Project description:To directly compare the SLE monocyte transcriptional program with that of blood mDC precursors, we purified lineage HLA-DRhighCD11chigh mDCs and CD14+ monocytes from the blood of five healthy donors. Their gene expression profiles were then compared to those of blood SLE monocytes. An unsupervised clustering analysis of transcripts present in >20% of the samples classified healthy monocytes, SLE monocytes and healthy mDCs into three well defined groups. A supervised analysis was then performed to find genes: 1) differentially expressed in healthy mDCs compared to monocytes; 2) shared by healthy blood mDCs and SLE blood monocytes. To directly compare the SLE monocyte transcriptional program with that of blood mDC precursors, we purified lineage HLA-DRhighCD11chigh mDCs and CD14+ monocytes from the blood of five healthy donors. Their gene expression profiles were then compared to those of blood SLE monocytes. An unsupervised clustering analysis of transcripts present in >20% of the samples classified healthy monocytes, SLE monocytes and healthy mDCs into three well defined groups. A supervised analysis was then performed to find genes: 1) differentially expressed in healthy mDCs compared to monocytes; 2) shared by healthy blood mDCs and SLE blood monocytes.
Project description:To directly compare the SLE monocyte transcriptional program with that of blood mDC precursors, we purified lineage HLA-DRhighCD11chigh mDCs and CD14+ monocytes from the blood of five healthy donors. Their gene expression profiles were then compared to those of blood SLE monocytes. An unsupervised clustering analysis of transcripts present in >20% of the samples classified healthy monocytes, SLE monocytes and healthy mDCs into three well defined groups. A supervised analysis was then performed to find genes: 1) differentially expressed in healthy mDCs compared to monocytes; 2) shared by healthy blood mDCs and SLE blood monocytes.
Project description:Monocytes from 3 healthy donors were cultured for 6 hours in the presence of 20% serum from three newly diagnosed, untreated SLE patients. Microarray analysis was then performed upon normalizing the gene expression levels of samples incubated with SLE sera to those incubated with autologous serum. Monocytes from 3 healthy donors were cultured for 6 hours in the presence of 20% serum from three newly diagnosed, untreated SLE patients. Microarray analysis was then performed upon normalizing the gene expression levels of samples incubated with SLE sera to those incubated with autologous serum.
Project description:Monocytes from 3 healthy donors were cultured for 6 hours in the presence of 20% serum from three newly diagnosed, untreated SLE patients. Microarray analysis was then performed upon normalizing the gene expression levels of samples incubated with SLE sera to those incubated with autologous serum.
Project description:We performed RNA-seq on peripheral blood mononuclear cells (PBMC) from healthy human donors treated with interferon alpha 2a (1000IU/mL) +/- dexamethasone 10^-7M, with the aims of studying interactions between IFN and glucocorticoid induced gene expression, as well as identifying potential transcripts that may be used as a glucocorticoid exposure signature in clinical practice in patients with SLE. Transcripts identified from RNA-seq data were analysed in SLE patient data sets to validate clinical utility. We found that dexamethasone minimally impacts on interferon stimulated gene expression however IFN altered gene transcription of many previously reported glucocorticoid induced genes.
Project description:Many cytokines are involved in the pathogenesis of autoimmune diseases and are recognized as relevant therapeutic targets to attenuate inflammation, such as TNFα in RA and IFNα/γ in SLE. To relate the transcriptional imprinting of cytokines in a cell type-specific 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 TNFα, IFNα2a and IFNγ. Monocytes from SLE and RA patients revealed disease-specific gene-expression profiles. In vitro-generated signatures induced by IFNα2a and IFNγ showed similar profiles that only partially overlapped with those induced by TNFα. 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 TNFα-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 TNFα 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 to 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. Expression profiles of human peripheral blood monocytes activated in vivo and stimulated in vitro. Monocytes from patients with SLE and RA and from healthy donors were used for generating disease-specific gene-expression profiles, where these profiles represent in vivo activation of monocytes. In addition, monocytes from healthy donors were stimulated in vitro by cytokines: TNFα, IFNα2a and IFNγ. Cytokine-specific gene-expression profiles were generated by comparing stimulated monocytes with unstimulated ones. TNFα-, IFNα2a- and IFNγ as cytokine-specific gene-expression profiles were compared with RA and SLE, as disease-specific gene-expression profiles.