Brain Insulin Resistance and Motivation in Mood Disorders
Phase: PHASE1
Conditions: Major Depressive Disorder, Bipolar Disorder, Anhedonia, Intranasal Insulin
Sponsor: University Health Network, Toronto

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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1. Hypothesis and Specific Aims 
Overarching Hypothesis: Insulin signaling is a critical neurobiological substrate of anhedonia in mood 
disorders 
Specific Hypotheses: In individuals with mood disorders, objective and self-reported measures of 
anhedonia and reward behaviors are associated with alterations in insulin signaling-related molecular, 
cellular and neural substrates. Considering the role of insulin in the regulation of energy expenditure, 
we primarily hypothesize that individuals with mood disorders will display decreased willingness to 
make effort for rewards, relative to healthy controls; and that this abnormality will be associated with: 
a) Molecular: Differential gene and protein expression of the metabolic (i.e. PI3K/Akt) and mitogenic 
(i.e. Ras/MAP kinase) components of the insulin signaling pathway, as well as with components of 
reward-related processes (i.e. dopamine receptors and transporter)  
b) Physiology: Reduced peripheral sensitivity to insulin and corresponding metabolic correlates, 
including increased body mass index and dyslipidemia (i.e. peripheral insulin resistance) 
c) Neural Circuits: Diminished response to insulin in cortico-striatal networks (i.e. brain insulin 
resistance) 
Overarching Aim: To determine the role of insulin signaling on the neurobiological substrates 
subserving anhedonia within individuals with mood disorders. 
Specific Aims: 
a) Molecular: Assessment of components of the insulin cascade, as well as of anhedonia and reward-
related processes, using a proteomics and gene expression approach; 
b) Physiology: Measurement of peripheral sensitivity to insulin and metabolic correlates, including 
body mass index and dyslipidemia; 
c) Neural Circuits: Evaluation of the insulin sensitivity of prefrontal (e.g. prefrontal cortex) and 
striatal (e.g. nucleus accumbens, ventral tegmental area) networks in the resting-state and during an 
effort-based decision making test, using acutely administered intranasal insulin and functional 
magnetic resonance imaging (fMRI); 
d) Behavioral: Measurement of willingness to make effort for rewards, as well as of other components 
of reward response and anhedonia, using validated behavioral tasks and clinical scales (e.g. Snaith-
Hamilton Pleasure Scale - SHPS). 
2. Background and Rationale 
Mood disorders (i.e. major depressive disorder [MDD] and bipolar disorder [BD]) and metabolic 
disorders (i.e. type 2 diabetes mellitus [T2DM], obesity) are highly prevalent and impactful conditions. 
Epidemiological studies have identified depressive disorders and diabetes as leading causes of 
disability worldwide1. Mood and metabolic disorders are also major causes of excessive and premature 
mortality. Mortality studies indicate that with individuals with MDD or BD have markedly reduced life 
expectation, on average of 10-15 years2; the main driver of excess and premature mortality in this 
population is cardiovascular disease and/or diabetes complications2,3. Conversely, depressive 
symptoms, particularly anhedonia, are consistently reported in T2DM populations and have been 
associated with an increased incidence of complications and all-cause mortality4,5. 
Comorbid metabolic disorders are extremely common in individuals with mood disorders. Meta-
analytic studies have documented that individuals with MDD or BD have an approximately 2-fold 
increased risk of T2DM, relative to the general population6. It is estimated that the prevalence of 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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T2DM in individuals with mood disorders is between 8 and 10%6, whereas the prevalence of metabolic 
syndrome is approximately 30%7. Convergent lines of inquiry indicate that mood and metabolic 
disorders have a bidirectional association8-10. For example, it is reported that individuals with T2DM 
have an approximate 2-3 fold greater risk for subsequently declaring MDD or BD11. Nonetheless, the 
association between metabolic and mood disorders is still poorly understood. Overlapping risk factors 
(e.g. diet, physical activity, psychotropic medications, sleep, childhood trauma) have an important 
role6; however there is insufficient data on the extent to which these environmental factors are 
responsible for the mood-metabolic disorders comorbidity. Mechanistic studies have documented a role 
for the biological substrates of metabolic and mental disorders, such as neurostructural alterations12,13, 
and differences in peripheral biomarkers14. A recent genetic study identified multiple genes that are 
likely shared between mood and metabolic disorders; pathway analysis revealed an over-representation 
of genes that encode for molecules involved in dopamine signaling15. There is considerable evidence 
that dopamine has a core role in anhedonia and reward-related behaviors, indicating that this is a 
particularly promising area for further advancing the knowledge on the association of mood and 
metabolic disorders.  
1.1. Mood Disorders and Anhedonia 
Anhedonia is defined as markedly diminished interests or pleasure in all, or almost all, activities 
most of the day, nearly every day for an extended period of time. Anhedonia is a core criterion item for 
the diagnosis of a major depressive episode. Anhedonia is also a robust predictor of poorer longitudinal 
course of symptoms of MDD and BD16-19. Existing psychological and pharmacological treatments are 
relatively ineffective for treating anhedonia, as standard medication treatments have little effect and in 
some cases may even worsen anhedonic symptoms17,20. As a result, anhedonia has been described as 
one of the most prevalent residual disturbances following treatment with selective serotonin re-uptake 
inhibitors17,21,22. 
Anhedonia includes elements of multiple reward processes23-25. Reward systems are primarily 
responsible for responses to positive motivational situations or contexts, such as reward seeking, and 
reward/habit learning23-25. Reward is a broad and heterogeneous construct. To effectively study it, it is 
important to consider its three main subconstructs: (1) reward responsiveness, including anticipatory 
and initial hedonic responses; (2) learning, or the acquisition of information about stimuli, actions and 
context; and (3) valuation, including the measurement of value and/or incentive salience of a 
prospective outcome and the willingness to work for it (i.e. effort)26,27. 
Evidence indicates that individuals with mood disorders exhibit abnormalities in multiple of these 
reward subcomponents28-32. Anhedonia is closely related to reward anticipation, motivation and 
decision making29,33. A consistent finding has been a decrease in the willingness to expend effort and/or 
in the modulation of effort expenditure for rewards28-31,33. It has been demonstrated that individuals 
with depression display reduced motivation on effort-based decision making29-31, a dissociation 
between liking a reward and the willingness to exert effort for it28, an increased subjective feeling of 
having exerted more effort31  and a lower ability to effectively use information about rewards to modify 
their behavioral choices29.  
1.2. Neural Substrates of Anhedonia and Reward 
The most well-characterized reward circuit is the mesolimbic pathway, which consists of 
dopaminergic projections from the ventral tegmental area (VTA) to the nucleus accumbens (NAc)34,35. 
These areas are heavily interconnected with the prefrontal cortex (PFC), amygdala and hippocampus, 
among other areas34. Specifically, connections between the dorsolateral PFC (dlPFC), NAc and VTA 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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have a key role in motivated behavior36. Indeed, connectivity between the PFC and striatal areas during 
