Clinical trial NCT04189939: Computational Psychiatric Approach to Depression
Official title: Computational Psychiatric Approach for Prognosis of Medication-Resistant Depression
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Depression
Treatment Resistant Depression
Keywords: ECT treatment
treatment-resistant depression
neural changes
Lead sponsor: Wake Forest University Health Sciences
Sponsor class: OTHER
First posted: 2019-12-06
Enrollment: 128
Sex: ALL
Minimum age (years): 18
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who meet the criteria in standard-of-care evaluation for ECT treatment, clinically depressed patients (non-treatment-resistant), and healthy adults.

Brief summary: The purpose of this research is to investigate how the brain changes in patients undergoing electroconvulsive (ECT) treatment for depression. Subjects will be invited to be in this study because (1) they are a patient about to receive ECT treatment for depression, or (2) they are a patient diagnosed with depression and do not qualify for ECT treatment, or (3) they are a healthy adult volunteer with no history of depression.

All volunteers must be between the ages of 18-85. Participation in this research will involve three visits. Each visit will last about 3-4 hours. If the subject is a patient receiving ECT for depression the study team will schedule study visits to go along with patient treatment visits. If the subject is diagnosed with depression (not treatment-resistant depression) or are a healthy volunteer, their first visit will be scheduled at their convenience, followed by a second visit 1-3 months post visit one and a third visit 1-2 months post visit two, for a total of three research visits.

Participation in this research will involve playing simple computer games while the subject's brain is scanned with magnetic resonance imaging (MRI). Additionally, the study team will assess symptoms of depression using questionnaires. Patients receiving ECT will not experience any changes to their standard of care ECT treatment plan. Healthy and non-treatment resistant depressed volunteers will not undergo ECT treatment.

Detailed description: The goal for this study will be to test the following overall hypotheses: (1) that adaptive decision-making processes are disrupted in patients with treatment-resistant depression, and (2) the neural and behavioral changes associated with treatment-resistant depression can be assessed using functional magnetic resonance imaging paired with computationally constrained adaptive decision-making games.

The investigators will use computational modeling of incentivized decision-making tasks, brain imaging (functional magnetic resonance imaging, fMRI), and standard clinical assessments, to characterize patients referred to Wake Forest Baptist Medical Center for ECT. Characterization will occur over multiple visits to be aligned with the normal course of patient care.

Data collected may be used in hypothesis driven analyses to:

1. classify treatment resistant depression versus healthy controls and non-treatment resistant depression
2. predictors of ECT treatment success versus failure
3. characterize brain and behavioral changes consistent with treatment success versus failure
4. predict who will need maintenance ECT therapy
5. determine what changes in decision-making behavior are apparent in patients who require ECT maintenance therapy versus those who do not.

Eligibility criteria: For patients:

Inclusion Criteria:

* Adult volunteers (ages 18-85)
* Treatment-resistant depressed patients must meet criteria in standard-of-care evaluation for ECT treatment
* Clinically depressed patients must meet criteria in standard-of-care evaluation for depression.

Exclusion Criteria:

* Individuals who cannot have MRI scanning
* Individuals not able to provide written consent and verbal assent
* Individuals not able to understand task instructions or consent documents
* Women who are pregnant

For healthy subject volunteers:

Inclusion Criteria:

* Healthy adult volunteers (ages 18-85)

Exclusion Criteria:

* Individuals diagnosed with depression (regardless of treatment status)
* Individuals who cannot have MRI scanning
* Individuals not able to provide written consent and verbal assent
* Individuals not able to understand task instructions or consent documents
* Women who are pregnant

Primary outcomes:
measure: Functional Brain scanning - Neural activation
timeFrame: Baseline
measure: Functional Brain scanning - Neural activation
timeFrame: month 1
measure: Functional Brain scanning - Neural activation
timeFrame: month 2
Secondary outcomes:
measure: Sensation Seeking Scale
timeFrame: Baseline, month 1, month 2
measure: Perceived Control of Internal States Scale (PCISS)
timeFrame: Baseline, month 1, month 2
measure: Montreal Cognitive Assessment
timeFrame: Baseline, month 1, month 2
measure: Physical Risk Assessment Inventory
timeFrame: Baseline, month 1, month 2
measure: Patient Health Questionnaire-9
timeFrame: Baseline, month 1, month 2
measure: Hamilton Depression Inventory (HAM-D)
timeFrame: Baseline, month 1, month 2
Other outcomes:
measure: Snaith-Hamilton Pleasure Scale (SHAPS)
timeFrame: Baseline, month 1, month 2
measure: Positive Valence Systems Scale (PVSS)
timeFrame: Baseline, month 1, month 2
measure: Columbia Suicide Scale (C-SSRS)
timeFrame: Baseline, month 1, month 2
measure: Apathy Motivation Index (AMI)
timeFrame: Baseline, month 1, month 2
Locations:
city: Winston-Salem
country: United States
facility: Wake Forest School of Medicine
state: North Carolina
Study officials:
affiliation: Wake Forest University Health Sciences
name: Kenneth T Kishida, PhD
role: PRINCIPAL_INVESTIGATOR
References:
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citation: Wang XJ, Krystal JH. Computational psychiatry. Neuron. 2014 Nov 5;84(3):638-54. doi: 10.1016/j.neuron.2014.10.018. Epub 2014 Nov 5.
citation: Huys QJ, Maia TV, Frank MJ. Computational psychiatry as a bridge from neuroscience to clinical applications. Nat Neurosci. 2016 Mar;19(3):404-13. doi: 10.1038/nn.4238.
citation: Berlim MT, Turecki G. Definition, assessment, and staging of treatment-resistant refractory major depression: a review of current concepts and methods. Can J Psychiatry. 2007 Jan;52(1):46-54. doi: 10.1177/070674370705200108.