Abstract
OBJECTIVE Canakinumab is a human anti-interleukin-1β (anti-IL-1β) blocking agent that effectively neutralizes IL-1β-mediated signaling for treatment of systemic juvenile idiopathic arthritis (JIA). While many patients have dramatic clinical response to IL-1 blockade, approximately one-third fail to respond, but there are currently no validated clinical or immunologic predictors of response. We undertook this study to characterize distinct gene signatures for treatment response and nonresponse to canakinumab in systemic JIA patients. METHODS We performed a secondary analysis of whole-blood gene expression microarrays using blood samples obtained from healthy controls and systemic JIA patients at baseline and on day 3 after canakinumab treatment (GEO accession no. GSE80060). Patients were considered strong clinical responders if they met the ACR90 response (exhibited ≥90% improvement in the American College of Rheumatology [ACR] JIA response criteria; nonresponders were those who met ACR30 [exhibiting ≤30% improvement in the ACR JIA response criteria]). A random-effects model with patient identity as the random variable was used for differential expression analysis. RESULTS We identified a distinct gene expression signature in patients with a strong clinical response to canakinumab treatment as compared to nonresponders, mediated by up-regulation of neutrophil- and IL-1-associated genes and characterized by increasing divergence from control transcriptomes with increasing clinical response. We also identified a signature including up-regulated CD163 expression that was associated with canakinumab nonresponse. Intriguingly, canakinumab treatment induced either up- or down-regulation of type I interferon (IFN) genes, independent of clinical response. CONCLUSION Here, we identify a gene signature in systemic JIA patients prior to receiving treatment that distinguishes strong responders to canakinumab from nonresponders. Further prospective studies are needed to assess the utility of these insights for treatment decisions in systemic JIA and to track the association of up-regulated type I IFN signatures with systemic JIA complications.
