Neurostructural Correlates of IL-1β rs16944 Polymorphism in Adolescents with and
without Bipolar Disorder
by
Daniel Oluwatobi Shonibare
A thesis submitted in conformity with the requirements
for the degree of Master of Science
Department of Pharmacology and Toxicology
University of Toronto
© Copyright by Daniel Oluwatobi Shonibare (2018) Neurostructural Correlates of IL-1β rs16944 Polymorphism in Adolescents with and
without Bipolar Disorder
Daniel Oluwatobi Shonibare
Master of Science
Department of Pharmacology and Toxicology
University of Toronto
2018
Abstract
Increased inflammation among youth with bipolar disorder (BD) is associated with increased illness severity. Functional inflammatory polymorphisms are associated with neurostructural changes in BD. This was examined for the first time in youth. T1-weighted images of 38 BD and 32 healthy controls (HCs) were processed through FreeSurfer to obtain cortical region of interest (ROI) volumes/surface area/thickness for dorsolateral prefrontal cortex and caudal anterior cingulate cortex, along with subcortical ROI volumes for hippocampus and amygdala. Our results show a main effect of interleukin (IL)-1β rs16944 in the lateral occipital cortex (LOC), along with a IL-1β rs16944-by-diagnosis interaction effect for a pars triangularis surface area cluster along with a LOC volume cluster. Our results suggest that the IL-1β rs16944 polymorphism is associated with neurostructural differences in youth with BD and HCs. Future studies including other imaging phenotypes and neurocognitive tasks are warranted to evaluate the relationship between IL-1β rs16944 and brain function.
ii Acknowledgements
I would like to express my sincerest gratitude and appreciation to my supervisor,
Dr. Benjamin Goldstein, for his leadership, guidance, and support over the course of this research project. Dr. Goldstein has truly inspired me to be a better researcher through his excellent mentorship and has challenged me to broaden the scope of my scientific thinking.
I appreciate the invaluable guidance he has given me throughout the duration of my schooling. I would also like to thank Dr. Bradley McIntosh and his research team for their neuroimaging knowledge and guidance.
My appreciation also goes to all the graduate students and staff at the Centre for
Youth Bipolar Disorder for their research support, personal support, and laughter. It was truly a blessing to be part of a team that is passionate about improving outcomes for adolescents with bipolar disorder. My experience at the Centre for Youth Bipolar Disorder was not just about acquiring an MSc degree, but leaving a lasting impact on many adolescents and their families.
Lastly, I would like to give a special thanks to my family and friends who supported me through my studies. I am truly fortunate and blessed to have such an excellent support system.
iii Table of Contents Acknowledgements ...... iii Table of Contents ...... iv List of Tables ...... vi List of Figures...... vii List of Abbreviations ...... viii 1. Introduction ...... 1 1.1 Statement of Problem ...... 1 1.2 Purpose of Study and Objectives ...... 3 1.3 Statement of Research Hypotheses and Rationale for Hypotheses ...... 4 1.4 Review of Literature ...... 5 1.4.1 Bipolar Disorder: Symptomology, Prevalence, and Burden ...... 5 1.4.2 Neuroimaging in BD ...... 7 1.4.3 Bipolar Disorder and Cardiovascular Disease ...... 11 1.4.4 Inflammation and Cardiovascular Disease ...... 12 1.4.5 The Relationship between Inflammation and BD ...... 13 1.4.6 Evidence of Anti-inflammatory Medications for BD ...... 16 1.4.7 Inflammatory Cytokine: IL-1β ...... 16 1.4.8 Summary of Literature and Rationale ...... 18 2. Materials & Methods ...... 18 2.1 Study Design ...... 18 2.2 Participant Selection ...... 19 2.2.1 Participant Recruitment ...... 19 2.2.2 Inclusion Criteria ...... 19 2.2.3 Exclusion Criteria ...... 20 2.3 Study Schedule ...... 20 2.4 Participant Demographics, Psychiatric, and Medical History ...... 21 2.5 Primary Interview Instruments ...... 22 2.6 Anthropometric Data ...... 23 2.7 Genetic Data ...... 23 2.7.1 Saliva Collection ...... 23 2.7.2 Genotyping ...... 24 2.7.3 Hardy-Weinberg Equilibrium ...... 25 2.8 Structural Imaging & Analysis ...... 25 2.8.1 Image Acquisition ...... 25 2.8.2 Pre-processing Quality Control: T1 Rating...... 25 2.8.3 Pre-processing and Surface Morphometry ...... 26 2.8.4 Imaging Data Quality Control: Correcting Parcellation Errors ...... 27 2.9 Defining Regions of Interest ...... 29 2.10 Statistical Analyses ...... 30 2.11 Two-step Sensitivity Analyses ...... 31 2.12 Whole-brain Vertex-wise Exploratory Analyses ...... 32 2.12.1 Characteristics of DOSS vs DODS Models ...... 33
iv 2.13 Power Analysis ...... 34 3. Results ...... 34 3.1 Demographic and Clinical Characteristics ...... 34 3.2 Hardy-Weinberg Calculation ...... 35 3.3 ROI Analyses...... 35 3.4 Sensitivity Analyses ...... 35 3.5 Whole-brain Vertex-wise Analyses ...... 40 4. Discussion...... 45 4.1 Summary of Findings ...... 45 4.2 Interpretation of Findings ...... 46 4.2.1 Main Effect: The IL-1β rs16944 Polymorphism Effect in LOC Cluster ...... 46 4.2.2 Interaction Effect: Diagnosis by Polymorphism Effect in LOC Cluster ...... 47 4.2.3 Interaction Effect: Diagnosis by Polymorphism Effect in Pars Triangularis Cluster...... 48 4.3 Proposed Bottom-up Framework of the LOC ...... 50 4.4 Cortical Surface Area vs Cortical Thickness Implications ...... 51 4.5 Limitations ...... 52 4.6 Future Directions ...... 54 4.6.1 Longitudinal Study Integrating Other Imaging Modalities ...... 54 4.6.2 Adjunctive Anti-inflammatory Treatment Options ...... 55 4.6.3 Interleukin-1β Treatment Targets ...... 57 4.7 Conclusion ...... 59 References ...... 60 Appendices ...... 72
v List of Tables Table 1 – Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) Criteria for Major Depression, Mania, and Hypomania ...... 6 Table 2 – Anthropometric Data: Measures & Method of Collection ...... 23 Table 3 – Crossover in association between BD and inflammation and selected ROIs ...... 30 Table 4 – Demographic and Clinical Characteristics of the Study Participants by BD Diagnosis, IL-1β rs16944 Polymorphism, and Diagnosis by IL-1β Polymorphism...... 37 Table 5 – Brain Region of Interest (ROI) Differences Among BD and HC by IL-1β rs16944 Allele Subtype ...... 39 Table 6a – Correlation Analyses (Sensitivity Analysis Step 1) ...... 40 Table 6b – Addition of Covariates (Sensitivity Analysis Step 2) ...... 40 Table 7 – Exploratory Vertex-wise Whole-brain Analyses: Significant Cluster-wise Results ...... 44
vi List of Figures Figure 1 – Key Nodes in Emotion Processing, Regulation, and Neural Circuitries...... 8 Figure 2 – Key Nodes in Reward Processing Neural Circuitry ...... 9 Figure 3 – Kynurenine Pathway of Tryptophan Metabolism ...... 15 Figure 4 – Overview of Study Chronology ...... 21
Figure 5 – Scoring System for T1-weighted Scans ...... 26 Figure 6 – Example of Erroneous Parcellation ...... 28 Figure 7 – IL-1β rs16944 by Diagnosis interaction effect on DLPFC surface area ...... 36 Figure 8 – LOC Surface Area in the Left Hemisphere ...... 41 Figure 9 – Graph for LOC Surface Area (SA) in the Left Hemisphere ...... 41 Figure 10 – LOC Volume Cluster in the Left Hemisphere and Pars Triangularis Surface Area Cluster in the Right Hemisphere ...... 42 Figure 11 – Graph for IL-1β rs16944-by-Diagnosis interaction effect in the LOC Volume Cluster in the Left Hemisphere ...... 43 Figure 12 – Graph for IL-1β rs16944-by-Diagnosis interaction effect in the Pars Triangularis Surface Area (SA) Cluster in the Right Hemisphere ...... 44 Figure 13 – Potential IL-1β Pathway Treatment Targets ...... 58
vii List of Abbreviations
ACC: Anterior Cingulate Cortex ADHD: Attention Deficit Hyperactivity Disorder ANCOVA: Analysis of Covariance BD: Bipolar Disorder BD-I: Bipolar Disorder Type I BD-II: Bipolar Disorder Type II BD-NOS: Bipolar Disorder Not Otherwise Specified BMI: Body Mass Index COX: Cyclooxygenase CVD: Cardiovascular Disease CVRF: Cardiovascular Risk Factor DLPFC: Dorsolateral Prefrontal Cortex DODS: Different Offset, Different Slope DOSS: Different Offset, Same Slope DSM: Diagnostic and Statistical Manual of Mental Disorders FDR: False Discovery Rate GLM: General Linear Model HC: Healthy Control ICV: Intracranial Volume IL: Interleukin KYN: Kynurenine LOC: Lateral Occipital Cortex MRI: Magnetic Resonance Imaging ROI: Region of Interest SNP: Single Nucleotide Polymorphism SSRI: Selective Serotonin Reuptake Inhibitor VLPFC: Ventrolateral Prefrontal Cortex
viii 1. Introduction
1.1 Statement of Problem
Bipolar disorder (BD) is considered a severe and impairing mood disorder. BD affects approximately 2-5% of adults and adolescents (Jann, 2014). Compared to psychiatrically healthy controls (HCs), adolescents with BD exhibit greater functional impairment, psychiatric comorbidities, hospitalizations, and suicide attempts (Peele,
Axelson, Xu, & Malley, 2004). Evidently, adolescents with BD report lower quality of life when compared to HCs (Freeman et al., 2009). Adolescents with BD spend a greater portion of time suffering from mood and comorbid related symptoms when compared to adults with BD (Birmaher et al., 2006).
Patients with BD have an increased occurrence of cardiovascular risk factors
(CVRFs) compared to the general population (Fiedorowicz, Palagummi, Forman-Hoffman,
Miller, & Haynes, 2008; Vancampfort et al., 2013). BD has been robustly linked with cardiovascular disease (CVD), in which patients with BD experience an excess of premature CVD associated mortality (Goldstein, Carnethon, et al., 2015). It is imperative to understand the underlying biological associations between BD and CVD as this will aid in the development of novel treatment approaches; thus, promoting long-term psychiatric and physical well-being (Price & Marzani-Nissen, 2012). Given that elevated inflammation levels are associated with both BD and cardiovascular risk factors, inflammation is a target for further investigations as it poses as a candidate for bridging the gap between BD and
CVD (Gabay & Kushner, 1999; Goldstein et al., 2011; Goldstein, Lotrich, et al., 2015;
Kauer-Sant'Anna et al., 2009).
1 Along with impairment from mood symptoms, extensive comorbidities, and increased burden from CVRFs, patients with BD also experience neurocognitive dysfunction (Hellvin et al., 2012). Neurocognitive deficits in executive functioning, sustained attention, and working memory has been observed even in adolescents with BD
(Best, Bowie, Naiberg, Newton, & Goldstein, 2017; Dickstein et al., 2015; Doyle et al.,
2005; Martínez-Arán et al., 2004; Robinson & Nicol Ferrier, 2006). These deficits have been linked to difficulties in learning and reduced academic achievement in adolescents with BD (Pavuluri, West, Hill, Jindal, & Sweeney, 2009). Studies have found that neurocognitive dysfunction is associated with increased inflammatory markers in patients with BD (Barbosa, Bauer, Machado-Vieira, & Teixeira, 2014; Rosenblat et al., 2015).
Many of the phenotypes expressed in BD have been linked to specific genetic polymorphisms. Genetics plays a significant role in BD susceptibility and yet little is known about the genetics of adolescent BD (Craddock & Sklar, 2013). Emerging research elucidates inflammatory proteins as candidate biomarkers for BD (Barbosa et al., 2014;
Frey et al., 2013; Mitchell & Goldstein, 2014; Modabbernia, Taslimi, Brietzke, & Ashrafi,
2013; Munkholm, Braüner, Kessing, & Vinberg, 2013). However, inflammatory proteins can fluctuate based on factors such as stress state (Slavich & Irwin, 2014). Therefore, it may not be ideal to rely simply on inflammatory proteins as biomarkers as they may be misleading. Instead, inflammatory genes are not prone to such fluctuations and so should be supplementary to inflammatory proteins to provide a more cohesive picture.
Research regarding inflammatory genes has begun to emerge. The interleukin (IL)-
1 rs16944 polymorphism has been associated with neurocognitive deficits (S.-J. Tsai,
2017; S.-J. Tsai et al., 2010). A potential underpinning for this observed neurocognitive
2 deficit is the IL-1β rs16944 polymorphism has been associated with neurostructural deficits. In particular, the IL-1β rs16944 polymorphism has been associated with reduced hippocampal volume in healthy adults, as well as white matter deficits, bilateral frontal- temporal gray matter deficits, and ventriculomegaly in patients with schizophrenia
(Meisenzahl et al., 2001; Raz, Daugherty, Bender, Dahle, & Land, 2015). In adult patients with BD, the IL-1β rs16944 polymorphism has been associated with whole-brain and left
DLPFC gray matter deficits (Papiol et al., 2008). Surprisingly, the effects of inflammatory genes on adolescent brain structure remains unexplored. In fact, no studies have examined the effects of inflammatory genes on brain structure exclusively among adolescents with
BD compared to psychiatrically healthy adolescents despite the overwhelming evidence of the relevance of inflammation to BD.
1.2 Purpose of Study and Objectives
The purpose of this study was to investigate the association between the IL-1β rs16944 polymorphism and structural neuroimaging phenotypes of select a priori regions of interest (ROIs) in adolescents with and without BD. The ROIs selected have been implicated in both BD and inflammation in adult and adolescent literature. The selected cortical ROIs were the dorsolateral prefrontal cortex (DLPFC) and caudal anterior cingulate cortex (caudal ACC), in which cortical volume, surface area, and thickness were examined. The selected subcortical ROIs were the hippocampus and amygdala, in which subcortical volume was examined. A secondary analysis was conducted to investigate the association between the IL-1β rs16944 polymorphism and structural neuroimaging
3 phenotypes in adolescents with and without BD using a whole-brain vertex-wise approach.
The whole-brain vertex-wise analysis is data-driven rather than literature-driven.
The objectives of this study were to:
1. Determine if there is a main effect of the IL-1β rs16944 polymorphism on brain
structure in adolescents.
2. Determine if there is an interaction effect between diagnosis and the IL-1β rs16944
polymorphism on brain structure in adolescents.
3. Identify additional neurostructural correlates of IL-1β rs16944 using the whole-
brain vertex-wise analyses.
1.3 Statement of Research Hypotheses and Rationale for Hypotheses
We hypothesized that the IL-1β rs16944 polymorphism would be significantly associated with brain structure in our sample of 70 participants. We also hypothesized that there would be an interaction effect such that there would be unique neurostructural correlates of IL-1β rs16944 among adolescents with BD compared to psychiatrically healthy control (HC) adolescents.
The rationale for these hypotheses is that inflammation has independently as well as in association with BD been related to neurostructural differences. The IL-1β rs16944 polymorphism has independently been related to hippocampal volume (Raz et al., 2015).
There has also previously been a report that the IL-1β rs16944 polymorphism was associated with whole-brain and left (DLPFC) gray matter deficits in adults with BD
(Papiol et al., 2008).
