Impact of Inflammation on Reward Circuits, Motivational Deficits and Negative Symptoms in Schizophrenia
Phase: NA
Conditions: Schizophrenia
Sponsor: Emory University

 
 
 
 
 
 
 
 
Impact of Inflammation on Reward Circuits, Motivational Deficits and 
Negative Symptoms in Schizophrenia 
NCT03818516 
 
Date:01/31/2022 
IRB00094972 

1. Impact of Inflammation on Reward Circuits, Motivational Deficits and Negative Symptoms in 
Schizophrenia
, MD (Principal Investigator)
, MD
, PhD
, PhD
, MD
The amended protocol includes:
Replacing the M.I.N.I. 6.0 with the updated M.I.N.I. 7.0 version for DSM-V.
Removing optional cortisol collection.
Version Date: 1-31-2022
2. Precis/Abstract
Negative symptoms of schizophrenia, including motivational deficits, are some of the most debilitating 
aspects of the disorder, being both difficult to treat and representing one of the most significant barriers to 
functional recovery. Regarding potential mechanisms of these deficits, individuals with schizophrenia reliably 
show decreased activation of the ventral striatum in reward-based neuroimaging tasks. One pathophysiologic 
pathway that may contribute to these alterations in reward circuitry in schizophrenia is inflammation. Previous 
work has demonstrated that inflammatory stimuli decrease neural activity in the ventral striatum and decrease 
connectivity in reward-relevant neural circuitry. Based on the previous findings that patients with schizophrenia 
reliably exhibit elevated concentrations of inflammatory markers and that inflammatory cytokines are related to 
negative symptoms including decreased motivation, I hypothesize that increased inflammation in schizophrenia 
contributes to negative symptoms by disrupting neural activity in reward circuits leading to motivational deficits. 
To test this hypothesis, I propose the following Specific Aims: (1) To determine the impact of inflammation on 
reward circuitry in patients with schizophrenia using both task-based and resting state functional magnetic 
resonance imaging. (2) To determine the impact of inflammation on objective and clinical measures of 
motivation and negative symptoms. (3) To explore whether the impact of inflammation on reward circuitry 
mediates the effects of inflammation on objective measures of reward processing and negative symptoms. 
Taken together, this work will inform future studies of novel therapeutic strategies to treat negative symptoms 
in patients with schizophrenia.
3. Introduction and Background
Schizophrenia is a severe mental illness that affects 1% of the population, but accounts for over $60 
billion in costs to the national healthcare system.1,2 Up to 30% of individuals with schizophrenia are considered 
“treatment-resistant,” adding to even greater morbidity and socioeconomic burden.3,4 Individuals with 
schizophrenia suffer from a constellation of symptoms including delusions, hallucinations, trouble expressing 
their thoughts and a lack of motivation. The disorder is a major public health concern, and many people with 
schizophrenia suffer chronic debilitating symptoms,5,6 have high rates of unemployment and homelessness,7,8 
and have a significantly reduced life expectancy (~20 years less than the general population).9 
The behavioral symptoms of schizophrenia are heterogeneous in nature and have traditionally been 
categorized as positive and negative symptoms. Positive symptoms reflect the constellation of symptoms that 
are not usually present and include hallucinations, delusions, and disorganized thinking and speech. Negative 
symptoms are those symptoms that characterize absent or diminished behavior and include decreased 
motivation, social withdrawal, as well as poverty of speech, decreased emotional reactivity and psychomotor 
retardation. Importantly, negative symptoms have consistently been identified as those features of the disorder 
that are most predictive of functional impairment and poor outcome.10-13 Moreover, antipsychotic medications 
are effective in treating positive symptoms, but are less effective in treating negative symptoms.14-16 Thus, our 
current armamentarium of medications to treat schizophrenia fails to address some of the most debilitating 
symptoms of the illness that have been most strongly related to measures of daily function and recovery.
Impaired reward processing and motivational deficits are core components of negative symptoms in 

schizophrenia that are most relevant for poor quality of life and impaired functional outcomes.17-21 For example, 
patients with schizophrenia may not expend the effort to seek out potentially or previously rewarding activities 
such as work and social interaction. These deficits can be further delineated into several domains, including 
decreased reward anticipation, impaired reinforcement learning, reward prediction errors, and reduced effort 
cost computation,22 all of which involve subcortical brain regions including the basal ganglia and more 
specifically the ventral striatum. Reduced neural responses in the ventral striatum have consistently been 
implicated in studies of patients with schizophrenia, including neuroimaging studies of reward anticipation,23-26 
reinforcement learning,27,28 and positive prediction errors.29-32 Importantly, decreased activation in the ventral 
striatum during motivation tasks has been associated with severity of negative symptoms in a number of 
studies.24,26,29,33,34 Patients with schizophrenia also show decreased reward processing as measured by 
objective assessments of effort expenditure for reward and reinforcement learning,35-46 such as the Effort 
Expenditure for Reward Task (EEfRT), which is known to involve ventral striatal circuits.23,24,26,47-49 Of note, 
decreased activity in the ventral striatum on a monetary reward based neuroimaging task has been directly 
related to both objective and clinical assessments of decreased motivation in patients with schizophrenia.46 In 
several studies, performance on these objective motivational tasks has also been consistently related to 
severity of negative symptoms,35,36,40,41,44-46,50 suggesting that deficits in reward processing are a core 
component of negative symptoms in schizophrenia.
One pathophysiologic pathway that may contribute to negative symptoms and decreased motivation in 
schizophrenia is inflammation. Increased inflammation has been reliably linked to deficits in reward processing 
and decreased motivation via effects of inflammatory cytokines on regions of the basal ganglia, including the 
ventral striatum.51 Inflammation has been shown to alter neural activity in ventral striatal regions as assessed 
by a variety of neuroimaging strategies following administration of several inflammatory stimuli including 
interferon (IFN)-alpha, typhoid vaccination and endotoxin.51-54 In addition, increased inflammation has been 
shown to mediate deficits in objective assessments of motivation as reflected by effort expenditure in 
laboratory animals including non-human primates.55-58 Recent work in the Miller lab has demonstrated that one 
potential mechanism by which inflammation may lead to alterations in reward processing and motivation is 
through effects on connectivity within brain reward circuitry. Felger and colleagues showed that using 
functional magnetic resonance imaging (fMRI), increased inflammation (as measured by peripheral blood C-
reactive protein; CRP) was associated with decreased functional connectivity between the ventral striatum and 
ventromedial prefrontal cortex (vmPFC) in patients with major depressive disorder.59 Decreased connectivity 
between these regions was, in turn, correlated with decreased motivation as assessed by the Snaith-Hamilton 
Pleasure Scale (SHAPS).60 Decreased connectivity in this study was also linked with other inflammatory 
markers including interleukin (IL)-6 and IL-1 receptor antagonist (IL-1RA). Taken together, these findings 
suggest that increased inflammation in schizophrenia may disrupt neural activity in reward circuits, leading to 
motivational deficits and negative symptoms in the disorder. This hypothesis will be tested in Specific Aims 1-3.
Of relevance to the potential role of inflammation in negative symptoms in schizophrenia, in a meta-
analytic study, it was recently reported that patients with schizophrenia reproducibly exhibit increased markers 
of inflammation in both acute and chronic phases of the illness.61 Preliminary data collected from the patient 
sample this proposed research will recruit from demonstrates a relationship between inflammatory cytokines 
and negative symptoms. In a study of 10 patients from Grady Memorial Hospital, there was a positive 
relationship between IL-1beta and the global rating of avolition on the Scale for the Assessment of Negative 
Symptoms (SANS), which most closely resembles assessments of reward processing deficits (r = 0.751, p = 
0.012).35 IL-1beta was also correlated with the avolition-impersistence at work or school (r = 0.644, p = 
0.045) and the attention-social inattentiveness (r = 0.665, p =0.036) items of the SANS, in addition to the 
passive/apathetic social withdrawal (r = 0.657, p = 0.039) and the disturbance of volition (r = 0.686, p = 
0.029) items on the Positive and Negative Symptom Scale (PANSS). Furthermore, the anti-inflammatory 
cytokine IL-10 was negatively correlated with the emotional withdrawal (r = -0.638, p = 0.047) and the 
passive/apathetic social withdrawal (r = -0.655, p = 0.04) items of the PANSS as well as the negative symptom 
total score of the PANSS (r = -0.792, p = 0.006).113 Taken together, these preliminary data from patients 
with schizophrenia indicate that inflammatory cytokines show the predicted relationship with negative 
symptoms such as avolition. Of note, patients reflected a range of negative symptom severity with the 
total score on the SANS ranging from 12 to 86 (M=46.2, sd=27.1).  
These findings are consistent with new data that inflammation and the innate immune response may 
play a fundamental role in the development and progression of schizophrenia.62 There is also a growing 
literature showing that increased inflammatory cytokines may be linked to negative symptoms in patients with 
schizophrenia.63-69 It should also be noted that inflammation has long been thought to play a role in the 

pathogenesis of schizophrenia, as early epidemiological studies demonstrated that exposure to infections in 
utero as well as in early childhood increased the risk for schizophrenia later in adulthood.70-72 Autoimmune 
conditions have also been shown to be increased in children who later develop schizophrenia,73 adults with the 
disorder,74 as well as first-degree relative of patients with schizophrenia.75 Moreover, the major 
histocompatibility complex (MHC) region on chromosome 6, in addition to other immune-related genes, have 
consistently been shown to be associated with schizophrenia in genome wide association studies.76-79 
Neuroimaging (positron emission tomography (PET)) studies in patients with schizophrenia have also 
demonstrated increased binding of a ligand to translocator protein (TSPO) in individuals considered to: be 
ultra-high risk for psychosis,80 have recent onset of the disorder,81 be in acute exacerbations of the illness,82 
and exhibit persistent symptoms.83 TSPO is expressed by activated microglia cells, the immune cells in the 
brain that respond to injury or inflammation by releasing a variety of inflammatory cytokines. Finally, treatment 
studies using anti-inflammatory agents have been tested in schizophrenia with variable success.84
The proposed research represents the first study to address the potential role of the immune system 
and inflammation in negative symptoms of schizophrenia, specifically by testing the hypothesis that 
inflammation affects fundamental reward circuitry in the ventral striatum leading to deficits in motivation and 
reward processing. Negative symptoms are highly resistant to treatment and have a major impact on functional 
outcomes. Therefore, understanding novel mechanisms by which negative symptoms occur will allow the 
development of innovative therapeutic strategies to improve quality of life and treatment outcomes in patients 
with this disorder. Moreover, given that inflammation can be measured in peripheral blood, the opportunity 
exists to target immune-based therapies to specific subpopulations of schizophrenia patients, thereby allowing 
a more personalized approach, supporting precision 
medicine. Indeed, the mixed results of previous studies 
that have used anti-inflammatory therapies in 
schizophrenia may be a result of not targeting the 
appropriate patients or the best outcome measures. There 
are currently no effective treatments for negative 
symptoms or motivational deficits in schizophrenia, which 
as noted above represents a significant obstacle to 
achieving functional recovery, and as such, the discovery 
of novel therapies are of paramount importance.85,86
Working Model
Based on these data, the scientific premise and driving hypothesis of the proposed research is that 
inflammation decreases activation of ventral striatal reward circuits, leading to decreased objective measures 
of motivation and ultimately negative symptoms in schizophrenia (see Figure 1 for working model).
As an amendment to the original protocol, this research also includes computational analysis of language. 
Recent developments in the automated analyses of language have shown promising findings in identifying 
computational measures of language to characterize thought disorder in schizophrenia. However, most of the 
research to date has focused on measure of incoherence and little attention has been paid to other central 
features of language in schizophrenia such as poverty of content. This additional research protocol aims to 
measure “semantic density” through the use of machine learning and Natural Language Processing. It also 
aims to detect latent semantic content reflective of the psychopathology of thought disorder in schizophrenia. 
The resulting linguistic findings can be potentially analyzed in conjunction with other biomarkers and future 
findings of the original study.
4. Objectives 
Objective 1. Determine the impact of inflammation on reward processing in patients with schizophrenia 
using functional magnetic resonance imaging (fMRI).
Hypothesis 1: Increased peripheral blood markers of inflammation will be associated with decreased
activation of reward-related ventral striatal regions and decreased connectivity between the ventral striatum 
and medial prefrontal cortex using whole brain analysis.
Figure 1: Working Model of Research Proposal

Dependent variables:
Immune Markers:
Peripheral inflammatory markers: plasma CRP, IFN-alpha, IL-6, sIL-6R, IL-10, TNF-
alpha, sTNFR 1 and 2, IL-1 beta, IL-1ra, sIL-2R, and MCP-1 
Neuroimaging Tasks: Degree of functional connectivity between the striatum and other brain regions on resting 
state scan (Z scores); performance on fMRI tasks (see below) 
Objective 2. Determine the impact of inflammation on objective and clinical measures of motivation 
and negative symptoms in patients with schizophrenia.
 
Hypothesis 2: Increased inflammation will be associated with increased impairment in objective and clinical 
measures of motivation and negative symptoms. 
Dependent variables:
Immune Markers:
Peripheral inflammatory markers: plasma CRP, IFN-alpha, IL-6, sIL-6R, IL-10, TNF-
alpha, sTNFR 1 and 2, IL-1 beta, IL-1ra, sIL-2R, and MCP-1 
Behavior: 
Scores on the: Positive and Negative Symptom Scale (PANSS); Brief Negative 
Symptom Scale (BNSS); Snaith Hamilton Pleasure Scale (SHAPS); Inventory of 
Depressive Symptomatology (IDS-SR), Childhood Trauma Questionnaire (CTQ); 
Motivation and Pleasure Scale (MAPS-SR) 
Neuropsychology:
Performance on the Effort Expenditure for Rewards Task (EEfRT), and neurocognitive
tasks (see below)
Objective 3. Explore the interrelationship among inflammation, altered reward processing as measured 
by fMRI, and objective and clinical measures of motivation and negative symptoms in patients with 
schizophrenia. 
Hypothesis 3: Decreased neural activation in reward-related regions will mediate the relationship between 
inflammatory markers, impaired motivation and negative symptoms.  
Immune Markers:
Peripheral inflammatory markers: plasma CRP, IFN-alpha, IL-6, sIL-6R, IL-10, TNF-
alpha, sTNFR 1 and 2, IL-1 beta, IL-1ra, sIL-2R, and MCP-1 
Neuroimaging Tasks: resting state scan; fMRI tasks
Behavior: 
Positive and Negative Symptom Scale (PANSS); Brief Negative Symptom Scale 
(BNSS); Snaith Hamilton Pleasure Scale (SHAPS); Inventory of Depressive 
Symptomatology (IDS-SR); Calgary Depression Scale for Schizophrenia (CDSS), 
Childhood Trauma Questionnaire (CTQ); Motivation and Pleasure Scale (MAPS-SR)
Neuropsychology:
Effort Expenditure for Rewards Task (EEfRT), and neurocognitive tasks (see below)
5. Study Design and Methods
Figure 2: Overview of Proposed Study Visits
Figure 2 gives an overview of the proposed study visits. 
Study Overview: The proposed experiments will 
evaluate the impact of inflammation on reward 
processing, motivation, and negative symptoms in 100 
male and female patients with schizophrenia or 
schizoaffective disorder. The Screening Visit will take 
place virtually or at one of the following sites; Grady 
Behavioral Health Clinic (Grady BHC), Emory University 
Hospital Georgia Clinical & Translational Science Alliance 
Clinical Research Center (EUH  GCRC), Woodruff 
Memorial Research Building (WMRB-PI Office Space) or 
at the Facility for Education and Research in 
Neuroscience (FERN) at Emory, where subjects will be 
recruited. During the Screening visit, subjects will be 
approached for inclusion in the study and will provide 
informed consent. The MINI International 
Screening Visit
Between 9:00 am – 
12:00pm
Subject arrives at Grady BHC for 
consenting and MINI diagnostic interview.  
They will also complete a physical and 
psychiatric exam, blood sampling for 
routine labs, CRP, urine drug screen and 
pregnancy test. All subjects will be eligible 
to also complete the MMSE, BNSS, 
WRAT, and MRI safety screen.
Visit 1
Subjects will be eligible to complete the 
PANSS, behavioral EEfRT, IDS-SR or 
SHAPS, and other assessments the PI 
and study staff may choose from other 
study visits.
Visit 2
9:00 am
Subject arrives at Emory University 
Hospital ACTSI suite
9:30 am
Blood Sampling
10:00 am
Behavioral Testing
12:00 pm
Lunch
13:00 pm
MRI Scan
14:30 pm
Complete Study
Visit 3
Complete Behavioral Testing

