ASSOCIATION STUDIES OF PERSONALITY TRAITS, PROBLEM GAMBLING, AND SEROTONERGIC … · 2012. 11....

ASSOCIATION STUDIES OF PERSONALITY TRAITS,

PROBLEM GAMBLING, AND SEROTONERGIC GENE

POLYMORPHISMS

by

Ryan Tong

A thesis submitted in conformity with the requirements

for the degree of Master of Science

Institute of Medical Science

University of Toronto

© Copyright by Ryan Tong (2011)

Ryan Tong

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Thesis Title: Association Studies of Personality Traits, Problem Gambling, and Serotonergic

Gene Polymorphisms

Degree: Master’s of Science

Year of Convocation: 2011

Name: Ryan Pak-Ling Tong

Department: Institute of Medical Science, University of Toronto

ABSTRACT

Problem gambling is the subclinical form of pathological gambling and both are

characterized by difficulties in the limiting of money and time spent on gambling. Genetic and

personality factors have been implicated in gambling disorders (PG). As PG is classified as an

impulse-control disorder, the serotonin (5-HT) system has been suggested to be involved. We

sought to better understand the complex relationship between personality traits, PG, and 5-HT

genes. We investigated ten 5-HT candidate genes for association with PG and personality traits.

We also examined personality traits for association with PG. We found that MAOA and HTR3A

haplotypes were associated with Agreeableness and Conscientiousness personality domains, PG

was associated with high Neuroticism and low Conscientiousness scores, and the MAOA gene

may play a role in PG. Our findings contribute to the better understanding of how 5-HT genes

may be involved in the neurobiological mechanisms underlying PG and personality.

Ryan Tong

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ACKNOWLEDGEMENTS

I would first like to express my gratitude to my supervisor, Dr. James Kennedy, and co-

supervisor, Dr. Daniela Lobo, for their dedication in guiding and supporting me throughout the

process of my Master’s project. Besides their role as my supervisors, they encouraged and

advised me in my pursuit of future career paths and helped opened doors that allowed me to do

so. I would also like to thank the members of my supervisory committee, Dr. Martin Zack and

Dr. John Strauss, who have walked alongside of me as I conducted my research. Their expertise

in their respective fields helped me gain insight and direction for my project. Additionally, to my

exam committee, Dr. Jose Nobrega, Dr. Louis Gliksman, and Dr. Stefano Pallanti, I offer my

sincere thanks for their sacrifice of time and effort. I would also like to thank the Ontario

Problem Gambling Research Institute for funding this project.

I would also like to thank and acknowledge the following who made my experience in

the Neurogenetics laboratory enjoyable: to Clement Zai for all his patience and his friendship; to

Mary Smirniw and Andrea Smart for their administrative assistance; to Natalie Freeman for her

leadership; to Maria Tampakeras, Olga Lihodi, David Sibony, and Sajid Shaikh for their

assistance in the laboratory; to Tamara Arenovich for her statistical analysis expertise; to my

labmates Zeynep Yilmaz, Nabilah Chowdhury, Tristram Lett, Rudi Hwang, Daniel Felsky, and

Eli Remington for all the shared experiences of laughter, frustration, and joy; and to Dr. Antonio

Strafella, Dr. David Mueller, and Dr. Vincenzo DeLuca for opening my eyes to the clinical side

of psychiatric disorders.

I would like to express my gratitude to my fellow collaborators (Dr. David Casey, Dr.

David Hodgins, Dr. Garry Smith, Dr. Robert Williams, Dr. Donald Schopflocher, and Dr. Nady

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el-Guebaly) from Alberta in this research and their assistance in subject recruitment. I must also

thank the participants who participated in my studies and made my research efforts possible.

Finally, I would like to thank my parents for their unconditional love and for always

being by my side through the most difficult storms and joys of life during the preparation of this

thesis. I must thank my dearest friends, Calvin, Jeffrey, Donald, and Ho-Ming for their constant

support and encouragement. Lastly, and most importantly, I want to thank my Saviour and Lord,

Jesus Christ, whose grace is sufficient for me and whose power is made perfect in my weakness.

To all those aforementioned, I dedicate this work.

Ryan Tong

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TABLE OF CONTENTS

CHAPTER SECTION PAGE

ABSTRACT ………………………………………………………………. ii

ACKNOWLEDGEMENTS ………………………………………………. iv

TABLE OF CONTENTS ………………………………………………… vi

List of Abbreviations …………………………………………………….. x

List of Figures …………………………………………………………… xii

List of Tables ……………………………………………………………. xiii

1 INTRODUCTION ………………………………………………………. 1

1.1 Problem and Pathological Gambling ………………………………... 1

1.1.1 Epidemiology ……………………………………………………… 1

1.1.2 Diagnostic Criteria ………………………………………………… 2

1.1.3 PG Instruments ……………………………………………………. 3

1.1.3.1 South Oaks Gambling Screen …………………………………… 4

1.1.3.2 Problem Gambling Severity Index ………………………………. 4

1.2 Genetics and Personality Implications in the

Development and Maintenance of PG ……………………………….. 5

1.2.1 Genetic Factors …………………………………………………….. 5

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1.2.1.1 Family and Twin Studies of PG …………………………………. 5

1.2.1.2 Neurobiological Studies of PG …………………………………… 8

1.2.1.3 Molecular Genetic Studies ……………………………………….. 11

1.2.1.4 Summary …………………………………………………………. 15

1.2.2 Personality Factors …………………………………………………. 16

1.2.2.1 The NEO-Five Factor Inventory …………………………………. 16

1.2.2.2 Personality Studies Investigating PG …………………………….. 23

1.2.2.3 Summary …………………………………………………………. 25

1.3 Rationale …………………………………………………………….. 25

1.3.1 Objectives and Hypotheses ……………………………………….... 25

2 ORIGINAL RESEARCH ARTICLE:…………………………………. 28

Association Study of Serotonin Gene Polymorphisms and NEO

Five-Factor Inventory (NEO-FFI) Personality Traits

2.1 Abstract …………………………………………………………. 29

2.2. Introduction …………………………………………………….. 31

2.3 Methods …………………………………………………………. 35

2.4 Results …………………………………………………………… 38

2.5 Discussion ……………………………………………………….. 44

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3 ORIGINAL RESEARCH ARTICLE:………..………………………….. 54

Association study of NEO-Five Factor Inventory and Problem

Gambling

3.1 Abstract …………………………………………………………. 55

2.2. Introduction …………………………………………………….. 57

2.3 Methods …………………………………………………………. 60

2.4 Results …………………………………………………………… 62

2.5 Discussion ……………………………………………………….. 63

4 ORIGINAL RESEARCH ARTICLE:………..………………………….. 70

Investigation of 10 Serotonin Genes in Problem Gambling:

Possible Role of MAOA

3.1 Abstract …………………………………………………………. 71

2.2. Introduction …………………………………………………….. 73

2.3 Methods …………………………………………………………. 75

2.4 Results …………………………………………………………… 78

2.5 Discussion ……………………………………………………….. 80

5 DISCUSSION ……………………………………………………………... 89

5.1 Summary of Findings and Implications ……………………………….. 89

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5.2 Limitations and Considerations ……………………………………….. 95

5.2.1 Sample Size ………………………………………………………….. 95

5.2.2 Retrospective Measures ……………………………………………… 95

5.2.3 Dichotomization ……………………………………………………... 96

5.2.4 Population Stratification ……………………………………………... 97

5.2.5 Multiple Testing ……………………………………………………… 97

5.3 Future Directions ………………………………………………………. 99

5.3.1 Gene-gene Interaction Studies ………………………………………. 99

5.3.2 Common Assessment Instruments Between Samples ………………. 99

5.3.3 Study Design ………………………………………………………… 100

5.4 Concluding Remarks ………………………………………………….. 101

6 REFERENCES …………………………………………………………... 103

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LIST OF ABBREVIATIONS

5-HIAA 5-hydroxyindoleacetic acid

5-HT Serotonin

5-HTT Serotonin transporter

5-HTTLPR Serotonin transporter promoter polymorphism

ANKK1 Ankryin repeat and kinase domain containin 1 gene

CPGI Canadian Problem Gambling Index

CSF Cerebrospinal fluid

DA Dopamine

DSM-III-R Diagnostic and Statistics Manual of Mental Disorders Revised - III

DSM-IV Diagnostic and Statistics Manual of Mental Disorders - IV

DZ Dizygotic

FDR First Degree Relatives

FFM Five factor model

KO Knockout

MAF Minimum allele frequency

MAOA Monoamine oxidase A

MZ Monozygotic

NEO-FFI NEO Five Factor Inventory

NEO-PI-R NEO Personality Inventory Revised

OR Odds ratio

PET Positron Emission Tomography

PG Problem and pathological gambling/ Problem and pathological gamblers

PGSI Problem Gambling Severity Index

SLC6A4 Serotonin transporter gene

SNP Single nucleotide polymorphisms

SOGS South Oaks Gambling Screen

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TCI Temperament and Character Inventory

TPH Tryptophan hydroxylase

TPQ Tridimensional Personality Questionnaire

UTR Untranslated region

VNTR Variable tandem number repeat

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List of Figures

1. Mean NEO-FFI domain score comparisons between PG and NPG groups 72

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List of Tables

1. Serotonin Candidate Gene Markers 52-53

2. Mean values of NEO-FFI Agreeableness and frequencies of MAOA

haplotypes significant after Nyholt correction 54

3. Mean values of NEO-FFI Conscientiousness and frequencies of MAOA

and HTR3A haplotypes significant after Nyholt correction 55

4. Demographic factor comparisons between the PG and NPG groups 70

5. Comparison of NEO-FFI personality domain scores between PG and NPG

with age and sex included as a covariates in the analysis 71

6. Serotonin Candidate Gene Markers 87-88

7. Nominal allelic associations of evaluated 5-HT variants with gambling behaviour 89

8. Nominal genotypic association of evaluated 5-HT variants with gambling behaviour 90

9. Nominal haplotypic associations of evaluated 5-HT variants

with gambling behaviour 91

Ryan Tong I. Introduction

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CHAPTER 1

1. INTRODUCTION

1.1 Problem and Pathological Gambling

Gambling is the act of wagering stakes, such as money, on an event with an uncertain

outcome with the objective of gaining back more than was initially bet. Gambling disorders

(problem and pathological gambling) are classified as impulse-control disorders by the

Diagnostic and Statistics Manual-IV (DSM-IV) and impulsivity is defined as “a predisposition

toward rapid, unplanned reactions to internal or external stimuli [with less] regard to the negative

consequences of these reaction to the impulsive individual or to others” ( Moeller et al., 2001).

Problem gambling is the subclinical and earlier stage of pathological gambling differing only

quantitatively, and not qualitatively, in diagnostic criteria and both are characterized by

behavioural difficulties in the limiting of money and/or time spent on gambling leading to

significant, negative consequences for the gambler, their relatives, community, and society

(Shaffer et al., 1999; Slutske et al., 2000; Lobo et al., 2006; Raylu and Oei, 2002; Blaszczynski

and Nower, 2001; Gambling Research Australia, 2005). In this thesis, “PG” will be used to

describe the overall gambling disorder which includes both problem and pathological gamblers.

1.1.1 Epidemiology

Despite the estimation that 86% of the general population has gambled at least once in

their lives (Center 1999), only a small percentage of individuals will develop a gambling

disorder. Epidemiological studies have estimated the lifetime prevalence rate of problem


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gambling and pathological gambling in the general population at 2-5% and 0.15-2.1%

respectfully (Abbott and Volberg, 1996; Kessler et al., 2008; Raylu and Oei, 2002; Ladouceur,

1991; Stucki and Rihs-Middel, 2007). In a nationally representative US household survey,

pathological gambling was significantly associated with younger age and the male sex (Kessler

et al., 2008). Though the majority of those who gamble are not likely to develop a gambling

disorder, it is expected that the prevalence rate of PG will rapidly grow due to the increasing

availability of legal gambling opportunities (Petry 2005). This is supported by the finding of

Ladouceur et al. (1999) who conducted a longitudinal study and found that local rates of

pathological gambling increased by 14% in a Quebec community seven years after the opening

of three casinos locally.

Due to the growing prevalence rates of PG, the economic impact of the disorder is large.

In Canada, the cost of therapy is growing quickly where costs were estimated at $28 million

annually in 1999 which was more than double the amount spent in 1997 (Azmier et al., 2001).

Other associated costs of PG include employment factors (lost productivity, unemployment

compensation), debts, court costs, and welfare support (Walker and Barnett, 1999) making the

disorder costly to society. Besides the impact of PG on society, the disorder also has a severe

negative effect on individuals with gambling problems and their families. PG is associated with

increased divorce rates, criminal offences, domestic violence, and suicide (Blaszycynski and

Farrell, 1998; Lesieur et al., 1984). Therefore, because of the growing negative impact of PG,

more research is needed to understand the risk factors and biological mechanisms underlying the

disorder in order to devise effective prevention strategies and pharmacotherapy.

1.1.2 Diagnostic Criteria


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According to the DSM-IV, pathological gambling is classified as an impulse-control

disorder with an essential feature being “persistent and recurrent maladaptive gambling

behaviour” (DSM-IV; American Psychiatric Association, 2000). Pathological gambling is

considered a behavioural addiction as it has been found to share common vulnerability factors

with substance use disorders (Potenza 2001). Thus, the criteria used for substance use disorders

were used as the basis to develop the items for pathological gambling (Black and Moyer, 1998).

Some adapted elements include preoccupation (“considerable time spent reliving past gambling

experiences, planning the next gambling venture, or thinking of ways to get money with which to

gamble”), tolerance (“needs to gamble with increasing amounts of money in order to achieve the

desired excitement”), withdrawal (“is restless or irritable when attempting to cut down or stop

gambling”), and loss of control (“has repeated unsuccessful efforts to control, cut back, or stop

gambling) while some symptoms are unique to the disorder such as chasing losses (“after losing

money gambling, often returns another day to get even”)(APA, 2000). These are some of the ten

diagnosis criteria for pathological gambling according to the DSM-IV. For a diagnosis of

pathological gambling, five of these symptoms are needed to be present for at least 12-months;

for subclinical pathological gambling, or problem gambling, the presentation of one to four of

these symptoms are required and individuals not meeting any symptom criteria are considered to

not have problems with gambling (APA 2000). Based on the DSM-IV criteria for pathological

gambling, research was undertaken to develop other instruments for the assessment of gambling

behaviour. The South Oaks Gambling Screen (SOGS) and Canadian Problem Gambling Index

(CPGI) are two instruments that are most commonly used in research studies of gambling.

1.1.3 PG Instruments


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The following reviews the two PG measures used in the studies of this thesis to measure

gambling behaviour.

1.1.3.1 South Oaks Gambling Screen (SOGS) (Lesieur and Blume, 1987)

The SOGS is a 20-item screen tool for pathological gambling that was developed for use

in a clinical context, although it has been frequently used in research studies. The items of the

SOGS were based on DSM-III-R diagnostic criteria for pathological gambling. Half of these

items pertain to borrowing money, a third to consequences of gambling, and the rest to gambling

behaviours and attitudes (Gambling Research Australia 2005). Individuals who endorse five or

more criteria in this instrument are classified as probable pathological gamblers.

The SOGS was found to have satisfactory reliability and stability in both a general

population and gambling treatment sample (Stinchfield 2002). The reliability of the SOGS was

estimated at 0.69 and 0.86 for the general population and gambling treatment samples,

respectively. To test the SOGS’ validity, the SOGS and DSM-IV criteria for pathological

gambling was compared and it was found that the two instruments were highly correlated (r =

0.77 in general population and r = 0.83 in gambling treatment sample). At the time of its

development, the SOGS was considered as the “gold standard” for identifying pathological

gambling in the general population (Volberg and Banks, 1990).

1.1.3.2 Problem Gambling Severity Index (PGSI) (Ferris and Wynne, 2001)

The PGSI is a 9-item, self-report instrument within the CPGI that was specifically

developed to measure problem gambling severity in the general population. It also assesses

gambling frequency and faulty cognitions. In the development of the PGSI items, three of the

gambling consequences items were taken from the SOGS, two of the gambling behaviour items

were adopted from the DSM-IV criteria, and the rest of the items were relatively unique to the


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PGSI. For the PGSI, a four-alternative scale is used for each item ranging from “never” to

“almost always”. Scores for the nine PGSI items classify individuals as follows: 0 = non-

problem gambler, 1-2 = low-risk gambler, 3-7 = moderate risk gambler, and >8 = problem

gambler. The scores range from 0-27. Internal consistency of the instrument was good with a

coefficient alpha of 0.85 in the sample emplyed by Holtgraves (2009). Also, the reliability of the

PGSI was high with a test retest reliability of 0.78 (Ferris and Wynne, 2001). The PGSI is an

appropriate instrument for the assessment of PG in a non-clinical context.

1.2 Genetics and Personality Implications in the Development and Maintenance of PG

To develop effective prevention and therapeutic strategies for a disorder, a clear

understanding of its etiological factors is first needed. However, the etiology of complex,

multifactorial, behavioural disorders, such as PG, is very difficult to determine and there has

been a scarcity of gambling-related research in this area. Currently, the literature on gambling

has focused on identifying factors associated with PG that may play a role in the development

and maintenance of the disorder. Factors that have been implicated in PG include individual

(personality, cognition, biology), familial (social learning and genetic factors), and sociological

factors (Raylu and Oei, 2002). In this thesis, we focused on the genetic and personality

influences on gambling behaviour and the following review explores these factors in PG.

1.2.1 Genetic Factors

1.2.1.1 Family and Twin Studies of PG

Family and twin studies have provided evidence that there is a genetic component

underlying pathological gambling. Family studies use the familial relative risk ratio (ratio of the


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risk of the disorder for a relative of an affected individual to the risk for the general population)

to estimate the combined effect of genetic and environmental factors in disorders. These

investigations have been used to identify susceptibility genes in complex diseases (Hopper et al.,

2005).

In a family study conducted by Gambino et al. (1993), it was shown that a significant risk

factor of pathological gambling was having ancestors with gambling problems. Assessing

gambling behaviour using the South Oaks Gambling Screen, they found that individuals who

reported that their parents were problem gamblers had a three-fold increase in risk of being

probable pathological gamblers. They also showed that individuals who reported that their

grandparents had gambling problems were twelve times more likely to be problem gamblers

compared to individuals who did not perceive their grandparents as having gambling problems.

However, the classification of parents and grandparents as problem gamblers may not be

accurate as it was based on subjects’ reports and not through gambling behaviour assessments.