4 1.4 Review of Literature
1.4.1 Bipolar Disorder: Symptomology, Prevalence, and Burden
Bipolar Disorder (BD) is a severely impairing mood disorder that characterized by recurrent episodes of mania/hypomania, and commonly alternates with periods of major depression as characterized in Table 1 (Jann, 2014; Kessler et al., 2009; Kowatch, 2016).
BD has many subtypes, the main three consisting of BD type 1 (BD-I), BD type II (BD-II), and BD not otherwise specified (BD-NOS). BD-NOS has been operationalized by Axelson and colleagues (Axelson et al., 2006; D. Hafeman et al., 2013). To meet criteria for BD-
NOS, participants must have had at least four lifetime days (does not need to be consecutive days) with at least four hours of either (i) elated mood alongside two associated manic symptoms, or (ii) irritable mood alongside three associated manic symptoms. Furthermore, mood disturbances must be accompanied with a change in functioning, could not meet full criteria for either hypomanic or a manic episode, and could not be largely accounted for by another disorder. BD-I is characterized by presenting full mania at least once, while BD-II is characterized by presence of a depressive episode and episodes of hypomania. BD-NOS is the presence of bipolar-like symptoms that does not exactly fit the criteria for BD-I or BD-II.
BD is considered one of the most debilitating psychiatric illnesses that affects approximately 2-5% of adolescents and adults (Jann, 2014; Kessler et al., 2009; Kowatch,
2016). Early onset during adolescence confers an increase in symptom severity, comorbidity, and suicidality, when compared to late onset during adulthood (Carter,
Mundo, Parikh, & Kennedy, 2003; Goldstein & Levitt, 2006; Leverich et al., 2007; Perlis et al., 2004). Additionally, compared to psychiatrically healthy adolescents and other
5 psychiatric adolescent populations such as Attention Deficit Hyperactive Disorder
(ADHD) and Major Depressive Disorder (MDD), adolescents with BD have greater functional impairment, reduced neurocognitive functioning, increased hospitalizations, and greater rates of comorbidities (Freeman et al., 2009; Lewinsohn, Klein, & Seeley, 1995;
Mann‐Wrobel, Carreno, & Dickinson, 2011; Peele et al., 2004; Rademacher, DelBello,
Adler, Stanford, & Strakowski, 2007).
DSM-5 Criteria for Major Depression Five or more of the following symptoms (including depressed or loss of interest/pleasure), lasting at least 2 weeks, comprising a change from previous functioning: 1. Depressed or irritable mood for most of the day, nearly every day as reported or observed 2. Markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day 3. Significant weight loss when not dieting or weight gain, or decrease or increase in appetite nearly every day 4. Insomnia or hypersomnia nearly every day 5. Observable psychomotor agitation or retardation nearly every day 6. Fatigue or loss of energy nearly every day 7. Feelings of worthlessness or excessive or inappropriate guilt nearly every day 8. Diminished ability to think or concentrate, or indecisiveness, nearly every day 9. Recurrent thoughts of death (not just fear of dying), recurrent suicidal ideation with a specific plan, or a suicide attempt or a specific plan for committing suicide DSM-5 Diagnostic Criteria for Mania and Hypomania A distinct period of abnormally and persistently elevated, expansive, or irritable mood and abnormally and persistently increased activity or energy, in addition to 3 or 4 (if the mood is only irritable) of the following: 1. Inflated self-esteem or grandiosity 2. Decreased need for sleep 3. More talkative than usual or pressure to keep talking 4. Flight of ideas or subjective experience that thoughts are racing 5. Distractibility as reported or observed 6. Increase in goal-directed activity or psychomotor agitation 7. Excessive involvement in pleasurable activities that have a high potential for painful consequences
6 Mania Hypomania • Episode lasts at least 1 week (or any • Episode lasts at least 4 days, most of duration if hospitalization is the day, every day necessary), most of the day, every • The mood disturbance must be day associated with an unambiguous and • The mood disturbance must be uncharacteristic change in sufficiently severe either to: functioning, and the mood o Cause noticeable functional symptoms and change in impairment (i.e. social, academic, functioning must be noticeable by work) or others o Necessitate hospitalization to • Marked impairment, need for prevent harm to self or others or hospitalization, and psychotic o Be associated psychotic features features preclude a diagnosis of (e.g. disorganized thinking, hypomania hallucinations and/or delusions)
Table 1 - Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5)
Criteria for Major Depression, Mania, and Hypomania.
1.4.2 Neuroimaging in BD
Advances in neuroimaging techniques has provided the opportunity to identify neurobiological markers that will identify risk for developing BD, increase diagnostic precision, and allow the development of personalized treatments based on our increased understanding of the pathological underpinnings of neurophysiological processes.
Although there are conflicting findings, two review articles have conceptualized the consistent theme that the psychopathology of BD is associated with neural circuitry abnormalities in systems that influence emotion (Figure 1) and reward processing (Figure
2) (Phillips & Swartz, 2014; Strakowski et al., 2012).
7
Figure 1 – Key Nodes in Emotion Processing, Regulation, and Neural Circuitries
(Phillips & Swartz, 2014). dlPFC: dorsloateral prefrontal cortex; vlPFC: ventrolateral
prefrontal cortex; mdPFC: mediodorsal prefrontal cortex; OFC: orbitofrontal cortex; ACC: anterior cingulate cortex. Arrows represent key associations between prefrontal regions and
amygdala. Red nodes represent reduced function and/or abnormal volume. Red arrows
represent abnormal connections in between regions in patients with bipolar disorder.
Patients with BD experience increased amygdala activity during emotion processing and
regulation, decreased activity in the vlPFC and OFC during emotion regulation, and
decreased functional connectivity between these prefrontal regions and the amygdala
during emotion regulation. Patients with BD also exhibit smaller hippocampal volume.
8
Figure 2 – Key Nodes in Reward Processing Neural Circuitry (Phillips & Swartz,
2014). Same abbreviations as Figure 1. Patients with BD experience increased vlPFC,
OFC, and ventral striatum activity during reward processing.
Neurofunctional Correlates of BD
Among the most consistent functional neuroimaging findings in BD is excessive amygdala activation. The amygdala plays a key role in emotion regulation (Goldstein et al.,
2017; Swanson, 2003). Emotion regulation has been sorted into automatic/implicit processes, regulated by the orbitofrontal cortex and the anterior cingulate cortex (ACC), and voluntary processes, regulated by the dorsolateral prefrontal cortex (DLPFC) and the ventrolateral prefrontal cortex (VLPFC) (Phillips, Ladouceur, & Drevets, 2008). The amygdala is modulated by the ventral prefrontal regions, specifically the orbitofrontal and ventrolateral prefrontal cortex (Strakowski et al., 2012). The orbitofrontal and ventrolateral prefrontal cortex have both exhibited decreased functional magnetic resonance imaging
9 (fMRI) during a variety of cognitive tasks such as response inhibition tasks (Townsend et al., 2012).
The ACC is also impaired in patients with BD. The ACC is important for information processing. The ventral portion is responsive to emotional stimuli, while the dorsal/caudal portion is responsive to cognitive stimuli (Strakowski et al., 2012). Research has shown that patients with BD have increased activity in the ventral portion of the anterior cingulate cortex, and decreased activity in the dorsal portion (Gruber, Rogowska,
& Yurgelun-Todd, 2004; Pavuluri, O'Connor, Harral, & Sweeney, 2008).
Altogether, functional imaging studies provide insight on the functional impairments experienced via emotional and reward brain networks.
Neurostructural Correlates of BD
Compared to healthy controls, patients with BD exhibit differences in cortical surface area, thickness, and volume which all relate to the functional impairments associated with cognition, symptoms, and behaviour (Hartberg et al., 2011; Hibar et al.,
2017; Padmanabhan et al., 2014; Rakic, 1988, 2007). Structural brain differences between patients with BD and HCs support the main themes in abnormal functional MRI findings of patients with BD. Patients with BD have been reported to express structural abnormalities in frontal and limbic brain regions, along with abnormalities in prefrontal- limbic connections (Hibar et al., 2017; Keener & Phillips, 2007; Phillips & Swartz, 2014).
Adolescents with BD have been described to have smaller amygdala volume compared to healthy adolescents; while adults with bipolar disorder have been described to have greater amygdala volume compared to healthy adults (Strakowski et al., 2012).
10 Studies performed in at-risk youth (i.e. offspring of parents with BD), prior to the development of any symptoms or behavioural disturbance found, suggested white matter abnormalities in the corpus callosum, prefrontal and temporal white matter tracts (Frazier et al., 2007; Sprooten et al., 2011; Versace et al., 2010). This suggests that structural connectivity differences through white matter may precede onset of BD and the functional impairments observed through neuroimaging.
1.4.3 Bipolar Disorder and Cardiovascular Disease
Patients with BD have a greater prevalence of CVRFs compared to the general population (Fiedorowicz et al., 2008; Vancampfort et al., 2013). Patients with BD are three times as likely to have type 2 diabetes mellitus when compared to the general population
(Calkin, Gardner, Ransom, & Alda, 2013). CVRFs are highly prevalent in patients with
BD, and may be a huge contributor to the elevated cardiovascular disease (CVD) risk and mortality observed in patients with BD. Recent meta-analyses have identified that patients with BD have a higher prevalence of metabolic syndrome along with obesity (Vancampfort et al., 2013; Zhao, Okusaga, Quevedo, Soares, & Teixeira, 2016). Another study in the US specifically found that obesity rates were approximately 50% in patients with BD versus
30% in the general population, based on Body Mass Index (BMI) (Fagiolini, Frank, Scott,
Turkin, & Kupfer, 2005).
The leading cause of mortality in adults with BD is CVD (Goldstein, Carnethon, et al., 2015; Ösby, Brandt, Correia, Ekbom, & Sparén, 2001). Adults with BD had a greater incidence of new-onset CVD compared to adults with MDD and healthy adults (Goldstein,
Schaffer, Wang, & Blanco, 2015). In fact, adults with BD-I developed new-onset CVD 11
11 years earlier than adults with MDD, and 17 years earlier than healthy control adults
(Goldstein, Schaffer, et al., 2015). CVD in patients with BD is greatly under-recognized and undertreated. A cross-sectional study found that patients with BD were less likely than healthy control adults to have a record of CVD (Smith et al., 2013). Moreover, patients with both BD and a primary-care record of coronary heart disease and hypertension were less likely to be prescribed cholesterol lowering and antihypertensive medications (Smith et al., 2013).
1.4.4 Inflammation and Cardiovascular Disease
Inflammatory cytokines play a crucial role in the pathogenesis of cardiovascular diseases. Patients with acute coronary syndromes had increased inflammatory cytokine levels (Libby, Ridker, & Maseri, 2002; Van Tassell, Toldo, Mezzaroma, & Abbate, 2013).
In fact, genetic polymorphisms in the interleukin (IL)-1 system, such as the IL-1β cytokine, has been linked to premature onset of atherosclerosis and acute myocardial infarction
(Andreotti, Porto, Crea, & Maseri, 2002; Van Tassell et al., 2013). Specifically, the IL-1β cytokine plays a role in atherothrombotic disease through the promotion of atheromatous lesions which promotes vascular inflammation and triggers the destabilization of plaques
(Bujak & Frangogiannis, 2009). Furthermore, IL-1β plays a role in the development of adverse remodeling post-infarction through adjusting the composition of the extracellular matrix and stimulating fibrous tissue deposition (Bujak & Frangogiannis, 2009). IL-1β also promotes heart failure through its ability to suppress cardiac contractility (Gulick, Chung,
Pieper, Lange, & Schreiner, 1989). Its ability to suppress cardiac contractility eventually induces cardiomyocyte apoptosis (Bujak & Frangogiannis, 2009). IL-1β also stimulates
12 atherosclerotic events through promoting the production of IL-6 (Libby, 2017). IL-6 in turn promotes the overexpression of atherothrombotic mediators such fibrinogen and plasminogen activator inhibitor (Libby, 2017).
1.4.5 The Relationship between Inflammation and BD
Inflammatory illnesses, such as systemic lupus erythematosus, multiple sclerosis, and autoimmune thyroiditis, have been described to occur in high frequency of patients with BD (Bachen, Chesney, & Criswell, 2009; Edwards & Constantinescu, 2004; Galeazzi et al., 2005; Kupka et al., 2002). Furthermore, one study has shown that a history of
Guillain-Barre syndrome, Crohn's disease, or autoimmune hepatitis results in an increased risk of developing BD (Eaton, Pedersen, Nielsen, & Mortensen, 2010). Inflammation has become a leading candidate biomarker posited to play a role in BD (Hatch et al., 2017;
Mitchell & Goldstein, 2014). Chronic mild inflammatory processes in the periphery and central nervous system are associated with the pathophysiology of BD (Berk et al., 2011;
Goldstein et al., 2017). Inflammatory cytokines that promote inflammation (pro- inflammatory cytokines) have been associated with the depressive and manic symptomology of BD. Pro-inflammatory cytokines are elevated during mania and depression (Goldstein, Kemp, Soczynska, & McIntyre, 2009; Kim, Jung, Myint, Kim, &
Park, 2007; Kim et al., 2004; O'Brien, Scully, Scott, & Dinan, 2006; Ortiz‐Domínguez et al., 2007). Additionally, there is elevation of inflammatory cytokines, such as IL-1β, in the cerebrospinal fluid in patients with BD which is exacerbated if they had experienced a recent manic episode (Söderlund et al., 2011). On the other hand, pro-inflammatory cytokine levels during euthymia are similar to healthy controls (Brietzke et al., 2009;
13 Rapaport, 1994). It has been posited that fluctuating levels in cytokine levels and their receptors are associated with symptom severity in BD (Ortiz‐Domínguez et al., 2007; S.-Y.
Tsai et al., 1999). It is believed these cytokines are associated with symptomology of BD through its influences on the hypothalamic-pituitary-adrenal (HPA) axis and central monoaminergic systems (Goldstein et al., 2009; Raison, Capuron, & Miller, 2006;
Schiepers, Wichers, & Maes, 2005). Evidence indicates that cytokines activate HPA axis, thus increasing levels of corticotrophin releasing hormone (CRH), adrenocorticotropic hormone (ACTH), and cortisol (Allan & Rothwell, 2001; Berk et al., 2011). As a result, there is elevated glucocorticoid levels which has been associated with mood symptoms
(Dantzer, O’Connor, Lawson, & Kelley, 2011).
The influence of inflammatory cytokines on neuronal cell damage and neurodegeneration has been well documented (Aktas, Ullrich, Infante-Duarte, Nitsch, &
Zipp, 2007; Allan & Rothwell, 2001). Furthermore, imbalances in pro- and anti- inflammatory cytokines have been observed among adolescents and adults with BD, whereby studies have shown increased pro-inflammatory and decreased anti-inflammatory markers in the frontal cortex of adults with BD (Barbosa et al., 2014; Hatch et al., 2017;
Papiol et al., 2004; Rao, Harry, Rapoport, & Kim, 2010). Pro-inflammatory cytokines stimulate indoleamine 2,3-dioxygenase (IDO), leading to an increased consumption of tryptophan (Barbosa et al., 2014; Berk et al., 2011). IDO is responsible for the conversion of tryptophan to kynurenine (KYN). As tryptophan is a precursor for serotonin, serotonin levels are indirectly reduced. Pro-inflammatory cytokines further activate kynurenine-3- monooxygenase enzyme (KMO). KMO is responsible for the conversion of KYN into 3- hydroxykynurenine, thus shifting the KYN pathway into the production of neurotoxic
14 metabolites such as quinolinic acid that stimulates neurotoxic effects via N-methyl-D- aspartate (NMDA) receptor over-activation (Berk et al., 2011). This KYN pathway is a proposed mechanism by which the IL-1β pro-inflammatory cytokine may influence neurogenesis and neurodegeneration (Zunszain et al., 2012). This KYN pathway is depicted in Figure 3.
