixed Model approach described above with Group and 
Genotype serving as between groups factors and Days as the repeated measure. Finally, the primary analyses 
of the startle magnitude described above will be repeated on the changes in skin conductance response and 
heart rate to determine the pattern of autonomic arousal displayed for baseline and withdrawal conditions.  
Although our initial genetic hypotheses are focused on the DRD2, we will also use assessments of 
emotional reactivity to characterize the phenotypes of several other biomarkers that have potential importance 
for neuroregulatory function and response to pharmacotherapy for smoking cessation. These include: the 
DRD4, SERT (serotonin transporter), DAT (dopamine transporter) and the NET (norepinephrine transporter). 
Several exploratory hypothesis are proposed.  
We will test the hypotheses that those carrying the long form of the DRD4 (6 repeat or longer) will 
experience less reactivity during either drug therapy than those homozygous for the short form.  
We will test the hypotheses that smokers who are heterozygous (S/L) or homozygous (L/L) for the long form of 
the SERT gene are likely to experience less emotional reactivity in response to nortriptyline therapy vs. either 
bupropion or placebo. 
Polymorphisms of the NET gene have not been extensively characterized in humans and its 
relationship to antidepressant therapy have not yet been explored. We will evaluate whether or not one the 

 
 
 
currently known polymorphisms (1287G/A) is associated with differences emotional reactivity during 
pharmacotherapy. As a working hypothesis we expect that smokers carrying the GG allele of the 1287G/A 
variant would be more likely to show reduced emotional reactivity during to nortriptyline therapy vs. bupropion 
or placebo, in comparison to their GA or AA counterparts, who are not expected to differ in response to the 
antidepressants. 
Each of these genetic markers will be included in the descriptive analysis described above. We will test 
our exploratory hypothesis by repeating the mixed models analysis described above for our main hypothesis 
and test for main effects and interactions as we described for the DRD2. 
 
 
 
 
Subjects recruited for this study (N=354) will be 
current smokers from the Houston metropolitan community. Inclusion criteria are presented in Table 1 All 
smokers meeting these qualifications will be accepted into the study. Given the nature of the study design it 
will be necessary to eliminate subjects who do not speak English or have a telephone. 
 Participants will be providing physiological data in the form of heart rate, skin 
conductance, and facial EMG. Participants will also provide several saliva samples for cotinine analysis 
and a serum blood sample for the use in genetic analyses.  Questionnaire data will be obtained that assess 
previous smoking and health history, mood, attitudes about quitting, coping behavior, and perceived stress. 
All data will be collected specifically for research purposes and will be coded to maintain confidentiality. 
The investigations into the genetics of nicotine dependence are just beginning. At present there is no 
specific disease ³risk´ information that would require automatic disclosure of the genetic profile to the 
participants. However, at the conclusion of the laboratory sessions we will share genetic profile information 
with all interested participants and provide a lay interpretation of the existing literature, with appropriate 
caveats.
 As with most antidepressant medications, bupropion and nortriptyline carry risks of side 
effects.  The typical side effects are not usually serious in nature (e.g., dry mouth, anxiety) and often abate 
within a few days to weeks after starting medication or once the medication is withdrawn.  A detailed 
description of these effects, are provided below. We will follow the Data and Safety Monitoring procedures 
for reporting and review of adverse events, approved by MD Anderson for this trial. Participants may also 
experience tobacco withdrawal effects (e.g., increased irritability, difficulty concentrating, etc.) during 
smoking cessation.  None of these effects typically result in serious adverse health consequences. There 
are no known risks associated with being subjected to startle probes and picture stimuli.  Physiological 
monitoring carries the minor risk of skin irritation from adhesives, however this reaction is rare and easily 
treated.  It is unlikely that completing questionnaires would lead to any potential risks for participants.  In 
sum, it is highly unlikely that any legal, social, or psychological problems will result from this research.
 
 
 Participants will be recruited from the Houston community sample 
using: (1) mail, public service announcements, media interviews, MD Anderson Internet access, 
newspaper advertisements, MD Anderson Conquest Magazine; (2) through the MDACC community liaison 
and outreach offices, sending advertisements and mailers to all affiliated providers on the mailing list. 
Consent will be obtained at the onset of the orientation/baseline interview. Participants will be provided with 
a detailed description of the study, information on risks, and on their right to withdraw from the study. 

 
 
 
 Bupropion is an FDA approved medication for smoking cessation and its 
administration will follow approved guidelines.  Nortriptyline is recommended as a second line medication 
in the Clinical Practice Guidelines for Smoking Cessation.  Our procedures closely follow those used in 
previous clinical trials involving these medications. Our study physician will identify participants who have 
contraindications for bupropion or nortriptyline use and will monitor participants for adverse reactions while 
they are on medication.   
 
Given the non-invasive, minimal risk nature of the proposed research, we anticipate that the types of 
adverse experiences that may occur, if any, will focus on concerns about medication side effects, 
phlebotomy, the discomfort of nicotine withdrawal, possible distress associated and with sensitive issues 
arising during data collection. We have taken several steps to minimize these risks, as described below. 
 
Adverse Experiences Associated with Nicotine Abstinence/Withdrawal 
Participants may experience nicotine abstinence/withdrawal effects. These effects may include irritability, 
difficulty concentrating, insomnia, anxiety, dysphoria, and increased hunger. None of these effects result in 
serious adverse health consequences.  
 
Adverse Experiences Associated with Bupropion Use 
Comprehensive screening will be conducted to ensure that all participants with contraindications for 
bupropion use (e.g., current or prior diagnosis of seizure disorder, current or prior diagnosis of bulimia or 
anorexia nervosa, concomitant use of monoamine oxidase inhibitors or other bupropion products, and 
hypersensitivity to bupropion) are excluded from participation. The most commonly adverse experiences 
associated with bupropion use are dry mouth and insomnia.  Other frequent adverse experiences may 
include asthenia, headache, dyspepsia, flatulence, vomiting, agitation, irritability, sweating, and urinary 
frequency.  Adverse effects and concomitant medications will be assessed at each of the post-baseline 
laboratory and counseling session.  Participants¶ blood pressure will also be measured at each of 
laboratory assessment.  The study physician will monitor participants¶ complaints of adverse events and, 
when necessary, adjust the dosage or discontinue medication.  Adverse experiences and medication 
assessments will continue until completion of the regimen (day 84 of the program).  
 
Adverse Experiences Associated with Nortriptyline Use 
Comprehensive screening will be conducted to ensure that all participants with contraindications for 
nortriptyline use (e.g., recent myocardial infarction, concomitant use of monoamine oxidase inhibitors, and 
hypersensitivity to nortriptyline) are excluded from participation. The commonly adverse experiences 
associated with nortriptyline are often antimuscarinic in nature.  They include dry mouth, constipation, 
urinary retention, blurred vision, increased intra-ocular pressure, and hyperthemia.  Other adverse effects 
may include drowsiness and headache.  In addition to monitoring the adverse effects, concomitant 
medications, and blood pressure at each of the post-baseline laboratory session, blood samples will be 
collected at weeks one and four of medication use to ensure the participants are receiving the therapeutic 
dose.  The study physician will monitor participants¶ complaints of adverse events and, when necessary, 
adjust the dosage or discontinue medication.  Adverse experiences and medication assessments will 
continue until completion of the regimen (day 84 of the program).  
 
Adverse Experiences Associated with Blood Collection 
Syncope, hematoma, and infection are among the common adverse experiences associated with 
phlebotomy.  To minimize participants¶ exposure to these adverse effects, trained phlebotomists will be 
employed to handle all blood collection procedures. 
 
The Tobacco Research & Treatment Program (TRTP) clinic is located adjacent to the Department of 
Clinical Cancer Prevention, which has trained medical personnel on staff that will be available to assist the 
study physician and other personnel in managing medically related study issues.  Confidentiality will be 
protected by identifying all subjects by ID numbers in all data files except those controlled by the data 

 
 
 
manger study physician and the PI. Genetic analyses are provided by sample number coded on each 
collection container and can not be connected to individual participant names by the laboratory conducting 
the assays. Only the PI and data manager will have access to the master file linking genetic and other data 
to participant names. All information will be reported in aggregate form and individual participants will not 
be identified in any public reports or documents.  We expect these procedures to be highly effective for 
protecting participant confidentiality.   
 
 
A primary benefit to participants in the proposed study is smoking cessation.  All participants will receive an 
empirically validated treatment for smoking cessation and we anticipate that many of them will continue to 
be non-smokers after the completion of the study.  Smoking cessation is important in cancer prevention, 
reducing medical costs, and increased well-being for both the participants and society in general. 
 
