Novel Insights Into Rheumatoid Arthritis Through Characterization of Concordant Changes in DNA Methylation and Gene Expression in Synovial Biopsies of Patients With Differing Numbers of Swollen Joints

Andrew Y. F. Li Yim, Enrico Ferrero, Klio Maratou, Huw D. Lewis, George Royal, David F. Tough, Chris Larminie, Marcel M. A. M. Mannens, Peter Henneman, Wouter J. de Jonge, Marleen G. H. van de Sande, Danielle M. Gerlag, Rab K. Prinjha, Paul P. Tak

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6 Citations (Scopus)

Abstract

In this study, we sought to characterize synovial tissue obtained from individuals with arthralgia and disease-specific auto-antibodies and patients with established rheumatoid arthritis (RA), by applying an integrative multi-omics approach where we investigated differences at the level of DNA methylation and gene expression in relation to disease pathogenesis. We performed concurrent whole-genome bisulphite sequencing and RNA-Sequencing on synovial tissue obtained from the knee and ankle from 4 auto-antibody positive arthralgia patients and thirteen RA patients. Through multi-omics factor analysis we observed that the latent factor explaining the variance in gene expression and DNA methylation was associated with Swollen Joint Count 66 (SJC66), with patients with SJC66 of 9 or more displaying separation from the rest. Interrogating these observed differences revealed activation of the immune response as well as dysregulation of cell adhesion pathways at the level of both DNA methylation and gene expression. We observed differences for 59 genes in particular at the level of both transcript expression and DNA methylation. Our results highlight the utility of genome-wide multi-omics profiling of synovial samples for improved understanding of changes associated with disease spread in arthralgia and RA patients, and point to novel candidate targets for the treatment of the disease.
Original languageEnglish
Article number651475
JournalFrontiers in immunology
Volume12
DOIs
Publication statusPublished - 22 Apr 2021

Keywords

  • DNA methylation
  • arthralgia
  • multi-omics analyses
  • rheumatoid arthritis
  • synovial biopsies
  • target identification
  • transcriptomics

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