Neuropsychiatric Interview for Schizophrenia and Psychotic Disorders (MINI) will be administered. Subjects will 
also be requested to provide detailed information on past medical and psychiatric history and treatment, as 
well as current symptom status. A physical exam will be completed, and vital signs will be recorded. Routine 
labs will be obtained to rule out chronic illness or acute infectious process and a urine toxicology screen will be 
obtained. A blood draw to measure CRP will be obtained at this visit to ensure a range of inflammation from 
low (CRP≤3 mg/L, n=30) to high (CRP>3mg/L, n=30) based on guidelines from the American Heart 
Association.87 Subjects will also complete the Mini Mental State Exam (MMSE), the Wide Reading 
Achievement Task (WRAT), the Brief Negative Symptom Scale (BNSS) and the MRI Safety Screening form. 
Subjects who meet the inclusion criteria will be asked to schedule Visit 1. All subjects who sign consent on the 
screening visit will be included in the following additional assessments at Visit 1: (1) Positive and Negative 
Symptom Scale (PANSS) (2) the behavioral EEfRT task, the Snaith Hamilton Pleasure Scale (SHAPS) or the 
Inventory of Depressive Symptomatology (IDS-SR) and any other behavioral assessments that the PI and 
designated study staff decide to include from the other study visits. Visit 1 will be take place at Grady BHC, 
EUH GCRC, WMRB or FERN.  Visit 2 will be scheduled within two weeks of Visit 1. Subjects will be brought 
by taxi to Emory University Hospital at the ACTSI Research Site. During this visit, patients will undergo: (1) 
fasting blood sampling for plasma inflammatory markers and isolation of peripheral blood mononuclear cells 
(PBMCs) (collected between 9:00AM and 10:00AM to control for circadian variations), optional blood for 
induced pluripotent stem cells (iPSCs), optional blood for immune repertoire sequencing, and mRNA gene 
expression analyses, (2) behavioral testing with the objective, self-report and clinician-rated described below, 
and (3) MRI scan with imaging tasks described below. See below for breakdown of each study visit. The PI 
and designated study staff will have the discretion to decide which tasks are to be completed at each study 
visit. Furthermore, the PI and designated study staff may decide that a subject may go through behavioral 
testing only at Visit 2 and not undergo the neuroimaging protocol. Visit 3 will be scheduled within 72 hours of 
Visit 2 (may be extended up to 1 week per the PI’s discretion). Visit 3 will be conducted virtually or in-person at 
one of the following sites; Grady BHC, EUH GCRC, WMRB or FERN. The remainder of the behavioral 
assessments will be completed at this visit. 
Part A
Study Sample:
Enrollment: One hundred patients between the ages of 18 to 59 with diagnoses of schizophrenia or 
schizoaffective disorder will be recruited. Both diagnoses will be included in this study as there is a high degree 
of overlap between these disorders and both are often included in similar studies.88,89 The upper age of 59 was 
chosen to limit the impact of cortical atrophy and age-related white matter changes in the basal ganglia on 
MRI. Given our previous experience working with this patient population, we plan to screen 200 individuals, 
assuming that at least half will decline or drop out. All patients will be recruited from the Grady Outpatient 
Behavioral Health Clinic (BHC), where the PI currently serves as co-director of the PSTAR Clinic (Persistent 
Symptoms: Treatment, Assessment and Recovery). The PI has an excellent working relationship with Dr. 
, the medical director of the BHC. Approximately 30% of patients in the BHC have a primary 
psychotic disorder and approximately 1000 individuals have a diagnosis of schizophrenia or schizoaffective 
disorder. We anticipate recruiting 2-3 patients per month (20-30 patients per year) who will consent to enter the 
study, though should more patients express interest, we would recruit more patients then 2-3 a month. Our 
estimate of the number of patients able to provide informed consent is based on another study being 
conducted at the BHC, where the majority (16 out of 17) of patients with schizophrenia recruited were able to 
provide informed consent. In the preliminary data described above, the 10 patients in the cytokine study were 
equally split between two groups with CRP ≤3mg/L and >3mg/L. While the sample was not recruited to 
ensure this split, it is consistent with clinical data from a random sample of 50 patients from the PSTAR 
Clinic, 21 of whom have CRP ≤3mg/L and 29 with a CRP >3mg/L. This suggests that we should be able 
to recruit the CRP range proposed herein.  
Figure 3 shows all proposed assessments and the study visits at which they will be collected. The PI reserves 
the right to waive any of these assessments or change the visit in which they are administered, should he feel 
they would not benefit the patient or the study procedures.
Screening visit/consent signing: Screening Visit will take virtually or in-person at one of the following sites; 
Grady BHC, EUH GCRC, WMRB or FERN. Subjects will be approached for inclusion in the study and will 
provide informed consent. After providing informed consent, subjects will undergo the Mini International 

Neuropsychiatric Interview for Schizophrenia and Psychotic Disorders (MINI) to determine diagnostic eligibility 
for the study. Subjects who sign consent and meet the diagnostic criteria to be eligible for the study will 
undergo the remainder of the screening visit, which will include the following assessments:
(1) Mini-Mental State Exam
(2) Wide Reading Achievement Test (WRAT-3)
(3) Psychiatric History Form
(4) Medical history and physical exam performed by a physician 
(5) Brief Negative Symptom Scale (BNSS) 
(6) Behavioral EEfRT
(7) Blood draw for CRP 
(8) Laboratory testing including
a) Complete blood count with automated differential
b) Comprehensive metabolic panel (with renal and hepatic function tests)
c)
Glycosylated hemoglobin test (HbA1C)
d) Urinalysis with microscopic
e) Serum quantitative pregnancy test (if female)
f)
Urine toxicology for drugs of abuse
g) Anti-nuclear antibodies (ANA)
h) Rheumatoid Factor (qualitative) (RF)
i)
Thyroid Stimulating Hormone (TSH)
j)
HIV-1/HIV-2
k)
Hepatitis C Antibody
l)
Hepatitis B Surface Antigen 
Inclusion and Exclusion Criteria:
Inclusion: a. willing and able to give written informed consent; b. men or women, 18-59 years of age; c. a 
primary diagnosis of DSM-V schizophrenia or schizoaffective disorder as diagnosed by the MINI 7.0; d. 
Mini Mental Status Examination Score ≥24; e. Brief Negative Symptom Scale Score ≥25; f. no 
psychotropic medication changes for one month prior to study enrollment; may be taking other 
psychotropic non-antipsychotic medications (i.e., antidepressants, mood stabilizers, benzodiazepines).
Exclusion: Exclusion criteria will be split between those related to data quality and those related to subject 
safety. Data quality exclusion criteria may be waived at the discretion of the PI, though those exclusion criteria 
for subject safety may not be waived under any circumstances.
Data Quality Exclusion Criteria: a. evidence of untreated or poorly controlled endocrine, thyroid, 
cardiovascular, hematological, renal, neurological disease, hepatitis B or C or HIV; b. current HbA1C ≥ 
8.5%; c. prior treatment with antiviral or immunomodulatory drugs, including corticosteroids within six 
months of study entry; d. current treatment with antibiotics; e. primary diagnosis of major depressive 
disorder or bipolar disorder; f. active abuse of alcohol or illicit/prescription drugs within the past 6 months 
including a urine toxicology screen positive for drugs of abuse (patients may still be included with a 
positive THC result at the discretion of the PI); g. predominant left-handedness excluded for portions of 
the MRI scan; h. WRAT-3 score indicating less than 8th grade reading level, unless otherwise approved by the 
PI or PI’s designee; i. any other condition which in the opinion of the investigator would make the patient 
unsuitable for enrollment, or could interfere with participating in or completing the protocol.
Subject Safety Exclusion Criteria: a. history of CNS trauma or active seizure disorder requiring medication; 
b. positive pregnancy test; c. presence of metal in the body (excludes from MRI scan only); d. active 
suicidal ideation as determined by the PI and/or study staff.
Visit 1: Visit 1 will be scheduled between the screening visit and visit 2 and will either occur at Grady BHC, 
EUH GCRC, WMRB or FERN. The following assessments may include (scales and tasks may not be 
administered at the discretion of the PI and the study team):
(1) Positive and Negative Symptom Scale (PANSS)
(2) Snaith-Hamilton Pleasure Scale (SHAPS-C)
(3) Inventory of Depressive Symptomatology (IDS-SR)
(4) Quality of Life Enjoyment and Satisfaction Scale (QLES-Q)
(5) World Health Organization Disability Assessment Scale (WHODAS)
(6) Childhood Trauma Questionnaire (CTQ)

If the PANSS and EEfRT are not completed at Visit 1, they may be completed at either Visit 2 or Visit 3 at the 
discretion of the PI or designated study team. Additionally, if the subject is not fatigued, the CANTAB and 
Neurocognitive battery may be administered at Visit 1 or Visit 2 in lieu of coming in for Visit 3. Should this 
occur, compensation for Visit 3 in the amount of $20.00 will be added to Visit 1 or Visit 3.  
Visit 2: Visit 2 will be scheduled within 2 weeks (may be extended by 1 week at the discretion of the PI) of Visit 
1. Subjects will be brought by taxi, arranged by study staff, to Emory University where they will undergo 
behavioral assessments, fasting blood sampling, and MRI scan. These assessments will be conducted at one 
of two sites to be determined by the PI and the study team:  either the ACTSI Emory University Hospital 
Clinical Research Site and complete the MRI scan at the Emory University Hospital BITC Research Scanner, 
or the Emory University Department of Psychology and their Facility for Education and Research in 
Neuroscience (FERN). Transportation will be arranged for patients to be picked up at their home or designated 
location and brought safely to the Emory University campus. During this visit, patients will undergo the 
following assessments: (1) fasting blood sampling for plasma inflammatory markers (collected between 9:00am 
and 10:00am to control for circadian variations), PBMCs, induced pluripotent stem cells (iPSCs), immune 
repertoire sequencing, and optional mRNA gene expression analyses, (2) Urine Drug Screen (THC 
quantitative test if required) (3) Urine pregnancy test, (4) Optional saliva collection for microbiome analysis, (5) 
behavioral testing with objective, self-report and clinician-rated assessments, (6) Optional saliva collection for 
cortisol testing, (7) MRI scan with imaging tasks described below. Patients will not be allowed to smoke or eat 
at least 1 hour before the scan. Breaks will be allowed throughout the day, and snacks and a standardized 
lunch will be provided. Taxi service will be arranged to safely transport the patients back to their home. The 
Calgary Depression Scale for Schizophrenia (CDSS) and the Motivation and Pleasure Scale (MAPS-SR) will 
also be administered (scales and tasks may not be administered at the discretion of the PI and the study 
team).
Visit 3: Visit 3 will be scheduled within 72 hours (up to a week per the PI’s discretion) of Visit 2. Visit 3 will take 
place virtually or at one of the following sites; Grady BHC, EUH GCRC, WMRB or FERN. All assessments that 
have not been completed will be completed at this visit. Alternatively, these assessments can be administered 
at Visit 1 or 2 at the study staff’s discretion, depending on scheduling and the patient’s preference. 
Assessments include the following:
(1) CANTAB
(2) Neurocognitive Battery (described below)
Figure 3: Schedule of Assessments
Procedures
Screening Visit
Visit 1
Visit 2
Visit 3
Medical Assessments
Physical Exam
X
X^
Concomitant Medications
X
X
X
X
Adverse Events
X
X
X
X
Medical History
X
X^
CRP
X
X
Safety Labs*
X
X
Additional Blood (immune)
X
Optional blood for mRNA
X
Optional Urine Collection for iPSC’s
X
Optional blood samples for iPSC’s and immune 
cell repertoire analyses
X
Optional saliva collection for Cortisol Testing
X
Optional Saliva Collection for Microbiome Testing
X
MRI Scan**
X
Neuropsychiatric Assessments
Mini International Neuropsychiatric Interview 
(MINI)
X
Mini-Mental State Exam (MMSE)
X
Wide Reading Achievement Test 3 (WRAT-3)
X
Positive and Negative Symptom Scale (PANSS)
X
X^
Brief Negative Symptom Scale (BNSS)
X
Effort-Expenditure for Reward Task (EEfRT)
X
X^
X^
Neurocognitive Battery (described below)
X^
X^
X
Self-Reports/Questionnaires
MRI Scan Form
X
X^
Psychiatric History Form
X

*Safety labs may include 
Comprehensive Metabolic 
Panel, Complete Blood Count 
with differential, Glycosylated, 
Pregnancy Test (females), 
Urinalysis with microscopic, 
Urine Drug Screen, TSH, HIV-
1/HIV-2, ANA, RF, HbA1C, 
Hepatitis B Surface Antigen, 
Hepatitis C Antibody
**MRI scan may include 
structural scan, resting state 
scan, diffusion tensor imaging (DTI) scan, task-based scans
^may be completed at this visit at the study staff’s discretion
Urine drug screening: A urine drug test (DrugCheck: NxScan Onsite Testcup/THC quantitative test) may be 
performed for each patient at screening and upon arrival at EUH for Visit 2. The urine test will allow for the 
qualitative detection of drug or drug metabolites in urine, including benzodiazepines, methamphetamine, 
cocaine, THC, and morphine. Identification of a urine test positive for substance use will exclude the subject 
from participation, unless substance is a prescribed medication, or otherwise approved by the PI or PI 
designee. The THC quantitative test will be performed to assess the varying levels of THC if the results for 
THC are positive from the UDS. 
Blood Collection for iPSCs: At Visit 2, an optional, additional blood sample (~15mL) may be collected and 
sent to a collaborating laboratory led by Dr. 
. The collaborator will use cells from this sample to 
create induced pluripotent stem cells (iPSC). Over the past decade, researchers – including Dr. 
(Wen et 
al., 2014; Tang et al., 2016; Wen et al., 2016) – have harnessed the power of cellular-reprogramming 
technologies to turn differentiated cells in the adult, like those found in urine, blood or skin, into induced 
pluripotent stem cells (iPSCs). Importantly, patient-derived iPSCs feature the same mutations as those found 
in the donor individual (Wen et al., 2016). Thus, researchers can use these cells to model a condition or 
disease in the context of an individual person. A description of how the cells will be used is laid out in detail in 
the consent form.
Blood Collection for Immune Repertoire Sequencing: At Visit 2, an additional optional blood sample (up to 
32 mL) may be collected and sent to a collaborating laboratory led by Dr. 
. His team will 
isolate cells from this blood sample to study different subpopulations of lymphocytes using adaptive immune 
repertoire sequencing to understand how lymphocytes may help mediate the neuroinflammation that can occur 
in schizophrenia. (Yaari and Kleinstein, 2015; Cashman et al., 2019).
Gender and Minorities: Based on the composition of the patients treated for psychosis at the Grady BHC, we 
anticipate that an equal number of men and women will be included in the study. Given the demographic 
makeup of the PSTAR Clinic at the BHC, we should not have any difficulty recruiting from minority populations 
as this represents the majority of individuals seen at the Grady BHC.
Drop-outs: The schizophrenia patient population can at times be difficult to recruit as their negative symptoms, 
in addition to cognitive deficits, often lead to refusal to participate and high no-show rates. We plan to address 
this by screening more than double the number of patients proposed to enroll in the study (approach 400 to 
screen 200 to enroll 100) to account for this challenge. We also plan to continue recruiting patients until we 
reach a total of 100 individuals who complete the study, even if individuals drop out between study visits.
Compensation: Patients will be compensated $15 for their participation in the screening visit irrespective of 
whether or not they meet eligibility requirements for the remainder of the study; however, following the 
informed consent process, a clean urine drug screen will be required to proceed with the screening visit. If the 
urine drug screen is positive for any drugs of abuse, the screening visit will not continue, and the participant will 
not be compensated, with the exception of a positive THC result which may be included at the discretion of the 
PI. In addition to the $15, patients will also get winnings from 2 random trials of the behavioral EEfRT task (up 
to $25 total). Patients will be compensated $15 for their participation in Visit 1. Patients will be compensated 
$50 for their participation in Visit 2 in addition to compensation for their performance on the two imaging tasks. 
Calgary Depression Scale for Schizophrenia 
(CDSS)
X
Motivation and Pleasure Scale (MAPS-SR)
X
Snaith-Hamilton Pleasure Scale (SHAPS-C)
X
Quality of Life Enjoyment and Satisfaction 
Questionnaire (Q-LES-Q_SF)
X
Inventory of Depressive Symptomatology (IDS-
SR)
X
Childhood Trauma Questionnaire (CTQ)
X
WHO Disability Assessment Scale 2.0 (WHODAS 
2.0)
X
MRI Scan Food, Drink and Cigarette Intake Form
X