 
The development of a new methodology for studying one of the most important factors in cessation relapse 
(i.e., negative affect) has the potential to significantly increase the efficacy of future treatments for smoking 
cessation. Differentiating the most salient aspects of smoking and nicotine withdrawal among certain 
groups of smokers, such as those carrying the A1 allele, may provide a basis for treatment matching, and 
the development of new interventions that specifically target the primary reinforcing properties of the drug 
for those individuals.  Given the significant benefits that would accrue with increased effectiveness in 
smoking cessation, these potential benefits far outweigh the relatively minor risks associated with the 
proposed research. 
Women participants will be included in this research and will comprise approximately 50% of the population 
sample.  In our previous research we have encountered no difficulty in the recruitment of women participants. 
The population of the greater Houston community from which the sample will be drawn (Harris and its 6 
adjacent counties) is estimated at 4,636,908 people. The ethnic distribution has been reported as 73.5% 
Caucasian; 18.4% Hispanic or Latino (of any race); 12.6% African-American; 3.2% Asian; and .5% Native 
American, 151.  Although the literature on the relationship of the DRD2 A1 allele to alcoholism 152, cocaine 153, 
other substance abuse 15, and smoking 24, 154 has been largely limited to Non-Hispanic Caucasians and some 
studies with African Americans 40 30, we will recruit without regard to race or ethnicity.  As described in the 
preliminary studies section, we have had good success recruiting from ethnic minority populations, especially 
African Americans and have been able to find comparable distributions among those smokers with and without 
the DRD2 A1 allele.  Our success with Hispanic smokers has been more modest although it must be noted that 
smoking rates are lower in the Hispanic and Latino community in comparison to the non-Hispanic community. 
We expect to attract minority smokers to the proposed study using direct public service advertisements 
targeted for minority smokers on Houston radio stations and newspapers supporting a large minority audience. 
Houston has two television stations, and several radio stations and newspapers that serve the Hispanic 
Community. The office of Public Affairs at MD Anderson has also agreed to assist us by arranging for our 
participation in institution wide Cancer Prevention outreach programs directed at the Hispanic Community. 
Such events are sponsored several times a year in areas of the community with high concentrations 
proportions of minority Houstonians. We will focus additional recruitment effort on these venues to increase our 
recruitment of Hispanic smokers. Such efforts will be in addition to the normal interviews, advertisements, and 
news releases conducted on our behalf by the Office of Public Affairs at MDACC.  Recruitment and enrollment 
for the proposed study is scheduled to begin within 3-5 months of funding. 

 
 
 
Genetics Mood & Nicotine Withdrawal -Previous study for the current application
150-completed Target
BS98-293 
P50CA70907
 Hispanic or Latino 
6
5
0
          11 
 Not Hispanic or Latino 
66
66
0
     132
 Unknown (Individuals not reporting ethnicity) 
0
0
0
         0
 Ethnic Category: Total of All Subjects*  
72
71
0
143
 
 
 American Indian/Alaska Native  
1
0
0
1
 Asian  
1
4
0
5
 Native Hawaiian or Other Pacific Islander  
0
0
0
0
 Black or African American  
28
28
0
56
 White  
37
30
0
67
 More than one race 
2
6
0
8
 Unknown or not reported 
3
3
0
6
 
72
71
0
143
*
 
 
 
 American Indian or Alaska Native  
0
0
0
0
 Asian  
0
0
0
0
 Native Hawaiian or Other Pacific Islander  
0
0
0
0
 Black or African American  
0
0
0
0
 White  
3
1
0
4
 More Than One Race 
0
1
0
1
 Unknown or not reported 
3
3
0
6

 
 
 
Genetics Mood & Nicotine Withdrawal -Previous study for the current application
150-completed Target
BS98-293 
P50CA70907
 
6
5
0
11
* Includes all pilots & those with unusable data  
 

 
 
 
Pharmacogenetics and Smoking Therapy 
354
 
 Hispanic or Latino 
29
28
57
 Not Hispanic or Latino 
148
149
237
 Ethnic Category Total of All Subjects* 
177
177
354
 American Indian/Alaska Native 
0
0
0
 Asian 
20
20
40
 Native Hawaiian or Other Pacific Islander  
0
0
0
 Black or African American  
57
57
114
 White 
120
120
240
 Racial Categories: Total of All Subjects * 
177
177
354
We will exclude smokers under the age of 18 because our hypotheses regarding interactions between startle 
response and nicotine withdrawal are not necessarily applicable to adolescents. There are likely to be 
significant differences between adults and adolescent in numerous domains including physiological (e.g., 
physiological responses to nicotine may be different in adolescents), and psychological (e.g., developmental 
processes may affect mood self-reports). Therefore, the study of the emotional processes related to smoking 
behavior among adolescent smokers requires a separate focus on those factors that are relevant for this 
population. In addition, the research protocol outlined in the application requires participants to smoke a 
baseline cigarette.  Fulfilling this protocol with participants under the age of 18 is a violation of Texas state law, 
that is, it is unlawful for us to furnish tobacco to minors (SS 161.082) and it is unlawful for minors to possess or 
consume tobacco products (SS 161.252).  Finally, the proposed medications listed in this application are not 
approved for use in children.  
 
Because of the ongoing monitoring of the project, study investigators and staff are responsible for ensuring that 
data quality assurance procedures are developed and maintained. Several procedures will be used to maintain 
the integrity of the data. All databases will be stored in a centralized location on one of the departmental 
servers, which is backed up daily, with access limited to specific users at the discretion of the PI. The PI will 

 
 
 
assure that audits of selected subsets of data are performed and that appropriate safeguards of participant 
privacy are maintained. Privacy safeguards will include appropriate password protection and physical security 
for all computer systems. 
 
Additional quality assurance procedures include a data collection protocol documented in a protocol manual; a 
two-stage editing procedure for survey data collection consisting of the initial review of the data collection form 
by a project member immediately following data collection, and a second review by a project member who will 
record any significant deviations from the protocol; and regular meetings between the study statistician, the PI, 
data managers, and other project staff to review problems and solutions, and discuss concerns. Data entry 
systems, whether via a CATI system, scannable forms, or hand entry with verification, specifically provide field 
checks, range checks for continuous variables and valid value checks for categorical variables; checks for 
legitimate dates and times and logical consistency. A specific audit trail system that identifies the date, time, 
and individual making changes on the database will be part of the data-entry system. During data collection, 
we will issue reports weekly, or even following any new data entry, depending on the needs of the project. 
Queries and reports will be provided to the study statistician and the PI. Preliminary analyses will be initiated 
shortly after data collection begins to allow monitoring of data quality. 
 
 
 
1. 
USDHHS  (U.S. Department of Health and Human Services, Public Health Service, Centers for 
Disease Control, Centers for Chronic Disease Prevention and Health Promotion, Office on Smoking 
and Health). The Health Benefits of Smoking Cessation:  a report of the Surgeon General. 1990 1990. 
Report No.: Publication No. (CDC) 90-8416. 
2. 
CDC  Smoking cessation during previous year among adults - United States 1990 &1991. MMWR Morb 
Mortal Wkly Rep. 1993;42:504-507. 
3. 
Richelson E  Pharmacology of antidepressants--characteristics of the ideal drug. Mayo Clin Proc. 
1994;69:1069-81. 
4. 
Wise R, Rompre P  Brain dopamine and reward. Annual Review of Psychology. 1989;40:191-225. 
5. 
DiChiara G, Imperato A  Drugs abused by humans preferentially increase synaptic dopamine 
concentrations in the mesolimbic system of freely moving rats. Proceedings of the National Academy of 
Sciences USA. 1988;85:5274-5278. 
6. 
Koob G, Weiss F  Neuropharmacology of cocaine and ethanol dependence. New York: Plenum Press; 
1992. (Galanter M, ed. Recent Developments in Alcoholism, Volume 10: Alcohol and Cocaine: 
Similarities and Differences.). 
7. 
Berridge KC, Robinson TE  What is the role of dopamine in reward: hedonic impact, reward learning, or 
incentive salience? Brain Res Brain Res Rev. 1998;28:309-69. 
8. 
Corrigall WA, Coen KM  Selective dopamine antagonists reduce nicotine self-administration. 
Psychopharmacology. 1991;104:171-176. 
9. 
Corrigall WA, Franklin KBJ, Coen KM, Clarke PBS  The mesolimbic dopaminergic system is implicated 
in the reinforcing effects of nicotine. Psychopharmacology. 1992;107:285-289. 
10. 
Nisell M, Marcus M, Nomikos GG, Svensson TH  Differential effects of acute and chronic nictoine on 
dopamine output in the core and shell of the rat nucleus accumbens. Journal of Neural Transmission. 
1997;104:1-10. 
11. 
Pontierl F, G T, Orzi F, Di chiara G  Effects of nicotine on the nucleus accumbens and similarity to 
those of addictive drugs. Nature. 1996;382:255-257. 
12. 
Izenwasser S, Cox BM  Inhibition of dopamine uptake by cocaine and nicotine: tolerance to chronic 
treatments. Brain Research. 1992;573:119-125. 

