Novel DNA methylome biomarkers associated with adalimumab response in rheumatoid arthritis patients - Hageman, Ishtu; Mol, Femke; Atiqi, Sadaf; Joustra, Vincent; Sengul, Hilal; Henneman, Peter; Visman, Ingrid; Hakvoort, Theodorus; Nurmohamed, Mike; Wolbink, Gertjan; Levin, Evgeni; Li Yim, Andrew Y.F.; et al. (Frontiers in Immunology, 2023)
Background and aims Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade, such as TNFα. Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood (PBL). Methods DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of adalimumab (ADA) was determined using Illumina HumanMethylationEPIC BeadChip array. After 6 months, treatment response was assessed according to the European Alliance of Associations for Rheumatology (EULAR) criteria for disease activity. Patients were classified as responders (DAS28<3.2 or decrease of 1.2 points) or as non-responders (DAS28>5.1 or decrease of less than 0.6 points). Machine learning models were built through stability selected gradient boosting to predict response prior to ADA treatment with predictor DNA methylation markers. Results From the 94 RA patients, 49 and 43 patients were classified as responders and non-responders, respectively. We were capable of differentiating responders from non-responders with a high performance (AUC 0.76) using a panel of 27 CpGs. These classifier CpGs annotated to genes involved in immunological- and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology and angiogenesis. Conclusion Our findings indicate that the DNA methylome of PBL provides discriminative capabilities in discerning responders and non-responders to ADA treatment and may therefore serve as a tool for therapy prediction.