reward-related tasks negatively correlates with anhedonia in individuals with MDD37,38. 
Dopaminergic neurotransmission has been highlighted as a key component of multiple reward 
processes39. Dopamine signaling has traditionally been implicated in arousal, motivation and 
psychomotor activation (i.e. incentive salience models), and reward learning/reinforcement (i.e. 
prediction error models)40-42. Recent work proposes that dopamine signals value, or the available 
reward for a certain effort, which is then employed for both learning and motivational functions42. 
Multiple studies from different lines of research, such as genetics, neuroimaging and pharmacology, 
have documented abnormalities in dopaminergic neurotransmission in individuals with mood disorders 
(8, 9). For example, neuroimaging studies have demonstrated alterations in dopamine receptor and 
transporter binding in individuals with MDD43-45. Conversely, the Val(158)Met polymorphism of the 
catechol-O-methyltransferase (COMT) gene, which affects dopamine catabolism and modulates 
prefrontal dopamine levels, has been associated with measures of anhedonia46,47. Overall, abnormalities 
in reward-related behaviors and dopaminergic transmission are well-established features of mood 
disorders phenomenology and neurobiology. 
1.3. Brain Insulin Signaling Pathway, Dopamine Signaling and Reward 
Dopamine signaling within and across brain circuits is in interplay with many systems relevant to 
reward, including the insulin signaling pathway34,48,49. Insulin acts via the insulin receptor (INSR). 
Activation of INSR initiates the recruitment of the insulin receptor substrate (IRS) family of proteins, 
which organize and mediate signaling cascades50,51. IRS1 and IRS2 are the most extensively studied 
substrates; they are expressed in the brain and have well-documented effects on insulin signaling and 
glucose homeostasis52-54. Insulin binding to INSRs activates several divergent signaling pathways, 
including the metabolic pathway (i.e. PI3K/Akt), which affects glucose and lipids homeostasis; and the 
mitogenic pathway (i.e. Ras/MAP kinase), which is implicated in the regulation of apoptosis and cell 
proliferation/differentiation.  
Multiple brain regions that are relevant to reward systems have relatively increased expression of 
INSRs (e.g., PFC, hippocampus, amygdala, substantia nigra)22,23. Specifically, midbrain dopamine 
neurons widely express INSRs49. Imaging studies have reported that, in healthy individuals, insulin 
modulates brain activity in the hypothalamus, hippocampus and prefrontal cortex34-36. Brain insulin 
signaling has traditionally been implicated in glucose and lipid metabolism, and eating behavior. 
However, replicated evidence, from multiple studies, has documented that insulin also has a role on 
emotional processing55-57 and reward processes, including, but not limited to, those pertaining feeding 
behaviors and energy expenditure58,59.  
An important way insulin affect reward processes is via interaction with dopaminergic signaling. 
Evidence indicated that insulin modulates multiple components of dopamine transmission, including 
synthesis and transport, receptors function and reuptake and degradation. For example, lower 
expression and function of tyrosine hydroxylase (TH), the rate-limiting enzyme in dopamine 
biosynthesis, have been reported in animal models of diabetes60,61.  In humans, insulin resistance was 
associated with less endogenous dopamine at D2/3 receptors in the ventral striatum and NAc, in both 
obese and non-obese participants62,63. A separate study documented that weight loss following bariatric 
surgery was associated with an increase in D2 receptor availability64.  
Termination of dopamine action, which is via reuptake from the synaptic cleft by the dopamine 
transporter (DAT), or by degradation by monoamine oxidases (MAOs) A/B and COMT, has also been 
shown to be affected by insulin. Studies with animal models of diabetes have reported lower 
availability and activity of DAT65,66 and lower activity of COMT67; whereas a murine model with a 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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brain specific knockout of the insulin receptor reported that decreased insulin function in the brain 
resulted in increased expression of MAO A/B in the striatum and NAc68. As a result, evidence indicates 
that insulin sensitivity modulates reward behavior in obese adults, wherein insulin resistance was 
associated with a stronger preference for immediately receiving a smaller, but certain, monetary reward 
over delaying the receipt of a larger, but less certain one (i.e. greater delay discounting)69.  
1.4. Insulin Signaling, Anhedonia and Major Depressive Disorder 
The epidemiological, phenomenological and biological associations between mood disorders and 
metabolic disturbances have been amply documented. The foregoing observations provide the rationale 
for hypothesizing that there is a neurobiological association between metabolic disorders (e.g. diabetes) 
and mood disorders. The devastating impact of mood and metabolic disorders on affected individuals 
underscores the importance of urgently understanding better the basis of this association. Anhedonia is 
a well-described symptom that similarly occurs in both disorders. The extant evidence of the 
association between insulin and dopamine signaling and the potential repercussions of disturbances in 
this system indicates that this is a promising target for clinical and neurobiological investigations. The 
interface between anhedonia and insulin represents a unique opportunity to integrate innovative and 
transdisciplinary lines of research in an investigative platform aiming at providing a more accurate and 
refined assessment of relevant mechanisms in the mood-metabolic disorders comorbidity.  
2. Preliminary Data  
Using the “Gene Expression in Postmortem DLPFC and Hippocampus from Schizophrenia and 
Mood Disorders” (dbGaP accession number phs000979.v1.p1) database, which contains microarray 
data from the post-mortem dlPFC (healthy controls [HC]: n = 209; patients: n = 321) and hippocampus 
(HC: n = 180; patients: n = 196), we conducted a hypothesis-driven analysis through the a priori 
selection of 12 dopamine- and 3 insulin-related genes (manuscript under review). Results showed that, 
in the dlPFC, after adjustment for relevant covariates, expressions of insulin receptors- (i.e. INSR, 
IRS1/2) and dopamine regulation-related genes (e.g. TH, DRD1-5, DAT) were influenced by body 
mass index (BMI), with significantly lower expression in high BMI patients with mood or psychotic 
disorders (Figure 1). In the hippocampus, we observed significantly lower expressions of these genes, 
which were not affected by BMI.   
Genes that were differentially expressed between groups were selected for mediation analyses. 
Diagnosis by BMI effects on expression of dopamine genes were fully mediated by expression of 
INSR. Analysis of conditional indirect effects showed interactions between INSR and BMI, indicating 
significantly stronger indirect effects at higher BMI values. In the hippocampus, we observed that 
expression of insulin receptor substrate 1 and 2 fully mediated the effects of diagnosis on expression of 
dopamine genes (Figure 2). All models were significant (e.g.  DRD1: R2 = 0.31, F6,385 = 29.519, p < 
0.001). These results suggest that the differential expression of dopamine-related molecules in the post-
mortem brain of individuals with mental disorders is related to altered expression of insulin signaling 
genes. We also observed that obesity has region-specific moderating effects on gene expression and co-
expression, supporting the hypothesis that metabolic systems are critical mediators of dopaminergic 
function and providing the rationale for further investigation. 
 