 
 
 
13. 
Carr L, Basham J, York B, Rowell P  Inihibition of uptake of 1-methyl-4-phenylpyridinium ion and 
dopamine in striatal synaptosomes by tobacco smoke components. European Journal of 
Pharmacology. 1992;215:285-287. 
14. 
Pidoplichko vI, DeBiasi M, Williams JT, Dani JA  Nicotine activates and desensitizes midbrain 
dopamine neurons. Nature. 1997;390:401-404. 
15. 
Uhl G, Blum E, Noble E, Smith S  Substance abuse vulnerability and D2 receptor genes. Trends in 
Neurosciences. 1993;3:83-88. 
16. 
Noble EP, Blum K, Ritchie T, Montgomery A, Sheridan PJ  Allelic Association of the D2 Dopamine 
Receptor Gene With Receptor-Binding Characteristics in Alcoholism. Arch Gen Psychiatry. 
1991;48:648-654. 
17. 
Jonsson EG, Nothen MM, Grunhage F, Farde L, Nakashima Y, Propping P, Sedvall GC  
Polymorphisms in the dopamine D2 receptor gene and their relationships to striatal dopamine receptor 
density of healthy volunteers. Mol Psychiatry. 1999;4:290-6. 
18. 
Volkow ND, Fowler JS, Gatley J, Logan J, Wang G-J, Ding Y-S, Dewey S  PET evaluation of the 
dopamine system of the human brain. The Journal of Nuclear Medicine. 1996;37:1242-1256. 
19. 
Volkow ND, Fowler JS, Wolf AP, al e  Effects of chronic cocaine abuse on postsynaptic dopmine 
receptors. Am J Psychiatry. 1990;147:719-724. 
20. 
Volkow N, Fowler J, Wang G-J, al e  Decreased dopamine D2 receptor availability is associated with 
reduced frontal metabolism in cocaine abusers. Synapse. 1993;14:169-177. 
21. 
Volkow ND, Wang GJ, Fowler JS, Logan J, Gatley SJ, Wong C, Hitzemann R, Pappas N  Reinforciing 
effects of psychostimulants in humans are associated with increases in brain dopamine and occupancy 
of D2 receptors. JPET. 1999;291:409-415. 
22. 
Caskey NH, Jarvik ME, Wirshing WC  The effects of dopaminergic D2 stimulation and blockade on 
smoking behavior. Experimental & Clinical Psychopharmacology. 1999;7:72-8. 
23. 
Jarvik ME, Caskey NH, Wirshing WC, Madsen DC, Iwamoto-Schaap PN, Elins JL, Eisenberger NI, 
Olmstead RE  Bromocriptine reduces cigarette smoking. Addiction. 2000;95:1173-83. 
24. 
Noble EP, Noble RE, Ritchie T, Syndulko K, Bohlman MC, Noble LA, Zhang Y, Sparkes RS, Grandy 
DK  D2 Dopamine Receptor Gene and Obesity. Int J Eat Disord. 1994;15:205-217. 
25. 
Comings D, Wu S, Chiu C, Ring R, Gade R, Ahn C, MacMurray J, Dietz G, Muhleman D  Polygenic 
inheritance of Tourette syndrome, stuttering, attention deficit hyperactivity, conduct, and oppositional 
definant disorder: The additive and subtractive effect of the three dopaminergic  genes- DRD2, D beta 
H, and DAT1. American Journal of Medical Genetics. 1996;67:264-288. 
26. 
Spitz MR, Shi H, Hudmon KS, Jiang H, Chamberlain RM, Amos CI, Wan Y, Cinciripini P, Xifeng W  A 
case-control study of the dopamine D2 receptor gene and smoking status in lung cancer. J Natl Cancer 
Inst. 1998;90:358-363. 
27. 
Bierut LJ, rice JP, Edenberg HJ, Goate A, Foroud T, al e  Family-based study of the association of the 
dopamine D2 receptor gene (DRD2) with habitual smoking. American Journal of Medicine Genetics. 
2000;90:299-302. 
28. 
Batra A, Gelfort G, Bartels M, Smoltczyk H, Buchkremer G, Riess O, Schols L  The dopamine D2 
receptor (DRD2) gene---a genetic risk factor in heavy smoking? Addiction Biology. 2000;5:429-436. 
29. 
Lerman C, Epstein L, Wileyto P, Audrain J, Hawk L, Pinto A, Roth D, Shields P, Niaura R  Genetics and 
response to bupropion. 8th annual meeting of the Society for Research on Nicotine and Tobacco. 
Savannah, GA; 2002. 
30. 
Lerman C, Caporaso N, Audrain J, Main D, Bowman E, Lockshin B, Boyd N, Shields P  Evidence 
suggesting the role of specific genetic factors in cigarette smoking. Health Psychology. 1999;18:14-20. 
31. 
Bannon M, Granneman J, Kapatos G  The dopamine transporter:  Potential involvement in 
neuropsychiatric disorders. New York: Raven Press; 1995. (Bloom F, Kupfer D, eds. 
Psychopharmacology:  The fourth generation of progress). 
32. 
Vandenbergh DJ, Persico AM, Hawkins AL, Griffin CA, Li X, Jabs EW, Uhl GR  Human dopamine 
transporter gene (DAT 1) maps to chomosome 5p 15.3 and displays a VNTR. Genomics. 1992;14. 

 
 