Per convention in the literature, patients will be given their total earnings in the MID task in addition to the 
amount of two random selections of “win” trials in the EEfRT task (up to $100 total compensation for Visit 2). 
Patients will be compensated $20 for their participation in Visit 3. The optional collection of blood samples at 
Visit 2 to generate induced pluripotent stem cells and/or perform immune repertoire sequencing will be 
compensated an additional $25. In total, patients will be compensated up to $185 for completing all study 
visits. 
Part C
Optional Oral Glucose Tolerance Test (OGTT) Arm:
Individuals who completed Part A will be invited to participate in an optional study (Part C), which will use an 
oral glucose tolerance test to test the hypothesis that insulin resistance drives inflammation. We will recruit 
subjects with a range of insulin resistance, as measured by the Homeostatic Model Assessment of Insulin 
Resistance (HOMA-IR) to ensure a range of IL from low to high (~50% <2.5 and ~50% >2.5). This will allow us 
to investigate the contributions of metabolic dysfunction and inflammation on inflammatory/metabolic markers, 
brain reward circuitry, motivational deficits, and negative symptoms. Relevant to the impact of inflammation on 
insulin signaling, measures of insulin sensitivity are significantly worse in patients with schizophrenia, including 
at illness onset.143, 144 Moreover, antipsychotic medications lead to metabolic syndrome, contributing to risk for 
insulin resistance and ultimately diabetes.145 Insulin resistance (IR) is believed to be caused by increased 
inflammation, and in turn can contribute to inflammation through alterations in glucose metabolism.146-150 The 
following specific aims are proposed in this optional study:
Specific Aim 1) To determine the impact of IR on inflammatory markers in patients with schizophrenia 
before and after a glucose challenge. Medically stable, male and female (n=20) subjects with metabolic 
syndrome and a range of insulin resistance (HOMA-IR; ~50% <2.5 and ~50% >2.5), who complete part A of 
the protocol will be enrolled. Baseline fasting blood glucose, insulin, leptin, adiponectin, resistin and lipids will 
be measured, and insulin and glucose will be assessed at 1, 2 and 3 hours post-OGTT. CRP, cytokines and 
their soluble receptors in plasma will also be measured before and after OGTT. Blood will also be drawn before 
and after OGTT for mRNA gene expression analyses. Hypothesis 1: Evidence of IR will be associated with 
enhanced inflammatory responses to OGTT and altered metabolic related signaling pathways in gene 
expression analyses.
Specific Aim 2) To determine the impact of IR and inflammation on reward circuits and negative 
symptoms in patients with schizophrenia, before and after glucose challenge. Participants described in 
Aim 1 will undergo the following assessments before and after OGTT: 1) Resting-state and task-based fMRI to 
assess changes in activation of functional connectivity between the ventral striatum and other reward relevant 
brain regions using targeted and network-based analyses in relation to inflammatory and metabolic markers. 2) 
clinical and objective assessments of motivation and negative symptoms. Inflammatory verses metabolic 
responses to OGTT will be examined as predictors and controlled for in the analyses. Hypothesis 2a: 
Peripheral IR will be associated with decreased functional connectivity within reward circuits, decreased ventral 
striatum activation, and greater motivational deficits/negative symptoms post-OGTT. Hypothesis 2b: 
Inflammation will mediate the effects of IR on reward circuit functional connectivity, as well as changes in 
motivational deficits/negative symptoms before and after OGTT.
Study design and methods: Participants from Part A will be approached to enroll in this optional study. A new 
written informed consent will be obtained from all patients before protocol-specified procedures are conducted. 
The schedule of assessments for the optional OGTT study can be found in Table 5.
 

Figure 5: Part C OGTT Schedule of Assessments
Procedures
Screening Visit (Grady BHC)*
Visit 1 Pre-OGTT (Emory 
GCRC/FERN)
Visit 1 Post-OGTT (Emory 
GCRC/FERN)
Medical Assessments
Physical Exam
x*
Concomitant Medications
x
x
x
Adverse Events
x
x
x
Safety Labs**
x
x
Vital Signs including waist 
circumference
x
x
x
CRP
x
Additional Research Blood (immune 
and metabolic markers)
x
x
MRI Scan
x***
x
Neuropsychiatric Assessments
Positive and Negative Symptom 
Scale (PANSS)
x^
Brief Negative Symptom Scale 
(BNSS)
x^
Calgary Depression Scale for 
Schizophrenia (CDSS)
x^
Effort-Expenditure for Reward Task 
(EEfRT)
x
x
Neurocognitive Battery 
x
x
Self-Reports/Questionnaires
Profile of Mood States (POMS)
x
x
 
*If >6 months
**Safety labs may include complete blood count, urinalysis, urine drug screen, chemistry
***If Part C is completed within 2 weeks of Visit 2 from Part A of the protocol (or at the discretion of the PI), MRI data may be used from part A as pre-
OGTT scan and the pre-OGTT MRI may be omitted.
^ If Part C is completed within 2 weeks of Visit 2 from Part A of the protocol (or at the discretion of the PI), data from these assessments may be used 
from part A and these may be omitted
Choice of OGTT as a metabolic challenge: We will use the OGTT because 1) responses to OGTT have 
been shown to be altered in patients with schizophrenia,144 2) it is a clinical diagnostic test, not an intervention, 
that can pull out differences in IR in non-diabetic but at-risk patients with schizophrenia, 2) IR is associated 
with dyslipidemia and changes in cholesteral,151 and altered OGTT response should be seen in patients with 
evidence of altered lipid/cholesterol metabolism in these panels, 3) it has been shown to cause changes in 
measures of brain functional connectivity, due to either leptin signaling or glucose uptake, that is altered in 
patients with evidence of IR,152-155  4) it stimulates inflammatory responses,158,159 allowing us to further probe 
immune and metabolic interactions, and 5) OGTT has been used to assess psychiatric/behavioral symptoms 
as they relate to IR in the Grady population through work in the Grady Trauma Project.156
Participant Selection
Inclusion Criteria: The same inclusion criteria from Part A will be used.
Exclusion Criteria: The same exclusion criteria from Part A will be used with the added criteria of a) diagnosis 
of diabetes mellitus. 
Description of Study Procedures
Optional Study Screening: Subjects who potentially qualify for enrollment in Part C will be approached at the 
end of Part A.  The exclusion of a diagnosis of diabetes will be made by medical history or HbA1C >6.5, both 
of which are assessed/measured in Part A. Of note, some individuals may qualify for both Parts B and C. If this 
is the case, subjects will first be offered Part B and then informed about Part C. This visit will occur at Grady 
BHC, EUH GCRC, WMRB or FERN. Fasting insulin and glucose will be measured to calculate HOMA-IR. 
CRP, CBC, urinalysis, vital signs, urine drug screen and pregnancy test (for women) will be collected as well to 
ensure that there are no active infections, active drug use, and/or pregnancy. If it has been >6 months since 
Part A, HbA1C will also be measured to ensure that the subject does not have diabetes. If >6 months, a 
physical exam will be repeated as well. If Part C is completed >2 weeks after Part A, the BNSS, PANSS, and 

CDSS will be repeated at this visit. In addition, subjects will also complete the MRI safety screening form again 
in case anything has changed since Part A. The total burden of the prescreening visit includes approximately 
~1-2 hours of informed consent and blood draw (if symptom measurements need to be completed at this visit, 
the visit will likely be closer to 2-3 hours). Subjects will be compensated $25 for the prescreening visit.
OGTT Visit 1: Subjects will be invited to participate in Visit 1 after signing informed consent at screening 
and meeting all inclusion/exclusion criteria. Visit 1 will be scheduled within 10 days (>10 days can be 
approved at the discretion of the PI) of Screening to ensure stability of CRP measurement (of note, the 
CRP at screening will not be used in analyses). Subjects will be brought by taxi/ride share (i.e, Uber) to 
Emory University Hospital at the Georgia CTSA Clinical Research Center (GCRC). All procedures during 
this visit will occur prior to and following a 75gm oral glucose tolerance test (OGTT).
Subjects enrolled and previously approved by the PI, with a positive UDS for THC will undergo a THC 
quantitative test. Subjects will undergo blood draw (fasting) for inflammatory and metabolic markers once 
before OGTT and at 15 min, 30 min, and 1, 2 and 3 hours post-OGTT. Whole blood will also be collected 
in Tempus Tubes for gene expression analyses at each time point. The following behavioral assessments 
will be administered pre and post OGTT administration: 1) Effort Expenditure for Reward Task, 2) Profile 
of Mood States, and 3) Neurocognitive Assessments described below. An MRI scan will be performed at 
the Emory Department of Psychology Facility for Education and Research in Neurosciences (FERN), 
where subjects were previously scanned during Part A. Subjects may undergo 1) Resting State fMRI, 2) 
Task Based MRI using the fMRI EEfRT and MID tasks, 3) DTI. Which of these MRI procedures will be 
made at the discretion of the PI. Post-OGTT MRI scan will be performed 3 hours after OGTT 
administration in order to measure reward circuitry at the peak of the inflammatory response. If Visit 1 is 
scheduled within 2 weeks of Part A from Visit 2, the pre-OGTT MRI scan may be omitted at the discretion 
of the PI. 
Given the pre-post design with blood draws, behavioral assessments, and MRI that will all be performed 
twice, Visit 1 will last approximately ~6 hours and the timeline can be found in Figure 2. Subjects will be 
compensated up to $150 for this visit based on their performance on the fMRI tasks. 
Figure 2. Visit 1 timeline for fMRI, blood, and behavior pre and post-OGTT.
Part D: Optional Antinuclear Antibodies (ANA) Study:
Individuals who completed Part A will be invited to participate in an optional study (Part D), which will use 
immune repertoire sequencing to understand the relationship between antinuclear antibody test positivity and 
schizophrenia. Though individuals that had a positive ANA screening result were excluded from Part A, this is 
still an important subpopulation to study as ANA positivity is three-fold more likely in individuals with 
schizophrenia than in healthy controls.166,167 Some antinuclear antibodies have the ability to bind to the GluN2A 
and GluN2B subunits of the NMDA receptor, which contributes to psychosis through glutamatergic dysfunction 
in systemic lupus erythematosus.168,169 We hypothesize that antinuclear antibodies contribute to schizophrenia 
pathogenesis in a similar manner. We propose to use B cell receptor sequencing to study how immune 
tolerance can breakdown in schizophrenia in order to explain the increased prevalence of antinuclear 
antibodies in schizophrenia. All individuals who previously tested positive for ANA and were therefore excluded 
from part A will be asked to participate in this study, up to a total of 20 male and female participants. 
Study design and methods: 
Adaptive immune repertoire sequencing will be performed with the collaboration of Dr. 
 at 

Emory University. B cell receptor sequencing will provide data about clonality, somatic hypermutation, and 
antibody selection. Data from ANA-positive individuals will be compared with ANA-negative participants 
(collected in Part A), as well as previously characterized datasets of healthy controls and individuals with 
systemic lupus erythematosus. These data will be combined with the PANSS to identify possible phenotypes of 
schizophrenia based on B cell repertoire fingerprints. We hypothesize that ANA-positive individuals with 
schizophrenia will show similar B cell repertoire fingerprints as individuals with lupus.
Participant Selection
Medically stable, male and female (n=20) subjects with ANA positivity who were screened out of part A of the 
protocol will be enrolled:
Inclusion Criteria: In addition to ANA positivity, the same inclusion criteria from Part A will be used.
Exclusion Criteria: The same exclusion criteria from Part A will be used with exception of ANA positivity. 
Additionally, a clean urine drug screen will be required for study participation and screening compensation.
Description of Study Procedures
Participants from Part A who were not eligible to participate due to ANA test positivity will be approached to 
enroll in this optional study. A new written informed consent will be obtained from all patients before protocol-
specified procedures are conducted. This visit will occur at Grady BHC. Following completion of informed 
consent, the PANSS will be administered. Up to 60 mL of blood will then be drawn for analysis. Lab draws will 
be timed to occur around 10 AM for consistency with Part A. A urine drug screen will be administered and a 
urine pregnancy test if you are a woman. CBC performed for screening in Part A will be repeated if indicated 
(e.g. if >6 months have passed since the screening visit). Blood will then be transported to Emory University 
using appropriate containment methods for use in immune repertoire sequencing. Additionally, CRP, cytokines 
and their soluble receptors in plasma will be measured at the discretion of the PI.
The total burden of all study procedures is estimated to by 120 to 150 minutes, including approximately 60 
minutes of informed consent, and an additional 60 to 90 minutes for lab collection and assessment 
administration. Subjects will be compensated $25 for the study visit provided their urine drug screen is 
unremarkable.
Figure 6: Part D ANA Schedule of Assessments
*If >6 months
**Safety labs may include complete blood count and urine drug screen
Part E Optional Study: Musical Preferences Assessment
Individuals who participate in Part A of this study will be invited to take part in this optional study that explores 
musical preferences and how music may impact symptoms associated with schizophrenia. The Part A 
informed consent will be modified to include this as an optional study to which patients may agree to 
participate. Patients who previously consented to Part A will be re-contacted and if interested, will sign a new 
informed consent in person or electronically.
Specific Aim 1) To determine how patients with auditory hallucinations experience music and how 
music impacts their symptoms.
Procedures
Screening Visit 
Safety Labs**
X
CRP
X
Additional Blood for immune repertoire 
sequencing (up to 60mL)
X
Neuropsychiatric Assessments
Positive and Negative Symptom Scale (PANSS)
X

Study design and methods
Twenty participants from Part A will be invited to participate in this optional study. If the participant is 
interested, a separate informed consent, either written or electronic, will be obtained from all patients before 
protocol-specified procedures are conducted. Following the informed consent process, an interview will 
commence. The interview, which lasts approximately 30-35 minutes, will include questions about musical 
preferences, whether or not the participant plays a musical instrument, and how music impacts one’s ability to 
deal with symptoms of schizophrenia.
Participant Selection
Inclusion Criteria: The same inclusion criteria for Part A will be used.
Exclusion Criteria: The same exclusion criteria for Part A will be used, with the added criteria of lack of self-
reported auditory hallucinations.
Description of Study Procedures
Following the informed consent process, a study team member will initiate the survey and take notes based on 
the participant’s responses. The participant may or may not consent to having the session recorded.   All audio 
recordings will be de-identified and used to ensure internal reliability.
The total burden of all study procedures is estimated to be approximately 50 minutes, including approximately 
20 minutes for the informed consent process. Participants will not be compensated for their time.
Part E Musical Preferences Assessment:
The Musical Preferences Questionnaire is a 19-item interview created by study team members that explores 
listening to and actively creating music as well as playing a musical instrument.
The Involuntary Musical Imagery Scale (IMIS)170: This scale assesses the positive or negative experience of 
music coming into the mind and repeating itself over and over without conscious effort.
Part A and C Study Procedures
Neuropsychiatric Assessments:
Observer-rated assessments
Demographic Data Form: Will be used to collect demographic data for the study.
Mini International Neuropsychiatric Interview for Schizophrenia and Psychotic Disorders (MINI): The 
MINI is a semi-structured interview conducted by trained interviewers aimed at establishing the presence of 
disorders according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V).90 
Mini-Mental State Exam (MMSE): The MMSE is a 27-item interviewer-administered questionnaire widely 
used for the evaluation of general cognitive functioning and identification of altered mental status.91 Previous 
work in patients with schizophrenia from community-based outpatient samples similar to the cohort we plan to 
recruit from demonstrates that a 24/30 on the MMSE represents having less than a 9th grade education.92
Positive and Negative Symptom Scale (PANSS): The PANSS is the most commonly used measure for 
assessing the symptoms of schizophrenia.93 Seven items measure positive symptoms, 7 measure negative 
symptoms, and 16 measure general psychopathology symptoms.
Brief Negative Symptom Scale (BNSS): The BNSS is a 13-item scale designed for research studies in 
response to the 2005 NIMH consensus development conference on negative symptoms of schizophrenia.94 
Based on findings from the meeting, the BNSS measures the five commonly accepted domains of negative 
symptoms: blunted affect, alogia, asociality, anhedonia and avolition.95 A BNSS cutoff of 25 is based on mean 
scores from various international validation studies of the BNSS.137-141 This cutoff will ensure that we enrich our 
sample with individuals who have negative symptoms, while still ensuring an adequate range for analyses. 
Wide Range Achievement Test-3 Reading Scale (WRAT-3): The WRAT-3 is a very brief screening measure 
for reading level, which has been shown to estimate premorbid intelligence in individuals with schizophrenia.96-
98
Calgary Depression Scale for Schizophrenia (CDSS): The CDSS is a clinician-administered, 9-item rating 
scale designed for the assessment of depressive symptoms in schizophrenia. Depressive symptoms are highly 

