Use of precision medicine to guide treatment of patients with rheumatoid arthritis: comment on the article by Tao et al

We read with great interest the article by Tao et al., in which they have described molecular signature-based machine learning models that can be used to predict response in patients with rheumatoid arthritis (RA) prior to treatment initiation with tumor necrosis factor-alpha inhibitors (TNFi) (1). Specifically, researchers in this study performed transcriptional and/or DNA methylomic profiling on peripheral blood mononuclear cells and immune cells from 80 patients with RA before treatment initiation with TNFi agents to find the differential molecular signatures of responders and non-responders. Next, they used machine learning models based on these molecular signatures to predict response to two TNFi, adalimumab and etanercept, in nine patients.