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P124 Altered CD4+ T cell DNA methylation in early rheumatoid arthritis
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  1. AD Clark1,
  2. N Naamane1,
  3. N Nair2,3,
  4. AE Anderson1,
  5. AJ Skelton1,
  6. J Diboll1,
  7. J Massey2,3,
  8. S Eyre2,3,
  9. A Barton2,3,
  10. JD Isaacs1,
  11. LN Reynard4,
  12. AG Pratt1
  1. 1National Institute for Health Research Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University, Newcastle upon Tyne
  2. 2Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, University of Manchester
  3. 3NIHR Manchester Musculoskeletal BRU, Central Manchester NHS Foundation Trust, Manchester
  4. 4Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK

Abstract

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

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