Association of epigenetic trajectory with development of clinical rheumatoid arthritis in anti‐citrullinated protein antibody positive individuals: Targeting Immune Responses for Prevention of Rheumatoid Arthritis ( <scp>TIP</scp> ‐ <scp>RA</scp> )

OBJECTIVE: The presence of anti-citrullinated protein antibodies (ACPAs) in the absence of clinical inflammatory arthritis (IA) identifies individuals at risk for rheumatoid arthritis (RA). We examined whether epigenetic remodeling of DNA methylation distinguishes those who ultimately develop RA ("Converters") from individuals who remain asymptomatic ("Non-converters"). METHODS: Genome-wide DNA methylation was quantified in peripheral blood mononuclear cells separated into CD4 T memory and naïve cells and B cells collected at baseline and longitudinally over up to 5 years from anti-CCP3+ "Converters" (n=21), anti-CCP3+ "Non-converters" (n=50), and anti-CCP3- "Controls" (n=69), as well as "Early RA" patients (n=29). Differentially methylated loci (DMLs) were identified, followed by pathway enrichment analysis. Machine-learning algorithms assessed the predictive value of individual CpG sites for future RA onset. RESULTS: At baseline, DMLs clearly separated Converters from Non-converters and patients with Early RA. Among the pathways associated with differentially methylated genes, enrichment of aberrant NOTCH-signaling and DNA-repair pathways was particularly prominent in B-cells. Longitudinally, methylomes remained stable in controls and Non-converters but underwent progressive remodeling in Converters, tracing a "RA methylome trajectory" towards the Early RA methylome involving regulatory elements. Machine-learning models incorporating top CpG predictors accurately classified future RA converters. CONCLUSION: DNA methylation is a dynamic process that continuously remodels in asymptomatic anti-CCP3-positive individuals as they progress to disease, while remaining relatively stable in Non-converters and Controls. Progressive epigenetic remodeling during the trajectory from At-Risk to clinical arthritis highlights pathogenic pathways and yields biomarkers that may inform prognostic testing and preventive intervention in preclinical RA.