ArticleJournal of orthopaedic surgery and research2023
Association between ankylosing spondylitis and m6A methylation.
Article in Journal of orthopaedic surgery and research, 2023. 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, 8 citations in OpenAlex.
- Identification and validation of PANoptosis-related genes in ankylosing spondylitis.BMC medical genomics · 2026Article
- Restoring adenosine balance in axial spondyloarthritis: a stage-specific framework for immune and structural modulation.Frontiers in immunology · 2026Review
- Crosstalk between N6-methyladenosine modification and ncRNAs in rheumatic diseases: therapeutic and diagnostic implications.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Review
- Review
- Identification of key genes with abnormal RNA methylation modification and selected m6A regulators in ankylosing spondylitis.Immunity, inflammation and disease · 2024Article
- Methylation of T and B Lymphocytes in Autoimmune Rheumatic Diseases.Clinical reviews in allergy & immunology · 2024Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundN6-methyl adenosine (m6A) is the most common reversible mRNA modification in eukaryotes implicated in key roles in various biological processes. The purpose of our analysis was to examine the association of ankylosing spondylitis (AS) with m6A methylation.
methodWe obtained 72 samples from the data set GSE73754, including 52 AS patients and 20 healthy people. We divided the samples into two groups: the experimental group and the control group, and then observed the differences of 26 m6A related genes in the two groups. We also analyzed the correlation between different m6A genes. We used a random forest tree model to screen seven m6A signature genes associated with AS to evaluate its prevalence. Next, the samples were classified according to the m6a content and differential genes. Immune analysis, gene ontology, and KEGG enrichment analyses were performed. Finally, we scored each sample with m6a and analyzed the relationship between different samples and inflammation-related factors. RESULTS AND
conclusionIn conclusion, we screened out AS-related genes and the nomogram showed that they were negatively correlated with the incidence of AS. And we found that AS may have some relationship with immunity. Our analysis results could provide further insights into the treatment of AS.
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