02.17 Rheumatoid arthritis driven alteration in t-cell epigenetic programing

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Abstract

Background

Alteration in epigenetic patterns have been related to several diseases including RA. Early detection of RA will enable more effective treatment. The aim of our project is to identify the early changes in DNA methylation patterns of naïve and memory CD4+T-cells, and monocytes in Early RA patient to help understanding early disease pathology and to help finding the potential for biomarker development.

Methods

The methylation patterns of 480,000 CpGs were measured in 3 cell types (memory T-cell, naïve T-cell and monocytes) in 6 healthy control and 10 RA patients using an Illumina methylation genome-wide array (EWAS). Standard t-test were performed to associate p-value to CpG. Hierarchical clustering of CpG (p<0.001) were performed and Heat maps were generated using R. Venn diagram were used to compare common CpG between cell types. Gene annotation and function analysis was performed using Panther.

Results

The analysis of the EWAS data showed 20,578 CpG sites differently methylated in RA for naïve T-cells, 15 794 for memory T-cells and 7180 for monocytes. Heat maps showed 42.97% over and 57.03% under methylated in RA for naïve T-cells, 89.95% over and 10.05% under methylated for memory T-cells, and 53.59% over and 46.41% under methylated for monocytes. The top 10 over and under methylated genes were identified with transcription factors, immunity-related protein/function, signalling protein, musculoskeletal protein, enzymes and activity related to nucleotides. Overlapping of 4 genes (ANKRD1, FAM20C, EFCAB1, HRAT92) were shown between 3 cell subsets. Venn diagrams showed 249 CpG common to all 3 subsets, 2662 common to the T-cell subsets, and 473 or 271 between monocytes and naïve or memory T-cells, respectively. A repeated Panther analysis of gene on the common 249 CpG showed genes to be related to HLA (1%), binding between protein DNA (17%), binding between proteins (19%), enzymatic activity (32%), receptors (9% of which 3% was associated with TNF signalling), and signalling (5%).

Conclusion

This analysis clearly demonstrate over and under methylation in several CpG islands in RA in all 3 subsets. The genes differentially methylated in all 3 subsets may offer potential for the development of biomarker for the early diagnosis of RA.

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