ArticleJournal of neurology2019
Integrative analysis revealed potential causal genetic and epigenetic factors for multiple sclerosis.
Article in Journal of neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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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.
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Who cites it
37 citing papers in PubMed, 55 citations in OpenAlex.
- Increased METTL1 expression in B cell subsets correlates with disease activity and immunological features in SLE.Clinical rheumatology · 2026Article
- Mapping epigenetic gene variant dynamics: comparative analysis of frequency, functional impact and trait associations in African and European populations.Scientific reports · 2026Article
- Integrated multi-omics and machine learning prioritize key immune genes for multiple sclerosis risk prediction.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- Epitranscriptomic regulation by m6A in immunity and autoimmune disorders: emerging mechanisms and clinical perspectives.Frontiers in immunology · 2026Review
- RNA methylation modifications in neurodegenerative diseases: Focus on their enzyme system.Journal of advanced research · 2025Review
- MiR-124 and MiR-155 as Therapeutic Targets in Microglia-Mediated Inflammation in Multiple Sclerosis.Cellular and molecular neurobiology · 2025Review
- The Roles of RNA N6-methyladenosine Modifications in Systemic Lupus Erythematosus.Cell biochemistry and biophysics · 2024Review
- Identification of key genes with abnormal RNA methylation modification and selected m6A regulators in ankylosing spondylitis.Immunity, inflammation and disease · 2024Article
- In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis.International journal of molecular sciences · 2024Article
- Exploring the impact of mFrontiers in immunology · 2024Review
- Potential biomarkers for multiple sclerosis stage from targeted proteomics and microRNA sequencing.Brain communications · 2024Article
- The role of mGenes & diseases · 2024Review
- M6A methylation modification in autoimmune diseases, a promising treatment strategy based on epigenetics.Arthritis research & therapy · 2023Review
- In Search of a Function for the N6-Methyladenosine in Epitranscriptome, Autophagy and Neurodegenerative Diseases.Neurology international · 2023Review
- METTL1 promotes tumorigenesis through tRNA-derived fragment biogenesis in prostate cancer.Molecular cancer · 2023Article
- NBiology · 2023Article
- Landscape analysis of m6A modification regulators related biological functions and immune characteristics in myasthenia gravis.Journal of translational medicine · 2023Article
- The Role of Oxidative Stress in Epigenetic Changes Underlying Autoimmunity.Antioxidants & redox signaling · 2022Review
- N6-methyladenosine and Neurological Diseases.Molecular neurobiology · 2022Review
- Differential transcriptomic changes in the central nervous system and urinary bladders of mice infected with a coronavirus.PloS one · 2022Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
objectiveMany genomic loci have been identified for multiple sclerosis (MS) by genome-wide association studies (GWAS). Discrimination of the most functionally relevant genes in these loci remains challenging. The aim of this study was to highlight potential causal genes for MS.
methodsWe detected potential causal DNA methylations and gene expressions for MS by integrating data from large scale GWAS and quantitative trait locus (QTL) studies using the summary data-based Mendelian randomization method. Potential functional SNPs in the identified genes were searched.
resultsWe found 178 DNA methylation sites and mRNA expressions of 29 genes that were causally associated with MS. The identified genes enriched in 21 specific KEGG pathways and 80 GO terms (e.g., antigen processing and presentation, interferon gamma mediated signaling pathway). Among the identified non-MHC genes, METTL21B, METTL1 and TSFM were strongly connected. MS-associated SNPs in DDR1 were strongly associated with plasma MHC class I polypeptide-related sequence B (MICB) and Granzyme A levels. And plasma MICB and Granzyme A levels were causally associated with MS. Many SNPs in the causal genes showed QTL effects. The association between m
conclusionsThis study identified many DNA methylations and genes as important risk factors for MS and provided novel evidence on the association between circulating MICB and Granzyme A and MS. We also showed that the interaction among DDR1, MICB and GZMA and interaction among METTL21B, METTL1 and TSFM may participate in the pathogenesis of MS.
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Registered trials
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