ArticleInternational journal of general medicine2021
Identification of Dysregulated Mechanisms and Potential Biomarkers in Ischemic Stroke Onset.
Article in International journal of general medicine, 2021. 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, 9 citations in OpenAlex.
- Article
- Temporal expression profiles of microRNAs associated with acute phase of brain ischemia in gerbil hippocampus.Heliyon · 2024Article
- Investigation of shared genes and regulatory mechanisms associated with coronavirus disease 2019 and ischemic stroke.Frontiers in neurology · 2023Article
- Role and Dysregulation of miRNA in Patients with Parkinson's Disease.International journal of molecular sciences · 2022Article
- Diagnostic model constructed by nine inflammation-related genes for diagnosing ischemic stroke and reflecting the condition of immune-related cells.Frontiers in immunology · 2022Article
- Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis.Neural plasticity · 2022Article
- Prediction of Mechanosensitive Genes in Vascular Endothelial Cells Under High Wall Shear Stress.Frontiers in genetics · 2021Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIschemic stroke (IS) is a major cause of severe disability. This study aimed to identify potential biomarkers closely related to IS diagnosis and treatment.
methodsProfiles of gene expression were obtained from datasets GSE16561, GSE22255, GSE112801 and GSE110993. Differentially expressed mRNAs between IS and controls were then subjected to weighted gene co-expression network analysis as well as multiscale embedded gene co-expression network analysis. The intersection of the two sets of module genes was subjected to analyses of functional enrichment and of microRNAs (miRNAs) regulation. Then, the area under receiver operating characteristic curves (AUC) was calculated to assess the ability of genes to discriminate IS patients from controls. IS diagnostic signatures were constructed using least absolute shrinkage and selection operator regression.
resultsA total of 234 common co-expression network genes were found to be potentially associated with IS. Enrichment analysis found that these genes were mainly associated with inflammation and immune response. The aberrantly expressed miRNAs (hsa-miR-651-5p, hsa-miR-138-5p, hsa-miR-9-3p and hsa-miR-374a-3p) in IS had regulatory effects on IS-related genes and were involved in brain-related diseases. We used the criterion AUC > 0.7 to screen out 23 hub genes from IS-related genes in the GSE16561 and GSE22255 datasets. We obtained an 8-gene signature (ADCY4, DUSP1, ATP5F1, DCTN5, EIF3G, ELAVL1, EXOSC7 and PPIE) from the training set of GSE16561 dataset, which we confirmed in the validation set of GSE16561 dataset and in the GSE22255 dataset. The genes in this signature were highly accurate for diagnosing IS. In addition, the 8-gene signature significantly correlated with infiltration by immune cells.
conclusionThese findings provide new clues to molecular mechanisms and treatment targets in IS. The genes in the signature may be candidate markers and potential gene targets for treatments.
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