Biomarkers of Depression and Treatment Response
Last updated on July 2021Recruitment
- Recruitment Status
- Recruiting
- Estimated Enrollment
- Same as current
Summary
- Conditions
- Depressive Disorder, Major
- Type
- Interventional
- Phase
- Not Applicable
- Design
- Allocation: Non-RandomizedIntervention Model: Parallel AssignmentIntervention Model Description: This will be a parallel-groups, stratified interventional study to investigate methods of optimizing clinical care in patients diagnosed with MDD.Masking: Single (Outcomes Assessor)Masking Description: A third party assessor will conduct a biweekly MADRS clinician rating to assess depression symptoms.Primary Purpose: Treatment
Participation Requirements
- Age
- Between 18 years and 70 years
- Gender
- Both males and females
Description
First, the study will examine the replicability and prognostic utility of two previously identified potential biomarkers for MDD using resting state imaging. Second, investigators will conduct an exploratory, whole brain analysis combining EEG and imaging techniques to identify new potential biomark...
First, the study will examine the replicability and prognostic utility of two previously identified potential biomarkers for MDD using resting state imaging. Second, investigators will conduct an exploratory, whole brain analysis combining EEG and imaging techniques to identify new potential biomarkers for MDD and treatment response as participants complete a course of TMS treatment. It is the hope to shed new light on the mechanisms underlying depression and relapse, which may allow for a more effective, personalized selection of treatment course. Participants will complete initial screening and baseline evaluation, along with resting-state functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI) and electroencephalography (EEG) scans prior to the initial TMS treatment. Participants will complete 30-36 TMS sessions and a post-treatment evaluation, along with mid- and post-treatment fMRI, DTI and EEG scans. It is anticipated that participants with MDD have a specific set of neural features that can classify with high precision patients with MDD from those who do not, and that align with clinical diagnoses. This set of neural features will change across the course of treatment. Further, investigators expect that improvement as rated by a common MDD measure is modulated by time of treatment.
Tracking Information
- NCT #
- NCT04581902
- Collaborators
- Not Provided
- Investigators
- Principal Investigator: Andrew Krystal, MD, MS University of California, San Francisco