P26 The effect of interleukin-23 stimulation on gene expression in CD4+ Jurkat cells

Abstract

Abstract Introduction and aims There is now robust evidence that genetic changes along the interleukin (IL)-23 axis increase the risk of developing psoriasis, with CD4+ T cells likely to be pivotal in the disease pathway. Here, we stimulated Jurkat CD4+ T-cell lines that expressed either the risk or protective version of IL23R, identified through genetic studies in psoriasis, and measured the effect in whole-genome expression at different timepoints poststimulation, with the aim of characterizing the downstream effect on the IL-23 pathway. Methods The transformed Jurkat CD4+IL12Rβ1+ IL23Rwt/IL23Rmut-R381Q T cells were stimulated with IL-23 protein (10 ng mL−1) for 0, 2, 4, 16 and 24 h, with triplicates used for each timepoint. RNA sequencing was performed by Novogene, and statistical analyses was performed using negative binomial generalized linear models and then a likelihood-ratio test to remove condition-specific differences over time. Results Of the identified significantly expressed genes (Padj > 10−5), five are also implicated as psoriasis risk genes, i.e. HLA-B, SOCS1, MARS, HLA-C and RUNX3. Specifically, a significant increase in RUNX3 expression in wildtype (WT) vs. mutant (MuT) at 16–24 h, and in suppressor of cytokine signalling (SOCS)-1 at 2–24 h was observed, with runt-related transcription factor (RUNX)3 expression peaking at 4 h and SOCS1 showing consistently high expression beyond 0 h. Decreased expression of SOCS1 disrupts IL-23 production and signalling, whereas increased expression of RUNX3 increases T helper (Th)17 and Th22 levels, key cells downstream of IL-23 signalling Conclusions Here, we show that carriage of the WT vs. MuT IL23R has downstream effects on expression of HLA-B, SOCS1, MARS, HLA-C and RUNX3, implicating these genes in the IL-23 pathway. This is important as defining pathways that are perturbed in patients has great potential within stratified medicine, with the possibility for better annotation of personalized genetic risk scores.