In order to account for this weakness, a family prevalence study of pathological gambling

was conducted by Black et al. (2006) in which the gambling behaviour of first degree relatives

(FDRs) of cases and controls were also measured. They used the DSM-IV criteria and the SOGS

to classify 31 case probands and 31 controls and the NORC Screen for Gambling Problems and

Minnesota Impulsive Disorders Interview to assess the gambling behaviour of 193 case and 142

control FDRs. They showed that lifetime rates of problem gambling and pathological gambling

were significantly higher among FDRs of case probands (12.4% and 8.3% respectively)

compared to FDRs of the control group (3.5% and 2.1% respectively). Thus, they suggested that

gambling disorders had a familial component. However, the finding that PG aggregates within


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families is not sufficient evidence for the disorder to have genetic etiological factors as the

results may be explained by familial environmental factors.

Therefore, twin studies have been conducted in order to determine whether genetic

factors are involved in pathological gambling. Twin studies are used to explore heritability by

comparing the concordance of the disorder between monozygotic (MZ) and dizygotic (DZ) twins

who are assumed to share ~100% and ~50% DNA sequence identity respectively. If the

concordance rate in MZ twins is significantly greater than that for DZ twins, this indicates that

genetic factors play a role in the disorder. The gambling behaviour of 3359 male twin pairs was

examined using the DSM-III-R by Eisen et al. (1998) and the results provided support for the

notion that problem and pathological gambling were heritable. They found the pair-wise

concordance rates of problem and pathological gambling for MZ twins to be 26.3% and 14.3%

respectively while for DZ twins, it was lower at 14.3% and 8.7% respectively. They estimated

that familial factors explained 35%-54% of the liability to develop any of the five symptoms of

pathological gambling and the heritability of pathological gambling disorder at 62%. Recently, a

similar analysis was conducted in a twin-pair sample that included females and they found that

there were no significant differences in genetic influence on gambling behaviour between the

sexes implying that the genetic influences on gambling behaviour are present in females as well

(Slutske et al., 2010).

Twin studies have also been used to test the continuity model of pathological gambling

which hypothesizes that subclinical problem and pathological gambling represent a continuum of

the same phenotype and share the same risk factors. In their analysis of 3372 twin pairs, Slutske

et al. (2000) found that the risk of pathological gambling was significantly higher among MZ

(6.1%) and DZ cotwins (3.1%) of subjects with problem or pathological gambling compared to


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cotwins of individuals with no PG symptoms. These results suggested that problem and

pathological gambling are not two etiologically distinct disorders but instead differ

quantitatively, and not qualitatively, in terms of risk factors.

Therefore, the evidence above (family and twin studies) provides evidence that PG is

heritable. However, PG is considered a “complex” disorder in which a variety of genes

contribute a portion to the disorder while also interacting with environmental factors.

Neurobiological research of PG has been conducted in order to gain a better understanding of the

biological mechanisms underlying the disorder and to guide gene selection for molecular genetic

association studies.

1.2.1.2 Neurobiological Studies of PG

Research into the neurobiology of PG has revealed that dysfunction of the serotonin (5-

HT) and dopamine (DA) systems may be involved in the disorder (Bergh et al., 1997; Moreno et

al., 1991; Nordin and Sjodin, 2005). It has been theorized that abnormal regulation of 5-HT and

DA may contribute to a deficit in inhibitory control and over-activation of motivated drives and

constitute part of the biological mechanisms underlying impulse-control disorders (Ibanez et al.,

2003).

A reduction of 5-HT in the brain has been associated with the enactment of inappropriate

motivated drives and multiple lines of evidence support the theory that the neurotransmitter plays

a role in the selection and inhibition of impulses (Chambers and Potenza, 2004). Serotonergic

neurons project from the raphe nucleus to various brain regions that compose the neurocircuitry

of motivated drives (Brewer and Potenza, 2008). These brain regions include the amygdala,

which facilitates associative learning by assigning salience to external stimuli (Everitt et al.,

2003), hippocampus, which is important for contextual memory retrieval (Maren and Holt,


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2000), and prefrontal cortex, which is an amalgamation centre of different brain signals in order

to establish response selection in accordance to one’s goals (Rowe et al., 2000; Funahashi 2000).

In order to examine the involvement of the 5-HT system in pathological gambling,

Nordin and Sjodin (2005) measured 5-HT levels, and its metabolite, 5-hydroxyindoleacetic acid

(5-HIAA), in the cerebrospinal fluid samples of pathological gamblers and a control group. They

found that pathological gamblers had higher 5-HIAA and lower 5-HT levels compared to the

control group indicating a dysregulated 5-HT system. A pharmacological study by Pallanti et al.

(2009) corroborated these results. They administered a 5-HT agonist to both pathological

gamblers and healthy controls and measured the growth hormone response, an indicator of 5-HT

system functionality. It was shown that pathological gamblers had a significantly lower response

compared to controls. Further evidence implicating the 5-HT system’s involvement in PG is the

fact that drugs modifying 5-HT action have been used to treat the disorder (Grant et al., 2003).

Selective 5-HT reuptake inhibitors have been used as an effective treatment for pathological

gambling by reducing gambling urges and symptom severity (Grant et al., 2003).

DA plays a critical role in the brain’s reward system and is involved in the processing of

natural reinforcers and modulation of rewarding behaviours (Wise 2002; Grant et al., 2006). It

has been theorized that the dopaminergic mesolimbic pathway, which links the ventral tegmental

area to the nucleus accumbens, is central to addictive behaviour (Nestler 2005). The mesolimbic

pathway is important for reward-driven learning as it encodes the salience of stimuli through the

phasic release of dopamine (Mirenowicz et al., 1994). DA has been hypothesized to play an

important role in PG as Riba et al. (2008) found that pharmacological-induced changes in the DA

system altered risk-taking and reward-related brain activity. Also, DA is thought to underlie the

behavioral and cognitive withdrawal effects associated with pathological gambling (Bergh and


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Kuhlhorn, 1994) as dysregulation of the system may lead to an altered sensitivity towards loss or

reward (Raylu and Oei, 2002).

Thus, neurobiological studies of PG have also focused on the DA system. Bergh et al.

(1997) measured DA and DA metabolites in the CSF of ten pathological gamblers and seven

controls. They found that compared to controls, pathological gamblers had lower DA and

increased DA metabolite levels. Further evidence indicating that the DA system plays a role in

PG were the findings from a clinical trial that found the dopamine antagonist naltrexone

significantly reduced pathological gambling symptoms and was suggested as a potential

treatment option for pathological gambling (Kim et al., 2001). Also, the finding that dopamine

agonist therapy for Parkinson’s disease has been associated with pathological gambling

strengthens the theory that DA is involved in PG (Driver-Dunckley et al., 2003). The estimated

prevalence rate of pathological gambling was significantly higher in Parkinson patients being

treated with a DA agonist compared to the general population (8% and 1-2% respectively)

(Gallagher et al., 2007).

As family and twin studies have implicated a genetic component and these neurobiology

studies have suggested the involvement of the 5-HT and DA system in PG, candidate gene

studies have focused on examining 5-HT and DA genes for association with PG. Genetic

association studies examine whether there is a significant difference in the frequency of selected

genetic variants’ alleles, genotypes, or haplotypes between individuals with the condition and

those who do not. If a particular gene polymorphism does predispose an individual to the

condition, the frequency of a particular allele, genotype, or haplotype should be significantly

higher in the case group compared to controls. The following is a review of 5-HT and DA

genetic association studies with PG.


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1.2.1.3 Molecular Genetic Studies

Serotonin genetic studies

In an attempt to elucidate the genetic basis of PG, 5-HT candidate genes were analyzed

for association with the disorder. However, the number of these investigations has been limited.

One group examined the alleles and genotypes of functional variants of the serotonin transporter

(5-HTT or SLC6A4) and monoamine oxidase A (MAOA) genes to determine whether there were

significant frequency differences between 68 pathological gamblers and 68 healthy volunteers

similar in age, sex, and ethnicity (Pérez de Castro et al., 1999; Pérez de Castro et al., 2002;

Ibanez et al., 2000). In these studies, the SOGS was used to assess the severity of gambling

behaviour. The 5-HTT and MAOA genes were selected for analysis due to the effect their gene

products have on 5-HT synaptic concentration. The 5-HTT encodes a reuptake transporter

removing 5-HT from the synapse back into the presynaptic terminal (Mossner et al., 2000). The

gene product of MAOA is an enzyme that degrades monoamines, including 5-HT, regulating

neurotransmitter availability and release (Youdim et al., 1972).

In their sample, Pérez de Castro et al. (1999) found an association between the less

functional, short allele of the 5-HTT promoter polymorphism (5-HTTLPR) and pathological

gambling in males at a relative risk of 3.4, but not females. This association was only found after

dividing the sample by sex. The short variant of this polymorphism results in decreased promoter

activity causing lower production of the serotonin transporter (Lesch et al., 1996). The same

sample was used to investigate the contribution of the MAOA variable number tandem repeat

(VNTR) and a MAOA(intron1) polymorphism to pathological gambling. It was shown that the

lower activity 3 repeat of the MAOA VNTR and the 4 repeat allele of the MAOA(intron1)

polymorphism were significantly associated with the diagnosis of pathological gambling in


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males though this result was not found in females (Pérez de Castro et al., 2002; Ibanez et al.,

2000). The MAOA VNTR is a functional polymorphism which affects the transcription rate of the

enzyme. Sabol et al. (1998) found that the 3 and 5 repeats of the polymorphism resulted in an

enzyme transcription rate that is two to ten times less efficient than the 3.5 and 4 repeat variants.

These early 5-HT genetic association findings suggest that 5-HT genes are involved in PG and

call for further studies investigating the contribution of other 5-HT gene variants to PG.

Dopamine genetic studies

Research efforts have also been taken to study the association between gambling

behaviour and DA candidate genes. DA genes that have been previously found to be positively

associated with pathological gambling are the DRD1, DRD2, and DRD4 (Comings et al., 1997;

Lobo et al., 2007; Comings et al., 1996; Comings et al., 1999; Perez de Castro et al., 1997) which

encode the D1, D2, and D4 receptors respectively. These genes were investigated for association

with pathological gambling based on the involvement of the receptors in other addictive

disorders.

Tran et al. (2005) investigated the function of the D1 receptor using knockout (KO) mice

and their findings suggested that the receptor plays a role in reward processes and spatial

associative learning. In their study, they demonstrated that compared to wildtype mice, D1

receptor KO mice had a higher intracranial self-stimulation threshold and a lack of prereward

excitatory response in the nucleus accumbens. These findings indicate impairment in the

mediation of rewards, specifically in reward prediction processes. Also, the D1 receptor KO

mice had spatial learning deficits as they were retarded in the acquisition of the place learning

task compared to wildtype mice. From this evidence, the authors suggested that the D1 receptor


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may contribute to the ability to perform spatial tasks based on environmental cues associated

with reward.

Tran et al. (2002) used the same approach of using KO mice to investigate the functional

role of the D2 receptor. They found that D2 receptors also play a critical role in the prediction of

reward as shown by the lack of prereward inhibitory neural activity in the nucleus accumbens of

D2 receptor KO mice.

The D1 and D2 receptors have also been shown to interact and play a functional role in

the relapse process of addictive disorders (Self et al., 1996). In a pharmacological study by Self

et al. (1996), D1- and D2-like receptor agonists were administered in rats to investigate the role

the receptors played in mediating relapse to cocaine-seeking behaviour. They found that the two

receptors had opposite effects on relapse as the D1 agonists they applied significantly prevented

the priming effect of cocaine while D2 agonists enhanced relapse into cocaine-seeking

behaviour. The fact that the two receptors have opposing effects upon activation of signaling

pathways may be relevant to their potential role in reward pathways and ultimately, gambling

behaviour. D1 receptors stimulate while D2 receptors inhibit the production of cyclic AMP in

neurons. Overall, the findings with the D1 and D2 receptors in animal models suggest that the

receptors play a critical role in addiction processes. However, the details remain to be elucidated.

Knockout animal models have been designed to investigate the function of the D4

receptor which has been found to be involved in addictions. Mutant mice deficient in the D4

receptor displayed hypersensitivity to drugs of abuse including cocaine, ethanol, and

methamphetamine compared to wildtype mice (Rubinstein et al., 1997). Also, in a battery of

behavioural tests assessing novelty-related exploration, D4 receptor KO mice showed a reduction

in behavioural responses to novelty (Dulawa et al., 1999). Novelty seeking is a personality trait


14

that has been consistently shown to be significantly associated with susceptibility to addiction

(Alemany 2008).

Based on these DA receptors’ function and DA’s role in addictive disorders,

polymorphisms of the DA genes encoding those DA receptors have been examined for

association with PG. However, the number of these studies has been limited. Comings et al.

(1997) examined whether the DRD1gene played a role in addictive behaviours by investigating

the Dde1polymorphism genotype frequencies in Tourette syndrome probands, smokers, and

pathological gamblers compared to a control group. The Dde1 polymorphism consists of an A to

G substitution in the 5’UTR (Cichon et al., 1994) and has been suggested to be in increased

linkage equilibrium with mutations affecting the production rate of the D1 receptor (Comings et

al., 1997). Comings et al. (1997) found that there was a significant increase in homozygosity for

either allele of the Dde1 in pathological gamblers, Tourette syndrome probands, and smokers

compared to the control group. The genotypic associations indicated that the DRD1 Dde1 may be

involved in compulsive-impulsive-addictive behaviours, including pathological gambling.

The same group of researchers also investigated the involvement of the DRD2 gene in

pathological gambling by examining the functional TaqIA variant. Specifically, the

polymorphism has been shown to be functional as the minor A1 allele was significantly

associated with lower receptor density and reduced D2 binding in the striatum as measured by

PET imaging (Jonsson et al., 1999; Noble, et al., 1991; Pohjalainen et al., 1998). However,

recently, a study has shown that the TaqIA polymorphism lies outside the DRD2 gene and is

located in the ankryin repeat and kinase domain containin 1 gene (ANKK1) (Neville et al., 2004)

making it difficult to explain its association with DRD2 function. Nevertheless, Comings et al.

(1996), using a sample of 222 pathological gamblers and 714 controls, examined the TaqIA


15

variant and found that the A1 allele was significantly associated with pathological gambling and

pathological gambling severity. 50.9% of pathological gamblers carried the A1 allele while

25.9% of the controls carried the allele resulting in an odds ratio of 2.96. Also, within the

gambling group, a significantly higher percentage of those with more severe gambling symptoms

were A1 carriers compared to gamblers with less severe gambling symptoms.

Another DA candidate gene that has been previously examined is the DRD4 gene and

two studies investigating the functional DRD4 exon III variable-number-of-tandem-repeats

(VNTR) polymorphism have found evidence for association with pathological gambling (Perez

de Castro et al., 1997; Comings et al., 1999). Perez de Castro et al. (1997) found a significant

association between the 7 repeat allele and pathological gambling, but only in females. Comings

et al. (1999) did not split their sample by sex and did not find any significant difference in the

number of 7 repeat allele carriers between pathological gamblers and the control group.

However, they reported that the overall long forms of the polymorphism (5-8 repeat alleles) were

significantly associated with pathological gambling. An investigation studying the functional

characteristics of the polymorphic forms of the DRD4 exon III VNTR showed that the 7 repeat

allele encoded receptors that had about half the efficacy compared to that of the D4 receptors

encoded by the 2 and 4 repeat alleles upon DA stimulation (Asghari et al., 1995).

Thus, overall, these molecular genetic findings of association between DA candidate

genes and PG indicate that DA may play a role in the impulsive disorder.

1.2.1.4 Summary

It is evident from the genetic association studies reviewed above that research in this area

has been limited despite the neurobiological findings implicating the involvement of the 5-HT

and DA systems in PG. Previous studies have found significant associations between


16

pathological gambling and polymorphisms of the following genes: DRD1, DRD2, DRD4, 5-HTT,

and MAOA. These genetic polymorphisms had previously been found to be associated with other

impulse-control and addictive disorders. Therefore, this indicates that these genes may not be

specific for PG, but may confer susceptibility to a diversity of impulse-control and addictive

disorders.

1.2.2 Personality Factors

Personality is defined as “the characteristic manner in which one thinks, feels, behaves,

and relates to others” (Widiger 2011). The study of personality traits and their association with

disease states is based upon the theory that personality may be associated with neurobiological

changes which make individuals more susceptible to the development of psychiatric disorders

(Eysenck 1997; Ball 2005). Different personality models have been used to study gambling, but

the five-factor model (FFM), considered as one of the most comprehensive models of

personality, has the most amount of empirical support (Widiger and Trull, 2006). Personality

questionnaires that have been utilized in the examination of personality in pathological gambling

are the Tridimensional Personality Questionnaire (Cloninger et al., 1991), the Multidimensional

Personality Questionnaire (Slutske et al., 2005), and the NEO-Personality Inventory-

Revised/NEO-Five Factor Inventory (NEO-PI-R/NEO-FFI) (Bagby et al., 2007). Based on the

FFM, the NEO-FFI was developed by McCrae and Costa (2004). Due to the empirical evidence

for the FFM, the NEO-FFI was used to assess personality in the studies of this thesis.

1.2.2.1 The NEO-Five Factor Inventory (NEO-FFI) (McCrae and Costa, 2004)

The NEO-FFI is a self-report personality questionnaire which assesses the personality

domains of the FFM (Neuroticism, Extraversion, Openness to Experience, Agreeableness, and


17

Conscientiousness). It was developed as a brief version of the 240-item NEO-Personality

Inventory Revised (NEO-PI-R), a well-established instrument validated in different cultures and

populations (McCrae and Costa, 2004). The NEO-PI-R is an appropriate questionnaire for

assessing the personality traits of the impulse-control disorder PG as it contains facets that can

predict 66% of the variance in common measures of impulsivity (Whiteside and Lynam, 2001).

In order to develop the NEO-FFI, a factor analysis was performed on the NEO-PI-R. Twelve

items with the highest positive loading from each domain were included in the NEO-FFI. The

NEO-FFI uses a five-point Likert scale ranging from “strongly disagree” to “strongly agree”.

The internal consistency of the instrument has been found to range from 0.68 to 0.85 (N= 0.85,

E= 0.80, O= 0.68, A= 0.75, C= 0.83) (Sherry et al., 2007) and the two-week retest reliability of

the five domains was high ranging from 0.86 to 0.90 (Robins et al., 2001). A description of the

five personality domains that the NEO-FFI assesses can be found below.

