Background <p>Rheumatoid arthritis (RA) is an autoimmune disease influenced by genetic, environmental, and epigenetic factors. Epigenetic modifications, particularly DNA methylation, in immune-related genes may impact inflammation and immune responses. This study aims to analyze methylation patterns in RA patients and controls to identify diagnostic and prognostic epigenetic biomarkers.</p> Methods <p>A cross-sectional study of a prospective cohort comprising 32 patients (16 with severe RA, 16 with nonsevere RA) and 32 healthy controls (discovery cohort) was performed. Severity was defined as a cumulative 28-joint Disease Activity Score with erythrocyte sedimentation rate (DAS28-ESR) ≥ 3.2, positive rheumatoid factor (RF) and anti–citrullinated peptide antibody (ACPA) values, and a high <i>Collinsella aerofaciens</i> count (OTU ≥ 0.15). Whole genome methylation analysis was performed using the Infinium Methylation EPIC BeadChip kit. Subsequently, validation by pyrosequencing (PyroMark Q48) was performed for the differentially methylated positions (DMPs) selected both in the discovery cohort and in the remainder of the inception cohort (78 patients and 78 controls).</p> Results <p>More than half of the participants were women (≥ 75%), and the mean age was 56 years. At whole genome level, an epigenetic signature was associated with both RA and severity of RA. Pyrosequencing confirmed that methylation levels at CpG sites in <i>TBC1D22A</i>, <i>PRHOXNB</i>, <i>ALLC</i>, and <i>PRG2</i> genes were associated with RA or severity of RA. The novel association between hypermethylation in <i>TBC1D22A</i> and RA was subsequently confirmed in an independent cohort.</p> Conclusions <p>Our results indicate that the level of DNA methylation in validated DMPs is associated with RA. Thus, these methylation levels are potential biomarkers for the diagnosis, prognosis and severity of RA.</p>

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Analysis of epigenetic biomarkers for diagnosis and assessment of severity in rheumatoid arthritis: a cross-sectional study

  • Arkaitz Mucientes,
  • Gracia María Martín Núñez,
  • Natalia Mena-Vázquez,
  • Jose Manuel Lisbona-Montañez,
  • Sara Manrique-Arija,
  • Andrés González-Jiménez,
  • Patricia Ruiz-Limón,
  • Aimara Garcia-Studer,
  • Fernando Ortiz-Márquez,
  • Laura Cano-García,
  • Antonio Fernández-Nebro

摘要

Background

Rheumatoid arthritis (RA) is an autoimmune disease influenced by genetic, environmental, and epigenetic factors. Epigenetic modifications, particularly DNA methylation, in immune-related genes may impact inflammation and immune responses. This study aims to analyze methylation patterns in RA patients and controls to identify diagnostic and prognostic epigenetic biomarkers.

Methods

A cross-sectional study of a prospective cohort comprising 32 patients (16 with severe RA, 16 with nonsevere RA) and 32 healthy controls (discovery cohort) was performed. Severity was defined as a cumulative 28-joint Disease Activity Score with erythrocyte sedimentation rate (DAS28-ESR) ≥ 3.2, positive rheumatoid factor (RF) and anti–citrullinated peptide antibody (ACPA) values, and a high Collinsella aerofaciens count (OTU ≥ 0.15). Whole genome methylation analysis was performed using the Infinium Methylation EPIC BeadChip kit. Subsequently, validation by pyrosequencing (PyroMark Q48) was performed for the differentially methylated positions (DMPs) selected both in the discovery cohort and in the remainder of the inception cohort (78 patients and 78 controls).

Results

More than half of the participants were women (≥ 75%), and the mean age was 56 years. At whole genome level, an epigenetic signature was associated with both RA and severity of RA. Pyrosequencing confirmed that methylation levels at CpG sites in TBC1D22A, PRHOXNB, ALLC, and PRG2 genes were associated with RA or severity of RA. The novel association between hypermethylation in TBC1D22A and RA was subsequently confirmed in an independent cohort.

Conclusions

Our results indicate that the level of DNA methylation in validated DMPs is associated with RA. Thus, these methylation levels are potential biomarkers for the diagnosis, prognosis and severity of RA.