Candidate Biomarkers For Response To Treatment In Psoriatic Disease.

Abstract

To determine whether biologic therapy alters serum CXCL10, MMP3, S100A8, ACP5, and CCL2 levels in psoriatic arthritis (PsA) and psoriasis (PsC) patients, and whether baseline levels of these proteins predict response to treatment for PsA. We included PsA patients on TNF inhibitors (TNFi), Interleukin-17 inhibitors (IL-17i), methotrexate (MTX), and untreated with bDMARDs or csDMARDs (untreated) and PsC patients on bDMARDs and matched untreated. Serum samples at baseline and 3-6 months follow-up were retrieved from the biobank. Protein levels were quantified using a Luminex multiplex assay. We compared follow-up vs baseline protein levels within groups and change in levels between groups. For the predictive potential of the biomarkers, we developed logistic regression classification models. Response to treatment was defined as: 1. Achieving low disease activity or remission (according to DAPSA), 2. 75% reduction in PASI, and 3. 50% reduction in actively inflamed joint count. In PsA, TNFi reduced serum levels of all five proteins, IL-17i increased ACP5 and CCL2, and MTX reduced MMP3. Changes in MMP3 and S100A8 levels were significantly different between untreated PsA and matched biologic-treated PsA (p<0.05). There were no significant differences between treated or untreated PsC patients. Baseline levels of CXCL10, MMP3, S100A8, and ACP5 had good predictive value (AUC>0.8) for response to biologics in PsA patients. Biologics treatment and MTX affect serum CXCL10, MMP3, S100A8, ACP5, and CCL2 levels in PsA patients. MMP3, S100A8, ACP5, and CXCL10 have potential use as serum biomarkers to predict response to treatment for PsA.