Neuroticism

Neuroticism represents individual differences in emotional stability and the likelihood to

experience negative affect, most namely depression and anxiety (McCrae and Costa, 1987). High

scorers in the Neuroticism domain have been described as having low self-esteem, poor impulse-

control, ineffective coping strategies, and irrational thinking (McCrae and Costa, 1987). The

following are NEO-PI-R facets that have been included in the Neuroticism domain: Anxiety,

Hostility, Depression, Self-consciousness, Impulsiveness, and Vulnerability to stress.

It has been suggested that Neuroticism scores serve as an index for vulnerability to

developing psychopathology (Ormel et al., 2004). In support of this, many studies have found

Neuroticism scores to be significantly associated with a variety of different psychiatric disorders

ranging from major depression to behavioural addictions (Hettema et al., 2006; Bagby et al.,


18

2007). Furthermore, Bienvenu et al. (2001) showed that Neuroticism was associated with

comorbidity between psychiatric disorders such as simple phobia, social phobia, agoraphobia,

panic disorder, and major depression. Neurobiological mechanisms have been explored to

explain the relationship between Neuroticism and psychopathology. Using PET imaging, Takano

et al. (2007) found that Neuroticism scores were positively correlated with 5-HTT binding in the

thalamus indicating that the 5-HT system may be involved in high Neuroticism.

Extraversion

Extraversion is defined as the disposition to engage with the social world and measures

positive emotionality (McCrae and Costa, 1987). Individuals with high scores in the Extraversion

domain enjoy the company of others and are characterized as being fun-loving, friendly,

affectionate, and talkative. The facets of Extravesion are Warmth, Gregariousness,

Assertiveness, Activity, Excitement-seeking, and Positive emotion.

Though the neurological basis for extraversion is still under debate, the dopaminergic

hypothesis proposed by Depue and Collins (1999) has gained some empirical support. They

posited that extraverted behaviour was based on incentive motivation processes which regulate

the salience of positive stimuli. This theory was supported by the finding that Extraversion, as

assessed by the NEO-FFI, was significantly correlated with increased activity in the orbitofrontal

cortex, a brain region previously shown to be involved in shifting attention to positive stimuli

(Deckersbach et al., 2006). Incentive motivation processes are mediated by the mesolimbic

reward system in which dopamine plays a central role (Depue 1995). Depue et al. (1994) found

that central DA functioning was significantly associated with Extraversion and thus theorized

that it may underlie individual differences in Extraversion scores.


19

The Extraversion domain may have significant implications for vulnerability to

psychopathology. As assessed by the NEO personality questionnaire, Extraversion scores were

associated with structural and signaling response differences to positive stimuli in various brain

regions including the prefrontal cortex, right fusiform gyrus, and amygdala (Canli 2004; Wright

et al., 2006; Omura et al., 2005). Wright et al. (2006) found that the prefrontal cortex and right

fusiform gyrus thickness were negatively associated with Extraversion. These brain regions have

been shown to be involved in decision-making under risk (Clark et al., 2008) and the thinning of

the cortex in these areas has been suggested to relate to decreased inhibition, impulsive

behaviour, and sensation seeking (Wright et al., 2006). Structural differences in the amygdala

have also been found to be correlated with Extraversion scores where gray matter concentration

in the left amygdala was positively associated with Extraversion (Omura et al., 2005). Though

high Extraversion scores have been implicated in impulsivity, Omura et al. (2005) have

suggested that Extraversion may be protective against depression as previous studies have shown

that lower concentrations of amygdalar gray matter and amygdala volume were associated with

depression (Wright et al., 2006; Rosso et al., 2005).

Openness to Experience

Openness to experience is the personality domain of the NEO-PI-R which measures an

individual’s active seeking and appreciation for experiences (McCrae and Costa, 1985).

Individuals that score high in this domain typically have original ideas, a daring disposition,

unconventional attitudes, an avid imagination, little difficulty expressing their insight and

feelings, and an intellectual curiosity (McCrae and Costa, 1987; Costa and McCrae, 1992). The

facets that define Openness to Experience include the following: Fantasy, Aesthetics, Feelings,

Actions, Ideas, and Values. In previous personality literature, intellect and Openness to


20

Experience were frequently considered as the same dimension, yet McCrae and Costa (1987)

found that these two factors, though highly correlated, are distinct.

The research that has been conducted investigating the neurological basis of Openness to

Experience has been limited. However, it has been hypothesized that the 5-HT system may be

involved in Openness to Experience as 5-HT has been associated with aspects related to the

personality domain such as cognitive flexibility and processing of affective stimuli (Evers et al.,

2007; Canli et al., 2008). Also, there is preliminary evidence that supports the 5-HT theory of

Openness to Experience. Kalbitzer et al. (2009) found that in 50 healthy volunteers, high scores

in Openness to Experience were significantly associated with lower binding of the 5-HTT, which

functions to regulate 5-HT synaptic concentrations (Mossner et al., 2000), in the midbrain,

putamen, thalamus, and caudate nuclei. The lower 5-HTT cerebral levels imply higher

extracellular 5-HT levels, which increase neural responsiveness, and this increase in 5-HT may

be involved in Openness to Experience.

Costa and Widiger (1994) found evidence that suggested that the Openness to Experience

domain was relevant to several addictive and psychiatric disorders. For example, it was shown

that individuals with symptoms of marijuana abuse scored significantly higher in the Openness

to Experience domain than those with no symptoms (Flory et al., 2002). Also, it has been

suggested that Openness may play a role in schizophrenia, narcissism, and obsessive compulsive

disorder based on some of their clinical features such as restricted affect, self-aggrandizing

fantasy, and behavioural rigidity respectively. However, most research has focused on the

possible role that the personality domain plays in mood disorders. Oswald et al. (2006) found

that Openness to Experience was associated with increased cortisol response to induced stress.

This increased sensitivity to stress suggests that individuals who scored higher in this domain


21

would be more vulnerable to developing depression. In support of this finding, multiple studies

have showed that high scores for Openness to Experience were associated with depression

(Bagby et al., 1996; Wolfestein and Trull, 1997).

Agreeableness

Agreeableness is a NEO-PI-R personality domain that has been described as a

combination of low agency and high communion (McCrae and Costa., 1989). Agency is defined

as an individual’s desire to assert themselves and to control their environment and experiences

while communion is an individual’s disposition to prefer cooperation and relating to others

(Bakan 1966). Those who score highly in the Agreeableness personality domain tend to be

empathetic, helpful to others, and compliant (Jensen-Campbell and Graziano, 2001). The facets

that compose the personality domain are Trust, Straightforwardness, Altruism, Compliance,

Modesty, and Tendermindedness.

Few studies have focused on the neurobiological mechanisms of the Agreeableness

domain though it has been proposed that the 5-HT system may underlie individual differences of

Agreeableness or related personality constructs such as affiliative behaviour. Firstly, animal

studies have shown that 5-HT can influence agnostic-affiliative behaviours. Higley et al. (1996)

measured 5-hydroxyindoleacetic acid (5-HIAA) levels in the CSF samples of sixteen female

macaque monkeys to determine whether it was correlated with nonhuman primate social

behaviour. They found that monkeys who had above average 5-HIAA levels, an indicator of 5-

HT function, were more likely to be accepted in the social group and exhibit less aggression.

Thus, the authors suggested that 5-HT may play a role in competent social behaviour in

nonhuman primates. In human pharmacological studies, it was shown that increasing 5-HT levels

by administering tryptophan significantly increased agreeable behaviour and perceptions of


22

agreeableness in others during social interactions (aan het Rot et al., 2006). However, Moskowitz

et al. (2001) did not replicate this result and found that tryptophan instead increased dominance

behaviour. Thus, though studies investigating the neurobiology of Agreeableness have been

limited, the research that has been completed suggests that 5-HT may be associated with

agreeable behaviour.

The Agreeableness domain has been associated with several personality disorders. High

scores in this personality domain are rarely associated with psychopathology. However, it has

been shown to be correlated with dependent personality disorder which is characterized by a

pervasive psychological dependence on others (Widiger and Simonsen, 2005). Conversely, low

scores in Agreeableness have been associated with many personality disorders. In a meta-

analysis by Saulsman and Page (2004), they found that the combination of low Agreeableness

and high Neuroticism scores was the most consistent personality profile underlying the

personality disorders classified in the DSM-IV. One personality disorder that has the most

empirical support for association with low Agreeableness scores is narcissistic personality

disorder (Saulsman and Page, 2004). Specifically, Widiger et al. (1994) suggested that the low

scores in the Agreeableness facets Modesty, Altruism, and Tendermindedness underlie the strong

correlation between low Agreeableness and narcissistic personality disorder.

Conscientiousness

Conscientiousness is the dimension of personality that contains both proactive (striving

for excellence and commitment to work despite boredom) and inhibitive aspects (adherence to

moral values and cautiousness) (Costa et al., 1991). It measures an individual’s ability to

organize goal-directed behaviour (Bergeman et al., 1993) and control impulses (Costa and


23

McCrae, 1992). The facets included in the Conscientiousness domain are Competence, Order,

Dutifulness, Achievement striving, Self-discipline, and Deliberation.

There has not been much research directly examining the neurobiology of

Conscientiousness but investigations have studied related personality constructs including

sensation seeking, novelty seeking, and impulsivity. As the 5-HT system plays a central role in

impulse control (Quednow et al., 2007) and has been implicated in sensation seeking (Netter et

al., 1996), researchers have suggested that lower 5-HT system function may be related to the

Conscientiousness domain (Manuck et al., 1998).

The Conscientiousness domain has been found to be associated with various addictive

and impulse control disorders such as alcohol dependence, drug dependence, substance use

disorders, pathological gambling, and shopping addiction (Trull and Sher, 1994; Bagby et al.,

2007; Rodriguez-Villarino et al., 2006). In the assessment of addiction potential in university

students, Zargar and Ghaffari (2009) found that Conscientiousness scores were negatively related

to addiction potential. Thus, the personality domain of Conscientiousness may be a risk factor for

the development of addictive disorders.

1.2.2.2 Personality Studies Investigating PG

Research undertaken to elucidate the personality traits associated with PG have revealed

that pathological gamblers are a heterogeneous group with distinct subtypes despite having one

common set of diagnostic criteria (Vachon and Bagby, 2009). Vachon and Bagby (2009)

empirically tested the subtypes of pathological gambling based on the FFM using cluster

analyses of personality traits in a non-treatment-seeking sample of gamblers. They identified

three pathological gambling subtypes characterized by differentiated impulsivity-trait profiles

classifying them as simple, hedonic, and demoralized pathological gamblers. Simple


24

pathological gamblers were portrayed as individuals with low levels of comorbid

psychopathology and normative personality trait scores. Hedonic pathological gamblers were

described as individuals with moderate rates of comorbid psychopathology and scored higher in

the Extraversion and Openness domains and facets related to excitement seeking and positive

affect. Demoralized pathological gamblers were characterized by high rates of comorbid

psychopathology and higher scores in Neuroticism, but lower scores in the Extraversion,

Agreeableness, and Conscientiousness domains. Also, they had higher scores in facets related to

negative affect and impulsivity.

Despite these findings that pathological gamblers are a heterogeneous group, there has

been a consensus that certain personality traits may contribute to PG overall (Raylu and Oei,

2002). The personality profile of high Neuroticism and low Conscientiousness scores has been

found to be associated with a variety of substance abuse disorders (Bottlender and Soyka 2005;

Terracciano et al., 2008; Kotov et al., 2010). A review of literature has shown that PG has

substantial similarities with substance use disorders in terms of diagnostic criteria, comorbidities,

neurocircuitry, and the personality trait of impulsivity (Potenza 2006). Thus, it has been

hypothesized that high Neuroticism and low Conscientiousness scores of the NEO personality

questionnaire, which is based on the FFM, would be associated with PG.

Studies have shown that Neuroticism represents the vulnerability of an individual to a

wide range of negative affect and psychopathology (Costa and McCrae, 1992; Malouff et al.,

2005; Ormel et al., 2004). Thus, high scorers in the Neuroticism domain are more susceptible to

developing addictive behaviour and psychiatric disorders, like major depressive disorder, which

are highly comorbid with PG (Cunningham-Williams et al., 1998). The Conscientiousness

domain is also particularly relevant to gambling behaviour as PG is classified as an impulse-


25

control disorder and Conscientiousness measures an individual’s capacity to resist impulses,

organize goal-directed behaviour, and control desires (Costa and McCrae, 1992). The hypothesis

was supported as personality studies revealed that pathological gambling was consistently

associated with higher Neuroticism and lower Conscientiousness scores compared to control

groups in a variety of samples (Bagby et al., 2007; Myrseth et al., 2009; Kaare et al., 2009;

MacLaren et al., 2011). These studies suggest that the personality profile of individuals with PG

is common to other addictive disorders and is one that is highly susceptible to negative affect and

low impulse control.

1.2.2.3 Summary

Personality studies provide another approach in which to investigate psychopathology

and allow for further implications and insight into the neurobiology of the disorders. The NEO-

PI-R and NEO-FFI, which are based on the five-factor model of personality, have strong

empirical support and are appropriate for the examination of individual differences of personality

traits in psychiatric disorders. From the personality studies reviewed above, researchers suggest

that there is a common personality profile (high Neuroticism and low Conscientiousness)

underlying addictive disorders. High Neuroticism has been associated with increased

vulnerability to developing psychopathology while low Conscientiousness has been associated

with impulse-control and addictive disorders. Previous research has shown that though PGs are a

heterogeneous group, high Neuroticism and low Conscientiousness scores are consistently

shown to be significantly associated with PG.

1.3 Rationale

1.3.1 Objectives and Hypotheses


26

After reviewing previous literature, there is strong evidence that personality and genetics

are involved in PG though the relationship between the three factors is complex. Investigations

have examined the role personality has in pathological gambling and found that a personality

profile, or specific combination of personality traits, was associated with the disorder. Other

research, using a twin study design, has shown that genetics are involved in both personality and

PG as they are heritable. Previous literature has also implicated 5-HT to play a significant role in

personality and PG. For personality, the 5-HT system has been found to regulate early brain

development and, if dysregulated, may lead to brain function and behaviour changes. For PG, 5-

HT concentrations in the brain have been shown to be associated with impulse control and PG,

which is classified as an impulse-control disorder in the DSM-IV.

Despite this evidence, there has been a paucity of studies investigating the association

between 5-HT genes, personality traits, and PG. Those that have been conducted have resulted in

mixed findings. This could be due to insufficiently powered samples to detect small genetic

effects and because only a few 5-HT candidate genes and polymorphisms have been

investigated. To fill this current gap in the literature and better understand the complex

relationship between 5-HT genes, personality traits, and PG, we had the following three

objectives and hypotheses in our studies:

1) To conduct a comprehensive 5-HT genetic association analysis of personality traits.

Most of the previous studies have only focused on the functional 5-HTTLPR and

MAOA VNTR polymorphisms. We hypothesized that genetic variations of the

polymorphisms we selected (including the 5-HTTLPR and MAOA VNTR) in ten 5-

HT candidate genes would be associated with personality traits.


27

2) To examine the differences in personality traits between problem gamblers and the

general population. Most of the previous studies have focused on investigating the

association between personality traits and pathological gamblers and some have used

a pathological gambling treatment-seeking sample, which do not represent the

majority of the pathological gambling population. Based on previous findings in

which pathological gambling was examined, we hypothesized that problem gamblers

would score higher in the Neuroticism and lower in the Conscientiousness domain

compared to controls.

3) To conduct a comprehensive 5-HT genetic association analysis of PG. Very few

studies have investigated the involvement of 5-HT gene variants in PG and focus has

been placed on the functional 5-HTTLPR and MAOA VNTR polymorphisms. We

hypothesized that other genetic variations of polymorphisms in the 5-HT system we

selected would be associated with PG.

Tong et al. II. 5-HT Genes and Personality

28

CHAPTER 2

2. Association Study of Serotonin Gene Polymorphisms and NEO Five-Factor Inventory

(NEO-FFI) Personality Traits

Ryan P. Tong B.Sc.1, Clement C. Zai Ph.D.

1, David M. Casey Ph.D.

2, David C. Hodgins Ph.D.

2,

Garry J. Smith Ph.D.3, Robert J. Williams Ph.D.

4, Donald P. Schopflocher Ph.D.

5, Nady el-

Guebaly M.D.6, Daniela S.S. Lobo M.D., Ph.D.

1,7,8, James L. Kennedy M.D.

1,7

1 Neurogenetics Section, Neuroscience Department, Centre for Addiction and Mental Health,

Toronto, ON, Canada

2 Department of Psychology, University of Calgary, Calgary, AB, Canada

3 Faculty of Extension, University of Alberta, Calgary, AB, Canada

4 Faculty of Health Sciences, University of Lethbridge, Lethbridge, AB, Canada

5 Faculty of Nursing, University of Alberta, Calgary, AB, Canada

6 Division of Addictions, Department of Psychiatry, University of Calgary, Calgary, AB, Canada

7 Department of Psychiatry, University of Toronto, Toronto, ON, Canada

8 Problem Gambling Service, Addictions Program, Centre for Addiction and Mental Health,

Toronto, ON, Canada

Running title: Serotonergic gene polymorphisms and NEO-FFI personality traits


29

2.1 ABSTRACT

2.1.1 Objective:

Studies have found that serotonin plays a significant role in the development of personality and

that personality traits are heritable. However, few studies have investigated the role serotonergic

gene variants play in personality. We evaluated the association between 97 serotonin gene

polymorphisms (HTR1B, HTR2A, HTR2C, HTR3A, HTR3B, HTR6, HTR7, TPH2, MAOA, and

SLC6A4) and NEO Five-Factor Inventory (NEO-FFI) domains.

2.1.2 Materials and Methods:

A sample of 302 healthy Caucasian subjects (35.4% male; mean age: 48.2 ± 16.4 years) was

assessed using the NEO-FFI, an instrument that assesses the personality trait dimensions of the

Five-Factor Model. UNPHASED 3.1.3 was used to analyze allele, genotype, and haplotype

associations with age and sex included as covariates. The Nyholt method was used to correct for

multiple testing.

2.1.3 Results:

There were nominal associations in allele, genotype, and haplotype analyses with NEO-FFI

domains before Nyholt corrections. However, only the MAOA and HTR3A haplotype

associations survived corrections for multiple testing. Specifically, for Agreeableness, the low

activity-A-A (MAOA VNTR-rs3788862-rs1465107) and A-A-A (rs3788862-rs1465107-

rs146510) haplotype of MAOA was significantly associated with lower scores (p= 0.0001 and

0.0005 respectively). For Conscientiousness, the low activity-A-A (MAOA VNTR-rs3788862-


30

rs1465107) haplotype of MAOA and the A-A-G (rs1176713/ rs11214800/ rs1379170) haplotype

of HTR3A remained significantly associated with lower scores.