Figure 3 - Kynurenine Pathway of Tryptophan Metabolism. Abbreviations: IDO,
indolamine-2,3-dioxygenase; TPH, tryptophan hydroxylase; KMO, kynurenine 3-
monooxygenase; KAT, kynurenine aminotransferase; KYNU, kynureninase. Thickened
arrows represent biased pathway that pro-inflammatory cytokines, such as IL-1β, promote.
The red rectangle represents a neurotoxic outcome, while the green rectangle represents a
competing neuroprotective outcome.
15 1.4.6 Evidence of Anti-inflammatory Medications for BD
Antidepressant effects have been observed in adjunctive anti-inflammatory medications, such as nonsteroidal anti-inflammatory drugs (NSAIDs), omega-3 polyunsaturated fatty acids, and N-acetylcysteine, without the risk of manic or hypomanic inductions (Rosenblat et al., 2016). Celecoxib, a selective cyclooxygenase (COX)-2 inhibitor, has been shown to reduce the severity of depressive and mixed episodes in patients with BD (Goldstein et al., 2009). In fact, a review article has indicated that anti- inflammatory medications are not only beneficial for depressive episodes, but also help reduce the severity of manic/hypomanic symptoms (Husain, Strawbridge, Stokes, &
Young, 2017).
Traditional mood stabilizers such as lithium have been posited to exert their effects largely through an anti-inflammatory pathway by reducing expression of COX-2, and inhibiting effects of pro-inflammatory cytokines such as IL-1β and IL-6 (Nassar & Azab,
2014). In a preclinical model, pre-treatment of rat glial cells with lithium exhibited anti- inflammatory effects through decreasing lipopolysaccharide-induced secretion of cytokines such as IL-1β and TNF-α (Nahman, Belmaker, & Azab, 2012). This highlights the role of inflammation in the pathophysiology of BD, since the available treatment methods largely target inflammatory pathways.
1.4.7 Inflammatory Cytokine: IL-1β
The interleukin-1β gene, IL1B, encodes for the IL-1β cytokine. This is an integral cytokine in the inflammatory response as the IL-1β cytokine is one of the early initiators of the immune response and leads to the cascade of further cytokine activation such as TNF-α
16 and IL-6, through the activation of nuclear factor kappa B (NF-κB) (Allan & Rothwell,
2001; Berk et al., 2011; Church, Cook, & McDermott, 2008). IL-1β is a prototypic pro- inflammatory cytokine containing pleiotropic effects on various cells (Ren & Torres,
2009). IL-1β also plays a key role in acute and chronic inflammation (Ren & Torres,
2009). A wide variety of cell types can release IL-1β, such as macrophages, mast cells, keratinocytes, endothelial cells, neuronal cells, fibroblasts, and glial cells such as Schwann cells, microglia and astrocytes (Clark et al., 2006; W. Guo et al., 2007; Perrin, Lacroix,
Avilés-Trigueros, & David, 2005; Shamash, Reichert, & Rotshenker, 2002; Sommer &
Kress, 2004; Thacker, Clark, Marchand, & McMahon, 2007). IL-1β is biologically produced as the 33-kDa inactive precursor, pro-IL-1β, and must be cleaved by caspase-1 to form the active 17-kDa IL-1β form (Allan & Rothwell, 2001; Libby, 2017). In the promoter region (position -511) of the IL1B gene is the functional single nucleotide polymorphism (SNP) rs16944, or -511C/T. This is a biallelic SNP in which the T allele is associated with greater IL-1β protein levels (Hall et al., 2004). Interestingly, a study on the expression patterns of various pro-inflammatory cytokines revealed that IL1B gene expression levels were significantly higher in the lymphocytes of patients with BD when compared to HCs (Pandey, Ren, Rizavi, & Zhang, 2015).
Extensive research has shown the impact that the IL-1β rs16944 polymorphism has on brain structure. Specifically, the IL-1β rs16944 polymorphism has been associated with reduced hippocampal volume in healthy adults, as well as white matter deficits, bilateral frontal-temporal gray matter deficits, and ventriculomegaly in patients with schizophrenia
(Meisenzahl et al., 2001; Raz et al., 2015). In fact, the IL-1β rs16944 polymorphism has
17 been associated with whole-brain and left DLPFC gray matter deficits in a structural MRI study of 20 adult patients with BD (Papiol et al., 2008).
1.4.8 Summary of Literature and Rationale
In summary, it is clear from prior literature that neurostructural changes are associated with both certain inflammatory SNPs, specifically IL-1β rs16944, and BD. One study has already investigated the effects of IL-1β rs16944 on brain structure in adults with
BD. However, no study has examined the effects of IL-1β rs16944 on neurostructure among adolescents with BD. Given evidence that early-stage BD is characterized by especially high levels of inflammation (Kauer-Sant'Anna et al., 2009), and given that inflammation among adolescents with BD is associated with increased burden of psychiatric symptoms and CVRFs (Goldstein et al., 2011; Goldstein, Lotrich, et al., 2015), we set out to examine brain structure as an intermediate phenotype of an inflammation- related gene in a relatively large clinical sample of adolescents with and without BD.
2. Materials & Methods
2.1 Study Design
This investigation was a cross-sectional and observational study which examined the neurostructural correlates of IL-1β rs16944 in adolescents with BD and HCs. This study was approved by the research ethics board at Sunnybrook Health Sciences Centre
(Appendix 1). Written informed consent was obtained from all participants along with their parent/guardian prior to study procedures (Appendix 2). All participants completed
18 standard semi-structured diagnostic interviews, psychiatric assessments, anthropometric measurements, and neurostructural MRI scans.
2.2 Participant Selection
2.2.1 Participant Recruitment
This study includes 38 adolescents with BD (types I, II, or not otherwise specified
[NOS]) and 32 HCs, all English-speaking and of European descent. Participants with BD were predominantly recruited via the Centre for Youth Bipolar Disorder (CYBD), a subspecialty clinic at Sunnybrook Health Sciences Centre in Toronto, Ontario. HC participants were recruited via hospital and community advertisements (local print media, newspaper ads). Diagnoses of BD types I, II, or NOS, were confirmed via gold-standard semi-structured diagnostic interviews as outlined below (See 2.5 Primary Interview
Instruments).
2.2.2 Inclusion Criteria
English-speaking adolescents between the ages of 13-20 years were recruited for this study. All participants were of European descent as determined on the Demographics form. BD participants met Diagnostic and Statistical Manual of Mental Disorders (DSM)
IV criteria for BD-I, BD-II, or operationalized criteria for BD-NOS from the Course and
Outcome of Bipolar Youth study (Axelson et al., 2006; Birmaher et al., 2009; Birmaher et al., 2006). HC participants must not have had any history of major psychiatry disorder (i.e. no lifetime mood or psychotic disorders, no anxiety disorders in the past 3 months, and no
19 alcohol or drug dependence in the past 3 months), or any first- or second-degree relatives with BD or family psychosis.
2.2.3 Exclusion Criteria
Participants were excluded if they met for any of the following criteria:
1) Unable to provide informed consent
2) Had a pre-existing cardiac condition, auto-immune illness, or inflammatory illness
3) Taking any anti-inflammatory, anti-platelet, anti-lipidemic, anti-hypertensive, or
hypoglycemic agent
4) Had an infectious illness within the past 14 days
5) Had any contraindications with MRI (e.g. large tattoos, intrauterine device,
irremovable piercings, any metal implanted in the body)
6) Had a health condition or physiological impairment that prohibits moderate to
intense exercise
7) Had neurological or severe cognitive impairment (e.g. autism)
This investigation was part of a multimodal study that examined the influence of exercise on neuroimaging measures such as cerebral blood flow, resting state and event-related fMRI.
2.3 Study Schedule
This study was separated into two visits. The first visit involved the participant and accompanying parent/guardian completing a semi-structured diagnostic interview
(approximately 1-4 hours to complete). The participant also provided a saliva sample for
20 genetic analysis. During the second visit, eligible participants underwent a clinical research interview to evaluate current mood symptoms and provided family medical and psychiatric history. Participants also underwent anthropometric measurements, where blood pressure and BMI were collected. The second visit concluded with the participant undergoing a T1- weighted MRI scan. See Figure 4 for an overview of the study.
Figure 4 – Overview of Study Chronology.
2.4 Participant Demographics, Psychiatric, and Medical History
Demographics and clinical variables such as age, sex, race, diagnoses, family psychiatric and medical history, and current and past medication use were obtained during the first and second visits at the CYBD. These demographic and clinical variables were re- visited and confirmed on the second visit along with post-interview questionnaires.
21 2.5 Primary Interview Instruments
Psychiatric diagnoses and current mood states were derived from the Kiddie
Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and
Lifetime Version (KSADS-PL). Adolescents were interviewed, and parents/guardians were separately interviewed about their adolescents. Diagnoses were confirmed at consensus meetings with a licensed child-adolescent psychiatrist. Comorbid diagnoses (e.g. anxiety disorders, ADHD) and clinical characteristics (e.g. psychosis, physical and sexual abuse) were determined from the KSADS-PL. Participants met for lifetime substance use disorder
(SUD) if they met DSM-IV criteria for abuse or dependence of alcohol or any drug excluding nicotine.
Participant global functioning levels were assessed using the Children’s Global
Assessment Scale (C-GAS). Medication Listing form was utilized to record the medications used in the past 24 hours prior to the second visit. Individual medical history along with family medical and psychiatric history was obtained using the CARDIA
Medical History, CARDIA Family Medical History, and Family Psychiatric History forms respectively. The Family History Screen screens for psychiatric disorders in first- and second-degree relatives. The CARDIA Family Medical History form obtains the family’s history of cardiovascular diseases, stroke, and metabolic syndrome in first- and second- degree relatives.
The Wechsler Abbreviated Scale of Intelligence (WASI) is an assessment tool for intellectual ability. This form consists of four subtests that evaluates difference aspects of intelligence: vocabulary, block design, similarities, and matrix reasoning.
22 2.6 Anthropometric Data
Measure Method of Measurement Blood Pressure Automated Life Source Digital Blood Pressure Monitor Height Stadiometer (Seca Inc; Chino, CA, USA) Weight Body Mass Analysis Scale (Conair Consumer Products; Woodbridge, ON, Canada) Waist Circumference Measuring Tape Table 2 - Anthropometric Data: Measures & Method of Collection.
After 10 minutes of rest, blood pressure was measured twice in the seated position.
Weight was adjusted to account for the approximate weight of the clothing using the following adjustments: subtract 1.4 kg for long pants and long sleeves, subtract 1.1 kg for either short pants or short sleeves, subtract 0.9 kg for short pants and short sleeves.
Adjusted BMI was calculated as adjusted weight in kilograms divided by square of height in meters. For waist circumference, participants were asked to locate both their lowest rib and top of their coxal bone. The flexible tape measure was placed at the centre between these points and the circumference was determined.
2.7 Genetic Data
2.7.1 Saliva Collection
Prior to saliva collection, eligible participants were instructed to refrain from eating, drinking, smoking, or chewing gum 30 minutes. Saliva was collected using DNA
Genotek Oragene-500 (DNA Genotek Inc, Ottawa, Canada) saliva collection kits, in which
2 mL of saliva is required to extract genomic DNA.
23 2.7.2 Genotyping
DNA was extracted and genotyped at a collaborating lab, the Neurogenetics
Laboratory of Dr. James Kennedy at the Centre for Mental Health and Addiction (Toronto,
Canada). DNA was extracted on a chemagen MSM-I DNA extractor (Perkin-Elmer,
Waltham, MA) as per manufacturer’s directions. The extracted DNA was quantified on a
Nanodrop 8000 spectrophotometre (ThermoFisher Scientific, Waltham, MA) and an aliquot was diluted to 20 ng/µL for use in later genotyping analyses.
The IL-1β rs16944 SNP was genotyped using the TaqMan® OpenArray®
Format32 method (ThermoFisher Scientific, Waltham, MA) as per manufacturer’s instructions on the QuantStudio™ 12K Flex Real-Time PCR System (ThermoFisher
Scientific, Waltham, MA). For quality control purposes, a custom assay for the
Amelogenin region was included. To summarize, 2 µL of DNA at a concentration of 20 ng/µL (the previously diluted aliquots) and 2 µL of 2X TaqMan® OpenArray® Master
Mix were coalesced in 384-well plates. Using the AccuFill System (ThermoFisher
Scientific, Waltham, MA), the combined mixtures were loaded onto the OpenArray® genotyping plates. Prepared arrays were amplified, visualized, and analyzed on the
QuantStudio™ system. Genotyping of 10% of samples from each run were replicated for purposes of quality control. Genotyped data was imported into the TaqMan® Genotyper software version 1.3 and two independent researchers from Dr. James Kennedy’s Lab manually confirmed the data.
Based on prior literature, differences in phenotypes were driven by the presence vs. absence of the T allele (i.e., TT/CT vs CC), rather than a dose effect of the allele
(Meisenzahl et al., 2001; Papiol et al., 2008; Raz et al., 2015).
24
2.7.3 Hardy-Weinberg Equilibrium
Deviations from the Hardy-Weinberg Equilibrium were tested using the chi-square,
χ2, test. Departures from the Hardy-Weinberg equilibrium suggests potential sampling bias, population stratification, or genotyping errors.
2.8 Structural Imaging & Analysis
2.8.1 Image Acquisition
MRI scans were collected on a research dedicated 3 Tesla Philips Achieva medical scanner (Philips Medical Systems, Best, Netherlands), utilizing an 8-channel head receiver coil and body coil transmission. The following parameters for the T1-weighted high resolution fast-field echo (FFE) imaging was used: repetition time of 9.5 milliseconds
(ms), echo time of 2.3 ms, field of view of 240 x 191 mm, spatial resolution of 0.94 × 1.17
× 1.2 mm, acquisition matrix of 256 × 164 × 140, flip angle of 8°, and scan duration of 8 minutes and 56 seconds. 3-Dimensional T1-weighted FFE scans quantified gray and white matter using a single slab FFE sequence with 140 slices and acquisition time of 8 minutes and 56 seconds. Prior to processing, the T1-weighted images were examined by radiologists for anatomic abnormalities and neurological abnormalities.
2.8.2 Pre-processing Quality Control: T1 Rating
Two independent raters visually inspected T1-weighted scans of all participants utilizing Freeview, a graphical user interface function in the FreeSurfer program (Fischl,
2012). Raters were trained to score based on overall image quality (e.g. graininess, motion
25 & image artifacts, and contrast between gray and white matter). Raters would examine through the T1-weighted slices in the axial plane and flag any abnormalities in the quality of the scan. Raters scored each subject’s T1-weighted scan on a scale between 0 and 3 as shown in Figure 5. Poor quality images (i.e. images rated a “3”) were removed from the dataset before being processed further.
Figure 5 – Scoring System for T1-weighted Scans.
2.8.3 Pre-processing and Surface Morphometry
The fully automated reconstruction function in FreeSurfer v5.3.0 was used to process T1-weighted images into surface-based morphometric data. Pre-processing consisted of re-sampling of 3D coronal images (1 mm isotropic voxels), automated skull stripping to remove non-brain tissues, intensity normalization correction, and registration to MNI space (12 degrees of freedom). Images were visually inspected to ensure quality of
26 skull stripping and registration. Images underwent automated parcellation and cortical surface reconstruction which consisted of the production of binary white matter masks that were used to generate a triangle-based mesh of the white matter surface and smoothed to remove voxel-based effects and topological defects were rectified (Dale, Fischl, & Sereno,
1999; Fischl & Dale, 2000; Fischl et al., 2002; Fischl, Sereno, & Dale, 1999; Fischl et al.,
2004). A deformation algorithm was implemented to estimate white matter and pial surfaces in which the surfaces were inflated spherically to be later registered to a canonical atlas. Lastly, a parcellation algorithm utilized the FreeSurfer’s default Desikan-Killiany atlas, spatial landmarks, curvatures, and sulcal depth to label 34 gyral regions of interest per hemisphere (Fischl et al., 2004). Each participant’s cortical thickness, surface area, and volume were obtained for each label.
