Prediction of Psoriatic Arthritis in Patients With Psoriasis Using DNA Methylation Profiles

Abstract

ObjectivePsoriatic arthritis (PsA) is an immune‐mediated inflammatory arthritis, associated with psoriasis, that significantly increases morbidity and mortality risk. We currently lack the means of predicting which psoriasis patients will develop PsA, and a large number of patients remain undiagnosed. Regulation of gene expression through DNA methylation can potentially trigger and maintain PsA pathophysiological processes. We aimed to identify DNA methylation markers that can predict which psoriasis patients will develop PsA prior to the onset of musculoskeletal symptoms.MethodsGenome‐wide DNA methylation was assessed in blood samples from psoriasis patients that went on to develop arthritis (converters) and psoriasis patients that did not (biologic naive, matched for age, sex, psoriasis duration and duration of follow up). Methylation differences between converters and non‐converters were identified by a multi‐variate linear regression model including clinical covariates (age, sex, BMI, smoking). Predictive performance of methylation markers was assessed by developing support vector machine classification models with and without the addition of clinical variables.ResultsWe identified a set of 36 highly relevant methylation markers (FDR‐adjusted p‐values lower than 0.05 and a minimum change in methylation of 0.05) across 15 genes and several intergenic regions. A classification model relying on these markers identified converters and non‐converters with an area under the ROC curve of 0.9644.ConclusionThis study shows that DNA methylation patterns at an early stage of psoriatic disease can distinguish between patients that will develop PsA from those that will not during the same follow‐up.This article is protected by copyright. All rights reserved.image