Studies in patients with rheumatoid arthritis, serum proteomics

Objective:To discover novel potential biomarkers for early-stage RA and to discover predictive factors for therapeutic response of TNF-a antagonists by using MALDI-TOF-MS combined with magnetic beads.Methods:The sera samples from RA patients and healthy controls were collected, and frozen at-80°C until thawed specifically for MALDI-TOF-MS analysis combined with weak cationic exchange magnetic beads. Proteomic fingerprinting of serum was identified and analyzed using Biomarker Wizard Software and Biomarker Patterns Software. A decision tree model which represented the highest sensitivity and specificity for differentiating early-stage RA patients from healthy controls was selected.Results:①We found16discriminative protein peaks between early-stage RA patients and healthy controls, and a decision tree model consisting of3protein peaks with m/z (mass to charge) value of8885.88、7974.48、2017.03was developed, which could distinguish early-stage RA from healthy controls with sensitivity of94.872%and specificity of96.552%.②Several protein markers were identified to be significantly different in patients before and after receiving TNF-α antagonists treatment and three of them (6431.93Da、8067.02Da、15901.5Da) had the similar variation trend in ETA and INF groups. The protein marker of7930.687Da was up-regulated in responsive group (ACR20positive) with INF treatment. The protein markers of2203.471Da,6472.352Da were up-regulated in responsive group (ACR20positive) with ETA treatment, while15343.48Da was down-regulated in nonresponsive group.③We found13discriminative protein peaks between the two groups receiving MTX or TNF-α antagonists, but only3discriminative protein peaks with similar intensity were found between ETA and INF groupConclusion:MALDI-TOF MS combined with magnetic beads was an effective technology to discover new biomarkers. Our decision tree model could differentiate early-stage RA patients from normal controls with good sensitivity and specificity. We also discovered4serum protein biomarkers which could predict the clinical response to TNF-α antagonists. Objective:To purify and identify the protein at11680Da in sera of RA patients using proteomic technology, and investigate the relationship between SAA and disease activity.Method:The protein of11.7kD was purified using SDS-PAGE and immuno-precipitation, and identified through LC-ESI-MS/MS and Western-Blot.Result:A distinct band was found at12kD in SDS-PAGE, which was identified as serum amyloid A(SAA) through LC-ESI-MS/MS. SAA was proved to be over-expressed in RA patients through the method of Western-Blot, and intensity of SAA tested by MALDI-TOF-MS significantly correlated with disease activity (DAS28) and ESR(p<0.01).Conclusion:SAA is over-expressed in RA patients, and might be an alternative index of inflammation and curative effect.