2.8.4 Imaging Data Quality Control: Correcting Parcellation Errors
Each pre-processed T1-weighted scan was inspected for any errors in the cortical parcellation in order to verify the accuracy of the parcellation algorithm. Two trained independent raters scored each scan’s parcellation quality with a score between 0 and 3 using the Freeview function in FreeSurfer. Parcellation quality was dependent on the accuracy by which the gray and white matter delineated. Raters would examine through the
T1-weighted slices in the axial, coronal, and sagittal planes and flag any abnormalities in boundary delineations. Raters are to ensure that parcellations match with the gray and white matter boundaries. Figure 6 provides an example of inaccurate parcellation by which the gray matter boundary does not fully encapsulate the gray matter.
27
Figure 6 – Example of Erroneous Parcellation. Parcellation error is indicated by the blue
arrow. The gray matter boundary (red) does not fully enclose the gray matter.
A score of 0 was assigned to scans that had no problems with parcellation accuracy.
A score of 1 was assigned to scans which had few small localized errors in parcellation. A score of 2 was assigned to scans which had multi-focal or large regional errors in parcellation. However, issues associated with scans assigned a “2” are still feasible for editing. A score of 3 was assigned to scans which had major distortions in parcellation and were deemed impossible to edit the parcellation accurately. Scores of 1 or 2 were edited and re-run through the FreeSurfer pipeline to consolidate the edits. The cortical segmentation editing tools (i.e. the Voxel Edit tool and Control Points White Matter
Detection Enhancer tool) on Freeview were used to edit the scans. Scores of 3 for scans beyond repair were discarded from the dataset to ensure high quality of dataset images.
28 2.9 Defining Regions of Interest
The following ROIs were selected due to the crossover in association with both BD and inflammation: hippocampus (Baune et al., 2012; Bearden et al., 2008; Kalmady et al.,
2014; Maletic & Raison, 2014; Raz et al., 2015), amygdala (Baune et al., 2010; Garrett &
Chang, 2008; Goldstein et al., 2017; Keener & Phillips, 2007; Kelley et al., 2013; Maletic
& Raison, 2014), DLPFC (Keener & Phillips, 2007; Maletic & Raison, 2014; Papiol et al.,
2008; Rajkowska, Halaris, & Selemon, 2001), and caudal ACC (Baune et al., 2010; Emsell
& McDonald, 2009; Javadapour et al., 2007; Maletic & Raison, 2014; Tu et al., 2014). All
ROIs were based on FreeSurfer’s default atlas, Desikan-Killiany (DK) atlas, except for
DLPFC which was defined as the Desikan-Killiany’s rostral middle frontal gyrus (Kikinis et al., 2010). Specific findings between selected ROIs, BD, and inflammation can be found in Table 3.
29 ROI Function BD-Findings Inflammation- Findings Caudal ACC Response selection • ↓ Volume • ↓ Activity and information • ↑ Volume (Baune et al., 2010) processing • ↓ Thickness (Emsell & McDonald, 2009) DLPFC Executive functions • ↓ Activity (Y) • ↓ Volume (working memory, • ↓ Thickness (Papiol et al., 2008) attention) • ↓ Volume (Y) (Keener & Phillips, 2007; Maletic & Raison, 2014) Amygdala Emotional • ↓ Volume (Y) • ↓ Activity regulation • ↑ Volume (Baune et al., 2010) • ↑ Activity (Y) (Keener & Phillips, 2007; Maletic & Raison, 2014) Hippocampus Learning and • ↓ Activity • ↓ Volume memory • ↓ Volume (Y) (Raz et al., 2015) (Bearden et al., 2008; Maletic & Raison, 2014) Table 3 - Crossover in association between BD and inflammation and selected ROIs.
Abbreviations: caudal ACC, caudal anterior cingulate cortex; DLPFC, dorsolateral
prefrontal cortex; Y, youth sample.
2.10 Statistical Analyses
The normality test was assessed for all continuous variables using the Shapiro-
Wilks test. For clinical and demographic characteristics, a univariate General Linear Model
(GLM) was used for continuous variables and a Chi-squared χ2 test for categorical variables. The main effect of the IL-1β rs16944 polymorphism and the interaction effect of diagnosis by IL-1β rs16944 polymorphism were tested through an analysis of covariance
(ANCOVA) model. In this ANCOVA model, ROI measures were inputted as the
30 dependent variable; IL-1β rs16944 polymorphism and diagnosis as the independent variables; age, sex, and intracranial volume (ICV) as the covariates. ICV was removed as a covariate for cortical thickness measurements as ICV does not explain cortical thickness
2 (Liem et al., 2015). Partial eta squared (휂푝) was used as a measure of effect size of the independent variables in the GLM models (Richardson, 2011). Prior to running these analyses, the homogeneity of regression slopes assumption was tested by running an
ANCOVA model with both the independent variables and covariate by independent variable interaction term for each covariate and independent variable combination. If the
ANCOVA assumption of homogeneity of regression slopes was violated (i.e. if a covariate by independent variable interaction term was significant), then a moderated regression analysis GLM was used in which the covariate by independent variable interaction term was included in the model as an independent variable. Statistical significance was defined to be p<0.05. Statistical tests were performed on IBM SPSS Statistics software version 23.
The Benjamini-Hochberg False Discovery Rate (FDR) method was used to correct for multiple ROI comparisons (Benjamini & Hochberg, 1995).
2.11 Two-step Sensitivity Analyses
Sensitivity analyses were conducted for all significant and relevant demographic and clinical variables found in Table 4. Sensitivity analyses were conducted in two sequential steps. First, correlational analyses were conducted for each ROI outcome measure against the relevant demographic and clinical variables in order to verify if the variables were exerting significant effects on the ROI outcome variables. Second, demographic and clinical variables that were significantly correlated with a given ROI
31 outcome measure were added to the ANCOVA design model as a covariate for the respective ROI outcome it was significantly affecting. Prior to running the new ANCOVA model, the homogeneity of regression slopes assumption was tested as described in 2.10
Statistical Analyses. Results from the ANCOVA model were assessed before and after the additional covariates were added in order to verify whether there were any discrepancies.
In the case that the demographic and clinical variables were at least almost exclusively prevalent in the BD group, then the two-step sensitivity analysis process was conducted within the BD group only to assess whether the demographic and clinical variables were significantly influencing ROI outcome measures in adolescents with BD and the main effect of the IL-1β rs16944 polymorphism in the BD group. An exception to this was performing a sensitivity analysis of BMI for both the whole sample and within BD group.
The reason for this was that BMI has already been established to be correlated with brain structure specifically in the BD group of our dataset (Islam, Metcalfe, MacIntosh, Korczak,
& Goldstein, 2018).
2.12 Whole-brain Vertex-wise Exploratory Analyses
The vertex-based GLM in the FreeSurfer package was used to conduct whole-brain analyses through the command-line stream in FreeSurfer (Fischl, 2012). Based on prior literature, surface-based smoothing with a full-width at half-maximum of 15 mm was employed (Fischl, 2012). There are two models that can be used through the command-line stream in FreeSurfer – “Different Offset, Same Slope” (DOSS), and “Different Offset,
Different Slope” (DODS). These models refer to the creation of different design matrices used by the command-line GLM. Both models assume the different groups begin at
32 different values of the outcome variable (different offset or y-intercept). However, the
DOSS model assumes that each group will have the same rate of change in the outcome variable (same slope). On the other hand, the DODS model assumes that each group will have different rates of change in the outcome variable (different slope).
2.12.1 Characteristics of DOSS vs DODS Models
The choice between DOSS and DODS depends on three factors: truth, power, and test of interest. Truth refers to the belief of how the data actually behaves. If it is the belief that the rate of change in the outcome variable is different between the groups, then this should be reflected in the model through the use of DODS. Power refers to the fact that the
DODS model has more regressors than DOSS. As a result, it will have a reduced number of degrees of freedom; and thus, reduced power. The formula for calculating the number of regressors for DODS is Number of Regressors = (Number of Groups)*(Number of
Variables + 1). The formula for calculating the number of regressors for DOSS is Number of Regressors = (Number of Groups) + (Number of Variables). The test of interest refers to whether or not there is interest in the interaction between the covariate and group. If this is the case, then a DODS model should be used.
In our investigation, we were not interested in any interactions between our covariates and groups; thus, we were only interested in truth whilst maximizing power.
Due to prior observation that there are differences in rate of change in certain brain regions and not others between groups based on age in our dataset, DODS was assumed for the age covariate depending on the brain region. To maximize the power of our model, DOSS was always assumed for the sex and ICV covariates. In the case that the rate of change in a
33 brain region was different between groups based on age (tested via the DODS model), then a hybrid DOSS-DODS model was created and used to reflect our assumptions.
2.13 Power Analysis
A sensitivity power analysis was performed using G*Power 3.1 (G*Power:
Statistical Power Analysis for Windows and Mac, Version 3.1.9.3). The sensitivity power analysis was performed on the entire dataset (N=70). Using α set at 0.05 and power set at
0.8, this study had enough power to detect effect sizes of Cohen’s d=0.68.
3. Results
3.1 Demographic and Clinical Characteristics
Adolescents with BD were older (p=0.001), had higher BMIs (p=0.002) and impulsivity scores (p=0.001) compared to adolescent HCs. Adolescents with BD also had greater psychiatric comorbidities, such as anxiety (p<0.001), ADHD (p=0.02), and substance use disorder (p=0.028), and greater substance use, such as lithium (p=0.003), second generation antipsychotics (p<0.001), SSRI antidepressants (p<0.001), and non-
SSRI antidepressants (p=0.028), compared to adolescent HCs. Adolescents with BD were also had more psychiatric hospitalizations when compared to adolescent HCs (p<0.001).
Refer to Table 4.
When compared to T-carriers, non-carriers had higher systolic blood pressure
(p=0.047) and lithium use (p=0.028). Non-carriers also had more psychiatric hospitalizations when compared to T-carriers (p=0.009). Refer to Table 4 for full report of demographic and clinical characteristics.
34 3.2 Hardy-Weinberg Calculation
The allelic distribution for the IL-1β rs16944 polymorphism is 51.4% CC homozygotes (n=36), 42.9% C/T heterozygotes (n=30), and 5.7% TT homozygotes (n=4).
The distribution of these alleles conforms to the Hardy-Weinberg equilibrium: χ2=0.37, p=0.83.
3.3 ROI Analyses
There was an IL-1β rs16944 by Diagnosis interaction effect for DLPFC surface area (p=0.043) presented in Figure 7. This ROI did not remain significant after post-hoc pairwise Bonferroni corrections. However, there was a trend whereby T-carrier adolescents with BD had greater surface area compared to non-carrier adolescents with BD (p=0.151); whereas T-carrier HC adolescents had smaller surface area compared to non-carrier HC adolescents (p=0.152). See Table 5 for a complete reporting of means of the ROIs. It should be noted that none of the ROIs survived FDR corrections for multiple ROI comparisons (pFDR>.172).
3.4 Sensitivity Analyses
In the whole sample, BMI, systolic blood pressure, and ADHD were assessed in a correlation analysis between ROI outcome measures. These variables all failed to influence any ROI outcome measures in the whole sample and so did not proceed to the second step of inclusion as a covariate. However, within the BD group only, BMI was observed to influence DLPFC volume measures. However, there was no significant main effect of the
IL-1β rs16944 polymorphism on DLPFC volume regardless of whether BMI was included
35 as an additional covariate or not. In addition, lifetime SSRI antidepressant and lithium use were both found to influence DLPFC and caudal ACC thickness respectively within the
BD group. However, there were no significant main effect of the IL-1β rs16944 polymorphism on DLPFC and caudal ACC thickness regardless of whether SSRI antidepressant or lithium use were included as an additional covariate or not to their respective associated ROI outcome measure. See Tables 6a and 6b for a report of significant correlation analyses and their respective influence on associated ROI outcome measures.
Figure 7 – Graph of IL-1β rs16944 by Diagnosis interaction effect on DLPFC surface
area. Error bars in standard error (SE).
