Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis
This paper describes the high-throughput proteomic analysis of the dorsolateral prefrontal cortex (DLPFC) from schizophrenia (SCHIZ), bipolar (BD), and normal control cohorts from the Harvard Brain Tissue Resource Center performed using ProteinChip technology based on the surface-enhanced laser deso...
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| Format: | Article |
| Language: | English |
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Elsevier
2006-07-01
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| Series: | Neurobiology of Disease |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0969996106000337 |
| _version_ | 1818417452605767680 |
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| author | Svetlana I. Novikova Fang He Nicholas J. Cutrufello Michael S. Lidow |
| author_facet | Svetlana I. Novikova Fang He Nicholas J. Cutrufello Michael S. Lidow |
| author_sort | Svetlana I. Novikova |
| collection | DOAJ |
| description | This paper describes the high-throughput proteomic analysis of the dorsolateral prefrontal cortex (DLPFC) from schizophrenia (SCHIZ), bipolar (BD), and normal control cohorts from the Harvard Brain Tissue Resource Center performed using ProteinChip technology based on the surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). The resultant profiles were utilized in classification-tree algorithms for selection of protein biomarker peaks contributing maximally to the differentiation between the examined diagnostic cohorts. Twenty-four such protein biomarker peaks were identified. All of them had lower levels in the SCHIZ cohort as compared to the BD cohort. Also, 21 of these peaks were down-regulated in the SCHIZ cohort vs. the control cohort, and 7 peaks were up-regulated in the BD cohort vs. the control cohort. The proteins constituting these biomarker peaks were recognized via matrix-assisted laser desorption time of flight/postsource decay mass spectrometry (MALDI-TOF-PSD-MS). These proteins represent a wide range of functional groups involved in cell metabolism, signaling cascades, regulation of gene transcription, protein and RNA chaperoning, and other aspects of cellular homeostasis. Finally, after statistical evaluation suggesting that the selected protein biomarkers are not significantly impacted by epidemiological/tissue storage parameters (although, influence of antipsychotic and mood stabilizing drugs could not be fully excluded), the ProteinChip-based profiling was engaged again to demonstrate that the detected SCHIZ-associated changes in the levels of our protein biomarkers could also be seen in DLPFC samples from the brain collection of the Mount Sinai Medical School/Bronx Veteran Affairs Medical Center. This study demonstrates the usefulness of ProteinChip-based SELDI-TOF protein profiling in gaining insight into the molecular pathology of SCHIZ and BD as it points to changes in protein levels characterizing these diseases. |
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| format | Article |
| id | doaj.art-b104103c3c5d44fcb6f1e8b8893212a1 |
| institution | Directory Open Access Journal |
| issn | 1095-953X |
| language | English |
| last_indexed | 2024-12-14T12:07:01Z |
| publishDate | 2006-07-01 |
| publisher | Elsevier |
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| series | Neurobiology of Disease |
| spelling | doaj.art-b104103c3c5d44fcb6f1e8b8893212a12022-12-21T23:01:50ZengElsevierNeurobiology of Disease1095-953X2006-07-012316176Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysisSvetlana I. Novikova0Fang He1Nicholas J. Cutrufello2Michael S. Lidow3Dept. of Biomedical Sciences, University of Maryland, HHH, 5-A-12, 666 W. Baltimore Street, Baltimore, MD 21201, USADept. of Biomedical Sciences, University of Maryland, HHH, 5-A-12, 666 W. Baltimore Street, Baltimore, MD 21201, USADept. of Biomedical Sciences, University of Maryland, HHH, 5-A-12, 666 W. Baltimore Street, Baltimore, MD 21201, USACorresponding author. Fax: +1 410 706 0865.; Dept. of Biomedical Sciences, University of Maryland, HHH, 5-A-12, 666 W. Baltimore Street, Baltimore, MD 21201, USAThis paper describes the high-throughput proteomic analysis of the dorsolateral prefrontal cortex (DLPFC) from schizophrenia (SCHIZ), bipolar (BD), and normal control cohorts from the Harvard Brain Tissue Resource Center performed using ProteinChip technology based on the surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). The resultant profiles were utilized in classification-tree algorithms for selection of protein biomarker peaks contributing maximally to the differentiation between the examined diagnostic cohorts. Twenty-four such protein biomarker peaks were identified. All of them had lower levels in the SCHIZ cohort as compared to the BD cohort. Also, 21 of these peaks were down-regulated in the SCHIZ cohort vs. the control cohort, and 7 peaks were up-regulated in the BD cohort vs. the control cohort. The proteins constituting these biomarker peaks were recognized via matrix-assisted laser desorption time of flight/postsource decay mass spectrometry (MALDI-TOF-PSD-MS). These proteins represent a wide range of functional groups involved in cell metabolism, signaling cascades, regulation of gene transcription, protein and RNA chaperoning, and other aspects of cellular homeostasis. Finally, after statistical evaluation suggesting that the selected protein biomarkers are not significantly impacted by epidemiological/tissue storage parameters (although, influence of antipsychotic and mood stabilizing drugs could not be fully excluded), the ProteinChip-based profiling was engaged again to demonstrate that the detected SCHIZ-associated changes in the levels of our protein biomarkers could also be seen in DLPFC samples from the brain collection of the Mount Sinai Medical School/Bronx Veteran Affairs Medical Center. This study demonstrates the usefulness of ProteinChip-based SELDI-TOF protein profiling in gaining insight into the molecular pathology of SCHIZ and BD as it points to changes in protein levels characterizing these diseases.http://www.sciencedirect.com/science/article/pii/S0969996106000337HumansDorsolateral prefrontal cerebral cortexMental disordersProteomicsClassification-tree algorithms |
| spellingShingle | Svetlana I. Novikova Fang He Nicholas J. Cutrufello Michael S. Lidow Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis Neurobiology of Disease Humans Dorsolateral prefrontal cerebral cortex Mental disorders Proteomics Classification-tree algorithms |
| title | Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis |
| title_full | Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis |
| title_fullStr | Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis |
| title_full_unstemmed | Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis |
| title_short | Identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using SELDI-TOF-MS ProteinChip profiling combined with MALDI-TOF-PSD-MS analysis |
| title_sort | identification of protein biomarkers for schizophrenia and bipolar disorder in the postmortem prefrontal cortex using seldi tof ms proteinchip profiling combined with maldi tof psd ms analysis |
| topic | Humans Dorsolateral prefrontal cerebral cortex Mental disorders Proteomics Classification-tree algorithms |
| url | http://www.sciencedirect.com/science/article/pii/S0969996106000337 |
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