ArticleJournal of translational medicine2021
N6-Methyladenosine RNA modification in cerebrospinal fluid as a novel potential diagnostic biomarker for progressive multiple sclerosis.
Article in Journal of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 32 citations in OpenAlex.
- mNature reviews. Neuroscience · 2026Review
- Neuromodulatory role and therapeutic potential of N 6 -methyladenosine RNA methylation in neurodegenerative diseases.Neural regeneration research · 2026Article
- Epitranscriptomic Stability-Variable Extents of N1-Methyladenosine to N6-Methyladenosine Conversion Under Different Experimental Conditions.Biomolecules · 2026Article
- Regulatory role and subtype analysis of m6A modifications in dermatomyositis.Global medical genetics · 2026Article
- FTO-dependent mInflammation · 2026Article
- Advances in biomarkers for diagnosing and prognosticating disorders of consciousness.Frontiers in neuroscience · 2026Review
- Epitranscriptomic regulation by m6A in immunity and autoimmune disorders: emerging mechanisms and clinical perspectives.Frontiers in immunology · 2026Review
- Epigenetic modifier m⁶A methylation: insights into the pathogenesis and therapeutic potential of autoimmune diseases.Journal of translational medicine · 2025Review
- The mCells · 2025Review
- RNA methylation modifications in neurodegenerative diseases: Focus on their enzyme system.Journal of advanced research · 2025Review
- Reduced Expression of mInternational journal of molecular sciences · 2025Article
- The Role of MClinical reviews in allergy & immunology · 2025Review
- The mJournal of inflammation research · 2025Review
- Regulatory roles of N6-methyladenosine (mCancer gene therapy · 2024Review
- Article
- mAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Advances in brain epitranscriptomics research and translational opportunities.Molecular psychiatry · 2024Review
- Exploring the impact of mFrontiers in immunology · 2024Review
- The role of mGenes & diseases · 2024Review
- M6A methylation modification in autoimmune diseases, a promising treatment strategy based on epigenetics.Arthritis research & therapy · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProgressive multiple sclerosis (PMS) is an uncommon and severe subtype of MS that worsens gradually and leads to irreversible disabilities in young adults. Currently, there are no applicable or reliable biomarkers to distinguish PMS from relapsing-remitting multiple sclerosis (RRMS). Previous studies have demonstrated that dysfunction of N6-methyladenosine (m6A) RNA modification is relevant to many neurological disorders. Thus, the aim of this study was to explore the diagnostic biomarkers for PMS based on m6A regulatory genes in the cerebrospinal fluid (CSF).
methodsGene expression matrices were downloaded from the ArrayExpress database. Then, we identified differentially expressed m6A regulatory genes between MS and non-MS patients. MS clusters were identified by consensus clustering analysis. Next, we analyzed the correlation between clusters and clinical characteristics. The random forest (RF) algorithm was applied to select key m6A-related genes. The support vector machine (SVM) was then used to construct a diagnostic gene signature. Receiver operating characteristic (ROC) curves were plotted to evaluate the accuracy of the diagnostic model. In addition, CSF samples from MS and non-MS patients were collected and used for external validation, as evaluated by an m6A RNA Methylation Quantification Kit and by real-time quantitative polymerase chain reaction.
resultsThe 13 central m6A RNA methylation regulators were all upregulated in MS patients when compared with non-MS patients. Consensus clustering analysis identified two clusters, both of which were significantly associated with MS subtypes. Next, we divided 61 MS patients into a training set (n = 41) and a test set (n = 20). The RF algorithm identified eight feature genes, and the SVM method was successfully applied to construct a diagnostic model. ROC curves revealed good performance. Finally, the analysis of 11 CSF samples demonstrated that RRMS samples exhibited significantly higher levels of m6A RNA methylation and higher gene expression levels of m6A-related genes than PMS samples.
conclusionsThe dynamic modification of m6A RNA methylation is involved in the progression of MS and could potentially represent a novel CSF biomarker for diagnosing MS and distinguishing PMS from RRMS in the early stages of the disease.
Indexed as
Identifiers
What OpenQuestion holds
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.