 
33. 
Sabol S, Nelson M, Fisher C, Gunzerath L, Brody C, Hu S, Sirota L, Hamer D  Association of the 
dopamine transporter gene with novelty seeking and cigarette smoking behavior. Health Psychol. 
1999;18:7-13. 
34. 
Jorm AF, Henderson AS, Jacomb PA, Christensen H, Korten AE, Rodgers B, Tan X, Easteal S  
Association of smoking and personality with a polymorphism of the dopamine transporter gene: results 
from a community survey. American Journal of Medical Genetics. 2000;96:331-4. 
35. 
Vandenbergh DJ, Bennett CJ, Grant MD, Strasser AA, O'Connor R, Stauffer RL, Vogler GP, Kozlowski 
LT  Smoking status and the human dopamine transporter variable number of tandem repeats (VNTR) 
polymorphism: failure to replicate and finding that never-smokers may be different.PG - 333-40. 
Nicotine Tob Res. 2002;4. 
36. 
Seeman P, Guan HC, Van Tol HH  Dopamine D4 receptors elevated in schizophrenia. Nature
(London). 1993;365:441-445. 
37. 
Cloninger CR  The Tridimensional Personality Questionnaire, Version IV. Washington University School 
of Medicine; 1987. 
38. 
Ebstein RP, Segman R, Benjamin J, Osher Y, Lubov N, Belmaker RH  5-HT2C (HTR2C) serotonin 
receptor gene polymorphism associated with the human personality trait of reward dependence:  
Interaction with dopamine D4 receptor (D4DR) and dopamine D3 receptor (D3DR) polymorphisms. 
American Journal of Medical Genetics. 1997;74:65-72. 
39. 
Benjamin J, Lin L, Patterson C, Greenberg B, Murphy D, Hamer D  Population and familial association 
between the D4 dopamine receptor gene and measures of Novelty Seekin. Nature Genetics. 
1996;12:81-84. 
40. 
Shields PG, Lerman C, Audrain J, Bowman ED, Main D, Boyd NR, Caporaso NE  Dopamine D4 
Receptors and the Risk of Cigarette Smoking in African-Americans and Caucasians. Cancer
Epidemiology, Biomarkers & Prevention. 1998;7:453-458. 
41. 
Hutchison KE, LaChance H, Niaura R, Bryan A, Smolen A  The DRD4 VNTR polymorphism influences 
reactivity to smoking cues. J Abnorm Psychol. 2002;111:134-43. 
42. 
Shiffman S, Paty J, Gnys M, Kassel J, Hickcox M  First lapses to smoking: Within-subjects analysis of 
real-time reports. J Consult Clin Psychol. 1996;64:366-379. 
43. 
Mihailescu S, Palomero-Rivero M, Meade-Huerta P, Maza-Flores A, Drucker-Colin R  Effects of 
nicotine and mecamylamine on rat dorsal raphe neurons. Eur J Pharmacol. 1998;360:31-6. 
44. 
Ribeiro EB, Bettiker RL, Bogdanov M, Wurtman RJ  Effects of systemic nicotine on serotonin release in 
rat brain. Brain Res. 1993;621:311-8. 
45. 
Kenny PJ, Markou A  Neurobiology of the nicotine withdrawal syndrome. Pharmacology, Biochemistry 
& Behavior. 2001;70:531-49. 
46. 
Stein EA, Pankiewicz J, Harsch HH, Cho JK, Fuller SA, Hoffmann RG, Hawkins M, Rao SM, Bandettini 
PA, Bloom AS  Nicotine-induced limbic cortical activation in the human brain: a functional MRI study. 
Am J Psychiatry. 1998;155:1009-15. 
47. 
Smith GS, Dewey SL, Brodie JD, Logan J, Vitkun SA, Simkowitz P, Schloesser R, Alexoff DA, Hurley 
A, Cooper T, Volkow ND  Serotonergic Modulation of Dopamine Measured With [11C]Raclopride and 
PET in Normal Human Subjects. Am J Psychiatry. 1997;154:490-496. 
48. 
Rasmussen K, Kallman MJ, Helton DR  Serotonin-1A antagonists attenuate the effects of nicotine 
withdrawal on the auditory startle response. Synapse. 1997;27:145-52. 
49. 
Harrison AA, Liem YT, Markou A  Fluoxetine combined with a serotonin-1A receptor antagonist 
reversed reward deficits observed during nicotine and amphetamine withdrawal in rats. 
Neuropsychopharmacology. 2001;25:55-71. 
50. 
Balfour DJ, Ridley DL  The effects of nicotine on neural pathways implicated in depression: a factor in 
nicotine addiction? Pharmacology, Biochemistry & Behavior. 2000;66:79-85. 
51. 
Cheeta S, Irvine EE, Kenny PJ, File SE  The dorsal raphe nucleus is a crucial structure mediating 
nicotine's anxiolytic effects and the development of tolerance and withdrawal responses. 
Psychopharmacology (Berl). 2001;155:78-85. 
52. 
Gobert A, Rivet JM, Lejeune F, Newman-Tancredi A, Adhumeau-Auclair A, Nicolas JP, Cistarelli L, 
Melon C, Millan MJ  Serotonin(2C) receptors tonically suppress the activity of mesocortical 

 
 
 
dopaminergic and adrenergic, but not serotonergic, pathways: a combined dialysis and 
electrophysiological analysis in the rat. Synapse. 2000;36:205-21. 
53. 
Di Matteo V, Di Giovanni G, Di Mascio M, Esposito E  Biochemical and electrophysiological evidence 
that RO 60-0175 inhibits mesolimbic dopaminergic function through serotonin(2C) receptors. Brain Res. 
2000;865:85-90. 
54. 
Millan MJ, Dekeyne A, Gobert A  Serotonin (5-HT)2C receptors tonically inhibit dopamine (DA) and 
noradrenaline (NA), but not 5-HT, release in the frontal cortex in vivo. Neuropharmacology. 
1998;37:953-5. 
55. 
Di Matteo V, Di Giovanni G, Di Mascio M, Esposito E  SB 242084, a selective serotonin2C receptor 
antagonist, increases dopaminergic transmission in the mesolimbic system. Neuropharmacology. 
1999;38:1195-205. 
56. 
Grottick AJ, Corrigall WA, Higgins GA  Activation of 5-HT(2C) receptors reduces the locomotor and 
rewarding effects of nicotine. Psychopharmacology. 2001;157:292-8. 
57. 
Esposito E  An indirect action for fluoxetine on the dopamine neurotransmitter system. Trends in 
Pharmacological Sciences. 1996;17:400-2. 
58. 
Prisco S, Esposito E  Differential effects of acute and chronic fluoxetine administration on the 
spontaneous activity of dopaminergic neurones in the ventral tegmental area. Br J Pharmacol. 
1995;116:1923-31. 
59. 
Carroll ME, Lac ST, Asencio M, Kragh R  Fluoxetine reduces intravenous cocaine self-administration in 
rats. Pharmacol Biochem Behav. 1990;35:237-44. 
60. 
Richardson NR, Roberts DC  Fluoxetine pretreatment reduces breaking points on a progressive ratio 
schedule reinforced by intravenous cocaine self-administration in the rat. Life Sci. 1991;49:833-40. 
61. 
Higgins GA, Wang Y, Corrigall WA, Sellers EM  Influence of 5-HT3 receptor antagonists and the 
indirect 5-HT agonist, dexfenfluramine, on heroin self-administration in rats. Psychopharmacology 
(Berl). 1994;114:611-9. 
62. 
Killen J, Fortmann S, Schatzberg A, Hayward C, Sussman L, Rothman M, Strausberg L, Varady A  
Nicotine patch and paroxetine for smoking cessation. J Consult Clin Psychol. 2000;68:885-889. 
63. 
Covey LS, Sullivan MA, Johnston JA, Glassman AH, Robinson MD, Adams DP  Advances in non-
nicotine pharmacotherapy for smoking cessation. Drugs. 2000;59:17-31. 
64. 
Cinciripini PM, McMclure JB  Smoking cessation:  Recent developments in behavioral and 
pharmacologic interventions. Oncology. 1998;12:249-270. 
65. 
Hitsman B, Pingitore R, Spring B, Mahableshwarkar A, Mizes JS, Segraves KA, Kristeller JL, Xu W  
Antidepressant pharmacotherapy helps some cigarette smokers more than others. Journal of 
Consulting and Clinical Psycholology. 1999;67:547-54. 
66. 
Blakely RD  Physiological genomics of antidepressant targets: keeping the periphery in mind. J
Neurosci. 2001;21:8319-23. 
67. 
Owens MJ, Nemeroff CB  Role of serotonin in the pathophysiology of depression: focus on the 
serotonin transporter. Clin Chem. 1994;40:288-95. 
68. 
Lesch KP, Balling U, Gross J, Strauss K, Wolozin BL, Murphy DL, Riederer P  Organization of the 
human serotonin transporter gene. J Neural Transm Gen Sect. 1994;95:157-62. 
69. 
Heils A, Mossner R, Lesch KP  The human serotonin transporter gene polymorphism--basic research 
and clinical implications. J Neural Transm. 1997;104:1005-14. 
70. 
Heils A, Teufel A, Petri S, Stober G, Riederer P, Bengel D, Lesch KP  Allelic variation of human 
serotonin transporter gene expression. J Neurochem. 1996;66:2621-4. 
71. 
Ishikawa H, Ohtsuki T, Ishiguro H, Yamakawa-Kobayashi K, Endo K, Lin YL, Yanagi H, Tsuchiya S, 
Kawata K, Hamaguchi H, Arinami T  Association between serotonin transporter gene polymorphism 
and smoking among Japanese males. Cancer Epidemiology, Biomarkers & Prevention. 1999;8:831-3. 
72. 
Lerman C, Shields P, Audrain J, Main D, Cobb B, Boyd N, Caporaso N  The role of the serotinin 
transporter gene in cigarette smoking. Cancer Epidemiol Biomarkers Prev. 1998;7:253-255. 
73. 
Lerman C, Caporaso NE, Audrain J, Main D, Boyd NR, Shields PG  Interacting effects of the serotonin 
transporter gene and neuroticism in smoking practices and nicotine dependence. Molecular Psychiatry. 
2000;5:189-92. 

