Objectives Synovial fibroblasts (SFs) are one of the major components of the inflamed synovium in rheumatoid arthritis (RA). We aimed to gain insight into the pathogenic mechanisms of SFs through elucidating the genetic contribution to molecular regulatory networks under inflammatory condition.
Methods SFs from RA and osteoarthritis (OA) patients (n=30 each) were stimulated with eight different cytokines (interferon (IFN)-α, IFN-γ, tumour necrosis factor-α, interleukin (IL)-1β, IL-6/sIL-6R, IL-17, transforming growth factor-β1, IL-18) or a combination of all 8 (8-mix). Peripheral blood mononuclear cells were fractioned into five immune cell subsets (CD4+ T cells, CD8+ T cells, B cells, natural killer (NK) cells, monocytes). Integrative analyses including mRNA expression, histone modifications (H3K27ac, H3K4me1, H3K4me3), three-dimensional (3D) genome architecture and genetic variations of single nucleotide polymorphisms (SNPs) were performed.
Results Unstimulated RASFs differed markedly from OASFs in the transcriptome and epigenome. Meanwhile, most of the responses to stimulations were shared between the diseases. Activated SFs expressed pathogenic genes, including CD40 whose induction by IFN-γ was significantly affected by an RA risk SNP (rs6074022). On chromatin remodelling in activated SFs, RA risk loci were enriched in clusters of enhancers (super-enhancers; SEs) induced by synergistic proinflammatory cytokines. An RA risk SNP (rs28411362), located in an SE under synergistically acting cytokines, formed 3D contact with the promoter of metal-regulatory transcription factor-1 (MTF1) gene, whose binding motif showed significant enrichment in stimulation specific-SEs. Consistently, inhibition of MTF1 suppressed cytokine and chemokine production from SFs and ameliorated mice model of arthritis.
Conclusions Our findings established the dynamic landscape of activated SFs and yielded potential therapeutic targets associated with genetic risk of RA.
- autoimmune diseases
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Handling editor Josef S Smolen
HT and MO contributed equally.
Contributors HT, SS, KI, YKo, KY and KF designed the research project. MO conducted bioinformatics analysis on the advice of KI, AS performed RNA sequencing. HT performed ChIP sequencing and other in vitro experiments. TS and KS performed Hi-C. HT, YT, HI, JH, YKa and ST contributed human samples. SS performed figure editing. HT and MO wrote the manuscript with critical inputs from YKo, KY and KF.
Funding This research was supported by funding from Takeda Pharmaceutical (YKo, KY and KF), the Ministry of Health, Labour and Welfare, Ministry of Education, Culture, Sports, Science and Technology KAKENHI Grant-in-Aid for Scientific Research (B) (18H02846) and Grant-in-Aid for Scientific Research (C) (17K09972) from the Japan Society for the Promotion of Science.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available in a public, open access repository. The datasets generated during this study are available at the National Bioscience Database Center (NBDC) with the study accession code hum0207.
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