doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.
Objective. The effector T cell and B cell cytokine networks have been implicated in the pathogenesis of systemic autoimmune diseases, but the association of these cytokine networks with the heterogeneity of clinical manifestations and immune profiles has not been carefully examined. This study was undertaken to examine whether cytokine profiles can delineate distinct groups of patients in 4 systemic autoimmune diseases (systemic lupus erythematosus, Sjögren's syndrome, rheumatoid arthritis, and systemic sclerosis).Methods. A total of 179 patients and 48 healthy volunteers were enrolled in the multicenter cross-sectional PRECISE Systemic Autoimmune Diseases (PRECISESADS) study. Multi-low-dimensional omics data (cytokines, autoantibodies, circulating immune cells) were examined. Coculture experiments were performed to test the impact of the cytokine microenvironment on T cell/B cell cross-talk.Results. A proinflammatory cytokine profile defined by high levels of CXCL10, interleukin-6 (IL-6), IL-2, and tumor necrosis factor characterized a distinct group of patients in the 4 systemic autoimmune diseases. In each disease, this proinflammatory cluster was associated with a specific circulating immune cell signature, more severe disease, and higher levels of autoantibodies, suggesting an uncontrolled proinflammatory Th1 immune response. We observed in vitro that B cells reinforce Th1 differentiation and naive T cell proliferation, leading to the induction of type 1 effector B cells and IgG production. This process was associated with an increase in CXCL10, IL-6, IL-2, and interferon-γ production.Conclusion. This composite analysis brings new insights into human B cell functional heterogeneity based on T cell/B cell cross-talk, and proposes a better stratification of patients with systemic autoimmune diseases, suggesting that combined biomarkers would be of great value for the design of personalized treatments.
Primary Sjögren’s syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study, we confirmed a vast coordinated hypomethylation and overexpression effects in IFN-related genes, what is known as the IFN signature. Stratified and conditional analyses suggest a strong interaction between SS-associated HLA genetic variation and the presence of Anti-Ro/SSA autoantibodies in driving the IFN epigenetic signature and determining SS. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified potential new genetic variants associated with SS that might mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, autoantibody profiles, DNA methylation and gene expression in SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.
Objective
To identify the genetic variants that affect gene expression (expression quantitative trait loci [eQTLs]) in systemic sclerosis (SSc) and to investigate their role in the pathogenesis of the disease.
Methods
We performed an eQTL analysis using whole‐blood sequencing data from 333 SSc patients and 524 controls and integrated them with SSc genome‐wide association study (GWAS) data. We integrated our findings from expression modeling, differential expression analysis, and transcription factor binding site enrichment with key clinical features of SSc.
Results
We detected 49,123 validated cis‐eQTLs from 4,539 SSc‐associated single‐nucleotide polymorphisms (SNPs) (PGWAS < 10−5). A total of 1,436 genes were within 1 Mb of the 4,539 SSc‐associated SNPs. Of those 1,436 genes, 565 were detected as having ≥1 eQTL with an SSc‐associated SNP. We developed a strategy to prioritize disease‐associated genes based on their expression variance explained by SSc eQTLs (r2 > 0.05). As a result, 233 candidates were identified, 134 (58%) of them associated with hallmarks of SSc and 105 (45%) of them differentially expressed in the blood cells, skin, or lung tissue of SSc patients. Transcription factor binding site analysis revealed enriched motifs of 24 transcription factors (5%) among SSc eQTLs, 5 of which were found to be differentially regulated in the blood cells (ELF1 and MGA), skin (KLF4 and ID4), and lungs (TBX4) of SSc patients. Ten candidate genes (4%) can be targeted by approved medications for immune‐mediated diseases, of which only 3 have been tested in clinical trials in patients with SSc.
Conclusion
The findings of the present study indicate a new layer to the molecular complexity of SSc, contributing to a better understanding of the pathogenesis of the disease.
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