 
 
 
74. 
Hu S, Brody CL, Fisher C, Gunzerath L, Nelson ML, Sabol SZ, Sirota LA, Marcus SE, Greenberg BD, 
Murphy DL, Hamer DH  Interaction between the serotonin transporter gene and neuroticism in cigarette 
smoking behavior. Molecular Psychiatry. 2000;5:181-188. 
75. 
Zhang K, Chamberlain RM, Spitz MR, Cinciripini PM, Grossman HB, Lerner SP, Wu X  Serotonin 
Transporter Gene (5-HTT) Polymorphism and Genetic Predisposition to Smoking in Bladder Cancer 
Patients. Manuscript submitted for publication. 
76. 
Nestler EJ, Alreja M, Aghajanian GK  Molecular control of locus coeruleus neurotransmission. Biol
Psychiatry. 1999;46:1131-9. 
77. 
Gallardo KA, Leslie FM  Nicotine-stimulated release of [3H]norepinephrine from fetal rat locus 
coeruleus cells in culture. J Neurochem. 1998;70:663-70. 
78. 
Klimek V, Zhu MY, 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;58:821-7. 
79. 
Nestler EJ, Barrot M, DiLeone RJ, Eisch AJ, Gold SJ, Monteggia LM  Neurobiology of depression. 
Neuron. 2002;34:13-25. 
80. 
Markou A, Kosten TR, Koob GF  Neurobiologcal similarities in depression and drug dependence- A 
self-medication hypotheses (Review). Neuropsychopharmacology. 1998;18:135-174. 
81. 
Stober G, Hebebrand J, Cichon S, Bruss M, Bonisch H, Lehmkuhl G, Poustka F, Schmidt M, 
Remschmidt H, Propping P, Nothen MM  Tourette syndrome and the norepinephrine transporter gene: 
results of a systematic mutation screening. Am J Med Genet. 1999;88:158-63. 
82. 
Owen D, Du L, Bakish D, Lapierre YD, Hrdina PD  Norepinephrine transporter gene polymorphism is 
not associated with susceptibility to major depression. Psychiatry Research. 1999;87:1-5. 
83. 
Runkel F, Bruss M, Nothen MM, Stober G, Propping P, Bonisch H  Pharmacological properties of 
naturally occurring variants of the human norepinephrine transporter. Pharmacogenetics. 2000;10:397-
405. 
84. 
Xu F, Gainetdinov RR, Wetsel WC, Jones SR, Bohn LM, Miller GW, Wang YM, Caron MG  Mice 
lacking the norepinephrine transporter are supersensitive to psychostimulants. Nature Neuroscience. 
2000;3:465-71. 
85. 
Zill P, Engel R, Baghai TC, Juckel G, Frodl T, Muller-Siecheneder F, Zwanzger P, Schule C, Minov C, 
Behrens S, Rupprecht R, Hegerl U, Moller HJ, Bondy B  Identification of a naturally occurring 
polymorphism in the promoter region of the norepinephrine transporter and analysis in major 
depression. Neuropsychopharmacology. 2002;26:489-93. 
86. 
Jonsson EG, Nothen MM, Gustavsson JP, Neidt H, Bunzel R, Propping P, Sedvall GC  Polymorphisms 
in the dopamine, serotonin, and norepinephrine transporter genes and their relationships to monoamine 
metabolite concentrations in CSF of healthy volunteers. Psychiatry Research. 1998;79:1-9. 
87. 
Hutchinson KE, al. e  The DRD4 VNTR Polymorphism Influences Reactivity to Smoking Cues. J
Abnorm Psychol. 2002;111:134-143. 
88. 
Cinciripini PM, Wetter DE, Tomlinson GE, Tsoh JT, De Moor CA, Cinciripini LG, Baile WS, Minna JD  
The effects of the DRD2 A1 allele on smoking cessation and negative affect: evidence for a 
pharmacogenetic effect on mood. In preparation. 
89. 
Lerman C, Roth D, Kaufman V, Audrain J, Hawk L, Liu A, Niaura R, Epstein L  Mediating mechanisms 
for the impact of bupropion in smoking cessation treatment. Drug  Alcohol Depend. 2002;67:219-223. 
90. 
Kenford SL, Wetter DW, Smith SS, Jorenby DE, Fiore MC, Baker TB  Predicting relapse back to 
smoking:Contrasting affective and physical models of dependence. J Consult Clin Psychol. 
2002;70:216-227. 
91. 
American Psychiatric Association  Diagnostic and Statistical Manual of Mental Disorders, 4th Edition 
Washington, D.C.: American Psychiatric Association; 1994. 
92. 
Breslau N, Kilbey MM, Andreski P  Nicotine dependence, major depression, and anxiety in young 
adults. Arch Gen Psychiatry. 1991;48:1069-1074. 
93. 
Glassman AH, Helzer JE, Covey LS, Cottler LB, Stetner F, Tipp JE, Johnson J  Smoking, smoking 
cessation, and major depression. J Am Med Asso. 1990;264:1546-1549. 

 
 
 
94. 
Kendler KS, Neale MC, MacLean CJ, Heath AC, Eaves LJ, Kessler RC  Smoking and major 
depression: A casual analysis. Arch Gen Psychiatry. 1993;50:36-43. 
95. 
Breslau N, Kilbey MM, Andreski P  Nicotine dependence and major depression: New evidence from a 
prospective investigation. Arch Gen Psychiatry. 1993;50:31-35. 
96. 
Covey LS, Glassman AH, Stetner F  Depression and depressive symptoms in smoking cessation. 
Compr Psychiatry. 1990;31:350-354. 
97. 
Breslau N, Kilbey MM, Andreski P  Nicotine withdrawal symptoms and psychiatric disorders: Findings 
from an epidemiologic study of young adults. Am J Psychiatry. 1992;149:464-469. 
98. 
Borrelli B, Bock B, King T, Pinto B, Marcus BH  The impact of depression on smoking cessation in 
women. American Journal of Prevention Medicine. 1996;12:378-387. 
99. 
Glassman AH, Covey LS, Stetner SR  Smoking cessation and the course of major depression: a follow-
up study. Lancet. 2001;357:1930-1932. 
100. 
Glassman AH, Stetner F, Walsh BT, Raizman PS, Fleiss JL, Cooper TB, Covey LS  Heavy smokers, 
smoking cessation, and clonidine: results of a double-blind, randomized trial. J Am Med Asso. 
1988;259:2863-2866. 
101. 
Anda RF, Williamson DF, Escobedo LG, Mast EE, Giovino GA, Remington PL  Depression and the 
dynamics of smoking: a national perspective. J Am Med Asso. 1990;264:1541-1545. 
102. 
Brandon TH, Tiffany ST, Obremski KM, Baker TB  Postcessation cigarette use:  The process of 
relapse. Addict Behav. 1990;15:105-114. 
103. 
Wetter DW, Kenford SL, Smith SS, Fiore MC, Jorenby DE, Baker TB  Gender differences in smoking 
cessation. J Consult Clin Psychol. 1999;67:555-562. 
104. 
Burgess ES, Kahler CW, Niaura R, Abrams DB, Goldstein MG, Miller IW  Patterns of change in 
depressive symptoms during smoking cessation: Who's at risk for relapse? Journal of Consulting & 
Clinical Psychology. 2002;70:356-361. 
105. 
Breslau N, Peterson EL, Schultz LR, Chilcoat HD, Andreski P  Major depression and stages of 
smoking: A longitudinal investigation. Arch Gen Psychiatry. 1998;55:161-166. 
106. 
Morris S, Mermelstein R  Depression and relapse:  Antecedent or consequence? SRNT Fifth Annual 
Conference. San Diego, CA: SRNT; 1999: 60. 
107. 
Niaura R, Britt DM, Borrelli B, Shadel WG, Abrams DB, Goldstein MG  History and symptoms of 
depression among smokers during a self-initiated quit attempt. Nicotine & Tobacco Research. 
1999;1:251-257. 
108. 
Ginsberg D, Hall SM, Reus VI, Muñoz RF  Mood and depression diagnosis in smoking cessation. Exp
Clin Psychopharmacol. 1995;3:389-395. 
109. 
Killen J  Do Heavy Smokers Benefit From Higher Dose Nicotine Patch Therapy? 1996. 
110. 
Kinnunen T, Doherty K, Militello FS, Garvey AJ  Depression and smoking cessation: characteristics of 
depressed smokers and effects of nicotine replacement. J Consult Clin Psychol. 1996;64:791-798. 
111. 
Cinciripini PM, Wetter DW, Fouladi RT, Blalock JA, Carter BL, Cinciripini LG, Baile WF  The effects of 
depressed mood on smoking cessation: Mediation by post-cessation self-efficacy. J Consult Clin 
Psychol. In press. 
112. 
Borrelli B, Niaura R, Keuthen NJ, Goldstein MG, DePue JD, Murphy C, Abrams DB  Development of 
major depressive disorder during smoking-cessation treatment. J Clin Psychiatry. 1996;57:534-538. 
113. 
Piasecki T, Fiore M, Baker T  Profiles in Discouragement:  Two Studies of Variability in the Time course 
of Smoking Withdrawal Symptoms. J Abnorm Psychol. 1998;107:238-251. 
114. 
Wetter D, Kenford S, Fiore M  Personal Communication. 1994. 
115. 
O'Neill S, Parrott A  Stress and arousal in sedative and stimulant cigarette smokers. 
Psychopharmacology. 1992;107:442-446. 
116. 
Shiffman S  Relapse following smoking cessation:  A situational analysis. Journal of Counsulting and 
Clinical Psychology. 1982;50:71-86. 
117. 
Shiffman S  Individual differences in smoking and nicotine addiction. Addicted to Nicotine:  A National 
Research Forum. Bethesda, MD; 1998. 
118. 
Cook EWI, Davis TL, Hawk LW, Spence EW, Gautier CH  Fearfulness and startle potentiation during 
aversive visual stimuli. Psychophysiology. 1992;29:633-645. 

