GENETIC PREDISPOSITION for HYPNOTIC SUSCEPTIBILITY: an INTRODUCTORY STUDY on the POTENTIAL of GENETIC PREDICTORS Kyle D

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GENETIC PREDISPOSITION FOR HYPNOTIC SUSCEPTIBILITY:

AN INTRODUCTORY STUDY ON THE POTENTIAL OF GENETIC PREDICTORS

Kyle David Wannigman

A Thesis Presented to

The Faculty of Humboldt State University

In Partial Fulfillment of the Requirements for the Degree

Master of Arts in Psychology: Academic Research

Committee Membership

Dr. Ethan Gahtan, Committee Chair

Dr. Chris Aberson, Committee Member

Dr. Gregg Gold, Committee Member

December 2014

Abstract

GENETIC PREDISPOSITION FOR HYPNOTIC SUSCEPTIBILITY: AN INTRODUCTORY STUDY ON THE POTENTIAL OF GENETIC PREDICTORS Kyle D. Wannigman

Hypnotherapy is an empirically supported, clinical intervention used in the treatment of a

wide variety of mental, physical, and emotional dysfunctions. Hypnotizability is a stable

and heritable personality trait. Individual differences in hypnotic susceptibility have been shown to correspond to hypnotherapeutic success. Increasingly, gene variants have been

linked to facets of personality as well as their related psychological and physiological

disorders. These variants are used as predictors of responses to medical treatments including drugs, psychotherapy, and placebo effects. These studies support hypotheses relating specific gene variants to differences in hypnotizability. This study investigated two allele variants and their associations to susceptibility: the serotonin transporter gene linked polymorphic region 5HTTLPR and the single nucleotide polymorphism of the catechol-O-methyltransferase at Codon 158. A secondary goal was to assess the validity of the Tellegen Absorption Scale (TAS) by comparing scores to actual hypnosis susceptibility. Hypnotic susceptibility was measured using a standardized group induction method – the Harvard Group Scale for Hypnotic Susceptibility (HGSHS-A).

Hypnotizability, TAS scores, COMT genotype, and SERT genotype, was measured in

253 participants. There were no main effects of either gene variant on hypnotic susceptibility and no interactions effects between these genes. TAS scores were not

significantly correlated with scores on the HGSHS-A, suggesting that TAS is not a valid measure of the hypnotizability construct. These negative results are consistent with other recently published studies. A review of the literature suggests that commonly used testing methods for hypnotic susceptibility may conflate multiple constructs and decrease the probability of detecting susceptibility correlates.

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Acknowledgements

I would like to begin by thanking Dr. Ethan Gahtan for not only being my thesis supervisor, but also my mentor and friend. Dr. Gahtan is one of those remarkable people who can help you regain faith in humanity, or at least the scientific community, when you are surrounded by bad articles compounded with faulty statistics. Countless times when I was ready to throw away my ideas, scrap the project, and quit science, Gahtan has stood up for this project and me as a competent researcher. By providing me guidance as a supervisor, but also as someone who supports my ideas and believes in my success,

Gahtan has facilitated an environment through which I was able to reach my full potential. Our relationship had started before we ever met, when I was desperate for an advisor and he was on sabbatical. Even though he was on his break, he still took the time to not only ease my worries, but also to ignite further determination and pride within myself. Gahtan has always been there when I needed him most and one of his best qualities is his heart. I will always remember the remarkable contributions – physically, emotionally, and financially – that Dr. Gahtan has made to this project and the exemplary role model of which to mirror in my future successes. Thanks for giving me someone to look up to!

I would like to thank James Barnett and Sarai Escalante for helping me in my early phases of recruitment and data collection.

I would like to thank Anthony Baker, Darrell Burlison, and Reginald Blackwell for their supervision in the genotyping biotechnology at the Core Facility here at HSU. iv

I would like to thank Patrick Panelli, Sarah Stednitz, and Edwin Vazquez for their statistical expertise.

I would like to thank Bruce Long for his detailed and dedicated editorial contributions.

I would like to thank my committee members, Gregg Gold and Chris Aberson for their leniency on deadlines and their academic professionalism throughout this project.

I would like to thank Cathy Maier, Mark Perry, Aleah Ames, Tim Simmerman,

Maria-Elena Whaples, Kim Hall, my sister Kenzie Wannigman, and my father David

Wannigman. It is because of these extraordinary people in my life that I made it

Humboldt State University and studied hypnotherapy.

I would like to thank my patient and remarkable partner Victoria Alexandria Brito for her support, humor, and confidence in my abilities – especially when I was recovering from a 14 fracture spinal injury during the early phases of this project. She has remained my pillar of stability and beam of inspiration throughout every frustrating setback.

Thanks again for reminding me to eat during long-lost hours spent in “the worm hole”. I

love you.

Finally I’d like to pay tribute to the G.I. Bill. Without this remarkable opportunity

to get my master’s degree after my service in the Air Force, these amazing investigations

into the science of hypnosis, biology, neuroscience, and genetics might not have been

possible.

I am forever touched and blessed by these remarkable individuals.

Table of Contents

Abstract ...... ii

Acknowledgements ...... iv

Table of Contents ...... vi

List of Tables ...... viii

List of Figures ...... ix

Introduction ...... 1

Literature review ...... 2

Hypnosis ...... 2 Genetics ...... 5 Serotonin ...... 7 COMT ...... 12 Dopamine ...... 14 COMT and Hypnosis ...... 16 Placebo ...... 19 Absorption ...... 22 5HTTLPR and COMT Amygdala Interactions ...... 23 Statement of the Problem ...... 26

Method ...... 35

Participants ...... 35 Instrumentation...... 36 Procedure ...... 37 Consent...... 39 Effect Size...... 40

Genotyping ...... 41 SERT...... 42 COMT...... 42 Data Analysis ...... 45 Results ...... 46

Discussion ...... 53

SERT Results ...... 53 COMT Results...... 54 SERT and COMT Interaction Results ...... 56 TAS Results...... 56 Future Directions ...... 61 Conclusions ...... 67

References ...... 69

Appendix - SERT’s 4 allelic breakdown protocol (S, LG, L, LA) ...... 88

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List of Tables

Table 1. Absolute Frequencies of Genotypes...…..… …………………………...... 43

Table 1. Allelic Frequencies of SERT for HGSHS-A..…………………………...... 48

Table 3. Allelic Frequencies of COMT for HGSHS-A…………………………...... 50

Table 4. Descriptive Statistics for the interaction effect…………………………...... 51

Table 5. Correlation Matrix of variables…………………………………………...... 52

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List of Figures

Figure 1. Hypotheses 1-3…………………………………..…………………………....34

Figure 2. SERT Polyacrylamide Gel Analysis……………..…………………………....44

Figure 3. SERT-Hypnotizability Results.………………………………………………..47

Figure 4. COMT-Hypnotizability Results…...……………………………………….….49

Introduction

Hypnosis is an effective type of therapy because it uses deep relaxation and vivid

imagination to create a world that the person believes in and desires. It is a natural state

of consciousness that people undergo on a daily basis, similar to daydreaming,

meditation, or zoning out on a long drive. The hypnotherapist merely guides the person

towards helping him or herself navigate this state to directly influence their desired

outcomes. To assist in understanding what hypnosis is I will offer my definition of

hypnosis to operationalize it: Hypnosis is the natural process of relaxing the conscious,

rational mind in order to access deeper subconscious mechanisms that aid in unraveling

psychological turmoil and control autonomic functioning. Hypnosis is seen as a surrender

or loss of control. Yet in actuality, studies show that highly hypnotizable people have

enhanced control over sensory, motor, and somatic functioning (Hoeft et al., 2012).

Moreover, people can do self-hypnosis which empowers them to choose their best-fit

modality for faster and longer lasting recoveries. Cognitive-behavioral therapy (CBT) – the most successful form of psychotherapy (Hofmann, Asnaani, Vonk, Sawyer, & Fang,

2012) – is similar in that the therapist guides the client into productive patterns of thinking and behaving to reach their desired goals. Other forms of psychotherapy operate with a similar purpose. Certain individuals and personality types are going to be more effective at directing their actions in a positive, productive manner. Individuals seeking help might be better suited for success if they were matched to a particular type of therapy that was most efficacious for them.

Literature review

Hypnosis

Hypnotherapy is a form of psychotherapy in which the client is relaxed and

guided into an altered state of consciousness, usually involving an induction. It promotes

therapeutic success through strategic use of positive imagery and suggestions. It is an

empirically supported, clinical intervention (Lynn, Kirsch, Barabasz, Cardeña, &

Patterson, 2000) that is used in the treatment of a wide variety of mental, physical, and

emotional dysfunctions (Rhue, Lynn, & Kirsch, 1993). Hypnotherapy is a safe, potent, noninvasive procedure (Holroyd, 1996). It is cost-effective, reversible, and useful as an alternative to drugs or medications (Valente, 2003). Based on its efficacy, many researchers advocate for the broader use of hypnosis in both medical and psychotherapeutic applications (i.e., Holroyd, 1996; Lynn et al., 2000; Valente, 2003).

Hypnosis has been used in the treatment of phobias, addictions, mood disorders

such as depression and anxiety, eating disorders, dissociative identity disorder, PTSD,

pain management, somatization, other psychotic disorders, and assists in overcoming

grief and trauma (Rhue et al., 1993). All these conditions are typically treated with

powerful psychotropic drugs. It is well documented that hypnosis has been used to

alleviate the suffering in cancer patients for over 200 years (Montgomery, Schnur, &

Kravits, 2013). Cancer patients using hypnosis need less overall medications and spend

less time in the hospital. Self-report shows that they are less anxious and more hopeful

3 before and after surgery/chemotherapy. Hypnotherapy has even been shown to boost successful patient outcomes when used as an adjunct in psychodynamic therapies – from

75% to 95% – and CBT – from 85% to 99.5% (Kirsch, 1996). The average client treated by hypnosis and CBT showed greater improvement than 90% of the clients treated with

CBT alone.

It is estimated that the majority of all individuals (70%) are moderately receptive to the benefits of hypnotherapy with an additional ten to fifteen percent labeled as highly susceptible (Nadon, Laurence, & Perry, 1987). Highly susceptible individuals respond equally well to hypnosis as they do active medications. A meta-analysis of 18 studies found – with a mean effect size of d = 0.87 – that patient outcome efficacy was highest

(top ten percent) in those using hypnosis as an adjunct to treatment as compared to non- hypnotic treatment options (Kirsch, Montgomery, & Sapirstein, 1995). The best of these effects came from obesity samples. The weight-loss effects for the obese participants who used hypnosis continued to increase 6 months after treatment and remained intact at the two year follow-up. After treatment ended, only those who utilized hypnosis continued to show improvement over time. A more recent and stringent meta-analysis on the efficacy of hypnosis confirms these results (d = 0.63) for patients classified by the International

Statistical Classification of Diseases and Related Health Problems (Flammer & Bongartz,

2003). These researchers make note that their results are conservative and underestimate the true efficacy of using hypnosis as support for medical procedures.

The ability to control and reduce pain is the most scientifically validated use for hypnotherapy. People using hypnosis report experiencing significantly less pain and

distress – as compared to controls and placebos – as well as higher pain thresholds in

experimental designs (De Pascalis, Magurano, & Bellusci, 1999). Researchers have been

able to show that patients experience less pain when using hypnosis exclusively or in

adjunct to other treatments in severe burn patients (Patterson, Everett, Burns, &

Marvin, 1992), fibromyalgia syndrome (Bernardy, Füber, Klose, & Häuser, 2011), cancer patients (Montgomery et al., 2013), childbirth (Cyna, McAuliffe, & Andrew, 2004)

people dealing with chronic back pain (Jensen & Patterson, 2006), dental pain (Barber &

Mayer, 1977), pediatrics (Wood & Bioy, 2008), procedural pain (Patterson & Jensen,

2003), chronic pain (Dillworth, Mendoza, & Jensen, 2012), and frequent and reoccurring

headaches (Jensen & Patterson, 2006). One meta-analysis looked at 18 studies with 27

effect sizes analyzed for hypnotic analgesia (pain management). Although 75% of

individuals (n = 933, d = 0.74) had substantial pain relief compared to control groups, the

magnitude of the effects varied greatly depending on levels (high d = 1.22; medium d =

0.64; low d = 0.10) of susceptibility (Montgomery, DuHamel, & Redd, 2000). This

suggests an individual’s level of responsiveness to hypnotic suggestion – or

hypnotizability – can predict successful patient outcomes. This is confirmed through

numerous studies showing high hypnotizables to have the greatest response (i.e., De

Pascalis et al., 1999; 2008). The main assessment for hypnotizability involves a series of

tests while hypnotized that check for hypnotic depth and adherence to suggestions (i.e.,

Harvard Group Scale for Hypnotic Susceptibility, Stanford Hypnotic Susceptibility Scale,

Form C).

