Dataset Information

Single-cell resolution of longitudinal blood transcriptome profiles in rheumatoid arthritis, systemic lupus erythematosus and healthy control pregnancies

ABSTRACT: Rheumatoid arthritis (RA), Systemic Lupus Erythematosus (SLE) are genetically the most closely related of the major rheumatic diseases as they share components of the type I IFN signalling pathway linked to treatment response and disease activity. One difference between the two is how they respond to pregnancy; while RA often improves, SLE is prone to flare. Multiple mechanisms contribute to immunological tolerance of the foetus during pregnancy. More research involving comparative analyses is needed, however, as understanding how pregnancy-related immune-modulation differs in RA and SLE can potentially lead to better treatment options. We provide data from a cohort of women with universal accessibility to health care that have been followed closely throughout their pregnancies, are well regulated and have low disease activity. We analysed samples both by bulk- and scRNA-seq, and ran a cell-type estimation, validated by flow cytometry, before combining this in a cell-type adjusted analysis. This novel comparative approach gives an improved resolution of expression profiles in RA and SLE pregnancies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE235508 | GEO | 2023/12/02

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

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.

Dataset Information

Single-cell resolution of longitudinal blood transcriptome profiles in rheumatoid arthritis, systemic lupus erythematosus and healthy control pregnancies

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure