ArticleAging2023
Identification of key biomarkers in ischemic stroke: single-cell sequencing and weighted co-expression network analysis.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Identification and experimental validation of biomarkers associated with the endocannabinoid system in major depressive disorder.Hereditas · 2025Article
- Bioinformatics analysis of comorbid mechanisms between ischemic stroke and end stage renal disease.Scientific reports · 2025Article
- Unraveling the mechanisms underlying diabetic cataracts: insights from Mendelian randomization analysis.Redox report : communications in free radical research · 2024Article
- Construction of a machine learning-based prediction model for unfavorable discharge outcomes in patients with ischemic stroke.Heliyon · 2024Article
- Revolutionizing Ischemic Stroke Diagnosis and Treatment: The Promising Role of Neurovascular Unit-Derived Extracellular Vesicles.Biomolecules · 2024Review
- Perspective from single-cell sequencing: Is inflammation in acute ischemic stroke beneficial or detrimental?CNS neuroscience & therapeutics · 2024Review
- Identification of ribosome biogenesis genes and subgroups in ischaemic stroke.Frontiers in immunology · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeAt present, there is a lack of accurate early diagnostic markers for ischemic stroke.
methodsBy using dimensionality reduction cluster analysis, differential expression analysis, weighted co-expression network analysis, protein-protein interaction network analysis, cell heterogeneity and key pathogenic genes were identified in ischemic stroke. Immunomicroenvironment analysis was used to explore the immune landscape and immune associations of key genes in ischemic stroke. The analysis platform we use is R software (version 4.0.5). PCR experiments were used to verify the expression of key genes.
resultsSingle cell sequencing data in ischemic stroke can be annotated as fibroblast cells, pre-B cell CD34, neutrophils cells, bone marrow (BM), keratinocytes, macrophage, neurons and mesenchymal stem cells (MSC). By the intersection of differential expression analysis and WGCNA analysis, 385 genes were obtained. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these genes were highly correlated with multiple functions and pathways. Protein-protein interaction network analysis revealed that MRPS11 and MRPS12 were key genes, both of which were down-regulated in ischemic stroke. The Pseudo-time series analysis found that the expression of MRPS12 decreased gradually with the differentiation of pre-B cell CD34 cells in ischemic stroke, suggesting that the downregulation of MRPS12 expression may play an important role in ischemic stroke. At last, PCR showed that MRPS11 and MRPS12 were significantly down-regulated in peripheral blood of patients with ischemic stroke.
conclusionsOur study provides a reference for the study of pathogenesis and key targets of ischemic stroke.
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