Hypnotizability is a stable and heritable personality trait. In a 25-year longitudinal

study by Piccione, Hilgard, and Zimbardo (1989) they found a statistically significant

stability coefficient of .64 (10-year retest), .82 (15-year retest), and .71 (25-year retest) of hypnotizability in a sample of fifty individuals. These fifty individuals did not differ significantly from the larger sample of 533. Twin studies show that hypnotizability is heritable (Lichtenberg, Bachner-Melman, Ebstein, & Crawford, 2004). Baumen and Bul’

(1981) found a concordance rate for hypnotizability of 78.3% for monozygotic twins and

60.5% for dizygotic twins in 60 Russian pairs (as cited in Raz, Fan, & Posner, 2006).

Although yielding a modest index of heritability (34%), other studies have shown estimates as high as 64% (Szeleky et al., 2010). Heritability index (h2) is the influence

that environment has on gene expression. A high index indicates a high level of genetic

influence.

Genetics

Over time the nature vs. nurture debate in psychology has come to an agreement

that personality (like many other phenotypes) originates from both genetics and environment (Tellegen et al., 1988). This evidence comes from investigations involving twins. Since monozygotic twins share 100% of their genetic makeup while dizygotic twins share on average only 50%, a higher concordance of phenotypic expression among the monozygotic pairs provides evidence for heritability. For example, one study gathered inventories from 660 monozygotic and 304 dizygotic twin pairs and tested them

on the NEO Five-Factor Inventory (BIG-5) personality questionnaire. They found that genetics explained around 50% (h2= .42 - .56) of the phenotypic variance in personality

characteristics in the self-reported data and even greater effects (h2= .57 - .81) for the

peer reported (Riemann, Angleitner, & Strelau, 1997). Another study involved observing

the behavior of 168 monozygotic and 132 dizygotic twin pairs to assess the similarities of

personality traits by using judges instead of self-reports. They found a slightly lower

genetic contribution (40%) but still strongly heritable (Borkenau, Riemann, Angleitner, &

Spinath, 2001). Due to the contribution of environmental influences, a person in an

enriched environment can overcome their genetic propensities and vice versa.

Genes influence the development and activation of certain propensities and

characteristics. Genes influence personality across different cultures (Yamagata et al.,

2006). They are the primary influence on personality stability over time (Kandler et al.,

2010). Specific genes are used as predictors for heritable traits including some

psychological conditions (Tellegen et al., 1988). Genes have also been shown to

influence the individual reactions people have to pharmaceutical drugs (Lesch &

Gutknecht, 2005) – and more recently – predict their success in cognitive behavioral

therapy (Bryant et al., 2010). The role an individual gene has on influencing a particular

characteristic is muddled within a complicated web of interacting ingredients that come

from widely varying individuality and environmental effects. The field of epigenetics –

changes in gene expression that originate from outside the DNA – teach us that our

choices (such as diet, exercise, and drug use) can also alter our DNA and thus our

resulting personality (Choi & Friso, 2010). Regardless, it is in studying these underlying

genetic contributions at their most fundamental level that allow current research to make

unprecedented strides forward (Caspi & Moffitt, 2006). Untangling many of the

intricacies involved in human development allow greater understanding of the human

psyche and its neurophysiological underpinnings. Genetic information promises

individuals greater chances for success, especially when faced with disorders and

irregularities for which medical treatment is necessary.

Serotonin

The serotonin (5HT) system has a pronounced effect on many complex human

functions such as circadian and neuroendocrine rhythms regulating food intake, sleep,

and reproductive activity (Lesch & Gutknecht, 2005). All of these factors are extremely

important to psychological well-being. The mood, cognition, and motor function of an

individual are modulated by 5HT (i.e., Kenna et al., 2012; Lesch et al., 1996). The

serotonin transporter (SERT) is an important protein that mediates the transportation and

availability of 5HT at the synapse. In-depth explorations into the genetic variances of the serotonin transporter gene (SLC6A4) show that different alleles in the gene-linked polymorphic region (5HTTLPR) respond differently to the transcription of serotonin

(Lesch & Gutknecht, 2005). The so-called polymorphic region of the serotonin transporter gene – located on chromosome 17 – is an area of the promoter region of the gene where the nucleotide sequence is especially variable. Two common variants – referred to as the short (S) and long (L) alleles – have different numbers of repeats of a

particular nucleotide sequence (fewer repeats in the short variant). These variants occur

in roughly equal proportions in the population. Thus, most individuals have one copy of

each variant (heterozygous) while smaller proportions have two copies of one or the other

– homozygous long or homozygous short (Bernet, Vnencak-Jones, Farahany, &

Montgomery, 2007). These gene variants are functionally important in that the long allele

produces more SERT messenger RNA so it is twice as good at removing serotonin at the

synapse (Lesch & Gutknecht, 2005). The short allele results in a less effective promoter

which leads to reduced transcription (gene->mRNA) and reduced translation (mRNA-

>protein). Basically, the short allele causes fewer SERTs to be available for transporting the serotonin back into the presynaptic terminal. There is more serotonin at the synapse,

but less available for reuse (Bernet et al., 2007; Kenna et al., 2012; Lesch & Gutknecht,

2005).

Activation of serotonergic neurons is a central part of the acute stress response in

the brain, leading Lesch and Gutknecht (2005) to propose that a healthy individual

requires just the right amount of serotonin to function normally and be effective at

responding to life’s stress. Too much serotonergic transcription – typical of overactive

homozygous L carriers – is associated to ADHD, obsessive compulsive disorder, and

autism. Low activity – common in S allele carriers (S/S or S/L) – is associated with

depression, bi-polar disorder, anxiety, eating disorders, substance abuse, and

neurodegenerative disorders (Lesch & Gutknecht, 2005). In a 23-year longitudinal study

of 847 Caucasians by Capsi and his colleges (2003), individuals carrying the S allele

were found to be more affected by a stressful environment than people carrying only L

9 alleles. The S carriers were diagnosed with depression and exhibited symptoms such as suicidal ideations and attempts at higher rates than L/L carriers. These findings have been duplicated in numerous studies (i.e., Anguelova, Benkelfat, & Turecki, 2003; Kenna et al., 2012)

Another study looked at selective attention in the two variants of the 5HTTLPR polymorphism. They discovered that L/L carriers are biased towards attending to positive material and avoid focusing on negative material. This selective attention is reversed in the S carriers. They propose that a genetically motivated propensity for attention to the positive aspects of life demonstrates resilience towards stress. Focusing more on the negative, the S carriers are more susceptible to mood disorders (Fox, Ridgewell, &

Ashwin, 2009). Similar results were found looking at the hippocampus and amygdala of the two variants of the 5HTTLPR polymorphism using multimodal magnetic resonance- based imaging. The variances in serotonin genotypes effect the resting activation in the amygdala and hippocampus – when triggered by life’s stress – oppositely. The L carriers had a reduction in resting activity with increased exposure to stressful life experiences whereas the S carriers had higher resting activity, even with a smaller number of stressful events. This shows that the S allele primes the individual to become even more vigilant to stressful events whereas the L allele primes the individual to become more resilient. Even with more overall stressful events (mean of 8.8 vs. 4.5), L carriers showed less rumination – a correlate of amygdala activation – on life’s stressful events than S carriers.

This means that the L groups may have a predisposition against mood disorders (i.e., anxiety and depression) whereas the S groups may be more vulnerable – mediated by

lesser or greater amygdala activation (Canli et al., 2006). Reduction of amygdala

activation is an important facet of reducing anxiety and depression as shown through

various treatment outcomes (Furmark et al., 2008). These studies and others demonstrate

that being homozygous for the L allele may be more advantageous in a variety of ways.

The serotonin transporter (SERT) is the location most antidepressants target

(Lesch & Gutknecht, 2005). SSRI’s (selective serotonin reuptake inhibitors) are one of

the most common treatments for mood disorders. Since the 5HTTLPR alleles affect the

rate of serotonin uptake, researchers are able to predict some drug responses using

genetic profiling (Stein, Seedat, & Gelernter, 2006). Estimates are moderate, however. In

a comprehensive meta-analysis, variances in the serotonin transporter caused 7-20% of

the total variance in the treatment efficacy of SSRI’s (Lesch and Gutknecht, 2005).

Looking at other medications targeted for the serotonin transporter, it is apparent that the

L carriers have better and faster responses to pharmaceutical drugs affecting the serotonin

system. See Table 1 in their article for a summary of the results. It is likely that any agent

affecting the serotonin system is altered by the 5HTTLPR variations. They found that

although genetics can likely predict the efficacy of drug responses, it only plays a

moderate role (8%) in the direct cause of depression and other mood disorders.

Recent studies testing genetics are showing that there may be a genetic

predisposition to success in psychotherapy. In one study, 45 participants with PTSD were

separated on the allelic variations in the serotonin polymorphism 5HTTLPR. Group 1

(having one or more short alleles) and Group 2 (homozygous for the L allele) were tested for improvement rates in the context of cognitive behavioral therapy (CBT). After eight

11 weeks of 90-minute CBT sessions, Group 2 had higher scores on the Clinician

Administered PTSD Scale during posttest examinations (d = 0.64) and even higher scores on follow up testing (d = 1.07) six months later. The authors suggest that the responses to

CBT might be mediated by the availability of serotonin (Bryant et al., 2010). Although this is the first study to test genetics as the predictor for successful CBT, these results could be the beginning of a necessary supporting structure to validate genetic profiling to determine psychotherapy placement. Accurate placement based on genetic profiling would require extensive research.

This predictive potential of the SERT gene polymorphism may extend to patients seeking hypnotherapy treatment. There are currently few reliable predictors of hypnotic susceptibly, which correspond to successful patient outcomes (Montgomery et al., 2000).

Better predictors of susceptibility would increase patient efficacy – saving valuable time, resources, and the dangers of using pharmaceutical drugs. The serotonin transporter polymorphism 5HTTLPR plays a role in the direction of attention (Fox et al., 2009), vulnerability to mood disorders (Capsi et al., 2003), and amygdala hyperactivity (Canli et al., 2006). Hypnosis requires an individual to direct their attention purposefully

(Crawford, Brown, & Moon, 1993), relax fully, and follow the guidance of the therapist.

Participants who have more apprehensive or anxious attitudes – characteristic of the S allele – participate less in the hypnotic process (Hilgard, 1979). Since hypnosis – similar to all other therapeutic modalities – involves the cooperation and adherence of the therapist’s recommendations, any deviation could result in lower success rates. Thus, finding a predisposition for susceptibility – be it genetic or otherwise – may illuminate an

12 entire population of individuals who would respond more efficaciously to a particular type of psychotheraputic treatment. This individualization of treatment may help to increase success rates while lowering rebound effects and dependencies on pharmacological interventions.

COMT

Catechol-o-methyltransferase (COMT) mediates the extra neuronal degradation of the catecholamines (dopamine, norepinephrine, and epinephrine) (Mier, Kirsch, &

Meyer-Lindenberg, 2010). It is involved in the inactivation of catecholamines by enzymatic break down at the synapse. One of the most investigated polymorphisms in neuroscience is the Codon 158 of the COMT gene (Montag, Jurkiewicz, & Reuter, 2012).

