P124 Altered CD4+ T Cell DNA Methylation in Early Rheumatoid Arthritis

Introduction Over 100 genetic variants associated with rheumatoid arthritis (RA) to date explain a relatively small proportion of its heritability. Epigenetic factors, including variation in DNA methylation, may in part account for this, impacting gene expression at a cellular level. Objectives Seeking insights into disease pathogenesis and discriminatory biomarkers of clinical value, we undertook an epigenome-wide association study (EWAS) of DNA methylation in CD4 +T cells of untreated RA and control patients attending a UK early arthritis clinic. Methods A cohort of 44 treatment-naive RA patients were recruited from the Newcastle Early Arthritis Clinic (NEAC) along with a comparator cohort of 53 matched disease controls with arthritis. CD4 +T cells were isolated from fresh peripheral blood by positive selection, and DNA/RNA extracted from lysates. DNA methylation was quantified on the Illumina Human MethylationEPIC array, and gene expression measured using the Illumina 12HT BeadChip. Following methylation data pre-processing, functional normalisation and probe filtering, 715,279 CpGs were considered. Batch effects were corrected using the ComBat function and a moderated T-statistic identified differentially methylated positions (DMPs) between RA patients and disease controls. Differentially methylated regions (DMRs; clusters of DMPs) were also sought using the DMRcate function. Linear Discriminant Analysis (LDA) combined with a Stepwise Forward Selection (SFS) procedure was used to identify the most discriminatory CpGs for downstream independent validation. Results Between RA and non-RA patients we identified a total of 263 DMPs in CD4 +T cells, of which 159 were hypomethylated in RA patients (adjusted p-value<0.05, Δβ>5%), as well as 14 DMRs. One DMR in particular, comprising 4 intronic CpG sites in the CD151 gene that were hypomethylated in RA patient CD4 +T cells, was notable for the strong association between CD151 expression and methylation. This suggests a mechanism whereby altered DNA methylation during early disease determines pathogenically relevant gene expression. We assessed the ability of our differentially-methylated CpG sites to discriminate patients by diagnosis through evaluating the performance of a classification algorithm. LDA classification based on CpGs selected by SFS achieved an area under the receiver operating characteristic (ROC) curve of 0.82 (95% confidence interval: 0.80–0.85). Conclusions The CD4 +T cell methylation landscape in age- and sex-matched early inflammatory arthritis patients has unique features in early RA, indicating a possible role for DNA methylation in conferring susceptibility to this condition. A further application of these data may be in predicting outcome in undifferentiated arthritis, though further work is required to explore this. Disclosure of interest None declared