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Mass spectrometric analysis of prefrontal cortex proteins in schizophrenia and bipolar disorder
BACKGROUND: Schizophrenia and bipolar disorder are the two most serious and debilitating neuropsychiatric disorders that share many characteristics, both symptomatic and epidemiological. There has yet to be a single diagnostic biomarker discovered for schizophrenia and bipolar disorder. Proteomics h...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3581108/ https://www.ncbi.nlm.nih.gov/pubmed/23984221 http://dx.doi.org/10.1186/2193-1801-1-3 |
Sumario: | BACKGROUND: Schizophrenia and bipolar disorder are the two most serious and debilitating neuropsychiatric disorders that share many characteristics, both symptomatic and epidemiological. There has yet to be a single diagnostic biomarker discovered for schizophrenia and bipolar disorder. Proteomics holds promise in elucidating the pathophysiology of these neuropsychiatric disorders from each other and healthy individuals. FINDINGS: Postmortem prefrontal cortex tissue from schizophrenia, bipolar disorder, and psychiatric-free controls (n = 35 in each group) were subject to SELDI-TOF-MS protein profiling. There were 13 protein peaks distinguishing schizophrenia versus control and 15 in bipolar versus control. Using a predictor set of 10 peaks for each comparison, 73% prediction accuracy (p = 2.3×10(−4)) was achieved. Three peaks were in common between schizophrenia and bipolar disorder. CONCLUSIONS: This pilot study found protein profiles that distinguished schizophrenia and bipolar patients from controls and notably from each other. Identifying and characterizing the proteins in this study may elucidate neuropsychiatric phenotypes and uncover therapeutic targets. Further, applying class prediction bioinformatics may allow the clinician to differentiate the two phenotypes by profiling CSF or even serum. |
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