36 Table 4 - Demographic and Clinical Characteristics of the Study Participants by BD Diagnosis, IL-1β rs16944 Polymorphism, and Diagnosis by IL-1β Polymorphism
Diagnosis IL-1β Allele Subtype Diagnosis by IL-1β Allele Subtype Interaction Characteristic BD HC CC CT/TT BD & CC HC & CC BD & HC & (n=38) (n=32) (n=36) (n=34) (n=21) (n=15) CT/TT CT/TT (n=17) (n=17) Age (Years) ± SE b 17.5 ± 0.2 16.4 ± 0.2 17.1 ± 0.2 16.8 ± 0.2 17.6 ± 0.3 16.6 ± 0.3 17.4 ± 0.3 16.2 ± 0.3 Sex (n) Male 15 (39%) 13 (41%) 15 (42%) 13 (38%) 8 (38%) 7 (47%) 7 (41%) 6 (35%) Female 23 (61%) 19 (59%) 21 (58%) 21 (62%) 13 (62%) 8 (53%) 10 (59%) 11 (65%) BD Subtype, n (%)a BD-I 10 (26%) - 9 (25%) 1 (3%) - - - - BD-II 14 (37%) - 6 (17%) 8 (24%) - - - - BD-NOS 14 (37%) - 6 (17%) 8 (24%) - - - - BMI ± SE b 23.9 ± 0.6 20.8 ± 0.7 22.6 ± 0.7 22.1 ± 0.7 23.9 ± 0.8 21.4 ± 1.1 23.9 ± 1.0 20.3 ± 0.9 Systolic Blood 109.7 ± 2.4 110.7 ± 2.6 113.7 ± 106.7 ± 113.3 ± 114.1 ± 106.0 ± 107.3 ± Pressure ± SE a 2.4 2.5 3.2 3.7 3.5 3.5 Diastolic Blood 68.4 ± 1.5 68.0 ± 1.6 68.4 ± 1.6 68.1 ± 1.6 67.6 ± 2.0 69.2 ± 2.4 69.3 ± 2.2 66.9 ± 2.2 Pressure ± SE Total IQ ± SE 109.4 ± 2.3 105.3 ± 2.7 106.2 ± 108.5 ± 108.6 ± 103.9 ± 110.3 ± 106.8 ± 2.5 2.5 2.9 4.2 3.6 3.5 Lifetime Psychosis, 2 (5%) - 1 (3%) 1 (3%) 1 (5%) - 1 (6%) - n (%) Lifetime 16 (42%) - 13 (36%) 3 (9%) 13 (62%) - 3 (18%) - Psychiatric Hospitalization, n (%)a, b ADHD, n (%)b 16 (42%) 5 (16%) 12 (33%) 9 (26%) 10 (48%) 2 (13%) 6 (35%) 3 (18%) Anxiety Disorder, n 30 (79%) 1 (3%) 19 (53%) 12 (35%) 18 (86%) 1 (7%) 12 (71%) 0 (0%) (%)b
37 Substance Use 6 (16%) - 5 (14%) 1 (3%) 5 (24%) - 1 (6%) - Disorder, n (%)b Second Generation 20 (53%) - 13 (36%) 7 (21%) 13 (62%) - 7 (41%) - Antipsychotic, n (%)b Lithium, n (%)a, b 9 (24%) - 8 (22%) 1 (3%) 8 (38%) - 1 (6%) - SSRI 12 (32%) - 8 (22%) 4 (12%) 8 (38%) - 4 (24%) - Antidepressants, n (%)b Non-SSRI 6 (16%) - 2 (6%) 4 (12%) 2 (10%) - 4 (24%) - Antidepressants, n (%)b Stimulants, n (%) 7 (18%) 2 (6%) 7 (19%) 2 (6%) 6 (29%) 1 (7%) 1 (6%) 1 (6%) LPI Impulsivity ± 30.1 ± 1.9 16.5 ± 3.4 22.0 ± 2.9 24.5 ± 2.6 26.9 ± 2.5 17.2 ± 5.2 33.3 ± 3.0 15.7 ± 4.4 SE b Abbreviations: BD = Bipolar Disorder; HC = Healthy Control; IL-1β = a Significant effect of Risk allele (p<0.05) Interleukin-1β; SE = Standard Error; n = Number of Participants; NOS b Significant effect of Diagnosis (p<0.05) = not otherwise specified; BMI = Body Mass Index; IQ = Intelligence Quotient; ADHD = Attention Deficit Hyperactivity Disorder; SSRI = Selective Serotonin Reuptake Inhibitor; LPI = Life Problems Inventory
38 Table 5 - Brain Region of Interest (ROI) Differences Among BD and HC by IL-1β rs16944 Allele Subtype
CC (n=36) CT/TT Allele (n=34) Allele Subtype Main Diagnosis x Effect Polymorphism Interaction Effect ROI ± SE BD HC Total BD HC Total p- FDR- Effect p- FDR- Effect (n=21) (n=15) (n=38) (n=17) (n=17) (n=34) value Corrected Size value Corrected Size 2 2 p-value 휂푝 p-value 휂푝 Caudal ACC 1617.9± 1564.7 1591.3 1561.7 1510.9 1536.3 .253 .506 .021 .979 .979 .000 Surface Area 44.0 ± 51.7 ± 33.2 ± 48.3 ± 49.4 ± 33.8 (mm2) Caudal ACC 2.6 ± 2.6 ± 2.6 ± 2.7 ± 2.6 ± 2.6 ± .994 .994 .000 .259 .828 .020 Thickness 0.0 0.0 0.0 0.0 0.0 0.0 (mm) Caudal ACC 4717.5 4628.5 4673.0 4608.5 4326.3 4467.4 .234 .562 .022 .570 .76 .005 Volume ± 157.7 ± 185.3 ± 119.2 ± 173.4 ± 177.3 ± 121.1 (mm3) DLPFC 12377.3 12774.9 12576.1 12878.0 12229.1 12553.6 .930 .979 .000 .043 .172 .063 Surface Area ± 236.5 ± 277.9 ± 178.6 ± 260.0 ± 265.9 ± 181.6 (mm2) DLPFC 4.9 ± 4.9 ± 4.9 ± 4.9 ± 5.0 ± 5.0 ± .621 .828 .004 .501 .828 .007 Thickness 0.1 0.1 0.0 0.1 0.1 0.0 (mm) DLPFC 36394.4 37320.0 36857.2 37361.5 36580.5 36971.0 .886 .886 .000 .281 .562 .018 Volume ± 731.6 ± 859.7 ± 552.7 ± 804.3 ± 822.6 ± 561.7 (mm3) Hippocampus 8598.3 8801.0 8699.6 8921.9 8897.1 8909.5 .103 .212 .044 .380 .380 .013 Volume ± 119.7 ± 143.0 ± 92.5 ± 130.9 ± 138.2 ± 95.2 (mm3) Amygdala 3253.3 3239.8 3246.5 3452.9 3220.0 3336.4 .189 .252 .027 .106 .212 .041 Volume ± 62.5 ± 73.4 ± 47.2 ± 68.7 ± 70.2 ± 48.0 (mm3)
39
Table 6a – Correlation Analyses (Sensitivity Analysis Step 1) Correlations Pearson p-value Correlation Significant Within BMI by DLPFC -.333 .041 BD Group Volume Correlations SSRI by DLPFC -.349 .032 Thickness Lithium by Caudal -.321 .049 ACC Thickness Significant Whole - - - Sample Correlations
Table 6b – Addition of Covariates (Sensitivity Analysis Step 2) Covariate Added ROI p-value Before p-value After Covariate Added Covariate Added BMI DLPFC Volume .822 .838 SSRI DLPFC Thickness .873 .625 Antidepressant Use Lithium Use Caudal ACC .477 .955 Thickness
3.5 Whole-brain Vertex-wise Analyses
In the whole sample, the IL-1β rs16944 polymorphism was associated with the lateral occipital cortex (LOC) as shown in Figure 8, whereby T-carriers had greater LOC surface area (p=0.013) and volume (p=0.019) in the left hemisphere when compared to non-carriers (see Figure 9). Whole-brain vertex-wise analyses also generated IL-1β rs16944-by-Diagnosis interaction effects in two clusters as shown in Figure 10. One of the two clusters is a left hemisphere volume cluster with a peak vertex in the LOC encapsulating the pericalcarine and inferior temporal regions (p=0.013). Post-hoc analysis revealed that T-carrier adolescents with BD had greater volume compared to non-carrier adolescents with BD (p=0.005); whereas T-carrier HC adolescents had smaller volume compared to non-carrier HC adolescents (p<0.001). The second cluster was generated in
40 the right hemisphere for surface area with a peak vertex in the pars triangularis encapsulating the pars orbitalis, rostral middle frontal and lateral orbitofrontal (p=0.006).
Post-hoc analysis revealed that T-carrier adolescents with BD had greater surface area compared to non-carrier adolescents with BD (p=0.029); whereas T-carrier HC adolescents had smaller surface area compared to non-carrier HC adolescents (p=0.001). Figures 11 and 12 display graphs of the LOC and pars triangularis clusters respectively. See Table 7 for a complete reporting of results for the whole-brain vertex-wise analyses.
Figure 8 – LOC Surface Area in the Left Hemisphere. This same region was found for
LOC volume.
Figure 9 – Graph of LOC Surface Area (SA) in the Left Hemisphere. Error bars in SE.
41
Figure 10 – LOC Volume Cluster in the Left Hemisphere and Pars Triangularis
Surface Area Cluster in the Right Hemisphere. The LOC cluster has the peak vertex in the LOC and comprises of the pericalcarine and inferior temporal gyrus regions. The pars
triangularis cluster has the peak vertex in the pars triangularis and comprises of the pars
orbitalis, rostral middle frontal, and lateral orbitofrontal regions.
42
Figure 11 - Graph of IL-1β rs16944-by-Diagnosis interaction effect in the LOC
Volume Cluster in the Left Hemisphere. Cluster also encompasses the pericalcarine and
inferior temporal gyrus. Error bars in SE.
43
Figure 12 - Graph of IL-1β rs16944-by-Diagnosis interaction effect in the Pars
Triangularis Surface Area (SA) Cluster in the Right Hemisphere. Cluster also
encompasses the pars orbitalis, rostral middle frontal, and lateral orbitofrontal regions.
Error bars in SE.
Table 7- Exploratory Vertex-wise Whole-brain Analyses: Significant Cluster-wise Results Cluster Peak Additional Cortical measure Hemisphere p-value Name Encapsulated Regions IL-1β rs16944 SNP Effect LOC / Surface Area Left 0.013 LOC / Volume Left 0.019 IL-1β rs16944 x Diagnosis Interaction Effect LOC Inferior Temporal & Volume Left 0.013 Pericalcarine Pars Pars Orbitalis, Surface Area Right 0.006 Triangularis Rostral Middle Frontal, Lateral Orbitofrontal
44 4. Discussion
4.1 Summary of Findings
This study examined the relationship between the IL-1β rs16944 polymorphism and neurostructural MRI measures in adolescents with and without BD. The ROIs were selected based on its previously associations with inflammation and BD. Findings from this study insinuates the implication that there are unique neurostructural correlates of the IL-1β rs16944 polymorphism in adolescents with BD, which are not present in adolescents without BD. This study controlled for sex, age, and ICV. After performing FDR corrections, there were no significant ROI results. As a result, none of the ROI analyses were in support of the hypotheses that there would be both a main effect of the IL-1β rs16944 polymorphism and an interaction effect between this polymorphism and BD. After controlling for additional relevant demographic and clinical variables as part of a sensitivity analysis in both the whole sample and within BD group, there were no changes in significance of reported findings regarding the ROI outcome measures.
Exploratory vertex-wise whole brain analyses revealed a main effect of the IL-1β rs16944 polymorphism whereby T-carriers had greater surface area and volume than non- carriers. This supports the hypothesis that there would be a main effect of the IL-1β rs16944 polymorphism. Furthermore, the vertex-wise whole brain analyses yielded two interaction effects in the LOC volume and pars triangularis surface area clusters. These clusters had the same relationship where BD T-carriers had a greater cluster volume/surface area than BD non-carriers, while the opposite was observed in HC adolescents. These clusters support the hypothesis of an interaction effect between the IL-
1β rs16944 polymorphism and diagnosis.
45 In summary, this is the first study to demonstrate an association between the IL-1β rs16944 polymorphism and neurostructural changes in adolescents with and without BD.
The findings in this study highlights the involvement of inflammation in the poor health outcomes experience in patients with BD. More importantly, these findings stress the need to enhance treatment studies associated with inflammation to evaluate the effect of optimizing inflammation levels on brain structure throughout the course of the BD illness.
4.2 Interpretation of Findings
4.2.1 Main Effect: The IL-1β rs16944 Polymorphism Effect in LOC Cluster
The results from this study supports the hypothesis of a main effect of the IL-1β rs16944 polymorphism on brain structure, specifically LOC surface area and volume. In particular, the T-carriers had greater LOC surface area and volume than non-carriers in the left hemisphere. The function of the LOC region is related to object recognition (Grill-
Spector, Kourtzi, & Kanwisher, 2001). The LOC’s relation to the cytokine IL-1β is consistent with a previous study in adults where increased cytokine levels resulted in decreased LOC volume (Bai, Tu, Li, Su, & Chen, 2016). In contrast to this study, our results indicate an increase in LOC surface area and volume associated with the T-allele which is assumed to lead to greater IL-1β cytokine production. Previous studies explain that the same allele can have opposite effects in adolescence versus adulthood (Cole et al.,
2011). As a result, although this T allele has been shown to increase inflammation in adulthood, it may not have this same effect in adolescence. A recent study has shown that increased plasma levels of inflammatory markers (such as white blood cell count, von
Willebrand factor, and Factor VIII) was associated with smaller occipital lobe volume
46 (Walker et al., 2017). Although this study was performed in adults and did not investigate cytokine levels, this study sheds light on the relationship between inflammation and occipital lobe regions, such as the LOC.
4.2.2 Interaction Effect: Diagnosis by Polymorphism Effect in LOC Cluster
The results from this study also supports the hypothesis of an interaction effect between diagnosis and the IL-1β rs16944 polymorphism on brain structure, specifically for the left hemisphere LOC and right hemisphere pars triangularis clusters. The LOC cluster also includes the pericalcarine and inferior temporal regions. The relationship between the
LOC cluster, diagnosis, and the IL-1β rs16944 polymorphism is that HC T-carriers had a smaller LOC cluster volume than non-carriers; while the opposite was found in adolescents with BD. As discussed above, LOC has been linked to inflammation. In addition, studies have shown that the LOC brain region is altered in patients with BD. Specifically, patients with BD had smaller LOC thickness when compared to healthy controls (Niu et al., 2017;
Reavis et al., 2017).
The structural alterations observed in our study of the occipital visual area pericalcarine is in agreement with reported pericalcarine volume and thickness reductions and visual perception deficits in BD (Abé et al., 2016; O'bryan, Brenner, Hetrick, &
O'donnell, 2014). Working memory tasks that involve pericalcarine have been shown to be impaired in patients with BD (Abé et al., 2016; Albers, Kok, Toni, Dijkerman, & de Lange,
2013; Diwadkar et al., 2011; Larrabee & Kane, 1986). Moreover, duration of BD illness was negatively correlated with the pericalcarine gyrus (Hibar et al., 2017). Pericalcarine has not only been implicated with BD, but also with inflammation. High inflammation has
47 been associated with smaller pericalcarine thickness in healthy adults (Fleischman et al.,
2010).
In recent years, the inferior temporal gyrus has received more attention in structural and functional imaging studies associated with BD and inflammation as it is involved in cognitive processes such as multimodal sensory integration and visual perception (Cabeza
& Nyberg, 2000; Herath, Kinomura, & Roland, 2001; Ishai, Ungerleider, Martin,
Schouten, & Haxby, 1999; Mesulam, 1998). One study found a decrease in the inferior temporal gyrus volume in patients with BD who were in a manic state (Cui et al., 2010). In addition, Niu and colleagues highlighted cortical thinning of the inferior temporal gyrus in patients with BD (Niu et al., 2017). Similarly, Rimol and colleagues revealed cortical thinning of the inferior temporal gyrus in patients with BD-I (Rimol et al., 2010). The inferior temporal gyrus has also been implicated with inflammation. A positron emission tomography (PET) imaging study revealed that an increase in inflammatory cytokines led to a decrease in resting glucose metabolism in the inferior temporal gyrus of healthy controls (Harrison, Doeller, Voon, Burgess, & Critchley, 2014).
4.2.3 Interaction Effect: Diagnosis by Polymorphism Effect in Pars Triangularis
Cluster
The pars triangularis cluster includes the pars orbitalis, rostral middle frontal and lateral orbitofrontal regions. The relationship between the pars triangularis cluster, diagnosis, and the IL-1β rs16944 polymorphism is that HC T-carriers had a smaller cluster surface area than non-carriers; while the opposite was found in adolescents with BD. These regions have all been found to be implicated in BD. Adults with BD showed reduced
48 cortical thickness in the pars triangularis and lateral orbitofrontal gyrus (Niu et al., 2017).
Furthermore, the pars triangularis, pars orbitalis, and pars opercularis all make up the inferior frontal cortex. Cross-sectional and longitudinal studies have shown a negative correlation between number of manic episodes experienced by patients with BD-I and inferior frontal gyrus volume (Abé et al., 2015; Lyoo et al., 2004). Moreover, patients with
BD had reduced activation in the inferior frontal cortex when performing inhibition tasks
(Townsend et al., 2012). A large consortium study, consisting of 6503 participants, revealed that patients with BD was associated with smaller rostral middle frontal gyrus thickness (Hibar et al., 2017). A longitudinal study also showed that a greater number of manic episodes was associated with decreased rostral middle frontal gyrus volume (Abé et al., 2015). Cortical thinning in the inferior frontal, rostral middle frontal, and lateral orbitofrontal gyrus have been shown to be heritable and linked with BD (Fears et al., 2014;
Hanford, Nazarov, Hall, & Sassi, 2016).
As the regions in the pars triangularis cluster have previously been associated with
BD, they have also been associated with inflammation. Elevated cytokine levels were associated with decreased inferior frontal gyrus thickness (Kaur et al., 2015). Further studies have found increased IL-1β mRNA and protein levels in the frontal cortex of post- mortem brains of patients with BD (Miller & Raison, 2016; Rao et al., 2010).
Although the ROI finding of DLPFC surface area did not remain significant after post-hoc pairwise Bonferroni corrections, it is worth mentioning that the rostral middle frontal region, circumscribed in the pars triangularis cluster, validates the DLPFC ROI finding since DLPFC was defined as the rostral middle frontal region in this study.
