Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.
De Seny, Dominique; Fillet, Marianne; Meuwis, Marie-Aliceet al.
2005 • In Arthritis and Rheumatism, 52 (12), p. 3801-12
[en] 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.
Disciplines :
Pharmacy, pharmacology & toxicology
Author, co-author :
De Seny, Dominique ✱; Centre Hospitalier Universitaire de Liège - CHU > Rhumatologie
Fillet, Marianne ✱; Université de Liège - ULiège > Département de pharmacie > Analyse des médicaments
Geurts, Pierre ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Lutteri, Laurence ; Centre Hospitalier Universitaire de Liège - CHU > Chimie médicale
Ribbens, Clio ; Centre Hospitalier Universitaire de Liège - CHU > Rhumatologie
Bours, Vincent ; Centre Hospitalier Universitaire de Liège - CHU > Génétique
Wehenkel, Louis ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Piette, Jacques ; Université de Liège - ULiège > Département des sciences de la vie > GIGA-R : Virologie - Immunologie - GIGA-Research
Malaise, Michel ; Centre Hospitalier Universitaire de Liège - CHU > Rhumatologie
Merville, Marie-Paule ; Université de Liège - ULiège > Département de pharmacie > Chimie médicale
✱ These authors have contributed equally to this work.
Language :
English
Title :
Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.
Publication date :
2005
Journal title :
Arthritis and Rheumatism
ISSN :
0004-3591
eISSN :
1529-0131
Publisher :
Wiley Liss, Inc., New York, United States - New York
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