 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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Figure 2 – Unstandardized path coefficients for a mediation model in the hippocampus, adjusted 
for age, gender, race, ethanol and nicotine/cotinine. * p < 0.05; ** p < 0.001.  
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
Mean Expression z-score
Non-obese HC
Non-obese MI
Obese HC
Obese MI
Figure 1 – Mean standardized expression values of insulin and dopamine signaling genes in the 
dorsolateral prefrontal cortex, according to group (HC vs. MI) and obesity (BMI ≥ 30 kg/m2). 
HC: healthy controls; MI: mental illness; BMI: body mass index. 
 
 
 
 
 
 
 
 
 
 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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3. Design and Methodology 
Study population: We propose to recruit 50 adults between the ages of 18 to 50 years: 25 patients with 
DSM-5 defined MDD or BDI/II, in a depressive episode, recruited from the Mood Disorder 
Psychopharmacology Unit, University Health Network, and 25 age- and sex-matched healthy controls 
recruited through local advertisements in the community. 
Inclusion criteria (patients): 
1. Age 18-50 
2. DSM-5 defined MDD/BD and a total score ≥20 on the  Montgomery-Åsberg Depression Rating 
Scale (MADRS) and no history of dementia or intellectual disability 
3. A written, voluntary informed consent prior to study enrollment  
Exclusion criteria (patients): 
1. Use of insulin and/or oral hypoglycemiants, due to its confounding effects 
2. Diagnosis of possible or probable AD, MCI, or any other dementia 
3. History of neurological disorder, or evidence of neurologic or other physical illness that could 
produce cognitive deterioration 
4. Substance use disorder within 3 months before screening or a positive baseline toxicology screen 
5. Presence of clinically unstable general medical illness 
6. Pregnancy or breastfeeding 
7. MRI contraindications 
 
