Discovery of serum protein biomarkers in rheumatoid arthritis using MALDI-TOF-MS combined with magnetic beads

2011 ◽  
Vol 12 (3) ◽  
pp. 145-151 ◽  
Author(s):  
Xiaoxue Zhang ◽  
Zhaolin Yuan ◽  
Bo Shen ◽  
Min Zhu ◽  
Chibo Liu ◽  
...  
2010 ◽  
Vol 22 (7) ◽  
pp. 611-618 ◽  
Author(s):  
Q. Niu ◽  
Z. Huang ◽  
Y. Shi ◽  
L. Wang ◽  
X. Pan ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Abeer A. Abdelati ◽  
Rehab A. Elnemr ◽  
Noha S. Kandil ◽  
Fatma I. Dwedar ◽  
Rasha A. Ghazala

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.


The Analyst ◽  
2019 ◽  
Vol 144 (7) ◽  
pp. 2231-2238 ◽  
Author(s):  
Han-Gyu Park ◽  
Kyoung-Soon Jang ◽  
Hae-Min Park ◽  
Won-Suk Song ◽  
Yoon-Yi Jeong ◽  
...  

Serum is one of the most commonly used samples in many studies to identify protein biomarkers to diagnose cancer.


2012 ◽  
Vol 295 (7) ◽  
pp. 1168-1173 ◽  
Author(s):  
Xin Wang ◽  
Mei Fen Zhang ◽  
Jing Xie ◽  
Zhi Li Li ◽  
Peng Wang

2011 ◽  
Vol 32 (24) ◽  
pp. 3510-3515 ◽  
Author(s):  
Elena Frisch ◽  
Matthias Kaup ◽  
Karl Egerer ◽  
Andreas Weimann ◽  
Rudolf Tauber ◽  
...  

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