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Summer 8-2012
Genetic Associations with Borderline Personality Disorder and Related Traits and Behaviors
Casey Roy Guillot University of Southern Mississippi
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GENETIC ASSOCIATIONS WITH BORDERLINE PERSONALITY
DISORDER AND RELATED TRAITS AND BEHAVIORS
by
Casey Roy Guillot
Abstract of a Dissertation Submitted to the Graduate School of The University of Southern Mississippi in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
August 2012 ABSTRACT
GENETIC ASSOCIATIONS WITH BORDERLINE PERSONALITY
DISORDER AND RELATED TRAITS AND BEHAVIORS
by Casey Roy Guillot
August 2012
Borderline personality disorder (BPD) and related traits and behaviors have been linked to a number of neurotransmitter systems, including serotonin, norepinephrine,
GABA, and dopamine. Because three human single-nucleotide polymorphisms (SNPs),
COMT rs4680, GABRA2 rs279871, and SNCA rs356195, have been linked to the above- mentioned neurotransmitter systems, they may be associated with BPD and related traits and behaviors. The purpose of the current study is to examine associations of COMT rs4680, GABRA2 rs279871, and SNCA rs356195 with both categorical and continuous measures of BPD and with continuous measures of impulse control and self-harm in a nonclinical sample. Healthy volunteers were categorized into genotypic and allelic groups, and then those groups were compared in order to determine if certain genotypes and alleles are associated with specific categorical and continuous outcomes. COMT rs4680 was the only SNP related to both categorically and continuously measured BPD as well as to impulse control and self-harm scores. However, results with COMT rs4680 often were suggestive of heterosis, which presents difficulty in explaining. In regard to the other SNPs, GABRA2 rs279871 was related to BPD, impulse control, and self-harm scores, whereas SNCA rs356195 was only related to the former two. All three SNPs yielded some gender-specific results, which may be explained by gender differences in
ii one or more of the following: COMT activity, steroid hormone and neurosteroid levels, neurosteroid effects, regional brain structure, and DA and alpha-synuclein systems. In conclusion, it appears that COMT, GABRA2, and SNCA may influence the development of BPD and related traits and behaviors.
iii
COPYRIGHT BY
CASEY ROY GUILLOT
2012
The University of Southern Mississippi
GENETIC ASSOCIATIONS WITH BORDERLINE PERSONALITY
DISORDER AND RELATED TRAITS AND BEHAVIORS
by
Casey Roy Guillot
A Dissertation Submitted to the Graduate School of The University of Southern Mississippi in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
Approved:
_Mitchell E. Berman______Director
_Sheree L. Watson______
_Randolph C. Arnau______
_Bradley A. Green______
_Susan A. Siltanen______Dean of the Graduate School
August 2012 ACKNOWLEDGMENTS
I wish to thank my dissertation director, Dr. Mitchell Berman, and my other committee members, Drs. Sheree Watson, Randolph Arnau, and Bradley Green, for their guidance and feedback during this project. I would especially like to thank Dr. Mitchell
Berman for generously supplying the data used in analyses.
This study was supported by funding from the National Institute on Alcohol
Abuse and Alcoholism to Mitchell E. Berman (AA14025).
iv TABLE OF CONTENTS
ABSTRACT ...... ii
ACKNOWLEDGMENTS ...... iv
LIST OF TABLES ...... vi
CHAPTER
I. INTRODUCTION………………………………………………………...1
Genetic Associations with BPD and Related Traits and Behaviors Purpose of the Current Study
II. METHOD ...... 8
Participants Measures Procedure Genotyping Data Analysis
III. RESULTS ...... 17
Genotype Frequencies and Group Demographics COMT Rs4680 GABRA2 Rs279871 SNCA Rs356195
IV. DISCUSSION ...... 59
COMT Rs4680 GABRA2 Rs279871 SNCA Rs356195 Limitations Future Directions Summary
APPENDIXES ...... 79
REFERENCES ...... 88
v LIST OF TABLES
Table
1. Genotype Frequencies and Percent Distributions in the Total Sample ...... 17
2. Demographics for Genotypic Groups in the Total Sample ...... 18
3. Scores for COMT rs4680 Genotypic Groups in the Total Sample ...... 24
4. Scores for COMT rs4680 Allelic Groups in the Total Sample ...... 25
5. Scores for COMT rs4680 Genotypic Groups in Men ...... 27
6. Scores for COMT rs4680 Allelic Groups in Men ...... 28
7. Scores for COMT rs4680 Genotypic Groups in Women ...... 30
8. Scores for COMT rs4680 Allelic Groups in Women ...... 31
9. COMT rs4680 Zygosity by SNAP-2 BPD Clinical/Subclinical Diagnosis (Frequencies)...... 34
10. Scores for GABRA2 rs279871 Genotypic Groups in the Total Sample ...... 37
11. Scores for GABRA2 rs279871 Allelic Groups in the Total Sample ...... 38
12. Scores for GABRA2 rs279871 Genotypic Groups in Men ...... 40
13. Scores for GABRA2 rs279871 Allelic Groups in Men ...... 41
14. Scores for GABRA2 rs279871 Genotypic Groups in Women ...... 43
15. Scores for GABRA2 rs279871 Allelic Groups in Women ...... 44
16. Scores for SNCA rs356195 Genotypic Groups in the Total Sample ...... 50
17. Scores for SNCA rs356195 Allelic Groups in the Total Sample...... 51
18. Scores for SNCA rs356195 Genotypic Groups in Men ...... 52
19. Scores for SNCA rs356195 Allelic Groups in Men...... 53
vi 20. Scores for SNCA rs356195 Genotypic Groups in Women ...... 55
21. Scores for SNCA rs356195 Allelic Groups in Women ...... 56
vii 1
CHAPTER I
INTRODUCTION
According to the revised 4th edition of the Diagnostic and Statistical Manual of
Mental Disorders (DSM-IV-TR) (American Psychiatric Association, 2000), biological relatives of individuals with borderline personality disorder (BPD) are at increased risk of being diagnosed with BPD, and impulsivity and self-harm (including non-suicidal self- injurious behavior and suicidal behavior) are both prominent features of BPD. Looking beyond the DSM-IV-TR, impulsivity has been prospectively associated with suicidal behavior (Mann et al., 2009; Yen et al., 2004) and with poorer long-term outcomes in
BPD patients (Links, Mitton, & Steiner, 1990), and the early emergence of impulsivity is suspected of playing a major role in the development of BPD (Crowell, Beauchaine, &
Linehan, 2009). Furthermore, BPD, impulsivity, non-suicidal self-injury (NSSI), and suicidal behavior all have been shown to be moderately heritable, with heritability estimates typically ranging from about 30% to 60% (Durrett, 2006; Mann et al., 2009), and a recent large-scale twin-family study has indicated that a common genetic factor accounts for a significant portion of the genetic variance in BPD and impulsivity/self- harm (Distel et al., 2010). In summary, BPD, impulsivity, and self-harm are hereditarily influenced and appear to be related both developmentally and genetically.
Notably, a DSM-IV-TR diagnosis of BPD is categorical. In other words, an individual meeting certain DSM-IV-TR criteria is classified as having BPD, whereas an individual not meeting certain DSM-IV-TR criteria is classified as not having BPD. From this perspective, BPD is a dichotomous variable: Each person either has or does not have
BPD at a specific point in time. Alternatively, BPD can be trichotomized, whereby 2 individuals are classified as having a clinical BPD diagnosis (e.g., a DSM-IV-TR diagnosis of BPD), a subclinical BPD diagnosis (i.e., falling one criterion short of a clinical diagnosis of BPD), or no BPD diagnosis, or BPD even can be dichotomized differently, such that individuals are classified as having a clinical/subclinical diagnosis of BPD (i.e., having either a clinical or subclinical diagnosis of BPD) or no diagnosis of
BPD. Regardless if BPD is trichotomized or dichotomized in one way or another, it still remains a categorical variable. Importantly, however, BPD can also be conceptualized dimensionally. In other words, the number of BPD symptoms present in a particular individual can be measured, and then that individual can be classified according to his or her degree of BPD symptoms. From this perspective, BPD is a continuous variable: Each person has a certain level of BPD symptoms at a specific point in time. Thus, BPD can be measured both categorically and continuously.
Although BPD traditionally has been conceptualized as a categorical diagnosis, the dimensional conceptualization of BPD has become increasingly relevant in recent decades. Taxometric analyses have indicated that BPD is optimally measured as a continuous variable (Edens, Marcus, & Ruiz, 2008; Trull, Widiger, & Guthrie, 1990). In nonclinical samples, BPD symptoms have been associated with alcohol and drug use disorders (Trull, Waudby, & Sher, 2004), and BPD features have been shown to predict future alcohol-related problems (Stepp, Trull, & Sher, 2005). Similarly, BPD has been shown to be one of the most commonly diagnosed personality disorders in samples of substance abusers (Grant et al., 2008, 2004; Sutker & Allain, 2001), and a diagnosis of
BPD also has been shown to predict future onsets of substance use disorders (Walter et al., 2009). Given the advantages of measuring BPD continuously instead of categorically 3 and also that symptoms and features of BPD have been related to negative outcomes similar to that of a diagnosis of BPD, it is important to search for genetic associations with BPD measured both categorically and continuously.
Genetic Associations with BPD and Related Traits and Behaviors
BPD and related traits and behaviors have been linked to a number of neurotransmitter systems, including serotonin (5-HT), norepinephrine (NE), gamma- aminobutyric acid (GABA), and dopamine (DA): Serotonergic dysfunction has been associated with BPD, impulsivity, NSSI, and suicidal behavior (Gurvits, Koenigsberg, &
Siever, 2000; Krakowski, 2003; Lester, 1995; Mann, 2002); excessive noradrenergic activity has been implicated in heightened reactivity to stress and has been associated with risk taking, impulsivity, and irritability (Gurvits et al., 2000; Morilak et al., 2005;
Swann, Birnbaum, Jagar, Dougherty, & Moeller, 2005); certain GABA agonists (e.g., valproate and carbamazepine) have been used to improve mood lability and impulsivity in patients with BPD (Gurvits et al., 2000; Siever & Weinstein, 2009); and DA-receptor antagonists (e.g., haloperidol and flupenthixol) have been shown to decrease impulsivity and suicidal behavior in patients with BPD (Friedel, 2004).
Given their relationship with the above-mentioned neurotransmitter systems, the following three human single-nucleotide polymorphisms (SNPs) may be associated with
BPD and related traits and behaviors: (1) COMT rs4680 (catechol-O-methyltransferase gene, reference SNP 4680), also known as COMT Val158Met; (2) GABRA2 rs279871
(gamma-aminobutyric acid A receptor subunit alpha-2 gene, reference SNP 279871); and
(3) SNCA rs356195 (alpha-synuclein gene, reference SNP 356195). To elaborate, catechol-O-methyltransferase (COMT) is an enzyme responsible for the inactivation of 4 catecholamines, including DA and NE, via catalysis of their methylation (Lachman et al.,
1996; Mannisto & Kaakkola, 1999; Weinshilboum, Otterness, & Szumlanski, 1999), and genotypic variation in COMT rs4680 has been shown to affect COMT activity in several organs, including the brain (Chen et al., 2004; Lachman et al., 1996; Mannisto &
Kaakkola, 1999; Weinshilboum et al., 1999). Although GABA-A receptor -2 subunits
(which are encoded by GABRA2) mostly have been related to anxiety (Dixon, Rosahl, &
Stephens, 2008; Lehner et al., 2010; Low et al., 2000), they are distributed in brain regions involved in the regulation of emotion (e.g., prefrontal cortex, amygdala, and hippocampus) (Akbarian et al., 1995; Dixon et al., 2008; Lehner et al., 2010; Low et al.,
2000; Tian, Chen, Cross, & Edenberg, 2005) and therefore may be involved in other emotional responses and emotionally driven behaviors, such as depression
(Vollenweider, Smith, Keist, & Rudolph, 2011) and impulsive actions motivated by negative affective states (Villafuerte et al., 2011). Finally, -synuclein (which is encoded by SNCA) has been shown to affect DA biosynthesis and release (Venda, Cragg,
Buchman, & Wade-Martins, 2010) and may modulate DA, 5-HT, and NE transporter activity (Venda et al., 2010; Wersinger, Jeannotte, & Sidhu, 2006; Wersinger, Rusnak, &
Sidhu, 2006; however, also see Senior et al., 2008).
As stated previously, BPD, impulsivity, and self-harm are all moderately heritable and appear to share genetic influence. In the following subsections, I have provided direct and indirect evidence regarding the association of COMT rs4680, GABRA2 rs279871, and SNCA rs356195 with BPD, impulsivity, and self-harm, although evidence pertaining to the latter two SNPs apparently is completely lacking in some areas at this time.
5
BPD and Symptoms of BPD
Of the three SNPs reviewed here, only COMT rs4680 has been examined in relation to BPD and symptoms of BPD. One study found a relationship between COMT rs4680 and BPD (Tadic et al., 2009), whereas another study failed to find a relationship between COMT rs4680 and symptoms of BPD (Nemoda et al., 2010).
Impulsivity and Impulsivity-Related Traits and Behaviors
Several studies have searched for a relationship between COMT rs4680 and impulsivity or impulsivity-related traits (e.g., novelty seeking and sensation seeking), yielding mixed results (Benjamin et al., 2000; Chen et al., 2011; Colzato, van den
Wildenberg, van der Does, & Hommel, 2010; Demetrovics et al., 2010; Drabant et al.,
2006; Forbes et al., 2009; Golimbet, Alfimova, Gritsenko, & Ebstein, 2007; Hashimoto et al., 2007; Hosak, Libiger, Cizek, Beranek, & Cermakova, 2006; Ishii et al., 2007; Kang,
Song, Namkoong, & Kim, 2010; Kim, Kim, Kim, Lee, & Kim, 2006; Lang, Bajbouj,
Sander, & Gallinat, 2007; Light et al., 2007; Paloyelis, Asherson, Mehta, Faraone, &
Kuntsi, 2010; Reuter & Hennig, 2005; Strobel, Lesch, Jatzke, Paetzold, & Brocke, 2003;
Tsai, Hong, Yu, & Chen, 2004; Zalsman et al., 2008). One study failed to reveal a relationship between GABRA2 rs279871 and novelty seeking (Dick, Agrawal, et al.,
2006); however, CSF GABA levels and cortical GABA concentrations have both been related to impulsivity in humans (Boy et al., 2011; Lee, Petty, & Coccaro, 2009), and
GABA-A agonists have been shown to increase impulsive responding in rodents (Le et al., 2008; Oliver, Ripley, & Stephens, 2009; Thiebot, Le Bihan, Soubrie, & Simon, 1985) and impair inhibitory control in humans (Acheson, Reynolds, Richards, & de Wit, 2006;
Deakin, Aitken, Dowson, Robbins, & Sahakian, 2004; Fillmore, Rush, Kelly, & Hays, 6
2001), which is consistent with the possibility that impulsivity is regulated in part by
GABA-A receptor -2 subunits. Although SNCA rs356195 has not been specifically related to impulsivity or impulsivity-related traits, -synuclein expression in the striatum has been shown to influence stimulant-induced locomotion in rodents (Abeliovich et al.,
2000; Boyer & Dreyer, 2007), which is a behavior associated with impulsive responding in rats (Dellu-Hagedorn, 2006).