Inclusion criteria (healthy controls): 
1. Age 18-50 
2. A written, voluntary informed consent prior to study enrollment  
Exclusion criteria (healthy controls): 
1. Use of insulin and/or oral hypoglycemiants, due to its confounding effects 
2. Presence of any current or lifetime psychiatric or neurological conditions  
3. Substance use disorder within 3 months before screening or a positive baseline toxicology screen 
4. Presence of clinically unstable general medical illness 
5. Pregnancy or breastfeeding 
6. MRI contraindications 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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Study Procedures: Single-dose, randomized, controlled, double-blinded, cross-over study (50 
participants) 
Screening and Baseline Assessment: Patients and healthy controls will first meet, in-person or virtually, 
with a staff psychiatrist for a clinical consultation or a research team member, respectively. After 
obtaining consent and if inclusion criteria are met, a medical comorbidity questionnaire will be 
administered to screen for concurrent and lifetime medical conditions. Participant’s demographic 
characteristics and current medications, as well as lifetime psychotropic medications received will be 
recorded. We will also assess dietary intake with the Diet History Questionnaire III (DHQ III); 
smoking, by questioning number of cigarettes smoked per day, age when smoking started, and quitting 
date, if applicable, to calculate a smoking pack-year history; physical activity using the International 
Physical Activity Questionnaire (IPAQ); and alcohol and/or substance abuse. In addition, we will 
assess demographics, socioeconomic status, medical history, and family psychiatric history; childhood 
trauma history with the Childhood Trauma Questionnaire (CTQ) will also be assessed. Participants will 
also be asked to complete an MRI screening questionnaire to ensure that they have no 
contraindications. The following self-reported measures will be carried out: Perceived Deficits 
Questionnaire-Depression (PDQ-D), Sheehan Disability Scale (SDS), UCLA life Stress (Episodic), 
DeJong Gierveld Loneliness Scale, and Pittsburg Sleep Quality Index (PSQI) (Table 1). 
When in-person visits are possible, participants will complete a urine drug screen. Female participants 
will be asked to do blood work to confirm they are not pregnant.  
Physiological Assessment: Anthropometric (i.e. BMI, waist-hip ratio) and metabolic measurements (i.e. 
fasting glucose, fasting insulin, glycated hemoglobin, lipids and HOMA-IR) will be completed at each 
study visit (1-3). In addition, physical activity and energy expenditure will be measured using an 
accelerometer. Participants must wear the accelerometer at all times for one week and return it upon 
Visit 3 for data collection and analysis. Additionally, a heart rate monitor device will be connected to 
the accelerometer that will monitor heart rate variability over one day of the week that the subjects 
wear the accelerometer.   
Laboratory Assessment: 
Routine: the following laboratory tests will be completed: 
Triglycerides 
Total Cholesterol 
Insulin 
Glucose 
HbA1c 
C-Peptide 
IGF-1 
TSH 
Free T4 
Free T3 
C-Reactive Protein 
hCG 
Biomarkers: High sensitivity CRP and TNFα will be measured at both visits (hs-CRP only). 
Ultrasensitive ELISA will be used to measure high-sensitivity CRP and TNF-α, TNF-RI and TNF-R2 
(measured at both visits).  For exploratory mechanistic analysis, a 10-plex immunoassay of 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
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inflammatory cytokines will be measured at both visits (e.g. IFN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-
10, IL-12p70, IL-13). Blood will be collected after a 12 hour fast and centrifuged at 1000g for 15 min 
at 4oC; plasma will be stored at -80 oC. 
Behavioral assessment: These tasks are simple, user-friendly tools that provide an opportunity, when 
used in conjunction with the most widely used questionnaires, to gain novel insights on reward 
behaviors in mood disorders. 
a) The primary behavioral measurement will be effort-based decision-making, assessed using the 
Effort-Expenditure for Rewards Task (EEfRT)33, which will be done in a fMRI paradigm73, as 
described below during Visits 2 and 3.  
b) Assessments will include the validated anhedonia scale Snaith-Hamilton Pleasure Scale 
(SHPS), the mood questionnaires Montgomery-Åsberg Depression Rating Scale (MADRS) and 
Young Mania Rating Scale (YMRS) during each study visit, and the Bandit Task during the 
first visit.  
Neural Circuits Assessment: A promising tool to study the effect of insulin on CNS is intranasal 
insulin, which is delivered directly into the brain, without relevant effects on peripheral glucose76,77. A 
single dose of intranasal insulin has been shown to influence brain activation, increasing regional 
perfusion and functional connectivity between the hippocampus and the PFC78-80. Acute administration 
of intranasal in randomized, placebo-controlled, cross-over designs has been previously used to 
determine regional responses to insulin in the resting-state or during tasks78,80. 
After screening and baseline assessment, participants will receive a crossover treatment 
assignment of either insulin or diluent followed by an MRI scan, with a washout period of 1 week. 
Therefore, participants will receive a total of 2 MRI scans throughout the course of the study- one 
following the first treatment, and one following the second treatment. The subsample will be enriched 
for the presence of self-reported anhedonia, using a score of greater than 2 on the SHPS as a cut-off, 
which provides the best discrimination between “normal” and “abnormal” level of hedonic tone81. This 
subsample will also have equal representation of normal weight and obese participants. 
To proxy insulin activity within pre-selected brain regions, we will use a provocation paradigm, 
involving the administration of exogenous intranasal insulin, based on the published work of other 
research groups78-80. Activation of brain regions will be assessed during the resting state and task-based 
reward paradigm (i.e. EEfRT), following an intranasal administration of either 160 units of intranasal 
insulin or diluent (insulin and placebo will be prepared as nasal sprays), in a randomized, double-
blinded, cross-over design. Please refer to the pharmacy manual for randomization details. A 
hypothesis-driven region of interest approach will be used to investigate initially the striatum and the 
medial PFC (mPFC).  Willingness to make effort for rewards will be measured with the EEfRT33. 
Briefly, participants have to select between an easy and a hard task. Both tasks involve pressing a key 
for a predetermined amount of time. The hard task offers more money (variable amounts), but is harder 
and takes twice as long. Participants make their selection knowingly under different win probabilities 
(i.e. they might not win money even if they are successful if the win probabilities are low). This task 
will measure proportions of hard-task choices with varying probabilities of reward and reward 
magnitudes. To provide stable estimations, the fMRI task will be conducted in three runs73. 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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Table 1 
Assessment 
Baseline (V1) 
First Spray (V2) 
Second Spray (V3) 
General Information  
Demographics 
Questionnaire 
  