This single nucleotide polymorphism has been correlated with variations in cognition, memory, affect, pain, and attention (Hall et al., 2012). Explorations into this gene coding for the enzyme COMT – located on chromosome 22 – show that different alleles in the

Val158Met (rs4680) polymorphism are responsible for varying degrees of enzymatic breakdown in dopaminergic neurotransmission (Montag et al., 2012). Individuals carrying two Val alleles will catabolize (break down molecules into smaller units of energy) three to four times more dopamine than those homozygous for the Met allele, with a codominant effect (falling in-between) for heterozygous individuals (Felten,

Montag, Markett, Walter, & Reuter, 2011).

There are strong, measurable differences in the two COMT alleles, Val and Met.

When it comes to emotionality, the Val allele has similar effects as the L allele

(5HTTLPR) in that it is associated with positive emotionality and resilience to

environmental stress. The Met allele has similar effects to the S allele (5HTTLPR) in that

it is associated with negative emotionality. Met carriers are more likely to develop

psychological disorders in response to life’s stressors (Montag et al., 2012). This

represents Goldman’s warrior/worrier model – the Val allele is the robust warrior while

the Met allele is the anxious worrier (Goldman, Oroszi, & Ducci, 2005). Findings agree

that Met allele carriers have more anxious personality traits and are more vulnerable to

anxiety disorders (Montag et al., 2012).

When it comes to cognition – particularly executive functioning and working memory – Met allele carriers have the advantage (Egan et al., 2001). The Met allele is associated with more efficient (lower) PFC activation when working on diverse cognitive tasks and less efficient (stronger) PFC activation during emotional tasks (Montag et al.,

2012). This means that the Met alleles are more efficient at processing complex data,

while the Val alleles are more efficient at processing emotions.

When it comes to executive attention, it appears that the Val allele carriers are

superior. Using the Attention Network Task (ANT) – a test designed to separate the three

aspects of attention (alerting, orienting, and executive) – having a Val allele corresponds

to a having more efficient attentional network. These results were replicated with several

genes that modulate synaptic dopamine and seem to produce an additive effect. The more

14 extra neuronal dopamine in the synapse, the less efficient attention a person has (Fossella et al., 2003).

Dopamine

Dopamine plays an important role at influencing personality traits and a range of affective phenotypes (Felten et al., 2011). Dopamine also influences behavioral aspects of motivation through motor control (Tucker & Williamson, 1984). The dopamine system affects the facilitation of executive functioning when it comes to the selection and sequencing of motor acts to be performed (Tucker & Williamson, 1984). Dopamine is associated with reward or reinforcement behaviors (Solanto, 1998). Putting this together, dopamine is associated with personality traits and actions that link the approach behavior of positive emotional states and the avoidant behavior of negative emotional states

(Felten et al., 2011). It is unclear whether high or low levels of dopamine relate to positive mood states (Montag et al., 2012). Too much or too little dopamine can both result in negative outcomes for the individual (Dang, O'Neil, & Jagust, 2012; Egan et al.,

2001). Dopamine is terminated either through dopamine transporters (DAT) or by the enzymes monoamine oxidase-B (MAO-B) and COMT (Montag et al., 2012). Since DATs are scarce in the prefrontal cortex, COMT is especially critical for catabolism of dopamine in these areas (Mier et al., 2010; Montag et al., 2012).

Dopamine plays a key role on attentional abilities. The original evidence for dopamine’s role in attention spawned from research with Parkinson’s disease patients – a

disease resulting from the death of dopamine-generating cells. A symptom of Parkinson’s

disease is an impaired ability to shift between mental sets (Lees & Smith, 1983). In a meta-analysis that looked at the neuroimaging of attention, the decision to switch attention – whether it is from internal to external or from one stimulus to the next – is an important executive function that stems from activation in the frontal and parietal regions of the cortex (Wager, Jonides, & Reading, 2004). This decision process comes from the integration of cognitive and affective information, especially those coming from dopaminergic reward centers. Furthermore, attention deficit hyperactivity disorder

(ADHD) is treated by targeting the dopamine system, postulating that dopamine modulates the functioning of the PFC (Solanto, 1998). fMRI findings add support by directly showing that COMT’s effect on dopamine synthesis, modulated cortical functioning – indicated by blood flow (Mier et al., 2010).

Dang et al. (2012) point out that the three networks fMRI studies show are important for attention are modulated by dopamine. The dorsal attention network is focused on the external world – indicating where, when, or what to direct attention to.

The default mode network is the introspective or internal awareness attention. It shuts off when focus is on the external world. The frontoparietal control network is the mediator between the two, assessing conflict monitoring, planning, and reasoning. They found that at resting conditions (when internal attention dominates) more dopamine is synthesized with increases of activation between the default mode network and the frontoparietal control network. Meanwhile, less dopamine is synthesized with increases of activation between the dorsal attention network and the frontoparietal control network. Put simply,

during internal cognition, dopamine strengthens the attention of the internal state and

decreases attention on the external state. These results give further evidence for

dopamine’s important role in altering attention and influencing hypnotizability.

COMT and Hypnosis

Highly hypnotizable individuals have greater abilities to sustain attention and

maintain it without disturbances (Crawford et al., 1993). Electophysiological findings

support that high hypnotizables have elevated attentional abilities outside of hypnosis as

well (Schnyer & Allen, 1995). Neurophysiological evidence suggests this is due to a

more effective frontolimbic attentional system (Crawford et al., 1993; Lichtenberg et al.,

2004). The Stroop test measures a person’s attentional abilities, primarily selective

attention (MacLeod, 1992; Raz, 2005; Stroop, 1935). Hypnosis has been shown to reduce

or eliminate the Stroop color-word interference effect in high hypnotizables (Raz et al.,

2003; Raz, Moreno-Iñiguez, Martin, & Zhu, 2007; Raz, Shapiro, Fan, & Posner, 2002;

Sheehan, Donovan, & MacLeod, 1988). This has been replicated using fMRI studies (Raz

et al., 2006) showing a reduction of activity in the anterior cingulate cortex (ACC). The

ACC is an area involved with executive functioning. It is also associated with dopamine

levels (Raz, 2008). The ACC is selectively active during the hypnotic state (Lichtenberg

et al., 2004).

Highly hypnotizable people have greater involvement in the dorsolateral PFC and

increased functional connectivity between the PFC and ACC (Hoeft et al., 2012). This

relates to increased coordination between brain areas, showing that highly hypnotizables

can activate and alter different modes of attention. For some things such as pain

analgesia, Stroop interference reduction, and hypnotic resting, higher hypnotizables have

reduced ACC activation (Hoeft et al., 2012), but increased far frontolimbic PFC

activation (Crawford et al., 1993). This shows an ability to disassociate from the present

moment but devote focus and sustained attention elsewhere. Yet during hypnotically

induced cognitive tasks – where attention is necessary – there is an increase in activation

in the ACC by those highly hypnotizable (Hoeft et al., 2012). To summarize these findings: highly hypnotizable people have enhanced control over sensory, motor, and somatic functioning through their dopamine-dependent control and direction of attention

(Hoeft et al., 2012). As we’ve just seen, dopamine modulates these attentional networks

(Mier et al., 2010; Montag et al., 2012; Solanto, 1998). Drugs that act on the dopamine system seem to induce hypnotic-like experiences (Raz, 2005). So through its mediation of the availability of dopamine, COMT is related and may help predict an individual’s level of hypnotic susceptibility.

In a comprehensive study testing COMT’s effects on hypnotizability, Szeleky et

al. (2010) found a significant positive correlation of COMT to hypnotizability ( = 2 .064). They discovered that the Val allele –Val/Val carriers having the highest 𝑛𝑛

susceptibility scores and Met/Met carriers the lowest – has an additive effect on

hypnotizability. However, her study is the only one of the three studies testing COMT’s

effects on hypnotizability that showed the Val/Val to be the most responsive to hypnosis.

This may be because she is the only researcher looking at COMT’s influence on susceptibility who conducted her tests using a group scale for hypnotic susceptibility –

The Waterloo-Stanford Group C (WSGC). The other researchers used the individually presented Stanford Hypnotic Susceptibility Scale, Form C (SHSS:C).

Lichtenberg et al. (2004) found that Val/Met positively correlated to hypnotizability for the total sample and for women, but not for men. They reported that the COMT provides a genetic predictor for women, but the Tellegen Absorption Scale

(TAS) was a better predictor for men. Using these same participants in an earlier study,

Lichtenberg, Bachner-Melman, Ebstein, & Crawford, 2004) found significant correlations between COMT and hypnotizability showing the Val/Met genotype to have the highest susceptibility scores (after Bonferroni post-hoc correction, the only significance was for the Val/Met vs. the Val/Val genotypes). This was also split between non-significance for males and significance for females. Lichtenberg goes on to state that when the Met alleles are present in one’s genotype, women’s hypnotizability scores are higher than men’s (Lichtenberg et al., 2000; 2004). The gender difference Lichtenberg’s team found is rare and may stem from his use of the same participants in both studies.

Raz (2005) also found the Val/Met genotype to be associated to higher susceptibility scores. However since he did not provide thorough statistical analyses, making inferences into the strength of these findings is not viable. Raz did point out that other genes related to dopamine synthesis – DRD3, DRD4, MAOA, and DAT – were not significant. It is important to note that many genetic polymorphisms would be involved in a complex phenomenon such as hypnotizability (Raz, 2005). Thus, at this point it is

19 unclear whether or not the Val allele – by removing dopamine faster from the synapse – is an additive predictor of susceptibility or whether having one Val and one Met allele would correspond to higher susceptibility. One result of Szeleky’s team using a group scale for susceptibility is that they postulated their results differ from others because the group setting may provide increases in arousal and stress. Since the Val allele is associated with better emotional responses (warrior) to life’s stress, it makes sense that in this study they would have the highest scores on susceptibility. Lastly, Raz (2008) and

Hoeft et al. (2012) point out that these attentional networks modulating the hypnotic experience are the same networks involved in placebo responders.

Placebo

The placebo effect is the effect of a sugar pill – or inactive compound – to create the same positive results as the active treatment or medication. Randomized double-blind placebo control groups have become the norm in most pharmacological studies as the method to evaluate drug efficacy (Furmark et al., 2008). It is well documented that in many instances the placebo response benefits individuals just as much as the active drug.

In a large meta-analysis using 19 double-blind clinical trials, 2,318 patients were assessed for changes in depression. A remarkable 75% of the remission response was due to the placebo, regardless of the type of medication (Kirsch & Sapirstein, 1998). Since this recovery rate could stem from other factors – such as spontaneous remission – and since the active drug efficacy could be enhanced by the placebo phenomenon simultaneously,

the exact effect the placebo has on patient outcomes is of yet undiscovered. However,

Kirsch and Sapirstein statistically estimate that 51% of depression remission is due to the

placebo effect alone and only 25% is due to the effects of the actual medication. Even more striking is the possibility that the active medication is providing patient remission through an undercover placebo effect. This effect is produced from experiencing side- effects that are typical of receiving pharmacological intervention. Negative side-effects from pharmacological interventions have become expected. When one experiences them, they are more likely to believe the medication is working – enhancing the placebo response in conjunction with the medication’s active ingredients. This gives evidence to the idea that all responses to active medications are being intensified by the placebo effect. The placebo has been shown to activate the same pathways as the active treatment

(Furmark et al., 2008) with the most activation happening in the prefrontal cortex (Hall et al., 2012).

Hall and his team (2012) looked at COMT – because of dopamine’s effects on the

PFC – as a predictor for high placebo responders. They assessed patients (n = 102) who were suffering from Irritable Bowel Syndrome (IBS) – affecting 10-15% of Northern

Americans – because of its typically high placebo success rates (40%). They found that the Met variant had an additive effect for placebo success (relief of IBS symptoms).

COMT could only predict placebo success in the “augmented arm condition” – which means there was a supportive patient-health care interaction. In this condition the

Met/Met genotype showed a six fold increase in relief compared to their Val/Val counterparts – who essentially showed no placebo response. This is an interesting finding

because it shows that individuals carrying the Met allele would have significantly greater improvement in patient success following a more supportive and interactive health-care environment. The supportive environment may curb their greater susceptibility to anxiety, especially during times of stress. Another interesting finding was that patients on the wait list – who received no treatment – showed a reverse effect. Those with the

Val/Val genotype showed an average 50% increase in relief compared to 0% in all the patients with the Met/Met genotype. This provides further evidence of the ‘warrior’ characterization of the Val/Val genotype, as they appear to handle stress better when no real treatment is given.

