# Identifying the shared genes and their related microRNAs, metabolites, and pathways in ischemic stroke and epilepsy

## TL;DR

This study finds shared genes and biological pathways between ischemic stroke and epilepsy, suggesting potential common biomarkers.

## Contribution

The novel contribution is identifying shared genes and their related miRNAs, metabolites, and pathways in ischemic stroke and epilepsy.

## Key findings

- 38 shared differentially expressed genes, including IL10RA, CD2, and C3AR1, were identified between ischemic stroke and epilepsy.
- C3AR1 was found to be involved in multiple pathways like synaptic vesicle cycle and nicotine addiction.
- A plasma metabolomics analysis revealed 139 differential metabolites associated with epilepsy.

## Abstract

Background This study aimed to identify shared genes between ischemic stroke (IS) and epilepsy and explore underlying mechanisms. Methods Transcriptomic datasets from the GEO database were analyzed using differential expression and weighted gene co-expression network analysis (WGCNA). Hub-shared genes were identified through protein-protein interaction networks, ROC analysis, and expression validation. Upstream miRNAs were predicted. Additionally, untargeted plasma metabolomics was performed on children with epilepsy and healthy controls, followed by differential metabolite analysis and metabolic pathway construction. Results WGCNA revealed 594 epilepsy-related and 2,623 IS-related DEGs, with 38 shared DEGs identified, including IL10RA, CD2, and C3AR1. These genes showed high diagnostic value, with their AUC value > 0.66 in both training and validation datasets. Additionally, hsa-let-7b-5p was predicted to target C3AR1. Metabolomics identified 139 differential metabolites, and C3AR1 was implicated in synaptic vesicle cycle, taste transduction, and nicotine addiction pathways via acetylcholine. Conclusions The shared genes, especially C3AR1 may be a key regulator in the development IS and epilepsy, showing potential as a biomarker for both diseases. However, its diagnostic efficacy requires further clinical validation. Given the complexity of these diseases, future research may focus on identifying a panel of biomarkers rather than relying on a single gene.

The online version contains supplementary material available at 10.1038/s41598-026-39299-5.