Schizophrenia is a chronic, complex and heterogeneous mental disorder, with pathological features of disrupted neuronal excitability and plasticity within limbic structures of the brain. These pathological features manifest behaviorally as positive symptoms (including hallucinations, delusions and thought disorder), negative symptoms (such as social withdrawal, apathy and emotional blunting) and other psychopathological symptoms (such as psychomotor retardation, lack of insight, poor attention and impulse control). Altered glutamate neurotransmission has for decades been linked to schizophrenia, but all commonly prescribed antipsychotics act on dopamine receptors. LY404039 is a selective agonist for metabotropic glutamate 2/3 (mGlu2/3) receptors and has shown antipsychotic potential in animal studies. With data from rodents, we provide new evidence that mGlu2/3 receptor agonists work by a distinct mechanism different from that of olanzapine. To clinically test this mechanism, an oral prodrug of LY404039 (LY2140023) was evaluated in schizophrenic patients with olanzapine as an active control in a randomized, three-armed, double-blind, placebo-controlled study. Treatment with LY2140023, like treatment with olanzapine, was safe and well-tolerated; treated patients showed statistically significant improvements in both positive and negative symptoms of schizophrenia compared to placebo (P < 0.001 at week 4). Notably, patients treated with LY2140023 did not differ from placebo-treated patients with respect to prolactin elevation, extrapyramidal symptoms or weight gain. These data suggest that mGlu2/3 receptor agonists have antipsychotic properties and may provide a new alternative for the treatment of schizophrenia.

We present a wrapper-based approach to estimate and control the false discovery rate for peptide identifications using the outputs from multiple commercially available MS/MS search engines. Features of the approach include the flexibility to combine output from multiple search engines with sequence and spectral derived features in a flexible classification model to produce a score associated with correct peptide identifications. This classification model score from a reversed database search is taken as the null distribution for estimating p-values and false discovery rates using a simple and established statistical procedure. Results from 10 analyses of rat sera on an LTQ-FT mass spectrometer indicate that the method is well calibrated for controlling the proportion of false positives in a set of reported peptide identifications while correctly identifying more peptides than rule-based methods using one search engine alone.

Recognizing specific protein changes in response to drug administration in humans has the potential for significant utility in clinical research. In spite of this, many methodological and practical questions related to assessing such changes are unanswered. We conducted a series of clinical studies to assess the feasibility of measuring changes in proteins related to drug administration using a mass-spectrometry proteomics technique capable of quantifying hundreds of proteins simultaneously in cerebrospinal fluid (CSF) and plasma. Initially, the normal variability of proteins in these compartments was characterized in 16 healthy volunteers over a 2-week period. Drug-associated changes were subsequently assessed in the plasma and CSF proteomes of 11 subjects given atomoxetine, which served as a selective, centrally active probe to test the model. Protein levels in the CSF and plasma were unchanged between visits in the normal variability study. In contrast, statistically significant changes were detected in the CSF protein pattern after drug treatment. These studies suggest that identification of changes in the CSF proteome associated with the administration of centrally active drugs is feasible, and may be of value in the development of new drugs, as well as broader clinical research.

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