Background/Purpose: Psoriatic arthritis (PsA) is a unique form of arthritis occurring in 30% of psoriasis patients. There is a high prevalence of undiagnosed PsA in patients seen in dermatology clinics and identifying soluble biomarkers for PsA will help in screening psoriasis patients for appropriate referral to a rheumatologist, as well as provide further insight into disease pathogenesis. However, identification of novel biomarkers in peripheral blood is difficult and unreliable. Potential PsA biomarkers are likely to originate in sites of inflammation such as inflamed joints and subsequently enter systemic circulation. Our purpose was to identify candidate PsA biomarkers by conducting high-throughput quantitative proteomic analysis of synovial fluid from inflammatory and non-inflammatory arthritides.

Methods: Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer in conjunction with database searching for protein identification and quantification, we extensively characterized the proteomes of SF from 3 individual PsA patients, as well as 2 Rheumatoid Arthritis (RA), 2 Gout, 3 Late Osteoarthritis (LOA), and 3 pooled non-inflammatory (NI) controls. All samples were analysed in triplicates, and extracted ion current (XIC) intensities were used to calculate protein abundance ratios. Two strategies were then employed for identification of candidate biomarkers: (1) examination of differential protein expression between the PsA, RA, Gout, LOA, and Non-Inflammatory controls, and (2) tissue specificity analysis through mining of publicly available databases

Results: A total of 594 non-redundant proteins were identified with one peptide (384 with two-peptides or more) in SF from all arthritis subsets, with a false discovery rate <1.5%. Of the 521 high-confidence proteins that were quantified from all patient groups, there were significant quantitative differences in 89 PsA SF-derived proteins compared to other arthritides. Following additional manual filtering, we obtained a preliminary list of 35 proteins as increased in PsA compared to all arthritic and non-inflammatory controls. Gene ontology (GO) analysis classified these proteins into categories pertaining to five main biological processes: complement activation, defense response, immunoglobulin mediated response, response to wounding, and extracellular matrix remodelling, all of which are attributes of PsA. The candidate proteins include also COMP, CD14, and MMP2, all of which have been previously investigated as PsA biomarkers.

Conclusion: Quantitative proteomic profiling of synovial fluid has the potential to identify candidate PsA screening biomarkers. Verification and validation of these markers in SF and serum, respectively, is essential and is currently under way.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/proteomic-profiling-of-synovial-fluid-reveals-candidate-psoriatic-arthritis-biomarkers/