Transcriptional Profiling of Tofacitinib Treatment in Juvenile Idiopathic Arthritis: Implications for Treatment Response Prediction
Year: 2024
Type: article
Abstract: Objective To assess changes in gene expression following tofacitinib treatment and investigate transcription patterns as potential predictors of treatment response in patients with active juvenile idiopathic arthritis (JIA). Methods Whole‐blood samples were collected from patients with JIA at baseline and after 18 weeks of open‐label tofacitinib treatment. Patients who achieved a JIA–American College of Rheumatology (ACR) response of 70% or above at week 18 were classified as treatment responders (TRs), whereas those with at most a JIA–ACR30 were classified as poor responders (PRs). Differential gene expression and gene ontology overrepresentation analyses were performed to compare RNA expression between week 18 and baseline samples, as well as between PR and TR samples at baseline. Results Samples from 67 patients at baseline and 60 patients at week 18 were analyzed. After 18 weeks of tofacitinib treatment across all patients with JIA, 883 genes showed significant differential expression (week 18 to baseline). The most strongly down‐regulated genes were overrepresented within interleukin‐7 (IL‐7) and type I and type II interferon pathways, whereas up‐regulated genes were enriched in ontologies related to neuronal cell processes and cell signaling. Comparing PRs and TRs at baseline, 663 genes showed differential expression. Up‐regulated genes were overrepresented within ontologies including activation of MAPK activity (P = 9.40 × 10−5), myeloid cell development (P = 8.13 × 10−5), activation of GTPase activity (P = 0.00015), and organelle transport along microtubules (P = 0.00021). Conclusion Tofacitinib treatment in JIA down‐regulated genes in interferon and IL‐7 signaling pathways regardless of effectiveness. Furthermore, baseline up‐regulation of MAPK signaling may predict poor response to tofacitinib treatment in JIA.
Source: Arthritis Care & Research
DOI: 10.1002/acr.25459
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,640
OpenAlex ID: W4404016389