 
 
Medical Comorbidity 
Questionnaire 
  
 
 
Family Psychiatric 
History 
Questionnaire 
  
 
 
SES Questionnaire 
  
 
 
MRI Questionnaire 
  
  
  
Anthropometric Measures 
Height (ft) 
  
 
 
Weight (kg) 
  
  
  
Blood Pressure 
(mmHg) 
  
  
  
Heart Rate (bpm) 
  
  
  
Waist/hip 
Circumference (cm) 
  
 
 
Physical Activity/ 
Energy Expenditure/ 
7-Day Accelerometer 
Wear Time Log 
  
  
  
Laboratory Assessment  
Triglycerides 
  
  
  
Total Cholesterol 
  
  
  
Insulin 
  
  
  
Glucose 
  
  
  
HbA1c 
  
  
  
C-Peptide 
  
  
  
IGF-1 
  
  
  
TSH 
  
  
  
Free T4 
  
  
  
Free T3 
  
  
  
C-Reactive Protein 
  
  
  
hCG 
  
 
 
Imaging 
fMRI-EEfRT 
 
  
  
Dimensional Measures 
Clinician Administered 
YMRS 
  
  
  
MADRS 
  
  
  
Bandit Task 
  
 
 
Self-Report 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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SHPS 
  
  
  
PDQ-D 
  
 
 
SDS 
  
 
 
UCLA Life Stress 
Interview (Episodic) 
  
 
 
CTQ 
  
 
 
DeJong Gierveld 
Loneliness Scale 
  
 
 
Diet History 
Questionnaire (III) 
  
 
 
IPAQ 
  
 
 
PSQI 
  
 
 
Neurocognitive Tasks 
DSST 
  
  
  
RAVLT 
  
  
  
TMT A/B 
  
  
  
 
 
 
 
 
 
 
 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
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Imaging procedures will be started with a safety monitoring for glucose and cardiovascular vital 
signs. An insulin/placebo spray will be administered intranasally and, within 30 min, fMRI 
measurement will be performed. Venous blood samples, for determination of plasma glucose and 
insulin concentrations, will be obtained at the time of the insulin/placebo spray administration and 
immediately after the scan. The 2 scans for each individuals will be acquired on the same scanner. 
Subjects will be scanned using a 3.0-Tesla Signa HDx scanner with an 8-channel phased-array receiver 
coil (GE Healthcare, Milwaukee, Wisconsin) consisting of a structural and functional neuroimaging, 
comprising: 
i. 
Whole-brain 3-D T1-weighted Inversion-Recovery prepared Fast Spoiled Gradient-Echo (IR-
FSPGR) anatomical scan with the following parameters: (TI/TR/TE = 450/8/3 ms, matrix size 256 
× 256, field of view 22 × 22 cm, slice thickness = 1 mm, and flip angle = 15°) 
ii. 
Whole-brain, T2*-weighted BOLD echo planar imaging (EPI) during awake resting state with the 
following parameters: (TR/TE = 2000/30 ms, 3.5 x 3.5 x 3.5 mm voxel size, field of view 24x24 
cm, 39 slices, slice thickness 3.5 mm, matrix size 64x64, number of frames = 405, flip angle = 
70°)),  
iii. 
Three runs of whole-brain, T2*-weighted BOLD EPI series during task-based reward paradigm 
with the same parameters as in ii. 
 
4. Study Treatment 
4.1 Treatments Administered 
Description of Study Medications  
The Investigational Pharmacy Services  (IPS, also known as the clinical trials pharmacy) at the 
University Health Network’s (UHN’s) Toronto Western Hospital (TWH) will be responsible for all 
study related preparation, dispensing, and documentation.  IPS will be responsible for the following 
study preparation procedures.  All active treatment and placebo will be prepared by an IV certified 
pharmacy technician, under aseptic conditions, in a sterile room, i.e., centralized intravenous additive 
services (CIVA) area, and verified by a pharmacist. 
 
Dose preparation for the active and placebo nasal sprays follow the same procedure.  This will be 
conducted upon the receipt of an order from the blinded investigator with regard to the number of nasal 
spray bottles of Humulin® R  insulin or diluent to be prepared the pharmacy. 
 
