Gene expression profiles of PBMCs from 48 SLE patients and 42 healthy controls. Shown are hierarchical clustering results of microarray data for 161 genes that distinguish lupus patients (dark blue) from healthy controls (aqua). All genes met the following criteria: >1.5-fold difference in mean gene expression levels between patients and controls, difference in mean gene expression level >100 units, and P < 0.001. The individual data points are expressed as the ratio of the expression value to the mean of control expression values. The ratios are depicted according to the scale shown at the bottom, and range from 0.0625 to 16.0 (−4 to 4 on a log₂ scale). Red indicates genes expressed at higher levels relative to the control mean, and green represents genes expressed at lower levels than control mean. Black bars on the left side of the figure indicate IFN-regulated genes. See supporting information for identification of individual samples on the clustering tree.

Genes differentially expressed between SLE and control PBMCs. Shown are representative genes from the data shown in Fig. 1. (A) Selected genes generally overexpressed in SLE compared with controls. (B) Selected genes generally underexpressed in SLE compared with controls. (C) IFN-regulated genes that did not show tight clustering in Fig. 1. (D) IFN-regulated genes that comprise the IFN signature shown in Fig. 1.

Identification of PBMC genes regulated by IFN. Depicted are 286 genes that showed a 2-fold or greater change in expression, and a difference of >500 expression units after treatment in vitro of normal control PBMCs with IFN-α/β or IFN-γ. For each sample, the expression value for each gene was divided by the average expression level of the 6-h untreated samples. This ratio was then visualized as in Fig. 1.

The IFN expression signature identifies a clinical subset of SLE patients with severe disease. (A) A numerical score was calculated by using the normalized expression levels of the 14 IFN-regulated genes that comprise the IFN signature. The differences between patients and controls were significant, P = 2.8 × 10⁻⁷. (B) Linear regression analysis demonstrates a significant correlation between IFN score and the number of SLE disease criteria (r = 0.51, P = 0.0002). (C) Patients were divided into two groups: IFN-high, the 24 patients with the highest IFN scores; and IFN-low, the 24 patients with the lowest scores. The data compare the two groups for number of ACR criteria for SLE (minimum of 4 to establish the disease, maximum of 11), P = 0.002. (D) The data compare the percent of patients in the IFN-high and IFN-low groups with ACR-defined criteria for renal and/or CNS disease (P = 7.7 × 10⁻⁶) or hematologic involvement (P = 6.1 × 10⁻⁹).