<p class="title">Scientists have identified blood markers that may help understand why antidepressant drugs do not successfully alleviate depression in everyone.</p>.<p class="bodytext">Researchers from University Medical Center Mainz and the Max Planck Institute of Psychiatry in Germany 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.</p>.<p class="bodytext">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 benefit from the first antidepressant prescribed.</p>.<p class="bodytext">Although the currently available treatments are safe, there is significant variability in the outcome of antidepressant treatment.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">They hypothesised that conditions in the mouse model would facilitate the identification of valid peripheral biomarkers for antidepressant treatment response and could potentially apply to humans.</p>.<p class="bodytext">"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," said Tania Carrillo-Roa from the Max Planck Institute of Psychiatry.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">In the future, this cross-species approach might serve as a template for the discovery of an improved and tailored treatment for patients who suffer from depression.</p>
<p class="title">Scientists have identified blood markers that may help understand why antidepressant drugs do not successfully alleviate depression in everyone.</p>.<p class="bodytext">Researchers from University Medical Center Mainz and the Max Planck Institute of Psychiatry in Germany 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.</p>.<p class="bodytext">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 benefit from the first antidepressant prescribed.</p>.<p class="bodytext">Although the currently available treatments are safe, there is significant variability in the outcome of antidepressant treatment.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">They hypothesised that conditions in the mouse model would facilitate the identification of valid peripheral biomarkers for antidepressant treatment response and could potentially apply to humans.</p>.<p class="bodytext">"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," said Tania Carrillo-Roa from the Max Planck Institute of Psychiatry.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">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.</p>.<p class="bodytext">In the future, this cross-species approach might serve as a template for the discovery of an improved and tailored treatment for patients who suffer from depression.</p>