Self-Harm
All of the self-harm research involving the currently reviewed SNPs has been conducted in relation to COMT rs4680. Several studies have reported a relationship between COMT rs4680 and suicidal behavior (Baud et al., 2007; Nolan et al., 2000; Ono,
Shirakawa, Nushida, Ueno, & Maeda, 2004; Rujescu, Giegling, Gietl, Hartmann, &
Moller, 2003), but a recent meta-analysis and a simultaneously conducted study both failed to reveal a relationship between COMT rs4680 and suicidal behavior (Calati et al.,
2011). In addition, one study failed to find a relationship between COMT rs4680 and self-harm scores (Silberschmidt & Sponheim, 2008). Although GABRA2 rs279871 has not been specifically related to self-harm, participants administered the benzodiazepine diazepam, a GABA-A agonist (Atack, 2005), have displayed increased self-aggression
(Berman, Jones, & McCloskey, 2005), and personality-disordered individuals with a history of suicide attempts have displayed higher CSF GABA levels than personality- disordered individuals without a history of suicide attempts (Lee et al., 2009).
Purpose of the Current Study
Most of the above-reviewed behavioral genetic studies involved the separate examination of one of the following two outcomes: (1) potential differences in genotypic 7 and allelic frequencies between groups of individuals with and without BPD, or (2) potential differences in mean scores on dimensional measures of BPD or related traits and behaviors between genotypic and allelic groups. The purpose of the current study is to examine associations of COMT rs4680, GABRA2 rs279871, and SNCA rs356195 with both categorical and continuous measures of BPD and also with continuous measures of impulse control and self-harm in a nonclinical sample. Therefore, in the current study healthy volunteers were categorized into genotypic and allelic groups, and then those groups were compared in order to determine if certain genotypes and alleles are associated with specific categorical and continuous outcomes. Because several studies have indicated that COMT and GABRA2 genotypic/allelic group differences in impulsivity or self-harm may be gender-specific (Baud et al., 2007; Chen et al., 2011;
Golimbet et al., 2007; Lang et al., 2007; Nolan et al., 2000; Ono et al., 2004; Villafuerte et al., 2011), separate analyses for men and women were also conducted.
8
CHAPTER II
METHOD
Participants
A total of 222 participants were included in genotype testing. One participant was excluded because of difficulty in genotyping across multiple polymorphisms, and two participants were excluded because of only having genotyping data. In order to limit the potentially confounding effects of population stratification, only participants who self- identified as Caucasian were retained. Of the remaining 145 participants, 5 were excluded because of lacking self-report data, leaving a total sample of 140 (77 male and
63 female) healthy Caucasian volunteers between the ages of 21 and 55 (M = 26.14; SD =
7.75). Participants were recruited from the university and community through fliers, university-based e-mail announcements, and newspaper and online advertisements requesting volunteers for a paid study ($10 per hour) on the effects of alcohol on motor skills. All potential participants were screened by telephone interview and were excluded if they reported that they had previously participated in alcohol-related research, had not experienced alcohol intoxication during the past few years, were currently taking medication with which alcohol should not be consumed, had ever experienced a significant medical problem that was directly attributed to alcohol use, had ever been diagnosed with schizophrenia or bipolar disorder, had experienced a depressive or anxiety disorder in the past six months, had a psychological problem for which they were currently engaged in treatment, or had a significant medical condition (e.g., heart, liver, or kidney problems, diabetes, neurological disorder, or hypertension). Participants were told that on the day of alcohol administration (which is not part of the current study but 9 usually occurred within a few days to a week of it) they would be screened for alcohol and drugs and would not be allowed to proceed if they had alcohol or any recreational drugs in their system. During the phone screen, a cut-off score of nine on the Alcohol
Use Disorders Identification Test (AUDIT) was used to exclude potential problem drinkers (58-92% sensitivity; Barry & Fleming, 1993; Fleming, Barry, & MacDonald,
1991; Kokotailo et al., 2004; Selin, 2006). In order to further limit the presence of problem drinking, non-excluded individuals scoring 7 or higher on the AUDIT (68-94% sensitivity; Barry & Fleming, 1993; Fleming et al., 1991; Kokotailo et al., 2004; Selin,
2006) were also administered the Short Michigan Alcoholism Screening Test (SMAST) and were excluded if they scored 3 or higher (67-100% sensitivity; Nanakorn, Fukuda,
Ogimoto, Tangseree, & Treethiptikhun, 2000; Selzer, Vinokur, & van Rooijen, 1975;
Zung, 1984). Finally, weight and height were recorded for all participants, and participants with a body mass index of 35 or greater (indicative of severe obesity) (World
Health Organization, 2003) were also excluded. The current study used data that was collected as part of a larger research project primarily devoted to the examination of the effects of alcohol on self-aggressive behavior. The overall study was approved by The
University of Southern Mississippi Human Subjects Protection Review Committee.
Measures
Impulse Control Measures
Barratt Impulsiveness Scale, Version 11 (BIS-11). The 30-item BIS-11 was used to measure trait impulsivity (Patton, Stanford, & Barratt, 1995). Items are answered on a
4-point frequency scale (Rarely/Never, Occasionally, Often, Almost Always/Always), and each item response is scored from 1 (indicative of the least impulsive response) to 4 10
(indicative of the most impulsive response). BIS-11 total scores have been shown to be higher in prison inmates in comparison to psychiatric and substance-abuse patients and lower in college undergraduates in comparison to prison inmates and both groups of patients (Patton et al., 1995). In the initial BIS-11 study, Cronbach’s alpha for the total score ranged from .79 to .83 (Patton et al., 1995).
Self-Control Scale (SCS). The SCS was used to measure ability to self-regulate
(Tangney, Baumeister, & Boone, 2004). The instrument consists of 36 items answered on a 5-point scale, with 1 representing not at all like me and 5 representing very much like me. Each item response is scored from 1 (indicative of the least amount of self-control) to
5 (indicative of the greatest amount of self-control). Higher SCS scores have been shown to predict greater emotional stability and less binge eating, alcohol abuse, and self- and other-directed aggression (Tangney et al., 2004). In the initial SCS study, Cronbach’s alpha and test-retest reliability both were .89 (Tangney et al., 2004).
Self-Harm Measures
Life History of Aggression (LHA). The 2-item LHA Self-Directed Aggression subscale was used to assess history of self-aggression (Coccaro, Berman, & Kavoussi,
1997). The first item pertains to past frequency of self-injurious behavior, and the second item pertains to past frequency of suicide attempts. Items are answered on a 6-point scale ranging from 0 (never happened) to 5 (happened so many times I couldn’t give a number). LHA Self-Directed Aggression scores have been shown to be higher in participants diagnosed with BPD in comparison to healthy participants (Coccaro et al.,
1997). In the initial LHA study, Cronbach’s alpha and test-retest reliability for the LHA
Self-Directed Aggression subscale were .48 and .97, respectively (Coccaro et al., 1997). 11
Self-Harm Inventory (SHI). The SHI was developed to assess history of intentional self-harm and to screen for BPD (Sansone, Wiederman, & Sansone, 1998).
The instrument consists of 22 yes/no items, and yes and no responses are scored 1 and 0, respectively, with higher scores representing a more extensive history of intentional self- harm and a greater likelihood of BPD. Cronbach’s alpha for the SHI has ranged from .80 to .90 (Sansone, Butler, Dakroub, & Pole, 2006; Sansone, Reddington, Sky, &
Wiederman, 2007; Sansone, Songer, & Sellbom, 2006).
Measures of BPD, Impulse Control, and Self-Harm
Schedule for Nonadaptive and Adaptive Personality-2 (SNAP-2). The SNAP-2 was used to assess personality traits and personality-disorder symptoms and to diagnose
DSM-IV personality disorders (Clark, Simms, Wu, & Casillas, in press). The SNAP-2 consists of 390 items comprising 12 trait scales, 3 temperament scales, and 12 diagnostic scales. The diagnostic scales can be used to assess personality disorders dimensionally and diagnostically based on number of symptoms and DSM-IV diagnostic criteria met, respectively. The following four SNAP-2 scales were included in the current study:
Borderline, Impulsivity, Disinhibition, and Self-Harm. One of the Self-Harm subscales,
Suicide Proneness, was also included. Items are answered using a true/false format, and item responses are scored 0 or 1, with 1 being indicative of a higher level of a trait or the presence of a personality-disorder symptom and/or diagnostic criterion. In normative samples, Cronbach’s alpha for SNAP-2 Impulsivity, Disinhibition, Self-Harm, and
Suicide Proneness ranged from .74 to .84, and test-retest reliability ranged from .76 to .93
(Clark et al., in press).
12
Procedure
Written informed consent was obtained from participants prior to participation.
All measures were self-report instruments. The SNAP-2 was administered in computerized form (Clark & Simms, 2004). All other measures were administered as online questionnaires.
Blood was collected for genotyping using the following procedure: Latex gloves were placed on both of the researcher’s hands. The participant’s index finger was swabbed with an alcohol swipe on the side opposite the nail in order to reduce the chance of local infection. An automatic fingerstick lancet device was then used to puncture the soft side of the participant’s fingertip, slightly removed from the center. After blood from the participant’s finger had accumulated into a tiny ball (which was eased with slight pressure to the surrounding tissue if necessary), the blood was spotted onto 3MM chromatography paper (Whatman, Inc., Florham Park, NJ) which was located inside a rectangular collection form. This was repeated until three approximately 1.25 cm spots of blood were created on the paper. The collection form was then labeled with the date, the participant’s initials and coded number, and the name of the research assistant who collected the blood sample. The sample was allowed a few minutes to dry before being placed in a small plastic zip bag, which was then placed in a hanging folder inside a metal file cabinet until all samples were ready to be mailed for genotype determination. Gloves, alcohol swipes, and lancets were disposed of in a biohazard container.
Genotyping
Dried blood samples were analyzed at the Alcohol Research Center at Indiana
University. DNA was isolated using the HotSHOT method, which is a fast and cost- 13 effective way to isolate PCR quality genomic DNA (Truett et al., 2000). In this method,
TaqMan probes are used for allelic discrimination (Applied BioSystems, Inc., Foster
City, CA). The allelic discrimination assay is a multiplexed (one primer pair/two probes per reaction), end-point (data is collected at the end of the PCR process) assay. Each assay mix contains two different TaqMan probes labeled with VIC or FAM fluorescent reporter dye which bind preferentially to one of the alleles. The genotype of each sample is determined by the fluorescence levels of the reporter dyes and is clustered on a graph with other samples of the same genotype. Each reaction contains 5 ul of 2X TaqMan
Universal PCR Mastermix, No AmpErase UNG, 3.75 ul of water, 0.25ul of 40X Assay
Mix, and 1ul of DNA sample. Eight or eleven controls are included on each 96-well plate: 2 no template controls, 2 or 3 heterozygous samples, and 2 or 3 of each of the homozygous samples. Because genotyping is done by endpoint reading, thermocycling is carried out in MJ Research PTC-200 thermocyclers. The PCR products are then analyzed in an ABI PRISM® 7300 Sequence Detection System (SDS) instrument. SDS Software
1.3.1 converts the raw data to pure dye components and plots the results of the allelic discrimination on a scatter plot of Allele X versus Allele Y; each genotype appears on the graph as a cluster of points.
Data Analysis
Data analysis was conducted primarily with SPSS Statistics 17.0 for Windows.
Alpha was set at .05 for all analyses unless otherwise noted. The SNAP-2 Borderline scale was analyzed both continuously and categorically, and the remaining continuous measures were grouped conceptually as follows: impulse control (BIS-11, SCS, SNAP-2
Impulsivity, and SNAP-2 Disinhibition) and self-harm (LHA Self-Directed Aggression, 14
SHI, SNAP-2 Self-Harm, and SNAP-2 Suicide Proneness). Two-tailed Fisher’s exact tests were used to evaluate relationships between genotypic/allelic groups and categorical measures (i.e., diagnoses of clinical and clinical/subclinical BPD). For one-way analyses of variance, Levene’s test was used to test for violations of homogeneity of variance.
Although Keppel (1991, p. 127) recommended increasing the power of a similar test of equality of variances (the Brown-Forsythe test) by setting the value of at .25, the sensitivity of Levene’s test has been called into question particularly for small cell sizes
(Lee, Katz, & Restori, 2010; Nordstokke & Zumbo, 2007; Zimmerman, 2004); therefore,
was set at .35 for comparisons involving any cell sizes of less than 15 and at .25 for comparisons involving only cell sizes of 15 or more, thus increasing the power of the test both generally and specifically for small cell sizes. The ANOVA F-test was used to test for group differences on continuous measures when there was no evidence of unequal variances; otherwise, the Welch test was used. For genotypic group comparisons, a post hoc multiple comparisons procedure was employed if the omnibus test was significant or nearly significant: Tukey’s test was used when there was no evidence of unequal variances; otherwise, the Games-Howell test was used. Because multiple comparisons procedures such as Tukey’s test and the Games-Howell test do not require a preliminary test in order to be valid (Myers & Well, 2003, pp. 248-252; Ryan, 1959), the significance or non-significance of the post hoc multiple comparisons procedure overrode that of the omnibus test when there was a discrepancy in significance between the two tests.
