Background/Purpose:

Rheumatoid arthritis (RA) is a long-lasting inflammatory autoimmune disorder that ultimately leads to the destruction of joint architecture. The activity of this disease is measured by the assessment of clinical symptoms. The aim of this study was to apply a proteomic strategy to find plasma biomarkers able to discriminate patients with different RA activities.

Methods:

80 plasma samples from the IMID (Immune-Mediated Inflammatory Diseases) Consortium, classified according to the DAS28 score into low (40 samples with DAS28: 2,6-3,2) and high (40 samples with DAS28>5,1) activity were randomly selected to be analyzed by mass spectrometry (MS). This study was conducted in two stages: a panel of proteins were firstly selected based on the regulation of the RA activity in an initial discovery phase, followed by the verification and absolute quantitation of this set of proteins on the 80 independent RA samples, using targeted MS.

A shotgun MS strategy was performed in the discovery phase. For this aim, four independent pools of each condition were firstly albumin-depleted, digested and differentially labelled with iTraq 8-plex reagents. Subsequently, the 8 labelled pools were combined, cleaned using StageTips-C18, fractionated by HPLC and analyzed by nanoLC-MS/MS using three different MS equipments. Afterwards, the verification phase was performed by a targeted Multiple Reaction Monitoring (MRM) strategy on a QTRAP 5500 on the 80 independent samples, using 26 synthetic heavy-labelled peptides as internal standards for absolute protein quantitation. The results were analyzed using the proteomic software Skyline and statistical tools from SPSS and PRISM.

Results:

In the discovery stage, 186 proteins were identified by shotgun MS. The abundance of 11 of these proteins was found to be significantly different (p<0.05) between patients with high and low RA activities. To verify these results, a method for the absolute quantitation of this 11-protein panel, based on targeted MS and the use of labelled internal standards, was developed and applied on the 80 RA plasma samples. The data obtained in this verification step showed a significant increase in four of these proteins, in accordance with that observed in the discovery phase: Haptoglobin, Serum Amyloid A1, Alpha-1-antichymotrypsin and Alpha-1-acid Glycoprotein 1. The increased abundance of these four proteins in plasma was significantly associated (p<0.05) with a high disease activity in RA patients. These proteins are related with the RA process and its effects (inflammation and immune disorder in joints), giving significance to the results obtained. This protein panel is being validated in a larger cohort of samples of similar characteristics (including healthy and disease controls) to qualify them for clinical applications.

Conclusion:

A two-step proteomic approach (including both discovery and verification phases) has been followed for the identification of protein biomarkers associated with disease activity in RA patients. A panel of four proteins has been verified as increased in the plasma of patients with high activity, and could be useful for the molecular monitoring of the disease.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/rheumatoid-arthritis-activity-monitoring-and-multiplex-biomarker-verification-by-tageted-proteomics/