Organized neuronal firing is critical for cortical processing and is disrupted in schizophrenia. Using 5’ RACE in human brain, we identified a primate-specific isoform (3.1) of the K+-channel KCNH2 that modulates neuronal firing. KCNH2-3.1 mRNA levels are comparable to KCNH2-1A in brain, but 1000-fold lower in heart. In schizophrenic hippocampus, KCNH2-3.1 expression is 2.5-fold greater than KCNH2-1A. A meta-analysis of 5 clinical samples (367 families, 1158 unrelated cases, 1704 controls) shows association of SNPs in KCNH2 with schizophrenia. Risk-associated alleles predict lower IQ scores and speed of cognitive processing, altered memory-linked fMRI signals, and increased KCNH2-3.1 expression in post-mortem hippocampus. KCNH2-3.1 lacks a domain critical for slow channel deactivation. Overexpression of KCNH2-3.1 in primary cortical neurons induces a rapidly deactivating K+ current and a high-frequency, non-adapting firing pattern. These results identify a novel KCNH2 channel involved in cortical physiology, cognition, and psychosis, providing a potential new psychotherapeutic drug target.
Understanding mental disorders and their neurobiological basis encompasses the conceptual management of "complexity" and "dynamics". For example, affective disorders exhibit several fluctuating state variables on psychological and biological levels and data collected of these systems levels suggest quasi-chaotic periodicity leading to use concepts and tools of the mathematics of nonlinear dynamic systems. Regarding this, we demonstrate that the concept of "Dynamic Diseases" could be a fruitful way for theory and empirical research in neuropsychiatry. In a first step, as an example, we focus on the analysis of dynamic cortisol regulation that is important for understanding depressive disorders. In this case, our message is that extremely complex phenomena of a disease may be explained as resulting from perplexingly simple nonlinear interactions of a very small number of variables. Additionally, we propose that and how widely used complex circuit diagrams representing the macroanatomic structures and connectivities of the brain involved in major depression or other mental disorders may be "animated" by quantification, even by using expert-based estimations (dummy variables). This method of modeling allows to develop exploratory computer-based numerical models that encompass the option to explore the system by computer simulations (in-silico experiments). Also inter- and intracellular molecular networks involved in affective disorders could be modeled by this procedure. We want to stimulate future research in this theoretical context.
Synapses are essential functional units of neurons in complex neuronal networks. Disturbances of their functions can have profound consequences and lead to psychiatric disorders. For instance, in schizophrenia and addiction the infl uence of dopamine synapses is being discussed, whereas norepinephrine and serotonin synapses appear to be major players in depression. Various treatments of these diseases try to infl uence synaptic transmission by molecular switches such as receptor blockades, reuptake blockers or by inhibiting enzymatic degradation of transmitters, etc. This means that not only synaptic molecular mechanisms, but also electrophysiological properties can be modulated. Often, signifi cant treatment takes as long as 10 days to show any eff ect. Although important progress has been made in the treatment of mental disorders, psychopharmacological treatment is not entirely satisfying, especially regarding its side eff ects. It follows, that we do not suffi ciently understand the dynamics of pathology and the reorganization of synapses. For this reason, the dynamics of various components of synaptic transmission should be studied further: e. g. the kinetics of control of synthesis, storage, release, reuptake, degradation, receptor occupation, up-, and down-regulatory events. First models representing these mechanisms are presented in the accordant scientifi c literature: Modelling the synthesis of dopamine, modelling the transmission from electrical signalling to intrasynaptic transmitter concentration and to postsynaptic electrical singalling. It seems useful to compare these models regarding their concepts of the neuropathology of mental disorders and their eff ects in terms of psychopharmaceuticals. This approach is fundamental to the molecular biological research, integrating more and more the perspective of systems biology. Systems biology aims to reconstruct the cell on the basis of molecular biological data. This " bottom-up " reconstruction is based on quantitative kinetic data that are integrated in mathematical models transformed into computerized models. By creating these models " in-silico " , computational experiments can be performed that help to understand processes in complex networks of chemical pathways.In 2005, we started a series of workshops on " Computational Neuropsychiatry " , with the aim to combine the views of clinical psychiatry with experimental neurobiology and computational sciences. We began with a workshop led by Arvid Carlsson and discussed his models of networks in schizophrenia. In 2006, we organized a second workshop in order to discuss clinical and experimental data and theoretical concepts of disturbances of working memory, the way it is observed in patients with schizophrenia. A year later, we discussed the perspective of molecular systems biology on schizophrenia. In 2008, we applied these experiences to addiction diseases. There we report on our discussion of the systems biology of the synapse that was organized in 2009. That workshop kindly was supported by Essex, ...
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