Background In management of rheumatoid arthritis (RA), initiating effective treatment as soon as possible within the so-called therapeutic “window of opportunity” is the strategy, and disease remission is a primary goal. Recent work from our group demonstrated that pre-treatment serum type I IFN-β/α activity ratio>1.3 can predict non-response to anti-TNF-alpha therapy in RA patients. The cellular mechanisms that underlie the IFN-β/α activity ratio that predicts response are not known. Effects of IFN on single immune cells and uncommon cell populations may be masked in whole blood or mixed cell populations.
Methods To better understand the underpinnings of the pre-treatment IFN-β/α activity ratio, we used single cell expression analysis to investigate whether monocyte gene expression differs significantly between RA patients according to their pre-TNF-α inhibitor serum IFN-β/α activity ratio. Single classical (CL) and single non-classical (NCL) blood-derived monocytes were isolated from 15 seropositive RA subjects prior to biologic therapy. Total serum type I IFN, IFN-α, and IFN-β activity were measured using a functional reporter cell assay. Subjects were grouped by pre-TNF-α inhibitor serum IFN-β/α activity ratio into two groups, IFN-β/α>1.3 (n=6) and IFN-β/α<1.3 (n=9). Comparisons between groups were by Mann-Whitney. Hierarchical clustering of 87 target genes was done to determine if there were functional gene expression differences between groups.
Results Hierarchical clustering revealed striking differences of expression of gene sets in CL monocytes between patients with IFN-β/α<1.3 and IFN-β/α>1.3, the groups which correspond to response/non-response to anti-TNF-α agents. This same clustering was not observed in NCL monocytes, and the differentiation between anti-TNF-α response patient groups was lost when hierarchical clustering was done on total monocytes (CL and NCL). Two major gene sets which differentiated subjects with IFN-β/α>1.3 (non-response to anti-TNF-α group) in CL monocytes included TLR and IFN pathway genes, cell surface markers and cytokines as follows: cluster 1 (TLR2, CD16, JAK1, IFI27, IL1A, and MAVS) and cluster 2 (GMCSF, TLR7, STAT2, ILT7, MYD88).
Conclusion These within-cell expression patterns demonstrate biological differences in CL monocytes of RA patients with an IFN-β/α>1.3, the ratio of type I IFNs previously found to be predictive of non-response to anti-TNF-α therapy. Differentiation by gene expression among the response/non-response patient groups is lost when comparing gene expression in single NCL monocytes and single mixed population monocytes (CL and NCL), suggesting that further study of CL monocytes will likely illuminate molecular differences that determine treatment response to TNF-α inhibition in RA. This work will help to develop a more individualized approach to therapy in RA based upon the underlying biology of disease in a given patient.
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