49 4.3 Proposed Bottom-up Framework of the LOC
Face emotion labelling deficits that are observed in BD had previously solely been attributable to high-order deficits in brain regions such as the amygdala and fusiform face area, regions that process fear and is largely responsible for face perception respectively
(Kanwisher, McDermott, & Chun, 1997; Perlman et al., 2013; Puce, Allison, Asgari, Gore,
& McCarthy, 1996). However, in recent years it has been proposed that lower-order brain regions, such as the LOC, may be exerting a bottom-up effect on face emotion recognition
(Javitt, 2009). This bottom-up model of LOC’s effect on face emotion recognition would assume that patients with BD have difficulty simply decrypting the complex facial configuration that people use to convey facial emotions (Javitt, 2009). In fact, one study, using visual masking procedures, directly observed a relationship between impaired social perception and early aspects of visual processing (Sergi & Green, 2003). Furthermore, crosstalk between the LOC and fusiform face area has been established (Nagy, Greenlee, &
Kovács, 2012). Nagy and colleagues suggest that object and face processing are not entirely segregated, and in fact the lower level processes of face emotion labelling may be attributable to the interaction between the fusiform and LOC (Nagy et al., 2012). As a result, this elucidates the influence of bottom-up pathways in the paradigm of impaired social cognition expressed in patients with BD. To validate this model, future studies should investigate whether face emotion labelling deficits are attributable to only emotion recognition (validating the high-order deficits model) or to other types of facial processing such as identity, age, or sex (validating the bottom-up model) (Javitt, 2009).
50 4.4 Cortical Surface Area vs Cortical Thickness Implications
The IL-1β rs16944 polymorphism was exclusively associated with cortical surface area rather than cortical thickness in this study. Cortical surface area and cortical thickness are independently related to domains such as genetic variance (Ecker et al., 2013; Winkler et al., 2010). As a result, the IL-1β rs16944 polymorphism may phenotypically affect cortical surface area rather than cortical thickness.
Cortical thickness is fully established much earlier than surface area. Studies have shown that cortical thickness is established earlier in life relative to cortical surface area in which cortical thickness only has a small window of rapid development (Haartsen, Jones,
& Johnson, 2016; Lyall et al., 2014). Therefore, surface area has a more extensive period of development and so has a longer period of being susceptible to neurodevelopmental setbacks. According to the radial unit hypothesis, the cerebral cortex is ordered into ontogenetic columns. Surface area reflects the number of columns, while thickness represents number and size of cells within a column (Ecker et al., 2013; Rakic, 1995).
Hogstrom et al. have further shown that ontogenetic increases in cortical volume is driven by expanding cortical surface area more so than increased cortical thickness (Hogstrom,
Westlye, Walhovd, & Fjell, 2012). Based on multiple studies, a hallmark phenotype for neurodevelopmental disorders, such as Autism Spectrum Disorder and Alcohol-related neurodevelopmental disorder, seem to be changes in cortical surface area rather than thickness (Mensen et al., 2017; Rajaprakash, Chakravarty, Lerch, & Rovet, 2014). These point towards cortical surface area being more closely associated with neurodevelopmental disorders rather than cortical thickness.
51 Cortical thickness, rather than surface area, has been more associated with neurodegenerative disorders such as Alzheimer’s disease and other dementias,
Huntington’s disease, and corticobasal degeneration (Fischl & Dale, 2000; Jack Jr et al.,
2015). In fact, exercising has shown to help reverse neurodegeneration by increasing cortical thickness in early stages of Alzheimer’s disease (Reiter et al., 2015). Past studies have shown cortical thinning as associated with bipolar patients (Hanford et al., 2016;
Hatton et al., 2013; Lyoo et al., 2006; Rimol et al., 2010; Rimol et al., 2012). In adults with
BD, the duration of illness was associated with cortical thickness reductions rather than cortical surface area (Hibar et al., 2017). As a result, as the illness progresses, degeneration also progressed. This provides more evidence that cortical thickness is more associated with neurodegenerative mechanisms rather than cortical surface area. Hence, it was previously believed that BD is a neurodegenerative disorder. However, in recent years cortical surface area has surfaced to be highly implicated with BD. Our study further advocates that changes in cortical surface area is a phenotype expressed with BD. As a result, our study strengthens the school of thought that perhaps BD is a combination of both neurodegenerative and neurodevelopmental pathways.
4.5 Limitations
There are several limitations to this study that must be acknowledged when interpreting these findings. First, this study implemented a cross-sectional and observational design, which precludes the inference of causality on the associations in this study. Second, although this study had a larger sample size than previous MRI studies of adolescents with BD, the sample size is modest. As a result, this study did not have enough
52 power to detect small to moderate effect sizes. Relatedly, the limited sample size prevented the ability of this study to conduct a three-way genotype analysis of the IL-1β rs16944 polymorphism. Our study would require 128 participants to detect a medium effect size of
Cohen’s d=0.5, power set to 0.80 and α=0.05. In order to run a three-way genotype analysis, our study would require 158 participants to detect a medium effect size of
Cohen’s d=0.5, power set to 0.80 and α=0.05.
Third, this study only investigated the association between the IL-1β rs16944 polymorphism and brain structure in exclusively participants of European descent. As a result, the findings may not be extrapolated to other races. Fourth, the sample in this study is heterogeneous (i.e. variability in medication use, family history, comorbidities, and BD subtype). Although extensive sensitivity analyses were performed to account for significant influences, the heterogeneity may introduce potential confounds that were unaccounted for.
However, the heterogeneity of this sample increases the representativeness and face validity of this study.
Fifth, despite the fact that the findings of this study survived sensitivity analyses for medications, psychotropic medications such as lithium present a normalizing effect on brain structure (Atmaca et al., 2007; D. M. Hafeman, Chang, Garrett, Sanders, & Phillips,
2012; McDonald, 2015). This suggests these medications may have neuroprotective properties in patients with BD. Although this normalizing effect of medications suggests a bias towards the null hypothesis, the findings of this study still supported the alternative hypothesis.
Additionally, the T-allele of the IL-1β rs16944 polymorphism has been associated with greater IL-1β levels in adults (Hall et al., 2004). This relationship has not yet been
53 investigated in an adolescent population. One study found that inflammatory cytokine
SNPs can have opposite effects on gene expression in adolescents versus adults (Cole et al., 2011). Future studies should determine the IL-1β rs16944 polymorphism relationship with gene expression whilst investigating any associations between this polymorphism and functional studies alongside cognitive tasks. This will aid in providing a more cohesive interpretation of neurostructural findings.
Lastly, as with any candidate gene study, an inherent limitation of this study is the possibility of loci being in linkage disequilibrium with the IL-1β rs16944. As a result, the neurostructural associations observed in this study may be more appropriately attributable to alleles at a different locus than to the IL-1β rs16944 polymorphism.
4.6 Future Directions
4.6.1 Longitudinal Study Integrating Other Imaging Modalities
Future prospective cohort observational study designs in participants with BD and
HCs may provide insight into the temporal developmental sequence of the association between the IL-1β rs16944 polymorphism and BD in structural brain morphology. It would be interesting to supplement these structural findings with diffusion tensor imaging (DTI) and fMRI. DTI is a noninvasive neuroimaging tool that utilizes diffusion of water to indirectly investigate differences in white matter microstructural integrity. White matter tract impairments have been shown to precede expression of BD (Versace et al., 2010). IL-
1β has been shown to promote the differentiation of oligodendrocyte progenitor cells and support the maturation and survival of these cells (Vela, Molina-Holgado, Arévalo-Martın,́
Almazán, & Guaza, 2002). In fact, IL-1β deficient mice was shown to have a delay in re-
54 myelination; thus supporting the notion that IL-1β may affect myelination processes such as synaptic pruning and synaptic strengthening (Allan, Tyrrell, & Rothwell, 2005; Mason,
Suzuki, Chaplin, & Matsushima, 2001). Including DTI modality will allow the elucidation of whether the IL-1β rs16944 polymorphism predisposes individuals to white matter integrity deficits in BD.
Functional studies should investigate whether the face emotion labelling deficits expressed in patients with BD are ensued from deficits in emotion recognition (validating the high-order deficits model) or to other deficits in facial processing such as identity, age, or sex (validating the bottom-up model). This would assist in validating whether the high- order deficits model, or the bottom-up model, or both are playing a role in the face emotion labelling deficits. As a result, emotion recognition tasks and simpler facial processing tasks may be used to delineate the previously mentioned models.
Future longitudinal studies examining brain structure and other imaging modalities in relation to the IL-1β rs16944 polymorphism should investigate these measures in other psychiatric illnesses, such as MDD. This will help distinguish whether the findings are relevant to the general neurobiology of psychiatric illnesses or if the findings are potential endophenotypes of BD.
4.6.2 Adjunctive Anti-inflammatory Treatment Options
A large problem with the medications used for BD is that they have severe side effects such as metabolic syndrome which amplifies the already present increased risk of
CVD associated with BD. Studies have shown that lithium and lamotrigine use is associated with increased weight gain and fasting glucose (Hermida, Fontela, Ghiglione, &
55 Uttenthal, 1994; Sachs et al., 2006; Vendsborg, Bech, & Rafaelsen, 1976). Valproate use has also been associated with increased weight gain and insulin levels (Dinesen, Gram,
Andersen, & Dam, 1984; Pylvänen et al., 2002). Furthermore, second generation antipsychotic (SGA) use has been associated with hyperlipidemia, insulin resistance, increased risk of diabetes mellitus, and weight gain (Gaulin, Markowitz, Caley, Nesbitt, &
Dufresne, 1999; Gianfrancesco, White, Wang, & Nasrallah, 2003; J. J. Guo et al., 2006;
Henderson et al., 2000; Pylvänen et al., 2002; Sernyak, Gulanski, & Rosenheck, 2005;
Simpson, 2005; Zipursky et al., 2005). However, adjunctive therapy using anti- inflammatory medications such as low doses of aspirin (a COX-1 and COX-2 inhibitor) can combat these side effects by acting as an antithrombotic and thrombolytic agent
(Muneer, 2016).
Other adjunctive therapy options are anakinra (an IL-1 receptor antagonist) and the newly developed canakinumab (a monoclonal antibody against IL-1β). Anakinra works by competing with both isoforms of the IL-1, IL-1β and IL-1α. Anakinra has been effective in reducing metabolic syndrome; however, anakinra may cause enhanced susceptibility to infection due to its unselective antagonism of the IL-1 system (Libby, 2017). In contrast, canakinumab selectively targets the IL-1β cytokine, and so poses less of a risk for infection. Canakinumab may also yield greater compliance than anakinra. This is because anakinra requires daily injections, while canakinumab allows a subcutaneous dose administered ever 3 months due to its longer half-life (Libby, 2017). In a randomized, double-blind, placebo-controlled trial, canakinumab was associated with a decreased risk for myocardial infarction, stroke, and cardiovascular-related deaths (Ridker et al., 2017).
As a result, potential adjunctive anti-inflammatory medications, such as canakinumab, may
56 help manage the high death rates from cardiovascular events experienced in patients with
BD (Muneer, 2016). However, it is imperative to balance potential therapeutic benefits with risk of adverse effects. Granted that anti-inflammatory medications serve many benefits towards reducing mood symptoms and CVRFs, they also pose a risk towards the integrity of the immune system.
4.6.3 Interleukin-1β Treatment Targets
There are various strategies that may be utilized to reduce IL-1β signalling and act as a neuroprotective mechanism (see Figure 13). Anti-inflammatory molecules such as IL-
10 may be utilized to reduce expression of the IL1B gene whilst producing opposing effects of IL-1β. Cannabinoids have been shown to have anti-inflammatory effects by inhibiting IL-1β expression and release from the cell (Allan & Rothwell, 2001). Caspase-1 inhibitors may also be utilized in order to reduce the amount of inactive pro-IL-1β conversions to active IL-1β. IL-1-receptor antagonists (IL-1RA) may be used to block the interaction between IL-1β and its receptor, IL-1 receptor (IL-1R). A recombinant drug of
IL-1RA, anakinra, is already in clinical practice. Downstream of IL-1β signalling include activation of NF-κB, mitogen-activated protein kinases (MAPKs) and extracellular-signal- regulated kinases (ERKs), which lead to production of nitric oxide (NO) and prostaglandin
E (PGE) (Allan et al., 2005). As a result, drugs that selectively inhibit of NF-κB, MAPKs,
ERKs, NO or PGEs may be effective in individuals who chronically express elevated IL-
1β levels.
However, anti-inflammatory medications have not always been beneficial at reducing mood symptoms. Two studies have highlighted that anti-inflammatory
57 medications may only exert therapeutic effects in patients with a high baseline of inflammatory markers (Husain et al., 2017; Raison et al., 2013). Investigating the influence that inflammatory genes might have on treatment response outcomes may prove as a useful tool for personalized medicine in treating mood disorders.
Figure 13 – Potential IL-1β Pathway Treatment Targets. IL: interleukin; IL-1RA:
interleukin-1 receptor antagonist; NF-κB: nuclear factor kappa-light-chain-enhancer of
activated B cells; MAPK: mitogen-activated protein kinase; ERK: extracellular-signal-
regulated kinases; PGE: prostaglandin E; NO: nitric oxide; NOS: nitric oxide synthase.
Green boxes represent downstream signalling of IL-1β. Purple boxes represent potential
pharmacological drug targets in the IL-1β pathway.
58 4.7 Conclusion
In conclusion, this was the first study to examine the association between an inflammatory SNP and brain structure in adolescents with BD compared to HC adolescents. This study unveiled significant interaction effects in regions involved with BD and BD-associated phenotypes. Future longitudinal studies are warranted to investigate the long-term impact of inflammatory genes on neurostructural changes. This study supplements the growing literature that connects inflammation with BD.
59 References
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71 Appendices Appendix 1
72
73 Appendix 2
CONSENT TO PARTICIPATE IN A RESEARCH STUDY For Adolescents 13-20 years of age
TITLE OF PROJECT:
Assessing Changes in Cerebral Perfusion and Neuropsychological Function in Response to Aerobic Exercise among Adolescents with versus without Bipolar Disorder
PRINCIPAL INVESTIGATOR:
Benjamin I. Goldstein, MD, PhD, FRCPC Sunnybrook Health Sciences Centre 2075 Bayview Avenue Toronto, Ontario M4N 3M5
CO-INVESTIGATORS:
Dr. Daphne Korczak, MD, FRCPC, FRCPC Dr. Bradley MacIntosh, PhD Hospital for Sick Children HSF Centre for Stroke Recovery 555 University Avenue Sunnybrook Research Institute Toronto, Ontario M5G 1X8 2075 Bayview Avenue Toronto, Ontario M4N 3M5 Dr. Arron Metcalfe, PhD Sunnybrook Research Institute 2075 Bayview Avenue Toronto, Ontario M4N 3M5
SPONSOR: Ontario Mental Health Foundation
INFORMED CONSENT You are being asked to consider taking part in a research study. It is important that you read and understand this document. It describes the purpose, procedures, benefits, risks, discomforts and precautions of the study. It also describes other options that are available to you and your right to withdraw from the study at any time. If this form contains anything you do not understand or would like to know more about, please ask the study doctor or study staff to explain it to you. Upon request, someone may verbally translate this form in your preferred language. You may take as much time as you need to decide whether or not to participate. Feel free to discuss it with your friends and family, or your family doctor. You must make sure that all of your questions are answered to your satisfaction before deciding whether or not you will participate in this study.
74 INTRODUCTION You are being asked to participate in this research study because you are either being treated for bipolar disorder through the Youth Psychiatry Division of Sunnybrook or because you responded to an advertisement to participate in the study as a psychiatrically healthy participant.
WHAT IS THE USUAL TREATMENT? Usually, bipolar disorder is treated by assessing symptom frequency and severity, safety and efficacy of medication therapy, and in some cases, psychosocial treatment. Height, weight, blood pressure, and, in some cases, waist circumference is collected. Non-invasive MRI scans of the brain can also be routine practice for some patients.