prevalent in patients with schizophrenia and may lead to a higher burden of disease. It is reliable, valid, and 
able to distinguish depressive symptoms from negative symptoms and extrapyramidal symptoms. 
Collecting Speech Data: The protocol aims to audio record the interview of patients during either the Brief 
Negative Symptom Scale (BNSS) assessment or the Positive and Negative Symptom Scale (PANSS). 
Additionally, patients will be presented with an abstract piece of art and asked to describe their impressions of 
the art to elicit free and more abstract speech. Patients will be audio recorded for up to 10 minutes for the latter 
question. Audio recording will only be performed if patients consent to the audio recording section of the 
informed consent form. Audio recordings will be transcribed, and all protected health information will be 
removed from the text and replaced by a token denoting this type of content. The transcribed text will be used 
for computational analyses of speech. The analyses involve the use of machine learning and distributional 
semantics to represent sentences as vectors in a high-dimensional space. The number of core semantic units 
in each sentence vector will be measured as an index of poverty of content.
For Optional Study Part E, participants will have the option of consenting to the audio recording of The Musical 
Preferences Questionnaire and the IMIS. 
Video-recording Clinical Interviews: Subjects will be offered the additional option to consent to the video-
recording of clinical interviews, including the PANSS, BNSS, and/or MINI. Video recordings will only be used 
for training purposes and to ensure internal reliability and validity of subjective measures. 
Self-report questionnaires:
Motivation and Pleasure Scale (MAPS-SR)55: The Motivation and Pleasure Scale – Self Report (MAPS-SR) 
is an 18 item self-report measure based on the Clinical Assessment Interview for Negative Symptoms 
(CAINS). The scale has been validated in patients with schizophrenia, shown to be associated with clinician-
rated negative symptom severity, and has thus been shown to be a reliable self-report measure of negative 
symptom severity.160
Snaith-Hamilton Pleasure Scale (SHAPS-C): This clinician administered scale is a reliable, valid and 
unidimensional instrument to assess hedonic capacity in adults with psychiatric disorders, including studies of 
effort-based motivation in schizophrenia. 36, 39, 60
Inventory of Depressive Symptomatology (IDS-SR): This 30-item self-report reliably assesses depressive 
symptom severity for the past 7 days.60
Childhood Trauma Questionnaire (CTQ): The CTQ is a self-report inventory assessing 3 types of childhood 
abuse: sexual, physical, and emotional. Studies have established the internal consistency, stability over time, 
and criterion validity of both the original 70-item CTQ and the current brief version.121 The CTQ yields a total 
score and subscale scores for each of the types of child abuse. The data from the CTQ will be used to classify 
subjects into 2 categories for each type of abuse (physical, sexual, and emotional): (1) those with CTQ scale 
scores in the none to mild range, and (2) those with CTQ scores in the moderate to severe range. We will then 
create a composite variable across all of the 3 types of abuse. Using this composite, we can divide participants 
into 2 groups with respect to the numbers of types of abuse that fall into the moderate to severe range: (1) 
those with no type of abuse in the moderate to severe range, and (2) those with at least 1 type of abuse in the 
moderate to severe range.122
World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0): The WHODAS 2.0 is a 
36-item interviewer administered assessment which provides a score for global disability as well as six domain 
scores in cognition, mobility, self-care, getting along with others, participation in society, and life activities. It is 
included in the DSM-5 as a measure of further study.103
Quality of Life Enjoyment and Satisfaction Questionnaire – Short Form (Q-LES-Q-SF):  The Q-LES-Q-SF 
is a 16 item self-report scale assessing the participant’s quality of life in various domains, including physical 
health, mood, social relationships, and overall sense of well-being. 127
Profile of Mood States (POMS): The POMS is a 30-item rating scale designed to measure mood states 
across short periods of time.161,162 The POMS has been widely used in studies with patients with schizophrenia. 
Neurocognitive Assessments:
Though the driving aim of this proposal is to investigate the effects of inflammation on reward relevant circuitry 
in the brain leading to motivational deficits and negative symptoms of schizophrenia, previous data has also 
demonstrated that inflammation leads to altered basal ganglia function, specifically impacting the dorsal 
striatum, and has been associated with reduced psychomotor speed. Inflammation has been shown to alter 

neural activity and dopamine metabolism in basal ganglia regions including the dorsal striatum as assessed by 
a variety of neuroimaging strategies following several inflammatory stimuli including Interferon-alpha, typhoid 
vaccination and endotoxin51-53, 59, 123  Administration of inflammatory stimuli have also been shown to lead to 
depressive symptoms, including psychomotor retardation as well as objective measures of psychomotor 
slowing.52,124, 125  In a recent study of the role of inflammation in patients with depression, IL-6, IL-10, and MCP-
1 were all shown to be associated with objective measures of psychomotor slowing126. These inflammatory 
markers have all been demonstrated to be aberrant in patients with schizophrenia61. Psychomotor retardation 
has been described in patients with schizophrenia and is considered to be a negative symptom of the disorder. 
As such, we will plan to test the hypothesis that inflammation also decreases activation of the dorsal striatum 
and its associated circuitry, leading to decreased objective measures of psychomotor speed and negative 
symptoms in schizophrenia.
A range of neuropsychological assessments will be used to probe basal ganglia function and will be associated 
with inflammation status as noted above. Assessments will lie along a continuum, progressing from more 
purely motor tasks (such as finger tapping) which assess circuitry within the basal ganglia to those that involve 
motor speed with increasing cognitive demand and cortical participation (e.g. the Digit Symbol Task). In 
addition, we will administer a test of procedural memory, with minimal processing speed or reaction time 
demands, that has been shown to be sensitive to dysfunction in the basal ganglia, without the executive 
demands associated with tests of frontal lobe function. Every effort will be made to match groups on the basis 
of demographic factors affecting test performance, such as age, education level, gender and ethnicity. These 
factors can significantly influence neuropsychological test results and while relatively small variations between 
groups can be handled through addition of covariates to statistical analyses, more significant differences in-
group composition will threaten the integrity and interpretation of the results. 
Finger Tapping Task (FTT): This task uses a specially adapted tapper that the subject is asked to tap as fast 
as possible. The subject is given 5 consecutive 10-second trials for the preferred and non-preferred hands.
The FTT is designed to assess subtle motor impairment and found to be altered in subjects with basal ganglia 
disorders and lesions.104
Reaction Time Task (CANTAB): This reaction time test includes simple and choice reaction time tasks and is 
divided into 5 stages requiring increasingly complex chains of responses and providing distinction between 
reaction (or decision) time and movement latencies. Movement times on the CANTAB reaction time task have 
been slowed during IFN-α treatment and correlated with IFN-alpha-induced depression and fatigue.105
Trail Making Test Part A (TMT-A): The Trail Making Test-A is a timed task that provides information on motor 
function and speed of processing.106 Previous studies have indicated that performance of TMT-A significantly 
correlates with reduced caudate volumes in older persons with depression.107
Digit Symbol Substitution Task (DSST): The DSST is a subtest of the Wechsler Adult Intelligence Scale and 
involves graphimotor speed, visual scanning and memory, with about half of the variance being accounted for 
by graphimotor speed, a third by visual scanning and 4-5% by memory.108 Performance on the Digit Symbol 
Test has been found to correlate with subcortical (caudate) atrophy in disorders involving the basal ganglia.105
Effort-Expenditure for Rewards Task (EEfRT): The EEfRT task is a multi-trial game in which participants are 
given an opportunity on each trial to choose between two different task difficulty levels in order to obtain 
monetary rewards.109 For all trials, participants make repeated manual button presses within a short period of 
time. Each button press raises the level of a virtual ‘‘bar’’ viewed onscreen by the participant. Participants are 
eligible to win the money allotted for each trial if they raise the bar to the ‘‘top’’ within the prescribed time 
period. Each trial presents subjects with a choice between two levels of task difficulty, a ‘high effort’ and ‘low 
effort’ task that require different amounts of speeded button pressing. Reward magnitudes for the high effort 
task will vary between $1 and $10, while reward magnitudes for the low effort task remain constant (between 
$0.50 and $1.00). The reward magnitudes will be decided at the discretion of the PI. Trials will also vary in 
terms of 3 levels of probability of winning the amount associated with the choice selected. Subjects participate 
in the task for approximately 20 minutes and the first 50 trials are used for analysis. Because of the 
requirement for rapid button presses for a long period of time, we will exclude participants who report chronic 
pain in their wrists/hands and or those who have wrist/hand injuries, such as Carpal Tunnel Syndrome. At the 
discretion of the PI, the EEfRT may be repeated after the neuroimaging scan.

Neuroimaging Tasks:
The PI will choose which of these fMRI tasks will be performed at the fMRI study visits.
Monetary Incentive Delay (MID) Task: Assessment of reward anticipation will be achieved using the MID 
task.26,110-112 Briefly, during this task participants have the opportunity to win or lose money by making a rapid 
button press in response to a target visual stimulus. The primary epoch of interest is the “anticipatory delay” – 
a period of ~2000ms that occurs after participants have been informed how much money they can win or lose 
on a given trial, but prior to the presentation of the target. This epoch has repeatedly been associated with 
robust ventral striatal activity.26,110,113-114 Participants will complete 2 functional runs of between 50 and 200 
trials each (the number of trials will be decided at the discretion of the PI), with evenly distributed reward 
magnitudes between $0.20 and $10.00, to be decided by the PI. 
fMRI-adapted version of the EEfRT task: Assessment of effort-based decision making will be assessed 
using the EEfRT task.109 During each trial, subjects are presented with a choice between two levels of task 
difficulty, a High Effort option and a Low Effort option. Unlike in the behavioral version of the task, subjects will 
not be required to make button presses during the scan. The reward magnitude for a No Effort option remains 
constant, while the reward magnitude for the High Effort option varies from $1.00 to $10.00. Additionally, the 
amount of effort required for the High Effort option will vary between 20%, 50%, 80% and 100% of the subject’s 
maximum effort (set for each individual prior to scan).
Reinforcement Learning (RL) Task: Trials for this task involve a 3s cue presentation during which subjects 
choose between two abstract stimuli, followed by an exponentially jittered delay, and then a 3s feedback 
presentation with positive (monetary win), negative (monetary loss) or neutral outcomes. This task has been 
shown to robustly activate the ventral striatum in response to prediction errors.
Safety and Tolerability
Adverse Event Recording: All adverse events will be coded in standard MeDRA terms (Version 14.1), and 
whether events are expected and study-related will be determined by the study PI. In addition, severity and 
start and end dates will be recorded as well as any evidence of unanticipated problems. This information will 
be provided to the Department of Psychiatry and Behavioral Sciences DSMB and IRB annually as described in 
the Human Subjects Section.
Laboratory Variables
Blood Collection: At screening, blood will be collected by venipuncture for measurement of CRP (for high 
versus low inflammatory screening only; this CRP will not be used for data analysis) and screening labs 
including Full Chemistry Panel (Chem14), Complete Blood Cell Count (CBC), and Hemoglobin A1C (HbA1C). 
At Visit 2, a fasting blood sample will be collected by venipuncture into EDTA-containing vacutainer tubes 
using standard sterile technique. Plasma for the evaluation of plasma cytokines and their receptors as well as 
CRP will be obtained by centrifugation of whole blood at 1000x g for 10 minutes at 4°C. Plasma and buffy coat 
will be removed and aliquoted into siliconized polypropylene tubes and stored at -80°C until batch assay. 
Additional blood samples (up to 55mL of blood) may also be collected for 1) the isolation of PBMCs, 2) induced 
pluripotent stem cell creation (optional; in collaboration with Dr. 
) and 3) immune repertoire 
analysis (optional; in collaboration with Dr. 
).
Plasma cytokines and soluble cytokine receptors: Fluorokine MAP Multiplex Human Biomarker Panels 
(R&D Systems, Minneapolis, MN) will be used to measure plasma TNA-alpha, sTNFR2, IL-1ra, IL-1beta, IL-6, 
sIL-6R, IL-10, and monocyte chemoattractant protein (MCP-1). These inflammatory markers have all been 
found to be altered in schizophrenia.61 Each determination requires 50-100 μl, and all samples will be assayed 
in duplicate according to manufacturer’s instructions. Quality control plasma of both low and high cytokine 
concentrations will be included with every assay. The mean inter- and intra-assay coefficients of variation for 
control samples are reliably 10% or less.
C-reactive protein (CRP): Plasma CRP for screening will be assessed by a high sensitivity turbidimetric assay 
using the CLIA-certified lab at Grady Memorial Hospital. For study purposes, an immunoturbidometric method 
will be used to measure high sensitivity CRP concentrations with a Beckman AU480 chemistry analyzer and 
Ultra WR CRP kit (Sekisui Diagnostics).
Optional mRNA collection: Subjects will be asked to collect peripheral blood at Part A Visit 2 for messenger 
RNA (mRNA) for gene expression analyses. If enrolled in Part B, subjects will be asked to collect peripheral 

blood at the Infusion Visit and Post-Infusion Visit 1. No DNA will be collected for analyses. One 9ml Tempus 
tube of blood will be collected and the tube will be inverted to mix for 10-15 seconds and immediately placed 
on wet ice. This tube will be stored overnight at 4°C. The next day, these Tempus tubes will be transferred to a 
-20°C freezer for storage. Patients may decline to provide blood for mRNA gene expression analyses, which 
will not affect their participation in the rest of the study.
Optional Blood for iPSCs: Optional blood samples (~15mL) collected at Part A Visit 2 and Part B Post 
Infusion Visit 1 may be sent to a collaborating research group at Emory (the laboratory of Dr. 
). 
From these samples, Dr. 
will reprogram adult somatic cells into induced pluripotent stem cells (iPSCs). 
From that point, Dr. 
 can use these cells (which can be differentiated into cells like neurons) in controlled 
experiments to study microglial cells, the immune cells found in the brain, for example (Wen et al., 2016). This 
further study would serve as a complement to the objective of the main study: examining the effects of 
inflammation on brain circuitry and negative symptoms in patients with schizophrenia. Blood samples may be 
stored for future research with Dr. 
. Blood samples collected for further research will be stored in 
the laboratory space of Dr. 
. It will be explained to participants in the consent form that their samples and 
data will be available for any research question, such as research to understand what causes certain diseases 
(for example heart disease, cancer, or psychiatric disorders), development of new scientific methods, or the 
study of where different groups of people may have come from. The PI will determine how samples and data 
collected through this study are used. Any use of the samples of data for other studies of the PI’s would be 
submitted to the IRB through a separate submission. Dr. 
 will receive no other information with 
the samples other than the study record ID and sex. The link between a participant’s study record ID and name 
or other information that could be used to identify him or her will not be shared with other researchers. This 
information will be kept in a password-protected computer file located stored on Emory Box or Microsoft One 
Drive. Only core research personnel will have access to this information.
Blood for immune repertoire sequencing: A blood sample (up to 32 mL) may be sent to a collaborating 
research group at Emory (the laboratory of Dr. 
). Blood samples collected for further 
research will be stored in the laboratory space of Dr. 
. These blood samples will be sorted into 
lymphocyte subpopulations and the B cell receptor will be sequenced to generate information about B cell 
somatic hypermutation and B cell clonal dynamics. It will be explained to participants in the consent form that 
their samples and data will be available for any research question, such as research to understand what 
causes certain diseases (for example heart disease, cancer, or psychiatric disorders), development of new 
scientific methods, or the study of where different groups of people may have come from. The PI will determine 
how samples and data collected through this study are used. Any use of the samples of data for other studies 
of the PI’s would be submitted to the IRB through a separate submission. Dr. 
 will receive no 
other information with the samples other than the study record ID. The link between a participant’s study record 
ID and name or other information that could be used to identify him or her will not be shared with other 
researchers. This information will be kept in a password-protected computer file located stored on Emory Box 
or Microsoft One Drive. Only core research personnel will have access to this information.
Reliability of ratings: All clinicians performing the MINI in this study will be trained to conduct the 
assessments according to standardized guidelines for the administration of the instrument and will conduct 
interim training sessions to maintain standardization. In addition, training on all other clinician rated scales will 
be provided for the relevant study personnel, and interrater reliability will be established. Trained staff will 
conduct the neurocognitive assessments. New staff joining the study team will go through an apprenticeship 
for the ratings and training for reliability prior to performing independent ratings. 
Magnetic Resonance Imaging: At Part A Visit 2 and Part B Post Infusion Visit 1, MRI experiments will be 
performed on a 3T MRI scanner (either at the BITC Research Scanner at the Emory University Hospital, the 
Department of Psychology Facility for Education and Research in Neuroscience (FERN) or the Center for 
Systems Imaging (CSI) at Wesley Woods, to be decided by the PI prior to the start of the study. Only one 
scanner will be used throughout the course of study to maintain consistency).  The subject will be pre-screened 
with the “MRI Screening form” to confirm that he/she is eligible to participate in the scan. Because MRI 
scanning can affect metallic and other implants, all subjects will be careful screening for metallic implants and 
other contra-indications to MRI prior to the procedure, using the standard Emory University Biomedical 
Information Technology Center MRI screening form. Subjects with contra-indications will not receive a MRI 

