Serum Peptidomic Profile as a Novel Biomarker for Rheumatoid Arthritis

Abeer A Abdelati; Rehab A Elnemr; Noha S Kandil; Fatma I Dwedar; Rasha A Ghazala

doi:10.1155/2020/6069484

Serum Peptidomic Profile as a Novel Biomarker for Rheumatoid Arthritis

Int J Rheumatol. 2020 Aug 3:2020:6069484. doi: 10.1155/2020/6069484. eCollection 2020.

Authors

Abeer A Abdelati¹, Rehab A Elnemr², Noha S Kandil³, Fatma I Dwedar⁴, Rasha A Ghazala⁴

Affiliations

¹ Department of Internal Medicine, Rheumatology and Clinical Immunology Unit, Faculty of Medicine, Alexandria University, Alexandria 21612, Egypt.
² Department of Physical Medicine Rheumatology and Rehabilitation, Faculty of Medicine, Alexandria University, Alexandria 22511, Egypt.
³ Department of Chemical Pathology, Medical Research Institute, Alexandria University, Alexandria 21523, Egypt.
⁴ Department of Medical Biochemistry, Faculty of Medicine, Alexandria University, Alexandria 21648, Egypt.

Abstract

Over the last decades, there has been an increasing need to discover new diagnostic RA biomarkers, other than the current serologic biomarkers, which can assist early diagnosis and response to treatment. The purpose of this study was to analyze the serum peptidomic profile in patients with rheumatoid arthritis (RA) by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The study included 35 patients with rheumatoid arthritis (RA), 35 patients with primary osteoarthritis (OA) as the disease control (DC), and 35 healthy controls (HC). All participants were subjected to serum peptidomic profile analysis using magnetic bead (MB) separation (MALDI-TOF-MS). The trial showed 113 peaks that discriminated RA from OA and 101 peaks that discriminated RA from HC. Moreover, 95 peaks were identified and discriminated OA from HC; 38 were significant (p < 0.05) and 57 nonsignificant. The genetic algorithm (GA) model showed the best sensitivity and specificity in the three trials (RA versus HC, OA versus HC, and RA versus OA). The present data suggested that the peptidomic pattern is of value for differentiating individuals with RA from OA and healthy controls. We concluded that MALDI-TOF-MS combined with MB is an effective technique to identify novel serum protein biomarkers related to RA.