More support for genetic predictors of placebo responders comes from a small sample (n = 25) that looked at the 5HTTLPR polymorphism. It was shown that less activation in the amygdala was prevalent in the placebo responders, typical of the L allele carriers (Furmark et al., 2008). This reduced amygdala activation in placebo responders was replicated in another small sample (n = 15), where subjects who reported the strongest placebo response had the greatest decrease in activity (Petrovic et al., 2005). It is important to note that results from such small sample sizes offer little evidence for an overall trend. However, studies testing for genetic makers of placebo responders are rare, so any evidence is vital for making further progress in the field.

Absorption

Absorption is a personality trait related to attention. It was developed by Tellegen

and Atkinson in 1974. Absorption is an ability to fully engage the perceptual senses with

complete attention to the moment. Many studies have looked at Absorption as the

personality trait most associated with hypnotizability (eg: Kihlstrom et al., 1980;

Lichtenberg et al., 2004; Nadon et al., 1987; Nadon, Hoyt, Register, & Kihlstrom, 1991;

Tellegen et al., 1988). Hypnosis involves amplifying and sustaining attention (Crawford

et al., 1993; Lichtenberg et al., 2004). Tellegen and Atkinson (1974) found absorption – measured through the Tellegen Absorption Scale (TAS) – to be moderately correlated to hypnotic susceptibility (r = .27 & r = .42). Since then, the TAS became the most widely used personality correlate of hypnotic susceptibility. It can predict hypnotizability (r =

.13 - .89) with mixed success (Roche & McConkey, 1990). In some instances, extremely low correlations were assessed (r = -.19 - .02) when particularly unfavorable information and negative attitudes about hypnosis were expected (Roche & McConkey, 1990). This agrees with others’ findings that expectation affects the hypnotic process (Spanos, Brett,

Menary, & Cross, 1987). Highly hypnotizable individuals score significantly higher on the TAS (Crawford et al., 1993). Even though there is extreme variance in the results,

Kihlstrom (1985) states that absorption represents the highest correlate of hypnotizability

against all other compared personality dimensions or scales.

5HTTLPR and COMT Amygdala Interactions

The major link between the 5HTTLPR polymorphism and the COMT polymorphism seems to relate to their similar activation patterns in the emotional

network, particularly in the amygdala. The amygdala plays a crucial role in terms of

emotional processing and fear conditioning (Rhodes et al., 2007). Rhodes and her team

(2007) found that serotonin availability was able explain 42% of the variability in the left

amygdala activity. Most studies report even stronger associations with the right amygdala

activity (i.e., Canli et al., 2005). Even with significant meta-analytic associations (d =

0.63) between the 5HTTLPR polymorphism and amygdala activation, only 10% of the

phenotypic variance can be account for (Munafò, Brown, & Hariri, 2008). It is likely

some of the unexplained variance comes from the addition of the Val158Met COMT

polymorphism.

Individuals who were homozygous for the Met allele showed greater activation in

the right amygdala to negative or unpleasant images (Montag et al., 2012). This is similar

to those individuals carrying the S allele (Canli et al., 2005; Fox et al., 2009; Lesch &

Gutknecht, 2005; Pacheco et al., 2009). The stronger amygdala reactivity mediates the

association between environmental threat and the resulting negative affect or mood

disorder (Munafò et al., 2008). This was confirmed using fMRI data shown in both the

Met allele carriers and the S allele carriers (Lesch & Gutknecht, 2005; Montag et al.,

2012). There is lower connectivity between the amygdala to PFC and ACC – important

for inhibiting amygdala activation – in S alleles and Met alleles (Pezawas et al., 2005).

This provides a mechanistic account for their higher amygdala activity.

Pharmacological – such as the chronic use of SSRI’s and benzodiazepines – as

well as cognitive behavioral therapeutic success has shown to decrease amygdala responsiveness and hyperactivity (Furmark et al., 2008). CBT is a form of extinction learning through the regulation of fear responses, produced by high amygdala firing

(Bryant et al., 2010). Individuals carrying the S allele or the Met allele have greater amygdala activation to threatening stimuli and hyperactivity to overly conditioned startle responses (Bryant et al., 2010; Montag et al., 2012). This basic mechanistic account has allowed predictions of both personality characteristics and treatment responses, regardless of treatment modality. It appears that over-activation of the amygdala – associated with either the S or Met alleles – is correlated to increase risk of mood disorders.

Benjamin and his team (2000) looked at personality correlates for both the

5HTTLPR and COMT genotypes using the Tridimensional Personality Questionnaire

(TPQ). They found a significant correlation in persistence (RD2) scores in sibling pairs

with identical genotypes. Siblings differing by one genotype – or both – did not show this

relationship. Absorption (r = .17) and hypnotizability (r = .27) are moderately correlated

to persistence (Lichtenberg et al., 2004). They discovered a main effect of 5HTTLPR and

COMT on persistence. However, the largest effect was due to the interaction between the two polymorphisms. This shows that not only do these genes influence personality, but their interactions can be an even more important target of investigation.

Single-gene studies do contribute to our understanding of how genes influence important aspects of individuality. However, the reality is much more complicated.

Looking at multiple genes and the way they interact with each other – including the influences by the environment – is the most effective way to individualize treatment options (pharmaceutical or otherwise).

Statement of the Problem

The current study investigates whether two common gene variants – a

polymorphism in the gene encoding the serotonin transporter (5HTTLPR) and a

polymorphism in the gene encoding dopamine metabolizing enzyme COMT – act

individually or together to influence individual susceptibility to hypnosis in healthy

people. These gene variants are known to influence other aspects of psychology and

behavior. This provides a foundation for the hypothesis that they may also influence

hypnotizability.

Genetics contribute to the phenotypic expression of an individual’s personality

(Borkenau et al., 2001; Riemann et al., 1997; Tellegen et al., 1988). The genetics of

personality are complex and polygenetic in nature (Schinka, Busch, & Robichaux-Keene,

2004). Nonetheless, certain gene variants have been shown to be consistently associated with particular personality traits. The availability of serotonin mediated by 5HTTLPR has been shown to correlate to personality (Hamer, Greenberg, Sabol, & Murphy, 1999: See their Table 1 & 2 for a review; Schinka et al., 2004; See their Table 1 for a review). The availability of catecholamines – especially dopamine – mediated by the enzyme COMT also influences personality (Montag et al., 2012: See their Table 3 & 4 for a review of results). Hypnotizability is a stable personality trait (Piccione et al., 1989). Because personality is influenced by a wide array of genetic contributors in extremely varying environments, studies using multiple genetic indicators are better able to find genetic linkages to neural functioning and resulting behaviors. To continue the difficult task of

finding genetic contributors to personality and behavior, this study will examine

associations of the 5HTTLPR and COMT gene variants – separately and together – with one facet of personality, hypnotizability. This study has implications for clinical psychology. Information about an individual’s susceptibility to hypnosis would aid clinicians in the diagnosis and prescription of this psychotherapeutic strategy. There are currently few good diagnostic tests for susceptibility to hypnosis.

Variants of the gene encoding the serotonin transporter 5HTTLPR result in various predictive outcomes. 5HTTLPR variants can predict success of antidepressant therapy with SSRI’s (Lesch & Gutknecht, 2005). 5HTTLPR variants can predict successful CBT responses for patients with PTSD (Bryant et al., 2010). CBT was shown to be the most effective type of psychotherapy in a large meta-analysis (Hofmann et al.,

2012), indicating the great importance of understanding genetic and other factors that

influence response to CBT. Variants of 5HTTLPR can also predict amygdala firing rates

(Lesch & Gutknecht, 2005). The S allele is shown to have increased amygdala activation

to emotional or threatening stimuli compared to the L allele (Munafò et al., 2008). Lower

amygdala reactivity results in greater resilience to environmental stressors (Lesch &

Gutknecht, 2005). Successful results with antidepressants, therapeutic treatments, and

placebos are associated with a reduction in amygdala reactivity to emotional or

threatening stimuli (Furmark et al., 2008; Petrovic et al., 2005). The fact that the L allele

and successful psychotherapy responses are both associated with lower amygdala activity

provides some explanation for the association of the L allele with more successful CBT

treatment in PTSD patients (Bryant et al., 2010). It is possible that 5HTTLPR variations

in amygdala activity can similarly predict success in hypnotherapy.

Initial evidence shows the catechol-o-methyltransferase (COMT) Val158Met polymorphism mediates the strength of placebo responders (Hall et al., 2012) which operate on the same neural networks as hypnotic susceptibility (Hoeft et al., 2012; Raz,

2008). Therefore, the present study also has implications for pharmaceutical industries who work hard as predicting and identifying who will respond in these ways. The placebo effect has an additive quality on hypnotizability. Participant attitudes can affect the hypnotic process (Spanos et al., 1987) and alter susceptibility (Roche & McConkey,

1990). Positive expectations and attitudes correspond to greater susceptibility (Roche &

McConkey, 1990) and higher success rates (Hall et al., 2012; Spanos et al., 1987). The influence of COMT on hypnotic susceptibility and on the placebo effect is proposed to be due to changes in the functioning of the prefrontal cortex (PFC) (Furmark et al., 2008;

Hall et al., 2012). PFC activation affects various aspects of attention (Dang et al., 2012).

COMT mediates the availability of dopamine, particularly in the PFC (Montag et al.,

2012). Dopamine modulates PFC functioning (Solanto 1998). It is through these series of connections that dopamine affects attentional networks (Dang et al., 2012). The analgesic effects of hypnosis may be explained in part by a shift of the patient’s attention away from the painful event (Crawford et al., 1993), providing further support for a relationship between hypnosis and dopamine neurotransmission. Thus, COMT’s mediation of the availability of dopamine in the PFC affects hypnotizability through its

affects on attention. Previous research supports COMT’s effects on hypnotic

susceptibility (Lichtenberg et al., 2000; Raz, 2005; Szekely et al., 2010), but results are

mixed on which polymorphism is most correlated. This is likely due to different testing

strategies and sample disparities.

The 5HTTLPR and COMT polymorphisms may interact in additive ways during

the hypnotic process. Variants of 5HTTLPR and COMT polymorphisms can both predict

amygdala firing rates (Montag et al., 2012; Munafò et al., 2008). There is greater amygdala activation to threatening stimuli and increased reactivity to stressful environments (Bryant et al., 2010; Montag et al., 2012). The S allele of the serotonin transporter gene and the Met allele of the COMT gene are both associated with weaker

connectivity between the amygdala and prefrontal cortex (Montag et al., 2012; Pezawas

et al., 2005). This amygdala activity affects attention – as shown with increased

rumination (Canli et al., 2006) and focus on the negative aspects of life (Fox et al., 2009).

The 5HTTLPR and COMT genotypes may therefore be expected to influence attention to

negative emotions through their effects on amygdala activity. Greater focus on negative

emotions – expected in S allele (5HTTLPR) and Met allele (COMT) carriers – also predicts lower hypnotizability (Hilgard, 1979). Negative attitudes were shown to decrease the correlation between absorption (Roche & McConkey, 1990) and hypnotizability

(Kihlstrom et al., 1980; Lichtenberg et al., 2004; Nadon et al., 1987; 1991; Spanos et al.,

1987; Tellegen et al., 1988). Thus, lower amygdala activation, or hyperactivity to emotional stimuli would alter hypnotizability. This corresponds to Szeleky’s team’s findings (2010) that participation in the group setting elicits greater stress but Val’s emotional coping mechanism counteracts any displacements in hypnotizability. Another

personality dimension persistence (RD2) is moderately correlated to absorption and

susceptibility (Lichtenberg et al., 2004). It was in the interaction of 5HTTLPR with

COMT that the largest effect was discovered (Benjamin et al., 2000). This shows that the

way 5HTTLPR and COMT interact may be more important – on personality constructs

such as hypnotizability – than the single-gene influence each has alone.

