Article Text
Abstract
Background and Objectives Ankylosing spondylitis (AS) is a debilitating chronic inflammatory condition characterised by sacroiliac/axial joint inflammation and peripheral/extra-articular manifestations in some cases. Anti-TNF treatment has revolutionised disease control, however, not all patients respond, creating a significant need for biomarkers to tailor biological treatments to appropriate patients. Interferon (IFN)-related genes (IRGs) and gene expression signatures have been associated with a number of inflammatory autoimmune arthritides, including AS. Therefore, the aims of this study were to explore a large panel of IRGs to select possible candidate for further work developing a signature.
Materials and Methods 12 AS patients treated with infliximab (4 infusions of 6 mg/kg over 22 weeks) were selected from our tissue bank. Response was defined as a decrease in Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) of > 2 points or > 50% at 6 months post treatment. cDNA was obtained from baseline peripheral blood mononuclear cells and was analysed for the expression of 75 IRGs using custom TaqMan Microfluidics Cards. Differences in gene expression between response groups was then evaluated using Mann-Whitney U tests, box- plots and unsupervised hierarchical clustering.
Results Overall 6 patients responded to treatment (R) and 6 did not (NR). Although the study was exploratory and not powered for statistical significance, between the two groups, a trend (P < 0.200) was observed for 12 IRGs (up/down regulated in R), with clear difference in levels of expression seen on box-plots. A number of these have been implicated in the pathogenesis of RA and SLE, as well as response to infliximab in RA, however 6 were unique to AS. Cluster analysis highlighted 20 genes driving the differences between patients. R and NR were relatively well segregated by this analysis with 5/7 responder in a group and 1/5 in the second.
Conclusions In this pilot study, we demonstrate the potential for IRGs to be associated with response to anti-TNF treatment in AS. Furthermore, certain genes may be unique to AS differentiating it from other autoimmune inflammatory diseases. However, due to small sample numbers, statistical significance could not be reliably determined. Selected genes will now be validated in a larger cohort to determine reproducibility and statistical significance.