Each product, whether intranasal Humulin® R  insulin or diluent, will be prepared under the laminar 
flow hood one at a time.  Using aseptic technique, the protective cap is removed from the vial of 
Humulin® R insulin or diluent (10 mL/vial, manufactured by Eli Lilly) and the rubber stopper is 
swabbed with an alcohol swab and allowed to dry.  Using an appropriate sterile Luer Lock syringe with 
an appropriately sized needle attached with the bevel of the needle facing up at a 45 degree angle, the 
Humulin® R insulin or diluent vial is punctured and 5 mL of insulin or diluent is removed and 
transferred to a metered dose nasal spray bottle (PharmaSystems, Inc.) provided by the study 
coordinator overseeing the project herein. The nasal spray bottle is then capped accordingly.  In 
summary, the intranasal solutions are prepared as follows: 
 
 Intranasal Insulin Arm:  IPS will obtain commercial supplies of Humulin® R insulin (10 
mL/vial, manufactured by Eli Lilly) and aseptically transfer a 5 mL sample into a metered dose 
nasal spray bottle (PharmaSystems Inc.).  
 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
Version 14: 29-June-2021 
 
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 Intranasal Placebo Arm: IPS will obtain commercial supplies of Humulin® R insulin’s diluent 
(10 mL/vial, manufactured by Eli Lilly) and aseptically transfer a 5 mL sample into a metered 
dose nasal spray bottle (PharmaSystems Inc.).  
 
This procedure is repeated until the required number of nasal spray bottles has been prepared.  Once 
completed, the nasal spray bottles are wiped with 70% isopropyl alcohol soaked gauge and removed 
from the laminar flow hood and appropriately labeled. 
 
Both active and placebo nasal spray bottles are kept separate from each other and a worksheet will be 
completed to document information, including date of preparation, batch #, expiry date, drug name and 
strength.  The IV certified pharmacy technician who has prepared the dose is responsible for 
completing the documentation and will be affixing the labels identifying what was prepared.  The 
labels, at a minimum, will contain information regarding the lot #, strength, date of manufacture, expiry 
date, and storage conditions.  All of this will be verified by a pharmacist. 
 
Labeling 
All labels will contain product name, volume, protocol number, investigational drug warning, dosage 
instructions, storage conditions, lot number, expiration date, and the pharmacy name. 
Storage 
Please refer to the pharmacy manual for information on storage.  
Study Medication Administration 
This will be a single-dose, randomized, double-blinded, cross-over study involving intranasal 
insulin/placebo solution.  
Designated pharmacy staff will dispense study medication, in a double-blind manner, according to the 
randomization code specific to each subject and dosing period.  
Details regarding intranasal insulin and diluent can be referred to in the pharmacy manual. 
The investigator and/or designee will instruct the study participant on how the intranasal 
insulin/placebo spray should be administered.  Each study participant is to receive a single dose of 
Humulin R 160 U / placebo. 
 Given: 
o The nasal spray bottles provide a deliverable volume of 0.1 mL/spray. 
o Humulin R insulin will be sourced as 100 units/mL in a vials of 10 mL from Eli 
Lilly. 
o Diluent will be sourced as 10 mL/vial from Eli Lilly. 
 
  Each spray will offer: 
o 0.1 mL (i.e., 10 units) of Humulin R insulin 
o 0.1 mL of diluent (to serve as placebo) 
 
 To obtain a dose Humulin R 160 U / placebo 
o 16 sprays (0.1 mL/spray) are to be given per dose 

 
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Project Title: Anhedonia and the insulin pathway: a mechanistic nexus for the mood and metabolic disorders comorbidity 
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o This works out to 16 sprays split between each nostril such that each nostril 
receives 8 sprays. 
o The sprays will be administered between alternating nostrils. 
Given this is a crossover study, the study participants will receive a total of two doses in this study. The 
time between 2 doses is one week.  
4.2 Accountability of Study Supplies  
Please refer to the pharmacy manual for information on accountability of study supplies.  
4.3 Disposition of Used/Unused Product 
Please refer to the pharmacy manual for information on the disposition of used/unused product.  
5.  Methods of Assigning Subjects to Treatment Groups  
Please refer to the pharmacy manual for information on the methods of assigning subjects to treatment 
groups (i.e. randomization, and blinking/masking). 
6. Analytic Plan, Power Analysis and Approach to Potential Challenges 
Initial data analyses will inspect socio-demographic and clinical group differences as well as 
correlations between clinical and biological variables and specified behavioral measures. Clinical or 
demographic variables demonstrating a correlation with both biological and behavioral measures, will 
be assessed as potential confounders82. The EEfRT behavioral data will be analyzed using generalized 
estimating equation (GEE) models, according to previous studies30,33. For the assessment of 
associations between the remaining behavioral measurements and biometric data, we will use 
generalized linear models, due to its greater flexibility and ability to analyze data with non-normal 
distributions. Group (mood disorders vs. non-psychiatric) effects will be analyzed, with age, gender, 
and other relevant covariates included in the models. Special considerations will be given to smoking 
and use psychotropic medications, given its potential effects of both reward processes and insulin 
signaling.  
Mediation and moderation models will be assessed using regression-based, bias-corrected bootstrap 
tests83. The main objective is to test whether there is a mediated effect of X (i.e. mood disorders) on the 
outcome Y (i.e. anhedonia and reward behavior) through M (i.e. insulin signaling and dopamine 
metabolism). If appropriate, moderated mediation models (conditional process analysis) will be used to 
test whether the mediation effect was contingent on a moderating variable W (e.g. obesity, 
medications). This method uses bootstrapping to determine bias-corrected (asymmetric) 95% 
confidence intervals for the indirect effects84. Bootstrapping methods have been recently advocated, as 
they are based on random sampling of the data and do not make assumptions about the shape of the 
sampling distribution; they are also more powerful and allow for the construction of more accurate 
confidence intervals, relative to normal theory methods83.  
For the imaging analysis, statistical parametric mapping (SPM8, Wellcome Department of 
Cognitive Neurology, London, U.K., www.fil.ion.ucl.ac.uk/spm) will be used to preprocess the raw 
fMRI data. A hypothesis-driven region of interest approach will be used to investigate initially the 
striatum and mPFC. For the resting-state data, BOLD signal in these regions will be compared between 
conditions (i.e. insulin and placebo) for each subject using GEE. For the task-based data, mean percent 
BOLD signal change in these regions under varying reward and probability conditions will be 
extracted, and we will compute a set of contrasts testing the main effects of reward magnitude, reward 

