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Anxiety and depressive disorders result from a complex interplay of genetic and environmental factors and are common mutual comorbidities. On the level of cellular signaling, regulator of G protein signaling 2 (Rgs2) has been implicated in human and rodent anxiety as well as rodent depression. Rgs2 negatively regulates G protein-coupled receptor (GPCR) signaling by acting as a GTPase accelerating protein towards the Gα subunit.
The present study investigates, whether mice with a homozygous Rgs2 deletion (Rgs2-/-) show behavioral alterations as well as an increased susceptibility to stressful life events related to human anxiety and depressive disorders and tries to elucidate molecular underlying’s of these changes.
To this end, Rgs2-/- mice were characterized in an aversive-associative learning paradigm to evaluate learned fear as a model for the etiology of human anxiety disorders. Spatial learning and reward motivated spatial learning were evaluated to control for learning in non-aversive paradigms. Rgs2 deletion enhanced learning in all three paradigms, rendering increased learning upon deletion of Rgs2 not specific for aversive learning. These data support reports indicating increased long-term potentiation in Rgs2-/- mice and may predict treatment response to conditioning based behavior therapy in patients with polymorphisms associated with reduced RGS2 expression. Previous reports of increased innate anxiety were corroborated in three tests based on the approach-avoidance conflict. Interestingly, Rgs2-/- mice showed novelty-induced hypo-locomotion suggesting neophobia, which may translate to the clinical picture of agoraphobia in humans and reduced RGS2 expression in humans was associated with a higher incidence of panic disorder with agoraphobia. Depression-like behavior was more distinctive in female Rgs2-/- mice. Stress resilience, tested in an acute and a chronic stress paradigm, was also more distinctive in female Rgs2-/- mice, suggesting Rgs2 to contribute to sex specific effects of anxiety disorders and depression.
Rgs2 deletion was associated with GPCR expression changes of the adrenergic, serotonergic, dopaminergic and neuropeptide Y systems in the brain and heart as well as reduced monoaminergic neurotransmitter levels. Furthermore, the expression of two stress-related microRNAs was increased upon Rgs2 deletion. The aversive-associative learning paradigm induced a dynamic Rgs2 expression change. The observed molecular changes may contribute to the anxious and depressed phenotype as well as promote altered stress reactivity, while reflecting an alter basal stress level and a disrupted sympathetic tone. Dynamic Rgs2 expression may mediate changes in GPCR signaling duration during memory formation.
Taken together, Rgs2 deletion promotes increased anxiety-like and depression-like behavior, altered stress reactivity as well as increased cognitive function.
Serotonin (5-HT) has been implicated in the regulation of emotions as well as in its pathological states, such as anxiety disorders and depression. Mice with targeted deletion of genes encoding various mediators of central serotonergic neurotransmission therefore provides a powerful tool in understanding contributions of such mediators to homeostatic mechanisms as well as to the development of human emotional disorders. Within this thesis a battery of electrophysiological recordings were conducted in the dorsal raphe nucleus (DRN) and the hippocampus of two murine knockout lines with deficient serotonergic systems. Serotonin transporter knockout mice (5-Htt KO), which lack protein responsible for reuptake of 5-HT from the extracellular space and tryptophan hydroxylase 2 knockout (Tph2 KO) mice, which lack the gene encoding the neuronal 5-HT-synthesising enzyme. First, 5-HT1A receptor-mediated autoinhibition of serotonergic neuron firing in the DRN was assessed using the loose-seal cell-attached configuration. Stimulation of 5-HT1A receptors by a selective agonist, R-8-hydroxy-2-(di-n-propylamino)tetralin (R-8-OH-DPAT), showed a mild sensitisation and a marked desensitisation of these receptors in Tph2 KO and 5-Htt KO mice, respectively. While application of tryptophan, a precursor of 5-HT and a substrate of Tph2, did not cause autoinhibition in Tph2 KO mice due to the lack of endogenously produced 5-HT, data from 5-Htt KO mice as well as heterozygous mice of both KO mice lines demonstrated the presence of autoinhibitory mechanisms as normal as seen in wildtype (WT) controls. When the Tph2-dependent step in the 5-HT synthesis pathway was bypassed by application of 5-hydroxytryptophan (5-HTP), serotonergic neurons of both Tph2 KO and 5-Htt KO mice showed decrease in firing rates at lower concentrations of 5-HTP than in WT controls. Elevated responsiveness of serotonergic neurons from Tph2 KO mice correspond to mild sensitisation of 5-HT1A receptors, while responses from 5-Htt KO mice suggest that excess levels of extracellular 5-HT, created by the lack of 5-Htt, stimulates 5-HT1A receptors strong enough to overcome desensitisation of these receptors. Second, the whole-cell patch clamp recording data from serotonergic neurons in the DRN showed no differences in basic electrophysiological properties between Tph2 KO and WT mice, except lower membrane resistances of neurons from KO mice. Moreover, the whole-cell patch clamp recording from CA1 pyramidal neurons in the hippocampus of 5-Htt KO mice showed increased conductance both at a steady state and at action potential generation. Lastly, magnitude of long-term potentiation (LTP) induced by the Schaffer collateral/commissural pathway stimulation in the ventral hippocampus showed no differences among Tph2 KO, 5-Htt KO, and WT counterparts. Taken together, lack and excess of extracellular 5-HT caused sensitisation and desensitisation of autoinhibitory 5-HT1A receptors, respectively. However, this may not directly translate to the level of autoinhibitory regulation of serotonergic neuron firing when these receptors are stimulated by endogenously synthesised 5-HT. In general, KO mice studied here showed an astonishing level of resilience to genetic manipulations of the central serotonergic system, maintaining overall electrophysiological properties and normal LTP inducibility. This may further suggest existence of as-yet-unknown compensatory mechanisms buffering potential alterations induced by genetic manipulations.
Integrating neurobiological markers of depression: an fMRI-based pattern classification approach
(2010)
While depressive disorders are, to date, diagnosed based on behavioral symptoms and course of illness, the interest in neurobiological markers of psychiatric disorders has grown substantially in recent years. However, current classification approaches are mainly based on data from a single biomarker, making it difficult to predict diseases such as depression which are characterized by a complex pattern of symptoms. Accordingly, none of the previously investigated single biomarkers has shown sufficient predictive power for practical application. In this work, we therefore propose an algorithm which integrates neuroimaging data associated with multiple, symptom-related neural processes relevant in depression to improve classification accuracy. First, we identified the core-symptoms of depression from standard classification systems. Then, we designed and conducted three experimental paradigms probing psychological processes known to be related to these symptoms using functional Magnetic Resonance Imaging. In order to integrate the resulting 12 high-dimensional biomarkers, we developed a multi-source pattern recognition algorithm based on a combination of Gaussian Process Classifiers and decision trees. Applying this approach to a group of 30 healthy controls and 30 depressive in-patients who were on a variety of medications and displayed varying degrees of symptom-severity allowed for high-accuracy single-subject classification. Specifically, integrating biomarkers yielded an accuracy of 83% while the best of the 12 single biomarkers alone classified a significantly lower number of subjects (72%) correctly. Thus, integrated biomarker-based classification of a heterogeneous, real-life sample resulted in accuracy comparable to the highest ever achieved in previous single biomarker research. Furthermore, investigation of the final prediction model revealed that neural activation during the processing of neutral facial expressions, large rewards, and safety cues is most relevant for over-all classification. We conclude that combining brain activation related to the core-symptoms of depression using the multi-source pattern classification approach developed in this work substantially increases classification accuracy while providing a sparse relational biomarker-model for future prediction.