The Tellegen Absorption Scale (TAS) assesses the personality trait most strongly

correlated to susceptibility (Kihlstrom, 1985). However, these associations vary widely (r

= .13 - .89) due to experimental conditions and sample variations (Roche & McConkey,

1990). Tellegen found correlations of .27 and .46 between absorption and susceptibility

to hypnosis (Tellegen & Atkinson, 1974). Since then, usage of the TAS has expanded

greatly. The current study will measure absorption and hypnotizability, along with information about potential genetic modifiers. This could support a new theoretical explanation for the mixed variance in this psychological trait – absorption.

Hypnosis is an empirically supported clinical intervention (Lynn et al., 2000) that provides a safe alternative to pharmaceuticals (Holroyd, 1996). Hypnosis has been shown effective at treating addiction, phobias, mood disorders, eating disorders, dissociative identity disorder, PTSD, pain management, somatization, other psychotic disorders, grief, trauma, aliments from cancer, and a wide range of pain related issues (Jensen &

Patterson, 2006; Kirsch et al., 1995; Montgomery et al., 2000; Patterson & Jensen, 2003;

Rhue et al., 1993). All of these conditions are typically treated with powerful psychotropic drugs. When used conjunctively, hypnosis increases the efficacy of

psychotherapeutic interventions, most notably with cognitive-behavioral techniques, d =

2.55 (Kirsch et al., 1995; Kirsch, 1996).

Some people find hypnosis more effective than others (Montgomery et al., 2000).

Better predictors of hypnotizability would result in higher hypnotherapeutic success – saving valuable time and resources. Establishing a knowledge base of genetic modifiers of hypnotic susceptibility could benefit patient outcomes across a wide range of psychotherapeutic goals, while simultaneously reducing our reliance on dangerous pharmacological interventions. Therefore, identifying reliable predictors of hypnotic susceptibility is a valuable research goal.

Hypothesis 1. Individuals homozygous for the L allele on the serotonin transporter 5HTTLPR polymorphism will score higher on the Harvard Group Scale for

Hypnotic Susceptibility Form A than those carrying one or two S alleles. Rationale for

Hypothesis 1: 5HTTLPR variants affect aspects of personality across a broad scale

(Lesch & Gutknecht, 2005; Schinka et al., 2004). Having one type of allele over another creates significant changes in the way someone perceives their surroundings, and where to focus attention (Fox et al., 2009). Hypnotizability is a stable personality trait (Piccione et al., 1989) that is positively correlated to abilities of enhanced and sustained attention

(Crawford et al., 1993). The S allele is associated to negative emotionality and vulnerability to mood disorders (Lesch & Gutknecht, 2005). Negative attitudes and expectations are associated with lower levels of hypnotizability (Spanos et al., 1987).

Participants who have more apprehensive or anxious attitudes participate less in the hypnotic process (Hilgard, 1979). Thus, it is likely the vulnerability of the S allele to

develop mood disorders will relate to participant’s involvement in the hypnotic process –

resulting in lower susceptibility scores. This may be particularly so when tested in the

group setting, potentially provoking more stress (Szekely et al., 2010) – something the S

allele carriers are less likely to handle constructively (Lesch & Gutknecht, 2005).

Hypothesis 2. Individuals homozygous for the Val allele on the COMT

Val158Met polymorphism will score higher on the Harvard Group Scale for Hypnotic

Susceptibility Form A than those carrying one or two Met alleles. Rationale for

Hypothesis 2: Hypnotizability is directly related to sustained attention (Crawford et al.,

1993). COMT alters the availability of dopamine, especially in the PFC (Montag et al.,

2012). Dopamine modulates the functioning in the PFC, altering attentional networks

(Dang et al., 2012; Mier et al., 2010; Solanto, 1998). The PFC is important for attention

(Wager et al., 2004). Previous studies have confirmed this association, demonstrating that

COMT influences hypnotic susceptibility (Lichtenberg et al., 2000; 2004; Raz, 2005;

Szekely et al., 2010). The Val allele was shown to have an additive effect – correlating to higher hypnotizability scores – when tested in the group setting (Szekely et al., 2010).

Additionally, Met carriers have overly reactive amygdala firing (Montag et al., 2012).

This leaves them more reactive to life’s stressors (Montag et al., 2012). Individuals undergoing hypnosis in a group setting are more likely to be anxious or have higher levels of stress (Szekely et al., 2010). Thus, the negative emotionality associated with the

Met allele will detrimentally impact individuals’ level of susceptibility.

Hypothesis 3. Individuals homozygous for the L (5HTTLPR) and Val (COMT) alleles will score the highest on the Harvard Group Scale for Hypnotic Susceptibility

Form A and individuals carrying both the S and the Met alleles will have the lowest

scores. Rationale for Hypothesis 3: SERT and COMT are associated with a wide range of

personality phenotypes (Hamer et al., 1999; Montag et al., 2012). There are similarities in

neurocognitive functioning between the polymorphic variants of 5HTTLPR and COMT

(Lesch & Gutknecht, 2005; Montag et al., 2012). 5HTTLPR and COMT interacted strongly when it came to a personality dimension correlated to hypnotizability (Benjamin et al., 2000). Szekely and her team (2010) showed that the Val/Val genotype scored highest for hypnotic susceptibility on the group scale and Met/Met scored the lowest.

When it came to hypnosis, the added arousal of the group experience could modulate the effects the COMT genotype has on hypnotizability. If being homozygous for the L allele is also advantageous towards susceptibility (see Hypothesis 1) there could be an additive effect of having both the better coping alleles. It can be hypothesized that the better coping Val allele can mediate the greater vulnerability of the S allele. The same advantage the Val allele provides during stressful environments, may correspond to the advantages the L allele provides in stress coping. It is therefore considered most likely that the Met/Met and S/S genotypes will score the lowest on hypnotizability, especially in the group setting.

Hypothesis 4. Individuals who have higher scores on the Tellegen Absorption

Scale will also have higher scores on the Harvard Group Scale for Hypnotic

Susceptibility Form A. Rationale for Hypothesis 4: Absorption is an ability to become fully absorbed in the moment with total focus in the present (Tellegen & Atkinson, 1974).

Hypnosis is also associated with an increased attentional functionality and an inability to

become distracted to external influences (Crawford et al., 1993). Higher absorption has

been shown to be related to higher hypnotic susceptibility scores in numerous studies

(i.e., Kihlstrom et al., 1980; Lichtenberg et al., 2004; Nadon et al., 1987; 1991; Spanos et al., 1987; Tellegen et al., 1988). The TAS is the strongest personality measure of

hypnotic susceptibility (Kihlstrom et al., 1985), although variations in testing strategies

and sampling procedures alter the strength of the association (Rosch & McConkey,

1990). Negative attitudes and expectations are correlated to lower hypnotizability and

lower absorption scores (Spanos et al., 1987). In these cases absorption has shown to

correlate negatively to hypnotizability (Rosch & McConkey, 1990).

See Figure 1 for a diagram of my hypotheses and their associated pathways.

Figure 1. Hypotheses 1-3. This figure shows the allelic breakdowns of the SERT and COMT genes and the pathways that they influence hypnotizability. I hypothesize that through the resiliency to stress and the more efficient attentional network, the LA and Val alleles will act independently and additively to increase participant hypnotizability.

Method

Participants

There were three different recruitment strategies used to obtain participants with a more representative sample size. One-hundred participants were recruited using the

psychology research participation pool at Humboldt State University. Due to the

demographic distribution in the psychology pool, these participants were predominately

Caucasian, female, and between 18-23 years of age. The second recruitment strategy was tabling on the HSU quad (an area in the center of campus) with a sign that reads

“interested in participating in exciting new research about hypnosis and genetics?”

Permission to table during the month of October of the 2013 Fall Semester at HSU was

approved by the head of Clubs and Services, Tanza Triggs, and authorized by the Dean of

Students, Randi Darnall Burke. Another hundred participants were recruited utilizing this

strategy. The third strategy for recruiting was through inviting HSU students to

participate by making announcements at the beginning or end of classes offered at

Humboldt State University. Course instructors were emailed to ask permission to make

an announcement about the study at the beginning of their classes. Courses relating to

psychology and biological sciences were targeted since these students are expected to be

more interested in the topic of research and therefore, more likely to participate. The

announcement in class will be “My name is Kyle Wannigman. I am recruiting

participants for my Master’s thesis, researching genetic factors that influence hypnosis.

The study takes about 120 minutes and participants can enter a raffle for three $50

Amazon gift cards. If you are interested, you can learn more and schedule a time to

participate by emailing me at [email protected].” The last fifty

participants were recruited using this strategy. There were more equal numbers of male

and female participants with a wider distribution of ages: 18-69 years old. An expedited

IRB approval (IRB #: IRB 13-012) for the protection of human subjects was granted on

August 28th, 2013.

Instrumentation

Participants were tested on both the Tellegen Absorption Scale and The Harvard

Group Scale for Hypnotic Susceptibility, Form A. The Tellegen Absorption Scale (TAS)

was developed by Tellegen and Atkinson in 1974. It is now included as one of the scales

in the Multidimensional Personality Questionnaire (MPQ) (Glisky,

Tataryn, Tobias, Kihlstrom, & McConkey, 1991). The TAS measures a personality

characteristic called “absorption” – a disposition to fully engage the perceptual senses with complete attention to the moment. The TAS includes 34 dichotomous items in a true and false format with an internal consistency reliability of .88 (Patrick, Curtin, &

Tellegen, 2002). The TAS has been shown to have a test-retest reliability of .91 during a

30-day interval (Angelini, Kumar, & Chandler, 1999).

Shor and Orne (1963) developed the Harvard Group Scale of Hypnotic

Susceptibility, Form A (HGSHS-A) to simultaneously test multiple individual’s

susceptibility to hypnosis. This test was developed to save research time. It has a Kuder-

Richardson reliability of .80 (Shor & Orne, 1963), although more recent studies have

shown less reliability: .74 in 1990 and .72 in 1996 (Angelini et al., 1999). This reliability

is comparable to that of Stanford’s (SHSS:C) individual susceptibility scale (α = .83).

The two scales are significantly correlated (r = .78). The HGSHS-A involves participants in a series of 12 tests with the possibility of getting one point for each passed test. An example of one of these tests is eye or arm catalepsy. After the group is induced into hypnosis, the participants are told that they cannot open their eyes or bend their arm and the harder they try, the stronger the hold. Those more susceptible will perform more of the tasks compared to those who are less susceptible. Thus, higher scores relate to higher susceptibility. The authors estimate a predictive validity coefficient of .74, assuming homoscedasticity and linearity of relationships (Shor & Orne, 1963). After each session, participants were given time to fill out the subjective experience response booklet which was scored from 0-12.

Procedure

Two-hundred and fifty-three college students (155 female, 143 Caucasian, 83

Psychology majors) from HSU were genotyped and assessed for hypnotic susceptibility.

People came into the BSS room 211 in groups of 8-14. Participants were given a packet of forms to fill out. The first was the informed consent. Next, participants completed the

Tellegen Absorption Scale (TAS), which took about 5 minutes to complete. Then

participants then were given an informational sheet about hypnosis – to standardize

expectations – and an opportunity to ask questions or leave the study was offered.

Participants then provided a DNA sample in the form of a cheek swab for later analysis.

The entire cheek swab process took approximately 2 minutes per person to complete,

using a commercial kit (Whatman EasiCollect). Each cheek swab was then given a

unique alphanumerical code. This ensured participant confidentiality. However, in the

unlikely case that somehow the information got taken, the participants are federally

protected under the Genetic Information Nondiscrimination Act of 2008. This act passed

by congress protects individuals from being discriminated against because of their

genetic profile, specifically with health insurance companies and employers. Thus, any

damage that could have come from the theft of genetic information was extremely

limited.

