Screening and identification of biomarkers associated with the immune infiltration of intracerebral hemorrhage

Background Recent studies showed that inflammation and immunity might play essential roles in the progression of intracerebral hemorrhage (ICH). However, the underlying mechanisms for changes at the cellular and molecular levels after ICH remain unclear. Methods We downloaded the microarray dataset of ICH from the Gene Expression Omnibus (GEO) database. The differential expression gene analysis was obtained by weighted gene co-expression network analysis (WGCNA). We got the hub genes and performed the biological functions and signaling pathways of these genes by Metascape. GSVA algorithm was used to evaluate the potential physical function of time-varying ICH samples. We used single-sample gene set enrichment analysis (ssGSEA) to assess the immune signatures infiltration and analyzed the correlation between hub genes and immune signatures. Results The data sets of all 22 ICH samples in were examined by the WGCNA R package. We finally screened five hub genes (GAPDH, PF4, SELP, APP, and PPBP) in the royal blue module. Metascape analysis displayed the biological processes related to inflammation and immunology. Cell adhesion molecule binding, myeloid leukocyte activation, CXCR chemokine receptor binding, and regulation of cytokine production were the most enriched pathophysiological process. The immune signatures infiltration analyses showed that ICH patients' early and late samples had different activity and abundance of immune-related cells and types. Conclusions GAPDH, PF4, SELP, APP, and PPBP are identified as potential biomarkers for predicting the progression of ICH. This study may help us better understand the immunologic mechanism and shed new light on the promising approaches of immunotherapy for ICH patients.

Automated summary

This study explores the roles of inflammation and immunity in the progression of intracerebral hemorrhage (ICH) by analyzing gene expression data. Five hub genes were identified as potential biomarkers for predicting ICH progression. The analysis of immune signatures infiltration revealed differences in immune-related cells and types in early and late samples of ICH patients.