 
 
 
119. 
Vrana SR, Spence EL, Lang PJ  The startle probe response: A new measure of emotion? J Abnorm 
Psychol. 1988;97:487-491. 
120. 
Cuthbert BN, Bradley MM, Lang PJ  Probing picture perception: Activation and emotion. 
Psychophysiology. 1996;33:103-111. 
121. 
Bradley MM, Lang PJ, Cuthbert BN  Emotion, novelty, and the startle reflex: Habituation in humans. 
Behavioral Neuroscience. 1993;107:970-980. 
122. 
Patrick CJ, Bradley MM, Lang PJ  Emotion in the criminal psychopath. J Abnorm Psychol. 1993;102:82-
92. 
123. 
Cuthbert BN, Drobes Dd, Strauss C, Patrick CJ, Lang PJ  Autonomic and startle responding during 
affective imagery among anxious patients. Psychophysiology. 1994;31 (Suppl.) S37. 
124. 
Hamm AO, Cuthbert BN, Globisch J, Vaitl D  Fear and the startle reflex: blink modulation and 
autonomic response patterns in animal and mutilation fearful subjects. Psychophysiology. 1997;34:97-
107. 
125. 
Balaban M  Affective influences on startle in five-month-old infants: Reactions to facial expressions of 
emotion. Child Development. 1995;66:28-36. 
126. 
Jennings P, Lovejoy S, Stirling J, Lara M  What We Tell Ourselves and How It Makes Us Feel:  The 
Psychophysiology of Self-Talk. Society for Psychophysiological Research Thirty-eighth Annual Meeting. 
Denver, Co; 1998. 
127. 
Grillon C, Morgan A  Startle Response in Posttraumatic Stress Disorder. Society for 
Psychophysiological Research Thirty-eighth Annual Meeting. Denver, Co; 1998. 
128. 
Panayiotou G, Vrana S  Effect of self-focused attention on the startle reflex, heart rate, and memory 
performance among socially anxious and nonanxious individuals. Psychophysiology. 1998;35:328-336. 
129. 
Lang PJ, Bradley MM, Cuthbert BN  Emotion, attention, and the startle reflex. Psychological Review. 
1990;97:377-395. 
130. 
Lang PJ, Bradley MM, Cuthbert BN  A motivational analysis of emotion: Reflex-cortex connections. 
Psychological Science. 1992;3:44-49. 
131. 
Ascher JA, Cole JO, Colin JN, Feighner JP, Ferris RM, Fibiger HC, Golden RN, Martin P, Potter WZ, 
Richelson E  Bupropion: A review of its mechanism of antidepressant activity. J Clin Psychiatry. 
1995;56:395-401. 
132. 
Sanchez C, Hyttel J  Comparison of the effects of antidepressants and their metabolites on reuptake of 
biogenic amines and on receptor binding. Cellular and Molecular Neurobiology. 1999;19:467-89. 
133. 
Nomikos GG, Damsma G, Wenkstern D, Fibiger HC  Acute effects of bupropion on extracellular 
dopamine concentrations in rat striatum and nucleus accumbens studied by in vivo microdialysis. 
Neuropsychopharmacology. 1989;2:273-279. 
134. 
Terry P, Katz JL  Dopaminergic mediation of the discriminative stimulus effects of bupropion in rats. 
Psychopharmacology. 1997;134:201-212. 
135. 
Britton J, Jarvis MJ  Bupropion: A new treatment for smokers. Br Med J. 2000;321:65-66. 
136. 
Slemmer JE, Martin BP, Damaj I  Bupropion is a nicotine antagonist. The Journal of Pharmacology and 
Experimental Therapeutics. 2000;295:321-327. 
137. 
Cooper BR, Wang CM, Cox RF, Norton R, Shea V, Ferris RM  Evidence that the acute behavioral and 
electrophysiological effects of bupropion (Wellbutrin) are mediated by a noradrenergic mechanism. 
Neuropsychopharmacology. 1994;11:133-141. 
138. 
Dong J, Blier P  Modification of norepinephrine and serotonin, but not dopamine, neuron firing by 
sustained bupropion treatment. Psychopharmacology. 2001;155:52-57. 
139. 
Hays JT, Hurt RD, Rigotti NA, Niaura R, Gonzales D, Durcan MJ, Sachs DPL, Wolter TD, Buist AS, 
Johnston JA, White JD  Sustained-release bupropion for pharmcologic relapse prevention after 
smoking cessation. Ann  Intern Med. 2001;135:423-433. 
140. 
Hurt RD, Sachs DPL, Glover ED, Offord KP, Johnston JA, Dale LC, Khayrallah MA, Schroeder DR, 
Glover PN, Sullivan CR, Croghan IT, Sullivan PM  A comparison of sustained-release bupropion and 
placebo for smoking cessation. The New England Journal of Medicine. 1997;337:1195-1202. 
141. 
Jorenby DE, Leischow SJ, Nides MA, Rennard SI, Johnston JA, Hughes AR, Smith SS, Muramoto ML, 
Daughton DM, Doan K, Fiore MC, Baker TB  A controlled trial of sustained-release bupropion, a 

 
 
 
nicotine patch, or both for smoking cessation. The New England Journal of Medicine. 1999;340:685-
691. 
142. 
Tashkin DP, Kanner R, Bailey W, Buist AS, Anderson P, Nides MA, Gonzales D, Dozier G, Patel MK, 
Jamerson BD  Smoking cessation in patients with chronic obstructive pulmonary disease: A double-
blind, placebo-controlled, randomised trial. Lancet. 2001;357:1571-1575. 
143. 
Watson D, Clark LA, Tellegen A  Development and validation of brief measures of positive and negative 
affect; The PANAS Scales. J Pers Socl Psychol. 1988;54:1063-1070. 
144. 
Fiore MC, Bailey, W. C., Cohen, S. J., Dorfman, S. F., Goldstein, M. G., Gritz, E. R., Heyman, R. B., 
Holbrook, J., Jaen, C. R., Kottke, T. E., Lando, H. A., Mecklenbur, R., Mullen, P. D., Nett, L. M., 
Robinson, L., Stitzer, M., Tommasello, A. C., Villejo, L., & Wewers, M. E. (U.S. Department of Health 
and Human Services. Public Health Service). Treating Tobacco Use and Dependence. Clinical Practice 
Guideline. 2000 June. 
145. 
Prochazka AV, EWeaver MJ, Keller RT, Fryer GE, Licari PA, Lofaso D  A randomized trial of 
nortriptyline for smoking cessation. Arch Intern Med. 1998;158:2035-2039. 
146. 
Hall SM, Reus VI, Munoz RF, Sees KL, Humfleet G, Hartz DT, Frederick S, Triffleman E  Nortriptyline 
and cognitive-behavioral therapy in the treatment of cigarette smoking. Arch Gen Psychiatry. 
1998;55:683-690. 
147. 
Cinciripini PM, Tsoh JT, Wetter DE, Cinciripini LG, Skaar L, Friedman K, Anderson CB, De Moor CA, 
Baile WS, Minna J  Combined effects of venlafaxine, nicotine replacement & brief counseling on 
smoking cessation. In preparation. 
148. 
Cinciripini PM, Wetter DE, Minna JD, Tsoh JT, Gritz ER, Baile WS, Hu S  The effects of brief 
counseling, transdermal nicotine replacement and antidepressant therapy on smoking cessation among 
smokers carrying the DRD2 A1 allele. Society for Research on Nicotine and Tobacco. San Diego, 
California; 1999. 
149. 
The international affective picture system: Photographic slides CSEA-NIMH. Gainesville, FL: The 
Center for Research in Psychophysiology, University of Florida; 1995. 
150. 
Carter BL, Cinciripini PM, Robinson JD, Long TY, Lam CY, Wetter DW, Sanders CA, Benjamin RH  
The effect of nicotine administration and deprivation on emotional reactivity in smokers. Society for 
Research on Nicotine and Tobacco. Savannah, GA.; 2002. 
151. 
U. S. Department of Commerce  (U. S. Department of Commerce). Profiles of General demographic 
characteristics: 2000 census of population and housing. 2000. 
152. 
Noble EP  The D2 dopamine receptor gene- A review of association studies in alcoholism and 
phenotypes. Alcohol. 1998;16:33-45. 
153. 
Noble EP, Blum K, Khalsa ME, Ritchie T, Montgomery A, Wood RC, Fitch RJ, Ozkaragoz T, Sheridan 
PJ, Anglin MD, Paredes A, Treiman LJ, Sparkes RS  Allelic association of the D2 dopamine receptor 
gene with cocaine dependence. Drug  Alcohol Depend. 1993;33:271-285. 
154. 
Comings DE, Ferry L, Bradshaw-Robinson S, Burchette R, Chiu C, Muhleman D  The dopamine D2 
receptor (DRD2) gene:  a genetic risk factor in smoking. Pharmacogenetics. 1996;6:73-79. 
155. 
Lerman C, Caporaso NE, Audrain J, Main D, Bowman ED, Lockshin B, Boyd NR, Shields PG  Evidence 
suggesting the role of specific genetic factors in cigarette smoking. Health Psychol. 1999;18:14-20. 
156. 
Spitzer RL, Williams JBW, Kroenke K, Linzer M, deGruy FV, Hahn SR, Brody D, Johnson JG  Utility of 
a new procedure for diagnosing mental disorders in primary care:  The PRIME-MD 1000 study. J Am 
Med Asso. 1994;272:1749-1756. 
157. 
Spitzer RL, Williams JB, Gibbon M  Structured clinical interview for DSM-III-R, Non-patient version. 
New York State Psychiatric Institute. 1989. 
158. 
Cinciripini PM, Tsoh JT, Wetter DE, Baile WS, Friedman K, Skaar L, Cinciripini LG, Chuang J, 
Anderson C, Lilly S  An evaluation of nicotine replacement, brief counseling, and antidepressant 
therapy for smoking cessation. Society for Research on Nicotine and Tobacco. New Orleans, 
Louisiana; 1997. 
159. 
Bryant K, Rounsaville B, Spitzer RL, Williams JB  Reliability of dual diagnosis: Substance dependence 
and psychiatric disorders. Journal of Nervous & Mental Disease. 1992;180:251-257. 