 
Rodrigo B. Mansur 
 
 
 
 
 
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probability, and the interaction for each subject73. These first-level individual contrast maps will be fed 
into a second-level group (i.e. mood disorders vs. controls) and condition analysis, which will also use 
GEE. Association between behavioral measurements, biometric data and neuroimaging measurements 
will be assessed with generalized linear models. The false discovery rate (FDR) method will be used to 
correct for multiple comparisons and significance will be taken at a FDR-corrected threshold of p < 
0.0586. 
Power Analysis: The primary hypothesis of this study is that anhedonic symptoms in individuals with 
mood disorders will be mediated by abnormalities in insulin signaling; therefore, the power analysis is 
based on a bias-corrected bootstrap test of mediation. Results from our preliminary data indicated that 
the path coefficients were mostly of medium effect sizes (e.g. β ≈ 0.25-0.35); empirical analysis 
indicated that in this condition a sample sizes of 116 is necessary to achieve 80% power85. To account 
for the possibility of subject attrition and/or inadequate measurements, we will set an initial enrollment 
goal of 150 subjects. 
Potential Challenges and Ways to Overcome Them: The primary challenge in this study is that of 
recruiting and retaining 150 participants over a 3-year period. Given the experience and volume of the 
mood disorders clinics involved in this study, we believe that this goal is attainable. There are two 
potential limitations in our sample composition proposal. First, it is expected that the majority of 
participants recruited in tertiary mood disorders clinics will report clinically significant anhedonic 
symptoms. Nonetheless, it is possible that some of the subconstructs analyzed will not display 
satisfactory psychometric properties for contrast/comparisons. Second, we propose to pre-stratify our 
sample based on overweight/obesity. There is a well-documented association between adiposity and 
insulin sensitivity; though these are not perfectly collinear constructs. There are no, however, validated, 
publicly available, normative data of anhedonic symptoms, whereas gold-standard evaluations of 
insulin sensitivity are invasive and costly (e.g. hyperinsulinemic euglycemic clamp); therefore 
approximations are initially necessary. We propose to conduct a preliminary analyses after one third of 
the sample (n=50) is recruited and reevaluate the sample selection procedures. 
A key challenge for the interpretation of results will be how to account for the role of potential 
confounding factors. These factors include, but are not limited to, psychotropic medications, smoking, 
socio-demographic characteristics, dietary and lifestyle factors. We opted for a “real-life” naturalistic 
treatment-seeking sample, as we seek to recruit a sample that is representative of other clinical samples. 
Moreover, ethical considerations preclude us from withdrawing or deferring initiation of medications. 
Therefore, we propose to systematically measure these confounding factors and use it as control and/or 
sub-stratification variables, as appropriate. 
ADVERSE EVENTS 
Definitions 
Adverse event 
An adverse event is the development of an undesirable medical condition or the deterioration of a 
pre-existing medical condition following or during exposure to a pharmaceutical product, whether or 
not considered causally related to the product.  An undesirable medical condition can be symptoms 
(e.g., nausea, chest pain), signs (e.g., tachycardia, enlarged liver) or the abnormal results of an 
investigation (e.g., laboratory findings, electrocardiogram).  In clinical studies, an AE can include an 
undesirable medical condition occurring at any time, including run-in or washout periods, even if no 
study treatment has been administered. 

 
Rodrigo B. Mansur 
 
 
 
 
 
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Serious adverse event 
A serious adverse event is an AE occurring during any study phase (i.e., run-in, treatment, washout, 
follow-up), and at any dose of the investigational product, comparator or placebo, that fulfils one or 
more of the following criteria: 
• 
results in death 
• 
is immediately life-threatening 
• 
requires in-patient hospitalization or prolongation of existing hospitalization 
• 
results in persistent or significant disability or incapacity 
• 
is a congenital abnormality or birth defect 
• 
is an important medical event that may jeopardize the patient or may require medical 
intervention to prevent one of the outcomes listed above. 
The causality of SAEs (i.e., their relationship to study treatment) will be assessed by the 
investigator(s).  Note that SAEs that could be associated with any study procedure should also be 
reported. For such events the casual relationship is implied as "yes". 
Recording of adverse events 
AEs will be collected during each visit. At each visit, subjects will be asked if they have had any 
health problems since the previous visit.  All AEs will be recorded appropriately, whether or not 
considered related to the investigational product. This will include AEs spontaneously reported by the 
patient and/or observed by the staff as well as AEs reported in response to a direct question e.g. “Have 
you had any health problems since your last visit?”  
For each AE, the following parameters be described: 
• 
start and stop date 
• 
action taken with regards to investigational product 
• 
outcome 
• 
if the AE caused the patient to discontinue 
• 
a statement if the AE fulfils the criteria for a SAE or not 
• 
the investigator’s assessment of the causal relationship between the event and the 
investigational product 
• 
intensity of the AE 
o mild (awareness of sign or symptom, but easily tolerated) 
o moderate (discomfort sufficient to cause interference with normal activities) 
o severe (incapacitating, with inability to perform normal activities) 

