Multiomics and Machine Learning Accurately Predict Clinical Response to Adalimumab and Etanercept Therapy in Patients With Rheumatoid Arthritis.

Objective: To predict response to anti-tumor necrosis factor (anti-TNF) prior to treatment in patients with rheumatoid arthritis (RA), and to comprehensively understand the mechanism of how different RA patients respond differently to anti-TNF treatment.

Methods: Gene expression and/or DNA methylation profiling on peripheral blood mononuclear cells (PBMCs), monocytes, and CD4+ T cells obtained from 80 RA patients before they began either adalimumab (ADA) or etanercept (ETN) therapy was studied. After 6 months, treatment response was evaluated according to the European League Against Rheumatism criteria for disease response.

Changes in macrophage inhibitory factor correlate with changes in bone mineral density in glucocorticoid-treated patients with rheumatoid arthritis.

Objectives: To investigate whether changes in bone density and turnover are associated with changes in inflammatory mediators in RA patients treated with glucocorticoids (GCs) upon vitamin D treatment in comparison with alendronate treatment.

Methods: RA patients (n = 40) on long-term oral GC treatment received either alfacalcidol or alendronate. At baseline and after 18 months, we measured cytokines capable of antagonizing GCs [macrophage migration inhibitory factor (MIF), IL-13 and IL-7], cytokines causing T-cell differentiation (IL-6, IL-7, IL-12, IL-10 and IL-23) and cytokines produced by effector T cells (IFN-γ, IL-4, IL-17, IL-22).