Although not as worrisome as the effects of variance heterogeneity, the ANOVA F-test has displayed some sensitivity to non-normality when variances are equal, particularly when group sizes are unequal (Games, 1983; Harwell, Rubinstein, Hayes, & Olds, 1992; 15
Levine & Dunlap, 1982; Milligan, Wong, & Thompson, 1987). Also, the Welch test has displayed sensitivity to departures from normality when variances are unequal (Clinch &
Keselman, 1982; Harwell et al., 1992; Lix, Keselman, & Keselman, 1996). However, non-normality under each of the preceding conditions rarely has been shown to increase the Type I error rate higher than approximately twice the nominal level relative to
ANOVA (Harwell et al., 1992; Levine & Dunlap, 1982; Lix et al., 1996; Milligan et al.,
1987) and the Welch test (Clinch & Keselman, 1982; Harwell et al., 1992; Lix et al.,
1996). Therefore, the Shapiro-Wilk test was used to test for non-normality when an
ANOVA or Welch test was significant or nearly significant at the standard level (p <
.10), and if the Shapiro-Wilk test was significant, then for the corresponding ANOVA or Welch test (and if applicable the subsequent multiple comparisons procedure) was adjusted to .025 in order to correct for potential Type I error inflation due to non- normality (a strategy suggested by Keppel, 1991, p. 97). Given the frequent violations of homogeneity of variance found in behavioral science data sets (Keselman et al., 1998), using the Mann-Whitney and Kruskal-Wallis tests when distributions were non-normal was not desirable because the Type I error rates of such nonparametric tests are often substantially more inflated by concurrent violations of normality and homogeneity of variance in comparison to parametric tests (Cribbie & Keselman, 2003; Zimmerman,
1998, 2003). In order to avoid reduced power for detecting relationships, Bonferroni corrections were not performed, and instead the effect sizes of significant findings were emphasized, which is a practice that has been recommended in whole or in part by a number of researchers (Garamszegi, 2006; Kirk, 2001; Moran, 2003; Nakagawa, 2004;
O’Keefe, 2003; Perneger, 1998; Stoehr, 1999). If SPSS yielded p = .000 for a parametric 16 analysis, then a more precise value for p was computed using the p-value calculator located at http://www.graphpad.com/quickcalcs/pvalue1.cfm (GraphPad Software, 2012).
Cohen’s ds for pairwise comparisons of means were computed using the effect size calculator retrieved from http://mason.gmu.edu/~dwilsonb/downloads/ES_Calculator.xls
(Lipsey & Wilson, 2001). Risk ratios (also known as relative risks) for binary categorical relationships were computed using the 2 x 2 contingency table calculator located at http://faculty.vassar.edu/lowry/odds2x2.html (Lowry, 2012). In regard to allelic group comparisons, each homozygote group was compared to the combined group of heterozygotes and opposing homozygotes (i.e., the combined group of individuals sharing at least one allele) for all SNPs, which is a widely held practice in the literature.
However, the heterozygote group was compared to the combined group of homozygotes only for COMT rs4680 and GABRA2 rs279871 because the homozygote groups were comparable in size for both of those SNPs, whereas for SNCA rs356195 the common homozygote group, CC participants, was about 7 times larger than the rare homozygote group, TT participants; consequently, the mean scores for the combined group of SNCA homozygotes (CC/TT participants) would have been severely biased in the direction of the mean scores for the common homozygotes.
17
CHAPTER III
RESULTS
Genotype Frequencies and Group Demographics
Genotype frequencies and percent distributions for COMT rs4680, GABRA2 rs279871, and SNCA rs356195 in the total sample are shown in Table 1. None of the genotypic frequency distributions deviated significantly from expected Hardy-Weinberg equilibrium, as ascertained with the Hardy-Weinberg equilibrium calculator located at http://www.oege.org/software/hwe-mr-calc.shtml (Rodriguez, Gaunt, & Day, 2009).
Table 1
Genotype Frequencies and Percent Distributions in the Total Sample
Genotype Frequency (%) ______
SNP Genotype 1 Genotype 2 Genotype 3
COMT rs4680 AA AG GG
41 (29.3) 74 (52.9) 25 (17.9)
GABRA2 rs279871 AA AG GG
40 (28.6) 72 (51.4) 28 (20.0)
SNCA rs356195 CC CT TT
78 (55.7) 51 (36.4) 11 (7.9)
18
Demographics for each of the genotypic groups in the total sample are shown in
Table 2. Genotypic groups for each of the three polymorphisms did not differ significantly in respect to gender, age, and years of education.
Table 2
Demographics for Genotypic Groups in the Total Sample
M (SD) ______
SNP Group 1 Group 2 Group 3
COMT rs4680 AA AG GG
Male/Female ratio 28/13 35/39 14/11
Age 27.10 (8.95) 25.97 (7.12) 25.08 (7.61)
Education (years) 16.72 (2.20) 16.44 (2.14) 16.68 (1.46)
GABRA2 rs279871 AA AG GG
Male/Female ratio 27/13 38/34 12/16
Age 26.88 (9.06) 25.34 (6.70) 27.15 (8.30)
Education (years) 17.13 (1.81) 16.28 (2.09) 16.48 (2.14)
19
Table 2 (continued).
M (SD) ______
SNP Group 1 Group 2 Group 3
SNCA rs356195 CC CT TT
Male/Female ratio 44/34 28/23 5/6
Age 26.10 (7.85) 26.74 (8.05) 23.64 (5.39)
Education (years) 16.61 (2.29) 16.51 (1.75) 16.55 (1.51)
COMT Rs4680
SNAP-2 Borderline scale
Although an omnibus Welch test indicated that the differences in Borderline scores between COMT genotypic groups in the total sample were only nearly significant
(adjusted = .025), Welch statistic (2, 61.94) = 3.62, p = .032, 2 = .041, the post hoc
Games-Howell test revealed significantly higher Borderline scores (p = .022, d = .47) in
AG participants (M = 7.96, SD = 5.19) in comparison to AA participants (M = 5.74, SD =
3.44). Moreover, COMT allelic group comparisons revealed significantly lower
Borderline scores (adjusted = .025) in AA participants (M = 5.74, SD = 3.44) relative to
GG/AG participants (M = 7.66, SD = 5.11), Welch statistic (1, 99.28) = 6.42, p = .013, d
= .41, and significantly higher Borderline scores (adjusted = .025) in AG participants
(M = 7.96, 5.19) relative to AA/GG participants (M = 6.14, SD = 4.05), Welch statistic
(1, 134.06) = 5.29, p = .023, d = .39. Analysis by gender failed to reveal any significant 20 differences in Borderline scores between COMT genotypic and allelic groups. To summarize results for COMT thus far, AG participants displayed higher Borderline scores, and AA participants displayed lower Borderline scores.
In regard to the relationship between COMT group membership and BPD diagnosis, a Fisher’s exact test revealed a significant relationship between COMT zygosity and clinical/subclinical BPD in the total sample (p = .038, = .186, RR = 6.81), such that COMT heterozygotes (AG participants) had a greater risk of being diagnosed with clinical/subclinical BPD than COMT homozygotes (AA/GG participants). This relationship was also significant in men (Fisher’s exact test, p = .043, = .254) but not in women (Fisher’s exact test, p = .643, = .105). No other categorical relationships were significant in the total sample or by gender. To summarize results for COMT in relation to the SNAP-2 Borderline scale, AA participants reported less symptoms of BPD, and
COMT heterozygosis was related to dimensionally and diagnostically measured BPD, such that COMT heterozygotes reported more symptoms of BPD and had a greater risk of being diagnosed with clinical/subclinical BPD.
Impulse Control
No significant differences in impulse control were detected between COMT genotypic and allelic groups in the total sample or in men. In women, however, an omnibus Welch test indicated that the differences in SNAP-2 Disinhibition scores between COMT genotypic groups were nearly significant (adjusted = .025), Welch statistic (2, 26.92) = 4.06, p = .029, 2 = .082, and the post hoc Games-Howell test revealed significantly higher SNAP-2 Disinhibition scores (p = .019, d = .72) in AG participants (M = 11.10, SD = 6.72) in comparison to GG participants (M = 6.64, SD = 21
3.70). Also in women, COMT allelic group comparisons revealed significantly lower
SNAP-2 Disinhibition scores (adjusted = .025) in GG participants (M = 6.64, SD =
3.70) relative to AA/AG participants (M = 10.63, SD = 6.22), Welch statistic (1, 24.15) =
7.97, p = .009, d = .68, nearly significantly higher BIS-11 scores in AG participants (M =
67.49, SD = 14.26) relative to AA/GG participants (M = 62.09, SD = 7.08), Welch statistic (1, 58.69) = 3.95, p = .052, d = .45, significantly lower SCS scores (indicative of greater impulsivity) in AG participants (M = 118.44, SD = 20.42) relative to AA/GG participants (M = 131.09, SD = 18.31), F (1, 60) = 5.98, p = .017, d = .64, and significantly higher SNAP-2 Disinhibition scores (adjusted = .025) in AG participants
(M = 11.10, SD = 6.72) relative to AA/GG participants (M = 7.91, SD = 4.01), Welch statistic (1, 59.97) = 5.48, p = .023, d = .54. To summarize results for COMT in regard to impulse control, group differences were found only in women, with female GG participants reporting less impulsivity on one measure and female AG participants reporting greater impulsivity across multiple measures.
Self-Harm
In the total sample, COMT genotype was significantly related (adjusted = .025) to LHA Self-Directed Aggression scores, Welch statistic (2, 74.50) = 7.74, p = .001, 2 =
.037, and SNAP-2 Self-Harm scores, Welch statistic (2, 72.31) = 4.50, p = .014, 2 =
.044, and the post hoc Games-Howell tests revealed significantly higher LHA Self-
Directed Aggression scores (p = .001, d = .51) in AG participants (M = .59, SD = 1.24) in comparison to GG participants (M = .04, SD = .20) and significantly higher SNAP-2 Self-
Harm scores (p = .01, d = .54) in AG participants (M = 1.74, SD = 2.05) in comparison to
GG participants (M = .72, SD = 1.21). COMT allelic group comparisons further revealed 22 significantly lower LHA Self-Directed Aggression scores (adjusted = .025) in GG participants (M = .04, SD = .20) relative to AA/AG participants (M = .50, SD = 1.20),
Welch statistic (1, 133.38) = 14.89, p = .0002, d = .42, significantly lower SNAP-2 Self-
Harm scores (adjusted = .025) in GG participants (M = .72, SD = 1.21) relative to
AA/AG participants (M = 1.58, SD = 1.95), Welch statistic (1, 56.02) = 8.01, p = .006, d
= .47, nearly significantly higher SNAP-2 Self-Harm scores (adjusted = .025) in AG participants (M = 1.74, SD = 2.05) relative to AA/GG participants (M = 1.05, SD = 1.55),
Welch statistic (1, 133.15) = 5.09, p = .026, d = .38, and significantly higher SNAP-2
Suicide Proneness scores (adjusted = .025) in AG participants (M = .86, SD = 1.34) relative to AA/GG participants (M = .43, SD = .86), Welch statistic (1, 125.83) = 5.32, p
= .023, d = .38. To summarize the self-harm results for COMT in the total sample thus far, GG and AG participants displayed lower and higher scores, respectively, across multiple measures.
No significant differences in self-harm were detected between COMT genotypic and allelic groups in women. In men, no significant differences in self-harm were detected between COMT genotypic groups, but COMT allelic group comparisons revealed significantly lower Suicide Proneness scores (adjusted = .025) in AA participants (M = .27, SD = .53) relative to GG/AG participants (M = .82, SD = 1.27),
Welch statistic (1, 70.32) = 6.83, p = .011, d = .51. Thus, COMT group differences in self-harm in the total sample did not appear to be primarily related to either gender, although one gender-specific difference was found in men.
23
COMT rs4680 Results Summary
Of all COMT genotypes, AG was most consistently associated with BPD and related traits and behaviors: COMT heterozygotes displayed higher SNAP-2 Borderline scores, greater risk of being diagnosed with clinical/subclinical BPD, and higher LHA
Self-Directed Aggression, SNAP-2 Self-Harm, and SNAP-2 Suicide Proneness scores. In addition, female heterozygotes displayed lower SCS scores (indicative of greater impulsivity) and higher BIS-11 and SNAP-2 Disinhibition scores. In contrast to heterozygotes, AA participants displayed lower SNAP-2 Borderline scores, and male AA participants displayed lower SNAP-2 Suicide Proneness scores. Also, GG participants displayed lower LHA Self-Directed Aggression and SNAP-2 Self-Harm scores, and female GG participants displayed lower SNAP-2 Disinhibition scores. Mean scores for
COMT genotypic and allelic groups in the total sample and by gender are shown in
Tables 3-8, and frequencies for COMT zygosity by BPD clinical/subclinical diagnosis are shown in Table 9.
24
Table 3
Scores for COMT rs4680 Genotypic Groups in the Total Sample
M (SD) ______
AA AG GG
Measure (n = 41) (n = 74) (n = 25)
SNAP-2 BDLa 5.74 (3.44)* 7.96 (5.19)* 6.76 (4.85)
BIS-11b 62.60 (11.22) 65.35 (12.08) 62.72 (7.91)
SCSb 124.68 (21.49) 121.61 (19.47) 127.04 (18.12)
SNAP-2 IMPa 5.18 (3.58) 5.85 (4.02) 5.36 (3.59)
SNAP-2 DISa 10.13 (5.83) 11.61 (6.08) 9.40 (4.75)
LHA SIBb .33 (1.12) .59 (1.24)** .04 (.20)**
SHIc 1.90 (3.05) 3.03 (3.24) 2.40 (1.98)
SNAP-2 SHa 1.26 (1.72) 1.74 (2.05)* .72 (1.21)*
SNAP-2 SPa .39 (.82) .86 (1.34) .48 (.92)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SIB = Self-Injurious Behavior; SH = Self-Harm; SP = Suicide
Proneness. aThree AA participants failed to complete the SNAP-2. bOne AA participant failed to complete the BIS-11, SCS, and LHA Self-
Injurious Behavior subscale. cOne AA and one AG participant failed to complete the SHI.
*different at p < .05; **different at p < .01
25
Table 4
Scores for COMT rs4680 Allelic Groups in the Total Sample
Measure M (SD) M (SD)
AA GG/AG
(n = 41) (n = 99)
SNAP-2 BDLa 5.74 (3.44)* 7.66 (5.11)*
BIS-11b 62.60 (11.22) 64.69 (11.19)
SCSb 124.68 (21.49) 122.98 (19.19)
SNAP-2 IMPa 5.18 (3.58) 5.73 (3.91)
SNAP-2 DISa 10.13 (5.83) 11.05 (5.83)
LHA SIBb .33 (1.12) .45 (1.10)
SHIc 1.90 (3.05) 2.87 (2.97)
SNAP-2 SHa 1.26 (1.72) 1.48 (1.92)
SNAP-2 SPa .39 (.82) .77 (1.25)
GG AA/AG
(n = 25) (n = 115)
SNAP-2 BDLa 6.76 (4.85) 7.21 (4.77)
BIS-11b 62.72 (7.91) 64.39 (11.81)
SCSb 127.04 (18.12) 122.68 (20.16)
SNAP-2 IMPa 5.36 (3.59) 5.63 (3.87)
SNAP-2 DISa 9.40 (4.75) 11.11 (6.01)
26
Table 4 (continued).
