Predicting the clinical efficacy of JAK inhibitor treatment for patients with rheumatoid arthritis based on Fas+ T cell subsets

Abstract

Rheumatoid arthritis (RA) is a common autoimmune disease. Janus kinase inhibitors (JAKi) have been approved for the treatment of RA; however, the impact of JAKi on immune cells remains inconclusive. This study investigated the response of immune cells to JAKi treatment to identify biomarkers by which to evaluate and predict clinical outcomes. Blood samples were collected from RA patients before and after JAKi treatment for the analysis of immunophenotypes. Our results revealed that JAKi mainly inhibited Fas+ T cell subsets. The percentage changes of Th Fas+ and Naive Th Fas+ cells were positively correlated with the 28-joint Disease Activity Score with erythrocyte sedimentation rate (DAS28-ESR) values. Following treatment, moderate response (MR) RA patients presented a decrease in the number of Naive Th Fas+ cells (p = 0.0001). Initial percentages of 14 T cell and 20 B cell subsets were correlated with percentage changes in DAS28-ESR. Overall, 16 cell subsets presented significant differences between the non-response (NR) and MR groups. Excluding the multicollinearity of the immune cells, we constructed a JAKi treatment response prediction index (JRPI) using 5 subsets of T/B cells, the results of which were strongly correlated with percentage changes in DAS28-ESR (receiver operating characteristic curve of 1). Note that the NR group was clearly distinguished from the MR group (p = 0.0167). In conclusion, the efficacy of JAKi can be attributed mainly to the suppression of Fas+ T cell subsets. A positive correlation was shown between the therapeutic efficacy of JAKi and the percentage changes in both Th Fas+ cells and Naive Th Fas+ cells. Furthermore, the proposed JRPI could potentially be used as an indicator to predict the efficacy of JAKi prior to treatment in RA patients. These findings may contribute to the development of personalized treatment strategies for RA patients using JAKi.

Keywords: Fas+; JAK inhibitor; immunophenotyping; prediction index; rheumatoid arthritis; therapeutic efficacy.