scan. The MRI scanner is an enclosed space and subjects may experience claustrophobia while being 
scanned. Should a subject develop claustrophobia during the procedure, the scan will be terminated. All 
subjects will be required to limit caffeine intake for two hours prior to the scan. Any food or drink intake during 
this time frame will be recorded using a MRI Scan Food, Drink and Cigarette Intake Form immediately prior to 
the scan. Subjects will be offered an opportunity to be scanned with one of two scanning protocols. Depending 
on which protocol they choose, the scan may take between 60 to 90 minutes in length, though will not exceed 
one and a half hours. The patients will be informed of the time requirements prior to participation in the study. 
Protocol one would include the following scans: Structural Scan (~6 minutes), Resting State Scan (~ 8 
minutes), Diffusion Tensor Imaging Scan (~6 minutes), Task-Based Scans (~24 minutes). Protocol two would 
be similar though would allow for a break between the Diffusion Tensor Imaging Scan and the Task-Based 
Scans where the subject would be allowed to exit the scanner, rest, go to the bathroom, and drink water, 
should they choose. This second protocol will be longer in total time given the break. Figure 4 details the two 
proposed scanning protocols.
Figure 7: Scanning Protocol Options
*All Times are Approximate
** Diffusion Tensor Imaging
*** Monetary Incentive Delay Task (may be substituted for another of the 
tasks at the PI’s discretion)
**** fMRI adapted Effort Expenditure For Reward Task (may be 
substituted for another of the tasks at the PI’s discretion)
Collection of structural and functional data includes: a 
13-s localizer scan; an “auto-align scout” scan that 
uses a reference database to ensure consistent slice 
positioning across subjects; a rapidly acquired, T1-
weighted, multi-echo MPRAGE volume for structural 
analysis and localization of fMRI data and multiband 
echo planar imaging for task related fMRI. This last sequence is re-used to acquire task-evoked fMRI data. 
During resting-state scan, participants will lie passively and refrain from thinking about anything specific. The 
Task Based Scans would consist of 1-2 of the following tasks chosen at the discretion of the PI or designee: 
fMRI-based Effort Expenditure for Reward task, Monetary Incentive Delay task, or the Reinforcement Learning 
Task. During the course of the imaging protocol, brief periodic checks of mood and psychosis (“Symptom 
Check”) will be conducted to ensure the safety/comfort of the patient and to ensure that fluctuations in 
symptoms do not interfere with the interpretation of the scanning data during analysis.
Confidentiality: All participant data will be de-identified. All paper copies of data will be kept in a locked file 
cabinet in a locked office, accessible only by the PI and study staff. Audio and video recordings and the 
transcribed speech will be input into the Box system, a secure data management system. An identifier will be 
assigned to each data file and no data will contain the participant’s name or any other identifying information. 
Neuroimaging data will be stored on Emory’s secure network. A password-protected master enrollment log, 
also stored on Emory’s secure network, will be the only key between participants’ identifying information and 
the participant ID numbers. All data will be input into the Redcap system, a secure data management system.
6. Participant selection
One hundred males and females between the ages of 18 and 59 will be recruited for this study. All 
subjects (50% males and 50% females) will meet criteria for schizophrenia or schizoaffective disorder. 50 of 
these subjects will have plasma CRP concentrations >3 mg/L and 50 will have plasma CRP concentrations ≤3 
mg/L.  We plan to prescreen 400 subjects in order to consent 200 medically stable individuals. Of these, we 
anticipate that 100 subjects will be eligible and complete the protocol for the study. There will be no exclusions 
for race/ethnicity, and we expect that >50% of participants will be of minority race/ethnicity given the 
demographic make-up of the Grady Behavioral Health Clinic. Women will be actively recruited to ensure that 
50% of the subjects will be female. No patients will be enrolled from vulnerable populations, including 
neonates, children, prisoners, or institutionalized individuals. Patients will largely be recruited from the Grady 
BHC, though we will also plan to recruit from the Emory Psychopharmacology Clinic as a secondary site to 
ensure we are successful at recruitment. We anticipate consenting 2-3 patients per month (20-30 patients per 
year). This estimate is based on ongoing projects that have recruited similar subjects for research studies. 
Patients enrolled in the study will meet DSM-V criteria for schizophrenia or schizoaffective disorder as 
Scanning Protocol One
Scanning Protocol Two
0:00*
Enter Scanner
0:00*
Enter Scanner
5:00
Symptom Check
5:00
Symptom Check
6:00
Start Scan
6:00
Start Scan
11:00
Structural Scan
11:00
Structural Scan
17:00
Symptom Check
17:00
Symptom Check
18:00
Resting State Scan
18:00
Resting State Scan
26:00
DTI Scan**
26:00
DTI Scan**
32:00
Symptom Check
32:00
Exit Scanner for Break
33:00
MID Task***
47:00
Symptom Check
45:00
fMRI EEfRT****
48:00
MID Task***
57:00
Exit Scanner
60:00
fMRI EEfRT****
58:00
Symptom Check
72:00
Exit Scanner
73:00
Symptom Check

determined by the MINI 7.0. To be included, subjects must not demonstrate active suicidal intent or plan and 
must have no suicide attempts within six months of screening. Subjects will not be enrolled if they have a 
primary diagnosis of a mood disorder (i.e; major depressive disorder or bipolar disorder), intellectual disability, 
delirium, or dementia or MMSE <24 (indicating cognitive impairment), unless otherwise approved by the PI or 
PI’s designee. Subjects may be taking psychotropic medications at the time of the study (including 
antipsychotics, antidepressants, mood stabilizers, benzodiazepines) but may have no psychotropic medication 
changes for one month prior to study enrollment. At the PI’s clinical discretion, subjects who screen positive for 
antinuclear antibodies (ANA) may be included as long as there is no evidence of an autoimmune disorder by 
history or on physical examination. Subjects will be at risk for exclusion for a urine toxicology screen positive 
for alcohol or drugs of abuse.  The presence of post-traumatic stress disorder, obsessive compulsive disorder, 
panic disorder or social phobia will not disqualify subjects from enrollment, though cannot be the subject’s 
primary diagnosis. Additionally, subjects may have a secondary diagnosis of major depressive disorder. 
Enrolled subjects may have a comorbid personality disorder; however, subjects who meet criteria in clinical 
interview for antisocial personality disorder will be disqualified, as will subjects with a history of hospitalization 
and/or recurrent suicidal behavior judged to be directly due to a personality disorder.
 
Potential subjects may be excluded for a number of medical conditions that might confound 
relationships between psychiatric diagnoses and inflammation, including uncontrolled cardiovascular disease, 
autoimmune condition (i.e. rheumatoid arthritis, inflammatory bowel disease, multiple sclerosis, lupus), chronic 
infection (i.e. HIV, hepatitis B or C, herpes), abnormal lab results deemed by study physicians as 
contraindicated for study participation, or pregnancy. Similarly, patients may be excluded for evidence of 
medical or neurological abnormality on physical examination. Subjects will also be excluded for the following: 
a) history of CNS trauma or active seizure disorder requiring medications; b) prior treatment with antiviral or 
immunomodulatory drugs, including corticosteroids within six months of entry into the protocol; c) current 
treatment with antibiotics. Subjects who develop signs of an infection between screening and commencing the 
protocol assessments will be rescheduled when symptoms have resolved, if agreeable to the subject. 
 
Risks in Participation
Behavioral Component: Participant risks are minimal. Participants may find the computer tasks to be boring,
and associated with mild fatigue. Additionally, some tasks may require some rapid key pressing, which could
induce mild discomfort in the hands. Consequently, individuals with medical conditions that limit the use of their
hands are ineligible for the study. 
Questionnaires: Minimal risks associated with completing questionnaires are subject fatigue and the possibility
of minor psychological distress associated with answering sensitive questions regarding psychological
functioning and/or the subject’s past of present emotional state. 
Confidentiality: This study has a Certificate of Confidentiality and as detailed, multiple procedures are in place
 to reduce the likelihood of a breach of confidentiality. However, there is a small risk that information about 
subjects could become known to people outside the study, and this risk is identified in the informed consent 
form. A number of procedures will be in place to prevent a breach of confidentiality from taking place. All 
potential subjects will be fully informed of their rights pertaining to disclosure of PHI in accordance with HIPAA 
regulations. Confidentiality will be maintained by assigning participants a study number and numerically coding 
all data. One hard copy file linking the code number with identifying information will be kept in a separate 
locked file with direct access available to the PI only. All records and research data will be kept in locked filing 
cabinets or computers. Only summaries of group data will be reported in any publications or presentations, 
with no identification of individuals. These precautions should serve to minimize legal risks to participants.
Additional Risks in Participation 
MRI Component: In addition to the risks described for the behavioral component, the MRI component involves 
several additional risks. MRI is non-invasive but due to the strong externally generated magnetic field, the 
participant's safety in ensured by excluding participants that are not compatible with this environment using the 
standard MRI screening form. MRI studies will use radiofrequency power deposition and gradient switching, 
which have been approved by the FDA. The magnetic fields are within the limits recommended by the FCC. 
The 3.0T field strength itself has been deemed a non-significant risk by the FDA. The scanner is loud, and 
participants will be given earplugs and headphones to reduce the noise of the MRI machine, while they are in 
the scanner.  Participants may additionally experience some muscle discomfort or feel too hot or cold. In these 
cases, participants may ask for an adjustment of room temperature or a blanket. Participants who become 

nervous or claustrophobic or feel a sense of dizziness while in the scanner may ask to be withdrawn 
immediately.
Blood Draw: Blood drawing may cause some pain and has a small risk of bleeding, bruising, infection at the 
puncture site, or dizziness. There is also a small risk of fainting. Standard sterile procedures for blood draw will 
be used. Blood draws will be conducted by clinicians with significant experience in the technique. Should any 
of these occur during blood draw, the PI and/or designee will be contacted to assess the situation and offer 
medical intervention if deemed necessary.
mRNA Collection: All stored specimens will be labeled with subject’s unique study identification without any 
other identifying information. The master list linking the study identifying code will be kept in a separate location 
from the storage of these samples and will be kept safely locked. Only the PI and Co-Is will have access to this 
master list. Specimens will be stored in freezers until all data has been collected and the study team is ready to 
conduct analyses (not greater than one year from study collection). Only the PI and Co-I’s will have access to 
these samples.  There are no currently known potential consequences of the genetic information to insurability, 
employability, or social esteem of the subject. Subjects will be informed that there could be future unknown 
consequences which could affect their insurability, employability, or social esteem and, as such, all efforts will 
be made to ensure there is no linked identifying information. The mRNA/gene expression data collected will 
only be used for the purposes of research and subjects, nor their families, will not be informed of the results of 
these tests. Subjects will have the right to withdraw from research, withdraw data, and/or withdraw their genetic 
information either before or after the research has begun or has been completed. We will not transfer this data 
to other researchers. If a subject wishes to withdraw any and/or all data from the study, they will be instructed 
to contact the PI. Subjects may participate in the other portions of the study while refusing to undergo genetic 
testing.
Part C OGTT (optional study): There are no additional risks to subjects beyond what has been described 
above for Part A regarding risks to MRI, blood draw, mRNA collection, and psychiatric assessments. The 
OGTT is a safe diagnostic procedure to determine insulin resistance frequently used in clinical practice and as 
such poses no additional risks to the subject.
7. Statistical Analysis
Power Analysis: For all three specific aims, analyses will be performed on data collected from 100 patients. 
Given that the primary statistical analyses will be correlational in nature, an N of 100 will be sufficiently 
powered (>80%) for moderate effect size (~r=0.5) at an alpha = 0.05, two-tailed.116 All analyses will correlate 
inflammatory markers with both neuroimaging and behavioral task performance.
For the optional OGTT, to investigate the correlational relationships between inflammatory markers and 
metabolic markers, a sample size of 19 would be required to find a correlation of 0.7 at an alpha of 0.05 
with Power of 0.95 (calculated in G*Power), which suggests that we have adequate power to investigate 
these primary relationships both before and after OGTT challenge. However, we are underpowered to 
identify relationships between changes in inflammatory and metabolic markers pre- and post-OGTT with 
reward circuitry or motivational deficits. These analyses are thus exploratory and will serve as preliminary 
data for future research proposals. 
Interim Monitoring and Early Stopping:
Subjects will receive a physical examination at Part A Screening or Visit 1. Subjects will also receive safety 
laboratory testing as well as pregnancy (if female) and substance abuse testing at the Part A Screening or Visit 
1, in addition to at Part A Visit 2.
The following events are considered sufficient reasons for discontinuing a subject from the study:

An adverse event (AE) that, in the judgment of the investigator, may cause severe or permanent harm

A clinical finding, such as an untreated medical condition, from safety labs or the history and physical 
examination

Subject withdraws consent


Subject lost to follow-up

Pregnancy

Protocol violation

Substance abuse

Death
Study:
If more than two individuals experience a reportable serious adverse event related to study procedures within a 
six-month period, the study will be stopped and reviewed by the DSMB. 
Analysis Plan and Statistical Methods:
Objective 1: The first-level individualized design matrices for each participant will be estimated using a general 
linear model. Effects of task (see above contrasts) will be computed on a voxelwise basis for each participant 
in the form of statistical parametric maps of discrete contrasts. Subsequent second level paired t test analyses 
will be performed on the SPM contrast images. Between-subject effects of task and individual inflammatory 
marker concentrations (beginning with CRP) will be determined using regression analysis. For the resting state 
and task based functional connectivity analysis, whole brain, subject-level correlation maps indicating regional 
similarity with the striatal seed region time series will be generated and Fisher transformed to Z-score maps. In 
addition, data reduction strategies will be employed to address inflammatory marker collinearity in analyses 
combining relevant inflammatory markers. To assess significance of correlated activity with each bilateral seed 
region, paired t-tests will be conducted on participants’ Z-score maps, adjusted for multiple comparisons. For 
significant brain regions, descriptive statistics will be used to characterize the mean, standard deviation, and 
standard error of the Z scores. Relevant covariates, which may be associated with alterations in functional 
connectivity or task performance, include body mass index (BMI), age, sex, education, nicotine use, 
antipsychotic dose (as measured by chlorpromazine equivalents), use of other medications, as well as 
depression, and will be included in the analyses as appropriate.
Region of Interest (ROI) seed placement and connectivity analysis: 8 basal ganglia seeds (4 per hemisphere) 
will be used representing regions of the ventral and dorsal striatum as defined in Montreal Neurological 
Institute (MNI) space. In each hemisphere, seeds will be comprised of a spherical mask with a 6 mm radius 
centered on the ROI. The ventral striatum will be defined by coordinates (±14, 5, -4) from a previous fMRI 
study in IFN-alpha-treated subjects demonstrating maximal decreases in response to a hedonic reward task. 
The other 3 regions, ventral rostral putamen (± 20,12, -3), dorsal caudate putamen (± 28, 1, 3), and dorsal 
caudate (±13, 15, 9), will be defined according to Di Martino et al. 2008 and other studies assessing functional 
connectivity with the striatum,117-119 and consistent with identified subdivisions of the striatum. Whole brain, 
subject-level correlation maps indicating regional similarity with the seed region time series will be generated 
and Fisher transformed to Z-score maps. To assess significance of correlated activity with each bilateral seed 
region, I will conduct paired t-tests on participants’ Z-score maps. To correct for multiple comparisons, resulting 
maps will be cluster corrected (p<0.05 whole-brain correction, with a height threshold of p <0.001, 
uncorrected), using SPM12.
Objective 2: Descriptive statistics will be used to characterize the mean, standard deviation, and standard 
error for each of these clinical and behavioral measures. For the EEfRT, proportion of hard-task choices across 
each level of probability as well as the difference between the proportions of hard task choices in low and high 
reward probabilities (effort allocation) will be calculated. Lower proportions of hard task choices indicate 
decreased motivation for monetary rewards. A larger difference in the proportion of hard task choices reflects 
more effort allocation. Regression analyses will be conducted to examine the relationship between task 
performance and concentrations of inflammatory markers (beginning with CRP). Regression analyses 
examining the relationship between changes in functional connectivity (Z scores) obtained using fMRI and 
changes in behavior and neuropsychological performance will also be conducted. In cases where data are not 
normally distributed, we will use standard transformation procedures to achieve normality, and/or use non-
parametric tests of significance. The same covariates and data reduction strategies described above will be 
used in these analyses.
Objective 3: Formal mediation analysis will be conducted to assess whether functional connectivity mediates 

