ArticleFrontiers in genetics2022
Identification of RNA N6-methyladenosine regulation in epilepsy: Significance of the cell death mode, glycometabolism, and drug reactivity.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- N 6 -methyladenosine modification regulates cell death in cognitive impairment.Neural regeneration research · 2026Article
- Somatic Mosaicism Patterns Define Clinical-Surgical Subtypes of Focal Cortical Dysplasia Through Cell-Type-Specific Expression.medRxiv : the preprint server for health sciences · 2025Article
- N6-methyladenosine (m6A) dysregulation contributes to network excitability in temporal lobe epilepsy.JCI insight · 2025Article
- Article
- m6A methylation: a new frontier in epilepsy research and therapeutics.EXCLI journal · 2025Review
- METTL14/YTHDC1-Mediated m6A Modification in Hippocampus Improves Pentylenetetrazol-Induced Acute Seizures.Molecular neurobiology · 2024Article
- The m6A reader YTHDC2 promotes the pathophysiology of temporal lobe epilepsy by modulating SLC7A11-dependent glutamate dysregulation in astrocytes.Theranostics · 2024Article
- EGR1-Driven METTL3 Activation Curtails VIM-Mediated Neuron Injury in Epilepsy.Neurochemical research · 2023Article
- Effects of DNA, RNA, and Protein Methylation on the Regulation of Ferroptosis.International journal of biological sciences · 2023Review
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epilepsy, a functional disease caused by abnormal discharge of neurons, has attracted the attention of neurologists due to its complex characteristics. N6-methyladenosine (m6A) is a reversible mRNA modification that plays essential role in various biological processes. Nevertheless, no previous study has systematically evaluated the role of m6A regulators in epilepsy. Here, using gene expression screening in the Gene Expression Omnibus GSE143272, we identified seven significant m6A regulator genes in epileptic and non-epileptic patients. The random forest (RF) model was applied to the screening, and seven m6A regulators (HNRNPC, WATP, RBM15, YTHDC1, YTHDC2, CBLL1, and RBMX) were selected as the candidate genes for predicting the risk of epilepsy. A nomogram model was then established based on the seven-candidate m6A regulators. Decision curve analysis preliminarily showed that patients with epilepsy could benefit from the nomogram model. The consensus clustering method was performed to divide patients with epilepsy into two m6A patterns (clusterA and clusterB) based on the selected significant m6A regulators. Principal component analysis algorithms were constructed to calculate the m6A score for each sample to quantify the m6A patterns. Patients in clusterB had higher m6A scores than those in clusterA. Furthermore, the patients in each cluster had unique immune cell components and different cell death patterns. Meanwhile, based on the M6A classification, a correlation between epilepsy and glucose metabolism was laterally verified. In conclusion, the m6A regulation pattern plays a vital role in the pathogenesis of epilepsy. The research on m6A regulatory factors will play a key role in guiding the immune-related treatment, drug selection, and identification of metabolism conditions and mechanisms of epilepsy in the future.
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