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Proteomics and Protein Markers |
1 Laboratory of Rheumatology, GIGA Research, CHU, University of Liège; 2 Laboratory of Clinical Chemistry, GIGA Research, University of Liège; 3 GIGA Bioinformatics Platform, University of Liège; 4 Bioinformatics and Modeling Unit, Department of Electrical Engineering & Computer Science, GIGA Research, University of Liège;5 Laboratory of Hepato-Gastroenterology, CHU, University of Liège, Liège, Belgium.
aAddress correspondence to this author at: Laboratory of Rheumatology, Tour GIGA +2, CHU, 4000 Liège, Belgium. Fax (32) 4 366 45 34; e-mail ddeseny{at}chu.ulg.ac.be
Background: SELDI-TOF mass spectrometry (MS) is a high-throughput proteomic approach with potential for identifying novel forms of serum biomarkers of arthritis.
Methods: We used SELDI-TOF MS to analyze serum samples from patients with various forms of inflammatory arthritis. Several protein profiles were collected on different Bio-Rad Laboratories ProteinChip arrays (CM10 and IMAC-Cu2+) and were evaluated statistically to select potential biomarkers.
Results: SELDI-TOF MS analyses identified several calgranulin proteins [S100A8 (calgranulin A), S100A9 (calgranulin B), S100A9*, and S100A12 (calgranulin C)], serum amyloid A (SAA), SAA des-Arg (SAA-R), and SAA des-Arg/des-Ser (SAA-RS) as biomarkers and confirmed the results with other techniques, such as western blotting, immunoprecipitation, and nano-LC-MS/MS. The S100 proteins were all able to significantly differentiate samples from patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and ankylosing spondylitis (AS) from those of patients with inflammatory bowel diseases used as an inflammatory control (IC) group, whereas the SAA, SAA-R, and SAA-RS proteins were not, with the exception of AS. The 4 S100 proteins were coproduced in all of the pathologies and were significantly correlated with the plasma calprotectin concentration; however, these S100 proteins were correlated with the SAA peak intensities only in the RA and IC patient groups. In RA, these S100 proteins (except for S100A12) were significantly correlated with the serum concentrations of C-reactive protein, matrix metalloproteinase 3, and anti–cyclic citrullinated peptide and with the Disease Activity Score (DAS28).
Conclusions: The SELDI-TOF MS technology is a powerful approach for analyzing the status of monomeric, truncated, or posttranslationally modified forms of arthritis biomarkers, such as the S100A8, S100A9, S100A12, and SAA proteins. The fact that the SELDI-TOF MS data were correlated with results obtained with the classic calprotectin ELISA test supports the reliability of this new proteomic technique.
The following articles in journals at HighWire Press have cited this article:
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  A. Baillet, C. Trocme, S. Berthier, M. Arlotto, L. Grange, J. Chenau, S. Quetant, M. Seve, F. Berger, R. Juvin, et al. Synovial fluid proteomic fingerprint: S100A8, S100A9 and S100A12 proteins discriminate rheumatoid arthritis from other inflammatory joint diseases Rheumatology, January 25, 2010; (2010): kep452v1 - kep452. [Abstract] [Full Text] [PDF]
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 L. Chung, A. E. Nelson, K. K. Y. Ho, and R. C. Baxter Proteomic Profiling of Growth Hormone-Responsive Proteins in Human Peripheral Blood Leukocytes J. Clin. Endocrinol. Metab., August 1, 2009; 94(8): 3038 - 3043. [Abstract] [Full Text] [PDF]
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