the relationship between inflammation (as measured by inflammatory marker concentrations – beginning with 
CRP) and behavior (clinical ratings and objective measures, as described above). Bootstrapping will be used 
to provide an empirical estimate of the sampling distribution for indirect effects and will be used to generate 
confidence intervals for the purpose of inferential testing. A model of moderated-mediation will also be tested 
to assess whether mediation pathways are influenced by the presence of high vs. low baseline inflammation. 
Path analysis will be implemented using macros developed by Preacher and Hayes 
(http://quantpsy.org/medn.htm), which enable inclusion of covariates as well as possible moderators. 
Optional Study C Aim 1: Relationships between inflammatory and metabolic markers will be examined by 
linear regression at baseline and pre and post-OGTT. Change in these markers pre and post-OGTT will also 
be calculated and compared. Cytokines and their soluble receptors, as well as glucose-related markers at 
baseline, will be combined into a composite score based on the sum of Z-scores for initial analyses, then 
assessed individually by linear regression models with selection including clinical covariates. Covariates such 
as sex, age, race and BMI will be explored as potential confounders or mediators in all analyses.
Optional Study C Aim 2: Targeted FC for each subject and condition will be calculated as the degree of 
correlation in activity between 3mm3 radius spheres placed in four regions of striatum,57, 163  142) that subserve 
reward processing and other goal-directed behaviors such as motor control,117,164 and the vmPFC ROI 
identified as being reward-sensitive in neuroimaging meta-analyses and as used to define vmPFC in our 
previous work (MNI coordinates x=0, y=44, z=-8, cluster size=1408 mm3 and encompassing parts of BA11 and 
ventral BA32 of ACC).57,163,165 Z-scores will be extracted for FC values at baseline and pre and post-OGTT. FC 
will be assessed between bilateral striatal seeds and the vmPFC ROI separately based on our previous work in 
MDD and IFN-a-induced depression,51,57 indicating that effects of inflammation are more pronounced on the 
left side. Linear regression models will be used to independently examine relationships between inflammation 
or metabolic dysfunction (Part C, Aim 1) and reward motor pathways. In our previously published work and 
Preliminary Data, use of inflammatory or metabolic measures as continuous rather than categorical variables 
were more sensitive for detecting associations with corticostriatal connectivity,57 and will be the primary method 
for assessing relationships between inflammation or metabolism (as independent variables) and motivation 
and motor pathways (as dependent variables, including FC and behaviors). Covariates such as sex, age, race 
and BMI will be explored as potential confounders or mediators of relationships between biomarkers, brain and 
behavior.
8. Adverse Event Reporting
Enrolled participants will be monitored closely by study clinicians for any adverse events. If any overt 
study-related adverse events occur, a decision will be made about study continuation. Additionally, a record of 
adverse events for study participants will be reported to the DSMB on a regular basis (see below). Subjects will 
be closely monitored during the course of the study for development of any serious or unexpected adverse 
reactions. Those events meeting Emory IRB criteria for a reportable event will be reported to the IRB or DSMB 
according to standard regulations and procedures. The Emory IRB defines a serious adverse event as: “any 
adverse experiences occurring that result in any of the following outcomes: death, a life-threatening adverse 
experience, inpatient hospitalization or prolongation of existing hospitalization, a persistent or significant 
disability/incapacity, or a congenital anomaly/birth defect. For the purposes of this policy, death is never 
expected.”
9. Data and Safety Monitoring Plan (DSMP)
Adverse events are a normal part of participation in human subjects research and thus will be assessed 
at each study visit.  For this reason, we have elected to utilize the Data Safety Monitoring Board (DSMB) of the 
Department of Psychiatry and Behavioral Sciences as a third-party oversight committee. The DSMB is 
described in detail below. In addition, study clinicians will be available 24 hrs/7 days a week during the period 
between screening and study completion. Should a subject’s psychiatric symptoms appreciably worsen or 
should active suicidal ideation develop, either Dr. 
 will be immediately notified. Drs. 
 are board certified psychiatrists with extensive experience in the treatment of psychiatric 
emergencies. If the assessment in question was done by a clinician other than either of them, one of them will 

immediately contact the subject and will evaluate the need for further psychiatric treatment and will arrange 
psychiatric follow-up. They will evaluate each case individually to make a determination regarding whether the 
subject can remain in the study or whether the subject should be terminated in addition to receiving a mental 
health referral. All adverse events, serious adverse events and unanticipated problems will be captured for 
severity and relatedness to study participation, evaluated by a study physician or designee, and reported to the 
IRB, the DSMB, and the NIH if appropriate.  
Of note, in regards to the Part B optional infliximab study, based on a random internal audit (not for cause) of a 
previous infliximab trial in Dr. 
lab, accolades were given for regulatory compliance and documentation 
of all adverse events as well as timely reporting and processing with the Emory DSMB and IRB.
Composition of the Data Safety Monitoring Board (DSMB)
Frequency of DSMB review for this protocol will follow recommendations from the IRB based on the assessed 
risk status of the study. The DSMB for this study will consist of the Clinical Research Oversight Committee with 
members including 
 
M.S.W.  They have agreed to serve as the external DSMB for investigator initiated clinical trials 
conducted by Emory researchers in the Department of Psychiatry & Behavioral Sciences. If the DSMB requires 
additional specialized expertise to evaluate safety issues related to the performance of this study, a relevant 
specialist will be consulted by the DSMB. 
Procedures and Responsibilities of the DSMB
The DSMB will meet quarterly. This protocol will be submitted to the DSMB simultaneously with the 
initial submission to the Emory IRB. The DSMB will review the research protocol and plans for data and safety 
monitoring. Once per year (or after 6 months if the protocol is considered 'high risk' by the IRB), the DSMB will 
review a report from the study’s data manager that includes: the number of participants who signed consent for 
the study, the number of dropouts, reasons for these dropouts, and any safety concerns, adverse events, an 
up-to-date consent form, and measures taken to protect confidentiality (e.g., data storage, use of coded ID 
numbers, etc.). The DSMB will also review the Principal Investigator’s summary of any new data or evidence 
that might alter the risk/benefit ratio for participating in the study (e.g., newly published studies, etc.). After 
reviewing this information, the DSMB will issue its own report summarizing any serious and unexpected 
adverse events or other unanticipated problems that involve risk to study participants, and whether these 
appear related to the study-based interventions or research assessment protocols. 
There will be regular, ongoing communication between the PI, Emory’s IRB, and the DSMB. The PI will 
take responsibility for submitting reportable serious and unexpected adverse events or other unanticipated 
study problems to Emory’s IRB according to standard regulations. A copy will be sent to the DSMB. Actions 
taken by the IRB in response to adverse event reports will be immediately reported to the DSMB.
The study will not involve a waiver of informed consent in an emergency room setting.
References
1.
Goeree R, Farahati F, Burke N, Blackhouse G, O'Reilly D, Pyne J, Tarride JE. The economic burden of 
schizophrenia in Canada in 2004. Current medical research and opinion. 2005;21:2017-2028.
2.  
McEvoy JP. The costs of schizophrenia. The Journal of clinical psychiatry. 2007;68 Suppl 14:4-7.
3.  
Kennedy JL, Altar CA, Taylor DL, Degtiar I, Hornberger JC. The social and economic burden of 
treatment-resistant schizophrenia: a systematic literature review. International clinical 
psychopharmacology. 2014;29:63-76.
4.  
Suzuki T, Remington G, Mulsant BH, Uchida H, Rajji TK, Graff-Guerrero A, Mimura M, Mamo DC. 
Defining treatment-resistant schizophrenia and response to antipsychotics: a review and 
recommendation. Psychiatry research. 2012;197:1-6.
5.
Kooyman I, Dean K, Harvey S, Walsh E. Outcomes of public concern in schizophrenia. The British 
journal of psychiatry Supplement. 2007;50:s29-36.
6. 
Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990-2020: Global 
Burden of Disease Study. Lancet (London, England). 1997;349:1498-1504.

7.  
Foster A, Gable J, Buckley J. Homelessness in schizophrenia. The Psychiatric clinics of North America. 
2012;35:717-734.
8.  
Marwaha S, Johnson S. Schizophrenia and employment - a review. Social psychiatry and psychiatric 
epidemiology. 2004;39:337-349.
9.  
Laursen TM, Nordentoft M, Mortensen PB. Excess early mortality in schizophrenia. Annual review of 
clinical psychology. 2014;10:425-448.
10.  
Fervaha G, Foussias G, Agid O, Remington G. Motivational and neurocognitive deficits are central to 
the prediction of longitudinal functional outcome in schizophrenia. Acta psychiatrica Scandinavica. 
2014;130:290-299.
11.  
Green MF, Llerena K, Kern RS. The "Right Stuff" Revisited: What Have We Learned About the 
Determinants of Daily Functioning in Schizophrenia? Schizophrenia bulletin. 2015;41:781-785.
12.  
Harvey PD. Assessment of everyday functioning in schizophrenia: implications for treatments aimed at 
negative symptoms. Schizophrenia research. 2013;150:353-355.
13.  
Leifker FR, Bowie CR, Harvey PD. Determinants of everyday outcomes in schizophrenia: the influences 
of cognitive impairment, functional capacity, and symptoms. Schizophrenia research. 2009;115:82-87.
14.  
Carbon M, Correll CU. Thinking and acting beyond the positive: the role of the cognitive and negative 
symptoms in schizophrenia. CNS spectrums. 2014;19 Suppl 1:38-52; quiz 35-37, 53.
15.  
Davis MC, Horan WP, Marder SR. Psychopharmacology of the negative symptoms: current status and 
prospects for progress. European neuropsychopharmacology : the journal of the European College of 
Neuropsychopharmacology. 2014;24:788-799.
16.  
Harvey PD, McClure MM. Pharmacological approaches to the management of cognitive dysfunction in 
schizophrenia. Drugs. 2006;66:1465-1473.
17.
Blanchard JJ, Cohen AS. The structure of negative symptoms within schizophrenia: implications for 
assessment. Schizophrenia bulletin. 2006;32:238-245.
18.  
Horan WP, Kring AM, Gur RE, Reise SP, Blanchard JJ. Development and psychometric validation of 
the Clinical Assessment Interview for Negative Symptoms (CAINS). Schizophrenia research. 
2011;132:140-145.
19.  
Strauss GP, Harrow M, Grossman LS, Rosen C. Periods of recovery in deficit syndrome schizophrenia: 
a 20-year multi-follow-up longitudinal study. Schizophrenia bulletin. 2010;36:788-799.
20.  
Strauss GP, Hong LE, Gold JM, Buchanan RW, McMahon RP, Keller WR, Fischer BA, Catalano LT, 
Culbreth AJ, Carpenter WT, Kirkpatrick B. Factor structure of the Brief Negative Symptom Scale. 
Schizophrenia research. 2012;142:96-98.
21.  
Strauss GP, Horan WP, Kirkpatrick B, Fischer BA, Keller WR, Miski P, Buchanan RW, Green MF, 
Carpenter WT, Jr. Deconstructing negative symptoms of schizophrenia: avolition-apathy and 
diminished expression clusters predict clinical presentation and functional outcome. Journal of 
psychiatric research. 2013;47:783-790.
22.  
Strauss GP, Waltz JA, Gold JM. A review of reward processing and motivational impairment in 
schizophrenia. Schizophrenia bulletin. 2014;40 Suppl 2:S107-116.
23.  
Juckel G, Friedel E, Koslowski M, Witthaus H, Ozgurdal S, Gudlowski Y, Knutson B, Wrase J, Brune M, 
Heinz A, Schlagenhauf F. Ventral striatal activation during reward processing in subjects with ultra-high 
risk for schizophrenia. Neuropsychobiology. 2012;66:50-56.
24.  
Juckel G, Schlagenhauf F, Koslowski M, Filonov D, Wustenberg T, Villringer A, Knutson B, Kienast T, 
Gallinat J, Wrase J, Heinz A. Dysfunction of ventral striatal reward prediction in schizophrenic patients 
treated with typical, not atypical, neuroleptics. Psychopharmacology. 2006;187:222-228.
25.  
Nielsen MO, Rostrup E, Wulff S, Bak N, Lublin H, Kapur S, Glenthoj B. Alterations of the brain reward 
system in antipsychotic naive schizophrenia patients. Biological psychiatry. 2012;71:898-905.
26.
Juckel G, Schlagenhauf F, Koslowski M, Wustenberg T, Villringer A, Knutson B, Wrase J, Heinz A. 
Dysfunction of ventral striatal reward prediction in schizophrenia. NeuroImage. 2006;29:409-416.
27.
Reiss JP, Campbell DW, Leslie WD, Paulus MP, Ryner LN, Polimeni JO, Foot BJ, Sareen J. Deficit in 
schizophrenia to recruit the striatum in implicit learning: a functional magnetic resonance imaging 
investigation. Schizophrenia research. 2006;87:127-137.
28.  
Weickert TW, Goldberg TE, Callicott JH, Chen Q, Apud JA, Das S, Zoltick BJ, Egan MF, Meeter M, 
Myers C, Gluck MA, Weinberger DR, Mattay VS. Neural correlates of probabilistic category learning in 
patients with schizophrenia. The Journal of neuroscience : the official journal of the Society for 
Neuroscience. 2009;29:1244-1254.

29.  
Morris RW, Vercammen A, Lenroot R, Moore L, Langton JM, Short B, Kulkarni J, Curtis J, O'Donnell M, 
Weickert CS, Weickert TW. Disambiguating ventral striatum fMRI-related BOLD signal during reward 
prediction in schizophrenia. Molecular psychiatry. 2012;17:235, 280-239.
30.  
Murray GK, Corlett PR, Clark L, Pessiglione M, Blackwell AD, Honey G, Jones PB, Bullmore ET, 
Robbins TW, Fletcher PC. Substantia nigra/ventral tegmental reward prediction error disruption in 
psychosis. Molecular psychiatry. 2008;13:239, 267-276.
31.  
Schlagenhauf F, Sterzer P, Schmack K, Ballmaier M, Rapp M, Wrase J, Juckel G, Gallinat J, Heinz A. 
Reward feedback alterations in unmedicated schizophrenia patients: relevance for delusions. Biological 
psychiatry. 2009;65:1032-1039.
32.  
Segarra N, Metastasio A. Abnormal Frontostriatal Activity During Unexpected Reward Receipt in 
Depression and Schizophrenia: Relationship to Anhedonia. 2015.
33.  
Simon JJ, Biller A, Walther S, Roesch-Ely D, Stippich C, Weisbrod M, Kaiser S. Neural correlates of 
reward processing in schizophrenia--relationship to apathy and depression. Schizophrenia research. 
2010;118:154-161.
34.  
Waltz JA, Schweitzer JB, Ross TJ, Kurup PK, Salmeron BJ, Rose EJ, Gold JM, Stein EA. Abnormal 
responses to monetary outcomes in cortex, but not in the basal ganglia, in schizophrenia. 
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology. 
2010;35:2427-2439.
35.
Treadway MT, Peterman JS, Zald DH, Park S. Impaired effort allocation in patients with schizophrenia. 
Schizophrenia research. 2015;161:382-385.
36.
DM, Treadway MT, Schoen N. Effort, anhedonia, and function in schizophrenia: reduced effort 
allocation predicts amotivation and functional impairment. Journal of abnormal psychology. 
2014;123:387-397.
37.  
Docx L, de la Asuncion J, Sabbe B, Hoste L, Baeten R, Warnaerts N, Morrens M. Effort discounting 
and its association with negative symptoms in schizophrenia. Cognitive neuropsychiatry. 2015;20:172-
185.
38.  
Fervaha G, Duncan M, Foussias G, Agid O, Faulkner GE, Remington G. Effort-based decision making 
as an objective paradigm for the assessment of motivational deficits in schizophrenia. Schizophrenia 
research. 2015;168:483-490.
39.  
Fervaha G, Graff-Guerrero A, Zakzanis KK, Foussias G, Agid O, Remington G. Incentive motivation 
deficits in schizophrenia reflect effort computation impairments during cost-benefit decision-making. 
Journal of psychiatric research. 2013;47:1590-1596.
40.  
Gold JM, Strauss GP, Waltz JA, Robinson BM, Brown JK, Frank MJ. Negative symptoms of 
schizophrenia are associated with abnormal effort-cost computations. Biological psychiatry. 
2013;74:130-136.
41.  
Hartmann MN, Hager OM, Reimann AV, Chumbley JR, Kirschner M, Seifritz E, Tobler PN, Kaiser S. 
Apathy but not diminished expression in schizophrenia is associated with discounting of monetary 
rewards by physical effort. Schizophrenia bulletin. 2015;41:503-512.
42.  
McCarthy JM, Treadway MT, Bennett ME, Blanchard JJ. Inefficient effort allocation and negative 
symptoms in individuals with schizophrenia. Schizophrenia research. 2016;170:278-284.
43.  
Reddy LF, Horan WP, Barch DM, Buchanan RW, Dunayevich E, Gold JM, Lyons N, Marder SR, 
Treadway MT, Wynn JK, Young JW, Green MF. Effort-Based Decision-Making Paradigms for Clinical 
Trials in Schizophrenia: Part 1-Psychometric Characteristics of 5 Paradigms. Schizophrenia bulletin. 
2015;41:1045-1054.
44.  
Strauss GP, Whearty KM, Morra LF, Sullivan SK, Ossenfort KL, Frost KH. Avolition in schizophrenia is 
associated with reduced willingness to expend effort for reward on a Progressive Ratio task. 
Schizophrenia research. 2016;170:198-204.
45.  
Wang J, Huang J, Yang XH, Lui SS, Cheung EF, Chan RC. Anhedonia in schizophrenia: Deficits in 
both motivation and hedonic capacity. Schizophrenia research. 2015;168:465-474.
46.  
Wolf DH, Satterthwaite TD, Kantrowitz JJ, Katchmar N, Vandekar L, Elliott MA, Ruparel K. Amotivation 
in schizophrenia: integrated assessment with behavioral, clinical, and imaging measures. 
Schizophrenia bulletin. 2014;40:1328-1337.
47.  
McClure SM, York MK, Montague PR. The neural substrates of reward processing in humans: the 
modern role of FMRI. The Neuroscientist : a review journal bringing neurobiology, neurology and 
psychiatry. 2004;10:260-268.