Next participants were seated to complete the Harvard Group Scale of Hypnotic

Susceptibility, Form A (HGSHS-A). This provided a way to simultaneously test individual’s susceptibility to hypnosis in groups less than 15. The script was prerecorded, with the volume and the lights adjusted equally to ensure the most control for testing conditions. As per the HGSHS-A, a brief introduction was given and then the recording was played. The entire process took approximately one hour. Once the recording finished, participants were asked to fill out the corresponding subjective response booklet. Those highly susceptible should report higher scores than those who are less susceptible. Participants’ entire time commitment was 2 hours. Lastly, participants were given a list of low cost mental health treatment centers in the unlikely case that their

39 experience in this study elicited a desire to have psychological counseling. Free counseling is available by trained professionals in HSU’s Student Health Center. Once all of the participants finished their testing sessions, data analysis began to ensure that this remained a double blind experiment. Neither participant nor researcher could know the allelic results until after all the data were collected.

Consent. There were two written consent forms that the participants had to sign prior to any participation in this study. One form was to participate in the study while the second form was for collecting genetic information in the form of a cheek swab.

Signatures on consent forms were required before each participant was allowed to take part in any aspects of testing. Participants were first given the consent form titled

“Consent to participate in the Wannigman Hypnosis Study”. Next, the participants were required to sign the second consent form before the cheek swab sample was collected from any participant. This consent form was titled “Consent to provide a cheek swab sample for genetic testing”. Lastly, participants who wish to know the results of their genetic testing will be given the opportunity. However, participants will only be given their genetic information if they sign a final consent form, notifying them of the potential repercussions of accessing this information. Since the genotyping is not complete yet, this final consent form has not been used. Once my analyses are finalized, this option will still be available to participants who wish to know their allelic variants. The form will explain that genetic factors do not determine psychology, behavior, or health, but merely contribute to it. Additionally, a list of local, low cost, mental health professionals will

again be provided in the unlikely case that someone has an aversive reaction to this

knowledge.

Any time a participant volunteered for testing they were required to fill out an informed consent sheet and were reminded of their right to withdrawal at any time, without any negative reflection or consequence. The consent procedure requested that minors and pregnant women do not participate.

Effect Size. Currently, no studies have looked directly at the effects the SERT gene has on susceptibility and only a few studies exist that relate COMT directly to hypnotizability (summarized in the lit review). Previous research supports the existence of the hypothesized relationships between the COMT and SERT genotypes with hypnotizability, but do not provide direct estimates of the magnitude of the hypothesized effects. Since this is a novel study, the predicted effect size used for this power analysis was based on two additional considerations:

This study was being designed to detect large effects because only a large effect would be of theoretical and clinical interest. Consistent findings in literature show main effects of both alleles on personality traits related to hypnotizability. If these alleles contribute significantly but only a small amount to determining a person’s level of hypnotic susceptibility, that would not be of practical use for matching patients to therapies in real world applications. Therefore, this study is designed to detect main effects of d = 0.5 for each gene.

The two genes being studied are hypothesized to influence hypnosis through different biological mechanisms (attention vs. susceptibility to mood disorders). It is this

rational framework and evidence from a previous study on a personality correlate of

susceptibility (Lichtenberg et al., 2004) that I could expect the effects from each gene to be additive. Therefore, the predicted interaction effect size should be larger than the main effects. I selected d = 0.65 as the predicted interaction effect size. This would mean that the presence of both susceptibility gene variants would lead to greater hypnotizability than the presence of either one alone.

This initial experiment could pave the way for future studies to emulate with a lager sample base. If significant effects contribute largely to predicting susceptibility, than larger studies or meta-analyses may validate these findings for some truly remarkable advances in personalized therapy – particularly hypnotherapy.

Genotyping

Genotyping was completed here at the Bio Core lab on campus with the supervision of Anthony Baker and Darrell Burlison. DNA extraction from cheek swabs was performed using a Whatman EasiCollect Kit protocol. The DNA can be stored on the

FTA cards for up to two years and there were four samples per card. To extract the DNA,

I cut out a small piece of the FTA card and added 150 µL of a 5% Chelex solution for each sample on a 96 well plate. It was placed on the thermocycler for 4 hrs at 56ºC, 30 min at 98ºC, and held at 4ºC. After centrifuging for 10 min, 30 µL of each supernatant was transferred to a new 96 well plate. Each sample was then diluted 9:1 by double distilled water and stored in a –20ºC freezer until PCR was ready to be accomplished.

SERT. DNA amplification of the 277bp short allele and the 310bp long allele,

was performed in a total volume of 25 µL containing 12.5 µL GoTaq 2X colorless master

mix, 0.75 µL Forward Primer from 10 µM stock, 0.75 µL Reverse Primer from 10 µM

stock, 7.0 µL Nuclease free water, and 4.0 µL of template DNA at 6ng/µL for a total of

24ng of DNA. The primers used for the amplification of the 5-HTTLPR were 5’-

TGAATGCCAGCACCTAACCC -3’ and 5’- TTGGAGGAACTGACCCCTGA -3’.

These were purchased from Integrated DNA Technologies. PCR cycle conditions

included 2 minutes of denaturation at 95oC, followed by 35 cycles of denaturation at

95oC for 30 seconds, 45 seconds annealing at 60oC, and extension for 45 seconds at 72oC.

The final extension was for 5 minutes at 72oC. Amplified products were run on a Bio-

Rad Criterion Cell gel system using a 5% polyacrylamide-TBE gel at 200V for 60

minutes. Three qualified raters examined each gel until a unanimous decision was made.

For the complete SERT genotyping protocol see the Appendix. Only 61 results were

established for the SERT gene at this time.

COMT. Genotypes for the COMT rs4680 were obtained using the DME Taqman

SNP genotyping assay in a total volume of 25 µL containing 12.5 µL Taqman

Genotyping Master mix 1x1ml, 1.25 µL 20X working stock of SNP Genotyping Assay, and 11.25 µL Nuclease free water. The primers used were (forward) 5'-

GAGATCAACCCCGACTGT-3' and (reverse) 5'- CAGGCATGCACACCTTGTC-3', and reporter sequences TTTCGCTGGCGTGAAG (vic) and TCGCTGGCATGAAG

(fam). Primers were purchased from Life Technologies. PCR cycle conditions included

10 min of denaturation at 95oC, followed by 40 cycles of denaturation at 92oC for 15

seconds and 60 seconds annealing at 60oC. An endpoint plate read was accomplished

using an applied biosystems real-time PCR System. The Sequence Detection System

(SDS) software uses the fluorescence measurements made during the plate read to plot fluorescence (Rn) values based on the signals from each well. The plotted fluorescence signals indicate which alleles are in each sample. All of the 253 results were positively identified for the COMT gene.

See Table 1 for the absolute frequencies of the SERT and COMT genotypes found in this sample. See Figure 2 for a sample of the gel analysis on the SERT gene.

Table 2 Absolute Frequencies of Genotypes COMT Val/Val Val/Met Met/Met

70 119 64

S/L, LG/L, S/LA SERT LA/LA S/S & S/LG LG/LA 6 31 24 Note. Results are consistent with what is expected in the population (Lesch & Gutknecht, 2005; Montag et al., 2012)

Figure 2. SERT Polyacrylamide Gel Analysis. Three qualified raters examined each gel until a unanimous decision was made. One gel is shown (as a negative) with the base pair band widths designated by the ladder to its left. Here the results are color coded by the experimenter to show the method through which the decisions were made. There is an extra band width at base pair 62 that all the SERT 5HTTLPR variants share.

Data Analysis

To look for a main effect (of the results I was able to obtain for the SERT gene) for SERT, COMT, and their interaction effects on hypnotizability, a 2 by 2 factorial

ANOVA was ran to test Hypothesis 1, 2 and 3, respectively. To look for a main effect of

COMT on hypnotizability with the full n = 253 sample size – a different version of

Hypothesis 2 – a one factor ANOVA was ran comparing HGSHS-A scores across the 3

COMT genotype groups. Lastly, a Pearson product-moment correlation coefficient was ran to assess the relationship between the TAS and HGSHS-A scores to determine if higher TAS scores related to higher susceptibility scores – Hypothesis 4.

Results

Out of 12 possible hypnotic suggestions on the HGSHS-A, the mean response

number was 7.2 (SD = 2.5), and the range was 0-12. These scores were normally

distributed as confirmed by skew and kurtosis values within limits.

Due to the complex nature of genetic analysis, only 61 of the 253 participants

were correctly identified for the Serotonin Transporter gene. There were complications

getting the secondary breakdown of the L allele into its two subparts, the LA and the LG.

The LG acts like a short allele, which leaves only the LA as a true long. Due to normal allelic frequencies in the population, I only ended up with 6 LA/LA genotypes. To

generate more interpretable results – consistent with previous research (Kenna et al.,

2012; Lesch & Gutknecht, 2005) – I dichotomized the SERT gene into two groups.

Group 1 is L carriers (S/L, LG/L, S/LA, LA/LA) and Group 2 is not L carrier (S/S & S/LG).

No main effect for the serotonin transporter gene on hypnotizability was found, n

2 = 61, F(1, 55) = 2.30, p = .135, ηp = .040. Group 2 (M = 7.80, SD = 2.41) was not

significantly different than Group 1 (M = 7.09, SD = 2.40) on hypnotizability scores as

measured by the HGSHS-A. This means my Hypothesis 1 – the L allele would result in

greater hypnotizability scores – was not supported (Figure 3). The good news is that

although the sample size was much smaller than my entire collection of participants, the

n = 61 was representative, both in allelic frequency in the population, and in overall

hypnosis susceptibility scores. See Table 2 for the genotypic frequencies of the SERT

gene on low, medium, and high HGSHS-A scores.

(S/S & S/LG)

8 (S/L, LG/L, S/LA, LA/LA) A Scores A -

HGSHS 7

6 Group 1 (L carriers) Group 2 (non-L carriers) SERT 5HTTLPR

Figure 3. SERT-Hypnotizability Results, n = 61. This figure shows the SERT gene dichotomized (because I only had 6 LA/LA) into 2 groups. 1 = L carriers (S/L, LG/L, S/LA, LA/LA); 2 = not L carrier (S/S & S/LG). Error bars represent standard error of the mean uncorrected for the influence of other factors (COMT genotype). Y-axis is HGSHS-A scores. SERT was not related to hypnotizability.

Table 3 Allelic Frequencies of SERT for HGSHS-A

SERT

S/L, LG/L, S/LA HGSHS-A LA/LA S/S & S/LG LG/LA Low 2 3 3

Med 1 19 8

High 3 9 13 Note. Scores are designated Low (0–4), Medium (5–7), and High (8–12) for HGSHS-A

All of the 253 analyses for the COMT gene were analyzed (Figure 4). It was

found that COMT was not related to susceptibility, n = 253, F(2, 250) = 0.384, p = .682,

2 ηp = .003. The Val/Met genotype (M = 7.26, SD = 2.66) was not significantly different

from the Val/Val genotype (M = 7.19, SD = 2.54), nor the Met/Met genotype (M = 6.92,

SD = 2.20). This means that my Hypothesis 2 – the Val allele would result in greater

hypnotizability scores – was not supported. See Table 3 for the genotypic frequencies of

the COMT gene on low, medium, and high HGSHS-A scores.

Figure 4. COMT-Hypnotizability Results (n = 253). This figure shows the COMT gene broken into its 3 groups. Error bars represent standard error of the mean uncorrected for the influence of other factors (SERT genotype). Y-axis is HGSHS-A scores. COMT was not related to hypnotizability.

Table 3 Allelic frequencies of COMT for HGSHS-A

COMT

HGSHS-A Val/Val Val/Met Met/Met

Low 13 23 7

Med 28 51 40

High 29 45 70 Note. Scores are designated Low (0–4), Medium (5–7), and High (8–12) for HGSHS-A

For the interaction effect, the smaller sample size had to be used. This caused

complications for the particular type of analysis I could do because there were unequal group sizes. Nonetheless, my results for the interaction effect showed that COMT and

SERT do not interact to influence susceptibility directly, n = 61, F(2, 55) =0.643, p =

2 .530, ηp = .023. This means my Hypothesis 3 – the LA and Val alleles would interact

additively to result in the greatest hypnotizability scores – was not supported. So far, no

inferences can be made on the link between the two genes of interest and susceptibility

scores. None of my first three hypotheses were supported. See Table 4 for the descriptive

statistics from the 2 by 2 factorial ANOVA.