2.1.4 Conclusion:

Our study indicates that MAOA and HTR3A haplotypes may play a role in Agreeableness and

Conscientiousness personality traits. Future studies should investigate whether or not these gene

variants are associated with impulse control and personality disorders. By investigating the

biological mechanism of personality, novel, effective medications for personality disorders may

be developed.

Keywords: genetics; candidate serotonin genes, NEO Five-Factor Inventory; personality


31

2.2 INTRODUCTION

Multiple studies indicate that the action of neurotransmitters in the brain, such as

dopamine and serotonin, play a significant role in personality traits (Kestler et al., 2000;

Kalbitzer et al., 2009; Frokjaer et al., 2008; Burke et al., 2011). These studies identify

relationships between neurotransmitters and personality traits which can, in turn, explain how

personality may be a vulnerability factor for various psychiatric disorders. In particular, research

has focused on serotonin’s (5-HT) role in the development of personality traits as the 5-HT

system has been found to regulate early brain development and, if dysregulated, may lead to

pathological changes in brain function and behaviour (Whitaker-Azmitia 2001).

Dysfunction of the 5-HT system is a common feature in personality disorders, and 5-HT

appears to play a role in the neurobiology of borderline personality disorder (Verkes et al., 1998)

and impulsive, aggressive behaviour (Booij et al., 2010). DSM-III-R personality disorder has

been shown to be associated with a reduction in paroxetine binding in platelets, an indicator of

presynaptic 5-HT reuptake, which suggests compromised 5-HT function (Coccaro et al., 1996).

In a sample of healthy subjects, it was found that selective serotonin reuptake inhibitors

modulated dimensions of normative personality by increasing affiliative behaviour and

attenuating aggressive behaviour (Knutson et al., 1998). Dolan and colleagues (2001) performed

a d-fenfluramine challenge study in a sample of male offenders and found that low central

serotonin function was associated with impulsivity, aggression, and borderline personality

disorder. Thus, the 5-HT system is implicated in individual differences in personality traits.

The NEO Five-Factor Inventory (NEO-FFI) is the short version of the revised NEO

Personality Inventory (NEO-PI-R); both instruments assess personality trait dimensions of the


32

Five-Factor Model (FFM), the most widely used and universally accepted dimensional model of

personality (Pytlik Zillig et al., 2002). The inventory is a well-established measure of personality

traits and has been validated in a variety of psychiatric samples, populations, and cultures

(McCrae and Costa, 2004). A significant portion of the variance in personality traits can be

explained by genetic factors where the genetic influence of the five domains of the FFM

(Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness) has been

estimated at 41%, 53%, 61%, 41%, and 44% respectively (Jang et al., 2006). A review by

Bouchard and Loehlin (2002) found that twin studies of the five-factor personality model

estimated the heritability of personality traits to range from 0.40-0.60. Overall, the evidence that

personality traits are heritable is quite strong.

Despite serotonin’s role in personality and the heritability of personality traits, few

studies have examined the association between serotonin gene polymorphisms and personality

traits. It has been hypothesized that a significant percentage of the variance in personality traits

can be explained by 5-HT gene variants (Jacob et al., 2005; Rosenberg et al., 2005; Greenberg et

al., 2000; Sen et al., 2004; Tochigi et al., 2005; Nakamura et al., 2010; Mizuta et al., 2008).

Specifically, genetic association studies have been conducted between HTR2A, MAOA,

and SLC6A4 gene variants and personality traits. Using the Temperament and Character

Inventory (TCI) or the Tridimensional Personality Questionnaire (TPQ) to measure personality

traits, various polymorphisms of the HTR2A gene were associated with harm avoidance, self-

determinism and self-transcendence, and novelty seeking (Nakamura et al., 2010; Ham et al.,

2004; Heck et al., 2009). However, Kusumi et al. (2002) found that the HTR2A gene was not

associated with any of the TPQ personality traits. In comparison, using the NEO-PI-R, our


33

collaborative group found an association between the domain of Extraversion and the HTR2A

T102C variant (Ni et al., 2006).

In assessing the association between MAOA gene polymorphisms and personality

domains as measured by the TPQ or TCI, Yu et al. (2005) found that the functional VNTR 4-

repeat variant was associated with higher harm avoidance while both Kim et al. (2006) while

Garpenstrand et al. (2002) did not find any significant associations in a similar comparison.

Using the NEO-PI-R instrument, Samochowiec et al. (2004) found a significant association

between the 3 repeat variant of the MAOA VNTR polymorphism and lower Openness scores

while Soliman et al. (2010) and Garpenstrand et al. (2002) had negative findings.

Another 5-HT gene investigated for its association with personality traits is the serotonin

transporter (5HTT or SLC6A4). Gonda et al. (2009) found that the short allele of the promoter

polymorphism (5-HTTLPR) of SLC6A4 was associated with higher self-directedness scores as

measured by the TCI. When assessing personality traits with the NEO-PI, Sen et al. (2004) and

Greenberg et al. (2000) found an association between the short allele of 5-HTTLPR and higher

Neuroticism, a personality domain correlated with self-directedness of the TCI (De Fruyt et al.,

2000). However, Terracciano et al. (2009) and Lang et al. (2004) did not replicate these findings

and found no association between the personality domains of the NEO-PI-R and the HTTLPR

polymorphism.

Thus, overall, the genetic association findings of previous studies between personality

traits and 5-HT genes have been mixed. This variability may be due to sample differences and

the use of different personality measuring instruments among the studies. The fact that many of

these studies did not control for ancestry (population stratification) or correct for multiple testing


34

may give rise to false positive or negative results. Also, in particular, it has been implicated that

there may not be a genetic basis for TPQ domains (Herbst et al., 2000) which would explain the

mixed findings of studies investigating the association between candidate genes and the TPQ.

Here, we investigate the influence of several serotonergic genes on personality traits, as

assessed by the five NEO-FFI domains in a sample of 302 healthy Caucasian subjects. This study

is the most comprehensive study of 5-HT genes and personality to date as many of the 5-HT

gene polymorphisms analyzed in this paper have never previously been investigated for

associations with personality traits (HTR1B, HTR2A, HTR2C, HTR3A, HTR3B, HTR6, HTR7,

TPH2, MAOA, and SLC6A4). These genes were selected for analysis because previous studies

found that these genes contained functional variants encoding enzymes or receptors regulating 5-

HT concentrations in the synapse (Drago et al., 2010; Iceta et al., 2009; Lesch et al., 1996; Sabol

et al., 1998) or polymorphisms of the gene had been associated with personality or mood

disorders (Tadic et al., 2009; Ducci et al., 2009; Mizuta et al., 2008; Gutknecht et al., 2007; Ni et

al., 2006; Ni et al., 2007). Due to the heritable nature of personality traits and the putative role

serotonin plays in the development of normal personality and personality disorders, we

hypothesized that there would be significant associations between serotonin gene variants and

NEO-FFI domain scores in our sample of Caucasian subjects.


35

2.3 METHODS

2.3.1 Subjects

Three hundred and two normal, unrelated, Caucasian volunteers (35.4% male; mean age:

48.2 ± 16.4 years) were recruited using television commercials, newspaper advertisements,

posters, and a random-digit dialing bank of rural and urban areas from Alberta, Canada. The data

collection was completed as part of the Leisure, Lifestyle and Lifecycle Project (el-Guebaly et

al., 2008) that examined risk factors for the development of gambling disorders and other

addictions. Using a self-report form for genealogical information, subjects who reported that at

least three of their grandparents were of Caucasian background were considered Caucasian and

included in the analysis. The research protocol was approved by the local ethics committees.

2.3.2 Assessment

Personality traits were measured for all subjects using the 60-item, self-report NEO Five-

Factor Inventory (NEO-FFI; Costa and McCrae, 2004). The NEO-FFI assesses the personality

trait domains that compose the FFM --Neuroticism, Extraversion, Openness to experience,

Agreeableness, and Conscientiousness.

2.3.3 Genotyping

Genomic DNA was isolated from study participants through extraction from blood using

a standard high-salt method (Lahiri and Nurnberger, 1991). We genotyped functional single

nucleotide polymorphisms (SNPs) and tag SNPs of 10 candidate genes in the 5-HT system which

were selected through pair-wise tagging analysis in Haploview (Version 4.1; Barrett et al., 2005)

at an r2 of 0.8. Based on previous findings of functional effect, the MAOA VNTR alleles can be


36

categorized into two functional groups (Sabol et al., 1998). In this study, the 3.5 and 4 repeats

(high activity) were grouped as one allele category while the 3 and 5 repeats (low activity) were

the other group. Similarly, the 5-HTTLPR polymorphism is considered functionally biallelic (Hu

et al., 2006). Thus, the long variant of the 5-HTTLPR polymorphism containing the A allele of

rs25531 (LA) was one allele group while the long variant containing the G allele of rs25531 (LG)

and the short variant together made up the other allele group. To ensure accuracy, 10% of the

total sample was re-genotyped. The MAOA VNTR and serotonin transporter 5-HTTLPR

polymorphisms were genotyped using the ABI-3130 Genetic Analyzer (Applied Biosystems,

Inc.). The genotyping of the remaining SNPs was carried out on an Illumina 384 SNP platform.

After exclusion of polymorphisms that failed quality control (Hardy-Weinberg

equilibrium p value < 0.05, call frequency < 0.95, and minor allele frequency < 0.01), 97

genotyped polymorphic markers were selected for analysis and tested for association with NEO-

FFI scores (Table 1).

2.3.4 Statistical Analysis

The statistical power of the sample was calculated using Quanto 1.2.4 (Gauderman and

Morrison, 2006: http://hydra.usc.edu/gxe). Assuming a minor allele frequency of 0.2 in a sample

size of n= 302, we had >80% power to detect a genetic effect (β) of 2.25 for the Neuroticism

dimension, 1.85 for Extraversion, 1.75 for Openness to experience, 1.60 for Agreeableness, and

1.75 for Conscientiousness in a log-additive model.

Haploview (Version 4.1; Barrett et al., 2005) was used to verify Hardy-Weinberg

equilibrium and identify tag SNPs. Statistical analyses were performed using the UNPHASED

program (version 3.1.3) (Dudbridge, 2003, 2008) and analyzed using the likelihood ratio chi


37

square tests with age and sex included in the analysis as covariates. We used a sliding window

size of three markers to define haplotype blocks. Also, to correct for multiple testing of SNPs,

we used the Nyholt method (Nyholt 2004).


38

2.4 RESULTS

To examine the associations between the genotyped markers and personality traits, NEO-

FFI scores were compared to alleles, genotypes, and haplotypes of each serotonin candidate

gene. Sex was included as a covariate in the analysis as some NEO-FFI domain scores

significantly differed between males and females (p = 0.0004, 0.727, 0.735, 0.004, and 0.025

respectively). Similarly, age was also included as a covariate as it had a significant effect on

NEO-FFI domain scores (p = 0.0002, 0.075, 0.007, 0.008, and 0.001 respectively). Using the

Nyholt correction method for multiple testing, the critical p-value threshold for statistical

significance was set at 9.75 x 10-4

. Shown below are both nominally significant and statistically

significant results.

2.4.1 Neuroticism

We found nominally significant associations between NEO-FFI Neuroticism scores and

alleles, genotypes, and haplotypes of the sample. In the allelic analysis, when the covariates of

age and gender were taken into account, the C allele of rs9659997 of HTR6 and both the G allele

of SNP rs7916403 and the C allele of rs11597471 of HTR7 were significantly associated with

higher NEO-FFI Neuroticism scores (puncorrected = 0.048, 0.045, and 0.022 for each marker

respectively).

In terms of genotype analyses, the C/C genotype of rs9359271 of HTR1B and the C/G

genotype of rs6318 of HTR2C were significantly associated with higher NEO-FFI Neuroticism

(puncorrected = 0.009 and 0.008 respectively).

In haplotype analysis, the following haplotypes were found to be significantly associated

with higher NEO-FFI Neuroticism scores (puncorrected): the G-A-C haplotype (rs3758987-


39

rs11606194- rs1176744; p= 0.026) of HTR3B, and the A-A-A haplotype (rs2276302-rs1176719-

rs1176713; p= 0.029) and the A-A-A haplotype (rs1176713-rs11214800-rs1379170; p= 0.030)

of HTR3A.

However, none of these associations remained significant after adjustment using Nyholt’s

method of correction for multiple testing.

2.4.2 Extraversion

We found nominally significant associations between NEO-FFI Extraversion scores and

alleles, genotypes, and haplotypes of the sample.

With covariates included in the analysis, the C allele of rs6354 and the G allele of

rs4251417 of SLC6A4, and the A allele of rs4911871 of HTR2C were significantly associated

with higher scores in Extraversion (puncorrected = 0.037, 0.050, and 0.045 respectively).

In genotypic analysis, the G/G genotype of rs3782025 of HTR3B, and the A/G genotype

of rs4941573, the A/G genotype of rs1328684, and the A/G genotype of rs6313 of HTR2A were

significantly associated with higher Extraversion scores (puncorrected = 0.022, 0.031, 0.041, and

0.004 respectively).

In haplotype analysis, the following 5-HT haplotypes were significantly associated with

higher Extraversion (puncorrected): the C-A-A haplotype (rs9359271-rs2000292-rs13212041; p =

0.023) of HTR1B; the A-G-G haplotype (rs10789970-rs3758987-rs11606194; p= 0.014) of

HTR3B; the C-G-T haplotype (rs1386485-rs1487280-rs1487279; p= 0.013) and the G-T-A

haplotype (rs1487280-rs1487279-rs1872824; p= 0.027) of TPH2; the G-C-G haplotype


40

(rs7997012-rs977003-rs1923885; p= 0.050) of HTR2A; and the haplotype C-G-LA (rs12150214-

rs4251417-HTTLPR; p= 0.034) of SLC6A4.

The associations above were only nominally significant as they did not survive Nyholt’s

correction for multiple testing.

2.4.3 Openness to Experience

For the allelic analysis of the NEO-FFI Openness to Experience domain, the following

alleles were significantly associated with higher Openness scores (puncorrected): the A allele of

rs2000292 of HTR1B, the A allele of rs10789970 and the A allele of rs3758987 of HTR3B (p=

0.014, 0.032, and 0.008 respectively); the A allele of rs1487275 of TPH (p= 0.012); and the G

allele of rs6318 of HTR2C (p= 0.028).

In terms of the genotypic analysis, the A/A genotype of rs2000292 of HTR1B was

significantly associated with higher Openness scores (puncorrected = 0.038).

For the haplotypic analysis, the following haplotypes were found to be associated with

higher scores in Openness (puncorrected): A-A-A haplotype (rs3758987-rs11606194-rs1176744; p=

0.026) of HTR3; the A-A-C haplotype (rs1487275-rs1386486-rs1386485; p= 0.033) and the A-

A-A haplotype (rs1487280-rs1487279-rs1872824; p= 0.023) of TPH; and the A-A-G haplotype

(rs1465107-rs1465108-rs909525; p= 0.049) and the A-A-G haplotype (rs979605-rs2064070-

rs6609257; p= 0.046) of MAOA.

However, after Nyholt correction, none of these associations remained significant.

2.4.4 Agreeableness


41

For Agreeableness scores, the allelic association analysis found the following alleles to

be associated with lower Agreeableness scores (puncorrected): the A allele of rs1185027 of HTR3B

(p=0.026); the A allele of rs10789980, the G allele of rs1176719, the G allele of rs1176713, the

C allele of rs11214800, the G allele of rs1379170, and the A allele of rs7126511 of HTR3A

(p=0.018, 0.033, 0.008, 0.009, 0.021, and 0.036 respectively); and the A allele of rs3788862 of

MAOA (p= 0.042).

In the genotype analysis, the following genotypes were significantly associated with

lower scores in the Agreeableness domain (puncorrected): the A/A genotype of rs1185027 of the

HTR3B gene (p= 0.014); the A/A genotype of rs10789980, the A/A genotype of rs11214800, and

the A/A genotype of rs7126511 of HTR3A (p= 0.012, 0.016, and 0.044 respectively); the A/A

genotype of rs1923885 of HTR2A (p= 0.035); and the A/A genotype of rs1465108 of MAOA (p=

0.013).

For the haplotype analysis, the following were significantly associated with lower

Agreeableness (puncorrected): the G-G-A haplotype (rs2276307-rs3782025-rs1185027) and A-A-A

haplotype (rs3782025-rs1185027-rs7942029) of HTR3B(p= 0.030 and 0.006 respectively); the

A-A-G haplotype (rs1176713-rs11214800-rs1379170; p= 0.017) of HTR3A; the A-A-A

haplotype (rs4760750-rs10506645-rs12229394), the A-A-A haplotype (rs10506645-rs12229394-

rs1352250), the A-A-A haplotype (rs12229394-rs1352250-rs9325202), and the A-A-A haplotype

(rs1352250-rs9325202-rs1487275; p= 0.011, 0.010, 0.005, and 0.009 respectively) of TPH2; the

G-C-A haplotype (rs1923886-rs2296972-rs9534495) and the A-A-A haplotype (rs1002513-

rs2770304-rs985933; p= 0.050 and 0.034 respectively) of HTR2A; and the low activity-A-A

haplotype (VNTR-rs3788862-rs1465107) and the A-G-G haplotype (rs3788862-rs1465107-

rs1465108) of MAOA (p= 0.0005 and 0.0001 respectively).


42

The two MAOA haplotypes survived Nyholt correction and were significantly associated

with Agreeableness scores.

2.4.5 Conscientiousness

Finally, for the Conscientiousness domain, we found the following alleles to be

significantly associated with lower scores of Conscientiousness (puncorrected): the G allele of

rs6297 of HTR1B (p= 0.019); the A allele of rs10789980, the A allele of rs2276302, the G allele

of rs1176719, the G allele of rs1176713, the A allele of rs11214800, and the G allele of

rs1379170 of HTR3A (p= 0.036, 0.035, 0.011, 0.008, 0.015, and 0.021 respectively); and the C

allele of rs1042173, the A allele of rs6354, the A allele of rs2020939, the A allele of rs2020936,

and the G allele of rs12150214 of SLC6A4 (p= 0.009, 0.005, 0.027, 0.005, and 0.005

respectively).

For the genotypic analysis, we found that the A/A genotype of rs6354, the A/A genotype

of rs2020936, and the G/G genotype of rs12150214 of SLC6A4 were significantly associated

with lower Conscientiousness (puncorrected = 0.046, 0.045, and 0.045 respectively).