Measure M (SD) M (SD)
GG AA/AG
(n = 25) (n = 115)
LHA SIBb .04 (.20)*** .50 (1.20)***
SHIc 2.40 (1.98) 2.63 (3.21)
SNAP-2 SHa .72 (1.21)** 1.58 (1.95)**
SNAP-2 SPa .48 (.92) .71 (1.21)
AG AA/GG
(n = 74) (n = 66)
SNAP-2 BDLa 7.96 (5.19)* 6.14 (4.05)*
BIS-11b 65.35 (12.08) 62.65 (10.01)
SCSb 121.61 (19.47) 125.58 (20.15)
SNAP-2 IMPa 5.85 (4.02) 5.25 (3.56)
SNAP-2 DISa 11.61 (6.08) 9.84 (5.40)
LHA SIBb .59 (1.24) .22 (.89)
SHIc 3.03 (3.24) 2.09 (2.68)
SNAP-2 SHa 1.74 (2.05)† 1.05 (1.55)†
SNAP-2 SPa .86 (1.34)* .43 (.86)*
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SIB = Self-Injurious Behavior; SH = Self-Harm; SP = Suicide
Proneness.
27
Table 4 (continued).
aThree AA participants failed to complete the SNAP-2. bOne AA participant failed to complete the BIS-11, SCS, and LHA Self-
Injurious Behavior subscale. cOne AA and one AG participant failed to complete the SHI.
†nearly significantly different; *different at p < .05; **different at p < .01; ***different at p < .001
Table 5
Scores for COMT rs4680 Genotypic Groups in Men
M (SD) ______
AA AG GG
Measure (n = 28) (n = 35) (n = 14)
SNAP-2 BDLa 5.65 (3.29) 7.66 (5.44) 8.07 (4.34)
BIS-11 63.04 (12.23) 62.97 (8.65) 62.79 (9.85)
SCS 122.07 (22.49) 125.14 (17.98) 123.57 (17.22)
SNAP-2 IMPa 5.08 (4.01) 5.31 (3.24) 5.93 (3.85)
SNAP-2 DISa 10.62 (6.49) 12.17 (5.33) 11.57 (4.43)
LHA SDA .14 (.53) .40 (1.01) .07 (.27)
SHI 1.64 (2.88) 2.77 (3.27) 2.50 (2.07)
SNAP-2 SHa 1.27 (1.76) 1.69 (2.13) .79 (1.31)
SNAP-2 SPa .27 (.53) .89 (1.32) .64 (1.15)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aTwo male AA participants failed to complete the SNAP-2.
28
Table 6
Scores for COMT rs4680 Allelic Groups in Men
Measure M (SD) M (SD)
AA GG/AG
(n = 28) (n = 49)
SNAP-2 BDLa 5.65 (3.29) 7.78 (5.11)
BIS-11 63.04 (12.23) 62.92 (8.90)
SCS 122.07 (22.49) 124.69 (17.60)
SNAP-2 IMPa 5.08 (4.01) 5.49 (3.40)
SNAP-2 DISa 10.62 (6.49) 12.00 (5.05)
LHA SDA .14 (.53) .31 (.87)
SHI 1.64 (2.88) 2.69 (2.96)
SNAP-2 SHa 1.27 (1.76) 1.43 (1.96)
SNAP-2 SPa .27 (.53)* .82 (1.27)*
GG AA/AG
(n = 14) (n = 63)
SNAP-2 BDLa 8.07 (4.34) 6.80 (4.72)
BIS-11 62.79 (9.85) 63.00 (10.30)
SCS 123.57 (17.22) 123.78 (20.00)
SNAP-2 IMPa 5.93 (3.85) 5.21 (3.56)
SNAP-2 DISa 11.57 (4.43) 11.51 (5.86)
29
Table 6 (continued).
Measure M (SD) M (SD)
GG AA/AG
(n = 14) (n = 63)
LHA SDA .07 (.27) .29 (.83)
SHI 2.50 (2.07) 2.27 (3.13)
SNAP-2 SHa .79 (1.31) 1.51 (1.97)
SNAP-2 SPa .64 (1.15) .62 (1.10)
AG AA/GG
(n = 35) (n = 42)
SNAP-2 BDLa 7.66 (5.44) 6.50 (3.82)
BIS-11 62.97 (8.65) 62.95 (11.37)
SCS 125.14 (17.98) 122.57 (20.68)
SNAP-2 IMPa 5.31 (3.24) 5.38 (3.93)
SNAP-2 DISa 12.17 (5.33) 10.95 (5.81)
LHA SDA .40 (1.01) .12 (.45)
SHI 2.77 (3.27) 1.93 (2.65)
SNAP-2 SHa 1.69 (2.13) 1.10 (1.61)
SNAP-2 SPa .89 (1.32) .40 (.81)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aTwo male AA participants failed to complete the SNAP-2.
30
Table 6 (continued).
*different at p < .05
Table 7
Scores for COMT rs4680 Genotypic Groups in Women
M (SD) ______
AA AG GG
Measure (n = 13) (n = 39) (n = 11)
SNAP-2 BDLa 5.92 (3.90) 8.23 (5.00) 5.09 (5.15)
BIS-11a 61.58 (8.83) 67.49 (14.26) 62.64 (4.88)
SCSa 130.75 (18.41) 118.44 (20.42) 131.45 (19.09)
SNAP-2 IMPa 5.42 (2.54) 6.33 (4.60) 4.64 (3.26)
SNAP-2 DISa 9.08 (4.08) 11.10 (6.72)* 6.64 (3.70)*
LHA SDAa .75 (1.87) .77 (1.40) .00 (.00)
SHIb 2.50 (3.45) 3.26 (3.24) 2.27 (1.95)
SNAP-2 SHa 1.25 (1.71) 1.79 (2.02) .64 (1.12)
SNAP-2 SPa .67 (1.23) .85 (1.37) .27 (.47)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne female AA participant failed to complete the SNAP-2, BIS-11, SCS, and LHA Self-Directed Aggression. bOne female AA participant and one female AG participant failed to complete the SHI.
*different at p < .05
31
Table 8
Scores for COMT rs4680 Allelic Groups in Women
Measure M (SD) M (SD)
AA GG/AG
(n = 13) (n = 50)
SNAP-2 BDLa 5.92 (3.90) 7.54 (5.15)
BIS-11a 61.58 (8.83) 66.42 (12.91)
SCSa 130.75 (18.41) 121.30 (20.68)
SNAP-2 IMPa 5.42 (2.54) 5.96 (4.37)
SNAP-2 DISa 9.08 (4.08) 10.12 (6.42)
LHA SDAa .75 (1.87) .60 (1.28)
SHIb 2.50 (3.45) 3.04 (3.01)
SNAP-2 SHa 1.25 (1.71) 1.54 (1.91)
SNAP-2 SPa .67 (1.23) .72 (1.25)
GG AA/AG
(n = 11) (n = 52)
SNAP-2 BDLa 5.09 (5.15) 7.69 (4.83)
BIS-11a 62.64 (4.88) 66.10 (13.34)
SCSa 131.45 (19.09) 121.33 (20.48)
SNAP-2 IMPa 4.64 (3.26) 6.12 (4.20)
SNAP-2 DISa 6.64 (3.70)** 10.63 (6.22)**
32
Table 8 (continued).
Measure M (SD) M (SD)
GG AA/AG
(n = 11) (n = 52)
LHA SDAa .00 (.00) .76 (1.51)
SHIb 2.27 (1.95) 3.08 (3.27)
SNAP-2 SHa .64 (1.12) 1.67 (1.95)
SNAP-2 SPa .27 (.47) .80 (1.33)
AG AA/GG
(n = 39) (n = 24)
SNAP-2 BDLa 8.23 (5.00) 5.52 (4.45)
BIS-11a 67.49 (14.26)† 62.09 (7.08)†
SCSa 118.44 (20.42)* 131.09 (18.31)*
SNAP-2 IMPa 6.33 (4.60) 5.04 (2.87)
SNAP-2 DISa 11.10 (6.72)* 7.91 (4.01)*
LHA SDAa .77 (1.40) .39 (1.37)
SHIb 3.26 (3.24) 2.39 (2.78)
SNAP-2 SHa 1.79 (2.02) .96 (1.46)
SNAP-2 SPa .85 (1.37) .48 (.95)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness.
33
Table 8 (continued).
aOne female AA participant failed to complete the SNAP-2, BIS-11, SCS, and LHA Self-Directed Aggression. bOne female AA participant and one female AG participant failed to complete the SHI.
†nearly significantly different; *different at p < .05; **different at p < .01
34
Table 9
COMT rs4680 Zygosity by SNAP-2 BPD Clinical/Subclinical Diagnosis (Frequencies)
Total Sample
No diagnosis Diagnosis
66 8 AG
AA/GG 62 1
Relationship between COMT zygosity and diagnosis (p = .038, = .186, OR = 7.52)
Men Women
No diagnosis Diagnosis No diagnosis Diagnosis
AG 31 4 35 4
AA/AG
40 0 22 1
Relationship between COMT Relationship between COMT zygosity and diagnosis zygosity and diagnosis (p = .043, = .254) (p = .643, = .105)
Note. Risk ratios by gender were not included because one of the cell counts for men was equal to zero.
35
GABRA2 Rs279871
SNAP-2 Borderline scale
No significant differences in Borderline scores were detected between GABRA2 genotypic and allelic groups in the total sample or in women. In men, no significant differences in Borderline scores were detected between GABRA2 genotypic groups, but
GABRA2 allelic group comparisons revealed significantly lower Borderline scores
(adjusted = .025) in GG participants (M = 4.50, SD = 3.71) relative to AA/AG participants (M = 7.52, SD = 4.68), Welch statistic (1, 18.39) = 6.13, p = .023, d = .66.
No significant relationships between GABRA2 group membership and BPD diagnosis were found in the total sample or by gender. To summarize results for GABRA2 thus far, male GG participants reported more symptoms of BPD.
Impulse Control
No significant differences in impulse control were detected between GABRA2 genotypic and allelic groups in the total sample or in men. Although an omnibus Welch test indicated that the differences between BIS-11 scores between GABRA2 genotypic groups in women were only nearly significant, Welch statistic (2, 27.79) = 3.29, p = .052,
2 = .076, the post hoc Games-Howell test revealed significantly higher BIS-11 scores (p
= .037, d = .60) in AG participants (M = 68.53, SD = 12.71) in comparison to GG participants (M = 61.87, SD = 5.62). GABRA2 allelic group comparisons in women also revealed significantly higher BIS-11 scores in AG participants (M = 68.53, SD = 12.71) relative to AA/GG participants (M = 61.79, SD = 10.92), F (1, 60) = 4.90, p = .031, d =
.56. To summarize results for GABRA2 in regard to impulse control, group differences 36 were found only in women, with female AG participants reporting greater impulsivity and female GG participants reporting less impulsivity on one measure.
Self-Harm
No significant differences in self-harm were detected between GABRA2 genotypic and allelic groups in the total sample or in women. In men, no significant differences in self-harm were detected between GABRA2 genotypic groups, but
GABRA2 allelic group comparisons revealed significantly lower SHI scores (adjusted
= .025) in GG participants (M = 1.08, SD = 1.31) relative to AA/AG participants (M =
2.54, SD = 3.12), Welch statistic (1, 38.78) = 7.22, p = .011, d = .50, and nearly significantly lower SNAP-2 Suicide Proneness scores (adjusted = .025) in GG participants (M = .25, SD = .45) relative to AA/AG participants (M = .70, SD = 1.17),
Welch statistic (1, 44.3) = 5.17, p = .028, d = .41. To summarize results for GABRA2 in regard to self-harm, male GG participants reported less self-harm across multiple measures.
GABRA2 rs279871 Results Summary
Of all GABRA2 genotypes, GG was most consistently associated with BPD and related traits and behaviors: Male GG participants displayed lower SNAP-2 Borderline,
SHI, and SNAP-2 Suicide Proneness scores, and female GG participants displayed lower
BIS-11 scores. Also, female AG participants displayed higher BIS-11 scores. Notably, all differences between GABRA2 genotypic and allelic groups were gender-specific. Mean scores for GABRA2 genotypic and allelic groups in the total sample and by gender are shown in Tables 10-15.
37
Table 10
Scores for GABRA2 rs279871 Genotypic Groups in the Total Sample
M (SD) ______
AA AG GG
Measure (n = 40) (n = 72) (n = 28)
SNAP-2 BDLa 7.26 (4.78) 7.59 (4.94) 5.79 (4.20)
BIS-11b 62.83 (12.28) 66.00 (10.71) 60.85 (10.15)
SCSb 122.43 (21.35) 122.61 (18.53) 127.30 (21.09)
SNAP-2 IMPa 5.00 (3.33) 6.17 (4.13) 4.89 (3.50)
SNAP-2 DISa 10.67 (5.35) 11.51 (6.04) 9.18 (5.76)
LHA SDAb .23 (.66) .58 (1.32) .26 (.94)
SHIc 2.93 (3.56) 2.72 (2.96) 1.74 (2.11)
SNAP-2 SHa 1.67 (2.11) 1.20 (1.54) 1.64 (2.23)
SNAP-2 SPa .74 (1.16) .59 (1.06) .75 (1.40)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne AA participant and two AG participants failed to complete the SNAP-2. bOne GG participant failed to complete the BIS-11,
SCS, and LHA Self-Directed Aggression. cOne AG and one GG participant failed to complete the SHI.
38
Table 11
Scores for GABRA2 rs279871 Allelic Groups in the Total Sample
Measure M (SD) M (SD)
AA GG/AG
(n = 40) (n = 100)
SNAP-2 BDLa 7.26 (4.78) 7.07 (4.79)
BIS-11b 62.83 (12.28) 64.60 (10.76)
SCSb 122.43 (21.35) 123.89 (19.26)
SNAP-2 IMPa 5.00 (3.33) 5.81 (3.98)
SNAP-2 DISa 10.67 (5.35) 10.85 (6.03)
LHA SDAb .23 (.66) .49 (1.23)
SHIc 2.93 (3.56) 2.45 (2.77)
SNAP-2 SHa 1.67 (2.11) 1.33 (1.76)
SNAP-2 SPa .74 (1.16) .63 (1.16)
GG AA/AG
(n = 28) (n = 112)
SNAP-2 BDLa 5.79 (4.20) 7.47 (4.86)
BIS-11b 60.85 (10.15) 64.87 (11.34)
SCSb 127.30 (21.09) 122.54 (19.49)
SNAP-2 IMPa 4.89 (3.50) 5.75 (3.89)
SNAP-2 DISa 9.18 (5.76) 11.21 (5.79)
39
Table 11 (continued).
