Identification of biological subtypes related to treatment resistant depression
Host: BIOMAX INFORMATICS AG, Germany
PhD awarding institution: LUDWIGMAXIMILIANSUNIVERSITAET MUENCHEN
Lead Supervisor: M Butz-Ostendorf
Objectives: Depression is among the top disorders associated with years lost to disability, treatment options are not guided by underlying pathobiology but mainly based on trial and error, leading to long lag-times of treatment response in over 2/3 of the patients and the development of treatment resistance in over 10%. This project will identify biologically-defined clusters of depressed patients related to their response to antidepressant treatment. For this, psychiatric symptom severity at baseline and following antidepressant treatment will be analyzed together with genetic, gene expression, DNA methylation, structural neuroimaging, laboratory and neuropsychological data. Data distribution and the suited type of analysis will be evaluated to identify biological features associated with different treatment outcome. This project will use an existing dataset of over 1400 depressed patients. This approach will allow to identify biologically distinct classes of patients that may benefit from distinct interventions and shed light on pathobiological mechanisms in depression.