Background Psoriatic arthritis (PsA), a form of inflammatory arthritis, associated with psoriasis, presents with heterogeneous manifestations making it challenging to diagnose. With no specific test to distinguish PsA from other arthropathies, notably rheumatoid arthritis (RA), the diagnosis of PsA is often problematic. It is widely acknowledged that the development of a blood based diagnostic test for PsA would be of significant clinical value (1). Candidate markers for PsA and RA have been documented but few have reached clinical use. Development of robust, multiplexed biomarker assays and their clinical validation is a vital bridge in the translational gap between discovery of biomarkers to their clinical validation (1-2).
Objectives To (i) identify candidate biomarkers with potential to distinguish between patients with early PsA and RA (ii) explore the value of combining different protein discovery platforms for the development of biomarker panels.
Methods Serum samples were obtained from a cohort of 64 (32 PsA and 32 RA) patients defined as early onset (<12 months) and DMARD naïve. Baseline samples were analysed using label free LC-MS/MS, Luminex xMAP (3) and SOMAscan technology (4). Statistical analysis was performed using Perseus (version 18.104.22.168), R (version 3.1.0) and SOMAsuite (version 1.0.3).
Results Statistical analysis of data derived from LC-MS/MS, Luminex and SOMAscan analysis revealed a total of 76, 33 and 175 proteins were differentially expressed across the two conditions, respectively. Interestingly there was limited overlap in the proteins identified by the 3 techniques (Figure 1). This was of interest for the proteins analysed by Luminex as 27 of the 33 of these were targeted in the SOMAscan assays. No proteins were shown to change by all 3 platforms. Principal component analysis of 76 differentially expressed proteins in LC-MS/MS data allowed the separation of patients with PsA form RA.Discrimination of PsA from RA was also possible with the two other platforms.
Conclusions Using 3 different and potentially complementary proteomic platforms we identified a panel of proteins differentially expressed in patients with early PsA or RA. These proteins represent candidates for inclusion in a protein signature that might discriminate PsA from RA. There was little overlap in the candidate biomarkers identified across the 3 platforms. This is not surprising given the different methods underlying the platforms and notable differences in their abilities to measure low abundance proteins.
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Disclosure of Interest None declared