Strategies using functional genomics in rheumatic diseases

The multifaceted balance of TNF-α and type I/II interferon responses in SLE and RA: how monocytes manage the impact of cytokines

Many cytokines are involved in the pathogenesis of autoimmune diseases and are recognized as relevant therapeutic targets to attenuate inflammation, such as tumor necrosis factor (TNF)-α in rheumatoid arthritis (RA) and interferon (IFN)-α/γ in systemic lupus erythematosus (SLE). To relate the transcriptional imprinting of cytokines in a cell type- and disease-specific manner, we generated gene expression profiles from peripheral monocytes of SLE and RA patients and compared them to in vitro-generated signatures induced by TNF-α, IFN-α2a, and IFN-γ. Monocytes from SLE and RA patients revealed disease-specific gene expression profiles. In vitro-generated signatures induced by IFN-α2a and IFN-γ showed similar profiles that only partially overlapped with those induced by TNF-α. Comparisons between disease-specific and in vitro-generated signatures identified cytokine-regulated genes in SLE and RA with qualitative and quantitative differences. The IFN responses in SLE and RA were found to be regulated in a STAT1-dependent and STAT1-independent manner, respectively. Similarly, genes recognized as TNF-α regulated were clearly distinguishable between RA and SLE patients. While the activity of SLE monocytes was mainly driven by IFN, the activity from RA monocytes showed a dominance of TNF-α that was characterized by STAT1 down-regulation. The responses to specific cytokines were revealed to be disease-dependent and reflected the interplay of cytokines within various inflammatory milieus. This study has demonstrated that monocytes from RA and SLE patients exhibit disease-specific gene expression profiles, which can be molecularly dissected when compared with in vitro-generated cytokine signatures. The results suggest that an assessment of cytokine-response status in monocytes may be helpful for improvement of diagnosis and selection of the best cytokine target for therapeutic intervention.

Gene expression profiles of systemic lupus erythematosus and rheumatoid arthritis

Gene expression profiling using microarray technology is being employed to define specific molecular mediators and pathways involved in immunobiology, to understand the intricate interplay of genes participating in the pathogenesis, and to develop biomarkers of disease activity in both systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). This review summarizes the latest information on the pathogenesis of SLE and RA and describes the utilization of microarray technology in these systemic autoimmune diseases.

Microarray analysis of autoimmune diseases by machine learning procedures

Microarray-based global gene expression profiling, with the use of sophisticated statistical algorithms is providing new insights into the pathogenesis of autoimmune diseases. We have applied a novel statistical technique for gene selection based on machine learning approaches to analyze microarray expression data gathered from patients with systemic lupus erythematosus (SLE) and primary antiphospholipid syndrome (PAPS), two autoimmune diseases of unknown genetic origin that share many common features. The methodology included a combination of three data discretization policies, a consensus gene selection method, and a multivariate correlation measurement. A set of 150 genes was found to discriminate SLE and PAPS patients from healthy individuals. Statistical validations demonstrate the relevance of this gene set from an univariate and multivariate perspective. Moreover, functional characterization of these genes identified an interferon-regulated gene signature, consistent with previous reports. It also revealed the existence of other regulatory pathways, including those regulated by PTEN, TNF, and BCL-2, which are altered in SLE and PAPS. Remarkably, a significant number of these genes carry E2F binding motifs in their promoters, projecting a role for E2F in the regulation of autoimmunity.

Gene expression profiling of rheumatoid arthritis synovial cells treated with antirheumatic drugs

Nonbiological therapeutics are frequently used for the treatment of patients with rheumatoid arthritis (RA). Because the mechanisms of action of these therapeutics are unclear, the authors aimed to elucidate the molecular effects of typical antirheumatic drugs on the expression profile of RA-related genes expressed in activated synovial fibroblasts. For reasons of standardization and comparability, immortalized synovial fibroblasts derived from RA (RASF) and normal donors (NDSF) were treated with methotrexate, prednisolone, or diclofenac and used for gene expression profiling with oligonucleotide microarrays. The cytotoxicity of the antirheumatic drugs was tested in different concentrations by MTS tetrazolium assay. Genes that were differentially expressed in RASF compared to NDSF and reverted by treatment with antirheumatic drugs were verified by semiquantitative polymerase chain reaction and by chemiluminescent enzyme immunoassay. Treatment with methotrexate resulted in the reversion of the RA-related expression profile of genes associated with growth and apoptosis including insulin-like growth factor binding protein 3, retinoic acid induced 3, and caveolin 2 as well as in the re-expression of the cell adhesion molecule integrin alpha6. Prednisolone reverted the RA-related profile of genes that are known from inflammation and suppressed interleukins 1beta and 8. Low or high doses of diclofenac had no effect on the expression profile of genes related to RA in synovial fibroblasts. These data give the first insight into the mechanisms of action of common antirheumatic drugs used for the treatment of arthritides. Synovial fibroblasts reflect the disease-related pathophysiology and are useful tools for screening putative antirheumatic compounds.