Measure M (SD) M (SD)
GG AA/AG
(n = 28) (n = 112)
LHA SDAb .26 (.94) .46 (1.14)
SHIc 1.74 (2.11) 2.79 (3.17)
SNAP-2 SHa 1.64 (2.23) 1.37 (1.77)
SNAP-2 SPa .75 (1.40) .64 (1.09)
AG AA/GG
(n = 72) (n = 68)
SNAP-2 BDLa 7.59 (4.94) 6.64 (4.58)
BIS-11b 66.00 (10.71) 62.03 (11.43)
SCSb 122.61 (18.53) 124.39 (21.22)
SNAP-2 IMPa 6.17 (4.13) 4.96 (3.38)
SNAP-2 DISa 11.51 (6.04) 10.04 (5.53)
LHA SDAb .58 (1.32) .24 (.78)
SHIc 2.72 (2.96) 2.45 (3.09)
SNAP-2 SHa 1.20 (1.54) 1.66 (2.14)
SNAP-2 SPa .59 (1.06) .75 (1.26)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness.
40
Table 11 (continued).
aOne AA participant and two AG participants failed to complete the SNAP-2. bOne GG participant failed to complete the BIS-11,
SCS, and LHA Self-Directed Aggression. cOne AG and one GG participant failed to complete the SHI.
Table 12
Scores for GABRA2 rs279871 Genotypic Groups in Men
M (SD) ______
AA AG GG
Measure (n = 27) (n = 38) (n = 12)
SNAP-2 BDLa 7.31 (4.98) 7.68 (4.52) 4.50 (3.71)
BIS-11 63.37 (10.89) 63.74 (8.05) 59.58 (14.15)
SCS 122.19 (19.00) 123.74 (17.03) 127.25 (27.48)
SNAP-2 IMPa 5.04 (3.19) 5.59 (3.59) 5.25 (4.62)
SNAP-2 DISa 10.77 (5.00) 12.49 (5.65) 10.17 (6.52)
LHA SDA .15 (.46) .39 (1.00) .00 (.00)
SHI 2.96 (3.89) 2.24 (2.45) 1.08 (1.31)
SNAP-2 SHa 1.62 (2.19) 1.16 (1.52) 1.50 (2.24)
SNAP-2 SPa .85 (1.32) .59 (1.07) .25 (.45)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne male AA participant and one male AG participant failed to complete the SNAP-2.
41
Table 13
Scores for GABRA2 rs279871 Allelic Groups in Men
Measure M (SD) M (SD)
AA GG/AG
(n = 27) (n = 50)
SNAP-2 BDLa 7.31 (4.98) 6.90 (4.51)
BIS-11 63.37 (10.89) 62.74 (9.85)
SCS 122.19 (19.00) 124.58 (19.77)
SNAP-2 IMPa 5.04 (3.19) 5.51 (3.82)
SNAP-2 DISa 10.77 (5.00) 11.92 (5.89)
LHA SDA .15 (.46) .30 (.89)
SHI 2.96 (3.89) 1.96 (2.28)
SNAP-2 SHa 1.62 (2.19) 1.24 (1.70)
SNAP-2 SPa .85 (1.32) .51 (.96)
GG AA/AG
(n = 12) (n = 65)
SNAP-2 BDLa 4.50 (3.71)* 7.52 (4.68)*
BIS-11 59.58 (14.15) 63.58 (9.25)
SCS 127.25 (27.48) 123.09 (17.75)
SNAP-2 IMPa 5.25 (4.62) 5.37 (3.42)
SNAP-2 DISa 10.17 (6.52) 11.78 (5.42)
42
Table 13 (continued).
Measure M (SD) M (SD)
GG AA/AG
(n = 12) (n = 65)
LHA SDA .00 (.00) .29 (.82)
SHI 1.08 (1.31)* 2.54 (3.12)*
SNAP-2 SHa 1.50 (2.24) 1.35 (1.82)
SNAP-2 SPa .25 (.45)† .70 (1.17)†
AG AA/GG
(n = 38) (n = 39)
SNAP-2 BDLa 7.68 (4.52) 6.42 (4.75)
BIS-11 63.74 (8.05) 62.21 (11.92)
SCS 123.74 (17.03) 123.74 (21.71)
SNAP-2 IMPa 5.59 (3.59) 5.11 (3.64)
SNAP-2 DISa 12.49 (5.65) 10.58 (5.44)
LHA SDA .39 (1.00) .10 (.38)
SHI 2.24 (2.45) 2.38 (3.41)
SNAP-2 SHa 1.16 (1.52) 1.58 (2.18)
SNAP-2 SPa .59 (1.07) .66 (1.15)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne male AA participant and one male AG participant failed to complete the SNAP-2.
43
Table 13 (continued).
†nearly significantly different; *different at p < .05
Table 14
Scores for GABRA2 rs279871 Genotypic Groups in Women
M (SD) ______
AA AG GG
Measure (n = 13) (n = 34) (n = 16)
SNAP-2 BDLa 7.15 (4.56) 7.48 (5.44) 6.75 (4.41)
BIS-11b 61.69 (15.21) 68.53 (12.71)* 61.87 (5.62)*
SCSb 122.92 (26.42) 121.35 (20.25) 127.33 (15.24)
SNAP-2 IMPa 4.92 (3.73) 6.82 (4.62) 4.63 (2.50)
SNAP-2 DISa 10.46 (6.21) 10.42 (6.36) 8.44 (5.22)
LHA SDAb .38 (.96) .79 (1.59) .47 (1.25)
SHIc 2.85 (2.88) 3.27 (3.40) 2.27 (2.49)
SNAP-2 SHa 1.77 (2.01) 1.24 (1.58) 1.75 (2.30)
SNAP-2 SPa .54 (.78) .58 (1.06) 1.13 (1.75)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne female AG participant failed to complete the SNAP-2. bOne female GG participant failed to complete the BIS-11, SCS, and LHA
Self-Directed Aggression. cOne female AG participant and one female GG participant failed to complete the SHI.
*different at p < .05
44
Table 15
Scores for GABRA2 rs279871 Allelic Groups in Women
Measure M (SD) M (SD)
AA GG/AG
(n = 13) (n = 50)
SNAP-2 BDLa 7.15 (4.56) 7.24 (5.09)
BIS-11b 61.69 (15.21) 66.49 (11.40)
SCSb 122.92 (26.42) 123.18 (18.91)
SNAP-2 IMPa 4.92 (3.73) 6.10 (4.16)
SNAP-2 DISa 10.46 (6.21) 9.78 (6.03)
LHA SDAb .38 (.96) .69 (1.49)
SHIc 2.85 (2.88) 2.96 (3.16)
SNAP-2 SHa 1.77 (2.01) 1.41 (1.84)
SNAP-2 SPa .54 (.78) .76 (1.33)
GG AA/AG
(n = 16) (n = 47)
SNAP-2 BDLa 6.75 (4.41) 7.39 (5.16)
BIS-11b 61.87 (5.62) 66.64 (13.63)
SCSb 127.33 (15.24) 121.79 (21.84)
SNAP-2 IMPa 4.63 (2.50) 6.28 (4.43)
SNAP-2 DISa 8.44 (5.22) 10.43 (6.25)
45
Table 15 (continued).
Measure M (SD) M (SD)
GG AA/AG
(n = 16) (n = 47)
LHA SDAb .47 (1.25) .68 (1.45)
SHIc 2.27 (2.49) 3.15 (3.24)
SNAP-2 SHa 1.75 (2.30) 1.39 (1.71)
SNAP-2 SPa 1.13 (1.75) .57 (.98)
AG AA/GG
(n = 34) (n = 29)
SNAP-2 BDLa 7.48 (5.44) 6.93 (4.40)
BIS-11b 68.53 (12.71)* 61.79 (10.92)*
SCSb 121.35 (20.25) 125.29 (20.88)
SNAP-2 IMPa 6.82 (4.62) 4.76 (3.06)
SNAP-2 DISa 10.42 (6.36) 9.34 (5.67)
LHA SDAb .79 (1.59) .43 (1.10)
SHIc 3.27 (3.40) 2.54 (2.65)
SNAP-2 SHa 1.24 (1.58) 1.76 (2.13)
SNAP-2 SPa .58 (1.06) .86 (1.41)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness.
46
Table 15 (continued).
aOne female AG participant failed to complete the SNAP-2. bOne female GG participant failed to complete the BIS-11, SCS, and LHA
Self-Directed Aggression. cOne female AG participant and one female GG participant failed to complete the SHI.
*different at p < .05
47
SNCA Rs356195
SNAP-2 Borderline scale
No significant differences in Borderline scores were detected between SNCA genotypic and allelic groups in the total sample or in men. In women, an omnibus Welch test indicated that SNCA genotype was significantly related (adjusted = .025) to
Borderline scores, Welch statistic (2, 13.30) = 6.13, p = .013, 2 = .172, but the post hoc
Games-Howell test only revealed nearly significantly higher Borderline scores in TT participants (M = 13.33, SD = 4.59) in comparison to CC participants (M = 6.24, SD =
3.61, p = .026, d = 1.89) and CT participants (M = 7.04, SD = 5.70, p = .045, d = 1.14).
Consistent with previous findings, however, SNCA allelic group comparisons revealed significantly higher Borderline scores (adjusted = .025) in female TT participants (M =
13.33, SD = 4.59) relative to female CC/CT participants (M = 6.57, SD = 4.55), F (1, 60)
= 11.94, p = .001, d = 1.48. No significant relationships between SNCA group membership and BPD diagnosis were found in the total sample or by gender. To summarize results for SNCA thus far, the only significant finding in relation to BPD was in women, with female TT participants reporting more symptoms of BPD.
Impulse Control
In the total sample, no significant differences in impulse control were detected between SNCA genotypic groups, but SNCA allelic group comparisons revealed significantly higher BIS-11 scores in CT/TT participants (M = 66.39, SD = 12.30) relative to CC participants (M = 62.28, SD = 9.97), Welch statistic (1, 114.02) = 4.50, p =
.036, d = .37, significantly lower SCS scores (indicative of greater impulsivity) in CT/TT participants (M = 119.28, SD = 20.11) relative to CC participants (M = 126.74, SD = 48
19.08), F (1, 137) = 5.00, p = .027, d = .38, nearly significantly higher SNAP-2
Impulsivity scores (adjusted = .025) in CT/TT participants (M = 6.38, SD = 4.39) relative to CC participants (M = 4.95, SD = 3.18), Welch statistic (1, 103.68) = 4.55, p =
.035, d = .38, nearly significantly higher SNAP-2 Disinhibition scores (adjusted = .025) in CT/TT participants (M = 11.97, SD = 6.20) relative to CC participants (M = 9.88, SD =
5.38), Welch statistic (1, 117.16) = 4.27, p = .041, d = .36, and nearly significantly higher
BIS-11 scores in TT participants (M = 70.18, SD = 12.97) relative to CC/CT participants
(M = 63.56, SD = 10.94), F (1, 137) = 3.61, p = .060, d = .60. To summarize results for
SNCA in the total sample, CT/TT participants reported greater impulsivity on all impulse control measures, and TT participants reported greater impulsivity on one measure.
In men, no significant differences were detected between SNCA genotypic groups, but SNCA allelic group comparisons revealed significantly lower SCS scores
(indicative of greater impulsivity) in CT/TT participants (M = 117.85, SD = 18.56) relative to CC participants (M = 128.16, SD = 19.05), F (1, 75) = 5.64, p = .020, d = .55.
Similar to men, no significant differences in impulse control were detected between
SNCA genotypic groups in women, but SNCA allelic group comparisons revealed nearly significantly higher BIS-11 scores in CT/TT participants (M = 68.75, SD = 13.55) relative to CC participants (M = 62.79, SD = 10.66), Welch statistic (1, 50.76) = 3.58, p =
.064, d = .50. Thus, SNCA group differences in impulsivity in the total sample did not appear to be primarily related to either gender overall, although differences on certain measures appeared to be more gender-specific.
49
Self-Harm
No significant differences in self-harm were detected across SNCA genotypic and allelic groups in the total sample or by gender.
SNCA rs356195 Results Summary
Although not as clear as with the other two SNPs, a pattern for SNCA did emerge in regard to BPD and related traits and behaviors: Female TT participants displayed higher SNAP-2 Borderline scores, and participants possessing at least one T allele
(CT/TT participants) reported greater impulsivity on all impulse control measures, with some evidence to suggest that possessing two T alleles may confer additional risk of greater impulsivity (higher BIS-11 scores in TT participants). Therefore, T seemed to be a risk allele for SNCA in relation to impulsivity generally and BPD symptoms specifically in women. Mean scores for SNCA genotypic and allelic groups in the total sample and by gender are shown in Tables 16-21.
50
Table 16
Scores for SNCA rs356195 Genotypic Groups in the Total Sample
M (SD) ______
CC CT TT
Measure (n = 78) (n = 51) (n = 11)
SNAP-2 BDLa 6.48 (4.19) 7.68 (5.14) 9.30 (6.45)
BIS-11b 62.28 (9.97) 65.56 (12.13) 70.18 (12.97)
SCSb 126.74 (19.08) 121.04 (18.57) 111.27 (25.52)
SNAP-2 IMPa 4.95 (3.18) 6.46 (4.50) 6.00 (4.03)
SNAP-2 DISa 9.88 (5.38) 11.90 (6.49) 12.30 (4.76)
LHA SDAb .40 (1.14) .38 (1.03) .73 (1.19)
SHIc 2.31 (3.04) 2.94 (3.09) 3.00 (2.49)
SNAP-2 SHa 1.22 (1.69) 1.52 (1.93) 2.50 (2.55)
SNAP-2 SPa .62 (1.06) .62 (1.21) 1.20 (1.55)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne CC, one CT, and one TT participant failed to complete the SNAP-2. bOne CT participant failed to complete the BIS-11, SCS, and LHA Self-Directed Aggression. cTwo CT participants failed to complete the SHI.
51
Table 17
Scores for SNCA rs356195 Allelic Groups in the Total Sample
Measure M (SD) M (SD)
CC CT/TT
(n = 78) (n = 62)
SNAP-2 BDLa 6.48 (4.19) 7.95 (5.35)
BIS-11b 62.28 (9.97)* 66.39 (12.30)*
SCSb 126.74 (19.08)* 119.28 (20.11)*
SNAP-2 IMPa 4.95 (3.18)† 6.38 (4.39)†
SNAP-2 DISa 9.88 (5.38)† 11.97 (6.20)†
LHA SDAb .40 (1.14) .44 (1.06)
SHIc 2.31 (3.04) 2.95 (2.97)
SNAP-2 SHa 1.22 (1.69) 1.68 (2.05)
SNAP-2 SPa .62 (1.06) .72 (1.28)
TT CC/CT
(n = 11) (n = 129)
SNAP-2 BDLa 9.30 (6.45) 6.95 (4.60)
BIS-11b 70.18 (12.97)† 63.56 (10.94)†
SCSb 111.27 (25.52) 124.52 (19.01)
SNAP-2 IMPa 6.00 (4.03) 5.54 (3.81)
SNAP-2 DISa 12.30 (4.76) 10.68 (5.90)
52
Table 17 (continued).
