A depressive disorder is a psychiatric disorder characterized by a depressive state of mind, negative thoughts, anhedonia and suicidality. Patients often suffer from recurrent psychotic episodes, which has an enormous impact on all aspects of their lives. A subpopulation of these patients also suffers from psychotic symptoms such as delusions and auditory hallucinations (Schatzberg, 2006) on top of the characteristic depressive symptoms. Current imaging studies and molecular studies point to specific characteristics that differentiate between psychotic depression and non-psychotic depression, such as reduced functional activity in the insula in psychotic depression (Farret et al., 2011), and to shared factors between both forms such as disruption of the HPA axis (review Dean and Keshavan, 2017). Although there is already some knowledge about the underlying neurobiology of psychotic depression, the characterization is far from complete, which is illustrated by the low diagnosis and suboptimal treatment of this serious disorder. This is problematic as these patients account for a significant 14-20 percent of patients (Ohayon & Schatzberg, 2002) and this subpopulation shows a different course of disease and a different response to treatment (Buoli et al., 2013, Van Diermen et al. , 2018). New techniques such as proteomics and transcriptomics can offer a solution. These techniques provide the opportunity to map both syndromes on a large scale and from an atheoretical perspective. For example, interesting findings have been made in post-mortem brains of patients with various syndromes such as schizophrenia, bipolar disorder and depressive disorder (review Saia-Cerada, 2017). As far as psychotic depression is concerned, so far only a small-scale study has been undertaken by Martin-De Souza et al (2012) in which quantitative differences were found between protein concentrations related to energy metabolism and synaptic activity. Furthermore, differences were also found in the expression of proteins previously linked to schizophrenia, as one would expect given the aforementioned overlap in genetic risk factors. Although these interesting initial findings show that this form of research can make a valuable contribution to the knowledge of psychotic depression in the field of neurobiology, larger studies are needed that ideally use predictive statistical methods such as sensitivity, specificity and reclassification tables (Pencina, 2008) to distill potential biomarkers for psychotic depression. Furthermore, knowledge of the underlying interaction network can yield interesting drug targets (Hopkins, 2008).
These two goals are therefore central to this PhD. In order to achieve this, brains from the Corsella collection will be examined with different molecular techniques. In the first phase medical records will be read and inventoried in an electronic database together with information about the available tissue. In a second phase, four types of cases will be selected from this database, namely healthy controls, patients with a depressive disorder without psychotic characteristics, patients with a psychotic depressive disorder and patients with a psychotic disorder without affective characteristics. These samples will then be analyzed by means of proteomics and transcriptomics.