From mice and men: Predicting anti-depressant response
Last Updated on January 2, 2018 by Joseph Gut – thasso
January 01, 2018 – Antidepressants are not at all a “one-size-fits-all pill”. Predicting treatment response in depression in order to get the “right” treatment, efficacious and adverse effects free at the same time, is still a huge challenge. Inter-individual variability to treatment spanning a spectrum from successfully realised clinical response to disastrous self-destructing behaviour up to completed suicide in some individuals is tremendous. Up to now, finding the most effective antidepressant medication for each individual patient did largely depends on trial and error; still today, it does so. In the age of theragenomic medicine, this underlines the urgent need to establish conceptually novel strategies for the identification of predictive biomarkers firmly associated with a positive response.
prediction of response status with an accuracy of 76% in the patient population. Finally, the researchers showed that glucocorticoid receptor (GR)-regulated genes are significantly enriched in this cluster of antidepressant-response genes. Overall, the findings point to the involvement of GR sensitivity as a potential key mechanism shaping response to antidepressant treatment and support the hypothesis that antidepressants could stimulate resilience-promoting molecular mechanisms. Moreover, these data also highlight the suitability of an appropriate animal experimental approach for the discovery of treatment response-associated pathways across species.
Major depression is the leading cause of disability according to the World Health Organization (WHO), affecting an estimated 350 million people worldwide. Only one-third of patients benefit from the first antidepressant prescribed. Although the currently available treatments are “safe”, however with the very broad spectrum of outcomes referred to above. The establishment of the present novel experimental approach in animals focusing on extreme phenotypes in response to antidepressant treatment, simulating the clinical situation by identifying good and poor responders to antidepressant treatment constitutes a huge step forward for the understanding of who could be a responder and who would not. Of course, there will have to be much larger trials in humans to confirm this concept, and also to understand the role genetic variation in the GR-regulated genes in individual patients might play in order to become a good or a bad responder.