Serum protein biomarker panel may help distinguish Psoriatic arthritis from rheumatoid arthritis
Recent research published in the Arthritis & Rheumatology Journal has observed that a serum protein biomarker panel which can separate inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA).
Angela Mc Ardle and colleagues from the UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Ireland carried out the present study to identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) and may be used to support appropriate early intervention.
The serum proteome of patients with PsA and RA was interrogated using nano-flow liquid chromatography mass spectrometry (nLC-MS/MS) (n=64 patients), an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients) and a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients).
Multiple reaction monitoring assays (MRM) were developed to evaluate the performance of putative markers using the discovery cohort (n=60) and subsequently an independent cohort of PsA and RA patients (n=167).
The following findings were revealed-
- Multivariate machine learning analysis of the protein discovery data from the three platforms revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for bead based immunoassay measurements and 0.73 for aptamer based analysis.
- Subsequently in the separate verification and evaluation studies, random forest models revealed that a subset of proteins measured by MRM could differentiate PsA and RA patients with AUCs of 0.79 and 0.85 respectively.
Therefore, the authors concluded that "there is a serum protein biomarker panel which can separate EIA patients with PsA from those with RA."
With continued evaluation and refinement using additional and larger patient cohorts including those with other arthropathies we suggest the panel identified here could contribute toward improved clinical decision making, they further added.