For the haplotype analysis, we found the following haplotypes to be significantly

associated with lower scores in the Conscientiousness (puncorrected): the G/C/C haplotype (rs6297/

rs6296/ rs11568817; p= 0.043) of HTR1B; the A/A/A haplotype (rs10789970/ rs3758987/

rs11606194; p= 0.023) and the A/A/A haplotype (rs3758987/ rs11606194/ rs1176744; p= 0.023)

of HTR3B; the A/A/A haplotype (rs2276302/ rs1176719 /rs1176713; p= 0.009), the G/A/A

haplotype (rs1176719/ rs1176713/ rs11214800; p= 0.016), and the A/A/G haplotype (rs1176713/

rs11214800/ rs1379170 of HTR3A; p= 0.0003); the A/A/A haplotype (rs1042173/ rs6354/

rs2020939; p= 0.021), the A/A/A haplotype (rs6354/ rs2020939/ rs2020936; p= 0.020), the


43

A/A/G haplotype (rs2020939/ rs2020936/ rs12150214; p= 0.008), and the A/G/G haplotype

(rs2020936/ rs12150214/ rs4251417; p= 0.018) of SLC6A4; and the low activity/A/A haplotype

(VNTR/ rs3788862/ rs1465107; p= 0.00002), the A/A/A haplotype (rs3788862/ rs1465107/

rs1465108; p= 0.016), and the A/A/A haplotype (rs979605/ rs2064070/ rs6609257; p= 0.040) of

MAOA.

Both the A/A/G haplotype (rs1176713/ rs11214800/ rs13791700 of HTR3A and the low

activity/A/A haplotype (VNTR/ rs3788862/ rs1465107) of MAOA remained significantly

associated with scores of Conscientiousness after Nyholt correction for multiple testing.

2.4.6 Overall

To summarize across these results, after correction for multiple testing, there were no

significant results for the Neuroticism, Extraversion, or Openness. For Agreeableness and

Conscientiousness, no allelic or genotypic associations were significant, but MAOA and HTR3A

haplotype associations remained significant after Nyholt corrections. Haplotype analysis

revealed that the low activity-A-A (MAOA VNTR-rs3788862-rs1465107) and A-A-A

(rs3788862-rs1465107-rs146510) haplotype of MAOA were significantly associated with lower

scores of Agreeableness (Table 2). In terms of Conscientiousness, both the low activity-A-A

(MAOA VNTR-rs3788862-rs1465107) haplotype of MAOA and the A/A/G (rs1176713/

rs11214800/ rs1379170) haplotype of HTR3A were significantly associated with lower scores:

the (Table 3).


44

2.5 DISCUSSION

In the present study, we investigated the association between 97 polymorphisms of ten

serotonin candidate genes and personality as assessed by the NEO-FFI in healthy subjects.

Serotonin is one of the key neurotransmitters involved in normal personality and dysfunction of

this neurotransmitter system has been associated with psychiatric disorders related to

aggressiveness and low impulse control including borderline personality disorder, suicidal

behaviour, and problem gambling (Hansenne et al., 2002; Ryding et al., 2008; Moreno et al.,

1991).

In this study, we found significant MAOA haplotype associations with Agreeableness that

remained significant after Nyholt correction. Additionally, MAOA and HTR3A haplotypes were

also found to be significantly associated with Conscientiousness. These results suggest that the

MAOA gene may play a role in both Agreeableness and Conscientiousness while the HTR3A

gene appears to be involved in Conscientiousness.

Monoamine oxidase A, an enzyme that is mostly found on the outer membranes of

mitochondria in neurons (Saura et al., 1996), catalyzes the degradative deamination of several

neurotransmitters, including serotonin (Rosenberg et al., 2006). A VNTR functional

polymorphism has been reported in the MAOA gene promoter where the 3.5 and 4 repeat variants

result in higher MAOA enzymatic activity compared to the 3 and 5 repeats (Sabol et al., 1998).

Studies have examined the association between NEO personality domain scores and the MAOA

VNTR, but the results have been mixed. Samochowiec and colleagues (2004) found a significant

association between the 3 repeat variant of the MAOA VNTR and lower Openness. However,

Rosenberg and colleagues (2006) failed to replicate this finding, but instead found that rare


45

haplotypes of the MAOA gene were significantly associated with Conscientiousness scores. In

our study, we found a significant association between the A/A/A (rs3788862/ rs1465107/

rs146510) MAOA haplotype and lower Agreeableness while the low activity/A/A (MAOA

VNTR/ rs3788862/ rs1465107) haplotype was significantly associated with both lower

Agreeableness and Conscientiousness. The apparent discrepancy between the results of these

studies might be accounted for by the small sample size used by Samochowiec et al. (2004) and

the fact that the haplotype association Rosenberg et al. (2006) found was in MAOA haplotypes of

rare genetic variants. Our haplotype analyses excluded rare haplotypes that occurred at a

frequency of ≤ 0.05.

The Agreeableness domain measures the ability to relate to other’s needs and understand

the intentions of others. It has been shown that patients with borderline personality disorder, a

disorder characterized by dysregulation in mood and poor interpersonal relationships, have a low

frequency of the low activity haplotype of MAOA (Ni et al., 2007). This does not support the

result of this study which found that the low activity haplotype of MAOA was associated with

low Agreeableness. However, this may be due to differences in the investigated populations. Ni

et al. (2007) conducted their analyses in borderline personality disorder patients while our

sample consisted of healthy individuals. In support of our finding, it was found that MAOA

knockout mice displayed more impulsive aggressive behaviour in a resident-intruder test where it

was observed that knockout mice attacked the intruder faster than control mice and also avoided

social investigation (Cases et al., 1995). Similarly, in a Dutch family, it was found that males

deficient in MAOA demonstrated disturbed regulation of impulsive aggressive behaviour

including arson, attempted rape, and exhibitionism (Brunner et al., 1993). Thus, the findings of

this study implicate MAOA haplotypes may play a role in the Agreeableness personality domain.


46

The Conscientiousness domain of the NEO-FFI is a measure of an individual’s ability to

organize goal-directed behaviour and low scores in this domain represent a lower ability to

control impulsive behaviour (Costa and McCrae, 1992). In a genetic association study, it was

found that the lower activity repeat variants of the MAOA VNTR polymorphism were

significantly associated with impulsive traits and early substance abuse (Huang et al., 2004).

Though the MAOA VNTR allelic association with Conscientiousness was not significant in our

study, we did find a significant association between the MAOA haplotypes containing the low

activity allele group and lower Conscientiousness. These findings suggest that the MAOA VNTR

may underlie impulsive behaviour and further investigation of the variant in impulse control

disorders is warranted. Soliman et al. (2011) found that in their sample of subjects who did not

have any current or past DSM-IV Axis I disorders, the continuum of MAOA binding in the

prefrontal cortex, a brain region where neurochemical changes are associated with impulsive

behaviour (Siever et al., 1999), was correlated with personality. Specifically, individuals high in

impulsiveness had the lowest levels of MAOA binding and individuals high in deliberation, a

personality facet related to the ability to consider and assess possible solution options, had the

highest levels of MAOA binding. Thus, our study shows that MAOA haplotypes are associated

with Conscientiousness personality traits and indicates that MAOA may play a role in impulsive

behaviour.

We also report an association between the A/A/G (rs1176713/ rs11214800/ rs1379170)

HTR3A haplotype with lower Conscientiousness domain scores. To our knowledge, this

represents the first study of the relationship between NEO personality domain scores and HTR3A

gene variants. The HTR3 receptor is unique from other 5-HT receptors as it is a ligand-gated ion

channel (Thompson and Lummis, 2006). HTR3 receptors are located throughout the brain but


47

are heavily concentrated in the hippocampus, cingulate cortex, and brainstem (Miguel et al.,

2002) which is consistent with the role HTR3 receptors play in cognition and affect (Tecott et al.,

1993). HTR3 receptors indirectly affect the release of neurotransmitters, such as the excitatory

neurotransmitter dopamine, by allowing sodium and potassium ions to freely pass into or out of

the neuron, thus modifying its action potential (Maricq et al., 1991). Therefore, HTR3A gene

variants that affect the receptor’s effect on ion flux across neuronal membranes may play a role

in the Conscientiousness personality domain by modifying neurotransmitter transmission.

Our study failed to replicate some findings of previous studies investigating serotonin

candidate genes and their role in personality traits. One commonly investigated gene variant for

its relation to personality traits is the functional 5-HTTLPR polymorphism. The 5-HTTLPR

affects the transcriptional efficiency of the 5-HTT gene and consequently affects 5-HT synapse

concentrations (Hu et al., 2006). Some genetic association studies have shown a robust

association between the short allele variant with higher NEO Neuroticism scores (Greenberg et

al., 2000; Sen et al., 2004) while another study did not replicate this association (Terracciano et

al., 2009). We report negative findings with no significant allelic, genotypic, or haplotype

association of the HTTLPR with NEO-FFI personality domain scores. This could possibly be

due to sample heterogeneity.

Additionally, the HTR2A gene has been studied for its association with personality traits,

but the results are also mixed. Ni et al. (2006) found a significant association between the C

allele of rs6313 (T102C) and the A allele of rs4941573 of HTR2A with higher Extraversion

scores. Tochigi et al. (2005) did not replicated this finding but found trends for association

between the T/T genotype of rs6313 with lower Neuroticism and higher Conscientiousness,

though these results did not survive correction for multiple testing. In our study, we also did not


48

find any significant allele, genotype, or haplotype HTR2A associations with NEO-FFI domains.

We did find a nominally significant association between the C/C genotype of rs6313 and higher

Extraversion but failed to replicate the rs4941573 association found by Ni et al. (2006). A

possible reason why the results of our studies differ may be because of how the samples were

selected. In the current study, we used a sample composed of healthy Caucasian individuals

while the sample used by Ni et al. (2006) consisted of borderline personality disorder patients

and Tochigi et al. (2005) used a healthy Japanese sample. Thus, results may not be replicated in

different populations.

To our knowledge, this study provides the most comprehensive investigation for the role

that a number of serotonergic genes play in personality traits. A particular strength of our study

was that the sample was relatively homogeneous because we did not include anyone with less

than three grandparents of Caucasian origin. However, a limitation of our study is that the full

variance of the personality traits may not have been captured by the short version of the NEO,

NEO-FFI. Thus, future studies would be well advised to investigate the association between 5-

HT genes and the 240-item NEO-PI-R.

In conclusion, after correction for multiple testing, we found no significant allelic or

genotypic associations between the 5-HT gene variants investigated and NEO-FFI personality

domains. We did observe significant associations between HTR3A haplotypes and

Conscientiousness and MAOA haplotypes with Agreeableness and Conscientiousness. These

findings suggest that these genes may play a role in the development or maintenance of

personality traits. It is hoped that by understanding the neurobiological mechanisms of normal

personality, we will also illuminate the pathological changes that occur in personality disorders


49

and mental illnesses in general. The findings of this study could also possibly aid in the

development of novel and more effective medications for personality disorders.


50

Table 1. Serotonin candidate gene markers included in the analysis.

Gene HTR6 HTR1B HTR7 HTR3B HTR3A

Markers

rs4912138 rs9352481

rs11599921 rs10789970 rs10789980

rs6699866 rs9359271 rs7916403 rs3758987 rs2276302

rs9659997 rs2000292 rs10785973 rs11606194 rs1176719

rs13212041 rs11597471

rs1176744

(Tyr129Ser)

rs1176713

(14396A/G)

rs6297 rs2276307 rs1379170

rs6296 rs3782025 rs7126511

rs11568817 rs1185027

rs4140535 rs7942029

rs1213371

Gene TPH2 HTR2A SLC6A4 MAOA HTR2C

rs4570625

(-703G/T) rs4942577 rs1042173 rs3788862 rs498207

rs10784941 rs9567733 rs6354 rs1465107

rs3813929

(-759T/C)

rs4565946 rs7997012 rs2020939 rs1465108

rs518147

(-697G/C)

rs1843809 rs977003 rs2020936 rs909525

rs6318

(Cys23Ser)

rs1386494 rs1923885 rs12150214

rs6323

(T914G) rs4911871


51

Markers

rs1386493 rs1923886 rs4251417 rs979606

rs2171363 rs2296972 rs2020930 rs979605

rs4760816 rs9534495 5-HTTLPR rs2064070

rs6582078 rs1885884 rs6609257

rs4760750 rs9534496

MAOA

VNTR

rs10506645 rs582854

rs12229394 rs582854

rs1352250 rs2770298

rs9325202 rs1002513

rs1487275 rs2770304

rs1386486 rs985933

rs1386485 rs927544

rs1487280 rs4941573

rs1487279 rs1328684

rs1872824 rs2296973

rs9534511

rs6313

(T102C)

rs9534512

rs2149434


52

Table 2. Mean values of NEO-FFI Agreeableness and frequencies of MAOA haplotypes

significant after Nyholt correction.

Haplotype Variants Global

P-Value

Individual

Haplotype

n Frequency Mean

Agreeableness

Score

χ2 p-

value

MAOA_VNTR -

rs3788862 -

rs1465107

1.0 x 10-4

Low activity-A-A

Low activity-G-G

High activity-G-G

137

27

248

0.34

0.06

0.60

34.56

34.70

35.02

1.78

0.47

5.23

0.18

0.50

0.02

MAOA_rs3788862 -

rs14651078 -

rs1465107

5.0 x 10-4

A- A- A

G- G- G

143

289

0.33

0.66

34.52

34.95

1.73

3.93

0.19

0.05


53

Table 3. Mean values of NEO-FFI Conscientiousness and frequencies of MAOA and HTR3A

haplotypes significant after Nyholt correction.

Haplotype Variants Global

P-Value

Individual

Haplotype

n Frequency Mean

Conscientiousness

Score

χ2 p-

value

MAOA_VNTR -

rs3788862 -

rs1465107

2.0 x 10-5

Low activity-A-A

Low activity-G-G

High activity-G-G

137

27

248

0.34

0.06

0.60

34.18

34.52

34.72

2.93

0.30

1.99

0.09

0.58

0.16

HTR3A_rs1176713 -

rs11214800 -

rs1379170

3.0 x 10-4

A-A-G

A-C-A

A-C-G

G-C-A

230

47

74

88

0.52

0.11

0.17

0.20

34.01

35.19

35.25

36.65

5.83

0.08

0.08

10.72

0.02

0.78

0.78

0.001

Tong et al. III. Personality and Problem Gambling

54

CHAPTER 3

3. Association study of NEO-Five Factor Inventory and Problem Gambling




2,


4, Donald P. Schopflocher Ph.D.

5, Nady el-

Guebaly M.D.6, Daniela S.S. Lobo M.D., Ph.D.


1,7


Toronto, ON, Canada








Toronto, ON, Canada

Running title: Personality traits and problem gambling

Ryan Tong III. Personality and Problem Gambling

55

3.1 ABSTRACT

3.1.1 Objective:

Differences in personality traits may predispose individuals to problem gambling. Using the

Five-Factor Model of personality, previous studies found pathological gambling was associated

with high Neuroticism and low Conscientiousness scores. However, these investigations

analyzed pathological gambling and not the subclinical form, PG. We investigate the association

between the NEO-Five Factor Inventory (NEO-FFI) scores with gambling behaviour in a non-

treatment seeking, general population sample and analyze the relationship between PG, age, and

sex.


Gambling behaviour was assessed using the Problem Gambling Severity Index (PGSI) while

personality traits were measured using the NEO-FFI in 302 Caucasian subjects. The sample was

divided into two groups: PG (PGSI ≥1) and NPG (PGSI = 0). The relationship between PG, age,

and sex were analyzed using t-test and χ2

comparisons. The association between the NEO-FFI

personality domain scores and group designation was analyzed using a multivariate general

linear model including age and sex as covariates.

3.1.3 Results:

The PG group was significantly younger and had a greater percentage of males than the NPG

group (p= 0.002 and 0.006 respectively). The PG group had significantly higher Neuroticism and

lower Conscientiousness scores (p= 0.004 and 0.006 respectively) than the NPG group and had a

trend for association with lower Agreeableness scores (p= 0.064).


56

3.1.4 Conclusion:

The results of our study corroborate previous research despite differences in sample make-up and

gambling assessment instruments. Future studies should investigate NEO-PI-R facets in a non-

treatment seeking, general population sample to determine a more specific PG personality

profile.

Keywords: problem gambling; NEO-Five Factor Inventory; Canadian Problem Gambling Index;

personality traits; general population


57

3.2 INTRODUCTION

Pathological gambling, classified by the Diagnostic and Statistical Manual for Mental

Disorders-IV (DSM-IV; American Psychiatric Association, 1994) as an impulse-control

disorder, is characterized by persistent and recurrent maladaptive gambling behaviour (Lesieur

and Rosenthal, 1991). Though the majority of those who gamble do not develop pathological

gambling, the likelihood of developing the disorder is expected to grow in society due to the

increase in gambling accessibility (Petry 2005). Currently, epidemiological studies have

estimated the lifetime prevalence rate of pathological gambling in the general population at 1%-

2% (Raylu and Oei, 2002) and have also shown that young males are more likely to develop

pathological gambling than females (Wallisch 1996).

It has been theorized that differences in personality traits may predispose individuals to

addictive behaviour (Eysenck 1997; Ball 2005). In particular, previous studies investigating the

personality profile of pathological gamblers have found personality traits to be associated with

gambling behaviour. Using the Tridimensional Personality Questionnaire (Cloninger et al.,

1991), a study found that pathological gamblers scored significantly higher than controls in the

novelty seeking dimension. In a longitudinal study, using the Multidimensional Personality

Questionnaire, it was found that personality traits of high negative emotionality and low

constraint predicted future gambling behaviour (Slutske et al., 2005).

The NEO personality questionnaire has also been used to study the relationship between

personality and gambling behaviour. The NEO Five-Factor Inventory (NEO-FFI) is a well-

established instrument that has been successfully used and validated in various psychiatrc

samples, cultures, and populations (Costa and McCrae, 2004). It assesses the personality


58

domains of the Five-Factor model (Neuroticism, Extraversion, Openness to Experience,

Agreeableness, and Conscientiousness) using a five-point Likert scale (ranging from “strongly

disagree” to “strongly agree”). Studies using the NEO personality questionnaire to investigate

the association between pathological gambling and personality trait domains have produced

mostly converging findings (Bagby et al., 2007; MacLaren et al., 2011; Myrseth et al., 2009;

Kaare et al., 2009). They all found that pathological gambling is associated with higher scores in

the Neuroticism domain and lower Conscientiousness scores. However, these studies did not

investigate the subclinical form of pathological gambling, problem gambling, and its association

with personality traits. In a twin study conducted by Slutske et al. (2000), it was found that PG

and pathological gambling represent a continuum of the same phenotype (not etiologically

distinct syndromes) and that they share many of the same risk factors. Thus, it appears that the

risk factors of PG and pathological gambling do not differ qualitatively, but rather,

quantitatively. Theoretically, the same combination of personality traits that may be risk factors

for pathological gambling also play a role in PG, yet this has never previously been studied.

