SAT0070 PROTEOMIC SPECTRUM PROFILE IN INFLAMMATORY AND DEGENERATIVE ARTHRITIS
Authors: Abeer Abdelati, Rasha Ghazala, Rehab Elnemr, Fatema Dweedar, Reham Shams-Eldeen, Noha Kandeel
Journal: Annals of the Rheumatic Diseases (2019)

<h3>Background</h3> The identification and quantification of protein biomarkers present in tissues and body fluids is a new area of interest in the clinical management of rheumatic diseases. Proteomics may identify novel biomarker(s) which assist in understanding the pathogenesis of rheumatic disorders with diagnostic and prognostic implications. In addition, proteomic techniques in RA may be helpful to identify newer autoantibodies and inflammatory acute phase proteins. Yet, the integration of potential biomarkers resulting from rheumatic proteomics analyses in differential diagnosis of rheumatologic disorders is not yet fully established and so several studies are needed to confirm the efficacy of these approaches. <h3>Objectives</h3> The purpose of this study was to use Matrix Assisted Laser Desorption Ionization – Time of Flight – Mass Spectrometry (MALDI-TOF-MS) to identify differentially expressed disease-related and condition-specific peptide in serum of patients with Rheumatoid arthritis (RA) and osteoarthritis (OA). <h3>Methods</h3> Hundred participants were divided into three groups as following: RA group (35 patients with Rheumatoid arthritis representing patients with inflammatory arthritis); OA group (35 patients with Osteoarthritis representing patients with non-inflammatory arthritis); healthy control group (30 healthy volunteers). All participants were subjected to full history taking; clinical examination; and clinical Assessment of disease activity in RA patients using Disease activity score 28 (DAS-28); routine laboratory investigations; Acute phase reactants; serological tests; plain x-ray of affected joints, as well as serum proteomic profile using Magnetic beads (MB) separation and (MALDI – TOF – MS<b>).<sup>[1]</sup></b> Using the spectral data from the three groups, three different classification models for the three groups were generated using GA, SNN and QC algorithms. The GA model showed the best sensitivity and specificity in the three trials (RA versus control, OA versus control, and RA versus OA). <h3>Results</h3> In comparing RA versus control group; the results revealed 101 peaks that discriminated the RA from the control group; 53 were significant (PWKW p&gt;0.05) and 48 nonsignificant. Three peaks (14;25;62) were significant and 2 were nonsignificant (43;53). Regarding OA versus control group; 95 peaks were identified that discriminated the OA from the control group; 38 were significant (PWKW p&gt;0.05) and 57 nonsignificant. Three peaks (18;3;14) were significant and peak 75 and 23 were nonsignificant. Finally the RA group was discriminated from the OA group, the trial showed 113 peaks 73 were significant (PWKW p&gt;0.05) and 40 nonsignificant. Five peaks were integrated (75:7767.82 40:2953.29 41:2991.59 48:4054.75 68:6434.51), and all integrated peaks were significant. The integrated peaks showed that all peaks were downregulated except peak 40 was upregulated. <h3>Conclusion</h3> Data obtained from proteomic analysis allow differentiation between RA, OA, and healthy subjects. Because of its simplicity and accuracy, (MALDI–TOF–MS) is a promising method for identifying differentially expressed inflammatory versus degenerative disease-related peptide. <h3>Reference</h3> [1] Lorenz P, Ruschpler P, Koczan D, Stiehl P, Thiesen HJ. From transcriptome to proteome: differentially expressed proteins identified in synovial tissue of patients suffering from rheumatoid arthritis and osteoarthritis by an initial screen with a panel of 791 antibodies. Proteomics2003; 3(6): 991–1002. <h3>Disclosure of Interests</h3> None declared