Novel expression signatures identified by transcriptional analysis of separated leucocyte subsets in systemic lupus erythematosus and vasculitis.

OBJECTIVE: To optimise a strategy for identifying gene expression signatures differentiating systemic lupus erythematosus (SLE) and antineutrophil cytoplasmic antibody-associated vasculitis that provide insight into disease pathogenesis and identify biomarkers. METHODS: 44 vasculitis patients, 13 SLE patients and 25 age and sex-matched controls were enrolled. CD4 and CD8 T cells, B cells, monocytes and neutrophils were isolated from each patient and, together with unseparated peripheral blood mononuclear cells (PBMC), were hybridised to spotted oligonucleotide microarrays. RESULTS: Using expression data obtained from purified cells a substantial number of differentially expressed genes were identified that were not detectable in the analysis of PBMC. Analysis of purified T cells identified a SLE-associated, CD4 T-cell signature consistent with type 1 interferon signalling driving the generation and survival of tissue homing T cells and thereby contributing to disease pathogenesis. Moreover, hierarchical clustering using expression data from purified monocytes provided significantly improved discrimination between the patient groups than that obtained using PBMC data, presumably because the differentially expressed genes reflect genuine differences in processes underlying disease pathogenesis. CONCLUSION: Analysis of leucocyte subsets enabled the identification of gene signatures of both pathogenic relevance and with better disease discrimination than those identified in PBMC. This approach thus provides substantial advantages in the search for diagnostic and prognostic biomarkers in autoimmune disease.

Microarray analysis of human leucocyte subsets: the advantages of positive selection and rapid purification.

BACKGROUND: For expression profiling to have a practical impact in the management of immune-related disease it is essential that it can be applied to peripheral blood cells. Early studies have used total peripheral blood mononuclear cells, and as a consequence the majority of the disease-related signatures identified have simply reflected differences in the relative abundance of individual cell types between patients and controls. To identify cell-specific changes in transcription it would be necessary to profile purified leucocyte subsets. RESULTS: We have used sequential rounds of positive selection to isolate CD4 and CD8 T cells, CD19 B cells, CD14 monocytes and CD16 neutrophils for microarray analysis from a single blood sample. We compared gene expression in cells isolated in parallel using either positive or negative selection and demonstrate that there are no significant consistent changes due to positive selection, and that the far inferior results obtained by negative selection are largely due to reduced purity. Finally, we demonstrate that storing cells prior to separation leads to profound changes in expression, predominantly in cells of the myeloid lineage. CONCLUSION: Leukocyte subsets should be prepared for microarray analysis by rapid positive selection.