bioRxivNeurosciencePreprint
Single-Cell and Spatial Transcriptomics Integration Identifies Mural Cell Oxidative Stress Genes Clu and Gria2 as Key Biomarkers in Ischemic Stroke
Abstract
Oxidative stress (OS) is a key factor in ischemic stroke (IS), but the characterization of OS-related genes in IS remains largely unexplored. Identifying key OS-associated genes could improve our understanding of OS in IS. We analysed single-cell RNA sequencing datasets and utilized AUCell, Ucell, singscore, ssgsea, and AddModuleScore algorithms, along with correlation analysis, identified 167 OS-related genes potentially linked to IS. Furthermore, we used seven machine learning algorithms, including least absolute shrinkage and selection operator, XGBoost, Boruta, random forest, gradient boosting machines, decision trees, and support vector machine recursive feature elimination, to identify the optimal feature genes: Clusterin (Clu) and Glutamate Ionotropic Receptor AMPA Type Subunit 2 (Gria2). Bulk RNA-sequencing showed that Clu expression was upregulated and Gria2 expression was downregulated in IS tissues. Single-cell analysis further revealed that these expression changes predominantly occurred in mural cells, emphasizing their cell-specific roles in IS. Subsequently, we validated these findings through spatial transcriptomics (ST) analysis and animal model experiments. These results suggest that Clu and Gria2 may participate in the progression of IS by altering the OS activity of mural cells. However, further research is needed to validate its clinical efficacy and ensure its application in the treatment of IS.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: differential expression
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 0
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