Here, we examined the relationship between personality traits of a healthy, non-treatment

seeking, general population sample and PG. Personality traits were measured using the NEO

Five Factor Inventory (NEO-FFI) while gambling behaviour was assessed using the Problem

Gambling Severity Index (PGSI) of the Canadian Problem Gambling Index (CPGI). The nine-

item PGSI instrument assesses the prevalence of problem gambling and has been found to be a

valid measure of the disorder (Holtgraves 2009). It is considered to be a viable alternative to the

South Oaks Gambling Screen (SOGS: Lesieur and Blume, 1987), one of the most widely used

clinical instruments for studying pathological gambling. In this study, we defined the PG group

as individuals who displayed any indication of problem gambling behaviour and who may have


59

experienced adverse consequences from gambling (PGSI score ≥ 1)(Ferris and Wynne, 2001).

The non-problem gambling group (NPG) consisted of individuals who did not (PGSI score = 0).

Based on previous findings that more severe gambling behaviour is associated with younger age

and the male sex, we hypothesized that the PG group will have a lower mean age and a higher

percentage of males compared to the NPG group. Also, we hypothesized that the PG group

would be associated with higher Neuroticism and lower Conscientiousness domain scores

compared to the NPG group.


60

3.3 METHODS

3.3.1 Subjects

Three hundred and two unrelated and healthy Caucasian participants were selected for

this study (35.4% male; mean age: 48.2 ± 16.4 years) from a sample recruited in Alberta,

Canada. The sample was recruited as part of the Leisure, Lifestyle, and Lifecycle Project (el-

Guebaly et al., 2008). Participants were recruited through various means including television

commercials, posters, advertisements in local newspapers, and a random-digit dialing bank of

rural and urban areas. The research protocol for this study was approved by the local ethics

committees.

3.3.2 Assessment

3.3.3.1 NEO Five-Factor Inventory (NEO-FFI)

Personality traits in our sample were measured using the 60-item, self-report NEO-FFI

(McCrae and Costa, 2004). Scores were collected from each participant for the personality trait

domains Neuroticism, Extraversion, Openness to Experience, Agreeableness, and

Conscientiousness.

3.3.3.2 Problem Gambling Severity Index (PGSI) of the Canadian Problem Gambling Index

(CPGI)

The gambling behaviour of subjects for the past 12 months was assessed using the PGSI

of the CPGI (Ferris and Wynne, 2001). In the current study, the sample was divided into two

gambling behaviour groups: the problem gambling group (PG: PGSI score ≥ 1) and the non-

problem gambling group (NPG: PGSI score = 0).


61

3.3.3.3 Statistical Analysis

We performed a Kruskal-Wallis test to compare the mean age and a chi-square

comparison to compare the sex frequencies between the two gambling behaviour groups. Then,

using a multivariate general linear model regression analysis with age and sex included as

covariates, the mean scores of the five NEO-FFI domains were compared between PG and NPG

groups. The statistical power of the sample was analyzed using G*Power (version 3.1.2; Faul et

al., 2007). Our sample was sufficiently powered (>80%) to detect an effect size of Cohen’s

d=0.37.


62

3.4 RESULTS

There were 77 subjects in the PG group and 225 subjects in the NPG group. For the

comparison of age between the PG and NPG groups, it was found that the PG group was

significantly younger than the NPG group (mean age(SD) = 43.35(17.33) vs. 49.88(15.74)

respectively; p = 0.002). Also, in the comparison of the distribution of sexes between the

gambling behaviour groups, the percentage of males in the PG group was significantly higher

compared to the NPG group (p = 0.006). The demographic information of the sample, as well as

the age and sex comparisons between PG and NPG groups, are summarized in Table 4.

In our sample, between males and females, there were significant differences in NEO-FFI

domain scores (Neuroticism, Extraversion, Openness to Experience, Agreeableness, and

Conscientiousness) (p = 0.0004, 0.727, 0.735, 0.004, and 0.025 respectively). Similarly, age was

also included as a covariate as it had a significant effect on NEO-FFI domain scores (p = 0.0002,

0.075, 0.007, 0.008, and 0.001 respectively). Thus, using a multivariate general linear model

with age and sex included as covariates, the NEO-FFI domain scores were compared between

the PG and NPG groups. The PG group scores were significantly higher in Neuroticism (p =

0.004), lower in Conscientiousness (p = 0.006), and there was a trend towards significance for

lower Agreeableness scores (p = 0.064) compared to the NPG group (Table 5) The significant

results with Neuroticism and Conscientiousness both survived Bonferroni corrections. Based on

Cohen’s criteria of effect size (Cohen 1988), Neuroticism, Conscientiousness, and Agreeableness

have a large effect on gambling behaviour (Table 5).


63

3.5. DISCUSSION

Consistent with our hypothesis, we found that the PG group had a significantly higher

percentage of males compared to the NPG group. The PG group was also significantly younger

than the NPG group. This finding supports epidemiological studies which have found that young

males are at greatest risk for developing pathological gambling (Volberg and Abbott, 1994).

Additionally, it was found that men begin gambling at an earlier age and develop pathological

gambling at a faster rate than women (Ibanez et al., 2003). Thus, our findings are consistent with

previous literature and indicate that young men are most at-risk for developing PG.

In this study, we also found that the PG group scored significantly higher in the NEO-FFI

Neuroticism domain and lower in the Conscientiousness domain compared to the NPG group.

These findings corroborate previous studies that found the same associations between NEO

personality domains and the more severe form of the disorder, pathological gambling (Maclaren

et al., 2010; Bagby et al., 2007; Myrseth et al., 2009; Kaare et al., 2009). The findings are

consistent between the investigations despite the variety of gambling behaviour assessment

instruments used and differences between the samples. Thus, the relationship between PG and

the personality domains, Neuroticism and Conscientiousness, appears to be quite robust.

In the present study, a trend of association between lower scores on the Agreeableness

domain and the PG group was found. The MacLaren et al. (2010) study, which also only used

healthy, non-treatment seeking individuals in their sample, found this association to be

significant. It may be due to the small sample size of this study that we did not have enough

power to detect a significant association between Agreeableness and the PG group.


64

The personality domain of Neuroticism is associated with irrational thinking, negative

affect, and ineffective coping strategies (McCrae and Costa, 1987). In a sample of healthy adults,

Denburg et al. (2009) found that individuals who had higher Neuroticism scores fared poorer on

the Iowa Gambling Task, an established instrument used to measure decision making. Thus,

because of impaired decision making and ability to weigh potential risks and benefits, high

scores in the Neuroticism domain may be a risk factor predisposing individuals to developing

PG. Another theory for the association between higher Neuroticism scores and PG may be that it

is due to the high rate of comorbidity between PG and major depression (Cunningham-Williams

et al., 1998). High scores in the Neuroticism domain have been found to be significantly

associated with major depression in a sample of nonpsychotic, depressed patients and are thought

to be a predisposing factor for major depression (Bagby et al, 1995). It has been theorized that

gambling behaviour emerges as an attempt by individuals to self-treat their negative affective

states such as depression (Blaszczynski and Nower, 2002). Thus, elevated Neuroticism scores

predisposing individuals to major depression may contribute to the association between PG and

Neuroticism. Further research into the association between high Neuroticism and PG is

warranted to resolve these competing theories. However, all together, the results of our study and

previous studies indicate that higher Neuroticism scores may frequently be part of the personality

profile of problem gamblers.

The Conscientiousness domain measures an individual’s ability to organize goal-directed

behaviour and low scores in this domain reflect a lower ability to resist impulses (Costa and

McCrae, 1992). Problem gambling is classified as an impulse control disorder (Lesieur and

Rosenthal, 1991) and the severity of gambling behaviour has been found to be associated with

the degree of impulsivity in pathological gamblers (Blaszcynski et al., 1997). This corroborates


65

our finding and previous studies that PG is associated with lower Conscientiousness (Maclaren et

al., 2010; Bagby et al., 2007; Myrseth et al., 2009; Kaare et al., 2009). Thus, low scores in the

Conscientiousness domain may contribute to PG.

Genetics may be one factor underlying the association between low NEO-FFI

Conscientiousness scores and PG. Twin studies have shown that genetic factors explain a

considerable portion of the variance in the NEO-FFI personality domains (estimated at 41%,

53%, 61%, 41%, and 44% for Neuroticism, Extraversion, Openness to Experience,

Agreableness, and Conscientiousness respectively) and gambling behaviour (estimated at 49%)

(Jang et al., 1996; Xian et al., 2007). Several serotonin (5-HT) genes have been implicated in PG

as the 5-HT neurotransmitter has been found to be dysregulated in pathological gamblers

(Pallanti et al., 2009). Pallanti et al. (2009) measured the growth hormone response to a 5-HT

agonist, an indicator of 5-HT system function, and found that pathological gamblers had a

blunted response compared to controls. The MAOA gene has been investigated for its role in PG.

Studies have shown that the low activity allele and haplotypes of MAOA are associated with

lower Conscientiousness scores and more severe gambling behaviour (Rosenberg et al., 2006;

Perez de Castro, 2002). These findings with serotonergic genes provide a potential biological

mechanism underlying the association between low Conscientiousness scores and PG.

This study has several strengths including the recruitment of a sample of healthy, non-PG

treatment seeking individuals to reduce the effects of selection bias. Previous association studies

used pathological gambling treatment-seeking samples (Myrseth et al., 2009; Kaare et al., 2009)

and their findings may be influenced by selection bias as pathological gamblers seeking

treatment only represent a small minority of the total pathological gambling population

(Cunningham 2005). Additionally, individuals with mental health disorders who seek treatment


66

also have higher Neuroticism and lower Conscientiousness (Goodwin et al., 2002). Thus, the

personality profile generated from these previous studies may not be an accurate representation

of pathological gamblers. Another strength of our study is that we used the NEO-FFI and CPGI

instruments, which are both established measures of personality traits and gambling behaviour

respectively. In future studies, further analysis of the NEO-PI-R domain facets and their

association with gambling behaviour should be completed in order to produce a more specific

personality profile of a problem gambler. Finally, to our knowledge, this is the first study that

investigates the association between personality traits and PG as previous association studies

have focused on pathological gambling (Maclaren et al., 2010; Bagby et al., 2007; Myrseth et al.,

2009; Kaare et al., 2009). The findings of our study indicate that PG and pathological gambling

share common personality risk factors which corroborates the finding of the twin study

conducted by Slutske et al. (2000) who found that PG and pathological gambling represent a

continuum of the same phenotype and the risk factors for both do not differ qualitatively, but

quantitatively.

In summary, the results of this study support previous findings that PG is associated with

higher Neuroticism and lower Conscientiousness. Thus, the personality profile of problem

gambler is an individual who is susceptible to negative affect, a poor decision-maker, and highly

impulsive. Given that 5-HT plays a central role in the regulation of impulsivity and decision-

making (Quednow et al., 2007), the involvement of the 5-HT system is implicated in PG. Thus,

future studies should investigate further details of the role of the 5-HT system in the biological

mechanisms underlying both PG and NEO-FFI personality domains. Understanding these

mechanisms may have important implications on designing more effective strategies for the

treatment of PG.


67

Table 4. Demographic factor comparisons between the PG and NPG groups.

Sample

Groups

N Mean Age

(SD)

χ2 p-value Gender (%

male)

χ2 p-value

PG Group 77 43.35

(17.33)

7.50

0.002

48.1

7.20

0.006

NPG

Group

225 49.88

(15.74)

31.1

Total 302 48.23

(16.41)

35.4


68

Table 5. Comparison of NEO-FFI personality domain scores between PG and NPG with age and

sex included as a covariates in the analysis.

NEO-FFI

Personality

Domains

PG Group

(n = 225)

NPG Group

(n = 77)

R-

squared

F t-score Cohen’s

d

p-

value

Mean SD Mean SD

Neuroticism 17.47 0.86 14.62 0.55 0.106 8.30 3.16 3.95 0.004

Extraversion 29.21 0.74 29.12 0.47 0.009 0.04 1.27 0.149 0.845

Openness 30.24 0.70 30.11 0.45 0.012 0.01 0.49 0.226 0.945

Agreeableness 33.02 0.62 34.49 0.39 0.081 3.46 2.124 -2.911 0.064

Conscientiousness 32.64 0.67 34.88 0.43 0.072 7.71 1.35 -3.663 0.006


69

Figure 1. Mean NEO-FFI domain score comparisons between PG and NPG.

0

5

10

15

20

25

30

35

40

Me

an N

EO-F

FI S

core

s

NEO-FFI Domains

PG

NPG

Tong et al. IV. 5-HT Genes and Problem Gambling

70

CHAPTER 4

4. Investigation of 10 Serotonin Genes in Problem Gambling: Possible Role of MAOA




2,


4, Don P. Schopflocher Ph.D.

5, Nady el-Guebaly

M.D.6, Daniela S.S. Lobo M.D., Ph.D.


1,7


Toronto, ON, Canada








Toronto, ON, Canada

Running title: Serotonergic gene polymorphisms and problem gambling


71

4.1 ABSTRACT

4.1.1 Objective:

Serotonin (5-HT) dysregulation has been implicated in problem gambling, a heritable impulse-

control disorder. However, few investigations have studied the role 5-HT candidate genes play in

PG. We investigated the association between 97 5-HT gene polymorphisms (HTR1B, HTR2A,

HTR2C, HTR3A, HTR3B, HTR6, HTR7, TPH2, MAOA, and SLC6A4) and PG.


The gambling behaviour of 822 Caucasian subjects (50.5% male; mean age: 43.6 ± 14.6 years)

was assessed using the South Oaks Gambling Screen and Problem Gambling Severity Index. The

sample was divided into two gambling behaviour groups: PG (PGSI or SOGS ≥ 1) and non-PG

(PGSI or SOGS = 0). Genetic associations with gambling groups were analyzed (age, sex, and

sampling site included as covariates) using UNPHASED 3.1.3. The Nyholt method was used to

correct for multiple testing.

4.1.3 Results:

There were nominal allele, genotype, and haplotype associations between 5-HT candidate genes

and PG, but none of these findings survived Nyholt corrections. Interestingly, rs6323 and

rs979606 of MAOA were nominally significant across all three analyses. Specifically, the G/G

genotype of rs6323, A/A genotype of rs979606, and A-G-A haplotype (rs909525-rs6323-

rs979606) of MAOA were nominally associated with the PG group.

4.1.4 Conclusion:


72

None of the 5-HT markers analyzed was significant after correction for multiple tests. However,

there were nominally significant results suggesting that the MAOA gene may play a role in PG,

and further investigation will be necessary to confirm this finding. The discovery of genetic

vulnerability factors in PG may aid in identifying high-risk groups for PG so that early measures

can be taken to prevent the disorder. Also, understanding the biological mechanism underlying

PG via genetic means may contribute to the discovery of new, more effective pharmacotherapy.

Keywords: genetics; candidate serotonin genes, problem gambling; gambling behaviour


73

4.2 INTRODUCTION

Pathological gambling is classified as an impulse-control disorder characterized by

persistent and recurrent maladaptive gambling behaviour (Lesieur and Rosenthal, 1991;

American Psychiatric Association, 2000). Problem gambling is considered a less severe form of

pathological gambling where DSM-IV criteria for pathological gambling is not met (Blascynski

and Nower, 2001). Epidemiological studies have estimated the lifetime prevalence rate of

problem gambling and pathological gambling at 2-5% and 1%-2% respectively in the general

population (Abbott and Volberg, 1996; Raylu and Oei, 2002), though these rates are expected to

grow because of the increasing accessibility to gamble (Petry 2005). PG is an etiologically

complex disorder that brings major economic and emotional burdens to patients, their relatives,

and society.

The serotonin (5-HT) neurotransmitter system plays an important role in impulse control

(Quednow et al., 2007), and thus previous studies have theorized that it may be involved in PG

(Petry 2005; Marazzati 2008). 5-HT neurons innervate the prefrontal cortex (PFC), a brain

region vital for decision-making, and 5-HT dysfunction in this area has been shown to impair

reward-related processing (Clarke et al., 2004). This may occur because of the inhibitory action

that 5-HT has on dopaminergic neurons, which are involved in the modulation of motivation and

reward (Kapur and Remington, 1996). Dysregulation of the 5-HT system has been found to be

associated with PG (Moreno et al., 1991) and selective serotonin reuptake inhibitors (SSRIs)

have been used to treat PG. Recent review of PG treatment literature has consistently found that

SSRIs are an effective treatment for PG which help in decreasing gambling urges and severity

(Grant and Kim, 2003).


74

In a twin study by Eisen et al. (1998), it was found that genetic factors explained 35-54%

of the risk for having five or more pathological gambling symptoms. Despite 5-HT’s role in

gambling behaviour and the heritability of PG, only a few investigations have examined the

involvement of 5-HT genes in PG. Specifically, genetic association studies have investigated the

relationship between PG and the serotonin transporter (5HTT or SLC6A4) and MAOA genes.

Pérez de Castro et al. (1999) found an association between the short allele of the 5-HTTLPR and

pathological gambling in males. For the MAOA VNTR polymorphism, Pérez de Castro et al.

(2002) found that the lower activity 3 repeat allele was significantly associated with pathological

gambling. Although preliminary, these findings warrant further investigation of the relationship

between 5-HT gene variants and PG.

Here, in a sample of 822 Caucasian subjects, we investigated the association between

several 5-HT candidate genes and PG, which was assessed using the South Oaks Gambling

Screen (SOGS) (Lesieur and Blume, 1987) and the Problem Gambling Severity Index (PGSI) of

the Canadian Problem Gambling Index (CPGI) (Ferris and Wynne, 2001). The SOGS and PGSI

are two well-established instruments used to assess the severity of gambling behaviour and a

strong correlation has been found between items in these instruments (Ferris and Wynne, 2001).

Due to the role 5-HT plays in gambling behaviour and the heritability of PG, we hypothesized

that there would be significant genetic associations between variants in 5-HT system genes and

PG.