 
 
 
160. 
Cinciripini PM, Lapitsky LG, Seay S, Wallfisch A, Kitchens K, Van Vunakis H  The effects of smoking 
schedules on cessation outcome:  Can we improve on common methods of gradual and abrupt nicotine 
withdrawal. J Consult Clin Psychol. 1995;63:388-399. 
161. 
Cinciripini PM, Cinciripini LG, Wallfisch A, Van Vunakis H, Haque W  Behavior therapy and the 
transdermal nicotine patch:  effects on cessation outcome, affect, and coping. J Consult Clin Psychol. 
1996;64:314-323. 
162. 
Fagerstrom KO  A comparison of psychological and pharmacological treatment in smoking cessation. J
Behav Med. 1982;5:343-351. 
163. 
Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO  The Fagerstrom test for nicotine 
dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict. 1991;86:1119-1127. 
164. 
Payne TJ, Smith PO, McCracken LM, McSherry WC, Anthony MM  Assessing nicotine dependence: A 
comparison of the Fagerstrom Tolerance Questionnaire (FTQ) with the Fagerstrom Test for Nicotine 
Dependence (FTND) in a clinical sample. Addict Behav. 1994;19:307-374. 
165. 
Pomerleau CS, Pomerleau OF, Majchrzak MJ, Kloska DD, Malakuti R  Relationship between 
Fagerstrom Tolerance Questionnaire scores and plasma cotinine. Addict Behav. 1990;15:73-80. 
166. 
Pinto RP, Abrams DB, Monti PM, Jacobus SI  Nicotine dependence and likelihood of quitting smoking. 
Addict Behav. 1987;12:371-374. 
167. 
Fagerstrom KO  Measuring degree of physical dependence to tobacco smoking with reference to 
individualization of treatment. Addict Behav. 1978;3:235-241. 
168. 
Welsch S, Smith S, Wetter D, Jorenby D, Fiore M, Baker T  Development and validation of the 
Wisconsin Smoking Withdrawal Scale. Exp Clin Psychopharmacol. 1999;7:354-361. 
169. 
Hughes JR, Hatsukami DK, Pickens RW, Svikis DS  Consistency of the tobacco withdrawal syndrome. 
Addict Behav. 1984;9:409-412. 
170. 
Ross CE, Mirowsky J  Components of depressed mood in married men and women.  The Center for 
Epidemiologic Studies' Depression Scale. Am J  Epidemiol. 1984;119:997-1004. 
171. 
Benowitz NB  The use of biologic fluid samples in assessing tobacco smoke consumption. In: 
Department of Health & Human Services, ed. Measurement in the analysis and treatment of smoking 
behavior. Rockville MD: DHHS Publication No. (ADM) 83-1285; 1983. 
172. 
Hariharan M, VanNoord T  Liquid-chromatographic determination of nicotine and cotinine in urine from 
passive smokers: comparison with gas chromatography with a nitrogen-specific detector.  Clinical 
chemistry. Clinical chemistry. 1991;37:1989-1993. 
173. 
George SR, Cheng R, Nguyen T, Israel Y, O'Dowd BF  Polymorphisms of the D4 dopamine receptor 
alleles in chronic alcoholism. Biochem. Biophys. Res. Common. 1993;196. 
174. 
Serretti A, al. e  Serotonin transporter gene (5-HTTLPR) is not associated with depressive 
symptomatology in mood disorders. Molecular Psychiatry. 1999;4:280-283. 
175. 
Fiore MC  US public health service clinical practice guideline: treating tobacco use and dependence. 
Respiratory Care. 2000;45:1200-62. 
176. 
Cinciripini PM, McClure JB, Tsoh J, Wetter D, Cinciripini L  LifeCheq Smoking Cessation Program 
(Program Manual) Houston, Texas: MD Anderson Cancer Center, Division of Cancer Prevention, 
Department of Behavioral Science Tobacco Research & Treatment Program; 1997. 
177. 
Kenford SL, Fiore MC, Jorenby DE, Smith SS, Wetter D, Baker TB  Predicting smoking cessation - 
Who will quit with and without the nicotine patch. J Am Med Asso. 1994;271:589-594. 
178. 
Hughes JR  Tobacco withdrawal in self-quitters. J Consult Clin Psychol. 1992;60:689-697. 
179. 
Hall SM, Reus VI, Humfleet G, Munoz RF  Extended nortriptyline in the treatment of cigarette smoking. 
Society for Research on Nicotine and Tobacco. Savannah, Ga.; 2002. 
180. 
Benowitz N, Hall S, Hatsukami D, Henningfield J, Hughes J, Mermelstein R, Shiffman S  Treatment 
outcomes methodology workshop. The Society for Research on Nicotine and Tobacco. Crystal 
Gateway Marriott Hotel, Arlington, Virginia; 2000. 
181. 
Cinciripini PM, McClure JB, Wetter DW, Perry J, Blalock JA, Cinciripini LG, Friedman KE, Skaar K  An 
evaluation of videotaped vignettes for smoking cessation and relapse prevention during pregnancy: The 
Very Important Pregnant Smokers (VIPS) Program. Tobacco Control. 2000;9:III61-63. 