Measure M (SD) M (SD)
TT CC/CT
(n = 11) (n = 129)
LHA SDAb .73 (1.19) .39 (1.10)
SHIc 3.00 (2.49) 2.55 (3.06)
SNAP-2 SHa 2.50 (2.55) 1.34 (1.79)
SNAP-2 SPa 1.20 (1.55) .62 (1.12)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne CC, one CT, and one TT participant failed to complete the SNAP-2. bOne CT participant failed to complete the BIS-11, SCS, and LHA Self-Directed Aggression. cTwo CT participants failed to complete the SHI.
†nearly significantly different; *different at p < .05
Table 18
Scores for SNCA rs356195 Genotypic Groups in Men
M (SD) ______
CC CT TT
Measure (n = 44) (n = 28) (n = 5)
SNAP-2 BDLa 6.66 (4.61) 8.22 (4.64) 3.25 (2.87)
BIS-11 61.89 (9.51) 63.61 (10.03) 68.80 (15.88)
SCS 128.16 (19.05) 118.68 (17.23) 113.20 (26.87)
53
Table 18 (continued).
M (SD) ______
CC CT TT
Measure (n = 44) (n = 28) (n = 5)
SNAP-2 IMPa 4.84 (3.26) 6.33 (4.17) 4.25 (1.71)
SNAP-2 DISa 10.75 (5.67) 12.96 (5.63) 10.25 (2.50)
LHA SDA .23 (.74) .29 (.85) .20 (.45)
SHI 2.16 (3.16) 2.75 (2.84) 1.20 (1.10)
SNAP-2 SHa 1.27 (1.84) 1.59 (2.08) 1.00 (.82)
SNAP-2 SPa .57 (1.02) .70 (1.26) .75 (.96)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne male CT participant and one male TT participant failed to complete the SNAP-2.
Table 19
Scores for SNCA rs356195 Allelic Groups in Men
Measure M (SD) M (SD)
CC CT/TT
(n = 44) (n = 33)
SNAP-2 BDLa 6.66 (4.61) 7.58 (4.73)
BIS-11 61.89 (9.51) 64.39 (10.95)
54
Table 19 (continued).
Measure M (SD) M (SD)
CC CT/TT
(n = 44) (n = 33)
SCS 128.16 (19.05)* 117.85 (18.56)*
SNAP-2 IMPa 4.84 (3.26) 6.06 (3.98)
SNAP-2 DISa 10.75 (5.67) 12.61 (5.38)
LHA SDA .23 (.74) .27 (.80)
SHI 2.16 (3.16) 2.52 (2.69)
SNAP-2 SHa 1.27 (1.84) 1.52 (1.96)
SNAP-2 SPa .57 (1.02) .71 (1.22)
TT CC/CT
(n = 5) (n = 72)
SNAP-2 BDLa 3.25 (2.87) 7.25 (4.65)
BIS-11 68.80 (15.88) 62.56 (9.68)
SCS 113.20 (26.87) 124.47 (18.83)
SNAP-2 IMPa 4.25 (1.71) 5.41 (3.68)
SNAP-2 DISa 10.25 (2.50) 11.59 (5.72)
LHA SDA .20 (.45) .25 (.78)
SHI 1.20 (1.10) 2.39 (3.03)
SNAP-2 SHa 1.00 (.82) 1.39 (1.92)
55
Table 19 (continued).
Measure M (SD) M (SD)
TT CC/CT
(n = 5) (n = 72)
SNAP-2 SPa .75 (.96) .62 (1.11)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne male CT participant and one male TT participant failed to complete the SNAP-2.
*different at p < .05
Table 20
Scores for SNCA rs356195 Genotypic Groups in Women
M (SD) ______
CC CT TT
Measure (n = 34) (n = 23) (n = 6)
SNAP-2 BDLa 6.24 (3.61)† 7.04 (5.70)† 13.33 (4.59)†
BIS-11b 62.79 (10.66) 68.05 (14.22) 71.33 (11.45)
SCSb 124.91 (19.24) 124.05 (20.15) 109.67 (26.79)
SNAP-2 IMPa 5.09 (3.13) 6.61 (4.94) 7.17 (4.83)
SNAP-2 DISa 8.73 (4.80) 10.65 (7.31) 13.67 (5.61)
LHA SDAb .62 (1.50) .50 (1.23) 1.17 (1.47)
56
Table 20 (continued).
M (SD) ______
CC CT TT
Measure (n = 34) (n = 23) (n = 6)
SHIc 2.50 (2.92) 3.19 (3.44) 4.50 (2.35)
SNAP-2 SHa 1.15 (1.50) 1.43 (1.78) 3.50 (2.88)
SNAP-2 SPa .70 (1.13) .52 (1.16) 1.50 (1.87)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. aOne female CC participant failed to complete the SNAP-2. bOne female CT participant failed to complete the BIS-11, SCS, and LHA
Self-Directed Aggression. cTwo female CT participants failed to complete the SHI.
†Scores for female TT participants were nearly significantly higher than those for female CC and CT participants.
Table 21
Scores for SNCA rs356195 Allelic Groups in Women
Measure M (SD) M (SD)
CC CT/TT
(n = 34) (n = 29)
SNAP-2 BDLa 6.24 (3.61) 8.34 (6.00)
BIS-11b 62.79 (10.66)† 68.75 (13.55)†
SCSb 124.91 (19.24) 120.96 (22.01)
SNAP-2 IMPa 5.09 (3.13) 6.72 (4.84)
57
Table 21 (continued).
Measure M (SD) M (SD)
CC CT/TT
(n = 34) (n = 29)
SNAP-2 DISa 8.73 (4.80) 11.28 (7.01)
LHA SDAb .62 (1.50) .64 (1.28)
SHIc 2.50 (2.92) 3.48 (3.24)
SNAP-2 SHa 1.15 (1.50) 1.86 (2.17)
SNAP-2 SPa .70 (1.13) .72 (1.36)
TT CC/CT
(n = 6) (n = 57)
SNAP-2 BDLa 13.33 (4.59)** 6.57 (4.55)**
BIS-11b 71.33 (11.45) 64.86 (12.33)
SCSb 109.67 (26.79) 124.57 (19.42)
SNAP-2 IMPa 7.17 (4.83) 5.71 (4.00)
SNAP-2 DISa 13.67 (5.61) 9.52 (5.98)
LHA SDAb 1.17 (1.47) .57 (1.39)
SHIc 4.50 (2.35) 2.76 (3.12)
SNAP-2 SHa 3.50 (2.88) 1.27 (1.61)
SNAP-2 SPa 1.50 (1.87) .63 (1.14)
Note. BDL = Borderline; IMP = Impulsivity; DIS = Disinhibition; SDA = Self-Directed Aggression; SH = Self-Harm; SP = Suicide
Proneness. 58
Table 21 (continued).
aOne female CC participant failed to complete the SNAP-2. bOne female CT participant failed to complete the BIS-11, SCS, and LHA
Self-Directed Aggression. cTwo female CT participants failed to complete the SHI.
†nearly significantly different; **different at p < .01
59
CHAPTER IV
DISCUSSION
COMT Rs4680
COMT rs4680 was the only SNP related to both categorically and continuously measured BPD: Heterozygotes (AG participants) displayed higher SNAP-2 Borderline scores (d = .39) and were nearly 7 times as likely to be diagnosed with clinical/subclinical
BPD ( = .186, RR = 6.81) relative to homozygotes (AA/GG participants). Although the relationship between COMT zygosity and clinical/subclinical BPD was also significant in men ( = .254) but not in women ( = .105), effect sizes for men and women as well as for the total sample were comparable according to the effect size standards set forth by
Cohen (1988/2009, pp. 223-225), in which = .1 is a “small” effect and = .3 is a
“medium” effect. Additionally, Met homozygotes (AA participants) displayed lower
SNAP-2 Borderline scores than heterozygotes (d = .47) and Val (G) carriers (d = .41).
According to the effect size standards recommended by Cohen (1988/2009, pp. 25-26), d = .2 is a “small” effect; d = .5 is a “medium” effect; and d = .8 is a large effect.
Therefore, all of the above-mentioned effects are rather small, albeit some are almost medium. Contrary to the current study, Tadic et al. (2009) found a higher percentage of
COMT Met/Met (AA) genotype in Caucasian BPD patients compared to healthy participants, and Nemoda et al. (2010) failed to find a relationship between COMT rs4680 and BPD symptoms in a sample of Caucasian psychiatric inpatients or in an ethnically heterogeneous sample of at-risk young adults. It is noteworthy, however, that the current study was the first study to examine the relationship between COMT rs4680 and BPD in an ethnically homogenous nonclinical sample. Thus, differences in study 60 design (i.e., case-control vs. cross-sectional) and sample selection (i.e., psychiatric/at-risk vs. nonclinical and also ethnically heterogeneous vs. ethnically homogeneous) may help to explain why results have been inconsistent across studies.
COMT rs4680 was related to impulse control only in women, which yielded several medium effects: Female Val homozygotes (GG participants) displayed lower
SNAP-2 Disinhibition scores than female heterozygotes (d = .72) and Met (A) carriers
(d = .68), and female heterozygotes also displayed higher BIS-11 (d = .45) and SNAP-2
Disinhibition scores (d = .54) and lower SCS scores (indicative of greater impulsivity; d = .64) than female homozygotes. Most studies that have examined the relationship between COMT rs4680 and impulsivity or impulsivity-related traits have included a measure of novelty seeking, and none of those studies have been entirely consistent with the current results. Eight studies conducted with Caucasian, Asian, or Israeli participants failed to find a relationship between COMT rs4680 and novelty seeking (Benjamin et al.,
2000; Drabant et al., 2006; Hashimoto et al., 2007; Ishii et al., 2007; Kim et al., 2006;
Light et al., 2007; Reuter & Hennig, 2005; Strobel et al., 2003), including those studies which separately analyzed men and women (Ishii et al., 2007; Kim et al., 2006; Reuter &
Hennig, 2005), and four studies found patterns that were inconsistent with the current study, such as Met homozygotes displaying the highest novelty seeking scores
(Demetrovics et al., 2010; Golimbet et al., 2007), Val homozygotes displaying higher novelty seeking scores than heterozygotes (Tsai et al., 2004), and Val homozygotes displaying lower novelty seeking scores than Met homozygotes in men but not in women
(Chen et al., 2011). One study did find that Val homozygotes had lower novelty seeking scores than Met carriers, but the sample size was small (N = 37); and approximately 61 three-fourths of participants were men (Hosak et al., 2006). Similar to studies that have examined the relationship between COMT rs4680 and novelty seeking, one study failed to find a relationship between COMT rs4680 and sensation seeking in Koreans (Kang et al., 2010), and another study conducted with participants of German descent found that female Val homozygotes displayed significantly higher sensation seeking scores than female heterozygotes and female Met homozygotes (Lang et al., 2007). Of greatest relevance to the current study, no previous study has found a relationship between COMT rs4680 and trait impulsivity (Colzato et al., 2010; Forbes et al., 2009; Paloyelis et al.,
2010; Zalsman et al., 2008). However, none of those four studies separately analyzed males and females, and each study had further limitations or differences relative to the current study: Zalsman et al. (2008) administered an earlier version of the Barratt
Impulsiveness Scale to currently depressed patients; Forbes et al. (2009) used a smaller sample (N = 86) that was somewhat ethnically heterogeneous (~90% white); Colzato et al. (2010) administered the Dickman Impulsivity Inventory and only compared Val homozygotes to Met carriers; and Paloyelis et al. (2010) administered the adolescent version of the BIS-11 to a smaller sample (N = 68) of males between the ages of 11 and
20 (M = 15.42). Although the current study was not entirely consistent with any of the past studies that examined the relationship between COMT rs4680 and impulsivity or impulsivity-related traits, the current study was the first study to examine the relationship between COMT rs4680 and impulsivity in women. Thus, past studies that have searched for a relationship between COMT rs4680 and impulsivity may have been precluded from obtaining significant results because of their use of mixed-gender or male samples.
Notably, the Val/Val genotype has been associated with higher levels of COMT activity, 62 which presumably leads to greater inactivation of DA and NE in the brain (Chen et al.,
2004; Lachman et al., 1996; Matsumoto et al., 2003). Consistent with female Val homozygotes displaying lower SNAP-2 Disinhibition scores in the current study, substances that increase DA or NE activity have been shown to increase impulsivity in patients with Parkinson’s disease and in healthy participants, respectively (Cools, Barker,
Sahakian, & Robbins, 2003; Swann et al., 2005).
COMT rs4680 was related to self-harm in the total sample and in men, which yielded several small-to-medium effects: COMT Val homozygotes displayed lower LHA
Self-Directed Aggression (d = .51) and SNAP-2 Self-Harm scores (d = .54) than heterozygotes and also lower LHA Self-Directed Aggression (d = .42) and SNAP-2 Self-
Harm scores (d = .47) than Met carriers, and heterozygotes further displayed higher
SNAP-2 Self-Harm (d = .38) and SNAP-2 Suicide Proneness scores (d = .38) than homozygotes. In addition, male Met homozygotes displayed lower Suicide Proneness scores (d = .51) than male Val carriers. Contrary to the current study, a recent meta- analysis (which included ten studies) and a simultaneously conducted study both failed to reveal a relationship between COMT rs4680 and suicidal behavior (Calati et al., 2011), and two other studies also were inconsistent with the current study: Massat et al. (2005) found a higher percentage of Val/Val genotype in bipolar disorder patients with a history of suicide attempt compared to patients who had never attempted suicide, and
Silberschmidt and Sponheim (2008) failed to find a relationship between COMT rs4680 and self-harm scores. However, all thirteen previous studies used samples of psychiatric patients or participants likely having a current psychiatric disorder (Baud et al., 2007; De
Luca et al., 2006; De Luca, Tharmalingam, Sicard, & Kennedy, 2005; Liou, Tsai, Hong, 63
Wang, & Lai, 2001; Nolan et al., 2000; Ohara, Nagai, Suzuki, & Ohara, 1998; Ono et al.,
2004; Rujescu et al., 2003; Russ, Lachman, Kashdan, Saito, & Bajmakovic-Kacila, 2000;
Zalsman et al., 2008). Although Ono et al. (2004) did not provide information concerning the psychiatric status of their participants, it can be safely assumed that the large majority of suicide completers in their study also had a psychiatric disorder given that past research has indicated that approximately 90% of suicide completers had a psychiatric disorder at the time of suicide (Mann, 2002). Furthermore, only three of the thirteen previous studies (Russ et al., 2000; Silberschmidt & Sponheim, 2008; Zalsman et al.,
2008) administered a continuous measure of self-harm or suicidal ideation instead of or in addition to ascertaining categorically-defined history of suicidal behavior (i.e., suicide or attempted suicide). In contrast to previous studies, in the current study healthy volunteers were administered a number of continuous self-harm measures representative of both suicidal behavior and less extreme forms of self-harm. For example, the LHA
Self-Directed Aggression subscale consists of two items pertaining to frequency of past self-injurious behavior and suicide attempts; the SHI consists of 22 items pertaining to history of intentional self-harm, including suicidal and self-injurious behavior as well as self-destructive thoughts and behaviors; the SNAP-2 Self-Harm scale consists of 16 items pertaining to poor self-esteem, pessimistic thoughts, history of suicidal and self-injurious behavior, and thoughts of suicide and self-injury; and lastly the SNAP-2 Suicide
Proneness subscale consists of 9 items pertaining to thoughts of suicide and self-injury and history of suicidal and self-injurious behavior (i.e., the SNAP-2 Self-Harm scale minus the items related to poor self-esteem and pessimistic thoughts). Therefore, differences in sample selection (i.e., clinical vs. nonclinical) and sensitivity of self-harm 64 measurement (i.e., measurement of suicidal behavior vs. continuous measurement of a wider range of self-harm) may help to explain the inconsistency across studies.