75

4.3. METHODS

4.3.1Subjects

A total of 822 Caucasian subjects (50.5% male; mean age: 43.6 ± 14.6 years) were

recruited from two different sites: a) Alberta, Canada as part of the data collected in the Leisure,

Lifestyle, and Lifecycle Project (el-Guebaly et al., 2008; n= 302) and b) Toronto, Canada (n=

520). In Alberta, subjects were invited to participate in the study through a random digit dialing

bank, television commercials, newspaper advertisements, and posters placed in casinos. In

Ontario, newspaper advertisements were used to recruit subjects. Subjects were classified as

Caucasian if at least three of their grandparents were of European Caucasian descent. Informed

consent was obtained for all subjects and the research protocol was approved by the institutional

ethics committees.

4.3.2 Assessment

The gambling behaviour of subjects from Alberta over the past 12 months was assessed

using the PGSI (Ferris and Wynne, 2001) while subjects from Toronto were measured using the

SOGS (Lesieur and Blume, 1987).

In the current study, the sample was divided based on gambling behaviour. They were

categorized into the problem gambling group (PG: PGSI score ≥ 1 or SOGS≥ 1) and the non-

problem gambling group (NPG: PGSI score = 0 or SOGS= 0). This classification was based on

the findings of a twin study by Slutske et al. (2000) who found that the risk for pathological

gambling was significantly higher for twins of subjects with PG and proposed that there was a

significant genetic difference between individuals who had at least one symptom of PG

compared to those who did not.


76

4.3.3 Genotyping

Genomic DNA was isolated through extraction from blood samples using a standard

high-salt method (Lahiri and Nurnberger, 1991). We genotyped functional single nucleotide

polymorphisms (SNPs) and tag SNPs of ten 5-HT candidate genes which were selected through

pair-wise tagging at an r2 of 0.8 and provided at least 75% gene coverage in Haploview (Version

4.1; Barrett et al., 2005). Many of the 5-HT gene (HTR1B, HTR2A, HTR2C, HTR3A, HTR3B,

HTR6, HTR7, TPH2, MAOA, and SLC6A4) variants analyzed have not previously been

investigated for association with PG, although they were selected based on a well-established 5-

HT hypothesis. We chose these genes for analysis because earlier investigations showed that

these genes contained functional variants influencing synaptic 5-HT concentrations (Drago et al.,

2010; Iceta et al., 2009; Lesch et al., 1996; Sabol et al., 1998; Hotamisligil and Breakefield,

1991) or that they were associated with impulsivity (Brunner and Hen, 1997; Paredes et al.,

2008; Huang et al., 2004).

The 5-HTTLPR polymorphism has been found to be functionally biallelic (Hu et al.,

2006). Therefore, in this study, we grouped the long variant containing the G allele of rs25531

(LG) and the short variant together as one allele group while the long variant containing the A

allele of rs25531 (LA) constituted the other allele group. Similarly, the MAOA VNTR variants

can be categorized into two functional groups (Sabol et al., 1998). We grouped the 3.5 and 4

repeat (high activity) variants into one allele category while the 3 and 5 repeat (low activity)

variants formed the other group. To ensure accuracy, 10% of the total sample was re-genotyped.

The 5-HTTLPR and MAOA VNTR polymorphisms were genotyped using the ABI-3130 Genetic

Analyzer (Applied Biosystems, Inc.) while the remaining SNPs were genotyped on an Illumina

384 SNP platform.


77

Polymorphisms that failed quality control (Hardy-Weinberg equilibrium < 0.05, call

frequency < 0.95, and MAF < 0.01) were excluded and in total, 97 5-HT markers were selected

for analysis and tested for association with PG (Table 7). Hardy-Weinberg equilibrium was

verified using Haploview (Version 4.1; Barrett et al., 2005).

4.3.4 Statistical Analysis

The statistical power of the sample was calculated using Quanto 1.2.4 (Gauderman and

Morrison, 2006). Assuming a minor allele frequency of 0.2 in a sample size of n= 822, we had

>80% power to detect an odds ratio (OR) of 1.30 in an additive genetic model.

We performed a t-test to compare mean age between the PG and control groups. A chi-

square comparison was used to compare the sex and sampling site frequencies between the two

gambling behaviour groups.

The allelic, genotypic, and haplotypic analyses were analyzed using the likelihood ratio

tests through UNPHASED 3.1.3 (Dudbridge, 2003, 2008) with age, sex, and sampling site

included in the analysis as covariates. We used a sliding window size of three markers to define

haplotype blocks. Also, we used the Nyholt method to correct for multiple testing of SNPs which

are in linkage disequilibrium (Nyholt 2004).


78

4.4 RESULTS

There were 444 subjects designated to the PG group and 378 subjects to the NPG group.

Allelic, genotypic, and haplotypic frequencies of 5-HT markers were compared between the PG

and NPG groups to examine the relationship between gambling behaviour and the 5-HT genes.

Using the Nyholt correction for multiple testing, the critical p-value threshold for statistical

significance was set at 9.37 x 10-4

.

4.4.1 Allelic Analysis

We found nominally significant associations between gambling behaviour and HTR2A

and MAOA alleles. The following alleles were significantly associated with the PG group

(puncorrected): the T allele of rs977003 and T allele of rs1923885 of HTR2A (p= 0.027 and 0.043

respectively); and the low activity allele of the MAOA VNTR (p= 0.045), the G allele of

rs3788862 (p= 0.038), the G allele of rs1465107(p= 0.044), the G allele of rs1465108 (p= 0.046),

the G allele of rs6323 (p= 0.006), the A allele of rs979606 (p= 0.007), and the C allele of

rs979605 (p= 0.008). The allelic results for all 5-HT polymorphisms included in the analysis are

summarized in Table 8. The allelic associations did not remain significant after Nyholt’s

correction for multiple testing.

4.4.2 Genotypic Analysis

The HTR1B, HTR7, HTR2A, and MAOA genotypes were nominally associated with

gambling behaviour. Specifically, the following genotypes were significantly associated with the

PG group (puncorrected): the C/C genotype of rs1213371of HTR1B (p= 0.041); the C/T genotype of

rs11599921 of HTR7 (p= 0.024); the G/T genotype of rs977003 and the C/T genotype of

rs985933 of HTR2A (p= 0.007 and 0.005 respectively); and the G/G genotype of rs6323, the A/A


79

genotype of rs979606, and the T/T genotype of rs979605 of MAOA (p= 0.007, 0.007, and 0.008

respectively). The genotypic association results for all the 5-HT polymorphisms included in the

analysis are summarized in Table 9. These nominal associations did not survive Nyholt

correction.

4.4.3 Haplotype Analysis

We found one nominally significant association between gambling behaviour and a

MAOA haplotype that did not remain significant after Nyholt correction. The A-G-A haplotype

(rs909525-rs6323-rs979606) of MAOA was associated with the PG group (p= 0.042). The

haplotype results for all 5-HT polymorphisms included in the analysis are summarized in Table

10.


80

4.5 DISCUSSION

In this study, we investigated the allele, genotype, and haplotype associations between 10

genes in the 5-HT system and PG in a sample of individuals ranging in severity of gambling

behaviour. We examined the 5-HT system given that its dysregulation has been implicated in

various impulse control disorders (Linnoila et al., 1993), including pathological gambling

(Moreno et al., 1991; Pallanti et al., 2009). In a pharmacological study by Pallanti et al. (2009), it

was shown that after administration of a 5-HT agonist, pathological gamblers had a lower growth

hormone response, an indicator of 5-HT system functionality, compared to healthy controls. In

our study, we found nominally significant allelic, genotypic, and haplotypic associations between

gene variants and gambling behaviour. However, these associations did not survive Nyholt

correction for multiple testing. Of interest, several MAOA SNPs were nominally significant

suggesting some gene-wide evidence that MAOA may play a role in gambling behaviour.

MAOA encodes an enzyme that degrades biologically active monoamines in the brain

(Youdim et al., 1972), including 5-HT. Because MAOA regulates 5-HT availability for storage

and release, it has been suggested that the enzyme may affect behaviour (Balciuniene and Jazin,

2001). In support of this, Cases et al. (1995) noted aggressive behaviour in mice deficient in

MAOA. Upon administration of a 5-HT synthesis inhibitor, the behavioural alterations in the

mice were reversed. Also, Brunner et al. (1993) identified a human knockout of the MAOA gene

leading to a deficiency of the enzyme in a large Dutch family. All males in the family with the

deletion of MAOA on their single X chromosome exhibited aggressive and impulsive behaviour

and were mildly mentally retarded. Thus, MAOA appears to play an important role in modifying

behaviour, and in predisposing individuals to neuropsychiatric disorders. However, given that


81

MAOA also catabolizes dopamine and norepinephrine, the relative role of increases in 5-HT

versus these other neurotransmitters remains uncertain in the cause of behavioural disturbances.

Dysregulation of the 5-HT system has been associated with PG which has led to the

theory that MAOA gene variants may play a role in gambling behaviour (Pérez de Castro et al.,

2002). In particular, Pérez de Castro et al. (2002) investigated the association between the

MAOA promoter polymorphism (MAOA VNTR), a variable number tandem repeat

polymorphism in the MAOA gene promoter, and pathological gambling. The polymorphism is

functional as it affects the transcription rate of the enzyme. The 3.5 and 4 repeat variants result in

two to ten times more efficient transcription of the gene compared to the 3 and 5 repeats (Sabol

et al., 1998). Pérez de Castro et al. (2002) found that the lower activity 3 repeat was significantly

associated with pathological gambling. Our study corroborates this finding in a larger sample as

we also found a nominally significant allelic association between the low activity MAOA VNTR

repeat variants and PG indicating that these alleles may influence gambling behaviour.

In our study, we also found nominally significant allelic, genotypic, and haplotypic

associations for the MAOA SNPs rs6323 (T941G) and rs979606 with gambling behaviour.

Specifically, the G (high activity) allele and G/G genotype of rs6323 in a recessive model, and

the A allele and A/A genotype of rs979606 in a dominant model were nominally associated with

the PG group. Previous studies have found rs6323 to be a functional SNP where the T allele is

the low-activity allele producing a 75% reduction in enzyme activity compared to the G allele

(Hotamisligil and Breakefield, 1991). To our knowledge, our study represents the first

investigation of the association between PG and the MAOA SNPs rs6323 and rs979606. It has

previously been shown that both these SNPs are also associated with alcohol dependence

(Parsian 1999; Wang et al., 2011), a disorder highly comorbid with pathological gambling


82

(Lesieur and Blume, 1991). In particular, Parsian (1999) found the same direction of association

with the MAOA SNP rs6323 as our study and showed that the frequency of the mutant G allele

was significantly higher in the alcoholic group of their sample compared to healthy controls. In a

twin study, Slutske et al. (2000) found that PG and alcohol dependence share common genetic

vulnerability factors which could contribute to the understanding of our finding of MAOA SNPs

being associated with PG.

Our study failed to replicate the previous finding of an association study that found a

relationship between the 5-HT transporter gene and PG. Pérez de Castro et al. (1999) analyzed

the functional 5-HTTLPR polymorphism of SLC6A4 and found that the short allele, which has

less transcription factor binding than the long allele, was significantly associated with

pathological gambling in males. However, this study was carried out in a small sample of n=

138. Our study, which had a larger sample size, failed to replicate their significant results and did

not show an increase of the short allele in PG cases.

A particular strength of our study was that we used a relatively ethnically homogenous

sample and in doing so, we reduced the chance of population stratification. To our knowledge,

this investigation is the most comprehensive analysis of the relationship between 5-HT genes and

gambling behaviour.

In conclusion, after Nyholt correction, we found no allelic, genotypic, or haplotypic

association between the 5-HT candidate genes and gambling behaviour. However, we found that

the functional low activity MAOA VNTR repeat variants were nominally associated with the PG

group which corroborates the results of Pérez de Castro et al. (2002). Additionally, the MAOA

SNPs, rs6323 and rs979606, were nominally significant across allelic, genotypic, and haplotypic


83

analyses. Taken together, our findings indicate that MAOA may be involved in PG. The findings

of this study can help elucidate the biological mechanisms that underlie PG and a better

understanding of the neurobiology of the disorder may aid in the development of novel and more

effective therapeutics.


84

Table 7. Serotonin candidate gene markers included in the analysis.

Gene HTR6 HTR1B HTR7 HTR3B HTR3A

Markers

rs4912138 rs9352481

rs11599921 rs10789970 rs10789980

rs6699866 rs9359271 rs7916403 rs3758987 rs2276302

rs9659997 rs2000292 rs10785973 rs11606194 rs1176719

rs13212041 rs11597471

rs1176744

(Tyr129Ser)

rs1176713

(14396A/G)

rs6297 rs2276307 rs1379170

rs6296 rs3782025 rs7126511

rs11568817 rs1185027

rs4140535 rs7942029

rs1213371

Gene TPH2 HTR2A SLC6A4 MAOA HTR2C

rs4570625

(-703G/T) rs4942577 rs1042173 rs3788862 rs498207

rs10784941 rs9567733 rs6354 rs1465107

rs3813929

(-759T/C)

rs4565946 rs7997012 rs2020939 rs1465108

rs518147

(-697G/C)

rs1843809 rs977003 rs2020936 rs909525

rs6318

(Cys23Ser)

rs1386494 rs1923885 rs12150214

rs6323

(T914G) rs4911871


85

Markers

rs1386493 rs1923886 rs4251417 rs979606

rs2171363 rs2296972 rs2020930 rs979605

rs4760816 rs9534495 5-HTTLPR rs2064070

rs6582078 rs1885884 rs6609257

rs4760750 rs9534496

MAOA

VNTR

rs10506645 rs582854

rs12229394 rs582854

rs1352250 rs2770298

rs9325202 rs1002513

rs1487275 rs2770304

rs1386486 rs985933

rs1386485 rs927544

rs1487280 rs4941573

rs1487279 rs1328684

rs1872824 rs2296973

rs9534511

rs6313

(T102C)

rs9534512

rs2149434


86

Table 8. Nominal allelic associations of evaluated 5-HT variants with gambling behaviour.

Gene Variants p-value Likelihood Ratio Chi

Square

Chromosome 13

HTR2A_rs977003

HTR2A_rs1923885

0.027

0.043

4.870

3.734

X Chromosome

MAOA_VNTR

MAOA_rs3788862

MAOA_rs1465107

MAOA_rs1465108

MAOA_rs6323

MAOA_rs979606

MAOA_rs979605

0.045

0.038

0.044

0.046

0.006

0.007

0.008

4.008

4.294

4.068

3.987

7.416

7.341

7.091


87

Table 9. Nominal genotypic association of evaluated 5-HT variants with gambling behaviour


Square

Chromosome 6

HTR1B_rs1213371

0.041

6.408

Chromosome 10

HTR7_rs11599921

0.024

7.465

Chromosome 13

HTR2A_rs985933

0.005

10.641

X Chromosome

MAOA_rs6323

MAOA_rs979606

MAOA_rs979605

0.007

0.007

0.008

9.891

9.852

9.732


88

Table 10. Nominal haplotypic associations of evaluated 5-HT variants with gambling behaviour


Square

X Chromosome

MAOA

rs909525-rs6323-rs979606

0.042

11.522

Ryan Tong V. Discussion

89

CHAPTER 5

5. GENERAL DISCUSSION

As outlined in the previous chapters of this thesis, we have found some intriguing results

in our investigations of the roles of personality and of 5-HT system genes in PG. We discovered

that HTR3A and MAOA haplotypes were associated with the NEO-FFI Agreeableness and

Conscientiousness domains. We showed that the personality profile of our PG group, a mixture

of problem and pathological gamblers, was similar to that of pathological gamblers found in

previous studies, which is characterized by high Neuroticism and low Conscientiousness scores.

We also found some gene-wide evidence that MAOA may be involved in PG. Altogether, our

findings add to the knowledge of the complex relationship between 5-HT genes, personality, and

PG. Our results indicate that MAOA may be an interesting target and focus for future drug

development for PG treatment as we show that it influences personality domains associated with

PG and that it may be associated with PG as well. Also, a better understanding of the biological

mechanism underlying PG and the role personality plays in PG might aid in the development of

effective prevention strategies.

5.1 Summary of Findings and Implications

In the first manuscript, we investigated the association between personality and a

relatively comprehensive set of 97 polymorphisms across 10 5-HT system candidate genes

(HTR1B, HTR2A, HTR2C, HTR3A, HTR3B, HTR6, HTR7, TPH2, MAOA, and SLC6A4).

Personality was assessed using the NEO-FFI, a measure of FFM personality domains. The genes

in this study were selected for analysis because they either encode for 5-HT presynaptic and


90

postsynaptic receptors (Parsons et al., 2004; Myers et al., 2007; Walstab et al., 2008) or for the

transporter and enzymes that regulate 5-HT synaptic concentrations (Drago et al., 2010; Iceta et

al., 2009; Lesch et al., 1996; Sabol et al., 1998). We tested the 5-HT polymorphisms for

association with scores in each of the five personality domains in an adult general population

sample. We found associations in allele, genotype, and haplotype analyses with NEO-FFI

domains that did not survive correction for multiple testing. However, we did find some

significant associations that did survive multiple test correction and they include the following:

the HTR3A haplotypes association with Conscientiousness scores and MAOA haplotypes

association with both Agreeableness and Conscientiousness scores. Specifically, the A-A-G

haplotype for the SNPs rs1176713/ rs11214800/ rs1379170 of HTR3A was significantly

associated with lower Conscientiousness. For MAOA, the A-A-A (rs3788862-rs1465107-

rs146510) haplotype was associated with lower Agreeableness while the low activity-A-A

(MAOA VNTR-rs3788862-rs1465107) haplotype was associated with both lower Agreeableness

and Conscientiousness.

To our knowledge, our study represents the first investigation of HTR3A variants in

NEO-FFI personality domains. The HTR3A receptor is a ligand-gated ion channel (Thompson

and Lummis, 2006) which indirectly affects the release of neurotransmitters (including 5-HT,

dopamine, and norepinephrine) by modifying the action potential of neurons (Maricq et al.,

1991). Thus, polymorphisms of the HTR3A gene which affect synaptic neurotransmitter

concentrations may play a role in individual differences in personality. In terms of our MAOA

findings, our results corroborate the results of Rosenberg et al. (2006) who found MAOA

haplotypes defined by SNPs downstream of the transcription start site were associated with the

Conscientiousness domain. However, this result was not in agreement with previous studies that


91

examined MAOA in which no significant associations were detected (Samochowiec et al., 2004;

Garpenstrand et al., 2002). These divergent findings may result from the fact that Rosenberg et

al. (2006) only found significant associations with rare MAOA haplotypes and also that

Smochowiec et al. (2004) sample was relatively small for genetic studies. Additionally, our study

failed to replicate other findings of previous 5-HT genetic association studies of personality.

