Getting the right treatment: Predicting treatment response in depression


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New evidence from mice suggests why an antidepressant treatment can alleviate depression in one person but not another. The study, publishing December 28 in the open access journal PLOS Biology, was led by Marianne Müller and an international team at the University Medical Center Mainz and the Max Planck Institute of Psychiatry. The researchers developed a mouse model that allowed them to identify blood signatures associated with response to antidepressant treatment and could show the importance of the stress-related glucocorticoid receptor in recovery from depression.

Major depression is the leading cause of disability according to the World Health Organization, affecting an estimated 350 million people worldwide, but only one-third of patients bene?t from the ?rst antidepressant prescribed. Although the currently available treatments are safe, there is significant variability in the outcome of antidepressant treatment. So far there are no clinical assessments that can predict with a high degree of certainty whether a particular patient will respond to a particular antidepressant. Finding the most effective antidepressant medication for each patient depends on trial and error, underlining the urgent need to establish conceptually novel strategies for the identification of biomarkers associated with a positive response.

To tackle this challenge, scientists established a novel experimental approach in animals focusing on extreme phenotypes in response to antidepressant treatment. This model simulated the clinical situation, by identifying good and poor responders to antidepressant treatment. The researchers hypothesized that conditions in the mouse model would facilitate the identification of valid peripheral biomarkers for antidepressant treatment response and could potentially apply to humans.

"We were able to identify a cluster of antidepressant response-associated genes in the mouse model that we then validated in a cohort of depressed patients from our collaborators from Emory University, Atlanta", explains Tania Carrillo-Roa from the Max Planck Institute of Psychiatry. This suggests that molecular signatures associated with antidepressant response in the mouse could in fact predict the outcome of antidepressant treatment in the patient cohort. Additional analyses indicated that the glucocorticoid receptor, which is one of the most important players in fine-tuning the stress hormone system, shapes the response to antidepressant treatment.

Ultimately, identification of biomarkers predictive of individual responses to treatment would dramatically improve the quality of care/ treatment for depressed patients by taking the trial and error out of prescribing antidepressants. In the future, this cross-species approach might serve as a template for the discovery of improved and tailored treatment for patients who suffer from depression.


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Citation: Carrillo-Roa T, Labermaier C, Weber P, Herzog DP, Lareau C, Santarelli S, et al. (2017) Common genes associated with antidepressant response in mouse and man identify key role of glucocorticoid receptor sensitivity. PLoS Biol 15(12): e2002690.

Funding: German Federal Ministry of Education and Research (grant number 01ZX1314J). Received by EBB. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. NIH (grant number MH077083). Funding for patient recruitment [Mayberg]. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. NIH (grant number 2R01MH073719). Funding for patient recruitment received by HS Mayberg. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. NIMH (grant number 1RO1MH080880). Funding for patient recruitment received by WE Craighead. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests. CLab, PW, MBM, TCR, MU, CLar, SS, KVW, MR-H, DH, SHS, and MVS declare no conflicts of interest. IS is cofounder/stockholder and CEO of Phenoquest AG. FH is founder and CEO of HMNC GmbH. EBB has received honoraria from Glaxo Smith Kline in the past 3 years and is co-inventor on the following patent applications: (1) FKBP5: a novel target for antidepressant therapy, European Patent #EP 1687443 B1, (2) Polymorphisms in ABCB1 associated with a lack of clinical response to medicaments, United States Patent #8030033, and (3) Means and methods for diagnosing predisposition for treatment emergent suicidal ideation (TESI), European application number 08016477.5, international application number PCT/ EP2009/061575. BWD received grant support from AstraZeneca, BMS, Forest, GSK, Janssen, NIMH, Otsuka, and Pfizer and has received honoraria for consulting from Hoffman LaRoche, MedAvante, and Pfizer. WEC is a board member of Hugarheill ehf, an Icelandic company dedicated to the prevention of depression; receives book royalties from John Wiley & Sons; research was supported by NIMH, the Mary and John Brock Foundation, and the Fuqua Family Foundations; and consultant for George West Mental Health Foundation and Scientific Advisory Board, ADAA. HSM received grant support from NIMH and Consultant and Intellectual Property Licenses fees from St. Jude Medical, Inc. CBN: research/grants: National Institutes of Health (NIH); consulting (last 3 years): Xhale, Takeda, Mitsubishi Tanabe Pharma Development America, Taisho Pharmaceutical Inc., Lundbeck, Prismic Pharmaceuticals, Bracket (Clintara), Total Pain Solutions (TPS), Gerson Lehrman Group (GLG) Healthcare & Biomedical Council, Fortress Biotech, and Sunovion Pharmaceuticals, Inc.

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Marianne Müller
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