Psoriatic arthritis, a form of inflammatory arthritis that is associated with psoriasis, presents with heterogeneous clinical manifestations making it challenging to diagnose. A range of classification criteria has been developed but diagnosis relies heavily on the experience and expertise of the treating clinician. Furthermore, treatment is often selected on a “trial and error” basis with the patient cycling through various treatments in the hope that one will prove effective and safe. With no specific diagnostic test to discriminate psoriatic arthritis from other arthrophathies and unpredictable patient response to treatment it is accepted widely that there is an urgent and significant as yet unmet need for biomarkers for both.
Despite widespread excitement and expectation that ‘omics technologies will deliver novel multiplexed biomarkers to herald a new era of personalized medicine only a few such ‘omics-derived tests have reached clinical use. Having established an excellent local clinical research capability and multi-disciplinary teams (including clinical investigators, biomedical researchers and statisticians) the we have undertaken focused proteomic biomarker discovery programmes and applied statistical algorithms to identify a panel of novel potential protein biomarkers for psoriatic arthritis. Notably to assemble this novel panel we have taken competitive advantage of excellent local clinical samples, a ‘quantitative proteomics’ mass spectrometry platform and access to a superb multiplex (Luminex) immunoassay facility. We now seek to bridge the important translational gap between discovery and clinical use by (i) developing robust analytically validated measurement of the candidate proteins in a dedicated biomarker validation lab in UCD and QA registered Luminex facility, and (ii) using the highest quality clinical samples obtained through a network of clinical collaborators to evaluate the clinical potential of them and generate data with the potential to support the subsequent large scale clinical trial based validation of the biomarkers for their progression to clinical adoption and utility.