48.  
Salamone JD, Correa M, Farrar A, Mingote SM. Effort-related functions of nucleus accumbens 
dopamine and associated forebrain circuits. Psychopharmacology. 2007;191:461-482.
49.  
Treadway MT, Zald DH. Parsing Anhedonia: Translational Models of Reward-Processing Deficits in 
Psychopathology. Current directions in psychological science. 2013;22:244-249.
50.  
Horan WP, Reddy LF, Barch DM, Buchanan RW, Dunayevich E, Gold JM, Marder SR, Wynn JK, 
Young JW, Green MF. Effort-Based Decision-Making Paradigms for Clinical Trials in Schizophrenia: 
Part 2-External Validity and Correlates. Schizophrenia bulletin. 2015;41:1055-1065.
51.
Capuron L, Pagnoni G, Drake DF, Woolwine BJ, Spivey JR, Crowe RJ, Votaw JR, Goodman MM, Miller
AH. Dopaminergic mechanisms of reduced basal ganglia responses to hedonic reward during 
interferon alfa administration. Archives of general psychiatry. 2012;69:1044-1053.
52.
Brydon L, Harrison NA, Walker C, Steptoe A, Critchley HD. Peripheral inflammation is associated with 
altered substantia nigra activity and psychomotor slowing in humans. Biological psychiatry. 
2008;63:1022-1029.
53.  
Eisenberger NI, Berkman ET, Inagaki TK, Rameson LT, Mashal NM, Irwin MR. Inflammation-induced 
anhedonia: endotoxin reduces ventral striatum responses to reward. Biological psychiatry. 
2010;68:748-754.
54.  
Harrison NA, Voon V, Cercignani M, Cooper EA, Pessiglione M, Critchley HD. A Neurocomputational 
Account of How Inflammation Enhances Sensitivity to Punishments Versus Rewards. Biological 
psychiatry. 2015.
55.  
Llerena K, Park SG, McCarthy JM, Couture SM, Bennett ME, Blanchard JJ. The Motivation and 
Pleasure Scale–Self-Report (MAP-SR): Reliability and validity of a self-report measure of negative 
symptoms. Comprehensive Psychiatry. 2013; 54:568-574.
56.  
Salamone JD, Cousins MS, Bucher S. Anhedonia or anergia? Effects of haloperidol and nucleus 
accumbens dopamine depletion on instrumental response selection in a T-maze cost/benefit 
procedure. Behavioural brain research. 1994;65:221-229.
57.  
Treadway MT. The Neurobiology of Motivational Deficits in Depression-An Update on Candidate 
Pathomechanisms. Current topics in behavioral neurosciences. 2015.
58.  
Vichaya EG, Hunt SC, Dantzer R. Lipopolysaccharide reduces incentive motivation while boosting 
preference for high reward in mice. Neuropsychopharmacology : official publication of the American 
College of Neuropsychopharmacology. 2014;39:2884-2890.
59.
Felger JC, Li Z, Haroon E. Inflammation is associated with decreased functional connectivity within 
corticostriatal reward circuitry in depression. Molecular Psychiatry. 2015.
60. 
Thrivedi MH, Rush AJ, Ibrahim HM, Carmody TJ, Biggs MM, Suppes T, Crismon ML, Shores-Wilson K, 
Toprac MG, Dennehy EB, Witte B, Kashner TM. The Inventory of Depressive Symptomatology, 
Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive 
Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with 
mood disorders: a psychometric evaluation. Psychol Med. 2004; 34(1):73-82.
61.  
Goldsmith DR, Rapaport MH, Miller BJ. A meta-analysis of blood cytokine network alterations in 
psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression. Molecular 
psychiatry. 2016.
62.  
Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, Kamitaki N, Tooley K, Presumey J, Baum M, 
Van Doren V, Genovese G, Rose SA, Handsaker RE, Daly MJ, Carroll MC, Stevens B, McCarroll SA. 
Schizophrenia risk from complex variation of complement component 4. Nature. 2016.
63.  
Asevedo E, Rizzo LB, Gadelha A, Mansur RB, Ota VK, Berberian AA, Scarpato BS, Teixeira AL, 
Bressan RA, Brietzke E. Peripheral interleukin-2 level is associated with negative symptoms and 
cognitive performance in schizophrenia. Physiology & behavior. 2014;129:194-198.
64.  
El Kissi Y, Samoud S, Mtiraoui A, Letaief L, Hannachi N, Ayachi M, Ali BB, Boukadida J. Increased 
Interleukin-17 and decreased BAFF serum levels in drug-free acute schizophrenia. Psychiatry 
research. 2015;225:58-63.
65.  
Garcia-Rizo C, Fernandez-Egea E, Oliveira C, Justicia A, Bernardo M, Kirkpatrick B. Inflammatory 
markers in antipsychotic-naive patients with nonaffective psychosis and deficit vs. nondeficit features. 
Psychiatry research. 2012;198:212-215.
66.  
Liu H, Kang Y, Liang J, Li C, Xiu M, Chen D, Yang F, Wang F, Wu G, Haile CN, Kosten TA, Kosten TR, 
Zhang XY. Lower serum interleukin-2 levels in schizophrenic patients with tardive dyskinesia. 
Psychiatry research. 2012;198:329-331.

67.  
Noto C, Maes M, Ota VK, Teixeira AL, Bressan RA, Gadelha A, Brietzke E. High predictive value of 
immune-inflammatory biomarkers for schizophrenia diagnosis and association with treatment 
resistance. The world journal of biological psychiatry : the official journal of the World Federation of 
Societies of Biological Psychiatry. 2015:1-8.
68.  
Stojanovic A, Martorell L, Montalvo I, Ortega L, Monseny R, Vilella E, Labad J. Increased serum 
interleukin-6 levels in early stages of psychosis: associations with at-risk mental states and the severity 
of psychotic symptoms. Psychoneuroendocrinology. 2014;41:23-32.
69.  
Xiu MH, Yang GG, Tan YL, Chen da C, Tan SP, Wang ZR, Yang FD, Okusaga O, Soares JC, Zhang 
XY. Decreased interleukin-10 serum levels in first-episode drug-naive schizophrenia: relationship to 
psychopathology. Schizophrenia research. 2014;156:9-14.
70.  
Brown AS, Derkits EJ. Prenatal infection and schizophrenia: a review of epidemiologic and translational 
studies. The American journal of psychiatry. 2010;167:261-280.
71.  
Khandaker GM, Zimbron J, Dalman C, Lewis G, Jones PB. Childhood infection and adult 
schizophrenia: a meta-analysis of population-based studies. Schizophrenia research. 2012;139:161-
168.
72.  
Khandaker GM, Zimbron J, Lewis G, Jones PB. Prenatal maternal infection, neurodevelopment and 
adult schizophrenia: a systematic review of population-based studies. Psychological medicine. 
2013;43:239-257.
73.  
Khandaker GM, Zammit S, Lewis G, Jones PB. A population-based study of atopic disorders and 
inflammatory markers in childhood before psychotic experiences in adolescence. Schizophrenia 
research. 2014;152:139-145.
74.  
Benros ME, Nielsen PR, Nordentoft M, Eaton WW, Dalton SO, Mortensen PB. Autoimmune diseases 
and severe infections as risk factors for schizophrenia: a 30-year population-based register study. The 
American journal of psychiatry. 2011;168:1303-1310.
75.  
Eaton WW, Byrne M, Ewald H, Mors O, Chen CY, Agerbo E, Mortensen PB. Association of 
schizophrenia and autoimmune diseases: linkage of Danish national registers. The American journal of 
psychiatry. 2006;163:521-528.
76.  
Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421-427.
77.  
Andreassen OA, Harbo HF, Wang Y, Thompson WK, Schork AJ, Mattingsdal M, Zuber V, Bettella F, 
Ripke S, Kelsoe JR, Kendler KS, O'Donovan MC, Sklar P, McEvoy LK, Desikan RS, Lie BA, Djurovic S, 
Dale AM. Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: 
differential involvement of immune-related gene loci. Molecular psychiatry. 2015;20:207-214.
78.  
Shi J, Levinson DF, Duan J, Sanders AR, Zheng Y, Pe'er I, Dudbridge F, Holmans PA, Whittemore AS, 
Mowry BJ, Olincy A, Amin F, Cloninger CR, Silverman JM, Buccola NG, Byerley WF, Black DW, Crowe 
RR, Oksenberg JR, Mirel DB, Kendler KS, Freedman R, Gejman PV. Common variants on 
chromosome 6p22.1 are associated with schizophrenia. Nature. 2009;460:753-757.
79.  
Stefansson H, Ophoff RA, Steinberg S, Andreassen OA, Cichon S, Rujescu D, Werge T, Pietilainen 
OP, Mors O, Mortensen PB, Sigurdsson E, Gustafsson O, Nyegaard M, Tuulio-Henriksson A, Ingason 
A, Hansen T, Suvisaari J, Lonnqvist J, Paunio T, Borglum AD, Hartmann A, Fink-Jensen A, Nordentoft 
M, Hougaard D, Norgaard-Pedersen B, Bottcher Y, Olesen J, Breuer R, Moller HJ, Giegling I, 
Rasmussen HB, Timm S, Mattheisen M, Bitter I, Rethelyi JM, Magnusdottir BB, Sigmundsson T, 
Olason P, Masson G, Gulcher JR, Haraldsson M, Fossdal R, Thorgeirsson TE, Thorsteinsdottir U, 
Ruggeri M, Tosato S, Franke B, Strengman E, Kiemeney LA, Melle I, Djurovic S, Abramova L, Kaleda 
V, Sanjuan J, de Frutos R, Bramon E, Vassos E, Fraser G, Ettinger U, Picchioni M, Walker N, 
Toulopoulou T, Need AC, Ge D, Yoon JL, Shianna KV, Freimer NB, Cantor RM, Murray R, Kong A, 
Golimbet V, Carracedo A, Arango C, Costas J, Jonsson EG, Terenius L, Agartz I, Petursson H, Nothen 
MM, Rietschel M, Matthews PM, Muglia P, Peltonen L, St Clair D, Goldstein DB, Stefansson K, Collier 
DA. Common variants conferring risk of schizophrenia. Nature. 2009;460:744-747.
80. 
Bloomfield PS, Selvaraj S, Veronese M, Rizzo G, Bertoldo A, Owen DR, Bloomfield MA, Bonoldi I, Kalk 
N, Turkheimer F, McGuire P, de Paola V, Howes OD. Microglial Activity in People at Ultra High Risk of 
Psychosis and in Schizophrenia: An [(11)C]PBR28 PET Brain Imaging Study. The American journal of 
psychiatry. 2016;173:44-52.
81.  
van Berckel BN, Bossong MG, Boellaard R, Kloet R, Schuitemaker A, Caspers E, Luurtsema G, 
Windhorst AD, Cahn W, Lammertsma AA, Kahn RS. Microglia activation in recent-onset schizophrenia: 
a quantitative (R)-[11C]PK11195 positron emission tomography study. Biological psychiatry. 
2008;64:820-822.

82.  
Doorduin J, de Vries EF, Willemsen AT, de Groot JC, Dierckx RA, Klein HC. Neuroinflammation in 
schizophrenia-related psychosis: a PET study. Journal of nuclear medicine : official publication, Society 
of Nuclear Medicine. 2009;50:1801-1807.
83.  
Kenk M, Selvanathan T, Rao N, Suridjan I, Rusjan P, Remington G, Meyer JH, Wilson AA, Houle S, 
Mizrahi R. Imaging neuroinflammation in gray and white matter in schizophrenia: an in-vivo PET study 
with [18F]-FEPPA. Schizophrenia bulletin. 2015;41:85-93.
84.  
Fond G, Hamdani N, Kapczinski F, Boukouaci W, Drancourt N, Dargel A, Oliveira J, Le Guen E, 
Marlinge E, Tamouza R, Leboyer M. Effectiveness and tolerance of anti-inflammatory drugs' add-on 
therapy in major mental disorders: a systematic qualitative review. Acta psychiatrica Scandinavica. 
2014;129:163-179.
85.
Millan MJ, Goodwin GM, Meyer-Lindenberg A, Ove Ogren S. Learning from the past and looking to the 
future: Emerging perspectives for improving the treatment of psychiatric disorders. European 
neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology. 
2015;25:599-656.
86.  
Tsapakis EM, Dimopoulou T, Tarazi FI. Clinical management of negative symptoms of schizophrenia: 
An update. Pharmacology & therapeutics. 2015;153:135-147.
87.
Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO, 3rd, Criqui M, Fadl YY, Fortmann
SP, Hong Y, Myers GL, Rifai N, Smith SC, Jr., Taubert K, Tracy RP, Vinicor F. Markers of inflammation
and cardiovascular disease: application to clinical and public health practice: A statement for healthcare
professionals from the Centers for Disease Control and Prevention and the American Heart
Association. Circulation. 2003;107:499-511.
88.  
Cheniaux E, Landeira-Fernandez J, Lessa Telles L, Lessa JL, Dias A, Duncan T, Versiani M. Does 
schizoaffective disorder really exist? A systematic review of the studies that compared schizoaffective 
disorder with schizophrenia or mood disorders. Journal of affective disorders. 2008;106:209-217.
89.  
Malaspina D, Owen MJ, Heckers S, Tandon R, Bustillo J, Schultz S, Barch DM, Gaebel W, Gur RE, 
Tsuang M, Van Os J, Carpenter W. Schizoaffective Disorder in the DSM-5. Schizophrenia research. 
2013;150:21-25.
90.  
Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar 
GC. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a 
structured diagnostic psychiatric interview for DSM-V and ICD-10. The Journal of clinical psychiatry. 
1998;59 Suppl 20:22-33;quiz 34-57.
91.  
Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive 
state of patients for the clinician. Journal of psychiatric research. 1975;12:189-198.
92.  
Ganguli R, Brar JS, Vemulapalli H, Jafar H, Ahuja R, Sharma S, Wirth RJ. Mini-Mental State 
Examination (MMSE) performance of partially remitted community-dwelling patients with schizophrenia. 
Schizophrenia research. 1998;33:45-52.
93.
Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale (PANSS) for schizophrenia. 
Schizophrenia bulletin. 1987;13:261-276.
94.
Kirkpatrick B, Fenton WS, Carpenter WT, Marder SR. The NIMH-MATRICS consensus statement on 
negative symptoms. Schizophrenia bulletin. 2006;32:214-219.  
95.
Kirkpatrick B, Strauss GP, Nguyen L, Fischer BA, Daniel DG, Cienfuegos A, Marder SR. The brief 
negative symptom scale: psychometric properties. Schizophrenia bulletin 2011;37:300-305
96.
Wilkinson GS. WRAT3: Wide Range Achievement Test Administration Manual. 1993; Wide Range Inc.
97. 
Gladsjo JA, Heaton RK, Palmer BW, Taylor MJ, Jeste DV. Use of oral reading to estimate premorbid 
intellectual and neuropsychological functioning. Journal of the international neuropsychological society 
1999;5:247-254.
98.
Keefe RE, Eesley CE, Poe MP. Defining a cognitive function decrement in schizophrenia. Biological 
psychiatry 2005;57:688-691.
99.  
Rush AJ, Giles DE, Schlesser MA, Fulton CL, Weissenburger J, Burns C. The Inventory for Depressive 
Symptomatology (IDS): preliminary findings. Psychiatry research. 1986;18:65-87.
100.  Choi J, Choi KH, Felice Reddy L, Fiszdon JM. Measuring motivation in schizophrenia: is a general state 
of motivation necessary for task-specific motivation? Schizophrenia research. 2014;153:209-213.
101.  Choi J, Mogami T, Medalia A. Intrinsic motivation inventory: an adapted measure for schizophrenia 
research. Schizophrenia bulletin. 2010;36:966-976.

