Role of Calcium Signaling Pathway-Related Gene Regulatory Networks in Ischemic Stroke Based on Multiple WGCNA and Single-Cell Analysis.

Weiwei Lin,Yangxin Wang,Yongjian Zhu,Yisheng Chen,Qiangwei Wang,Zhaowen Gu,Wen-Jun Tu

doi:10.1155/2021/8060477

Abstract

Background This study is aimed at investigating the changes in relevant pathways and the differential expression of related gene expression after ischemic stroke (IS) at the single-cell level using multiple weighted gene coexpression network analysis (WGCNA) and single-cell analysis. Methods The transcriptome expression datasets of IS samples and single-cell RNA sequencing (scRNA-seq) profiles of cerebrovascular tissues were obtained by searching the Gene Expression Omnibus (GEO) database. First, gene pathway scoring was calculated via gene set variation analysis (GSVA) and was imported into multiple WGCNA to acquire key pathways and pathway-related hub genes. Furthermore, SCENIC was used to identify transcription factors (TFs) regulating these core genes using scRNA-seq data. Finally, the pseudotemporal trajectory analysis was used to analyse the role of these TFs on various cell types under hypoxic and normoxic conditions. Results The scores of 186 KEGG pathways were obtained via GSVA using microarray expression profiles of 40 specimens. WGCNA of the KEGG pathways revealed the two following pathways: calcium signaling pathway and neuroactive ligand-receptor interaction pathways. Subsequently, WGCNA of the gene expression matrix of the samples revealed the calcium signaling pathway-related genes (AC079305.10, BCL10, BCL2A1, BRE-AS1, DYNLL2, EREG, and PTGS2) that were identified as core genes via correlation analysis. Furthermore, SCENIC and pseudotemporal analysis revealed JUN, IRF9, ETV5, and PPARA score gene-related TFs. Jun was found to be associated with hypoxia in endothelial cells, whereas Irf9 and Etv5 were identified as astrocyte-specific TFs associated with oxygen concentration in the mouse cerebral cortex. Conclusions Calcium signaling pathway-related genes (AC079305.10, BCL10, BCL2A1, BRE-AS1, DYNLL2, EREG, and PTGS2) and TFs (JUN, IRF9, ETV5, and PPARA) were identified to play a key role in IS. This study provides a new perspective and basis for investigating the pathogenesis of IS and developing new therapeutic approaches.

Highlights

Ischemic stroke (IS) is the most prevalent type of stroke, accounting for 87% of all strokes [1,2,3]
Microarray technology is effective in screening for pathways and functional genes associated with stroke, and weighted gene coexpression network analysis (WGCNA) can be used to construct coexpression networks between genes and pathways to predict changes in related signaling pathways after ischemic stroke (IS) [10]
We found that the calcium signaling pathway was positively correlated with genes in the pink module, including AC079305.10, BCL10, BCL2A1, BRE-AS1, DYNLL2, EREG, and PTGS2

Summary

Introduction

Ischemic stroke (IS) is the most prevalent type of stroke, accounting for 87% of all strokes [1,2,3]. Gene set variation analysis (GSVA) is an approach that allows the assessment of potential changes in pathway activity [4]. It has recently been used in studies on pancreatic and breast cancers and has demonstrated excellent potential for identifying prognosis-related. WGCNA of the gene expression matrix of the samples revealed the calcium signaling pathway-related genes (AC079305.10, BCL10, BCL2A1, BRE-AS1, DYNLL2, EREG, and PTGS2) that were identified as core genes via correlation analysis. Calcium signaling pathway-related genes (AC079305.10, BCL10, BCL2A1, BRE-AS1, DYNLL2, EREG, and PTGS2) and TFs (JUN, IRF9, ETV5, and PPARA) were identified to play a key role in IS. This study provides a new perspective and basis for investigating the pathogenesis of IS and developing new therapeutic approaches

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Discussion

Conclusion