Table 4 Descriptive Statistics for the interaction effect HGSHS-A Scores

SERT Group 1 SERT Group 2 (S/L, LG/L, S/LA, LA/LA) (S/S & S/LG) COMT n M SD n M SD Val/Val 12 7.5 2.32 5 9.6 0.55

Val/Met 16 6.9 2.78 11 7.3 2.83 Met/Met 9 6.9 1.90 8 7.4 2.13 Note. A 2X2 factorial ANOVA was used to observe the interaction of SERT and COMT on HGSHS-A scores. No interaction effect was observed.

Lastly, the TAS (M = 17.94, SD = 7.53) was not related to susceptibility, n = 253,

r(251) = .067, p = .144, as measured by the HGSHS-A scores (M = 7.15, SD = 2.51).

This means that my Hypothesis 4 – the TAS would be positively correlated with susceptibility scores – was not supported.

See Table 5 for the correlation matrix between all four variables.

Table 5 Correlation Matrix of variables Measure 1 2 3 4

1. SERT

2. COMT -.126

3. TAS .077 -.042

4. HGSHS-A .145 .008 .067

Note. The SERT is dichotomously scored. None of my results are significant (p < .05).

Discussion

At the time this study was designed there was no published research on the

relationship of hypnotizability – a personality dimension related to successful

hypnotherapeutic outcomes – to the two genetic components most widely known for their

effects on personality, COMT and SERT. Previous research had looked at COMT’s

associations but this would have been the first study ever to look at the serotonin

transporter as an independent and interactional link to hypnotizability. However, a recent

publication reports the first ever test of COMT and SERT associations with

hypnotizability (Rominger et al., 2014). Nonetheless, I was unable to find a direct

relationship of SERT, COMT, or the interaction of the two, on hypnotizability. I was also

unable to find a relationship for the TAS on hypnotizability. A thorough discussion of the

possible implications, limitations, and future directions from this research are as follows.

SERT Results

The serotonin transporter gene-linked polymorphic region 5HTTLPR was not

related to hypnotizability using the HGSHS-A. This agrees with the most recently

published research. Rominger et al. (2014) found no main effect or interaction effect of

the SERT variants on hypnotizability – regardless of a potential moderator, attentional

control. Yet, they did not break down the L allele into its constituent parts – LA and LG. It may be this oversight which has led to their lack of positive results. That makes my current study the first ever to look at the SERT gene – with its appropriate breakdown of

the L polymorphism based on its biological functionality – as a direct link to

hypnotizability. So far, my results provide no linking support for this relationship. It

would be beneficial to get more data on the link between the SERT gene and

hypnotizability – with its appropriate L allele breakdown – before it is ruled out as a

possible candidate gene for predicting hypnotizability.

COMT Results

The catechol-o-methyltransferase Val158Met polymorphism was not related to

hypnotizability using the HGSHS-A. Rominger and his team (2014) discovered that those homozygous for the Met allele (COMT) have the highest susceptibility scores when attentional control is high. However, when you remove the moderating variable of attention, you also take away this relationship. COMT was not associated to hypnotizability on its own. This moderating variable of attention is consistent with the theory behind my current hypothesis. Although I had a failure to replicate previous findings (Lichtenberg et al., 2000; 2004; Raz, 2005; Szekely et al., 2010), it is very likely due to differences in attentional abilities. Another recently published article with a larger sample size (n = 185) used the HGSHS-A for their hypnotizability measure (Bryant,

Hung, Dobson-Stone, & Schofield, 2013). They too were unable to find a main polymorphic effect of the COMT gene.

Whether hypnotizability was tested in a group setting, or individually, may explain some of these inconsistencies in published studies. The testing method may

55 interact with genetic factors to influence responsiveness to hypnotic suggestions.

Specifically, in group settings where participant anxiety may be greater, Val allele carriers would prosper (Szekely et al., 2010) because faster dopamine clearance enhances attention and performance under pressure. However, in individual testing, attentional demands may be lower because of the exclusive focus from the tester. In those settings,

Met allele carriers may prosper because slower dopamine clearance promotes attention and performance in calm, non-stressful environments (Rominger et al., 2014). Three studies have tested individuals in the group setting, but only two have shown this interaction effect. The Rominger study (2014) used the individual testing measure

(SHSS:C) in small groups of 5-10 people with two trained experimenters. However, since the SHSS:C was not intended for groups, it is unclear what exactly produced the low level participant responsiveness in this study. It could have been an artifact with the test itself or it could have been because they used two experimenters simultaneously in a smaller group size. The important point to take away is that to find the most reliable genetic contribution towards hypnotizability, individually-administering the SHSS:C while also assessing attention is the best approach. COMT is not the only influence on attention. Attention is a complex neurocognitive process that is still not completely understood. Other gene variants (i.e., the MAO-B gene) and complex interactions are also likely to influence attentional faculties. A comprehensive and thorough investigation into the contributing genes for attention and their interactive effects would be a worthy and valuable project.

SERT and COMT Interaction Results

At this time there is no evidence that SERT and COMT interact to influence hypnotic susceptibility. Previous research has yet to find any two alleles that interact additively to increase hypnotizability. Given that my results show non-significant main effects and the non-significant results of the most recent publication (Rominger et al.,

2014), it is likely that there will not be a relationship. However – as with the SERT gene polymorphic main effect – it would be beneficial to produce more SERT results before these hypotheses are put to rest. Given the status of my unequal group size, a larger sample would provide more interpretable results and yield greater statistical power.

TAS Results

In my current study, the Tellegen Absorption Scale did not correlate significantly with hypnotic susceptibility. In general, the research literature shows inconsistent results on the TAS-hypnotizability relationship. One possible explanation for this discrepancy is that highly hypnotizable people use different strategies than other people when responding to standardized hypnotic susceptibility scales (Balthazard & Woody, 1992).

The problem is that, although these scales provide a single hypnotizability score, they may be measuring three distinct constructs: ideomotor – when a response to hypnotic suggestion requires a motor movement (your arm is becoming heavy); challenges – when a response requires the inhibition of a motor movement (eyes shut so tightly, they cannot be opened); and cognitive tests – when a response requires alterations of cognitive or

57 sensory perceptions (go ahead and swat the annoying ‘but imaginary’ fly). There is even evidence for a fourth construct: posthypnotic amnesia – when a response elicits forgetfulness so that the person does not remember accomplishing it (Woody, Barnier, &

McConkey, 2005). Not all aspects are treated equally in commonly used scales. For example, an ideomotor response is easier to elicit and score than a cognitive response, so high hypnotizables are likely to be the only individuals who can and will respond to cognitive tests. Therefore, absorption is only correlated with the most difficult hypnotic items on the standardized scales. If a study recruits mostly highly hypnotizable subjects, it is more likely to find a positive correlation between the TAS and hypnosis scores. With regards to neurophysiological and genetic correlates of hynotizability, Horton and

Crawford (2004) point out that associations are more likely to be found when more difficult hypnotic tasks are used to assess susceptibility. Thus, it may be that the best approach to identifying factors that modify hypnotizability is to study only highly hypnotizable individuals – or as some authors call them, hypnosis “virtuosos.” This may be why research has failed to show consistent findings on hypnotic susceptibility factors using these scales (Balthazard & Woody, 1992).

Limitations of the current study

Although the COMT sample size in this study (n = 253) was larger than the sample sizes of any previously published study of genetic factors influencing hypnotizability, the SERT sample size (n = 61) was relatively small. In addition, because

58 of the uneven distribution of alleles in the population, some of the comparison groups in the current sample contained very few cases. For example, there were only 5 individuals who were both Val/Val for the COMT gene and non-L carriers for the SERT gene.

Inspection of the variances across comparison groups also suggests that the equality of variances assumption for ANOVA is not met. However, with so few cases in some of groups the meaningfulness of statistical comparisons including those groups is questionable.

Another problematic issue with this study is that testing individuals using the

HGSHS-A is the only measure where the induction is prerecorded and the participants self-rate susceptibility. Besides Bryant et al. (2013), every other study employed live inductions and objective judges to measure participant’s responses. This certainly could have caused variability among the studies as it presents confounds. By doing a live induction, you are building more rapport with the participants and thereby enhancing both suggestibility and susceptibility (Bryant, Hung, Guastella, & Mitchell, 2012).

Looking at the self-report booklets and talking to participants after the study, it is clear that they are not revealing the true subjective nature of the hypnosis experience. One participant could have rated a particular test as successful, stated that it was mostly involuntary (a core criterion of hypnotic responsiveness; Terhune et al., 2011b), and yet still scored a zero overall. This is due to the nature of the test. If someone is told that,

“their arm is a steal rod and any attempt to bend it, causes it to become more stiff and rigid”, it may provoke a bit of anxiety for the novice client to not be able to bend their arm. This would pull them out of the trance state where their conscious, rational mind

would regain its sensibility and easily bend the arm. Objectively, this would get scored a

one because they clearly struggled to bend their arm. Yet because the final score is

determined by whether the arm moved two inches or more, their subjective response is a zero (because they could move their arm). The good thing about the subjective scoring booklet of the HGSHS-A is that it asks several other questions about the induction experience. This could provide avenues for interesting post hoc analyses.

For example, it is of particular interest to see if different susceptibility levels –

low, medium, and high – responded better to ideomotor suggestions, challenges, or

cognitive tests. The high hypnotizables are said to be the only ones who respond to the

cognitive tests (Horton & Crawford, 2004) and I’m wondering if this is what my study

found. I also want to see if there are particular trends in the types of tests people reported

to be the most involuntary. Finally, another investigation I will examine is to create a new

HGSHS-A scale by factoring in the measures in the subjective response booklet. Having

these data to play with is tantalizing and provides a benefit to the response booklet.

However, these questions are beyond the scope of this particular investigation so I will

not be answering any of them until I have more data on the SERT polymorphism.

In addition to high hypnotizables responding to suggestions through different

cognitive mechanisms than low hypnotizables (Balthazard & Woody, 1992), it appears

there is variability in response pathways among high hypnotizables. Using dissociation as

a moderator, it was shown that high hypnotizables who have low dissociative tendencies

respond very similarly to the hypnotic suggestions as low hypnotizables, except with a

superior object visual imagery (Terhune et al., 2011b). Meanwhile, the high

hypnotizables with high dissociative tendencies respond superiorly to hallucinations, have greater involuntary movements and fantasy-projections, and even have a negative consequence of being more reactive to life’s stressors – like the S allele carriers.

Realizing that even among similar susceptibility levels there are different mechanisms behind hypnotic responsiveness illustrates that this construct, hypnotizability, is much more complex than originally theorized. Although hypnosis has been around for about

3,000 years (Peterfy, 1973), hypnotizability and its neurobiological components are still poorly understood (Kihlstrom, 2013; Bryant et al., 2012). Hypnotic susceptibility is a multifaceted phenotype, so original projections of single gene association seem to underestimate the intricacies involved.

Single-gene effects are attractive to study for a variety of reasons, but the single gene approach to understanding behavioral phenotypes is fraught with potential error.

Advantages of single candidate gene studies include the ability to precisely characterize the biological effects of different variants – for example, the effects of different COMT variants on dopamine catabolism rate. This makes it relatively easy to generate clear and concise theories about the behavioral consequences of those biological effects. One problem with the single candidate gene approach is that it invites a bias to discount effects of other factors, especially other genetic factors. Another problem is in the notoriously low statistical power of single gene association studies, which is not inherent to the method but very widespread nevertheless (Wang, Clayton, Barratt, & Todd, 2005).