102.  Plant RW, Ryan RM. Intrinsic motivation and the effects of self-consciousness, self-awareness, and 
ego-involvement: An investigation of internally controlling styles. Journal of Personality. 1985;53:435-
449.
103.
Üstün, TB. Measuring health and disability: manual for WHO Disability Assessment Schedule 
WHODAS 2.0. 2010. Geneva: World Health Organization.
104.  Aparicio P, Diedrichsen J, Ivry RB. Effects of focal basal ganglia lesions on timing and force control. 
Brain and cognition. 2005;58:62-74.
105.
Majer M, Welberg LA, Capuron L, Pagnoni G, Raison CL, Miller AH. IFN-alpha-induced motor slowing 
is associated with increased depression and fatigue in patients with chronic hepatitis C. Brain, behavior, 
and immunity. 2008;22:870-880.
106.  Spreen OSE: A Compendium of Neuropsychological Tests. New York, Oxford University Press; 1991.
107.  Naismith S, Hickie I, Ward PB, Turner K, Scott E, Little C, Mitchell P, Wilhelm K, Parker G. Caudate 
nucleus volumes and genetic determinants of homocysteine metabolism in the prediction of 
psychomotor speed in older persons with depression. The American journal of psychiatry. 
2002;159:2096-2098.
108.  Joy S, Fein D, Kaplan E. Decoding digit symbol: speed, memory, and visual scanning. Assessment. 
2003;10:56-65.
109.
Treadway MT, Buckholtz JW, Schwartzman AN, Lambert WE, Zald DH. Worth the 'EEfRT'? The effort 
expenditure for rewards task as an objective measure of motivation and anhedonia. PloS one. 
2009;4:e6598.
110.  Knutson B, Fong GW, Adams CM, Varner JL, Hommer D. Dissociation of reward anticipation and 
outcome with event-related fMRI. Neuroreport. 2001;12:3683-3687.
111.  Knutson B, Bhanji JP, Cooney RE, Atlas LY, Gotlib IH. Neural responses to monetary incentives in 
major depression. Biological psychiatry. 2008;63:686-692.
112.  Pizzagalli DA, Holmes AJ, Dillon DG, Goetz EL, Birk JL, Bogdan R, Dougherty DD, Iosifescu DV, 
Rauch SL, Fava M. Reduced caudate and nucleus accumbens response to rewards in unmedicated 
individuals with major depressive disorder. The American journal of psychiatry. 2009;166:702-710.
113.  Knutson B, Cooper JC. Functional magnetic resonance imaging of reward prediction. Current opinion in 
neurology. 2005;18:411-417.
114.  Knutson B, Fong GW, Bennett SM, Adams CM, Hommer D. A region of mesial prefrontal cortex tracks 
monetarily rewarding outcomes: characterization with rapid event-related fMRI. NeuroImage. 
2003;18:263-272.
115.  Samanez-Larkin GR, Gibbs SE, Khanna K, Nielsen L, Carstensen LL, Knutson B. Anticipation of 
monetary gain but not loss in healthy older adults. Nature neuroscience. 2007;10:787-791.
116.
Rothpearl AB, Mohs RC, Davis KL. Statistical power in biological psychiatry. Psychiatry research. 
1981;5:257-266.
117.
Di Martino A, Scheres A, Margulies DS, Kelly AM, Uddin LQ, Shehzad Z, Biswal B, Walters JR,
Castellanos FX, Milham MP. Functional connectivity of human striatum: a resting state FMRI study.
Cerebral cortex (New York, NY : 1991). 2008;18:2735-2747.
118. 
Furman DJ, Hamilton JP, Gotlib IH. Frontostriatal functional connectivity in major depressive disorder.
Biology of mood & anxiety disorders. 2011;1:11.
119.
Kwak Y, Peltier S, Bohnen NI, Muller ML, Dayalu P, Seidler RD. Altered resting state cortico-striatal
connectivity in mild to moderate stage Parkinson's disease. Frontiers in systems neuroscience.
2010;4:143.
120.
Preacher KJ, Hayes AG. Asymptomatic and resampling strategies for assessing and comparing indirect 
effects in multiple mediator models. Behavior research methods. 2008;40:879-891. 
121.
Bernstein DP, Stein JA, Newcomb MD, Walker E, Pogge D, Ahluvalia T, Stokes J, Handelsman L, 
Medrano M, Desmond D, Zule W. Development and validation of a brief screening version of the 
Childhood Questionnaire. Child abuse and neglect. 2003;27:169-190.
122. 
Bradley RG, Binder EB, Epstein MP, Tang Y, Nair HP, Liu W, Gillespie CF, Berg T, Evces M, Newport 
DJ, Stowe ZN, Heim CM, Nemeroff CB, Schwartz A, Cubells JF, Ressler KJ. Influence of child abuse 
on adult depression: moderation by the corticotropin-releasing hormone receptor gene. Archives of 
general psychiatry. 2008;65:190-200.
123.
Harrison NA, Brydon L, Walker C, Gray MA, Steptoe A, Critchley HD. Inflammation causes mood 
changes through alterations in subgenual cingulate activity and mesolimbic connectivity. Biological 
psychiatry. 2009; 66: 407–414.

124. 
Capuron L, Gumnick JF, Musselman DL, Lawson DH, Reemsnyder A, Nemeroff CB, Miller AH. 
Neurobehavioral effects of interferon-alpha in cancer patients: phenomenology and paroxetine 
responsiveness of symptom dimensions. Neuropsychopharmacology. 2002; 26:643–652.
125.
Musselman DL, Miller AH, Porter MR, Manatunga A., Gao F, Penna S, Pearce BD, Landry J, Glover S., 
McDaniel JS, Nemeroff CB. Higher than normal plasma interleukin-6 concentrations in cancer patients 
with depression: preliminary findings. American journal of psychiatry. 2001; 158:1252–1257.
126.
Goldsmith DR, Haroon E, Woolwine BJ, Jung MY, Wommack EC, Harvey PD, Treadway MT, Felger 
JC, Miller AH. Inflammatory markers are associated with decreased psychomotor speed in patients with 
major depressive disorder. Brain behavioral immunity. 2016; 56: 281-288.
127.
Endicott J, Nee J, Harrison W, Blumenthal R. Quality of Life Enjoyment and Satisfaction Questionnaire 
–A New Measure. Psychopharmacological Bulletin. 1993; 29(2): 321-326.
128.
Tang H., et al. Zika virus infects human cortical neural progenitors and attenuates their growth. Cell 
Stem Cell. 2016; 18(5): 587-590.
129.
Wen Z., et al. Synaptic dysregulation in a human iPS cell model of mental disorders. Nature. 2014; 
515(7527): 414-418.
130.
Wen Z., Christian KM, Song H, Ming GL. Curr Opin Neurobiol. 2016;36: 118-127.
131.
Raison, CL, Rutherford RE, Woolwine BJ, Shuo C, Schettler P, Drake DF, Haroon E, Miller AH. A 
randomized controlled trial of the tumor necrosis factor antagonist infliximab for treatment-resistant depression: 
the role of baseline inflammatory biomarkers. JAMA Psychiatry. 2013;70(1):31-41.
132.
Mehta D, Raison CL, Woolwine BJ, Haroon E, Binder EB, Miller AH, Felger JC. Transcriptional 
signatures related to glucose and lipid metabolism predict treatment response to the tumor necrosis 
factor antagonist infliximab in patients with treatment-resistant depression. Brain Behav Immun. 
2013;31:205-15.
133.
Rutgeerts P, Feagan BG, Lichtenstein GR, Mayer LF, Schreiber S, Colombel JF, Rachmilewitz D, Wolf 
DC, Olson A, Bao W, Hanauer SB. Comparison of scheduled and episodic treatment strategies of 
infliximab in Crohn’s disease. Gastroenterology. 2004;126(2):402-13.
134.
Goldsmith DR, Haroon E, Miller AH, Strauss GP, Buckley PF, Miller BJ. TNF- and IL-6 are associated 
with the deficit syndrome and negative symptoms in patients with chronic schizophrenia. Schizophrenia 
Research. 2018; epub ahead of print.
135.
Keystone EC. Does anti-tumor necrosis factor-alpha therapy affect risk of serious infection and cancer 
in patients with rheumatoid arthritis: a review of longterm data. The Journal of rheumatology.
2011;38(8):1552-62.
136.
Mariette X, Matucci-Cerinic M, Pavelka K, Taylor P, van Vollenhoven R, Heatley R, Walsh C, Lawson 
R, Reynolds A, Emery P. Malignancies associated with tumour necrosis factor inhibitors in registries
and prospective observational studies: a systematic review and meta-analysis. Ann Rheum Dis.
2011;70(11):1895-904.
137.
Kirkpatrick B, Strauss GP, Nguyen L, Fischer BA, Daniel DG, Cienfuegos A, Marder SR. The Brief 
Negative Symptom Scale: Psychometric Properties. Schizophrenia Bulletin. 2011;37:300-305.
138.
Mane A, Garcia-Rizo C, Garcia-Portilla MP, Berge D, Sugranyes G, Garcia-Alvarez L, Bernardo M, 
Bobes J, Fernandez-Egea E. Spanish adaptation and validation of the Brief Negative Symptom Scale. 
Comprehensive Psychiatry. 2014;55:1726-1729.
139.
Mucci A, Galderisi S, Merlotti E, Rossi A, Rocca P, Bucci P, Piegari G, Chieffi M, Vignapiano A, Maj M. 
The Brief Negative Symptom Scale (BNSS): Independent validation in a large sample of Italian patients 
with schizophrenia. European Psychiatry. 2015;30:641-647.
140.
Nazli IP, Ergul C, Aydemir O, Chandhoke S, Ucok A, Gonul AS. Validation of Turkish version of brief 
negative symptom scale. International Journal of Psychiatry in Clinical Practice. 2016;20:265-271.
141.
Strauss GP, Vertinski M, Vogel SJ, Ringdahl EN, Allen DN. Negative symptoms in bipolar disorder and 
schizophrenia: A psychometric evaluation of the brief negative symptom scale across diagnostic 
categories. Schizophrenia Research. 2016;170:285-289.
142.
Park, S. H., Yoon, J. S., Won, K. C., & Lee, H. W. (2012). Usefulness of glycated hemoglobin 
as diagnostic criteria for metabolic syndrome. Journal of Korean medical science, 27(9), 1057-
1061.
143.  Perry BI, McIntosh G, Weich S, Singh S, Rees K. The association between first-episode psychosis and 
abnormal glycaemic control: systematic review and meta-analysis. The lancet Psychiatry. 2016;3:1049-
1058.
144.  Pillinger T, Beck K, Gobjila C, Donocik JG, Jauhar S, Howes OD. Impaired Glucose Homeostasis in

First-Episode Schizophrenia: A Systematic Review and Meta-analysis. JAMA psychiatry. 2017;74:261-
269.
145.     Manu P, Dima L, Shulman M, Vancampfort D, De Hert M, Correll CU. Weight gain and obesity in 
schizophrenia: epidemiology, pathobiology, and management. Acta psychiatrica Scandinavica. 
2015;132:97-108.
146.  Borst SE. The role of TNF-alpha in insulin resistance. Endocrine. 2004;23:177-182.
147.  Hotamisligil GS, Murray DL, Choy LN, Spiegelman BM. Tumor necrosis factor alpha inhibits signaling
from the insulin receptor. Proceedings of the National Academy of Sciences of the United States of 
America. 1994;91:4854-4858.
148.
Nieto-Vazquez I, Fernandez-Veledo S, Kramer DK, Vila-Bedmar R, Garcia-Guerra L, Lorenzo M. 
Insulin resistance associated to obesity: the link TNF-alpha. Archives of physiology and biochemistry. 
2008;114:183-194.
149.
Popa C, Netea MG, van Riel PL, van der Meer JW, Stalenhoef AF. The role of TNF-alpha in chronic 
inflammatory conditions, intermediary metabolism, and cardiovascular risk. J Lipid Res. 2007;48:751-
762.
150.  Pal M, Febbraio MA, Whitham M. From cytokine to myokine: the emerging role of interleukin-6 in 
metabolic regulation. Immunol Cell Biol. 2014;92:331-339.
151.
Lewis GF, Carpentier A, Adeli K, Giacca A. Disordered fat storage and mobilization in the pathogenesis
of insulin resistance and type 2 diabetes. Endocr Rev. 2002;23:201-229.
152.
Al-Zubaidi A, Heldmann M, Mertins A, Jauch-Chara K, Munte TF. Influences of Hunger, Satiety and 
Oral Glucose on Functional Brain Connectivity: A Multimethod Resting-State fMRI Study. 
Neuroscience. 2018;382:80-92.
153.
Page KA, Chan O, Arora J, Belfort-Deaguiar R, Dzuira J, Roehmholdt B, Cline GW, Naik S, Sinha R, 
Constable RT, Sherwin RS. Effects of fructose vs glucose on regional cerebral blood flow in brain 
regions involved with appetite and reward pathways. Jama. 2013;309:63-70.
154.  van Opstal AM, Hafkemeijer A, van den Berg-Huysmans AA, Hoeksma M, Blonk C, Pijl H, Rombouts S, 
van der Grond J. Brain activity and connectivity changes in response to glucose ingestion. Nutritional 
neuroscience. 2018:1-8.
155.  Jastreboff AM, Sinha R, Arora J, Giannini C, Kubat J, Malik S, Van Name MA, Santoro N, Savoye M, 
Duran EJ, Pierpont B, Cline G, Constable RT, Sherwin RS, Caprio S. Altered Brain Response to 
Drinking Glucose and Fructose in Obese Adolescents. Diabetes. 2016;65:1929-1939.
156.  Stojek MM, Maples-Keller JL, Dixon HD, Umpierrez GE, Gillespie CF, Michopoulos V. Associations of 
childhood trauma with food addiction and insulin resistance in African-American women with diabetes 
mellitus. Appetite. 2019;141:104317.
157.
Expert Panel on Detection E, Treatment of High Blood Cholesterol in A. Executive Summary of The 
Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, 
Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). Jama. 
2001;285:2486-2497.
158. 
Chu CS, Lee KT, Cheng KH, Lee MY, Kuo HF, Lin TH, Su HM, Voon WC, Sheu SH, Lai WT. 
Postchallenge responses of nitrotyrosine and TNF-alpha during 75-g oral glucose tolerance test are 
associated with the presence of coronary artery diseases in patients with prediabetes. Cardiovascular 
diabetology. 2012;11:21.
159. 
Esposito K, Nappo F, Marfella R, Giugliano G, Giugliano F, Ciotola M, Quagliaro L, Ceriello A, 
Giugliano D. Inflammatory cytokine concentrations are acutely increased by hyperglycemia in humans: 
role of oxidative stress. Circulation. 2002;106:2067-2072.
160.
Llerena, K., Park, S. G., McCarthy, J. M., Couture, S. M., Bennett, M. E., & Blanchard, J. J. (2013). The 
Motivation and Pleasure Scale-Self-Report (MAP-SR): reliability and validity of a self-report measure of 
negative symptoms. Compr Psychiatry, 54(5), pp. 568-574. doi:10.1016/j.comppsych.2012.12.001 
161.
Pollock, V., Cho, D. W., Reker, D., & Volavka, J. (1979). Profile of Mood States: the factors and their 
physiological correlates. J Nerv Ment Dis, 167(10), pp. 612-614. doi:10.1097/00005053-197910000-
00004 
162.
Shacham, S. (1983). A shortened version of the Profile of Mood States. J Pers Assess, 47(3), pp. 305-
306. doi:10.1207/s15327752jpa4703_14 
163.
Haroon E, Chen X, Li Z, Patel T, Woolwine BJ, Hu XP, Felger JC, Miller AH. Increased inflammation 
and brain glutamate define a subtype of depression with decreased regional homogeneity, impaired 
network integrity, and anhedonia. Transl Psychiatry. 2018;8:189.

164.
Haber SN, Knutson B. The reward circuit: linking primate anatomy and human imaging.
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology.
2010;35:4-26.
165.
Mehta ND, Haroon E, Xu X, Woolwine BJ, Li Z, Felger JC. Inflammation negatively correlates with
amygdala-ventromedial prefrontal functional connectivity in association with anxiety in patients with
depression: Preliminary results. Brain, behavior, and immunity. 2018;73:725-730.
166. Ezeoke A, Mellor A, Buckley P, Miller B. A systematic, quantitative review of blood 
autoantibodies in schizophrenia. Schizophr Res. 2013;150(1):245-251. 
doi:10.1016/j.schres.2013.07.029
167. Pollak TA, Rogers JP, Nagele RG, et al. Antibodies in the Diagnosis, Prognosis, and Prediction 
of Psychotic Disorders. Schizophr Bull. 2019;45(1):233-246. doi:10.1093/schbul/sby021
168. Kowal C, DeGiorgio LA, Lee JY, et al. Human lupus autoantibodies against NMDA receptors 
mediate cognitive impairment. Proc Natl Acad Sci U S A. 2006;103(52):19854-19859. 
doi:10.1073/pnas.0608397104
169. Chan K, Nestor J, Huerta TS, et al. Lupus autoantibodies act as positive allosteric modulators 
at GluN2A-containing NMDA receptors and impair spatial memory. Nat Commun. 2020;11(1):1-
11. doi:10.1038/s41467-020-15224-w
170. The Involuntary Musical Imagery Scale (IMIS).  Floridou, G. A., Williamson, V. J., Stewart, L., & 
Müllensiefen, D. (2015). The Involuntary Musical Imagery Scale (IMIS). Psychomusicology: 
Music, Mind, and Brain, 25(1)