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Project context and summary :
Mood disorders such as bipolar and major depressive disorders affects 2-5% of the population worldwide. They are relapsing, major psychiatric illnesses with poorly understood neurobiology, typically incomplete treatment responses, and often unsatisfactory clinical outcomes, with a high risk of premature mortality due to suicide and clinical comorbidities. Its complex manifestations include marked disturbances of emotional regulation, sensory-perception as well as major changes in mood, thinking, and many aspects of behavior. It is of crucial importance to be able to discriminate mood states in clinical practice, as pharmacological and psychological treatments as well as course of illness and outcome differ across the different mood states. By applying advanced mathematical approaches (with statistical/computational advice from a C3BI’s colleagues) this study aims to explore how sociodemographic, psychosocial and behavioral predictors may contribute for better characterizing patients with mood disorders. The study also aims to identify biological predictors of different mood states as well as of treatment response in mood disorders. Having a deeper understanding of phenomenology and pathophysiological mechanisms of mood disorders may help clinicians to provide more personalized interventions for individuals at-risk or suffering from mood disorders.Related team publications :
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