 
 
 
182. 
Maude-Griffin PM, Tiffany ST  Production of smoking urges through imagery: The impact of affect and 
smoking abstinence. Exp Clin Psychopharmacol. 1996;4:198-208. 
183. 
Witvliet C, Vrana S  Psychophysiological responses as indices of affective dimensions. 
Psychophysiology. 1995;32:436-443. 
184. 
Carter BL, Cinciripini PM, Robinson JD, Long TY, Lam CY, Wetter DE, Sanders-Munoz C, Berry MF  A 
comparison of startle eyeblink responses to affective and cigarette-related stimuli in smokers. Society 
for Research on Nicotine and Tobacco. Seattle Washington; 2001. 
185. 
Lang PJ, Greenwald MK, Bradley MM, Hamm AO  Looking at pictures:  Affective, facial, visceral, and 
behavioral reactons. Psychophysiology. 1993;30:261-273. 
186. 
Prokasy W, Raskin D, eds. Electrodermal activity in psychological research. New York: Academic 
Press; 1973. 
187. 
McCullagh P, Nedler JA  Generalized Linear Models. 2nd ed New York, New York: Whapman & Hall; 
1989. 
188. 
Gibbons R, Hedeker D, Waternaux C  Random regression models: a comprehensive approach to the 
analysis of longitudinal psychiatric data. Psychopharmacology. 1988;24:438-443. 
189. 
Gibbons R, Hedeker D, Elkin I, Waternaux C, Kraemer KH, Greehouse J, Shea T, Imber S, Sotsky S, 
Watkins J  Some conceptual and statistical issues in the analysis of logitudintal psychiatric data. Arch 
Gen Psychiatry. 1993;50:739-750. 
190. 
Noble EP, St. Jeor ST, Ritchie T, Syndulko K, St. Jeor SC, Fitch RJ, Brunner RL, Sparkes RS  D2 
Dopamine Receptor Gene and Cigarette Smoking: A Reward Gene? Medical Hypotheses. 
1994;42:257-260. 
191. 
Gelernter J, al. e  DRD2 Allele Frequencies and Linkage Disequilibria, Including the -141CIns/Del 
Promoter Polymorphism, in European-American, African-American, and Japanese Subjects. Genomics. 
1998;51:21-26. 
192. 
Patkar AA, Berrettini WH, Hoehe M, Hill KP, Sterling RC, Gottheil E, Weinstein SP  Serotonin 
transporter (5-HTT) gene polymorphisms and susceptibility to cocaine dependence among African-
American individuals. Addict Biol. 2001;6:337-345. 
 
We have entered into a subcontract with Hamon Center For Therapeutic Oncology Research, at UT 
Southwestern Medical Center in Dallas, TX., to provide the genetic analysis described in this proposal. Dr. Gail 
Tomlinson is the PI of the sub contract. She will oversee all aspects of processing the blood samples into DNA, 
their cataloguing and storage, and subsequent genotyping analyses for genes relevant to nicotine addiction as 
described in the proposal. Dr. Tomlinson has over 20 years experience leading research into genetic 
abnormalities in lung and breast cancer and other cancers including the conduct of multiple clinical trials and 
translational research.  All of this is well documented in papers in the peer-reviewed literature and her 
biosketch. She has provided all the analysis to date for our previous trial (approximately 200 samples) and 
current clinical trial on scheduled smoking (approximately 1000 samples). Dr. Tomlinson¶s laboratory set up all 
of the protocols for accessioning large number of blood specimens and preparing DNA for other genetic 
epidemiology studies, as well.  Her lab has established all of the PCR based genotyping studies for the DRD2, 
DRD4, SERT, CYP2A6, DAT receptor alleles and will set up all the assays for genotyping for other relevant 
genes (such as the norepinephrine transporter gene).  Her lab is establishing high-throughput methods for 
these genetic analyses. Her lab, and the Hamon Center For Therapeutic Oncology Research, at UT 
Southwestern Medical Center in Dallas, TX is fully equipped, modern new facility, for the conduct of molecular 
biology and molecular genetic research including having two ABI 377 sequencers/genotypers.  Dr Tomlinson 
has at her disposal, two of our other collaborators, Dr. Eric Nestler, Professor and Chairman, Department of 
Psychiatry, The University of Texas Southwestern Medical Center at Dallas, and Dr. John Minna, Professor 
and Director, Hamon Center For herapeutic Oncology Research, at UT Southwestern Medical Center in Dallas, 
TX. Drs. Tomlinson, Cinciripini , Nestler and Minna are linked via email and the Internet and the Hamon Center 
has a large file server for exchanging information.
 

 
 
 
Terry D. Blumenthal is a Professor of Psychology at Wake Forest University, Winston-Salem, NC, where he 
has been teaching and conducting human psychophysiological research for 15 years. Dr. Blumenthal received 
his B. Sc. from the University of Alberta, Edmonton, Canada, and his M. S. and Ph. D. from the University of 
Florida. He taught psychology courses and conducted research for three years at Hamilton College, Clinton, 
NY, before joining the faculty at Wake Forest University. In addition to his position in the Department of 
Psychology, he is Adjunct Assistant Professor in the Neuroscience Doctoral Program, and a member of the 
Center for Investigative Neuroscience, at Wake Forest University School of Medicine (formerly Bowman Gray 
School of Medicine). Dr. Blumenthal is regarded as an expert in the use of the startle response as a tool in 
research dealing with topics in many areas of psychology, including psychophysiology, psychopharmacology, 
social, developmental, personality, cognitive, and research methodology. He has published dozens of papers 
and presented over 100 peer-reviewed papers and posters in the area of human psychophysiology in the past 
20 years. Dr. Blumenthal has also served as a consultant to the Department of Defense Polygraph Institute, 
the Brain Resource Company (Australia), Imperception Inc. (Los Angeles, CA), the Australian Research 
Council, the Swiss Institute of Technology, and research labs in several countries. 
Dr Blumenthal has served as a consultant to our previous startle projects and has provided invaluable 
technical expertise on physiological recording methodology and startle scoring methodology. He will have a 
similar role on the current project, providing technical expertise and assisting in certain aspects of data 
interpretation (artifact checking/rejection etc). Dr Blumenthal will work with the PI, review the laboratory 
protocol, and cross check our data scoring algorithms throughout the course of the project. 
Dr Nestler is the Lou and Ellen McGinley Distinguished Professor and Chairman, Department of Psychiatry, 
The University of Texas Southwestern Medical Center at Dallas.  Dr. Nestler received his B.A. in 1976, Ph.D. 
in 1982, and M.D. in 1983, all from Yale University. After completing residency training in psychiatry at McLean 
Hospital and Yale in 1987, he joined the Yale faculty where he became the Elizabeth Mears and House 
Jameson Professor of Psychiatry and Neurobiology. From 1992 to 2000, Dr. Nestler served as Director of the 
Abraham Ribicoff Research Facilities and of the Division of Molecular Psychiatry. In 2000, Dr. Nestler moved 
to The University of Texas Southwestern Medical Center at Dallas, where he is the Lou and Ellen McGinley 
Distinguished Professor and Chairman of the Department of Psychiatry. Dr. Nestler is the recipient of 
numerous awards and honors, including the Pfizer Scholars Award (1987), Sloan Research Fellowship (1987), 
McKnight Scholar Award (1989), Efron Award of the American College of Neuropsychopharmacology (1994), 
and Pasarow Foundation Award for Neuropsychiatric Research (1998). He serves on the Board of Scientific 
Counselors of the National Institute on Drug Abuse, and on the Scientific Advisory Boards of the National 
Alliance for Research in Schizophrenia and Depression and of the National Alliance for Autism Research. He is 
currently a member of the National Advisory Mental Health Council. Dr. Nestler was elected to the Institute of 
Medicine in 1998. The goal of Dr. Nestler¶s research is to better understand the ways in which the brain 
responds to repeated perturbations under normal and pathological conditions. A major focus of the research is 
drug addiction: to identify molecular changes that drugs of abuse produce in the brain to cause addiction, and 
to characterize the genetic and environmental factors that determine individual differences in the ability of the 
drugs to produce these changes. This work is based on the view that a greater knowledge of the 
neurobiological basis of drug addiction will lead to more effective treatments and preventive measures.  
 
Dr. Nestler will provide intellectual and technical expertise to the project. He will assist the PI and Dr. 
Tomlinson in interpreting and the genetic analysis and will provide advise for the choice of additional genetic 
markers related to drug dependence that could be incorporated into the study as new scientific discoveries 
become available.  At the onset of the study and periodically thereafter, he will meet with the PI and his staff, to 
review the assessment and genetic analysis protocols and discuss updates or changes that may be 
incorporated into the current design. 
 

 
 
 
John D. Minna, M.D. Is Professor of Internal Medicine and Pharmacology and Director of the Hamon Center for 
Therapeutic Oncology Research and the Moncrief Center for Cancer Genetics at the University of Texas 
Southwestern Medical Center, Dallas, TX. His research has focused on the molecular pathogenesis of lung 
cancer and its translation into the clinic.  As part of this he has been studying the role of nicotine receptors in 
lung cancer pathogenesis, and polymorphic markers leading to inter-individual variations in nicotine addiction.  
He is Principal Investigator on a Lung Cancer SPORE (Special Program of Research Excellence Grant), which 
is a joint endeavor with M. D. Anderson Cancer Center.