1. Academic Validation
  2. Parsing multiomics landscape of activated synovial fibroblasts highlights drug targets linked to genetic risk of rheumatoid arthritis

Parsing multiomics landscape of activated synovial fibroblasts highlights drug targets linked to genetic risk of rheumatoid arthritis

  • Ann Rheum Dis. 2021 Apr;80(4):440-450. doi: 10.1136/annrheumdis-2020-218189.
Haruka Tsuchiya  # 1 Mineto Ota  # 1 2 Shuji Sumitomo 1 Kazuyoshi Ishigaki 3 Akari Suzuki 4 Toyonori Sakata 5 Yumi Tsuchida 1 Hiroshi Inui 6 Jun Hirose 6 Yuta Kochi 4 7 Yuho Kadono 8 Katsuhiko Shirahige 5 Sakae Tanaka 6 Kazuhiko Yamamoto 4 Keishi Fujio 9
Affiliations

Affiliations

  • 1 Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • 2 Department of Functional Genomics and Immunological Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • 3 Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • 4 Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
  • 5 Laboratory of Genome Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, Japan.
  • 6 Department of Orthopaedic Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • 7 Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
  • 8 Department of Orthopaedic Surgery, Saitama Medical University, Saitama, Japan.
  • 9 Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan kfujio-tky@umin.ac.jp.
  • # Contributed equally.
Abstract

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.

Keywords

arthritis; autoimmune diseases; cytokines; fibroblasts; rheumatoid; synovitis.

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