Exploring biomarkers and therapeutic targets for ischemic stroke through integrated microarray data analysis

Abstract Stroke was the third leading cause of global disability-adjusted life years and its treatment drugs were limited. Researchers still need to find reliable diagnostic biomarkers and therapeutic targets. This study aimed to explore hub genes associated with ischemic stroke (IS) through bioinformatics analysis and identify its potential diagnostic biomarkers and therapeutic targets. The microarray data sets of GSE58294 and GSE16561 related to IS were downloaded from the Gene Expression Omnibus (GEO) database. Weighted co-expression network analysis (WGCNA) and differential expression analysis were integrated to find overlapping genes, and then hub genes were screened by Least absolute shrinkage and selection operator (LASSO) regression. NetworkAnalyst database was used to construct the TF-gene network and miRNA-TF regulatory network of the hub genes. DGIdb and CMap databases were used to predict targeted drugs and small molecule compounds. Through the Comprehensive analysis of GSE58294 and GSE16561, 10 hub genes were screened by LASSO regression, namely ARG1, LY96, ABCA1, SLC22A4, CD163, TPM2, SLC25A42, ID3, FAM102A and CD79B. NetworkAnalyst database analysis showed that ABCA1 was the hub gene most regulated by miRNA and TF. TRRUST and NetworkAnalyst databases showed that SP1 (P=0.0246) was a key transcription factor for hub genes. Finally, DGIdb database analysis identified 7 therapeutic drugs targeted with ABCA1 and SLC22A4, and 4 small molecule compounds targeted with ID3 and SLC22A4 were obtained from CMap database. We identified IS-related diagnostic biomarkers and therapeutic drugs, which can provide new insights for the diagnosis and treatment of IS.