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Updated: Oct 27, 2025
A Method for Measuring RNA N6-methyladenosine Modifications in Cells and Tissues
Published on: December 5, 2016
N6-Methyladenosine RNA modification in cerebrospinal fluid as a novel potential diagnostic biomarker for progressive
Fei Ye1,2, Tianzhu Wang3, Xiaoxin Wu1
1Department of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Background:
Progressive 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).
Methods:
Gene 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.
Results:
The 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.
Conclusions:
The 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.
Insights
N6-methyladenosine (m6A) RNA modification may serve as a novel biomarker for progressive multiple sclerosis (PMS). This study identified m6A regulatory genes in cerebrospinal fluid (CSF) to distinguish PMS from relapsing-remitting multiple sclerosis (RRMS).
Area of Science:
- Neuroscience
- Genetics
- Biochemistry
Background:
- Progressive multiple sclerosis (PMS) is a severe subtype of MS causing irreversible disabilities.
- Current diagnostic methods lack reliable biomarkers to differentiate PMS from relapsing-remitting multiple sclerosis (RRMS).
- Dysregulation of N6-methyladenosine (m6A) RNA modification is implicated in neurological disorders.
Purpose of the Study:
- To explore novel diagnostic biomarkers for PMS using m6A regulatory genes in cerebrospinal fluid (CSF).
- To investigate the potential of m6A RNA methylation as a distinguishing factor between PMS and RRMS.
Main Methods:
- Downloaded gene expression matrices from ArrayExpress.
- Identified differentially expressed m6A regulatory genes and clustered MS subtypes.
- Utilized random forest (RF) and support vector machine (SVM) algorithms to build a diagnostic model.
- Validated findings using CSF samples and m6A RNA Methylation Quantification Kit.
Main Results:
- All 13 central m6A RNA methylation regulators were upregulated in MS patients compared to non-MS patients.
- Two MS clusters associated with subtypes were identified.
- An SVM model constructed using eight feature genes showed good diagnostic performance.
- CSF analysis revealed significantly higher m6A RNA methylation and related gene expression in RRMS than in PMS samples.
Conclusions:
- Dynamic m6A RNA methylation modification is involved in MS progression.
- m6A RNA methylation in CSF shows potential as a novel biomarker for diagnosing MS.
- This approach may help distinguish PMS from RRMS in early disease stages.
