Background/Purpose:

The identification of prognostic markers of responsiveness to the therapy  in JIA would not only radically improve clinical management, but also shed light on the immune mechanisms underlying clinical outcomes, with the potential of improving and eventually personalizing clinical care. In this context, adaptive immunity plays a central role. Indeed, it is well known that CD4⁺ T cells are implicated in the pathogenesis of different subtypes of arthritis, including JIA.  Many studies have relied on the use of whole transcriptome analysis to identify new biomarkers and get insights into the disease mechanisms. However, transcriptomes are volatile, quickly fluctuating in response to multiple factors, often clinically irrelevant. By contrast, epigenetics is more stable, possibly capturing only those changes slowly introduced by regular and consistent events such as therapy. As such, here we aimed at investigating the DNA methylation profile of JIA patients responding or not to therapy.

Methods:

 Patients treated with MTX+Etanercept+Prednisolone from the TREAT study were stratified based on the response to the therapy. Total CD4⁺ T cells were sorted from PBMCs at baseline (T0) and at end of study (Tend). DNA was extracted and bisulfite converted to analyze the cytosine methylation pattern. Converted DNA was analyzed using Illumina Infinium HumanMethylation450 BeadChip, yielding the methylation percentage of more than 485,000 CpG sites across the genome.

Results:

Both hypothesis-driven and hypothesis-agnostic approaches were pursued. In hypothesis-driven approaches, DNA methylation of genes governing immune functions, which our group has identified as correlated to clinical outcome, was investigated. In hypothesis-agnostic approaches, no assumptions were made and the most relevant sites were selected by computational methods. In both scenarios, descriptive and predictive models were built to test the diagnostic value of the identified epigenetic signature, which, in some cases, could reach an accuracy close to 100%. In preliminary analyses, we found that, regardless of the approach taken, the HLA-DRB1 gene is differentially metilated between responders and non responders. This finding is striking  in correspondence with our recent data obtained though an high-throughput Immunomics approach, which also evidenced higher HLA-DR expression on CD4⁺ T cells in clinical non-responders at phenotypical level (manuscript in preparation).

Conclusion:

In summary, we have identified a set of genes with high predictive and prognostic power for discriminating the responsiveness to treatment, which may be developed as a screening tool. Importantly, some of the differentially methylated genes identified through whole genome DNA methylation analysis correlate with phenotypical and functional changes previously described by our group, strongly putting forward further investigation of the functional role of HLA-DRB1 expression on CD4⁺ T cells.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/epigenetic-signature-of-the-response-to-anti-tnf-in-juvenile-idiopathic-arthritis/