Although several new biomarkers have been recently proposed for psoriasis (Ps) and psoriasis arthritis (PsA), nothing is known about their diagnostic sensitivity and specificity, and their routine use. We therefore searched in-depth for new biomarker candidates using a biobank with EDTA-plasma from 158 individuals, patients and healthy controls. Samples from 6 selected pairs (patients against healthy controls) were searched proteomically using a workflow of extensive and precise design that is highly comprehensive. Subsequent verification was performed using ELISA and the entire biobank. By proteomic methods, 208 altered proteins were identified. Of these, 15 biomarker candidates were selected for verification. Of these 15, 4 individual parameters and 11 combinations significantly discriminated between patient and control groups. These individual parameters were Zn-α2-glycoprotein, complement C3, polymeric immunoglobulin receptor, and plasma kallikrein. Significant discrimination was obtained by combinations of 2 or 3 parameters. One combination seemed suitable for diagnosing PsA. Moreover, several candidates desmoplakin, complement C3, polymeric immunoglobulin receptor, and cytokeratin 17, correlated with PASI in all patients. This first comprehensive proteomic study on non-depleted plasma identified several biomarker candidates that have not been described before as well as some known from previous studies.
Biological significance: Our non-gel proteomic analysis is based on the highly comprehensive and significantly optimized chromatographic protein pre-fractionation. The method allows a biomarker search in non-depleted plasma. The subsequent verification by ELISA identifies several biomarker-candidates for the unbiased diagnosis of psoriasis and psoriasis arthritis. Four of the identified candidate markers might be used individually. Combinations of several parameters improve the diagnostic sensitivity and specificity. The still not validated candidates form a reserve for further evaluation. Moreover, mass spectrometric data uncover several biomarker-candidates which show diverse protein species of the same protein with opposing changes in the same sample.
Keywords: Chromatographic pre-fractionation; Plasma biomarker; Psoriasis.
Copyright © 2016 Elsevier B.V. All rights reserved.