Investigation on Potential Biomarkers and Immune-Related Mechanisms of Ischemic Stroke

Abstract

Background: This study aimed to reveal the detailed immune-related mechanisms underlying ischemic stroke (IS) and identify new immune-associated biomarkers for clinical management.

Methods: Differentially expressed genes (DEGs) between IS samples and normal controls were identified using the GSE16561 dataset. The feature genes of the immune cells were investigated using the GSE72642 dataset. Weighted correlation network analysis (WGCNA) was performed to reveal module genes, followed by an investigation of common DEGs and a functional enrichment analysis. Potential biomarkers were identified based on hub genes in protein-protein interaction networks and WGCNA. Finally, GSE158312 was used for biomarker verification.

Results: In total, 1230 DEGs were identified between the IS samples and normal controls. Seven clinically significant modules were identified using WGCNA. The yellow module genes were positively correlated with polymorphonuclear cells (PMNC), whereas the brown module genes were positively correlated with CD4+ T cells. Eight genes were selected as hub genes. These genes are mainly involved in functions such as the innate immune response. Upregulated TLR2 and ARG1 levels were significantly different between the two groups in the verification dataset.

Conclusions: Our findings suggest ARG1 and TLR2 as novel biomarkers for IS. Upregulated TLR2 might play a role in IS development by participating in the innate immune response function.

Keywords: differentially expressed genes; functional enrichment analysis; immune cells; ischemic stroke; weighted correlation network analysis.