Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach
| العنوان: | Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach |
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| المؤلفون: | Marie-Alice Meuwis, Michel Malaise, Laurence Lutteri, Vincent Bours, Clio Ribbens, Louis Wehenkel, Jacques Piette, Pierre Geurts, Marianne Fillet, Marie-Paule Merville, Dominique de Seny |
| المصدر: | Arthritis & Rheumatism. 52:3801-3812 |
| بيانات النشر: | Wiley, 2005. |
| سنة النشر: | 2005 |
| مصطلحات موضوعية: | Adult, Male, Oncology, medicine.medical_specialty, Immunology, Protein Array Analysis, Arthritis, Osteoarthritis, Mass spectrometry, Peptides, Cyclic, Sensitivity and Specificity, Arthritis, Rheumatoid, Psoriatic arthritis, Crohn Disease, Rheumatology, Internal medicine, medicine, Humans, Immunology and Allergy, Pharmacology (medical), Aged, Autoantibodies, business.industry, Arthritis, Psoriatic, Decision Trees, Reproducibility of Results, Middle Aged, medicine.disease, Surface-enhanced laser desorption/ionization, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization, Rheumatoid arthritis, Female, Time-of-flight mass spectrometry, business, Biomarkers |
| الوصف: | Objective To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. Methods A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps. Results The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti–cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8. Conclusion SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA. |
| تدمد: | 1529-0131 0004-3591 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e430d3166f56f4a6ef6f6573d4b5d09bTest https://doi.org/10.1002/art.21607Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....e430d3166f56f4a6ef6f6573d4b5d09b |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15290131 00043591 |
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