Our group demonstrated that pre-treatment serum type I IFN-β/α ratio>1.3 predicts non-response to anti-TNFα therapy (TNFi) in RA patients. However, mechanisms that underlie the IFN-β/α ratio that predicts response are unknown. Effects of IFN on uncommon cell populations may be masked in whole blood or mixed cell populations. We used single cell analysis to investigate whether monocyte gene expression differs significantly between RA patients according to their pre-TNFi serum IFN-β/α ratio. Single classical (CL) and non-classical (NC) blood-derived monocytes were isolated from seropositive RA subjects prior to biologic therapy. Subjects were grouped by pre-TNFi serum IFN-β/α ratio: IFN-β/α>1.3(n=6) and IFN-β/α<1.3(n=9). 87 target genes were analyzed. Genes that varied significantly between groups by categorical analyses were tested in multivariate logistic regression models. JAK1,IL1A,TLR2,CD32A,CD36,CXCR3,IL8,IRAK1, and TYK2 expression were retained in the mixed monocyte gene expression model for differentiating between groups. JAK1 and IL1A were also retained in the models from monocyte subsets. TLR9,STAT1, and FCER were retained in the CL model. STAT2 and IFI27 were retained in the NC model. Regression models from the monocyte subsets provided increased discriminatory potential in comparison to the mixed monocyte model. Within-cell co-expression patterns demonstrate biological differences in monocyte subsets of RA patients with an IFN-β/α>1.3, the ratio of type I IFNs which predicts non-response to TNFi. When monocyte subsets were analyzed separately, differentiation by gene expression was strongest and distinct expression signatures were identified, suggesting that further study of monocyte subsets will illuminate molecular differences that determine response to TNFi in RA. A better understanding of mechanisms that underlie the IFN-β/α ratio that determines treatment response should allow us to focus down to a more specific marker that would be easier to measure, and, may reveal other targets for therapy. This work will help to develop a more individualized approach to treatment in RA.