Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs

Abstract

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation and is mediated by multiple immune cell types. In this work, we aimed to determine the relevance of changes in cell proportions in peripheral blood mononuclear cells (PBMCs) during the development of disease and following treatment. Samples from healthy blood donors, newly diagnosed RA patients, and established RA patients that had an inadequate response to MTX and were about to start tumor necrosis factor inhibitors (TNFi) treatment were collected before and after 3 months of treatment. We used in parallel a computational deconvolution approach based on RNA expression and flow cytometry to determine the relative cell-type frequencies. Cell-type frequencies from deconvolution of gene expression indicate that monocytes (both classical and non-classical) and CD4+ cells (Th1 and Th2) were increased in RA patients compared to controls, while NK cells and B cells (naïve and mature) were significantly decreased in RA patients. Treatment with MTX caused a decrease in B cells (memory and plasma cell), and a decrease in CD4 Th cells (Th1 and Th17), while treatment with TNFi resulted in a significant increase in the population of B cells. Characterization of the RNA expression patterns found that most of the differentially expressed genes in RA subjects after treatment can be explained by changes in cell frequencies (98% and 74% respectively for MTX and TNFi).

Computational approaches in rheumatic diseases – Deciphering complex spatio-temporal cell interactions

“…Going beyond biomarker identification, peripheral blood transcriptomics in combination with in vitro studies could inform on novel therapeutic targets for subpopulations of patients with RA while deconvolution of transcriptomic data could provide insights regarding the relative frequency of immune cell populations at different stages of disease [54] , [55] . The added benefit compared to flow cytometric analysis is that as deconvolution methods and cell specific signatures become more detailed, the same data can be reanalysed to achieve higher resolution or to identify new immune cell populations and activation states [56] . Currently, however, bioinformatically deconvoluted data should be supported by flow cytometric analysis.…”

An Elevated IL10 mRNA Combined with Lower TNFA mRNA Level in Active Rheumatoid Arthritis Peripheral Blood

“…Respectively, blood-based mRNA gene expression has the potential to identify patients suitable for a given treatment regimen. Recent studies suggest cytokine gene expression analyses in different cell compositions of peripheral blood mononuclear cells (PBMCs) as a helpful approach to the efficacy of response to disease-modifying drugs in RA patients [ 19 , 20 , 21 ].…”