1 and 1. 0 ng ml IFN2 treated as well as 0. little 1 ng ml IFNB treated THP 1 cells, but it peaked at 4 h and began to decrease rapidly. For 1. 0 ng ml IFNB treatment of THP 1 cells, the peak was shifted by 2 h Inhibitors,Modulators,Libraries so that CCL2 peaked at 2 h and began to rapidly de crease. CXCL10 displayed a trend similar to CCL2 for 1. 0 ng ml IFN2 treated and 0. 1 ng ml IFNB treated THP 1 cells. In 1. 0 ng ml IFNB treatment of THP 1 cells, CXCL10 continued till 8 h. These results indicated that CCL2 and CXCL10 rapidly responded to IFN2 and IFNB stimula tion whereas TLR4 stimulation appeared to induce a slow gradual increase, but then a rapid increase after STAT1 reached its maximum expression. miR 146a appeared to differ in its response from the other biomarkers. LPS upregulated miR 146 3 fold and it rapidly reached a peak of an 11 fold increase at 12 h.

miR 146a in IFN2 or IFNB treated cells showed a modest of 3 to 4 fold peak at 8 h, potentially indicating that IFN I did not induce significant produc tion of miR 146a. Discussion In this study, expression of previously identified SLE bio markers was examined and correlation tested with demo graphic and clinical parameters, Inhibitors,Modulators,Libraries focusing on the analysis of a possible correlation among them. The primary analyses used ordinary linear regression, even for data from multiple visits, as reported in Figures 4, 5, and 7. Alternatively, the GEE model for repeated measures was also used to ac count for possible within subject effects from patients with multiple visits. When we compared the parameters from the GEE and ordinary linear regression, the results were practically identical.

It is known that unless the vast majority of the samples have repeated measures, the ordinary linear regression is expected to closely approximate the GEE model. Furthermore, even if Inhibitors,Modulators,Libraries there was strong correlation between visits of patients, or dinary linear regression would underestimate the correl ation because it assumes that the visits are independent. Inhibitors,Modulators,Libraries therefore, the correlations of ordinary linear regressions are more stringent than those of GEE. In addition, we also assessed the normality of each dataset before applying lin ear regression. With the exception of STAT1, the IFN Inhibitors,Modulators,Libraries score, ADAR, CCL2, and CXCL10 resembled normal distribu tions. In most cases when dealing with such large datasets, even moderate deviations from nor malcy are not critical due to the central limit theorem.

For these reasons, we decided to report ordinary linear re gression rather than the more complex GEE model for re peated samples. Biomarker assessment Our results show that ADAR, STAT1, CCL2, and CXCL10 levels were significantly elevated in the SLE cohort as expected. This is in part validated by previously published results showing increased selleck chemicals levels of these biomarkers and their correlation to IFN I production in SLE patients.