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Identification of Senescence-Related Biomarkers and Regulatory Networks in Intracerebral Hemorrhage.
Neurologist 2024 January 22
OBJECTIVES: Intracerebral hemorrhage (ICH) is a severe neurological disorder with substantial societal implications. Cellular senescence plays a critical role in ICH pathogenesis. This study aims to identify senescence-related biomarkers in ICH for diagnostic and therapeutic purposes.
METHODS: Raw data from GSE24265 in Gene Expression Omnibus was downloaded. Senescence-related genes were acquired from CellAge. Differential gene analysis was done between patients with ICH and controls. The intersection of ICH differentially expressed genes and senescence-related genes for senescence-related ICH genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Protein-protein interaction network was constructed through the Search Tool for the Retrieval of Interacting Genes. Single sample gene set enrichment analysis was done for immune cell infiltration and function evaluation in control and ICH groups. miRWalk2.0 database was used for microRNA predictions targeting ICH biomarkers. Transcriptional regulatory relationships unraveled by sentence-based text mining database was employed to predict transcription factors regulating identified biomarkers.
RESULTS: Thirteen senescence-related ICH genes were identified. They were primarily enriched in the positive regulation of angiogenesis and the Advanced Glycation End Product -Receptor for AGE signaling pathway in diabetic complications. Validation in the GSE149317 data set and receiver operating characteristic analysis highlighted Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 as potential ICH biomarkers. Single sample gene set enrichment analysis revealed increased Type 2 T helper cell 2_cells, Treg cells, and immune functions like Antigen-presenting cells_co_stimulation in patients with ICH. Fourteen microRNA, including has-miR-6728-3p, were predicted to regulate these biomarkers. transcription factors such as PPARG, RARA, HMGA1, and NFKB1 were identified as potential regulators of the ICH biomarkers.
CONCLUSION: Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 may serve as valuable biomarkers in ICH. Targeting these genes could contribute to ICH prevention and treatment.
METHODS: Raw data from GSE24265 in Gene Expression Omnibus was downloaded. Senescence-related genes were acquired from CellAge. Differential gene analysis was done between patients with ICH and controls. The intersection of ICH differentially expressed genes and senescence-related genes for senescence-related ICH genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Protein-protein interaction network was constructed through the Search Tool for the Retrieval of Interacting Genes. Single sample gene set enrichment analysis was done for immune cell infiltration and function evaluation in control and ICH groups. miRWalk2.0 database was used for microRNA predictions targeting ICH biomarkers. Transcriptional regulatory relationships unraveled by sentence-based text mining database was employed to predict transcription factors regulating identified biomarkers.
RESULTS: Thirteen senescence-related ICH genes were identified. They were primarily enriched in the positive regulation of angiogenesis and the Advanced Glycation End Product -Receptor for AGE signaling pathway in diabetic complications. Validation in the GSE149317 data set and receiver operating characteristic analysis highlighted Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 as potential ICH biomarkers. Single sample gene set enrichment analysis revealed increased Type 2 T helper cell 2_cells, Treg cells, and immune functions like Antigen-presenting cells_co_stimulation in patients with ICH. Fourteen microRNA, including has-miR-6728-3p, were predicted to regulate these biomarkers. transcription factors such as PPARG, RARA, HMGA1, and NFKB1 were identified as potential regulators of the ICH biomarkers.
CONCLUSION: Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 may serve as valuable biomarkers in ICH. Targeting these genes could contribute to ICH prevention and treatment.
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