Study on the role of immune‑related genes after intracranial subarachnoid hemorrhage

Abstract

We aimed to screen the feature genes related to subarachnoid hemorrhage (SAH). The datasets (GSE73378 and GSE36791) were downloaded from National Center for Biotechnology Information database. Limma package in R was used to screen the differentially expressed genes (DEGs). Single sample gene set enrichment analysis algorithm was used to evaluate the type of immune infiltration. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze function of DEGs. The support vector machine (SVM) was used to constructed classifier, which was evaluated using receiver operating characteristic curves. The E‑TABM‑421 was used to verify the DEGs related to immunity and the classifier. Seven types of immune cells with significant differences were screened, such as activated CD8 T cell and center memory CD4 T cell. We then obtained 408 DEGs related to immune cell. Subsequently, 10 overlapped KEGG pathways related to the DEGs were obtained, such as hematopoietic cell lineage, NOD‑like receptor signaling pathway and T cell receptor signaling pathway. Finally, 9 DEGs related to immune cells (CCL5, CD27, CD3D, CREB5, FYN, ITPR3, TAB1, NCR3 and S1PR5) were screened to constructed SVM classifier. The area under the curve was 0.865 in training dataset and the AUC was 0.75 in the validation set. A SVM classifier based on the 9 DEGs (CCL5, CD27, CD3D, CREB5, FYN, ITPR3, TAB1, NCR3 and S1PR5) related to immune cells might effectively identify SAH patients or healthy people.