 
Rodrigo B. Mansur 
 
 
 
 
 
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It is important to distinguish between serious and severe AEs.  Severity is a measure of intensity 
whereas seriousness is defined by the criteria in Section.  An AE of severe intensity need not 
necessarily be considered serious.  For example, nausea that persists for several hours may be 
considered severe nausea, but not an SAE.  On the other hand, a stroke that results in only a limited 
degree of disability may be considered a mild stroke but would be an SAE.  
Symptoms associated with overdose should be reported as AEs. For further information regarding 
overdose, see section. 
Pregnancy in itself is not regarded as an AE unless there is a suspicion that an investigational 
product may have interfered with the effectiveness of a contraceptive medication.  
Follow-up of adverse events should be based upon the clinical judgement of the investigator. 
Reporting of serious adverse events 
Reporting of SAEs to regulatory authorities will be done by the investigator in accordance with 
local regulations. A copy of the report will also be sent to the manufacturer of the investigational 
product. 
7. Anticipated Timeline 
Study start-up is planned immediately after REB approval. The last six months will focus on data 
management, image processing and analyses. This will allow 27 months of subject recruitment and 
study execution, with a target of an average of 2-3 participants per site per month.  
8. Personnel and Facilities 
Dr. Rodrigo B. Mansur (co-principal investigator [PI]) is an Assistant Professor of Psychiatry at the 
University of Toronto and a Clinician-Investigator at the Mood Disorders Psychopharmacology Unit 
(MDPU) at the University Health Network.  His role on the project is to oversee all of the procedures 
and he will be involved in the design, implementation, and interpretation of all aspects of the study. Dr. 
Roger S. McIntyre is a Professor of Psychiatry and Pharmacology at the University of Toronto and is 
Head of MDPU at the University Health Network; he will facilitate the design and implementation of 
the study and provide clinical and statistical expertise. As clinicians, they will also be involved in 
subject recruitment and screening. Dr. Jian Chen is the Director of Proteomic Sciences, Indoc 
Research, and an Assistant Professor at the Department of Pathology and Molecular Medicine, Queen’s 
University. He will be responsible for the proteomic/genomics analysis.  
Other Personnel: We will employ part-time research coordinators who will oversee all endeavors 
related to startup and completion of the study. 
Infrastructure and Facilities: 
The study will be conducted at the University Health Network (UHN), which is among the largest 
Health Science Centers in Canada. The investigators will work with a research coordinator, clinicians, 
and scientists on this project. Investigators all have access to full-service clinical laboratories at UHN. 
Neuroimaging will be acquired at the Toronto Neuroimaging Facility at the University of Toronto, 
which has a 3T GE Signa HDx MRI scanners equipped with an 8-channel phased-array head coil.   
9. Innovation, Impact and Future Research Plans 

 
Rodrigo B. Mansur 
 
 
 
 
 
Research Proposal 
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The proposed study is the first to integrate an innovative theoretical framework with unique 
methodological components, which are, nonetheless, extensively supported by the current literature. 
The study of obesity and insulin sensitivity in mood disorders has often been a secondary concern; this 
study is among the first to propose approaching metabolic factors as integral to mood disorders 
pathophysiology. Our proposed methodology includes multiple levels of assessment, using validated 
tools and techniques, and has the potential to provide a more comprehensive view of insulin’s role. We 
are also proposing a systematic and detailed evaluation of environmental factors, which have a key role 
on the mood-metabolic disorders comorbidity.  
 We expect that results from this study will advance the knowledge on the mechanistic basis of 
anhedonia, which is a critical step for the development of targeted and more effective therapeutic 
options for individuals with MDD and BD. In addition, by highlighting the role of insulin signaling in 
the pathophysiology of mood disorders, we hope to refine the conceptual framework on the association 
between mood and metabolic disorders. Understanding better the impact of insulin signaling 
disturbances has tremendous potential to reframe how researchers and clinicians conceptualize mood 
disorders. Ultimately, the aim is to support the development of empirically supported, integrated 
therapies, such as medications and/or behavioral modifications (e.g. exercise programs) that target both 
mood and metabolic manifestations. These are urgently necessary to address adequately the 
multifaceted needs of affected individuals and families. 
Future research plans consists of eventually establishing a longitudinal cohort, focused on the 
interface of metabolic and mood disorders. There is a clear need for longitudinal studies in this area; it 
is the only design that allows for the exploration of developmental trajectories and for definitive 
conclusions on causality. Moreover, our research team has ongoing collaborations with international 
groups, including Brazil, China, Denmark and South Korea, which have generated published articles 
and collaborative projects; we also intend to further develop these collaborations and explore 
opportunities for replication studies and cross-cultural comparisons. Finally, our research group has 
extensive experience with clinical trials, especially with metabolic/inflammatory treatments, such as 
the immunomodulatory infliximab and the antidiabetic medication liraglutide. We expect that this 
study will provide opportunities for translational studies, specifically by identifying novel 
pharmacological targets and/or subgroups of individuals (e.g. obese patients with disturbances in 
reward valuation) more likely to respond to novel therapies. 
 
 
 
 
 
 
 
 
 
 

 
Rodrigo B. Mansur 
 
 
 
 
 
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