The timely selection of the best treatment for patients with depression is critical to the goal of improving remission rates. Due to the biological heterogeneity and variable symptom presentation of depression, it is unlikely that a single clinical or biological marker can guide treatment selection. Rather, a biosignature developed from a systematic exploration of a group of clinical and biological markers is more likely to be successful. Two types of biosignatures are needed to achieve improved outcomes: 1) biosignatures to maximize the selection of optimal treatment for individual patients at the beginning of treatment (moderators) and 2) biosignatures to identify indicators of eventual outcomes early in treatment (mediators). This approach has great potential to personalize treatment and maximize the number of patients who can be treated to full remission with a given treatment. We propose a comparative effectiveness trial of three mechanistically distinct treatments for MDD (citalopram, bupropion, and cognitive behavioral therapy) in which we will assess a comprehensive array of carefully selected clinical (i.e. anxious depression, early life trauma, &gender) and biological (i.e. genetic, neuroimaging, serum, epigenetic &qEEG) moderators and mediators of outcome. Using innovative statistical approaches the identified moderators and mediators will then be used to develop a differential depression treatment response index (DTRI). The proposed study is a randomized two-stage trial (Stagel:12 wks;Stage2: 12 wks) design with 675 MDD patients (with a history of one adequate trial of an SSRI except citalopram) assigned to one of three treatment conditions (n=225 each). This two stage approach is similar to a Sequential Multiple Assignment Randomized Trial (SMART) design. This application brings together researchers with extensive experience in conducting large clinical trials and experts at the forefront ofthe neurobiology of depression, including: clinical trials (Trivedi, Fava, Schatzberg,Nierenberg, Shelton, Gaynes, Hollon), genetics (Smoller, Binder, McMahan, Perils), neuroimaging (Phillips, Sheline, Etkin, Pizzagalli, Buckner), qEEG (losifescu, Ellenbogen), neurotrophins/cytokines (Duman, Sanacora, Turck, Shelton), clinical predictors (Shelton, Hollon, Trivedi, Fava, Nierenberg, Goodman, Yehuda), neuroendocrine markers (Holsboer, Schatzberg, Shelton, Yehuda), epigenetics (Nestler, Yehuda),and cognitive behavior therapy (Hollon, Manber, Arnow). This team will also be guided by internationally known biomarker scientists (Holsboer, Schatzberg, Krystal, Charney, Goodman), as well as a highly qualified group of biostatisticians (Kraemer, Wisniewski, Schoenfeld).

Public Health Relevance

: This study will examine multiple carefully selected clinical and biological markers, using both existing state of-the-art technologies as well as pioneering, innovative approaches. Evaluation of the usefulness of these markers in a trial with three different treatments will assist in generating a depression treatment response index (DTRI). The DTRI will help clinicians match treatments to patients with MDD, resulting in timely selection of treatments best suited for individual patients. Results from this study could significantly improve the treatment of patients with MDD.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01MH092221-03
Application #
8333172
Study Section
Special Emphasis Panel (ZMH1-ERB-F (09))
Program Officer
Hillefors, MI
Project Start
2010-09-30
Project End
2014-06-30
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
3
Fiscal Year
2012
Total Cost
$1,964,156
Indirect Cost
$451,630
Name
University of Texas Sw Medical Center Dallas
Department
Psychiatry
Type
Schools of Medicine
DUNS #
800771545
City
Dallas
State
TX
Country
United States
Zip Code
75390
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Chase, Henry W; Fournier, Jay C; Greenberg, Tsafrir et al. (2015) Accounting for Dynamic Fluctuations across Time when Examining fMRI Test-Retest Reliability: Analysis of a Reward Paradigm in the EMBARC Study. PLoS One 10:e0126326
Frank, E; Nimgaonkar, V L; Phillips, M L et al. (2015) All the world's a (clinical) stage: rethinking bipolar disorder from a longitudinal perspective. Mol Psychiatry 20:23-31
Dillon, D G; Wiecki, T; Pechtel, P et al. (2015) A computational analysis of flanker interference in depression. Psychol Med 45:2333-44

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