Background/Purpose:

There is a high prevalence of undiagnosed psoriatic arthritis (PsA) in patients seen in dermatology clinics. 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 protein 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. We hypothesize that quantitative proteomic analysis of synovial fluid (SF) obtained from PsA patients, will generate a comprehensive list of proteins specific to PsA, facilitating the identification of potential PsA screening biomarkers.

Methods:

SF was obtained from swollen knee joints of PsA patients, and age/sex matched early osteoarthritis (OA) controls. Using strong cation exchange chromatography, followed by liquid chromatography and tandem mass spectroscopy, we extensively characterized the proteomes of pooled SF from ten PsA and ten controls. Extracted ion current (XIC) intensities were used to calculate protein abundance ratios, and were utilized to identify upregulated proteins (PsA/OA ratio>2). Selected reaction monitoring (SRM) assays were developed to relatively quantify potential markers in individual SF samples.

Results: We identified and quantified 443 proteins from both groups (False Discovery Rate <0.05). Only 45 proteins represented upregulated proteins in PsA SF (p<0.05). These were investigated using two publicly available databases (Ingenuity Pathway Analysis and DAVID Bioinformatics Resources 6.7) to identify disease relevant proteins. 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 remodeling, all of which are attributes of PsA. Application of subsequent filtering criteria yielded approximately 17 proteins, which served as putative PsA biomarkers. SRM validation confirmed that 13 proteins were indeed elevated in the 10 PsA SF samples, and these included positive controls, MMP3, S100A9, and CRP.

Conclusion:

We have developed and utilized a high-throughput proteomics platform using LC-MS/MS to delineate the SF proteome from PsA patients and controls with early OA. Proteins that were differentially expressed were validated using targeted mass-spectrometric assays. Using these methods we have identified several candidate PsA biomarkers. In the future, these proteins must be verified using highly specific immunoassays in serum, in order to identify their clinical utility.

ACR Meeting Abstracts - https://acrabstracts.org/abstract/proteomic-profiling-of-synovial-fluid-for-the-identification-of-psoriatic-arthritis-soluble-biomarkers/