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Most importantly, our analysis identifies a DNA methylation signature characteristic of those UA cases that differentiate to RA. We demonstrate that the methylome of peripheral mononuclear cells can be used to anticipate the evolution of UA to RA, and that this methylome is associated with a number of inflammatory pathways and transcription factors. Finally, we design a machine-learning strategy for DNA methylation-based classification that predicts the differentiation of UA patients towards RA. DNA methylation profiling provides a good
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