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).
: 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.
|Delaparte, Lauren; Yeh, Fang-Cheng; Adams, Phil et al. (2017) A comparison of structural connectivity in anxious depression versus non-anxious depression. J Psychiatr Res 89:38-47|
|Fortin, Jean-Philippe; Cullen, Nicholas; Sheline, Yvette I et al. (2017) Harmonization of cortical thickness measurements across scanners and sites. Neuroimage 167:104-120|
|Petkova, Eva; Ogden, R Todd; Tarpey, Thaddeus et al. (2017) Statistical Analysis Plan for Stage 1 EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care) Study. Contemp Clin Trials Commun 6:22-30|
|Fournier, Jay C; Chase, Henry W; Greenberg, Tsafrir et al. (2017) Neuroticism and Individual Differences in Neural Function in Unmedicated Major Depression: Findings from the EMBARC Study. Biol Psychiatry Cogn Neurosci Neuroimaging 2:138-148|
|Tenke, Craig E; Kayser, Jürgen; Pechtel, Pia et al. (2017) Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response. Psychophysiology 54:34-50|
|Jiang, Bei; Petkova, Eva; Tarpey, Thaddeus et al. (2017) LATENT CLASS MODELING USING MATRIX COVARIATES WITH APPLICATION TO IDENTIFYING EARLY PLACEBO RESPONDERS BASED ON EEG SIGNALS. Ann Appl Stat 11:1513-1536|
|Friedman, Lee; Nixon, Mark S; Komogortsev, Oleg V (2017) Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases. PLoS One 12:e0178501|
|Perlman, Greg; Bartlett, Elizabeth; DeLorenzo, Christine et al. (2017) Cortical thickness is not associated with current depression in a clinical treatment study. Hum Brain Mapp 38:4370-4385|
|Ham, Byung-Joo; Greenberg, Tsafrir; Chase, Henry W et al. (2016) Impact of the glucocorticoid receptor BclI polymorphism on reward expectancy and prediction error related ventral striatal reactivity in depressed and healthy individuals. J Psychopharmacol 30:48-55|
|Trivedi, Madhukar H; McGrath, Patrick J; Fava, Maurizio et al. (2016) Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design. J Psychiatr Res 78:11-23|
Showing the most recent 10 out of 26 publications