WHY IS THE STUDY BEING DONE? This study aims to measure changes in brain activity and blood flow after aerobic exercise among adolescents with and without bipolar disorder, and to find out whether these changes are associated with performance on neurocognitive tests. Furthermore, this study aims to examine how these factors relate to blood vessel functioning, biomarkers, and certain genetic markers. By including these factors in the same study, we hope to learn about the mechanism behind these cognitive benefits of exercise, and how they relate to one another in adolescents with bipolar disorder and in healthy adolescents.
WHAT WILL HAPPEN DURING THIS STUDY? Study Visit 1 Visit 1 involves taking part in a screening interview to see if you are eligible to participate in this study. The interview will consist of questions about you regarding specific medical illnesses and medications that might interfere with the assessment of the factors listed above, and it will take about 10-15 minutes. If you do not have these illnesses or take these medications, you will be asked to complete a psychiatric interview and to answer questions regarding your medical history, eating habits, physical activity, life events including family conflict, and use of nicotine, alcohol and street drugs. In addition, an intelligence test will be completed with the interviewer. The interview will take about 3 hours to complete. Study Visit 2 If you meet the study criteria for being a participant with bipolar disorder or a control participant, you will be asked to return to Sunnybrook for a second visit to complete the following tasks: IMPORTANT: Before arriving for Visit 2, you will be asked to abstain from all food and drink (no caffeine and alcohol, water is permitted) for at least 8 hours prior. You must also not drink water, smoke or chew gum 30 minutes prior. Saliva Collection: We will first ask you to provide us with a 4mL sample of your saliva (about 1 teaspoonful) by spitting into a special tube. This will take approximately 10-15
75 minutes. Additionally, we will ask you to provide us with a sample of your saliva at 5 time points during the course of the study visit by asking you to place a cotton swab in your mouth for 60 seconds. Altogether, this additional saliva collection may take up to 10 minutes. Blood Vessel Functioning: Next, we will measure your blood vessel functioning using a device called the EndoPAT. This will involve gently placing non-invasive probes on the index fingers of your hands while you are lying on your back. The EndoPAT will gather information for 10 minutes while you are resting. Then a blood pressure cuff will be tightly inflated on your arm for 5 minutes to prevent blood flow. The ultrasound will again gather information for 10 minutes after the blood pressure cuff is released. This will take up to about 60 minutes to complete. Break: After the completion of these two tasks, you will be given a 30 minute break. Food and drink (non-caffeinated) will be provided. Questionnaires: After returning from your break, you will be asked to complete questionnaires regarding your medical history, eating habits, physical activity, life events including family conflict, and use of nicotine, alcohol and street drugs. This should take about 30 minutes. Aerobic Exercise and MRI Scans: Finally, you will be asked to complete a task that assesses brain changes while you perform a cognitive test. This will include a practice of the test, a pre-exercise assessment, a bout of aerobic exercise, and a post-exercise assessment. You will practice the cognitive test for 10 minutes so that you are familiar with it, and complete it two more times both before and after the exercise session. The test gathers information on cognitive function (thinking and memory) by using a reaction test, and may require you to press an appropriate button quickly after a stimulus appears. After the practice, your brain will be imaged using non-invasive magnetic resonance imaging (MRI) at rest and while you complete the cognitive test. This will take approximately 1 hour. This scan assesses changes in activity and blood flow in the brain, and involves lying stationary on a bed that moves into the centre of the main magnetic field. MRI technologists will perform all MRI scans and are trained to address participant needs and maximize comfort. You will have constant communication with the MRI technologists and study staff while undergoing the MRI and you are free to withdraw at any time. During one of the MRI scans, there will also be a breath hold task that will require your active participation. This task measures how breath holding may affect blood flow to your brain. You will be asked to hold your breath six separate times for 15 seconds each. You will see instructions on the screen that will switch from “rest” for 30 seconds to “breathe out” for 5 seconds followed by “hold breath” for 15 seconds. After the MRI, you will be asked to ride a stationary bike for 25 minutes just outside of the MRI scanning room. This will include a five minute warm-up period and 20 minutes of exercise that will increase your breathing and heart rate. The goal is to maintain a constant rate and workload such that your heart rate stays between 60-80% of your age calculated maximum (208-0.7*AGE). You will be monitored for safety and are free to stop exercising at any time. After the exercise, your brain will be imaged again while at rest and during the
76 cognitive test. This will take approximately 30 minutes. In total, this study phase will take about 2.5 hours to complete.
1 2 3 4 5
Practice Run MRI at rest In-scanner cognitive In-scanner at Task Exercise cognitive task task with MRI Scan Bike with MRI Scan
Your parent can accompany you to the MRI scan and wait just outside the testing room. Since the procedures must be the same for all participants, parents may not be inside the testing room.
Visit 1 Visit 2
TOTAL TIME: 1 – 4 hours Approximately 4.5 hours
Informed Consent = 45 minutes Saliva Collection = 10 minutes
Screening = 10 – 15 minutes Blood Vessel Assessment = 60 minutes
Psychiatric Interview / Complete Break = 30 minutes self – report forms = 3 hours
Questionnaires = 30 minutes
Cognitive Practice Test = 10 minutes
Aerobic Exercise = 25 minutes
MRI Scans = 1.5 hours
HOW MANY PEOPLE WILL TAKE PART IN THE STUDY? It is expected that about 120 adolescents and their parents will take part in this study at Sunnybrook. The length of this study for participants include 2 separate sessions lasting approximately 8.5 hours total. The entire study is expected to take about 4 years to complete and the results should be known in 1 year following the completion of study procedures.
77
WHAT ARE THE RESPONSIBILITES OF STUDY PARTICIPANTS? Although participation in this study is entirely voluntary, you are responsible for completing the full procedure for each visit, as outlined above. If you choose not to complete any of the requirements, you will not be able to participate in the study. Please note the following information regarding the use and storage of the saliva sample you will provide at visit 2: Duration of Storage of Information All saliva samples will be stored at Sunnybrook Health Sciences Centre. Your individual results of genetic markers and other results pertaining to cognitive test performance will not be reported to you because, at this point in time, these are research measurements, and they do not currently have any clear relevance to your medical health. Any samples obtained from you will be destroyed once analysis is complete. If the research study is extended beyond this time, you will be asked once again to give consent to extend the storage period for a specified amount of time. If you cannot be reached, your samples will be destroyed at that time. Limits to Sharing Information with Collaborators and Laboratories The saliva samples obtained from you will not be used for any other investigations outside of this study (i.e. for the purpose of investigating bipolar disorder). The information may be sent for specific testing to the laboratories of collaborators with Dr. Goldstein’s team; however information will not be shared with any individuals who are not involved in this study.
WHAT ARE THE POTENTIAL RISKS AND/OR DISCOMFORTS OF PARTICIPATING IN THIS STUDY? You may experience side effects from participating in this study. Some side effects are known and are listed below, but there may be other side effects that are not expected. If you decide to take part in this study, you should contact the study doctor (Dr. Benjamin Goldstein) or study staff during business hours with questions or concerns regarding any side effects or study-related injuries that you experience.The telephone number for this purpose is: 416-480-5328. Frequency Severity Long Term Impact Very Likely Less Rare Side Effect Likely (10- Likely (0- Mild Moderate Severe Temporary Permanent (30- 30%) (1-10%) 1%) 100%) Muscle X X X Fatigue/Sore ness Heart X X X X Trouble Heart or Attack Light X X X
78 Headedness Eye Strain or X X X Headache Emotional X X X Discomfort Hunger Pains X X X There is a chance you may experience temporary muscle fatigue or soreness from the exercise. There are no known risks associated with magnetic resonance imaging other than discomfort while remaining still for the scanning period. You may experience temporary light headedness from the breath hold task. You may experience eye strain or headaches while concentrating on the computerized cognitive test. You may experience emotional discomfort when completing the psychiatric interview and questionnaires. You may experience hunger and/or hunger pains while fasting. There is a minimal risk of heart trouble with exercise which could make you feel short of breath, pain or pressure in your chest, or pain down your arm. The risk includes the rare possibility of a heart attack. We will minimize the risk by monitoring your heart rate and having appropriate emergency services on hand. You may discontinue any of the procedures at any time. You will be told about any new information that might reasonably affect your willingness to continue to participate in this study as soon as the information becomes available to study staff.
WHAT ARE THE POTENTIAL BENEFITS OF PARTICIPATING IN THIS STUDY? There are no direct benefits from participation in this study. However, this study relies on your participation in order to explore bipolar disorder among adolescents, which will broaden understandings of the illness and may eventually lead to novel assessment, prevention and treatment strategies. Findings from this study may therefore benefit future individuals or families affected with or at risk for bipolar disorder.
CAN PARTICIPATION IN THIS STUDY END EARLY? The investigator(s) may decide to remove you from this study without your consent for any of the following reasons: • You are unable or unwilling to follow the study procedures • If you are disruptive to the study If you are removed from this study, the investigator(s) will discuss the reasons with you. You can also choose to end your participation at any time without having to provide a reason. If you choose to withdraw, your choice will not have any effect on your current or future medical treatment or health care. There will be no penalty or loss of benefits to which you are otherwise entitled. If you withdraw voluntarily from the study, you are encouraged to contact: Dr. Benjamin Goldstein at 416-480-5328; 2075 Bayview Avenue, Toronto, Ontario, M4N 3M5. If you withdraw consent to participate after beginning the study, the data collected up to that time point will be used.
79 WHAT ARE THE COSTS FOR PARTICIPATING IN THIS STUDY? There is no cost for participation.
WHAT HAPPENS IF I HAVE A RESEARCH RELATED INJURY? If you become sick or injured as a direct result of your participation in this study, your medical care will be provided. Financial compensation for such things as discomfort due to injury is not routinely available. By signing this consent form, you do not give up any of your legal rights.
ARE STUDY PARTICIPANTS PAID TO PARTICIPATE IN THIS STUDY? Parents will be compensated $50 for travel expenses and parking. Adolescents will be compensated $20 for completing study screening procedures. Eligible participants will also receive $90 at the completion of Visit 2. HOW WILL MY INFORMATION BE KEPT CONFIDENTIAL? You have the right to have any information about you and your health that is collected, used or disclosed for this study to be handled in a confidential manner. If you decide to participate in this study, the investigator and study staff will look at your personal health information and collect only the information they need for this study. Personal health information refers to health information about you that could identify you because it includes information such as your: • Name, • Address, • Telephone number, • Date of birth, • New and existing medical records, or • The types, dates and results of various tests and procedures.
You have the right to access, review and request changes to your personal health information.
The following people may come to the hospital to look at your personal health information to check that the information collected for the study is correct and to make sure the study followed the required laws and guidelines:
• Representatives of the Sunnybrook Research Ethics Board, a group of people who oversee the ethical conduct of research studies at Sunnybrook
Access to your personal information will take place under the supervision of the Principal Investigator.
80
“Study data" is information about you that is collected for the study, but that does not directly identify you. Any study data that is sent outside of the hospital will have a study code and will not contain your name or address or any information that directly identifies you. Study data that is sent outside of the hospital will be used for the research purposes explained in this consent form.
The investigator(s), study staff and the other people listed above will keep the information they see or receive about you confidential, to the extent permitted by applicable laws. Even though the risk of identifying you from the study data is very small, it can never be completely eliminated. All study data will be stored in a secure and confidential location for a period of at least 5 years. All reasonable measures to protect the confidentiality of participants’ study records and their identity will be taken to the extent permitted by the applicable laws and/or regulations, and will not be made publicly available. The results of this study may be presented at meetings or in publications; however, participant’s identity will not be disclosed. When the results of this study are published, your identity will not be disclosed.
You have the right to be informed of the results of this study once the entire study is complete. If you would like to be informed of the results of this study, please contact the study doctor: Dr. Benjamin Goldstein, 416-480-5328.
DOES (DO) THE INVESTIGATOR(S) HAVE ANY CONFLICTS OF INTEREST? The study doctors do not have any conflicts of interest regarding this study.
WHAT ARE THE RIGHTS OF PARTICIPANTS IN A RESEARCH STUDY? You have the right to receive all significant information that could help you make a decision about participating in this study. You also have the right to ask questions about this study and your rights as a research participant, and to have them answered to your satisfaction, before you make any decision. You also have the right to ask questions and to receive answers throughout this study. If you have any questions about this study, you are encouraged to contact the study doctor: Dr. Benjamin Goldstein at 416-480-5328. The Sunnybrook Research Ethics Board has reviewed this study. If you have questions about your rights as a research participant or any ethical issues related to this study that you wish to discuss with someone not directly involved with the study, you may call Chair of the Sunnybrook Research Ethics Board at 416-480-6100 ext. 88144.
81 Assessing Changes in Cerebral Perfusion and Neuropsychological Function in Response to Aerobic Exercise among Adolescents with versus without Bipolar Disorder
Name of Participant: ______
Participant:
By signing this form, I confirm that: • This research has been fully explained to me and all of my questions answered to my satisfaction • I understand the requirements of participating in this research study • I have been informed of the risks and benefits, if any, of participating in this research study • I have been informed of any alternatives to participating in this research study • I have been informed of the rights of research participants • I have read each page of this form • I authorize access to my personal health information, medical record and research study data as explained in this form • I have agreed to participate in this research study, or agree to allow the person I am responsible for, to participate in this research study • I understand that my family doctor may be informed of my participation in this research study • This informed consent document may be placed in my medical records
______Name of Adolescent (print) Signature Date
Assistance Declaration
Was the participant assisted during the consent process? Yes No
82 The consent form was read to the participant/substitute decision-maker, and the person signing below attests that the study was accurately explained to, and apparently understood by, the participant/substitute decision-maker. The person signing below acted as a translator for the participant/substitute decision-maker during the consent process. He/she attests that they have accurately translated the information for the participant/substitute decision-maker, and believe that that participant/substitute decision-maker has understood the information translated.
______Name of Person Assisting (print) Signature Date
Person Obtaining Consent By signing this form, I confirm that: • This study and its purpose has been explained to the participant named above • All questions asked by the participant have been answered • I will give a copy of this signed and dated document to the participant
______Name of Person Obtaining Signature Date Consent (print)
83 CONSENT TO PARTICIPATE IN A RESEARCH STUDY For Parents of Adolescents 13-20 years of age
TITLE OF PROJECT:
Assessing Changes in Cerebral Perfusion and Neuropsychological Function in Response to Aerobic Exercise among Adolescents with versus without Bipolar Disorder
PRINCIPAL INVESTIGATOR:
Benjamin I. Goldstein, MD, PhD, FRCPC Sunnybrook Health Sciences Centre 2075 Bayview Avenue Toronto, Ontario M4N 3M5
CO-INVESTIGATORS:
Dr. Daphne Korczak, MD, FRCPC, FRCPC Dr. Bradley MacIntosh, PhD Hospital for Sick Children HSF Centre for Stroke Recovery 555 University Avenue Sunnybrook Research Institute Toronto, Ontario M5G 1X8 2075 Bayview Avenue Toronto, Ontario M4N 3M5 Dr. Arron Metcalfe, PhD Sunnybrook Research Institute 2075 Bayview Avenue Toronto, Ontario M4N 3M5
SPONSOR: Ontario Mental Health Foundation
INFORMED CONSENT Your adolescent is being asked to consider taking part in a research study. As part of the study, you will be asked to answer questions and fill out questionnaires about your adolescent. It is important that you read and understand this document. It describes the purpose, procedures, benefits, risks, discomforts and precautions of the study. It also describes other options that are available to your adolescent and his/her right to withdraw from the study at any time. If this form contains anything you do not understand or would like to know more about, please ask the study doctor or study staff to explain it to you. Upon request, someone may verbally translate this form in your preferred language. You may take as much time as you need to decide whether or not to participate. Feel free to discuss it with your friends and family, or your family doctor. You must make sure that all of your questions are answered to your satisfaction before deciding whether or not you will participate in this study. INTRODUCTION
84 Your adolescent is being asked to participate in this research study because he/she is either being treated for bipolar disorder through the Youth Psychiatry Division of Sunnybrook or because he/she responded to an advertisement to participate in the study as a psychiatrically healthy participant.
