Prediction of SSRI Treatment in Major Depression.
Study Details
Study Description
Brief Summary
This project will combine the data collected from EEG, Eye tracking, structural and functional MRI scans and neuropsychological performance from patients with major depression receiving SSRI treatment. The purpose of this research is to predict the success of the SSRI treatment and to categorize patients into sub-groups according to similar patterns of brain activation to personalize treatment.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Detailed Description
Major depression is a mood disorder affecting 350 million people worldwide. The disorder is characterized by depressed mood, anhedonia, decreased quality of life, deficits in cognitive functions and even suicide thoughts. Treatment of depression is often a long process and includes taking different types and quantities of medications. Therefore, there is a need to predict the success of the SSRI treatment. Our research will examine the outcomes of the combined technologies: BNA (EEG), Eye-tracker, structural and functional MRI scans and neuropsychology tasks in patients with depression while receiving SSRI treatment. The purpose of the research is to track biomarkers and other measures, which will allow predicting the SSRI treatment's success within 4 weeks instead of 8 weeks. In addition, the investigators will attempt to categorize patients into different subgroups according to their brain activation and eye movements. This division into subgroups may contribute to the understanding of the mechanisms that account for the responsiveness to SSRI treatment and to the possibility of targeting patients with depression towards a particular treatment. From this research, the investigators aim to personalize the treatment of depression, make it more efficient and reduce the amount of time for the patient to reach an optimal responsiveness.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Healthy subjects 50 healthy subjects for a control group |
Device: SIEMENS PRISMA MRI
Collect data on brain activation from different methods
Other Names:
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| Patients with Major Depression 50 patients with major depression for a research group |
Device: SIEMENS PRISMA MRI
Collect data on brain activation from different methods
Other Names:
|
Outcome Measures
Primary Outcome Measures
- EEG responses to cognitive tasks in combination with the Eye-tracker Device. [2 years]
Categorize patients into subgroups according to combined measures of EEG and Eye
Secondary Outcome Measures
- Resting state connectivity analysis [2 years]
Examine the difference in resting state connectivity between the groups.
- Examine correlations between the different methods [2 years]
Examine correlations between the different methods EEG, Eye-tracking and fMRI
- EEG brain activation to cognitive tasks [2 years]
Categorize patients into subgroups according to similar brain activity
- Eye-tracking tasks [2 years]
Categorize patients into subgroups according to similar patterns of eye movements.
- Examine MRI structural changes [2 years]
Compare structural changes between the groups (patients with depression, healthy subjects).
- Cognitive scores on CANTAB (computerized cognitive assessments) [2 years]
Examine the difference in responses to different cognitive exams between the groups
Eligibility Criteria
Criteria
Inclusion Criteria:
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Patients 18-65 years old
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Male and female
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Ability to comprehend and sign informed consent
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DSM-5 diagnosis with MINI 7.0.2 (healthy subjects need to be ruled out)
Inclusion Criteria for patients with depression:
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DSM-5 diagnosis
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0-2 failed treatments
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Patients which will start SSRI treatment
Exclusion Criteria:
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unconsciousness
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Pregnancy or nursing
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Cardiovascular instability
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Metabolic instability (water, electrolytes, sugar)
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Fever or evidence of microbiological pollutant
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Deafness or blindness
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Schizophrenia
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Addiction disorders
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Eating disorders
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Bi-polar disorder
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Cognitive deficits
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Start a new psychotherapy during the research
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Unable to enter the MRI scanner
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Sheba Medical CENTER | Ramat Gan | Israel | 52621 |
Sponsors and Collaborators
- ElMindA Ltd
- Sheba Medical Center
- Hebrew University of Jerusalem
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
- Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho RN, Zebley B, Oathes DJ, Etkin A, Schatzberg AF, Sudheimer K, Keller J, Mayberg HS, Gunning FM, Alexopoulos GS, Fox MD, Pascual-Leone A, Voss HU, Casey BJ, Dubin MJ, Liston C. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017 Jan;23(1):28-38. doi: 10.1038/nm.4246. Epub 2016 Dec 5. Erratum in: Nat Med. 2017 Feb 7;23 (2):264.
- Ogawa T, Sekino H, Uzura M, Sakamoto T, Taguchi Y, Yamaguchi Y, Hayashi T, Yamanaka I, Oohama N, Imaki S. Comparative study of magnetic resonance and CT scan imaging in cases of severe head injury. Acta Neurochir Suppl (Wien). 1992;55:8-10.
- Raichle ME, Snyder AZ. A default mode of brain function: a brief history of an evolving idea. Neuroimage. 2007 Oct 1;37(4):1083-90; discussion 1097-9. Epub 2007 Mar 6. Review.
- Rohden AI, Benchaya MC, Camargo RS, Moreira TC, Barros HMT, Ferigolo M. Dropout Prevalence and Associated Factors in Randomized Clinical Trials of Adolescents Treated for Depression: Systematic Review and Meta-analysis. Clin Ther. 2017 May;39(5):971-992.e4. doi: 10.1016/j.clinthera.2017.03.017. Epub 2017 May 2. Review.
- ELM-55 5323-18-SMC