Screening of acute ischemic stroke-related biomarkers based on bioinformatics methods
10.13602/j.cnki.jcls.2025.09.11
- VernacularTitle:基于生物信息学方法筛选急性缺血性卒中相关生物学标志物
- Author:
Jitao LIU
1
;
Tao XU
;
Xiaolin SUN
;
Mengmeng XIE
Author Information
1. 淄博市第一医院 检验科&淄博市分子免疫检验医学重点实验室,山东 淄博 255200
- Publication Type:Journal Article
- Keywords:
acute ischemic stroke;
bioinformatics;
differentially expressed gene;
weighted correlation network analysis;
biomarker
- From:
Chinese Journal of Clinical Laboratory Science
2025;43(9):695-701
- CountryChina
- Language:Chinese
-
Abstract:
Objective To screen hub genes and signaling pathways associated with acute ischemic stroke(AIS)using bioinformatics methods,identify potential biomarkers,and provide new evidence for the mechanism research of AIS.Methods The gene expression dataset GSE37587 of AIS patients and healthy controls was obtained from the public database gene expression omnibus(GEO).The differentially expressed genes(DEGs,|log2 FC|≥1.2,FDR＜0.05)were screened using the limma package.The enrichment analysis of GO/KEGG was performed with the DAVID database.The weighted correlation network analysis(WGCNA)was used to construct a gene co-expression network for screening key modules.Then,a protein-protein interaction(PPI)network was constructed based on the STRING database and Cytoscape software to identify hub genes.The dataset GSE16561 was used to validate.Meanwhile,the clinical samples from 30 AIS patients and 30 healthy controls visited Zibo First Hospital from January to May 2025 were validated by the real time fluorescence quantitative PCR(qRT-PCR).The diagnostic efficacy was evaluated using the receiver operating characteristics(ROC)curve.Results A total of 653 DEGs were identified,including 252 up-regulated and 401 down-regulated genes.They were mainly enriched in biological processes such as ribosome biogenesis,endoplasmic reticulum protein processing,and oxidative phospho-rylation,as well as signaling pathways such as viral infection-related pathways and PD-L1/PD-1 checkpoint pathways in cancer.The core genes in the light green module identified by the WGCNA analysis were significantly enriched in the pathways such as mitophagy,ribosome,and endocytosis.The hub genes such as RPL34 and DDIT3 were screened from the PPI network,and their expression levels were significantly correlated with AIS.The analysis of the ROC curve showed that the areas under the ROC curve(AUCROC)of the hub genes for the diagnosis of AIS were 0.78-0.82,which had high clinical application value.Conclusion Ribosomal proteins,endoplas-mic reticulum stress-related genes,and viral infection response pathways are key molecular events in the occurrence of AIS.The genes such as RPL34 and DDIT3 are expected to be potential biomarkers for AIS,providing experimental evidence for the development of di-agnostic markers.