Although COMT is involved in the inactivation of DA and NE, COMT activity in the brain has mostly been related to its ability to modulate DA neurotransmission in the prefrontal cortex (Matsumoto et al., 2003), and genotypic variation in COMT rs4680 has been shown to influence COMT activity in the human brain, with Val homozygotes displaying greater COMT activity in the dorsolateral prefrontal cortex (DLPFC) than heterozygotes and Met homozygotes (Chen et al., 2004). Thus, in regard to the current findings in which Val homozygotes scored lower than heterozygotes or Met carriers, those findings may be explained (at least in part) by differences in DA neurotransmission in the DLPFC resulting from genotypically driven variation in COMT activity.
Importantly, however, COMT activity may also indirectly affect the tonic and phasic release of DA in subcortical regions as a consequence of its aforementioned modulatory effect on cortical DA neurotransmission (Bilder, Volavka, Lachman, & Grace, 2004).
Furthermore, COMT activity across various regions of the human brain as a function of
COMT genotype has not been studied, and prior research involving other tissues (e.g., blood and liver) evidenced greater genotypically driven variation in COMT activity than that observed in the DLPFC, with distinctly low, medium, and high levels of COMT activity among Met/Met, Val/Met, and Val/Val genotypes, respectively (Lachman et al.,
1996). Therefore, a number of the current findings (including those in which Met homozygotes scored lower than heterozygotes or Val carriers) may be explained by differences in DA neurotransmission in some other brain region besides the DLPFC 65
(perhaps even in another prefrontal region) as a result of genotypically driven variation in
COMT activity.
Gender-specific results with COMT rs4680 may be explained by gender differences in COMT activity and dopaminergic function, both of which may be a consequence of the effects of estrogen. Men have displayed greater COMT activity than women (Chen et al., 2004; Xie, Ho, & Ramsden, 1999), which may be the result of higher estrogen levels in women leading to decreased COMT activity (Overpeck, Colson,
Hohmann, Applestine, & Reilly, 1978; Xie et al., 1999). In addition, men and women have displayed differences in brain DA levels and receptor binding as well as differences in amphetamine-induced positive affect and regional DA release, which may be related to the effects of estrogen on dopaminergic function (Cantuti-Castelvetri et al., 2007;
Haaxma et al., 2007; Munro et al., 2006; Riccardi et al., 2011, 2006).
Admittedly, one set of findings in the current study presents greater difficulty in explaining: COMT heterozygotes frequently differed from homozygotes (i.e., Val and
Met homozygotes combined). Previously mentioned research indicated that Val and Met homozygosity are at opposite ends in terms of level of COMT activity, and thus one would not expect heterozygotes to differ from homozygotes if self-reported differences are assumed to be the result of differences in DA neurotransmission in a particular brain region secondary to genotypically driven variation in COMT activity. However, this set of findings is consistent with the phenomenon known as molecular heterosis. Molecular heterosis occurs when individuals heterozygous for a genetic polymorphism display significantly more or less of an effect for a continuous or dichotomous trait than homozygotes, with positive heterosis indicating a greater effect and negative heterosis 66 indicating a lesser effect in heterozygotes (Comings & MacMurray, 2000). In the current study, results for COMT rs4680 were suggestive of positive heterosis for the following measures: SNAP-2 clinical/subclinical BPD diagnosis and SNAP-2 Borderline, Self-
Harm, and Suicide Proneness scores in the total sample, and BIS-11, SCS, and SNAP-2
Disinhibition scores in women. Similar to the current study, one study reported a higher percentage of COMT heterozygosity (Val/Met genotype) in methamphetamine abusers who relapsed in comparison to abusers who remained abstinent after one year, suggestive of positive heterosis (Hosak, Horacek, Beranek, & Cermakova, 2007). In contrast to the current study, a recent meta-analysis of the relationship between COMT rs4680 and schizophrenia revealed a protective effect for heterozygosity, suggestive of negative heterosis (Costas et al., 2011). Negative COMT heterosis in relation to mental disorder or symptoms of mental disorder could be explained by an inverted U-shaped response curve, in which heterozygosity is associated with an optimal level of neurotransmitter function (Comings & MacMurray, 2000; Costas et al., 2011). Although positive COMT heterosis in relation to mental disorder or symptoms of mental disorder is not as readily explainable, one potential explanation is that COMT activity below a certain threshold may induce compensatory changes in the brain, and another potential explanation is that the trait in question may be excited or inhibited by multiple brain regions which are differentially affected by variation in COMT activity (Gogos et al., 1998). One final potential explanation is that COMT activity may also play a major role in modulating NE neurotransmission in the hippocampus (Matsumoto et al., 2003), which may interact with the effects of COMT activity on DA neurotransmission in the hippocampus and other parts of the brain. Consistent with this potential explanation and some other previously 67 mentioned ones, neuroimaging studies of BPD patients have revealed abnormalities in the frontolimbic network, including the hippocampus, DLPFC, and other prefrontal regions
(Leichsenring, Leibing, Kruse, New, & Leweke, 2011; Schmahl & Bremner, 2006).
GABRA2 Rs279871
GABRA2 rs279871 was related to BPD only in men, which yielded one medium effect: Male G homozygotes displayed lower SNAP-2 Borderline scores than male A- allele carriers (d = .66). This is the first study to report a relationship between GABRA2 and BPD symptoms. Interestingly, however, some previous studies have positively associated the A allele of GABRA2 rs279871 with conduct disorder symptoms (Dick,
Bierut, et al., 2006), alcohol dependence (Dick, Bierut, et al., 2006; Edenberg et al., 2004;
Philibert et al., 2009), and other drug dependence (Agrawal et al., 2006; Dick, Bierut, et al., 2006; Philibert et al., 2009), and another study using two large subsamples (n = 1105 and n = 816) reported a higher percentage of antisocial personality disorder (ASPD) in participants with the AA genotype relative to G-carriers in both samples (Dick, Agrawal, et al., 2006). Because those studies did not separately analyze males and females, it is possible that the relationships they detected were more specific to males but were strong enough to yield significant results using mixed-gender samples, especially given that previous studies genotyped hundreds or even thousands of individuals. Based on current and past results, it appears that the A allele of GABRA2 rs279871 may be a risk factor for the development of personality- and substance-related psychopathology, particularly in males.
GABRA2 rs279871 was related to impulse control only in women, which yielded two medium effects: Female heterozygotes (AG participants) displayed higher BIS-11 68 scores than female GG participants (d = .60) and homozygotes (d = .56). Although no previous studies have examined the relationship between GABRA2 rs279871 and impulsivity, one study failed to reveal a relationship between GABRA2 rs279871 and novelty seeking (Dick, Agrawal, et al., 2006); however, that particular study only compared AA participants to G-allele carriers and did not separately analyze men and women. Consistent with the possibility that variation in GABRA2 influences the development of impulsivity, CSF GABA levels and cortical GABA concentrations have both been related to impulsivity in humans (Boy et al., 2011; Lee et al., 2009), and
GABA-A agonists have been shown to increase impulsive responding in rodents (Le et al., 2008; Oliver et al., 2009; Thiebot et al., 1985) and impair inhibitory control in humans (Acheson et al., 2006; Deakin et al., 2004; Fillmore et al., 2001). Also, two other
GABRA2 SNPs, GABRA2 rs279826 and GABRA2 rs279858, have been associated with impulsiveness scores, particularly in women (Villafuerte et al., 2011). Therefore, it is possible that variation in GABRA2 influences the development of impulsivity, particularly in women.
GABRA2 rs279871 was related to self-harm only in men, which yielded two small-to-medium effects: Male G homozygotes displayed lower SNAP-2 Suicide
Proneness (d = .41) and SHI (d = .50) scores than A-allele carriers. Although no previous studies have examined the relationship between GABRA2 and self-harm, participants administered diazepam, a GABA-A agonist (Atack, 2005), have displayed increased self- aggression (Berman et al., 2005), and personality-disordered individuals with a history of suicide attempts have displayed higher CSF GABA levels than personality-disordered individuals without a history of suicide attempts (Lee et al., 2009). Also as previously 69 mentioned, past studies have positively associated the A allele of GABRA2 rs279871 with conduct disorder symptoms (Dick, Bierut, et al., 2006), alcohol dependence
(Edenberg et al., 2004; Dick, Bierut, et al., 2006; Philibert et al., 2009), and other drug dependence (Agrawal et al., 2006; Dick, Bierut, et al., 2006; Philibert et al., 2009) and have associated the AA genotype with ASPD (Dick, Agrawal, et al., 2006). Thus, the A allele of GABRA2 rs279871 may be a risk factor for the development of personality- and substance-related psychopathology, including self-harm, again particularly in males.
Although GABA-A receptor -2 subunits mostly have been related to anxiety
(Dixon et al., 2008; Lehner et al., 2010; Low et al., 2000), they may be involved in other emotional responses and emotionally driven behaviors, such as depression (Vollenweider et al., 2011) and impulsive actions motivated by negative affective states (Villafuerte et al., 2011). As stated previously, GABA-A receptor -2 subunits are distributed throughout brain regions involved in the regulation of emotion (e.g., prefrontal cortex, amygdala, and hippocampus) (Akbarian et al., 1995; Dixon et al., 2008; Lehner et al.,
2010; Low et al., 2000; Tian et al., 2005), and neuroimaging studies of BPD patients have revealed abnormalities in the frontolimbic network, including the prefrontal cortex, amygdala, and hippocampus (Leichsenring et al., 2011; Schmahl & Bremner, 2006).
According to the DSM-IV-TR, BPD is characterized in part by mood reactivity (e.g., intense intermittent states of depression, anxiety, or irritability) and impairments in impulse control, possibly including substance abuse (American Psychiatric Association,
2000). Given all of the preceding information, it is reasonable to suspect that GABRA2 may influence a diversity of emotional responses and emotionally driven behaviors and 70 by extension may influence the development of BPD and related traits and behaviors, such as impulsivity and self-harm.
Intriguingly, all of the current findings in relation to GABRA2 rs279871 were gender-specific. Such findings may be explained by gender differences in the levels of steroid hormones (e.g., progesterone and testosterone) and neurosteroids as well as by gender differences in the effects of neurosteroids and in the structure of brain regions containing GABA-A receptor -2 subunits. Neurosteroids, such as allopregnanolone (a neuroactive metabolite of progesterone), androstanediol (a neuroactive metabolite of testosterone), dehydroepiandrosterone (DHEA), and its sulfated metabolite, DHEA sulfate (DHEAS), can act as positive or negative allosteric modulators of GABA-A receptor function (Engel & Grant, 2001; Reddy, 2010). Furthermore, allopregnanolone,
DHEA, and DHEAS can also enhance or attenuate GABA-A receptor-mediated inhibition of 5-HT neuronal activity (Gartside, Griffith, Kaura, & Ingram, 2010; Kaura,
Ingram, Gartside, Young, & Judge, 2007). In regard to gender differences, circulating levels of progesterone and allopregnanolone have been shown to be higher in women during the luteal phase than in men (Genazzani et al., 1998; Overpeck et al., 1978); blood levels of testosterone and androstanediol have been shown to be higher in men than in women (Overpeck et al., 1978; Strickland & Apland, 1977; Wudy, Wachter, Homoki, &
Teller, 1996); blood-serum concentrations of DHEA have been shown to be higher in women than in men (Genazzani et al., 1998); and serum levels of DHEAS have been shown to be higher in males in comparison to females across all age groups between the ages of 17 and 69 years, with the largest difference in DHEAS levels occurring between the ages of 20 and 29 years (Young, Skibinski, Mason, & James, 1999). Also, one study 71 revealed sex differences in the anxiogenic effects of acute exposure to progesterone and allopregnanolone in rats (Gulinello & Smith, 2003), raising the possibility that gender differences in the effects of neurosteroids may occur in humans. Finally, neuroimaging has revealed gender differences (relative to cerebrum size) in the sizes of the amygdala and prefrontal regions (Goldstein et al., 2001), which are brain regions containing
GABA-A receptor -2 subunits (Akbarian et al., 1995; Dixon et al., 2008; Lehner et al.,
2010; Low et al., 2000; Tian et al., 2005).
In the current study, BIS-11 results for GABRA2 rs279871 were suggestive of positive heterosis in women. Perhaps related to impulsivity, one previous GABRA2 rs279871 study reported a higher proportion of AG genotype and a lower proportion of
GG genotype in polysubstance abusers compared to control participants (Drgon,
D’Addario, & Uhl, 2006). Similar to one aforementioned potential explanation for positive COMT heterosis in relation to symptoms of mental disorder, positive GABRA2 heterosis in relation to impulsivity may be explained by impulsive behavior being excited or inhibited by multiple brain regions which are differentially affected by genetically influenced variation in GABA-A -2 subunit receptor function.
