Search

Objective: Patients with rheumatoid arthritis (RA) usually receive triple therapy with methotrexate (MTX), leflunomide (LEF) and infliximab (IFX), but nearly one-third of them do not respond to triple therapy. This study aimed to identify biomarkers for predicting the efficacy of triple therapy to optimize personalized treatment of RA., Methods: All 20 enrolled patients met 2010 ACR/EULAR criteria for RA and were classified into good, moderate and non-responders (GR, MR, NR) for triple therapy. The Responders (R) were defined as the sum of GR and MR. Protein profiles of 4 responders and 4 non-responders were investigated via isobaric tags for relative and absolute quantification (iTRAQ), and differentially expressed proteins (DEPs) with high-confidence peptides were validated in 15 responders and 5 non-responders by parallel response monitoring (PRM)., Results: iTRAQ identified 51 DEPs between responders and non-responders (p < 0.05, fold change >±1.2). The top five up-regulated DEPs were B7Z7M2, A0A087WZR4, Q53FL1, P08254 and G3V2V8, while the top five down-regulated proteins were Q6MZX9, B3KP77, P0DJI9, P0DJI8 and P02787. Targeted mass spectrometry by PRM identified 10 candidate biomarkers, and 3 DEPs including fibrinogen beta chain, epididymal secretory protein Li 282 and testicular tissue protein Li 70 were confirmed as predictive biomarkers., Conclusion: This study demonstrated the feasibility of exploring biomarkers by applying iTRAQ and PRM mass spectrometry techniques, and a panel of biomarkers were identified to predict clinical response of IFX + MTX + LEF treatment in active RA patients., (Copyright © 2019 The Author. Published by Elsevier Masson SAS.. All rights reserved.)

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by progressive joint erosion. Tumor necrosis factor (TNF) antagonists are the most widely used biological disease-modifying anti-rheumatic drug in RA. However, there continue to be one third of RA patients who have poor or no response to TNF antagonists. Following consideration of the uncertainty of therapeutic effects and the high price of TNF antagonists, it is worthy to predict the treatment responses before anti-TNF therapy. According to the comparisons between the responders and non-responders to TNF antagonists by omic technologies, such as genomics, transcriptomics, proteomics, and metabolomics, rheumatologists are eager to find significant biomarkers to predict the effect of TNF antagonists in order to optimize the personalized treatment in RA.

This study aims to investigate the incidence of hepatitis B virus (HBV) reactivation in inflammatory arthritis (IA) patients with HBV infection using anti-tumor necrosis factor (TNF) agents and evaluate the efficacy of antiviral therapy in reducing the risk of viral reactivation in chronic HBV infection. IA patients using anti-TNF agents from six centers were enrolled. Their HBV infection conditions and ALT and HBV-DNA levels were monitored periodically. Among the six chronic hepatitis B patients, HBV reactivation was found in two patients without antivirus prophylaxis and no viral replication was detected in the other four patients with antivirus prophylaxis. In the 31 inactive carriers, the increase of viral load was detected in 6 of 22 (27.3 %) patients without antiviral prophylaxis, and there was no viral reactivation in the other 9 patients with antiviral prophylaxis. HBV reactivation was not found in the 50 patients with resolved HBV infection. It is suggested that anti-TNF therapy might increase the risk of HBV reactivation in patients with chronic HBV infection, and antiviral prophylaxis could effectively decrease the risk. Anti-TNF agents seem to be safe in patients with resolved HBV infection.