Molecular validation of the acute phencyclidine rat model for schizophrenia: identification of translational changes in energy metabolism and neurotransmission.

Administration of the noncompetitive N-methyl-D-aspartate (NMDA) receptor antagonist phencyclidine (PCP) to rodents is widely used as preclinical model for schizophrenia. Most studies on this model employ methods investigating behavior and brain abnormalities. However, little is known about the corresponding peripheral effects. In this study, we analyzed changes in brain and serum molecular profiles, together with alterations in behavior after acute PCP treatment of rats. Furthermore, abnormalities in peripheral protein expression of first and recent onset antipsychotic free schizophrenia patients were assessed for comparison with the preclinical model. PCP treatment induced hyperlocomotion and stereotypic behavior, which have been related to positive symptoms of schizophrenia. Multiplex immunoassay profiling of serum revealed molecular abnormalities similar to those seen in first and recent onset, antipsychotic free schizophrenia patients. Also, increased insulin levels were detected after administration of a glucose tolerance test (GTT), consistent with previous studies showing changes in insulin signaling in patients with schizophrenia. Finally, schizophrenia-relevant alterations in brain molecules were found in the hippocampus and to a lesser extent in the frontal cortex using liquid-chromatography mass spectrometry and (1)H nuclear magnetic resonance spectroscopy. In conclusion, this study identified behavioral and molecular alterations in the acute PCP rat model, which are also observed in human schizophrenia. We propose that the corresponding changes in serum in both animals and patients may have utility as surrogate markers in this model to facilitate discovery and development of novel drugs for treatment of certain pathological features of schizophrenia.

Proteomic systems evaluation of the molecular validity of preclinical psychosis models compared to schizophrenia brain pathology.

Pharmacological and genetic rodent models of schizophrenia play an important role in the drug discovery pipeline, but quantifying the molecular similarity of such models with the underlying human pathophysiology has proved difficult. We developed a novel systems biology methodology for the direct comparison of anterior prefrontal cortex tissue from four established glutamatergic rodent models and schizophrenia patients, enabling the evaluation of which model displays the greatest similarity to schizophrenia across different pathophysiological characteristics of the disease. Liquid chromatography coupled tandem mass spectrometry (LC-MSE) proteomic profiling was applied comparing healthy and "disease state" in human post-mortem samples and rodent brain tissue samples derived from models based on acute and chronic phencyclidine (PCP) treatment, ketamine treatment or NMDA receptor knockdown. Protein-protein interaction networks were constructed from significant abundance changes and enrichment analyses enabled the identification of five functional domains of the disease such as "development and differentiation", which were represented across all four rodent models and were thus subsequently used for cross-species comparison. Kernel-based machine learning techniques quantified that the chronic PCP model represented schizophrenia brain changes most closely for four of these functional domains. This is the first study aiming to quantify which rodent model recapitulates the neuropathological features of schizophrenia most closely, providing an indication of face validity as well as potential guidance in the refinement of construct and predictive validity. The methodology and findings presented here support recent efforts to overcome translational hurdles of preclinical psychiatric research by associating functional dimensions of behaviour with distinct biological processes.

A combined metabonomic and proteomic approach identifies frontal cortex changes in a chronic phencyclidine rat model in relation to human schizophrenia brain pathology.

Current schizophrenia (SCZ) treatments fail to treat the broad range of manifestations associated with this devastating disorder. Thus, new translational models that reproduce the core pathological features are urgently needed to facilitate novel drug discovery efforts. Here, we report findings from the first comprehensive label-free liquid-mass spectrometry proteomic- and proton nuclear magnetic resonance-based metabonomic profiling of the rat frontal cortex after chronic phencyclidine (PCP) intervention, which induces SCZ-like symptoms. The findings were compared with results from a proteomic profiling of post-mortem prefrontal cortex from SCZ patients and with relevant findings in the literature. Through this approach, we identified proteomic alterations in glutamate-mediated Ca(2+) signaling (Ca(2+)/calmodulin-dependent protein kinase II, PPP3CA, and VISL1), mitochondrial function (GOT2 and PKLR), and cytoskeletal remodeling (ARP3). Metabonomic profiling revealed changes in the levels of glutamate, glutamine, glycine, pyruvate, and the Ca(2+) regulator taurine. Effects on similar pathways were also identified in the prefrontal cortex tissue from human SCZ subjects. The discovery of similar but not identical proteomic and metabonomic alterations in the chronic PCP rat model and human brain indicates that this model recapitulates only some of the molecular alterations of the disease. This knowledge may be helpful in understanding mechanisms underlying psychosis, which, in turn, can facilitate improved therapy and drug discovery for SCZ and other psychiatric diseases. Most importantly, these molecular findings suggest that the combined use of multiple models may be required for more effective translation to studies of human SCZ.

The application of selective reaction monitoring confirms dysregulation of glycolysis in a preclinical model of schizophrenia.

BACKGROUND: Establishing preclinical models is essential for novel drug discovery in schizophrenia. Most existing models are characterized by abnormalities in behavioral readouts, which are informative, but do not necessarily translate to the symptoms of the human disease. Therefore, there is a necessity of characterizing the preclinical models from a molecular point of view. Selective reaction monitoring (SRM) has already shown promise in preclinical and clinical studies for multiplex measurement of diagnostic, prognostic and treatment-related biomarkers. METHODS: We have established an SRM assay for multiplex analysis of 7 enzymes of the glycolysis pathway which is already known to be affected in human schizophrenia and in the widely-used acute PCP rat model of schizophrenia. The selected enzymes were hexokinase 1 (Hk1), aldolase C (Aldoc), triosephosphate isomerase (Tpi1), glyceraldehyde-3-phosphate dehydrogenase (Gapdh), phosphoglycerate mutase 1 (Pgam1), phosphoglycerate kinase 1 (Pgk1) and enolase 2 (Eno2). The levels of these enzymes were analyzed using SRM in frontal cortex from brain tissue of PCP treated rats. RESULTS: Univariate analyses showed statistically significant altered levels of Tpi1 and alteration of Hk1, Aldoc, Pgam1 and Gapdh with borderline significance in PCP rats compared to controls. Most interestingly, multivariate analysis which considered the levels of all 7 enzymes simultaneously resulted in generation of a bi-dimensional chart that can distinguish the PCP rats from the controls. CONCLUSIONS: This study not only supports PCP treated rats as a useful preclinical model of schizophrenia, but it also establishes that SRM mass spectrometry could be used in the development of multiplex classification tools for complex psychiatric disorders such as schizophrenia.

Behavioral and molecular biomarkers in translational animal models for neuropsychiatric disorders.

Modeling neuropsychiatric disorders in animals poses a significant challenge due to the subjective nature of diverse often overlapping symptoms, lack of objective biomarkers and diagnostics, and the rudimentary understanding of the pathophysiology. Successful translational research requires animal models that can inform about disease mechanisms and therapeutic targets. Here, we review behavioral and neurobiological findings from selected animal models, based on presumed etiology and risk factors, for schizophrenia, bipolar disorder, and major depressive disorder. We focus on the use of appropriate statistical tools and newly developed Research Domain Criteria (RDoC) to link biomarkers from animal models with the human disease. We argue that this approach will lead to development of only the most robust animal models for specific psychiatric disorders and may ultimately lead to better understanding of the pathophysiology and identification of novel biomarkers and therapeutic targets.