ArticleAging2023
Identification of m6A regulator-mediated RNA methylation modification patterns and key immune-related genes involved in atrial fibrillation.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Epigenetics in Atrial Fibrillation: Molecular Mechanisms and Therapeutic Avenues.Reviews in cardiovascular medicine · 2026Review
- The mechanism of m6A modification in cardiovascular diseases: A systematic review.Genes & diseases · 2026Review
- Epigenetic Drivers of Atrial Fibrillation: Mechanisms, Biomarkers, and Therapeutic Targets.International journal of molecular sciences · 2025Review
- Single-cell transcriptomics reveals writers of RNA modification-mediated immune microenvironment and cardiac resident Macro-MYL2 macrophages in heart failure.BMC cardiovascular disorders · 2024Article
- Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning.ESC heart failure · 2024Article
- Identification and experimental validation of KMO as a critical immune-associated mitochondrial gene in unstable atherosclerotic plaque.Journal of translational medicine · 2024Article
- Article
- Unveiling the Molecular Links Between Atrial Fibrillation and Atherosclerosis: Insights into Shared Pathogenesis and Ferroptosis Diagnostic Biomarkers.Journal of inflammation research · 2024Article
- Integrative bioinformatics analysis reveals STAT2 as a novel biomarker of inflammation-related cardiac dysfunction in atrial fibrillation.Open medicine (Warsaw, Poland) · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The role of m6A in the regulation of the immune microenvironment in atrial fibrillation (AF) remains unclear. This study systematically evaluated the RNA modification patterns mediated by differential m6A regulators in 62 AF samples, identified the pattern of immune cell infiltration in AF and identified several immune-related genes associated with AF. A total of six key differential m6A regulators between healthy subjects and AF patients were identified by the random forest classifier. Three distinct RNA modification patterns (m6A cluster-A, -B and -C) among AF samples were identified based on the expression of 6 key m6A regulators. Differential infiltrating immune cells and HALLMARKS signaling pathways between normal and AF samples as well as among samples with three distinct m6A modification patterns were identified. A total of 16 overlapping key genes were identified by weighted gene coexpression network analysis (WGCNA) combined with two machine learning methods. The expression levels of the
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.