Literature DB >> 24561326

Are there meaningful biomarkers of treatment response for depression?

Barbara Breitenstein1, Sandra Scheuer2, Florian Holsboer3.   

Abstract

During the past decades, the prevalence of affective disorders has been on the rise globally, with only one out of three patients achieving remission in acute treatment with antidepressants. The identification of physiological markers that predict treatment course proves useful in increasing therapeutic success. On the basis of well-documented, recent findings in depression research, we highlight and discuss the most promising biomarkers for antidepressant therapy response. These include genetic variants and gene expression profiles, proteomic and metabolomic markers, neuroendocrine function tests, electrophysiology and imaging techniques. Ultimately, this review proposes an integrative use of biomarkers for antidepressant treatment outcome.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 24561326     DOI: 10.1016/j.drudis.2014.02.002

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  16 in total

Review 1.  Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years.

Authors:  G Voegeli; M L Cléry-Melin; N Ramoz; P Gorwood
Journal:  Drugs       Date:  2017-12       Impact factor: 9.546

2.  Abnormal self-schema in semantic memory in major depressive disorder: Evidence from event-related brain potentials.

Authors:  Michael Kiang; Faranak Farzan; Daniel M Blumberger; Marta Kutas; Margaret C McKinnon; Vinay Kansal; Tarek K Rajji; Zafiris J Daskalakis
Journal:  Biol Psychol       Date:  2017-04-03       Impact factor: 3.251

3.  Amygdala response to explicit sad face stimuli at baseline predicts antidepressant treatment response to scopolamine in major depressive disorder.

Authors:  Joanna Szczepanik; Allison C Nugent; Wayne C Drevets; Ashish Khanna; Carlos A Zarate; Maura L Furey
Journal:  Psychiatry Res Neuroimaging       Date:  2016-06-20       Impact factor: 2.376

Review 4.  Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder.

Authors:  R C Kessler; H M van Loo; K J Wardenaar; R M Bossarte; L A Brenner; D D Ebert; P de Jonge; A A Nierenberg; A J Rosellini; N A Sampson; R A Schoevers; M A Wilcox; A M Zaslavsky
Journal:  Epidemiol Psychiatr Sci       Date:  2016-01-26       Impact factor: 6.892

Review 5.  Suggested Biomarkers for Major Depressive Disorder.

Authors:  Yunus Hacimusalar; Ertuğrul Eşel
Journal:  Noro Psikiyatr Ars       Date:  2018-05-28       Impact factor: 1.339

6.  Establishing Evidence for Clinical Utility of a Neuroimaging Biomarker in Major Depressive Disorder: Prospective Testing and Implementation Challenges.

Authors:  Mary E Kelley; Ki Sueng Choi; Justin K Rajendra; W Edward Craighead; Jeffrey J Rakofsky; Boadie W Dunlop; Helen S Mayberg
Journal:  Biol Psychiatry       Date:  2021-02-26       Impact factor: 12.810

Review 7.  Inflammatory biomarkers as differential predictors of antidepressant response.

Authors:  Kenji Hashimoto
Journal:  Int J Mol Sci       Date:  2015-04-08       Impact factor: 5.923

8.  Effect of the fragrance inhalation of essential oil from Asarum heterotropoides on depression-like behaviors in mice.

Authors:  Hyun-Jung Park; Eun-Ju Lim; Rong Jie Zhao; Sa Rang Oh; Ji Wook Jung; Eun-Mi Ahn; Eun Sook Lee; Jin Suk Koo; Hee Young Kim; Suchan Chang; Hyun Soo Shim; Kwang Joong Kim; Young Seob Gwak; Chae Ha Yang
Journal:  BMC Complement Altern Med       Date:  2015-03-06       Impact factor: 3.659

9.  Differential Peripheral Proteomic Biosignature of Fluoxetine Response in a Mouse Model of Anxiety/Depression.

Authors:  Indira Mendez-David; Céline Boursier; Valérie Domergue; Romain Colle; Bruno Falissard; Emmanuelle Corruble; Alain M Gardier; Jean-Philippe Guilloux; Denis J David
Journal:  Front Cell Neurosci       Date:  2017-08-16       Impact factor: 5.505

10.  Longitudinal Changes in Depressive Circuitry in Response to Neuromodulation Therapy.

Authors:  Yagna Pathak; Oludamilola Salami; Sylvain Baillet; Zhimin Li; Christopher R Butson
Journal:  Front Neural Circuits       Date:  2016-07-29       Impact factor: 3.492

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