ArticlePloS one2021
Bioinformatic analysis identifies potential key genes of epilepsy.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- The role of AI-assisted drug repurposing in neurological disorders: a systematic review of validation strategies, challenges and opportunities.Journal of nanobiotechnology · 2026Pooled it
- Potential Pleiotropic Genes and Shared Biological Pathways in Epilepsy and Depression Based on GWAS Summary Statistics.Computational intelligence and neuroscience · 2022Pooled it
- ASGR2 and CLEC12A as Prognostically Relevant C-Type Lectin Hubs in Glioblastoma.International journal of molecular sciences · 2026Article
- The Biomarkers and Underlying Mechanisms of Mitochondrial and Programmed Cell Death Related Genes in Epilepsy by Combining Transcriptome and Single-Cell Sequencing.Journal of Korean Neurosurgical Society · 2026Article
- Identification and verification of hub genes related to mitochondrial dysfunction in epilepsy based on bioinformatics analysis.BMC neurology · 2026Article
- Identification and Validation of Potential Biomarkers and Therapeutic Targets of COVID-19-related Depression.Combinatorial chemistry & high throughput screening · 2025Article
- A multi-omics Mendelian randomization identifies putatively causal genes and DNA methylation sites for asthma.The World Allergy Organization journal · 2024Article
- Article
- Identification of hub genes significantly linked to subarachnoid hemorrhage and epilepsyFrontiers in neurology · 2023Article
- Bioinformatics Analysis of Novel Targets for Treating Cervical Cancer by Immunotherapy Based on Immune Escape.Cancer genomics & proteomicsArticle
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEpilepsy is one of the most common brain disorders worldwide. It is usually hard to be identified properly, and a third of patients are drug-resistant. Genes related to the progression and prognosis of epilepsy are particularly needed to be identified.
methodsIn our study, we downloaded the Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE143272. Differentially expressed genes (DEGs) with a fold change (FC) >1.2 and a P-value <0.05 were identified by GEO2R and grouped in male, female and overlapping DEGs. Functional enrichment analysis and Protein-Protein Interaction (PPI) network analysis were performed.
resultsIn total, 183 DEGs overlapped (77 ups and 106 downs), 302 DEGs (185 ups and 117 downs) in the male dataset, and 750 DEGs (464 ups and 286 downs) in the female dataset were obtained from the GSE143272 dataset. These DEGs were markedly enriched under various Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. 16 following hub genes were identified based on PPI network analysis: ADCY7, C3AR1, DEGS1, CXCL1 in male-specific DEGs, TOLLIP, ORM1, ELANE, QPCT in female-specific DEGs and FCAR, CD3G, CLEC12A, MOSPD2, CD3D, ALDH3B1, GPR97, PLAUR in overlapping DEGs.
conclusionThis discovery-driven study may be useful to provide a novel insight into the diagnosis and treatment of epilepsy. However, more experiments are needed in the future to study the functional roles of these genes in epilepsy.
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