Identification of Potential Biomarkers for Depressive Disorders

Abstract

The understanding of the individual variability of depressive disorders is in urgent need of improvement which could be accelerated by identification of biomarkers for the diagnosis and treatment individualization of depressions. Here, we focused on the identification of potential biomarkers by application of cell based and neuroimaging based approaches to further advance the field of personalized medicine of depressive disorders.<br /> The therapy effectiveness of antidepressants requires improvement due to low response rates, a delay in clinical improvement and the lack of predictive biomarkers. Since depressions seem to be associated with decreased hippocampal volumes and antidepressant treatments are able to stimulate neurogenesis, individual susceptibility to antidepressant induced proliferation may act as a surrogate marker for the prediction of individual responses to antidepressant drugs. We measured proliferative effects by antidepressant drugs in human lymphoblastoid cell lines (LCLs) derived from depressed patients with monitored response progresses. A high variability in individual proliferation and significant overall proliferative effects were reported. Furthermore, we conducted transcriptome analyses in order to identify potential gene expression biomarkers. Significant correlations between clinical parameters of LCL donors and gene expression levels have been detected for several genes. With this we identified potential biomarkers that might support the guidance of individual therapy regimes in depressed patients and help to advance the personalized treatment approach.<br /> Another approach is the usage of neuroimaging techniques which has the potential to support the differential diagnosis of depression or to predict non-response or response to antidepressants. Here, we performed a clinical study to explore the individual variability of drug-induced depressions. Participants of this study were screened for depressive symptoms by psychometric testing and for changes in activation patterns of depression-related brain regions using functional magnetic resonance imaging (fMRI) techniques in order to find evidence for the depression inducing side-effects of interferon beta. During the fMRI sessions, conducted before and after interferon beta administration, the participants were instructed to complete two tasks that target specific depression-related brain functions (emotion processing and reward system). Although the role of emotion recognition in depression is usually of high relevance, we did not find any significant changes in amygdala activation after the short-term treatment with interferon using a passive exposure paradigm to emotional faces. In contrast, we measured a significantly decreased activity of the ventral striatum following the treatment with interferon beta in a money-rewarding paradigm. After exposure to interferon beta in healthy volunteers, we detected changes in the reward system functionality consistent with the existence of an anhedonia-like syndrome, while reactivity to salient negative stimuli was absent. This pattern was in accordance with the lack of change in anxiety scores in behavioral testing (usually present in depression), outlining a specific syndrome accompanying the depression-inducing action or sickness behavior of interferon. After long-term therapy, this sickness behavior might turn into serious depression through cytokine actions in the brain because chronic inflammation seems to be a strong risk factor for the occurrence of depressive episodes. Based on our data one might speculate that interferon beta mainly affects dopaminergic circuits of reward and not serotonergic circuits of emotion recognition. We therefore propose that the depression-inducing effects of interferon beta after long-term therapy are at least partly based on an impaired reward system functionality.