WHAT IS THE USUAL TREATMENT? Usually, bipolar disorder is treated by assessing symptom frequency and severity, safety and efficacy of medication therapy, and in some cases, psychosocial treatment. Height, weight, blood pressure, and, in some cases, waist circumference is collected. Non-invasive MRI scans of the brain can also be routine practice for some patients.
WHY IS THE STUDY BEING DONE? This study aims to measure changes in brain activity and blood flow after aerobic exercise among adolescents with and without bipolar disorder, and to find out whether these changes are associated with performance on neurocognitive tests. Furthermore, this study aims to examine how these factors relate to blood vessel functioning, and certain genetic markers. By including these factors in the same study, we hope to learn about the mechanism behind these cognitive benefits of exercise, and how they relate to one another in adolescents with bipolar disorder and in healthy adolescents.
WHAT WILL HAPPEN DURING THIS STUDY? Study Visit 1 Visit 1 involves taking part in a screening interview to see if you and your adolescent are eligible to participate in this study. The interview will consist of questions about your adolescent regarding specific medical illnesses and medications that might interfere with the assessment of the factors listed above, and it will take about 10-15 minutes. If your adolescent does not have these illnesses or take these medications, you will be asked to complete a psychiatric interview regarding your adolescent and to answer questions regarding his/her medical history, eating habits, physical activity, life events including family conflict, and use of nicotine, alcohol and street drugs. In addition, your adolescent will complete an intelligence test with the interviewer. The interview will take about 3 hours to complete. Study Visit 2 If your adolescent meets the study criteria for being a participant with bipolar disorder or a control participant, you will both be asked to return to Sunnybrook for a second visit to complete the following tasks: IMPORTANT: Before arriving for Visit 2, your adolescent will be asked to abstain from all food and drink (no caffeine and alcohol, water is permitted) for at least 8 hours prior. Your adolescent must also not drink water, smoke or chew gum 30 minutes prior.
85 Saliva Collection: We will first ask your adolescent to provide us with a 4mL sample of his/her saliva (about 1 teaspoonful) by spitting into a special tube. This will take approximately 10-15 minutes. Additionally, we will ask your adolescent to provide us with a sample of his/her saliva at 5 time points during the course of the study visit by asking them to place a cotton swab in their mouth for 60 seconds. Altogether, this additional saliva collection may take up to 10 minutes. Blood Vessel Functioning: Next, we will measure your adolescent’s blood vessel functioning using a device called the EndoPAT. This will involve gently placing non- invasive probes on the index fingers of your adolescent’s hands while he/she is lying on his/her back. The EndoPAT will gather information for 10 minutes while your adolescent is resting. Then a blood pressure cuff will be tightly inflated on your adolescent’s arm for 5 minutes to prevent blood flow. The ultrasound will again gather information for 10 minutes after the blood pressure cuff is released. This will take up to about 60 minutes to complete. Break: After the completion of these two tasks, you will be given a 30 minute break. Food and drink (non-caffeinated) will be provided. Questionnaires: After returning from your break, your adolescent will be asked to complete questionnaires regarding his/her medical history, eating habits, physical activity, life events including family conflict, and use of nicotine, alcohol and street drugs. This should take about 30 minutes. Aerobic Exercise and MRI Scans: Finally, your adolescent will be asked to complete a task that assesses brain changes while he/she performs a cognitive test. This will include a practice of the test, a pre-exercise assessment, a bout of aerobic exercise, and a post- exercise assessment. Your adolescent will practice the cognitive test for 10 minutes so that he/she is familiar with it, and complete it two more times both before and after the exercise session. The test gathers information on cognitive function (thinking and memory) by using a reaction test, and may require your adolescent to press an appropriate button quickly after a stimulus appears. After the practice, your adolescent’s brain will be imaged using non-invasive magnetic resonance imaging (MRI) at rest and while he/she completes the cognitive test. This will take approximately 1 hour. This scan assesses changes in activity and blood flow in the brain, and involves your adolescent lying stationary on a bed that moves into the centre of the main magnetic field. MRI technologists will perform all MRI scans and are trained to address participant needs and maximize comfort. Your adolescent will have constant communication with the MRI technologists and study staff while undergoing the MRI and he/she is free to withdraw at any time. During one of the MRI scans, there will also be a breath hold task that will require the active participation of your adolescent. This task measures how breath holding may affect blood flow to his or her brain. Your adolescent will be asked to hold his or her breath six separate times for 15 seconds each. They will see instructions on the screen that will switch from “rest” for 30 seconds to “breathe out” for 5 seconds followed by “hold breath” for 15 seconds. After the MRI, your adolescent will be asked to ride a stationary bike for 25 minutes just outside of the MRI scanning room. This will include a five minute warm-up period and 20 minutes of exercise that will increase your adolescent’s breathing and heart rate. The goal
86 is to maintain a constant rate and workload such that your adolescent’s heart rate stays between 60-80% of his/her age calculated maximum (208-0.7*AGE). Your adolescent will be monitored for safety and he/she is free to stop exercising at any time. After the exercise, your adolescent’s brain will be imaged again while at rest and during the cognitive test. This will take approximately 30 minutes. In total, this study phase will take about 2.5 hours to complete.
1 2 3 4 5
Practice Run MRI at rest In-scanner In-scanner at Task Exercise cognitive task cognitive task Bike with MRI Scan with MRI Scan
You can accompany your adolescent to the MRI scan and wait just outside the testing room. Since the procedures must be the same for all participants, parents may not be inside the testing room.
Visit 1 Visit 2
TOTAL TIME: 1 – 4 hours Approximately 4.5 hours
Informed Consent = 45 minutes Saliva Collection = 10 minutes
Screening = 10 – 15 minutes Blood Vessel Assessment = 60 minutes
Psychiatric Interview / Complete Break = 30 minutes self – report forms = 3 hours
Questionnaires = 30 minutes
Cognitive Practice Test = 10 minutes
Aerobic Exercise = 25 minutes
MRI Scans = 1.5 hours
HOW MANY PEOPLE WILL TAKE PART IN THE STUDY? It is expected that about 120 adolescents and their parents will take part in this study at Sunnybrook. The length of this study for participants include 2 separate sessions lasting approximately 8.5 hours total. The entire study is expected to take about 4 years to complete and the results should be known in 1 year following the completion of study procedures.
87
WHAT ARE THE RESPONSIBILITES OF STUDY PARTICIPANTS? Although participation in this study is entirely voluntary, you and your adolescent are responsible for completing the full procedure for each visit, as outlined above. If you or your adolescent chooses not to complete any of the requirements, you will both not be able to participate in the study. Please note the following information regarding the use and storage of the saliva sample your adolescent will provide at visit 2: Duration of Storage of Information All saliva samples will be stored at Sunnybrook Health Sciences Centre. Your adolescent’s individual results of genetic markers and other results pertaining to his/her cognitive test performance will not be reported to you or your adolescent because, at this point in time, these are research measurements, and they do not currently have any clear relevance to your adolescent’s medical health. Any samples obtained from your adolescent will be destroyed once analysis is complete. If the research study is extended beyond this time, your adolescent will be asked once again to give consent to extend the storage period for a specified amount of time. If your adolescent cannot be reached, his/her samples will be destroyed at that time. Limits to Sharing Information with Collaborators and Laboratories The saliva samples obtained from your adolescent will not be used for any other investigations outside of this study (i.e. for the purpose of investigating bipolar disorder). The information may be sent for specific testing to the laboratories of collaborators with Dr. Goldstein’s team; however information will not be shared with any individuals who are not involved in this study.
WHAT ARE THE POTENTIAL RISKS AND/OR DISCOMFORTS OF PARTICIPATING IN THIS STUDY? Your adolescent may experience side effects from participating in this study. Some side effects are known and are listed below, but there may be other side effects that are not expected. If your adolescent decides to take part in this study, he/she should contact the study doctor (Dr. Benjamin Goldstein) or study staff during business hours with questions or concerns regarding any side effects or study-related injuries that he/she experiences.The telephone number for this purpose is: 416-480-5328. Frequency Severity Long Term Impact Very Likely Less Rare Side Effect Likely (10- Likely (0- Mild Moderate Severe Temporary Permanent (30- 30%) (1-10%) 1%) 100%) Muscle X X X Fatigue/Sore ness Heart X X X X Trouble or Heart Attack
88 Light X X X Headedness Eye Strain or X X X Headache Emotional X X X Discomfort Hunger pains X X X There is a chance your adolescent may experience temporary muscle fatigue or soreness from the exercise. There are no known risks associated with magnetic resonance imaging other than discomfort while remaining still for the scanning period. Your adolescent may experience temporary light headedness from the breath hold task. Your adolescent may experience eye strain or headaches while concentrating on the computerized cognitive test. Your adolescent may experience emotional discomfort when completing the psychiatric interview and questionnaires. Your adolescent may experience hunger or hunger pains while fasting. There is a minimal risk of heart trouble with exercise which could make your adolescent feel short of breath, pain or pressure in his/her chest, or pain down his/her arm. The risk includes the rare possibility of a heart attack. We will minimize the risk by monitoring your adolescent’s heart rate and having appropriate emergency services on hand. Your adolescent may discontinue any of the procedures at any time. You and your adolescent will be told about any new information that might reasonably affect your willingness to continue to participate in this study as soon as the information becomes available to study staff.
WHAT ARE THE POTENTIAL BENEFITS OF PARTICIPATING IN THIS STUDY? There are no direct benefits from participation in this study. However, this study relies on you and your adolescent’s participation in order to explore bipolar disorder among adolescents, which will broaden understandings of the illness and may eventually lead to novel assessment, prevention and treatment strategies. Findings from this study may therefore benefit future individuals or families affected with or at risk for bipolar disorder.
CAN PARTICIPATION IN THIS STUDY END EARLY? The investigator(s) may decide to remove your adolescent from this study without his/her consent for any of the following reasons: • He/she is unable or unwilling to follow the study procedures • He/she is disruptive to the study If your adolescent is removed from this study, the investigator(s) will discuss the reasons with him/her. You and your adolescent can also choose to end participation at any time without having to provide a reason. If your adolescent chooses to withdraw, his/her choice will not have any effect on his/her current or future medical treatment or health care. There will be no penalty or loss of benefits to which you are otherwise entitled. If you withdraw voluntarily from the study, you are encouraged to contact: Dr. Benjamin Goldstein at 416-480-5328;
89 2075 Bayview Avenue, Toronto, Ontario, M4N 3M5. If you withdraw consent to participate after beginning the study, the data collected up to that time point will be used.
WHAT ARE THE COSTS FOR PARTICIPATING IN THIS STUDY? There is no cost for participation. WHAT HAPPENS IF I HAVE A RESEARCH RELATED INJURY? If your adolescent becomes sick or injured as a direct result of his/her participation in this study, his/her medical care will be provided. Financial compensation for such things as discomfort due to injury is not routinely available. By signing this consent form, you or your adolescent do not give up any of your legal rights.
ARE STUDY PARTICIPANTS PAID TO PARTICIPATE IN THIS STUDY? Parents will be compensated $50 for travel expenses and parking. Adolescents will be compensated $20 for completing study screening procedures. Eligible participants will also receive $90 at the completion of Visit 2.
HOW WILL MY INFORMATION BE KEPT CONFIDENTIAL? Your adolescent has the right to have any information about him/her and his/her health that is collected, used or disclosed for this study to be handled in a confidential manner. If your adolescent decides to participate in this study, the investigator and study staff will look at his/her personal health information and collect only the information they need for this study. Personal health information refers to health information about your adolescent that could identify him/her because it includes information such as your adolescent’s: • Name, • Address, • Telephone number, • Date of birth, • New and existing medical records, or • The types, dates and results of various tests and procedures.
Your adolescent has the right to access, review and request changes to his/her personal health information.
The following people may come to the hospital to look at your adolescent’s personal health information to check that the information collected for the study is correct and to make sure the study followed the required laws and guidelines:
• Representatives of the Sunnybrook Research Ethics Board, a group of people who oversee the ethical conduct of research studies at Sunnybrook
90 Access to your adolescent’s personal information will take place under the supervision of the Principal Investigator.
“Study data" is information about your adolescent that is collected for the study, but that does not directly identify your adolescent. Any study data that is sent outside of the hospital will have a study code and will not contain your adolescent’s name or address or any information that directly identifies him/her. Study data that is sent outside of the hospital will be used for the research purposes explained in this consent form.
The investigator(s), study staff and the other people listed above will keep the information they see or receive about you confidential, to the extent permitted by applicable laws. Even though the risk of identifying your adolescent from the study data is very small, it can never be completely eliminated.
All study data will be stored in a secure and confidential location for a period of at least 5 years. All reasonable measures to protect the confidentiality of participants’ study records and their identity will be taken to the extent permitted by the applicable laws and/or regulations, and will not be made publicly available. The results of this study may be presented at meetings or in publications; however, participant’s identity will not be disclosed. When the results of this study are published, your adolescent’s identity will not be disclosed. You and your adolescent have the right to be informed of the results of this study once the entire study is complete. If either of you would like to be informed of the results of this study, please contact the study doctor: Dr. Benjamin Goldstein, 416-480-5328.
DOES (DO) THE INVESTIGATOR(S) HAVE ANY CONFLICTS OF INTEREST? The study doctors do not have any conflicts of interest regarding this study.
WHAT ARE THE RIGHTS OF PARTICIPANTS IN A RESEARCH STUDY? You have the right to receive all significant information that could help you make a decision about participating in this study. You also have the right to ask questions about this study and your rights as a research participant, and to have them answered to your satisfaction, before you make any decision. You also have the right to ask questions and to receive answers throughout this study. If you have any questions about this study, you are encouraged to contact the study doctor: Dr. Benjamin Goldstein at 416-480-5328. The Sunnybrook Research Ethics Board has reviewed this study. If you have questions about your rights as a research participant or any ethical issues related to this study that you wish to discuss with someone not directly involved with the study, you may call Chair of the Sunnybrook Research Ethics Board at 416-480-6100 ext. 88144.
91 Assessing Changes in Cerebral Perfusion and Neuropsychological Function in Response to Aerobic Exercise among Adolescents with versus without Bipolar Disorder
Name of Participant: ______
Parent:
By signing this form, I confirm that: • This research has been fully explained to me and all of my questions answered to my satisfaction • I understand the requirements of participating in this research study • I have been informed of the risks and benefits, if any, of participating in this research study • I have been informed of any alternatives to participating in this research study • I have been informed of the rights of research participants • I have read each page of this form • I have agreed to participate in this research study, or agree to allow the person I am responsible for, to participate in this research study
______Name of Parent (print) Signature Date
Assistance Declaration
Was the participant assisted during the consent process? Yes No The consent form was read to the participant/substitute decision-maker, and the person signing below attests that the study was accurately explained to, and apparently understood by, the participant/substitute decision-maker. The person signing below acted as a translator for the participant/substitute decision-maker during the consent process. He/she attests that they have accurately translated the information for the participant/substitute decision-maker, and believe that that participant/substitute decision-maker has understood the information translated.
92 ______Name of Person Assisting (print) Signature Date
Person Obtaining Consent By signing this form, I confirm that: • This study and its purpose has been explained to the participant named above • All questions asked by the participant have been answered • I will give a copy of this signed and dated document to the participant
______Name of Person Obtaining Consent (print) Signature Date
93