ArticleFrontiers in genetics2020
Detection and Comparative Analysis of Methylomic Biomarkers of Rheumatoid Arthritis.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Epigenetic alterations in rheumatoid arthritis: multilayer mechanisms and translational opportunities.Frontiers in immunology · 2026Review
- Identifying AIM2 Circulating Methylation Levels as a Novel Diagnostic Biomarker for Rheumatoid Arthritis Using Targeted DNA Methylation Sequencing.Endocrine, metabolic & immune disorders drug targets · 2026Article
- Rheumatoid Arthritis: Biomarkers and the Latest Breakthroughs.International journal of molecular sciences · 2025Review
- A DNA methylation-based algorithm for diagnosing rheumatoid arthritis.Arthritis research & therapy · 2025Article
- Transcriptomics secondary analysis of severe human infection with SARS-CoV-2 identifies gene expression changes and predicts three transcriptional biomarkers in leukocytes.Computational and structural biotechnology journal · 2023Article
- Contribution of Dysregulated DNA Methylation to Autoimmunity.International journal of molecular sciences · 2021Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rheumatoid arthritis (RA) is a common autoimmune disorder influenced by both genetic and environmental factors. To investigate possible contributions of DNA methylation to the etiology of RA with minimum confounding genetic heterogeneity, we investigated genome-wide DNA methylation in disease-discordant monozygotic twin pairs. This study hypothesized that methylomic biomarkers might facilitate accurate RA detection. A comprehensive series of biomarker detection algorithms were utilized to find the best methylomic biomarkers for detecting RA patients using the methylomic data of the peripheral blood samples. The best model achieved 100.00% in accuracy (Acc) with 81 methylomic biomarkers and a 10-fold cross-validation (10FCV) strategy. Some of the methylomic biomarkers were experimentally confirmed to be associated with the onset or development of RA. It is also interesting to observe that many of the detected biomarkers were from chromosome Y, supporting the knowledge that RA has a significant gender discrepancy.
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Registered trials
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