Both Greenberg et al. (2000) and Sen et al. (2004) found a robust association between the short

allele variant of the 5-HTTLPR and higher scores in the Neuroticism domain. This difference in

findings may have resulted from the fact that we used the NEO-FFI instrument to assess

personality while Greenberg et al. (2000) and Sen et al. (2004) used the NEO-PI-R which

captures more variance in personality traits. Our study provided a thorough and comprehensive

analysis of 5-HT genes in personality as we investigated allelic, genotypic, and haplotypic

associations while many of the aforementioned studies focused only on allelic and genotypic

associations.

The mixed results between our study and others may arise from a number of different

factors. Firstly, the sample sizes of previous genetic association studies may not have been

adequate to detect small genetic effects. The small sample sizes in these studies may result from

the fact that they were conducted during the initial stages of genetic candidate gene studies in

psychiatry when genotyping costs were high, most studies only investigated a single

polymorphism in each gene, and it was expected that single SNPs would be able to explain a

larger proportion of the variance in psychiatric disorders. For our study, we calculated the power

of the sample and found that we could detect small genetic effects. Secondly, sampling

methodology may have contributed to different findings across the studies. Some of the studies

did not control for ethnicity giving rise to greater sample heterogeneity. Also, the study by


92

Rosenberg et al. (2006) only included males in their sample and thus their finding may not be

replicable in samples that include females as well. Another explanation for the significant results

in our study that were not found in others could be that they were spurious. However, we took

measures to control for this by employing the Nyholt method of correction for multiple testing,

yet our results still remained significant. Replication of our study in a larger sample is required

and the full NEO-PI-R should be employed as the full variance of the personality traits may not

have been captured by the NEO-FFI used in our study. Our study shows that the HTR3A and

MAOA genes may play a role in personality traits. Further investigation of these 5-HT genes in

personality may help uncover the biological mechanisms of normal personality and direct future

genetic research into personality disorders.

In the second manuscript, we analyzed the association between the five personality

domains of the NEO-FFI and PG. There have been a number of previous studies examining

personality traits in pathological gambling using a variety of different personality assessment

instruments. Of these investigations, those using the FFM-based personality measures have

resulted in mostly converging findings (Bagby et al., 2007; Kaare et al., 2009; Myrseth et al.,

2009; MacLaren et al., 2011). They found that pathological gamblers were associated with

higher Neuroticism and lower Conscientiousness scores compared to healthy general population

controls. However, these studies focused on pathological gambling and not its subclinical form,

problem gambling. Previous investigations have suggested that problem and pathological

gambling share similar risk factors (Slutske et al., 2000). Thus, the same personality profile

associated with pathological gambling may also be a risk factor for PG, but there has not been

much research in this area. Therefore, we tested the association between PG and NEO

personality traits. We found that the same personality profile (high Neuroticism and low


93

Conscientiousness) that had previously been found in pathological gambling was significantly

associated with PG. Earlier investigations have shown that individuals seeking treatment for

psychiatric treatment also score high on the Neuroticism and low on the Conscientiousness

domains (Goodwin et al., 2002). However, in our study, because we used a healthy, general

population sample that were not seeking treatment, our findings were not influenced by this

potential confounding factor. For future studies, in order to find a more specific and detailed

personality profile of problem gamblers, the full NEO-PI-R should be applied. Our study

suggests that the problem gamblers are more susceptible to negative affect, poor decision

making, and impulsivity, all aspects that have implicated the involvement of the 5-HT system

(Quednow et al., 2007). Combining one finding of the first manuscript (a significant association

between 5-HT gene variants and Conscientiousness) and the results of this study, which found

that Conscientiousness was part of the personality profile of problem gamblers, strengthens the

rationale for examining the association between 5-HT genes and PG.

In the third manuscript, we investigated the relationship between the 97 polymorphisms

of our 5-HT candidate genes and PG. The rationale for selecting these genes in this study was the

same as in the first manuscript. Additionally, some of these genes in earlier reports by other

investigators were found to be significantly associated with impulsivity (Brunner and Hen, 1997;

Huang et al., 2004; Paredes et al., 2008). We analyzed the relationship between allele, genotype,

and haplotype frequencies and PG in a healthy, general population sample representing a wide

range of gambling severity. We found nominally significant associations with PG, but these

results did not survive Nyholt corrections for multiple testing. However, we did find that the low

activity allele group of the functional VNTR polymorphism of MAOA and several MAOA SNPs

were nominally significant, suggesting some gene-wide evidence that MAOA may be involved in


94

gambling behaviour. Specifically, the G allele and G/G genotype of rs6323, A allele and A/A

genotype of rs979606, and A-G-A haplotype (rs909525-rs6323-rs979606) of the MAOA gene

were nominally associated with the PG group in our study.

To our knowledge, our study is the most comprehensive genetic association analysis of 5-

HT genes in PG thus far, given that it examined a relatively large number of 5-HT genes and a

large number of polymorphisms at each gene. There has not been much research completed in

this area and few hypotheses have been generated; thus, our investigation was largely

exploratory in nature, although based on a well-established 5-HT hypothesis. It has been found

that a decrease in 5-HT plays a role in controlling impulses (Quednow et al., 2007) and as such,

5-HT has been implicated in pathological gambling (Petry 2005; Marazzati 2008). Therefore, our

findings with MAOA are particularly relevant as its gene product is an enzyme which degrades

monoamines, including 5-HT (Youdim et al., 1972). We found that the low activity allele group

of the MAOA VNTR, which decreases the production rate of the enzyme (Sabol et al., 1998), was

nominally associated with greater gambling severity, which corroborated the results of Pérez de

Castro et al. (2002). It is unclear whether it is the enzyme’s effects on 5-HT, other

neurotransmitters, or a combination of the two that underlies this association. Also, our findings

with MAOA SNPs rs6323 (T941G) and rs979606 in PG further strengthen the gene-wide

evidence that MAOA may be involved in gambling behaviour. These associations have not been

studied before and require replication in other samples.

A previous investigation focusing on the functional 5-HTTLPR’s role in pathological

gambling has shown a significant association between the lower expressing allele in males

(Pérez de Castro et al. 1999). Our 5-HTTLPR result was not in agreement with theirs as we

failed to replicate their significant finding. This may be due to the differences between our


95

samples. Pérez de Castro et al. (1999) only found a significant result after selecting for males in

their sample while we investigated the association in our large sample composed of both sexes.

The mixed results between our studies may also arise because of the small sample size used by

Pérez de Castro et al. (1999) making their investigation more prone to false positive results.

Thus, our study has shown some gene-wide evidence that MAOA may be involved in PG.

For future research, more SNPs of the 5-HT genes we selected should be analyzed to provide

better coverage. Hopefully, our findings may help uncover the biological mechanisms that

underlie PG and may help lead future research in the development of more effective and specific

pharmacotherapy.

5.2 Limitations and Considerations

5.2.1 Sample Size

A major concern amongst genetic association studies is having a sufficient sample size to

have enough power to detect relatively small genetic effects in complex disorders, such as PG. In

the analysis of 5-HT genes and personality domains, assuming a minor allele frequency of 20%

and setting the critical p-value α at 0.05, our sample of 302 healthy, general population

individuals had >80% power to detect a genetic effect (β) as low as 2.25 for the Neuroticism

dimension, 1.85 for Extraversion, 1.75 for Openness to experience, 1.60 for Agreeableness, and

1.75 for Conscientiousness in a log-additive model. We used the same sample to test the

association between the personality domains and PG. In that analysis, our sample of 77 problem

gamblers and 225 controls had >80% power to detect an effect size of Cohen’s d= 0.37, which,

according to Cohen’s criteria of effect sizes (Cohen 1988), is between a small and medium

effect. Finally, in our last analysis examining the association between 5-HT genes and PG,


96

assuming a minor allele frequency of 20% and setting the critical p-value α at 0.05, our sample

of 444 problem gamblers and 378 controls had >80% power to detect a genotypic relative risk

for PG as low as 1.30. Thus, the samples used in our studies were of moderate to large sizes for

genetic studies, but only the last study (PG vs. 5-HT genes) was sufficiently powered to detect

small effects (genetic relative risk ~ 1.2-1.5). The sample sizes of the first two studies should be

increased in order to increase the sensitivity to detect smaller effect sizes. This could account for

the limited genetic association findings in the first manuscript. Replication of the investigations

in other samples should be completed in order that meta-analyses could be conducted which

would have more power to detect even small effects.

5.2.2 Retrospective Measures

One key limitation of our studies is that they were retrospective in nature. The

ramification of this is that though correlations were found between the variables analyzed, it was

not possible to determine the cause and effect relationship between them. One possible solution

to better determining causality for the genetic association studies is to design a prospective

longitudinal study as well as animal behaviour investigations. However, prospective longitudinal

studies are very expensive due to long follow-up periods. Also, a large sample must be initially

recruited in order to be sufficiently powered to detect small effect sizes and to account for

subjects who drop out from the study over time. For the behavioural studies, animal models have

been already been designed to measure the FFM personality domains (Gosling and John, 1999)

and gambling behaviour (Zeeb et al., 2009). However, creating a genetically modified animal is

costly and approximating the human biology may not be possible.

5.2.3 Dichotomization


97

For our studies examining PG, we dichotomized our sample into the PG and NPG group

(SOGS or PGSI ≥1 and SOGS or PGSI =0 respectively), though the instruments we used to

assess gambling behaviour would result in continuous scores. There were two reasons why we

chose to dichotomize the sample. First, from a genetics standpoint, it was found that the risk for

problem and pathological gambling was significantly higher for twins of subjects with either of

the disorders (Eisen et al., 1998; Slutske et al., 2000). They concluded that problem gamblers and

pathological gamblers represented a continuum of the same phenotype and may not be

etiologically distinct. Furthermore, they suggested that there was a significant genetic difference

between individuals who had at least one symptom of pathological gamblnig compared to those

that did not. We used these findings to rationalize the dichotomization of our sample into cases

and controls. Second, from a statistics standpoint, we split our sample based on the argument by

Streiner (2002). One of the only scenarios that Streiner (2002) endorsed dichotomizing a sample

was when the variable of interest is not normally distributed and is highly skewed so that even

transforming the variable would not be effective. In our sample from Alberta, most of the

subjects were non-gamblers and only a small proportion had problem gambling symptoms,

which reflects the findings of gambling epidemiological studies of the general population (Raylu

and Oei, 2002). By dichotomizing the sample into cases and controls, the size of the PG group

was sufficient to make statistically meaningful comparisons.

However, by dichotomizing our sample, we lost some useful information by placing

pathological gamblers in the same group as subclinical problem gamblers to form the PG group.

Thus, we assumed that there was minimal difference between these groups. Thus, in our studies,

we could not determine any specific associations with pathological gambling but were limited to

examining relationships with the mixture of problem and pathological gambling. Also, the


98

dichotomization of data leads to higher rates of misclassification error. Because of the degree of

error in all measures, individuals near the cut-off score may have been misclassified as PG or

NPG which would not occur as frequently if we kept the data in continuous format. Finally, the

dichotomization of our sample may have reduced the power of our study as well.

5.2.4 Population Stratification

Population stratification in genetic studies may give rise to spurious associations or mask

true associations. We tried to limit this confounding effect by selecting for only Caucasian

individuals in our samples. We controlled for this to the best of our ability by determining that all

subjects included for analysis had at least three grandparents of Caucasian origin using a self-

report questionnaire. Though this reduces the heterogeneity of the sample, it does not completely

eliminate the population genetic heterogeneity since there is significant heterogeneity present

within Caucasians.

5.2.5 Multiple Testing

We conducted two genetic association studies in which we examined 97 polymorphisms

in ten 5-HT candidate genes. Due to the large number of association tests, a method for

corrections for multiple testing was required in order to control for the possibility of inflated

false-positive rates. There were several methods that were considered including Bonferroni,

permutation, and Nyholt correction. The Bonferroni correction method works by setting a new

critical p-value for all the independent tests in the experiment. The new p-value is calculated by

dividing 0.05 by the number of comparisons. However, one common criticism of this correction

method is that it is too conservative, thus increasing the rate of false negatives. Also, one of the

underlying assumptions of the Bonferroni correction is that the individual tests are independent


99

of each other. This is not the case in our study, nor for many other genetic association

investigations, as the markers we selected are not completely independent of each other due to

some linkage disequilibrium. Thus, we did not use the Bonferroni correction method as it is too

conservative and would not be appropriate for the non-dependent nature of within-gene

association tests.

The permutation approach has also been used in previous studies to correct for multiple

comparisons. This method of correction has distinct advantages. Namely, it determines the new

threshold of significance based on the experimental data from the study. By randomizing the

affected status for case-control samples, a distribution of simulated data is produced which the

experimental results are compared against to determine if findings are still significant.

Unfortunately, permutation testing is time consuming and computationally intensive requiring

computers with very high processing speeds.

Researchers have developed methods to adjust the Bonferroni correction to make it

appropriate for genetic association studies. Nyholt et al. (2004) proposed an approach to derive

the effective number of independent tests in order to account for correlation between SNP

markers (usually across a given gene) and calculate the new critical p-value. We decided to use

this method of multiple comparisons correction as it is relatively straight-forward and takes

linkage disequilibrium between markers into account.

5.3 Future Directions

5.3.1 Gene-gene interaction studies

Based on the effects of 5-HT affecting dopamine (DA) signaling, it has been suggested

that the interaction between 5-HT and DA in the brain may affect impulsivity (Zeeb et al., 2009).


100

Genetic studies have been conducted for several DA candidate genes and significant associations

with pathological gambling have been found in DRD1, DRD2, and DRD4 gene variants

(Comings et al., 1996; Comings et al., 1997; Comings et al., 1999; Perez de Castro et al., 1997;

Lobo et al., 2007). Taking our findings and the results of these previous studies, future

investigations should conduct a gene-gene interaction analysis between 5-HT and DA candidate

genes. Additional interactions should be considered as the understanding of the neurobiology of

gambling advances. Genetic research in this area may provide a better understanding of the

genetic and molecular pathways of PG.

5.3.2 Common Assessment Instruments Between Samples

It would have been preferable if we were able to use the same large sample that was

employed by the third manuscript (n = 822) in the first two manuscripts as this would increase

the power to detect small effects. The third manuscript used the sample consisting of a

combination of the Alberta and Ontario samples while the first two manuscripts only used the

Alberta sample. The reason why the combined sample could not be used in all three manuscripts

was because the NEO-FFI personality questionnaire was only administered in the Alberta

sample. In the future, our studies should be replicated with the Ontario sample included after

those subjects have also completed the NEO-FFI in order to increase power of the studies and

strengthen the results.

The two samples also differed as the SOGS gambling assessment instrument was used in

the Ontario sample while the PGSI was given to the Alberta sample. There have been several

criticisms of the SOGS being used to identify pathological gambling in a general population. It

was designed for a clinical context and when used in a general population setting, there were


101

high rates of type-I error misclassifying individuals as pathological gamblers (Dickerson 1993).

However, this was the only measure of gambling available to us from the Ontario sample. We

recommend for future studies that the PGSI should be completed in the Ontario sample as well in

order to better combine the two samples.

It should be noted that the two samples were collected at different times. The Ontario

sample was collected between the years 2002-2006 while the Alberta sample was collected

between the years 2008-present. Thus, there could be differences between the samples due to

cohort effects, including changes in availability of gambling opportunities (e.g. increase in

internet gambling) over these time periods.

5.3.3 Study Design

In our studies involving personality, the NEO-FFI was used to measure the personality

domains of the FFM. As mentioned earlier, the NEO-FFI may not be sufficient in assessing the

full variance of personality traits. Future studies should employ the full 240-item NEO-PI-R

version in order to examine 5-HT genetic effects in personality facets and determine a more

specific personality profile of PG.

Furthermore, based on the limitations that arise by the dichotomization of our sample

(explained above), we recommend that future studies should repeat our analysis after increasing

the sample size in order to include more problem and pathological gamblers. This would allow

for analysis of gambling behaviour as a continuous variable and more specific relationships

between the factors of gambling behaviour, 5-HT genes, and personality traits could be

elucidated.


102

Finally, we also recommend that prospective longitudinal studies investigating these

same three factors should be completed in order to better approach causality. These studies

would be helpful in providing a better understanding of etiological processes and consequential

effects of PG. Additional insight of etiological risk factors may help in the creation of novel or

more effective therapeutics by targeting specific neurotransmitter systems and the development

of specific preventative measures for PG.

5.4 Concluding Remarks

With the prevalence of PG expected to rise in the future because of increased availability

and access to gambling sources, there is a need for the discovery of biological and environmental

factors associated with PG in order to better understand the neurobiology underlying the

disorder. This research may help aid in the development of novel and more effective

pharmacological therapies. Thus, our study set out to explore the complex relationship between

personality traits, 5-HT gene variants, and PG, an effort which no investigations had previously

attempted. We had strong biological rationale and support from other studies to examine whether

5-HT genes and personality played a role in PG. Through our experiments, we conclude the

following:

1) A significant amount of the variance in the personality domains of the FFM can be

explained by 5-HT gene factors. Specifically, we found that variants of MAOA and

HTR3A were associated with Agreeableness and Conscientiousness scores. We did not

find evidence for HTR1B, HTR2A, HTR2C, HTR3B, HTR6, HTR7, or SLC6A4 being

major factors in personality traits. Future studies should investigate whether MAOA and

HTR3A polymorphisms affect behaviour associated with the Agreeableness and


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Conscientiousness, such as altruism and impulsivity respectively. Also, efforts should be

taken to increase the power of our sample in order to detect smaller genetic effects and

our study should be repeated but with the NEO-PI-R used to assess personality.

2) The personality profile of PG describes an individual with high Neuroticism and low

Conscientiousness scores. This is the same personality profile previous studies found

associated to the clinical form of the disorder, pathological gambling. This implies PGs

are individuals who are more susceptible to negative affect and more impulsive than the

general population. Overall, we found that personality was a factor associated with PG.

3) MAOA gene variants may not only be indirectly involved in PG by playing a role in the

Conscientiousness personality domain previously found to be correlated with PG, but it

may be directly associated with PG. Specifically, we found MAOA SNPs rs6323 and

rs979606 that were nominally associated with PG across all three types of analyses

(allelic, genotypic, and haplotypic). However, these results should be interpreted with

caution as they did not survive Nyholt correction for multiple testing. Overall, our studies

found that MAOA may be involved in PG and in personality domains associated with PG.

Thus, this implicates that MAOA may be an interesting target for pharmacotherapy of PG

and should be the focus of future studies. Also, genetically modified animals should be

used to study the effects of 5-HT genes on gambling behaviour.

Ryan Tong VI. References

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CHAPTER 6

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