SNCA Rs356195
SNCA rs356195 was related to BPD only in women, which yielded three large effects: Female T homozygotes displayed higher SNAP-2 Borderline scores than female
C homozygotes (d = 1.89), heterozygotes (d = 1.14), and C-allele carriers (d = 1.48). This is the first study to report a relationship between SNCA and BPD symptoms. SNCA rs356195 was also related to impulsivity across all four measures of impulse control, which yielded several small-to-medium effects: T-allele carriers displayed lower SCS 72 scores (indicative of greater impulsivity; d = .38) and higher BIS-11 (d = .37), SNAP-2
Impulsivity (d = .38), and SNAP-2 Disinhibition scores (d = .36) than C homozygotes, and T homozygotes displayed higher BIS-11 scores than C-allele carriers (d = .60). In addition, gender-specific analyses revealed higher BIS-11 scores in female T-allele carriers in comparison to female C homozygotes (d = .50) and lower SCS scores
(indicative of greater impulsivity) in male T-allele carriers in comparison to male C homozygotes (d = .55). Although no previous studies have examined the relationship between SNCA and impulsivity or impulsivity-related traits, -synuclein expression in the striatum has been shown to influence stimulant-induced locomotion in rodents
(Abeliovich et al., 2000; Boyer & Dreyer, 2007), which is a behavior associated with impulsive responding in rats (Dellu-Hagedorn, 2006). Of potential relevance to the current findings, the C allele of SNCA rs356195 has been negatively associated with history of alcohol craving (Foroud et al., 2007), and blood -synuclein levels have been positively correlated with alcohol and cocaine craving scores (Bonsch et al., 2004; Mash et al., 2008). Notably, alcohol-related psychopathology has been related both to dimensionally and diagnostically measured BPD: More specifically, BPD symptoms have been positively correlated with alcohol use disorder in a nonclinical sample of 395 young adults (Trull et al., 2004), and BPD is estimated to be the most commonly diagnosed lifetime personality disorder among individuals with a 12-month alcohol use disorder in the general population (Grant et al., 2008, 2004). Based on past and present findings, it is tempting to speculate that the C allele of SNCA 356195 may be a protective factor against the development of impulsivity, which in turn may serve as a protective factor 73 against the development of disorders involving poor impulse control, such as BPD and substance-related disorders.
SNCA rs356195 was not significantly related to self-harm in the total sample or by gender. One possible explanation is that there is no relationship between SNCA rs356195 and self-harm. However, another possibility is that the current study lacked adequate power to detect a relationship between SNCA rs356195 and self-harm. A visual examination of Tables 16 and 20 appears to support the latter possibility: T homozygotes displayed the highest scores across all four self-harm measures in the total sample and particularly in women. Greater self-harm in female T homozygotes also would have been consistent with the current study’s finding of greater BPD symptoms in female T homozygotes. Thus, it would be premature to conclude that SNCA rs356195 is probably not related to self-harm, especially given that this is the first study to examine the relationship between SNCA and self-harm.
Although -synuclein may modulate DA, 5-HT, and NE transporter activity
(Venda et al., 2010; Wersinger, Jeannotte, et al., 2006; Wersinger, Rusnak, et al., 2006; however, also see Senior et al., 2008), it most clearly has been shown to reduce DA biosynthesis and release (Venda et al., 2010). Consistent with a role for -synuclein (and thus SNCA) in the etiology of BPD and related traits and behaviors, DA blockers have been shown to decrease impulsivity and suicidal behavior in patients with BPD (Friedel,
2004), and L-DOPA (which increases DA activity) has been shown to increase impulsivity in patients with Parkinson’s disease (Cools et al., 2003). Moreover, DA receptors are found in the prefrontal cortex, amygdala, and hippocampus (Matsumoto et al., 2003; Wise, 2009), which are all brain regions where -synuclein is highly expressed 74
(Clayton & George, 1998; Jakes, Spillantini, & Goedert, 1994; Venda et al., 2010;
Ziolkowska et al., 2005) and where abnormalities have been detected in BPD patients
(Leichsenring et al., 2011; Schmahl & Bremner, 2006). Therefore, SNCA may influence the development of BPD and related traits and behaviors via the effects of -synuclein on
DA biosynthesis and release in the prefrontal cortex, amygdala, and/or hippocampus.
In regard to gender-specific results with SNCA rs356195, such findings may be explained by gender differences in the DA and -synuclein systems. As stated previously, men and women have displayed differences in brain DA levels and receptor binding as well as differences in amphetamine-induced positive affect and regional DA release, which may be related to the effects of estrogen on dopaminergic function
(Cantuti-Castelvetri et al., 2007; Haaxma et al., 2007; Munro et al., 2006; Riccardi et al.,
2011, 2006). Lewy bodies, which are intracellular inclusions primarily found in brain neurons and mostly composed of -synuclein, are characteristic of neurodegenerative disorders such as Parkinson’s disease and dementia with Lewy bodies (Clayton &
George, 1998; Nelson et al., 2010; Venda et al., 2010; Ziolkowska et al., 2005), and men are at greater risk of developing Parkinson’s disease and neocortical and limbic Lewy bodies and have displayed greater -synuclein expression in dopaminergic neurons
(Cantuti-Castelvetri et al., 2007; Haaxma et al., 2007; Nelson et al., 2010).
Limitations
In a nationally representative sample, the majority of individuals diagnosed with lifetime BPD also had at least one 12-month substance use, mood, or anxiety disorder
(Grant et al., 2008), and in large nonclinical samples BPD symptoms or features have been positively correlated with anxiety, mood, and alcohol and drug use disorders (Trull, 75
1995; Trull et al., 2004). Thus, one limitation is that, as part of a larger research project, the current study discouraged recent drug use and also excluded potential problem drinkers and individuals who reported experiencing a lifetime bipolar disorder or a recent depressive or anxiety disorder, which may have made it more difficult to detect genetic associations as a result of restricting the number of individuals diagnosed with BPD as well as the range of BPD, impulse control, and self-harm scores. For example, although one SNP (COMT rs4680) was associated with a diagnosis of clinical/subclinical BPD, the current study failed to detect an association between any of the SNPs and a diagnosis of clinical BPD; however, only 2.9% of participants (n = 4) received a diagnosis of clinical BPD in the total sample (83.3% of which was composed of individuals between the ages of 21 and 29). In comparison, 9.3% of individuals between the ages of 20 and 29 in a nationally representative sample received a diagnosis of lifetime BPD (Grant et al.,
2008). Nevertheless, the use of a nonclinical sample free of a number of psychiatric and medical disorders and current exposure to psychiatric medications is also a strength because it removes several factors that may confound genetic associations with BPD.
Another limitation of the current study is its sample size. The effect size of any single
SNP tends to be rather small, and detecting such an effect may require a sample size in the hundreds. In the current study (which used a total sample of 140 participants), only effect sizes that were approximately mid-range between small and medium or larger were significant in the total sample, and only effect sizes that were about medium-to-large were significant when analyzed by gender. Sample size also would not have been sufficient to search for SNP interactions because cell sizes for several genotypic pairings in the total sample would have been less than 5 (with some cell sizes as small as 1). 76
Another limitation of the current study is its reliance on self-report instruments. It would have been interesting and perhaps more compelling if self-report measures of impulse control and self-harm had been supplemented with behavioral measures of impulsivity and self-aggression. Another limitation is that the current study only included individuals who self-identified as Caucasian. Although this practice was employed in order to limit the potentially confounding effects of population stratification, it also limits the ability to generalize current results beyond that of Caucasians. One final limitation of the current study, which is a limitation common to genetic association studies, is that genetic variation in particular SNPs cannot be inferred to be causative but only suggestive of a causative role for the genes in which those SNPs partially represent. COMT rs4680 has been shown to be a functional SNP (i.e., has been shown to influence physiological differences in the body), but it is still possible that genotypes or alleles of all three SNPs are not independent of genotypes or alleles of other SNPs (i.e., that all three SNPs are in linkage disequilibrium with other SNPs) and that it is those other SNPs which play a more direct role in the development of BPD and related traits and behaviors.
Future Directions
In addition to attempting to replicate current results, future studies should search for associations between the current SNPs and behavioral measures of impulsivity and self-aggression. Future research should also attempt to expand the current results by examining SNP-SNP and SNP-environment interactions in relation to BPD, impulse control, and self-harm. Specifically related to COMT rs4680, it may be fruitful to genotype and administer behavioral measures of impulsivity and self-aggression to individuals acutely exposed to placebo or a centrally active COMT inhibitor, such as 77 tolcapone (Apud et al., 2007). In relation to SNCA rs356195 (and other SNPs of SNCA), it may be useful to measure -synuclein expression (i.e., protein or mRNA levels) in the blood combined with genotyping and the administration of tests or tasks. Given the possible role of GABA-A receptor -2 subunits in the regulation of emotion, the literature is in need of studies involving GABRA2 genotyping and measurement of mood and anxiety disorder symptoms. Because results for all three of the current SNPs may have been affected by steroid hormones and neurosteroids, it may also be beneficial to record the temporal proximity to menstruation in women (as a proxy measure of progesterone, allopregnanolone, and estrogen) or to measure the levels of circulating steroids in participants in addition to genotyping and administering behavioral measures of impulsivity and self-aggression. Finally, the addition of functional neuroimaging
(particularly of the frontolimbic network) to future genetic association studies would be helpful in increasing knowledge of gene-brain-behavior relationships.
Summary
COMT rs4680 was the only SNP related to both categorically and continuously measured BPD as well as to impulse control and self-harm scores. However, COMT heterozygotes often differing from the combined group of homozygotes (suggestive of heterosis) presents difficulty in explaining, although some potential explanations were proposed. In regard to the other SNPs, GABRA2 rs279871 was related to BPD, impulse control, and self-harm scores, whereas SNCA rs356195 was only related to the former two. Results in relation to GABRA2 rs279871 were entirely gender-specific, and COMT rs4680 and SNCA rs356195 also yielded some gender-specific results. Gender-specific results with COMT rs4680 may be explained by gender differences in COMT activity 78 and dopaminergic function; gender-specific results with GABRA2 rs279871 may be explained by gender differences in the levels of steroid hormones and neurosteroids as well as by gender differences in the effects of neurosteroids and in the structure of brain regions containing GABA-A receptor -2 subunits; and gender-specific results with
SNCA rs356195 may be explained by gender differences in the DA and -synuclein systems. In conclusion, it appears that COMT, GABRA2, and SNCA may influence the development of BPD and related traits and behaviors.
79
APPENDIX A
IRB FORM
80
APPENDIX B
BARRATT IMPULSIVENESS SCALE, VERSION 11 (BIS-11)
Instructions: For each item, please select the number corresponding to how often the statement is true of you.
1 = Rarely/Never 2 = Occassionally 3 = Often 4 = Almost Always/Always
1. I plan tasks carefully
1 2 3 4
2. I do things without thinking
1 2 3 4
3. I make-up my mind quickly
1 2 3 4
4. I am happy go lucky
1 2 3 4
5. I don’t “pay attention”
1 2 3 4
6. I have “racing” thoughts
1 2 3 4
7. I plan trips well ahead of time
1 2 3 4
8. I am self-controlled
1 2 3 4
81
9. I concentrate easily
1 2 3 4
10. I save regularly
1 2 3 4
11. I “squirm” at plays or lectures
1 2 3 4
12. I am a careful thinker
1 2 3 4
13. I plan for job security
1 2 3 4
14. I say things without thinking
1 2 3 4
15. I like to think about complex problems
1 2 3 4
16. I change jobs
1 2 3 4
17. I act “on impulse”
1 2 3 4
18. I get easily bored when solving thought problems
1 2 3 4
19. I act on the spur of the moment
1 2 3 4
82
20. I am a steady thinker
1 2 3 4
21. I change residences
1 2 3 4
22. I buy things on impulse
1 2 3 4
23. I can only think about one problem at a time
1 2 3 4
24. I change hobbies
1 2 3 4
25. I spend or charge more than I earn
1 2 3 4
26. I often have extraneous thoughts when thinking
1 2 3 4
27. I am more interested in the present than in the future
1 2 3 4
28. I am restless at theaters or lectures
1 2 3 4
29. I like puzzles
1 2 3 4
30. I am future oriented
1 2 3 4
83
APPENDIX C
LIFE HISTORY OF AGGRESSION SELF-DIRECTED AGGRESSION SUBSCALE
(LHA SELF-DIRECTED AGGRESSION)
Instructions: Rate yourself on each of the following items using the rating system below. Only rate actual behavior be it verbal and/or physical. Do not include in your ratings thoughts not followed by any action or fantasies. For these questions it is important to rate any events that have occurred over your lifetime (including your years as a teenager and a young adult).
0 = Never Happened 1 = Only Happened Once 2 = Happened a Couple of Times (2-3) 3 = Happened Several Times (4-9) 4 = Happened Many Times (10+) 5 = Happened So Many Times I Couldn't Give a Number
How Many Times Would You Say You Did the Following Things Over the Course of Your Life to DATE?
1. Deliberately tried to physically hurt yourself in anger or desperation.
0 1 2 3 4 5
2. Deliberately tried to end your life or kill yourself in anger or desperation.
0 1 2 3 4 5
84
APPENDIX D
SELF-CONTROL SCALE (SCS)
Instructions: Using the following scale, please indicate how much each of the following statements reflects how you typically are.
1 = Not Like Me At All 2 3 4 5 = Very Much Like Me
1. I have a hard time breaking bad habits.
1 2 3 4 5
2. I am lazy.
1 2 3 4 5
3. I say inappropriate things.
1 2 3 4 5
4. I never allow myself to lose control.
1 2 3 4 5
5. I do certain things that are bad for me, if they are fun.
1 2 3 4 5
6. People can count on me to keep on schedule.
1 2 3 4 5
7. Getting up in the morning is hard for me.
1 2 3 4 5
8. I have trouble saying no.
1 2 3 4 5
85
9. I change my mind fairly often.
1 2 3 4 5
10. I blurt out whatever is on my mind.
1 2 3 4 5
11. People would describe me as impulsive
1 2 3 4 5
12. I refuse things that are bad for me.
1 2 3 4 5
13. I spend too much money.
1 2 3 4 5
14. I keep everything neat.
1 2 3 4 5
15. I am self-indulgent at times.
1 2 3 4 5
16. I wish I had more self-discipline.
1 2 3 4 5
17. I am good at resisting temptation.
1 2 3 4 5
18. I get carried away by my feelings.
1 2 3 4 5
19. I do many things on the spur of the moment.
1 2 3 4 5
86
20. I don't keep secrets very well.
1 2 3 4 5
21. People would say that I have iron self-discipline.
1 2 3 4 5
22. I have worked or studied all night at the last minute.
1 2 3 4 5
23. I'm not easily discouraged.
1 2 3 4 5
24. I'd be better off if I stopped to think before acting.
1 2 3 4 5
25. I engage in healthy practices.
1 2 3 4 5
26. I eat healthy foods.
1 2 3 4 5
27. Pleasure and fun sometimes keep me from getting work done.
1 2 3 4 5
28. I have trouble concentrating.
1 2 3 4 5
29. I am able to work effectively toward long-term goals.
1 2 3 4 5
30. Sometimes I can't stop myself from doing something, even if I know it is wrong.
1 2 3 4 5
87
31. I often act without thinking through all the alternatives.
1 2 3 4 5
32. I lose my temper too easily.
1 2 3 4 5
33. I often interrupt people.
1 2 3 4 5
34. I sometimes drink or use drugs to excess.
1 2 3 4 5
35. I am always on time.
1 2 3 4 5
36. I am reliable.
1 2 3 4 5
88
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