Deep Phenotyping for Clinical Inferring Response in Treatment Resistant Depression

DECIDE- Deep phenotyping for clinical inferring response in treatment resistant depression -Study Building upon the "Biobanking" initiative at the Max Planck Institute of Psychiatry, the present project aims to identify clinically relevant subtypes of treatment-resistant depression (TRD) through Clinical Deep Phenotyping (CDP). According to clinical trials, 30-40% of the patients suffering from TRD benefit from lithium treatment. By collecting multimodal biological and clinical-diagnostic markers, such as structural and functional brain imaging via magnetic resonance imaging (MRI), brain signals from electroencephalography, comprehensive blood tests, assessment of perception and cognition through neuropsychological testing, as well as the evaluation of specific depression symptoms and psychological and other comorbidities using standardized questionnaires, a bio-clinical signature will be identified using multivariate machine learning algorithms as an integration method. This signature aims to predict the response to lithium therapy in TRD. Prospectively, such an algorithm could later personalize the treatment decision of 'lithium administration in TRD'. This concept is in line with the Research Domain Criteria (RDoC) of the National Institute of Mental Health (NIH) and aims to offer lithium therapy as a personalized treatment strategy for TRD. Specifically, this means that the likelihood of treatment response can be estimated before administration based on the results of the present study, thus enabling lithium to be offered specifically to those patients who are likely to benefit from it. The study design is non-interventional, meaning the decision for lithium treatment is made for patients according to clinical routine in accordance with the recommendation of the German National Treatment Guideline (NVL) independent of study enrollment. Study participation does not influence treatment decisions for the patients.