Low power costs the researchers in more ways than one. It can inflate the chances of getting a type II error and produce a false negative – which means that there is a true

effect of the gene, but you were unable to find it. And it can lead to the Jackpot effect – where the first to publish a single-gene result is almost certain to have overestimated its true effect (Hirschhorn, Lohmueller, Byrne, & Hirschhorn, 2002). This results in a false positive. Although both issues result in poor quality research, the false positives waste future researchers’ time and money searching to replicate previous findings that are in actuality false. This is the case with my COMT link for hypnotizability. This current study was an attempt to clear up past inconsistencies with the genetic contributions to hypnotizability, and to do it with more statistical power. Although this is the largest participation pool of any previous genetic assessment of hypnotic susceptibility, it is still a relatively small sample, and as it stands, it too lacks adequate power. This very likely contributed to my null findings.

Future Directions

One exciting item of future interest is oxytocin’s role on hypnotizability. Injected nasally, oxytocin acts as a moderator of hypnotizability (Bryant et al., 2012). Participants that self-administered oxytocin before a hypnotic assessment had higher susceptibility scores. This was true even though they were not consciously aware of any alterations in their cognitive/emotional experience. This did not occur through oxytocin’s classic effect of enhancing social bonding, rather, it was an attention-mediated effect. Oxytocin increases the sensitivity to social information, which may have made participants more susceptible to social cues in the environment. When this environment is a hypnotic

setting, it subconsciously motivates the participants to respond more dramatically. This

provides a secondary pathway to positively impact a client’s responsiveness. Oxytocin

may in fact play a double moderator effect, enhancing hypnotizability through both

increased trust (essential for any client-therapist relationship) and increased attentional

control. Given the ease with which oxytocin can be administered and its fast effects, its

use as an adjunctive component of hypnotherapy could lead to very prosperous outcomes.

Using oxytocin in conjunction with group scales for hypnotic responsiveness may curb

the negative effects of administering the scale to multiple individuals simultaneously.

This would provide a way to continue to value the use of these time-saving methods.

While investigating possible rationales for the S carrier’s higher responsiveness to

hypnosis, I was unable to find any literature that looked at an individual’s measure of

hope for successful outcomes on their actual hypnotic results. Hope is a powerful

psychological mechanism related to adaptive life outcomes (Snyder, Rand, King,

Feldman, & Woodward, 2002). It is a good predictor of psychological well-being in both healthy and chronically ill subjects (Ho, Ho, Bonanno, Chu, & Chan, 2010). Hope is similar to optimism (Snyder et al., 1991) which was shown in a world-wide representative sample of over 150,000 individuals to predict well-being and perceived health (Gallagher, Lopez, & Pressman, 2013). Testing to see if individual differences in hope relate to more successful hypnotherapeutic outcomes could prove valuable. If manipulating a client’s hope for success could increase susceptibility and hypnotic response rates (Hall et al., 2012; Roche & McConkey, 1990; Spanos et al., 1987), it would be a cheap and easy step towards boosting patient success in hypnotherapy.

Another important topic for investigation that was outside the scope of this paper is the link between hypnosis and meditation. Hypnosis and mediation are very similar and may fall along the same spectrum of consciousness. Evidence shows that the two phenomena involve overlapping neural and cognitive networks (Lifshitz & Raz, 2008).

Meditation creates similar effects as hypnosis because it involves a relaxed state of consciousness and reduces stress. Meditation involves an ability to sustain attention and maintain it without disturbances (Brefczynski-Lewis, Lutz, Schaefer, Levinson, &

Davidson, 2007; Lutz, Slagter, Dunne, & Davidson, 2008) and has even been shown to reduce the Stroop interference effect (Moore & Malinowski, 2009). Mindfulness meditation has been effective for the treatment and prevention of PTSD (Kearney,

McDermott, Malte, Martinez, & Simpson, 2012), for controlling and suppressing pain

(Zeidan et al., 2011), as well as treating numerous physical, psychosomatic, and psychiatric disorders (Grossman, Niemann, Schmidt, & Walach, 2004). Mindfulness meditation can rapidly rebuild the brain’s grey matter concentration (Hölzel et al., 2011), lengthen telomeres (Schutte & Malouff, 2014), and help individuals attain higher psychological well-being (Eberth & Sedlmeier, 2012). Even brief mindfulness training has shown to improve cognition, even enhancing attention (Zeidan, Johnson, Diamond,

David, & Goolkasian, 2010). Since hypnosis is a directed form of meditation to produce a specific result, it is here that hypnosis has the potential to extend and maybe even surpass the results shown by meditation alone. A synergistic effect of both hypnosis and meditation has yet to be examined thoroughly and deserves scientific scrutiny.

One last, yet important future direction to take is what to do about the current

model for measuring hypnotizability. Recent information shows that the best predictors

of the truly hypnotized experience are the two most difficult tests to pass – the cognitive

tests and posthypnotic amnesia (Woody et al., 2005). But high hypnotizables are typically

the only ones who perform these constructs (Horton & Crawford, 2004). It would seem

beneficial that if the objective was to separate high hypnotizables from the rest of the

population, maybe standard scales should test people on the hardest constructs only. This

would disentangle extraneous variables from finding stable and reliable predictors of those who are highly responsive. However, the motor actions and inhibitions provided by the ideomotor and challenge constructs are reported by participants to be the more

compelling experience (Woody et al., 2005). Maybe then the answer is not to get rid of

constructs, but to combine multiple scales for a larger amount of total tests. The SHSS:C

is the gold standard for hypnotic susceptibility and has greater involvement of the harder

constructs. Meanwhile, the HGSHS-A is more focused towards measuring the easier

constructs. Combining these two scales – thereby increasing the total number of hypnotic

tests – improves the internal consistency and reliability over any single measure alone

(Woody et al., 2005). This could provide us with a more accurate representation of

hypnotizability. Although these scales have variation when it comes to the types of tests

they provide participants, there is one aspect of all standardized hypnotic susceptibility

scales that remains similar – the induction.

The induction is the part of hypnosis where the person is induced into a trance.

Although the induction has very little to do with the hypnotic experience overall (Kirsch

& Braffman, 2001), it would likely impact participant expectation – especially for a first

time client. This could directly influence the hypnotic susceptibility of the individual

because expectations are shown to modulate hypnotizability (Roche & McConkey, 1990).

For every standardized scale I’ve seen, the person is induced using a highly repetitive,

progressive relaxation. This may benefit some individuals more than others – typically

those who are more anxious, have trouble relaxing, or just ingested a high dose of

caffeine prior to testing. Yet, some individuals may benefit from a more rapid or complex induction. These individuals may not be represented accurately due to cognitive boredom or annoyance with the excessive repetition. This could create complications by pulling

the person out of trance or by putting them to sleep. Several participants did comment on the disagreeable nature of the induction script during my current investigations. A future direction that has yet to be investigated would be to test hypnotizability based on different types of inductions. Matching personality dimensions (maybe using the five

factor model from the big five personality scale) to different induction styles would take

some initial trial and error, but could prove highly beneficial. If it were found that people

were not undergoing the full hypnotic experience due to diverse interpretations of what

the hypnotic experience is like, or a shallower depth of trance, then this would seem to be

the next logical step. Providing a hypnosis info sheet was this study’s method for

standardizing expectations, but maybe individuating induction styles could help to

standardize the depth of trace for everyone – especially in a group setting.

There are well-supported hypotheses for genetic effects on personality and

cognitive traits that may in turn influence hypnotic susceptibility. This study and others

66 have examined likely candidate genes for these effects but have, as yet, found no clear evidence for genetic modifiers of hypnotic susceptibility.

Conclusions

It is in initial investigations that remarkable strides forward can be taken. It takes

new ideas to create new science and only one to forever change the current paradigm of

health and mental treatment. One important stride forward that my research can take is in

showing that hypnotizability is not the construct that it once was believed to be. Future

research should break hypnotizability down into its constituent parts and analyze

predictors for each. That would provide a more ideal way of discovering what it is that

makes someone highly hypnotizable. Then real progression towards a reliable and

affordable predictor of these “virtuosos” could be unlocked. Clearing up inconsistencies

and providing an understanding for why the TAS and genetic markers show such

variability in the research is another valuable outcome from this current study. Genetic

analyses are getting more time and cost-effective, but until that technology is here, I think

it is safe to say that investigating gene effects on something as complex as hypnotizability

is not the correct path to take. A better approach would involve attentional measures,

non-hypnotic responsiveness scales (Kirsch & Braffman, 2001), and finding new

measures to determine hypnotizability levels. Plus, searching for ways to enhance hypnotizability – e.g. instilling high expectations of hope or adding a nasally injected spray of oxytocin – may provide a cheap and easy way to immediately boost patient success with hypnotherapy.

The good news is that most people can enhance their hypnotic responsiveness with appropriate practice and training. Hypnosis is a valid and potent treatment option

68 that can reduce or eliminate reliance on some pharmaceutical interventions. It boosts the effectiveness of psychological treatments and has helped as an adjunct to accelerate positive outcomes for many clinical and medical conditions. Therefore, it is a worthy and important goal to investigate predictors and modifiers of hypnotic susceptibility. I hope this research can be used to educate people on the scientific basis of hypnosis.

Individualizing treatments may be an important next step towards increasing positive patient outcomes. Regardless, the research on hypnotic interventions is clear and hypnosis should now be acknowledged as an empirically supported therapeutic option.

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Appendix - SERT’s 4 allelic breakdown protocol (S, LG, L, LA)

PCR conditions

95C- 2:00 minutes 35 cycles of: 95C- 30 seconds 60C- 45 seconds 72C- 45 seconds 72C- 5:00 minutes

PCR cocktail per 25uL reaction

12.5uL GoTaq 2X colorless master mix 0.75uL Forward Primer from 10uM stock 0.75uL Reverse Primer from 10uM stock 7.0uL Nuclease free/PCR water 4.0uL of template DNA@ 6ng/uL for a total of 24ng of DNA (several papers use as much as 50ng of DNA)

HPAII Enzyme digestion conditions

37C- for 12 hours (enzyme cuts DNA into fragments for identification. 65C- for 20 minutes (deactivates enzyme)

Thermo-cycler settings for digestion

6 cycles of: 37C-1 hour 37C-1 hour 65C-20 minutes

HPAII Enzyme cocktail per 10uL of PCR product

1.0uL Tango Buffer 0.5uL HPAII enzyme

Calculate volume needed for total samples to be digested and make a cocktail of the enzyme and buffer. Pipette 1.5uL from cocktail into bottom of 200uL microcentrifuge tube. Add 10 uL of PCR product, pipette to mix and place on thermocycler

8% Nondenaturing Polyacrylamide Gel -1X TBE

4mL- 5X TBE 5.32mL- 29:1 Polyacrylamide liquid solution (in refrigerator) 10.68mL-Nanopure water

Mix gel reagents above together and off-gas under vacuum for 15 minutes.

100uL of 10% ammonium persulfate (solid powder in drawer beside gel supply drawer under scale) 10uL of TEMED (in refrigerator)

After off-gassing pour TBE/polyacrylamide/water solution into a beaker. Weigh out and mix together ammonium persulfate crystals and hydrate with Nanopure water. After crystal dissolve add 100uL to the gel solution in the beaker. Next add 10uL of TEMED to the beaker and stir, being careful not to introduce bubbles to the solution. Remove the green comb from the gel cassette. Use a 5mL syringe to fill empty BioRad gel cassette with the gel solution. Work quickly, TEMED is a catalyst and will start to solidify the gel solution within 15 minutes. Replace the gel comb into the cassette and cover cassette opening tightly with plastic wrap to decrease exposure to air. Decreasing the amount of air exposure will help to ensure the gel will harden completely. Let cassette sit upright for one hour before use. After gel has hardened remove the white plastic strip from the bottom of the cassette and the gel comb, place the cassette into the gel rig. Fill the gel rig with 1X TBE buffer up to the fill line and the entire gel cassette mouth. Next load 5uL the PCR or Enzyme digestion product to a well.

MSPL ladder for identification (cuts at CCGG)

1uL of MSPL ladder 1uL of 6X loading dye 5uL of Nuclease free water

Mix above reagents and pipette 5uL into gel.

Load settings for the electrophoresis box:

Initial setting; 200Volts 55mA 50W Actual; 200Volts 34 mA 7W

Run for 1 hour, remove gel cassette and stain gel with ethidium bromide, visualize with ultraviolet light for identification.