Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • Resource and Technical Advances
    • Clinical Medicine
    • Reviews
    • Editorials
    • Perspectives
    • Top read articles
  • JCI This Month
    • Current issue
    • Past issues

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Concise Communication
  • Editorials
  • Viewpoint
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact
The synovial and blood monocyte DNA methylomes mirror prognosis, evolution, and treatment in early arthritis
Carlos de la Calle-Fabregat, … , Juan D. Cañete, Esteban Ballestar
Carlos de la Calle-Fabregat, … , Juan D. Cañete, Esteban Ballestar
Published March 24, 2022
Citation Information: JCI Insight. 2022;7(9):e158783. https://doi.org/10.1172/jci.insight.158783.
View: Text | PDF
Research Article Inflammation

The synovial and blood monocyte DNA methylomes mirror prognosis, evolution, and treatment in early arthritis

  • Text
  • PDF
Abstract

Identifying predictive biomarkers at early stages of inflammatory arthritis is crucial for starting appropriate therapies to avoid poor outcomes. Monocytes (MOs) and macrophages, largely associated with arthritis, are contributors and sensors of inflammation through epigenetic modifications. In this study, we investigated associations between clinical features and DNA methylation in blood and synovial fluid (SF) MOs in a prospective cohort of patients with early inflammatory arthritis. DNA methylation profiles of undifferentiated arthritis (UA) blood MOs exhibited marked alterations in comparison with those from healthy donors. We identified additional differences both in blood and SF MOs after comparing patients with UA grouped by their future outcomes, i.e., good versus poor. Patient profiles in subsequent visits revealed a reversion toward a healthy level in both groups, those requiring disease-modifying antirheumatic drugs and those who remitted spontaneously. Changes in disease activity between visits also affected DNA methylation, which was partially concomitant in the SF of UA and in blood MOs of patients with rheumatoid arthritis. Epigenetic similarities between arthritis types allow a common prediction of disease activity. Our results constitute a resource of DNA methylation–based biomarkers of poor prognosis, disease activity, and treatment efficacy for the personalized clinical management of early inflammatory arthritis.

Authors

Carlos de la Calle-Fabregat, Javier Rodríguez-Ubreva, Laura Ciudad, Julio Ramírez, Raquel Celis, Ana Belén Azuaga, Andrea Cuervo, Eduard Graell, Carolina Pérez-García, César Díaz-Torné, Georgina Salvador, José A. Gómez-Puerta, Isabel Haro, Raimon Sanmartí, Juan D. Cañete, Esteban Ballestar

×

Figure 3

DNA methylation study in synovial MOs.

Options: View larger image (or click on image) Download as PowerPoint
DNA methylation study in synovial MOs.
(A) Heatmap showing DMPs between ...
(A) Heatmap showing DMPs between blood (n = 20) and SF (n = 16) MOs, paired by patient (FDR < 0.05, Δβ ≥ 0.15). (B) Significant GO categories selected from the analysis with GREAT of the DMPs. The number of CpGs, fold enrichment, and hypergeometric test P value is depicted for every category. (C) Significantly enriched TF motifs in the DMP regions, identified by HOMER. (D) PCA of the DMPs between the UA data set (HD, n = 15), UA blood (n = 20) and UA SF (n = 16), on one hand, and between conditions in the MAC in vitro differentiation data set (MO, n = 3), M-CSF (n = 3) and GM-CSF (n = 3), on the other (see Methods). (E) Heatmap of the DMPs in D for HD, UA blood, SF blood, M-CSF, and GM-CSF with hierarchical clustering. (F) PCA of the DMPs in the M-CSF versus GM-CSF. MAC subtypes and UA SF samples are displayed in different colors, and the prognostic group is indicated by shape. (G) Chromatin functional state enrichment analysis of the DMPs on CD14 primary cells public data from the Roadmap Epigenomics Project. (H) Enrichment of MO and MAC histone mark ChIP-Seq public data around the hypermethylated DMP coordinates. Cell types are indicated by colors. Arrows specify which histone marks are contained in each of the chromatin state categories in F. RHD, Rel homology domain; TssA, active TSS; TssAFlnk, flanking active TSS; TxFlnk, transcript at gene 5′ and 3′; Tx, strong transcription; TxWk, weak transcription; EnhG, genic enhancers; Enh, enhancers; Het, heterochromatin; TssBiv, bivalent/poised TSS; BivFlnk, flanking bivalent TSS/Enh; EnhBiv, bivalent enhancer; ReprPC, repressed PolyComb; ReprPCWk, weak repressed PolyComb; Quies, quiescent.

Copyright © 2022 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts