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.
Highlights
Progressive multiple sclerosis (PMS) is an uncommon and severe subtype of Multiple sclerosis (MS) that worsens gradually and leads to irreversible disabilities in young adults
Details relating to the E-MTAB-69 and E-MTAB-2374 datasets are available in the ArrayExpress database (Additional file 1: Tables S2, S3)
A single dataset was created by batch normalization for background correction and consisted of 61 MS cerebrospinal fluid (CSF) samples and 31 non-MS CSF samples (Additional file 2: Table S4)
Summary
Progressive multiple sclerosis (PMS) is an uncommon and severe subtype of MS that worsens gradually and leads to irreversible disabilities in young adults. There are no applicable or reliable biomarkers to distinguish PMS from relapsing–remitting multiple sclerosis (RRMS). The aim of this study was to explore the diagnostic biomarkers for PMS based on m6A regulatory genes in the cerebrospinal fluid (CSF). 80–85% of patients with MS experience a natural course of relapse and remission at disease onset that is referred to as relapsing–remitting MS (RRMS) [1]. 10–15% of patients initially present with a gradually increasing and irreversible deterioration of neurological functions; this condition is referred to as primary-progressive MS (PPMS) [3]. There is a need to discover a novel biomarker for the early and accurate diagnosis of PMS to enhance survival with personalized therapeutic management
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