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.

Papel de la interleuquina 23 en la diferenciación hacia Th17

The incidence of inflammatory and autoimmune diseases has increased among developed countries in the past 30 years, creating a demand for the development of effective and economic therapies for these diseases. Interleukin 23 (IL-23) is a pro-inflammatory cytokine whose increased production has been shown to play a key role in the establishment and maintenance of inflammatory and autoimmune diseases in different murine models such as inflammatory bowel disease, psoriasis and experimental autoimmune encephalomyelitis. More importantly, increased levels of IL-23 have been found in biopsies from patients with Crohn’s disease and ulcerative colitis, and psoriasis. The pathological consequences of excessive IL-23 signalling have been linked to its ability to promote the production of interleukin 17 (IL-17), particularly in the subpopulation of CD4 T cells Th17. However, the precise molecular mechanisms by which IL-23 sustains the Th17 response and induces pathogenic effector functions in these cells remain largely unknown. The global objective of the experiments carried out in this work was to determine the effect of IL-23 on the proliferation, survival and IL-17 and interferon gamma (IFN-ɣ) production in Th17 cells. These experiments have shown that IL-23 does not promote proliferation or survival of in vitro generated Th17 cells, and that there is no difference in the production of IL -17 in the absence or presence of IL -23. The IL-23 receptor, like other cytokine receptors, lacks intrinsic enzymatic activity. Instead, IL-23 receptor associates with members of the Janus tyrosine kinase family (Jaks). Cytokine binding to a Jak-associated receptor triggers the activation of the Signal Transducers and Activators of Transcription (STAT) family of transcription factors. Previous work indicated that the IL-23 receptor complex is associated with the tyrosine kinases Jak2 and Tyk2 that promote STAT3 phosphorylation. Subsequent studies showed that IL23 activation of STAT3 induces the expression of the transcription factor RORγt, which is crucial for IL-17 production. This work has explored the IL-23 signalling cascade, determining the optimal conditions for STAT3 activation and demonstrating the activation of other transcription factors such as STAT4, STAT5 and STAT1 that contribute to IL-23-mediated signalling pathways.